Physica Medica-European Journal of Medical Physics最新文献

{"title":"Automated whole-breast ultrasound tumor diagnosis using attention-inception network","authors":"Jun Zhang ,&nbsp;Yao-Sian Huang ,&nbsp;You-Wei Wang ,&nbsp;Huiling Xiang ,&nbsp;Xi Lin ,&nbsp;Ruey-Feng Chang","doi":"10.1016/j.ejmp.2025.104989","DOIUrl":"10.1016/j.ejmp.2025.104989","url":null,"abstract":"<div><h3>Purpose</h3><div>Automated Whole-Breast Ultrasound (ABUS) has been widely used as an important tool in breast cancer diagnosis due to the ability of this technique to provide complete three-dimensional (3D) images of breasts. To eliminate the risk of misdiagnosis, computer-aided diagnosis (CADx) systems have been proposed to assist radiologists. Convolutional neural networks (CNNs), renowned for the automatic feature extraction capabilities, have developed rapidly in medical image analysis, and this study proposes a CADx system based on 3D CNN for ABUS.</div></div><div><h3>Materials and methods</h3><div>This study used a private dataset collected at Sun Yat-Sen University Cancer Center (SYSUCC) from 396 breast tumor patients. First, the tumor volume of interest (VOI) was extracted and resized, and then the tumor was enhanced by histogram equalization. Second, a 3D U-Net++ was employed to segment the tumor mask. Finally, the VOI, the enhanced VOI, and the corresponding tumor mask were fed into a 3D Attention-Inception network to classify the tumor as benign or malignant.</div></div><div><h3>Results</h3><div>The experiment results indicate an accuracy of 89.4%, a sensitivity of 91.2%, a specificity of 87.6%, and an area under the receiver operating characteristic curve (AUC) of 0.9262, which suggests that the proposed CADx system for ABUS images rivals the performance of experienced radiologists in tumor diagnosis tasks.</div></div><div><h3>Conclusion</h3><div>This study proposes a CADx system consisting of a 3D U-Net++ tumor segmentation model and a 3D attention inception neural network tumor classification model for diagnosis in ABUS images. The results indicate that the proposed CADx system is effective and efficient in tumor diagnosis tasks.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104989"},"PeriodicalIF":3.3,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947919","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":"Evaluation of secondary cancers risk induction in adjuvant breast radiotherapy: creation of technique independent dose–effect curves for OARs dose optimization","authors":"Francesco Moretti ,&nbsp;Luca Marzoli ,&nbsp;Luigi De Cicco ,&nbsp;Rita Lorusso ,&nbsp;Paolo Imperiale ,&nbsp;Annalisa Pepe ,&nbsp;Daniela Corletto ,&nbsp;Barbara Bortolato ,&nbsp;Lorenzo Bianchi","doi":"10.1016/j.ejmp.2025.105002","DOIUrl":"10.1016/j.ejmp.2025.105002","url":null,"abstract":"<div><h3>Purpose</h3><div>We investigated the relationship between the risk estimation models for the induction of secondary cancers in adjuvant breast radiotherapy, in competition model hypothesis, and the average dose on OARs to create technique independent dose–effect curves, useful in treatment planning optimization.</div></div><div><h3>Methods and materials</h3><div>We examined 37 three-dimensional conformal radiotherapy (3D-CRT) and 49 volumetric modulated arc therapy (VMAT) plans, studied between September 2022 and September 2023, targeting breast and surgical bed boost with or without regional nodal irradiation.</div><div>For every treatment plans we collected the average dose for Ipsilateral Lung, Contralateral Lung and Contralateral Breast. Using different parameters for LQ models, we calculated the Excess of Relative Risk (ERR) from planned DVHs for each OARs. Finally, we fitted the ERR data against the average organ dose to draw different dose–effect curves for each organ of interest.</div></div><div><h3>Results</h3><div>All dose–effect curves calculated, using both plan technique, have shown a good fitting coefficient (<span><math><mrow><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup><mo>&gt;</mo><mn>0.86</mn></mrow></math></span>) so the curves obtained could be considered technique independent. The values of ERR in each curve obtained with different α/β values (<span><math><mrow><mi>α</mi><mo>/</mo><mi>β</mi><mo>=</mo><mn>3.91</mn><mi>G</mi><mi>y</mi></mrow></math></span> for breast and <span><math><mrow><mi>α</mi><mo>/</mo><mi>β</mi><mo>=</mo><mn>4.50</mn><mi>G</mi><mi>y</mi></mrow></math></span> for lung) result of the same order of magnitude with case-control studies reported in literature especially in the low-dose range.