Conventional Magnetic Resonance Imaging Sequences Research Articles

MRI based evaluation of carcinoma gallbladder using apparent diffusion coefficient (ADC) and diffusion weighted imaging (DWI)

Background Carcinoma of the gallbladder is a malignant neoplasm, which is associated with a poor prognosis due to its often-asymptomatic nature and late-stage diagnosis. Non-invasive imaging techniques play a key role in the early detection and characterization of gallbladder carcinoma. This thesis presents a comprehensive analysis of the utility of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) mapping in the magnetic resonance imaging (MRI) evaluation of carcinoma of the gallbladder. The primary objective of this research was to investigate the exact diagnostic accuracy and potential clinical applications of DWI and ADC in assessing carcinoma of the gallbladder and related tumour aggressiveness. A systematic review of existing literature was conducted to establish a foundation for this study with efforts to acquire relevant imaging data. The results of this study demonstrate the efficacy of DWI and ADC in the detection of carcinoma of the gallbladder when compared to conventional MRI sequences. These advanced imaging techniques hold promise in increasing the accuracy of diagnosis, ultimately leading to improved patient outcomes and more informed clinical decision making. The potential of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) mapping in the evaluation of gallbladder cancer using magnetic resonance imaging (MRI) is thoroughly analysed in this thesis. Methods A descriptive prospective study will be done at Acharya Vinoba Bhave Rural Hospital, Sawangi, involving 20 patients with clinically suspected carcinoma gallbladder, who are referred to the department of Radiodiagnosis. These patients will be subjected to study-purposive sampling. Conclusion After an appropriate statistical analysis, we expect to assess the role of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) mapping in the magnetic resonance imaging (MRI) evaluation of carcinoma of the gallbladder. CTRI registration This trial has been submitted to Clinical Trials Registry-India (CTRI) for Review. Registration Number: REF/2023/09/072780 Registration date:01/05/2023 URL of trial: https://www.ctri.nic.in/

Measuring synovial thickness on knee MRI in pediatric patients with arthritis: is contrast necessary?

The use of contrast-enhanced imaging has long been standard for magnetic resonance imaging (MRI) assessments of synovitis in juvenile idiopathic arthritis (JIA). However, advancements in MRI technology have allowed for reliable identification of synovium without contrast. To assess the equivalence of unenhanced MRI with contrast-enhanced MRI in evaluating synovial thickness. This is an institutional review board approved, retrospective study performed in a tertiary children's hospital. Pediatric JIA patients under 21 years old were included who underwent knee MRI scans (1.5 T or 3 T) without and with contrast between January 2012 and January 2022. Two radiologists independently measured synovial thickness at 6 knee sites on contrast-enhanced and unenhanced sequences. Numerical measurements and ordinal scores based on juvenile idiopathic arthritis magnetic resonance imaging scoring (JAMRIS) system were recorded, and tests of equivalence were conducted, as well as between-reader and within-reader reliability by concordance correlation coefficient (CCC). All tests were considered significant at the 5% level. A total of 38 studies from 35 patients (25 females, median age 14 years; interquartile range 7 to 15.7) were included. Equivalence was demonstrated at each of the 6 sites for both continuous measurements (P-values < 0.05) and ordinal scores (P-values < 0.05) based on the average over readers. Within-reader reliability was moderate to high (CCC 0.50-0.89), except for the cruciate ligaments site. Averaged over the 6 sites, reliability between readers was low for unenhanced (CCC 0.47, with 95% CI: [0.41, 0.53]) and moderate for contrast-enhanced (CCC 0.64, with 95% CI: [0.59, 0.69]) sequences. Unenhanced knee MRI is equivalent to contrast-enhanced MRI in assessment of synovial thickness using conventional MRI sequences. Contrast material helped improve inter-reader reliability.

Deep learning-based reconstruction enhances image quality and improves diagnosis in magnetic resonance imaging of the shoulder joint.

