Strahlentherapie und Onkologie最新文献

{"title":"[Olaparib for high-risk biochemically recurrent prostate cancer following prostatectomy].","authors":"Katharina Hintelmann, Lukas Böckelmann","doi":"10.1007/s00066-024-02350-3","DOIUrl":"10.1007/s00066-024-02350-3","url":null,"abstract":"","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":"343-345"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142847800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MR-linac: role of artificial intelligence and automation.","authors":"Serena Psoroulas, Alina Paunoiu, Stefanie Corradini, Juliane Hörner-Rieber, Stephanie Tanadini-Lang","doi":"10.1007/s00066-024-02358-9","DOIUrl":"10.1007/s00066-024-02358-9","url":null,"abstract":"<p><p>The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5 years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanced consistency, accuracy, and efficiency in clinical practice. Magnetic resonance (MR)-guided linear accelerators (MR-linacs) have greatly improved treatment accuracy and real-time plan adaptation, particularly for tumors near radiosensitive organs. Despite these improvements, MR-guided radiotherapy (MRgRT) remains labor intensive and time consuming, highlighting the need for AI to streamline workflows and support rapid decision-making. Synthetic CTs from MR images and automated contouring and treatment planning will reduce manual processes, thus optimizing treatment times and expanding access to MR-linac technology. AI-driven quality assurance will ensure patient safety by predicting machine errors and validating treatment delivery. Advances in intrafractional motion management will increase the accuracy of treatment, and the integration of imaging biomarkers for outcome prediction and early toxicity assessment will enable more precise and effective treatment strategies.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":"298-305"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143024786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Can stereotactic radiotherapy for neovascular age-related macular degeneration (STAR trial) enhance quality of life?]","authors":"Stephanie Göller, Heinz Schmidberger","doi":"10.1007/s00066-024-02351-2","DOIUrl":"10.1007/s00066-024-02351-2","url":null,"abstract":"","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":"346-348"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.","authors":"Christian Trapp, Nina Schmidt-Hegemann, Michael Keilholz, Sarah Frederike Brose, Sebastian N Marschner, Stephan Schönecker, Sebastian H Maier, Diana-Coralia Dehelean, Maya Rottler, Dinah Konnerth, Claus Belka, Stefanie Corradini, Paul Rogowski","doi":"10.1007/s00066-024-02342-3","DOIUrl":"10.1007/s00066-024-02342-3","url":null,"abstract":"<p><strong>Background: </strong>This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and patients.</p><p><strong>Methods: </strong>Six questions about definitive radiotherapy for prostate cancer were designed based on common patient inquiries. These questions were presented to different LLMs [ChatGPT‑4, ChatGPT-4o (both OpenAI Inc., San Francisco, CA, USA), Gemini (Google LLC, Mountain View, CA, USA), Copilot (Microsoft Corp., Redmond, WA, USA), and Claude (Anthropic PBC, San Francisco, CA, USA)] via the respective web interfaces. Responses were evaluated for readability using the Flesch Reading Ease Index. Five radiation oncologists assessed the responses for relevance, correctness, and completeness using a five-point Likert scale. Additionally, 35 prostate cancer patients evaluated the responses from ChatGPT‑4 for comprehensibility, accuracy, relevance, trustworthiness, and overall informativeness.</p><p><strong>Results: </strong>The Flesch Reading Ease Index indicated that the responses from all LLMs were relatively difficult to understand. All LLMs provided answers that clinicians found to be generally relevant and correct. The answers from ChatGPT‑4, ChatGPT-4o, and Claude AI were also found to be complete. However, we found significant differences between the performance of different LLMs regarding relevance and completeness. Some answers lacked detail or contained inaccuracies. Patients perceived the information as easy to understand and relevant, with most expressing confidence in the information and a willingness to use ChatGPT‑4 for future medical questions. ChatGPT-4's responses helped patients feel better informed, despite the initially standardized information provided.