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

{"title":"A dual-stage framework for segmentation of the brain anatomical regions with high accuracy.","authors":"Peyman Sharifian, Alireza Karimian, Hossein Arabi","doi":"10.1007/s10334-025-01233-7","DOIUrl":"10.1007/s10334-025-01233-7","url":null,"abstract":"<p><strong>Objective: </strong>This study presents a novel deep learning-based framework for precise brain MR region segmentation, aiming to identify the location and the shape details of different anatomical structures within the brain.</p><p><strong>Materials and methods: </strong>The approach uses a two-stage 3D segmentation technique on a dataset of adult subjects, including cognitively normal participants and individuals with cognitive decline. Stage 1 employs a 3D U-Net to segment 13 brain regions, achieving a mean DSC of 0.904 ± 0.060 and a mean HD95 of 1.52 ± 1.53 mm (a mean DSC of 0.885 ± 0.065 and a mean HD95 of 1.57 ± 1.35 mm for smaller parts). For challenging regions like hippocampus, thalamus, cerebrospinal fluid, amygdala, basal ganglia, and corpus callosum, Stage 2 with SegResNet refines segmentation, improving mean DSC to 0.921 ± 0.048 and HD95 to 1.17 ± 0.69 mm.</p><p><strong>Results: </strong>Statistical analysis reveals significant improvements (p-value < 0.001) for these regions, with DSC increases ranging from 1.3 to 3.2% and HD95 reductions of 0.06-0.33 mm. Comparisons with recent studies highlight the superior performance of the performed method.</p><p><strong>Discussion: </strong>The inclusion of a second stage for refining the segmentation of smaller regions demonstrates substantial improvements, establishing the framework's potential for precise and reliable brain region segmentation across diverse cognitive groups.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"299-315"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143557251","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":"Initial assessment of PNS safety for interventionalists during image-guided procedures.","authors":"Feng Jia, Axel Vom Endt, Philipp Amrein, Maximilian Frederik Russe, Heiko Rohdjess, Martino Leghissa, Maxim Zaitsev, Sebastian Littin","doi":"10.1007/s10334-025-01228-4","DOIUrl":"10.1007/s10334-025-01228-4","url":null,"abstract":"<p><strong>Purpose: </strong>This study investigates peripheral nerve stimulation (PNS) safety thresholds for health professionals performing MRI procedures and the variation of arm rotations in close vicinity to the magnet bore.</p><p><strong>Methods: </strong>Employing two posable human body models, this research utilized quasi-static electromagnetic calculations and neurodynamic simulations to assess PNS thresholds. Different arm rotations are compared for standing interventionalist's posture assuming the supine patient position, typical for medical interventions inside MRI devices.</p><p><strong>Results: </strong>This study reveals that arm rotations in standing postures result in variations in PNS thresholds. However, for all the arm poses considered, the threshold was at least 2.4 times higher compared to the patient position. Differences in PNS thresholds and electric field distributions were observed between male and female models.</p><p><strong>Conclusions: </strong>The findings suggest that when the PNS thresholds for imaging subjects are not exceeded, it is likely that a subject leaning into the bore will also not experience PNS. However, variations in PNS thresholds due to arm movements highlight the importance of considering body posture in MRI safety protocols.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"239-251"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914522/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143391361","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":"Clinical validation of fully automated cartilage transverse relaxation time (T2) and thickness analysis using quantitative DESS magnetic resonance imaging.","authors":"Wolfgang Wirth, Simon Herger, Susanne Maschek, Anna Wisser, Oliver Bieri, Felix Eckstein, Annegret Mündermann","doi":"10.1007/s10334-025-01227-5","DOIUrl":"10.1007/s10334-025-01227-5","url":null,"abstract":"<p><strong>Objective: </strong>To clinically validate a fully automated cartilage segmentation technique from quantitative double-echo steady-state (qDESS) MRI supporting simultaneous estimation of cartilage T2 and morphology. Here, we test whether laminar (superficial and deep layer) T2 results from convolutional neural network (CNN) segmentations are consistent with those from manual expert segmentations.