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Purpose of this study is to evaluate patient characteristics, treatments and outcomes in bone metastasis radiotherapy practice. Patients for whom radiotherapy for bone metastasis was planned at 26 institutions in Japan between December 2020 and March 2021 were consecutively registered in this prospective, observational study. Study measures included patient characteristics, pain relief, skeletal-related events (SREs), overall survival and incidence of radiation-related adverse events. Pain was evaluated using a numerical rating scale (NRS) from 0 to 10. Irradiated dose was analyzed by the biologically effective dose (BED) assuming α/β = 10. Overall, 232 patients were registered; 224 patients and 302 lesions were fully analyzed. Eastern Cooperative Oncology Group Performance Status was 0/1/2/3/4 in 23%/38%/22%/13%/4%; 59% of patients had spinal metastases and 84% had painful lesions (NRS ≥ 2). BED was <20 Gy (in 27%), 20–30 Gy (24%), 30–40 Gy (36%) and ≥ 40 Gy (13%); 9% of patients were treated by stereotactic body radiotherapy. Grade 3 adverse events occurred in 4% and no grade 4–5 toxicity was reported. Pain relief was achieved in 52% at 2 months. BED is not related to pain relief. The cumulative incidence of SREs was 6.5% (95% confidence interval (CI) 3.1–9.9) at 6 months; no factors were significantly associated with SREs. With spinal lesions, 18% of patients were not ambulatory at baseline and 50% of evaluable patients in this group could walk at 2 months. The 6-month overall survival rate was 70.2% (95% CI 64.2–76.9%). In conclusion, we report real-world details of radiotherapy in bone metastasis. [ABSTRACT FROM AUTHOR]

Whereas extracellular vesicles (EVs) have been engineered for cargo loading, innovative strategies for it can still be developed. Here, we describe domain 4 (D4), a cholesterol‐binding domain derived from perfringolysin O, as a viable candidate for EV cargo loading. D4 and its mutants localized to the plasma membrane and the membranes of different vesicular structures in the cytoplasm, and facilitate the transport of proteins of interest (POIs) into EVs. D4‐EVs were internalized by recipient cells analogous to EVs engineered with CD9. Intracellular cargo discharge from D4‐EVs was successfully detected with the assistance of vesicular stomatitis virus glycoprotein. This study presents a novel strategy for recruiting POIs into EVs via a lipid‐binding domain that ensures content release in recipient cells. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to develop a normal tissue complication probability model using a machine learning approach (ML-based NTCP) to predict the risk of radiation-induced liver disease in hepatocellular carcinoma (HCC) patients. Materials and methods: The study population included 201 HCC patients treated with radiotherapy. The patients' medical records were retrospectively reviewed to obtain the clinical and radiotherapy data. Toxicity was defined by albumin-bilirubin (ALBI) grade increase. The normal liver dose-volume histogram was reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose (2 Gy/fraction and α/β = 2). Three types of ML-based classification models were used, a penalized logistic regression (PLR), random forest (RF), and gradient-boosted tree (GBT) model. Model performance was compared using the area under the receiver operating characteristic curve (AUROC). Internal validation was performed by 5-fold cross validation and external validation was done in 44 new patients. Results: Liver toxicity occurred in 87 patients (43.1%). The best individual model was the GBT model using baseline liver function, liver volume, and MLD as inputs and the best overall model was an ensemble of the PLR and GBT models. An AUROC of 0.82 with a standard deviation of 0.06 was achieved for the internal validation. An AUROC of 0.78 with a standard deviation of 0.03 was achieved for the external validation. The behaviors of the best GBT model were also in good agreement with the domain knowledge on NTCP. Conclusion: We propose the methodology to develop an ML-based NTCP model to estimate the risk of ALBI grade increase. [ABSTRACT FROM AUTHOR]

Simple Summary: Using a consistent experimental protocol, we found a large heterogeneity in the relative biological effectiveness (RBE) values of both proton and carbon-ion beams in various sarcomas and normal-tissue-derived cell lines. Our data suggest that proton beam therapy may be more beneficial for some types of tumors. In carbon-ion therapy, for some types of tumors, large heterogeneity in RBE should prompt consideration of dose reduction or an increased dose per fraction. In particular, a higher RBE value in normal tissues requires caution. Specific dose evaluations for tumor and normal tissues are needed for both proton and carbon-ion therapies. This study investigated variations in the relative biological effectiveness (RBE) values among various sarcoma and normal-tissue-derived cell lines (normal cell line) in proton beam and carbon-ion irradiations. We used a consistent protocol that specified the timing of irradiation after plating cells and detailed the colony formation assay. We examined the cell type dependence of RBE for proton beam and carbon-ion irradiations using four human sarcoma cell lines (MG63 osteosarcoma, HT1080 fibrosarcoma, SW872 liposarcoma, and SW1353 chondrosarcoma) and three normal cell lines (HDF human dermal fibroblast, hTERT-HME1 mammary gland, and NuLi-1 bronchus epithelium). The cells were irradiated with gamma rays, proton beams at the center of the spread-out Bragg peak, or carbon-ion beams at 54.4 keV/μm linear energy transfer. In all sarcoma and normal cell lines, the average RBE values in proton beam and carbon-ion irradiations were 1.08 ± 0.11 and 2.08 ± 0.36, which were consistent with the values of 1.1 and 2.13 used in current treatment planning systems, respectively. Up to 34% difference in the RBE of the proton beam was observed between MG63 and HT1080. Similarly, a 32% difference in the RBE of the carbon-ion beam was observed between SW872 and the other sarcoma cell lines. In proton beam irradiation, normal cell lines had less variation in RBE values (within 10%), whereas in carbon-ion irradiation, RBE values differed by up to 48% between hTERT-HME1 and NuLi-1. Our results suggest that specific dose evaluations for tumor and normal tissues are necessary for treatment planning in both proton and carbon-ion therapies. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the dosimetric advantages of daily adaptive radiotherapy (DART) in intensity‐modulated proton therapy (IMPT) for high‐risk prostate cancer by comparing estimated doses of the conventional non‐adaptive radiotherapy (NART) that irradiates according to an original treatment plan through the entire treatment and the DART that uses an adaptive treatment plan generated by using daily CT images acquired before each treatment. Methods: Twenty‐three patients with prostate cancer were included. A treatment plan with 63 Gy (relative biological effectiveness (RBE)) in 21 fractions was generated using treatment planning computed tomography (CT) images assuming that all patients had high‐risk prostate cancer for which the clinical target volume (CTV) needs to include prostate and the seminal vesicle (SV) in our treatment protocol. Twenty‐one adaptive treatment plans for each patient (total 483 data sets) were generated using daily CT images, and dose distributions were calculated. Using a 3 mm set‐up uncertainty in the robust optimization, the doses to the CTV, prostate, SV, rectum, and bladder were compared. Results: Estimated accumulated doses of NART and DART in the 23 patients were 60.81 ± 3.47 Gy (RBE) and 63.24 ± 1.04 Gy (RBE) for CTV D99 (p < 0.01), 62.99 ± 1.28 Gy (RBE) and 63.43 ± 1.33 Gy (RBE) for the prostate D99 (p = 0.2529), and 59.07 ± 5.19 Gy (RBE) and 63.17 ± 1.04 Gy (RBE) for SV D99 (p < 0.001). No significant differences were observed between NART and DART in the estimated accumulated dose for the rectum and bladder. Conclusion: Compared with the NART, DART was shown to be a useful approach that can maintain the dose coverage to the target without increasing the dose to the organs at risk (OAR) using the 3 mm set‐up uncertainty in the robust optimization in patients with high‐risk prostate cancer. [ABSTRACT FROM AUTHOR]

The prediction of liver Dmean with 3-dimensional radiation treatment planning (3DRTP) is time consuming in the selection of proton beam therapy (PBT), and deep learning prediction generally requires large and tumor-specific databases. We developed a simple dose prediction tool (SDP) using deep learning and a novel contour-based data augmentation (CDA) approach and assessed its usability. We trained the SDP to predict the liver Dmean immediately. Five and two computed tomography (CT) data sets of actual patients with liver cancer were used for the training and validation. Data augmentation was performed by artificially embedding 199 contours of virtual clinical target volume (CTV) into CT images for each patient. The data sets of the CTVs and OARs are labeled with liver Dmean for six different treatment plans using two-dimensional calculations assuming all tissue densities as 1.0. The test of the validated model was performed using 10 unlabeled CT data sets of actual patients. Contouring only of the liver and CTV was required as input. The mean relative error (MRE), the mean percentage error (MPE) and regression coefficient between the planned and predicted Dmean was 0.1637, 6.6%, and 0.9455, respectively. The mean time required for the inference of liver Dmean of the six different treatment plans for a patient was 4.47±0.13 seconds. We conclude that the SDP is cost-effective and usable for gross estimation of liver Dmean in the clinic although the accuracy should be improved further if we need the accuracy of liver Dmean to be compatible with 3DRTP. [ABSTRACT FROM AUTHOR]