</p><p><strong>Conclusion: </strong>Overall, LLMs show promise as a tool for patient education in prostate cancer radiotherapy. While improvements are needed in terms of accuracy and readability, positive feedback from clinicians and patients suggests that LLMs can enhance patient understanding and engagement. Further research is essential to fully realize the potential of artificial intelligence in patient education.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":"333-342"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839798/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142955461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives.","authors":"Ayhan Can Erdur, Daniel Rusche, Daniel Scholz, Johannes Kiechle, Stefan Fischer, Óscar Llorián-Salvador, Josef A Buchner, Mai Q Nguyen, Lucas Etzel, Jonas Weidner, Marie-Christin Metz, Benedikt Wiestler, Julia Schnabel, Daniel Rueckert, Stephanie E Combs, Jan C Peeken","doi":"10.1007/s00066-024-02262-2","DOIUrl":"10.1007/s00066-024-02262-2","url":null,"abstract":"<p><p>The rapid development of artificial intelligence (AI) has gained importance, with many tools already entering our daily lives. The medical field of radiation oncology is also subject to this development, with AI entering all steps of the patient journey. In this review article, we summarize contemporary AI techniques and explore the clinical applications of AI-based automated segmentation models in radiotherapy planning, focusing on delineation of organs at risk (OARs), the gross tumor volume (GTV), and the clinical target volume (CTV). Emphasizing the need for precise and individualized plans, we review various commercial and freeware segmentation tools and also state-of-the-art approaches. Through our own findings and based on the literature, we demonstrate improved efficiency and consistency as well as time savings in different clinical scenarios. Despite challenges in clinical implementation such as domain shifts, the potential benefits for personalized treatment planning are substantial. The integration of mathematical tumor growth models and AI-based tumor detection further enhances the possibilities for refining target volumes. As advancements continue, the prospect of one-stop-shop segmentation and radiotherapy planning represents an exciting frontier in radiotherapy, potentially enabling fast treatment with enhanced precision and individualization.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":"236-254"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839850/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Segment Anything foundation model achieves favorable brain tumor auto-segmentation accuracy in MRI to support radiotherapy treatment planning.","authors":"Florian Putz, Sogand Beirami, Manuel Alexander Schmidt, Matthias Stefan May, Johanna Grigo, Thomas Weissmann, Philipp Schubert, Daniel Höfler, Ahmed Gomaa, Ben Tkhayat Hassen, Sebastian Lettmaier, Benjamin Frey, Udo S Gaipl, Luitpold V Distel, Sabine Semrau, Christoph Bert, Rainer Fietkau, Yixing Huang","doi":"10.1007/s00066-024-02313-8","DOIUrl":"10.1007/s00066-024-02313-8","url":null,"abstract":"<p><strong>Background: </strong>Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in RT treatment planning.</p><p><strong>Methods: </strong>Segment Anything was evaluated in an interactive point-to-mask auto-segmentation task for glioma brain tumor auto-contouring in 16,744 transverse slices from 369 MRI datasets (BraTS 2020 dataset). Up to nine interactive point prompts were automatically placed per slice. Tumor boundaries were auto-segmented on contrast-enhanced T1w sequences. Out of the three auto-contours predicted by SA, accuracy was evaluated for the contour with the highest calculated IoU (Intersection over Union, \"oracle mask,\" simulating interactive model use with selection of the best tumor contour) and for the tumor contour with the highest model confidence (\"suggested mask\").</p><p><strong>Results: </strong>Mean best IoU (mbIoU) using the best predicted tumor contour (oracle mask) in full MRI slices was 0.762 (IQR 0.713-0.917). The best 2D mask was achieved after a mean of 6.6 interactive point prompts (IQR 5-9). Segmentation accuracy was significantly better for high- compared to low-grade glioma cases (mbIoU 0.789 vs. 0.668). Accuracy was worse using the suggested mask (0.572). Stacking best tumor segmentations from transverse MRI slices, mean 3D Dice score for tumor auto-contouring was 0.872, which was improved to 0.919 by combining axial, sagittal, and coronal contours.</p><p><strong>Conclusion: </strong>The Segment Anything foundation segmentation model can achieve high accuracy for glioma brain tumor segmentation in MRI datasets. The results suggest that foundation segmentation models could facilitate RT treatment planning when properly integrated in a clinical application.