</p><p><strong>Materials and methods: </strong>The 3D qDESS sequence was acquired using 3 T MRI (resolution: 0.3125 × 0.3125x1.5 mm) in both knees of 37 subjects with unilateral anterior cruciate ligament (ACL) injury and 48 uninjured controls. Automated femorotibial cartilage (FTJ) segmentation was based on a 2D U-Net. Laminar T2 and cartilage thickness across the FTJ) were compared between ACL-injured and contralateral knees, and between ACL-injured and control knees. Effect sizes of these differences were measured using non-parametric Cohen's d (d_n-p).</p><p><strong>Result: </strong>Significant differences were observed only in deep T2, with longer T2 in ACL-injured knees than in contralateral and healthy control knees in most of the comparisons and with similar effect sizes for automated and manual segmentations (range d_n-p automated/manual: 0.58-1.04/0.58-0.74). No significant differences were observed in superficial T2 or cartilage thickness.</p><p><strong>Discussion: </strong>Fully-automated, CNN-based analysis showed similar sensitivity to differences in laminar cartilage T2 as manual segmentation, allowing automated qDESS-analyses to be applied to larger datasets.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"285-297"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143483489","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":"Systematic evaluation of adhesives for implant fixation in multimodal functional brain MRI.","authors":"Anna Zsófia Szinyei, Bastian Maus, Jonas Q Schmid, Matthias Klimek, Daniel Segelcke, Esther M Pogatzki-Zahn, Bruno Pradier, Cornelius Faber","doi":"10.1007/s10334-024-01220-4","DOIUrl":"10.1007/s10334-024-01220-4","url":null,"abstract":"<p><strong>Objective: </strong>Invasive multimodal fMRI in rodents is often compromised by susceptibility artifacts from adhesives used to secure cranial implants. We hypothesized that adhesive type, shape, and field strength significantly affect susceptibility artifacts, and systematically evaluated various adhesives.</p><p><strong>Materials and methods: </strong>Thirty-one adhesives were applied in constrained/unconstrained geometries and imaged with T2*-weighted EPI at 7.0 and 9.4 T to assess artifact depths. Spherical and flat patch shapes, both unconstrained geometries, were compared for artifact depth in vitro and in vivo. Adhesion strength was assessed on post-mortem mouse crania. Finally, an integrative scoring system rated adhesive properties, including artifact depth, handling, and adhesion strength.</p><p><strong>Results: </strong>Susceptibility artifacts were two times larger at 9.4 than at 7.0 T (p < 0.001), strongest at the patch edges, and deeper with spherical than flat patches (p < 0.05). Artifact size depended more on shape and volume after curing than adhesive type. Our integrative scoring system showed resins, bonding agents, and acrylics offered the best overall properties, while silicones and cements were less favorable.</p><p><strong>Discussion: </strong>Adhesive selection requires balancing handling, curing time, strength, and artifact depth. To minimize artifacts, adhesives should be applied in a spread-out, flat and thin layer. Our integrative scoring system supports classification of future classes of adhesives.