The purpose of this work is to show the usefulness of a prediction method of tumor location based on partial least squares regression (PLSR) using multiple fiducial markers. The trajectory data of respiratory motion of four internal fiducial markers inserted in lungs were used for the analysis. The position of one of the four markers was assumed to be the tumor position and was predicted by other three fiducial markers. Regression coefficients for prediction of the position of the tumor-assumed marker from the fiducial markers' positions is derived by PLSR. The tracking error and the gating error were evaluated assuming two possible variations. First, the variation of the position definition of the tumor and the markers on treatment planning computed tomograhy (CT) images. Second, the intra-fractional anatomical variation which leads the distance change between the tumor and markers during the course of treatment. For comparison, rigid predictions and ordinally multiple linear regression (MLR) predictions were also evaluated. The tracking and gating errors of PLSR prediction were smaller than those of other prediction methods. Ninety-fifth percentile of tracking/gating error in all trials were 3.7/4.1 mm, respectively in PLSR prediction for superior–inferior direction. The results suggested that PLSR prediction was robust to variations, and clinically applicable accuracy could be achievable for targeting tumors. [ABSTRACT FROM AUTHOR]

In spot scanning proton therapy (SSPT), the spot position relative to the target may fluctuate through tumor motion even when gating the radiation by utilizing a fiducial marker. We have established a procedure that evaluates the delivered dose distribution by utilizing log data on tumor motion and spot information. The purpose of this study is to show the reliability of the dose distributions for liver tumors treated with real-time-image gated SSPT (RGPT). In the evaluation procedure, the delivered spot information and the marker position are synchronized on the basis of log data on the timing of the spot irradiation and fluoroscopic X-ray irradiation. Then a treatment planning system reconstructs the delivered dose distribution. Dose distributions accumulated for all fractions were reconstructed for eight liver cases. The log data were acquired in all 168 fractions for all eight cases. The evaluation was performed for the values of maximum dose, minimum dose, D99, and D5–D95 for the clinical target volumes (CTVs) and mean liver dose (MLD) scaled by the prescribed dose. These dosimetric parameters were statistically compared between the planned dose distribution and the reconstructed dose distribution. The mean difference of the maximum dose was 1.3% (95% confidence interval [CI]: 0.6%—2.1%). Regarding the minimum dose, the mean difference was 0.1% (95% CI: −0.5%—0.7%). The mean differences of D99, D5–D95 and MLD were below 1%. The reliability of dose distributions for liver tumors treated with RGPT-SSPT was shown by the evaluation of the accumulated dose distributions. [ABSTRACT FROM AUTHOR]

Purpose: The real‐time tumor tracking radiotherapy (RTRT) system requires periodic quality assurance (QA) and quality control. The goal of this study is to propose QA procedures from the viewpoint of imaging devices in the RTRT system. Methods: Tracking by the RTRT system (equips two sets of colored image intensifiers (colored I.I.s) fluoroscopy units) for the moving gold‐marker (diameter 2.0 mm) in a rotating phantom were performed under various X‐ray conditions. To analyze the relationship between fluoroscopic image quality and precision of gold marker coordinate calculation, the standard deviation of the 3D coordinate (σ3D [mm]) of the gold marker, the mean of the pattern recognition score (PRS) and the standard deviation of the distance between rays (DBR) (σDBR [mm]) were evaluated. Results: When tracking with speed of 10‐60 mm/s, σDBR increased, though the mean PRS did not change significantly (p>0.05). On the contrary, the mean PRS increased depending on the integral noise equivalent quanta (∫NEQ) that is an indicator of image quality calculated from the modulation transfer function (MTF) as an indicator of spatial resolution and the noise power spectrum (NPS) as an indicator of noise characteristic. Conclusion: The indicators of NEQ, MTF, and NPS were useful for managing the tracking accuracy of the RTRT system. We propose observing the change of these indicators as additional QA procedures for each imaging device from the commissioning baseline. [ABSTRACT FROM AUTHOR]

We developed a confidence interval-(CI) assessing model in multivariable normal tissue complication probability (NTCP) modeling for predicting radiation-induced liver disease (RILD) in primary liver cancer patients using clinical and dosimetric data. Both the mean NTCP and difference in the mean NTCP (ΔNTCP) between two treatment plans of different radiotherapy modalities were further evaluated and their CIs were assessed. Clinical data were retrospectively reviewed in 322 patients with hepatocellular carcinoma (n  = 215) and intrahepatic cholangiocarcinoma (n  = 107) treated with photon therapy. Dose–volume histograms of normal liver were reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose. The most predictive variables were used to build the model based on multivariable logistic regression analysis with bootstrapping. Internal validation was performed using the cross-validation leave-one-out method. Both the mean NTCP and the mean ΔNTCP with 95% CIs were calculated from computationally generated multivariate random sets of NTCP model parameters using variance–covariance matrix information. RILD occurred in 108/322 patients (33.5%). The NTCP model with three clinical and one dosimetric parameter (tumor type, Child–Pugh class, hepatitis infection status and MLD) was most predictive, with an area under the receiver operative characteristics curve (AUC) of 0.79 (95% CI 0.74–0.84). In eight clinical subgroups based on the three clinical parameters, both the mean NTCP and the mean ΔNTCP with 95% CIs were able to be estimated computationally. The multivariable NTCP model with the assessment of 95% CIs has potential to improve the reliability of the NTCP model-based approach to select the appropriate radiotherapy modality for each patient. [ABSTRACT FROM AUTHOR]

Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its image quality is degraded due to noise and scatter. Although several correction methods have been proposed, techniques that include estimation of uncertainty are limited. This study proposes a novel uncertainty-aware pCT image correction method using a Bayesian convolutional neural network (BCNN). A DenseNet-based BCNN was constructed to predict both a corrected SPR image and its uncertainty from a noisy SPR image. A total 432 noisy SPR images of 6 non-anthropomorphic and 3 head phantoms were collected with Monte Carlo simulations, while true noise-free images were calculated with known geometric and chemical components. Heteroscedastic loss and deep ensemble techniques were performed to estimate aleatoric and epistemic uncertainties by training 25 unique BCNN models. 200-epoch end-to-end training was performed for each model independently. Feasibility of the predicted uncertainty was demonstrated after applying two post-hoc calibrations and calculating spot-specific path length uncertainty distribution. For evaluation, accuracy of head SPR images and water-equivalent thickness (WET) corrected by the trained BCNN models was compared with a conventional method and non-Bayesian CNN model. BCNN-corrected SPR images represent noise-free images with high accuracy. Mean absolute error in test data was improved from 0.263 for uncorrected images to 0.0538 for BCNN-corrected images. Moreover, the calibrated uncertainty represents accurate confidence levels, and the BCNN-corrected calibrated WET was more accurate than non-Bayesian CNN with high statistical significance. Computation time for calculating one image and its uncertainties with 25 BCNN models is 0.7 s with a consumer grade GPU. Our model is able to predict accurate pCT images as well as two types of uncertainty. These uncertainties will be useful to identify potential cause of SPR errors and develop a spot-specific range margin criterion, toward elaboration of uncertainty-guided proton therapy. [ABSTRACT FROM AUTHOR]

Circadian disturbance of clock gene expression is a risk factor for diseases such as obesity, cancer, and sleep disorders. To study these diseases, it is necessary to monitor and analyze the expression rhythm of clock genes in the whole body for a long duration. The bioluminescent reporter enzyme firefly luciferase and its substrate d‐luciferin have been used to generate optical signals from tissues in vivo with high sensitivity. However, little information is known about the stability of d‐luciferin to detect gene expression in living animals for a long duration. In the present study, we examined the stability of a luciferin solution over 21 days. l‐Luciferin, which is synthesized using racemization of d‐luciferin, was at high concentrations after 21 days. In addition, we showed that bioluminescence of Period1 (Per1) expression in the liver was significantly decreased compared with the day 1 solution, although locomotor activity rhythm was not affected. These results showed that d‐luciferin should be applied to the mouse within, at most, 7 days to detect bioluminescence of Per1 gene expression rhythm in vivo. [ABSTRACT FROM AUTHOR]

Purpose: To investigate potential advantages of adaptive intensity‐modulated proton beam therapy (A‐IMPT) by comparing it to adaptive intensity‐modulated X‐ray therapy (A‐IMXT) for nasopharyngeal carcinomas (NPC). Methods: Ten patients with NPC treated with A‐IMXT (step and shoot approach) and concomitant chemotherapy between 2014 and 2016 were selected. In the actual treatment, 46 Gy in 23 fractions (46Gy/23Fx.) was prescribed using the initial plan and 24Gy/12Fx was prescribed using an adapted plan thereafter. New treatment planning of A‐IMPT was made for the same patients using equivalent dose fractionation schedule and dose constraints. The dose volume statistics based on deformable images and dose accumulation was used in the comparison of A‐IMXT with A‐IMPT. Results: The means of the Dmean of the right parotid gland (P < 0.001), right TM joint (P < 0.001), left TM joint (P < 0.001), oral cavity (P < 0.001), supraglottic larynx (P = 0.001), glottic larynx (P < 0.001), , middle PCM (P = 0.0371), interior PCM (P < 0.001), cricopharyngeal muscle (P = 0.03643), and thyroid gland (P = 0.00216), in A‐IMPT are lower than those of A‐IMXT, with statistical significance. The means of, D0.03cc, and Dmean of each sub portion of auditory apparatus and D30% for Eustachian tube and D0.5cc for mastoid volume in A‐IMPT are significantly lower than those of A‐IMXT. The mean doses to the oral cavity, supraglottic larynx, and glottic larynx were all reduced by more than 20 Gy (RBE = 1.1). Conclusions: An adaptive approach is suggested to enhance the potential benefit of IMPT compared to IMXT to reduce adverse effects for patients with NPC. [ABSTRACT FROM AUTHOR]

