Conventional Magnetic Resonance Imaging Research Articles

Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer

BACKGROUND Lymph node (LN) staging in rectal cancer (RC) affects treatment decisions and patient prognosis. For radiologists, the traditional preoperative assessment of LN metastasis (LNM) using magnetic resonance imaging (MRI) poses a challenge. AIM To explore the value of a nomogram model that combines Conventional MRI and radiomics features from the LNs of RC in assessing the preoperative metastasis of evaluable LNs. METHODS In this retrospective study, 270 LNs (158 nonmetastatic, 112 metastatic) were randomly split into training (n = 189) and validation sets (n = 81). LNs were classified based on pathology-MRI matching. Conventional MRI features [size, shape, margin, T2-weighted imaging (T2WI) appearance, and CE-T1-weighted imaging (T1WI) enhancement] were evaluated. Three radiomics models used 3D features from T1WI and T2WI images. Additionally, a nomogram model combining conventional MRI and radiomics features was developed. The model used univariate analysis and multivariable logistic regression. Evaluation employed the receiver operating characteristic curve, with DeLong test for comparing diagnostic performance. Nomogram performance was assessed using calibration and decision curve analysis. RESULTS The nomogram model outperformed conventional MRI and single radiomics models in evaluating LNM. In the training set, the nomogram model achieved an area under the curve (AUC) of 0.92, which was significantly higher than the AUCs of 0.82 (P < 0.001) and 0.89 (P < 0.001) of the conventional MRI and radiomics models, respectively. In the validation set, the nomogram model achieved an AUC of 0.91, significantly surpassing 0.80 (P < 0.001) and 0.86 (P < 0.001), respectively. CONCLUSION The nomogram model showed the best performance in predicting metastasis of evaluable LNs.

Image Quality Assessment Tool for Conventional and Dynamic Magnetic Resonance Imaging Acquisitions

Image quality assessment of magnetic resonance imaging (MRI) data is an important factor not only for conventional diagnosis and protocol optimization but also for fairness, trustworthiness, and robustness of artificial intelligence (AI) applications, especially on large heterogeneous datasets. Information on image quality in multi-centric studies is important to complement the contribution profile from each data node along with quantity information, especially when large variability is expected, and certain acceptance criteria apply. The main goal of this work was to present a tool enabling users to assess image quality based on both subjective criteria as well as objective image quality metrics used to support the decision on image quality based on evidence. The evaluation can be performed on both conventional and dynamic MRI acquisition protocols, while the latter is also checked longitudinally across dynamic series. The assessment provides an overall image quality score and information on the types of artifacts and degrading factors as well as a number of objective metrics for automated evaluation across series (BRISQUE score, Total Variation, PSNR, SSIM, FSIM, MS-SSIM). Moreover, the user can define specific regions of interest (ROIs) to calculate the regional signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), thus individualizing the quality output to specific use cases, such as tissue-specific contrast or regional noise quantification.

Differentiation of hemispheric white matter lesions in migraine and multiple sclerosis with similar radiological features using advanced MRI

Background and aimWhite matter hyperintensities (WMHs), presented on T2-weighted or fluid-attenuated inversion recovery magnetic resonance imaging (MRI) sequences, are lesions in the human brain that can be observed in both migraine and multiple sclerosis (MS).MethodsSeventeen migraine patients and 15 patients with relapsing–remitting multiple sclerosis with WMHs, and 17 healthy subjects age-and sex-matched to the migraine group were prospectively enrolled and underwent conventional and advanced MRI studies with diffusion-and perfusion-weighted imaging and single voxel proton magnetic resonance spectroscopy.ResultsIn both disease groups, elevated T2 relaxation time, apparent diffusion coefficient (ADC) values, and decreased N-acetyl-aspartate levels were found in the intralesional white matter compared to the contralateral normal-appearing white matter (NAWM), while there was no difference between the hemispheres of the control subjects. Migraine patients had the lowest intralesional creatine + phosphocreatine and myo-inositol (mI) values among the three groups, while patients with MS showed the highest intralesional T1 and T2 relaxation times, ADC, and mI values. In the contralateral NAWM, the same trend with mI changes was observed in migraineurs and MS patients. No differences in perfusion variables were observed in any groups.ConclusionOur multimodal study showed that tissue damage is detectable in both diseases. Despite the differences in various advanced MRI measures, with more severe injury detected in MS lesions, we could not clearly differentiate the two white matter lesion types.

