Interobserver variation in tumor delineation of liver metastases using Magnetic Resonance Imaging.

Background and purpose: Magnetic Resonance Imaging (MRI) guided stereotactic body radiotherapy (SBRT) of liver metastases is an upcoming high-precision non-invasive treatment. Interobserver variation (IOV) in tumor delineation, however, remains a relevant uncertainty for planning target volume (PTV) margins. The aims of this study were to quantify IOV in MRI-based delineation of the gross tumor volume (GTV) of liver metastases and to detect patient-specific factors influencing IOV. Materials and methods: A total of 22 patients with liver metastases from three primary tumor origins were selected (colorectal(8), breast(6), lung(8)). Delineation guidelines and planning MRI-scans were provided to eight radiation oncologists who delineated all GTVs. All delineations were centrally peer reviewed to identify outliers not meeting the guidelines. Analyses were performed both in- and excluding outliers. IOV was quantified as the standard deviation (SD) of the perpendicular distance of each observer's delineation towards the median delineation. The correlation of IOV with shape regularity, tumor origin and volume was determined. Results: Including all delineations, average IOV was 1.6 mm (range 0.6-3.3 mm). From 160 delineations, in total fourteen single delineations were marked as outliers after peer review. After excluding outliers, the average IOV was 1.3 mm (range 0.6-2.3 mm). There was no significant correlation between IOV and tumor origin or volume. However, there was a significant correlation between IOV and regularity (Spearman's ρs = -0.66; p = 0.002). Conclusion: MRI-based IOV in tumor delineation of liver metastases was 1.3-1.6 mm, from which PTV margins for IOV can be calculated. Tumor regularity and IOV were significantly correlated, potentially allowing for patient-specific margin calculation.

Online Adaptive MR-Guided Ultrahypofractionated Radiotherapy of Prostate Cancer on a 1.5 T MR-Linac: Clinical Experience and Prospective Evaluation.

The use of hypofractionated radiotherapy in prostate cancer has been increasingly evaluated, whereas accumulated evidence demonstrates comparable oncologic outcomes and toxicity rates compared to normofractionated radiotherapy. In this prospective study, we evaluate all patients with intermediate-risk prostate cancer treated with ultrahypofractionated (UHF) MRI-guided radiotherapy on a 1.5 T MR-Linac within our department and report on workflow and feasibility, as well as physician-recorded and patient-reported longitudinal toxicity. A total of 23 patients with intermediate-risk prostate cancer treated on the 1.5 T MR-Linac with a dose of 42.7 Gy in seven fractions (seven MV step-and-shoot IMRT) were evaluated within the MRL-01 study (NCT04172753). The duration of each treatment step, choice of workflow (adapt to shape-ATS or adapt to position-ATP) and technical and/or patient-sided treatment failure were recorded for each fraction and patient. Acute and late toxicity were scored according to RTOG and CTC V4.0, as well as the use of patient-reported questionnaires. The median follow-up was 12.4 months. All patients completed the planned treatment. The mean duration of a treatment session was 38.2 min. In total, 165 radiotherapy fractions were delivered. ATS was performed in 150 fractions, 5 fractions were delivered using ATP, and 10 fractions were delivered using both ATS and ATP workflows. Severe acute bother (G3+) regarding IPS-score was reported in five patients (23%) at the end of radiotherapy. However, this tended to normalize and no G3+ IPS-score was observed later at any point during follow-up. Furthermore, no other severe genitourinary (GU) or gastrointestinal (GI) acute or late toxicity was observed. One-year biochemical-free recurrence survival was 100%. We report the excellent feasibility of UHF MR-guided radiotherapy for intermediate-risk prostate cancer patients and acceptable toxicity rates in our preliminary study. Randomized controlled studies with long-term follow-up are warranted to detect possible advantages over current state-of-the-art RT techniques.

Patient-Relevant Costs for Organ Preservation versus Radical Resection in Locally Advanced Rectal Cancer.