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"191-205"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142984014","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":"New physiological insights using multi-TE ASL MRI measuring blood-brain barrier water exchange after caffeine intake.","authors":"Amnah Mahroo, Mareike Alicja Buck, Simon Konstandin, Jörn Huber, Daniel Christopher Hoinkiss, Jochen Hirsch, Matthias Günther","doi":"10.1007/s10334-024-01219-x","DOIUrl":"10.1007/s10334-024-01219-x","url":null,"abstract":"<p><strong>Objectives: </strong>Caffeine, a known neurostimulant and adenosine antagonist, affects brain physiology by decreasing cerebral blood flow. It interacts with adenosine receptors to induce vasoconstriction, potentially disrupting brain homeostasis. However, the impact of caffeine on blood-brain barrier (BBB) permeability to water remains underexplored. This study investigated the water exchange via the BBB in a perturbed physiological condition caused by caffeine ingestion, using the multiple echo time (multi-TE) arterial spin labeling (ASL) technique.</p><p><strong>Material and methods: </strong>Ten healthy, regular coffee drinkers (age = 31 ± 9 years, 3 females) were scanned to acquire five measurements before and six measurements after caffeine ingestion. Data were analyzed with a multi-TE two-compartment model to estimate exchange time (Tex), serving as a proxy for BBB permeability to water. Additionally, cerebral blood flow (CBF), arterial transit time (ATT), and intravoxel transit time (ITT) were investigated.</p><p><strong>Results: </strong>Following caffeine intake, mean gray matter CBF showed a significant time-dependent decrease (P < 0.01). In contrast, Tex, ATT, and ITT did not exhibit significant time-dependent change. However, a non-significant decreasing trend was observed for Tex and ITT, respectively, while ATT showed an increasing trend over time.</p><p><strong>Discussion: </strong>The observed decreasing trend in Tex after caffeine ingestion suggests a potential increase in water flux across the BBB, which may represent a compensatory mechanism to maintain brain homeostasis in response to the caffeine-induced reduction in CBF. Further studies with larger sample sizes are needed to validate and expand upon these findings.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"207-219"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913962/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143039443","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":"Fast whole brain relaxometry with Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) at 3 T: a retrospective cohort study.","authors":"Martin B Schilder, Stefano Mandija, Sarah M Jacobs, Jordi P D Kleinloog, Hanna Liu, Oscar van der Heide, Beyza Köktaş, Federico D'Agata, Vera C W Keil, Evert-Jan P A Vonken, Jan Willem Dankbaar, Jeroen Hendrikse, Tom J Snijders, Cornelis A T van den Berg, Anja G van der Kolk, Alessandro Sbrizzi","doi":"10.1007/s10334-025-01237-3","DOIUrl":"10.1007/s10334-025-01237-3","url":null,"abstract":"<p><strong>Objective: </strong>To report T₁/T₂-values of normal and normal appearing brain tissues (NBTs, healthy volunteers; NABTs, patients) acquired with a whole-brain 5-minute Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) protocol, and to explore relaxometry behavior in a brain tumor and in a multiple sclerosis patient.</p><p><strong>Methods: </strong>MR-STAT was acquired in 49 participants (39 patients with neurological pathologies, age range: 21-79 years) at 3 T. Mean T₁/T₂-values were computed for: normal and normal appearing grey matter (NGM/NAGM)/white matter (NWM/NAWM)/thalamus/putamen/caudate nucleus (CN)/globus pallidus (GP). Differences between sex, brain lobes, and left/right were assessed. The age-dependency of T₁/T₂-values in N(A)BTs was investigated. Relaxometry analysis was performed in two clinical case examples.</p><p><strong>Results: </strong>Mean (standard deviation) T₁/T₂-values were measured in N(A)GM = 1086(73)/74(9) ms; N(A)WM = 658(24)/48(3) ms; thalamus = 783(51)/42(4) ms; putamen = 863(40)/46(3) ms; CN = 1042(97)/63(9) ms; GP = 652(36)/36(3) ms. Differences between sex were not significant. T₁/T₂-values between the left/right parietal lobe and the left/right temporal lobe were significantly different. The quadratic age-dependency of T₁-values in the CN (p = 0.00039) and GP (p = 0.00037), and of T₂-values in the thalamus (p = 0.00044) and GP (p = 0.003) were significant. Pathological tissues could be discerned from NABTs using T₁/T₂-values.