Isolated bilateral fornix anterior columns infarction with acute amnesia and fiber tracts damage, a case report

ABSTRACT Isolated fornix anterior column infarction has rarely been described and is difficult to assess accurately using conventional magnetic resonance imaging (MRI). We report the case of a 75-year-old female who experienced acute anterograde amnesia. MRI performed within 24 h after amnesia onset showed an isolated infarction of the bilateral anterior columns of the fornix on diffusion-weighted imaging (DWI). Her symptoms persisted for up to 50 days, and diffusion tensor imaging (DTI) showed disruption of the fiber tracts of the fornix. when acute amnesia syndrome onset, fornix anterior column infarction should be considered, and optimized DWI and DTI methods are needed to study the fornix in vivo in future research.

Diagnostic performance of computed tomography-digital subtraction angiography and conventional magnetic resonance imaging for evaluating the vascularity of osseous spinal tumors

Background and purposePatients with hypervascular spinal tumors may have severe blood loss during tumor resection, which increases the risks of perioperative morbidity and mortality. However, the preoperative evaluation of tumor vascularity may be challenging; moreover, the reliability of the data obtained in conventional preoperative noninvasive imaging is debatable. In this study, we compared conventional magnetic resonance imaging (MRI) and subtraction computed tomography angiography (CTA) in terms of their performance in vascularity evaluation. The catheter digital subtraction angiography (DSA) technique was used as a reference standard. MethodsThis study included 123 consecutive patients with spinal tumor who underwent subtraction CTA, catheter DSA, and subsequent surgery between October 2015 and October 2021. Data regarding qualitative and semiquantitative subtraction CTA parameters and conventional MRI signs were collected for comparison with tumor vascularity graded through catheter DSA. The diagnostic performance of qualitative CTA, quantitative CTA, and conventional MRI in assessing spinal tumor vascularity was analyzed. ResultsQualitative subtraction CTA was the best noninvasive imaging modality in terms of diagnostic performance (area under the receiver operating characteristic curve [AUROC], 0.95). Quantitative CTA was relatively inferior (AUROC, 0.87). MRI results had low reliability (AUROC, 0.51 to 0.59). Intratumoral hemorrhage and prominent foraminal venous plexus were found to be the specific signs for hypervascularity (specificity 93.2%). ConclusionsQualitative subtraction CTA offers the highest diagnostic value in evaluating spinal tumor vascularity, compared to quantitative CTA and MRI. Although conventional MRI may not be a reliable approach, certain MRI signs may have high specificity, which may be crucial for assessing spinal tumor vascularity.

Assessing brain microstructural changes in chronic kidney disease: a diffusion imaging study using multiple models

ObjectivesTo explore the effectiveness of diffusion quantitative parameters derived from advanced diffusion models in detecting brain microstructural changes in patients with chronic kidney disease (CKD).MethodsThe study comprised 44 CKD patients (eGFR<59 mL/min/1.73 m2) and 35 age-and sex-matched healthy controls. All patients underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging. Reconstructed to obtain diffusion MRI models, including diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI, were processed to obtain multi-parameter maps. The Tract-Based Spatial Statistics (TBSS) analysis was utilized for detecting microstructural differences and Pearson correlation analysis assessed the relationship between renal metabolism markers and diffusion parameters in the brain regions of CKD patients. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic performance of diffusion models, with AUC comparisons made using DeLong’s method.ResultsSignificant differences were noted in DTI, NODDI, and MAP-MRI parameters between CKD patients and controls (p < 0.05). DTI indicated a decrease in Fractional Anisotropy(FA) and an increase in Mean and Radial Diffusivity (MD and RD) in CKD patients. NODDI indicated decreased Intracellular and increased Extracellular Volume Fractions (ICVF and ECVF). MAP-MRI identified extensive microstructural changes, with elevated Mean Squared Displacement (MSD) and Q-space Inverse Variance (QIV) values, and reduced Non-Gaussianity (NG), Axial Non-Gaussianity (NGAx), Radial Non-Gaussianity (NGRad), Return-to-Origin Probability (RTOP), Return-to-Axis Probability (RTAP), and Return-to-Plane Probability (RTPP). There was a moderate correlation between serum uric acid (SUA) and diffusion parameters in six brain regions (p < 0.05). ROC analysis showed the AUC values of DTI_FA ranged from 0.70 to 0.793. MAP_NGAx in the Retrolenticular part of the internal capsule R reported a high AUC value of 0.843 (p < 0.05), which was not significantly different from other diffusion parameters (p > 0.05).ConclusionThe advanced diffusion models (DTI, NODDI, and MAP-MRI) are promising for detecting brain microstructural changes in CKD patients, offering significant insights into CKD-affected brain areas.

