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• With online verification on a 6D robotic couch, the non-rigid setup errors are found to be up to four times larger below the cricoid cartilage than above it, reducing dosimetric robustness below the neck regions. • The tumor control probability based on the primary tumor is not strongly correlated with the positioning errors of the prophylactic CTV in the neck regions. • Based on the obtained residual setup errors, robustness optimization setup setting of 2 mm is substantiated for head and neck cancers. • Care should be taken when applying this 2 mm margin to the lower neck regions when head and neck movements are large and irregular or when shoulder positioning is less reproducible: asymmetrical patient and location specific margins could be considered. To assess the residual geometrical errors (dr) and their impact on the clinical target volumes (CTV) dose coverage for head and neck cancer (HNC) proton therapy patients. We analysed 28 HNC patients treated with 70 Gy (RBE) and 54.25 Gy (RBE) to the therapeutic CTV 70 and prophylactic CTV 54.25 , respectively. Daily cone beam CTs were converted to high quality synthetic CTs (sCTs). The CTVs from the nominal CT were propagated to the corresponding sCTs using a hybrid deformable image registration (propagated CTVs) in RayStation 11B. For 11 patients, all propagated CTVs were reviewed by our HNC radiation oncologist (physician corrected CTVs). The residual geometrical error dr was quantified as a function of the daily CTVs volume overlap with the nominal plan CTV. The errors dr(propagated CTVs) and dr(physician corrected CTVs) and the difference in dice similarity coefficients (ΔDSC) were determined. Using clinical plans, dose coverage and the tumor control probability (TCP) for the nominal, accumulated and voxel-wise minimum scenarios were determined. The difference in the residual geometrical error dr (propagated CTVs – physician corrected CTVs) and mean DSC (|ΔDSC|mean) were minor: Δdr(CTV 70) = 0.16 mm, Δdr(CTV 54.25) = 0.26 mm, |ΔDSC|mean < 0.9%. For all 28 patients, dr(CTV 70) = 1.91 mm and dr(CTV 54.25) = 1.90 mm. However, CTV 54.25 above and below the cricoid cartilage differed substantially (1.00 mm c.f. 3.93 mm). The CTV 54.25 coverage below the cricoid was then almost always lower, although the TCP of the accumulated dose was higher than the TCP of the voxel-wise minimum dose. Setup uncertainty setting of 2 mm is possible. The feasibility of using propagated CTVs for error determination is demonstrated. [ABSTRACT FROM AUTHOR]

Purpose To report on a universal bolus (UB) designed to replace the range shifter (RS); the UB allows the treatment of shallow tumors while keeping the pencil beam scanning (PBS) spot size small. Methods and Materials Ten patients with brain cancers treated from 2010 to 2011 were planned using the PBS technique with bolus and the RS. In-air spot sizes of the pencil beam were measured and compared for 4 conditions (open field, with RS, and with UB at 2- and 8-cm air gap) in isocentric geometry. The UB was applied in our clinic to treat brain tumors, and the plans with UB were compared with the plans with RS. Results A UB of 5.5 cm water equivalent thickness was found to meet the needs of the majority of patients. By using the UB, the PBS spot sizes are similar with the open beam (P>.1). The heterogeneity index was found to be approximately 10% lower for the UB plans than for the RS plans. The coverage for plans with UB is more conformal than for plans with RS; the largest increase in sparing is usually for peripheral organs at risk. Conclusions The integrity of the physical properties of the PBS beam can be maintained using a UB that allows for highly conformal PBS treatment design, even in a simple geometry of the fixed beam line when noncoplanar beams are used. [ABSTRACT FROM AUTHOR]

Purpose: We performed a treatment planning study to demonstrate the potential dosimetric benefits of anterior-oriented fields for prostate irradiation by proton beam. A novel in vivo beam range control method shows millimeter accuracy, suggesting that such fields could be safely used to spare the rectum given the sharp distal penumbra of protons. Methods and Materials: Ten prostate patients treated with water-filled endorectal balloon were selected. Bilateral fields were planned following the conventional treatment protocol. Three anterior-oriented fields (0, +30, −30°) were planned, with the range compensators manually adjusted to improve rectal sparing. Dose distributions to the clinical target volume, rectum, anterior rectal wall (ARW), bladder, bladder wall (BW), and femoral heads were compared for: A) equally weighted bilateral fields, B) a single straight anterior field, and C) two equally weighted anterior-oblique fields. Results: The anterior-oriented fields required much less beam energy, ∼10 cm water equivalent path length less than lateral fields. For ARW, the V95% for Plans A, B, and C were 39%, 8%, and 6%, respectively; the corresponding V80% were 59%, 27%, and 26%, respectively (p = 0.002 when Plan A was compared with B or C). Plan B irradiated a larger volume of BW than did Plan A by 3% at V95%, 11% at V80%, and 16% at V50% (p = 0.002), whereas Plan C differs little from Plan A for BW at these dose levels. The femoral heads received ∼40% of the prescription dose in Plan A, but negligible dose in Plans B and C. Conclusions: Compared to lateral fields, anterior-oriented fields can significantly reduce dose to the ARW, particularly at high dose levels. These fields alone, or in combination with lateral fields, allow for the possibility of either reducing treatment toxicity at current prescription doses or further dose escalation in the treatment of prostate cancer. [Copyright &y& Elsevier]

Background: Our purpose was to report acute gastrointestinal (GI) and genitourinary (GU) toxicity rates for prostate cancer patients undergoing image-guided intensity modulated radiation therapy (IG-IMRT) with a daily endorectal water-filled balloon (ERBH2O), and assess associations with planning parameters and pretreatment clinical characteristics. Methods: The first 100 patients undergoing prostate and proximal seminal vesicle IG-IMRT with indexed-lumen 100 cc ERBH2O to 79.2 Gy in 1.8 Gy fractions at our institution from 12/2008- 12/2010 were assessed. Pretreatment characteristics, organ-at-risk dose volume histograms, and maximum GU and GI toxicities (CTCAE 3.0) were evaluated. Logistic regression models evaluated univariate association between toxicities and dosimetric parameters, and uni- and multivariate association between toxicities and pretreatment characteristics. Results: Mean age was 68 (range 51-88). Thirty-two, 49, and 19 patients were low, intermediate, and high-risk, respectively; 40 received concurrent androgen deprivation. No grade 3 or greater toxicities were recorded. Maximum GI toxicity was grade 0, 1, and 2 in 69%, 23%, and 8%, respectively. Infield (defined as 1 cm above/below the CTV) rectal mean/median doses, D75, V30, and V40 and hemorrhoid history were associated with grade 2 GI toxicity (Ps < 0.05). Maximum acute GU toxicity was grade 0, 1, and 2 for 17%, 41%, and 42% of patients, respectively. Infield bladder V20 (P = 0.03) and pretreatment International Prostate Symptom Scale (IPSS) (P = 0.003) were associated with grade 2 GU toxicity. Conclusion: Prostate IG-IMRT using a daily ERBH2O shows low rates of acute GI toxicity compared to previous reports of air-filled ERB IMRT when using stringent infield rectum constraints and comparable GU toxicities. [ABSTRACT FROM AUTHOR]

Purpose: To prospectively investigate intrafraction prostate motion during radiofrequency-guided prostate radiotherapy with implanted electromagnetic transponders when daily endorectal balloon (ERB) is used. Methods and Materials: Intrafraction prostate motion from 24 patients in 787 treatment sessions was evaluated based on three-dimensional (3D), lateral, cranial-caudal (CC), and anterior-posterior (AP) displacements. The mean percentage of time with 3D, lateral, CC, and AP prostate displacements >2, 3, 4, 5, 6, 7, 8, 9, and 10 mm in 1 minute intervals was calculated for up to 6 minutes of treatment time. Correlation between the mean percentage time with 3D prostate displacement >3 mm vs. treatment week was investigated. Results: The percentage of time with 3D prostate movement >2, 3, and 4 mm increased with elapsed treatment time (p < 0.05). Prostate movement >5 mm was independent of elapsed treatment time (p = 0.11). The overall mean time with prostate excursions >3 mm was 5%. Directional analysis showed negligible lateral prostate motion; AP and CC motion were comparable. The fraction of time with 3D prostate movement >3 mm did not depend on treatment week of (p > 0.05) over a 4-minute mean treatment time. Conclusions: Daily endorectal balloon consistently stabilizes the prostate, preventing clinically significant displacement (>5 mm). A 3-mm internal margin may sufficiently account for 95% of intrafraction prostate movement for up to 6 minutes of treatment time. Directional analysis suggests that the lateral internal margin could be further reduced to 2 mm. [Copyright &y& Elsevier]

Purpose: To assess whether whole-pelvis (WP) intensity-modulated radiation therapy (IMRT) is associated with increased toxicity compared with prostate-only (PO) IMRT. Methods and Materials: We retrospectively analyzed all patients with prostate cancer undergoing definitive IMRT to 79.2 Gy with concurrent androgen deprivation at our institution from November 2005 to May 2007 with a minimum follow-up of 12 months. Thirty patients received initial WP IMRT to 45 Gy in 1.8-Gy fractions, and thirty patients received PO IMRT. Study patients underwent computed tomography simulation and treatment planning by use of predefined dose constraints. Bladder and rectal dose–volume histograms, maximum genitourinary (GU) and gastrointestinal (GI) Radiation Therapy Oncology Group toxicity grade, and late Grade 2 or greater toxicity-free survival curves were compared between the two groups by use of the Student t test, Fisher exact test, and Kaplan-Meier curve, respectively. Results: Bladder minimum dose, mean dose, median dose, volume receiving 5 Gy, volume receiving 20 Gy, volume receiving 40 Gy, and volume receiving 45 Gy and rectal minimum dose, median dose, and volume receiving 20 Gy were significantly increased in the WP group (all p values < 0.01). Maximum acute GI toxicity was limited to Grade 2 and was significantly increased in the WP group at 50% vs. 13% the PO group (p = 0.006). With a median follow-up of 24 months (range, 12–35 months), there was no difference in late GI toxicity (p = 0.884) or in acute or late GU toxicity. Conclusions: Despite dosimetric differences in the volume of bowel, bladder, and rectum irradiated in the low-dose and median-dose regions, WP IMRT results only in a clinically significant increase in acute GI toxicity, in comparison to PO IMRT, with no difference in GU or late GI toxicity. [ABSTRACT FROM AUTHOR]