Accelerated magnetic resonance imaging sequences reconstructed using the vendor-provided Recon deep learning algorithm (DL-MRI) were found to be more likely than conventional magnetic resonance imaging (MRI) sequences to detect subacromial (SbA) bursal thickening. However, the extent of this thickening was not extensively explored. This study aimed to compare the image quality of DL-MRI with conventional MRI sequences reconstructed via conventional pipelines (Conventional-MRI) for shoulder examinations and evaluate the effectiveness of DL-MRI in accurately demonstrating the degree of SbA bursal and subcoracoid (SC) bursal thickening. This prospective cross-sectional study enrolled 41 patients with chronic shoulder pain who underwent 3-T MRI (including both Conventional-MRI and accelerated MRI sequences) of the shoulder between December 2022 and April 2023. Each protocol consisted of oblique axial, coronal, and sagittal images, including proton density-weighted imaging (PDWI) with fat suppression (FS) and oblique coronal T1-weighted imaging (T1WI) with FS. The image quality and degree of artifacts were assessed using a 5-point Likert scale for both Conventional-MRI and DL-MRI. Additionally, the degree of SbA and SC bursal thickening, as well as the relative signal-to-noise ratio (rSNR) and relative contrast-to-noise ratio (rCNR) were analyzed using the paired Wilcoxon test. Statistical significance was defined as P<0.05. The utilization of accelerated sequences resulted in a remarkable 54.7% reduction in total scan time. Overall, DL-MRI exhibited superior image quality scores and fewer artifacts compared to Conventional-MRI. Specifically, DL-MRI demonstrated significantly higher measurements of SC bursal thickenings in the oblique sagittal PDWI sequence compared to Conventional-MRI [3.92 (2.83, 5.82) vs. 3.74 (2.92, 5.96) mm, P=0.028]. Moreover, DL-MRI exhibited higher detection of SbA bursal thickenings in the oblique coronal PDWI sequence [2.61 (1.85, 3.46) vs. 2.48 (1.84, 3.25) mm], with a notable trend towards significant differences (P=0.071). Furthermore, the rSNRs of the muscle in DL-MRI images were significantly higher than those in Conventional-MRI images across most sequences (P<0.001). However, the rSNRs of bone on Conventional-MRI of oblique axial and oblique coronal PDWI sequences showed adverse results [oblique axial: 1.000 (1.000, 1.000) vs. 0.444 (0.367, 0.523); and oblique coronal: 1.000 (1.000, 1.000) vs. 0.460 (0.387, 0.631); all P<0.001]. Additionally, all DL-MRI images exhibited significantly greater rSNRs and rCNRs compared to accelerated MRI sequences reconstructed using traditional pipelines (P<0.001). In conclusion, the utilization of DL-MRI enhances image quality and improves diagnostic capabilities, making it a promising alternative to Conventional-MRI for shoulder imaging.

Diagnostic contribution of diffusion-weighted imaging in liver hemangiomas

Objective: To evaluate the contribution of diffusion-weighted imaging (DWI) and measure apparent diffusion coefficient values (ADC) in hepatic hemangiomas.&#x0D; Material and Methods: Seventy patients with liver hemangiomas were evaluated with DWI with a b value of 800 s/mm2. ADC map was created and ADC values were measured for 70 liver masses and normal liver tissue following DWI. ADC measurements of 70 normal liver parenchyma and mean ADC values of 80 hemangiomas are performed.&#x0D; Results: Eighty hemangiomas of 70 patients (50 female and 20 male) were evaluated. The mean age of the patients was 49.61±10.96 years. Hemangiomas were most frequently demonstrated at segment 7 (%28.8), segment 6 (%21.3), and least demonstrated at segment 5 (%5). While the mean ADC measurements of normal livers were 1.06±0.11 x 10-3 mm2/sn, the mean ADC values of hemangiomas were measured as 1.70±0.29 x 10-3 mm2/sn.&#x0D; Conclusion: DWI and the ADC measurements seem to be useful for the diagnosis of liver hemangiomas. DWI should be routinely added to conventional magnetic resonance imaging sequences.

Development and validation of a multi-modality fusion deep learning model for differentiating glioblastoma from solitary brain metastases.