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/

Multiparametric Mapping via Cardiovascular Magnetic Resonance in the Risk Stratification of Ventricular Arrhythmias and Sudden Cardiac Death

Risk stratification for malignant ventricular arrhythmias and sudden cardiac death is a daunting task for physicians in daily practice. Multiparametric mapping sequences obtained via cardiovascular magnetic resonance imaging can improve the risk stratification for malignant ventricular arrhythmias by unveiling the presence of pathophysiological pro-arrhythmogenic processes. However, their employment in clinical practice is still restricted. The present review explores the current evidence supporting the association between mapping abnormalities and the risk of ventricular arrhythmias in several cardiovascular diseases. The key message is that further clinical studies are needed to test the additional value of mapping techniques beyond conventional cardiovascular magnetic resonance imaging for selecting patients eligible for an implantable cardioverter defibrillator.

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index.

The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade. Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

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.

Magnetic resonance metrics for identification of cuprizone-induced demyelination in the mouse model of neurodegeneration: a review.

Neurodegenerative disorders, including Multiple Sclerosis (MS), are heterogenous disorders which affect the myelin sheath of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) provides a non-invasive method for studying, diagnosing, and monitoring disease progression. As an emerging research area, many studies have attempted to connect MR metrics to underlying pathophysiological presentations of heterogenous neurodegeneration. Most commonly, small animal models are used, including Experimental Autoimmune Encephalomyelitis (EAE), Theiler's Murine Encephalomyelitis (TMEV), and toxin models including cuprizone (CPZ), lysolecithin, and ethidium bromide (EtBr). A contrast and comparison of these models is presented, with focus on the cuprizone model, followed by a review of literature studying neurodegeneration using MRI and the cuprizone model. Conventional MRI methods including T1 Weighted (T1W) and T2 Weighted (T2W) Imaging are mentioned. Quantitative MRI methods which are sensitive to diffusion, magnetization transfer, susceptibility, relaxation, and chemical composition are discussed in relation to studying the CPZ model. Overall, additional studies are needed to improve both the sensitivity and specificity of MRI metrics for underlying pathophysiology of neurodegeneration and the relationships in attempts to clear the clinico-radiological paradox. We therefore propose a multiparametric approach for the investigation of MR metrics for underlying pathophysiology.

Application of 3D-PCASL combined with t-ASL and MRA in the diagnosis of patients with isolated vertigo induced by posterior circulation ischemia

ObjectivesIsolated vertigo induced by posterior circulation ischemia (PCIV) can further progress into posterior circulation infarction. This study aimed to explore the diagnostic values of three-dimensional pseudo-continuous arterial spin labeling (3D-PCASL) combined with territorial arterial spin labeling (t-ASL) and magnetic resonance angiography (MRA) in visualizing and evaluating PCIV, seeking improved diagnostic tools for clinical guidance. Methods28 PCIVs (11 males, 17 females, aged from 55 to 83 years, mean age: 69.68 ± 9.01 years) and 28 healthy controls (HCs, 12 male, 16 female, aged from 56 to 87 years, mean age: 66.75 ± 9.86 years) underwent conventional magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), MRA, 3D-PCASL, and t-ASL. We compared the incidence of anatomic variants of the posterior circle of Willis in MRA, cerebral blood flow (CBF) and anterior collateral blood flow on postprocessing maps obtained from 3D-PCASL and t-ASL sequence between PCIVs and HCs. Chi-square test and paired t-test were analyzed statistically with SPSS 24.0 software. Results7 PCIVs (7/28, 25%) and 6 HCs (6/28, 21%) showed fetal posterior cerebral artery (FPCA) on MRA, including 1 HC, and 6 PCIVs with FPCA appeared hypoperfusion. 18 PCIVs (64%) and 2 HCs (7%) showed hypoperfusion in the posterior circulation (PC), including 1 HC and 7 PCIVs displayed anterior circulation collateral flow. Chi-square analyses demonstrated a difference in PC hypoperfusion between PCIVs and HCs, whether in the whole or FPCA-positive group assessment (P < 0.05). Paired t-test showed that the CBF values were significant difference for the bilateral PC asymmetrical perfusion in the PCIVs (P < 0.01). When compared to the bilateral PC symmetrical non-hypoperfusion area in the PCIVs and HCs, the CBF values were not significant (P > 0.05). The CBF values of the PC in PCIVs were lower than in HCs (P < 0.05). The reduction rate in the hypoperfusion side of the bilateral PC asymmetrical perfusion of the PCIVs ranged from 4% to 37%, while the HCs reduction rate was 7.7%. The average PC symmetrical perfusion average reduction rate of the PCIVs was 52.25%, while the HCs reduction rate was 42.75%. Conclusion3D-PCASL is a non-invasive and susceptible method for detecting hypoperfusion in PC, serving as a potential biomarker of PCIV. The suspected hypoperfusion in PC may be attributed to the emergence of FPCA and the manifestation of anterior collateral flow when combining t-ASL and MRA sequences. These findings demonstrated that 3D-PCASL combined with t-ASL and MRA sequences are the potential method to identify PCIV, leading to early diagnosis of PCIV and reducing the risk of progressing into infarction.

