Deep brain stimulation of symptom-specific networks in Parkinson's disease.
Nanditha RajamaniHelen FriedrichKonstantin ButenkoTill DembekFlorian LangePavel NavrátilPatricia ZvarovaBarbara HollunderRob M A de BieVincent J J OdekerkenJens VolkmannXin XuZhipei LingChen YaoPetra RitterWolf-Julian NeumannGeorgios P SkandalakisSpyridon KomaitisAristotelis KalyvasChristos KoutsarnakisGeorge StranjalisMichael BarbeVanessa MilaneseMichael D FoxAndrea A KühnErik MiddlebrooksNingfei LiMartin M ReichClemens NeudorferChristos GanosPublished in: Nature communications (2024)
Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.
Keyphrases
- deep brain stimulation
- parkinson disease
- obsessive compulsive disorder
- patient reported
- white matter
- machine learning
- end stage renal disease
- case report
- magnetic resonance
- newly diagnosed
- deep learning
- ejection fraction
- magnetic resonance imaging
- chronic kidney disease
- multiple sclerosis
- sleep quality
- depressive symptoms
- patient reported outcomes
- physical activity
- climate change
- peritoneal dialysis
- neural network