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Background and Purpose: The development of Magnetic Resonance Imaging (MRI)-only Radiotherapy (RT) represents a significant advancement in the field. This study introduces a Deep Learning (DL) algorithm designed to quickly generate synthetic CT (sCT) images from low-field MR images in the brain, an area not yet explored. Methods: Fifty-six patients were divided into training (32), validation (8), and test (16) groups. A conditional Generative Adversarial Network (cGAN) was trained on pre-processed axial paired images. sCTs were validated using mean absolute error (MAE) and mean error (ME) calculated within the patient body. Intensity Modulated Radiation Therapy (IMRT) plans were optimised on simulation MRI and calculated considering sCT and original CT as electron density (ED) map. Dose distributions using sCT and CT were compared using global gamma analysis at different tolerance criteria (2 %/2mm and 3 %/3mm) and evaluating the difference in estimating different Dose Volume Histogram (DVH) parameters for target and organs at risk (OARs). Results: The network generated sCTs of each single patient in less than two minutes (mean time = 103 ± 41 s). For test patients, the MAE was 62.1 ± 17.7 HU, and the ME was −7.3 ± 13.4 HU. Dose parameters on sCTs were within 0.5 Gy of those on original CTs. Gamma passing rates 2 %/2mm, and 3 %/3mm criteria were 99.5 %±0.5 %, and 99.7 %±0.3 %, respectively. Conclusion: The proposed DL algorithm generates in less than 2 min accurate sCT images in the brain for online adaptive radiotherapy, potentially eliminating the need for CT simulation in MR-only workflows for brain treatments.

Abstract Background Oligo-progression or further recurrence is an open issue in the multi-integrated management of oligometastatic disease (OMD). Re-irradiation with stereotactic body radiotherapy (re-SBRT) technique could represent a valuable treatment option to improve OMD clinical outcomes. MRI-guided allows real-time visualization of the target volumes and online adaptive radiotherapy (oART). The aim of this retrospective study is to evaluate the efficacy and toxicity profile of MRI-guided repeated SBRT (MRIg-reSBRT) in the OMD setting and propose a re-SBRT classification. Methods We retrospectively analyzed patients (pts) with recurrent liver metastases or abdominal metastatic lesions between 1 and 5 centimeters from liver candidate to MRIg-reSBRT showing geometric overlap between the different SBRT courses and assessing whether they were in field (type 1) or not (type 2). Results Eighteen pts completed MRIg-reSBRT course for 25 metastatic hepatic/perihepatic lesions from July 2019 to January 2020. A total of 20 SBRT courses: 15 Type 1 re-SBRT (75%) and 5 Type 2 re-SBRT (25%) was delivered. Mean interval between the first SBRT and MRIg-reSBRT was 8,6 months. Mean prescribed dose for the first treatment was 43 Gy (range 24–50 Gy, mean BEDα/β10=93), while 41 Gy (range 16–50 Gy, mean BEDα/β10=92) for MRIg-reSBRT. Average liver dose was 3,9 Gy (range 1–10 Gy) and 3,7 Gy (range 1,6–8 Gy) for the first SBRT and MRIg-reSBRT, respectively. No acute or late toxicities were reported at a median follow-up of 10,7 months. The 1-year OS and PFS was 73,08% and 50%, respectively. Overall Clinical Benefit was 54%. Conclusions MRIg-reSBRT could be considered an effective and safe option in the multi-integrated treatment of OMD.

Introduction: Organ motion (OM) and volumetric changes pose challenges in radiotherapy (RT) for locally advanced cervical cancer (LACC). Magnetic Resonance-guided Radiotherapy (MRgRT) combines improved MRI contrast with adaptive RT plans for daily anatomical changes. Our goal was to analyze cervico-uterine structure (CUS) changes during RT to develop strategies for managing OM. Materials and methods: LACC patients received chemoradiation by MRIdian system with a simultaneous integrated boost (SIB) protocol. Prescription doses of 55–50.6 Gy at PTV1 and 45–39.6 Gy at PTV2 were given in 22 and 25 fractions. Daily MRI scans were co-registered with planning scans and CUS changes were assessed.Six PTVs were created by adding 0.5, 0.7, 1, 1.3, 1.5, and 2 cm margins to the CUS, based on the simulation MRI. Adequate margins were determined to include 95 % of the CUSs throughout the entire treatment in 95 % of patients. Results: Analysis of 15 LACC patients and 372 MR scans showed a 31 % median CUS volume decrease. Asymmetric margins of 2 cm cranially, 0.5 cm caudally, 1.5 cm posteriorly, 2 cm anteriorly, and 1.5 cm on both sides were optimal for PTV, adapting to CUS variations. Post-14th fraction, smaller margins of 0.7 cm cranially, 0.5 cm caudally, 1.3 cm posteriorly, 1.3 cm anteriorly, and 1.3 cm on both sides sufficed. Conclusion: CUS mobility varies during RT, suggesting reduced PTV margins after the third week. MRgRT with adaptive strategies optimizes dose delivery, emphasizing the importance of streamlined IGRT with reduced PTV margins using a tailored MRgRT workflow with hybrid MRI-guided systems.

