Author Of 3 Presentations
P0019 - A Comparison of Digital Gait Technologies in a Population of People with MS –When the Same Isn’t Always Exactly the Same (ID 1944)
Abstract
Background
Multiple Sclerosis (MS), a disease characterized both by relapses and progression, commonly impacts ambulation. Impaired ambulation results in loss of independence. Current approaches to document disease impact/progression on ambulation including EDSS/T25FW are insufficiently sensitive to quantify subtle but critical change. Patient Reported Outcomes (PRO) for gait relate to several critical elements of the gait cycle beyond velocity. Earlier recognition of critical change might improve disease modifying therapy choice and timing of change. Objective multi-dimensional analytics have included digital devices of varying types utilizing different technologies (e.g. foot pressure, accelerometer, 3D video capture). Comparing different technologies in people with MS (PwMS) along a spectrum of disability would be important to optimal technology choice. Simultaneous comparisons of similar outcome measures of gait components would enhance technology choice.
Objectives
To compare and contrast quantified outcome measures of the gait cycle as measured by the use of three different validated and digital ambulatory devices.
Methods
PwMS performed one pass (20 feet) while ambulating at a preferred walking speed along the Zeno™ walkway (ZW, ProtoKinetics), while wearing Opal sensors (OS, APDM), and captured using VSTBalance (VB, VirtuSense) simultaneously. Relevant gait parameters (GP) captured: velocity, stride length, total double support, and cadence. Univariate regression modeling and T-tests were used for statistical analysis for each GP.
Results
9 PwMS (69% female, average age =53.1±11.8 years). Regression modeling showed the following relationships: velocity: ZWvsVB (r2 =0.93, p=1.2E-25), ZWvsOS (r2 =0.99, p=6.9E-40), VBvsOS (r2 =0.96, p=1.8E-25) Stride Length: ZWvsVB (r2 =0.32, p=7.8E-25), ZWvsOS (r2 =0.9, p=1.02E-16), VBvsOS (r2 =0.30, p=1.3E-4). Total double support %: ZWvsVB (r2 =0.22, p=1.6E-3), ZWvsOS (r2 =0.87, p=3.2E-20), VBvsOS (r2 =0.27, p=3.9E-4). Cadence: ZWvsVB (r2 =0.18, p=5.3E-3), ZWvsOS (r2 =0.92, p=1.2E-23), VBvsOS (r2 =0.19, p=4.2E-3). T-tests showed the following relationships: velocity: ZWvsVB (p=0.47), ZWvsOS (p=0.21), VBvsOS (p=0.63). Stride Length: ZWvsVB (p=7.25E-6), ZWvsOS (p=0.08), VBvsOS (p=0.001). Total Double Support %: ZWvsVB (p=0.91), ZWvsOS (p=0.01), VBvsOS (p=0.02). Cadence: ZWvsVB (p=5.6E-5), ZWvsOS (p=0.92), VBvsOS (p=6.3E-5).
Conclusions
Gait velocity had the strongest concordant relationship between all three technologies. Despite this concordance, there was still ~10% variability of this important measure. Other elements of the gait cycle had sub-optimal cross-device relationships. There was considerable discordance with stride length and cadence (ZWvsVB and OSvsVB), and double support (ZWvsOS and VBvsOS). Inconsistent relationships demonstrate the need to carefully select digital gait outcome measurement devices for PwMS.
P0116 - Multiple Sclerosis and Cognitive Impairment: Computerized Cognitive Assessment and PROMIS-Cognitive Function Questionnaire: An Unfulfilled Promis (ID 1873)
Abstract
Background
Cognitive impairment (CI) is common in people with Multiple Sclerosis (PwMS) but often not addressed in routine care. Disease burden/progression in PwMS is traditionally measured by reported relapse, EDSS, and MRI change. CI is a source of significant disability independent of findings on examination. Use of a validated multi-domain screening cognitive assessment battery (NeuroTrax, CAB-NT) provides quantitative patient centric information to track CI longitudinally. Patient self-reported outcome measures (PRO) are also often used to gauge disability progression. PROMIS–Cognitive Function Short Form (CF-SF) is a validated disease agnostic PRO that can be incorporated to evaluate patient perception of disease impact. The relationship of the PROMIS PRO to a multi-domain quantitative cognitive assessment tool has not been explored in PwMS.
