Physics and Imaging in Radiation Oncology最新文献

{"title":"Proof-of-concept of real-time electromagnetic guidance for gynecologic interstitial catheters in high dose rate brachytherapy","authors":"Audrey Cantin ,&nbsp;Marie-Claude Lavallée ,&nbsp;Eric Poulin ,&nbsp;Gilion Hautvast ,&nbsp;William Foster ,&nbsp;Luc Beaulieu","doi":"10.1016/j.phro.2024.100661","DOIUrl":"10.1016/j.phro.2024.100661","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>The addition of interstitial needles to intracavitary gynecologic (GYN) high dose rate (HDR) brachytherapy has been shown to improve target coverage and organs-at-risk (OAR) sparing. However, no commercial solution allows real-time guidance of interstitial catheter placement. This phantom study aimed to evaluate the feasibility of an electromagnetic (EM) tracking system guidance workflow for GYN HDR brachytherapy treatment in a magnetic resonance imaging (MRI) and real-time transrectal ultrasound (TRUS) fusion scenario.</div></div><div><h3>Materials and Methods</h3><div>A clinical investigational system combining a treatment planning system and the EM tracking technology was used. The 3D T2 weighted magnetic resonance (MR) image set of a patient treated with intracavitary and interstitial HDR brachytherapy was retrospectively chosen. The MR image set was used to delineate the target and the OARs. A preplan was generated to determine needles positions in advance. The implant was reproduced in a water phantom. A 3D TRUS scan was acquired, and a rigid registration between the MR and the TRUS images was performed.</div></div><div><h3>Results</h3><div>The accuracy of the EM tracking system was &lt; 1 mm for both the sagittal and the transverse modes of the TRUS probe. Contours that were delineated on the MRI were propagated on the TRUS images after the rigid registration. Needle insertion was successfully guided in real time with the EM tracking system on the TRUS live image using the MRI contours for guidance.</div></div><div><h3>Conclusion</h3><div>Based on this proof-of-concept, real-time EM-guidance of interstitial needle for GYN HDR brachytherapy appears to be feasible.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100661"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552814","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":"Reduced-distortion diffusion weighted imaging for head and neck radiotherapy","authors":"Eric Aliotta ,&nbsp;Ramesh Paudyal ,&nbsp;Alex Dresner ,&nbsp;Amita Shukla-Dave ,&nbsp;Nancy Lee ,&nbsp;Laura Cerviño ,&nbsp;Ricardo Otazo ,&nbsp;Victoria Y. Yu","doi":"10.1016/j.phro.2024.100653","DOIUrl":"10.1016/j.phro.2024.100653","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Quantitative Diffusion Weighted Imaging (DWI) has potential value in guiding head and neck (HN) cancer radiotherapy. However, clinical translation has been hindered by severe distortions in standard single-shot Echo-Planar-Imaging (ssEPI) and prolonged scan time and low SNR in Turbo-Spin-Echo (ssTSE) sequences. In this study, we evaluate “multi-shot” (ms) msEPI and msTSE acquisitions in the context of HN radiotherapy.</div></div><div><h3>Materials and methods</h3><div>ssEPI, ssTSE, msEPI with 2 and 3 shots (2sEPI, 3sEPI), and msTSE DWI were acquired in a phantom, healthy volunteers (N=10), and patients with HN cancer (N=5) on a 3-Tesla wide-bore MRI in radiotherapy simulation RF coil setup, with matched spatial resolution (2x2x5mm) and b = 0, 200, 800 s/mm².</div><div>Geometric distortions measured with deformable vector field (DVF) and contour analysis, apparent diffusion coefficient (ADC) values, and signal-to-noise-ratio efficiency (SNR_eff) were quantified for all scans.</div></div><div><h3>Results</h3><div>All techniques significantly (P&lt;1x10^-3) reduced distortions compared with ssEPI (DVF_mean = 3.1 ± 1.3 mm). Distortions were marginally lower for msTSE (DVF_mean = 1.5 ± 0.6 mm) than ssTSE (1.8 ± 0.9 mm), but were slightly higher with 2sEPI and 3sEPI (2.6 ± 1.0 mm, 2.2 ± 1.0 mm). SNR_eff reduced with decreasing distortion with ssEPI=21.9 ± 7.9, 2sEPI=15.1 ± 5.0, 3sEPI=12.1 ± 4.5, ssTSE=6.0 ± 1.6, and msTSE=5.7 ± 1.9 for b = 0 images. Phantom ADC values were consistent across all protocols (errors ≤ 0.03x10^-3mm²/s), but <em>in vivo</em> ADC values were ∼ 4 % lower with msEPI and ∼ 12 % lower with ssTSE/msTSE compared with ssEPI.