Medical physics最新文献

{"title":"Risk-minimizing tube current and tube voltage modulation for CT: A simulation study","authors":"Edith Baader, Marc Kachelrieß","doi":"10.1002/mp.18047","DOIUrl":"10.1002/mp.18047","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The optimal tube voltage in clinical CT depends on the patient's attenuation and the imaging task. Although the patient's attenuation changes with view angle and longitudinal position of the X-ray tube, the tube voltage remains constant throughout the scan in current clinical practice. In general, the optimum tube voltage increases with patient diameter. For iodine-enhanced scans, the tube voltage is ideally low to increase contrast. However, 70 kV, the lowest clinically available tube voltage today, can not always be used due to tube current restrictions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To determine the additional relative reduction in effective dose of a tube voltage modulation in addition to a tube current modulation for unenhanced and iodine-enhanced CT scans.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>For patient models based on CT scans, the effective dose was simulated per projection for different voltages using Monte Carlo simulations. Using these dose data and analytical estimations of noise and iodine contrast, tube voltage and tube current curves were optimized for circular scans. For unenhanced scans, the dose-weighted noise was minimized, and for iodine-enhanced scans, the dose-weighted contrast-to-noise ratio (CNRD) was maximized. The effective dose values of the optimized tube voltage and tube current curves (riskTCTVM) were compared at the same noise or same contrast-to-noise ratio (CNR) to a pure tube current modulation minimizing the effective dose (riskTCM) and to conventional mAs-minimizing tube current modulation (mAsTCM).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>For unenhanced scans, riskTCTVM reduces the effective dose by less than <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>1</mn>\u0000 <mspace></mspace>\u0000 <mo>%</mo>\u0000 </mrow>\u0000 <annotation>$1 ,%$</annotation>\u0000 </semantics></math> compared to riskTCM at its optimal tube voltage. For iodine-enhanced scans, the effective dose benefit increases with the availability of low tube voltages and the eccentricity of the patient's anatomy. For a lowest voltage of 70 kV, we found average effective dose benefits of riskTCTVM to riskTCM of less than <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>3</mn>\u0000 <mspace></mspace>\u0000 <mo>%</mo","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935063","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":"Quality assurance and reporting for FLASH clinical trials: The experience of the FEATHER trial","authors":"Isabella Colizzi,&nbsp;Robert Schäfer,&nbsp;Jonas Brückner,&nbsp;Gaia Dellepiane,&nbsp;Martin Grossmann,&nbsp;Maximilian Körner,&nbsp;Antony John Lomax,&nbsp;David Meer,&nbsp;Benno Rohrer,&nbsp;Carla Rohrer Bley,&nbsp;Michele Togno,&nbsp;Serena Psoroulas","doi":"10.1002/mp.18100","DOIUrl":"10.1002/mp.18100","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Research on ultra-high dose rate (UHDR) radiation therapy has indicated its potential to spare normal tissue while maintaining equivalent tumor control compared to conventional treatments. First clinical trials are underway. The randomized phase II/III FEATHER clinical trial at the Paul Scherrer Institute in collaboration with the University of Zurich Animal Hospital is one of the first curative domestic animal trials to be attempted, and it is designed to provide a good example for human trials. However, the lack of standardized quality assurance (QA) guidelines for FLASH clinical trials presents a significant challenge in trial design.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This work aims to demonstrate the development and testing of QA and reporting procedures implemented in the FEATHER clinical trial.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We have expanded the clinical QA program to include UHDR-specific QA and additional patient-specific QA. Furthermore, we have modified the monitor readout to enable time-resolved measurements, allowing delivery log files to be used for dose and dose rate recalculations. Finally, we developed a reporting strategy encompassing relevant parameters for retrospective studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We evaluated our QA and reporting procedures with simulated treatments. This testing confirmed that our QA procedures effectively ensure the correct and safe delivery of the planned dose (3%/3 mm gamma criteria, pass <i>&gt;</i> 90%). Additionally, we demonstrated that we could reconstruct the delivered dose and dose rate using the delivery log files.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We developed and used in practice a comprehensive QA and reporting protocol for a FLASH clinical trial at the Paul Scherrer Institute. This work aims to establish guidelines and standardize reporting practices for future advancements in the FLASH-RT field.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935163","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":"X-ray multimeter performance under calibration laboratory conditions","authors":"John T. Stasko,&nbsp;Wesley S. Culberson","doi":"10.1002/mp.18106","DOIUrl":"10.1002/mp.18106","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Estimating dose delivered to patients for a typical mammographic or radiologic examination requires accurate knowledge of several beam quantities. X-ray multimeters (XMMs) are compact, solid-state semiconductor dosimeters that have become common for conventional QA measurements due to their ease of use.