Medical physics最新文献

{"title":"AAPM Truth-based CT (TrueCT) reconstruction grand challenge","authors":"Ehsan Abadi, W. Paul Segars, Nicholas Felice, Saman Sotoudeh-Paima, Eric A. Hoffman, Xiao Wang, Wei Wang, Darin Clark, Siqi Ye, Giavanna Jadick, Milo Fryling, Donald P. Frush, Ehsan Samei","doi":"10.1002/mp.17619","DOIUrl":"10.1002/mp.17619","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>This Special Report summarizes the 2022, AAPM grand challenge on Truth-based CT image reconstruction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To provide an objective framework for evaluating CT reconstruction methods using virtual imaging resources consisting of a library of simulated CT projection images of a population of human models with various diseases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two hundred unique anthropomorphic, computational models were created with varied diseases consisting of 67 emphysema, 67 lung lesions, and 66 liver lesions. The organs were modeled based on clinical CT images of real patients. The emphysematous regions were modeled using segmentations from patient CT cases in the COPDGene Phase I dataset. For the lung and liver lesion cases, 1–6 malignant lesions were created and inserted into the human models, with lesion diameters ranging from 5.6 to 21.9 mm for lung lesions and 3.9 to 14.9 mm for liver lesions. The contrast defined between the liver lesions and liver parenchyma was 82 ± 12 HU, ranging from 50 to 110 HU. Similarly, the contrast between the lung lesions and the lung parenchyma was defined as 781 ± 11 HU, ranging from 725 to 805 HU. For the emphysematous regions, the defined HU values were −950 ± 17 HU ranging from −918 to −979 HU. The developed human models were imaged with a validated CT simulator. The resulting CT sinograms were shared with the participants. The participants reconstructed CT images from the sinograms and sent back their reconstructed images. The reconstructed images were then scored by comparing the results against the corresponding ground truth values. The scores included both task-generic (root mean square error [RMSE] and structural similarity matrix [SSIM]), and task-specific (detectability index [d’] and lesion volume accuracy) metrics. For the cases with multiple lesions, the measured metric was averaged across all the lesions. To combine the metrics with each other, each metric was normalized to a range of 0 to 1 per disease type, with “0” and “1” being the worst and best measured values across all cases of the disease type for all received reconstructions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The True-CT challenge attracted 52 participants, out of which 5 successfully completed the challenge and submitted the requested 200 reconstructions. Across all participants and disease types, SSIM absolute values ranged from 0.22 to 0.90, RMSE from 77.6 to 490.5 HU, d’ from 0.1 to 64.6, and volume accuracy ranged from 1.2 to 7","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"1978-1990"},"PeriodicalIF":3.2,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17619","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142981078","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":"CT material decomposition with contrast agents: Single or multiple spectral photon-counting CT scans? A simulation study","authors":"Stefan Sawall, Edith Baader, Philip Trapp, Marc Kachelrieß","doi":"10.1002/mp.17604","DOIUrl":"10.1002/mp.17604","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>With the widespread introduction of dual energy computed tomography (DECT), applications utilizing the spectral information to perform material decomposition became available. Among these, a popular application is to decompose contrast-enhanced CT images into virtual non-contrast (VNC) or virtual non-iodine images and into iodine maps. In 2021, photon-counting CT (PCCT) was introduced, which is another spectral CT modality. It allows for scans with more than two different detected spectra. With these systems, it becomes possible to distinguish more than two materials. It is frequently proposed to administer more than one contrast agent, perform a single PCCT scan, and then calculate the VNC images and the contrast agent maps. This may not be optimal because the patient is injected with a material, only to have it computationally extracted again immediately afterwards by spectral CT. It may be better to do an unenhanced scan followed by one or more contrast-enhanced scans. The main argument for the spectral material decomposition is patient motion, which poses a significant challenge for approaches involving two or more temporally separated scans. In this work, we assume that we can correct for patient motion and thus are free to scan the patient more than once. Our goal is then to quantify the penalty for performing a single contrast-enhanced scan rather than a clever series of unenhanced and enhanced scans. In particular, we consider the impact on patient dose and image quality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We simulate CT scans of three differently sized phantoms containing various contrast agents. We do this for a variety of tube voltage settings, a variety of patient-specific prefilter (PSP) thicknesses and a variety of threshold settings of the photon-counting detector with up to four energy bins. The reconstructed bin images give the expectation values of soft tissue and of the contrast agents. Error propagation of projection noise into the images yields the image noise. Dose is quantified using the total CT dose index (CTDI) value of the scans. When combining multiple scans, we further consider all possible tube current (or dose) ratios between the scans. Material decomposition is done image-based in a statistical optimal way. Error propagation into the material-specific images yields the signal-to-noise ratio at unit dose (SNRD). The winning scan strategy is the one with the highest total SNRD, which is related to the SNRD of the material that has the lowest signal-to-noise ratio (SNR) among the materials to decompose into. We consider scan strategies with up to three scans and up to three materials (water W, contrast agent X and contrast agent Y).