Purpose: This study evaluated the success rate and complications of percutaneous implantation of hepatic fiducial true-spherical gold markers for real-time adaptive radiotherapy (RAR), which constitutes real-time image-guided radiotherapy with gating. Material and methods: We retrospectively evaluated 100 patients who underwent 116 percutaneous intrahepatic implantations of 2-mm-diameter, spherical, gold fiducial markers before RAR from 1999 to 2016, with Seldinger's method. We defined technical success as marker placement at the intended liver parenchyma, without mispositioning, and clinical success as successful tracking of the gold marker and completion of planned RAR. Complications related to marker placement were assessed. Results: The technical success rate for true-spherical gold marker implantation was 92.2% (107/116). Nine of 116 markers migrated (intra-procedurally in seven patients, delayed in two patients). Migration out of the liver (n = 4) or intrahepatic vessels (n = 5) occurred without complications; these markers were not retrieved. The clinical success rate was 100.0% (115/115). Abdominal pain occurred in 16 patients, fever and hemorrhage in seven patients each, and pneumothorax and nausea in one patient each. No major complications were encountered. Conclusions: Percutaneous transhepatic implantation of true-spherical gold markers for RAR is feasible and can be conducted with a high success rate and low complication rate. [ABSTRACT FROM AUTHOR]

Because the disruption of circadian clock gene is a risk factor in many diseases such as obesity and cancer, it is important to monitor and analyzed the expression of the rhythm of the clock gene throughout the body over a long period of time. Although we previously reported on a new gene expression analysis system tracking a target position on the body surface of freely moving mice, the experimental apparatus required a large space. We have therefore developed an in vivo recording system using a portable photomultiplier tube (PMT) system attached to an optical fibre. Directly connecting the target area with the device, we could easily measure the photon counts in a very small space. However, little information is known about the characteristics of optical fibres when exposed to twisting/looping in association with a moving mouse and the effect of the surface of optical fibre. In the present study, we report on the characteristics of optical fibres to detect gene expression rhythm in freely moving mice. Using this portable optical device directly connected with a target area, we were able to measure the circadian rhythm of clock gene expression over a prolonged period in freely moving mice in a small space. [ABSTRACT FROM AUTHOR]

A synchrotron‐based real‐time image gated spot‐scanning proton beam therapy (RGPT) system with inserted fiducial markers can irradiate a moving tumor with high accuracy. As gated treatments increase the beam delivery time, this study aimed to investigate the frequency of intra‐field adjustments corresponding to the baseline shift or drift and the beam delivery efficiency of a synchrotron‐based RGPT system. Data from 118 patients corresponding to 127 treatment plans and 2810 sessions between October 2016 and March 2019 were collected. We quantitatively analyzed the proton beam delivery time, the difference between the ideal beam delivery time based on a simulated synchrotron magnetic excitation pattern and the actual treatment beam delivery time, frequency corresponding to the baseline shift or drift, and the gating efficiency of the synchrotron‐based RGPT system according to the proton beam delivery machine log data. The mean actual beam delivery time was 7.1 min, and the simulated beam delivery time in an ideal environment with the same treatment plan was 2.9 min. The average difference between the actual and simulated beam delivery time per session was 4.3 min. The average frequency of intra‐field adjustments corresponding to baseline shift or drift and beam delivery efficiency were 21.7% and 61.8%, respectively. Based on our clinical experience with a synchrotron‐based RGPT system, we determined the frequency corresponding to baseline shift or drift and the beam delivery efficiency using the beam delivery machine log data. To maintain treatment accuracy within ± 2.0 mm, intra‐field adjustments corresponding to baseline shift or drift were required in approximately 20% of cases. Further improvements in beam delivery efficiency may be realized by shortening the beam delivery time. [ABSTRACT FROM AUTHOR]

This study proposes a near-real-time spot-scanning proton dose calculation method with probabilistic uncertainty estimation using a three-dimensional convolutional neural network (3D-CNN). CT images and clinical target volume contours of 215 head and neck cancer patients were collected from a public database. 1484 and 488 plans were extracted for training and testing the 3D-CNN model, respectively. Spot beam data and single-field uniform dose (SFUD) labels were calculated for each plan using an open-source dose calculation toolkit. Variable spot data were converted into a fixed-size volume hereby called a 'peak map' (PM). 300 epochs of end-to-end training was implemented using sets of stopping power ratio and PM as input. Moreover, transfer learning techniques were used to adjust the trained model to SFUD doses calculated with different beam parameters and calculation algorithm using only 7.95% of training data used for the base model. Finally, accuracy of the 3D-CNN-calculated doses and model uncertainty was reviewed with several evaluation metrics. The 3D-CNN model calculates 3D proton dose distributions accurately with a mean absolute error of 0.778 cGyE. The predicted uncertainty is correlated with dose errors at high contrast edges. Averaged Sřrensen-Dice similarity coefficients between binarized outputs and ground truths are mostly above 80%. Once the 3D-CNN model was well-trained, it can be efficiently fine-tuned for different proton doses by transfer learning techniques. Inference time for calculating one dose distribution is around 0.8 s for a plan using 1500 spot beams with a consumer grade GPU. A novel spot-scanning proton dose calculation method using 3D-CNN was developed. The 3D-CNN model is able to calculate 3D doses and uncertainty with any SFUD spot data and beam irradiation angles. Our proposed method should be readily extendable to other setups and plans and be useful for dose verification, image-guided proton therapy, or other applications. [ABSTRACT FROM AUTHOR]

Enhanced invasiveness, a critical determinant of metastasis and poor prognosis, has been observed in cancer cells that survive cancer therapy, including radiotherapy. Here, we show that invasiveness in radiation-surviving cancer cells is associated with alterations in lysosomal exocytosis caused by the enhanced activation of Arl8b, a small GTPase that regulates lysosomal trafficking. The binding of Arl8b with its effector, SKIP, is increased after radiation through regulation of BORC-subunits. Knockdown of Arl8b or BORC-subunits decreases lysosomal exocytosis and the invasiveness of radiation-surviving cells. Notably, high expression of ARL8B and BORC-subunit genes is significantly correlated with poor prognosis in breast cancer patients. Sp1, an ATM-regulated transcription factor, is found to increase BORC-subunit genes expression after radiation. In vivo experiments show that ablation of Arl8b decreases IR-induced invasive tumor growth and distant metastasis. These findings suggest that BORC-Arl8b-mediated lysosomal trafficking is a target for improving radiotherapy by inhibiting invasive tumor growth and metastasis. Wu et al. discover a role for Arl8b-dependent lysosomal trafficking and exocytosis in promoting invasion and metastasis of breast cancer cells and tumours that survive irradiation treatment. These findings provide insights that may aid future strategies to improve radiotherapy outcome. [ABSTRACT FROM AUTHOR]

