Medical physics最新文献

{"title":"A novel direct-indirect dual-layer flat-panel detector for contrast-enhanced breast imaging: Monte Carlo simulation","authors":"Xiaoyu Duan, Hailiang Huang, Wei Zhao","doi":"10.1002/mp.18122","DOIUrl":"10.1002/mp.18122","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Contrast-enhanced digital mammography (CEDM) and contrast-enhanced digital breast tomosynthesis (CEDBT) utilize weighted subtraction of low-energy (LE) and high-energy (HE) images to highlight breast lesions with iodine uptake. Typically, LE and HE images are acquired with two separate exposures, with intervals up to 10 s for CEDM and longer for CEDBT. Patient motion during these intervals can lead to incomplete subtraction of normal breast structures in recombined dual-energy (DE) images. The residual tissue structure masks lesions, distorts lesion margins, and reduces contrast enhancement– thus degrading diagnostic accuracy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study introduces a novel direct-indirect dual-layer flat-panel detector (DI-DLFPD) to eliminate the effect of patient motion by acquiring LE and HE images simultaneously. The proposed DI-DLFPD system consists of a silver (Ag) x-ray filter at the tube port, a 200 µm direct conversion amorphous selenium (a-Se) front layer (FL) detector, and a 400 µm indirect conversion cesium iodide (CsI) back layer (BL) detector. We validated the DI-DLFPD design using Monte Carlo simulations, assessing iodine objects detectability in CEDM images across different system designs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Simulations were generated with a digital phantom mimicking a 4-cm thick breast with 25 % glandularity. Cylindrical iodinated objects with 5-mm size in diameter and height were embedded with 1, 2, 3, and 5 mg/ml iodine concentration. A 5-mm cubic was designed as glandular tissue inside the phantom to evaluate the background cancellation in DE subtracted images. Four imaging scenarios (A–D) were Monte Carlo simulated with different configurations of the x-ray filter and FL and BL detectors. Post-imaging processing, including image registration and modulation transfer function matching, was conducted. Besides, an analytical method for generating virtual FL-LE images was introduced to further improve the iodine detectability in the DE subtracted image. The signal difference to noise ratio (<span></span><math>\u0000 <semantics>\u0000 <msub>\u0000 <mi>SDNR</mi>\u0000 <mi>mean</mi>\u0000 </msub>\u0000 <annotation>${mathrm{SDNR}}_{{mathrm{mean}}}$</annotation>\u0000 </semantics></math>) of iodinated objects in DE images served as the figure of merit for quantitative comparison.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The proposed DI-DLFPD configuration outperformed all other scenarios in DE image quality, effectivel","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038320","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":"An adaptive proton FLASH therapy using modularized pin ridge filter","authors":"Ahmal Jawad Zafar,&nbsp;Xiaofeng Yang,&nbsp;Zachary Diamond,&nbsp;Tian Sibo,&nbsp;David Yu,&nbsp;Pretesh R. Patel,&nbsp;Jun Zhou","doi":"10.1002/mp.18109","DOIUrl":"10.1002/mp.18109","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In our previous study, we developed a modular pin ridge filter (pRF) design framework to streamline assembly, enabling the fast manufacture of custom filters optimized for single-energy proton FLASH planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>In this paper, we propose a method to optimize adaptive proton FLASH therapy (ADP-FLASH) using modularized pRFs by recycling module pins from the initial plan while reducing pRF adjustments in adaptive FLASH planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Initially, single energy (250 MeV) FLASH-pRF plans were created using pencil beam directions (PBDs) from initial IMPT plans on the planning CT (pCT). PBDs are classified as new/changed (Δ<i>E</i> &gt; 5 MeV) or unchanged by comparing spot maps for targets between pCT and re-CT. We used an iterative least-square regression model to identify recyclable PBDs with minimal relative changes to spot MU weighting. Two PBDs with the least square error were retrieved per iteration and added to the background plan, and the remaining PBDs were reoptimized for the adaptive plan in subsequent iterations. The method was validated on three liver SBRT cases (50 Gy in five fractions) by comparing various dosimetric parameters across initial pRF plans on pCT, re-CT, and the ADP-FLASH-pRF plans on re-CT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>V₁₀₀ for initial-pRF plans on pCT, re-CT, and ADP-FLASH-pRF plans for the three cases were as follows: (93.7%, 89.2%, 91.4%), (93.5%, 