</div></div><div><h3>Conclusions</h3><div>msEPI and TSE acquisitions exhibited improved geometric distortion at the cost of SNR_eff and scan time. While msTSE exhibited the least distortion, 3sEPI may offer an appealing middle-ground with improved geometric fidelity but superior efficiency and <em>in vivo</em> ADC quantification.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100653"},"PeriodicalIF":3.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326657","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 review of whole gland prostate brachytherapy with focal dose escalation to intra-prostatic lesions: Clinical efficacy and technical aspects","authors":"Joel Poder ,&nbsp;Peter Hoskin ,&nbsp;Hayley Reynolds ,&nbsp;Tsz Him Chan ,&nbsp;Annette Haworth","doi":"10.1016/j.phro.2024.100645","DOIUrl":"10.1016/j.phro.2024.100645","url":null,"abstract":"<div><div>Focal boost to intra-prostatic lesions (IPLs) in radiotherapy could enhance treatment efficacy. Brachytherapy (BT), delivering highly conformal dose with sharp dose gradients emerges as a potentially optimal approach for precise dose escalation to IPLs. This study aims to consolidate clinical and planning studies that implemented whole gland prostate BT and focal dose escalation to IPLs, with the view to synthesize evidence on the strategy’s effectiveness and variability. In this review, we identified nine clinical studies and ten planning/simulation studies focusing on whole gland prostate BT with IPL dose escalation. From the clinical studies, the use of whole gland prostate BT with focal dose escalation in combination with external beam radiotherapy (EBRT) appears to be a safe and effective 21 form of treatment for men with T1b – T2c prostate cancer with average five-year biochemical failure22 free survival (BFFS) of 94 % (range 81.1 %−100 %) and minimal grade three toxicities reported. Both clinical and planning studies exemplified the high level of focal dose escalation achievable using BT with a mean IPL D90 % of 132 % and 146 %, respectively (expressed as a % of the whole gland prescription dose). There was considerable variation in the reporting of clinical and technical data in the identified studies. To facilitate a more widespread and uniform adoption of the technique, recommendations on essential and desirable items to be included in future studies incorporating whole gland prostate BT with focal boost to IPLs are provided.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100645"},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001155/pdfft?md5=fb857f773cb65fce3a672a8b177ccbbf&pid=1-s2.0-S2405631624001155-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311434","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":"Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy","authors":"Chavelli M. Kensen ,&nbsp;Rita Simões ,&nbsp;Anja Betgen ,&nbsp;Lisa Wiersema ,&nbsp;Doenja M.J. Lambregts ,&nbsp;Femke P. Peters ,&nbsp;Corrie A.M. Marijnen ,&nbsp;Uulke A. van der Heide ,&nbsp;Tomas M. Janssen","doi":"10.1016/j.phro.2024.100648","DOIUrl":"10.1016/j.phro.2024.100648","url":null,"abstract":"<div><h3>Background and purpose</h3><p>In online adaptive magnetic resonance image (MRI)-guided radiotherapy (MRIgRT), manual contouring of rectal tumors on daily images is labor-intensive and time-consuming. Automation of this task is complex due to substantial variation in tumor shape and location between patients. The aim of this work was to investigate different approaches of propagating patient-specific prior information to the online adaptive treatment fractions to improve deep-learning based auto-segmentation of rectal tumors.</p></div><div><h3>Materials and methods</h3><p>243 T2-weighted MRI scans of 49 rectal cancer patients treated on the 1.5T MR-Linear accelerator (MR-Linac) were utilized to train models to segment rectal tumors. As benchmark, an MRI_only auto-segmentation model was trained. Three approaches of including a patient-specific prior were studied: 1. include the segmentations of fraction 1 as extra input channel for the auto-segmentation of subsequent fractions, 2. fine-tuning of the MRI_only model to fraction 1 (PSF_1) and 3. fine-tuning of the MRI_only model on all earlier fractions (PSF_cumulative). Auto-segmentations were compared to the manual segmentation using geometric similarity metrics. Clinical impact was assessed by evaluating post-treatment target coverage.