</p>\u0000 </section>\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2167-2190"},"PeriodicalIF":3.2,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142960760","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":"Risk assessment and quality management in AIO based on CT-linac for nasopharyngeal carcinoma: An improved FMEA and FTA approach","authors":"Guangyu Wang, Shouliang Ding, Xin Yang, Sijuan Huang, Guanqun Zhou, Lu Liu, Hua Li, Lecheng Jia, Wenchao Diao, Ying Sun, Yanfei Liu, Zun Piao, Chendi Xu, Li Chen, Xiaoyan Huang","doi":"10.1002/mp.17620","DOIUrl":"10.1002/mp.17620","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>All-in-one radiotherapy workflow (AIO) is a novel one-stop solution that integrates the multiple conventional radiotherapy steps from simulation, contouring, planning, image guidance, beam delivery, and in vivo dosimetry into a single device (integrated computed tomography linac, the uRT-linac 506c), making the treatment process more efficient and convenient while reducing errors for cancer patients' initial radiotherapy. Despite its numerous advantages, the implementation of AIO faces challenges such as interdisciplinary coordination, software and hardware complexity, and reliance on artificial intelligence. To ensure its safety and effectiveness, it is necessary to conduct a risk assessment and identify appropriate quality management measures.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To perform risk assessment on the AIO for nasopharyngeal carcinoma using failure mode and effects analysis (FMEA) and fault tree analysis (FTA), and to validate the effectiveness of the quality management measures.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A flowchart was established for the AIO of nasopharyngeal carcinoma. FMEA analysis was conducted based on the flowchart, and quantitative assessments of each failure mode (FM) were performed to obtain <span></span><math>\u0000 <semantics>\u0000 <mi>O</mi>\u0000 <annotation>$O$</annotation>\u0000 </semantics></math> (occurrence), <span></span><math>\u0000 <semantics>\u0000 <mi>S</mi>\u0000 <annotation>$S$</annotation>\u0000 </semantics></math> (severity), and <span></span><math>\u0000 <semantics>\u0000 <mi>D</mi>\u0000 <annotation>$D$</annotation>\u0000 </semantics></math> (Detectability). Weighted <span></span><math>\u0000 <semantics>\u0000 <msub>\u0000 <mi>O</mi>\u0000 <mrow>\u0000 <mi>w</mi>\u0000 <mi>i</mi>\u0000 </mrow>\u0000 </msub>\u0000 <annotation>${O}_{wi}$</annotation>\u0000 </semantics></math>, <span></span><math>\u0000 <semantics>\u0000 <msub>\u0000 <mi>S</mi>\u0000 <mrow>\u0000 <mi>w</mi>\u0000 <mi>i</mi>\u0000 </mrow>\u0000 </msub>\u0000 <annotation>${S}_{wi}$</annotation>\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2425-2437"},"PeriodicalIF":3.2,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142967576","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 patient-specific four-dimensional in vivo tracking system for high-dose-rate brachytherapy: Experimental evaluation","authors":"Geon Oh, Jeongshim Lee, Hunjung Kim, Wonjoong Cheon, Dong-seok Shin, Jaehyeon Seo, Jiwon Sung, Dongho Shin, Myonggeun Yoon, Jin-beom Chung, Boram Lee","doi":"10.1002/mp.17614","DOIUrl":"10.1002/mp.17614","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>High-dose-rate (HDR) brachytherapy using Iridium-192 as a radiation source is widely employed in cancer treatment to deliver concentrated radiation doses while minimizing normal tissue exposure. In this treatment, the precision with which the sealed radioisotope source is delivered significantly impacts clinical outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to evaluate the feasibility of a new four-dimensional (4D) in vivo source tracking and treatment verification system for HDR brachytherapy using a patient-specific approach.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A hardware system was developed for the experiments, featuring a high-resolution compact gamma camera with a redesigned diverging collimator, enhanced detector, and precision control system. The collimator was redesigned to improve spatial resolution by reducing the hole size and increasing the hole array, while reducing the pixel size of the detector and increasing the number of pixels. The performance was evaluated using Monte Carlo simulations, which demonstrated significant improvements in spatial resolution. Experiments were conducted in a controlled setup using a phantom to simulate clinical conditions. The phantom was positioned at various distances from the gamma camera (327.30, 377.30, and 427.30 mm) and imaged at multiple angles. The accuracy of the system was tested in four different cases: three with fixed distances and one employing a multi-focusing method. The multi-focusing method allows the gamma camera to adjust its focus based on the anatomical characteristics of individual patients, thereby enhancing source-tracking accuracy. The performance of the system was evaluated under these four different scenarios. The Euclidean distance and three-dimensional gamma analysis were used to evaluate tracking accuracy and dose distribution.