Summary: For HD-ISS Stage 2 and Stage 3 participants, whole-brain volume shows significant association with clinical change for all four clinical variables examined here. For caudate and putamen volume, the association depended on the clinical variable. Our results provide further evidence on the use of volume change as a surrogate endpoint.
Summary: This poster shows our further investigation on the amyloid PET differences between Black and White participants in the GAP Bio-Hermes study and to better understand the relationship between Aβ+ status from visual read and quantitative SUVR.
Summary: We developed and validated scalable and robust methods for automated volumetric analysis of brain white matter hyperintensities (T2 lesions) and regions of interest in multiple sclerosis.
We discuss our latest work to evaluate a fully automated image analysis pipeline to process vesicular monoamine transporters type 2 (VMAT2) [18F]AV-133 tracer positron emission tomography (PET) images, by comparison with a methodology requiring manual intervention.
Here we train an AI method to segment the hippocampus into subfields (CA1-3 CA4+DG, and Subiculum) from standard resolution T1W MRI alone to assess utility as biomarkers compared to whole hippocampal volume, in the absence of a high-resolution T2 MRI.
As members of the Ataxia Global Initiative (AGI) MR Biomarkers Study Group that authored the paper Kirsi Kinnunen and Niccolo Fuin hope that these guidelines on harmonizing MRI data acquisition will be helpful for ataxia study sponsors.
We have developed a fully automated framework that uses deep learning for caudate segmentation (IXIQ. Ai) and generalised BSI (gBSI) for longitudinal measurements. Here, we validate the new method by comparing its volumetric scores with those of the standard manual pipeline (Man+BSI). Man+BSI produced larger caudate volumes than IXIQ.
The accurate, consistent, and scalable estimation of cerebellar atrophy would be highly beneficial for clinical trials in multiple system atrophy (MSA)1-3.
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