Magnetic Resonance Materials in Physics, Biology and Medicine最新文献

{"title":"Open-source quality assurance for multi-parametric MRI: a diffusion analysis update for the magnetic resonance biomarker assessment software (MR-BIAS).","authors":"James C Korte, Stanley A Norris, Madeline E Carr, Lois Holloway, Glenn D Cahoon, Ben Neijndorff, Petra van Houdt, Rick Franich","doi":"10.1007/s10334-025-01252-4","DOIUrl":"10.1007/s10334-025-01252-4","url":null,"abstract":"<p><strong>Objective: </strong>To validate the automated analysis of magnetic resonance imaging (MRI) diffusion phantoms with an updated version of the magnetic resonance biomarker assessment software (MR-BIAS), an open-source tool initially developed for the analysis of MRI relaxometry phantoms.</p><p><strong>Materials and methods: </strong>The updated MR-BIAS was validated against two published diffusion weighted MRI datasets: (i) a single-site study (n = 48) was used for validation of apparent diffusion coefficients (ADC) and to identify optimal region of interest (ROI) selection, and (ii) a multi-centre multi-vendor study including diffusion imaging from a shared benchmark protocol (n = 49) and site-specific protocols (n = 43). ADC analysis compared both datasets with ROIs manually matched to the original studies, and with automatically detected optimal ROIs.</p><p><strong>Results: </strong>MR-BIAS ADC values were statistically equivalent (p < 0.05) to original studies within tolerances (manual ROI, automatic ROI) for the single-site study (± 0.01, ± 6 μm²/s) and for the multi-vendor study for benchmark (± 4, ± 7 μm²/s) and site-specific (± 3, ± 6 μm²/s) protocols. The optimal ROI was a central cylinder (height = 10mm, diameter = 10mm). MR-BIAS ADC summary metrics were comparable to those of the original studies.</p><p><strong>Discussion: </strong>MR-BIAS can automatically and accurately perform ADC analysis of diffusion phantoms, making the software suitable for the quality assurance of multi-centre studies of multi-parametric MRI.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"639-651"},"PeriodicalIF":2.5,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443916/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144015508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing fatty tissue in quantitative susceptibility mapping of human knee cartilage.","authors":"Cornelia Säll, Emelie Lind, Emma Einarsson, Aleksandra Turkiewicz, Martin Englund, Pernilla Peterson","doi":"10.1007/s10334-025-01280-0","DOIUrl":"https://doi.org/10.1007/s10334-025-01280-0","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the effects of excluding fatty tissue in QSM of human knee cartilage.</p><p><strong>Materials and methods: </strong>Gradient echo images from 18 knee-healthy volunteers were acquired, from which chemical shift corrected field perturbation maps were calculated. Based on these, QSM maps were reconstructed using morphology enabled dipole inversion and one of three masking alternatives: (1) excluding no tissue, (2) excluding bone marrow, and (3) excluding all fatty tissues. The slope of a linear regression [ppm/%] between susceptibility values and the relative distance from the bone surfaces was used as a measurement of contrast between cartilage layers. The average differences in slopes between methods are reported with 95% confidence intervals.</p><p><strong>Results: </strong>The expected susceptibility differences between cartilage layers from literature were observed for all tested reconstruction techniques. However, smaller slopes (average difference (confidence interval)) were detected when either all fatty tissue (- 0.090 (- 0.121, - 0.059) ppm/%) or bone marrow (- 0.088 (- 0.121, - 0.055) ppm/%) was excluded from reconstruction.</p><p><strong>Discussion: </strong>All tested methods result in adequate image quality in QSM of knee cartilage. However, exclusion of fatty tissue decreased the susceptibility contrast between cartilage layers. Assuming that phase contributions from chemical shift are addressed, inclusion of fatty tissue may be preferable.