Glioblastoma (GBM) and brain metastases (BMs) are the two most common malignant brain tumors in adults. Magnetic resonance imaging (MRI) is a commonly used method for screening and evaluating the prognosis of brain tumors, but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited. In recent years, deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system. This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases (SBMs), and to further explore the impact of multimodality data fusion on classification tasks. Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed. First, structural T1-weight, T1C-weight, and T2-weight were selected as 3 inputs to the entire model, regions of interest (ROIs) were manually delineated on the registered three modal MR images, and multimodality radiomics features were obtained, dimensions were reduced using a random forest (RF)-based feature selection method, and the importance of each feature was further analyzed. Secondly, we used the method of contrast disentangled to find the shared features and complementary features between different modal features. Finally, the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs. Furthermore, compared with single-modal data, the multimodal fusion models using machine learning algorithms such as support vector machine (SVM), Logistic regression, RF, adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) achieved significant improvements, with area under the curve (AUC) values of 0.974, 0.978, 0.943, 0.938, and 0.947, respectively; our comparative disentangled multi-modal MR fusion method performs well, and the results of AUC, accuracy (ACC), sensitivity (SEN) and specificity(SPE) in the test set were 0.985, 0.984, 0.900, and 0.990, respectively. Compared with other multi-modal fusion methods, AUC, ACC, and SEN in this study all achieved the best performance. In the ablation experiment to verify the effects of each module component in this study, AUC, ACC, and SEN increased by 1.6%, 10.9% and 15.0%, respectively after 3 loss functions were used simultaneously. A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

A Cross-sectional Study on Neuroimaging in Epilepsy: Diagnostic Value of T2 Relaxometry in Mesial Temporal Lobe Epilepsy

Introduction: The use of Magnetic Resonance Imaging (MRI) T2 relaxometry and spectroscopy has added new dimensions to the imaging of Temporal Lobe Epilepsy (TLE). Advanced techniques like MRI diffusion and MRI perfusion are new additions to the MRI protocol for epilepsy. Aim: To study the diagnostic value of T2 relaxation time in Electroencephalogram (EEG) confirmed seizure cases. Materials and Methods: A single-centre, cross-sectional study was conducted at Department of Radiodiagnosis, Saveetha Medical College, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India, from December 2020 to November 2022 at a tertiary care hospital. All patients were subjected to MRI with a special epilepsy protocol and T2 relaxometry. Hippocampal T2 relaxation values for each slice were measured by placing a Region of Interest (ROI) on the representative image obtained from the T2 relaxometry sequence, focusing on the hippocampus in both the control and study groups. The control group (n=30) consisted of healthy volunteers, whereas the case group (n=36) comprised patients presenting with a history of seizures with positive MRI and EEG findings. Mean T2 relaxation time was calculated in each ROI, and an average was derived. Mean and Standard Deviation (SD) were calculated for the continuous variables, while ratios and proportions were calculated for the categorical variables. To determine the association of T2 relaxometry values in the study and control groups, an unpaired t-test was used. Results: The mean age of participants was 25.14±9.35 years (ranging from 9 to 51 years). The male-to-female ratio was 1.25:1. Hippocampal atrophy (32 out of 36 cases) and T2 signal alteration (30 out of 36 cases) were the most commonly identified features in Mesial Temporal Sclerosis (MTS). MRI without T2 relaxometry had a sensitivity of 94%. In two cases, where only mild hippocampal atrophy was identified in the conventional MRI sequence, making the diagnosis dubious, T2 relaxometry revealed increased T2 relaxation time in the head of the hippocampus and guided a proper diagnosis. EEG was able to lateralise seizures in 8 out of 13 right MTS cases (61.5%), 10 out of 17 left MTS cases (58.9%), and 5 out of 6 cases of bilateral MTS (83%). Conclusion: T2 relaxometry allows quantification of hippocampal signal intensity, allowing the detection of even subtle changes in signal intensity that are difficult to perceive by visual assessment.

