Abstract Details

Title Volumetric Brain Measurements as a Predictive Factor in LEDD

Topic Movement Disorders

Presentation(s) P6 - Poster Session 6 (5:00 PM-6:00 PM)

Poster/Presentation
Number 16-011

Objective To characterize the relationship between brain morphometry and the levodopa equivalent daily dose (LEDD) in patients with Parkinson’s Disease (PD).

Background The daily amount of antiparkinsonian medication taken can be estimated via the levodopa equivalent daily dose (LEDD). PD patients typically require increasing LEDD as the disease progresses, however the individual trajectory of medication requirements may be highly variable.

Design/Methods We conducted a retrospective study using the Parkinson’s Progression Markers Initiative (ppmi-info.org) and collected the following variables: baseline MRIs, clinical demographics and medication logs. We defined “LEDD delta” as the change in LEDD between the first visit and 5-year follow up visit. Then we performed whole brain morphometry using Freesurfer’s SynthSeg. Using this information, we built an AI model using 60% training, 20% validation and 20% hold out test set design along with a 5-fold cross validation paradigm.

Results 76 PD patients were included in our analysis. We defined LEDD delta below the 25th percentile was “stable LEDD” (38 patients) and above the 75th percentile was “progressive LEDD” (38 patients). Stochastic gradient descent-based ML model achieved a mean AUCROC of 70.6% (8.6) across the 5 folds for predicting high versus low LEDD requirements. 11 brain areas were identified as important features. There was a significant difference in the left acumbens and left caudal middle frontal cortex volumes between stable and progressive LEDD groups.

Conclusions We developed a preliminary model that accurately predicts high versus low LEDD requirements within the first 5 years of disease. Key structures identified include the left acumbens and left caudal middle frontal cortex. Further studies are needed to explore the relationship between these brain regions and levodopa requirements.

Authors/Disclosures
Leonid Gozman, MD (UFHealth) PRESENTER	Dr. Gozman has nothing to disclose.
Rukmini Sundaraneedi (Norman Fixel Institute for Neurological Diseases, University of Florida)	No disclosure on file
Venkat S. Lavu, MBBS (University of Arkansas Medical Sciences)	Dr. Lavu has nothing to disclose.
Qingqi Yuan	Miss Yuan has nothing to disclose.
Joshua Wong, MD (University of Florida College of Medicine - Neurology)	The institution of Dr. Wong has received research support from NIH.

��ɫ��

��ɫ��