Quantitative evaluation of meniscus injury using synthetic magnetic resonance imaging.

Magnetic resonance imaging (MRI) can diagnose meniscal lesions anatomically, while quantitative MRI can reflect the changes of meniscal histology and biochemical structure. Our study aims to explore the association between the measurement values obtained from synthetic magnetic resonance imaging (SyMRI) and Stoller grades. Additionally, we aim to assess the diagnostic accuracy of SyMRI in determining the extent of meniscus injury. This potential accuracy could contribute to minimizing unnecessary invasive examinations and providing guidance for clinical treatment. Total of 60 (n=60) patients requiring knee arthroscopic surgery and 20 (n=20) healthy subjects were collected from July 2022 to November 2022. All subjects underwent conventional MRI and SyMRI. Manual measurements of the T1, T2 and proton density (PD) values were conducted for both normal menisci and the most severely affected position of injured menisci. These measurements corresponded to the Stoller grade of meniscus injuries observed in the conventional MRI. All patients and healthy subjects were divided into normal group, degeneration group and torn group according to the Stoller grade on conventional MRI. One-way analysis of variance (ANOVA) was employed to compare the T1, T2 and PD values of the meniscus among 3 groups. The accuracy of SyMRI in diagnosing meniscus injury was assessed by comparing the findings with arthroscopic observations. The diagnostic efficiency of meniscus degeneration and tear between conventional MRI and SyMRI were analyzed using McNemar test. Furthermore, a receiver operating characteristic curve (ROC curve) was constructed and the area under the curve (AUC) was utilized for evaluation. According to the measurements of SyMRI, there was no statistical difference of T1 value or PD value measured by SyMRI among the normal group, degeneration group and torn group, while the difference of T2 value was statistically significant among 3 groups (P=0.001). The arthroscopic findings showed that 11 patients were meniscal degeneration and 49 patients were meniscal tears. The arthroscopic findings were used as the gold standard, and the difference of T1 and PD values among the 3 groups was not statistically significant, while the difference of T2 values (32.81±2.51 of normal group, 44.85±3.98 of degeneration group and 54.42±3.82 of torn group) was statistically significant (P=0.001). When the threshold of T2 value was 51.67 (ms), the maximum Yoden index was 0.787 and the AUC value was 0.934. The measurement values derived from SyMRI could reflect the Stoller grade, illustrating that SyMRI has good consistency with conventional MRI. Moreover, the notable consistency observed between SyMRI and arthroscopy suggests a potential role for SyMRI in guiding clinical diagnoses.