Background: Identifying structural and functional abnormalities in bipolar (BD) and major depressive disorders (MDD) is important for understanding biological processes.Hypothesis: Diffusion kurtosis imaging (DKI) may be able to detect the brain's microstructural alterations in BD and MDD and any differences between the two.Study Type: Prospective.Subjects: In all, 16 BD patients, 19 MDD patients, and 20 age- and gender-matched healthy volunteers.Field Strength/sequence: DKI at 3.0T.Assessment: The major DKI indices of the brain were compared voxel-by-voxel among the three groups. Significantly different voxels were tested for correlation with clinical variables (ie, Young Mania Rating Scale [YMRS], 17-item Hamilton Depression Rating Scale [17-HDRS], Montgomery-Åsberg Depression Rating Scale, total disease duration, duration of current episode, and the number of past manic/depressive episodes). The performance of the DKI indices in identifying microstructural alterations was estimated.Statistical Tests: One-way analysis of variance (ANOVA) was used for group comparison of DKI indices. The performance of these indices in detecting microstructural alterations was determined by receiver operating characteristic (ROC) analysis. Pearson's product-moment correlation analyses were used to test the correlations of these indices with clinical variables.Results: DKI revealed widespread microstructural alterations across the brain in each disorder (P < 0.05). Some were significantly different between the two disorders. Mean kurtosis (MK) in the gray matter of the right inferior parietal lobe was able to distinguish BD and MDD with an accuracy of 0.906. A strong correlation was revealed between MK in that region and YMRS in BD patients (r = -0.641, corrected P = 0.042) or 17-HDRS in MDD patients (r = -0.613, corrected P = 0.030). There were also strong correlations between a few other DKI indices and disease duration (r = -0.676 or 0.626, corrected P < 0.05).Data Conclusion: DKI detected microstructural brain alterations in BD and MDD. Its indices may be useful to distinguish the two disorders or to reflect disease severity and duration.Level Of Evidence: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:1187-1196. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to evaluate the sublethal damage (SLD) repair effect in prolonged proton irradiation using the biophysical model with various cell‐specific parameters of (α/β)x and T1/2 (repair half time). At present, most of the model‐based studies on protons have focused on acute radiation, neglecting the reduction in biological effectiveness due to SLD repair during the delivery of radiation. Nevertheless, the dose‐rate dependency of biological effectiveness may become more important as advanced treatment techniques, such as hypofractionation and respiratory gating, come into clinical practice, as these techniques sometimes require long treatment times. Also, while previous research using the biophysical model revealed a large repair effect with a high physical dose, the dependence of the repair effect on cell‐specific parameters has not been evaluated systematically. Methods: Biological dose [relative biological effectiveness (RBE) × physical dose] calculation with repair included was carried out using the linear energy transfer (LET)‐dependent linear‐quadratic (LQ) model combined with the theory of dual radiation action (TDRA). First, we extended the dose protraction factor in the LQ model for the arbitrary number of different LET proton irradiations delivered sequentially with arbitrary time lags, referring to the TDRA. Using the LQ model, the decrease in biological dose due to SLD repair was systematically evaluated for spread‐out Bragg peak (SOBP) irradiation in a water phantom with the possible ranges of both (α/β)x and repair parameters ((α/β)x = 1–15 Gy, T1/2 = 0–90 min). Then, to consider more realistic irradiation conditions, clinical cases of prostate, liver, and lung tumors were examined with the cell‐specific parameters for each tumor obtained from the literature. Biological D99% and biological dose homogeneity coefficient (HC) were calculated for the clinical target volumes (CTVs), assuming dose‐rate structures with a total irradiation time of 0–60 min. Results: The differences in the cell‐specific parameters resulted in considerable variation in the repair effect. The biological dose reduction found at the center of the SOBP with 30 min of continuous irradiation varied from 1.13% to 14.4% with a T1/2 range of 1–90 min when (α/β)x is fixed as 10 Gy. It varied from 2.3% to 6.8% with an (α/β)x range of 1–15 Gy for a fixed value of T1/2 = 30 min. The decrease in biological D99% per 10 min was 2.6, 1.2, and 3.0% for the prostate, liver, and lung tumor cases, respectively. The value of the biological D99% reduction was neither in the order of (α/β)x nor prescribed dose, but both comparably contributed to the repair effect. The variation of HC was within the range of 0.5% for all cases; therefore, the dose distribution was not distorted. Conclusion: The reduction in biological dose caused by the SLD repair largely depends on the cell‐specific parameters in addition to the physical dose. The parameters should be considered carefully in the evaluation of the repair effect in prolonged proton irradiation. [ABSTRACT FROM AUTHOR]

Spot‐scanning particle therapy possesses advantages, such as high conformity to the target and efficient energy utilization compared with those of the passive scattering irradiation technique. However, this irradiation technique is sensitive to target motion. In the current clinical situation, some motion management techniques, such as respiratory‐gated irradiation, which uses an external or internal surrogate, have been clinically applied. In surrogate‐based gating, the size of the gating window is fixed during the treatment in the current treatment system. In this study, we propose a dynamic gating window technique, which optimizes the size of gating window for each spot by considering a possible dosimetric error. The effectiveness of the dynamic gating window technique was evaluated by simulating irradiation using a moving target in a water phantom. In dosimetric characteristics comparison, the dynamic gating window technique exhibited better performance in all evaluation volumes with different effective depths compared with that of the fixed gate approach. The variation of dosimetric characteristics according to the target depth was small in dynamic gate compared to fixed gate. These results suggest that the dynamic gating window technique can maintain an acceptable dose distribution regardless of the target depth. The overall gating efficiency of the dynamic gate was approximately equal or greater than that of the fixed gating window. In dynamic gate, as the target depth becomes shallower, the gating efficiency will be reduced, although dosimetric characteristics will be maintained regardless of the target depth. The results of this study suggest that the proposed gating technique may potentially improve the dose distribution. However, additional evaluations should be undertaken in the future to determine clinical applicability by assuming the specifications of the treatment system and clinical situation. [ABSTRACT FROM AUTHOR]

We developed a synchrotron‐based real‐time‐image gated‐spot‐scanning proton‐beam therapy (RGPT) system and utilized it to clinically operate on moving tumors in the liver, pancreas, lung, and prostate. When the spot‐scanning technique is linked to gating, the beam delivery time with gating can increase, compared to that without gating. We aim to clarify whether the total treatment process can be performed within approximately 30 min (the general time per session in several proton therapy facilities), even for gated‐spot‐scanning proton‐beam delivery with implanted fiducial markers. Data from 152 patients, corresponding to 201 treatment plans and 3577 sessions executed from October 2016 to June 2018, were included in this study. To estimate the treatment process time, we utilized data from proton beam delivery logs during the treatment for each patient. We retrieved data, such as the disease site, total target volume, field size at the isocenter, and the number of layers and spots for each field, from the treatment plans. We quantitatively analyzed the treatment process, which includes the patient load (or setup), bone matching, marker matching, beam delivery, patient unload, and equipment setup, using the data obtained from the log data. Among all the cases, 90 patients used the RGPT system (liver: n = 34; pancreas: n = 5; lung: n = 4; and prostate: n = 47). The mean and standard deviation (SD) of the total treatment process time for the RGPT system was 30.3 ± 7.4 min, while it was 25.9 ± 7.5 min for those without gating treatment, excluding craniospinal irradiation (CSI; head and neck: n = 16, pediatric: n = 31, others: n = 15); for CSI (n = 11) with two or three isocenters, the process time was 59.9 ± 13.9 min. Our results demonstrate that spot‐scanning proton therapy with a gating function can be achieved in approximately 30‐min time slots. [ABSTRACT FROM AUTHOR]

Purpose: While cone beam computed tomography (CBCT) is able to provide patient anatomical information, its image quality is severely degraded due to scatter contamination, which degrades the accuracy of CBCT‐based dose distribution estimation in proton therapy. In this work, we combined two existing scatter kernel correction methods: the point‐spread function (PSF)‐based scatter kernel derivation method and the fast adaptive scatter kernel superposition (fASKS) model, and evaluated the impact of the modified fASKS (mfASKS) correction on the accuracy of proton dose distribution estimation. To evaluate feasibility of the mfASKS approach using accurate scatter distributions, both Monte Carlo simulations and experiments were performed for an on‐board CBCT machine integrated with a proton therapy machine. Methods: We developed a strategy to modify central intensity, constant intensity, and amplitude of the scatter kernels derived from PSFs for the fASKS model. A parameter required for the fASKS model was derived by optimizing uniformity in the mfASKS‐corrected reconstructed images. Subsequently, the mfASKS model was used to remove scatter in CBCT imaging. We quantitatively compared the Hounsfield Unit (HU) and proton stopping power ratio (SPR) images for five different phantoms. To assess improvement of dose calculation accuracy, a series of proton treatment plans were produced using the CBCT images with and without the mfASKS correction. Results: The accuracies of both HU and SPR intensity quantifications are improved as a result of the mfASKS correction. Mean absolute water‐equivalent path length difference to the true value decreases from 10.3 to 0.934 mm for the Gammex phantom (simulation). At the same time, mfASKS is able to offer more accurate dose distributions, especially at the distal fall‐off region where noticeable dose overestimation is observed in the uncorrected scenario. Mean absolute relative error of proton range in the pelvic phantom improves from 5.03% to 2.57% (experiment). Conclusions: mfASKS enables more accurate CBCT‐based proton dose calculation. This technique has significant implications in image‐guided radiotherapy and dose verifications in adaptive proton therapy. [ABSTRACT FROM AUTHOR]

Purpose: To determine the best method to contour the planning organ at risk volume (PRV) for the urethra, this study aimed to investigate the displacement of a Foley catheter in the urethra with a soft and thin guide-wire.Methods: For each patient, the study used two sets of computed tomography (CT) images for radiation treatment planning (RT-CT): (1) set with a Foley urethral catheter (4.0 mm diameter) plus a guide-wire (0.46 mm diameter) in the first RT-CT and (2) set with a guide-wire alone in the second CT recorded 2 min after the first RT-CT. Using three fiducial markers in the prostate for image fusion, the displacement between the catheter and the guide-wire in the prostatic urethra was calculated. In 155 consecutive patients treated between 2011 and 2017, 5531 slices of RT-CT were evaluated.Results: Assuming that ≥3.0 mm of difference between the catheter and the guide-wire position was a significant displacement, the urethra with the catheter was displaced significantly from the urethra with the guide-wire alone in > 20% of the RT-CT slices in 23.2% (36/155) of the patients. The number of patients who showed ≥3.0 mm anterior displacement with the catheter in ≥20% RT-CT slices was significantly larger at the superior segment (38/155) than at the middle (14/155) and inferior segments (18/155) of the prostatic urethra (p < 0.0167).Conclusions: The urethral position with a Foley catheter is different from the urethral position with a thin and soft guide-wire in a significant proportion of the patients. This should be taken into account for the PRV of the urethra to ensure precise radiotherapy such as in urethra-sparing radiotherapy. [ABSTRACT FROM AUTHOR]