Abstract Background The THUNDER-2 phase II single institutional trial investigates the benefits of MRI-guided radiotherapy (MRIgRT) in treating locally advanced rectal cancer (LARC). This study focuses on evaluating the impact of escalating radiation therapy dose in non-responder patients using the Early Tumour Regression Index (ERI) for predicting complete response (CR). The trial’s primary endpoint is to increase the CR rate in non-responders by 10% and assess the feasibility of the delta radiomics-based MRIgRT predictive model. This interim analysis assesses the feasibility and safety of the proposed MRIgRT dose escalation strategy in terms of acute toxicity (gastrointestinal, genitourinary and haematological) and treatment adherence. Methods Stage cT2-3, N0-2, or cT4 patients with anal sphincter involvement, N0-2a, M0, but without high-risk features were enrolled. MRIgRT treatment consisted of a standard dose of 55 Gy to the Gross Tumor Volume (GTV) and mesorectum, and 45 Gy to the mesorectum and drainage nodes in 25 fractions with concomitant chemotherapy. 0.35 T MRI was used for simulation imaging and daily alignment. ERI was calculated at the 10th fraction. Non-responders with an ERI above 13.1 received intensified dose escalation from the 11th fraction, resulting in a total dose of 60.1 Gy. Acute toxicity was assessed using the CTCAE v.5 scale. Results From March 2021 to November 2022, 33 out of the total number of 63 patients to be enrolled (52.4%) were included, with one withdrawal unrelated to treatment. Sixteen patients (50%) underwent dose escalation. Treatment was well tolerated, with only one patient (3.1%) in the standard treatment group experiencing acute Grade 3 diarrhea, proctitis, and cystitis. No significant differences in toxicity were observed between the two groups (p = 0.5463). Conclusions MRIgRT treatment with dose escalation up to 60.1 Gy is well tolerated in LARC patients predicted as non-responders by ERI, confirming the feasibility and safety of this approach. The THUNDER-2 trial’s primary and secondary endpoints will be fully analyzed when all planned patients will be enrolled.

Introduction: Advancements in MRI-guided radiotherapy (MRgRT) enable clinical parallel workflows (CPW) for online adaptive planning (oART), allowing medical physicists (MPs), physicians (MDs), and radiation therapists (RTTs) to perform their tasks simultaneously. This study evaluates the impact of this upgrade on the total treatment time by analyzing each step of the current 0.35T-MRgRT workflow. Methods: The time process of the workflow steps for 254 treatment fractions in 0.35 MRgRT was examined. Patients have been grouped based on disease site, breathing modality (BM) (BHI or FB), and fractionation (stereotactic body RT [SBRT] or standard fractionated long course [LC]). The time spent for the following workflow steps in Adaptive Treatment (ADP) was analyzed: Patient Setup Time (PSt), MRI Acquisition and Matching (MRt), MR Re-contouring Time (RCt), Re-Planning Time (RPt), Treatment Delivery Time (TDt). Also analyzed was the timing of treatments that followed a Simple workflow (SMP), without the online re-planning (PSt + MRt + TDt.). Results: The time analysis revealed that the ADP workflow (median: 34 min) is significantly (p

IntroductionContouring of gas pockets is a time consuming step in the workflow of adaptive radiotherapy. We would like to better understand which gas pockets electronic densitiy should be used and the dosimetric impact on adaptive MRgRT treatment.Materials and methods21 CT scans of patients undergoing SBRT were retrospectively evaluated. Anatomical structures were contoured: Gross Tumour Volume (GTV), stomach (ST), small bowel (SB), large bowel (LB), gas pockets (GAS) and gas in each organ respectively STG, SBG, LBG. Average HU in GAS was converted in RED, the obtained value has been named as Gastrointestinal Gas RED (GIGED). Differences of average HU in GAS, STG, SBG and LBG were computed. Three treatment plans were calculated editing the GAS volume RED that was overwritten with: air RED (0.0012), water RED (1.000), GIGED, generating respectively APLAN, WPLAN and the GPLAN. 2-D dose distributions were analyzed by gamma analysis. Parameter called active gas volume (AGV) was calculated as the intersection of GAS with the isodose of 5% of prescription dose.ResultsAverage HU value contained in GAS results to be equal to -620. No significative difference was noted between the average HU of gas in different organ at risk. Value of Gamma Passing Rate (GPR) anticorrelates with the AGV for each plan comparison and the threshold value for GPR to fall below 90% is 41, 60 and 139 cc for WPLANvsAPLAN, GPLANvsAPLAN and WPLANvsGPLAN respectively.DiscussionsGIGED is the right RED for Gastrointestinal Gas. Novel AGV is a useful parameter to evaluate the effect of gas pocket on dose distribution.