60.2%, 91.7%), and (97.3%, 69.9%, 98.8%). We observe a decline in plan quality when applying the initial pRF to the re-CT, whereas the ADP-FLASH-pRF approach restores quality comparable to the initial pRF on the pCT. FLASH effect of the initial pRF and ADP pRF plans were evaluated with a dose and dose rate threshold of 1 and 40 Gy/s, respectively, using the FLASH effectiveness model. The proposed method recycled 91.2%, 71%, and 64.7% of PBDs from initial pRF plans for the three cases while maintaining all clinical goals and preserving FLASH effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study validated a method for recycling the pRFs in single-energy proton FLASH planning for SBRT cases. This framework offers a scalable solution for adaptive proton therapy, balancing clinical effectiveness and practicality.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038162","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":"Quantitative ultrasound moment-based double Nakagami distribution method","authors":"Ladan Yazdani,&nbsp;Cameron Hoerig,&nbsp;Tadashi Yamaguchi,&nbsp;Kazuki Tamura,&nbsp;Jonathan Mamou,&nbsp;Jeffrey A. Ketterling","doi":"10.1002/mp.18116","DOIUrl":"10.1002/mp.18116","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;Ultrasound imaging is a valuable diagnostic tool, but quantifying tissue characteristics can be challenging. While models like the Nakagami distribution help characterize tissue microstructure based on envelope statistics, they may not fully capture the complexity of tissues with multiple scatterer types.&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 aims to develop and validate an enhanced version of the Double Nakagami Distribution (DND) model using moment equations for quantitative ultrasound imaging. We seek to establish its theoretical foundation and demonstrate its effectiveness through numerical simulations and experimental results.&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;Five versions of the DND estimation model were developed to compute the five associated model parameters. Using the method of moments, the estimators directly computed 5, 4, or 3 DND parameters with any remaining parameters derived from statistical relationships. After selecting the initial solution for the DND methods, Monte Carlo simulations were employed to generate random combinations of Nakagami parameters within two-scatterer media. For experimental validation, four phantoms with different mixtures of nylon and acrylic scatterers were used. Ex vivo validations were conducted using radio-frequency data from four excised fatty rat livers, each exhibiting low and high concentrations of fat droplets. The median and interquartile range of error values from numerical simulations were analyzed, and the Kruskal–Wallis test was used to assess statistical differences, with post hoc Dunn tests with Bonferroni correction for pairwise comparisons. Effect sizes were calculated using Cohen's &lt;i&gt;d&lt;/i&gt; to quantify improvements in fitting performance.&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 DND estimation model with three parameter estimations demonstrated the least computation time (&lt;i&gt;p &lt;/i&gt;&lt; 0.05) and was identified as the most robust of the proposed DND models for further assessments. In simulations with 10&lt;sup&gt;6&lt;/sup&gt; independents, identically distributed random data points, the errors of all five DND parameters remained below 5%. Our results indicated that increasing the mode ratio of the two scatterers' probability density function histograms enhanced the model's performance. In in vitro phantoms, the DND method estimated the scatterer mixture ratios with errors of less than 6%. Additionally, the DND estimation model exhibited lower Kullback–Leibler divergence (KLD) values compared to the Single Nakagami Distribution (&lt;i&gt;p &lt;/i&gt;&lt; 0.0001), indicating that DND provided a superior fit. The eff","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037949","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":"A motion analysis of cardiac substructures for guiding stereotactic arrhythmia radiotherapy motion management","authors":"Yuhao Wang,&nbsp;Trevor McKeown,&nbsp;Yao Hao,&nbsp;Hongyu An,&nbsp;H Michael Gach,&nbsp;Clifford G. Robinson,&nbsp;Phillip S. Cuculich,&nbsp;Deshan Yang","doi":"10.1002/mp.18115","DOIUrl":"10.1002/mp.18115","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;Stereotactic arrhythmia radiotherapy (STAR) has recently emerged as a novel noninvasive treatment option for critically ill and drug-refractory VT patients who cannot be treated or re-treated by catheter ablation. However, STAR requires precise management of cardiorespiratory motion to minimize radiation toxicity to the healthy heart and nearby organs-at-risk (OARs) and to ensure the radiation precision to deliver the prescribed dose to the VT target.