Exploratory Assessment of K-means Clustering to Classify 18F-Flutemetamol Brain PET as Positive or Negative

Abstract

Rationale: We evaluated K-means clustering to classify amyloid brain PETs as positive or negative. Patients and Methods: Sixty-six participants (31 men, 35 women; age range, 52–81 years) were recruited through a multicenter observational study: 19 cognitively normal, 25 mild cognitive impairment, and 22 demen- tia (11 Alzheimer disease, 3 subcortical vascular cognitive impairment, and 8 Parkinson–Lewy Body spectrum disorder). As part of the neurocognitive and imaging evaluation, each participant had an 18F-flutemetamol (Vizamyl, GE Healthcare) brain PET. All studies were processed using Cortex ID soft- ware (General Electric Company, Boston, MA) to calculate SUV ratios in 19 regions of interest and clinically interpreted by 2 dual-certified radiologists/ nuclear medicine physicians, using MIM software (MIM Software Inc, Cleveland, OH), blinded to the quantitative analysis, with final interpreta- tion based on consensus. K-means clustering was retrospectively used to classify the studies from the quantitative data. Results: Based on clinical interpretation, 46 brain PETs were negative and 20 were positive for amyloid deposition. Of 19 cognitively normal partici- pants, 1 (5%) had a positive 18F-flutemetamol brain PET. Of 25 participants with mild cognitive impairment, 9 (36%) had a positive 18F-flutemetamol brain PET. Of 22 participants with dementia, 10 (45%) had a positive 18F-flutemetamol brain PET; 7 of 11 participants with Alzheimer disease (64%), 1 of 3 participants with vascular cognitive impairment (33%), and 2 of 8 participants with Parkinson–Lewy Body spectrum disorder (25%) had a positive 18F-flutemetamol brain PET. Using clinical interpretation as the criterion standard, K-means clustering (K = 2) gave sensitivity of 95%, specificity of 98%, and accuracy of 97%. Conclusions: K-means clustering may be a powerful algorithm for classifying amyloid brain PET.