This study suggests that FoG in PD can be the result of a poor structural and functional integration between motor and extramotor (cognitive) neural systems.

We investigated the diagnostic accuracy of brainstem MRI measurements in patients with different progressive supranuclear palsy (PSP) syndromes and Parkinson's disease (PD). Using 3D T1-weighted images, midbrain, and pons areas, as well as superior (SCP) and middle cerebellar peduncle (MCP) widths were measured in 10 patients with Richardson's syndrome (PSP-RS), 10 patients with PSP-parkinsonism (PSP-P), 25 patients with PD, and 24 healthy controls. The ratio between pons and midbrain areas (pons/midbrain), that between MCP and SCP widths (MCP/SCP), and the MR parkinsonism index ([pons/midbrain]*[MCP/SCP]) were calculated. The pons/midbrain and the MR parkinsonism index allowed to differentiate PSP-RS from PD with high sensitivity (90%, 100%), specificity (96%, 92%), and accuracy (94%, 97%). Only the pons/midbrain was found to distinguish PSP-P from PD, but with a lower diagnostic accuracy (sensitivity = 60%, specificity = 96%, accuracy = 86%). Compared to PSP-RS, PSP-P experience a relatively less severe involvement of infratentorial brain. The pons/midbrain looks as a promising measure in the differentiation of individual PSP-P from PD patients.

Purpose To investigate the structural brain connectome in patients with Parkinson disease (PD) and mild cognitive impairment (MCI) and in patients with PD without MCI. Materials and Methods This prospective study was approved by the local ethics committees, and written informed consent was obtained from all subjects prior to enrollment. The individual structural brain connectome of 170 patients with PD (54 with MCI, 116 without MCI) and 41 healthy control subjects was obtained by using deterministic diffusion-tensor tractography. A network-based statistic was used to assess structural connectivity differences among groups. Results Patients with PD and MCI had global network alterations when compared with both control subjects and patients with PD without MCI (range, P = .004 to P = .048). Relative to control subjects, patients with PD and MCI had a large basal ganglia and frontoparietal network with decreased fractional anisotropy (FA) in the right hemisphere and a subnetwork with increased mean diffusivity (MD) involving similar regions bilaterally (P < .01). When compared with patients with PD without MCI, those with PD and MCI had a network with decreased FA, including basal ganglia and frontotemporoparietal regions bilaterally (P < .05). Similar findings were obtained by adjusting for motor disability (P < .05, permutation-corrected P = .06). At P < .01, patients with PD and MCI did not show network alterations relative to patients with PD without MCI. Network FA and MD values were used to differentiate patients with PD and MCI from healthy control subjects and patients with PD without MCI with fair to good accuracy (cross-validated area under the receiver operating characteristic curve [principal + secondary connected components] range, 0.75-0.85). Conclusion A disruption of structural connections between brain areas forming a network contributes to determine an altered information integration and organization and thus cognitive deficits in patients with PD. These results provide novel information concerning the structural substrates of MCI in patients with PD and may offer markers that can be used to differentiate between patients with PD and MCI and patients with PD without MCI. RSNA, 2016 Online supplemental material is available for this article.