{"doi":"10.3233/jpd-213062","title":"Neurodegeneration of the Globus Pallidus Internus as a Neural Correlate to Dopa-Response in Freezing of Gait","abstract":"BACKGROUND: Background: Parkinson's disease (PD) patients who develop freezing of gait (FOG) have reduced mobility and independence. While some patients experience improvement in their FOG symptoms with dopaminergic therapies, a subset of patients have little to no response. To date, it is unknown what changes in brain structure underlie dopa-response and whether this can be measured using neuroimaging approaches. OBJECTIVE: We tested the hypothesis that structural integrity of brain regions (subthalamic nucleus and globus pallidus internus, GPi) which link basal ganglia to the mesencephalic locomotor region (MLR), a region involved in automatic gait, would be associated with FOG response to dopaminergic therapy. METHODS: In this observational study, thirty-six participants with PD and definite FOG were recruited to undergo diffusion kurtosis imaging (DKI) and multiple assessments of dopa responsiveness (UPDRS scores, gait times ON versus OFF medication). RESULTS: The right GPi in participants with dopa-unresponsive FOG showed reduced fractional anisotropy, mean kurtosis (MK), and increased radial diffusivity relative to those with dopa-responsive FOG. Furthermore, using probabilistic tractography, we observed reduced MK and increased mean diffusivity along the right GPi-MLR tract in dopa-unresponsive FOG. MK in the right GPi was associated with a subjective dopa-response for FOG (r = -0.360, df = 30, p = 0.043) but not overall motor dopa-response. CONCLUSION: These results support structural integrity of the GPi as a correlate to dopa-response in FOG. Additionally, this study suggests DKI metrics may be a sensitive biomarker for clinical studies targeting dopaminergic circuitry and improvements in FOG behavior.","journal":"Journal of Parkinson s Disease","year":2022,"id":288864,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9597,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":970533,"name":"Kathryn Keith","orcid":null,"position":1,"is_corresponding":false},{"id":970534,"name":"Sandra Wilson","orcid":null,"position":2,"is_corresponding":false},{"id":970535,"name":"Lucas Padgett","orcid":null,"position":3,"is_corresponding":false},{"id":391287,"name":"Andreana Benitez","orcid":"0000-0002-8294-7809","position":4,"is_corresponding":false},{"id":507163,"name":"Viswanathan Ramakrishnan","orcid":"0000-0002-4098-0539","position":5,"is_corresponding":false},{"id":453573,"name":"Jens H. Jensen","orcid":"0000-0003-3219-4287","position":6,"is_corresponding":false},{"id":241340,"name":"Leonardo Bonilha","orcid":"0000-0002-6153-8942","position":7,"is_corresponding":false},{"id":490578,"name":"Gonzalo J. Revuelta","orcid":"0000-0003-3917-8634","position":8,"is_corresponding":false},{"id":490576,"name":"Daniel H. Lench","orcid":"0000-0003-1491-8579","position":0,"is_corresponding":true}],"reference_count":42,"raw_metadata":null,"created_at":"2026-07-19T00:30:18.766838Z","pmid":"35367969","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}