P4‐333: Issues Regarding [18f]mk6240 Reference Region Selection Based on the Full Kinetic Modeling
Year: 2019
Type: article
Abstract: [F]MK6240, has been accepted widely as a novel PET tracer for neurofibrillary tangles. However, there has yet to be a close examination of its appropriate reference region. Here, we evaluated several potential reference regions based on full quantification and 30 longitudinal data to assess and validate the reference tissue methods. Total 5 patients underwent 3-hour dynamic PET scans in HRRT with continuous arterial sampling using Twilite. We collected 8 blood samples to calculate the parent fraction and metabolite throughout the scan. Total 30 longitudinal static scans (90-100 min, baseline and 1-year follow-up) were acquired in the TRIAD cohort. The dynamic [F]MK6240 were quantified with 2 Tissue Compartment Model (2TCM) VT for target regions and 1 Tissue Compartment Model (1TCM) for different reference regions. The nondisplacable (ND) binding compartments from 2TCM in the targets were compared VT in the reference regions. To validate the reference tissue and its accuracy, 2TCM VT in the targets were associated with Logan reference region method (DVR). Last, the variance of the reference regional fits was examined based on the mean square error. The longitudinal changes in the standard uptake value (SUV) in the reference regions were assessed based on paired-t test with FDR correction. 8 potential reference regions investigated - cerebellar grey (CerebGM), cerebellar vermis, pons, striatum, white matter (WM), eroded CerebGM, inferior CerebGM, and Pons & Inferior CerebGM. The striatum, WM, and inferior CerebGM showed significantly different level of ND binding compared to the target ND binding. Furthermore CerebGM, cerebellar vermis, pons, inferior CerebGM, and pons&inferior CerebGM showed significant correlation between VT and DVR in the targets. Moreover, only Pons, Inferior CerebGM, and Pon&inferior CerebGM showed no changes in the SUV after 1-year follow-up. However, Pons demonstrated the highest variance.
Source: Alzheimer s & Dementia
Authors: Min Su Kang, Tharick A. Pascoal, Monica Shin, Mira Chamoun, Sulantha Mathotaarachchi, Andrea Lessa Benedet, Joseph Therriault, Melissa Savard, Reda Bouhachi, Chris Hsiao, Emilie Thomas, Daniel Chartrand, Firoza Zubeida Lussier, Cecile Tissot, Muhammad Naveed Iqbal Qureshi, Jean-Paul Soucy, Gassan Massarweh, Pedro Rosa-Neto
Institutions: Douglas Mental Health University Institute, McGill University Research Centre for Studies in Aging, McGill University, Coordenação de Aperfeicoamento de Pessoal de Nível Superior, Montreal Neurological Institute and Hospital, Gwangju Institute of Science and Technology, Centre Hospitalier de l’Université de Montréal, Concordia University, Université de Montréal
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4244696147