Mustafa Mert Hanilce, Cemal Ugur Dursun, Beyhan Ceylaner Bicakci
{"title":"Comment on the article by Fleischmann et al. on treatment for recurrent glioma","authors":"Mustafa Mert Hanilce, Cemal Ugur Dursun, Beyhan Ceylaner Bicakci","doi":"10.1016/j.radonc.2024.110564","DOIUrl":"10.1016/j.radonc.2024.110564","url":null,"abstract":"","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110564"},"PeriodicalIF":4.9,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142381529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emma Skarsø Buhl , Ebbe Laugaard Lorenzen , Lasse Refsgaard , Anders Winther Mølby Nielsen , Annette Torbøl Lund Brixen , Else Maae , Hanne Spangsberg Holm , Joachim Schøler , Linh My Hoang Thai , Louise Wichmann Matthiessen , Maja Vestmø Maraldo , Mathias Maximiliano Nielsen , Marianne Besserman Johansen , Marie Louise Milo , Marie Benzon Mogensen , Mette Holck Nielsen , Mette Møller , Maja Sand , Peter Schultz , Sami Aziz-Jowad Al-Rawi , Stine Sofia Korreman
{"title":"Development and comprehensive evaluation of a national DBCG consensus-based auto-segmentation model for lymph node levels in breast cancer radiotherapy","authors":"Emma Skarsø Buhl , Ebbe Laugaard Lorenzen , Lasse Refsgaard , Anders Winther Mølby Nielsen , Annette Torbøl Lund Brixen , Else Maae , Hanne Spangsberg Holm , Joachim Schøler , Linh My Hoang Thai , Louise Wichmann Matthiessen , Maja Vestmø Maraldo , Mathias Maximiliano Nielsen , Marianne Besserman Johansen , Marie Louise Milo , Marie Benzon Mogensen , Mette Holck Nielsen , Mette Møller , Maja Sand , Peter Schultz , Sami Aziz-Jowad Al-Rawi , Stine Sofia Korreman","doi":"10.1016/j.radonc.2024.110567","DOIUrl":"10.1016/j.radonc.2024.110567","url":null,"abstract":"<div><h3>Background and purpose</h3><div>This study aimed at training and validating a multi-institutional deep learning (DL) auto segmentation model for nodal clinical target volume (CTVn) in high-risk breast cancer (BC) patients with both training and validation dataset created with multi-institutional participation, with the overall aim of national clinical implementation in Denmark.</div></div><div><h3>Materials and methods</h3><div>A gold standard (GS) dataset and a high-quality training dataset were created by 21 BC delineation experts from all radiotherapy centres in Denmark. The delineations were created according to ESTRO consensus delineation guidelines. Four models were trained: One per laterality and extension of CTVn internal mammary nodes. The DL models were tested quantitatively in their own test-set and in relation to interobserver variation (IOV) in the GS dataset with geometrical metrics, such as the Dice Similarity Coefficient (DSC). A blinded qualitative evaluation was conducted with a national board, presented to both DL and manual delineations.</div></div><div><h3>Results</h3><div>A median DSC > 0.7 was found for all, except the CTVn interpectoral node in one of the models. In the qualitative evaluation ‘no corrections needed’ were acquired for 297 (36 %) in the DL structures and 286 (34 %) for manual delineations. A higher rate of ‘major corrections’ and ‘easier to start from scratch’ was found in the manual delineations. The models performed within the IOV of an expert group, with two exceptions.</div></div><div><h3>Conclusion</h3><div>DL models were developed on a national consensus cohort and performed on par with the IOV between BC experts and had a comparable or higher clinical acceptance than expert manual delineations.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110567"},"PeriodicalIF":4.9,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142392885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A systems theory-based safety assessment of pre-treatment patient-specific quality assurance for intensity-modulated treatments in a single-vendor environment","authors":"Lawrence M. Wong, Todd Pawlicki","doi":"10.1016/j.radonc.2024.110569","DOIUrl":"10.1016/j.radonc.2024.110569","url":null,"abstract":"<div><h3>Background and purpose</h3><div>While patient-specific quality assurance (PSQA) has been integral to intensity-modulated treatments, its value is debated. A systems approach to safety is essential for understanding complex systems like radiation oncology but is often overlooked in PSQA research. This study aims to elucidate PSQA’s fundamental value and identify opportunities for enhancing safety in intensity-modulated treatments.