Common carotid segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based and manual method
Journal article, 2023

Background: Carotid atherosclerosis is a major cause of stroke, traditionally diagnosed late. Positron emission tomography/computed tomography (PET/CT) with 18F-sodium fluoride (NaF) detects arterial wall micro-calcification long before macro-calcification becomes detectable by ultrasound, CT or magnetic resonance imaging. However, manual PET/CT processing is time-consuming and requires experience. We compared a convolutional neural network (CNN) approach with manual segmentation of the common carotids. Methods: Segmentation in NaF-PET/CT scans of 29 healthy volunteers and 20 angina pectoris patients were compared for segmented volume (Vol) and mean, maximal, and total standardized uptake values (SUVmean, SUVmax, and SUVtotal). SUVmean was the average of SUVmeans within the VOI, SUVmax the highest SUV in all voxels in the VOI, and SUVtotal the SUVmean multiplied by the Vol of the VOI. Intra and Interobserver variability with manual segmentation was examined in 25 randomly selected scans. Results: Bias for Vol, SUVmean, SUVmax, and SUVtotal were 1.33 ± 2.06, −0.01 ± 0.05, 0.09 ± 0.48, and 1.18 ± 1.99 in the left and 1.89 ± 1.5, −0.07 ± 0.12, 0.05 ± 0.47, and 1.61 ± 1.47, respectively, in the right common carotid artery. Manual segmentation lasted typically 20 min versus 1 min with the CNN-based approach. Mean Vol deviation at repeat manual segmentation was 14% and 27% in left and right common carotids. Conclusions: CNN-based segmentation was much faster and provided SUVmean values virtually identical to manually obtained ones, suggesting CNN-based analysis as a promising substitute of slow and cumbersome manual processing.

artificial intelligence

positron emission tomography




Reza Piri

Odense Universitetshospital

University of Southern Denmark

Yaran Hamakan

Odense Universitetshospital

Ask Vang

Odense Universitetshospital

L. Edenbrandt

University of Gothenburg

Sahlgrenska University Hospital

Måns Larsson

Eigenvision AB

Olof Enqvist

Imaging and Image Analysis

Eigenvision AB

Oke Gerke

Odense Universitetshospital

University of Southern Denmark

P. F. Hoilund-Carlsen

University of Southern Denmark

Odense Universitetshospital

Clinical Physiology and Functional Imaging

1475-0961 (ISSN)

Vol. 43 2 71-77

Subject Categories

Medical Laboratory and Measurements Technologies

Radiology, Nuclear Medicine and Medical Imaging

Medical Image Processing





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