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The redesigned collimator demonstrated significant improvements (compared to the previous design) in the spatial resolution of the gamma camera, showing 34.21% and 23.46% enhancements in the horizontal and vertical profiles, respectively. These improvements in gamma camera resolution are crucial for enhancing the tracking system's accuracy. The experimental results demonstrated varying degrees of accuracy across different cases, reflecting the performance of the system under different conditions. The average Euclidean distance errors were Case 1 (327.30 mm): 1.358 mm; Case 2 (377.30 mm): 1.731 mm; Case 3 (427.30 mm): 1.973 mm; and Case 4 (multi-focusing): 1.527 mm. The gamma pass rates for the four cases were:-","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2533-2550"},"PeriodicalIF":3.2,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142960761","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 practical approach to the spatial-domain calculation of nonprewhitening model observers in computed tomography","authors":"Gavin Poludniowski, Rebecca Titternes, Daniel Thor","doi":"10.1002/mp.17599","DOIUrl":"10.1002/mp.17599","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Modern reconstruction algorithms for computed tomography (CT) can exhibit nonlinear properties, including non-stationarity of noise and contrast dependence of both noise and spatial resolution. Model observers have been recommended as a tool for the task-based assessment of image quality (Samei E et al., Med Phys. 2019; 46(11): e735-e756), but the common Fourier domain approach to their calculation assumes quasi-stationarity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>A practical spatial-domain approach is proposed for the calculation of the nonprewhitening (NPW) family of model observers in CT, avoiding the disadvantages of the Fourier domain. The methodology avoids explicit estimation of a noise covariance matrix. A formula is also provided for the uncertainty on estimates of detectability index, for a given number of slices and repeat scans. The purpose of this work is to demonstrate the method and provide comparisons to the conventional Fourier approach for both iterative reconstruction (IR) and a deep Learning-based reconstruction (DLR) algorithm.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and methods</h3>\u0000 \u0000 <p>Acquisitions were made on a Revolution CT scanner (GE Healthcare, Waukesha, Wisconsin, USA) and reconstructed using the vendor's IR and DLR algorithms (ASiR-V and TrueFidelity). Several reconstruction kernels were investigated (Standard, Lung, and Bone for IR and Standard for DLR). An in-house developed phantom with two flat contrast levels (2 and 8 mgI/mL) and varying feature size (1–10 mm diameter) was used. Two single-energy protocols (80 and 120 kV) were investigated with two dose levels (CTDI<sub>vol</sub> = 5 and 13 mGy).</p>\u0000 \u0000 <p>The spatial domain calculations relied on repeated scanning, region-of-interest placement and simple operations with image matrices. No more repeat scans were utilized than required for Fourier domain estimations. Fourier domain calculations were made using techniques described in a previous publication (Thor D et al., Med Phys. 2023;50(5):2775-2786). Differences between the calculations in the two domains were assessed using the normalized root-mean-square discrepancy (NMRSD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Fourier domain calculations agreed closely with those in the spatial domain for all zero-strength IR reconstructions, which most closely resemble traditional filtered backprojection. The Fourier-based calculations, however, displayed higher detectability compared to those in the spatial domain for IR with strong iterati","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2106-2122"},"PeriodicalIF":3.2,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142960759","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":"Optimizing the deliverability of binary collimation-based SRS treatment for multiple metastases with multiple prescriptions","authors":"Eva Lee,&nbsp;Christopher G. Thomas,&nbsp;Alasdair Syme,&nbsp;R. Lee MacDonald","doi":"10.1002/mp.17597","DOIUrl":"10.1002/mp.17597","url":null,"abstract":"<p>intra-arc binary collimation (iABC) is a novel treatment technique in which dynamic conformal arcs are periodically interrupted with binary collimation. It has demonstrated its utility through planning studies for the treatment of multiple metastases. However, the binary collimation approach is idealized in the planning system, while the treatment deliveries must adhere to the physical limitations of the mechanical systems involved [e.g., multi-leaf collimation (MLC) leaf speed]. This work focuses on optimizing the delivery of the binary collimation-based stereotactic radiosurgery/radiotherapy (SRS/SRT) plans on a Varian TrueBeam accelerator, considering both dosimetric fidelity and treatment efficiency as variables. A transition window (TW) was defined as the fraction of a control point (CP) during which the requested MLC motion must be completed. The width of TWs was varied between 0% (or step-and-shoot which represents the idealized dose distribution), 20%, 40%, 60%, 80%, and 100%. A variable TW approach was also studied. Delivery accuracy was quantified with gamma analysis (gamma criteria 5%/2mm) on a PTW Octavius detector. The total beam-on-time was manually recorded. Smaller TWs were associated with more accurate dose deliveries and longer treatment delivery times. The variable TW method was found to be an effective compromise, achieving an average gamma pass rate of 98% and an average delivery time of 9 min.