Introduction: The first-line treatment for acromegaly is transsphenoidal surgery. In approximately 50% of patients, however, a cure is not possible with surgery and alternatives are needed. Somatostatin analog therapy is the recommended first-line treatment in patients with such cases. Here we provide the first report of a high-dose lanreotide primary therapy in patients with acromegaly. Case presentation: Six patients who were not suitable for surgery were given 60 mg of lanreotide (Autogel®) every four weeks. All patients were German nationals and Caucasian. When the response of our patients was unsatisfactory, the dose was increased sequentially to 90 mg every four weeks, 120 mg every four weeks, 120 mg every three weeks and 180 mg every three weeks. Treatment duration was 12 to 24 months. In all cases, the lanreotide dose was 120 mg every 4 weeks or higher. In five of our patients, growth hormone (GH) levels were successfully reduced (in three patients GH <2.5 ng/ml was achieved). Insulin-like growth factor 1 levels were normalized in three patients and decreased in two patients. One patient failed to show a biochemical response to lanreotide therapy or pegvisomant therapy. Tumor shrinkage or degeneration was observed in the five responding patients. No drug-related adverse events were noted. Conclusions: These results suggest that lanreotide at high doses of 120 mg every four weeks or more is an effective first-line therapy for patients with acromegaly that surgery alone cannot treat. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate the dosimetric characteristics of a 2D diode array device (MAPCHECK™) and provide correction factors for clinically relevant conditions. Measurements were performed for various collimator settings (5×5–40×40 cm2), SSDs (80–110 cm), and depths (5–20 cm) for 6 and 15 MV photon beams. The correction factor was determined as the ratio of dose measured by an ionization chamber in a large full scatter water phantom to the dose measured by the MAPCHECK with 30×30 cm2 solid water phantom. The total correction factor was separated into three components. The phantom scatter factor was evaluated by taking the ratio of dose measured by MAPCHECK with backscatter material and 30×30 cm2 phantom to that by the ionization chamber in an infinite large water phantom renormalized to the reference field size (10×10 cm2). This was also compared to the theoretical calculation using ratios of phantom scatter factor between an infinitely large water phantom and 30×30 cm2 solid water phantoms. The backscatter effect was determined by taking the ratio of the MAPCHECK measurements with and without 10 cm thick solid water backscatter material also normalized to the reference field size at the depth of measurement. The extra correction factor is defined as the ratio of dose measured by the MAPCHECK (without backscatter) to that measured by the ionization chamber in a large water phantom at depth d for the reference field size (10×10 cm2) normalized to the reference depth (10 cm) and reference field size. The total correction factors for 6 and 15 MV photon beams were up to 16% and 11.5%, respectively, due to the difference in phantom scatter in MAPCHECK measurements when the field sizes are larger than 30 cm. The result was consistent with theoretical analysis with phantom scatter alone. The backscatter correction factor varied by up to 2% and increased with increasing field size. The extra correction factor decreases with depths and is <0.4% for all depths. The authors have verified that correction factors for MAPCHECK are a function of the scaled field size and depth only and are independent of the SSD. Results were verified for off-axis points measured by MAPCHECK. [ABSTRACT FROM AUTHOR]

Background: Deep learning has shown promising results to generate MRI‐based synthetic CTs and to enable accurate proton dose calculations on MRIs. For clinical implementation of synthetic CTs, quality assurance tools that verify their quality and reliability are required but still lacking. Purpose: This study aims to evaluate the predictive value of uncertainty maps generated with Monte Carlo dropout (MCD) for verifying proton dose calculations on deep‐learning‐based synthetic CTs (sCTs) derived from MRIs in online adaptive proton therapy. Methods: Two deep‐learning models (DCNN and cycleGAN) were trained for CT image synthesis using 101 paired CT‐MR images. sCT images were generated using MCD for each model by performing 10 inferences with activated dropout layers. The final sCT was obtained by averaging the inferred sCTs, while the uncertainty map was obtained from the HU variance corresponding to each voxel of 10 sCTs. The resulting uncertainty maps were compared to the observed HU‐, range‐, WET‐, and dose‐error maps between the sCT and planning CT. For range and WET errors, the generated uncertainty maps were projected along the 90‐degree angle. To evaluate the dose distribution, a mask based on the 5%‐isodose curve was applied to only include voxels along the beam paths. Pearson's correlation coefficients were calculated to determine the correlation between the uncertainty maps and HUs, range, WET, and dose errors. To evaluate the dosimetric accuracy of synthetic CTs, clinical proton treatment plans were recalculated and compared to the pCTs Results: Evaluation of the correlation showed an average of r = 0.92 ± 0.03 and r = 0.92 ± 0.03 for errors between uncertainty‐HU, r = 0.66 ± 0.09 and r = 0.62 ± 0.06 between uncertainty‐range, r = 0.64 ± 0.06 and r = 0.58 ± 0.07 between uncertainty‐WET, and r = 0.65 ± 0.09 and r = 0.67 ± 0.07 between uncertainty and dose difference for DCNN and cycleGAN model, respectively. Dosimetric comparison for target volumes showed an average 3%/3 mm gamma pass rate of 99.76 ± 0.43 (DCNN) and 99.10 ± 1.27 (cycleGAN). Conclusion: The observed correlations between uncertainty maps and the various metrics (HU, range, WET, and dose errors) demonstrated the potential of MCD‐based uncertainty maps as a reliable QA tool to evaluate the accuracy of deep learning‐based sCTs. [ABSTRACT FROM AUTHOR]

Simple Summary: While the dosimetric advantages of proton therapy over conventional treatment for CSI are typically emphasized for spine fields, only lens dose reduction has been reported for brain fields. In this retrospective in silico planning study, the aim is to assess the potential gains of proton CSI for organs at risk in the whole-brain part of CSI. Different optimization techniques and beam arrangements as well as pencil beam spot editing were employed to determine the potential gains. The study shows that: (1) cochlear sparing is impractical, (2) improving the lens dose is possible mainly by adding a posterior field direction, and (3) an incremental scalp dose reduction is possible, particularly in adult patients. Proton therapy is a promising modality for craniospinal irradiation (CSI), offering dosimetric advantages over conventional treatments. While significant attention has been paid to spine fields, for the brain fields, only dose reduction to the lens of the eye has been reported. Hence, the objective of this study is to assess the potential gains and feasibility of adopting different treatment planning techniques for the entire brain within the CSI target. To this end, eight previously treated CSI patients underwent retrospective replanning using various techniques: (1) intensity modulated proton therapy (IMPT) optimization, (2) the modification/addition of field directions, and (3) the pre-optimization removal of superficially placed spots. The target coverage robustness was evaluated and dose comparisons for lenses, cochleae, and scalp were conducted, considering potential biological dose increases. The target coverage robustness was maintained across all plans, with minor reductions when superficial spot removal was utilized. Single- and multifield optimization showed comparable target coverage robustness and organ-at-risk sparing. A significant scalp sparing was achieved in adults but only limited in pediatric cases. Superficial spot removal contributed to scalp V30 Gy reduction at the expense of lower coverage robustness in specific cases. Lens sparing benefits from multiple field directions, while cochlear sparing remains impractical. Based on the results, all investigated plan types are deemed clinically adoptable. [ABSTRACT FROM AUTHOR]

Background: Adaptive proton therapy workflows rely on accurate imaging throughout the treatment course. Our centre currently utilizes weekly repeat CTs (rCTs) for treatment monitoring and plan adaptations. However, deep learning‐based methods have recently shown to successfully correct CBCT images, which suffer from severe imaging artifacts, and generate high quality synthetic CT (sCT) images which enable CBCT‐based proton dose calculations. Purpose: To compare daily CBCT‐based sCT images to planning CTs (pCT) and rCTs of head and neck (HN) cancer patients to investigate the dosimetric accuracy of CBCT‐based sCTs in a scenario mimicking actual clinical practice. Methods: Data of 56 HN cancer patients, previously treated with proton therapy was used to generate 1.962 sCT images, using a previously developed and trained deep convolutional neural network. Clinical IMPT treatment plans were recalculated on the pCT, weekly rCTs and daily sCTs. The dosimetric accuracy of sCTs was compared to same day rCTs and the initial planning CT. As a reference, rCTs were also compared to pCTs. The dose difference between sCTs and rCTs/pCT was quantified by calculating the D98 difference for target volumes and Dmean difference for organs‐at‐risk. To investigate the clinical relevancy of possible dose differences, NTCP values were calculated for dysphagia and xerostomia. Results: For target volumes, only minor dose differences were found for sCT versus rCT and sCT versus pCT, with dose differences mostly within ±1.5%. Larger dose differences were observed in OARs, where a general shift towards positive differences was found, with the largest difference in the left parotid gland. Delta NTCP values for grade 2 dysphagia and xerostomia were within ±2.5% for 90% of the sCTs. Conclusions: Target doses showed high similarity between rCTs and sCTs. Further investigations are required to identify the origin of the dose differences at OAR levels and its relevance in clinical decision making. [ABSTRACT FROM AUTHOR]

The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While PT has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of PT cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effect difference compared to photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because PT treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in PT categorized into four different themes, 'improving efficiency', 'improving planning and delivery', 'improving imaging', and 'improving patient selection'. [ABSTRACT FROM AUTHOR]

The aim of the study was to test the hypothesis that Intensity Modulated Proton Therapy (IMPT) reduces acute and late radiation toxicity in nasopharyngeal cancer (NPC) patients compared to photon-based radiation techniques including IMRT and VMAT. The study population of this prospective cohort study was composed of 131 NPC patients treated with curative radiotherapy (RT) or chemoradiotherapy. Between July 2007 and December 2017, all patients were treated with IMRT or VMAT. Since January 2018, 97 out of 99 patients (98%) qualified for IMPT according to model-based selection. All patients were included in a prospective data registration program in which acute and late toxicity was prospectively scored weekly during RT and at fixed time points after RT (6 weeks, 6, 12, 18 and 24 months). To determine the overall effect on acute and late toxicity, the Weighted Overall Toxicity Burden (WOTB) was calculated, defined as the sum of all toxicities weighted by toxicity grading. In addition, the WOTB Area Under the Curve (WOTB-AUC) was calculated representing the WOTB from the start of treatment until 24 months after completion of treatment. The two groups were well balanced regarding gender, age, race, T-stage, N-stage, AJCC-stage, and EBV-status. However, there was a significant difference regarding the chemotherapy regimens used between the two groups. In the photon cohort, 33% of patients were treated with conventional RT, 7% with concurrent chemoradiation, 2% with induction chemotherapy + concurrent chemoradiation and 57% with concurrent chemoradiation + adjuvant chemotherapy, while this was 25%, 37%, 36% and 2% in the proton cohort, respectively. The mean dose to all relevant organs at risk (i.e., oral cavity, pharyngeal constrictor muscles, parotid, and submandibular glands) were significantly lower with IMPT compared to photons. This was particularly true for the mean dose to the oral cavity which decreased from 27.2 Gy with IMRT/ VMAT to 10.7 Gy with IMPT (p<0.001). From January 2018, a plan comparison was made in all NPC patients referred for radiotherapy to our centre between IMPT and VMAT. In total, 97 out of 99 patients qualified for protons based on the estimated risk difference on dysphagia and xerostomia resulting from the dose reductions obtained with IMPT. IMPT resulted in significant reductions of various acute and late toxicities (Figure 1), including xerostomia, loss of taste, dysphagia, tube feeding dependence, sore mouth, and mucosal reactions. Only acute dermatitis was significantly worse at the end of IMPT, but completely recovered at 5 weeks after treatment in all patients. [Display omitted] The WOTB was significantly lower after IMPT (Figure 2) at all time points. In the IMPT group, the WOTB-AUC as measure for overall toxicity was 68% lower. The WOTB-AUC reduction was 60% in the acute phase (week 1 to 7), 69% in the recovery phase (from end of treatment to 6 months after RT) and 70% in the late phase (from 6 to 24 months after RT). In this prospective cohort study, patients treated with IMPT had statistically significant and clinically relevant reductions of various acute and late toxicities as compared to modern photon techniques like IMRT and VMAT as a historical control group. [ABSTRACT FROM AUTHOR]