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":"255-265"},"PeriodicalIF":2.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11839838/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing treatment for Gleason 10 prostate cancer: radiation dose escalation and ⁶⁸Ga-PSMA-PET/CT staging.","authors":"Cem Onal, Ozan Cem Guler, Birhan Demirhan, Petek Erpolat, Aysenur Elmali, Melek Yavuz","doi":"10.1007/s00066-025-02376-1","DOIUrl":"https://doi.org/10.1007/s00066-025-02376-1","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to investigate the effects of dose escalation through focal boost (FB) to intraprostatic lesions (IPLs) as well as the role of gallium-68 prostate-specific membrane antigen positron-emission tomography (⁶⁸Ga-PSMA-PET/CT) for staging and treatment planning in patients with Gleason score (GS) 10 prostate cancer (PCa) receiving definitive radiotherapy (RT) and androgen deprivation therapy (ADT).</p><p><strong>Materials and methods: </strong>We retrospectively analyzed data of 92 patients with GS 10 PCa who underwent definitive RT and ADT from March 2010 to October 2022. Freedom from biochemical failure (FFBF), prostate cancer-specific survival (PCSS), distant metastasis-free survival (DMFS), and overall survival (OS) rates were calculated using the Kaplan-Meier method. Survival outcomes were compared between patients staged with ⁶⁸Ga-PSMA-PET/CT and those staged with conventional imaging modalities as well as between those who received a simultaneous integrated boost (SIB) and those who did not.</p><p><strong>Results: </strong>At a median follow-up time of 73 months, the 5‑year FFBF, PCSS, DMFS, and OS rates were 59.2%, 77.0%, 62.9%, and 67.6%, respectively. Disease progression was observed in 39 patients (42.4%), with most cases manifesting as distant metastasis (DM). A total of 56 patients (60.9%) were staged using ⁶⁸Ga-PSMA-PET/CT, while 43 patients (46.7%) received FB to IPLs. Patients staged with ⁶⁸Ga-PSMA-PET/CT had better FFBF and PCSS compared to those staged with conventional imaging. Patients undergoing an SIB had improved PCSS and DMFS. In the multivariable analysis, an ADT duration of 18 months or more was associated with improved FFBF, PCSS, DMFS, and OS. Application of an SIB was an additional independent predictor for improved FFBF, while staging with ⁶⁸Ga-PSMA-PET/CT was associated with better PCSS.</p><p><strong>Conclusion: </strong>We found that long-term ADT, increasing the radiation dose to primary tumor, and staging with ⁶⁸Ga-PSMA-PET/CT improved clinical outcomes. Additional research is needed for validation.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143531797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advantages of 3D printed patient-individual moulds in brachytherapy for facial skin cancer.","authors":"Jörg Licher, Julia Achenbach, Janett Köhn, Markus Diefenhardt, Maximilian Fleischmann, Claus Rödel, Nikolaos Tselis, Ulla Ramm, Christian Scherf","doi":"10.1007/s00066-025-02372-5","DOIUrl":"https://doi.org/10.1007/s00066-025-02372-5","url":null,"abstract":"<p><strong>Purpose: </strong>Facial skin cancer of 42 elderly frail patients was treated with individualised 3D-printed mould applicators for high-dose-rate (HDR) brachytherapy. The dosimetric outcome was compared to conventionally manufactured individual moulds used before.</p><p><strong>Methods: </strong>Tumour-adapted HDR brachytherapy source paths were pre-planned and dosimetrically optimised in the brachytherapy treatment planning system (TPS) using computed tomography (CT) data and considered in the design of the patient-individual moulds. Dosimetric outcome for the planning target volumes and organs at risk were statistically evaluated and compared for pre-planning, final clinical treatment planning with TG-43 formalism and retrospective tissue, material and CT density related TG-186 calculations.</p><p><strong>Results: </strong>Pre-planning allows reliable brachytherapy source paths design to achieve intended dosimetric clinical goals. The 3D-printed patient-specific moulds show a clear advantage in the dosimetric coverage of the target volume (improving D₉₀ from 98.3% to 104.3%) and the protection of the relevant organs at risk (reduction up to 30% of maximum Dose). With the 3D-printed moulds only minor deviations were observed for TG-43 and TG-186 dose recalculations of the treated plans.