Comparison of efficacy of plasma exchange versus intravenous immunoglobulin as an add-on therapy in acute attacks of neuromyelitis optica spectrum disorder.

INTRODUCTION: Plasma exchange (PE) is considered a Category II option for the treatment of acute attacks and relapse cases of neuromyelitis optica spectrum disorder (NMOSD). However, neurologists are also considering intravenous immunoglobulins (IVIg) as an add-on therapy for this disorder. AIMS: The aim of this study is to evaluate the efficacy of PE in acute attacks of NMOSD when compared with IVIg, in terms of improvement in the Expanded disability status scale (EDSS) and activities of daily living (ADL) scale score and levels of anti-Aquaporin P4 (AQP4) antibody in seropositive patients. METHODS: We enrolled 43 NMOSD patients in two groups: Group 1 (n = 29) received steroids and PE, and Group 2 (n = 14) received steroids with IVIg. The baseline EDSS and ADL scores were recorded and compared with scores at the end of therapy, 4 weeks, and 3 months after. Also, anti-AQP4 antibody was measured at baseline and post-therapy in seropositive patients of both groups. RESULTS: We observed a significant difference in EDSS (p = 0.00) and ADL score (p = 0.00) at day 10 and 3 months in both groups. However, no significant difference in EDSS, as well as ADL score from baseline (p = 0.83; p = 0.25) to 3 months (p = 0.85; p = 0.19), was observed when delta change of score at 3 months was compared across the two groups (p = 0.39; p = 0.52). We observed improved visual acuity in both groups with mild improvement in findings of magnetic resonance imaging at 3 months. We observed a significant decline in AQP4 antibody concentration (at day 10) in group 1 seropositive patients (p = 0.013) with improved EDSS (p = 0.027) and ADL scores (p = 0.026) of these patients. CONCLUSIONS: PE should be considered as a choice of an add-on therapy in anti-AQP4 antibody-positive NMOSD patients compared with IVIg as it is more effective in reducing antibody concentrations.

An Integrated Clinical Score to Predict Remission in Cushing's Disease.

Objective: To derive a clinical score from parameters that favor remission of Cushing's disease (CD) after pituitary surgery. Methods: This is an analysis of 11 clinical, hormonal, and post-operative parameters that each favored remission in a cohort of 145 patients with CD treated by trans-sphenoidal surgery (TSS). Each parameter was designated as a categorical variable (presence/absence), and several favorable parameters present for each patient were calculated. From this, a median parameter score (clinical score) of the entire cohort was derived, which was then compared to the event of remission/persistence of CD. Results: The median number of favorable parameters present in the entire cohort was 3 (0-7). The significant count of patients in remission increased with the increasing number of parameters. The receiver-operator characteristic curve showed that the presence of ≥3 parameters was associated with remission in CD with a sensitivity of 84.2% and a specificity of 80%. Patients with a clinical score ≥3 had significantly higher remission rates (88.9%) than those who had persistent disease (27.3%; P = 0.001). Conclusion: A clinical score of ≥3 predicts remission in CD treated by TSS; however, it requires validation in other large cohorts. Rather than assessing individual parameters to predict remission in CD, an integrated clinical score is a better tool for follow-up and patient counseling.

Super Resolution of Magnetic Resonance Images.

In this work, novel denoising and super resolution (SR) approaches for magnetic resonance (MR) images are addressed, and are integrated in a unified framework, which do not require example low resolution (LR)/high resolution (HR)/cross-modality/noise-free images and prior information of noise-noise variance. The proposed method categorizes the patches as either smooth or textured and then denoises them by deploying different denoising strategies for efficient denoising. The denoising algorithm is integrated into the SR approach, which uses a gradient profile-based constraint in a sparse representation-based framework to improve the resolution of MR images with reduced smearing of image details. This constraint regularizes the estimation of HR images such that the estimated HR image has gradient profiles similar to the gradient profiles of the original HR image. For this, the gradient profile sharpness (GPS) values of an unknown HR image are estimated using an approximated piece-wise linear relation among GPS values of LR and upsampled LR images. The experiments are performed on three different publicly available datasets. The proposed SR approach outperforms the existing unsupervised SR approach addressed for real MR images that exploits low rank and total variation (LRTV) regularization, by an average peak signal to noise ratio (PSNR) of 0.73 dB and 0.38 dB for upsampling factors 2 and 3, respectively. For the super resolution of noisy real MR images (degraded with 2% noise), the proposed approach outperforms the LRTV approach by an average PSNR of 0.54 dB and 0.46 dB for upsampling factors 2 and 3, respectively. The qualitative analysis is shown for real MR images from healthy subjects and subjects with Alzheimer's disease and structural deformity, i.e., cavernoma.