Physics and Imaging in Radiation Oncology最新文献

{"title":"Cone-beam computed tomography reconstruction for a commercial proton beam therapy system","authors":"Josh W.H. Lindsay ,&nbsp;Simon J.P. Meara ,&nbsp;Matthew Clarke ,&nbsp;Matthew Lowe ,&nbsp;David Lines ,&nbsp;Marianne C. Aznar ,&nbsp;Marcel van Herk","doi":"10.1016/j.phro.2025.100745","DOIUrl":"10.1016/j.phro.2025.100745","url":null,"abstract":"<div><h3>Background &amp; Purpose:</h3><div>Cone-beam computed tomography (CBCT) images are used in image-guided radiotherapy to track anatomical changes throughout treatment and to set up patients to ensure accurate delivery of therapeutic radiation at each treatment session. An offline method of CBCT reconstruction workflow, operating on 2D projection images and specific to the imaging system in question, is needed for many image optimisation studies. Here we present a methodology to reconstruct CBCT images from these data for a commercial proton beam therapy machine, accounting for the variation in exposure and beam hardening from filtration due to gantry rotation during CBCT acquisition.</div></div><div><h3>Materials &amp; Methods:</h3><div>Projection data of solid water phantoms were acquired to model bow-tie filter motion and beam hardening effects. Projection data and system CBCT reconstructions of a Catphan504 phantom were acquired for validation of the method, as well as a retrospectively accessed patient image. The presented workflow was assessed against the clinical reconstructions using uniformity, signal-to-noise-ratio, and contrast-to-noise-ratio measured in the phantom images.</div></div><div><h3>Results:</h3><div>The offline workflow eliminated crescent artefacts due to variable exposure and beam hardening in phantom and patient images. Signal-to-noise and contrast-to-noise ratios were similar compared to system reconstructions, although with slight differences thought to be due to interplay effects in the bow-tie filter.</div></div><div><h3>Conclusion:</h3><div>A workflow was developed to emulate the CBCT reconstruction process for a commercial proton therapy machine, providing a useful tool for optimised acquisition parameters and novel reconstruction processes using this system.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100745"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799976","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":"Spot-optimization reduces beam delivery time in liver breath hold intensity modulated proton therapy","authors":"Michael Butkus ,&nbsp;Daniel Bastawros ,&nbsp;Yunze Yang ,&nbsp;Roberto Cassetta ,&nbsp;Roni Hytonen ,&nbsp;Robert Kaderka","doi":"10.1016/j.phro.2025.100763","DOIUrl":"10.1016/j.phro.2025.100763","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Liver irradiations with intensity-modulated proton therapy (IMPT) often require motion mitigation techniques that prolong treatment. A prototype spot-optimization algorithm was tested to evaluate whether plan delivery time could be reduced while preserving quality.</div></div><div><h3>Methods and materials</h3><div>Fifteen patients previously treated with liver IMPT using breath-hold were re-planned with nominal treatment planning system (TPS) settings and using a prototype spot-optimization algorithm in which combinations of minimum Monitor Unit (MU) and layer-spacing settings were tested: 1MU/1MeV, 3MU/3MeV, 1MU/5MeV, 5MU/3MeV. Spot-optimized and nominals plans were compared using standard dose-volume histogram (DVH) metrics for targets and organs-at-risk. A Wilcoxon signed-rank test was applied (p &lt; 0.05). Delivery time for all plans were measured by creating and delivering IMPT quality assurance (QA) plans. Gamma analyses were performed on all plans to test deliverability. Plans were considered deliverable if &gt;90 % of points passed a gamma criterion of 3 %/3mm.</div></div><div><h3>Results</h3><div>Minimal DVH differences were observed between nominal and spot-optimized plans. For the 3MU/3MeV setting, no DVH metrics were significantly different. Median and interquartile range (IQR) delivery times for these plans were 40 % (38 %<strong>–</strong>44 %) faster than nominal plans. 5MU/3MeV plans had median (IQR) delivery times 59 % (52 %<strong>–</strong>61 %) faster than nominal plans but had a small but significant increase in Liver_Eff D_mean with a median (IQR) difference of 0.2 Gy(RBE) (0.0<strong>–</strong>0.4 Gy(RBE)). QA analysis showed all spot-optimized plans were deliverable.