Physics and Imaging in Radiation Oncology最新文献

{"title":"Adaptive radiotherapy in locally advanced head and neck cancer: The importance of reduced margins","authors":"Hedda Enocson ,&nbsp;André Haraldsson ,&nbsp;Per Engström ,&nbsp;Sofie Ceberg ,&nbsp;Maria Gebre-Medhin ,&nbsp;Gabriel Adrian ,&nbsp;Per Munck af Rosenschöld","doi":"10.1016/j.phro.2025.100696","DOIUrl":"10.1016/j.phro.2025.100696","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Adaptive radiotherapy (ART) involves treatment re-planning based on anatomical changes, which may improve target coverage and sparing of organs-at-risk (OARs). This study retrospectively assessed the technical feasibility and potential benefits of daily ART in combination with reduced planning target volume (PTV) margins for head and neck squamous cell carcinoma (HNSCC).</div></div><div><h3>Materials and Methods</h3><div>Thirty-one patients, encompassing 902 treatment fractions, treated with radiotherapy to 60.0–68.0 Gy in 2 Gy/fraction were studied. Synthetic CTs (sCT) from daily kVCT images were created and contours propagated using deformable image registration (DIR). Target contours were reviewed and corrected. On the sCT, non-adapted delivered doses and ART-plans with 5 mm (clinical standard) and 2 mm PTV-margin were evaluated. All daily dose distributions were then accumulated.</div></div><div><h3>Results</h3><div>Target contours required correction in 48 % of the fractions. Daily non-adapted D_98%,CTV was &gt; 95 % in 890 (5 mm) and 825 (2 mm) out of 902 fractions. All adapted plans achieved D_98%,CTV &gt; 95 %. Significant reductions in mean doses to OARs were observed for PTV = 2 mm ART-plans: 4.1 Gy for parotid, 2.6 Gy for submandibular, 3.3 Gy for oral cavity, 4.0 Gy for esophagus, and 3.8 Gy for larynx.</div></div><div><h3>Conclusion</h3><div>ART-planning on sCT and DIR propagated contours was feasible and promising for further clinical testing. To obtain a potential clinical benefit of ART, a synchronous reduction of the PTV-margin was warranted. Daily ART can be used to maintain adequate target dosimetry for every fraction, though for the accumulated treatment, insufficient target coverage without ART is unlikely to occur.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100696"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11787698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143081205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination of patient-specific trajectory for biaxially rotational dynamic-radiation therapy using a new O-ring-shaped image guided radiotherapy system","authors":"Hideaki Hirashima ,&nbsp;Hiroki Adachi ,&nbsp;Tomohiro Ono ,&nbsp;Mitsuhiro Nakamura ,&nbsp;Yuka Ono ,&nbsp;Takahiro Iwai ,&nbsp;Michio Yoshimura ,&nbsp;Takashi Mizowaki","doi":"10.1016/j.phro.2025.100698","DOIUrl":"10.1016/j.phro.2025.100698","url":null,"abstract":"<div><h3>Background and purpose</h3><div>This study developed a trajectory search method for biaxially rotational dynamic-radiation therapy (BROAD-RT) using a new O-ring-shaped linac, aimed at identifying a patient-specific trajectory in a commercial treatment planning system. Subsequently, its efficacy in the treatment of pancreatic cancer was assessed.</div></div><div><h3>Materials and methods</h3><div>BROAD-RT is a beam delivery technique in which the gantry and O-ring are simultaneously rotated around two axes. A beam’s eye view-based structure map was generated, and the Dijkstra algorithm was then applied to explore the BROAD-RT for minimizing radiation doses to critical organs in RayStation. This procedure was evaluated in 10 patients with pancreatic cancer. For each patient, two different plans were created: volumetric modulated arc therapy (VMAT) plan with coplanar and BROAD-RT trajectory. The effects of different trajectories on the plan and dosimetric indices were assessed for each delivery technique.</div></div><div><h3>Results</h3><div>The mean modulation complexity score for VMAT (MCS_v) and aperture area (AA) (×10³ cm²) were 0.3 ± 0.0 and 24.8 ± 3.9 for the coplanar trajectory and 0.4 ± 0.1 and 35.2 ± 7.1 for the BROAD-RT trajectory, respectively, with both MCS_v (p = 5 × <span><math><msup><mrow><mn>10</mn></mrow><mrow><mo>-</mo><mn>5</mn></mrow></msup></math></span>) and AA (p = 0.0002) values significantly higher for the BROAD-RT trajectory. Dose difference between the coplanar and BROAD-RT trajectories reduced the dose to the stomach and duodenum.