Physics in medicine and biology最新文献

{"title":"Myocardial<i>T</i>₁mapping at 5T using multi-inversion recovery real-time spoiled GRE.","authors":"Linqi Ge, Yihang Zhang, Huibin Zhu, Lang Zhang, Yihang Zhou, Haifeng Wang, Dong Liang, Hairong Zheng, Yanjie Zhu","doi":"10.1088/1361-6560/add986","DOIUrl":"10.1088/1361-6560/add986","url":null,"abstract":"<p><p><i>Objective.</i>To develop an accurate myocardial<i>T</i>₁mapping technique at 5T using Look-Locker-based multiple inversion-recovery with the real-time spoiled gradient echo (GRE) acquisition.<i>Approach.</i>The proposed<i>T</i>₁mapping technique (mIR-rt) samples the recovery of inverted magnetization using the real-time GRE and the images captured during diastole are selected for<i>T</i>₁fitting. Multiple-inversion recoveries are employed to increase the sample size for accurate fitting. The<i>T</i>₁mapping method was validated using Bloch simulation, phantom studies, and in 16 healthy volunteers at 5T.<i>Main Results.</i>In both simulation and phantom studies, the<i>T</i>₁values measured by mIR-rt closely approximate the reference<i>T</i>₁values, with errors less than 3%, while the conventional MOLLI sequence underestimates<i>T</i>₁values. The myocardial<i>T</i>₁values at 5T are 1553 ± 52 ms, 1531 ± 53 ms, and 1526 ± 60 ms (mean ± standard deviation) at the apex, middle, and base, respectively. The<i>T</i>₁values measured by MOLLI (1350 ± 48 ms, 1349 ± 47 ms, and 1354 ± 45 ms at the apex, middle, and base) were significantly lower than those of mIR-rt with<i>p</i>< 0.001 for all three layers. The mIR-rt sequence method used in our study provides high reproducibility, particularly in the middle slices, supporting its practical relevance for myocardial<i>T</i>₁mapping.<i>Significance.</i>The proposed method is feasible for myocardial<i>T</i>₁mapping at 5T and provides better accuracy than the conventional MOLLI sequence.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dosimetric commissioning of small animal FLASH radiation research platform.","authors":"Mohammad-Ali Tajik Mansoury, Daniel Sforza, John Wong, Iulian Iordachita, Mohammad Rezaee","doi":"10.1088/1361-6560/add641","DOIUrl":"10.1088/1361-6560/add641","url":null,"abstract":"<p><p><i>Objective.</i>The FLASH-SARRP, a new small animal radiation research platform has been designed to support conventional, high and ultrahigh dose-rate kV x-rays for preclinical research. This self-shielded system features two high-capacity x-ray sources with rotating-anode technology. This study characterizes the dosimetric and mechanical performances of the system for preclinical FLASH radiation research.<i>Approach.</i>Mechanical alignment of two x-ray tubes was performed using a custom-designed jig by aligning the outlet ports of the tube housings. Alignment of mechanical and radiation centers was evaluated by scanning a highly-collimated slit across the focal-spot. The linearity of the x-ray tube voltage, current and exposure-time was evaluated using silicon diode and ion-chamber detectors. Dosimetric characteristics of beam e.g. output linearity, depth dose-rate and profiles were measured using calibrated radiochromic films, thermoluminescence, and ion-chamber detectors in kV solid-water phantom or air, with and without external energy filtration. Dose-rate uniformity, flatness, symmetry, beam width, and penumbra were assessed for single and parallel-opposed x-ray beams across various field sizes.<i>Results.</i>The x-ray sources were aligned at 0.3 mm accuracy. The radiation beam center was within 1.0 mm of mechanical center. Beam output was highly linear with wide ranges of tube current (5-630 mA) and exposure-time (5-6300 ms), supporting accurate dose-rate and dose adjustments. The FLASH-SARRP supports a wide range of dose-rates from <1 Gy s^-1to 100 Gy s^-1, depending on field size. The uniformity of the depth and crossbeam dose-rates is ±3.6 Gy s^-1and ±1.5 Gy s^-1between 5-15 mm phantom depth without and with external filter, respectively.<i>Significance.</i>The FLASH-SARRP provides desirable dosimetric performance for small animal irradiation, supporting both conventional and FLASH dose-rate across field sizes from 5 mm-diameter circular to 20 mm-square apertures. This platform enables comparative studies between FLASH and conventional dose-rates in small animal (e.g. mouse) models.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144063552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting and monitoring response to head and neck cancer radiotherapy using multimodality imaging and radiobiological digital twin simulations.","authors":"Eric Aliotta, Jeho Jeong, Ramesh Paudyal, Milan Grkovski, Bill Diplas, James Han, Vaios Hatzoglou, Michalis Aristophanous, Nadeem Riaz, Heiko Schöder, Nancy Y Lee, Amita Shukla-Dave, Joseph O Deasy","doi":"10.1088/1361-6560/add9de","DOIUrl":"10.1088/1361-6560/add9de","url":null,"abstract":"<p><p><i>Objective.