Recognition of necrotic regions in MRI images of chronic spinal cord injury based on superpixel.

BACKGROUND AND OBJECTIVE: The cystic cavity and its surrounding dense glial scar formed in chronic spinal cord injury (SCI) hinder the regeneration of nerve axons. Accurate location of the necrotic regions formed by the scar and the cavity is conducive to eliminate the re-growth obstacles and promote SCI treatment. This work aims to realize the accurate and automatic location of necrotic regions in the chronic SCI magnetic resonance imaging (MRI). METHODS: In this study, a method based on superpixel is proposed to identify the necrotic regions of spinal cord in chronic SCI MRI. Superpixels were obtained by a simple linear iterative clustering algorithm, and feature sets were constructed from intensity statistical features, gray level co-occurrence matrix features, Gabor texture features, local binary pattern features and superpixel areas. Subsequently, the recognition effects of support vector machine (SVM) and random forest (RF) classification model on necrotic regions were compared from accuracy (ACC), positive predictive value (PPV), sensitivity (SE), specificity (SP), Dice coefficient and algorithm running time. RESULTS: The method is evaluated on T1- and T2-weighted MRI spinal cord images of 24 adult female Wistar rats. And an automatic recognition method for spinal cord necrosis regions was established based on the SVM classification model finally. The recognition results were 1.00±0.00 (ACC), 0.89±0.09 (PPV), 0.88±0.12 (SE), 1.00±0.00 (SP) and 0.88±0.07 (Dice), respectively. CONCLUSIONS: The proposed method can accurately and noninvasively identify the necrotic regions in MRI, which is helpful for the pre-intervention assessment and post-intervention evaluation of chronic SCI research and treatments, and promoting the clinical transformation of chronic SCI research.

Effect of b Value on Imaging Quality for Diffusion Tensor Imaging of the Spinal Cord at Ultrahigh Field Strength.

OBJECTIVE: To explore the optimal b value setting for diffusion tensor imaging of rats' spinal cord at ultrahigh field strength (7 T). METHODS: Spinal cord diffusion tensor imaging data were collected from 14 rats (5 healthy, 9 spinal cord injured) with a series of b values (200, 300, 400, 500, 600, 700, 800, 900, and 1000 s/mm2) under the condition that other scanning parameters were consistent. The image quality (including image signal-to-noise ratio and image distortion degree) and data quality (i.e., the stability and consistency of the DTI-derived parameters, referred to as data stability and data consistency) were quantitatively evaluated. The min-max normalization method was used to process the calculation results of the four indicators. Finally, the image and data quality under each b value were synthesized to determine the optimal b value. RESULTS: b = 200 s/mm2 and b = 900 s/mm2 ranked in the top two of the comprehensive evaluation, with the best image quality at b = 200 s/mm2 and the best data quality at b = 900 s/mm2. CONCLUSION: Considering the shortcomings of the ability of low b values to reflect the microstructure, b = 900 s/mm2 can be used as the optimal b value for 7 T spinal cord diffusion tensor scanning.

Oxime-mediated facile access to 5-methylisoxazoles and applications in the synthesis of valdecoxib and oxacillin.

A palladium-catalyzed efficient synthesis of 5-methylisoxazoles via oxime-mediated functionalization of unactivated olefins is described. The reaction affords a variety of 5-methylisoxazoles in moderate to good yields. To further demonstrate the utility of the method, the rapid synthesis of valdecoxib and oxacillin is reported.