Total neoadjuvant therapy (TNT) is an evolving treatment schedule for locally advanced rectal cancer (LARC), allowing for organ preservation in a relevant number of patients in the case of complete response. Patients who undergo this so-called "watch and wait" approach are likely to benefit regarding their quality of life (QoL), especially if definitive ostomy could be avoided. In this work, we performed the first cost-effectiveness analysis from the patient perspective to compare costs for TNT with radical resection after neoadjuvant chemoradiation (CRT) in the German health care system. Individual costs for patients insured with a statutory health insurance were calculated with a Markov microsimulation. A subgroup analysis from the prospective "FinTox" trial was used to calibrate the model's parameters. We found that TNT was less expensive (-1540 EUR) and simultaneously resulted in a better QoL (+0.64 QALYs) during treatment and 5-year follow-up. The average cost for patients under TNT was 4711 EUR per year, which was equivalent to 3.2% of the net household income. CRT followed by resection resulted in higher overall costs for ostomy care, medication and greater loss of earnings. Overall, TNT appeared to be more efficacious and cost-effective from a patient's point of view in the German health care system.

Full daily re-optimization improves plan quality during online adaptive radiotherapy.

Background and purpose: Daily online treatment plan adaptation requires a fast workflow and planning process. Current online planning consists of adaptation of a predefined reference plan, which might be suboptimal in cases of large anatomic changes. The aim of this study was to investigate plan quality differences between the current online re-planning approach and a complete re-optimization. Material and methods: Magnetic resonance linear accelerator reference plans for ten prostate cancer patients were automatically generated using particle swarm optimization (PSO). Adapted plans were created for each fraction using (1) the current re-planning approach and (2) full PSO re-optimization and evaluated overall compliance with institutional dose-volume criteria compared to (3) clinically delivered fractions. Relative volume differences between reference and daily anatomy were assessed for planning target volumes (PTV60, PTV57.6), rectum and bladder and correlated with dose-volume results. Results: The PSO approach showed significantly higher adherence to dose-volume criteria than the reference approach and clinical fractions (p < 0.001). In 74 % of PSO plans at most one criterion failed compared to 56 % in the reference approach and 41 % in clinical plans. A fair correlation between PTV60 D98% and relative bladder volume change was observed for the reference approach. Bladder volume reductions larger than 50 % compared to the reference plan recurrently decreased PTV60 D98% below 56 Gy. Conclusion: Complete re-optimization maintained target coverage and organs at risk sparing even after large anatomic variations. Re-planning based on daily magnetic resonance imaging was sufficient for small variations, while large variations led to decreasing target coverage and organ-at-risk sparing.

Reproducibility of diffusion-weighted magnetic resonance imaging in head and neck cancer assessed on a 1.5 T MR-Linac and comparison to parallel measurements on a 3 T diagnostic scanner.

BACKGROUND AND PURPOSE: Before quantitative imaging biomarkers (QIBs) acquired with magnetic resonance imaging (MRI) can be used for interventional trials in radiotherapy (RT), technical validation of these QIBs is necessary. The aim of this study was to assess the reproducibility of apparent diffusion coefficient (ADC) values, derived from diffusion-weighted (DW) MRI, in head and neck cancer using a 1.5 T MR-Linac (MRL) by comparison to a 3 T diagnostic scanner (DS). MATERIAL AND METHODS: DW-MRIs were acquired on MRL and DS for 15 head and neck cancer patients before RT and in week 2 and rigidly registered to the planning computed tomography. Mean ADC values were calculated for submandibular (SG) and parotid (PG) glands as well as target volumes (TV, gross tumor volume and lymph nodes), which were delineated based on computed tomography. Mean absolute ADC differences as well as within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs) were calculated for all volumes of interest. RESULTS: A total of 23 datasets were analyzed. Mean ADC difference (DS-MRL) for SG, PG and TV resulted in 142, 254 and 93·10-6 mm2/s. wCVs/ICCs, comparing MRL and DS, were determined as 13.7 %/0.26, 24.4 %/0.23 and 16.1 %/0.73 for SG, PG and TV, respectively. CONCLUSION: ADC values, measured on the 1.5 T MRL, showed reasonable reproducibility with an ADC underestimation in contrast to the DS. This ADC shift must be validated in further experiments and considered for future translation of QIB candidates from DS to MRL for response adaptive RT.

