Role of Multiparametric MRI in Diagnosis of Prostate Cancer

Aims: The main objectives of our study were to evaluate the role of Multiparametric MRI (mp-MRI) in diagnosis of carcinoma prostate and to compare the various MRI sequences used in MRI in evaluating carcinoma prostate with histopathological diagnosis kept as reference standard. Materials and Methods: This prospective cross-sectional study of 40 patients was performed by using various sequences used in mp-MRI i.e. T2 weighted imaging (T2WI), Diffusion Weighted Imaging (DWI), Magnetic Resonance Spectroscopy (MRS) and Dynamic Contrast Enhanced study (DCE). Findings of mp-MRI sequences were compared with histopathological diagnosis. Statistical analysiswasperformed using SPSS computer statistical program for window release 16. Results: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of DCE in diagnosing carcinoma prostate were 88.89%, 50.00%, 94.12% and 33.33% respectively where assensitivities, specificities, PPVs, NPVs of DWI and MRS were same in our study i.e. 94.44%, 75.00%, 97.14% and 60.00%respectively. Overall sensitivity, specificity, PPV, NPV of mp-MRI by combining these sequences were found to be 97.22%, 75%, 97.22% and 75% respectively. Diagnostic accuracies of DWI, DCE and MRS were 92.5%, 85% and 92.5% respectively and overall diagnostic accuracy after combining these sequences in mp-MRI was 95%. Conclusions: mp-MRI including all the sequences has very good role in evaluation of carcinoma prostate. Diagnostic accuracy of mp-MRI increases when all sequences used together to assess prostatic lesions, so all the sequences should be used together in prostate cancer evaluation rather than using individual sequences.

A Comparison of Substantia Nigra T1 Hyperintensity in Parkinson's Disease Dementia, Alzheimer's Disease and Age-Matched Controls: Volumetric Analysis of Neuromelanin Imaging

OBJECTIVE: Neuromelanin loss of substantia nigra (SN) can be visualized as a T1 signal reduction on T1-weighted high-resolution imaging. We investigated whether volumetric analysis of T1 hyperintensity for SN could be used to differentiate between Parkinson's disease dementia (PDD), Alzheimer's disease (AD) and age-matched controls. MATERIALS AND METHODS: This retrospective study enrolled 10 patients with PDD, 18 patients with AD, and 13 age-matched healthy elderly controls. MR imaging was performed at 3 tesla. To measure the T1 hyperintense area of SN, we obtained an axial thin section high-resolution T1-weighted fast spin echo sequence. The volumes of interest for the T1 hyperintense SN were drawn onto heavily T1-weighted FSE sequences through midbrain level, using the MIPAV software. The measurement differences were tested using the Kruskal-Wallis test followed by a post hoc comparison. RESULTS: A comparison of the three groups showed significant differences in terms of volume of T1 hyperintensity (p < 0.001, Bonferroni corrected). The volume of T1 hyperintensity was significantly lower in PDD than in AD and normal controls (p < 0.005, Bonferroni corrected). However, the volume of T1 hyperintensity was not different between AD and normal controls (p = 0.136, Bonferroni corrected). CONCLUSION: The volumetric measurement of the T1 hyperintensity of SN can be an imaging marker for evaluating neuromelanin loss in neurodegenerative diseases and a differential in PDD and AD cases.

T1-weighted MR Imaging of the Neonatal Brain at 3.0 Tesla: Comparison of Spin Echo, Fast Inversion Recovery, and Magnetization-prepared Three Dimensional Gradient Echo Techniques

PURPOSE: The purpose of this study was to evaluate the usefulness of fast inversion recovery (FIR) and magnetization-prepared three dimensional gradient echo sequence (3D GRE) T1-weighted sequences for neonatal brain imaging compared with spin echo (SE) sequence in a 3T MR unit. MATERIALS AND METHODS: T1-weighted axial SE, FIR and 3D GRE sequences were evaluated from 3T brain MR imaging in 20 neonates. The signal-to-noise ratio (SNR) of different tissues was measured and contrast-to-noise ratios (CNR) were determined and compared in each of the sequences. Visual analysis was carried out by grading gray-white matter differentiation, myelination, and artifacts. The Wilcoxon signed ranked test was used for evaluation of the statistical significance of CNR differences between the sequences. RESULTS: Among the three sequences, the 3D GRE had the best SNRs. CNRs obtained with FIR and 3D GRE were statistically superior to those obtained with SE; these CNRs were better on the 3D GRE compared to the FIR. Gray to white matter differentiation and myelination were better delineated on the FIR and 3D GRE than the SE. However, motion artifacts were more commonly observed on the 3D GRE and flow-related artifacts of vessels were frequently seen on the FIR. CONCLUSION: FIR and 3D GRE are valuable alternative T1-weighted sequences to conventional SE imaging of the neonatal brain at 3T providing superior image quality.