Objective: To identify factors significantly associated with quality of life (QOL) and determine if these associations are strong enough to predict certain aspects of QOL without measuring them. Methods: We conducted an exploratory secondary analysis of baseline data of 224 patients (enrolled between December 2020 and March 2021) from a previously published prospective observational study on radiotherapy for bone metastases at 26 centres. Using univariable linear regression, we assessed the association between patient/treatment factors and QOL scale scores as measured by the European Organization for Research and Treatment of Cancer (EORTC) QOL Questionnaire Core 15‐Palliative (QLQ‐C15‐PAL) and the EORTC QOL Questionnaire Bone Metastases module (QLQ‐BM22). Results: Age and sex were not significantly associated with QOL. Worse performance status, higher pain scores, and opioid and single‐fraction use were significantly associated with most QOL scales; these four factors were associated with worse global QOL, worse functioning status, and more severe symptoms. The coefficients of determination for most QOL scales were less than 0.2, indicating that most of the variability in QOL scores was not explained by any of the explanatory variables. Conclusion: Performance status, pain intensity, and opioid and single‐fraction use were significantly associated with most QOL scales. However, the associations were not strong enough to estimate QOL. Advances in knowledge: To date, the association between treatment factors and QOL in patients with bone metastases has not been fully studied. We identified the factors that were significantly associated with QOL and found that these associations were not strong enough to predict QOL. [ABSTRACT FROM AUTHOR]

Although prostate cancer control using radiotherapy is dose‐dependent, dose–volume effects on late toxicities in organs at risk, such as the rectum and bladder, have been observed. Both protons and carbon ions offer advantageous physical properties for radiotherapy, and create favorable dose distributions using fewer portals compared with photon‐based radiotherapy. Thus, particle beam therapy using protons and carbon ions theoretically seems suitable for dose escalation and reduced risk of toxicity. However, it is difficult to evaluate the superiority of particle beam radiotherapy over photon beam radiotherapy for prostate cancer, as no clinical trials have directly compared the outcomes between the two types of therapy due to the limited number of facilities using particle beam therapy. The Japanese Society for Radiation Oncology organized a joint effort among research groups to establish standardized treatment policies and indications for particle beam therapy according to disease, and multicenter prospective studies have been planned for several common cancers. Clinical trials of proton beam therapy for intermediate‐risk prostate cancer and carbon‐ion therapy for high‐risk prostate cancer have already begun. As particle beam therapy for prostate cancer is covered by the Japanese national health insurance system as of April 2018, and the number of facilities practicing particle beam therapy has increased recently, the number of prostate cancer patients treated with particle beam therapy in Japan is expected to increase drastically. Here, we review the results from studies of particle beam therapy for prostate cancer and discuss future developments in this field. [ABSTRACT FROM AUTHOR]

Background: We investigated the usefulness of the minimum ADC value of primary breast lesions for predicting axillary lymph node (LN) status in luminal A-like breast cancers with clinically negative nodes in comparison with the mean ADC. Methods: Forty-four luminal A-like breast cancers without axillary LN metastasis at preoperative clinical evaluation, surgically resected with sentinel LN biopsy, were retrospectively studied. Mean and minimum ADC values of each lesion were measured and statistically compared between LN positive (n = 12) and LN negative (n = 32) groups. An ROC curve was drawn to determine the best cutoff value to differentiate LN status. Correlations between mean and minimum ADC values and the number of metastatic axillary LNs were investigated. Results: Mean and minimum ADC values of breast lesions with positive LN were significantly lower than those with negative LN (mean 839.9 ± 110.9 vs. 1022.2 ± 250.0 × 10− 6 mm2/s, p = 0.027, minimum 696.7 ± 128.0 vs. 925.0 ± 257.6 × 10− 6 mm2/s, p = 0.004). The sensitivity and NPV using the best cutoff value from ROC using both mean and minimum ADC were 100%. AUC of the minimum ADC (0.784) was higher than that of the mean ADC (0.719). Statistically significant negative correlations were observed between both mean and minimum ADCs and number of positive LNs, with stronger correlation to minimum ADC than mean ADC. Conclusions: The minimum ADC value of primary breast lesions predicts axillary LN metastasis in luminal A-like breast cancer with clinically negative nodes, with high sensitivity and high NPV. [ABSTRACT FROM AUTHOR]

Purpose: Interplay effects may influence dose distributions to a moving target when using dynamic delivery techniques such as intensity‐modulated radiotherapy (IMRT). The aim of this study was to evaluate the impact of organ motion on volumetric and dosimetric parameters in stomach lymphomas treated with IMRT. Methods: Ten patients who had been treated with IMRT for stomach lymphomas were enrolled. The clinical target volume (CTV) was contoured as the whole stomach. Considering interfractional uncertainty, the internal target volume (ITV) margin was uniformly 1.5 cm to the CTV and then modified based on the 4DCT images in case of the large respiratory motion. The planning target volume (PTV) was created by adding 5 mm to the ITV. The impact of organ motion on the volumetric and dosimetric parameters was evaluated retrospectively (4D simulation). The organ motion was reproduced by shifting the isocenter on the radiation treatment planning system. Several simulation plans were created to test the influence of the beam‐on timing in the respiration cycle on the dose distribution. The homogeneity index (HI), volume percentage of stomach covered by the prescribed dose (Vp), and D99 of the CTV were evaluated. Results: The organ motion was the largest in the superior‐inferior direction (10.1 ± 4.5 mm [average ± SD]). Stomach volume in each respiratory phase compared to the mean volume varied approximately within a ± 5% range in most of the patients. The PTV margin was sufficiently large to cover the CTV during the IMRT. There was a significant reduction in Vp and D99 but not in HI in the 4D simulation in free‐breathing and multiple fractions compared to the clinically‐used plan (P < 0.05) suggesting that interplay effects deteriorate the dose distribution. The absolute difference of D99 was less than 1% of the prescribed dose. Conclusions: There were significant interplay effects affecting the dose distribution in stomach IMRT. The magnitude of the dose reduction was small when patients were treated on free‐breathing and multiple fractions. [ABSTRACT FROM AUTHOR]

Purpose: Scatter is a major factor degrading the image quality of cone beam computed tomography (CBCT). Conventional scatter correction strategies require handcrafted analytical models with ad hoc assumptions, which often leads to less accurate scatter removal. This study aims to develop an effective scatter correction method using a residual convolutional neural network (CNN). Methods: A U‐net based 25‐layer CNN was constructed for CBCT scatter correction. The establishment of the model consists of three steps: model training, validation, and testing. For model training, a total of 1800 pairs of x‐ray projection and the corresponding scatter‐only distribution in nonanthropomorphic phantoms taken in full‐fan scan were generated using Monte Carlo simulation of a CBCT scanner installed with a proton therapy system. An end‐to‐end CNN training was implemented with two major loss functions for 100 epochs with a mini‐batch size of 10. Image rotations and flips were randomly applied to augment the training datasets during training. For validation, 200 projections of a digital head phantom were collected. The proposed CNN‐based method was compared to a conventional projection‐domain scatter correction method named fast adaptive scatter kernel superposition (fASKS) method using 360 projections of an anthropomorphic head phantom. Two different loss functions were applied for the same CNN to evaluate the impact of loss functions on the final results. Furthermore, the CNN model trained with full‐fan projections was fine‐tuned for scatter correction in half‐fan scan by using transfer learning with additional 360 half‐fan projection pairs of nonanthropomorphic phantoms. The tuned‐CNN model for half‐fan scan was compared with the fASKS method as well as the CNN‐based method without the fine‐tuning using additional lung phantom projections. Results: The CNN‐based method provides projections with significantly reduced scatter and CBCT images with more accurate Hounsfield Units (HUs) than that of the fASKS‐based method. Root mean squared error of the CNN‐corrected projections was improved to 0.0862 compared to 0.278 for uncorrected projections or 0.117 for the fASKS‐corrected projections. The CNN‐corrected reconstruction provided better HU quantification, especially in regions near the air or bone interfaces. All four image quality measures, which include mean absolute error (MAE), mean squared error (MSE), peak signal‐to‐noise ratio (PSNR), and structural similarity (SSIM), indicated that the CNN‐corrected images were significantly better than that of the fASKS‐corrected images. Moreover, the proposed transfer learning technique made it possible for the CNN model trained with full‐fan projections to be applicable to remove scatters in half‐fan projections after fine‐tuning with only a small number of additional half‐fan training datasets. SSIM value of the tuned‐CNN‐corrected images was 0.9993 compared to 0.9984 for the non‐tuned‐CNN‐corrected images or 0.9990 for the fASKS‐corrected images. Finally, the CNN‐based method is computationally efficient — the correction time for the 360 projections only took less than 5 s in the reported experiments on a PC (4.20 GHz Intel Core‐i7 CPU) with a single NVIDIA GTX 1070 GPU. Conclusions: The proposed deep learning‐based method provides an effective tool for CBCT scatter correction and holds significant value for quantitative imaging and image‐guided radiation therapy. [ABSTRACT FROM AUTHOR]