</p></div><div><h3>Results</h3><p>All patient-specific methods outperformed the MRI_only segmentation approach. Median 95th percentile Hausdorff (95HD) were 22.0 (range: 6.1–76.6) mm for MRI_only segmentation, 9.9 (range: 2.5–38.2) mm for MRI+prior segmentation, 6.4 (range: 2.4–17.8) mm for PSF_1 and 4.8 (range: 1.7–26.9) mm for PSF_cumulative. PSF_cumulative was found to be superior to PSF_1 from fraction 4 onward (p = 0.014).</p></div><div><h3>Conclusion</h3><p>Patient-specific fine-tuning of automatically segmented rectal tumors, using images and segmentations from all previous fractions, yields superior quality compared to other auto-segmentation approaches.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100648"},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001180/pdfft?md5=bf30e0e5baddbf3b8635126444c1301f&pid=1-s2.0-S2405631624001180-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239769","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":"Impact of motion management strategies on abdominal organ at risk delineation for magnetic resonance-guided radiotherapy","authors":"Mairead Daly ,&nbsp;Lisa McDaid ,&nbsp;Carmel Anandadas ,&nbsp;Andrew Brocklehurst ,&nbsp;Ananya Choudhury ,&nbsp;Alan McWilliam ,&nbsp;Ganesh Radhakrishna ,&nbsp;Cynthia L. Eccles","doi":"10.1016/j.phro.2024.100650","DOIUrl":"10.1016/j.phro.2024.100650","url":null,"abstract":"<div><h3>Background and purpose</h3><div>The impact of respiratory motion management strategies for abdominal radiotherapy, such as abdominal compression (AC) and breath hold (BH), on abdominal organ at risk (OAR) delineation on magnetic resonance imaging (MRI) is unknown. This feasibility study compared the inter- and intra- observer delineation variation on MRI acquired with AC, BH for three critical abdominal OAR.</div></div><div><h3>Materials and methods</h3><div>T2-weighted (W) 3D MRI in free-breathing (FB) and with AC, and T1W 3D mDixon exhale BH were acquired. Four observers blinded to motion management strategy used, delineated stomach, liver, and duodenum on all MRI. One case per strategy was repeated over 6 weeks later to quantify intra-observer variation. Simultaneous truth and performance level estimation (STAPLE) contours for each OAR were generated, median and IQR mean distance to agreement (mDTA) and maximum Hausdorff distance (HD) between observer and STAPLE contours were calculated. Observers scored organ visibility on each MRI using a four-point Likert scale.</div></div><div><h3>Results</h3><div>A total of 27 scans including repeats were delineated. Pooled mDTA for all OARs was 1.3 mm (0.5 mm) with AC, 1.4 mm (1.0 mm) with BH, and 1.3 mm (0.5 mm) in FB. Intra-observer mDTA was highest for all organs in FB with 10.8 mm for duodenum, 1.8 mm for liver, and 2.7 mm for stomach. The pooled mean perceptual quality score value was highest for AC across organs.</div></div><div><h3>Conclusions</h3><div>No motion management strategy demonstrated superior similarity across OAR, emphasizing the need for personalised approaches based on individual clinical and patient factors.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100650"},"PeriodicalIF":3.4,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001209/pdfft?md5=3ca1884b9a70abce37c31b168701b85f&pid=1-s2.0-S2405631624001209-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311511","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":"Machine learning automated treatment planning for online magnetic resonance guided adaptive radiotherapy of prostate cancer","authors":"Aly Khalifa ,&nbsp;Jeff D. Winter ,&nbsp;Tony Tadic ,&nbsp;Thomas G. Purdie ,&nbsp;Chris McIntosh","doi":"10.1016/j.phro.2024.100649","DOIUrl":"10.1016/j.phro.2024.100649","url":null,"abstract":"<div><h3>Background and purpose</h3><p>No best practices currently exist for achieving high quality radiation therapy (RT) treatment plan adaptation during magnetic resonance (MR) guided RT of prostate cancer. This study validates the use of machine learning (ML) automated RT treatment plan adaptation and benchmarks it against current clinical RT plan adaptation methods.