Multi-contrast echo-planar imaging sequence (Echo-planar imaging mix) in clinical situations demanding faster MRI-brain scans

Objectives: The excellent resolution offered by magnetic resonance imaging (MRI) has a trade-off in the form of scan duration. The purpose of the present study was to assess the clinical utility of echo-planar imaging mix (EPIMix), an echo-planar imaging-based MRI sequence for the brain with a short acquisition time. Materials and Methods: This was a retrospective observational study of 50 patients, who could benefit from faster MRI brain scans. The T1, T2, fluid attenuated inversion recovery, diffusion-weighted imaging (DWI), and T2*/susceptibility-weighted imaging sequences were acquired, conventionally and with EPIMix. Conventional and EPIMix images were assessed by two radiologists for overall quality, motion, and susceptibility artifacts and scored on a Likert scale. The scores given for conventional and EPIMix images were compared. The diagnostic performance of EPIMix was also assessed by the ability to detect clinically relevant findings. Results: The acquisition time for conventional MRI was 11 min and 45 s and for EPIMix 1 min and 15 s. All EPIMix images were sufficient for diagnostic use. On assessment of the diagnostic performance, it was excellent for ischemic and hemorrhagic strokes. Smaller lesions, lesions adjacent to bone, and post-operative tumors were difficult to identify. Moderate to perfect agreement (Kappa values 0.41–1) was seen between radiologists for all categories except skull base, calvarial, and orbital lesions. Image quality, artifact assessment showed excellent interobserver agreement (&gt;90%) for the scores. All EPIMix images showed reduced motion artifacts. The EPIMix-DWI was comparable to conventional-DWI in terms of quality and artifacts. The remaining sequences showed reduced quality and increased susceptibility. Conclusion: The EPIMix has a significantly reduced acquisition time than conventional MRI and could be used instead of conventional MRI in situations demanding faster scans such as suspected acute ischemic or hemorrhagic stroke. In other clinical scenarios, it could help tailor the MRI examination for each patient.

Amide proton transfer weighted and diffusion weighted imaging based radiomics classification algorithm for predicting 1p/19q co-deletion status in low grade gliomas

Background1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI.MethodsThis retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant.ResultsThe radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist.ConclusionsOur results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG.

Diagnostic accuracy of diffusion-weighted imaging and perfusion-weighted imaging with dynamic susceptibility contrast in differentiating World Health Organization Grade-I meningioma from high-grade meningioma with histopathology as gold standard

Abstract Background: Conventional magnetic resonance imaging may not be able to distinguish between the benign and malignant forms of meningioma. It has some limitations such as differentiating the grades of malignant meningioma. Diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) techniques can help to overcome these problems. Aims: The aim of this study was to study the diagnostic accuracy of DWI and PWI with dynamic susceptibility contrast in the differentiating World Health Organization Grade-I meningioma from high-grade meningioma with histopathology as the gold standard. Settings and Design: A hospital-based diagnostic evaluation study was carried out at the Department of Radio Diagnosis, Malla Reddy Institute of Medical Sciences, Hyderabad. Materials and Methods: Fifty cases of suspected meningioma were included in the study. The histopathology was the gold standard in this diagnostic evaluation study. DWI and PWI with dynamic susceptibility contrast results were compared against the gold standard. Statistical Analysis: Sensitivity, specificity, positive predictive value, and the negative predictive value were calculated to study the efficacy of DWI compared to histopathology as the gold standard. Results: The males (24%) were lesser than the females (76%). The female-to-male ratio was 3.2:1. The diagnostic accuracy values of apparent diffusion coefficient (ADC) with 0.6 as cutoff were sensitivity = 81.8%, specificity = 97.4%, positive predictive value = 90%, negative predictive value = 95%, and area under curve = 0.98 (95% confidence interval = 0.93–0.99) P = 0.0003. Thus, DWI using ADC with 0.6 as cutoff was found to be a very good diagnostic noninvasive tool. The diagnostic accuracy values of relative cerebral blood volume (rCBV) with 0.6 as cutoff were sensitivity = 90.5%, specificity = 98.7%, positive predictive value = 91.8%, and negative predictive value = 98.5%. Thus, DWI using rCBV with 2.52 as cutoff was found to be a very good diagnostic noninvasive tool. Conclusion: The ADC with cutoff of 0.6 and rCBV with cutoff value of 2.52 yield very good sensitivity, specificity, positive predictive value, and the negative predictive value as compared to histopathology. Hence, they can be used as noninvasive technique in differentiating Grade I meningioma from that of high-grade meningioma.

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.

