Medical physics最新文献

{"title":"List of Advertisers","authors":"","doi":"10.1002/mp.15751","DOIUrl":"https://doi.org/10.1002/mp.15751","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 8","pages":"5836"},"PeriodicalIF":3.2,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.15751","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility study of photon-counting CT for material identification based on YSO/SiPM detector: A proof of concept","authors":"Du Zhang, Bin Wu, Daoming Xi, Rui Chen, Peng Xiao, Qingguo Xie","doi":"10.1002/mp.17341","DOIUrl":"10.1002/mp.17341","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Current photon-counting computed tomography (CT) systems utilize semiconductor detectors, such as cadmium telluride (CdTe), cadmium zinc telluride (CZT), and silicon (Si), which convert x-ray photons directly into charge pulses. An alternative approach is indirect detection, which involves Yttrium Orthosilicate (YSO) scintillators coupled with silicon photomultipliers (SiPMs). This presents an attractive and cost-effective option due to its low cost, high detection efficiency, low dark count rate, and high sensor gain.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study aims to establish a comprehensive quantitative imaging framework for three-energy-bin proof-of-concept photon-counting CT based on YSO/SiPM detectors developed in our group using multi-voltage threshold (MVT) digitizers and assess the feasibility of this spectral CT for material identification.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We developed a proof-of-concept YSO/SiPM-based benchtop spectral CT system and established a pipeline for three-energy-bin photon-counting CT projection-domain processing. The empirical A-table method was employed for basis material decomposition, and the quantitative imaging performance of the spectral CT system was assessed. This evaluation included the synthesis errors of virtual monoenergetic images, electron density images, effective atomic number images, and linear attenuation coefficient curves. The validity of employing A-table methods for material identification in three-energy-bin spectral CT was confirmed through both simulations and experimental studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In both noise-free and noisy simulations, the thickness estimation experiments and quantitative imaging results demonstrated high accuracy. In the thickness estimation experiment using the practical spectral CT system, the mean absolute error for the estimated thickness of the decomposed Al basis material was 0.014 ± 0.010 mm, with a mean relative error of 0.66% ± 0.42%. Similarly, for the decomposed polymethyl methacrylate (PMMA) basis material, the mean absolute error in thickness estimation was 0.064 ± 0.058 mm, with a mean relative error of 0.70% ± 0.38%. Additionally, employing the equivalent thickness of the basis material allowed for accurate synthesis of 70 keV virtual monoenergetic images (relative error 1.85% ± 1.26%), electron density (relative error 1.81% ± 0.97%), and effective atomic number (relative error 2.64% ± 1.26%) of the tested materials. In addition, the average synthesis error of the linear attenuation coefficient curves in the energy range from 40 to 15","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8151-8167"},"PeriodicalIF":3.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17341","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141972447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing prostate cancer segmentation on multiparametric magnetic resonance imaging with background information and gland masks","authors":"Lei Wang,&nbsp;Rong Sun,&nbsp;Xiaobin Wei,&nbsp;Jie Chen,&nbsp;Shouqiang Jia,&nbsp;Guangyu Wu,&nbsp;Shengdong Nie","doi":"10.1002/mp.17346","DOIUrl":"10.1002/mp.17346","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The landscape of prostate cancer (PCa) segmentation within multiparametric magnetic resonance imaging (MP-MRI) was fragmented, with a noticeable lack of consensus on incorporating background details, culminating in inconsistent segmentation outputs. Given the complex and heterogeneous nature of PCa, conventional imaging segmentation algorithms frequently fell short, prompting the need for specialized research and refinement.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study sought to dissect and compare various segmentation methods, emphasizing the role of background information and gland masks in achieving superior PCa segmentation. The goal was to systematically refine segmentation networks to ascertain the most efficacious approach.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A cohort of 232 patients (ages 61–73 years old, prostate-specific antigen: 3.4–45.6 ng/mL), who had undergone MP-MRI followed by prostate biopsies, was analyzed. An advanced segmentation model, namely Attention-Unet, which combines U-Net with attention gates, was employed for training and validation. The model was further enhanced through a multiscale module and a composite loss function, culminating in the development of Matt-Unet. Performance metrics included Dice Similarity Coefficient (DSC) and accuracy (ACC).