</p><p><strong>Conclusion: </strong>Customised 3D printed moulds offer a safe and efficient technique to treat facial skin cancer in critical locations and complex clinical situations with HDR brachytherapy. The two-step planning process results in reliable PTV dose coverage and efficient sparing of eye lenses and eyeballs. Dosimetric outcome and interfractional position reproducibility with 3D printed moulds were superior to conventionally manufactured facial moulds with respect to the clinical goals.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143504294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FBXL18 increases cell proliferation and reduces cell radiosensitivity in esophageal squamous cell carcinoma.","authors":"Yahui Kang, Ning Ge, Xiaolong Yuan, Bihong Zhan, Hongbo Zhang","doi":"10.1007/s00066-025-02373-4","DOIUrl":"https://doi.org/10.1007/s00066-025-02373-4","url":null,"abstract":"<p><strong>Background: </strong>Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant tumors worldwide. In this study, we aimed to investigate the pathophysiological mechanism through which F‑box and leucine-rich repeat protein 18 (FBXL18) promotes the progression of ESCC.</p><p><strong>Methods: </strong>ESCC cell lines KYSE150 and TE‑1 were infected with PLVX-FBXL18 or shFBXL18-derived lentivirus to overexpress or knock down FBXL18. A Cell-Counting Kit 8 and colony-forming assay were used to assess cell viability and proliferation. Cells were irradiated with varying doses of X‑ray (IR) to determine whether FBXL18 influenced the radiosensitivity of ESCC cells. KYSE450 cells, stably transduced with shNC or shFBXL18-derived lentivirus, were injected into nude mice to assess whether FBXL18 affected ESCC tumor growth. KYSE150 and TE-1 cells overexpressing FBXL18 were lysed for Western blot analysis to evaluate protein expression.</p><p><strong>Results: </strong>FBXL18 overexpression enhanced cell viability and colony formation, and proliferation of ESCC cells. In contrast, FBXL18 knockdown inhibited tumor growth in vivo. Additionally, FBXL18 overexpression reduced the radiosensitivity of ESCC cells. Mechanistically, FBXL18 was found to exert its effects by suppressing the expression of FBXL7 in ESCC cells.</p><p><strong>Conclusion: </strong>FBXL18 promotes cell proliferation and diminishes radiosensitivity in ESCC cells. Most likely, it exerts its pro-tumorigenic effects by downregulating FBXL7.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143459646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radio(chemo)therapy in anal cancer: evaluation of sex-specific disparities across AJCC stages.","authors":"F Fuchs, P Rogowski, M Rottler, M A Shouman, K Heinrich, F Kühn, C Belka, K Unger, F Walter","doi":"10.1007/s00066-025-02368-1","DOIUrl":"https://doi.org/10.1007/s00066-025-02368-1","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to investigate sex differences in anal squamous cell carcinomas (ASCC), with a particular focus on the prognostic significance of the American Joint Committee on Cancer (AJCC) 9th edition staging system for oncological outcome.</p><p><strong>Methods: </strong>A retrospective analysis was conducted in 188 patients with histologically confirmed ASCC who underwent definitive (chemo)radiotherapy between 2004 and 2020. Patient- and tumor-related data were collected. Tumor stage groups were classified according to the AJCC 9th edition. Overall survival (OS), disease-free survival (DFS), freedom from recurrence (FFR), and colostomy-free survival (CFS) were analyzed using the Kaplan-Meier method for univariate testing and Cox regression models for multivariate analysis. Differences between sexes were assessed.</p><p><strong>Results: </strong>The cohort included 134 females and 54 males, with a median follow-up of 83 months. Females exhibited significantly better OS (p = 0.01), DFS (p = 0.01), and CFS (p = 0.03). For male patients, there was a clear trend towards better OS (p = 0.08), DFS (p = 0.10), and FFR (p = 0.09) in earlier tumors as well as significantly better CFS (p = 0.04). In contrast, in the female subgroup, there were no significant differences in OS (p = 0.64), DFS (p = 0.52), and CFS (p = 0.25) with respect to tumor stage. In multivariate analysis, male sex, older age, and advanced tumor stages were significant risk factors for poorer OS, DFS, and CFS.</p><p><strong>Conclusion: </strong>This study highlights significant sex differences in ASCC prognoses, with females showing better survival outcomes. The prognostic value of the AJCC 9th edition staging system differs between sexes; thus, we support the inclusion of sex as a prognostic factor in staging systems.</p>","PeriodicalId":21998,"journal":{"name":"Strahlentherapie und Onkologie","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143365985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}