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Background and Purpose: MR-guided radiotherapy (MRgRT) online plan adaptation accounts for tumor volume changes, interfraction motion and thus allows daily sparing of relevant organs at risk. Due to the high interfraction variability of bladder and rectum, patients with tumors in the pelvic region may strongly benefit from adaptive MRgRT. Currently, fast automatic annotation of anatomical structures is not available within the online MRgRT workflow. Therefore, the aim of this study was to train and validate a fast, accurate deep learning model for automatic MRI segmentation at the MR-Linac for future implementation in a clinical MRgRT workflow., Materials and Methods: For a total of 47 patients, T2w MRI data were acquired on a 1.5 T MR-Linac (Unity, Elekta) on five different days. Prostate, seminal vesicles, rectum, anal canal, bladder, penile bulb, body and bony structures were manually annotated. These training data consisting of 232 data sets in total was used for the generation of a deep learning based autocontouring model and validated on 20 unseen T2w-MRIs. For quantitative evaluation the validation set was contoured by a radiation oncologist as gold standard contours (GSC) and compared in MATLAB to the automatic contours (AIC). For the evaluation, dice similarity coefficients (DSC), and 95% Hausdorff distances (95% HD), added path length (APL) and surface DSC (sDSC) were calculated in a caudal-cranial window of ± 4 cm with respect to the prostate ends. For qualitative evaluation, five radiation oncologists scored the AIC on the possible usage within an online adaptive workflow as follows: (1) no modifications needed, (2) minor adjustments needed, (3) major adjustments/ multiple minor adjustments needed, (4) not usable., Results: The quantitative evaluation revealed a maximum median 95% HD of 6.9 mm for the rectum and minimum median 95% HD of 2.7 mm for the bladder. Maximal and minimal median DSC were detected for bladder with 0.97 and for penile bulb with 0.73, respectively. Using a tolerance level of 3 mm, the highest and lowest sDSC were determined for rectum (0.94) and anal canal (0.68), respectively. Qualitative evaluation resulted in a mean score of 1.2 for AICs over all organs and patients across all expert ratings. For the different autocontoured structures, the highest mean score of 1.0 was observed for anal canal, sacrum, femur left and right, and pelvis left, whereas for prostate the lowest mean score of 2.0 was detected. In total, 80% of the contours were rated be clinically acceptable, 16% to require minor and 4% major adjustments for online adaptive MRgRT., Conclusion: In this study, an AI-based autocontouring was successfully trained for online adaptive MR-guided radiotherapy on the 1.5 T MR-Linac system. The developed model can automatically generate contours accepted by physicians (80%) or only with the need of minor corrections (16%) for the irradiation of primary prostate on the clinically employed sequences., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [The authors report institutional collaborations with TheraPanacea, Elekta, Philips, Kaiku and PTW Freiburg which provided technical and/or financial support. TheraPanacea developed the proposed model, but were not involved in the analysis and scoring of the testing dataset.], (Copyright © 2023 The Author(s). Published by Elsevier GmbH.. All rights reserved.)