</p><p><strong>Discussion: </strong>T₁/T₂-values and data trends agree with literature, supporting the validity of MR-STAT as a clinical option for fast relaxometry despite the relatively low number of subjects in the study. Future work should aim to include healthy participants of a wider age-range and to include B₁-field corrections.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"333-345"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143542471","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":"Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction.","authors":"S Sophie Schauman, Siddharth S Iyer, Christopher M Sandino, Mahmut Yurt, Xiaozhi Cao, Congyu Liao, Natthanan Ruengchaijatuporn, Itthi Chatnuntawech, Elizabeth Tong, Kawin Setsompop","doi":"10.1007/s10334-024-01222-2","DOIUrl":"10.1007/s10334-024-01222-2","url":null,"abstract":"<p><strong>Object: </strong>Spatio-temporal MRI methods offer rapid whole-brain multi-parametric mapping, yet they are often hindered by prolonged reconstruction times or prohibitively burdensome hardware requirements. The aim of this project is to reduce reconstruction time using deep learning.</p><p><strong>Materials and methods: </strong>This study focuses on accelerating the reconstruction of volumetric multi-axis spiral projection MRF, aiming for whole-brain T1 and T2 mapping, while ensuring a streamlined approach compatible with clinical requirements. To optimize reconstruction time, the traditional method is first revamped with a memory-efficient GPU implementation. Deep Learning Initialized Compressed Sensing (Deli-CS) is then introduced, which initiates iterative reconstruction with a DL-generated seed point, reducing the number of iterations needed for convergence.</p><p><strong>Results: </strong>The full reconstruction process for volumetric multi-axis spiral projection MRF is completed in just 20 min compared to over 2 h for the previously published implementation. Comparative analysis demonstrates Deli-CS's efficiency in expediting iterative reconstruction while maintaining high-quality results.</p><p><strong>Discussion: </strong>By offering a rapid warm start to the iterative reconstruction algorithm, this method substantially reduces processing time while preserving reconstruction quality. Its successful implementation paves the way for advanced spatio-temporal MRI techniques, addressing the challenge of extensive reconstruction times and ensuring efficient, high-quality imaging in a streamlined manner.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"221-237"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074990","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":"Whole pancreas water T₁ mapping at 3 Tesla.","authors":"Elizabeth Huaroc Moquillaza, Kilian Weiss, Lisa Steinhelfer, Jonathan Stelter, Marcus R Makowski, Rickmer Braren, Mariya Doneva, Dimitrios C Karampinos","doi":"10.1007/s10334-025-01224-8","DOIUrl":"10.1007/s10334-025-01224-8","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;A fast T&lt;sub&gt;1&lt;/sub&gt; mapping method of the whole pancreas remains a challenge, due to the complex anatomy of the organ. In addition, a technique for pancreas water T&lt;sub&gt;1&lt;/sub&gt; mapping is needed, since the T&lt;sub&gt;1&lt;/sub&gt; is biased in the presence of fat. The purpose of this work is to accelerate the acquisition of water selective T&lt;sub&gt;1&lt;/sub&gt; (wT&lt;sub&gt;1&lt;/sub&gt;) mapping for the whole pancreas at 3 T.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The proposed method combines a continuous inversion-recovery Look-Locker acquisition with a single-shot gradient echo spiral readout, water-fat separation and dictionary matching for wT&lt;sub&gt;1&lt;/sub&gt; mapping of the whole pancreas at 3 T. The bias of T&lt;sub&gt;1&lt;/sub&gt; in the presence of fat was evaluated in a phantom by comparing the modified Look-Locker inversion-recovery (MOLLI) and the proposed method to MRS measurements. The present method was validated in 11 volunteers by evaluating its pancreas coverage and repeatability and by comparing it to MOLLI. Four pancreatitis patients were evaluated using the proposed method and clinical scans.