The predictive value of conventional magnetic resonance imaging combined with intravoxel incoherent motion parameters for evaluating maternal and neonatal clinical outcomes in patients with placenta accreta spectrum disorders

IntroductionWe aimed to identify factors predictive of adverse maternal and neonatal outcomes in patients with placenta accreta spectrum (PAS) disorders using magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) parameters. MethodFifty-six normal singleton pregnancies at 33-39 weeks of gestation underwent MRI examination at 1.5 T. The IVIM parameters were obtained from the placenta. The correlation between the f value and postpartum hemorrhage (PPH) and between the f value and transfused units of red blood cells (RBCs) was estimated by linear regression. The correlation between various influencing factors (clinical risk factors, MRI features, and IVIM parameters) and poor outcomes was investigated using univariate and multivariate analyses. ResultThe interobserver agreement ranged from fair to excellent (k = 0.30–0.88). Multivariate analyses showed that previous cesarean sections, low signal intensity bands on T2WI and the D value were independent risk factors for adverse outcomes. The combination of three risk factors demonstrated the highest AUC of 0.903, with a sensitivity and specificity of 73.10% and 96.90%, respectively. Last, f was positively correlated with PPH and units of RBCs transfused. DiscussionPreoperative MRI features and IVIM parameters may be used to predict poor outcomes in patients with invasive placental disorders like PAS.

THE ROLE OF THE LOW FIELD MAGNETIC RESONANCE IMAGING IN THE DIAGNOSIS OF THE COMMON SHOULDER JOINT LESIONS

This article reviews the role of the low field magnetic resonance imaging (MRI) with magnetic field strengths of 0.4 Tesla in the evaluation of the main pathologic conditions of the shoulder joint commonly encountered in clinical practice. Shoulder pain is a common clinical complaint that may be caused by abnormalities of the rotator cuff tendon, labrum and a variety of other pathological conditions. The differential diagnosis is extensive and includes tendinosis and rotator cuff pathology, instability, labral lesions, biceps disorders, radiculopathy, and thoracic outlet syndrome. In older patients, arthritis may even be a factor. The goal of this study was to evaluate the feasibility and diagnostic confidence of an open low field MRI in patients with shoulder joint pain. Our data was obtained from 40 patients: 24 Male (60%) and 16-Female (40%). Their ages ranged between 17 and 70 years. All patients were investigated by conventional X-rays and MRI in the medical diagnostic center of Aden Resonance in  Al-Mansoura district in Aden city. MRI was performed at an open 0. 4 Tesla MR-unit (Hitachi - Japan-Aperto Lucent). The study protocol comprised axial, sagittal &amp; coronal STIR-T2 and T1 weighted images of 3-4 mm thickness. 55 patients (52.4%) were investigated by high field MRI 1. 5 T (Neusoft) as a reference method.

Stroke-Induced Secondary Neurodegeneration of the Corticospinal Tract-Time Course and Mechanisms Underlying Signal Changes in Conventional and Advanced Magnetic Resonance Imaging.

Secondary neurodegeneration refers to the final result of several simultaneous and sequential mechanisms leading to the loss of substance and function in brain regions connected to the site of a primary injury. Stroke is one of the most frequent primary injuries. Among the subtypes of post-stroke secondary neurodegeneration, axonal degeneration of the corticospinal tract, also known as Wallerian degeneration, is the most known, and it directly impacts motor functions, which is crucial for the motor outcome. The timing of its appearance in imaging studies is usually considered late (over 4 weeks), but some diffusion-based magnetic resonance imaging (MRI) techniques, as diffusion tensor imaging (DTI), might show alterations as early as within 7 days from the stroke. The different sequential pathological stages of secondary neurodegeneration provide an interpretation of the signal changes seen by MRI in accordance with the underlying mechanisms of axonal necrosis and repair. Depending on the employed MRI technique and on the timing of imaging, different rates and thresholds of Wallerian degeneration have been provided in the literature. In fact, three main pathological stages of Wallerian degeneration are recognizable-acute, subacute and chronic-and MRI might show different changes: respectively, hyperintensity on T2-weighted sequences with corresponding diffusion restriction (14-20 days after the injury), followed by transient hypointensity of the tract on T2-weighted sequences, and by hyperintensity and atrophy of the tract on T2-weighted sequences. This is the main reason why this review is focused on MRI signal changes underlying Wallerian degeneration. The identification of secondary neurodegeneration, and in particular Wallerian degeneration, has been proposed as a prognostic indicator for motor outcome after stroke. In this review, the main mechanisms and neuroimaging features of Wallerian degeneration in adults are addressed, focusing on the time and mechanisms of tissue damage underlying the signal changes in MRI.