The value of 3D high-resolution IR-prepared fast spoiled gradient-recalled MRI in the diagnosis of meningeal carcinomatosis involving the cranial nerves

PurposeThe purpose of this study was to investigate the clinical utility of three-dimension (3D) high-resolution inversion recovery (IR)-prepared fast spoiled gradient-recalled (SPGR) magnetic resonance imaging (MRI) in the diagnosis of cranial nerve meningeal carcinomatosis (MC).MethodsA total of 114 patients with MC from January 2015 to March 2020 were enrolled and their MRIs were analyzed retrospectively. All patients underwent MRIs before being administered a contrast agent. Both a 2D conventional MRI sequence and a 3D IR-prepared fast SPGR high-resolution T1-weighted (BRAVO) scan sequence were measured after contrast agent administration. The characteristics of MC and the involved cranial nerves were then examined.ResultsAmong the 114 MC patients, 81 (71.05%) had cranial nerve enhancement on contrast-enhanced 3D-BRAVO imaging, while only 41 (35.96%) had image enhancement on conventional MRI. The contrast-enhanced 3D-BRAVO displayed stronger image contrast enhancement of the cranial nerves than the conventional MRI (P < 0.001). Furthermore, detection rates for the facial and auditory nerves, trigeminal nerve, oculomotor nerve, sublingual nerve, optic nerve, glossopharyngeal/vagal/accessory nerve, and abductor nerve on contrast-enhanced 3D-BRAVO imaging were 58.77%, 47.37%, 9.65%, 8.77%, 5.26%, 3.51%, and 0.88%, respectively. We found a statistically significant difference between the affected facial and auditory nerves, as well as the trigeminal nerve, oculomotor nerve, sublingual nerve, and optic nerve.ConclusionIn MC, contrast-enhanced 3D-BRAVO imaging displayed the cranial nerves more effectively than 2D conventional enhanced MRI. The facial, auditory, and trigeminal nerves are the primary nerves involved in MC, and improved scanning of these nerves would aid in the early detection and treatment of MC.

Papel de la resonancia magnética de difusión en el diagnóstico inicial de los tumores de partes blandas

BackgroundSoft tissue tumours (STT) constitute a heterogeneous group of lesions frequently studied by Magnetic Resonance Imaging (MRI). It has not yet been clearly established whether the inclusion of apparent diffusion coefficient (ADC) diffusion-weighted imaging (DWI) maps would better determine tumour aggressiveness. PurposeTo assess the diagnostic value of quantitative ADC DWI maps in the initial diagnosis of STT; and to determine whether the inclusion of DWI provides more valuable information than conventional sequences alone. Material and methodsRetrospective study of patients with histologically proven STT. Conventional morphological MRI sequences and the DWI sequence were analysed. The ADC was quantified using a region of interest (ROI) that covered the largest sectional area (global ADC) and another that selected the area of greatest restriction (selected ADC). Differences in ADC values were analysed between both benign and malignant lesions and high and low-grade sarcomas. A multivariate analysis was performed to determine the ability of ADC to adequately diagnose the nature of STTs when associated with other morphological characteristics. Results84 patients with STT, of which 40 were benign and 44 malignant. The malignant group included 10 low-grade sarcomas, 23 high-grade sarcomas, 4 non-sarcomatous neoplasms and 7 sarcomas with no histological grading. The ADC values were significantly higher in benign lesions for the selected ADC. Significantly higher selected ADC values were also obtained in low-grade sarcomas. In the multivariate analysis, the highest diagnostic precision values were obtained when morphological features and ADC were included, with a sensitivity, specificity, and area under the curve (AUC) of 84, 75 and 91%, respectively. ConclusionThe inclusion of ADC DWI values improves the diagnostic accuracy of MRI for STTs, especially when used in combination with conventional MRI sequences.

Role of diffusion-weighted MR imaging in the initial diagnosis of soft tissue tumours