</div></div><div><h3>Conclusions</h3><div>Our study conducted an automated search for patient-specific BROAD-RT trajectory using a new O-ring-shaped linac and implemented these trajectories in RayStation. Dose distributions were reduced in the intermediate-dose regions with BROAD-RT trajectory.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100698"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrocardiogram-gated cardiac computed tomography-based patient- and segment-specific cardiac motion estimation method in stereotactic arrhythmia radioablation for ventricular tachycardia","authors":"Jingyang Xie ,&nbsp;Alicia S. Bicu ,&nbsp;Melanie Grehn ,&nbsp;Mustafa Kuru ,&nbsp;Adrian Zaman ,&nbsp;Xinyu Lu ,&nbsp;Christian Janorschke ,&nbsp;Luuk H.G. van der Pol ,&nbsp;Martin F. Fast ,&nbsp;Jens Fleckenstein ,&nbsp;Marcus Both ,&nbsp;Stephan Hohmann ,&nbsp;Egor Borzov ,&nbsp;Peter Winkler ,&nbsp;Roland R. Tilz ,&nbsp;Dirk Rades ,&nbsp;Frank A. Giordano ,&nbsp;Daniel Buergy ,&nbsp;Boris Rudic ,&nbsp;David Duncker ,&nbsp;Lena Kaestner","doi":"10.1016/j.phro.2025.100700","DOIUrl":"10.1016/j.phro.2025.100700","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Motion management strategies such as gating under breath-hold can reduce breathing-induced motion during stereotactic arrhythmia radioablation (STAR) for refractory ventricular tachycardia. However, heartbeat-induced motion is essential to define an appropriate cardiac internal target volume (ITV) margin. In this study, we introduce a patient- and segment-specific cardiac motion estimation method and cardiac motion data of the clinical target volume (CTV), ICD lead tips and left ventricle (LV) segments.</div></div><div><h3>Materials and methods</h3><div>Data from 10 STAR-treated patients were retrospectively analyzed. The LV was semi-automatically segmented according to the 17-segment model. Electrocardiogram-gated contrast-enhanced breath-hold cardiac CTs were automatically non-rigidly registered for motion estimation. The correlation and significant differences between ICD tip motion and CTV motion were assessed using the Pearson correlation coefficient (PCC) and Wilcoxon signed-rank test, while spatial discrepancies with both CTV and segment motion were quantified using the Euclidean distance.</div></div><div><h3>Results</h3><div>The CTVs (center of mass) moved 3.4 ± 1.4 mm and the ICD lead tips moved 4.9 ± 2.2 mm. The maximum motion per patient was observed in basal and mid-cavity LV segments in 3D. The PCC showed a strong positive motion correlation between the ICD tip and CTV in 3D (0.84), while the p-values indicated statistically significant differences in the right-left, anterior-posterior and 3D directions.</div></div><div><h3>Conclusion</h3><div>The proposed methods enable patient- and segment-specific cardiac ITV margin estimation. The motion in most LV segments was limited, however, cardiac ITV margins may need adjustment in individual cases. The impact of cardiac motion on the dosimetry needs further investigation.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100700"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simplified online adaptive workflow for long-course magnetic resonance-guided radiotherapy in esophageal cancer","authors":"Koen M. Kuijer,&nbsp;Roel Bouwmans,&nbsp;Lando S. Bosma,&nbsp;Stella Mook ,&nbsp;Gert J. Meijer","doi":"10.1016/j.phro.2025.100717","DOIUrl":"10.1016/j.phro.2025.100717","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Online adaptive magnetic resonance-guided radiotherapy (MRgRT) enables high-precision radiotherapy for esophageal cancer patients but is less feasible due to long on-table times in combination with long-course treatment. In this study, we conducted an in-silico assessment of a simplified online adaptive workflow, Adapt-To-Shape-lite (ATS-lite), in which deformable propagated contours are not modified, and assessed its feasibility.</div></div><div><h3>Materials and Methods</h3><div>The ATS-lite workflow was simulated for all fractions of nine esophageal cancer patients who had previously received full online adaptive MRgRT with manual contour corrections if needed. The deformable propagated contours were not adjusted. A dose of 41.4 Gy in 23 fractions was prescribed. Intra- and interfraction dose accumulation were performed to evaluate target coverage per fraction and across the entire treatment. For individual fractions, coverage of the manually corrected clinical target volume (CTV) was considered adequate if V95% &gt; 98 % and V90% &gt; 99.5 %. Feasibility was assessed by recording treatment times in the first patients treated with ATS-lite.