&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;To investigate the characteristics of cardiac motion of VT patients to facilitate cardiac motion management for STAR 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;Breath-hold cardiac 4DCTs (c4DCT) of 18 patients previously treated with STAR were analyzed retrospectively. Each c4DCT contained ten 3DCTs corresponding to 10 phases of an entire cardiac motion cycle. For each c4DCT, a group-wise deformable image registration (DIR) method was used to register all ten 3DCTs, resulting in ten 3D deformation vector fields (DVFs) and an average position 3DCT. The DVFs were computed from each phase to the average position 3DCT instead of between pairs of phases. Metal artifacts caused by the Implantable Cardioverter-Defibrillator (ICD) leads were reduced using a diffusion procedure before DIR. The heart chambers were segmented on the average position 3DCT using an AI segmentation tool, followed by manual evaluation and correction. Cardiac motion characteristics (magnitude and direction) were investigated temporally over the 10 cardiac phases and spatially for the outer myocardium walls of the heart and per chamber, AV (atrium-ventricle) valves, septa (the muscular walls dividing the chambers), and STAR targets.&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 motion magnitude maximum over cardiac phases was computed by taking each voxel's maximum motion magnitude in 10 phases, referring to the average position. The cardiac motion magnitudes were found to be strongly patient-specific. The maximum, 99&lt;sup&gt;th&lt;/sup&gt; percentile, and 95&lt;sup&gt;th&lt;/sup&gt; percentile of the motion maximum for the myocardium wall among patients ranged from 8.7 to 17.8 mm, 4.9 to 11.9 mm, and 2.9 to 8.9 mm, respectively. The same metrics for STAR target motion ranged from 2.9 to 11.6 mm, 2.6 to 6.4 mm, and 2.4 to 6.0 mm, respectively. &lt;i&gt;Z&lt;/i&gt;-tests showed a significant difference between the maximum motion magnitude of the myocardium and the STAR target, while there was no significant difference between the mean motion magnitude of the myocardium and the STAR target. The 95&lt;sup&gt;th&lt;/sup&gt; percentiles of the myocardium motion magn","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038161","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":"Method research on magneto-acoustic-electric tomography using liquid conductor","authors":"Yuheng Wang,&nbsp;Junjie Lin,&nbsp;Yi Wu,&nbsp;Jingna Jin,&nbsp;Ren Ma,&nbsp;Tao Yin,&nbsp;Zhipeng Liu,&nbsp;Shunqi Zhang","doi":"10.1002/mp.18095","DOIUrl":"10.1002/mp.18095","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Magneto-acoustic-electric tomography (MAET) has the potential for noninvasive imaging of tissue electrical properties, which is valuable for early tumor detection and detection of electric current within tissues. However, it is plagued by challenges like low signal-to-noise ratio (SNR) and long imaging time, restricting its practical applications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to address these issues by introducing a novel method. A gallium-based liquid conductor (Ga₆₇In₂₀.₅Sn₁₂.₅) with high conductivity is combined with M-sequence coded excitation in MAET.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The performance of Barker code and M-sequence in improving MAET SNR was compared and analyzed through simulation. To validate the simulation results of coded excitation and compare and analyze electrode placement methods in actual complex scenarios, a gel–liquid conductor model was prepared. Paired <i>t</i>-test was used to analyze the difference in SNR. The experiment used a 0.3T magnetic field and an 80 mm focused ultrasound transducer, and the signal was compressed through matched filtering, followed by signal reconstruction in B-scan mode. Finally, 31bit M-sequence was used to reconstruct liquid conductor MAET images of mice in vivo.