</i>To predict radiotherapy treatment response for head and neck cancer (HNC) using multimodality imaging and personalized radiobiological modeling.<i>Approach.</i>A mechanistic radiobiological model was combined with multi-modality imaging data from diffusion weighted-magnetic resonance imaging and positron emission tomography scans with [¹⁸F]Fluorodeoxyglucose (FDG) and [¹⁸F]Fluoromisonidazole (FMISO) tracers to develop personalized treatment response models for human papilloma virus associated HNC patients undergoing chemo-radiotherapy. Models were initialized to incorporate patient-specific imaging and updated to reflect longitudinal measurements of nodal gross tumor volume throughout treatment. Prediction accuracy was assessed based on mean absolute error (MAE) of weekly volume predictions and in predicting locoregional recurrence (LRR) following treatment.<i>Main results.</i>Personalized modeling based on pretreatment imaging significantly improved longitudinal volume prediction accuracy and correlation with measurement compared with a generic population model (MAE = 23.4 ± 10.0% vs 24.9 ± 9.0%,<i>p</i>= 0.002 on paired<i>t</i>-test,<i>R</i>= 0.82 vs 0.72). Adding volume measurements from weeks 1 and 2 further improved prediction accuracy for subsequent weeks (MAE = 12.5 ± 8.1%, 10.7 ± 9.9%). When incorporating feedback with longitudinal measurements, penalizing large deviations from pretreatment model parameters using a variational regularization method was necessary to maintain model stability. Model-predicted volumes based on baseline + week-1 information significantly improved LRR prediction compared with week-1 volume data alone (area under the curve, AUC = 0.83 vs 0.77,<i>p</i>= 0.03) and was similar to prediction using week-3 volume data (AUC = 0.83 vs 0.85,<i>p</i>= non-significant).<i>Significance.</i>The proposed approach, which integrates clinical imaging and radiobiological principles, could be a basis to guide pretreatment prescription personalization as well as on-treatment adaptations.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial dose-distribution-based risk mapping to predict moist desquamation in breast radiotherapy.","authors":"Aria Malhotra, Elisa K Chan, Alan Nichol, Cheryl Duzenli","doi":"10.1088/1361-6560/add985","DOIUrl":"10.1088/1361-6560/add985","url":null,"abstract":"<p><p><i>Objective.</i>A relationship between the regional spatial distribution of skin dose and the development of moist desquamation (MD) was established for patients treated with breast radiotherapy.<i>Approach.</i>A 56-patient dataset was used to develop and validate a dose-distance based metric to predict MD. Dose distributions for the skin were extracted from AcurosXB treatment plans, and patient reported outcomes were used to classify the incidence of MD across the whole breast and then more specifically in the inferior breast. The sensitivity and specificity of the metric was compared against dose-area (A38 Gy ⩽ 50 cm²) and dose-volume (V105% ⩽ 2% of the breast volume) predictive metrics with the same dataset.<i>Main results.</i>With a sensitivity of 70% and a specificity of 72%, the dose-distance metric outperformed the dose-area (45%, 55%) and dose-volume (43%, 56%) predictive metrics. The test performance improves to a sensitivity and specificity of 81% when excluding the full coverage breast support devices that confounded the skin dose identification in the analysis.<i>Significance.</i>This metric offers regional MD prediction and risk mapping to highlight regions at high risk of developing severe skin toxicity and is suitable for implementation within the treatment planning process.This work is based on data acquired for the following clinical trials: ClinicalTrials.gov NCT04543851 and NCT04257396.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"First experimental test of a coded-mask gamma camera for proton therapy monitoring.","authors":"Magdalena Kołodziej, Stephan Brons, Mikołaj Dubiel, George N Farah, Alexander Fenger, Ronja Hetzel, Jonas Kasper, Monika Kercz, Barbara Kołodziej, Linn Mielke, Gabriel Ostrzołek, Magdalena Rafecas, Jorge Roser, Katarzyna Rusiecka, Achim Stahl, Vitalii Urbanevych, Ming-Liang Wong, Aleksandra Wrońska","doi":"10.1088/1361-6560/adc96b","DOIUrl":"10.1088/1361-6560/adc96b","url":null,"abstract":"<p><p><i>Objective.</i>The objective of the presented study was to evaluate the feasibility of a coded-mask (CM) gamma camera for real-time range verification in proton therapy, addressing the need for a precise and efficient method of treatment monitoring.