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>In this investigation, the performance of two XMMs in low-energy x-ray calibration beams was assessed, and the stability of the manufacturer's calibration over time was evaluated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An RTI Piranha and Radcal Accu-Gold+ with AGMS-DM+ sensor were used to measure air-kerma rates and half-value layers of UW-MO and UW-M series calibration beams. Measurement results were compared to reference values collected with standard instruments. The same measurements were repeated every 3–5 months for 2.5 years to evaluate whether the XMMs’ energy response changes over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>All air-kerma rate measurements and nearly all half-value layer measurements were within tolerance of the reference measurements. Both XMMs were satisfactorily stable over the course of the study, with all measured air-kerma rates within a 2% range relative to the reference for a specific beam. However, some drift in response was observed, particularly for the RTI Piranha.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Both XMMs met the performance standards provided by their respective manufacturers. An additional calibration would result in increased measurement accuracy for some beam series. One limitation of this study is that the detectors were not subject to more rigorous clinical conditions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18106","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935354","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":"A novel personalized time-varying biomechanical model for estimating lung tumor motion and deformation","authors":"Liang Tan,&nbsp;Wenyou Hu,&nbsp;Liyuan Chen,&nbsp;Huanli Luo,&nbsp;Shi Li,&nbsp;Bin Feng,&nbsp;Xin Yang,&nbsp;Yongzhong Wu,&nbsp;Ying Wang,&nbsp;Fu Jin","doi":"10.1002/mp.18086","DOIUrl":"10.1002/mp.18086","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;Accurate prediction of lung tumor motion and deformation (LTMD) is essential for precise radiotherapy. However, existing models often rely on static, population-based material parameters, overlooking patient-specific and time-varying lung biomechanics. Personalized dynamic models that capture temporal changes in lung elasticity are needed to improve LTMD prediction and guide treatment planning more effectively.&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 a patient-specific, time-varying biomechanical model to predict LTMD more accurately.&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;Four-dimensional computed tomography (4DCT) images from 27 patients, each with 10 breathing phases, were analyzed. A finite element model was developed, modeling lung as a hyper-elastic material and tumor as linear elastic. Lung elasticity parameters, including Young's modulus (&lt;i&gt;E&lt;/i&gt;) and Poisson's ratio (&lt;i&gt;v&lt;/i&gt;), were optimized for each phase using Efficient Global Optimization algorithm. Four functions were tested to model the variation of &lt;i&gt;E&lt;/i&gt; and &lt;i&gt;v&lt;/i&gt; across different phases. For each patient, average values of these parameters were computed, and their correlation with 11 clinical features was analyzed. The model's accuracy in predicting LTMD was evaluated using tumor center of mass motion error (ΔTCM) and volumetric Dice similarity coefficient (vDSC). Factors influencing the model's accuracy were investigated. Specifically, lung surface traction vector fields (STVFs) were calculated during the transition from end-expiration to end-inspiration phases, and their relationship with LTMD was also analyzed.&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 first-order Fourier function provided the best fit among four tested functions, with average R-squared values of 0.93 ± 0.03 for &lt;i&gt;E&lt;/i&gt; and 0.91 ± 0.03 for &lt;i&gt;v&lt;/i&gt;. The average values of &lt;i&gt;E&lt;/i&gt; and &lt;i&gt;v&lt;/i&gt; were significantly correlated with patient age. The model showed a mean ΔTCM of 1.47 ± 0.68 mm and a mean vDSC of 0.93 ± 0.02. A negative correlation was found between tumor deformation vDSC and ΔTCM (&lt;i&gt;r&lt;/i&gt; = −0.55, &lt;i&gt;p&lt;/i&gt; &lt; 0.05). Higher STVFs were observed near diaphragm and intercostal muscles, with correlations between STVFs and tumor motion amplitude (&lt;i&gt;r&lt;/i&gt; ≥ 0.92, &lt;i&gt;p&lt;/i&gt; &lt; 0.05).&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;These findings offer new insights into developing personalized, time-varying mot","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935029","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":"Feature level quantitative ultrasound and CT information fusion to predict the outcome of head & neck cancer radiotherapy treatment: Enhanced principal component analysis","authors":"Amir Moslemi,&nbsp;Aryan Safakish,&nbsp;Lakshmanan Sannachi,&nbsp;David Alberico,&nbsp;Gregory J. Czarnota","doi":"10.1002/mp.18078","DOIUrl":"10.1002/mp.18078","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;Radiation therapy is a common treatment for head and neck (H&amp;N) cancers. Radiomic features, which are determined from biomedical imaging, can be effective biomarkers used to assess tumor heterogeneity and have been used to predict response to treatment. However, most studies employ only a single biomedical imaging modality to determine radiomic features.