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Simulation results show that the M-sequence offers better SNR enhancement compared to Barker code, especially with longer bit lengths. Experimentally, the 31bit M-sequence excitation increases the peak SNR (PSNR) by approximately 13 dB compared to single-pulse excitation, significantly better than that of 13bit Barker code. It also maintains a stable 1 MHz central frequency across different conductor thicknesses and coding bit. In complex geometries, M-sequence shows clearer boundaries than 13bit Barker code in electrode placement studies. Moreover, in vivo imaging successfully visualizes the liquid conductor in mouse tissues without adverse effects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This research presents an effective MAET framework. By using the combination of a liquid conductor and M-sequence coded excitation, it enhances the SNR, speeds up imaging, and improves the reconstruction quality, providing a foundational basis for clinical translation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038274","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 tumor detection with a transmission-based microwave imaging system","authors":"Pedram Mojabi,&nbsp;Roger Y. Tsang,&nbsp;Bobbie Docktor,&nbsp;Danielle Deutscher,&nbsp;Anita Garland,&nbsp;Md Mahsin,&nbsp;Jeremie Bourqui,&nbsp;Elise Fear","doi":"10.1002/mp.18080","DOIUrl":"10.1002/mp.18080","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;Microwave imaging has been proposed for breast cancer detection, relying on differences between the microwave frequency properties of healthy and cancerous tissues. Specifically, localized increases in permittivity and/or conductivity may be identified in images of the breast created with microwave tomography. In radar-based images, responses may be noted where property changes occur. Our team has developed a microwave imaging approach that creates maps of permittivity by analyzing the characteristics of signals transmitted through the tissues, scanning the breast in views similar to mammography.&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 aims to assess the feasibility of tumor detection with a transmission-based microwave imaging system. Specifically, both breasts of a control group and a group of women with a cancer diagnosis are scanned in both cranial–caudal (CC) and medial–lateral oblique (MLO) orientations to facilitate comparison with mammography.&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;The microwave scanner consists of planar transmit and receive arrays that are placed in contact with the breast. The arrays are placed horizontally to collect the CC view, then tilted to an angle of 45 degrees to collect the MLO view. Signals with frequency content from 0.1 to 8 GHz are transmitted through the tissue, and the characteristics of the detected signals are used to estimate the microwave frequency properties (permittivity). Estimates at each sensor pair are mapped to the imaging plane. The average microwave frequency properties are calculated for the breast region identified in each image. Images are also segmented using k-means and thresholding to further explore tumor detection. Statistical analysis is applied, specifically analysis of variance (ANOVA) to determine differences between views and groups.&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;20 healthy participants and 14 cancer patients are scanned. Right and left breasts are compared for each patient. Consistency is noted when comparing the CC scans of the breasts of healthy participants; similar observations are made for the MLO scans. Similarity between CC and MLO views of the same breast is also noted and confirmed via ANOVA testing. For patients with confirmed cancer, greater differences are noted between the breasts in at least one view when observing images and average properties. The ratio of the average permittivity of the cancerous breast to the contralateral breast is significantly different than the ratio observed in ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037950","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":"Automatic catheter digitization in breast brachytherapy","authors":"Sébastien Quetin,&nbsp;Hossein Jafarzadeh,&nbsp;Jonathan Kalinowski,&nbsp;Hamed Bekerat,&nbsp;Boris Bahoric,&nbsp;Farhad Maleki,&nbsp;Shirin A. Enger","doi":"10.1002/mp.18107","DOIUrl":"10.1002/mp.18107","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;High dose rate (HDR) brachytherapy requires clinicians to digitize catheters manually. This process is time-consuming, complex, and depends heavily on clinical experience–especially in breast cancer cases, where catheters may be inserted at varying angles and orientations due to an irregular anatomy.&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 is the first to automate catheter digitization specifically for breast HDR brachytherapy, emphasizing the unique challenges associated with this treatment site. It also introduces a pipeline that automatically digitizes catheters, generates dwell positions, and calculates the delivered dose for new breast cancer patients.