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144698951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Myelin water imaging from accelerated 3D-GRASE acquisitions using subspace constrained reconstruction.","authors":"Riwaj Byanju, Stefan Klein, Alexandra Cristobal-Huerta, Juan A Hernandez-Tamames, Dirk H J Poot","doi":"10.1007/s10334-025-01276-w","DOIUrl":"https://doi.org/10.1007/s10334-025-01276-w","url":null,"abstract":"<p><strong>Purpose: </strong>Quantitative MRI markers, such as myelin water fraction (MWF) and geometric mean <math><msub><mi>T</mi> <mn>2</mn></msub> </math> (IET2) (the intra-/extra-cellular water compartment), can be biomarkers for various brain disorders. However, these markers require acquiring multi-echo spin-echo images which requires long scan times. Undersampled 3D-GRAdient Echo and Spin Echo (3D-GRASE) scans with parallel imaging have been used for faster scans. Still, further acceleration is desirable. Reconstruction techniques that utilize redundancy along the echoes could be employed to achieve artifact-free maps at higher acceleration. This work examines the possibility of using one such technique, subspace constrained reconstruction (SCR), for further accelerating the 3D-GRASE scan.</p><p><strong>Methods: </strong>We propose two techniques to undersample the 3D-GRASE acquisition and exploit the redundancy across echoes. We retrospectively undersample fully sampled data from phantom and in-vivo acquisition to test these techniques. We compared our results for mapping MWF and IET2 to a reference multi-spin-echo technique. Additionally, we compare the proposed, state-of-the-art, and reference techniques with prospectively undersampled in-vivo acquisitions.</p><p><strong>Results: </strong>The RMSD of the MWF in retrospectively undersampled data was worse for the proposed techniques than the state-of-the-art. However, for IET2, RMSD was similar or slightly improved. In prospectively undersampled scans, undersampling artifacts deteriorated MWF maps, but not IET2 maps, which were within 10 ms of the reference map.</p><p><strong>Conclusion: </strong>Our findings suggest that exploiting redundancy across echoes does not result in additional acceleration beyond the current state-of-the-art for MWF mapping, while it is possible to accelerate beyond state-of-the-art for IET2 mapping.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-vivo liver proton density fat fraction quantification at 0.55 T: a pilot study with comparison against 3 T MRI.","authors":"Rochelle E Wong, Bilal Tasdelen, Ye Tian, Darryl Hwang, Sophia X Cui, Liyun Yuan, Krishna S Nayak","doi":"10.1007/s10334-025-01277-9","DOIUrl":"https://doi.org/10.1007/s10334-025-01277-9","url":null,"abstract":"<p><strong>Background: </strong>Proton density fat fraction (PDFF)- the ratio of unconfounded fat signal to the sum of the unconfounded fat and water signals, is a valuable quantitative imaging biomarker of metabolic associated steatotic liver disease (MASLD) widely applied in clinical practice and clinical trials. PDFF of the liver is commonly measured using 3 T MRI systems. However, low-field systems are increasingly favored due to lower cost, improved safety profile, minimized artifacts around metallic implants, and enhanced patient comfort.</p><p><strong>Objective: </strong>In this pilot study, we used knowledge of standardized and widely used 3 T liver PDFF protocols, and adapted parameters to be appropriate for the 0.55 T MRI. We evaluate a liver fat quantification protocol at 0.55 T compared to a standard clinical 3 T protocol to measure liver fat in patients with MASLD.</p><p><strong>Material and methods: </strong>Eight adult patients (average age 53.6 ± 13.6 years, 5 females) with ≥ 5% PDFF on 3 T MRI underwent a 0.55 T MRI PDFF protocol within 90 days. To keep the acquisition time to be within a reasonable breath hold duration and with reasonable signal-to-noise ratio (SNR), four echoes were acquired at a lower resolution and fewer number of slices at 0.55 T compared to 3 T which uses a 6-echo multi-echo Dixon volumetric interpolated breath hold examination (VIBE) protocol. PDFF quantification accuracy of the 0.55 T approach was evaluated using a commercial PDFF phantom and in vivo.