Medical physics最新文献

{"title":"Impact of deep learning reconstructions on image quality and liver lesion detectability in dual-energy CT: An anthropomorphic phantom study","authors":"Aurélie Pauthe, Milan Milliner, Hugo Pasquier, Lucie Campagnolo, Sébastien Mulé, Alain Luciani","doi":"10.1002/mp.17651","DOIUrl":"10.1002/mp.17651","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Deep learning image reconstruction (DLIR) algorithms allow strong noise reduction while preserving noise texture, which may potentially improve hypervascular focal liver lesions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To assess the impact of DLIR on image quality (IQ) and detectability of simulated hypervascular hepatocellular carcinoma (HCC) in fast kV-switching dual-energy CT (DECT).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An anthropomorphic phantom of a standard patient morphology (body mass index of 23 kg m<sup>−2</sup>) with customized liver, including mimickers of hypervascular lesions in both late arterial phase (AP) and portal venous phase (PVP) enhancement, was scanned on a DECT. Virtual monoenergetic images were reconstructed from raw data at four energy levels (40/50/60/70 keV) using filtered back-projection (FBP), adaptive statistical iterative reconstruction-V 50% and 100% (ASIRV-50 and ASIRV-100), DLIR low (DLIR-L), medium (DLIR-M), and high (DLIR-H). The contrast between the lesion and the liver parenchyma, the noise magnitude, the average and peak frequencies (f<sub>avg</sub> and f<sub>peak</sub>) of the noise power spectrum (NPS) reflecting noise texture, and the task-based measure of the modulation transfer function (MTF<sub>task</sub>) were measured to evaluate spatial resolution. A detectability index (d′) was computed to model the detection of hypervascular lesions in both AP and PVP. Metrics were compared between reconstructions and between energy levels using a Friedman test with follow-up post-hoc multiple comparison.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Lesion-to-liver contrast significantly increased with decreasing energy level in both AP and PVP (<i>p</i> ≤ 0.042) but was not affected by reconstruction algorithm (<i>p</i> ≥ 0.57). Overall, noise magnitude increased with decreasing energy levels and was the lowest with ASIRV-100 at all energy levels in both AP and PVP (<i>p</i> ≤ 0.01) and significantly lower with DLIR-M and DLIR-H reconstructions compared to ASIRV-50 and DLIR-L (<i>p</i> < 0.001). For all reconstructions, noise texture within the liver tended to get smoother with decreasing energy; f<sub>avg</sub> significantly shifted towards lower frequencies from 70 to 40 keV (<i>p</i> ≤ 0.01). Noise texture was the smoothest with ASIRV-100 (<i>p</i> < 0.001) while DLIR-L had the noise texture closer to the one of FBP. The spatial resolution was not significantly affected by the energy level, but it was degraded when increasing the level of ASIRV and ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2257-2268"},"PeriodicalIF":3.2,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143070209","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":"Implicit neural representation-based method for metal-induced beam hardening artifact reduction in X-ray CT imaging","authors":"Hyoung Suk Park,&nbsp;Jin Keun Seo,&nbsp;Kiwan Jeon","doi":"10.1002/mp.17649","DOIUrl":"10.1002/mp.17649","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In X-ray computed tomography (CT), metal-induced beam hardening artifacts arise from the complex interactions between polychromatic X-ray beams and metallic objects, leading to degraded image quality and impeding accurate diagnosis. A previously proposed metal-induced beam hardening correction (MBHC) method provides a theoretical framework for addressing nonlinear artifacts through mathematical analysis, with its effectiveness demonstrated by numerical simulations and phantom experiments. However, in practical applications, this method relies on precise segmentation of highly attenuating materials and parameter estimations, which limit its ability to fully correct artifacts caused by the intricate interactions between metals and other dense materials, such as bone or teeth.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to develop a parameter-free MBHC method that eliminates the need for accurate segmentation and parameter estimations, thereby addressing the limitations of the original MBHC approach.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The proposed method employs implicit neural representations (INR) to generate two tomographic images: one representing the monochromatic attenuation distribution at a specific energy level, and another capturing the nonlinear beam hardening effects caused by the polychromatic nature of X-ray beams. A loss function drives the generation of these images, where the predicted projection data is nonlinearly modeled by the combination of the two images. This approach eliminates the need for geometric and parameter estimation of metals, providing a more generalized solution.