The outcomes of intensity-modulated proton craniospinal irradiation (ipCSI) are unclear. We evaluated the clinical benefit of our newly developed ipCSI system that incorporates two gantry-mounted orthogonal online X-ray imagers with a robotic six-degrees-of-freedom patient table. Nine patients (7–19 years old) were treated with ipCSI. The prescribed dose for CSI ranged from 23.4 to 36.0 Gy (relative biological effectiveness) in 13–20 fractions. Four adolescent and young adult (AYA) patients (15 years or older) were treated with vertebral-body-sparing ipCSI (VBSipCSI). Myelosuppression following VBSipCSI was compared with that of eight AYA patients treated with photon CSI at the same institution previously. The mean homogeneity index (HI) in the nine patients was 0.056 (95% confidence interval: 0.044–0.068). The mean time from the start to the end of all beam delivery was 37 min 39 s ± 2 min 24 s (minimum to maximum: 22 min 49 s – 42 min 51 s). The nadir white blood cell, hemoglobin, and platelet levels during the 4 weeks following the end of the CSI were significantly higher in the VBSipCSI group than in the photon CSI group (P = 0.0071, 0.0453, 0.0024, respectively). The levels at 4 weeks after the end of CSI were significantly higher in the VBSipCSI group than in the photon CSI group (P = 0.0023, 0.0414, 0.0061). Image-guided ipCSI was deliverable in a reasonable time with sufficient HI. Using VBSipCSI, AYA patients experienced a lower incidence of serious acute hematological toxicity than AYA patients treated with photon CSI. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the biological effects of proton beams as part of daily clinical routine, fast and accurate calculation of dose‐averaged linear energy transfer (LETd) is required. In this study, we have developed the analytical LETd calculation method based on the pencil‐beam algorithm (PBA) considering the off‐axis enhancement by secondary protons. This algorithm (PBA‐dLET) was then validated using Monte Carlo simulation (MCS) results. Methods: In PBA‐dLET, LET values were assigned separately for each individual dose kernel based on the PBA. For the dose kernel, we employed a triple Gaussian model which consists of the primary component (protons that undergo the multiple Coulomb scattering) and the halo component (protons that undergo inelastic, nonelastic and elastic nuclear reaction); the primary and halo components were represented by a single Gaussian and the sum of two Gaussian distributions, respectively. Although the previous analytical approaches assumed a constant LETd value for the lateral distribution of a pencil beam, the actual LETd increases away from the beam axis, because there are more scattered and therefore lower energy protons with higher stopping powers. To reflect this LETd behavior, we have assumed that the LETs of primary and halo components can take different values (LETp and LEThalo), which vary only along the depth direction. The values of dual‐LET kernels were determined such that the PBA‐dLET reproduced the MCS‐generated LETd distribution in both small and large fields. These values were generated at intervals of 1 mm in depth for 96 energies from 70.2 to 220 MeV and collected in the look‐up table. Finally, we compared the LETd distributions and mean LETd (LETd,mean) values of targets and organs at risk between PBA‐dLET and MCS. Both homogeneous phantom and patient geometries (prostate, liver, and lung cases) were used to validate the present method. Results: In the homogeneous phantom, the LETd profiles obtained by the dual‐LET kernels agree well with the MCS results except for the low‐dose region in the lateral penumbra, where the actual dose was below 10% of the maximum dose. In the patient geometry, the LETd profiles calculated with the developed method reproduces MCS with the similar accuracy as in the homogeneous phantom. The maximum differences in LETd,mean for each structure between the PBA‐dLET and the MCS were 0.06 keV/μm in homogeneous phantoms and 0.08 keV/μm in patient geometries under all tested conditions, respectively. Conclusions: We confirmed that the dual‐LET‐kernel model well reproduced the MCS, not only in the homogeneous phantom but also in complex patient geometries. The accuracy of the LETd was largely improved from the single‐LET‐kernel model, especially at the lateral penumbra. The model is expected to be useful, especially for proper recognition of the risk of side effects when the target is next to critical organs. [ABSTRACT FROM AUTHOR]

Background: Respiration-induced phase shift affects B0 /B1+ mapping repeatability in parallel transmission (pTx) calibration for 7T brain MRI, but is improved by breath-holding (BH). However, BH cannot be applied during long scans.Purpose: To examine whether interleaved acquisition during calibration scanning could improve pTx repeatability and image homogeneity.Study Type: Prospective.Subjects: Nine healthy subjects.Field Strength/sequence: 7T MRI with a two-channel RF transmission system was used.Assessment: Calibration scanning for B0 /B1+ mapping was performed under sequential acquisition/free-breathing (Seq-FB), Seq-BH, and interleaved acquisition/FB (Int-FB) conditions. The B0 map was calculated with two echo times, and the B1+ map was obtained using the Bloch-Siegert method. Actual flip-angle imaging (AFI) and gradient echo (GRE) imaging were performed using pTx and quadrature-Tx (qTx). All scans were acquired in five sessions. Repeatability was evaluated using intersession standard deviation (SD) or coefficient of variance (CV), and in-plane homogeneity was evaluated using in-plane CV.Statistical Tests: A paired t-test with Bonferroni correction for multiple comparisons was used.Results: The intersession CV/SDs for the B0 /B1+ maps were significantly smaller in Int-FB than in Seq-FB (Bonferroni-corrected P < 0.05 for all). The intersession CVs for the AFI and GRE images were also significantly smaller in Int-FB, Seq-BH, and qTx than in Seq-FB (Bonferroni-corrected P < 0.05 for all). The in-plane CVs for the AFI and GRE images in Seq-FB, Int-FB, and Seq-BH were significantly smaller than in qTx (Bonferroni-corrected P < 0.01 for all).Data Conclusion: Using interleaved acquisition during calibration scans of pTx for 7T brain MRI improved the repeatability of B0 /B1+ mapping, AFI, and GRE images, without BH.Level Of Evidence: 1 Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2017. [ABSTRACT FROM AUTHOR]

Abstract: To evaluate preliminary results of proton radiotherapy (PRT) for pediatric patients with rhabdomyosarcoma (RMS). From 1987 to 2014, PRT was conducted as initial radiotherapy in 55 patients (35 males, 20 females, median age 5 years, range 0–19) with RMS at four institutes in Japan. Thirty‐one, 18, and six patients had embryonal, alveolar, and other RMS, respectively. One, 11, 37, and six patients were in IRSG groups I, II, III, and IV, respectively, and the COG risk group was low, intermediate, and high for nine, 39, and seven patients, respectively. The irradiation dose was 36–60 GyE (median: 50.4 GyE). The median follow‐up period was 24.5 months (range: 1.5–320.3). The 1‐ and 2‐year overall survival rates were 91.9% (95% CI: 84.3–99.5%) and 84.8% (95% CI 75.2–94.3%), respectively, and these rates were 100% and 100%, 97.1% and 90.1%, and 57.1% and 42.9% for COG low‐, intermediate‐, and high‐risk groups, respectively. There were 153 adverse events of Grade ≥3, including 141 hematologic toxicities in 48 patients (87%) and 12 radiation‐induced toxicities in nine patients (16%). Proton‐specific toxicity was not observed. PRT has the same treatment effect as photon radiotherapy with tolerable acute radiation‐induced toxicity. [ABSTRACT FROM AUTHOR]

Radiotherapy induces anti‐tumor immunity by induction of tumor antigens and damage‐associated molecular patterns (DAMP). DNA, a representative DAMP in radiotherapy, activates the stimulator of interferon genes (STING) pathway which enhances the immune response. However, the immune response does not always parallel the inflammation associated with radiotherapy. This lack of correspondence may, in part, explain the radiation‐resistance of tumors. Additive immunotherapy is expected to revive tumor‐specific CTL facilitating radiation‐resistant tumor shrinkage. Herein pre‐administration of the double‐stranded RNA, polyinosinic‐polycytidylic acid (polyI:C), in conjunction with radiotherapy, was shown to foster tumor suppression in mice bearing radioresistant, ovalbumin‐expressing Lewis lung carcinoma (LLC). Extrinsic injection of tumor antigen was not required for tumor suppression. No STING‐ and CTL‐response was induced by radiation in the implant tumor. PolyI:C was more effective for induction of tumor growth retardation at 1 day before radiation than at post‐treatment. PolyI:C targeted Toll‐like receptor 3 with minimal effect on the mitochondrial antiviral‐signaling protein pathway. Likewise, the STING pathway barely contributed to LLC tumor suppression. PolyI:C primed antigen‐presenting dendritic cells in draining lymph nodes to induce proliferation of antigen‐specific CTL. By combination therapy, CTL efficiently infiltrated into tumors with upregulation of relevant chemokine transcripts. Batf3‐positive DC and CD8+ T cells were essential for therapeutic efficacy. Furthermore, polyI:C was shown to stimulate tumor‐associated macrophages and release tumor necrosis factor alpha, which acted on tumor cells and increased sensitivity to radiation. Hence, polyI:C treatment prior to radiotherapy potentially induces tumor suppression by boosting CTL‐dependent and macrophage‐mediated anti‐tumor responses. Eventually, polyI:C and radiotherapy in combination would be a promising therapeutic strategy for radiation‐resistant tumors. [ABSTRACT FROM AUTHOR]