</p><p><strong>Results: </strong>In the phantom, there was excellent match (R² > 0.999) between PDFF estimated by 0.55 T MRI and ground truth. Mean in vivo 3 T MRI-PDFF was 16.5%, compared to 16.3% 0.55 T MRI-PDFF (correlation coefficient r = 0.99). The Bland-Altman analysis showed good agreement of in vivo PDFF measurements across 0.55 T and 3 T estimating a bias or mean difference of - 0.25% and the limits of agreements (LoA) of - 3.98% and 3.48%.</p><p><strong>Discussion: </strong>Our data demonstrate that 0.55 T MRI is feasible and comparable to 3 T MRI in quantifying liver PDFF among patients with MASLD.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion-weighted magnetic resonance spectroscopy with selective refocusing.","authors":"Emile Berg, Renate Grüner, John Georg Seland","doi":"10.1007/s10334-025-01275-x","DOIUrl":"https://doi.org/10.1007/s10334-025-01275-x","url":null,"abstract":"<p><strong>Objective: </strong>To reduce errors from J-modulations and spectral overlap in dMRS of brain metabolites, this study combines the use of diffusion-weighted gradients with selective refocusing and spectral editing.</p><p><strong>Materials and methods: </strong>Bipolar gradients were combined with spectral refocusing and editing in a dMEGA-PRESS sequence. Experimental parameters were optimised for spectral editing of GABA, with co-editing of Glutamate and Glutamine. The method was tested in metabolite phantom solutions, followed by pre-clinical experiments on rats.</p><p><strong>Results: </strong>The dMEGA-PRESS sequence enabled reliable spectral editing and quantification of GABA. Selective refocusing and editing resulted in reduced uncertainty in the diffusion data for GABA and Glutamate in the metabolite phantoms, and also for the combined Glutamate/Glutamine diffusion data obtained in vivo. Reliable diffusion data for GABA was not possible to obtain from the in vivo spectra.</p><p><strong>Discussion: </strong>For metabolites with significant J-modulations but without spectral overlap, selective refocusing improved the quality of diffusion data. For metabolites with spectral overlap where editing is necessary, spectral subtraction makes it more challenging to improve the quality of diffusion-weighted data.</p><p><strong>Conclusion: </strong>The dMEGA-PRESS sequence reduces the uncertainty in obtained diffusion data for brain metabolites that are significantly influenced by J-modulations.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144637454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fat-water MRI separation using deep complex convolution network.","authors":"Moorthy Ganeshkumar, Devasenathipathy Kandasamy, Raju Sharma, Amit Mehndiratta","doi":"10.1007/s10334-025-01268-w","DOIUrl":"https://doi.org/10.1007/s10334-025-01268-w","url":null,"abstract":"<p><strong>Objective: </strong>Deep complex convolutional networks (DCCNs) utilize complex-valued convolutions and can process complex-valued MRI signals directly without splitting them into two real-valued magnitude and phase components. The performance of DCCN and real-valued U-Net is thoroughly investigated in the physics-informed subject-specific ad-hoc reconstruction method for fat-water separation and is compared against a widely used reference approach.</p><p><strong>Materials and methods: </strong>A comprehensive test dataset (n = 33) was used for performance analysis. The 2012 ISMRM fat-water separation workshop dataset containing 28 batches of multi-echo MRIs with 3-15 echoes from the abdomen, thigh, knee, and phantoms, acquired with 1.5 T and 3 T scanners were used. Additionally, five MAFLD patients multi-echo MRIs acquired from our clinical radiology department were also used.</p><p><strong>Results: </strong>The quantitative results demonstrated that DCCN produced fat-water maps with better normalized RMS error and structural similarity index with the reference approach, compared to real-valued U-Nets in the ad-hoc reconstruction method for fat-water separation. The DCCN achieved an overall average SSIM of 0.847 ± 0.069 and 0.861 ± 0.078 in generating fat and water maps, respectively, in contrast the U-Net achieved only 0.653 ± 0.166 and 0.729 ± 0.134. The average liver PDFF from DCCN achieved a correlation coefficient R of 0.847 with the reference approach.