The value of subcutaneous xenografts for individualised radiotherapy in HNSCC: Robust gene signature correlates with radiotherapy outcome in patients and xenografts.

PURPOSE: To assess the robustness of prognostic biomarkers and molecular tumour subtypes developed for patients with head and neck squamous cell carcinoma (HNSCC) on cell-line derived HNSCC xenograft models, and to develop a novel biomarker signature by combining xenograft and patient datasets. MATERIALS AND METHODS: Mice bearing xenografts (n = 59) of ten HNSCC cell lines and a retrospective, multicentre patient cohort (n = 242) of the German Cancer Consortium-Radiation Oncology Group (DKTK-ROG) were included. All patients received postoperative radiochemotherapy (PORT-C). Gene expression analysis was conducted using GeneChip Human Transcriptome Arrays. Xenografts were stratified based on their molecular subtypes and previously established gene classifiers. The dose to control 50 % of tumours (TCD50) was compared between these groups. Using differential gene expression analyses combining xenograft and patient data, a gene signature was developed to define risk groups for the primary endpoint loco-regional control (LRC). RESULTS: Tumours of mesenchymal subtype were characterized by a higher TCD50 (xenografts, p < 0.001) and lower LRC (patients, p < 0.001) compared to the other subtypes. Similar to previously published patient data, hypoxia- and radioresistance-related gene signatures were associated with high TCD50 values. A 2-gene signature (FN1, SERPINE1) was developed that was prognostic for TCD50 (xenografts, p < 0.001) and for patient outcome in independent validation (LRC: p = 0.007). CONCLUSION: Genetic prognosticators of outcome for patients after PORT-C and subcutaneous xenografts after primary clinically relevant irradiation show similarity. The identified robust 2-gene signature may help to guide patient stratification, after prospective validation. Thus, xenografts remain a valuable resource for translational research towards the development of individualized radiotherapy.

Satisfaction with radiotherapy care among cancer patients treated in Germany-secondary analysis of a large multicenter study.

PURPOSE: Patient satisfaction with healthcare has been linked to clinical outcomes and regulatory agencies demand its regular assessment. Therefore, we aimed to investigate patient satisfaction with radiotherapy care and its determinants. METHODS: This is a secondary analysis of a multicenter prospective cross-sectional study. Eligible cancer patients anonymously completed questionnaires at the end of a course of radiotherapy. The outcome variable was overall patient satisfaction with radiotherapy care measured with a 10-point Likert scaled single-item. Given patient satisfaction was defined for patients scoring ≥ 8 points. Determinants of given patient satisfaction were assessed by univariable and multivariable analyses. A p-value < 0.05 was considered statistically significant. RESULTS: Out of 2341 eligible patients, 1075 participated (participation rate 46%). Data on patient satisfaction was provided by 1054 patients. There was a right-skewed distribution towards more patient satisfaction (mean = 8.8; SD = 1.68). Given patient satisfaction was reported by 85% (899/1054) of the patients. Univariable analyses revealed significant associations of lower patient satisfaction with tumor entity (rectal cancer), concomitant chemotherapy, inpatient care, treating center, lower income, higher costs, and lower quality of life. Rectal cancer as tumor entity, treating center, and higher quality of life remained significant determinants of patient satisfaction in a multivariable logistic regression. CONCLUSION: Overall patient satisfaction with radiotherapy care was high across 11 centers in Germany. Determinants of patient satisfaction were tumor entity, treating center, and quality of life. Although these data are exploratory, they may inform other centers and future efforts to maintain high levels of patient satisfaction with radiotherapy care.

Multitask Learning with Convolutional Neural Networks and Vision Transformers Can Improve Outcome Prediction for Head and Neck Cancer Patients.