Abstract: This is the first multi‐institutional retrospective survey of the long‐term outcomes of proton therapy (PT) for prostate cancer in Japan. This retrospective analysis comprised prostate cancer patients treated with PT at seven centers between January 2008 and December 2011 and was approved by each Institutional Review Board. The NCCN classification was used. Biochemical relapse was based on the Phoenix definition (nadir + 2.0 ng/mL). Toxicities were evaluated with the Common Terminology Criteria for Adverse Events version 4.0. There were 215, 520, and 556 patients in the low‐risk, intermediate‐risk, and high‐risk groups, respectively. The median follow‐up period of surviving patients was 69 months (range: 7–107). Among all patients, 98.8% were treated using a conventional fractionation schedule and 1.2% with a hypofractionation schedule; 58.5% and 21.5% received neoadjuvant and adjuvant androgen deprivation therapy, respectively. The 5‐year biochemical relapse‐free survival (bRFS) and overall survival rates in the low‐risk, intermediate‐risk, and high‐risk groups were 97.0%, 91.1%, and 83.1%, and 98.4%, 96.8%, and 95.2%, respectively. In the multivariate analysis, the NCCN classification was a significant prognostic factor for bRFS, but not overall survival. The incidence rates of grade 2 or more severe late gastrointestinal and genitourinary toxicities were 4.1% and 4.0%, retrospectively. This retrospective analysis of a multi‐institutional survey suggested that PT is effective and well‐tolerated for prostate cancer. Based on this result, a multi‐institutional prospective clinical trial (UMIN000025453) on PT for prostate cancer has just been initiated in order to define its role in Japan. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate heterogeneity of myocardial contraction in relation to extensive late gadolinium enhancement (LGE) in hypertrophic cardiomyopathy (HCM) patients with preserved left ventricular ejection fraction, using fast strain-encoded magnetic resonance imaging.Materials and Methods: Twenty-two HCM patients and 24 age-matched control subjects were included in this retrospective study. The regional and global peak values of longitudinal and circumferential strain (LSregional, LSglobal, CSregional, CSglobal), and their regional heterogeneities were evaluated using coefficients of variation (LSCoV, CSCoV) in relation to LGE. Receiver operating characteristic curve analysis was performed to identify patients with a total left ventricular myocardial LGE ≥ 15%.Results: LSglobal in HCM patients was significantly decreased compared to that in controls (- 14.4 ± 2.4% vs - 17.2 ± 2.0%; p = 0.0004), while CSglobal was not (p = 1.0). Negative LGE segments demonstrated decreased LSregional in HCM patients compared to in controls (p < 0.0001), while CSregional was not decreased. CSCoV demonstrated the largest area under the curve (AUC) (0.91), with high sensitivity (83%) and specificity (94%) for detection of HCM patients with extensive LGE, while the AUC of LSCoV was low (0.49).Conclusion: The heterogeneity in CSregional has a high diagnostic value for detection of HCM patients with extensive LGE. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the homogeneity of the radiofrequency magnetic field (B1+ ) and signal intensity using different arm positions during 3T thoracolumbar spinal imaging.Materials and Methods: Twenty volunteers were scanned with a four-channel radiofrequency (RF) transmit coil at 3T, with arms on the bed (conventional), arms elevated by 100 mm (arm lift), or with the arms-up position (elevated arm). Axial B1+ maps and sagittal T1 -weighted image (T1 WI)-performed RF shimming were obtained for each arm position. The mean and standard deviation (SD) of the flip angle (FA) at the center of the vertebra on each B1+ map, and contrast noise ratios (CNRs) between the spinal cord and cerebrospinal fluid of sagittal T1 WI, were calculated and compared among the different arm positions.Results: Mean FA values (degrees) for the arm lift and elevated arm positions were significantly larger than for the conventional position (P < 0.001 for both) at the twelfth thoracic vertebra (Th12). FA SD values for the arm lift and elevated arm position were significantly smaller than for the conventional position (P < 0.001 for both) at Th12. CNR for the arm lift and elevated arm position were significantly higher than for the conventional position (P = 0.007 and 0.002, respectively). The mean and SD of the FA and the CNR did not differ significantly for the arm lift and elevated arm positions (P = 0.591, 0.958, and 0.927, respectively).Conclusion: Inhomogeneities of B1+ and signal intensities were improved by simply changing the arm position in 3T thoracolumbar spinal imaging.Level Of Evidence: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:123-130. [ABSTRACT FROM AUTHOR]

Objectives: This study noninvasively examined the electrical conductivity (σ) characteristics of diffuse gliomas using MRI and tested its validity.Methods: MRI including a 3D steady-state free precession (3D SSFP) sequence was performed on 30 glioma patients. The σ maps were reconstructed from the phase images of the 3D SSFP sequence. The σ histogram metrics were extracted and compared among the contrast-enhanced (CET) and noncontrast-enhanced tumour components (NCET) and normal brain parenchyma (NP). Difference in tumour σ histogram metrics among tumour grades and correlation of σ metrics with tumour grades were tested. Validity of σ measurement using this technique was tested by correlating the mean tumour σ values measured using MRI with those measured ex vivo using a dielectric probe.Results: Several σ histogram metrics of CET and NCET of diffuse gliomas were significantly higher than NP (Bonferroni-corrected p ≤ .045). The maximum σ of NCET showed a moderate positive correlation with tumour grade (r = .571, Bonferroni-corrected p = .018). The mean tumour σ measured using MRI showed a moderate positive correlation with the σ measured ex vivo (r = .518, p = .040).Conclusions: Tissue σ can be evaluated using MRI, incorporation of which may better characterise diffuse gliomas.Key Points: • This study tested the validity of noninvasive electrical conductivity measurements by MRI. • This study also evaluated the electrical conductivity characteristics of diffuse glioma. • Gliomas have higher electrical conductivity values than the normal brain parenchyma. • Noninvasive electrical conductivity measurement can be helpful for better characterisation of glioma. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) characteristics of the breast tumor and background parenchyma can distinguish molecular subtypes (ie, luminal A/B or basal) of breast cancer.Materials and Methods: In all, 84 patients from one institution and 126 patients from The Cancer Genome Atlas (TCGA) were used for discovery and external validation, respectively. Thirty-five quantitative image features were extracted from DCE-MRI (1.5 or 3T) including morphology, texture, and volumetric features, which capture both tumor and background parenchymal enhancement (BPE) characteristics. Multiple testing was corrected using the Benjamini-Hochberg method to control the false-discovery rate (FDR). Sparse logistic regression models were built using the discovery cohort to distinguish each of the three studied molecular subtypes versus the rest, and the models were evaluated in the validation cohort.Results: On univariate analysis in discovery and validation cohorts, two features characterizing tumor and two characterizing BPE were statistically significant in separating luminal A versus nonluminal A cancers; two features characterizing tumor were statistically significant for separating luminal B; one feature characterizing tumor and one characterizing BPE reached statistical significance for distinguishing basal (Wilcoxon P < 0.05, FDR < 0.25). In discovery and validation cohorts, multivariate logistic regression models achieved an area under the receiver operator characteristic curve (AUC) of 0.71 and 0.73 for luminal A cancer, 0.67 and 0.69 for luminal B cancer, and 0.66 and 0.79 for basal cancer, respectively.Conclusion: DCE-MRI characteristics of breast cancer and BPE may potentially be used to distinguish among molecular subtypes of breast cancer.Level Of Evidence: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1017-1027. [ABSTRACT FROM AUTHOR]

Objective: To develop and validate a volume-based, quantitative imaging marker by integrating multi-parametric MR images for predicting glioblastoma survival, and to investigate its relationship and synergy with molecular characteristics.Methods: We retrospectively analysed 108 patients with primary glioblastoma. The discovery cohort consisted of 62 patients from the cancer genome atlas (TCGA). Another 46 patients comprising 30 from TCGA and 16 internally were used for independent validation. Based on integrated analyses of T1-weighted contrast-enhanced (T1-c) and diffusion-weighted MR images, we identified an intratumoral subregion with both high T1-c and low ADC, and accordingly defined a high-risk volume (HRV). We evaluated its prognostic value and biological significance with genomic data.Results: On both discovery and validation cohorts, HRV predicted overall survival (OS) (concordance index: 0.642 and 0.653, P < 0.001 and P = 0.038, respectively). HRV stratified patients within the proneural molecular subtype (log-rank P = 0.040, hazard ratio = 2.787). We observed different OS among patients depending on their MGMT methylation status and HRV (log-rank P = 0.011). Patients with unmethylated MGMT and high HRV had significantly shorter survival (median survival: 9.3 vs. 18.4 months, log-rank P = 0.002).Conclusion: Volume of the high-risk intratumoral subregion identified on multi-parametric MRI predicts glioblastoma survival, and may provide complementary value to genomic information.Key Points: • High-risk volume (HRV) defined on multi-parametric MRI predicted GBM survival. • The proneural molecular subtype tended to harbour smaller HRV than other subtypes. • Patients with unmethylated MGMT and high HRV had significantly shorter survival. • HRV complements genomic information in predicting GBM survival. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incorporating novel biomarkers such as mammographic density. Artificial neural networks (ANN) are adaptive algorithms capable of performing pattern-to-pattern learning and are well suited for medical applications. They are potentially useful for calibrating full-field digital mammography (FFDM) for quantitative analysis. This study uses ANN modeling to estimate volumetric breast density (VBD) from FFDM on Japanese women with and without breast cancer. ANN calibration of VBD was performed using phantom data for one FFDM system. Mammograms of 46 Japanese women diagnosed with invasive carcinoma and 53 with negative findings were analyzed using ANN models learned. ANN-estimated VBD was validated against phantom data, compared intra-patient, with qualitative composition scoring, with MRI VBD, and inter-patient with classical risk factors of breast cancer as well as cancer status. Phantom validations reached an R of 0.993. Intra-patient validations ranged from R of 0.789 with VBD to 0.908 with breast volume. ANN VBD agreed well with BI-RADS scoring and MRI VBD with R ranging from 0.665 with VBD to 0.852 with breast volume. VBD was significantly higher in women with cancer. Associations with age, BMI, menopause, and cancer status previously reported were also confirmed. ANN modeling appears to produce reasonable measures of mammographic density validated with phantoms, with existing measures of breast density, and with classical biomarkers of breast cancer. FFDM VBD is significantly higher in Japanese women with cancer. [ABSTRACT FROM AUTHOR]

