Abstract Details

Title Differentiating the dopaminergic midbrain nuclei in early-stage Parkinson’s disease using quantitative susceptibility mapping and R2* relaxometry

Topic Movement Disorders

Presentation(s) P1 - Poster Session 1 (9:00 AM-5:00 PM)

Poster/Presentation
Number 273

Objective

To determine if iron imaging is a potential diagnostic biomarker of Parkinson's disease.

Background Degeneration in the midbrain dopaminergic system plays a major role in the pathophysiology of Parkinson’s disease (PD). The degeneration of the substantia nigra pars compacta (SNc) causes motor symptoms while neuronal loss in the ventral tegmental area (VTA) causes non-motor symptoms. Excessive iron accumulation in the midbrain is thought to cause this degeneration through mechanisms such as ferroptosis. Magnetic resonance imaging (MRI) can localize and quantify iron in the brain based on its magnetic susceptibility, conferring potential for diagnosing and staging PD. Despite this knowledge, there are no validated and reproducible imaging biomarkers of PD, but MRI shows great potential for their discovery.

Design/Methods Twenty early-stage PD patients and twenty age-matched healthy controls were scanned using 3 Tesla (T) MRI and 7T MRI. T1-weighted anatomicals were used for segmenting the midbrain nuclei based on the CIT168 probabilistic subcortical atlas (2018). Then using quantitative susceptibility mapping (QSM) and R2* images registered to these anatomicals, we segmented the midbrain structures and analyzed the average iron content in the SNc, VTA, and substantia nigra pars reticulata (SNr).

Results Repeated measures analysis of variance of average susceptibility values from QSM revealed significantly higher SNc iron content in early-stage PD patients compared to elderly controls at both field strengths. R2* mapping could not detect this SNc iron overload suggesting this method is less sensitive than QSM. No significant group differences in iron content were found in the SNr or the VTA. To assess these values as biomarkers, we compared them using receiver operating characteristic curves. Findings from these curves suggest that QSM outperforms R2* at both field strengths.

Conclusions The increased iron load in the SNc of early-stage PD patients, best detected using QSM, could be the first diagnostic biomarker of PD following validation.

Authors/Disclosures
Erind Alushaj, MSc PRESENTER	Mr. Alushaj has nothing to disclose.
	No disclosure on file
	No disclosure on file
	No disclosure on file
Adrian Owen (The Brain and Mind Institute)	Adrian Owen has stock in Creyos Inc.
	No disclosure on file
Penny MacDonald, MD PhD (University of Western Ontario)	No disclosure on file

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