This study evaluates the suitability of convolutional neural networks (CNNs) to automatically process proton radiography (PR)-based images. CNNs are used to classify PR images impaired by several sources of error affecting the proton range, more precisely setup and calibration curve errors. PR simulations were performed in 40 head and neck cancer patients, at three different anatomical locations (fields A, B and C, centered for head and neck, neck and base of skull coverage). Field sizes were 26 × 26cm2 for field A and 4.5 × 4.5cm2 for fields B and C. Range shift maps were obtained by comparing an unperturbed reference PR against a PR where one or more sources of error affected the proton range. CT calibration curve errors in soft, bone and fat tissues and setup errors in the anterior–posterior and inferior–superior directions were simulated individually and in combination. A CNN was trained for each type of PR field, leading to three CNNs trained with a mixture of range shift maps arising from one or more sources of range error. To test the full/partial/wrong agreement between predicted and actual sources of range error in the range shift maps, exact, partial and wrong match percentages were computed for an independent test dataset containing range shift maps arising from isolated or combined errors, retrospectively. The CNN corresponding to field A showed superior capability to detect isolated and combined errors, with exact matches of 92% and 71% respectively. Field B showed exact matches of 80% and 54%, and field C resulted in exact matches of 77% and 41%. The suitability of CNNs to classify PR-based images containing different sources of error affecting the proton range was demonstrated. This procedure enables the detection of setup and calibration curve errors when they appear individually or in combination, providing valuable information for the interpretation of PR images. [ABSTRACT FROM AUTHOR]

Background: Personalized treatment is increasingly required for oropharyngeal squamous cell carcinoma (OPSCC) patients due to emerging new cancer subtypes and treatment options. Outcome prediction model can help identify low or high‐risk patients who may be suitable to receive de‐escalation or intensified treatment approaches. Purpose: To develop a deep learning (DL)‐based model for predicting multiple and associated efficacy endpoints in OPSCC patients based on computed tomography (CT). Methods: Two patient cohorts were used in this study: a development cohort consisting of 524 OPSCC patients (70% for training and 30% for independent testing) and an external test cohort of 396 patients. Pre‐treatment CT‐scans with the gross primary tumor volume contours (GTVt) and clinical parameters were available to predict endpoints, including 2‐year local control (LC), regional control (RC), locoregional control (LRC), distant metastasis‐free survival (DMFS), disease‐specific survival (DSS), overall survival (OS), and disease‐free survival (DFS). We proposed DL outcome prediction models with the multi‐label learning (MLL) strategy that integrates the associations of different endpoints based on clinical factors and CT‐scans. Results: The multi‐label learning models outperformed the models that were developed based on a single endpoint for all endpoints especially with high AUCs ≥ 0.80 for 2‐year RC, DMFS, DSS, OS, and DFS in the internal independent test set and for all endpoints except 2‐year LRC in the external test set. Furthermore, with the models developed, patients could be stratified into high and low‐risk groups that were significantly different for all endpoints in the internal test set and for all endpoints except DMFS in the external test set. Conclusion: MLL models demonstrated better discriminative ability for all 2‐year efficacy endpoints than single outcome models in the internal test and for all endpoints except LRC in the external set. [ABSTRACT FROM AUTHOR]

Background: Proton arcs have shown potential to reduce the dose to organs at risks (OARs) by delivering the protons from many different directions. While most previous studies have been focused on dynamic arcs (delivery during rotation), an alternative approach is discrete arcs, where step‐and‐shoot delivery is used over a large number of beam directions. The major advantage of discrete arcs is that they can be delivered at existing proton facilities. However, this advantage comes at the expense of longer treatment times. Purpose: To exploit the dosimetric advantages of proton arcs, while achieving reasonable delivery times, we propose a partitioning approach where discrete arc plans are split into subplans to be delivered over different fractions in the treatment course. Methods: For three oropharyngeal cancer patients, four different arc plans have been created and compared to the corresponding clinical IMPT plan. The treatment plans are all planned to be delivered in 35 fractions, but with different delivery approaches over the fractions. The first arc plan (1×30) has 30 directions to be delivered every fraction, while the others are partitioned into subplans with 10 and 6 beam directions, each to be delivered every third (3×10), fifth fraction (5×6), or seventh fraction (7×10). All plans are assessed with respect to delivery time, target robustness over the treatment course, doses to OARs and NTCP for dysphagia and xerostomia. Results: The delivery time (including an additional delay of 30 s between the discrete directions to simulate manual interaction with the treatment control system) is reduced from on average 25.2 min for the 1×30 plan to 9.2 min for the 3×10 and 7×10 plans and 5.7 min for the 5×6 plans. The delivery time for the IMPT plan is 7.9 min. When accounting for the combination of delivery time, target robustness, OAR sparing, and NTCP reduction, the plans with 10 directions in each fraction are the preferred choice. Both the 3×10 and 7×10 plans show improved target robustness compared to the 1×30 plans, while keeping OAR doses and NTCP values at almost as low levels as for the 1×30 plans. For all patients the NTCP values for dysphagia are lower for the partitioned plans with 10 directions compared to the IMPT plans. NTCP reduction for xerostomia compared to IMPT is seen in two of the three patients. The best results are seen for the first patient, where the NTCP reductions for the 7×10 plan are 1.6 p.p. (grade 2 xerostomia) and 1.5 p.p. (grade 2 dysphagia). The corresponding NTCP reductions for the 1×30 plan are 2.7 p.p. (xerostomia, grade 2) and 2.0 p.p. (dysphagia, grade 2). Conclusions: Discrete proton arcs can be implemented at any proton facility with reasonable treatment times using a partitioning approach. The technique also makes the proton arc treatments more robust to changes in the patient anatomy. [ABSTRACT FROM AUTHOR]

Purpose: Medical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomography (sCT) generation have increased interest in public challenges to provide data and evaluation metrics for comparing different approaches openly. This paper describes a dataset of brain and pelvis computed tomography (CT) images with rigidly registered cone‐beam CT (CBCT) and magnetic resonance imaging (MRI) images to facilitate the development and evaluation of sCT generation for radiotherapy planning. Acquisition and Validation Methods: The dataset consists of CT, CBCT, and MRI of 540 brains and 540 pelvic radiotherapy patients from three Dutch university medical centers. Subjects' ages ranged from 3 to 93 years, with a mean age of 60. Various scanner models and acquisition settings were used across patients from the three data‐providing centers. Details are available in a comma separated value files provided with the datasets. Data Format and Usage Notes: The data is available on Zenodo (https://doi.org/10.5281/zenodo.7260704, https://doi.org/10.5281/zenodo.7868168) under the SynthRAD2023 collection. The images for each subject are available in nifti format. Potential Applications: This dataset will enable the evaluation and development of image synthesis algorithms for radiotherapy purposes on a realistic multi‐center dataset with varying acquisition protocols. Synthetic CT generation has numerous applications in radiation therapy, including diagnosis, treatment planning, treatment monitoring, and surgical planning. [ABSTRACT FROM AUTHOR]

Purpose: Patient selection for proton therapy is increasingly based on proton to photon plan comparisons. To improve efficient decision making, we developed a dose mimicking and reducing (DMR) algorithm to automatically generate a robust proton plan from a reference photon dose, as well as target and organ at risk (OAR) delineations.Methods and Materials: The DMR algorithm was evaluated in 40 patients with head and neck cancer. The first step of the DMR algorithm comprises dose-volume histogram-based mimicking of the photon dose distribution in the clinical target volumes and OARs. Target robustness is included by mimicking the nominal photon dose in 21 perturbed scenarios. The second step of the optimization aims to reduce the OAR doses while retaining the robust target coverage as achieved in the first step. We evaluated each DMR plan against the manually robustly optimized reference proton plan in terms of plan robustness (voxel-wise minimum dose). Furthermore, the DMR plans were evaluated against the reference photon plan using normal tissue complication probability (NTCP) models of xerostomia, dysphagia, and tube feeding dependence. Consequently, ΔNTCPs were defined as the difference between the NTCPs of the photon and proton plans.Results: The dose distributions of the DMR and reference proton plans were very similar in terms of target robustness and OAR dose values. Regardless of proton planning technique (ie, DMR or reference proton plan), the same treatment modality was selected in 80% (32 of 40) of cases based on the ∑ΔNTCPs. In 15% (6 of 40) of cases, a conflicting decision was made based on relatively small dose differences to the OARs (<2.0 Gy).Conclusions: The DMR algorithm automatically optimized robust proton plans from a photon reference dose that were comparable to the dosimetrist-optimized proton plans in patients with head and neck cancer. This algorithm has been successfully embedded into a framework to automatically select patients for proton therapy based on NTCPs. [ABSTRACT FROM AUTHOR]

