Age-stratified Assessment of Brain Volumetric Segmentation on the Indian Population Using Quantitative Magnetic Resonance Imaging.

BACKGROUND AND PURPOSE: Automated methods for quantifying brain tissue volumes have gained clinical interest for their objective assessment of neurological diseases. This study aimed to establish reference curves for brain volumes and fractions in the Indian population using Synthetic MRI (SyMRI), a quantitative imaging technique providing multiple contrast-weighted images through fast postprocessing. METHODS: The study included a cohort of 314 healthy individuals aged 15-65 years from multiple hospitals/centers across India. The SyMRI-quantified brain volumes and fractions, including brain parenchymal fraction (BPF), gray matter fraction (GMF), white matter fraction (WMF), and myelin. RESULTS: Normative age-stratified quantification curves were created based on the obtained data. The results showed significant differences in brain volumes between the sexes, but not after normalization by intracranial volume. CONCLUSION: The findings provide normative data for the Indian population and can be used for comparative analysis of brain structure values. Furthermore, our data indicate that the use of fractions rather than absolute volumes in normative curves, such as BPF, GMF, and WMF, can mitigate sex and population differences as they account for individual differences in head size or brain volume.

A review on investigation of the basic contrast mechanism underlying multidimensional diffusion MRI in assessment of neurological disorders.

INTRODUCTION: Multidimensional diffusion MRI (MDD MRI) is a novel diffusion technique that uses advanced gradient waveforms for microstructural tissue characterization to provide information about average rate, anisotropy and orientation of the diffusion and to disentangle the signal fraction from specific cell types i.e., elongated cells, isotropic cells and free water. AIM: To review the diagnostic potential of MDD MRI in the clinical setting for microstructural tissue characterization in patients with neurological disorders to aid in patient care and treatment. METHOD: A scoping review on the clinical applications of MDD MRI was conducted from original articles published in PubMed and Scopus from 2015 to 2021 using the keywords "Multidimensional diffusion MRI" OR "diffusion tensor distribution" OR "Tensor-Valued Diffusion" OR "b-tensor encoding" OR "microscopic diffusion anisotropy" OR "microscopic anisotropy" OR "microscopic fractional anisotropy" OR "double diffusion encoding" OR "triple diffusion encoding" OR "double pulsed field gradients" OR "double wave vector" OR "correlation tensor imaging" AND "brain" OR "axons". RESULTS: Initially 145 articles were screened and after applying inclusion and exclusion criteria, nine articles were included in the final analysis. In most of these studies, microscopic diffusion anisotropy within the lesion showed deviation from the normal-appearing tissue. CONCLUSION: Multidimensional diffusion MRI can provide better quantification and visualization of tissue microstructure than conventional diffusion MRI and can be used in the clinical setting for diagnosis of neurological disorders.

Device for Assessing Knee Joint Dynamics During Magnetic Resonance Imaging.

BACKGROUND: Knee assessment with and without load using magnetic resonance imaging (MRI) can provide information on knee joint dynamics and improve the diagnosis of knee joint diseases. Performing such studies on a routine MRI-scanner require a load-exerting device during scanning. There is a need for more studies on developing loading devices and evaluating their clinical potential. PURPOSE: Design and develop a portable and easy-to-use axial loading device to evaluate the knee joint dynamics during the MRI study. STUDY TYPE: Prospective study. SUBJECTS: Nine healthy subjects. FIELD STRENGTH/SEQUENCE: A 0.25 T standing-open MRI and 3.0 T MRI. PD-T2 -weighted FSE, 3D-fast-spoiled-gradient-echo, FS-PD, and CartiGram sequences. ASSESSMENT: Design and development of loading device, calibration of loads, MR safety assessment (using projectile angular displacement, torque, and temperature tests). Scoring system for ease of doing. Qualitative (by radiologist) and quantitative (using structural similarity index measure [SSIM]) image-artifact assessment. Evaluation of repeatability, comparison with various standing stances load, and loading effect on knee MR parameters (tibiofemoral bone gap [TFBG], femoral cartilage thickness [FCT], tibial cartilage thickness [TCT], femoral cartilage T2 -value [FCT2], and tibia cartilage T2 -value [TCT2]). The relative percentage change (RPC) in parameters due to the device load was computed. STATISTICAL TEST: Pearson's correlation coefficient (r). RESULTS: The developed device is conditional-MR safe (details in the manuscript and supplementary materials), 15 × 15 × 45 cm3 dimension, and <3 kg. The ease of using the device was 4.9/5. The device introduced no visible image artifacts, and SSIM of 0.9889 ± 0.0153 was observed. The TFBG intraobserver variability (absolute difference) was <0.1 mm. Interobserver variability of all regions of interest was <0.1 mm. The load exerted by the device was close to the load during standing on both legs in 0.25 T scanner with r > 0.9. Loading resulted in RPC of 1.5%-11.0%, 7.9%-8.5%, and -1.5% to 13.0% in the TFBG, FCT, and TCT, respectively. FCT2 and TCT2 were reduced in range of 1.5-2.7 msec and 0.5-2.3 msec due to load. DATA CONCLUSION: The proposed device is conditionally MR safe, low cost (material cost < INR 6000), portable, and effective in loading the knee joint with up to 50% of body weight. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

A semi-automatic framework based upon quantitative analysis of MR-images for classification of femur cartilage into asymptomatic, early OA, and advanced-OA groups.

