Usage of SWI (susceptibility weighted imaging) acquired at 7T for qualitative evaluation of temporal lobe epilepsy patients with histopathological and clinical correlation: An initial pilot study.

OBJECTIVES: Ultra high field MRI at 7T is able to provide much improved spatial and contrast resolution which may aid in the diagnosis of hippocampal abnormalities. This paper presents a preliminary experience on qualitative evaluation of 7T MRI in temporal lobe epilepsy patients with a focus on comparison to histopathology. METHODS: 7T ultra high field MRI data, using T1-weighted, T2*-weighted and susceptibility-weighted images (SWI), were acquired for 13 patients with drug resistant temporal lobe epilepsy (TLE) during evaluation for potential epilepsy surgery. Qualitative evaluation of the imaging data for scan quality and presence of hippocampal and temporal lobe abnormalities were scored while blinded to the clinical data. Correlation of imaging findings with the clinical data was performed. Blinded evaluation of 1.5T scans was also performed. RESULTS: On the 7T MRI findings, eight out of 13 cases demonstrated concordance with the clinically suspected TLE. Among these concordant cases, three exhibited supportive abnormal 7T MRI findings which were not detected by the clinical 1.5T MRI. Of the ten cases that progressed to epilepsy surgery, seven showed concordance between 7T MRI findings and histopathology; of these, four cases had hippocampal sclerosis. SWI had the highest concordance with the clinical and histopathological findings. Similar clinical and histopathological concordance was found with 1.5T MRI. CONCLUSIONS: There was moderate and high concordance between the 7T imaging findings with the clinical data and histopathology respectively

Contrast agent-free synthesis and segmentation of ischemic heart disease images using progressive sequential causal GANs.

The elimination of gadolinium contrast agent (CA) injections and manual segmentation are crucial for ischemic heart disease (IHD) diagnosis and treatment. In the clinic, CA-based late gadolinium enhancement (LGE) imaging and manual segmentation remain subject to concerns about potential toxicity, interobserver variability, and ineffectiveness. In this study, progressive sequential causal GANs (PSCGAN) are proposed. This is the first one-stop CA-free IHD technology that can simultaneously synthesize an LGE-equivalent image and segment diagnosis-related tissues (i.e., scars, healthy myocardium, blood pools, and other pixels) from cine MR images. To this end, the PSCGAN offer three unique properties: 1) a progressive framework that cascades three phases (i.e., priori generation, conditional synthesis, and enhanced segmentation) for divide-and-conquer training synthesis and segmentation of images. Importantly, this framework leverages the output of the previous phase as a priori condition to input the next phase and guides its training for enhancing performance, 2) a sequential causal learning network (SCLN) that creates a multi-scale, two-stream pathway and a multi-attention weighing unit to extract spatial and temporal dependencies from cine MR images and effectively select task-specific dependence. It also integrates the GAN architecture to leverage adversarial training to further facilitate the learning of interest dependencies of the latent space of cine MR images in all phases; and 3) two specifically designed self-learning loss terms: a synthetic regularization loss term leverages the spare regularization to avoid noise during synthesis, and a segmentation auxiliary loss term leverages the number of pixels for each tissue to compensate for discrimination during segmentation. Thus, the PSCGAN gain unprecedented performance while stably training in both synthesis and segmentation. By training and testing a total of 280 clinical subjects, our PSCGAN yield a synthetic normalization root-mean-squared-error of 0.14 and an overall segmentation accuracy of 97.17%. It also produces a 0.96 correlation coefficient for the scar ratio in a real diagnostic metric evaluation. These results proved that our method is able to offer significant assistance in the standardized assessment of cardiac disease

Comparing Baseline Presentation of Giant Cell Arteritis in White Versus Black Patients

Giant cell arteritis (GCA) is the most prevalent systemic vasculitis in the elderly, and can lead to permanent vision loss if untreated. Most earlier studies have only evaluated GCA in primarily white populations, and GCA was traditionally thought to occur at nearly negligible frequency in black populations. However, our previous study showed that GCA may occur at similar rates in white and black patients.1 The purpose of this follow-up study was to determine whether or not black and white patients with GCA present with different baseline characteristics