BackgroundSoft tissue tumours (STT) constitute a heterogeneous group of lesions frequently studied by Magnetic Resonance Imaging (MRI). It has not yet been clearly established whether the inclusion of apparent diffusion coefficient (ADC) diffusion-weighted imaging (DWI) maps would better determine tumour aggressiveness. PurposeTo assess the diagnostic value of quantitative ADC DWI maps in the initial diagnosis of STT; and to determine whether the inclusion of DWI provides more valuable information than conventional sequences alone. Material and methodsRetrospective study of patients with histologically proven STT. Conventional morphological MRI sequences and the DWI sequence were analysed. The ADC was quantified using a region of interest (ROI) that covered the largest sectional area (global ADC) and another that selected the area of ​​greatest restriction (selected ADC). Differences in ADC values ​​were analysed between both benign and malignant lesions and high and low-grade sarcomas. A multivariate analysis was performed to determine the ability of ADC ​​to adequately diagnose the nature of STTs when associated with other morphological characteristics. Results84 patients with STT, of which 40 were benign and 44 malignant. The malignant group included 10 low-grade sarcomas, 23 high-grade sarcomas, 4 non-sarcomatous neoplasms and 7 sarcomas with no histological grading. The ADC values ​​were significantly higher in benign lesions for the selected ADC. Significantly higher selected ADC values ​​were also obtained in low-grade sarcomas. In the multivariate analysis, the highest diagnostic precision values were obtained when morphological features and ADC were included, with a sensitivity, specificity, and area under the curve (AUC) of 84, 75 and 91%, respectively. ConclusionThe inclusion of ADC DWI values ​​improves the diagnostic accuracy of MRI for STTs, especially when used in combination with conventional MRI sequences.

Radiogenomics for predicting microsatellite instability status and PD-L1 expression with machine learning in endometrial cancers: A multicenter study

PurposeTo evaluate the effectiveness of machine learning model based on magnetic resonance imaging (MRI) in identifying microsatellite instability (MSI) status and PD-L1 expression in endometrial cancer (EC). MethodsThis retrospective study included 82 EC patients from 2 independent centers. Radiomics features from the intratumoral and peritumoral regions, obtained from four conventional MRI sequences (T2-weighted images; contrast-enhanced T1-weighted images; diffusion-weighted images; apparent diffusion coefficient), were combined with clinicopathologic characteristics to develop machine learning model for predicting MSI status and PD-L1 expression. 60 patients from center 1 were used as the training set for model construction, while 22 patients from center 2 were used as an external validation set for model evaluation. ResultsFor predicting MSI status, the clinicopathologic model, radscore model, and combination model achieved area under the curves (AUCs) of 0.728, 0.833, and 0.889 in the training set, respectively, and 0.595, 0.790, and 0.848 in the validation set, respectively. For predicting PD-L1 expression, the clinicopathologic model, radscore model, and combination model achieved AUCs of 0.648, 0.814, and 0.834 in the training set, respectively, and 0.660, 0.708, and 0.764 in the validation set, respectively. Calibration curve analysis and decision curve analysis demonstrated good calibration and clinical utility of the combination model. ConclusionThe machine learning model incorporating MRI-based radiomics features and clinicopathologic characteristics could be a potential tool for predicting MSI status and PD-L1 expression in EC. This approach may contribute to precision medicine for EC patients.

Modern neuroimaging criteria for diagnosing multiple sclerosis in children

The article presents a clinical case of multiple sclerosis (MS) in a 10-year-old female patient, the use of one of the advanced magnetic resonance imaging (MRI) techniques, namely proton magnetic resonance spectroscopy (1H-MRS), in the diagnosis of MS. MRI is an integral part of the diagnostic algorithm for patients with multiple sclerosis according to the McDonald criteria, which were last updated in 2017. In addition, MRI allows assessing the course of the disease, serving as a criterion for confirming the aggravation of the pathological process. Although the McDonald criteria are applied in adults, they are also used to diagnose MS in children, and MS in children has its own particularities. The McDonald criteria include traditional (conventional) MRI sequences: T2-weighted images, T1-weighted images, post-contrast T1-weighted images. With the rapid development of MRI, cutting-edge (advanced) MRI techniques have emerged that allow for a better understanding of changes in the brain matter in MS: brain volumetry, magnetization transfer imaging, cortical imaging, diffusion tensor imaging, 1H-MRS, susceptibility-weighted imaging. In particular, 1H-MRS allows us to assess the degree of white matter integrity by detecting increased resonance of myelin breakdown metabolites. The studies have shown that changes in MS have their own specificity, but there is no consensus on this issue. Currently, there are no agreed guidelines that would include advanced MRI techniques, but we believe they will allow us to better understand the course of MS and to predict the development of the disease. This approach will improve the management of MS in both adults and children and quality of their life.

The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging.

In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.

Diffusion-Weighted Imaging and Chemical Shift Imaging to Differentiate Benign and Malignant Vertebral Lesion: A Hospital-Based Cross-Sectional Study.