• ΔNTCP based on (reconstructed) delivered dose is compared to ΔNTCP based on planned dose. • ΔNTCP based on the planned dose is an unbiased predictor of ΔNTCP based on the delivered dose. • For a single patient, variations of ±2% compared to planned ΔNTCP can be expected. • The deformable image registration algorithm affects ΔNTCP up to 1.6%. • The choice of α / β ratio has only a minor effect on the ΔNTCP. Model-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, but NTCP can be affected when the delivered treatment deviates from the plan due to delivery inaccuracies. Especially for proton therapy of lung cancer, this can be important because of tissue density changes and, with pencil beam scanning, the interplay effect between the proton beam and breathing motion. In this work, we verified whether the expected benefit of proton therapy is retained despite delivery inaccuracies by reconstructing the delivered treatment using log-file based dose reconstruction and inter- and intrafractional accumulation. Additionally, the importance of two uncertain parameters for treatment reconstruction, namely deformable image registration (DIR) algorithm and α / β ratio, was assessed. The expected benefit or proton therapy was confirmed in 97% of all studied cases, despite regular differences up to 2 percent point (p.p.) NTCP between the delivered and planned treatments. The choice of DIR algorithm affected NTCP up to 1.6 p.p., an order of magnitude higher than the effect of α / β ratio. For the patient population and treatment technique employed, the predicted clinical benefit for patients selected for proton therapy was confirmed for 97.0% percent of all cases, although the NTCP based proton selection was subject to 2 p.p. variations due to delivery inaccuracies. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate an automated treatment planning method for robustly optimized intensity modulated proton therapy (IMPT) plans for oropharyngeal carcinoma patients and to compare the results with manually optimized robust IMPT plans. An atlas regression forest-based machine learning (ML) model for dose prediction was trained on CT scans, contours, and dose distributions of robust IMPT plans of 88 oropharyngeal cancer (OPC) patients. The ML model was combined with a robust voxel and dose volume histogram-based dose mimicking optimization algorithm for 21 perturbed scenarios to generate a machine-deliverable plan from the predicted dose distribution. Machine learning optimization (MLO) configuration was performed using a cross-validation approach with 3 × 8 tuning patients and comprised of adjustments to the mimicking optimization, to generate higher-quality MLO plans. Independent testing of the MLO algorithm was performed with another 25 patients. Plan quality of clinical and MLO plans was evaluated by the clinical target volume (D98% voxel-wise minimum dose >94%), organ at risk (OAR) doses, and the normal tissue complication probability (NTCP) (sum (Σ) of grade-2 and grade-3 dysphagia and xerostomia). Adequate robust target coverage was achieved in 24/25 clinical plans and in 23/25 MLO plans in the primary clinical target volume (CTV). In the elective CTV, 22/25 clinical plans and 24/25 MLO plans passed the robust target coverage evaluation threshold. The MLO average Σgrade 2 and Σgrade 3 NTCPs were comparable to the clinical plans (Σgrade 2 NTCPs: clinical 47.5% vs MLO 48.4%, Σgrade 3 NTCPs: clinical 11.9% vs MLO 12.3%). Significant increases in OAR average doses in MLO plans were found in the pharynx constrictor muscles (163 cGy, P =.002) and cervical esophagus (265 cGy, P =.002). The MLO plans were created within 45 minutes. This study showed that automated MLO planning can generate robustly optimized MLO plans with quality comparable to clinical plans in OPC patients. [ABSTRACT FROM AUTHOR]

Background: Proton radiography (PR) uses highly energetic proton beams to create images where energy loss is the main contrast mechanism. Waterequivalent path length (WEPL) measurements using flat panel PR (FP-PR) have potential for in vivo range verification. However, an accurate WEPL measurement via FP-PR requires irradiation with multiple energy layers, imposing high imaging doses. Purpose: A FP-PR method is proposed for accurate WEPL determination based on a patient-specific imaging field with a reduced number of energies (n) to minimize imaging dose. Methods: Patient-specific FP-PRs were simulated and measured for a head and neck (HN) phantom.An energy selection algorithm estimated spot-wise the lowest energy required to cross the anatomy (Emin) using a water-equivalent thickness map.Starting from Emin, n was restricted to certain values (n = 26, 24, 22, …, 2 for simulations, n = 10 for measurements), resulting in patient-specific FP-PRs. A reference FP-PR with a complete set of energies was compared against patient-specific FP-PRs covering the whole anatomy via mean absolute WEPL differences (MAD), to evaluate the impact of the developed algorithm. WEPL accuracy of patient-specific FP-PRs was assessed using mean relative WEPL errors (MRE) with respect to measured multi-layer ionization chamber PRs (MLIC-PR) in the base of skull, brain, and neck regions. Results: MADs ranged from 2.1 mm (n = 26) to 21.0 mm (n = 2) for simulated FP-PRs, and 7.2 mm for measured FP-PRs (n = 10). WEPL differences below 1 mm were observed across the whole anatomy,except at the phantom surfaces. Measured patient-specific FP-PRs showed good agreement against MLIC-PRs, with MREs of 1.3 ± 2.0%, −0.1 ± 1.0%, and −0.1 ± 0.4% in the three regions of the phantom. Conclusion: A method to obtain accurate WEPL measurements using FP-PR with a reduced number of energies selected for the individual patient anatomy was established in silico and validated experimentally. Patient-specific FP-PRs could provide means of in vivo range verification. [ABSTRACT FROM AUTHOR]

Background: Proton arc technology has recently shown dosimetric gains for various treatment indications. The increased number of beams and energy layers (ELs) in proton arc plans, increases the degrees of freedom in plan optimization and thereby flexibility to spare dose in organs at risk (OARs).A relationship exists between dosimetric plan quality, delivery efficiency, the number of ELs -and beams in a proton arc plan. Purpose: This work aims to investigate the effect of the number of beams and ELs in a proton arc plan, on toxicity and delivery time for oropharyngeal cancer patients (OPC) selected for intensity modulated proton therapy (IMPT) based on the Dutch model-based approach. Methods: The EL reduction algorithm iteratively selects ELs from beams equidistantly spaced over a 360◦ arc. The beams in the final plan may contain multiple ELs, making them suited for static delivery on the studied treatment machine. The produced plans can therefore be called “step and shoot” proton arc plans. The number of beams and ELs were varied to determine the relationship with the planning cost function value, normal tissue complication probability (NTCP) and delivery time. Proton arc plans with robust target coverage and optimal energy layer reduction (ELR) settings to reduce NTCP, were generated for 10 OPC patients. Proton arc plans were compared to clinical volumetric modulated arc therapy (VMAT) and IMPT plans in terms of integral dose, OAR dose,NTCP for xerostomia and dysphagia and delivery time. Furthermore, dose-weighted average linear energy transfer (LETd) distributions were compared between the IMPT and proton arc plans. A dry run delivery of a plan containing 20 beams and 360 ELs was performed to evaluate delivery time and accuracy. Results: We found 360 ELs distributed over 30 beams generated proton arc plans with near minimal expected plan toxicity. Relative to corresponding IMPT and VMAT plans, an average reduction of 21 ± 3% and 58 ± 10% in integral dose was observed. Dmean was reduced most in the pharyngeal constrictor muscle (PCM) medius structure, with on average 9.0 ± 4.2 Gy(RBE) (p = 0.0002) compared to the clinical IMPT plans. The average NTCP for grade≥2 and grade≥3 xerostomia at 6 months after treatment significantly decreased with 4.7 ± 1.8% (p = 0.002) and 1.7 ± 0.8% (p = 0.002), respectively, while the average NTCP for grade≥2 and grade≥3 dysphagia decreased with 4.4 ± 2.9% (p = 0.002) and 0.9 ± 0.4% (p = 0.002), respectively, increasing the benefit of protons relative to VMAT. For a “step and shoot” proton arc delivery with auto beam sequencing the estimated delivery time is 11 min, similar to the delivery time of a 6-field IMPT treatment. Gamma analysis between the planned and delivered dose distribution resulted in a 99.99% pass rate using 1mm/1% dose difference/distance to agreement criteria. Conclusions: “Step and shoot” proton arc demonstrates potential to further reduce toxicity compared to IMPT and VMAT in OPC treatment. By employing 360 ELs and 30 beams in the proposed ELR method, delivery time can reach clinically acceptable levels without compromising plan toxicity when automatic beam sequencing is available. [ABSTRACT FROM AUTHOR]

Objectives: The goal of this study is to validate different CBCT correction methods to select the superior method that can be used for dose evaluation in breast cancer patients with large anatomical changes treated with photon irradiation. Materials and method: Seventy-six breast cancer patients treated with a partial VMAT photon technique (70% conformal, 30% VMAT) were included in this study. All patients showed at least a 5 mm variation (swelling or shrinkage) of the breast on the CBCT compared to the planning-CT (pCT) and had a repeat-CT (rCT) for dose evaluation acquired within 3 days of this CBCT. The original CBCT was corrected using four methods: (1) HU-override correction (CBCTHU), (2) analytical correction and conversion (CBCTCC), (3) deep learning (DL) correction (CTDL) and (4) virtual correction (CTV). Image quality evaluation consisted of calculating the mean absolute error (MAE) and mean error (ME) within the whole breast clinical target volume (CTV) and the field of view of the CBCT minus 2 cm (CBCT-ROI) with respect to the rCT. The dose was calculated on all image sets using the clinical treatment plan for dose and gamma passing rate analysis. Results: The MAE of the CBCT-ROI was below 66 HU for all corrected CBCTs, except for the CBCTHU with a MAE of 142 HU. No significant dose differences were observed in the CTV regions in the CBCTCC, CTDL and CTv. Only the CBCTHU deviated significantly (p < 0.01) resulting in 1.7% (± 1.1%) average dose deviation. Gamma passing rates were > 95% for 2%/2 mm for all corrected CBCTs. Conclusion: The analytical correction and conversion, deep learning correction and virtual correction methods can be applied for an accurate CBCT correction that can be used for dose evaluation during the course of photon radiotherapy of breast cancer patients. [ABSTRACT FROM AUTHOR]

• Our offline adaptive clinical workflow for proton radiotherapy in oesophageal cancer assured adequate target dose coverage. • Target dose coverage was mainly affected by diaphragm displacements in VMAT, and target displacements in IMPT. • Most clinically relevant replanning was performed in the first treatment week. • The difference of organ-at-risk dose between IMPT and VMAT remained unchanged during treatment, ensuring adequate model-based patient selection. In the Netherlands, oesophageal cancer (EC) patients are selected for intensity modulated proton therapy (IMPT) using the expected normal tissue complication probability reduction (ΔNTCP) when treating with IMPT compared to volumetric modulated arc therapy (VMAT). In this study, we evaluate the robustness of the first EC patients treated with IMPT in our clinic in terms of target and organs-at-risk (OAR) dose with corresponding NTCP, as compared to VMAT. For 20 consecutive EC patients, clinical IMPT and VMAT plans were created on the average planning 4DCT. Both plans were robustly evaluated on weekly repeated 4DCTs and if target coverage degraded, replanning was performed. Target coverage was evaluated for complete treatment trajectories with and without replanning. The planned and accumulated mean lung dose (MLD) and mean heart dose (MHD) were additionally evaluated and translated into NTCP. Replanning in the clinic was performed more often for IMPT (15x) than would have been needed for VMAT (8x) (p = 0.11). Both adaptive treatments would have resulted in adequate accumulated target dose coverage. Replanning in the first week of treatment had most clinical impact, as anatomical changes resulting in insufficient accumulated target coverage were already observed at this stage. No differences were found in MLD between the planned dose and the accumulated dose. Accumulated MHD differed from the planned dose (p < 0.001), but since these differences were similar for VMAT and IMPT (1.0 and 1.5 Gy, respectively), the ΔNTCP remained unchanged. Following an adaptive clinical workflow, adequate target dose coverage and stable OAR doses with corresponding NTCPs was assured for both IMPT and VMAT. [ABSTRACT FROM AUTHOR]

