Magnetic resonance imaging最新文献

Purpose

Multi-echo, multi-contrast methods are increasingly used in dynamic imaging studies to simultaneously quantify $R_2^{\ast }$ and R₂. To overcome the computational challenges associated with nonlinear least squares (NLSQ) fitting, we propose a generalized linear least squares (LLSQ) solution to rapidly fit $R_2^{\ast }$ and R₂.

Methods

Spin- and gradient-echo (SAGE) data were simulated across $T_2^{\ast }$ and T₂ values at high (200) and low (20) SNR. Full (four-parameter) and reduced (three-parameter) parameter fits were implemented and compared with both LLSQ and NLSQ fitting. Fit data were compared to ground truth using concordance correlation coefficient (CCC) and coefficient of variation (CV). In vivo SAGE perfusion data were acquired in 20 subjects with relapsing-remitting multiple sclerosis. LLSQ $R_2^{\ast }$ and R₂, as well as cerebral blood volume (CBV), were compared with the standard NLSQ approach.

Results

Across all fitting methods, $T_2^{\ast }$ was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.87, CV ≤ 0.08) SNR. Except for short $T_2^{\ast }$ values (5–15 ms), T₂ was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.99, CV ≤ 0.03) SNR. In vivo, LLSQ $R_2^{\ast }$ and R₂ estimates were similar to NLSQ, and there were no differences in $R_2^{\ast }$ across fitting methods at high SNR. However, there were some differences at low SNR and for R₂ at high and low SNR. In vivo NLSQ and LLSQ three parameter fits performed similarly, as did NLSQ and LLSQ four-parameter fits. LLSQ CBV nearly matched the standard NLSQ method for $R_2^{\ast }$- (0.97 ratio) and R₂-CBV (0.98 ratio). Voxel-wise whole-brain fitting was faster for LLSQ (3–4 min) than NLSQ (16–18 h).

Conclusions

LLSQ reliably fit for $R_2^{\ast }$ and R₂ in simulated and in vivo data. Use of LLSQ methods reduced the computational demand, enabling rapid estimation of $R_2^{\ast }$ and R₂.

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Background

Magnetic resonance elastography (MRE) is a rapidly developing medical imaging technique that allows for quantitative assessment of the biomechanical properties of the tissue. MRE is now regarded as the most accurate noninvasive test for detecting and staging liver fibrosis. A two-dimensional (2D MRE) acquisition version is currently deployed at >2000 locations worldwide. 2D MRE allows for the evaluation of the magnitude of the complex shear modulus, also referred to as stiffness. The development of 3D vector MRE has enabled researchers to assess the biomechanical properties of small organs where wave propagation cannot be adequately analyzed with the 2D MRE imaging approach used in the liver. In 3D vector MRE, the shear waves are imaged and processed throughout a 3D volume and processed with an algorithm that accounts for wave propagation in any direction. Additionally, the motion is also imaged in x, y, and z directions at each voxel, allowing for more advanced processing to be applied.

Purpose

This review describes the technical principles of 3D vector MRE, surveys its clinical applications in small organs, and discusses potential clinical significance of 3D vector MRE.

Conclusion

3D vector MRE is a promising tool for characterizing the biomechanical properties of small organs such as the uterus, pancreas, thyroid, prostate, and salivary glands. However, its potential has not yet been fully explored.

Introduction

Although ischemia-reperfusion (I/R) injury varies between cortical and subcortical regions, its effects on specific regions remain unclear. In this study, we used various magnetic resonance imaging (MRI) techniques to examine the spatiotemporal dynamics of I/R injury within the salvaged ischemic penumbra (IP) and reperfused ischemic core (IC) of a rodent model, with the aim of enhancing therapeutic strategies by elucidating these dynamics.

Materials and methods

A total of 17 Sprague–Dawley rats were subjected to 1 h of transient middle cerebral artery occlusion with a suture model. MRI, including diffusion tensor imaging (DTI), T2-weighted imaging, perfusion-weighted imaging, and T1 mapping, was conducted at multiple time points for up to 5 days during the I/R phases. The spatiotemporal dynamics of blood–brain barrier (BBB) modifications were characterized through changes in T1 within the IP and IC regions and compared with mean diffusivity (MD), T2, and cerebral blood flow.

