Anna Inguanzo1,2,3, Barbara Segura1,2,3,4, Roser Sala-Llonch1,3,5,6, Gemma Monte-Rubio1,2, Alexandra Abos1,2,3, Anna Campabadal1,2,3, Carme Uribe1,2,3,7, Hugo Cesar Baggio1,2, Maria Jose Marti1,3,4,8, Francesc Valldeoriola1,3,4,8, Yaroslau Compta1,3,4,8, Nuria Bargallo9,10, Carme Junque1,2,3,4. 1. Institute of Neurosciences, University of Barcelona, Barcelona, Catalonia, Spain. 2. Medical Psychology Unit, Department of Medicine, University of Barcelona, Barcelona, Catalonia, Spain. 3. Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain. 4. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED: CB06/05/0018-ISCIII), Barcelona, Catalonia, Spain. 5. Department of Biomedicine, University of Barcelona, Barcelona, Catalonia, Spain. 6. Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Catalonia, Spain. 7. Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Canada. 8. Movement Disorders Unit, Neurology Service, Institut de Neurociències, University of Barcelona, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain. 9. Centre de Diagnostic per la Imatge, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain. 10. Magnetic Resonance Core Facility, Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain.
Abstract
Background: Probabilistic tractography, in combination with graph theory, has been used to reconstruct the structural whole-brain connectome. Threshold-free network-based statistics (TFNBS) is a useful technique to study structural connectivity in neurodegenerative disorders; however, there are no previous studies using TFNBS in Parkinson's disease (PD) with and without mild cognitive impairment (MCI). Materials and Methods: Sixty-two PD patients, 27 of whom classified as PD-MCI, and 51 healthy controls (HC) underwent diffusion-weighted 3T magnetic resonance imaging. Probabilistic tractography, using FMRIB Software Library (FSL), was used to compute the number of streamlines (NOS) between regions. NOS matrices were used to find group differences with TFNBS, and to calculate global and local measures of network integrity using graph theory. A binominal logistic regression was then used to assess the discrimination between PD with and without MCI using non-overlapping significant tracts. Tract-based spatial statistics were also performed with FSL to study changes in fractional anisotropy (FA) and mean diffusivity. Results: PD-MCI showed 37 white matter connections with reduced connectivity strength compared with HC, mainly involving temporal/occipital regions. These were able to differentiate PD-MCI from PD without MCI with an area under the curve of 83-85%. PD without MCI showed disrupted connectivity in 18 connections involving frontal/temporal regions. No significant differences were found in graph measures. Only PD-MCI showed reduced FA compared with HC. Discussion: TFNBS based on whole-brain probabilistic tractography can detect structural connectivity alterations in PD with and without MCI. Reduced structural connectivity in fronto-striatal and posterior cortico-cortical connections is associated with PD-MCI.
Background: Probabilistic tractography, in combination with graph theory, has been used to reconstruct the structural whole-brain connectome. Threshold-free network-based statistics (TFNBS) is a useful technique to study structural connectivity in neurodegenerative disorders; however, there are no previous studies using TFNBSin Parkinson's disease (PD) with and without mildcognitive impairment (MCI). Materials and Methods: Sixty-two PDpatients, 27 of whom classified as PD-MCI, and 51 healthy controls (HC) underwent diffusion-weighted 3T magnetic resonance imaging. Probabilistic tractography, using FMRIB Software Library (FSL), was used to compute the number of streamlines (NOS) between regions. NOS matrices were used to find group differences with TFNBS, and to calculate global and local measures of network integrity using graph theory. A binominal logistic regression was then used to assess the discrimination between PD with and without MCI using non-overlapping significant tracts. Tract-based spatial statistics were also performed with FSL to study changes in fractional anisotropy (FA) and mean diffusivity. Results:PD-MCI showed 37 white matter connections with reduced connectivity strength compared with HC, mainly involving temporal/occipital regions. These were able to differentiate PD-MCI from PD without MCI with an area under the curve of 83-85%. PD without MCI showed disrupted connectivity in 18 connections involving frontal/temporal regions. No significant differences were found in graph measures. Only PD-MCI showed reduced FA compared with HC. Discussion: TFNBS based on whole-brain probabilistic tractography can detect structural connectivity alterations in PD with and without MCI. Reduced structural connectivity in fronto-striatal and posterior cortico-cortical connections is associated with PD-MCI.
Authors: Javier Oltra; Carme Uribe; Barbara Segura; Anna Campabadal; Anna Inguanzo; Gemma C Monté-Rubio; Jèssica Pardo; Maria J Marti; Yaroslau Compta; Francesc Valldeoriola; Carme Junque; Alex Iranzo Journal: NPJ Parkinsons Dis Date: 2022-05-24