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Numerical and phantom experiments demonstrates that the proposed method effectively reduces beam hardening artifacts caused by interactions between highly attenuating materials such as metals, bone, and teeth. Additionally, the proposed INR-based method demonstrates potential in addressing challenges related to data insufficiencies, such as photon starvation and truncated fields of view in CT imaging.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The proposed generalized MBHC method provides high-quality image reconstructions without requiring parameter estimations and segmentations, offering a robust solution for reducing metal-induced beam hardening artifacts in CT imaging.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2201-2211"},"PeriodicalIF":3.2,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143070332","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":"Radiogenomic explainable AI with neural ordinary differential equation for identifying post-SRS brain metastasis radionecrosis","authors":"Jingtong Zhao,&nbsp;Eugene Vaios,&nbsp;Zhenyu Yang,&nbsp;Ke Lu,&nbsp;Scott Floyd,&nbsp;Deshan Yang,&nbsp;Hangjie Ji,&nbsp;Zachary J. Reitman,&nbsp;Kyle J. Lafata,&nbsp;Peter Fecci,&nbsp;John P. Kirkpatrick,&nbsp;Chunhao Wang","doi":"10.1002/mp.17635","DOIUrl":"10.1002/mp.17635","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 radiosurgery (SRS) is widely used for managing brain metastases (BMs), but an adverse effect, radionecrosis, complicates post-SRS management. Differentiating radionecrosis from tumor recurrence non-invasively remains a major clinical challenge, as conventional imaging techniques often necessitate surgical biopsy for accurate diagnosis. Machine learning and deep learning models have shown potential in distinguishing radionecrosis from tumor recurrence. However, their clinical adoption is hindered by a lack of explainability, limiting understanding and trust in their diagnostic decisions.&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 utilize a novel neural ordinary differential equation (NODE) model for discerning BM post-SRS radionecrosis from recurrence. This approach integrates image-deep features, genomic biomarkers, and non-image clinical parameters within a synthesized latent feature space. The trajectory of each data sample towards the diagnosis decision can be visualized within this feature space, offering a new angle on radiogenomic data analysis foundational for AI explainability.&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;By hypothesizing that deep feature extraction can be modeled as a spatiotemporally continuous process, we designed a novel model based on heavy ball NODE (HBNODE) in which deep feature extraction was governed by a second-order ODE. This approach enabled tracking of deep neural network (DNN) behavior by solving the HBNODE and observing the stepwise derivative evolution. Consequently, the trajectory of each sample within the Image-Genomic-Clinical (I-G-C) space became traceable. A decision-making field (&lt;b&gt;&lt;i&gt;F&lt;/i&gt;&lt;/b&gt;) was reconstructed within the feature space, with its gradient vectors directing the data samples’ trajectories and intensities showing the potential. The evolution of &lt;b&gt;&lt;i&gt;F&lt;/i&gt;&lt;/b&gt; reflected the cumulative feature contributions at intermediate states to the final diagnosis, enabling quantitative and dynamic comparisons of the relative contribution of each feature category over time. A velocity curve was designed to determine key intermediate states (locoregional ∇&lt;b&gt;&lt;i&gt;F &lt;/i&gt;&lt;/b&gt;=&lt;b&gt; &lt;/b&gt;0) that are most predictive. Subsequently, a non-parametric model aggregated the optimal solutions from these key states to predict outcomes.&lt;/p&gt;\u0000 \u0000 &lt;p&gt;Our dataset included 90 BMs from 62 NSCLC patients, and 3-month post-SRS T1+c MR image features, seven NSCLC genomic features, and seven clinical features were analyzed. An 8:2 train/test assignment was employed, and five independent models were trained to ensure robustness. Performance was benchmarked in sensitivity, specificity, accuracy, and ROC&lt;sub&gt;AUC","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2661-2674"},"PeriodicalIF":3.2,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061632","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":"Segmentation of coronary artery and calcification using prior knowledge based deep learning framework","authors":"Jinda Wang,&nbsp;Qian Chen,&nbsp;Xingyu Jiang,&nbsp;Zeyu Zhang,&nbsp;Zhenyu Tang","doi":"10.1002/mp.17642","DOIUrl":"10.1002/mp.17642","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Computed tomography angiography (CTA) is used to screen for coronary artery calcification. As the coronary artery has complicated structure and tiny lumen, manual screening is a time-consuming task. Recently, many deep learning methods have been proposed for the segmentation (SEG) of coronary artery and calcification, however, they often neglect leveraging related anatomical prior knowledge, resulting in low accuracy and instability.