Background and Purpose: The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it., Materials and Methods: Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm 2 , region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CV D ) and calculation methods (CV C ). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group., Results: The median (range) CV D and CV C were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CV C to 0.04 (0.01-0.16). CV D was comparable between ROI types., Conclusion: Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Introduction: Non-surgical management of rectal cancer aiming for organ-preservation is an important development to improve rectal cancer treatment. Dose escalated radiotherapy represents one approach to increase clinical complete response (cCR) rates. In the present study we present feasibility and outcome data on rectal cancer patients who were treated with dose escalated radiotherapy using an MR guided online response-adaptive workflow., Material and Methods: A total of five patients were treated with 45 Gy in 25 fractions to the mesorectum and the internal iliac lymph nodes and a simultaneous integrated boost to the primary tumor with 50 Gy in 25 fractions on a conventional linac. In addition, weekly response-adaptive boost fractions with 3 Gy per fraction were scheduled on a 1.5 T MR-Linac. Concomitant chemotherapy with 5-fluorouracil was given as continuous venous infusion during the first and last week of treatment. Response was evaluated approximately-three months after the end of treatment and surgery was omitted in case of a clinical complete response (cCR) or a near cCR. Toxicity was graded by using PRO-CTCAE, Quality of life by the EORTC-QLQ-C30 questionnaire and continence according to the Wexner scale., Results: Response-adaptive dose escalated radiotherapy was feasible and well tolerated by all patients. Four reached a clinical complete response, one had a local excision confirming pathological complete response (pCR). All PRO-CTCAE grade 3 toxicities resolved within six months after the end of treatment. Quality of life and continence scores during follow-up were comparable to baseline levels., Conclusion: Dose-escalated online response-adaptive MR-guided radiotherapy appears to be a very promising treatment with the goal of organ preservation in rectal cancer leading to high response rates, excellent organ function and limited side effects. Further prospective evaluation is needed., Competing Interests: The Department of Radiation Oncology Tübingen receives financial and technical support by Elekta, Philips, Siemens, Dr. Sennewald Medizintechnik, Kaiku Health, TheraPanacea, PTW Freiburg and ITV in the context of research cooperations. Travel costs were covered by Elekta for CG, SB., (© 2022 The Author(s).)

Background: Online adaptive MR-guided radiotherapy allows for the reduction of safety margins in dose escalated treatment of rectal tumors. With the use of smaller margins, precise tumor delineation becomes more critical. In the present study we investigated the impact of rectal ultrasound gel filling on interobserver variability in delineation of primary rectal tumor volumes., Methods: Six patients with locally advanced rectal cancer were scanned on a 1.5 T MRI-Linac without (MRI&#95;e) and with application of 100 cc of ultrasound gel transanally (MRI&#95;f). Eight international radiation oncologists expert in the treatment of gastrointestinal cancers delineated the gross tumor volume (GTV) on both MRI scans. MRI&#95;f scans were provided to the participating centers after MRI&#95;e scans had been returned. Interobserver variability was analyzed by either comparing the observers' delineations with a reference delineation (approach 1) and by building all possible pairs between observers (approach 2). Dice Similarity Index (DICE) and 95 % Hausdorff-Distance (95 %HD) were calculated., Results: Rectal ultrasound gel filling was well tolerated by all patients. Overall, interobserver agreement was superior in MRI&#95;f scans based on median DICE (0.81 vs 0.74, p < 0.005 for approach 1 and 0.76 vs 0.64, p < 0.0001 for approach 2) and 95 %HD (6.9 mm vs 4.2 mm for approach 1, p = 0.04 and 8.9 mm vs 6.1 mm, p = 0.04 for approach 2). Delineated median tumor volumes and inter-quartile ranges were 26.99 cc [18.01-50.34 cc] in MRI&#95;e and 44.20 [19.72-61.59 cc] in MRI&#95;f scans respectively, p = 0.012., Conclusions: Although limited by the small number of patients, in this study the application of rectal ultrasound gel resulted in higher interobserver agreement in rectal GTV delineation. The endorectal gel filling might be a useful tool for future dose escalation strategies., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The Department of Radiation Oncology Tübingen (SB, CG, DT, DZ) receives within the frame of research agreements financial and technical support as well as sponsoring for travels and scientific symposia from: Elekta AB (Stockholm, Sweden), Philips GmbH, Siemens, PTW Freiburg Physikalisch-Technische Werkstätten Dr. Pychlau GmbH. SB: Honoraria for talks by Elekta. AT: Travel and speaking funding by Elekta. from Elekta. PBR is supported by an NIH/NCI grant (K08CA255574), the Memorial Sloan Kettering Cancer Center, an NIH Loan Repayment Program (LRP) award. PBR and RS are supported in part by a National Institutes of Health/National Cancer Institute (NIH/NCI) Memorial Sloan Kettering Cancer Center (MSK) Support Grant (P30 CA008748)., (© 2022 The Author(s).)