</div></div><div><h3>Conclusions</h3><div>The spot-optimization algorithm produced clinically deliverable plans with negligible DVH differences to nominal plans and reduced delivery time of liver IMPT by over one-third.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100763"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786027","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 0.05 mm3 diode-based single charged-particle real-time radiation detector for electron radiotherapy","authors":"Kyoungtae Lee ,&nbsp;Rahul Lall ,&nbsp;Michel M. Maharbiz ,&nbsp;Mekhail Anwar","doi":"10.1016/j.phro.2025.100762","DOIUrl":"10.1016/j.phro.2025.100762","url":null,"abstract":"<div><div>Real-time radiation monitoring at the single-particle level is an unmet need for electron radiotherapy, especially for dose deposition to targets in motion or critical OARs. We have developed a first-in-class CMOS-based 0.05 mm³ single electron sensitive detector. The chiplet integrates all the requisite electronics. The functionality of the system is verified under 6 and 9 MeV clinical electron beams. Percentage depth vs. pulse-width curves for 6 and 9 MeV beams are measured and verified using Monte-Carlo simulations. The proposed system has the potential to enhance the electron radiotherapy quality and safety, providing real-time dosimetry from multiple sites simultaneously.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100762"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786028","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":"Partial adaptation for online-adaptive proton therapy triggered by during-delivery treatment verification: Feasibility study on prostate cancer treatments","authors":"Virginia Gambetta ,&nbsp;Victoria Pieta ,&nbsp;Jonathan Berthold ,&nbsp;Tobias Hölscher ,&nbsp;Albin Fredriksson ,&nbsp;Christian Richter ,&nbsp;Kristin Stützer","doi":"10.1016/j.phro.2025.100755","DOIUrl":"10.1016/j.phro.2025.100755","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Online treatment verification during proton therapy delivery may detect deviations due to anatomical changes occurring along the treatment course and trigger immediate intervention, if necessary. We investigated the potential of partial plan adaptation in two-field prostate cancer treatments as a solution for online-adaptive proton therapy (OAPT) after the detection of relevant treatment deviations during the first field delivery.</div></div><div><h3>Materials and Methods</h3><div>In a retrospective study, ten fractions from eight prostate cancer patients with prompt gamma imaging (PGI) detected treatment deviations, which were confirmed on respective in-room control computed tomography (cCT) scans, were considered. For each cCT, a dose-mimicking-based robust partial adaptation reoptimized the second field by considering the suboptimal dose delivery of the first non-adapted, PGI-monitored field. The results were compared to the non-adapted scenario and upfront full adaptation (both fields) in terms of achievable target coverage (prescription: 48 Gy/60 Gy to low-risk/high-risk target) and organ-at-risk (OAR) sparing.</div></div><div><h3>Results</h3><div>Partially adapted plans showed comparable target coverage (median <em>D</em>_98%: 99.9%/98.0% for low-/high-risk target) to fully adapted plans (100.3%/98.7%) and were superior to non-adapted plans (98.7%/94.5%). Achievable OAR sparing was patient-specific depending on the proximity to the target region, but within clinical goals for the partially and fully adapted plans.</div></div><div><h3>Conclusions</h3><div>Partial adaptation triggered mid-delivery of a fraction can still generate plans of comparable conformity to full adaptation, even in the case of plans with only two, opposing fields. A verification-triggered OAPT may therefore become an alternative to upfront OAPT, saving time and imaging dose in fractions without relevant anatomy changes.