Neural-network-based outcome predictions may enable further treatment personalization of patients with head and neck cancer. The development of neural networks can prove challenging when a limited number of cases is available. Therefore, we investigated whether multitask learning strategies, implemented through the simultaneous optimization of two distinct outcome objectives (multi-outcome) and combined with a tumor segmentation task, can lead to improved performance of convolutional neural networks (CNNs) and vision transformers (ViTs). Model training was conducted on two distinct multicenter datasets for the endpoints loco-regional control (LRC) and progression-free survival (PFS), respectively. The first dataset consisted of pre-treatment computed tomography (CT) imaging for 290 patients and the second dataset contained combined positron emission tomography (PET)/CT data of 224 patients. Discriminative performance was assessed by the concordance index (C-index). Risk stratification was evaluated using log-rank tests. Across both datasets, CNN and ViT model ensembles achieved similar results. Multitask approaches showed favorable performance in most investigations. Multi-outcome CNN models trained with segmentation loss were identified as the optimal strategy across cohorts. On the PET/CT dataset, an ensemble of multi-outcome CNNs trained with segmentation loss achieved the best discrimination (C-index: 0.29, 95% confidence interval (CI): 0.22-0.36) and successfully stratified patients into groups with low and high risk of disease progression (p=0.003). On the CT dataset, ensembles of multi-outcome CNNs and of single-outcome ViTs trained with segmentation loss performed best (C-index: 0.26 and 0.26, CI: 0.18-0.34 and 0.18-0.35, respectively), both with significant risk stratification for LRC in independent validation (p=0.002 and p=0.011). Further validation of the developed multitask-learning models is planned based on a prospective validation study, which has recently completed recruitment.

Automatic AI-based contouring of prostate MRI for online adaptive radiotherapy.

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.

Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models.

PURPOSE: Tumor hypoxia and other microenvironmental factors are key determinants of treatment resistance. Hypoxia positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are established prognostic imaging modalities to identify radiation resistance in head-and-neck cancer (HNC). The aim of this preclinical study was to develop a multi-parametric imaging parameter specifically for focal radiotherapy (RT) dose escalation using HNC xenografts of different radiation sensitivities. METHODS: A total of eight human HNC xenograft models were implanted into 68 immunodeficient mice. Combined PET/MRI using dynamic [18F]-fluoromisonidazole (FMISO) hypoxia PET, diffusion-weighted (DW), and dynamic contrast-enhanced MRI was carried out before and after fractionated RT (10 × 2 Gy). Imaging data were analyzed on voxel-basis using principal component (PC) analysis for dynamic data and apparent diffusion coefficients (ADCs) for DW-MRI. A data- and hypothesis-driven machine learning model was trained to identify clusters of high-risk subvolumes (HRSs) from multi-dimensional (1-5D) pre-clinical imaging data before and after RT. The stratification potential of each 1D to 5D model with respect to radiation sensitivity was evaluated using Cohen's d-score and compared to classical features such as mean/peak/maximum standardized uptake values (SUVmean/peak/max) and tumor-to-muscle-ratios (TMRpeak/max) as well as minimum/valley/maximum/mean ADC. RESULTS: Complete 5D imaging data were available for 42 animals. The final preclinical model for HRS identification at baseline yielding the highest stratification potential was defined in 3D imaging space based on ADC and two FMISO PCs ([Formula: see text]). In 1D imaging space, only clusters of ADC revealed significant stratification potential ([Formula: see text]). Among all classical features, only ADCvalley showed significant correlation to radiation resistance ([Formula: see text]). After 2 weeks of RT, FMISO_c1 showed significant correlation to radiation resistance ([Formula: see text]). CONCLUSION: A quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.

Psychosocial distress in cancer patients undergoing radiotherapy: a prospective national cohort of 1042 patients in Germany.