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The objective of this study was to evaluate the effectiveness of radiomic feature fusion, combining quantitative ultrasound spectroscopy (QUS) and computed tomography (CT) imaging modalities, in predicting the outcomes of radiation therapy for H&amp;N cancer prior to start.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;An enhanced version of principal component analysis (EPCA) was proposed to fuse 70 radiomic features from CT and 476 radiomic features from QUS in order to predict the response to radiation therapy in patients with H&amp;N cancers (partial response vs. complete response). EPCA is a PCA method with Hessian matrix regularization and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;l&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;mo&gt;,&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;${{l}_{2,1 - 2}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; -regularization, and was proposed here for information fusion at a feature level. Leave-one-patient-out methodology with bootstrap was applied to conduct train-test analysis and fused features were used to train two (support vector machine (SVM) and k-nearest neighbor (KNN)) classifiers to build a predictive model in order to predict response to treatment for patients with H&amp;N cancers. Five-fold (5) cross validation was applied on the training set to tune the hyperparameters of SVM and KNN classifiers. Consequently, the performance of classifiers was evaluated by examining accuracy (ACC), F1-score (F1), balanced accuracy (BACC), Sensitivity (S&lt;sub&gt;n&lt;/sub&gt;), and Specificity (&lt;i&gt;S&lt;/i&gt;&lt;sub&gt;p&lt;/sub&gt;) metrics. Additionally, a two-sided &lt;i&gt;t&lt;/i&gt;-test was applied to the top principal components derived from EPCA methodology in order to assess the statistical significance of the selected components. The proposed method developed here was compared with minimum redundancy maximum relevance (mRMR) feature selection, conventional PCA, kernel PCA, autoen","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935355","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":"4D-MRI at 0.55T for internal target volume delineation in liver radiation therapy planning","authors":"Xin Miao,&nbsp;Pan Su,&nbsp;Michael A. Ohliger,&nbsp;Yang Yang,&nbsp;Jianing Pang,&nbsp;Alexandra E. Hotca,&nbsp;Thomas A. Hope,&nbsp;Cheng William Hong,&nbsp;Emily K. Bergsland,&nbsp;Mary Feng,&nbsp;Jessica E. Scholey","doi":"10.1002/mp.18069","DOIUrl":"10.1002/mp.18069","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;Low-field MRI provides superior soft-tissue contrast compared to CT while costing significantly less than high-field MRI, which makes it a more accessible option for MRI-guided radiation therapy planning. Four-dimensional MRI (4D-MRI) is a technique that has been increasingly adopted clinically for internal target volume (ITV) delineation in free-breathing liver radiotherapy planning, and it requires high spatial resolution and accurate respiratory phase differentiation to enable precise dose planning. The feasibility of 4D-MRI at low-field strength, specifically at 0.55T, has not been evaluated.&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 investigate the feasibility of 4D-MRI for ITV delineation in liver radiation therapy planning using a commercial 0.55T MRI scanner.&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 3D stack-of-stars T1-weighted sequence was implemented with two respiratory self-navigation methods: (1) k-space center point tracking (“k-center”) and (2) superior-inferior one-dimensional projection-based tracking (“SI-projection”). These methods were evaluated using ten phantom scans simulating diverse respiratory motion patterns and five liver tumor patient scans.&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;Both self-navigation approaches demonstrated strong correlation between the extracted self-gating signals (SGS) and ground-truth motion traces across four breathing patterns: sinusoidal waveform, typical respiration, drifting motion, and irregular breathing. For sinusoidal motion, measured ITV deviations were within 1.1% of the true ITV for both methods. In non-sinusoidal cases, ITV deviations remained within 2% except for two drifting motion cases where k-center SGS based reconstructions showed deviations of 6.0% and 2.4%. In liver tumor patient scans, both self-navigation techniques produced images with sufficient tumor delineation for treatment planning, with SI-projection SGS-based reconstructions yielding sharper images than k-center SGS-based reconstructions. ITV volumes contoured by two radiation oncologists showed strong and comparable inter-observer agreement across both techniques.