Magnetic resonance imaging最新文献

{"title":"Association between radiomics of diffusion-weighted imaging and histopathology in hepatocellular carcinoma. A preliminary investigation","authors":"Hans-Jonas Meyer ,&nbsp;Jakob Leonhardi ,&nbsp;Johann Potratz ,&nbsp;Dörthe Jechorek ,&nbsp;Kai Ina Schramm ,&nbsp;Jan Borggrefe ,&nbsp;Alexey Surov","doi":"10.1016/j.mri.2025.110356","DOIUrl":"10.1016/j.mri.2025.110356","url":null,"abstract":"<div><h3>Objective</h3><div>Diffusion-weighted imaging and the quantified apparent diffusion coefficient (ADC) correlate with cell density and histopathological features in tumors. Radiomics analysis may provide more insight into the underlying microstructure and may better correlate with histopathology. The present study used cross-sectional guided biopsy specimens to exploit the precise spatial localization of the performed biopsy to correlate radiomics features of the ADC map with immunohistochemical features in hepatocellular carcinoma (HCC).</div></div><div><h3>Materials and methods</h3><div>A total of 51 patients (11 female patients, 21.6 %) were included in the present study. The mean age was 71.9 ± 9.9 years, ranging from 42 to 91 years. Prebioptic liver MRI with diffusion-weighted imaging was used to correlate the radiomics features of the ADC maps with the immunohistochemical features quantified in liver biopsy. Proliferation potential Ki 67, leukocyte count and tumor-stroma ratio were evaluated as histopathological parameters.</div></div><div><h3>Results</h3><div>The following ADC texture features were correlated with the Ki 67 index _MinNorm (<em>r</em> = −0.307, <em>p</em> = 0.03), Vertl_RLNonUni (<em>r</em> = − 0.309, p = 0.03), 135dr_RLNonUni (<em>r</em> = −0.346, <em>p</em> = 0.01). The texture feature _MinNorm achieved the best diagnostic accuracy with an area under the curve of 0.76 (95 % CI 0.60–0.91, <em>p</em> &lt; 0.01) to discriminate between low and high proliferative HCC. Multiple statistically significant correlations were found between ADC texture features and tumor-stroma-ratio, the highest for S(0,1)Contrast (<em>r</em> = 0.460, <em>p</em> = 0.001). No statistically significant correlations were found between the ADC texture features with the CD45+ leukocyte count and grading.</div></div><div><h3>Conclusion</h3><div>Radiomics features of the ADC maps can reflect the underlying histopathology in HCC patients including the proliferation potential and tumor-stroma ratio but not CD45 positive cells and tumor grading. The complex interactions between quantitative imaging and histopathology need to be further investigated in a validation cohort.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110356"},"PeriodicalIF":2.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143408810","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":"Use of deep learning-accelerated T2 TSE for prostate MRI: Comparison with and without hyoscine butylbromide admission","authors":"M. Boschheidgen ,&nbsp;L. Drewes ,&nbsp;B. Valentin ,&nbsp;T. Ullrich ,&nbsp;S. Trappe ,&nbsp;R. Al-Monajjed ,&nbsp;J.P. Radtke ,&nbsp;P. Albers ,&nbsp;H.J. Wittsack ,&nbsp;G. Antoch ,&nbsp;L. Schimmöller","doi":"10.1016/j.mri.2025.110358","DOIUrl":"10.1016/j.mri.2025.110358","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate the use of deep learning (DL) T2-weighted turbo spin echo (TSE) imaging sequence with deep learning acceleration (T2DL) in prostate MRI regarding the necessity of hyoscine butylbromide (HBB) administration for high image quality.</div></div><div><h3>Methods</h3><div>One hundred twenty consecutive patients divided into four groups (30 for each group) were included in this study. All patients received a T2DL (version 2022/23) and a conventional T2 TSE (cT2) sequence on an implemented 3 T scanner and software system. Group A received cT2 with HBB compared to T2DL without HBB with a field of view (FOV) of 130 mm and group B with a FOV of 160 mm. Group C received both sequences with a FOV of 160 mm plus HBB and group D without HBB. Two radiologists independently evaluated all imaging datasets in a blinded reading regarding motion, sharpness, noise, and diagnostic confidence. Furthermore, we analyzed quantitative parameters by calculating edge rise distance (ERD), signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR). Friedman test was used for group comparisons.