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The Matt-Unet model, which integrated background information and gland masks, outperformed the baseline U-Net model using raw images, yielding significant gains (DSC: 0.7215 vs. 0.6592; ACC: 0.8899 vs. 0.8601, <i>p </i>&lt; 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A targeted and practical PCa segmentation method was designed, which could significantly improve PCa segmentation on MP-MRI by combining background information and gland masks. The Matt-Unet model showcased promising capabilities for effectively delineating PCa, enhancing the precision of MP-MRI analysis.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8179-8191"},"PeriodicalIF":3.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141972445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of capturing vessel expansion with 4D-CTA: Phantom study to determine reproducibility, spatial and temporal resolution","authors":"Sabine M. L. Linden,&nbsp;Lotte B. Stam,&nbsp;René Aquarius,&nbsp;Alessa Hering,&nbsp;Chris L. de Korte,&nbsp;Mathias Prokop,&nbsp;Hieronymus D. Boogaarts,&nbsp;Frederick J. A. Meijer,&nbsp;Luuk J. Oostveen","doi":"10.1002/mp.17348","DOIUrl":"10.1002/mp.17348","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Dynamic Computed Tomography Angiography (4D CTA) has the potential of providing insight into the biomechanical properties of the vessel wall, by capturing motion of the vessel wall. For vascular pathologies, like intracranial aneurysms, this could potentially refine diagnosis, prognosis, and treatment decision-making.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The objective of this research is to determine the feasibility of a 4D CTA scanner for accurately measuring harmonic diameter changes in an in-vitro simulated vessel.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A silicon tube was exposed to a simulated heartbeat. Simulated heart rates between 40 and 100 beats-per-minute (bpm) were tested and the flow amplitude was varied, resulting in various changes of tube diameter. A 320-detector row CT system with ECG-gating captured three consecutive cycles of expansion. Image registration was used to calculate the diameter change. A vascular echography set-up was used as a reference, using a 9 MHz linear array transducer. The reproducibility of 4D CTA was represented by the Pearson correlation (&lt;i&gt;r&lt;/i&gt;) between the three consecutive diameter change patterns, captured by 4D CTA. The peak value similarity (pvs) was calculated between the 4D CTA and US measurements for increasing frequencies and was chosen as a measure of temporal resolution. Spatial resolution was represented by the Sum of the Relative Percentual Difference (SRPD) between 4D CTA and US diameter change patterns for increasing amplitudes.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The reproducibility of 4D CTA measurements was good (&lt;i&gt;r&lt;/i&gt; ≥ 0.9) if the diameter change was larger than 0.3 mm, moderate (0.7 ≤ &lt;i&gt;r&lt;/i&gt; &lt; 0.9) if the diameter change was between 0.1 and 0.3 mm, and low (&lt;i&gt;r&lt;/i&gt; &lt; 0.7) if the diameter change was smaller than 0.1 mm. Regarding the temporal resolution, the amplitude of 4D CTA was similar to the US measurements (pvs ≥ 90%) for the frequencies of 40 and 50 bpm. Frequencies between 60 and 80 bpm result in a moderate similarity (70% ≤ pvs &lt; 90%). A low similarity (pvs &lt; 70%) is observed for 90 and 100 bpm. Regarding the spatial resolution, diameter changes above 0.30 mm result in SRPDs consistently below 50%.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In a phantom setting, 4D CTA can be used to reliably capture reproducible tube diameter changes exceeding 0.30 mm. Low pulsation frequencies (40 or 50","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 10","pages":"7171-7179"},"PeriodicalIF":3.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17348","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141972446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning models for separate segmentations of intracerebral and intraventricular hemorrhage on head CT and segmentation quality assessment","authors":"Yifan Li,&nbsp;Ruijie Zhang,&nbsp;Ying Li,&nbsp;Xinbing Zuo,&nbsp;Qian Wang,&nbsp;Shicai Zhang,&nbsp;Xiankai Huo,&nbsp;Zhenhe Liu,&nbsp;Quan Zhang,&nbsp;Meng Liang","doi":"10.1002/mp.17343","DOIUrl":"10.1002/mp.17343","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The volume measurement of intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) provides critical information for precise treatment of patients with spontaneous ICH but remains a big challenge, especially for IVH segmentation. However, the previously proposed ICH and IVH segmentation tools lack external validation and segmentation quality assessment.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study aimed to develop a robust deep learning model for the segmentation of ICH and IVH with external validation, and to provide quality assessment for IVH segmentation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In this study, a Residual Encoding Unet (REUnet) for the segmentation of ICH and IVH was developed using a dataset composed of 977 CT images (all contained ICH, and 338 contained IVH; a five-fold cross-validation procedure was adopted for training and internal validation), and externally tested using an independent dataset consisting of 375 CT images (all contained ICH, and 105 contained IVH). The performance of REUnet was compared with six other advanced deep learning models. Subsequently, three approaches, including Prototype Segmentation (ProtoSeg), Test Time Dropout (TTD), and Test Time Augmentation (TTA), were employed to derive segmentation quality scores in the absence of ground truth to provide a way to assess the segmentation quality in real practice.