</p></div><div><h3>Materials and methods</h3><p>We trained an atlas-based ML automated treatment planning model using reference MR RT treatment plans (42.7 Gy in 7 fractions) from 46 patients with prostate cancer previously treated at our institution. For a held-out test set of 38 patients, retrospectively generated ML RT plans were compared to clinical human-generated adaptive RT plans for all 266 fractions. Differences in dose-volume metrics and clinical objective pass rates were evaluated using Wilcoxon tests (p &lt; 0.05) and Exact McNemar tests (p &lt; 0.05), respectively.</p></div><div><h3>Results</h3><p>Compared to clinical RT plans, ML RT plans significantly increased sparing and objective pass rates of the rectum, bladder, and left femur. The mean ± standard deviation of rectum D20 and D50 in ML RT plans were 2.5 ± 2.2 Gy and 1.6 ± 1.3 Gy lower than clinical RT plans, respectively, with 14 % higher pass rates; bladder D40 was 4.6 ± 2.9 Gy lower with a 20 % higher pass rate; and the left femur D5 was 0.8 ± 1.8 Gy lower with a 7 % higher pass rate.</p></div><div><h3>Conclusions</h3><p>ML automated RT treatment plan adaptation increases robustness to interfractional anatomical changes compared to current clinical adaptive RT practices by increasing compliance to treatment objectives.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100649"},"PeriodicalIF":3.4,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001192/pdfft?md5=2171029966e3c5a6468365da4d535bfd&pid=1-s2.0-S2405631624001192-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239969","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":"Autodelineation methods in a simulated fully automated proton therapy workflow for esophageal cancer","authors":"Pieter Populaire ,&nbsp;Beatrice Marini ,&nbsp;Kenneth Poels ,&nbsp;Stina Svensson ,&nbsp;Edmond Sterpin ,&nbsp;Albin Fredriksson ,&nbsp;Karin Haustermans","doi":"10.1016/j.phro.2024.100646","DOIUrl":"10.1016/j.phro.2024.100646","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Proton Online Adaptive RadioTherapy (ProtOnART) harnesses the dosimetric advantage of protons and immediately acts upon anatomical changes. Here, we simulate the clinical application of delineation and planning within a ProtOnART-workflow for esophageal cancer. We aim to identify the most appropriate technique for autodelineation and evaluate full automation by replanning on autodelineated contours.</div></div><div><h3>Materials and methods</h3><div>We evaluated 15 patients who started treatment between 11-2022 and 01-2024, undergoing baseline and three repeat computed tomography (CT) scans in treatment position. Quantitative and qualitative evaluations compared different autodelineation methods. For Organs-at-risk (OAR) deep learning segmentation (DLS), rigid and deformable propagation from baseline to repeat CT-scans were considered. For the clinical target volume (CTV), rigid and three deformable propagation methods (default, heart as controlling structure and with focus region) were evaluated. Adaptive treatment plans with 7 mm (ATP_7mm) and 3 mm (ATP_3mm) setup robustness were generated using best-performing autodelineated contours. Clinical acceptance of ATPs was evaluated using goals encompassing ground-truth CTV-coverage and OAR-dose.</div></div><div><h3>Results</h3><div>Deformation was preferred for autodelineation of heart, lungs and spinal cord. DLS was preferred for all other OARs. For CTV, deformation with focus region was the preferred method although the difference with other deformation methods was small. Nominal ATPs passed evaluation goals for 87 % of ATP_7mm and 67 % of ATP_3mm. This dropped to respectively 2 % and 29 % after robust evaluation. Insufficient CTV-coverage was the main reason for ATP-rejection.</div></div><div><h3>Conclusion</h3><div>Autodelineation aids a ProtOnART-workflow for esophageal cancer. Currently available tools regularly require manual annotations to generate clinically acceptable ATPs.