Results

During the I/R phases, the MD of the IC initially decreased, normalized after recanalization, decreased again at 24 h, and peaked on day 5. By contrast, the IP remained relatively stable. Both the IP and IC exhibited hyperperfusion, with the IP reaching its peak at 24 h, followed by resolution, whereas hyperperfusion was maintained in the IC until day 5. Despite hyperperfusion, the IP maintained an intact BBB, whereas the IC experienced persistent BBB leakage. At 24 h, the IC exhibited an increase in the T2 signal, corresponding to regions exhibiting BBB disruption at 5 days.

Conclusions

Hyperperfusion and BBB impairment have distinct patterns in the IP and IC. Quantitative T1 mapping may serve as a supplementary tool for the early detection of malignant hyperemia accompanied by BBB leakage, aiding in precise interventions after recanalization. These findings underscore the value of MRI markers in monitoring ischemia-specific regions and customizing therapeutic strategies to improve patient outcomes.

Objective

To compare and explore the characteristics of squamous cell carcinoma (SCC), adenocarcinoma (AC) and adenosquamous carcinoma (ASC), usual-type endocervical adenocarcinoma (UEA) and gastric adenocarcinoma (GAC) of cervix.

Materials and methods

A total of 728 cervical cancers (254 cases of AC, 252 cases of ASC, and 222 cases of SCC) confirmed by histopathology were retrospectively reviewed. Among AC, 119 UEA and 47 GAC were included. Clinical baseline data and tumor morphological features on MRI (including tumor location, shape, diameter and volume, margin, growth pattern, presence of fluid component or cyst, heterogenous and peritumoral enhancement) of all cases were collected and analyzed. The signal intensity (SI) of tumor and gluteus maximus muscle were measured and their ratios (SIR) were calculated based on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and contrast-enhanced T1WI at arterial and delay phases (A/DCE-T1WI). These clinical and MRI features were compared between SCC, AC and ASC, UEA and GAC, and the specific ones of each subtype were identified.

Results

There was a significant difference in SCC-Ag, CA-199, CEA, ADC value, SIR-DWI, presence of intratumor cyst and peritumoral enhancement between AC and ASC; in patient age, menopausal status, International Federation of Gynecology and Obstetrics (FIGO) stage, SCC-Ag, CA-125, CA-199, CEA, tumor shape, growth pattern, margin, presence of intratumor fluid component and cyst, tumor diameter and volume, ADC value, SIR-T1WI, SIR-T2WI, and SIR-DWI between SCC and AC, as well as SCC and ASC. Also, there was a significant difference in deep stromal invasion (DSI), peritumoral and heterogenous enhancement between SCC and AC, and in SIR-ACE-T1WI between SCC and ASC. There was a significant difference in reproductive history, menopausal status, FIGO stage, CA-199, DSI, lymph node metastasis (LNM), parametrial invasion (PMI), tumor location, shape, margin, growth pattern, presence of fluid component and cyst, tumor diameter and volume, SIR-T1WI, SIR-DWI, and heterogenous enhancement between GAC and UEA.

Conclusion

The clinical and MRI features with significant differences among SCC, AC and ASC, and between UEA and GAC, can help to identify each subtype of cervical cancer.

Background

To compare the value of adipose tissues in abdomen and lumbar vertebra for predicting Crohn's disease (CD) activity based on chemical shift encoded magnetic resonance imaging (CSE-MRI).

Methods

84 CD patients were divided into remission, mild, and moderate-severely groups based on CD activity index (CDAI). Differences in different adipose parameters [subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), mesenteric fat index (MFI), and bone marrow fat fraction (BMFF)] and blood inflammatory indicators among three groups, as well as the correlation of above parameters and CDAI were analyzed. The areas under the receiver-operating characteristic curves (AUCs) for the parameters selected by multivariate logistic regression analysis for predicting active CD were calculated.

Results

There were no significant differences in VAT and MFI among three groups (both P > 0.05). The cross-sectional areas of SAT in moderate-severe group were significantly lower than those in remission group (P = 0.014). BMFF values of remission group were significantly higher than those in the mild and moderate-severe groups (both P < 0.001). BMFF was negatively correlated with CDAI (r = −0.595, P < 0.001). SAT exhibited no significant correlation with CDAI. Erythrocyte sedimentation rate (ESR) and BMFF were the independent predictors of CDAI. Both combined had a higher diagnostic efficacy for active CD with an AUC of 0.895.

Conclusions

BMFF is the best marker for predicting CD activity in fat parameters of abdomen and lumbar vertebra based on CSE-MRI. The model based on BMFF and ESR has a high efficiency in predicting active CD.

Trial registration

No. 22 K164 (Registered 18-07-2022).

