Abstract
The differential diagnosis of MSA-P and PSP-P remains a difficult issue in clinical practice due to their overlapping clinical manifestation and the lack of tools enabling a definite diagnosis ante-mortem. This paper describes the usefulness of SPECT HMPAO in MSA-P and PSP-P differentiation through the analysis of cerebellar perfusion of small ROIs. Thirty-one patients were included in the study—20 with MSA-P and 11 with PSP-P; the analysis performed indicated that the most significant difference in perfusion was observed in the anterior quadrangular lobule (H IV and V) on the left side (p < 0.0026). High differences in the median perfusion between the groups were also observed in a few other regions, with p < 0.05, but higher than premised p = 0.0026 (the Bonferroni correction was used in the statistical analysis). The assessment of the perfusion may be interpreted as a promising method of additional examination of atypical parkinsonisms with overlapping clinical manifestation, as in the case of PSP-P and MSA-P. The results obtained suggest that the interpretation of the differences in perfusion of the cerebellum should be made by evaluating the subregions of the cerebellum rather than the hemispheres. Further research is required.
Funder
Department of Neurology and the Department of Nuclear Medicine
Reference33 articles.
1. REM Sleep Behavior Disorder: Diagnosis, Clinical Implications, and Future Directions;Louis;Mayo Clin. Proc.,2017
2. A Guide for the Differential Diagnosis of Multiple System Atrophy in Clinical Practice;Kauppila;J. Park. Dis.,2022
3. The Movement Disorder Society Criteria for the Diagnosis of Multiple System Atrophy;Wenning;Mov. Disord.,2022
4. Diagnosis of MSA-P and PSP-P in Early Stage;Yamawaki;Brain Nerve.,2020
5. Clinical diagnosis of progressive supranuclear palsy: The movement disorder society criteria;Respondek;Mov. Disord.,2017
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