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;For ICH segmentation, the median (lower-quantile—upper quantile) of Dice scores obtained from REUnet were 0.932 (0.898–0.953) for internal validation and 0.888 (0.859–0.916) for external test, both of which were better than those of other models while comparable to that of nnUnet3D in external test. For IVH segmentation, the Dice scores obtained from REUnet were 0.826 (0.757–0.868) for internal validation and 0.777 (0.693–0.827) for external tests, which were better than those of all other models. The concordance correlation coefficients between the volumes estimated from the REUnet-generated segmentations and those from the manual segmentations for both ICH and IVH ranged from 0.944 to 0.987. For IVH segmentation quality assessment, the segmentation quality score derived from ProtoSeg was correlated with the Dice Score (Spearman &lt;i&gt;r&lt;/i&gt; = 0.752 for the external test) and performed better than those from TTD (Spearman &lt;i&gt;r&lt;/i&gt; = 0.718) and TTA (Spearman &lt;i&gt;r&lt;/i&gt; = 0.260) in the external test. By setting a threshold to the segmentation quality score, we were able to identify low-quality IVH segmentation results by ProtoSeg.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8317-8333"},"PeriodicalIF":3.2,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141972507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI","authors":"Brendan M. Whelan,&nbsp;Paul Z. Y. Liu,&nbsp;Shanshan Shan,&nbsp;David E. J. Waddington,&nbsp;Bin Dong,&nbsp;Michael G. Jameson,&nbsp;Paul J. Keall","doi":"10.1002/mp.17342","DOIUrl":"10.1002/mp.17342","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Geometric distortion is a serious problem in MRI, particularly in MRI guided therapy. A lack of affordable and adaptable tools in this area limits research progress and harmonized quality assurance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To develop and test a suite of open-source hardware and software tools for the measurement, characterization, reporting, and correction of geometric distortion in MRI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An open-source python library was developed, comprising modules for parametric phantom design, data processing, spherical harmonics, distortion correction, and interactive reporting. The code was used to design and manufacture a distortion phantom consisting of 618 oil filled markers covering a sphere of radius 150 mm. This phantom was imaged on a CT scanner and a novel split-bore 1.0 T MRI magnet. The CT images provide distortion-free dataset. These data were used to test all modules of the open-source software.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>All markers were successfully extracted from all images. The distorted MRI markers were mapped to undistorted CT data using an iterative search approach. Spherical harmonics reconstructed the fitted gradient data to 1.0 ± 0.6% of the input data. High resolution data were reconstructed via spherical harmonics and used to generate an interactive report. Finally, distortion correction on an independent data set reduced distortion inside the DSV from 5.5 ± 3.1 to 1.6 ± 0.8 mm.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI have been developed. The utility of these tools has been demonstrated via their application on a novel 1.0 T split bore magnet.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8399-8410"},"PeriodicalIF":3.2,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17342","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141904066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technical note: Determination of \u0000 \u0000 \u0000 C\u0000 Q\u0000 \u0000 $C_{Q}$\u0000 for a miniature x-ray source using a soft x-ray ionization chamber calibrated in NIST reference beam qualities","authors":"Peter G. F. Watson,&nbsp;Stephen Davis,&nbsp;Wesley S. Culberson","doi":"10.1002/mp.17345","DOIUrl":"10.1002/mp.17345","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;Q&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;$C_Q$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; formalism proposed by Watson et al. allows users of the INTRABEAM (Carl Zeiss Medical AG, Jena, Germany) electronic brachytherapy system to accurately determine the absorbed dose to water, in the absence of a primary dosimetry standard. However, all published &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;Q&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;$C_Q$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; values are for PTW 34013 ionization chambers calibrated in a TW30 reference beam, traceable to PTB (Germany). For North American users, it would be advantageous to have &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;Q&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;$C_Q$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; data for chambers calibrated in a kV reference beam maintained by the National Institute of Standards and Technology (NIST).