&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;Treatment data from 117 breast cancer patients treated with HDR brachytherapy were used. Pseudo-contours for the catheters were created from the treatment digitization points and divided into three classes: catheter body, catheter head, and catheter tip. An nnU-Net pipeline was trained to segment the pseudo-contours on treatment planning computed tomography images of 88 patients (training and validation). Then, pseudo-contours were digitized by separating the catheters into connected components. Predicted catheters with an unusual volume were flagged for manual review. A custom algorithm was designed to report and separate connected components containing colliding catheters. Finally, a spline was fitted to every separated catheter, and the tip was identified on the spline using the tip contour prediction. Dwell positions were placed from the created tip at a regular step size extracted from the DICOM plan file. Distance from each dwell position used during the clinical treatment to the fitted spline (shaft distance) was computed, as well as the distance from the treatment tip to the one identified by our pipeline. Dwell times from the clinical plan were assigned to the nearest generated dwell positions. TG-43 dose in water was computed analytically, and the absorbed dose in the medium was predicted using a published AI-based dose prediction model. Dosimetric comparison between the clinically delivered plan dose and the created automated plan dose was evaluated regarding dosimetric indices percent error.&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;Our pipeline was used to digitize 408 catheters on a test set of 29 patients. Shaft distance was on average &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0.70&lt;/mn&gt;\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038163","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":"AAPM TG report 330: EPID-based quality assurance of linear accelerators","authors":"Baozhou Sun,&nbsp;Sridhar Yaddanapudi,&nbsp;Sasa Mutic,&nbsp;Chengyu Shi,&nbsp;Boyd M. C. McCurdy,&nbsp;Richard A. Popple,&nbsp;Minghui Lu,&nbsp;Taeho Kim,&nbsp;Jennifer R Clark,&nbsp;Peter B Greer","doi":"10.1002/mp.18114","DOIUrl":"10.1002/mp.18114","url":null,"abstract":"<p>Electronic portal imaging devices (EPIDs) have been in widespread clinical use for almost two decades due to favorable measurement characteristics such as fast image acquisition, high sensitivity and resolution, digital data format, long-term stability, linear dose response, and large detection area. On-board EPIDs are widely used as a quality assurance (QA) tool to monitor nearly every aspect of linear accelerator (linac) performance. In both the commercial QA equipment market and in clinical practice, there is a trend toward replacing conventional QA approaches with fully automated, EPID-based QA tools. Despite widespread use, EPIDs are complex devices, and there has yet to be consensus or formal recommendations published by the AAPM for their use in routine linac QA. Task Group 330 (TG-330) was, therefore, formed to provide guidelines and recommendations for physicists on the safe and appropriate use of EPIDs for linac QA. In particular, the report: (a) provides a comprehensive review of the characteristics and limitations of EPIDs as time-resolved measurement devices and dosimeters; (b) summarizes the application of EPIDs for linac QA; (c) provides recommendations on efficient and effective implementations of EPID-based QA techniques; (d) describes risks associated with the use of EPIDs for linac QA and provides examples of how risk analysis can be used to ensure the safe use of EPIDs for linac QA. Many of the guidelines in this report are drawn from the literature that is included in the references and from the collective experience of the task group members. This report does not provide recommendations on the implementation of EPID-based patient-specific IMRT or VMAT QA, which is the topic of AAPM's report from AAPM TG-307.</p>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038164","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":"Predicting anatomical variations in radiotherapy with a vector quantized variational autoencoder generative model","authors":"Yue Zou,&nbsp;Zhenhao Li,&nbsp;Menghan Zhang,&nbsp;Ziwei Li,&nbsp;Xiaojie Yin,&nbsp;Long Yang,&nbsp;Weigang Hu,&nbsp;Jiazhou Wang","doi":"10.1002/mp.18120","DOIUrl":"10.1002/mp.18120","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Anatomical variations during radiotherapy fractions can lead to deviations in radiation delivery. Predicting these changes may benefit adaptive radiotherapy (ART) in nasopharyngeal cancer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study proposes a vector quantized variational autoencoder (VQ-VAE) based generative model to predict anatomical changes in nasopharyngeal cancer patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The model integrates a VQ-VAE with Adaptive Instance Normalization (AdaIN). VQ-VAE encodes anatomical structures from planning CT images, while a convolutional neural network (CNN) extracts latent codes that capture potential anatomical variations. AdaIN then modulates the VQ-VAE's latent space to generate daily CT images that reflect these anatomical changes. The model was trained and validated on 522 CT images from 90 nasopharyngeal cancer patients and tested using 102 CT images from 18 patients. The quality of the generated images was evaluated through visual inspection, while the model's accuracy was assessed by comparing the predicted and actual volumes of the parotid and submandibular glands at both individual and population levels.