</div></div><div><h3>Results</h3><div>Baseline characteristics showed no significant differences between groups A-D. After HBB cT2 showed less motion artifacts, more sharpness, and a higher diagnostic confidence than T2DL, though DL sequences had significantly lower noise (<em>p</em> &lt; 0.01). Quantitative analysis revealed higher SNR and CNR for T2DL sequences (p &lt; 0.01), while edge rise distance (ERD) remained similar. Inter-reader agreement was good to excellent, with ICCs ranging from 0.84 to 0.93. T2DL acquisition time was significantly lower than for cT2.</div></div><div><h3>Conclusions</h3><div>In our study, cT2 sequences with HBB showed superior image quality and diagnostic confidence while the T2DL sequence offer promising potential for reducing MRI acquisition times and performed better in quantitative measures like SNR and CNR. Additional studies are required to evaluate further adjusted and developed DL applications for prostate MRI on upcoming scanner generations and to assess tumor detection rates.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110358"},"PeriodicalIF":2.1,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143408833","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":"Concurrent water T2 and fat fraction mapping of the breast using the radial gradient and spin echo (RADGRASE) pulse sequence","authors":"Tomoe Hagio ,&nbsp;Jean-Philippe Galons ,&nbsp;Denise Roe ,&nbsp;Marylin T. Marron ,&nbsp;Cynthia Thomson ,&nbsp;Patricia Thompson ,&nbsp;Alison T. Stopeck ,&nbsp;Ali Bilgin ,&nbsp;Maria I. Altbach ,&nbsp;Jing-Tzyh Alan Chiang","doi":"10.1016/j.mri.2025.110355","DOIUrl":"10.1016/j.mri.2025.110355","url":null,"abstract":"<div><div>This work describes and evaluates an efficient radial gradient- and spin-echo (RADGRASE) pulse sequence and reconstruction algorithm for concurrent measurement of proton-density weighted fat fraction (FF) and water component T₂ (T_2w) within breast tissues. The ability to estimate T_2w in breast tissues, where fat can be highly abundant, is demonstrated using oil/gel phantoms across a wide range of FF values (0.1–0.7). Successful T_2w mapping of breast tissues is also demonstrated in vivo by comparison with fat suppressed T₂ values. The sensitivity of RADGRASE to detect changes in the breast was assessed by tracking T_2w in 3 healthy volunteers through their menstrual cycle, demonstrating T_2w values in the late luteal phase to be 18–29 ms higher than in the follicular phase. The technique is also applied to a cohort of 68 patients taking tamoxifen for breast cancer risk reduction, where significant positive correlation between the FF parameter Frac50 and T_2w (<em>p</em> = 0.035) was observed in premenopausal subjects (<em>n</em> = 20). Our findings demonstrate the ability and efficacy of RADGRASE for simultaneously mapping FF and T_2w within breast tissues, and the potential utility of the technique in studying breast tissue changes in clinical applications.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110355"},"PeriodicalIF":2.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143373085","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":"Quantification of tissue stiffness with magnetic resonance elastography and finite difference time domain (FDTD) simulation-based spatiotemporal neural network","authors":"Jiaying Zhang ,&nbsp;Xin Mu ,&nbsp;Xi Lin ,&nbsp;Xiangwei Kong ,&nbsp;Yanbin Li ,&nbsp;Lianjun Du ,&nbsp;Xueqin Xu ,&nbsp;Jeff L. Zhang","doi":"10.1016/j.mri.2025.110353","DOIUrl":"10.1016/j.mri.2025.110353","url":null,"abstract":"<div><div>Quantification of tissue stiffness with magnetic resonance elastography (MRE) is an inverse problem that is sensitive to noise. Conventional methods for the purpose include direct inversion (DI) and local frequency estimation (LFE). In this study, we propose to