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.

MR Imaging of Rotator Cuff Tears: Correlation with Arthroscopy.

INTRODUCTION: Rotator cuff tears are quite common and can cause significant disability. Magnetic Resonance Imaging (MRI) has now emerged as the modality of choice in the preoperative evaluation of patients with rotator cuff injuries, in view of its improved inherent soft tissue contrast and resolution. AIM: To evaluate the diagnostic accuracy of routine MRI in the detection and characterisation of rotator cuff tears, by correlating the findings with arthroscopy. MATERIALS AND METHODS: This prospective study was carried out between July 2014 and August 2016 at the AJ Institute of Medical Sciences, Mangalore, Karnataka, India. A total of 82 patients were diagnosed with rotator cuff injury on MRI during this period, out of which 45 patients who underwent further evaluation with arthroscopy were included in this study. The data collected was analysed for significant correlation between MRI diagnosis and arthroscopic findings using kappa statistics. The sensitivity, specificity, predictive value and accuracy of MRI for the diagnosis of full and partial thickness tears were calculated using arthroscopic findings as the reference standard. RESULTS: There were 27 males and 18 females in this study. The youngest patient was 22 years and the oldest was 74 years. Majority of rotator cuff tears (78%) were seen in patients above the age of 40 years. MRI showed a sensitivity of 89.6%, specificity of 100%, positive predictive value of 100% and negative predictive value of 83.3% for the diagnosis of full thickness rotator cuff tears. For partial thickness tears, MRI showed a sensitivity of 100%, specificity of 86.6%, positive predictive value of 78.9% and negative predictive value of 100%. The accuracy was 93.1% for full thickness tears and 91.1% for partial thickness tears. The p-value was less than 0.01 for both full and partial thickness tears. There was good agreement between the MRI and arthroscopic findings, with kappa value of 0.85 for full thickness tears and 0.81 for partial thickness tears. CONCLUSION: MRI revealed high sensitivity and specificity for the diagnosis of rotator cuff tears with accuracy of 93.1% for full thickness tears and 91.1% for partial thickness tears. MRI provides useful information about the size and extent of the tear, involvement of adjacent structures, presence of muscle atrophy and tendon retraction, all of which have important therapeutic and prognostic implications.