</div></div><div><h3>Materials and Methods</h3><div>First, causal scenarios that could lead to patient harm were identified using a prospective safety assessment technique developed for complex systems. Second, PSQA’s ability to mitigate these scenarios was evaluated using standard stability and control principles. The analysis also included safeguards related to PSQA, such as daily linac QA, equipment commissioning, and equipment design.</div></div><div><h3>Results</h3><div>Ten causal scenarios were identified, highlighting well-known issues like flawed algorithms, data corruption, and hardware errors. Mitigation is achieved through advanced dose calculation and optimization algorithms, software and data integration, and preconfigured beam data, which improve decision-making and system state determination. Modern linac control systems enhance all aspects of system stability and control. Commissioning, daily linac QA, and PSQA are effective in enhancing the determination of system states only when feedback is non-overlapping and unambiguous.</div></div><div><h3>Conclusion</h3><div>Given equipment improvement and related safeguards, the feedback generated from PSQA has diminished in value. To better complement other safeguards, PSQA should evolve to provide automated, unambiguous detection of any potential catastrophic treatment deviations prior to treatment. This evolution would allow physicists to focus on more critical aspects of patient care in radiation oncology.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110569"},"PeriodicalIF":4.9,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cédric Draulans , Karin Haustermans , Floris J. Pos , Uulke A. van der Heide , Lisa De Cock , Jochem van der Voort van Zyp , Hans De Boer , Robert J. Smeenk , Martina Kunze-Busch , Evelyn M. Monninkhof , Robin De Roover , Sofie Isebaert , Linda G.W. Kerkmeijer
{"title":"Stereotactic body radiotherapy with a focal boost to the intraprostatic tumor for intermediate and high risk prostate cancer: 5-year efficacy and toxicity in the hypo-FLAME trial","authors":"Cédric Draulans , Karin Haustermans , Floris J. Pos , Uulke A. van der Heide , Lisa De Cock , Jochem van der Voort van Zyp , Hans De Boer , Robert J. Smeenk , Martina Kunze-Busch , Evelyn M. Monninkhof , Robin De Roover , Sofie Isebaert , Linda G.W. Kerkmeijer","doi":"10.1016/j.radonc.2024.110568","DOIUrl":"10.1016/j.radonc.2024.110568","url":null,"abstract":"<div><h3>Background</h3><div>The addition of an integrated focal boost to the intraprostatic lesion is associated with improved biochemical disease-free survival (bDFS) in patients with intermediate- and high-risk prostate cancer (PCa) in conventionally fractionated radiotherapy. Furthermore, whole gland stereotactic body radiotherapy (SBRT) demonstrated to be non-inferior to conventional radiotherapy for low- and intermediate-risk PCa. To investigate the combination of ultra-hypofractionated prostate SBRT with iso-toxic focal boosting for intermediate- and high-risk PCa, we performed the hypo-FLAME trial.</div></div><div><h3>Methods</h3><div>Patients with intermediate- or high-risk PCa were enrolled in the phase II hypo-FLAME trial. All patients were treated with 35 Gy in 5 weekly fractions to the whole prostate gland with an iso-toxic integrated boost up to 50 Gy to the multiparametric MRI-defined tumor(s). If the dose constraints to the normal tissues would be exceeded, these were prioritised over the focal boost dose. The current analysis reports on the 5-year bDFS, late toxicity and health-related quality of life (HRQoL).</div></div><div><h3>Results</h3><div>Between 2016 and 2018, 100 men were treated with a median follow-up of 61 months. The estimated 5-year bDFS (95 % CI) was 93 % (86 % to 97 %). At 5 years, the prevalence of grade 2 + genitourinary and gastrointestinal toxicity was 12 % and 4 %, respectively.