1. Defining diagnostic brain MRI markers in early MSA
Florian KRISMER, MD, PhD
Department of Neurology
Medical University Innsbruck
Austria

2. Early diagnosis of MSA – an unmet need
Due to overlapping symptoms, particularly in early disease stages, MSA is often misdiagnosed as Parkinson’s disease or other related disorders
Current diagnostic criteria rely primarily on clinical symptoms and physical examination.

3. Study design
Development of a novel MR brain atlas for automated segmentation by manually labelling relevant brain regions in 48 healthy individuals.
Evaluate the diagnostic accuracy of the novel atlas for the differential diagnosis of MSA (parkinsonian and cerebellar variant) versus Parkinson’s disease in a cross-sectional study.

4. Key findings I – Automated Segmentation of the MCP
Three‐dimensional models of automatically segmented middle cerebellar peduncles (in red/orange) in a PD patient (a) and a MSA‐C patient (b).
Krismer et al.; Movement Disorders, Volume: 34, Issue: 7, Pages: , First published: 28 March 2019, DOI: ( /mds.27669);

5. Key findings II - Brain atrophy profile
Data points above or to the right side of the red dotted lines indicate significant brain atrophy (as compared with age-matched healthy controls)
Krismer et al.; Movement Disorders, Volume: 34, Issue: 7, Pages: , First published: 28 March 2019, DOI: ( /mds.27669);

6. Key findings III – Diagnostic algorithm
Exploiting this algorithm 96.8% of MSA patients and all PD patients were classified correctly.
Krismer et al.; Movement Disorders, Volume: 34, Issue: 7, Pages: , First published: 28 March 2019, DOI: ( /mds.27669);

7. Conclusions
Our automated morphometric analysis corroborates previous neuropathological studies that showed that most MSA patients have a mixed striatonigral and olivopontocerebellar pathology and that brain atrophy patterns do not necessarily correspond to the clinical impression of predominant motor deficits.
Automated subcortical brain segmentation accurately discriminates MSA from PD patients.
The full paper is freely available from

8. Acknowledgments
We are grateful to for a grant in 2015 supporting this and other related projects.