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[IC‐P‐158]: IMPLEMENTING THE CENTILOID TRANSFORMATION FOR 18 F‐FLORBETABEN AND 18 F‐NAV4694 USING CAPAIBL
Author(s) -
Bourgeat Pierrick,
Dore Vincent,
Ames David,
Masters Colin L.,
Fripp Jurgen,
Salvado Olivier,
Villemagne Victor L.,
Rowe Christopher C.
Publication year - 2017
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2017.06.2533
Subject(s) - nuclear medicine , linear regression , medicine , mathematics , statistics
p<0.001; r(26)1⁄40.54, p<0.01) and 2) with total burden volume (r(26)1⁄4 0.58, p<0.01) and total ePVS number detected by mMAPS (r(26)1⁄4 0.76, p<0.01, Figure 4C). Average ePVS was 24.6 (range 3 to 71) and total burden volume (SD) 303.0 (267.74) mm per dataset. Average width of ePVS was 3.12 mm (min 1.7, max 13.5). Whole brain counts were 7.1 times that of a single slice, a nearly 100-fold increase in the range of the measured proxy variable for burden. In this limited dataset, no significant relationships were observed between automated or visual assessment of ePVS and age, diastolic blood pressure, or white matter hyperintensity volume. mMAPS quantified ePVS, but not visual counts, were associated with systolic blood pressure (Table 1). Conclusions: To our knowledge, this is the first fully automated segmentation method to provide morphological (linearity, volume, width) information of ePVS in whole brain clinical field strength MRI.