</div></div><div><h3>Conclusion</h3><div>Ultra-hypofractionated focal boost SBRT is associated with encouraging biochemical control rates up to 5-year follow-up in patients with intermediate- and high-risk PCa. Furthermore, prostate SBRT with iso-toxic focal boosting is associated with acceptable late genitourinary and gastrointestinal toxicity rates.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110568"},"PeriodicalIF":4.9,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcus A. Florez , Brian De , Roman Kowalchuk , Chad Tang , Andrew J. Bishop , Ramez Kouzy , Behrang Amini , Tina Briere , Thomas H. Beckham , Chenyang Wang , Jing Li , Claudio E. Tatsui , Laurence D. Rhines , Paul D. Brown , Kenneth Merrell , Amol J. Ghia
{"title":"Validation of the prognostic index for spine metastasis (PRISM) for stratifying survival in patients treated with spinal stereotactic body radiation","authors":"Marcus A. Florez , Brian De , Roman Kowalchuk , Chad Tang , Andrew J. Bishop , Ramez Kouzy , Behrang Amini , Tina Briere , Thomas H. Beckham , Chenyang Wang , Jing Li , Claudio E. Tatsui , Laurence D. Rhines , Paul D. Brown , Kenneth Merrell , Amol J. Ghia","doi":"10.1016/j.radonc.2024.110570","DOIUrl":"10.1016/j.radonc.2024.110570","url":null,"abstract":"<div><h3>Purpose</h3><div>The Prognostic Index for Spinal Metastasis (PRISM) is a scoring system derived from prospective data from a single institution that stratifies patients undergoing spine stereotactic radiosurgery (SSRS) for spinal metastases into subgroups by overall (OS). We sought to further demonstrate its generalizability by performing validation with a large dataset from a second high-volume institution, Mayo Clinic.</div></div><div><h3>Methods and materials</h3><div>Eight hundred seventy-nine patients—424 from Mayo Clinic and 455 from MD Anderson Cancer Center (MDACC)—who received SSRS between 2007 and 2019 were identified. Patients were stratified by PRISM criteria, and overall survival (OS) for the PRISM groups for each cohort was compared using Kaplan-Meier estimations and univariate Cox proportional analyses. Model calibration and concordance indices (C-indices) were calculated for each cohort to assess the quality of the scoring system.</div></div><div><h3>Results</h3><div>Patient and tumor characteristics varied significantly between both cohorts including histology, sex, performance status, and number of organs involved (all <em>P <</em> 0.001). Median OS was 30.3 and 22.1 months for the Mayo and MDACC cohorts, respectively. Kaplan-Meier survival curves revealed robust separation between prognostic groups within both cohorts. The Mayo cohort showed median OS of 57.1, 37.0, 23.7, and 8.8 months for Groups 1, 2, 3, and 4, respectively. Univariate analysis revealed hazard ratios of 3.0 (95 % confidence interval [CI], 1.9–4.9), 5.2 (95 % CI, 3.2–8.3), and 12.9 (95 % CI, 7.8–21.4) for groups 2, 3 and 4, respectively all <em>P</em> < 0.001). The C-indices were 0.69 and 0.66 for the unstratified and stratified scores for the Mayo cohort, and 0.70 and 0.68 for the MDACC cohort, respectively.</div></div><div><h3>Conclusion</h3><div>These data demonstrate robust validation of the PRISM score to stratify OS in patients treated with SSRS by a large external cohort, despite substantial differences among the cohorts. Overall, the PRISM scoring may help guide optimal treatment selection for patients with spine metastases.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110570"},"PeriodicalIF":4.9,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sang Kyun Yoo , Kyung Hwan Kim , Jae Myoung Noh , Jaewon Oh , Gowoon Yang , Jihun Kim , Nalee Kim , Hojin Kim , Hong In Yoon