PURPOSE: Psychosocial distress is common among cancer patients in general, but those undergoing radiotherapy may face specific challenges. Therefore, we investigated the prevalence and risk factors for distress in a large national cohort. METHODS: We performed a secondary analysis of a multicenter prospective cross-sectional study which surveyed cancer patients at the end of a course of radiotherapy using a patient-reported questionnaire. Distress was measured with the distress thermometer (DT), using a cut-off of ≥ 5 points for clinically significant distress. Univariate analyses and multivariate multiple regression were used to assess associations of distress with patient characteristics. A two-sided p-value < 0.05 was considered statistically significant. RESULTS: Out of 2341 potentially eligible patients, 1075 participated in the study, of which 1042 completed the DT. The median age was 65 years and 49% (511/1042) of patients were female. The mean DT score was 5.2 (SD = 2.6). Clinically significant distress was reported by 63% (766/1042) of patients. Of the patient characteristics that were significantly associated with distress in the univariate analysis, a lower level of education, a higher degree of income loss, lower global quality of life, and a longer duration of radiotherapy in days remained significantly associated with higher distress in the multivariate analysis. Yet effect sizes of these associations were small. CONCLUSION: Nearly two in three cancer patients undergoing radiotherapy reported clinically significant distress in a large multicenter cohort. While screening and interventions to reduce distress should be maintained and promoted, the identified risk factors may help to raise awareness in clinical practice. TRIAL REGISTRY IDENTIFIER: DRKS: German Clinical Trial Registry identifier: DRKS00028784.

Financial toxicity in cancer patients undergoing radiotherapy in a universal health care system - A prospective multicenter study of 1075 patients.

PURPOSE: To establish and confirm prevalence as well as risk factors of financial toxicity in a large national cohort of cancer patients undergoing radiotherapy in a universal health care system. METHODS: We conducted a prospective cross-sectional study offering a patient-reported questionnaire to all eligible cancer patients treated with radiotherapy in 11 centers in Germany during 60 consecutive days. The four-point subjective financial distress question of the EORTC QLQ-C30 was used as a surrogate for financial toxicity. Confirmatory hypothesis testing evaluated the primary study outcomes: overall prevalence of financial toxicity and its association with predefined risk factors. P-values < 0.05 were considered statistically significant. RESULTS: Of 2341 eligible patients, 1075 (46%) participated. The prevalence of subjective financial distress (=any grade higher than not present) was 41% (438/1075) exceeding the hypothesized range of 26.04-36.31%. Subjective financial distress was felt "A little" by 26% (280/1075), "Quite a bit" by 11% (113/1075) and "Very much" by 4% (45/1075) of the patients. Lower household income, lower global health status/ quality of life, higher direct costs and higher loss of income significantly predicted higher subjective financial distress per ordinal regression and confirmed these risk factors. Higher psychosocial distress and lower patient satisfaction were significantly associated with higher subjective financial distress in an exploratory ordinal regression model. CONCLUSION: The overall prevalence of financial toxicity was higher than anticipated, although reported at low or moderate degrees by most affected patients. As we confirmed risk factors associated with financial toxicity, patients at risk should be addressed early for potential support.

Impact of endorectal filling on interobserver variability of MRI based rectal primary tumor delineation.

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_e) and with application of 100 cc of ultrasound gel transanally (MRI_f). Eight international radiation oncologists expert in the treatment of gastrointestinal cancers delineated the gross tumor volume (GTV) on both MRI scans. MRI_f scans were provided to the participating centers after MRI_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_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_e and 44.20 [19.72-61.59 cc] in MRI_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.

Online MR guided dose escalated radiotherapy for organ preservation in distal rectal cancer.

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.

First Experience and Prospective Evaluation on Feasibility and Acute Toxicity of Online Adaptive Radiotherapy of the Prostate Bed as Salvage Treatment in Patients with Biochemically Recurrent Prostate Cancer on a 1.5T MR-Linac.