IntroductionPatients treatment compliance increases during free-breathing (FB) treatment, taking generally less time and fatigue with respect to deep inspiration breath-hold (DIBH). This study quantifies the gross target volume (GTV) motion on cine-MRI of apical lung lesions undergoing a SBRT in a MR-Linac and supports the patient specific treatment gating pre-selection.Material and methodsA total of 12 patients were retrospectively enrolled in this study. During simulation and treatment fractions, sagittal 0.35 T cine-MRI allows real-time GTV motion tracking. Cine-MRI has been exported, and an in-house developed MATLAB script performed image segmentation for measuring GTV centroid position on cine-MRI frames. Motion measurements were performed during the deep inspiration phase of DIBH patient and during all the session for FB patient. Treatment plans of FB patients were reoptimized using the same cost function, choosing the 3 mm GTV-PTV margin used for DIBH patients instead of the original 5 mm margin, comparing GTV and OARs DVH for the different TP.ResultsGTV centroid motion is

Immunotherapy has become a cornerstone for the treatment of renal cell carcinoma. Nevertheless, some patients are resistant to immune checkpoint inhibitors. The possibility to identify patients who cannot benefit from immunotherapy is a relevant clinical challenge. We analyzed the association between several radiomics features and response to immunotherapy in 53 patients treated with checkpoint inhibitors for advanced renal cell carcinoma. We found that the following features are associated with progression of disease as best tumor response: F_stat.range (p

Abstract Hybrid magnetic resonance (MR)-guided linear accelerators represent a new horizon in the field of radiation oncology. By harnessing the favorable combination of on-board MR-imaging with the possibility to daily recalculate the treatment plan based on real-time anatomy, the accuracy in target and organs-at-risk identification is expected to be improved, with the aim to provide the best tailored treatment. To date, two main MR-linac hybrid machines are available, Elekta Unity and Viewray MRIdian. Of note, compared to conventional linacs, these devices raise practical issues due to the positioning phase for the need to include the coil in the immobilization procedure and in order to perform the best reproducible positioning, also in light of the potentially longer treatment time. Given the relative novelty of this technology, there are few literature data regarding the procedures and the workflows for patient positioning and immobilization for MR-guided daily adaptive radiotherapy. In the present narrative review, we resume the currently available literature and provide an overview of the positioning and setup procedures for all the anatomical districts for hybrid MR-linac systems.

Magnetic Resonance-guided Radiotherapy (MRgRT) allows direct monitoring of treated volumes. The aim of this study was to investigate the feasibility of a new gating strategy consisting in using an isodose as boundary. Forty-four patients treated for thoracic and abdominal lesions using MRgRT were enrolled. The accuracy of the new strategy was compared to the conventional one in terms of area improvement available for gating without compromising target coverage. A mean increase of 24% for lung, 15% for liver and 11% for pancreas was observed, demonstrating how the new method can be useful in challenging situations with low dose conformality.

Abstract Background Internal Target Volume (ITV) is one of the most common strategies to passively manage tumour motion in Radiotherapy (RT). The reliability of this approach is based on the assumption that the tumour motion estimated during pre-treatment 4D Computed Tomography (CT) acquisition is representative of the motion during the whole RT treatment. With the introduction of Magnetic Resonance-guided RT (MRgRT), it has become possible to monitor tumour motion during the treatment and verify this assumption. Aim of this study was to investigate the reliability of the ITV approach with respect to the treatment fraction time (TFT) in abdominal and thoracic lesions. Methods A total of 12 thoracic and 15 abdominal lesions was analysed. Before treatment, a 10-phase 4DCT was acquired and ITV margins were estimated considering the envelope of the lesion contoured on the different 4DCT phases. All patients underwent MRgRT treatment in free-breathing, monitoring the tumour position on a sagittal plane with 4 frames per second (sec). ITV margins were projected on the tumour trajectory and the percentage of treatment time in which the tumour was inside the ITV (%TT) was measured to varying of TFT. The ITV approach was considered moderately reliable when %TT ≥ 90% and strongly reliable when %TT ≥ 95%. Additional ITV margins required to achieve %TT ≥ 95% were also calculated. Results In the analysed cohort of patients, ITV strategy can be considered strongly reliable only for lung lesions with TFT ≤ 7 min (min). The ITV strategy can be considered only moderately reliable for abdominal lesions, and additional margins are required to obtain %TT ≥ 95%. Considering a TFT ≤ 4 min, additional margins of 2 mm in cranio-caudal (CC) and 1 mm in antero-posterior (AP) are suggested for pancreatic lesions, 3 mm in CC and 2 mm in AP for renal and liver ones. Conclusions On the basis of the analysed cases, the ITV approach appears to be reliable in the thorax, while it results more challenging in the abdomen, due to the higher uncertainty in ITV definition and to the observed larger intra and inter-fraction motion variability. The addition of extra margins based on the TFT may represent a valid tool to compensate such limitations.