Objective The aim of this study was to evaluate the role of diffusion-weighted imaging (DWI) and chemical shift imaging (CSI) for the differentiation of benign and malignant vertebral lesions. Methods Patients with vertebral lesions underwent routine magnetic resonance imaging (MRI) along with DWI and CSI. Qualitative analysis of the morphological features was done by routine MRI. Quantitative analysis of apparent diffusion coefficient (ADC) from DWI and fat fraction (FF) from CSI was done and compared between benign and malignant vertebral lesions. Results Seventy-two patients were included. No significant difference was noted in signal intensities of benign and malignant lesions on conventional MRI sequences. Posterior element involvement, paravertebral soft-tissue lesion, and posterior vertebral bulge were common in malignant lesion, whereas epidural/paravertebral collection, absence of posterior vertebral bulge, and multiple compression fractures were common in benign vertebral lesion ( p < 0.001). The mean ADC value was 1.25 ± 0.27 mm 2 /s for benign lesions and 0.9 ± 0.19 mm 2 /s for malignant vertebral lesions ( p ≤ 0.001). The mean value of FF was 12.7 ± 7.49 for the benign group and 4.04 ± 2.6 for the malignant group ( p < 0.001). A receiver operating characteristic (ROC) curve analysis showed that an ADC cutoff of 1.05 × 10 -3 mm 2 /s and an FF cutoff of 6.9 can differentiate benign from malignant vertebral lesions, with the former having 86% sensitivity and 82.8% specificity and the latter having 93% sensitivity and 96.6% specificity. Conclusion The addition of DWI and CSI to routine MRI protocol in patients with vertebral lesions promises to be very helpful in differentiating benign from malignant vertebral lesions when difficulty in qualitative interpretation of conventional MR images arises.

Added Value of MRI Knee Cartigram in Assessment of Anterior Knee Pain in Comparison to Conventional Standard MRI

Background Osteoarthritis (OA) is a multi-tissue, multi-factorial disease and worldwide a major cause of disability resulting from reduced joint mobility and function. Progressive loss of hyaline cartilage is one of the hallmark features of osteoarthritis, initiated by a loss of proteoglycans and an increase in water content, followed by a loss of type II collagen and a change in collagen fiber orientation. Objective To evaluate the role of T2 mapping in detection of degenerative changes in articular cartilage of knee joint as compared to standard clinical magnetic resonance imaging (MRI) at 1.5T. Patients and Methods From April 2020 to November 2020, this prospective Study was done to use T2 mapping to visualize the articular cartilage of the knee on 1.5 T MR Scanner using special software to evaluate the efficiency Of T2 mapping to detect cartilage lesions. The material of this study included 380 patients. The study includes all of them come complaining of knee pain and 2 of them had previous minor knee trauma, each patient had a single MRI exanimation including conventional MRI routine protocol and added a single complementary T2 mapping. Results there were significant differences between T2 mapping and conventional MRI sequence in the ability to detect cartilage degeneration as T2 mapping was capable of detecting all lesions that were visible on the clinical MRI. Moreover, T2 mapping showed more cartilage lesions than clinical MRI T2 mapping showed more cartilage lesions than clinical MRI, and in T2 maps the lesions appeared generally wider. This proposes that T2 mapping is feasible in the clinical setting and may reveal cartilage lesions not seen on the standard knee MRI. Conclusion Our results suggest that T2 mapping is an interesting MRI sequence for the exploration of patients articular cartilage in and should be included in the routine protocol if cartilage pathology is suspecting as it may improve the diagnostic accuracy of MRI for focal chondral lesions, and should help decide whether and MR-arthrography or CT-arthrography is necessary.

Shear wave elastography and T2* mapping in the detection of early-stage trochlear cartilage damage.