INTRODUCTION: Novel MRI-linear accelerator hybrids (MR-Linacs, MRL) promise an optimization of radiotherapy (RT) through daily MRI imaging with enhanced soft tissue contrast and plan adaptation on the anatomy of the day. These features might potentially improve salvage RT of prostate cancer (SRT), where the clinical target volume is confined by the mobile organs at risk (OAR) rectum and bladder. So far, no data exist about the feasibility of the MRL technology for SRT. In this study, we prospectively examined patients treated with SRT on a 1.5 T MRL and report on workflow, feasibility and acute toxicity. PATIENTS AND METHODS: Sixteen patients were prospectively enrolled within the MRL-01 study (NCT: NCT04172753). All patients were staged and had an indication for SRT after radical prostatectomy according to national guidelines. RT consisted of 66 Gy in 33 fractions or 66.5/70 Gy in 35 fractions in case of a defined high-risk region. On the 1.5 T MRL, daily plan adaption was performed using one of two workflows: adapt to shape (ATS, using contour adaptation and replanning) or adapt to position (ATP, rigid replanning onto the online anatomy with virtual couch shift). Duration of treatment steps, choice of workflow and treatment failure were recorded for each fraction of each patient. Patient-reported questionnaires about patient comfort were evaluated as well as extensive reporting of acute toxicity (patient reported and clinician scored). RESULTS: A total of 524/554 (94.6%) of fractions were successfully treated on the MRL. No patient-sided treatment failures occurred. In total, ATP was chosen in 45.7% and ATS in 54.3% of fractions. In eight cases, ATP was performed on top of the initial ATS workflow. Mean (range) duration of all fractions (on-table time until end of treatment) was 25.1 (17.6-44.8) minutes. Mean duration of the ATP workflow was 20.60 (17.6-25.2) minutes and of the ATS workflow 31.3 (28.2-34.1) minutes. Patient-reported treatment experience questionnaires revealed high rates of tolerability of the treatment procedure. Acute toxicity (RTOG, CTC as well as patient-reported CTC, IPSS and ICIQ) during RT and 3 months after was mild to moderate with a tendency of recovery to baseline levels at 3 months post RT. No G3+ toxicity was scored for any item. CONCLUSIONS: In this first report on SRT of prostate cancer patients on a 1.5 T MRL, we could demonstrate the feasibility of both available workflows. Daily MR-guided adaptive SRT of mean 25.1 min per fraction was well tolerated in this pretreated collective, and we report low rates of acute toxicity for this treatment. This study suggests that SRT on a 1.5 T MRL can be performed in clinical routine and it serves as a benchmark for future analyses.

Repeatability of diffusion-weighted magnetic resonance imaging in head and neck cancer at a 1.5 T MR-Linac.

BACKGROUND AND PURPOSE: Functional information acquired through diffusion-weighted magnetic resonance imaging (DW-MRI) may be beneficial for personalized head and neck cancer (HNC) radiotherapy. Technical validation is required before DW-MRI based radiotherapy interventions can be realized clinically. The aim of this study was to assess the repeatability of apparent diffusion coefficients (ADC) derived from DW-MRI in HNC using echo-planar imaging (EPI) on a 1.5 T MR-Linac. MATERIAL AND METHODS: A total of eleven HNC patients underwent test/retest DW-MRI scans at least once per week during fractionated radiotherapy at the MR-Linac. An EPI DW-MRI test scan (b = 0, 150, 500 s/mm2) was acquired before the start of adaptive MR-guided radiotherapy in addition to an identical retest scan after irradiation. Volumes-of-interest (VOI) were defined manually for parotid (PTs) and submandibular glands (SMs), gross tumor volume (GTV) and lymph nodes (LNs). Mean ADC was calculated for all VOI in all test/retest scans. Absolute/relative repeatability coefficients (RCs/relRCs) as well as intraclass correlation coefficients (ICCs) were determined for all VOIs. RESULTS: A total of 81 datasets were analyzed. Mean test ADC values were 1380/1416, 950/1010, 1520 and 1344 · 10-6 mm2/s for left/right SM and PT, GTV and LNs, respectively. Accordingly, RC (relRC) values were determined as 271/281 (19.4/21.8%) and 138/155 (13.3/15.2%), 457 (31.3%) and 310 · 10-6 mm2/s (23.5%). ICC resulted in 0.80/0.87, 0.97/0.94, 0.75 and 0.83 for left/right SM and PT, GTV and LNs, respectively. CONCLUSION: The repeatability of ADC derived from EPI DW-MRI at the 1.5 T MR-Linac appears reasonable to be used for future biologically adapted MR-guided radiotherapy.