</p>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 3","pages":"1430-1435"},"PeriodicalIF":3.2,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142960788","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":"Design optimization of a 1-D array of stemless plastic scintillation detectors","authors":"Samaneh Aynehband,&nbsp;Ian G Hill,&nbsp;Alasdair Syme","doi":"10.1002/mp.17608","DOIUrl":"https://doi.org/10.1002/mp.17608","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;A stemless plastic scintillation detector (SPSD) is composed of an organic plastic scintillator coupled to an organic photodiode. Previous research has shown that SPSDs are ideally suited to challenging dosimetry measurements such as output factors and profiles in small fields. Lacking from the current literature is a systematic effort to optimize the performance of the photodiode component of the detector. An optimized detector could permit a reduction in detector element size, thus improving spatial resolution without degradation of the signal to noise ratio values seen previously.&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;SPSDs use an organic photodiode coupled to a plastic scintillator to measure ionizing radiation fields. The design retains the benefits of plastic scintillation detectors (energy and dose rate independence, no perturbation factors, etc.) but avoids the challenges of optical fiber-based systems (Cerenkov radiation). In this work, the design of a 1-dimensional array of SPSDs is optimized to maximize the measured signal.&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;ITO-covered PET was etched using hydrochloric acid, and the substrate was cleaned. PEDOT: PSS and P3HT: PCBM (different weight ratios) were then applied to the substrate using spin-coating. Finally, aluminum top electrodes were added using vacuum thermal evaporation to complete the fabrication process. The variables studied for the optimization included: spin coater's speed (i.e., film thickness), P3HT: PCBM ratio, solution concentration, and scintillator coating.&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;Increasing the film thickness from ∼80 nm to ∼138 nm increased the measured signal by a factor of approximately 7.7. Changing the ratio of P3HT to PCBM from (1:1) to (4:1) resulted in approximately 3.5 times higher signal. Additionally, increasing the total concentration of the solution from 2% to 4% by weight ratio increased the signal by roughly a factor of 2.5 for a P3HT: PCBM ratio of 2:1. However, for a P3HT: PCBM ratio of 4:1, increased solution concentration reduced measured signals to approximately 1.7 times lower than normal concentration. Covering the air gaps of the etched scintillator with white paint resulted in a signal increase of about 2.2 times higher compared to black paint.&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;An optimization process was conducted to improve the signal output of the radiation detector, which consisted of a 1-dimensional photodiode array combined with a scintillator. This appro","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2560-2569"},"PeriodicalIF":3.2,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143784312","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":"List of Advertisers","authors":"","doi":"10.1002/mp.17196","DOIUrl":"https://doi.org/10.1002/mp.17196","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 1","pages":"717"},"PeriodicalIF":3.2,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17196","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112015","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":"Erratum: “A multiple x-ray-source array (MXA) system with a planar two-dimensional source distribution for digital breast tomosynthesis”","authors":"","doi":"10.1002/mp.17538","DOIUrl":"10.1002/mp.17538","url":null,"abstract":"<p>This article adds inadvertently omitted conflict of interest disclosures.</p><p>Alejandro Sisniega¹, Andrew M. Hernandez², Shadi A. Shakeri², Elizabeth A. Morris², John M. Boone^2,3, Jeffrey H. Siewerdsen⁴, Paul R. Schwoebel⁵</p><p>¹Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA</p><p>²Department of Radiology, University of California Davis, Davis, California, USA</p><p>³Department of Biomedical Engineering, University of California Davis, Davis, California, USA</p><p>⁴Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Hoston, Texas, USA</p><p>⁵Department of Physics, University of New Mexico, Albuquerque, New Mexico, USA</p><p>First published October 2024, https://doi.org/10.1002/mp.17452</p><p>Authors J.M.B. and P.R.S. disclose that they are inventors on two licensed patents (US 11,123,027 and 11,534,118) on multiple x-ray source arrays. Author J.M.B. discloses that in his capacity as Editor-in-Chief of Medical Physics, he had no role in the review or acceptance process with this paper.</p>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 1","pages":"716"},"PeriodicalIF":3.2,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142928605","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":"Cover","authors":"","doi":"10.1002/mp.17195","DOIUrl":"https://doi.org/10.1002/mp.17195","url":null,"abstract":"","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 1","pages":"C1"},"PeriodicalIF":3.2,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17195","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112089","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}