{"title":"Development of learning-based predictive models for radiation-induced atrial fibrillation in non-small cell lung cancer patients by integrating patient-specific clinical, dosimetry, and diagnostic information","authors":"Sang Kyun Yoo , Kyung Hwan Kim , Jae Myoung Noh , Jaewon Oh , Gowoon Yang , Jihun Kim , Nalee Kim , Hojin Kim , Hong In Yoon","doi":"10.1016/j.radonc.2024.110566","DOIUrl":"10.1016/j.radonc.2024.110566","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Radiotherapy (RT) in non-small cell lung cancer (NSCLC) can induce cardiac adverse events, including atrial fibrillation (AF), despite advanced RT. This study integrates patient-specific information to develop learning-based models to predict the incidence of AF following NSCLC chemoradiotherapy (CRT) and evaluates these models using institutional and external datasets.</div></div><div><h3>Materials and methods</h3><div>Institutional and external patient cohorts consisted of 321 and 187 NSCLC datasets who received definitive CRT, including 17 and 6 AF incidences, respectively. The network input had 159 features with clinical, dosimetry, and diagnostic. The class imbalance was mitigated by synthetic minority oversampling technique. To handle various types of input features, machine learning-based model adopted an intervention technique that chose one feature with the largest weight at each dosimetry sub-group in feature selection process, while deep learning-based model employed a hybrid architecture assigning different types of networks to corresponding input paths. Performance was assessed by area under the curve (AUC). The key features were investigated for the machine and deep learning-based models.</div></div><div><h3>Results</h3><div>The hybrid deep learning model outperformed the machine learning-based algorithm in internal validation (AUC: 0.817 vs. 0.801) and produced more consistent performance in external validation (AUC: 0.806 vs. 0.776). Importantly, maximum dose to heart and sinoatrial node (SAN) were found to be the key features for both learning-based models in external and internal validations.</div></div><div><h3>Conclusions</h3><div>The learning-based predictive models showed consistent prediction performance across internal and external cohorts, identifying maximum heart and SAN dose as key features for the incidence of AF.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110566"},"PeriodicalIF":4.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142372732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kristian Kirkelund Bentsen, Carsten Brink, Tine Bjørn Nielsen, Rasmus Bank Lynggaard, Pernille Just Vinholt, Tine Schytte, Olfred Hansen, Stefan Starup Jeppesen
{"title":"Response to commentary on \"Cumulative rib fracture risk after stereotactic body radiotherapy in patients with localized non-small cell lung cancer\" by Tugcu et al.","authors":"Kristian Kirkelund Bentsen, Carsten Brink, Tine Bjørn Nielsen, Rasmus Bank Lynggaard, Pernille Just Vinholt, Tine Schytte, Olfred Hansen, Stefan Starup Jeppesen","doi":"10.1016/j.radonc.2024.110538","DOIUrl":"10.1016/j.radonc.2024.110538","url":null,"abstract":"","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":" ","pages":"110538"},"PeriodicalIF":4.9,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142366373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michelle Oud , Sebastiaan Breedveld , Marta Giżyńska , Yi Hsuan Chen , Steven Habraken , Zoltán Perkó , Ben Heijmen , Mischa Hoogeman
{"title":"Dosimetric advantages of adaptive IMPT vs. Enhanced workload and treatment time – A need for automation","authors":"Michelle Oud , Sebastiaan Breedveld , Marta Giżyńska , Yi Hsuan Chen , Steven Habraken , Zoltán Perkó , Ben Heijmen , Mischa Hoogeman","doi":"10.1016/j.radonc.2024.110548","DOIUrl":"10.1016/j.radonc.2024.110548","url":null,"abstract":"<div><h3>Introduction</h3><div>In head-and-neck IMPT, trigger-based offline plan adaptation (Offline<sub>trigger-based</sub>) is often used. Our goal was to compare this to four alternative adaptive strategies for dosimetry, workload and treatment time, considering also foreseen further technological advancements, including anticipated automation.</div></div><div><h3>Materials and methods</h3><div>Alternative strategies included weekly offline re-planning (Offline<sub>weekly</sub>), daily plan selection from a library (Library<sub>static</sub> and Library<sub>progsressive</sub>) and a fast, approximate daily online re-optimization approach (Online<sub>re-opt</sub>). Impact on CTV coverage and NTCPs was assessed by simulations based on repeat-CTs from 15 patients. Full daily re-planning was used as dosimetric benchmark. Increases in workload and treatment time were estimated.