A Novel 2-Metagene Signature to Identify High-Risk HNSCC Patients amongst Those Who Are Clinically at Intermediate Risk and Are Treated with PORT.

(1) Background: Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who are biologically at high risk for the development of loco−regional recurrences after postoperative radiotherapy (PORT) but at intermediate risk according to clinical risk factors may benefit from additional concurrent chemotherapy. In this matched-pair study, we aimed to identify a corresponding predictive gene signature. (2) Methods: Gene expression analysis was performed on a multicenter retrospective cohort of 221 patients that were treated with postoperative radiochemotherapy (PORT-C) and 283 patients who were treated with PORT alone. Propensity score analysis was used to identify matched patient pairs from both cohorts. From differential gene expression analysis and Cox regression, a predictive gene signature was identified. (3) Results: 108 matched patient pairs were selected. We identified a 2-metagene signature that stratified patients into risk groups in both cohorts. The comparison of the high-risk patients between the two types of treatment showed higher loco−regional control (LRC) after treatment with PORT-C (p < 0.001), which was confirmed by a significant interaction term in Cox regression (p = 0.027), i.e., the 2-metagene signature was indicative for the type of treatment. (4) Conclusion: We have identified a novel gene signature that may be helpful to identify patients with high-risk HNSCC amongst those at intermediate clinical risk treated with PORT, who may benefit from additional concurrent chemotherapy.

First multicentre experience of SABR for lymph node and liver oligometastatic disease on the unity MR-Linac.

The treatment of oligometastatic disease using MR guidance is an evolving field. Since August 2018 patients are treated on a 1.5 Tesla MR-Linac (MRL). We present current workflows and practice standards from seven institutions for the initial patients treated for lymph node and liver metastases.

Development and validation of a 6-gene signature for the prognosis of loco-regional control in patients with HPV-negative locally advanced HNSCC treated by postoperative radio(chemo)therapy.

PURPOSE: The aim of this study was to develop and validate a novel gene signature from full-transcriptome data using machine-learning approaches to predict loco-regional control (LRC) of patients with human papilloma virus (HPV)-negative locally advanced head and neck squamous cell carcinoma (HNSCC), who received postoperative radio(chemo)therapy (PORT-C). MATERIALS AND METHODS: Gene expression analysis was performed using Affymetrix GeneChip Human Transcriptome Array 2.0 on a multicentre retrospective training cohort of 128 patients and an independent validation cohort of 114 patients from the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG). Genes were filtered based on differential gene expression analyses and Cox regression. The identified gene signature was combined with clinical parameters and with previously identified genes related to stem cells and hypoxia. Technical validation was performed using nanoString technology. RESULTS: We identified a 6-gene signature consisting of four individual genes CAV1, GPX8, IGLV3-25, TGFBI, and one metagene combining the highly correlated genes INHBA and SERPINE1. This signature was prognostic for LRC on the training data (ci = 0.84) and in validation (ci = 0.63) with a significant patient stratification into two risk groups (p = 0.005). Combining the 6-gene signature with the clinical parameters T stage and tumour localisation as well as the cancer stem cell marker CD44 and the 15-gene hypoxia-associated signature improved the validation performance (ci = 0.69, p = 0.001). CONCLUSION: We have developed and validated a novel prognostic 6-gene signature for LRC of HNSCC patients with HPV-negative tumours treated by PORT-C. After successful prospective validation the signature can be part of clinical trials on the individualization of radiotherapy.

Clinical evaluation of autonomous, unsupervised planning integrated in MR-guided radiotherapy for prostate cancer.

This retrospective study aimed at clinical evaluation of autonomous radiotherapy planning for ten prostate cancer cases, including organ-at-risk/target contouring and treatment planning. Five experts scored the clinical acceptability of each step using a 4-level Likert-scale resulting in 78%, 66% and 90% acceptance. For 6/10 patients the entire workflow was considered acceptable.