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144553928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-center and multi-vendor evaluation study across 1.5 T and 3 T scanners (part 2): T1 and T2 standardization in the ISMRM/NIST MR phantom.","authors":"Siria Pasini, Steffen Ringgaard, Tau Vendelboe, Leyre Garcia-Ruiz, Anika Strittmatter, Giulia Villa, Anish Raj, Rebeca Echeverria-Chasco, Michela Bozzetto, Paolo Brambilla, Malene Aastrup, Esben S S Hansen, Luisa Pierotti, Matteo Renzulli, Susan T Francis, Frank G Zöllner, Christoffer Laustsen, Maria A Fernandez-Seara, Anna Caroli","doi":"10.1007/s10334-025-01260-4","DOIUrl":"10.1007/s10334-025-01260-4","url":null,"abstract":"<p><strong>Objective: </strong>To assess multi-site and multi-vendor accuracy, and intra- and inter-scanner variability of T1 and T2 measurements using the ISMRM/NIST System MRI phantom at room temperature.</p><p><strong>Materials and methods: </strong>T1 and T2 measurements were acquired using standardized NIST protocols on 13 scanners (1.5 T and 3 T) from 3 vendors at 7 sites and compared with reference values at room temperature. Pearson's correlation (r) and accuracy error were used for comparison with reference values, while inter-scanner agreement was assessed using the coefficient of variation (CV%). Short-term reproducibility was evaluated using Bland-Altman plots and precision error. Generalized linear mixed models and post hoc tests (α = 0.05) were adopted to compare accuracy and precision across field strengths, vendors, and scanners. T2 measurements were corrected with StimFit toolbox for stimulated echo compensation.</p><p><strong>Results: </strong>T1 and T2 measurements had excellent correlation with reference values at both field strengths. Stimfit significantly improved T2 accuracy in the renal range for 9 of 13 scanners. Short-term reproducibility (limits of agreement < 10%) and inter-scanner agreement were good (median CV < 7%) for both T1 and T2 values. Inter-scanner CV was < 5% in the renal range for both parameters.</p><p><strong>Discussion: </strong>These findings support the need of scanner evaluation processes to ensure reliable T1-T2 measurements in multi-center MRI studies.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"611-627"},"PeriodicalIF":2.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12255571/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Field-cycling imaging yields repeatable brain R₁ dispersion measurement at fields strengths below 0.2 Tesla with optimal fitting routine.","authors":"Nicholas Senn, P James Ross, Reina Ayde, Vasiliki Mallikourti, Adarsh Krishna, Charly James, Clarisse F de Vries, Lionel M Broche, Gordon D Waiter, Mary Joan MacLeod","doi":"10.1007/s10334-025-01230-w","DOIUrl":"10.1007/s10334-025-01230-w","url":null,"abstract":"<p><strong>Objectives: </strong>By rapidly changing magnetic field strength between 0.2 and 200 mT during the pulse sequence Field-Cycling Imaging (FCI) makes it possible to identify and evaluate new quantitative markers of pathology derived from dispersion of spin-lattice relaxation rate (R₁) in vivo. The aim of this work was to determine the most effective approach to reliably estimate multi-field R₁ dispersion measurements in brain tissue using FCI.</p><p><strong>Materials and methods: </strong>This repeatability study consisted of twenty participants with moderate or severe small vessel disease. Each participant underwent 3 T MRI and FCI scans, repeated 30 days apart. After R₁ maps were generated at 0.2, 2, 20, and 200 mT, co-registered tissue labels generated from 3 T MRI were used to extract tissue averaged values of R₁ dispersion from regions of white matter (WM) and WM hyperintensities (WMHs).</p><p><strong>Results: </strong>The fitted model which yielded best overall image contrast between WM and WMH regions and R₁ dispersion model adherence was determined. Tissue averaged values of R₁ (0.2 mT) and R₁ dispersion slope exhibited Cohen's d effect sizes of 3.07 and 1.48, respectively, between regions of WM and WMH. The cohort study results were repeatable between study visits.</p><p><strong>Discussion: </strong>Differences in R₁ measurements could repeatably be discerned between normal and abnormal appearing brain tissues.