train a spatiotemporal neural network using MRE data simulated by the Finite Difference Time Domain method (FDTDNet), and to use the trained network to estimate tissue stiffness from MRE data. The proposed method showed significantly better robustness to noise than DI or LFE. For simulated data with signal-to-noise ratio (SNR) of 15 dB, tissue stiffness by FDTDNet had mean absolute error of 0.41 kPa or 7 %, 77.8 % and 84.4 % lower than those by DI and LFE respectively (<em>P</em> &lt; 0.0001). For a homogeneous phantom with driver power decreasing from 30 % to 5 %, FDTDNet, DI and LFE provided stiffness estimates with deviation of 6.9 % (0.21 kPa), 9.2 % (0.28 kPa) and 45.8 % (1.20 kPa) of the respective stiffness level at driver power of 30 %. Detectability of small inclusions in estimated stiffness maps is also critical. For simulated data with inclusions of radius of 0.31 cm, FDTDNet achieved contrast-to-noise ratio (CNR) of 4.20, 6900 % and 347 % higher than DI and LFE respectively (<em>P</em> &lt; 0.0001), and structural similarity index (SSIM) of 0.61, 27 % and 177 % higher than DI and LFE respectively (<em>P</em> &lt; 0.0001). For phantom with inclusion of radius 0.39 cm, CNR of FDTDNet was 2.98, 90 % and 80 % higher than DI and LFE respectively (<em>P</em> &lt; 0.0001) and SSIM was 0.80, 89 % and 28 % higher than DI and LFE respectively (P &lt; 0.0001). We also demonstrated the feasibility of FDTDNet in MRE data acquired from calf muscles of human subjects. In conclusion, by using a spatiotemporal neural network trained with simulated data, FDTDNet estimated tissue stiffness from MRE with superior noise robustness and detectability of focal inclusions, therefore showed potential in precisely quantifying MRE of human subjects.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110353"},"PeriodicalIF":2.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349797","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":"Predicting progression in triple-negative breast cancer patients undergoing neoadjuvant chemotherapy: Insights from peritumoral radiomics","authors":"Soo-Yeon Kim ,&nbsp;Jungwoo Woo ,&nbsp;Sewon Lee ,&nbsp;Hyunsook Hong","doi":"10.1016/j.mri.2024.110292","DOIUrl":"10.1016/j.mri.2024.110292","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate whether radiomic features obtained from the intratumoral and peritumoral regions of pretreatment magnetic resonance imaging (MRI) can predict progression in patients with triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy (NAC) in comparison with the previously determined clinical score.</div></div><div><h3>Methods</h3><div>This single-center retrospective study evaluated 224 women with TNBC who underwent NAC between 2010 and 2019. Women were randomly allocated to the training set (<em>n</em> = 169) for model development and the test set (<em>n</em> = 55) for model validation. The clinical score consisted of the histologic type, Ki-67 index, and degree of edema on T2-weighted imaging. Intratumoral and peritumoral radiomic features were extracted from T2-weighted images and the first- and last-phase images of dynamic contrast-enhanced MRI. The radiomics model was built using only radiomic features, whereas the combined model incorporated the clinical score along with radiomic features. The area under the receiver operating characteristic curve (AUC) was used to assess performance.</div></div><div><h3>Results</h3><div>Progression occurred in 18 and five patients in the training and test sets, respectively. The radiomics model selected three radiomic features (two peritumoral and one intratumoral), while the combined model selected the clinical score and five radiomic features (four peritumoral and one intratumoral). Among the total radiomic features, Inverse Difference Normalized of the peritumoral region of the T2-weighted images, reflective of peritumoral heterogeneity, demonstrated the highest level of association with tumor progression. In the test set, the AUC values of the radiomics-only model, the combined model, and the clinical score were 0.592, 0.764, and 0.720, respectively. Compared to the clinical score, the radiomics-only model (0.720 vs. 0.592, <em>p</em> = 0.468) and the combined model (0.720 vs. 0.764, <em>p</em> = 0.553) did not show superior performance.