Background: Time‐resolved 4D cone beam–computed tomography (4D‐CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D‐CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose calculations. Deep learning can be used to correct CT numbers and generate synthetic CTs (sCTs) that can enable CBCT‐based proton dose calculations. Purpose: In this work, sparse view 4D‐CBCTs were converted into 4D‐sCT utilizing a deep convolutional neural network (DCNN). 4D‐sCTs were evaluated in terms of image quality and dosimetric accuracy to determine if accurate proton dose calculations for adaptive proton therapy workflows of lung cancer patients are feasible. Methods: A dataset of 45 thoracic cancer patients was utilized to train and evaluate a DCNN to generate 4D‐sCTs, based on sparse view 4D‐CBCTs reconstructed from projections acquired with a 3D acquisition protocol. Mean absolute error (MAE) and mean error were used as metrics to evaluate the image quality of single phases and average 4D‐sCTs against 4D‐CTs acquired on the same day. The dosimetric accuracy was checked globally (gamma analysis) and locally for target volumes and organs‐at‐risk (OARs) (lung, heart, and esophagus). Furthermore, 4D‐sCTs were also compared to 3D‐sCTs. To evaluate CT number accuracy, proton radiography simulations in 4D‐sCT and 4D‐CTs were compared in terms of range errors. The clinical suitability of 4D‐sCTs was demonstrated by performing a 4D dose reconstruction using patient specific treatment delivery log files and breathing signals. Results: 4D‐sCTs resulted in average MAEs of 48.1 ± 6.5 HU (single phase) and 37.7 ± 6.2 HU (average). The global dosimetric evaluation showed gamma pass ratios of 92.3% ± 3.2% (single phase) and 94.4% ± 2.1% (average). The clinical target volume showed high agreement in D98 between 4D‐CT and 4D‐sCT, with differences below 2.4% for all patients. Larger dose differences were observed in mean doses of OARs (up to 8.4%). The comparison with 3D‐sCTs showed no substantial image quality and dosimetric differences for the 4D‐sCT average. Individual 4D‐sCT phases showed slightly lower dosimetric accuracy. The range error evaluation revealed that lung tissues cause range errors about three times higher than the other tissues. Conclusion: In this study, we have investigated the accuracy of deep learning–based 4D‐sCTs for daily dose calculations in adaptive proton therapy. Despite image quality differences between 4D‐sCTs and 3D‐sCTs, comparable dosimetric accuracy was observed globally and locally. Further improvement of 3D and 4D lung sCTs could be achieved by increasing CT number accuracy in lung tissues. [ABSTRACT FROM AUTHOR]

Purpose: To perform a dosimetric comparison of intensity-modulated radiotherapy (IMRT), passive scattering proton therapy (PSPT), and intensity-modulated proton therapy (IMPT) to the para-aortic (PA) nodal region in women with locally advanced gynecologic malignancies. Methods and Materials: The CT treatment planning scans of 10 consecutive patients treated with IMRT to the pelvis and PA nodes were identified. The clinical target volume was defined by the primary tumor for patients with cervical cancer and by the vagina and paravaginal tissues for patients with endometrial cancer, in addition to the regional lymph nodes. The IMRT, PSPT, and IMPT plans were generated using the Eclipse Treatment Planning System and were analyzed for various dosimetric endpoints. Two groups of treatment plans including proton radiotherapy were created: IMRT to pelvic nodes with PSPT to PA nodes (PSPT/IMRT), and IMRT to pelvic nodes with IMPT to PA nodes (IMPT/IMRT). The IMRT and proton RT plans were optimized to deliver 50.4 Gy or Gy (relative biologic effectiveness [RBE)), respectively. Dose–volume histograms were analyzed for all of the organs at risk. The paired t test was used for all statistical comparison. Results: The small-bowel V20, V30, V35, andV40 were reduced in PSPT/IMRT by 11%, 18%, 27%, and 43%, respectively (p < 0.01). Treatment with IMPT/IMRT demonstrated a 32% decrease in the small-bowel V20. Treatment with PSPT/IMRT showed statistically significant reductions in the body V5–20; IMPT/IMRT showed reductions in the body V5–15. The dose received by half of both kidneys was reduced by PSPT/IMRT and by IMPT/IMRT. All plans maintained excellent coverage of the planning target volume. Conclusions: Compared with IMRT alone, PSPT/IMRT and IMPT/IMRT had a statistically significant decrease in dose to the small and large bowel and kidneys, while maintaining excellent planning target volume coverage. Further studies should be done to correlate the clinical significance of these findings. [ABSTRACT FROM AUTHOR]

• Optimal timing of re-planning was suggested for a comprehensive set of OARs. • Generic re-planning timing was suggested considering different combinations of OARs. • D mean increase due to anatomical changes were most frequently > 3 Gy in Supraglottic. • The 3rd week is suggested as the optimal timing of re-planning for 10 OARs. • A maximum of 3 re-plannings can guarantee D mean increase below 3 Gy for all OARs. Adaptive radiotherapy (ART) relies on re-planning to correct treatment variations, but the optimal timing of re-planning to account for dose changes in head and neck organs at risk (OARs) is still under investigation. We aimed to find out the optimal timing of re-planning in head and neck ART. A total of 110 head and neck cancer patients were retrospectively enrolled. A semi auto-segmentation method was applied to obtain the weekly mean dose (D mean) to OARs. The K-nearest-neighbour method was used for missing data imputation of weekly D mean. A dose deviation map was built using the planning D mean and weekly D mean values and then used to simulate different ART scenarios consisting of 1 to 6 re-plannings. The difference between accumulated D mean and planning D mean before re-planning (ΔD mean_acc_noART) and after re-planning (ΔD mean_acc_ART) were evaluated and compared. Among all the OARs, supraglottic showed the largest ΔD mean_acc_noART (1.23 ± 3.13 Gy) and most cases of ΔD mean_acc_noART > 3 Gy (26 patients). The 3rd week is suggested in the optimal timing of re-planning for 10 OARs. For all the organs except arytenoid, 2 re-plannings were able to guarantee the ΔD mean_acc_ART below 3 Gy while the average |ΔD mean_acc_ART | was below 1 Gy. ART scenarios of 2_4, 3_4, 3_5 (week of re-planning separated with "_") were able to guarantee ΔD mean_acc_ART of 99 % of patients below 3 Gy simultaneously for 19 OARs. The optimal timing of re-planning was suggested for different organs at risk in head and neck adaptive radiotherapy. Generic scenarios of timing and frequency for re-planning can be applied to guarantee the increase of accumulated mean dose within 3 Gy simultaneously for multiple organs. [ABSTRACT FROM AUTHOR]

Purpose: To develop a quantitative early decision making metric for prediction of breathing pattern and irregular breathing and validate the metric in a large patient population receiving clinical phase-sorted four-dimensional computed tomography (4DCT). Methods: This study employed three patient cohorts. The first cohort contained 47 patients, imaged with a nonclinical tidal volume metric. The second cohort contained a sample of 256 patients who received a clinical 4DCT. The third cohort contained 86 patients who received three 4DCT scans at 1-week increment during the course of radiotherapy. The second and third cohorts did not have tidal volume measurements, as per standard radiation oncology clinical practice. Based on a previously published technique that used a single abdominal surrogate, the ratio of extreme inhalation tidal volume to normal inhalation tidal volume (?) metric was calculated and the patient breathing pattern was characterized. The use of a single surrogate precluded the use of a ? determined by tidal volume, so a ?rel was defined based on the amplitude of the surrogate. Patients were classified as either Type 1 or Type 2, based on a previously published technique, where Type 1 patients were apneic at end of exhalation and Type 2 patients exhibited forced respiration. The Ansari-Bradley test was used to determine the statistical similarity between the Type 1 and Type 2 distributions. A Kruskal-Wallis one way analysis of variance was used to determine the statistical similarities among the classified breathing types, ?rel, and the qualified medical physicist denoted breathing classification (regular or irregular). Receiver operator characteristic curves were used to quantitatively determine optimal cutoff value (j?) and efficiency cutoff value (τ?) ?rel to provide a quantitative early warning of irregular breathing during 4DCT procedures. Results: The statistical tests show a significant consistency for the breathing pattern classifications between the physiologically measured cohort #1 and the remaining cohorts. The classification types were statistically different between Type 1 and Type 2 patients over all cohorts. Values of ?rel in excess of 1.72 indicated a substantial presence of irregular breathing that could negatively affect the quality of a 4DCT image dataset. Values of ?rel in lower than 1.45 indicated minimal presence of irregular breathing. For values of ?rel such that j? = ?rel = τ?, the decision to reacquire the 4DCT would be at the discretion of the physician. This accounted for only 11.9% of the patients in this study. The magnitude of ?rel held consistent over three weeks of treatment for 73% of the patients in cohort #3. Conclusions: The decision making metric based on ? was shown to be an accurate classifier of regular and irregular breathing patterns in a large patient population. Breathing type, as defined in a previous published work, was accurately classified by ?rel with the use of a single respiratory surrogate compared to the physiological use of multiple respiratory surrogates. This work provided a quantitative early decision making metric to quickly and accurately assess breathing patterns as well as the presence and magnitude of irregular breathing during 4DCT. [ABSTRACT FROM AUTHOR]

• First study to report clinical experiences using robustly optimised IMPT in nasopharyngeal cancer. • Dose accumulation performed on robustly evaluated weekly repeat CTs for 25 patients. • Plan adaptation rate was low (2/25 patients). • Target coverage, critical organ maximum doses and NTCP were stable despite uncertainties and anatomy changes. To evaluate the dosimetric changes occurring over the treatment course for nasopharyngeal carcinoma (NPC) patients treated with robustly optimised intensity modulated proton therapy (IMPT). 25 NPC patients were treated to two dose levels (CTV1: 70 Gy, CTV2: 54.25 Gy) with robustly optimised IMPT plans. Robustness evaluation was performed over 28 error scenarios using voxel-wise minimum distributions to assess target coverage and voxel-wise maximum distributions to assess possible hotspots and critical organ doses. Daily CBCT was used for positioning and weekly repeat CTs (rCT) were taken, on which the plan dose was recalculated and robustly evaluated. Deformable image registration was used to warp and accumulate the nominal, voxel-wise minimum and maximum rCT dose distributions. Changes to target coverage, critical organ and normal tissue dose between the accumulated and planned doses were investigated. 2 patients required a plan adaptation due to reduced target coverage. The D98% in the accumulated voxel-wise minimum distribution was higher than planned for CTV1 in 24/25 patients and for CTV2 in 20/25 patients. Maximum doses to the critical organs remained acceptable in all patients. Other normal tissue doses showed some variation as a result of soft tissue deformations and weight change. Normal tissue complication probabilities for grade ≥ 2 dysphagia and grade ≥ 2 xerostomia remained similar to planned values. Robustly optimised IMPT plans, in combination with volumetric verification imaging and adaptive planning, provided robust target coverage and acceptable OAR dose variation in our NPC cohort when accumulated over longitudinal data. [ABSTRACT FROM AUTHOR]

