Neuroimaging signatures predicting motor improvement to focused ultrasound subthalamotomy in Parkinson's disease.
Sue-Jin LinRafael Rodriguez-RojasTobias R BaumeisterChristophe LenglosJose A Pineda-PardoJorge U Máñez-MiróMarta Del AlamoRaul Martinez-FernandezJose A ObesoYasser Iturria-MedinaPublished in: NPJ Parkinson's disease (2022)
Subthalamotomy using transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) is a novel and promising treatment for Parkinson's Disease (PD). In this study, we investigate if baseline brain imaging features can be early predictors of tcMRgFUS-subthalamotomy efficacy, as well as which are the post-treatment brain changes associated with the clinical outcomes. Towards this aim, functional and structural neuroimaging and extensive clinical data from thirty-five PD patients enrolled in a double-blind tcMRgFUS-subthalamotomy clinical trial were analyzed. A multivariate cross-correlation analysis revealed that the baseline multimodal imaging data significantly explain (P < 0.005, FWE-corrected) the inter-individual variability in response to treatment. Most predictive features at baseline included neural fluctuations in distributed cortical regions and structural integrity in the putamen and parietal regions. Additionally, a similar multivariate analysis showed that the population variance in clinical improvements is significantly explained (P < 0.001, FWE-corrected) by a distributed network of concurrent functional and structural brain changes in frontotemporal, parietal, occipital, and cerebellar regions, as opposed to local changes in very specific brain regions. Overall, our findings reveal specific quantitative brain signatures highly predictive of tcMRgFUS-subthalamotomy responsiveness in PD. The unanticipated weight of a cortical-subcortical-cerebellar subnetwork in defining clinical outcome extends the current biological understanding of the mechanisms associated with clinical benefits.
Keyphrases
- white matter
- resting state
- magnetic resonance
- clinical trial
- high resolution
- functional connectivity
- body mass index
- newly diagnosed
- randomized controlled trial
- working memory
- data analysis
- physical activity
- machine learning
- magnetic resonance imaging
- multiple sclerosis
- pain management
- big data
- open label
- single cell
- patient reported outcomes
- replacement therapy
- rectal cancer
- photodynamic therapy
- cerebral blood flow