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In this work, we determine &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;Q&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;$C_Q$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; for a PTW 34013 chamber calibrated in three NIST-traceable reference beams: M30, L40, and L50.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using available photon spectra data for M30, L40, and L50 reference beam qualities, Monte Carlo simulations using EGSnrc were performed to calculate the ratio of the absorbed dose to the PTW 34013 chamber air cavity to air-kerma (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;D&lt;/mi&gt;\u0000 &lt;mi&gt;gas&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;/&lt;/mo&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;K&lt;/mi&gt;\u0000 &lt;mi&gt;a&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$D_{text","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8597-8601"},"PeriodicalIF":3.2,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17345","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based dose prediction for magnetic resonance-guided prostate radiotherapy","authors":"Samuel Fransson,&nbsp;Robin Strand,&nbsp;David Tilly","doi":"10.1002/mp.17312","DOIUrl":"10.1002/mp.17312","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Daily adaptive radiotherapy, as performed with the Elekta Unity MR-Linac, requires choosing between different adaptation methods, namely ATP (Adapt to Position) and ATS (Adapt to Shape), where the latter requires daily re-contouring to obtain a dose plan tailored to the daily anatomy. These steps are inherently resource-intensive, and quickly predicting the dose distribution and the dosimetric evaluation criteria while the patient is on the table could facilitate a fast selection of adaptation method and decrease the treatment times.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In this work, we aimed to develop a deep-learning-based dose-prediction pipeline for prostate MR-Linac treatments.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Two hundred twelve MR-images, structure sets, and dose distributions from 35 prostate patients treated with 6.1 Gy for 7 or 6 fractions at our MR-Linac were included, split into train/test partitions of 152/60 images, respectively. A deep-learning segmentation network was trained to segment the CTV (prostate), bladder, and rectum. A second network was trained to predict the dose distribution based on manually delineated structures. At inference, the predicted segmentations acted as input to the dose prediction network, and the predicted dose was compared to the true (optimized in the treatment planning system) dose distribution.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Median DSC values from the segmentation network were 0.90/0.94/0.87 for CTV/bladder/rectum. Predicted segmentations as input to the dose prediction resulted in mean differences between predicted and true doses of 0.7%/0.7%/1.7% (relative to the prescription dose) for &lt;i&gt;D&lt;/i&gt;&lt;sub&gt;98%&lt;/sub&gt;/&lt;i&gt;D&lt;/i&gt;&lt;sub&gt;95%&lt;/sub&gt;/&lt;i&gt;D&lt;/i&gt;&lt;sub&gt;2%&lt;/sub&gt; for the CTV. For the bladder, the difference was 0.7%/0.3% for &lt;i&gt;D&lt;/i&gt;&lt;sub&gt;mean&lt;/sub&gt;&lt;i&gt;/D&lt;/i&gt;&lt;sub&gt;2%&lt;/sub&gt; and for the rectum 0.1/0.2/0.2 pp (percentage points) for &lt;i&gt;V&lt;/i&gt;&lt;sub&gt;33Gy&lt;/sub&gt;/&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;38Gy&lt;/sub&gt;/&lt;i&gt;V&lt;/i&gt;&lt;sub&gt;41Gy&lt;/sub&gt;. In comparison, true segmentations as input resulted in differences of 1.1%/0.9%/1.6% for CTV, 0.5%/0.4% for bladder, and 0.7/0.4/0.3 pp for the rectum. Only &lt;i&gt;D&lt;/i&gt;&lt;sub&gt;2%&lt;/sub&gt; for CTV and &lt;i&gt;D&lt;/i&gt;&lt;sub&gt;mean&lt;/sub&gt;/&lt;i&gt;D&lt;/i&gt;&lt;sub&gt;2%&lt;/sub&gt; for bladder were found to be statistically significantly better when using true structures instead of predicted structures as input to the dose prediction.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Sma","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 11","pages":"8087-8095"},"PeriodicalIF":3.2,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17312","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technical note: Phantom-based evaluation of CBCT dose calculation accuracy for use in adaptive radiotherapy","authors":"Claas Wessels,&nbsp;Adam Strzelecki,&nbsp;Mathieu Plamondon,&nbsp;Mathias Lehmann,&nbsp;Igor Peterlik,&nbsp;Pascal Paysan,&nbsp;Balazs Nagy,&nbsp;Alexander Heinz,&nbsp;Dieter Seghers,&nbsp;Stephen Thompson,&nbsp;Stefan G. Scheib","doi":"10.1002/mp.17325","DOIUrl":"10.1002/mp.17325","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>High-quality 3D-anatomy of the day is needed for treatment plan adaptation in radiotherapy. For online x-ray-based CBCT workflows, one approach is to create a synthetic CT or to utilize a fan-beam CT with corresponding registrations. The former potentially introduces uncertainties in the dose calculation if deformable image registration is used. The latter can introduce burden and complexity to the process, the facility, and the patient.