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to build a deep learning based SEG framework, which leverages anatomical prior knowledge of coronary artery and calcification, to improve the SEG accuracy. Moreover, based on the SEG results, this study also try to reveal the predictive ability of the volume ratio of coronary artery and calcification for rotational atherectomy (RA).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We present a new SEG framework, which is composed of four modules: the variational autoencoder based centerline extraction (CE) module, the self-attention (SA) module, the logic operation (LO) module, and the SEG module. Specifically, the CE module is used to crop a series of 3D CTA patches along the coronary artery, from which the continuous property of vessels can be utilized by the SA module to produce vessel-related features. According to the spatial relations between coronary artery lumen and calcification regions, the LO module with logic union and intersection is designed to refine the vessel-related features into lumen- and calcification-related features, based on which SEG results can be produced by the SEG module.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Experimental results demonstrate that our framework outperforms the state-of-the-art methods on CTA image dataset of 72 patients with statistical significance. Ablation experiments confirm that the proposed modules have positive impacts to the SEG results. Moreover, based on the volume ratio of segmented coronary artery and calcification, the prediction accuracy of RA is 0.75.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Integrating anatomical prior knowledge of coronary artery and calcification into the deep learning based SEG framework can effectively enhance the performance. Moreover, the volume ratio of segmented coronary artery and calcification is a good predictive factor for RA.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 5","pages":"3030-3043"},"PeriodicalIF":3.2,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061577","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":"MR imaging of proton beam-induced oxygen depletion","authors":"Juliane Schieferecke,&nbsp;Aswin Hoffmann,&nbsp;Jörg Pawelke","doi":"10.1002/mp.17622","DOIUrl":"10.1002/mp.17622","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;Previous studies have shown that in-beam magnetic resonance imaging (MRI) can be used to visualize a proton beam during the irradiation of liquid-filled phantoms. The beam energy- and current-dependent local image contrast observed in water was identified to be predominantly caused by beam-induced buoyant convection and associated flow effects. Besides this flow dependency, the MR signal change was found to be characterized by a change in the &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;${rm T}_{1}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; relaxation time of water, hinting at a radiochemical contribution, which was hypothesized to lie in oxygen depletion-evoked &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;${rm T}_{1}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; relaxation time lengthening. The elucidation of the underlying contrast mechanism is required to enable the further assessment of the application potential of MRI-based proton beam visualization in tissue.&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 underlying radiochemical cause of the observed local beam-induced change in the &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;${rm T}_{1}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; relaxation time of water should be identified in beam visualization experiments testing the hypothesis of beam-induced oxygen depletion-evoked &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;${rm T}_{1}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; relaxation time lengthening.&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;Combined irradiation and imaging experiments were performed using static proton pencil beam irradiation, background-nulled inversion recovery (IR) MRI and a range of flow-restricted phantoms differing in initial oxygen concentration and homogeneity. The similarity of the irradiation-induced MRI contrast to the proton pencil beam dose distribution ac","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2454-2464"},"PeriodicalIF":3.2,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054697","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":"Photon mini-GRID therapy for preoperative breast cancer tumor treatment: A treatment plan study","authors":"Angela Corvino,&nbsp;Tim Schneider,&nbsp;Jeremi Vu-Bezin,&nbsp;Pierre Loap,&nbsp;Youlia Kirova,&nbsp;Yolanda Prezado","doi":"10.1002/mp.17634","DOIUrl":"10.1002/mp.17634","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;Breast