Proton beam therapy ( PBT) is a potential new alternative to treatment with photon radiotherapy that may reduce the risk of late toxicity and secondary cancer, especially for pediatric tumors. The goal of this study was to evaluate the long-term benefits of PBT in cancer survivors. A retrospective observational study of pediatric patients who received PBT was performed at four institutions in Japan. Of 343 patients, 62 were followed up for 5 or more years. These patients included 40 males and 22 females, and had a median age of 10 years (range: 0-19 years) at the time of treatment. The irradiation dose ranged from 10.8 to 81.2 GyE (median: 50.4 GyE). The median follow-up period was 8.1 years (5.0-31.2 years). The 5-, 10- and 20-year rates for grade 2 or higher late toxicities were 18%, 35% and 45%, respectively, and those for grade 3 or higher late toxicities were 6%, 17% and 17% respectively. Univariate analysis showed that the irradiated site (head and neck, brain) was significantly associated with late toxicities. No malignant secondary tumors occurred within the irradiated field. The 10- and 20-year cumulative rates for all secondary tumors, malignant secondary tumors, and malignant nonhematologic secondary tumors were 8% and 16%, 5% and 13%, and 3% and 11%, respectively. Our data indicate that PBT has the potential to reduce the risk of late mortality and secondary malignancy. Longer follow-up is needed to confirm the benefits of PBT for pediatric tumors. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the diagnostic value of intravoxel incoherent motion (IVIM) and diffusional kurtosis imaging (DKI) parameters in nasal or sinonasal squamous cell carcinoma (SCC) patients to determine local control/failure.Methods: Twenty-eight patients were evaluated. MR acquisition used single-shot spin-echo EPI with 12 b-values. Quantitative parameters (mean value, 25th, 50th and 75th percentiles) of IVIM (perfusion fraction f, pseudo-diffusion coefficient D*, and true-diffusion coefficient D), DKI (kurtosis value K, kurtosis corrected diffusion coefficient Dk) and apparent diffusion coefficient (ADC) were calculated. Parameter values at both the pretreatment and early-treatment period, and the percentage change between these two periods were obtained.Results: Multivariate logistic regression analysis: the percentage changes of D (mean, 25th, 50th, 75th), K (mean, 50th, 75th), Dk (mean, 25th, 50th), and ADC (mean, 25th, 50th) were predictors of local control. ROC curve analysis: the parameter with the highest accuracy = the percentage change of D value with the histogram 25th percentile (0.93 diagnostic accuracy). Multivariate Cox regression analyses: the percentage changes of D (mean, 25th, 50th), K (mean, 50th, 75th), Dk (mean, 25th, 50th) and ADC (mean, 25th, 50th) are predictors.Conclusions: IVIM and DKI parameters, especially the D-value's histogram 25th percentile, are useful for predicting local control.Key Points: • Noninvasive assessment of treatment outcome in SCC patients was achieved using IVIM/DKI. • Several IVIM and DKI parameters can predict the local control. • Especially, the D-value's histogram 25th percentile has high diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Background: We aimed to assess the positivity, distribution, quantitative degree of vessel inflammation, and clinical characteristics of IgG4-related aortitis/periarteritis and periarteritis (IgG4-aortitis), and to examine the difference in these characteristics between cases with and without IgG4-aortitis, using fluorodeoxyglucose positron-emission tomography/computed tomography (FDG-PET/CT) co-registered with contrast-enhanced CT (CECT). We retrospectively evaluated 37 patients with IgG4-related disease (IgG4-RD) who underwent both FDG-PET/CT and CECT. The arterial SUVmax and its value normalized to the background venous blood pool (BP)-the target-to-background ratio (TBR) in the entire aorta and the major first branches-were measured. Active vascular inflammation was considered in cases with a higher FDG uptake than BP and a thickened arterial wall (>2 mm). Results: Fifteen (41%) patients exhibited IgG4-aortitis. Most patients (80%) showed multiple region involvement. The entire aorta, including the major first branches, were involved, typically showing a thickened wall and high FDG uptakes. The most common site was the iliac arteries (35%), followed by the infrarenal abdominal aorta (33%), thoracic aorta (8%), first branches of the thoracic aorta (8%), suprarenal abdominal aorta (6%), and the first branches of the abdominal aorta (5%). The IgG4-aortitis-positive vessel regions were thickened, with an average maximal wall thickness of 6.3 ± 2.9 mm. The SUVmax and TBR values were significantly higher in the IgG4-aortitis-positive regions (median 3.7 [1.6-5.5] and 2.1 [1.4-3.7], respectively) than in the IgG4-aortitis-negative regions (median 2.1 [1.2-3.7] and 1.3 [0.9-2.3], respectively; p < 0.0001). The IgG4-aortitis-positive group patients were older (69.5 ± 6.0 vs. 63.3 ± 12.6 years, respectively) and had a higher male predominance (80 vs. 55%, respectively) than the negative group, although the differences were not significant ( p = 0.17 and p = 0.06, respectively). Conclusions: We investigated the image characteristics of IgG4-aortitis. The entire aorta and major branches can be involved with more than 2-fold higher FDG uptake than the venous background pool, and with wall thickening. The most common involved site is the iliac arteries, followed by the infrarenal abdominal aorta. [ABSTRACT FROM AUTHOR]

Reference 1 Prayongrat A, Srimaneekarn N, Thonglert K, Khorprasert C, Amornwichet N, Alisanant P, Shirato H, Kobashi K, Sriswasdi S. Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients. B Correction: Radiation Oncology (2022) 17:202 b https://doi.org/10.1186/s13014-022-02138-8 After publication of this article [[1]], the authors reported that Sira Sriswasdi should have been denoted as co-corresponding author. [Extracted from the article]

The effect of 1-(3-C-ethynyl-β-D-ribo-pentofuranosyl)cytosine (ECyd) on proton-induced cell death was evaluated in human lung carcinoma cell line A549 and Chinese hamster fibroblast cell line V79 to enhance relative biological effectiveness (RBE) within the spread-out Bragg peak (SOBP) of proton beams. Treatment with ECyd significantly enhanced the proton-induced loss of clonogenicity and increased senescence at the center, but not at the distal edge of SOBP. The p53-binding protein 1 foci formation assay showed that ECyd decelerated the rate of DNA double-strand break (DSB) repair at the center, but not the distal region of SOBP, suggesting that the ECyd-induced enhancement of proton-induced cell death is partially associated with the inhibition of DSB repair. This study demonstrated that ECyd enhances proton-induced cell killing at all positions of SOBP, except for the distal region and minimizes the site-dependent differences in RBE within SOBP. Thus, ECyd is a unique radiosensitizer for proton therapy that may be useful because it levels the biological dose within SOBP, which improves tumor control and reduces the risk of adverse effects at the distal edge of SOBP. [ABSTRACT FROM AUTHOR]

Objective: To determine the relationship between tumor glucose metabolism and tumor blood flow (TBF) in head and neck squamous cell carcinoma (HNSCC). Methods: We retrospectively analyzed 57 HNSCC patients. Tumor glucose metabolism was assessed by maximum and mean standardized uptake values (SUVmax and SUVmean) obtained by 18F-fluorodeoxyglucose positron-emission tomography. TBF values were obtained by arterial spin labeling with 3-tesla MRI. The correlations between both SUVs and TBF were assessed in the total series and among patients divided by T-stage (T1–T3 and T4 groups) and tumor location (pharynx/oral cavity and sinonasal cavity groups). Pearson’s correlation coefficients were calculated for significant correlations. Results: Significant correlations were detected: a negative correlation in the advanced T-stage group (TBF and SUV max: r, −0.61, SUVmean: r, −0.62), a positive correlation in the non-advanced T-stage pharynx/oral cavity group (TBF and SUVmax: r, 0.70, SUVmean: r, 0.73), a negative correlation in the advanced T-stage pharynx/oral cavity group (TBF and SUVmax: r, −0.62, SUVmean: r, −0.65), and a negative correlation in the advanced T-stage sinonasal cavity group (TBF and SUVmax: r, −0.61, SUVmean: r, −0.65). Conclusion: Significant correlations between glucose uptake and TBF in HNSCC were revealed by the division of T-stage and tumor location. [ABSTRACT FROM AUTHOR]