&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;This study demonstrates that 4D-MRI at 0.55T is feasible and provides adequate image quality for ITV delineation. Self-navigation techniques play an important role in improving the sharpness of tumor boundaries, with SI-projection ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935031","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":"Simulating and correcting the pileup effect in deep-silicon photon-counting CT","authors":"Erik Fredenberg,&nbsp;Daniel Collin,&nbsp;Louis Carbonne,&nbsp;Mingye Wu,&nbsp;Bruno De Man,&nbsp;Fredrik Grönberg","doi":"10.1002/mp.18075","DOIUrl":"10.1002/mp.18075","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;Photon-counting computed tomography (CT) bears promise to substantially improve spectral and spatial resolution. One reason for the relatively slow evolution of photon-counting detectors in CT—the technology has been used in nuclear medicine and planar radiology for decades—is pulse pileup, that is, the random staggering of pulses, resulting in count loss and spectral distortion, which in turn cause image bias and reduced contrast-to-noise ratio (CNR). The deterministic effects of pileup can be mitigated with a pileup-correction algorithm, but the loss of CNR cannot be recovered, and must be minimized by hardware design. In the deep-silicon photon-counting detector, each pixel is split into depth segments, which enables optimization of the count rate per detector channel to reduce pileup. Virtual clinical trials are attracting growing interest for efficient evaluation of cutting-edge technology like the deep-silicon design, but a virtual trial requires an accurate simulation model of the imaging system, a digital twin, which captures all relevant aspects of the system over the full spectrum of clinical applications.&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 are developing a framework for digital twins of deep-silicon photon-counting CT to enable in-silico system evaluation and virtual clinical trials of the technology. The primary purpose of this study is to validate the framework with respect to pileup, that is, it is not a validation of the detector performance, but a validation of the correspondence between simulation and measurements from a prototype device. A secondary purpose is to employ the framework for investigating the impact of pileup on image quality and the effectiveness of a data-driven pileup correction algorithm.&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 pileup model that simulates individual photon events in accordance with the semi-nonparalyzable detector behavior was integrated into the CatSim environment. Measured count data from a prototype deep-silicon system were used to validate the simulation framework with respect to pileup. A typical image chain was integrated into the framework, including material decomposition (MD) and data-driven pileup correction. Images of a software phantom were generated to illustrate the effect of pileup on images and to assess the effectiveness of the pileup correction algorithm.&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;Simulated data were described well by the semi-nonparalyzable detector model and exhibited deviations to the measured co","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935095","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":"Retinal vessel segmentation driven by structure prior tokens","authors":"Jiaqi Guo,&nbsp;Xinyu Guo,&nbsp;Quanyong Yi,&nbsp;Huaying Hao,&nbsp;Yitian Zhao","doi":"10.1002/mp.18018","DOIUrl":"10.1002/mp.18018","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;Accurate retinal vessel segmentation from Optical Coherence Tomography Angiography (OCTA) images is vital in ophthalmic medicine, particularly for the early diagnosis and monitoring of diseases, such as diabetic retinopathy and hypertensive retinopathy. The retinal vascular system exhibits complex characteristics, including branching, crossing, and continuity, which are crucial for precise segmentation and subsequent medical analysis. However, traditional pixel-wise vessel segmentation methods focus on learning how to effectively divide each pixel into different categories, relying mainly on local features, such as intensity and texture, and often neglecting the intrinsic structural properties of vessels. This can cause suboptimal segmentation accuracy and robustness, particularly when handling low-contrast, noisy, or pathological images.&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 integrate structural priors into a segmentation framework. Prior embeddings are used to guide the segmentation process, which encode the typical morphology and topological structure of blood vessels. Incorporating these embeddings can improve the accuracy of retinal vessel segmentation, particularly in challenging areas such as small vessels and regions with ambiguous boundaries. This approach could help to preserve the integrity and continuity of the vascular structure, resulting in more reliable and precise segmentation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study adopts a generative image segmentation framework. A structured representation in a latent embedding space is presented to explore retinal vessel priors. On this basis, a prior-driven retinal vessel segmentation network is introduced. First, the retinal vessel priors from ground truth data are learned, which are encoded as embedding tokens through a residual quantization reconstruction network. The learned priors are stored in a codebook. In our network, a raw OCTA image is transformed into semantic features using an encoder. Each semantic feature is subsequently represented by a set of embedding tokens from the codebook. Finally, the retinal vessels are reconstructed, preserving the integrity and continuity of the vascular structures using the learned structural priors.