<i>Approach.</i>A CM gamma camera prototype was tested in clinical conditions. The setup incorporated a scintillator-based detection system and a structured tungsten collimator. The experiment consisted of the irradiation of PMMA phantom with proton beams of energies ranging from 70.51 to 108.15 MeV. Experimental data were benchmarked against Monte Carlo simulations. The distal falloff position (DFP) was determined for both experimental data and simulations.<i>Main results.</i>The tested CM camera achieved a statistical precision of DFP determination of 1.7 mm for 10⁸protons, which is consistent with simulation predictions, despite hardware limitations such as non-functional detector pixels. Simulations indicated that a fully operational setup would further improve the performance of the detector. The system demonstrated rate capability sufficient for clinical proton beam intensities and maintained performance without significant dead time.<i>Significance.</i>This study validates the potential of the CM gamma camera for real-time proton therapy monitoring. The technology promises to enhance treatment accuracy and patient safety, offering a competitive alternative to existing approaches such as single-slit and multi-slit systems.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dose adaptation to compensate for cumulative intra-fraction motion effects in online adaptive radiotherapy.","authors":"Erik van der Bijl, Robert Jan Smeenk, Lukas Schröder, Jan-Jakob Sonke, Uulke A van der Heide, Tomas Janssen","doi":"10.1088/1361-6560/add984","DOIUrl":"10.1088/1361-6560/add984","url":null,"abstract":"<p><p><i>Objective.</i>The objective of this work was to investigate the feasibility of using 0 mm PTV margin in online adaptive radiotherapy for the first fractions, in combination with treatment-specific local compensation of accumulated underdosage to the target in the last fraction.<i>Approach.</i>Intrafraction motion patterns and delineations of twelve patients with prostate cancer were selected to cover a range of observed systematic and random inter- and intrafraction motion patterns. Treatment plans with 0 and 3 mm margins were created and dose was accumulated rigidly using the observed motion patterns. For the dose-adaptation approach a plan was created for the last treatment fraction locally compensating for dose missed in the previous fractions. Robustness of the accumulation was estimated by simulating treatments with random registration errors added to the observed registrations, with standard deviations of 0.5 and 1.0 mm.<i>Main results.</i>Target coverage of the dose-adaptive workflow was not-significantly below the standard approach, and at the desired level but for the two patients with the largest systematic prostate motion. The near-maximum dose to the organs at risk is lowered for all patients with a median of 1.5 Gy. The total volume receiving 95% of the prescribed dose was reduced by 15% to 1.6 times the clinical target volume indicating better conformity, at the cost of an increased near-maximum dose to the target. However, the dose-adaptive plan was less robust leading to a median 0.5% decrease in dose to the target also with decreasing robustness with larger motion patterns.<i>Significance.</i>The results demonstrate that a post-hoc correction of missed dose leads to an overall lower dose to nearby organs at risk at the cost of target dose near-maximum dose, making it a feasible approach for consideration.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the redundancy of Radon transform using a set of partial derivative equations: could we precisely reconstruct the image from a sparse-view projection without any image prior?","authors":"Xuanqin Mou, Jiayu Duan","doi":"10.1088/1361-6560/add839","DOIUrl":"10.1088/1361-6560/add839","url":null,"abstract":"<p><p>In this study, we propose a universal<i>n</i>th order partial differential equation (PDE) of 2D Radon transform to disclose the correlation of Radon transform among neighboring integration line. Specifically, a CT geometry of dual centers of rotation is introduced to formulate an object independent PDE that presents the local correlation of Radon transform on the variables of distance and angle, named LCE (local correlation equation). The LCE is directly available to divergent beam CT geometries, e.g. fan beam CT or cone beam CT. In this case, one rotation center is set at the focal spot, so that the LCE becomes a general PDE for actually used CT systems with single rotation center (origin). Thus, we deduce two equivalent LCE forms for two widely used CT geometries, i.e. cLCE for circular scanning trajectory and sLCE for stationary linear array scanning trajectory, respectively. The LCE also