Ascertainment

We performed a retrospective chart review to identify all the patients affected with visual symptoms in PD cases. Patients were identified from a movement disorder clinic at the University of Utah Hospital and Clinics in Salt Lake City, Utah; the sole movement disorder center in a 5-state area. Our study was approved by the University of Utah's Institutional Review Board. We only included patients that were diagnosed with PD by a movement disorder specialist (DS) based on the Queen Square Brain Bank criteria (12). We reviewed the medical records of 572 PD patients seen by three providers (DS, MZ, and RS) from January 1st 2011 to December 31st 2014 searching for the presence of NMS (including hallucinations) in the clinical history. The clinical history template was a consistent collection of clinical questions been developed to ensure the completeness of clinical information. These included all motor and NMS. Exclusion criteria included charts with insufficient information, patients lost to follow-up, or patients with an unclear diagnosis. Forty-seven charts met the exclusion criteria, leaving 525 patients in our final sample. The inclusion criteria involved any PD patient who had experienced a visual symptom in one of their last three clinic visits. A neurologist (KJS) reviewed the 525 medical records to determine which patients met the inclusion criteria. One hundred and seventy-seven patients reported visual complaints, which included blurred vision, dry eyes, double vision, VH, or VM. We collected demographic information and clinical characteristics of each patient with PD and visual complaints [age, sex, age-of-onset, type of visual complaints, RBD, cognitive complaints, and use of dopamine agonists (Das)]. We took advantage of the data collected in the medical records of the movement disorders clinic that specifically addressed cognitive complaints, visual complaints, psychiatric complaints, and RBD (defined using the Mayo Clinic Questionnaire) (13). When available, the Montreal Cognitive Assessment (MoCA) was used to define and characterize the presence of cognitive complaints (MoCa score < 26); if unavailable, we used the clinical diagnosis determined by the clinician.

We differentiated between hallucinations and VM (or illusions) by using a structured set of questions that were adopted in the review of the medical records. Hallucinations were defined as a perception of an object (in this case visual) in the absence of an external stimulus (14). In comparison, VM involved identifiable external stimuli (in this case visual) that were integrated incorrectly resulting in a transient phenomenon including shadows, movement, presence, flashing figures, distortions, or corner of eye phenomena. If visual symptoms were only reported in the setting of acute delirium due to a medical illness, they were excluded from the study. We excluded all the cases that reported cataracts diagnosis, cataract surgery, macular degeneration, or had a sudden decline of visual acuity secondary to trauma, presbyopia, or other ophthalmologic reasons.

We also reviewed the available brain MRIs in order to study the volumetric structural changes among the patients with different visual symptoms. Eighty two of our 177 patients (46.3%) had a brain MRI in our hospital and clinics or at an outside institution and were scanned into PACS (picture archiving and communication system). The MRI was performed according to the clinician judgment for clinical or diagnostic reasons. In a minority of cases, MRI scan included a magnetization-prepared rapid acquisition gradient echo (MPRAGE) sequence with spatial resolution of 2 mm isotropic voxels or better. Among patients in our sample, we obtained MRI scans of sufficient quality for volumetric analysis from 11 patients with VH, 4 patients with VM, and 20 patients without VH or misperceptions.

Cortical reconstruction and volumetric segmentation was performed with the FreeSurfer Image Analysis Suite, which is documented and freely available for download online (http://surfer.nmr.mgh.harvard.edu/). The technical details of these procedures are described in prior publications (15, 16). Briefly, this processing includes motion correction and averaging of multiple volumetric T1-weighted images (when more than one is available), removal of non-brain tissue using a hybrid watershed/surface deformation procedure, automated Talairach transformation, segmentation of the subcortical white matter and deep gray matter volumetric structures (including hippocampus, amygdala, caudate, putamen, ventricles) (15, 16), intensity normalization (17), tessellation of the gray matter-white matter boundary, automated topology correction (18), and surface deformation following intensity gradients to optimally place the gray/white and gray/cerebrospinal fluid borders at the location where the greatest shift in intensity defines the transition to the other tissue class (19). This was followed by parcellation of the cerebral cortex into units with respect to gyral and sulcal structure using the Destrieux atlas (20).