To develop a semi-automatic framework for quantitative analysis of biochemical properties and thickness of femur cartilage using magnetic resonance (MR) images and evaluate its potential for femur cartilage classification into asymptomatic (AS), early osteoarthritis (OA), and advanced OA groups. In this study, knee joint MRI data (fat suppressed-proton density-weighted and multi-echo T2-weighted images) of eight AS-volunteers (data acquired twice) and 34 OA patients including 20 early OA (16 Grade-I and 4 Grade-II), 14 advanced-OA (Grade-III) were acquired at 3.0T MR scanner. Modified Outerbridge classification criteria was performed for the clinical evaluation of data by an experienced radiologist. Cartilage segmentation, T2-mapping, 2D-WearMap generation, and subregion analysis were performed semi-automatically using in-house developed algorithms. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) were computed for testing the reproducibility of T2 values. One-way analysis of variance with Tukey-Kramer post hoc test was performed for evaluating the differences among the groups. The performance of individual T2 and thickness, as well as their combination using logistic regression, were evaluated with receiver operating characteristics (ROC) curve analysis. The interscan agreement based on the ICC index was 0.95 and the CV was 2.45 ± 1.33%. T2 mean of values greater than 75th percentile showed sensitivity and specificity of 94.1% and 81.3% (AUC = 0.93, cut-off value = 47.9 ms) in differentiating AS volunteers versus OA group, while sensitivity and specificity of 90.0% and 81.3% (AUC = 0.90, cut-off value = 47.9 ms) in differentiating AS volunteers versus early OA groups, respectively. In the differentiation of early OA versus advanced-OA group, ROC results of combination (T2 and thickness) showed the highest sensitivity and specificity of 85.7%, and 70.0% (AUC = 0.79, cut-off value = 0.39) compared with individual T2 and thickness features, respectively. A computer-aided quantitative evaluation of femur cartilage degeneration showed promising results and can be used to assist clinicians in diagnosing OA.

Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis.

BACKGROUND: Appropriate structural and material properties are essential for finite-element-modeling (FEM). In knee FEM, structural information could extract through 3D-imaging, but the individual subject's tissue material properties are inaccessible. PURPOSE: The current study's purpose was to develop a methodology to estimate the subject-specific stiffness of the tibiofemoral joint using finite-element-analysis (FEA) and MRI data of knee joint with and without load. METHODS: In this study, six Magnetic Resonance Imaging (MRI) datasets were acquired from 3 healthy volunteers with axially loaded and unloaded knee joint. The strain was computed from the tibiofemoral bone gap difference (ΔmBGFT) using the knee MR images with and without load. The knee FEM study was conducted using a subject-specific knee joint 3D-model and various soft-tissue stiffness values (1 to 50 MPa) to develop subject-specific stiffness versus strain models. RESULTS: Less than 1.02% absolute convergence error was observed during the simulation. Subject-specific combined stiffness of weight-bearing tibiofemoral soft-tissue was estimated with mean values as 2.40 ± 0.17 MPa. Intra-subject variability has been observed during the repeat scan in 3 subjects as 0.27, 0.12, and 0.15 MPa, respectively. All subject-specific stiffness-strain relationship data was fitted well with power function (R2 = 0.997). CONCLUSION: The current study proposed a generalized mathematical model and a methodology to estimate subject-specific stiffness of the tibiofemoral joint for FEM analysis. Such a method might enhance the efficacy of FEM in implant design optimization and biomechanics for subject-specific studies. Trial registration The institutional ethics committee (IEC), Indian Institute of Technology, Delhi, India, approved the study on 20th September 2017, with reference number P-019; it was a pilot study, no clinical trail registration was recommended.

Modified radial-search algorithm for segmentation of tibiofemoral cartilage in MR images of patients with subchondral lesion.