explores the redundancy property existed in Radon transform. One usage of the LCE is that it supports a sparse-view projection could contain enough information of complete projection, and hence projection completeness in CT scanning would be no longer needed. In this regard, based on the circular scanning trajectory, we explore whether the cLCE is able to solve sparse-view problem without the help of image prior. We propose a discrete cLCE based interpolation scheme that can be solved by a matrix inversion based on Lagrange multiplier method. The analysis on the matrix inversion shows that the interpolation matrix is full rank although the condition number of the matrix is larger when the sparsity increases. The fact suggests that sparse-view CT projection indeed contains enough information of complete projection, which is independent of the scanned object. Moreover, a unified reconstruction framework combining a regularized iterative reconstruction with the cLCE based interpolation is also proposed to cope with higher sparsity level. In experimental validation, we chose 1/4 and 1/8 sparsity to verify the discrete cLCE interpolation method and the unified reconstruction scheme, respectively. The results confirm that the sparse-view projection is feasible to realize a comparable reconstruction as from complete projection based on the LCE. It would be expected that combining the LCE property will boost various researches on CT reconstructions in the future.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty quantification for deep learning-based metastatic lesion segmentation on whole body PET/CT.","authors":"Brayden Schott, Victor Santoro-Fernandes, Žan Klaneček, Scott Perlman, Robert Jeraj","doi":"10.1088/1361-6560/add9df","DOIUrl":"10.1088/1361-6560/add9df","url":null,"abstract":"<p><p><i>Objective.</i>Deep learning models are increasingly being implemented for automated medical image analysis to inform patient care. Most models, however, lack uncertainty information, without which the reliability of model outputs cannot be ensured. Several uncertainty quantification (UQ) methods exist to capture model uncertainty. Yet, it is not clear which method is optimal for a given task. The purpose of this work was to investigate several commonly used UQ methods for the critical yet understudied task of metastatic lesion segmentation on whole body PET/CT.<i>Approach.</i>59 whole body⁶⁸Ga-DOTATATE PET/CT images of patients undergoing theranostic treatment of metastatic neuroendocrine tumors were used in this work. A 3D U-Net was trained for lesion segmentation following five-fold cross validation. Uncertainty measures derived from four UQ methods-probability entropy, Monte Carlo dropout, deep ensembles, and test time augmentation-were investigated. Each uncertainty measure was assessed across four quantitative evaluations: (1) its ability to detect artificially degraded image data at low, medium, and high degradation magnitudes; (2) to detect false-positive (FP) predicted regions; (3) to recover false-negative (FN) predicted regions; and (4) to establish correlations with model biomarker extraction and segmentation performance metrics.<i>Main</i><i>results.</i>Test time augmentation and probability entropy respectively achieved the highest and lowest degraded image detection at low (AUC = 0.54 vs. 0.68), medium (AUC = 0.70 vs. 0.82), and high (AUC = 0.83 vs. 0.90) degradation magnitudes. For detecting FPs, all UQ methods achieve strong performance, with AUC values ranging narrowly between 0.77 and 0.81. FN region recovery performance was strongest for test time augmentation and weakest for probability entropy. Performance for the correlation analysis was mixed, where the strongest performance was achieved by test time augmentation for SUV_totalcapture (ρ= 0.57) and segmentation Dice coefficient (ρ= 0.72), by Monte Carlo dropout for SUV_meancapture (ρ= 0.35), and by probability entropy for segmentation cross entropy (ρ= 0.96).<i>Significance.</i>Overall, test time augmentation demonstrated superior UQ performance and is recommended for use in metastatic lesion segmentation task. It also offers the advantage of being post hoc and computationally efficient. In contrast, probability entropy performed the worst, highlighting the need for advanced UQ approaches for this task.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A semiclassical model of the immediate temperature distribution surrounding the track of heavy ions with therapeutic energies.","authors":"Martin Rädler, Niayesh Afshordi, Reza Taleei, Katia Parodi, Ramin Abolfath, Julie Lascaud","doi":"10.1088/1361-6560/add83b","DOIUrl":"10.1088/1361-6560/add83b","url":null,"abstract":"<p><p><i>Objective.