</div></div><div><h3>Conclusion</h3><div>The radiomics features were not superior in predicting the progression of TNBC compared to the clinical score, although the peritumoral heterogeneity on T2-weighted images showed a potential.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110292"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780491","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":"Preclinical validation of a metasurface-inspired conformal elliptical-cylinder resonator for wrist MRI at 1.5 T","authors":"Yakui Wang ,&nbsp;Zhonghai Chi ,&nbsp;Yi Yi ,&nbsp;Yingyi Qi ,&nbsp;Xinxin Li ,&nbsp;Qian Zhao ,&nbsp;Zhuozhao Zheng","doi":"10.1016/j.mri.2024.110291","DOIUrl":"10.1016/j.mri.2024.110291","url":null,"abstract":"<div><h3>Objective</h3><div>To design a metasurface-inspired conformal elliptical-cylinder resonator (MICER) for wrist magnetic resonance imaging at 1.5 T and evaluate its potential for clinical applications.</div></div><div><h3>Methods</h3><div>An electromagnetic simulation was used to characterize the effect of MICER on radio frequency fields. A phantom and 14 wrists from 7 healthy volunteers were examined using a 1.5 T MRI system. The examination included T1-weighted spin echo, fat-saturation proton density-weighted fast spin echo, and three-dimensional T1-weighted gradient echo sequences. All scans were repeated using two methods: MICER combined with the spinal coil, which is a surface coil built-in examination table, and the 12-channel wrist array coil, to receive signals. Image signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and the differences between the two methods were compared using a paired Student's <em>t</em>-test.</div></div><div><h3>Results</h3><div>In the phantom study, the image obtained with MICER had a higher SNR compared to the image obtained with the 12-channel wrist coil. Almost all wrist tissues showed a higher SNR on the images obtained with MICER than on the images obtained with the 12-channel wrist coil (<em>P</em> &lt; 0.05). And the CNR between wrist tissues on images obtained with MICER was higher than that obtained with the 12-channel wrist coil (<em>P</em> &lt; 0.05).</div></div><div><h3>Conclusions</h3><div>The quality of the MRI using MICER is superior to that of the commercially available 12-channel wrist coil, indicating its potential value for clinical practice.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110291"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142769868","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":"P53 status combined with MRI findings for prognosis prediction of single hepatocellular carcinoma","authors":"Hong Huang ,&nbsp;Qinghua Wu ,&nbsp;Hongyan Qiao ,&nbsp;Sujing Chen ,&nbsp;Shudong Hu ,&nbsp;Qingqing Wen ,&nbsp;Guofeng Zhou","doi":"10.1016/j.mri.2024.110293","DOIUrl":"10.1016/j.mri.2024.110293","url":null,"abstract":"<div><h3>Object</h3><div>To develop and validate a nomogram for predicting recurrence in individuals suffering single hepatocellular carcinoma (HCC) after curative hepatectomy.</div></div><div><h3>Material and methods</h3><div>A retrospective analysis was conducted on 189 patients with single HCC undergoing curative resection in our center were randomized into training and validation cohorts. P53 status was determined using immunohistochemistry. Clinical data, such as age, and gender were collected. MRI findings, such as tumor size, intratumoral arteries, the presence of peritumoral enhancement and intratumoral necrosis were also recorded. Nomograms were established based on the predictors selected in the training cohort, and receiver operating characteristic (ROC) curve analyses were used to compare the predictive ability among single predictors and nomogram model. The Kaplan-Meier method was used to assess the impact of each predictor and nomogram model on HCC recurrence. The results were validated in the validation cohort.