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The phantom wT&lt;sub&gt;1&lt;/sub&gt; results are in better agreement to MRS ( &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mtext&gt;wT&lt;/mtext&gt; &lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt; &lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;1.02&lt;/mn&gt; &lt;msub&gt;&lt;mtext&gt;*wT&lt;/mtext&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mtext&gt;MRS&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;mo&gt;-&lt;/mo&gt; &lt;mn&gt;47.81&lt;/mn&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;mrow&gt;&lt;/mrow&gt; &lt;msup&gt;&lt;mi&gt;R&lt;/mi&gt; &lt;mn&gt;2&lt;/mn&gt;&lt;/msup&gt; &lt;mrow&gt;&lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;0.99&lt;/mn&gt; &lt;mo&gt;)&lt;/mo&gt; &lt;mrow&gt;&lt;/mrow&gt;&lt;/mrow&gt; &lt;/mrow&gt; &lt;/math&gt; than MOLLI ( &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mtext&gt;T&lt;/mtext&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mtext&gt;MOLLI&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;1.13&lt;/mn&gt; &lt;mrow&gt;&lt;/mrow&gt; &lt;mo&gt;∗&lt;/mo&gt; &lt;msub&gt;&lt;mtext&gt;wT&lt;/mtext&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mtext&gt;MRS&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;mo&gt;-&lt;/mo&gt; &lt;mn&gt;74.65&lt;/mn&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msup&gt;&lt;mi&gt;R&lt;/mi&gt; &lt;mn&gt;2&lt;/mn&gt;&lt;/msup&gt; &lt;mrow&gt;&lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;0.98&lt;/mn&gt; &lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt; &lt;/mrow&gt; &lt;/math&gt; . The volunteer wT&lt;sub&gt;1&lt;/sub&gt; results demonstrate the whole pancreas coverage capability for different fat fractions, good repeatability ( &lt;math&gt; &lt;mrow&gt;&lt;mmultiscripts&gt;&lt;mtext&gt;wT&lt;/mtext&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;mrow&gt;&lt;/mrow&gt; &lt;msup&gt;&lt;mn&gt;2&lt;/mn&gt; &lt;mo&gt;∘&lt;/mo&gt;&lt;/msup&gt; &lt;/mrow&gt; &lt;mrow&gt;&lt;/mrow&gt;&lt;/mmultiscripts&gt; &lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;0.98&lt;/mn&gt; &lt;mrow&gt;&lt;/mrow&gt; &lt;mo&gt;∗&lt;/mo&gt; &lt;mmultiscripts&gt;&lt;mtext&gt;wT&lt;/mtext&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;mrow&gt;&lt;/mrow&gt; &lt;msup&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mo&gt;∘&lt;/mo&gt;&lt;/msup&gt; &lt;/mrow&gt; &lt;mrow&gt;&lt;/mrow&gt;&lt;/mmultiscripts&gt; &lt;mo&gt;+&lt;/mo&gt; &lt;mn&gt;17.40&lt;/mn&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msup&gt;&lt;mi&gt;R&lt;/mi&gt; &lt;mn&gt;2&lt;/mn&gt;&lt;/msup&gt; &lt;mrow&gt;&lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;0.69&lt;/mn&gt; &lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt; &lt;/mrow&gt; &lt;/math&gt; and lower T&lt;sub&gt;1&lt;/sub&gt; values than MOLLI ( &lt;math&gt; &lt;mrow&gt;&lt;msub&gt;&lt;mtext&gt;wT&lt;/mtext&gt; &lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt; &lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;0.34&lt;/mn&gt; &lt;msub&gt;&lt;mtext&gt;*T&lt;/mtext&gt; &lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt; &lt;mtext&gt;MOLLI&lt;/mtext&gt;&lt;/mrow&gt; &lt;/msub&gt; &lt;mo&gt;+&lt;/mo&gt; &lt;mn&gt;383.65&lt;/mn&gt; &lt;mo&gt;,&lt;/mo&gt; &lt;msup&gt;&lt;mrow&gt;&lt;mspace&gt;&lt;/mspace&gt; &lt;mtext&gt;R&lt;/mtext&gt;&lt;/mrow&gt; &lt;mn&gt;2&lt;/mn&gt;&lt;/msup&gt; &lt;mrow&gt;&lt;mo&gt;=&lt;/mo&gt; &lt;mn&gt;0.26&lt;/mn&gt; &lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt; &lt;/mrow&gt; &lt;/math&gt; . The wT&lt;sub&gt;1&lt;/sub&gt; maps in patients captured diverse pancreatitis regions with higher values &lt;","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"271-283"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143567581","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":"Myelin water fraction mapping with joint inversion of gradient-echo and spin-echo data.","authors":"Ségolène Dega, Mónica Ferreira, Marten Veldmann, Rüdiger Stirnberg, Hendrik Paasche, Tony Stöcker","doi":"10.1007/s10334-025-01235-5","DOIUrl":"10.1007/s10334-025-01235-5","url":null,"abstract":"<p><strong>Objective: </strong>Accurate estimation of brain myelin-water content from multi-echo data is challenging due to the inherent ill-posedness of the inversion problem. In this study, we propose a novel method for myelin-water imaging that jointly utilizes gradient-echo and spin-echo imaging data to enhance the accuracy of myelin-water estimation.