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100755"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739446","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":"Improving outcome prediction in oropharyngeal carcinoma through the integration of diffusion-weighted magnetic resonance imaging radiomics","authors":"Heleen Bollen ,&nbsp;Rüveyda Dok ,&nbsp;Frederik De Keyzer ,&nbsp;Sarah Deschuymer ,&nbsp;Annouschka Laenen ,&nbsp;Johannes Devos ,&nbsp;Vincent Vandecaveye ,&nbsp;Sandra Nuyts","doi":"10.1016/j.phro.2025.100759","DOIUrl":"10.1016/j.phro.2025.100759","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Locoregional recurrence (LRR) is the primary pattern of failure in head and neck cancer (HNC) following radiation treatment (RT). Predicting an individual patient’s LRR risk is crucial for pre-treatment risk stratification and treatment adaptation during RT. This study aimed to evaluate the feasibility of integrating pre-treatment and mid-treatment diffusion-weighted (DW)-MRI radiomic parameters into multivariable prognostic models for HNC.</div></div><div><h3>Materials and methods</h3><div>A total of 178 oropharyngeal cancer (OPC) patients undergoing (chemo)radiotherapy (CRT) were analyzed on DW-MRI scans. 105 radiomic features were extracted from ADC maps. Cox regression models incorporating clinical and radiomic parameters were developed for pre-treatment and mid-treatment phases. The models’ discriminative ability was assessed with the Harrel C-index after 5-fold cross-validation.</div></div><div><h3>Results</h3><div>Gray Level Co-occurrence Matrix (GLCM)-correlation emerged as a significant pre-treatment radiomic predictor of locoregional control (LRC) with a C-index (95 % CI) of 0.66 (0.57–0.75). Significant clinical predictors included HPV status, stage, and alcohol use, yielding a C-index of 0.70 (0.62–0.78). Combining clinical and radiomic data resulted in a C-index of 0.72 (0.65–0.80), with GLCM-correlation, disease stage and alcohol use as significant predictors. The mid-treatment model, which included delta (Δ) mean ADC, stage, and additional chemotherapy, achieved a C-index of 0.74 (0.65–0.82). Internal cross-validation yielded C-indices of 0.60 (0.51–0.69), 0.56 (0.44–0.66), and 0.63 (0.54–0.73) for the clinical, combined, and mid-treatment models, respectively.</div></div><div><h3>Conclusion</h3><div>The addition of Δ ADC improves the clinical model, highlighting the potential complementary value of radiomic features in prognostic modeling.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100759"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767653","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":"Multicentre prospective risk analysis of a fully automated radiotherapy workflow","authors":"Geert De Kerf ,&nbsp;Ana Barragán-Montero ,&nbsp;Charlotte L. Brouwer ,&nbsp;Pietro Pisciotta ,&nbsp;Marie-Claude Biston ,&nbsp;Marco Fusella ,&nbsp;Geoffroy Herbin ,&nbsp;Esther Kneepkens ,&nbsp;Livia Marrazzo ,&nbsp;Joshua Mason ,&nbsp;Camila Panduro Nielsen ,&nbsp;Koen Snijders ,&nbsp;Stephanie Tanadini-Lang ,&nbsp;Aude Vaandering ,&nbsp;Tomas M. Janssen","doi":"10.1016/j.phro.2025.100765","DOIUrl":"10.1016/j.phro.2025.100765","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Fully automated workflows (FAWs) for radiotherapy treatment preparation are feasible, but remain underutilized in clinical settings. A multicentre prospective risk analysis was conducted to support centres in managing FAW-related risks and to identify workflow steps needing improvement.</div></div><div><h3>Material and Methods</h3><div>Eight European radiotherapy centres performed a failure mode and effect analysis (FMEA) on a hypothetical FAW, with a manual review step at the end. Centres assessed occurrence, severity and detectability of provided, or newly added, failure modes to obtain a risk score. Quantitative analysis was performed on curated data, while qualitative analysis summarized free text comments.</div></div><div><h3>Results</h3><div>Manual review and auto-segmentation were identified as the highest-risk steps and the highest scoring failure modes were associated with inadequate manual review (high detectability and severity score), incorrect (i.e. outside of intended use) application of the FAW (high severity score) and protocol violations during patient preparation (high occurrence score). The qualitative analysis highlighted amongst others the risk of deviation from protocol and the difficulty for manual review to recognize automation errors. The risk associated with the technical parts of the workflow was considered low.</div></div><div><h3>Conclusions</h3><div>The FMEA analysis highlighted that points where people interact with the FAW were considered higher risk than lack of trust in the FAW itself. Major concerns were the ability of people to correctly judge output in case of low generalizability and increasing skill degradation. Consequently, educational programs and interpretative tools are essential prerequisites for widespread clinical application of FAWs.