cancer is the leading cause of female cancer mortality worldwide, accounting for 1 in 6 cancer deaths. Surgery, radiation, and systemic therapy are the three pillars of breast cancer treatment, with several strategies developed to combine them. The association of preoperative radiotherapy with immunotherapy may improve breast cancer tumor control by exploiting the tumor radio-induced immune priming. However, this requires the use of hypofractionated radiotherapy (3 × 8 Gy), increasing the risk of toxicity. Mini-GRID therapy (mini-GRT) is an innovative form of spatially fractionated radiation therapy (SFRT) characterized by narrow beam widths between 1 to 2 mm that promises a significant increase in normal tissue dose tolerances and could thereby represent a new alternative for preoperative breast cancer treatment. Mini-GRT has been successfully implemented at the Hospital de Santiago de Compostela (Spain) with a flattening filter-free LINAC (megavoltage x-rays).&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 dosimetry proof-of-concept study, we evaluate the feasibility of photon mini-GRT for preoperative breast cancer treatment. We also assess the clinical potential of mini-GRT and compare it with the current treatment standard of intensity-modulated radiotherapy (IMRT).&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;Seven unbiased breast cancer dosimetries of patients treated with stereotactic body radiotherapy (SBRT) (3 × 8 Gy, IMRT) were selected for the study. Photon mini-GRT was compared with SBRT using three main criteria: (i) the dose to organs at risk (OARs), (ii) the dose constraints dictated by normal tissue tolerance, and (iii) the lateral penumbra in OARs. Tumor coverage was evaluated in terms of normalized total dose at 8 Gy-fractions. The optimized SBRT by IMRT was realized at the Institut Curie, Paris, France. The dose in mini-GRT was calculated by means of Monte Carlo simulations based on the mini-GRT implementation realized at the University Hospital in Santiago de Compostela.&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;Compared to SBRT plans, mini-GRT resulted in a reduction of the mean dose to the lungs, heart, chest wall, and lymph nodes in the studied cases by a factor ranging from 50% to 100%. Additionally, valley, mean, and peak doses to normal tissues meet the dose tolerance limits for the considered OARs, the most challenging of all being the skin. The mean dose to the skin was reduced (20%–60% less) for most of the studied cases. Mini-GRT also yielded sharper lateral p","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2493-2506"},"PeriodicalIF":3.2,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17634","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054701","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":"Scanning K-edge subtraction (SKES) imaging with laser-compton x-ray sources","authors":"Trevor Reutershan,&nbsp;Christine V. Nguyen,&nbsp;Haytham H. Effarah,&nbsp;Eric C. Nelson,&nbsp;Kyle D. Chesnut,&nbsp;Christopher P. J. Barty","doi":"10.1002/mp.17638","DOIUrl":"10.1002/mp.17638","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;K-edge subtraction (KES) imaging is a dual-energy imaging technique that enhances contrast by subtracting images taken with x-rays that are above and below the K-edge energy of a specified contrast agent. The resulting reconstruction spatially identifies where the contrast agent accumulates, even when obscured by complex and heterogeneous distributions of human tissue. This method is most successful when x-ray sources are quasimonoenergetic and tunable, conditions that have traditionally only been met at synchrotrons. Laser-Compton x-ray sources (LCSs) are a compact alternative to synchrotron radiation with a quasimonoenergetic x-ray spectrum. One limitation in the clinical application of KES imaging with LCSs has been the extensive time required to tune the x-ray spectrum to two different energies.&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 introduce an imaging technique called scanning K-edge subtraction (SKES) that leverages the angle-correlated laser-Compton x-ray spectrum in the setting of mammography. The feasibility and utility of this technique will be evaluated through a series of simulation studies. The goal of SKES imaging is to enable rapid K-edge subtraction imaging using a laser-Compton x-ray source. The technique does not rely on the time-consuming process of tuning laser-Compton interaction parameters.&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;Laser-Compton interaction physics are modeled using conditions based on an X-band linear electron accelerator architecture currently under development using a combination of 3D particle tracking software and Mathematica. The resulting angle-correlated laser-Compton x-ray beam is propagated through digitally compressed breast phantoms containing iodine contrast-enhanced inserts and then to a digital flat-panel detector using a Matlab Monte Carlo propagation software. This scanning acquisition technique is compared to the direct energy tuning method (DET), as well as to a clinically available dual-energy contrast-enhanced mammography (CEM) system.