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>For individual patients, Mann–Whitney and Kruskal–Wallis tests found no significant differences in organ-at-risk (OAR) volume distributions between generated and actual daily CT images. At the population level, predicted mean ROI volumes (parotid glands: 26.9 ± 2.1 cm³; submandibular glands: 7.0 ± 0.71 cm³) closely matched ground truth values (parotid: 29.5 ± 3.2 cm³; submandibular: 7.2 ± 0.67 cm³) and outperformed the previous Daily Anatomy Model (DAM) model (parotid: 20.4 ± 1.9 cm³; submandibular: 6.2 ± 0.6 cm³). The Pearson correlation coefficients between actual and generated daily CT ROI volumes were 0.92, 0.87, 0.89, and 0.93 for right parotid, left parotid, right submandibular, and left submandibular, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The VQ-VAE model effectively predicts anatomical changes during radiotherapy based on planning CT, demonstrating its potential to inform adaptive decision-making in radiotherapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038273","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":"Image-domain metal artifact reduction in low-energy VMI using high-energy regional prior","authors":"Dan Wang,&nbsp;Yu Zou,&nbsp;Qilin Zhang,&nbsp;Yi Yang,&nbsp;Zhe Shi,&nbsp;Juying Huang,&nbsp;Zhi Yang","doi":"10.1002/mp.18118","DOIUrl":"10.1002/mp.18118","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;Metal artifacts degrade the clinical utility of virtual monochromatic images (VMIs), particularly in low energy levels. Nevertheless, low-energy VMIs have essential clinical applications, such as reducing the volume of iodinated contrast material administered, salvaging poorly attenuated contrast-enhanced CT studies, and analyzing arterial vasculature during the venous phase. Conventional metal artifact reduction algorithms may introduce new artifacts and obscure soft tissue details.&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 aim of this study is to develop a practical image-domain solution for significantly reducing the metal artifacts in low-energy VMIs while preserving the clarity of soft tissues and metal boundaries.&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 mapping model was developed to establish a relationship between optimal VMI and the material basis images (MBIs) in artifact-free regions. This model was subsequently used to correct artifact-affected regions in MBIs. Finally, artifact-reduced low-energy VMIs were synthesized from the updated MBIs. The approach, referred to as regional model-based metal artifact reduction (rMAR), utilized the mapping model to effectively reduce metal artifacts. To validate the efficacy of the proposed method, both phantom and patient data acquired from Philips scanner were used. The scanner's built-in metal artifact reduction for orthopedic implants, known as OMAR, was employed. Comprehensive comparisons were conducted among four image processing strategies: VMI alone, VMI combined with OMAR (VMI + OMAR), VMI combined with the proposed rMAR (VMI + rMAR), and a combination of all three methods (VMI + OMAR + rMAR). Evaluations were performed using visual assessment, line profile analysis, and measurement of the ∆CT number.&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;High-energy VMIs exhibit significantly fewer metal artifacts compared to those at low energy levels, as demonstrated in both phantom and patient results. Although conventional metal artifact reduction algorithms can mitigate the existing artifacts, they often introduce new ones. In contrast, the proposed rMAR method effectively reduces artifacts in low-energy VMIs, achieving improved image quality without introducing new artifacts. In specific cases, such as postoperative VMIs of hip prosthesis implants, the combined VMI + OMAR + rMAR approach demonstrates superior metal artifact reduction compared to either OMAR or rMAR alone. Quantitative line profile analysis indicated that the proposed rMA","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038160","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}