</div></div><div><h3>Results</h3><div>The ATS-lite workflow provided adequate target coverage over the entire treatment for all patients, with sufficient coverage in 90% of the 177 fractions analyzed. Closer inspection revealed that inadequate target coverage in individual fractions was primarily attributed to enlargement of the manually corrected CTV, rather than poor contour propagation in the ATS-lite workflow. In seven patients, the ATS-lite workflow achieved a median time per fraction of 23 min.</div></div><div><h3>Conclusions</h3><div>The ATS-lite workflow provides adequate target coverage and is feasible for online adaptive MRgRT in long-course esophageal cancer treatments.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100717"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Added value of non-rigid image registration for intrafraction dose accumulation in magnetic resonance imaging-guided prostate radiotherapy","authors":"Georgios Tsekas,&nbsp;Cornel Zachiu,&nbsp;Gijsbert H. Bol,&nbsp;Johannes C.J. de Boer,&nbsp;Bas W. Raaymakers","doi":"10.1016/j.phro.2025.100711","DOIUrl":"10.1016/j.phro.2025.100711","url":null,"abstract":"<div><div>This work investigates potential advantages of non-rigid versus rigid image registration for intrafraction dose reconstruction in hypofractionated prostate radiotherapy. The data of 15 patients were analyzed using 3D cine magnetic resonance imaging (MRI) in combination with machine log files and the accumulated dose distributions were compared to the planned ones. Both image registration methods resulted in comparable results for the majority ( <span><math><mo>∼</mo></math></span> 95%) of patient fractions. However, better image alignment was reported for the non-rigid method compared to rigid in cases of transient gas pockets, indicating better image registration quality in the presence of large intrafraction deformations.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100711"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dose-volume parameter evaluation of a sub-fractionation workflow for adaptive radiotherapy of prostate cancer patients on a 1.5 T magnetic resonance imaging radiotherapy system","authors":"Georgios Tsekas,&nbsp;Cornel Zachiu,&nbsp;Gijsbert H. Bol,&nbsp;Jochem R.N. van der Voort van Zyp,&nbsp;Sandrine M.G. van de Pol,&nbsp;Johannes C.J. de Boer,&nbsp;Bas W. Raaymakers","doi":"10.1016/j.phro.2025.100706","DOIUrl":"10.1016/j.phro.2025.100706","url":null,"abstract":"<div><h3>Background and purpose:</h3><div>This study focuses on evaluating a sub-fractionation workflow for intrafraction motion mitigation of prostate cancer patients on a 1.5 T magnetic resonance imaging radiotherapy system.</div></div><div><h3>Materials and methods:</h3><div>The investigated workflow consisted of two sub-fractions where intrafraction drift correction steps were applied based on a daily reference plan. However, the daily contours were only rigidly shifted to match the intrafraction anatomies and therefore the clinical dosimetric constraints might be violated. In this work, daily contours were deformed to match the intrafraction anatomies and the online plans were re-calculated for a total of 15 patients. The deformed prostate contours were inspected by radiation oncologists and corrections were performed when necessary. Finally, a dose-volume parameter evaluation was performed on a sub-fraction level using the clinical plan parameters.</div></div><div><h3>Results:</h3><div>Clinically acceptable coverage was reported for the target structures resulting in mean V_95% of 99.7 % and 97.8 % for the clinical target volume (CTV) and planning target volume (PTV) respectively. Sub-fractions with insufficient CTV dose can be explained by the presence of intrafraction rotations and deformations that were not taken into account during intrafraction corrections. Additionally, for no sub-fraction the dose to the organs-at-risk exceeded the clinical constraints.</div></div><div><h3>Conclusion:</h3><div>Given our results on the CTV coverage we can conclude that the sub-fractionation workflow met the dosimetric constraints for the hypofractionated treatment of the analyzed group of prostate cancer patients. A future dose accumulation study can provide further insights into the suitability of the clinical margins.