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100765"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143791665","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":"Organs at risk proximity in central lung stereotactic ablative radiotherapy: A comparison of four-dimensional computed tomography and magnetic resonance-guided breath-hold delivery techniques","authors":"Nicolas Giraud ,&nbsp;Hilâl Tekatli ,&nbsp;Famke L. Schneiders ,&nbsp;John R. van Sornsen de Koste ,&nbsp;Marco Marzo ,&nbsp;Miguel A. Palacios ,&nbsp;Suresh Senan","doi":"10.1016/j.phro.2025.100761","DOIUrl":"10.1016/j.phro.2025.100761","url":null,"abstract":"<div><div>Higher toxicity rates are associated with stereotactic ablative radiotherapy (SABR) to central lung tumors. Breath-hold (BH) magnetic resonance-guided SABR (MR-SABR) can reduce doses to organs at risk (OAR). We quantified the planning target volumes (PTV) to OAR distance in 45 lesions treated using MR-SABR and generated a corresponding four-dimensional computed tomography (4D-CT) based PTV (motion-encompassing internal target volume plus 5 mm). For lesions located ≦3 cm from airways, BH MR-SABR increased the median PTV distance to OAR by 3.7 mm. For lesions ≦3 cm from pericardium, median PTV-OAR separation increased by 2.0 mm with BH. These findings highlight the advantage of BH SABR for central lung tumors.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100761"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777553","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":"Development and external multicentric validation of a deep learning-based clinical target volume segmentation model for whole-breast radiotherapy","authors":"Maria Giulia Ubeira-Gabellini ,&nbsp;Gabriele Palazzo ,&nbsp;Martina Mori ,&nbsp;Alessia Tudda ,&nbsp;Luciano Rivetti ,&nbsp;Elisabetta Cagni ,&nbsp;Roberta Castriconi ,&nbsp;Valeria Landoni ,&nbsp;Eugenia Moretti ,&nbsp;Aldo Mazzilli ,&nbsp;Caterina Oliviero ,&nbsp;Lorenzo Placidi ,&nbsp;Giulia Rambaldi Guidasci ,&nbsp;Cecilia Riani ,&nbsp;Andrei Fodor ,&nbsp;Nadia Gisella Di Muzio ,&nbsp;Robert Jeraj ,&nbsp;Antonella del Vecchio ,&nbsp;Claudio Fiorino","doi":"10.1016/j.phro.2025.100749","DOIUrl":"10.1016/j.phro.2025.100749","url":null,"abstract":"<div><h3>Background and purpose:</h3><div>In order to optimize the radiotherapy treatment and minimize toxicities, organs-at-risk (OARs) and clinical target volume (CTV) must be segmented. Deep Learning (DL) techniques show significant potential for performing this task effectively. The availability of a large single-institute data sample, combined with additional numerous multi-centric data, makes it possible to develop and validate a reliable CTV segmentation model.</div></div><div><h3>Materials and methods:</h3><div>Planning CT data of 1822 patients were available (861 from a single center for training and 961 from 8 centers for validation). A preprocessing step, aimed at standardizing all the images, followed by a 3D-Unet capable of segmenting both right and left CTVs was implemented. The metrics used to evaluate the performance were the Dice similarity coefficient (DSC), the Hausdorff distance (HD), and its 95th percentile variant (HD_95) and the Average Surface Distance (ASD).</div></div><div><h3>Results:</h3><div>The segmentation model achieved high performance on the validation set (DSC: 0.90; HD: 20.5 mm; HD_95: 10.0 mm; ASD: 2.1 mm; epoch 298). Furthermore, the model predicted smoother contours than the clinical ones along the cranial–caudal axis in both directions. When applied to internal and external data the same metrics demonstrated an overall agreement and model transferability for all but one (Inst 9) center.</div></div><div><h3>Conclusion:</h3><div>. A 3D-Unet for CTV segmentation trained on a large single institute cohort consisting of planning CTs and manual segmentations was built and externally validated, reaching high performance.