Objectives
To examine the cross-sectional relationship between PRO PROMIS-Cognitive Function (CF-SF) scores and CAB-NT scores.
Methods
Retrospective review of consecutive PwMS who completed both the CAB-NT and PROMIS-CF-SF in the course of routine care on the same day. CAB-NT included 7 cognitive domains: memory (Mem), executive function (Exe), attention (Att), information processing speed (Inf), visual spatial (Vis), verbal function (Ver), motor skills (Mot) as well as a global cognitive summary score (GCS). Cognitive domains impaired (CDI, domain score’s <85) are also calculated.
Results
147 PwMS, average age 49+/- 12, 70% female. Significant relationships (p<0.05) were identified through regression analysis with Pearson’s correlation coefficient (r) only for the following Cognitive Domain scores: GCS (r=0.27), Mem (r=0.23), Exe (r=0.27), Att (r=0.27), Inf (r=0.42), and Mot (r=0.27), CDI (r=0.4).
Conclusions
The PROMIS-Cognitive Function Short Form PRO does not provide a meaningful alternative to objective measures of CI in PwMS. Computerized Multi-domain Cognitive Testing provides an accurate tool to evaluate the degree of cognitive impairment across multiple relevant cognitive domains as well as the combination of domain impairment and accumulative cognitive impairment. The promise of the PROMIS-Cognitive Function Short Form to provide an effective PRO to evaluate cognitive impairment in PwMS has not been fulfilled.
P0577 - Feasibility of thalamic atrophy measurement in clinical routine using artificial intelligence: Results from multi-center study in RRMS patients (ID 1058)
Abstract
Background
The thalamus is a key gray matter structure, and a sensitive marker of neurodegeneration in multiple sclerosis (MS). Previous reports have indicated that thalamic volumetry on clinical-quality T2-FLAIR images alone is fast and reliable, using artificial intelligence (AI).
Objectives
To investigate the feasibility of thalamic atrophy measurement using AI in patients with MS, in a large multi-center, clinical routine study.
Methods
DeepGRAI (Deep Gray Rating via Artificial Intelligence) is a multi-center (31 USA sites), longitudinal, observational, real-word, registry study that will enroll 1,000 relapsing-remitting MS patients. Brain MRI exams previously acquired at baseline and at follow-up on 1.5T or 3T scanners with no prior standardization are used, in order to resemble real-world situation. Thalamic volume measurement is performed at baseline and follow-up on T2-FLAIR by DeepGRAI tool and on 3D T1-weighted image (WI) and 2D T1-WI by using FIRST software.
Results
In this pre-planned interim analysis, 515 RRMS patients were followed for an average of 2.7 years. There were 487 (94.6%) T2-FLAIR, 342 (66.4%) 2D T1-WI and 176 (34.2%) 3D T1-WI longitudinal pair of MRI exams available for analyses. Estimation of thalamic volume by DeepGRAI on T2-FLAIR correlated significantly with FIRST on 3D-T1-WI (r=0.733 and r=0.816, p<0.001) and with FIRST on 2D-T1-WI (r=0.555 and r=0.704, p<0.001) at baseline and at follow-up. The correlation between thalamic volume estimated by FIRST on 3D T1-WI and 2D T1-WI was r=0.642 and r=0.679, p<0.001, respectively. The thalamic volume % change over the follow-up was similar between DeepGRAI (-0.75) and 3D T1-WI (-0.82), but somewhat higher for 2D T1-WI (-0.92). Similar relationship was found between the Expanded Disability Status Scale (EDSS) and thalamic volume by DeepGRAI on T2-FLAIR and by FIRST on 3D T1-WI at baseline (r=-0.214, p=0.01 and r=-0.287, p=0.001) and at follow-up (r=-0.298, p=0.001 and r=-0.291, p=0.001).
Conclusions
DeepGRAI provides feasible thalamic volume measurement on multi-center clinical-quality T2-FLAIR images. The relationship between thalamic atrophy and physical disability is similar using DeepGRAI T2-FLAIR and standard high-resolution research approaches. This indicates potential for real-world thalamic volume monitoring, as well as quantification on legacy datasets without research-quality MRI.