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100706"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demonstration of motion-compensated volumetric modulated arc radiotherapy on an MR-linac","authors":"Pim T.S. Borman ,&nbsp;Prescilla Uijtewaal ,&nbsp;Jeffrey Snyder ,&nbsp;Bryan Allen ,&nbsp;Caiden K. Atienza ,&nbsp;Peter Woodhead ,&nbsp;Daniel E. Hyer ,&nbsp;Bas W. Raaymakers ,&nbsp;Martin F. Fast","doi":"10.1016/j.phro.2025.100729","DOIUrl":"10.1016/j.phro.2025.100729","url":null,"abstract":"<div><div>Intensity-modulated radiotherapy (IMRT) in combination with magnetic resonance imaging (MRI)-guided gated delivery represents the latest development in the treatment of abdominothoracic tumours on MR-linac. In contrast, volumetric-modulated arc therapy (VMAT) is typically used on conventional linacs due to its superior delivery efficiency and speed. Non-inferior VMAT plans were created in a research treatment planning system for eight lung cancer patients previously treated on an MR-linac. VMAT plans were delivered on a moving dosimeter using respiratory multi-leaf collimator (MLC) tracking. VMAT with MLC tracking achieved an average 2%/2 mm local gamma pass rate of 93% relative to planned dose with a delivery efficiency of 83%.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100729"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning combining imaging, dose and clinical data for predicting bowel toxicity after pelvic radiotherapy","authors":"Behnaz Elhaminia ,&nbsp;Alexandra Gilbert ,&nbsp;Andrew Scarsbrook ,&nbsp;John Lilley ,&nbsp;Ane Appelt ,&nbsp;Ali Gooya","doi":"10.1016/j.phro.2025.100710","DOIUrl":"10.1016/j.phro.2025.100710","url":null,"abstract":"<div><h3>Background and Purpose:</h3><div>A comprehensive understanding of radiotherapy toxicity requires analysis of multimodal data. However, it is challenging to develop a model that can analyse both 3D imaging and clinical data simultaneously. In this study, a deep learning model is proposed for simultaneously analysing computed tomography scans, dose distributions, and clinical metadata to predict toxicity, and identify the impact of clinical risk factors and anatomical regions.</div></div><div><h3>Materials and methods</h3><div>: A deep model based on multiple instance learning with feature-level fusion and attention was developed. The study used a dataset of 313 patients treated with 3D conformal radiation therapy and volumetric modulated arc therapy, with heterogeneous cohorts varying in dose, volume, fractionation, concomitant therapies, and follow-up periods. The dataset included 3D computed tomography scans, planned dose distributions to the bowel cavity, and patient clinical data. The model was trained on patient-reported data on late bowel toxicity.</div></div><div><h3>Results:</h3><div>Results showed that the network can identify potential risk factors and critical anatomical regions. Analysis of clinical data jointly with imaging and dose for bowel urgency and faecal incontinence improved performance (area under receiver operating characteristic curve [AUC] of 88% and 78%, respectively) while best performance for diarrhoea was when analysing clinical features alone (68% AUC).</div></div><div><h3>Conclusions:</h3><div>Results demonstrated that feature-level fusion along with attention enables the network to analyse multimodal data. This method also provides explanations for each input’s contribution to the final result and detects spatial associations of toxicity.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100710"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model","authors":"Yafei Dong ,&nbsp;Thibault Marin ,&nbsp;Yue Zhuo ,&nbsp;Elie Najem ,&nbsp;Maryam Moteabbed ,&nbsp;Fangxu Xing ,&nbsp;Arnaud Beddok ,&nbsp;Rita Maria Lahoud ,&nbsp;Laura Rozenblum ,&nbsp;Zhiyuan Ding ,&nbsp;Xiaofeng Liu ,&nbsp;Kira Grogg ,&nbsp;Jonghye Woo ,&nbsp;Yen-Lin E. Chen ,&nbsp;Ruth Lim ,&nbsp;Chao Ma ,&nbsp;Georges El Fakhri","doi":"10.1016/j.phro.2025.100734","DOIUrl":"10.1016/j.phro.2025.100734","url":null,"abstract":"<div><h3>Background and purpose:</h3><div>Accurate delineation of the gross tumor volume (GTV) is essential for radiotherapy of soft tissue sarcomas. However, manual GTV delineation from multi-modality images is time-consuming. Furthermore, GTV delineation is subject to inter- and intra-reader variability, which reduces the reproducibility of treatment planning. To address these issues, this work aims to develop a highly accurate automatic delineation technique modeling reader variability for soft tissue sarcomas using deep learning.