The presence of degenerative changes in joint cartilage is one of the major features in osteoarthritis. To investigate the contribution of shear wave elastography and T2* mapping to the early diagnosis of femoral trochlear cartilage damage. A total of 30 individuals whose trochlear cartilage structure was evaluated as normal in conventional magnetic resonance imaging (MRI) sequences (control group) were prospectively compared with 30 patients who had early-stage cartilage damage findings on conventional MRI (study group), by performing B-mode ultrasonography, shear wave elastography, and T2* mapping. Cartilage thickness, shear wave, and T2* mapping measurements were recorded. After evaluating B-mode ultrasound and conventional MRI sequences, cartilage thickness was found to be significantly higher in the study group on both B-mode ultrasound and MRI. Shear wave velocity values of the study group (medial condyle [MC] 4.65 ± 1.11 m/sn, intercondylar [IC] 4.74 ± 1.20 m/sn, and lateral condyle [LC] 5.42 ± 1.48 m/sn) were observed to be significantly lower than the control group (MC 5.60 ± 0.77 m/sn, IC 5.85 ± 0.96 m/sn, and LC 5.63 ± 1.05 m/sn) (P < 0.05). T2* mapping values were significantly higher in the study group (MC 32.38 ± 4.04 ms, IC 35.78 ± 4.85 ms, and LC 34.04 ± 3.40 ms) than that of the control group (MC 28.07 ± 3.29 ms, IC 30.63 ± 3.45 ms, and LC 29.02 ± 3.24 ms). Shear wave elastography and T2* mapping are reliable methods for evaluating early-stage trochlear cartilage damage.

Magnetic Resonance Imaging in Cerebral Venous Thrombosis

Cerebral venous thrombosis (CVT) is a category of stroke that occurs when blood clots form in dural sinuses cerebral veins or, resulting in inflammation and injury to brain tissue. Magnetic resonance imaging (MRI) is a valuable non-invasive tool for diagnosing and managing CVT, as it enables visualization of cerebral veins and sinuses and can differentiate CVT from similar conditions. MRI gives information on the location, severity, extent, and complications of thrombosis, including hemorrhage and brain edema. Advanced MRI sequences, such as diffusion-weighted imaging (DWI), can detect acute ischemic changes and differentiate between cytotoxic and vasogenic edema. This study intended to assess the effectiveness of conventional and advanced MRI techniques in diagnosing CVT in a group of 50 patients. MR venogram and other conventional MRI sequences were used to diagnose CVT in 96% patients, while contrast venography was used in 4% patients. The study was conducted over 18 months, and statistical analysis was performed on the data to assess the significance of the findings. The study found that the majority of patients experienced headaches, and the SSS (superior sagittal sinus) was the most commonly affected sinus. The thrombosis location was associated with parenchymal involvement in different regions. The age of the thrombus correlated with clinical presentation and imaging findings, and the presence of intraparenchymal hematoma in acute phase and hemorrhagic infarct in subacute phase and was significantly correlated. These findings can help guide timely and appropriate treatment for CVT.

Pediatric posterior fossa tumors

Tumors of the posterior fossa account for about 50-55% of brain tumors in childhood. The most frequent tumor entities are medulloblastomas, pilocytic astrocytomas, ependymomas, diffuse midline gliomas and atypical teratoid-rhabdoid tumors. Neuroradiological differential diagnosis with magnetic resonance imaging (MRI) is of considerable importance for preoperative planning as well as planning of follow-up therapy. Most important findings for differential diagnosis of pediatric posterior fossa tumors are tumor location, patient age and the intratumoral apparent diffusion assessed by diffusion-weighted imaging. Advanced MR techniques like MRI perfusion and MR spectroscopy can be helpful both in the initial differential diagnosis and in tumor surveillance, but exceptional characteristics of certain tumor entities should be kept in mind. Standard clinical MRI sequences including diffusion-weighted imaging are the main diagnostic tool in evaluating posterior fossa tumors in children. Advanced imaging methods can be helpful, but should never be interpreted separately from conventional MRI sequences.