</p><p><strong>Material and methods: </strong>Multi-echo gradient-echo and spin-echo data were simulated and acquired in vivo. The simulations are based on a parameterized myelin and free water signal model, which is also used for the inversion by means of nonlinear local-search optimization. Single inversions of the individual datasets as well as joint inversion of the combined datasets were performed on simulated and real data. While single inversions estimate either the <math><msub><mi>T</mi> <mn>2</mn></msub> </math> or <math><mmultiscripts><mi>T</mi> <mrow><mn>2</mn></mrow> <mrow><mrow></mrow> <mo>∗</mo></mrow> </mmultiscripts> </math> relaxation spectrum, the joint inversion estimates both spectra simultaneously.</p><p><strong>Results: </strong>Simulation results show that the accuracy of myelin-water imaging improves when jointly inverting gradient-echo and spin-echo synthetic data. In vivo experiments show that the joint inversion of both datasets leads to sharper and more distinct myelin-water images as compared to the individual inversions.</p><p><strong>Discussion: </strong>Our method addresses the ill-posed nature of the myelin-water inversion problem by leveraging complementary information from multi-echo gradient-echo and multi-echo spin-echo imaging sequences, thus improving the reliability of myelin-water quantification.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"317-332"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914316/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143573408","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":"Importance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases.","authors":"Sandra Martin, Rémi André, Amira Trabelsi, Constance P Michel, Etienne Fortanier, Shahram Attarian, Maxime Guye, Marc Dubois, Redha Abdeddaim, David Bendahan","doi":"10.1007/s10334-024-01221-3","DOIUrl":"10.1007/s10334-024-01221-3","url":null,"abstract":"<p><strong>Objective: </strong>Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness in this field. However, the impact of reducing neural network complexity remains unexplored in the FF quantification in individual muscles.</p><p><strong>Material and methods: </strong>U-Net architectures with different complexities have been compared for the quantification of the fat fraction in each muscle group selected in the central part of the thigh region. The corresponding performance has been assessed in terms of Dice score (DSC) and FF quantification error. The database contained 1450 thigh images from 59 patients and 14 healthy subjects (age: 47 ± 17 years, sex: 36F, 37M). Ten individual muscles were segmented in each image. The performance of each model was compared to nnU-Net, a complex architecture with 4.35 <math><mo>×</mo></math> 10⁷ parameters, 12.8 Gigabytes of peak memory usage and 167 h of training time.</p><p><strong>Results: </strong>As expected, nnU-Net achieved the highest DSC (94.77 ± 0.13%). A simpler U-Net (5.81 <math><mo>×</mo></math> 10⁵ parameters, 2.37 Gigabytes, 14 h of training time) achieved a lower DSC but still above 90%. Surprisingly, both models achieved a comparable FF estimation.</p><p><strong>Discussion: </strong>The poor correlation between observed DSC and FF indicates that less complex architectures, reducing GPU memory utilization and training time, can still accurately quantify FF.</p>","PeriodicalId":18067,"journal":{"name":"Magnetic Resonance Materials in Physics, Biology and Medicine","volume":" ","pages":"175-189"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142965498","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}