Purpose: In modern conformal radiation therapy of distal esophageal cancer, target coverage can be affected by variations in the diaphragm position. We investigated if daily position verification (PV) extended by a diaphragm position correction would optimize target dose coverage for esophageal cancer treatment.Methods and Materials: For 15 esophageal cancer patients, intensity modulated proton therapy (IMPT) and volumetric modulated arc therapy (VMAT) plans were computed. Displacements of the target volume were correlated with diaphragm displacements using repeated 4-dimensional computed tomography images to determine the correction needed to account for diaphragm variations. Afterwards, target coverage was evaluated for 3 PV approaches based on: (1) bony anatomy (PV_B), (2) bony anatomy corrected for the diaphragm position (PV_BD) and (3) target volume (PV_T).Results: The cranial-caudal mean target displacement was congruent with almost half of the diaphragm displacement (y = 0.459x), which was used for the diaphragm correction in PV_BD. Target dose coverage using PV_B was adequate for most patients with diaphragm displacements up till 10 mm (≥94% of the dose in 98% of the volume [D98%]). For larger displacements, the target coverage was better maintained by PV_T and PV_BD. Overall, PV_BD accounted best for target displacements, especially in combination with tissue density variations (D98%: IMPT 94% ± 5%, VMAT 96% ± 5%). Diaphragm displacements of more than 10 mm were observed in 22% of the cases.Conclusions: PV_B was sufficient to achieve adequate target dose coverage in case of small deviations in diaphragm position. However, large deviations of the diaphragm were best mitigated by PV_BD. To detect the cases where target dose coverage could be compromised due to diaphragm position variations, we recommend monitoring of the diaphragm position before treatment through online imaging. [ABSTRACT FROM AUTHOR]

• Imaging data only achieved the highest C-index for LC. • Tumor probability maps improve outcome prediction models for LC and RC. • We showed that for all endpoints the best DL models were always multi-modal. • Hybrid models achieved the highest C-indexes results for RC, DMFS, and OS. Recently, deep learning (DL) algorithms showed to be promising in predicting outcomes such as distant metastasis-free survival (DMFS) and overall survival (OS) using pre-treatment imaging in head and neck cancer. Gross Tumor Volume of the primary tumor (GTVp) segmentation is used as an additional channel in the input to DL algorithms to improve model performance. However, the binary segmentation mask of the GTVp directs the focus of the network to the defined tumor region only and uniformly. DL models trained for tumor segmentation have also been used to generate predicted tumor probability maps (TPM) where each pixel value corresponds to the degree of certainty of that pixel to be classified as tumor. The aim of this study was to explore the effect of using TPM as an extra input channel of CT- and PET-based DL prediction models for oropharyngeal cancer (OPC) patients in terms of local control (LC), regional control (RC), DMFS and OS. We included 399 OPC patients from our institute that were treated with definitive (chemo)radiation. For each patient, CT and PET scans and GTVp contours, used for radiotherapy treatment planning, were collected. We first trained a previously developed 2.5D DL framework for tumor probability prediction by 5-fold cross validation using 131 patients. Then, a 3D ResNet18 was trained for outcome prediction using the 3D TPM as one of the possible inputs. The endpoints were LC, RC, DMFS, and OS. We performed 3-fold cross validation on 168 patients for each endpoint using different combinations of image modalities as input. The final prediction in the test set (100) was obtained by averaging the predictions of the 3-fold models. The C-index was used to evaluate the discriminative performance of the models. The models trained replacing the GTVp contours with the TPM achieved the highest C-indexes for LC (0.74) and RC (0.60) prediction. For OS, using the TPM or the GTVp as additional image modality resulted in comparable C-indexes (0.72 and 0.74). Adding predicted TPMs instead of GTVp contours as an additional input channel for DL-based outcome prediction models improved model performance for LC and RC. [ABSTRACT FROM AUTHOR]

• Relating organ LET to head and neck toxicity not feasible for current practice. • Does not contradict previous evidence for increased RBE for high LET. • Lack of variation in LET causes high required sample size. • Other methods to investigate RBE and LET in clinical practice are suggested. The relative biological effectiveness (RBE) of proton therapy is predicted to vary with the dose-weighted average linear energy transfer (LET d). However, RBE values may substantially vary for different clinical endpoints. Therefore, the aim of this study was to assess the feasibility of relating mean D⋅LET d parameters to patient toxicity for HNC patients treated with proton therapy. The delivered physical dose (D) and the voxel-wise product of D and LET d (D⋅LET d) distributions were calculated for 100 head and neck cancer (HNC) proton therapy patients using our TPS (Raystation v6R). The means and covariance matrix of the accumulated D and D⋅LET d of all relevant organs-at-risk (OARs) were used to simulate 2.500 data sets of different sizes. For each dataset, an attempt was made to add mean D⋅LET d parameters to a multivariable NTCP model based on mean D parameters of the same OAR for xerostomia, tube feeding and dysphagia. The likelihood of creating an NTCP model with statistically significant parameters (i.e. power) was calculated as a function of the simulated sample size for various RBE models. The sample size required to have a power of at least 80% to show an independent effect of mean D⋅LET d parameters on toxicity is over 15,000 patients for all toxicities. For current clinical practice, it is not feasible to directly model NTCP with both mean D and mean D⋅LET d of OARs. These findings should not be interpreted as a contradiction of previous evidence for the relationship between RBE and LET d. [ABSTRACT FROM AUTHOR]

Purpose: Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone‐beam CT (CBCT) can provide these daily images, but x‐ray scattering limits CBCT‐image quality and hampers dose calculation accuracy. The purpose of this study was to generate CBCT‐based synthetic CTs using a deep convolutional neural network (DCNN) and investigate image quality and clinical suitability for proton dose calculations in lung cancer patients. Methods: A dataset of 33 thoracic cancer patients, containing CBCTs, same‐day repeat CTs (rCT), planning‐CTs (pCTs), and clinical proton treatment plans, was used to train and evaluate a DCNN with and without a pCT‐based correction method. Mean absolute error (MAE), mean error (ME), peak signal‐to‐noise ratio, and structural similarity were used to quantify image quality. The evaluation of clinical suitability was based on recalculation of clinical proton treatment plans. Gamma pass ratios, mean dose to target volumes and organs at risk, and normal tissue complication probabilities (NTCP) were calculated. Furthermore, proton radiography simulations were performed to assess the HU‐accuracy of sCTs in terms of range errors. Results: On average, sCTs without correction resulted in a MAE of 34 ± 6 HU and ME of 4 ± 8 HU. The correction reduced the MAE to 31 ± 4HU (ME to 2 ± 4HU). Average 3%/3 mm gamma pass ratios increased from 93.7% to 96.8%, when the correction was applied. The patient specific correction reduced mean proton range errors from 1.5 to 1.1 mm. Relative mean target dose differences between sCTs and rCT were below ± 0.5% for all patients and both synthetic CTs (with/without correction). NTCP values showed high agreement between sCTs and rCT (<2%). Conclusion: CBCT‐based sCTs can enable accurate proton dose calculations for APT of lung cancer patients. The patient specific correction method increased the image quality and dosimetric accuracy but had only a limited influence on clinically relevant parameters. [ABSTRACT FROM AUTHOR]

• First time comparison of auto- and human segmentation accuracy using dose and NTCP. • DLC performs better than contour warping by DIR for majority of head and neck OARs. • Human segmentation of parotid glands is needed during adaptive radiotherapy (ART) • Semi auto-segmentation is feasible for accurate dose and NTCP calculation in ART. Accurate segmentation of organs-at-risk (OARs) is crucial but tedious and time-consuming in adaptive radiotherapy (ART). The purpose of this work was to automate head and neck OAR-segmentation on repeat CT (rCT) by an optimal combination of human and auto-segmentation for accurate prediction of Normal Tissue Complication Probability (NTCP). Human segmentation (HS) of 3 observers, deformable image registration (DIR) based contour propagation and deep learning contouring (DLC) were carried out to segment 15 OARs on 15 rCTs. The original treatment plan was re-calculated on rCT to obtain mean dose (D mean) and consequent NTCP-predictions. The average D mean and NTCP-predictions of the three observers were referred to as the gold standard to calculate the absolute difference of D mean and NTCP-predictions (|Δ D mean | and |ΔNTCP|). The average |Δ D mean | of parotid glands in HS was 1.40 Gy, lower than that obtained with DIR and DLC (3.64 Gy, p < 0.001 and 3.72 Gy, p < 0.001, respectively). DLC showed the highest |Δ D mean | in middle Pharyngeal Constrictor Muscle (PCM) (5.13 Gy, p = 0.01). DIR showed second highest |Δ D mean | in the cricopharyngeal inlet (2.85 Gy, p = 0.01). The semi auto-segmentation (SAS) adopted HS, DIR and DLC for segmentation of parotid glands, PCM and all other OARs, respectively. The 90th percentile |ΔNTCP|was 2.19%, 2.24%, 1.10% and 1.50% for DIR, DLC, HS and SAS respectively. Human segmentation of the parotid glands remains necessary for accurate interpretation of mean dose and NTCP during ART. Proposed semi auto-segmentation allows NTCP-predictions within 1.5% accuracy for 90% of the cases. [ABSTRACT FROM AUTHOR]

Purpose: To ensure target coverage in the treatment of esophageal cancer, a density override to the region of diaphragm motion can be applied in the optimization process. Here, we evaluate the benefit of this approach during robust optimization for intensity modulated proton therapy (IMPT) planning. Materials and methods: For 10 esophageal cancer patients, two robustly optimized IMPT plans were created either using (WDO) or not using (NDO) a diaphragm density override of 1.05 g/cm3 during plan optimization. The override was applied to the excursion of the diaphragm between exhale and inhale. Initial robustness evaluation was performed for plan acceptance (setup errors of 8 mm, range errors of ±3%), and subsequently, on all weekly repeated 4DCTs (setup errors of 2 mm, range errors of ±3%). Target coverage and hotspots were analyzed on the resulting voxel‐wise minimum (Vwmin) and voxel‐wise maximum (Vwmax) dose distributions. Results: The nominal dose distributions were similar for both WDO and NDO plans. However, visual inspection of the Vwmax of the WDO plans showed hotspots behind the right diaphragm override region. For one patient, target coverage and hotspots improved by applying the diaphragm override. We found no differences in target coverage in the weekly evaluations between the two approaches. Conclusion: The diaphragm override approach did not result in a clinical benefit in terms of planning and interfractional robustness. Therefore, we do not see added value in employing this approach as a default option during robust optimization for IMPT planning in esophageal cancer. [ABSTRACT FROM AUTHOR]