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100749"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767951","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":"Clinical implementation of patient-specific quality assurance for synthetic computed tomography","authors":"Francesca Nella ,&nbsp;Stephanie Tanadini-Lang,&nbsp;Riccardo Dal Bello","doi":"10.1016/j.phro.2025.100764","DOIUrl":"10.1016/j.phro.2025.100764","url":null,"abstract":"<div><h3>Background and purpose</h3><div>In a magnetic resonance (MR) only planning workflow, MR image is the sole dataset acquired. In order to calculate the dose deposition, a synthetic CT (sCT) is generated to substitute the planning computed tomography (CT). This study aimed to establish acceptance criteria for the clinical implementation of patient-specific quality assurance (PSQA) for sCT.</div></div><div><h3>Materials and methods</h3><div>A retrospective study was conducted on 60. 30 patients underwent a CT scan in treatment position and an MR in diagnostic position. 30 patients had both CT and MR images acquired in treatment position. For the latter group, a sCT for dose calculation was generated and compared against three PSQA methods: recalculation on (A) water override of the body, (B) tissue classes with bulk density overrides and (C) planning CT. The relative dose differences (ΔD [%]) between the sCT and the PSQA methos were evaluated.</div></div><div><h3>Results</h3><div>ΔD for PTV Dmean for method (A) were within 3% for pelvis and 4% for brain cohorts, with standard deviations below 1%. Methods (B) and (C) remained within 2% and 1%, respectively, with deviations up to 1%.</div></div><div><h3>Conclusion</h3><div>The present study proposes a robust PSQA method for MR-only planning. Method (A) is a valuable tool for identifying potential large outliers for Dmean deviations (&gt; 5 %) and it is proposed as the routine PSQA. Method (B) can be used for pelvis cases to improve detection to the 2 % level if method (A) fails. If both (A) and (B) fail, method (C) can be used as a fall-back.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100764"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143791666","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":"Ultra-low field magnetic resonance breast imaging in prone and seated positions for radiation therapy","authors":"Friderike K. Longarino ,&nbsp;Sheng Shen ,&nbsp;Neha Koonjoo ,&nbsp;Torben P.P. Hornung ,&nbsp;Rachel B. Jimenez ,&nbsp;Elie K. Mehanna ,&nbsp;John T. Burge ,&nbsp;Zoelle Wilson ,&nbsp;Kathryn E. Keenan ,&nbsp;Thomas R. Bortfeld ,&nbsp;Matthew S. Rosen ,&nbsp;Susu Yan","doi":"10.1016/j.phro.2025.100758","DOIUrl":"10.1016/j.phro.2025.100758","url":null,"abstract":"<div><h3>Background &amp; purpose</h3><div>The aim of this first-in-human study was to investigate the potential of ultra-low field (ULF) magnetic resonance imaging (MRI) at 6.5<!--> <!-->mT for breast imaging in healthy female participants in prone and seated positions for radiation therapy, especially compact proton therapy systems.</div></div><div><h3>Materials &amp; methods</h3><div>An experimental setup for breast imaging in prone and seated positions utilizing an ULF MRI scanner and a conical RF coil was developed. ULF MR images of the left breast of ten healthy women were acquired in prone and seated positions using a 3D balanced steady-state free precession sequence without the use of contrast agents. The visibility of the breast outline, chest wall, and cardiac silhouette in prone and seated position ULF breast MR images was evaluated by two radiation oncologists (ROs) and two radiation therapists (RTTs), respectively.</div></div><div><h3>Results</h3><div>ULF breast MRI obtained at 6.5<!--> <!-->mT can show breast outline, chest wall, and cardiac silhouette in prone and seated positions. ULF prone/seated images were found to be acceptable by the ROs (RTTs) for treatment planning (setup) purposes in 100%/95% (95%/85%) of cases for breast outline visibility, in 70%/50% (75%/70%) of cases for chest wall visibility, and in 65%/65% (0%/10%) of cases for cardiac silhouette visibility.</div></div><div><h3>Conclusions</h3><div>This proof-of-concept study demonstrated that breast imaging is feasible in prone and seated positions utilizing ULF MRI and partially suitable for treatment planning and setup in proton therapy. Yet an increased spatio-temporal resolution is required for applications to MRI-guided proton therapy. ULF MRI may enable position monitoring and adaptive treatment procedures in radiation therapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100758"},"PeriodicalIF":3.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725298","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}