Abstract

Three-dimensional stereotactic surface projection (3D-SSP) is a widely used method for the analysis of clinical <sup>18</sup>F-FDG brain studies. However, for PET amyloid scans the use of 3D-SSP is challenging because of nonspecific uptake in white matter. Our objective was to implement a method for 3D-SSP quantification and visualization of <sup>18</sup>F-flutemetamol images that avoids extraction of white matter signal. <b>Methods:</b> Triangulated brain surface models were extracted from a T1-weighted MR template image. Using an <sup>18</sup>F-flutemetamol–negative template, a maximum depth for each vertex on the surface models was calculated to avoid extraction of white matter. The method was evaluated using <sup>18</sup>F-flutemetamol images from 2 cohorts. Cohort 1 consisted of 105 healthy volunteers and was used to create a normal database for each reference region. Cohort 2 consisted of 171 subjects including patients with Alzheimer disease and mild cognitive impairment and healthy volunteers. Images were spatially normalized using an adaptive template registration method, and SUV ratio 3D-SSP values were computed using the pons and cerebellar cortex as reference regions. Images from cohort 2 were then compared with the normal database and classified into negatives and positives, based on a calculated <i>z</i> score threshold. The results were compared with consensus visual interpretation results from 5 trained interpreters blinded to clinical data. <b>Results:</b> With the pons as the reference region, the optimal <i>z</i> score threshold was 1.97, resulting in an overall agreement with visual interpretation results in 170 of 171 images (99.42%). With the cerebellar cortex as the reference region, the optimal <i>z</i> score threshold was 2.41, with an overall agreement with visual interpretation in 168 of 171 images (98.25%). <b>Conclusion:</b> Variable-depth 3D-SSP allows computation and visualization of <sup>18</sup>F-flutemetamol 3D-SSP maps, with minimized contribution from white matter signal while retaining sensitivity in detecting gray matter signal.

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