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100646"},"PeriodicalIF":3.4,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001167/pdfft?md5=1b1eb557e68831ef41fd49ccf36d36d0&pid=1-s2.0-S2405631624001167-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314571","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":"Tools and recommendations for commissioning and quality assurance of deformable image registration in radiotherapy","authors":"Lando S. Bosma ,&nbsp;Mohammad Hussein ,&nbsp;Michael G. Jameson ,&nbsp;Soban Asghar ,&nbsp;Kristy K. Brock ,&nbsp;Jamie R. McClelland ,&nbsp;Sara Poeta ,&nbsp;Johnson Yuen ,&nbsp;Cornel Zachiu ,&nbsp;Adam U. Yeo ,&nbsp;the 2021 ESTRO Physics Workshop on Commissioning and Quality Assurance for Deformable Image Registration in Radiotherapy","doi":"10.1016/j.phro.2024.100647","DOIUrl":"10.1016/j.phro.2024.100647","url":null,"abstract":"<div><p>Multiple tools are available for commissioning and quality assurance of deformable image registration (DIR), each with their own advantages and disadvantages in the context of radiotherapy. The selection of appropriate tools should depend on the DIR application with its corresponding available input, desired output, and time requirement. Discussions were hosted by the ESTRO Physics Workshop 2021 on Commissioning and Quality Assurance for DIR in Radiotherapy. A consensus was reached on what requirements are needed for commissioning and quality assurance for different applications, and what combination of tools is associated with this.</p><p>For commissioning, we recommend the target registration error of manually annotated anatomical landmarks or the distance-to-agreement of manually delineated contours to evaluate alignment. These should be supplemented by the distance to discordance and/or biomechanical criteria to evaluate consistency and plausibility. Digital phantoms can be useful to evaluate DIR for dose accumulation but are currently only available for a limited range of anatomies, image modalities and types of deformations.</p><p>For quality assurance of DIR for contour propagation, we recommend at least a visual inspection of the registered image and contour. For quality assurance of DIR for warping quantitative information such as dose, Hounsfield units or positron emission tomography-data, we recommend visual inspection of the registered image together with image similarity to evaluate alignment, supplemented by an inspection of the Jacobian determinant or bending energy to evaluate plausibility, and by the dose (gradient) to evaluate relevance. We acknowledge that some of these metrics are still missing in currently available commercial solutions.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100647"},"PeriodicalIF":3.4,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001179/pdfft?md5=117e12fc4f59df7add1108a1a3c70176&pid=1-s2.0-S2405631624001179-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239968","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":"Monte Carlo-based simulation of virtual 3 and 4-dimensional cone-beam computed tomography from computed tomography images: An end-to-end framework and a deep learning-based speedup strategy","authors":"Frederic Madesta ,&nbsp;Thilo Sentker ,&nbsp;Clemens Rohling ,&nbsp;Tobias Gauer ,&nbsp;Rüdiger Schmitz ,&nbsp;René Werner","doi":"10.1016/j.phro.2024.100644","DOIUrl":"10.1016/j.phro.2024.100644","url":null,"abstract":"<div><h3><strong>Background and purpose:</strong></h3><div>In radiotherapy, precise comparison of fan-beam computed tomography (CT) and cone-beam CT (CBCT) arises as a commonplace, yet intricate task. This paper proposes a publicly available end-to-end pipeline featuring an intrinsic deep-learning-based speedup technique for generating virtual 3D and 4D CBCT from CT images.</div></div><div><h3><strong>Materials and methods:</strong></h3><div>Physical properties, derived from CT intensity information, are obtained through automated whole-body segmentation of organs and tissues. Subsequently, Monte Carlo (MC) simulations generate CBCT X-ray projections for a full circular arc around the patient employing acquisition settings matched with a clinical CBCT scanner (modeled according to Varian TrueBeam specifications). In addition to 3D CBCT reconstruction, a 4D CBCT can be simulated with a fully time-resolved MC simulation by incorporating respiratory correspondence modeling. To address the computational complexity of MC simulations, a deep-learning-based speedup technique is developed and integrated that uses projection data simulated with a reduced number of photon histories to predict a projection that matches the image characteristics and signal-to-noise ratio of the reference simulation.