RESUMEN
ObjectivesWe explored whether adapting traditional neuropsychological tests for online administration against the backdrop of COVID-19 was feasible for people with diverse forms of dementia and healthy older controls. We compared face-to-face and remote settings to ascertain whether remote administration affected performance. DesignWe used a longitudinal design for healthy older controls who completed face-to-face neuropsychological assessments between three and four years before taking part remotely. For patients, we used a cross-sectional design, contrasting a prospective remote cohort with a retrospective face-to-face cohort matched in age, education, and disease duration. SettingRemote assessments were performed using video-conferencing and online testing platforms, with participants using a personal computer or tablet and situated in a quiet room in their own home. Face-to-face assessments were carried out in dedicated testing rooms in our research centre. ParticipantsThe remote cohort comprised ten healthy older controls (also seen face-to-face 3-4 years previously) and 25 patients (n=8 Alzheimers disease (AD); n=3 behavioural variant frontotemporal dementia (bvFTD); n=4 semantic dementia (SD); n=5 progressive nonfluent aphasia (PNFA); n=5 logopenic aphasia (LPA)). The face-to-face patient cohort comprised 64 patients (n=25 AD; n=12 bvFTD; n=9 SD; n=12 PNFA; n=6 LPA). Primary and secondary outcome measuresThe outcome measures comprised the strength of evidence under a Bayesian analytic framework for differences in performances between face-to-face and remote testing environments on a general neuropsychological (primary outcomes) and neurolingustic battery (secondary outcomes). ResultsThere was evidence to suggest comparable performance across testing environments for all participant groups, for a range of neuropsychological tasks across both batteries. ConclusionsOur findings suggest that remote delivery of neuropsychological tests for dementia research is feasible. Strengths and limitations of this studyO_ST_ABSMethodological strengths of this study includeC_ST_ABSO_LIDiverse patient cohorts representing rare dementias with specific communication difficulties C_LIO_LISampling of diverse and relevant neuropsychological domains C_LIO_LIUse of Bayesian statistics to quantify the strength of evidence for the putative null hypothesis (no effect between remote and face-to-face testing) C_LI Limitations includeO_LIRelatively small cohort sizes C_LIO_LILack of direct head-to-head comparisons of test environment in the same patients C_LI
RESUMEN
Objective@#Brainstem segmentation has been useful in identifying potential imaging biomarkers for diagnosis and progression in atypical parkinsonian syndromes (APS). However, the majority of work has been performed using manual segmentation, which is time consuming for large cohorts. @*Methods@#We investigated brainstem involvement in APS using an automated method. We measured the volume of the medulla, pons, superior cerebellar peduncle (SCP) and midbrain from T1-weighted MRIs in 67 patients and 42 controls. Diagnoses were corticobasal syndrome (CBS, n = 14), multiple system atrophy (MSA, n = 16: 8 with parkinsonian syndrome, MSA-P; 8 with cerebellar syndrome, MSA-C), progressive supranuclear palsy with a Richardson’s syndrome (PSP-RS, n = 12), variant PSP (n = 18), and APS not otherwise specified (APS-NOS, n = 7). @*Results@#All brainstem regions were smaller in MSA-C (19–42% volume difference, p < 0.0005) and in both PSP groups (18–33%, p < 0.0005) than in controls. MSA-P showed lower volumes in all regions except the SCP (15–26%, p < 0.0005). The most affected region in MSA-C and MSA-P was the pons (42% and 26%, respectively), while the most affected regions in both the PSP-RS and variant PSP groups were the SCP (33% and 23%, respectively) and midbrain (26% and 24%, respectively). The brainstem was less affected in CBS, but nonetheless, the pons (14%, p < 0.0005), midbrain (14%, p < 0.0005) and medulla (10%, p = 0.001) were significantly smaller in CBS than in controls. The brainstem was unaffected in APS-NOS. @*Conclusion@#Automated methods can accurately quantify the involvement of brainstem structures in APS. This will be important in future trials with large patient numbers where manual segmentation is unfeasible.