PurposeAs a discipline in its infancy, online adaptive RT (ART) needs new ontologies and ad hoc criteria to evaluate the appropriateness of its use in clinical practice. In this experience, we propose a predictive model able to quantify the dosimetric impact due to daily inter-fraction variability in a standard RT breast treatment, to identify in advance the treatment fractions where patients might benefit from an online ART approach.MethodsThe study was focused on right breast cancer patients treated using standard adjuvant RT on an artificial intelligence (AI)-based linear accelerator. Patients were treated with daily CBCT images and without online adaptation, prescribing 40.05 Gy in 15 fractions, with four IMRT tangential beams. ESTRO guidelines were followed for the delineation on planning CT (pCT) of organs at risk and targets. For each patient, all the CBCT images were rigidly aligned to pCT: CTV and PTV were manually re-contoured and the original treatment plan was recalculated. Various radiological parameters were measured on CBCT images, to quantify inter-fraction variability present in each RT fraction after the couch shifts compensation. The variation of these parameters was correlated with the variation of V95% of PTV (ΔV95%) using the Wilcoxon Mann–Whitney test. Fractions where ΔV95% > 2% were considered as adverse events. A logistic regression model was calculated considering the most significant parameter, and its performance was quantified with a receiver operating characteristic (ROC) curve.ResultsA total of 75 fractions on 5 patients were analyzed. The body variation between daily CBCT and pCT along the beam axis with the highest MU was identified as the best predictor (p = 0.002). The predictive model showed an area under ROC curve of 0.86 (95% CI, 0.82–0.99) with a sensitivity of 85.7% and a specificity of 83.8% at the best threshold, which was equal to 3 mm.ConclusionA novel strategy to identify treatment fractions that may benefit online ART was proposed. After image alignment, the measure of body difference between daily CBCT and pCT can be considered as an indirect estimator of V95% PTV variation: a difference larger than 3 mm will result in a V95% decrease larger than 2%. A larger number of observations is needed to confirm the results of this hypothesis-generating study.

The aim of this study is to investigate the role of Delta Radiomics analysis in the prediction of one-year local control (1yLC) in patients affected by locally advanced pancreatic cancer (LAPC) and treated using Magnetic Resonance guided Radiotherapy (MRgRT). A total of 35 patients from two institutions were enrolled: A 0.35 Tesla T2*/T1 MR image was acquired for each case during simulation and on each treatment fraction. Physical dose was converted in biologically effective dose (BED) to compensate for different radiotherapy schemes. Delta Radiomics analysis was performed considering the gross tumour volume (GTV) delineated on MR images acquired at BED of 20, 40, and 60 Gy. The performance of the delta features in predicting 1yLC was investigated in terms of Wilcoxon Mann–Whitney test and area under receiver operating characteristic (ROC) curve (AUC). The most significant feature in predicting 1yLC was the variation of cluster shade calculated at BED = 40 Gy, with a p-value of 0.005 and an AUC of 0.78 (0.61–0.94). Delta Radiomics analysis on low-field MR images might play a promising role in 1yLC prediction for LAPC patients: further studies including an external validation dataset and a larger cohort of patients are recommended to confirm the validity of this preliminary experience.

Background: Recent studies have highlighted the potentialities of a radiobiological parameter, the early regression index (ERITCP), in the treatment response prediction for rectal cancer patients treated with chemoradiotherapy followed by surgery. The aim of this study is to evaluate the performance of this parameter in predicting pathological complete response (pCR) in the context of low field MR guided radiotherapy (MRgRT) for cervical cancer (CC). Methods: A total of 16 patients affected by CC were enrolled. All patients underwent a MRgRT treatment, with prescription of 50.6 Gy in 22 fractions. A daily MR acquisition was performed at simulation and on each treatment fraction. Gross tumor volume (GTV) was delineated on the MR images acquired at the following biological effective dose (BED) levels: 14, 28, 42, 54 and 62 Gy. The ERITCP was calculated at the different BED levels and its predictive performance was quantified in terms of receiver operating characteristic (ROC) curve. Results: pCR was observed in 11/16 cases. The highest discriminative power of ERITCP was reported when a BED value of 28 Gy is reached, obtaining an area under curve (AUC) of 0.84. Conclusion: This study confirmed ERITCP as a promising response biomarker also for CC, although further studies with larger cohort of patients are recommended.