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Automatic liver detection and standardised uptake value evaluation in whole-body Positron Emission Tomography/Computed Tomography scans

Authors :
Fabrizio Bergesio
Elisa Bertone
Stephane Chauvie
Piergiorgio Cerello
Alessandra Terulla
Davide Botto
Publication Year :
2018
Publisher :
Elsevier, 2018.

Abstract

Background and objective: Standardised Uptake Value (SUV), in clinical research and practice, is a marker of tumour avidity in Positron Emission Tomography/Computed Tomography (PET/CT). Since many technical, physical and physiological factors affect the SUV absolute measurement, the liver uptake is often used as reference value both in quantitative and semi-quantitative evaluation. The purpose of this investigation was to automatically detect the liver position in whole-body PET/CT scans and extract its average SUV value. Methods: We developed an algorithm, called LIver DEtection Algorithm (LIDEA), that analyses PET/CT scans, and under the assumption that the liver is a large homogeneous volume near the centre of mass of the patient, finds its position and automatically places a region of interest (ROI) in the liver, which is used to calculate the average SUV. The algorithm was validated on a population of 630 PET/CT scans coming from more than 60 different scanners. The SUV was also calculated by manually placing a large ROI in the liver. Results: LIDEA identified the liver with a 97.3% sensitivity with PET/CT images only and reached a 98.9% correct detection rate when using the co-registered CT scan to avoid liver misidentification in the right lung. The average liver SUV obtained with LIDEA was successfully validated against its manual assessment, with no systematic difference (0.11 ± 0.36 SUV units) and a R 2 = 0.89 correlation coefficient. Conclusions: LIDEA proved to be a reliable tool to automatically identify and extract the average SUV of the liver in oncological whole-body PET/CT scans.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d98c430c1baf2a1a2cacbff02aa9f8e6