&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 performance of our proposed network was assessed across three OCTA datasets: publically available ROSE-1 and ROSE-2, and the private dataset OCTA-Z. Both quantitative and qualitative evaluations revealed that our network outperformed current state-of-the-art methods. In particular, our approach achieved ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935350","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":"Super-resolution PET/CT radiomics nomogram for predicting spread through air spaces in stage I lung adenocarcinoma","authors":"Cheng Zheng,&nbsp;Liuwei Xu,&nbsp;Yang Lin,&nbsp;Jiangfeng Miao,&nbsp;Yujie Cai,&nbsp;BingShu Zheng,&nbsp;YiCong Wu,&nbsp;Chen Shen,&nbsp;ShanLei Bao,&nbsp;Jun liu,&nbsp;ZhongHua Tan,&nbsp;ChunFeng Sun","doi":"10.1002/mp.18077","DOIUrl":"10.1002/mp.18077","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Super-resolution (SR) reconstruction-based positron emission tomography (PET) imaging has been widely applied in the field of computer vision. However, their definitive clinical benefits have yet to be validated. Radiomics-based modeling provides an effective approach to evaluate the clinical utility of SRPET imaging.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aimed to evaluate the role of a multimodal radiomics nomogram based on SR-enhanced fluorine-18 fluorodeoxyglucose PET/computed tomography ([¹⁸F]FDG PET/CT) in predicting the status of spread through air spaces (STAS) preoperatively in patients with clinical stage I lung adenocarcinoma (LUAD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 131 clinical stage I lung cancer patients were retrospectively included and randomly divided into two cohorts: training (<i>n</i> = 91) and test (<i>n</i> = 40). A transfer learning network enhanced PET image resolution to produce preoperative SRPET images. Radiomics features were extracted from SRPET, PET, and CT images. A radiomics nomogram was developed using clinically independent predictors and the optimal radiomics signature. Its predictive performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Five models were constructed to predict STAS status. Among these, the comprehensive model—which integrated 1 clinical feature, 6 CT features, and 14 SRPET features—demonstrated the highest area under the curve (AUC) values of 0.948 in the training cohort and 0.898 in the test cohort. It outperformed previous models in net benefits on calibration and decision curves. These findings support developing a nomogram for visualizing STAS prediction preoperatively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The SRPET/CT radiomics nomogram effectively predicted STAS in clinical stage I LUAD and may aid in guiding individualized therapy plans before surgical intervention.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935030","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":"Validation of the collapsed-cone superposition for whole-body patient-specific dosimetry in [177Lu]Lu-PSMA-617 radionuclide therapy","authors":"Aya Terro,&nbsp;Solène Perret,&nbsp;Arthur Dumouchel,&nbsp;David Tonnelet,&nbsp;Agathe Edet-Sanson,&nbsp;Pierre Vera,&nbsp;Pierre Decazes,&nbsp;Arnaud Dieudonné","doi":"10.1002/mp.18076","DOIUrl":"10.1002/mp.18076","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 dosimetry in radiopharmaceutical therapy (RPT) offers a promising approach to optimize the balance between treatment efficacy and toxicity. The introduction of 360° CZT gamma cameras enables the development of personalized dosimetry studies using whole-body single photon emission computed tomography and computed tomography (SPECT/CT) data.&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 proposes to validate the collapsed-cone superposition (CCS) approach against Monte Carlo (MC) simulations for whole-body dosimetry of [177Lu]Lu-PSMA-617 therapy in patients with metastatic castration resistant prostate cancer (mCRPC).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Materials and methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Thirty patients with mCRPC were retrospectively included in this study. SPECT/CT images were acquired after the infusion of [177Lu]Lu-PSMA-617 therapy. SimpleDose was used to generate dose-rate maps (mGy/h) from a single SPECT/CT scan. The dosimetry relies on the CCS approach, which adjusts dose-point kernels according to tissue densities. Organ and lesion delineation were automated using the nnU-Net V2 neural network. MC simulations were performed with GATE 10 for 10&lt;sup&gt;8&lt;/sup&gt; events. To assess the impact of density-scaled DPK on the accuracy of the dosimetry, we implement a simplified version of CCS, denoted as &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;S&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;S&lt;/mi&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$CC{S}_{ST}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, which assumes a homogeneous soft tissue medium without incorporating the patient-specific density information derived from the CT image. The comparison between CCS, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;mi&gt;C&lt;/mi&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;S&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;S&lt;/mi&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$CC{S}_{ST}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and MC was conducted","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 8","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/mp.18076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935094","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}