PURPOSE: The quantitative analysis of weight-bearing articular cartilage superficial to subchondral abnormality is important in osteoarthritis (OA) progression studies. The current study aimed to address the challenges of a semi-automatic segmentation of tibiofemoral cartilage in MR images of OA patient with and without subchondral bone abnormalities (SBA). METHODS: In this study, knee MRI data [fat-suppressed proton density-weighted, multi-echo T2-weighted (CartiGram) images] of 29 OA patients, acquired at 3.0T MR scanner, were retrospectively collected. Out of 29 data, 9 had SBA in femur bone. Initially, a semi-automatic femur cartilage segmentation based on radial intensity search approach by Akhtar et al. was implemented in-house. This algorithm was considered as the radial-search method for further comparison. In this current study, the reported radial-search (RS)-based semi-automatic cartilage segmentation method was modified using thresholding, connected component labelling, convex-hull operation and spline-based curve fitting for the improved segmentation of tibiofemoral cartilage. Cartilage was manually segmented by two experienced radiologists, and inter-reader variability was estimated using coefficient of variation (CV). The segmentation results were validated using dice coefficient (DC), Jaccard coefficient (JC) and sensitivity index measurements. RESULTS: DC values for segmented femur cartilage in patients with SBA were 64.6 ± 7.8% and 81.4 ± 2.8% using reported RS method and modified radial-search method, respectively. DC values for segmented femur cartilage in patients without SBA were 82.5 ± 4.5% and 84.8 ± 2.0% using RS method and modified radial method, respectively. Similarly, DC values for tibial cartilage in all OA patients were 80.4 ± 1.6% and 81.9 ± 2.4% using RS method and modified radial method, respectively. Similar segmentation results were also obtained from the T2-weighted images. Inter-reader variability result based on CV in femur cartilage was 3.40 ± 2.12% (without SBA) and 4.18 ± 3.18% (with SBA). CONCLUSION: In the current study, a semi-automated segmentation of tibiofemoral cartilage was presented. Modified radial-search approach can successfully segment tibiofemoral cartilage, and the results were tested and validated on knee MRI data of OA patients with and without SBA.

Radiological protocol in spinal trauma: literature review and Spinal Cord Society position statement.

PURPOSE: The Spinal Cord Society constituted a panel tasked with reviewing the literature on the radiological evaluation of spinal trauma with or without spinal cord injury and recommend a protocol. This position statement provides recommendations for the use of each modality, i.e., radiographs (X-rays), computed tomography (CT), magnetic resonance imaging (MRI), as well as vascular imaging, and makes suggestions on identifying or clearing spinal injury in trauma patients. METHODS: PubMed was searched for the corresponding keywords from January 1, 1980, to August 1, 2017. A MEDLINE search was subsequently undertaken after applying MeSH filters. Appropriate cross-references were retrieved. Out of the 545 articles retrieved, 105 relevant papers that address the present topic were studied and the extracted content was circulated for further discussions. A draft position statement was compiled and circulated among the panel members via e-mail. The draft was modified by incorporating relevant suggestions to reach a consensus. RESULTS AND CONCLUSION: For imaging cervical and thoracolumbar spine trauma patients, CT without contrast is generally considered to be the initial line of imaging and radiographs are required if CT is unavailable or unaffordable. CT screening in polytrauma cases is best done with a multidetector CT by utilizing the reformatted images obtained when scanning the chest, abdomen, and pelvis (CT-CAP). MRI is indicated in cases with neurological involvement and advanced cervical degenerative changes and to determine the extent of soft tissue injury, i.e., disco-ligamentous injuries as well as epidural space compromise. MRI is also usually performed when X-rays and CT are unable to correlate with patient symptomatology. These slides can be retrieved under Electronic Supplementary Material.

Imaging of ruptured endocyst in an isolated intramuscular hydatid cyst--the Scroll appearance.

The present article reports a case of a 21 years male that was diagnosed to have isolated intramuscular hydatid cyst of the biceps brachii on Ultrasound and MRI. The 'Scroll appearance' of the ruptured endocyst in this case is likely to be an intervening transient stage in evolution of the disease and also indicates recent rupture of the endocyst.

Eagle syndrome.

Eagle syndrome occurs due to elongation of the styloid process or calcification of the stylohyoid ligament, which then may produce a pain sensation due the pressure exerted on various structures in the head and neck. When suspected, imaging helps in identifying the abnormally elongated styloid process or the calcified ligament. In recent years, three-dimensional CT (3DCT) has proved to be valuable in these cases. We report the case of a 62-year-old man with this syndrome in whom imaging with 3DCT conclusively established the diagnosis.

Accuracy of 64-slice CT coronary angiography: our initial experience.

OBJECTIVE: The objective of our study was to evaluate the diagnostic accuracy of 64-slice computed tomography coronary angiography to detect haemodynamically significant stenosis (>50% luminal narrowing) in comparison to invasive coronary angiography and further analyze the result accounting for heart rate, coronary calcification and location of lesion in the coronary tree. METHODS AND RESULTS: Forty patients (39 male, 1 female; mean age 50.9 years) underwent both CT coronary angiography and invasive coronary angiography with in a gap of one day. All vessels were included in the study and no patient was excluded due to high heart rate. On per-segment based analysis with invasive coronary angiography as the gold standard, CT coronary angiography correctly identified 62 out of 78 significant stenoses with an overall sensitivity of 79.5% (62 of 78), specificity of 98.5% (532 of 540), positive predictive value of 88.6% (62 of 70) and negative predictive value of 97.1% (532 of 548). CONCLUSION: Our result suggests that 64-slice CT coronary angiography has high diagnostic accuracy to detect haemodynamically significant stenosis.