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"465-474"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12255585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143425724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time automated quality control for quantitative MRI.","authors":"Andrew Dupuis, Rasim Boyacioglu, Kathryn E Keenan, Mark A Griswold","doi":"10.1007/s10334-024-01205-3","DOIUrl":"10.1007/s10334-024-01205-3","url":null,"abstract":"<p><strong>Objective: </strong>This work presents an automated quality control (QC) system within quantitative MRI (qMRI) workflows. By leveraging the ISMRM/NIST quantitative MRI system phantom, we establish an open-source pipeline for rapid, repeatable, and accurate validation and stability tracking of sequence quantification performance across diverse clinical settings.</p><p><strong>Materials and methods: </strong>A microservice-based QC system for automated vial segmentation from quantitative maps was developed and tested across various MRF acquisition and protocol designs, with reports generated and returned to the scanner in real time.</p><p><strong>Results: </strong>The system demonstrated consistent and repeatable value segmentation and reporting, successfully extracted all 252 T1 and T2 vial samples tested. Values extracted from the same sequence were found to be repeatable with 0.09% ± 1.23% and - 0.26% ± 2.68% intersession error, respectively.</p><p><strong>Discussion: </strong>By providing real-time quantification performance assessment, this easily deployable automated QC approach streamlines sequence validation and long-term performance monitoring, vital for the broader acceptance of qMRI as a standard component of clinical protocols.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"491-501"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142365755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative image quality metrics enable resource-efficient quality control of clinically applied AI-based reconstructions in MRI.","authors":"Owen A White, Joshua Shur, Francesca Castagnoli, Geoff Charles-Edwards, Brandon Whitcher, David J Collins, Matthew T D Cashmore, Matt G Hall, Spencer A Thomas, Andrew Thompson, Ciara A Harrison, Georgina Hopkinson, Dow-Mu Koh, Jessica M Winfield","doi":"10.1007/s10334-025-01253-3","DOIUrl":"10.1007/s10334-025-01253-3","url":null,"abstract":"<p><strong>Objective: </strong>AI-based MRI reconstruction techniques improve efficiency by reducing acquisition times whilst maintaining or improving image quality. Recent recommendations from professional bodies suggest centres should perform quality assessments on AI tools. However, monitoring long-term performance presents challenges, due to model drift or system updates. Radiologist-based assessments are resource-intensive and may be subjective, highlighting the need for efficient quality control (QC) measures. This study explores using image quality metrics (IQMs) to assess AI-based reconstructions.</p><p><strong>Materials and methods: </strong>58 patients undergoing standard-of-care rectal MRI were imaged using AI-based and conventional T2-weighted sequences. Paired and unpaired IQMs were calculated. Sensitivity of IQMs to detect retrospective perturbations in AI-based reconstructions was assessed using control charts, and statistical comparisons between the four MR systems in the evaluation were performed. Two radiologists evaluated the image quality of the perturbed images, giving an indication of their clinical relevance.</p><p><strong>Results: </strong>Paired IQMs demonstrated sensitivity to changes in AI-reconstruction settings, identifying deviations outside ± 2 standard deviations of the reference dataset. Unpaired metrics showed less sensitivity. Paired IQMs showed no difference in performance between 1.5 T and 3 T systems (p > 0.99), whilst minor but significant (p < 0.0379) differences were noted for unpaired IQMs.</p><p><strong>Discussion: </strong>IQMs are effective for QC of AI-based MR reconstructions, offering resource-efficient alternatives to repeated radiologist evaluations. Future work should expand this to other imaging applications and assess additional measures.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"547-560"},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12255595/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}