</div></div><div><h3>Conclusions</h3><div>The calculated ERR vs Average Dose curves could be used to optimize average organ doses in treatment planning study in relation to the risk of a secondary radiation-induced cancer. We can use these curves to prioritize OARs dose optimization.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 105002"},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935471","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":"Automated field-in-field planning for tangential breast radiation therapy based on digitally reconstructed radiograph","authors":"Patthanee Srikornkan ,&nbsp;Chirasak Khamfongkhruea ,&nbsp;Panatda Intanin ,&nbsp;Sangutid Thongsawad","doi":"10.1016/j.ejmp.2025.104994","DOIUrl":"10.1016/j.ejmp.2025.104994","url":null,"abstract":"<div><h3>Background</h3><div>The tangential field-in-field (FIF) technique is a widely used method in breast radiation therapy, known for its efficiency and the reduced number of fields required in treatment planning. However, it is labor-intensive, requiring manual shaping of the multileaf collimator (MLC) to minimize hot spots.</div></div><div><h3>Purpose</h3><div>This study aims to develop a novel automated FIF planning approach for tangential breast radiation therapy using Digitally Reconstructed Radiograph (DRR) images.</div></div><div><h3>Methods</h3><div>A total of 78 patients were selected to train and test a fluence map prediction model based on U-Net architecture. DRR images were used as input data to predict the fluence maps. The predicted fluence maps for each treatment plan were then converted into MLC positions and exported as Digital Imaging and Communications in Medicine (DICOM) files. These files were used to recalculate the dose distribution and assess dosimetric parameters for both the PTV and OARs.</div></div><div><h3>Results</h3><div>The mean absolute error (MAE) between the predicted and original fluence map was 0.007 ± 0.002. The result of gamma analysis indicates strong agreement between the predicted and original fluence maps, with gamma passing rate values of 95.47 ± 4.27 for the 3 %/3 mm criteria, 94.65 ± 4.32 for the 3 %/2 mm criteria, and 83.4 ± 12.14 for the 2 %/2 mm criteria. The plan quality, in terms of tumor coverage and doses to organs at risk (OARs), showed no significant differences between the automated FIF and original plans.</div></div><div><h3>Conclusion</h3><div>The automated plans yielded promising results, with plan quality comparable to the original.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104994"},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935472","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":"Fully automated image quality assessment based on deep learning for carotid computed tomography angiography: A multicenter study","authors":"Wanyun Fu ,&nbsp;Zhangman Ma ,&nbsp;Zhiwen Yang ,&nbsp;Shufeng Yu ,&nbsp;Yongsheng Zhang ,&nbsp;Xinsheng Zhang ,&nbsp;Bozhe Mei ,&nbsp;Yu Meng ,&nbsp;Chune Ma ,&nbsp;Xiangyang Gong","doi":"10.1016/j.ejmp.2025.104990","DOIUrl":"10.1016/j.ejmp.2025.104990","url":null,"abstract":"<div><h3>Purpose</h3><div>To develop and evaluate the performance of fully automated model based on deep learning and multiple logistics regression algorithm for image quality assessment (IQA) of carotid computed tomography angiography (CTA) images.</div></div><div><h3>Methods</h3><div>This study retrospectively collected 840 carotid CTA images from four tertiary hospitals. Three radiologists independently assessed the image quality using a 3-point Likert scale, based on the degree of noise, vessel enhancement, arterial vessel contrast, vessel edge sharpness, and overall diagnostic acceptability. An automated assessment model was developed using a training dataset consisting of 600 carotid CTA images. The assessment steps included: (i) selection of objective representative slices; (ii) use of 3D Res U-net approach to extract objective indices from the representative slices and (iii) use of single objective index and multiple indices combinedly to develop logistic regression models for IQA. In the internal and external test datasets (n = 240), the performance of models was evaluated using sensitivity, specificity, precision, F-score, accuracy, the area under the receiver operating characteristic curve (AUC), and the IQA results of models was compared with radiologists’ consensus.