Objectives

To evaluate the performance of the multimodal model, termed variable Vision Transformer (vViT), in the task of predicting isocitrate dehydrogenase (IDH) status among adult patients with diffuse glioma.

Materials and methods

vViT was designed to predict IDH status using patient characteristics (sex and age), radiomic features, and contrast-enhanced T1-weighted images (CE-T1WI). Radiomic features were extracted from each enhancing tumor (ET), necrotic tumor core (NCR), and peritumoral edematous/infiltrated tissue (ED). CE-T1WI were split into four images and input to vViT. In the training, internal test, and external test, 271 patients with 1070 images (535 IDH wildtype, 535 IDH mutant), 35 patients with 194 images (97 IDH wildtype, 97 IDH mutant), and 291 patients with 872 images (436 IDH wildtype, 436 IDH mutant) were analyzed, respectively. Metrics including accuracy and AUC-ROC were calculated for the internal and external test datasets. Permutation importance analysis combined with the Mann–Whitney U test was performed to compare inputs.

Results

For the internal test dataset, vViT correctly predicted IDH status for all patients. For the external test dataset, an accuracy of 0.935 (95% confidence interval; 0.913–0.945) and AUC-ROC of 0.887 (0.798–0.956) were obtained. For both internal and external test datasets, CE-T1WI ET radiomic features and patient characteristics had higher importance than other inputs (p < 0.05).

Conclusions

The vViT has the potential to be a competent model in predicting IDH status among adult patients with diffuse glioma. Our results indicate that age, sex, and CE-T1WI ET radiomic features have key information in estimating IDH status.

Diffusion tensor imaging (DTI) is commonly used to establish three-dimensional mapping of white-matter bundles in the supraspinal central nervous system. DTI has also been the subject of many studies on cranial and peripheral nerves. This non-invasive imaging technique enables virtual dissection of nerves in vivo and provides specific measurements of microstructural integrity. Adverse effects on the lumbosacral plexus may be traumatic, compressive, tumoral, or malformative and thus require dedicated treatment. DTI could lead to new perspectives in pudendal neuralgia diagnosis and management.

We performed a systematic review of all articles or posters reporting results and protocols for lumbosacral plexus mapping using the DTI technique between January 2011 and December 2023.

Twenty-nine articles published were included. Ten studies with a total of 351 participants were able to track the lumbosacral plexus in a physiological context and 19 studies with a total of 402 subjects tracked lumbosacral plexus in a pathological context. Tractography was performed on a 1.5T or 3T MRI system. DTI applied to the lumbosacral plexus and pudendal nerve is feasible but no microstructural normative value has been proposed for the pudendal nerve. The most frequently tracking parameters used in our review are: 3T MRI, b-value of 800 s/mm², 33 directions, 3 × 3 × 3 mm³, AF threshold of 0.1, minimum fiber length of 10 mm, bending angle of 30°, and 3DT2 TSE anatomical resolution.

Increased use of DTI could lead to new perspectives in the management of pudendal neuralgia due to entrapment syndrome, whether at the diagnostic, prognostic, or preoperative planning level.

Prospective studies of healthy subjects and patients with the optimal acquisition parameters described above are needed to establish the accuracy of MR tractography for diagnosing pudendal neuralgia and other intrapelvic nerve entrapments.

Purpose

To look for links between diffusion and IVIM parameters and different molecular subtypes and prognostic factors through histogram analysis.

Materials and methods

A total of 139 patients with breast cancer who had pre-operative MRI examinations were enrolled in this retrospective study. Histograms of the diffusion and IVIM parameters were analyzed for the whole tumor, and an association was investigated between the parameters and the different molecular prognostic factors and subtypes using the nonparametric test, Spearman's rank correlation, and receiver operating characteristic (ROC) curve.

Results

The histogram metrics of the diffusion and IVIM parameters were significantly different for molecular prognostic factors such as human epidermal receptor factor-2 (HER2), progesterone receptor, estrogen receptor, and ki-67. All histogram metrics displayed a poor correlation with all groups (r = −0.28-0.29). There were significant differences in the histogram metrics for the Luminal B-HER2 (−) vs. HER2-positive (non-luminal) subtypes in the mean and 10th percentile D, with the area under the curves (AUCs) of 0.742 and 0.700, respectively, and for the Luminal A and HER2-positive (non-luminal) subtypes in the 90th percentile and entropy of D*, with AUCs of 0.769 and 0.727, respectively.

Conclusion

The histogram metrics of IVIM parameters exhibited links with breast cancer prognosis factors and combined subtypes.