Microstructural Changes in Normal-Appearing White Matter in Pediatric X-Linked Adrenoleukodystrophy: A Diffusion Tensor Imaging Study

Abstract Objective Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique that provides quantitative diffusion data of water molecules in tissue. Usage of DTI in pediatric X-linked adrenoleukodystrophy (X-ALD) may adjunct earlier detection of brain involvement. This study aimed to analyze the normal-appearing white matter in pediatric patients with X-ALD using DTI. Materials and Methods A retrospective database search was performed. Children with genetically diagnosed X-ALDs with a reportedly normal brain MRI between January 2010 and September 2021 were included. Fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and apparent diffusion coefficient were serially measured in 8 regions of the brain, and these measurements were compared with those in control patients. Results The study group included 21 X-ALD patients and 11 control patients. The mean age was 6.64 ± 5.14 years. FA values of the genu and body of the corpus callosum were significantly lower in the ALD group than controls. There was also a statistically significant difference in FA, AD, and RD values of cerebellar white matter in the two groups. Conclusion There is evidence of white matter damage on DTI in X-ALD patients with the normal-appearing white matter on conventional MRI sequences. The inclusion of DTI in routine MRI examinations of X-ALD patients may provide additional insight into possible white matter damage in that population.

Prediction of microvascular invasion in hepatocellular carcinoma with magnetic resonance imaging using models combining deep attention mechanism with clinical features

To investigate the consistency and diagnostic performance of magnetic resonance imaging (MRI) for detecting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and the validity of deep learning attention mechanisms and clinical features for MVI grade prediction. This retrospective study was conducted among 158 patients with HCC treated in Shunde Hospital Affiliated to Southern Medical University between January, 2017 and February, 2020. The imaging data and clinical data of the patients were collected to establish single sequence deep learning models and fusion models based on the EfficientNetB0 and attention modules. The imaging data included conventional MRI sequences (T1WI, T2WI, and DWI), enhanced MRI sequences (AP, PP, EP, and HBP) and synthesized MRI sequences (T1mapping-pre and T1mapping-20 min), and the high-risk areas of MVI were visualized using deep learning visualization techniques. The fusion model based on T1mapping-20min sequence and clinical features outperformed other fusion models with an accuracy of 0.8376, a sensitivity of 0.8378, a specificity of 0.8702, and an AUC of 0.8501 for detecting MVI. The deep fusion models were also capable of displaying the high-risk areas of MVI. The fusion models based on multiple MRI sequences can effectively detect MVI in patients with HCC, demonstrating the validity of deep learning algorithm that combines attention mechanism and clinical features for MVI grade prediction.

The use of slice encoding for metal artifact correction (SEMAC) sequencing improves the diagnostic evaluation of graft integrity following anterior cruciate ligament reconstruction

ObjectivesTo determine whether magnetic resonance imaging (MRI) with metal artifact reduction sequencing is superior to conventional knee MRI in the evaluation of an injured anterior cruciate ligament (ACL) graft, where visualisation on conventional MRI can be limited by the metal artifact from fixation devices. MethodsEighteen patients underwent conventional MRI sequence (proton density fat saturated [PDFS]) and two types of metal artifact reduction sequencing MRI (WARP, slice encoding for metal artifact correction (SEMAC); Siemens) following a secondary injury to their ACL reconstructed knee. Six raters with experience in knee MRI evaluation reviewed sagittal PDFS, WARP, and SEMAC sequences, providing semi-quantitative grades for visualisation and diagnostic confidence assessing the ACL, posterior cruciate ligament , menisci, tibial and femoral tunnel margins, and articular cartilage. Intra-class correlation coefficients for inter-rater reliability were evaluated. The 6-rater mean scores for the visualisation and diagnostic confidence derived from each sequence were compared using the Friedman test for multiple paired samples. ResultsNo statistically significant difference in the ACL visualisation among the sequences was found (p ​= ​0.193). Further, a subgroup analysis was performed in cases evaluated as “moderately blurry” or “indistinct ACL visualisation” on PDFS (58% of cases). SEMAC significantly improved diagnostic confidence in ACL visualisation (p ​= ​0.041) and ACL graft rupture (p ​= ​0.044) compared to PDFS.There was no statistically significant difference in the inter-observer reliability between sequences. The WARP sequence added 2.84 ​± ​0.69 ​min, while SEMAC added 2.95 ​± ​0.40 ​min to the standard knee MRI scan time. Conclusionuse of the SEMAC metal reduction sequence significantly improved diagnostic accuracy and confidence in the detection of ACL graft rupture in cases where the ACL was moderately blurry or indistinct on the PDFS sequence. This sequence should be considered as an adjunct to conventional PDFS in cases where graft visualisation is limited by the metal artifact from fixation devices. Level of evidenceIII.