</div></div><div><h3>Results</h3><div>The representative slices were determined based on the same length model. The performance of multi-index model was excellent in internal and external test datasets with AUCs of 0.98 and 0.97. And the consistency between model and radiologists achieved 91.8% (95% CI: 87.0–96.5) and 92.6% (95 % CI: 86.9–98.4) in internal and external test datasets respectively.</div></div><div><h3>Conclusion</h3><div>The fully automated multi-index model showed equivalent performance to the subjective perceptions of radiologists with greater efficiency for IQA.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104990"},"PeriodicalIF":3.3,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929035","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":"Dosimetric performance of cone beam CT-guided adaptive carbon-ion radiotherapy with daily replanning for pancreatic cancer","authors":"Lukas Fabrizio Klassen ,&nbsp;Hideaki Hirashima ,&nbsp;Hiraku Iramina ,&nbsp;Takahiro Iwai ,&nbsp;Michio Yoshimura ,&nbsp;Hiroki Tanaka ,&nbsp;Takashi Mizowaki ,&nbsp;Mitsuhiro Nakamura","doi":"10.1016/j.ejmp.2025.104991","DOIUrl":"10.1016/j.ejmp.2025.104991","url":null,"abstract":"<div><h3>Purpose</h3><div>We investigated whether an ultra-hypofractionated carbon-ion radiotherapy (CIRT) protocol for pancreatic cancer (PC) could produce satisfactory dosimetric results with or without cone-beam CT-guided adaptive replanning and explored the potential dosimetric advantages of the adapted protocol.</div></div><div><h3>Methods</h3><div>Eleven PC patients who underwent CBCT-guided online adaptive photon radiotherapy were selected. Data were imported into a CIRT treatment planning software to develop new plans for an ultra-hypofractionated CIRT protocol. Prescriptions and constraints were recalculated for a five-fraction schedule using a linear quadratic model for organs-at-risk (OARs) and targets, respectively. The biologically effective dose-equivalent prescribed dose was set at 43.2 Gy (relative biological effectiveness [RBE]). Each day, a synthetic CT (SCT) was generated from the planning CT (PCT) with the daily CBCT. A reference plan based on the PCT was compared to an adapted plan based on the SCT. Deformable image registration was used to allow summation of the daily doses.</div></div><div><h3>Results</h3><div>The adapted plans met the clinical goals, whereas the reference plans exceeded the constraints in 27 % (stomach), 53 % (duodenum), and 31 % (small bowel) of the fractions. The adapted plans notably decreased V_{35.5 Gy[RBE]} for all gastrointestinal OARs, while significantly enhancing the gross tumor volume (GTV) D_95% and planning target volume (PTV) D_90%. The accumulated doses showed significant improvements in the duodenum V_{35.5 Gy[RBE]}, GTV D_95%, and PTV D_90%.</div></div><div><h3>Conclusion</h3><div>CBCT-guided adaptive CIRT for PC demonstrated favorable dosimetric results, notably enhancing the sparing of OARs and ensuring superior target coverage compared with non-adaptive CIRT protocols.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104991"},"PeriodicalIF":3.3,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929037","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":"Determination of beam quality correction factors for alanine dosimetry in clinical proton beams","authors":"Chae-Eon Kim ,&nbsp;Jong In Park ,&nbsp;Seongmoon Jung ,&nbsp;Sang-il Pak ,&nbsp;Seonghoon Jeong ,&nbsp;Seohyeon An ,&nbsp;Chankyu Kim ,&nbsp;Jong Hwi Jeong ,&nbsp;Haksoo Kim ,&nbsp;Young Kyung Lim ,&nbsp;Dongho Shin ,&nbsp;Yoonsun Chung ,&nbsp;In Jung Kim ,&nbsp;Se Byeong Lee","doi":"10.1016/j.ejmp.2025.104992","DOIUrl":"10.1016/j.ejmp.2025.104992","url":null,"abstract":"<div><h3>Introduction</h3><div>With the advent of FLASH radiotherapy, alanine dosimetry has gained attention as a promising dosimeter owing to its dose-rate independence. However, before utilized in radiotherapy, procedures for determining the absorbed dose to water using alanine under clinical proton beams must be established. This study sought to develop a formula for alanine dosimetry by deriving beam quality correction factors and validating them through Monte Carlo simulations and experimental measurements.</div></div><div><h3>Materials and Methods</h3><div>To calculate the absorbed dose to water using alanine dosimeters, a formula was developed specifically for the plateau region. Alanine dosimeters were irradiated under both a reference beam (Cobalt-60) and clinical proton beams. Beam quality correction factors were calculated and subsequently validated through Monte Carlo simulations using the Tool for Particle Simulation (TOPAS), which is based on GEANT4, as well as through experimental measurements. During the simulations, both crystalline and bulk densities of alanine were considered.