E003 Update on the iMarkHD study

<h3>Background</h3> In the iMarkHD study, we aim to investigate changes in the binding profiles of four distinct molecular PET markers and various MRI markers across different disease stages in people with Huntington’s disease (PwHD), compared to healthy controls, with the aim to identify novel biomarkers for disease and symptom progression. <h3>Aims</h3> To provide an update on recruitment and study progression of the iMarkHD study. <h3>Methods</h3> We report the number of currently enrolled participants (figure 1) per group, and provide demographic data for these participants, number of participants and reasons for screen-fails, as well as participant feedback. <h3>Results</h3> Recruitment efforts have resulted in the enrolment of 64 participants with 17 participants (70.8% of target) in group B (HD-ISS 0/1 PwHD), 15 participants (62.5% of target) in group C (HD-ISS 1/2 PwHD), 13 participants (54.2% of target) in group D (HD-ISS 2–3 PwHD), and 19 healthy volunteers (52.8% of target) (figure 2). PwHD were successfully enrolled through 11 participant identification sites across the United Kingdom, providing a representative cohort of PwHD in terms of geographical distribution and demographics. We have had 13 screen fails, most commonly because of ineligible medication use, and 10 participants withdrew, mostly related to progression of their disease and travel distance. Strategies that have supported enrolment and retainment include covering travel and accommodation costs, and flexibility with dates for study visits. Participants have all rated their participation as very good or excellent. <h3>Conclusions</h3> In demanding observational studies, such as the iMarkHD study, appropriate recruitment and retainment strategies are crucial.

Authors

Institutions

Publication Details

Published
2024-09-01
DOI
https://doi.org/10.1136/jnnp-2024-ehdn.99
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

E003 Update on the iMarkHD study

Andrew T. Wood, Monika Hartmann, James Badenoch, Jose Manuel Valera‐Bermejo et al.
Radiomics and Machine Learning in Medical Imaging
article

E003 Update on the iMarkHD study

Andrew T. Wood, Monika Hartmann, James Badenoch, Jose Manuel Valera‐Bermejo, Daniel J. van Wamelen, Naomi Martin, Steven Williams, Alay Rangel Cristales, Orsolya Makos, Nikki Palasits
article en

Abstract

<h3>Background</h3> In the iMarkHD study, we aim to investigate changes in the binding profiles of four distinct molecular PET markers and various MRI markers across different disease stages in people with Huntington’s disease (PwHD), compared to healthy controls, with the aim to identify novel biomarkers for disease and symptom progression. <h3>Aims</h3> To provide an update on recruitment and study progression of the iMarkHD study. <h3>Methods</h3> We report the number of currently enrolled participants (figure 1) per group, and provide demographic data for these participants, number of participants and reasons for screen-fails, as well as participant feedback. <h3>Results</h3> Recruitment efforts have resulted in the enrolment of 64 participants with 17 participants (70.8% of target) in group B (HD-ISS 0/1 PwHD), 15 participants (62.5% of target) in group C (HD-ISS 1/2 PwHD), 13 participants (54.2% of target) in group D (HD-ISS 2–3 PwHD), and 19 healthy volunteers (52.8% of target) (figure 2). PwHD were successfully enrolled through 11 participant identification sites across the United Kingdom, providing a representative cohort of PwHD in terms of geographical distribution and demographics. We have had 13 screen fails, most commonly because of ineligible medication use, and 10 participants withdrew, mostly related to progression of their disease and travel distance. Strategies that have supported enrolment and retainment include covering travel and accommodation costs, and flexibility with dates for study visits. Participants have all rated their participation as very good or excellent. <h3>Conclusions</h3> In demanding observational studies, such as the iMarkHD study, appropriate recruitment and retainment strategies are crucial.

Wellcome Centre for Human Neuroimaging (GB), King's College London (GB), CHDI Foundation (US), King's College Hospital NHS Foundation Trust (GB)
Openalex Percentile: Top 75%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.