</div></div><div><h3><strong>Results:</strong></h3><div>MC simulations with default parameter setting yield CBCT images with high agreement to ground truth data acquired by a clinical CBCT scanner. Furthermore, the proposed speedup technique achieves up to 20-fold speedup while preserving image features and resolution compared to the reference simulation.</div></div><div><h3><strong>Conclusion:</strong></h3><div>The presented MC pipeline and speedup approach provide an openly accessible end-to-end framework for researchers and clinicians to investigate limitations of image-guided radiation therapy workflows built on both (4D) CT and CBCT images.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100644"},"PeriodicalIF":3.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405631624001143/pdfft?md5=a2ef1733dec9a86dd7b884c1ab4db9d1&pid=1-s2.0-S2405631624001143-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311512","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":"Cherenkov imaging combined with scintillation dosimetry provides real-time positional and dose monitoring for radiotherapy patients with cardiac implanted electronic devices","authors":"Savannah M. Decker ,&nbsp;Allison L. Matous ,&nbsp;Rongxiao Zhang ,&nbsp;David J. Gladstone ,&nbsp;Evan K. Grove ,&nbsp;Benjamin B. Williams ,&nbsp;Michael Jermyn ,&nbsp;Shauna McVorran ,&nbsp;Lesley A. Jarvis","doi":"10.1016/j.phro.2024.100642","DOIUrl":"10.1016/j.phro.2024.100642","url":null,"abstract":"<div><h3>Background and purpose</h3><p>Cardiac implanted electronic devices (CIED) require dose monitoring during each fraction of radiotherapy, which can be time consuming and may have delayed read-out times. This study explores the potential of Cherenkov imaging combined with scintillation dosimetry as an alternative verification system.</p></div><div><h3>Methods and materials</h3><p>Time-gated, complementary metal–oxide–semiconductor (iCMOS) cameras were used to collect video images of anthropomorphic phantoms and patients undergoing radiation treatment near chest wall cardiac devices. Scintillator discs and optically stimulated luminescence dosimeters (OSLDs) were used for dose measurement. Accuracy of spatial delivery was assessed by overlaying predicted surface dose outlines derived from the treatment planning system (TPS) with the Cherenkov images. Dose measurements from OSLDs and scintillators were compared.</p></div><div><h3>Results</h3><p>In phantom studies, Cherenkov images visibly indicated when dose was delivered to the CIED as compared to non-overlapping dose deliveries. Comparison with dose overlays revealed congruence at the planned position and non-congruence when the phantom was shifted from the initial position. Absolute doses derived from scintillator discs aligned well with the OSLD measurements and TPS predictions for three different positions, measuring within 10 % for in-field positions and within 5 % for out-of-field positions. For two patients with CIEDs imaged over 18 fractions, Cherenkov imaging confirmed positional accuracy for all fractions, and dose measured by scintillator discs deviated by &lt;0.015 Gy from the OSLD measurements.</p></div><div><h3>Conclusions</h3><p>Cherenkov imaging combined with scintillation dosimetry presents an alternative methodology for CIED monitoring with the added benefit of instantly detecting deviations, enabling timely corrective actions or proper patient triage.</p></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100642"},"PeriodicalIF":3.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S240563162400112X/pdfft?md5=bcc54fe1b2a9adcb0173fd6499217ee7&pid=1-s2.0-S240563162400112X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232134","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}