</div></div><div><h3>Results</h3><div>Multivariate Cox regression analysis showed that P53 (<em>P</em> &lt; 0.001), tumor size (<em>P</em> = 0.009), and intratumoral artery (<em>P</em> = 0.026) were the independent risk factors for HCC recurrence. The nomogram model demonstrated favorable C-index of 0.740 (95 %CI:0.653–0.826) and 0.767 (95 %CI: 0.633–0.900) in the training and validation cohorts, and the areas under the curve was 0.740 and 0.752, which was better than the performance of P53 and MR factors alone. Calibration curves indicated a good agreement between observed actual outcomes and predicted values. Kaplan-Meier curves indicated that nomogram model was powerful in discrimination and clinical usefulness.</div></div><div><h3>Conclusions</h3><div>The integrated nomogram combining P53 status and MRI findings can be a valuable prognostic tool for predicting postoperative recurrence of single HCC.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"116 ","pages":"Article 110293"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142780474","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":"Effectiveness of fat suppression methods and influence on proton-resonance frequency shift (PRFS) MR thermometry","authors":"Anne Josset ,&nbsp;Jonathan Vappou ,&nbsp;Ounay Ishak ,&nbsp;Paolo Cabras ,&nbsp;Élodie Breton","doi":"10.1016/j.mri.2025.110340","DOIUrl":"10.1016/j.mri.2025.110340","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the effectiveness of fat suppression techniques experimentally and illustrate their influence on the accuracy of PRFS MR-thermometry.</div></div><div><h3>Methods</h3><div>The residual magnitudes of the main fat peaks are measured using a water-fat decomposition algorithm in an oil phantom and in vivo in swine bone marrow, either with spectral fat saturation (FS), water excitation (WE) or fast water excitation (FWE), as implemented on 1.5 T whole-body clinical MRIs. Thermometry experiments in tissue-mimicking oil-water phantoms (10 and 30 % fat) allow determining temperature errors in PRFS MR-thermometry with no fat suppression, FS and WE, compared against reference fiber optic thermometry.</div></div><div><h3>Results</h3><div>WE attenuates the signal of the main methylene fat peak more than FS (2 % and 22 % amplitude attenuation in the oil phantom, respectively), while the olefinic and glycerol peaks surrounding the water peak remain unaltered with both FS and WE. Within the 37 °C to 60 °C temperature range explored, FS and WE strongly attenuate temperature errors compared to PRFS without fat suppression. The residual fat signal after FS and WE leads to errors in PRFS thermometry, that increase with the fat content and oscillate with TE and temperature. In our tests limited to a single MR provider, fat suppression with WE appears to suppress fat signal more effectively.</div></div><div><h3>Conclusions</h3><div>We propose a protocol to quantify the remaining fraction of each spectral fat peak after fat suppression. In PRFS thermometry, despite spectral fat suppression, the remnant fat signal leads to temperature underestimation or overestimation depending on TE, fat fraction and temperature range. Fat suppression techniques should be evaluated specifically for quantitative MRI methods such as PRFS thermometry.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110340"},"PeriodicalIF":2.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074610","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":"Large blood vessel segmentation in quantitative DCE-MRI of brain tumors: A Swin UNETR approach","authors":"Anshika Kesari ,&nbsp;Satyajit Maurya ,&nbsp;Mohammad Tufail Sheikh ,&nbsp;Rakesh Kumar Gupta ,&nbsp;Anup Singh","doi":"10.1016/j.mri.2025.110342","DOIUrl":"10.1016/j.mri.2025.110342","url":null,"abstract":"<div><div>Brain tumor growth is associated with angiogenesis, wherein the density of newly developed blood vessels indicates tumor progression and correlates with the tumor grade. Quantitative dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) has shown potential in brain tumor grading