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Using the CBCT of the day, acquired on the treatment device, for direct dose calculation and plan adaptation can overcome these limitations. This study aims to assess the accuracy of the calculated dose on the CBCT scans acquired on a Halcyon linear accelerator equipped with HyperSight.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>HyperSight's new CBCT reconstruction algorithm includes improvements in scatter correction, HU calibration of the imager, and beam shape adaptation. Furthermore, HyperSight introduced a new x-ray detector. To show the effect of the implemented improvements, gamma comparisons of 2%/2 mm, 2%/1 mm, and 1%/1 mm were made between the dose distribution in phantoms calculated on the CBCT reconstructions and the simulation CT scans, considering this the standard of care. The resulting gamma passing rates were compared to those obtained with the Halcyon 3.0 reconstruction and hardware without HyperSight's technologies. Various anatomical phantoms for dosimetric evaluations on brain, head and neck, lung, breast, and prostate cases have been used in this study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The overall results demonstrated that HyperSight outperformed the Halcyon 3.0 version. Based on the gamma analysis, the calculated dose using HyperSight was closer to the CT scan-based doses than the calculated dose using iCBCT Halcyon 3.0 for most cases. Over all plans and gamma criteria, Halcyon 3.0 achieved an average passing rate of 92.9%, whereas HyperSight achieved 98.1%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Using HyperSight CBCT images for direct dose calculation, for example, in (online) plan adaptation, seems feasible for the investigated cases.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 10","pages":"7492-7499"},"PeriodicalIF":3.2,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141891447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of hydrogen peroxide production in pure water: Ultrahigh versus conventional dose-rate irradiation and mechanistic insights","authors":"Tengda Zhang,&nbsp;Christina Stengl,&nbsp;Larissa Derksen,&nbsp;Kristaps Palskis,&nbsp;Konstantinos Koritsidis,&nbsp;Klemens Zink,&nbsp;Sebastian Adeberg,&nbsp;Gerald Major,&nbsp;David Weishaar,&nbsp;Ulrike Theiß,&nbsp;Jing Jin,&nbsp;Maria Francesca Spadea,&nbsp;Elpida Theodoridou,&nbsp;Jürgen Hesser,&nbsp;Kilian-Simon Baumann,&nbsp;Joao Seco","doi":"10.1002/mp.17335","DOIUrl":"10.1002/mp.17335","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Ultrahigh dose-rate radiation (UHDR) produces less hydrogen peroxide (H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt;) in pure water, as suggested by some experimental studies, and is used as an argument for the validity of the theory that FLASH spares the normal tissue due to less reactive oxygen species (ROS) production. In contrast, most Monte Carlo simulation studies suggest the opposite.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We aim to unveil the effect of UHDR on H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt; production in pure water and its underlying mechanism, to serve as a benchmark for Monte Carlo simulation. We hypothesized that the reaction of solvated electrons (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msubsup&gt;\u0000 &lt;mi&gt;e&lt;/mi&gt;\u0000 &lt;mi&gt;aq&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;/msubsup&gt;\u0000 &lt;annotation&gt;${mathrm{e}}_{{mathrm{aq}}}^ - $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) removing hydroxyl radicals (•OH), the precursor of H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt;, is the reason why UHDR leads to a lower G-value (molecules/100 eV) for H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt; (G[H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt;]), because: 1, the third-order reaction between &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msubsup&gt;\u0000 &lt;mi&gt;e&lt;/mi&gt;\u0000 &lt;mi&gt;aq&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;/msubsup&gt;\u0000 &lt;annotation&gt;${mathrm{e}}_{{mathrm{aq}}}^ - $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and •OH is more sensitive to increased instantaneous ROS concentration by UHDR than a two-order reaction of •OH self-reaction producing H&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;2&lt;/sub&gt;; 2, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msubsup&gt;\u0000 &lt;mi&gt;e&lt;/mi&gt;\u0000 &lt;mi&gt;aq&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;/msubsup&gt;\u0000 &lt;annotation&gt;${mathrm{e}}_{{mathrm{aq}}}^ - $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; has two times higher diffusion coefficient and higher reaction rate constant than that of •OH, which means &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msubsup&gt;\u0000 &lt;mi&gt;e&lt;/mi&gt;\u0000 &lt;mi&gt;aq&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;/msubsup&gt;\u0000 &lt;annotation&gt;${mathrm{e}}_{{mathrm{aq}}}^ - $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; would dominate the competition for •OH and benefit more from the inter-track effect of UHDR. Meanwhile, we also experimentally verify the","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"51 10","pages":"7439-7452"},"PeriodicalIF":3.2,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17335","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141877039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}