</div></div><div><h3>Results</h3><div>The simulation results showed that the average beam quality correction factors for alanine were 1.005 for crystalline density and 1.012 for bulk density. Experimental measurements under clinical proton beams yielded a beam quality correction factor of 1.014, with a standard uncertainty of 2.2%.</div></div><div><h3>Conclusions</h3><div>These results suggest that alanine dosimeters provide reliable and reproducible measurements for proton therapy. The robust methodology demonstrated here highlights the potential of alanine dosimeters in clinical applications, demonstrating their effectiveness and reliability in determining the absorbed dose to water under clinical proton beam conditions.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104992"},"PeriodicalIF":3.3,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929036","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":"Evaluating robustness for respiratory motion in accelerated partial breast irradiation using virtual bolus and robust optimization methods","authors":"Fumihiro Tomita,&nbsp;Ryohei Yamauchi,&nbsp;Shinobu Akiyama,&nbsp;Tomoyuki Masuda,&nbsp;Nobue Uchida,&nbsp;Satoshi Ishikura","doi":"10.1016/j.ejmp.2025.105001","DOIUrl":"10.1016/j.ejmp.2025.105001","url":null,"abstract":"","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 105001"},"PeriodicalIF":3.3,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931960","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":"Dosimetric optimization and evaluation of hepatocellular carcinoma treatment effect prediction in Y-90 radioembolization","authors":"Laura Grikke ,&nbsp;Massimo De Giorgio ,&nbsp;Claudia Bianchi ,&nbsp;Emanuele Balduzzi ,&nbsp;Francesco Saverio Carbone ,&nbsp;Alberto Gerali ,&nbsp;Arianna Ghirardi ,&nbsp;Riccardo Muglia ,&nbsp;Carolina Prussia ,&nbsp;Mauro Viganò ,&nbsp;Paolo Marra ,&nbsp;Paola Anna Erba ,&nbsp;Sandro Sironi ,&nbsp;Stefano Fagiuoli ,&nbsp;Gian Luca Poli","doi":"10.1016/j.ejmp.2025.105000","DOIUrl":"10.1016/j.ejmp.2025.105000","url":null,"abstract":"<div><h3>Background</h3><div>Liver transarterial radioembolization (TARE) with ⁹⁰Y microspheres is a common treatment for hepatocellular carcinoma (HCC). A pre-treatment SPECT/CT dosimetric study is performed using ^99mTc macroaggregated albumin, followed by PET-based dosimetry to assess dose distribution of ⁹⁰Y. Recent studies show a significant correlation between absorbed doses and treatment outcomes in terms of radiological response, adverse events and overall survival.</div><div>This study aims to present optimized TARE dosimetry protocols and assess outcome predictions according to voxel-based dosimetry.</div></div><div><h3>Methods</h3><div>Dosimetry protocols were refined according to EANM guidelines using the Planet Dose software. Pre-treatment dosimetry was conducted for all patients while post-treatment dosimetry was performed for patients treated after the installation of a new PET/CT system. Statistical analysis was employed to evaluate predictors of complete radiological response (CR) and survival outcomes.</div></div><div><h3>Results</h3><div>133 HCC patients treated with ⁹⁰Y microspheres (95 resin, 38 glass) at single institution were analyzed. ROC curve analysis for resin microspheres indicated a dose threshold of 233.2 Gy (AUC = 0.62) as the best predictor for CR, with higher CR rates in patients receiving this dose. No lung toxicity was noted nor correlation was found between doses to normal liver tissue and adverse events.</div></div><div><h3>Conclusions</h3><div>Lesion absorbed dose is a significant predictor of CR in resin microspheres, with a mean dose of at least 233.2 Gy leading to better oncologic response rates. The absence of correlation between healthy liver tissue dose and adverse events suggests the potential for further increasing the dose to achieve event better outcomes in future protocols.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 105000"},"PeriodicalIF":3.3,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929038","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":"A hybrid AI method for lung cancer classification using explainable AI techniques","authors":"Resham Raj Shivwanshi,&nbsp;Neelam Shobha Nirala","doi":"10.1016/j.ejmp.2025.104985","DOIUrl":"10.1016/j.ejmp.2025.104985","url":null,"abstract":"<div><h3>Purpose</h3><div>The use of Artificial Intelligence (AI) methods for the analysis of CT (computed tomography) images has greatly contributed to the development of an effective computer-assisted diagnosis (CAD) system for lung cancer (LC). However, complex structures, multiple radiographic interrelations, and the dynamic locations of abnormalities within lung CT images make extracting relevant information to process and implement LC CAD systems difficult. These prominent problems are addressed in this paper by presenting a hybrid method of LC malignancy classification, which may help researchers and experts properly engineer the model’s performance by observing how the model makes decisions.