• Quality of Life (QOL)-optimised radiotherapy for head and neck cancer. • Efficient and consistent QOL-weighted NTCP-guided optimisation. • Prioritised sparing of OARs related to high impact toxicities. • QOL-based treatment plan evaluation and selection. • Systematic improvement of QOL compared to conventional VMAT. To evaluate the feasibility of semi-automatic Quality of Life (QOL)-weighted normal tissue complication probability (NTCP)-guided VMAT treatment plan optimisation in head and neck cancer (HNC) and compare predicted QOL to that obtained with conventional treatment. This study included 30 HNC patients who were treated with definitive radiotherapy. QOL-weighted NTCP-guided VMAT plans were optimised directly on 80 multivariable NTCP models of 20 common toxicities and symptoms on 4 different time points (6, 12, 18 and 24 months after radiotherapy) and each NTCP model was weighted relative to its impact on QOL. Planning results, NTCP and predicted QOL were compared with the clinical conventional VMAT plans. QOL-weighted NTCP-guided VMAT plans were clinically acceptable, had target coverage equally adequate as the clinical plans, but prioritised sparing of organs at risk (OAR) related to toxicities and symptoms that had the highest impact on QOL. NTCP was reduced for, e.g., dysphagia (−6.1% for ≥grade 2/−7.6% for ≥grade 3) and moderate-to-severe fatigue/speech problems/hoarseness (−0.7%/−1.5%/−2.5%) at 6 months, respectively. Concurrently, the average NTCP of toxicities related to salivary function increased with +0.4% to +5.7%. QOL-weighted NTCP-guided plans were produced in less time, were less dependent on the treatment planner experience and yielded more consistent results. The average predicted QOL improved by 0.7, 0.9, 1.0, and 1.1 points on a 0–100 scale (p < 0.001) at 6, 12, 18, and 24 months, respectively, compared to the clinical plans. Semi-automatic QOL-weighted NTCP-guided VMAT treatment plan optimisation is feasible. It prioritised sparing of OARs related to high-impact toxicities and symptoms and resulted in a systematic improvement of predicted QOL compared to conventional VMAT. [ABSTRACT FROM AUTHOR]

Background: A range pull-back device, such as a machine-related range shifter (MRS) or a universal patient-related range shifter (UPRS), is needed in pencil beam scanning technique to treat shallow tumors.Methods: Three UPRS made by QFix (Avondale, PA, USA) allow treating targets across the body: U-shaped bolus (UB), anterior lateral bolus (ALB), and couch top bolus. Head-and-neck (HN) patients who used the UPRS were tested. The in-air spot sizes were measured and compared in this study at air gaps: 6 cm, 16 cm, and 26 cm. Measurements were performed in a solid water phantom using a single-field optimization pencil beam scanning field with the ALB placed at 0, 10, and 20 cm air gaps. The two-dimensional dose maps at the middle of the spread-out Bragg peak were measured using ion chamber array MatriXX PT (IBA-Dosimetry, Schwarzenbruck, Germany) located at isocenter and compared with the treatment planning system.Results: A UPRS can be consistently placed close to the patient and maintains a relatively small spot size resulting in improved dose distributions. However, when a UPRS is non-removable (e.g. thick couch top), the quality of volumetric imaging is degraded due to their high Z material construction, hindering the value of Image-Guided Radiation Therapy (IGRT). Limitations of using UPRS with small air gaps include reduced couch weight limit, potential collision with patient or immobilization devices, and challenges using non-coplanar fields with certain UPRS. Our experience showed the combination of a U-shaped bolus exclusively for an HN target and an MRS as the complimentary device for head-and-neck targets as well as for all other treatment sites may be ideal to preserve the dosimetric advantages of pencil beam scanning proton treatments across the body.Conclusion: We have described how to implement UPRS and MRS for various clinical indications using the PBS technique, and comprehensively reviewed the advantage and disadvantages of UPRS and MRS. We recommend the removable UB only to be employed for the brain and HN treatments while an automated MRS is used for all proton beams that require RS but not convenient or feasible to use UB. [ABSTRACT FROM AUTHOR]

Purpose: Cone‐beam CT (CBCT)‐based synthetic CTs (sCT) produced with a deep convolutional neural network (DCNN) show high image quality, suggesting their potential usability in adaptive proton therapy workflows. However, the nature of such workflows involving DCNNs prevents the user from having direct control over their output. Therefore, quality control (QC) tools that monitor the sCTs and detect failures or outliers in the generated images are needed. This work evaluates the potential of using a range‐probing (RP)‐based QC tool to verify sCTs generated by a DCNN. Such a RP QC tool experimentally assesses the CT number accuracy in sCTs. Methods: A RP QC dataset consisting of repeat CTs (rCT), CBCTs, and RP acquisitions of seven head and neck cancer patients was retrospectively assessed. CBCT‐based sCTs were generated using a DCNN. The CT number accuracy in the sCTs was evaluated by computing relative range errors between measured RP fields and RP field simulations based on rCT and sCT images. Results: Mean relative range errors showed agreement between measured and simulated RP fields, ranging from −1.2% to 1.5% in rCTs, and from −0.7% to 2.7% in sCTs. Conclusions: The agreement between measured and simulated RP fields suggests the suitability of sCTs for proton dose calculations. This outcome brings sCTs generated by DCNNs closer toward clinical implementation within adaptive proton therapy treatment workflows. The proposed RP QC tool allows for CT number accuracy assessment in sCTs and can provide means of in vivo range verification. [ABSTRACT FROM AUTHOR]

• A tool is developed to preselect HNC patients for proton therapy. • The tool uses data from VMAT plan and/or delineation to predict proton indication. • Photon vs. proton plan comparison result was predicted with a 80% accuracy by tool. • Redundant plan comparisons were prevented by 68% using the tool. • This will significantly increase cost-effectiveness of patient selection for proton. In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons. This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT D mean to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy. Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49–68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57–68%, negative predictive value: 100%). The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT. [ABSTRACT FROM AUTHOR]

• Thoracic indications achieved clinically acceptable VMAT and IMPT treatment plans. • The superior dosimetric sparing of IMPT relative to VMAT was demonstrated. • Comprehensive 4D robustness evaluation of IMPT optimisation was conducted. • For this study, plan robustness with 3D robust optimisation was sufficient. • Accurate patient positioning and recurrent volumetric imaging remained essential. Compared to volumetric modulated arc therapy (VMAT), clinical benefits are anticipated when treating thoracic tumours with intensity-modulated proton therapy (IMPT). However, the current concern of plan robustness as a result of motion hampers its wide clinical implementation. To define an optimal protocol to treat lung and oesophageal cancers, we present a comprehensive evaluation of IMPT planning strategies, based on patient 4DCTs and machine log files. For ten lung and ten oesophageal cancer patients, a planning 4DCT and weekly repeated 4DCTs were collected. For these twenty patients, the CTV volume and motion were assessed based on the 4DCTs. In addition to clinical VMAT plans, layered rescanned 3D and 4D robust optimised IMPT plans (IMPT_3D and IMPT_4D respectively) were generated, and approved clinically, for all patients. The IMPT plans were then delivered in dry runs at our proton facility to obtain log files, and subsequently evaluated through our 4D robustness evaluation method (4DREM). With this method, for each evaluated plan, fourteen 4D accumulated scenario doses were obtained, representing 14 possible fractionated treatment courses. From VMAT to IMPT_3D, nominal D mean (lungs-GTV) decreased 2.75 ± 0.56 Gy RBE and 3.76 ± 0.92 Gy RBE over all lung and oesophageal cancer patients, respectively. A more pronounced reduction was verified for D mean (heart): 5.38 ± 7.36 Gy RBE (lung cases) and 9.51 ± 2.25 Gy RBE (oesophagus cases). Target coverage robustness of IMPT_3D was sufficient for 18/20 patients. Averaged dose in critical structures over all 4DREM scenarios changed only slightly for both IMPT_3D and IMPT_4D. Relative to IMPT_3D, no gain in IMPT_4D was observed. The dosimetric superiority of IMPT over VMAT has been established. For most thoracic tumours, our IMPT_3D planning protocol showed to be robust and clinically suitable. Nevertheless, accurate patient positioning and adapting to anatomical variations over the course of treatment remain compulsory. [ABSTRACT FROM AUTHOR]

Purpose: The capability of proton therapy to provide highly conformal dose distributions is impaired by range uncertainties. The aim of this work is to apply range probing (RP), a form of a proton radiography‐based quality control (QC) procedure for range accuracy assessment in head and neck cancer (HNC) patients in a clinical setting. Methods and Materials: This study included seven HNC patients. RP acquisition was performed using a multi‐layer ionization chamber (MLIC). Per patient, two RP frames were acquired within the first two weeks of treatment, on days when a repeated CT scan was obtained. Per RP frame, integral depth dose (IDD) curves of 81 spots around the treatment isocenter were acquired. Range errors are determined as a discrepancy between calculated IDDs in the treatment planning system and measured residual ranges by the MLIC. Range errors are presented relative to the water equivalent path length of individual proton spots. In addition to reporting results for complete measurement frames, an analysis, excluding range error contributions due to anatomical changes, is presented. Results: Discrepancies between measured and calculated ranges are smaller when performing RP calculations on the day‐specific patient anatomy rather than the planning CT. The patient‐specific range evaluation shows an agreement between calculated and measured ranges for spots in anatomically consistent areas within 3% (1.5 standard deviation). Conclusions: The results of an RP‐based QC procedure implemented in the clinical practice for HNC patients have been demonstrated. The agreement of measured and simulated proton ranges confirms the 3% uncertainty margin for robust optimization. Anatomical variations show a predominant effect on range accuracy, motivating efforts towards the implementation of adaptive radiotherapy. [ABSTRACT FROM AUTHOR]

