Global Excellence Seminar with Markus Schirmer

  • 28 September 2018 |
  • Markus D. Schirmer |
  • MR Conference Room |
  • Time 9:00 |

Global Excellence logo English

On Friday 28 September 2018 at 9:00 o'clock, Markus Schirmer is giving a Global Excellence Lecture entitled: "Studying stroke outcome by utilizing clinical data segmentation".

Markus D. Schirmer is a Research Fellow at Massachusetts General Hospital and Doctor of Philosophy at Harvard Medical School, Department of Neurology.

Abstract:

"One of the most promising, but challenging, areas of research is the identification of biomarkers which can help predict disease outcome. Particularly in stroke patients, outcome prediction has been proven difficult, due to the heterogeneity of the data and/or methodology used. White matter hyperintensity volume, as seen on FLAIR images, has been identified as a risk factor for stroke outcome. However, other clinical variables can modify the spatial patterns of this disease burden. Here, we first demonstrate this effect for hypertension and smoking status using manual segmentation, and show that these clinical variables lead to a shift of disease burden from posterior to anterior vascular regions. The lack of an automated segmentation methodology for clinical data has so far hindered full investigation. Clinical acute ischemic stroke imaging data, due to important time constraints in the emergency room, is characterized by low through-plane resolution, as well as motion artifacts, and a limited amount of modalities available for analyses. To alleviate the resulting challenges, we developed an automated pipeline for monomodal automatic WMH volume estimation in a cohort of 2,533 patients and demonstrate that higher WMH burden is associated with poorer outcome after stroke. This illustrates the potential of using these pipelines to help pave the way for large-scale fully automated analyses and genetic discovery."

The Global Excellence Lecture will be held on Friday 28 September 2018 in the MR Conference Room at 9:00 o'clock.