</div></div><div><h3>Materials and methods:</h3><div>We employed a publicly available soft tissue sarcoma dataset consisting of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET), X-ray Computed Tomography (CT), and pre-contrast T1-weighted Magnetic Resonance Imaging (MRI) scans for 51 patients, of which 49 were selected for analysis. The GTVs were delineated by six experienced readers, each reader performing GTV contouring multiple times for every patient. The confidence maps were calculated by averaging the labels provided by all readers, resulting in values ranging from 0 to 1. We developed and trained a diffusion model-based neural network to predict confidence maps of GTV for soft tissue sarcomas from multi-modality medical images.</div></div><div><h3>Results:</h3><div>Quantitative analysis showed that the proposed diffusion model performed competitively with U-Net-based models, frequently ranking first or second across five evaluation metrics: Dice Index, Hausdorff Distance, Recall, Precision, and Brier Score. Additionally, experiments evaluating the impact of different imaging modalities demonstrated that incorporating multi-modality image inputs provided improved performance compared to single-modality and dual-modality inputs.</div></div><div><h3>Conclusion:</h3><div>The proposed diffusion model is capable of predicting accurate confidence maps of GTV for soft tissue sarcomas from multi-modality inputs.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100734"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143547973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Normal tissue complication probability model for severe radiation-induced lymphopenia in patients with pancreatic cancer treated with concurrent chemoradiotherapy","authors":"Fuki Koizumi ,&nbsp;Norio Katoh ,&nbsp;Takahiro Kanehira ,&nbsp;Yasuyuki Kawamoto ,&nbsp;Toru Nakamura ,&nbsp;Tatsuhiko Kakisaka ,&nbsp;Miyako Myojin ,&nbsp;Noriaki Nishiyama ,&nbsp;Akio Yonesaka ,&nbsp;Manami Otsuka ,&nbsp;Rikiya Takashina ,&nbsp;Hideki Minatogawa ,&nbsp;Hajime Higaki ,&nbsp;Yusuke Uchinami ,&nbsp;Hiroshi Taguchi ,&nbsp;Kentaro Nishioka ,&nbsp;Koichi Yasuda ,&nbsp;Naoki Miyamoto ,&nbsp;Isao Yokota ,&nbsp;Keiji Kobashi ,&nbsp;Hidefumi Aoyama","doi":"10.1016/j.phro.2024.100690","DOIUrl":"10.1016/j.phro.2024.100690","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Radiation-induced lymphopenia (RIL) may be associated with a worse prognosis in pancreatic cancer. This study aimed to develop a normal tissue complication probability (NTCP) model to predict severe RIL in patients with pancreatic cancer undergoing concurrent chemoradiotherapy (CCRT).</div></div><div><h3>Materials and methods</h3><div>We reviewed pancreatic cancer patients treated at our facility for model training and internal validation. Subsequently, we reviewed data from three other facilities to validate model fit externally. An absolute lymphocyte count (ALC) of ＜0.5 × 10³/μL during CCRT was defined as severe RIL. An NTCP model was trained using a least absolute shrinkage and selection operator (LASSO)-based logistic model. The model’s predictive performance was evaluated using the receiver operating characteristic area under the curve (AUC), scaled Brier score, and calibration plots.</div></div><div><h3>Results</h3><div>Among the 114 patients in the training set, 78 had severe RIL. LASSO showed that low baseline ALC, large planning target volume, and high percentage of bilateral kidneys receiving ≥ 5Gy were selected as parameters of the NTCP model for severe RIL. The AUC and scaled Brier score were 0.91 and 0.49, respectively. Internal validation yielded an average AUC of 0.92. In the external validation with 68 patients, the AUC and scaled Brier score was 0.83 and 0.30, respectively. Calibration plots showed good conformity.</div></div><div><h3>Conclusions</h3><div>The NTCP model for severe RIL during CCRT for pancreatic cancer, developed and validated in this study, demonstrated good predictive performance. This model can be used to evaluate and compare the risk of RIL.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100690"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11733268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}