and treatment response assessment. Segmentation of large-blood-vessels is crucial for automatic and accurate tumor grading using quantitative DCE-MRI. Traditional manual and semi-manual rule-based large-blood-vessel segmentation methods are time-intensive and prone to errors. This study proposes a novel deep learning-based technique for automatic large-blood-vessel segmentation using Swin UNETR architectures and comparing it with U-Net and Attention U-Net architectures. The study employed MRI data from 187 brain tumor patients, with training, validation, and testing datasets sourced from two centers, two vendors, and two field-strength magnetic resonance scanners. To test the generalizability of the developed model, testing was also carried out on different brain tumor types, including lymphoma and metastasis. Performance evaluation demonstrated that Swin UNETR outperformed other models in segmenting large-blood-vessel regions (achieving Dice scores of 0.979, and 0.973 on training and validation sets, respectively, with test set performance ranging from 0.835 to 0.982). Moreover, most quantitative parameters showed significant differences (<em>p</em> &lt; 0.05) between with and without large-blood-vessel. After large-blood-vessel removal, using both ground truth and predicted masks, the values of parameters in non-vascular tumoral regions were statistically similar (<em>p</em> &gt; 0.05). The proposed approach has potential applications in improving the accuracy of automatic grading of tumors as well as in treatment planning.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110342"},"PeriodicalIF":2.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074766","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":"Simultaneous acquisition of water, fat and velocity images using a phase-contrast 3p-Dixon method","authors":"Esteban Denecken ,&nbsp;Cristóbal Arrieta ,&nbsp;Diego Hernando ,&nbsp;Julio Sotelo ,&nbsp;Hernán Mella ,&nbsp;Sergio Uribe","doi":"10.1016/j.mri.2025.110341","DOIUrl":"10.1016/j.mri.2025.110341","url":null,"abstract":"<div><h3>Purpose</h3><div>Phase-contrast MRI (2D PC-MRI) and Dixon techniques share the characteristic that the difference in frequency between water and fat, as well as the velocity, are encoded in the phase of the MR signal. We propose to take advantage of this characteristic to obtain both sets of images simultaneously. Such an acquisition will improve efficiency by obtaining both types of images in the same scan and will provide co-registered images of water-fat species and velocity images. This, in turn, will correct fat artifacts due to chemical shift in PC-MRI based measurements.</div></div><div><h3>Methods</h3><div>This study presents a novel PC multi-echo (PCME-MRI) sequence jointly with a 3-point (3p-) Dixon pipeline that enables reconstruction of water, fat, and velocity images simultaneously. The proposed 3p-Dixon approach preserves the phase information of water-fat images, while velocity images are obtained from the resulting water components.</div></div><div><h3>Results</h3><div>Numerical phantom tests and 2D MR axial images of the neck acquired in 12 healthy volunteers demonstrated the feasibility of the PC 3p-Dixon method, showing comparable performance to standard techniques. In volunteers the median and range MAE comparing PC 3p-Dixon, and standard 3p-Dixon fat fraction were 0.06 and [0.03, 0.09]. The median and range of velocity for PC 3p-Dixon were 6.15 ml and [3.86, 7.21]ml, compared to 6.43 ml and [4.62, 8.27]ml obtained by 2D PC-MRI.</div></div><div><h3>Conclusion</h3><div>Numerical phantom experiments and acquisitions from healthy volunteers showed promising results in fat fraction and velocity estimation of PC 3p-Dixon compared with standard 3p-Dixon and 2D PC-MRI, obtaining both data sets in similar times as standard 3p Dixon.</div></div>","PeriodicalId":18165,"journal":{"name":"Magnetic resonance imaging","volume":"118 ","pages":"Article 110341"},"PeriodicalIF":2.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074827","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}