</div></div><div><h3>Methods</h3><div>The proposed methodology is named IncCat-LCC: Explainer (Inception Net Cat Boost LC Classification: Explainer), which consists of feature extraction (FE) using the handcrafted radiomic Feature (HcRdF) extraction technique, InceptionNet CNN Feature (INCF) extraction, Vision Transformer Feature (ViTF) extraction, and XGBOOST (XGB)-based feature selection, and the GPU based CATBOOST (CB) classification technique.</div></div><div><h3>Results</h3><div>The proposed framework achieves better and highest performance scores for lung nodule multiclass malignancy classification when evaluated using metrics such as accuracy, precision, recall, f-1 score, specificity, and area under the roc curve as 96.74 %, 93.68 %, 96.74 %, 95.19 %, 98.47 % and 99.76 % consecutively for classifying highly normal class.</div></div><div><h3>Conclusion</h3><div>Observing the explainable artificial intelligence (XAI) explanations will help readers understand the model performance and the statistical outcomes of the evaluation parameter. The work presented in this article may improve the existing LC CAD system and help assess the important parameters using XAI to recognize the factors contributing to enhanced performance and reliability.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104985"},"PeriodicalIF":3.3,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917378","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":"Kilovoltage triggered imaging for moderately hypofractionated prostate radiotherapy: Insights into intrafraction motion and intervention through log file analysis","authors":"Dean Wilkinson ,&nbsp;Liam Ainsworth ,&nbsp;Chelsea Shelley ,&nbsp;Stephen Dowdell ,&nbsp;Adam Briggs ,&nbsp;Belinda Arnold ,&nbsp;Stefanie Micevski ,&nbsp;Alexis A. Miller ,&nbsp;Senthilkumar Gandhidasan","doi":"10.1016/j.ejmp.2025.104998","DOIUrl":"10.1016/j.ejmp.2025.104998","url":null,"abstract":"<div><h3>Purpose</h3><div>To report on intrafraction motion and frequency of intervention observed during kilovoltage imaging and monitoring of implanted fiducial markers (FM) in patients receiving moderately hypofractionated prostate radiotherapy.</div></div><div><h3>Methods</h3><div>Gold FM implanted in the prostate of 50 patients were tracked during volumetric-modulated arc therapy, delivered over 20 fractions, with the Varian intrafraction motion review (IMR) system. Images were acquired orthogonal to the treatment beam at 3 s intervals. A 5 mm radial tolerance was set around all FMs, resulting in interruption to treatment delivery and intervention when FM position exceeded this threshold. Data was programmatically extracted from system log files and analysed to retrospectively reconstruct the individual position and centroid of FM during treatment.</div></div><div><h3>Results</h3><div>Log file data for 991 treatment fractions were analysed. Mid-treatment interventions were required on 12 % of fractions due to one or more FM exceeding the 5 mm tolerance. The maximum centroid displacement was always smaller than the maximum individual FM displacement. The mean added time with intervention was 3.1 ± 0.9 min. Almost 3 in 4 patients had ≥1 fraction requiring intervention. The mean intrafraction change in centroid position across all fractions was 1.8 ± 1.0 mm. The largest displacements were most-commonly observed in the anterior-posterior (AP) and superior-inferior (SI) directions.</div></div><div><h3>Conclusion</h3><div>Interrogation of IMR log files yielded quantitative data for a comprehensive analysis of intrafraction prostate motion not available at the clinical interface. Examining the relationship between centroid and individual FM positions can further guide the clinical use of the system.</div></div>","PeriodicalId":56092,"journal":{"name":"Physica Medica-European Journal of Medical Physics","volume":"134 ","pages":"Article 104998"},"PeriodicalIF":3.3,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917377","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}