[Display omitted] • Proton therapy can be as robust as photon therapy to inter-fraction motion. • Proton therapy significantly reduces organ at risk doses compared to photon therapy. • Two ITV-based treatment planning techniques for PBS-PT presented. Large-field photon radiotherapy is current standard in the treatment of cervical cancer patients. However, with the increasing availability of Pencil Beam Scanning Proton Therapy (PBS-PT) and robust treatment planning techniques, protons may have significant advantages for cervical cancer patients in the reduction of toxicity. In this study, PBS-PT and photon Volumetric Modulated Arc Therapy (VMAT) were compared, examining target coverage and organ at risk (OAR) dose, taking inter- and intra-fraction motion into account. Twelve cervical cancer patients were included in this in-silico planning study. In all cases, a planning CT scan, five weekly repeat CT scans (reCTs) and an additional reCT 10 min after the first reCT were available. Two-arc VMAT and robustly optimised two- and four-field (2F and 4F) PBS-PT plans were robustly evaluated on planCTs and reCTs using set-up and range uncertainty. Nominal OAR doses and voxel-wise minimum target coverage robustness were compared. Average voxel-wise minimum accumulated doses for pelvic target structures over all patients were adequate for both photon and proton treatment techniques (D98 > 95%, [91.7–99.3%]). Average accumulated dose of the para-aortic region was lower than the required 95%, D98 > 94.4% [91.1–98.2%]. With PBS-PT 4F, dose to all OARs was significantly lower than with VMAT. Major differences were observed for mean bowel bag V 15Gy : 60% [39–70%] for VMAT vs 30% [10–52%] and 32% [9–54%] for PBS-PT 2F and 4F and for mean bone marrow V 10Gy : 88% [82–97%] for VMAT vs 66% [60–73%] and 67% [60–75%] for PBS-PT 2F and 4F. Robustly optimised PBS-PT for cervical cancer patients shows equivalent target robustness against inter- and intra-fraction variability compared to VMAT, and offers significantly better OAR sparing. [ABSTRACT FROM AUTHOR]

• Probabilistic dose accumulation was performed for ten IMPT head and neck cancer. • Comparisons were made between different setup and range uncertainty settings. • A setup uncertainty setting of 2 mm was found to give sufficient target coverage. To establish optimal robust optimization uncertainty settings for clinical head and neck cancer (HNC) patients undergoing 3D image-guided pencil beam scanning (PBS) proton therapy. We analyzed ten consecutive HNC patients treated with 70 and 54.25 Gy RBE to the primary and prophylactic clinical target volumes (CTV) respectively using intensity-modulated proton therapy (IMPT). Clinical plans were generated using robust optimization with 5 mm/3% setup/range uncertainties (RayStation v6.1). Additional plans were created for 4, 3, 2 and 1 mm setup and 3% range uncertainty and for 3 mm setup and 3%, 2% and 1% range uncertainty. Systematic and random error distributions were determined for setup and range uncertainties based on our quality assurance program. From these, 25 treatment scenarios were sampled for each plan, each consisting of a systematic setup and range error and daily random setup errors. Fraction doses were calculated on the weekly verification CT closest to the date of treatment as this was considered representative of the daily patient anatomy. Plans with a 2 mm/3% setup/range uncertainty setting adequately covered the primary and prophylactic CTV (V 95 ≥ 99% in 98.8% and 90.8% of the treatment scenarios respectively). The average organ-at-risk dose decreased with 1.1 Gy RBE /mm setup uncertainty reduction and 0.5 Gy RBE /1% range uncertainty reduction. Normal tissue complication probabilities decreased by 2.0%/mm setup uncertainty reduction and by 0.9%/1% range uncertainty reduction. The results of this study indicate that margin reduction below 3 mm/3% is possible but requires a larger cohort to substantiate clinical introduction. [ABSTRACT FROM AUTHOR]

The treatment of moving targets with pencil beam scanned proton therapy (PBS-PT) may rely on rescanning strategies to smooth out motion induced dosimetric disturbances. PBS-PT machines, such as Proteus®Plus (PPlus) and Proteus®One (POne), deliver a continuous or a pulsed beam, respectively. In PPlus, scaled (or no) rescanning can be applied, while POne implies intrinsic 'rescanning' due to its pulsed delivery. We investigated the efficacy of these PBS-PT delivery types for the treatment of lung tumours. In general, clinically acceptable plans were achieved, and PPlus and POne showed similar effectiveness. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep convolutional neural networks. In this study, we compared sCTs based on CBCTs and MRs for head and neck (H&N) cancer patients in terms of image quality and proton dose calculation accuracy. A dataset of 27 H&N-patients, treated with proton therapy (PT), containing planning CTs (pCTs), repeat CTs, CBCTs and MRs were used to train two neural networks to convert either CBCTs or MRs into sCTs. Image quality was quantified by calculating mean absolute error (MAE), mean error (ME) and Dice similarity coefficient (DSC) for bones. The dose evaluation consisted of a systematic non-clinical analysis and a clinical recalculation of actually used proton treatment plans. Gamma analysis was performed for non-clinical and clinical treatment plans. For clinical treatment plans also dose to targets and organs at risk (OARs) and normal tissue complication probabilities (NTCP) were compared. CBCT-based sCTs resulted in higher image quality with an average MAE of 40 ± 4 HU and a DSC of 0.95, while for MR-based sCTs a MAE of 65 ± 4 HU and a DSC of 0.89 was observed. Also in clinical proton dose calculations, sCTCBCT achieved higher average gamma pass ratios (2%/2 mm criteria) than sCTMR (96.1% vs. 93.3%). Dose-volume histograms for selected OARs and NTCP-values showed a very small difference between sCTCBCT and sCTMR and a high agreement with the reference pCT. CBCT- and MR-based sCTs have the potential to enable accurate proton dose calculations valuable for daily adaptive PT. Significant image quality differences were observed but did not affect proton dose calculation accuracy in a similar manner. Especially the recalculation of clinical treatment plans showed high agreement with the pCT for both sCTCBCT and sCTMR. [ABSTRACT FROM AUTHOR]

Purpose: The number of pencil beam scanned proton therapy (PBS‐PT) facilities equipped with cone‐beam computed tomography (CBCT) imaging treating thoracic indications is constantly rising. To enable daily internal motion monitoring during PBS‐PT treatments of thoracic tumors, we assess the performance of Motion‐Aware RecOnstructiOn method using Spatial and Temporal Regularization (MA‐ROOSTER) four‐dimensional CBCT (4DCBCT) reconstruction for sparse‐view CBCT data and a realistic data set of patients treated with proton therapy. Methods: Daily CBCT projection data for nine non‐small cell lung cancer (NSCLC) patients and one SCLC patient were acquired at a proton gantry system (IBA Proteus® One). Four‐dimensional CBCT images were reconstructed applying the MA‐ROOSTER and the conventional phase‐correlated Feldkamp‐Davis‐Kress (PC‐FDK) method. Image quality was assessed by visual inspection, contrast‐to‐noise ratio (CNR), signal‐to‐noise ratio (SNR), and the structural similarity index measure (SSIM). Furthermore, gross tumor volume (GTV) centroid motion amplitudes were evaluated. Results: Image quality for the 4DCBCT reconstructions using MA‐ROOSTER was superior to the PC‐FDK reconstructions and close to FDK images (median CNR: 1.23 [PC‐FDK], 1.98 [MA‐ROOSTER], and 1.98 [FDK]; median SNR: 2.56 [PC‐FDK], 4.76 [MA‐ROOSTER], and 5.02 [FDK]; median SSIM: 0.18 [PC‐FDK vs FDK], 0.31 [MA‐ROOSTER vs FDK]). The improved image quality of MA‐ROOSTER facilitated GTV contour warping and realistic motion monitoring for most of the reconstructions. Conclusion: MA‐ROOSTER based 4DCBCTs performed well in terms of image quality and appear to be promising for daily internal motion monitoring in PBS‐PT treatments of (N)SCLC patients. [ABSTRACT FROM AUTHOR]

• Model-based selection of patients with HNC for proton is clinically feasible. • Around 35% of HNC patients qualify for protons. • Most patients are selected based on ΔNTCP in dysphagia-related models. • Patients with advanced and pharyngeal tumor have higher probability to be selected. In the Netherlands, head and neck cancer (HNC) patients qualify for intensity modulated proton therapy (IMPT) based on model-based selection (MBS). The aim of this study was to evaluate the first experience in MBS of HNC patients. Patients who were subjected to MBS (Jan 2018–Sep 2019) were evaluated. A VMAT plan was created for all patients with optimal sparing of organ at risks (OARs) in normal tissue complication probability (NTCP) models for a number of toxicities. An IMPT plan was created only for those with NTCP difference (ΔNTCP) between VMAT and best-case scenario for proton (assuming 0 Gy dose for all OARs in IMPT plan) that exceeded any ΔNTCP-thresholds defined in Dutch National Indication Protocol. These patients qualified for a robust IMPT-plan creation with similar target doses and subsequent plan comparison. Of 227 patients, 141 (62%) qualified for plan comparison, of which 80 (35%) were eventually selected for proton therapy. Most patients were selected based on the ΔNTCP for dysphagia-related toxicities. The selection rate was higher among patients with advanced disease, pharyngeal tumors, and/or baseline complaints. A significant reduction in all OAR doses and NTCP values was obtained with IMPT compared with VMAT in both selected and non-selected patients, but more pronounced in patients selected for protons. Model-based selection of patients with HNC for proton therapy is clinically feasible. Approximately one third of HNC patients qualify for protons and these patients have the highest probability to benefit from protons in terms of toxicity prevention. [ABSTRACT FROM AUTHOR]

• IMPT accomplishes a significant and consistent dose reduction to OARs. • IMPT has comparable robustness compared to VMAT for oesophageal cancer. • Re-planning was required more often for IMPT compared to VMAT. Intensity-modulated proton therapy (IMPT) is expected to result in clinical benefits by lowering radiation dose to organs-at-risk (OARs). However, there are concerns about plan robustness due to motion. To address this uncertainty we evaluated the robustness of IMPT compared to the widely clinically used volumetric modulated arc therapy (VMAT) on weekly repeated computed tomographies (CT). 19 patients with oesophageal cancer were evaluated. IMPT and VMAT plans were created on a planning 4-Dimensional CT (p4DCT) and evaluated on weekly repeated 4DCTs (r4DCT). In case of inadequate target coverage or unacceptable high dose to normal tissue, re-planning was performed. Dose distributions of the r4DCTs were warped to p4DCT, resulting in an estimated actual given dose (EAGD). Compared to VMAT, IMPT resulted in significantly lowered dose to heart, lungs, spleen, liver and kidneys. For IMPT, target coverage was adequate (after max 1 replanning) in 17/19 cases. In two cases target coverage remained insufficient. However, in one of these patients the summed dose was insufficient (due to tumor shrinkage) while weekly coverage was adequate. For the other patient the target coverage was also insufficient by VMAT, due to large anatomical changes during treatment. For VMAT, adequate target coverage was achieved in 18/19 cases without re-planning. However, for reasons of high OAR dose re-planning was required in two cases. IMPT reduces the dose to OARs significantly, while achieving adequate target coverage in the majority of patients. Re-planning was necessary for both IMPT and VMAT due to anatomical changes. [ABSTRACT FROM AUTHOR]

The article highlights a study on initial clinical outcomes for prostate cancer patients undergoing adjuvant or salvage proton therapy after radical prostatectomy. It reports that adjuvant radiotherapy has shown benefits in biochemical relapse-freeand overall survival in large cooperative group randomized clinical trials despite mild to moderate increased toxicity.