</i>Spikes of high temperature and pressure are created in the vicinity of heavy ions, especially at the Bragg peak. The expected subsequent thermoacoustic effects are however not well understood. In particular, the distribution of the densely packed primary interactions has not been considered in molecular dynamics (MDs) simulations or shock wave solutions. In this work, we derive a dedicated model to describe the primary interactions and their radial distribution, applicable to the modeling of acoustic and thermodynamic effects at the nanoscale.<i>Approach.</i>Starting from first principles, we assemble a semiclassical model of the energy loss of the primary heavy ions, consistent with the expected linear energy transfer and parametrized with the distance from the track. Based on the interaction energies, we then disentangle the primary energy depositions, i.e. the primary excitations and binding energies of the secondary electrons. Thereby we obtain the radial distribution of the primary interactions, independent of empirical parameters. Our theoretical description is kept general, however, numerical results are presented for protons stopped in water. Validity and uncertainties of our model are analyzed in detail.<i>Main results.</i>Following from the sought radial energy distribution, we find that the primary interactions are the dominant energy depositions below a radius of 1 nm. This can give rise to thermal spikes as high as 10³ K even for low-<i>Z</i>projectiles, such as protons stopped in water. The presented model is valid down to primary proton energies of approximately 0.5 MeV.<i>Significance.</i>Our results can be used to revise the thermodynamic modeling at the nanoscale and investigate their potential involvement in the intriguing biological response to novel modalities such as FLASH or spatially fractionated radiotherapies. Also, our findings can be integrated into microscale track structure Monte Carlo codes, or<i>ab initio</i>MD simulations, for more accurate modeling in the nanometer domain.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144015679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DP-MDM: detail-preserving MR reconstruction via multiple diffusion models.","authors":"Mengxiao Geng, Jiahao Zhu, Ran Hong, Qiqing Liu, Dong Liang, Qiegen Liu","doi":"10.1088/1361-6560/add83a","DOIUrl":"10.1088/1361-6560/add83a","url":null,"abstract":"<p><p><i>Objective.</i>Magnetic resonance imaging (MRI) is critical in medical diagnosis and treatment by capturing detailed features, such as subtle tissue changes, which help clinicians make precise diagnoses. However, the widely used single diffusion model has limitations in accurately capturing more complex details. This study aims to address these limitations by proposing an efficient method to enhance the reconstruction of detailed features in MRI.<i>Approach.</i>We present a detail-preserving reconstruction method that leverages multiple diffusion models (DP-MDM) to extract structural and detailed features in the k-space domain, which complements the image domain. Since high-frequency information in k-space is more systematically distributed around the periphery compared to the irregular distribution of detailed features in the image domain, this systematic distribution allows for more efficient extraction of detailed features. To further reduce redundancy and enhance model performance, we introduce virtual binary masks with adjustable circular center windows that selectively focus on high-frequency regions. These masks align with the frequency distribution of k-space data, enabling the model to focus more efficiently on high-frequency information. The proposed method employs a cascaded architecture, where the first diffusion model recovers low-frequency structural components, with subsequent models enhancing high-frequency details during the iterative reconstruction stage.<i>Main results.</i>Experimental results demonstrate that DP-MDM achieves superior performance across multiple datasets. On the<i>T1-GE brain</i>dataset with 2D random sampling at<i>R</i>= 15, DP-MDM achieved 35.14 dB peak signal-to-noise ratio (PSNR) and 0.8891 structural similarity (SSIM), outperforming other methods. The proposed method also showed robust performance on the<i>Fast-MRI</i>and<i>Cardiac MR</i>datasets, achieving the highest PSNR and SSIM values.<i>Significance.</i>DP-MDM significantly advances MRI reconstruction by balancing structural integrity and detail preservation. It not only enhances diagnostic accuracy through improved image quality but also offers a versatile framework that can potentially be extended to other imaging modalities, thereby broadening its clinical applicability.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}