&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;KES imaging in a scanning configuration using an LCS was able to generate a KES image of comparable quality to the direct energy tuning method. SKES was able to detect tumors with iodine contrast concentrations lower than what is clinically available today including lesions that are typically obscured by dense fibroglandular tissue. After normalizing to mean glandular dose, SKES is able to generate a KES image with equal contrast to CEM using only 3% of the ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2475-2492"},"PeriodicalIF":3.2,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061644","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":"Harmonic analysis and optimization for closed-loop superconducting shim coils of 7 T MRI magnet","authors":"Zijie Lin,&nbsp;Zhan Zhang,&nbsp;Jiaxin Li,&nbsp;Zhaoyao Gao,&nbsp;Zhenyu Chu,&nbsp;Yongsuo Liu,&nbsp;Panfeng Zhang,&nbsp;Leping Wu,&nbsp;Chao Zhou","doi":"10.1002/mp.17641","DOIUrl":"10.1002/mp.17641","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>High-resolution brain imaging is crucial in clinical diagnosis and neuroscience, with ultra-high field strength MRI systems (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≥</mo>\u0000 <mn>7</mn>\u0000 <mspace></mspace>\u0000 <mi>T</mi>\u0000 </mrow>\u0000 <annotation>$ ge 7 {mathrm{T}}$</annotation>\u0000 </semantics></math>) offering significant advantages for imaging neuronal microstructures. However, achieving magnetic field homogeneity is challenging due to engineering faults during the installation of superconducting strip windings and the primary magnet.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to design and optimize active superconducting shim coils for a 7 T animal MRI system, focusing on the impact of safety margin, size, and adjustability of the second-order shim coils on the MRI system's optimization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study employs a nonlinear optimization method to determine the parameters of the shim coils, considering the size of the coil, the level of undesired harmonics, and the whole number approximation of the turns in each coil. The study also conducts a thorough robustness analysis, examining the effects of coil winding accuracy, former processing accuracy, and assembly angle accuracy on the harmonic intensity of each coil.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The optimization design results for the 7 T MRI system's shim coils show that the magnetic field changes are less than 0.5 %. After second-order shimming and the harmonic coupling an, the low-order harmonics are minimized, resulting in an improved magnetic field peak-to-peak uniformity from 254.47 to 8.970 ppm.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The study successfully demonstrates the creation of a set of second-order shim coils for a 7 T animal MRI system through numerical optimization. The design outputs provide essential technological support for the development of a human whole-body 7 T MRI system, ensuring high-quality imaging at the neuronal level. The project also highlights the importance of considering manufacturing and assembly flaws in the shim coil design process to achieve effective shimming in practical engineering scenarios.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 5","pages":"3270-3279"},"PeriodicalIF":3.2,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061629","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":"Validity of one-time phantomless patient-specific quality assurance in proton therapy with regard to the reproducibility of beam delivery","authors":"Lukas Cornelius Wolter,&nbsp;Fabian Hennings,&nbsp;Jozef Bokor,&nbsp;Christian Richter,&nbsp;Kristin Stützer","doi":"10.1002/mp.17637","DOIUrl":"10.1002/mp.17637","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;Patient-specific quality assurance (PSQA) is a crucial yet resource-intensive task in proton therapy, requiring special equipment, expertise and additional beam time. Machine delivery log files contain information about energy, position and monitor units (MU) of all delivered spots, allowing a reconstruction of the applied dose. This raises the prospect of phantomless, log file-based QA (LFQA) as an automated replacement of current phantom-based solutions, provided that such an approach guarantees a comparable level of safety.&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 retrieve a reliable LFQA conclusion from a one-time plan delivery before treatment initiation, deviations between planned and logged parameters must either be persistent over all following treatment fractions or, in case of random fluctuations, must not have a relevant impact on the reconstructed dose distribution. We therefore investigated the reproducibility of log file parameters over multiple patient treatment fractions and compared the reconstructed dose distributions.