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National Leaders in Organ Transplant

The Washington University and Barnes-Jewish Hospital Transplant Center has one of the oldest and most established transplant programs in the country.

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Quantitative signal properties from standardized MRIs correlate with multiple sclerosis disability

Objective: To enable use of clinical magnetic resonance images (MRIs) to quantify abnormalities in normal appearing (NA) white matter (WM) and gray matter (GM) in multiple sclerosis (MS) and to determine associations with MS-related disability. Identification of these abnormalities heretofore has required specialized scans not routinely available in clinical practice. 

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In vivo evolution of biopsy-proven inflammatory demyelination quantified by R2t* mapping

A 35-year-old man with an enhancing tumefactive brain lesion underwent biopsy, revealing inflammatory demyelination. We used quantitative Gradient- Recalled-Echo (qGRE) MRI to visualize and measure tissue damage in the lesion. Two weeks after biopsy, qGRE showed significant R2t* reduction in the left optic radiation and surrounding tissue, consistent with the histopathological and clinical findings. qGRE was repeated 6 and 14 months later, demonstrating partially recovered optic radiation R2t*, in concert with improvement of the hemianopia to ultimately involve only the lower right visual quadrant. These results support qGRE metrics as in vivo biomarkers for tissue damage and longitudinal monitoring of demyelinating disease.

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Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions

Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterogeneity. We hypothesized that the profiles of multiple DBSI metrics can identify lesion-defining patterns. Here we test this hypothesis by combining a deep learning algorithm using deep neural network (DNN) with DBSI and other imaging methods.

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Central vein sign and other radiographic features distinguishing myelin oligodendrocyte glycoprotein antibody disease from multiple sclerosis and aquaporin-4 antibody-positive neuromyelitis optica

Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) can radiographically mimic multiple sclerosis (MS) and aquaporin-4 (AQP4) antibody-positive neuromyelitis optica spectrum disorder (NMOSD). Central vein sign (CVS) prevalence has not yet been well-established in MOGAD. The objective of this study is to characterize the magnetic resonance imaging (MRI) appearance and CVS prevalence of MOGAD patients in comparison to matched cohorts of MS and AQP4+ NMOSD.

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Illumination Gala Special Preview

Join us virtually on June 5 for our annual Illumination Gala to learn more about how the Cancer Frontier Fund is supporting breakthrough research at Siteman Cancer Center.

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Can CSF biomarkers predict future MS disease activity and severity?

Multiple sclerosis (MS) is a heterogeneous disease. With several disease modifying treatments of different
mechanisms of action in use now and in development, it is important to identify reliable biomarkers
to identify those higher risk MS patients in whom stronger but riskier treatments might be used, as well as
to identify those for whom safer treatments of lower efficacy would be sufficient.

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