</div></div><div><h3>Results</h3><div>Both for coverage and NTCPs, fast Online<sub>re-opt</sub> performed as well as full re-planning. Compared to current practice, Online<strong><sub>re</sub></strong><sub>-opt</sub> showed enhanced probabilities for high coverage, and resulted in reductions in grade ≥ II NTCPs of 4.6 ± 1.7 %-point for xerostomia and 4.2 ± 2.3 %-point for dysphagia. Offline<sub>weekly</sub> and library strategies did not show coverage enhancements and resulted in smaller NTCP improvements. Further automation can largely limit workload and treatment time increases. With anticipated further automation, adaptation-related workload of Offline<sub>weekly</sub>, Library<sub>static</sub>, Library<sub>progressive</sub>, and Online<sub>re-opt</sub> was expected to increase by 3, 8, 21, and 66 h for 35 fraction treatment courses compared to Offline<sub>trigger-based</sub>. The corresponding adaptation-related prolonged treatment times were estimated to be 0, 4, 6, and 29 min/fraction.</div></div><div><h3>Conclusion</h3><div>Online adaptive strategies could approach dosimetric quality of full re-planning at the cost of additional workload and prolonged treatment time compared to the current offline adaptive strategy. Automation needs to play a key role in making more complex adaptive approaches feasible.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110548"},"PeriodicalIF":4.9,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ling He , Kruttika Bhat , Angeliki Ioannidis , Frank Pajonk
{"title":"Effects of dopamine receptor antagonists and radiation on mouse neural stem/progenitor cells","authors":"Ling He , Kruttika Bhat , Angeliki Ioannidis , Frank Pajonk","doi":"10.1016/j.radonc.2024.110562","DOIUrl":"10.1016/j.radonc.2024.110562","url":null,"abstract":"<div><h3>Background</h3><div>Dopamine receptor antagonists have recently been identified as potential anti-cancer agents in combination with radiation, and a first drug of this class is in clinical trials against pediatric glioma. Radiotherapy causes cognitive impairment primarily by eliminating neural stem/progenitor cells and subsequent loss of neurogenesis, along with inducing inflammation, vascular damage, and synaptic alterations. Here, we tested the combined effects of dopamine receptor antagonists and radiation on neural stem/progenitor cells.</div></div><div><h3>Methods</h3><div>Using transgenic mice that report the presence of neural stem/progenitor cells through Nestin promoter-driven expression of EGFP, the effects of dopamine receptor antagonists alone or in combination with radiation on neural stem/progenitor cells were assessed in sphere-formation assays, extreme limiting dilution assays, flow cytometry and real-time PCR <em>in vitro</em> and <em>in vivo</em> in both sexes.</div></div><div><h3>Results</h3><div>We report that hydroxyzine and trifluoperazine exhibited sex-dependent effects on murine newborn neural stem/progenitor cells <em>in vitro</em>. In contrast, amisulpride, nemonapride, and quetiapine, when combined with radiation, significantly increased the number of neural stem/progenitor cells in both sexes. <em>In vivo</em>, trifluoperazine showed sex-dependent effects on adult neural stem/progenitor cells, while amisulpride demonstrated significant effects in both sexes. Further, amisulpride increased sphere forming capacity and stem cell frequency in both sexes when compared to controls.</div></div><div><h3>Conclusion</h3><div>We conclude that a therapeutic window for dopamine receptor antagonists in combination with radiation potentially exists, making it a novel combination therapy against glioblastoma. Normal tissue toxicity following this treatment scheme likely differs depending on age and sex and should be taken into consideration when designing clinical trials.</div></div>","PeriodicalId":21041,"journal":{"name":"Radiotherapy and Oncology","volume":"201 ","pages":"Article 110562"},"PeriodicalIF":4.9,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}