&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;Log file variability was examined at both spot parameter and integral dose levels. The log files of 14 patient treatment plans were analyzed retrospectively for a total of 339 delivered fractions. From the recorded &lt;i&gt;x&lt;/i&gt;/&lt;i&gt;y&lt;/i&gt; position and MU parameters per spot, the respective mean difference to the planned value (accuracy) and the standard deviation (reproducibility) were calculated for 108,610 planned spots. The dose distributions reconstructed from the log files of each fraction were evaluated against the planned fraction dose using 3D gamma index analysis. The dose-based gamma pass rate &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mi&gt;Γ&lt;/mi&gt;\u0000 &lt;annotation&gt;$Gamma$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; was correlated with a new spot-based log file pass rate &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mi&gt;Λ&lt;/mi&gt;\u0000 &lt;annotation&gt;${Lambda}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. Beam timing information from the log files was used to quantify the total plan/field delivery time stability after excluding machine interlocks.&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 mean spot-wise accuracy with respect to distance from planned positions and MUs was (0.6 ± 0.3) mm and (0.0001 ± 0.0023) MU, respectively. The mean reproducibility of the observed single spot deviations was (0.2 ± 0","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 5","pages":"3173-3182"},"PeriodicalIF":3.2,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17637","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054705","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":"Model-based perfusion reconstruction with time separation technique in cone-beam CT dynamic liver perfusion imaging","authors":"Hana Haseljić,&nbsp;Robert Frysch,&nbsp;Vojtěch Kulvait,&nbsp;Thomas Werncke,&nbsp;Inga Brüsch,&nbsp;Oliver Speck,&nbsp;Jessica Schulz,&nbsp;Michael Manhart,&nbsp;Georg Rose","doi":"10.1002/mp.17652","DOIUrl":"10.1002/mp.17652","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 success of embolization, a minimally invasive treatment of liver cancer, could be evaluated in the operational room with cone-beam CT by acquiring a dynamic perfusion scan to inspect the contrast agent flow.&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 reconstruction algorithm must address the issues of low temporal sampling and higher noise levels inherent in cone-beam CT systems, compared to conventional CT.&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;Therefore, a model-based perfusion reconstruction based on the time separation technique (TST) was applied. TST uses basis functions to model time attenuation curves. These functions are either analytical or based on prior knowledge (PK), extracted using singular value decomposition of the classical CT perfusion data of animal subjects. To explore how well the PK can model perfusion dynamics and what the potential limitations are, the dynamic cone-beam CT (CBCT) perfusion scan was simulated from a dynamic CT perfusion scan under different noise levels. The TST method was compared to static reconstruction.&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;It was demonstrated on this simulated dynamic CBCT perfusion scan that a set consisting of only four basis functions results in perfusion maps that preserve relevant information, denoise the data, and outperform static reconstruction under higher noise levels. TST with PK would not only outperform static reconstruction but also the TST with analytical basis functions. Furthermore, it has been shown that only eight CBCT rotations, unlike previously assumed ten, are sufficient to obtain the perfusion maps comparable to the reference CT perfusion maps. This contributes to saving dose and reconstruction time. The real dynamic CBCT perfusion scan, reconstructed under the same conditions as the simulated scan, shows potential for maintaining the accuracy of the perfusion maps. By visual inspection, the embolized region was matching to that in corresponding CT perfusion maps.&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;CBCT reconstruction of perfusion scan data using the TST method has shown promising potential, outperforming static reconstructions and potentially saving dose by reducing the necessary number of acquisition sweeps. Further analysis of a larger cohort of patient data is needed to draw final conclusions regarding the expected advantages of the TST.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 &lt;/d","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2074-2088"},"PeriodicalIF":3.2,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.17652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054643","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}