Volume 40, Issue 9 092504
Nuclear medicine physics

Evaluation of CT-based lean-body SUV

James J. Hamill

James J. Hamill

Siemens Healthcare, Knoxville, Tennessee 37932

Author to whom correspondence should be addressed. Electronic mail: [email protected]; Telephone: (865)218-2278; Fax: (865)218-3010.

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John J. Sunderland

John J. Sunderland

University of Iowa Hospitals, Iowa City, Iowa 52242

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Amy K. LeBlanc

Amy K. LeBlanc

University of Tennessee Graduate School of Medicine and Veterinary Medical Center, University of Tennessee, Knoxville, Tennessee 37920

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Cheryl J. Kojima

Cheryl J. Kojima

Department of Animal Science, University of Tennessee, Knoxville, Tennessee 37996

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Jonathan Wall

Jonathan Wall

Amyloid and Preclinical Molecular Imaging Laboratory and Graduate School of Medicine, University of Tennessee, Knoxville, Tennessee 37920

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Emily B. Martin

Emily B. Martin

Department of Medicine, University of Tennessee Graduate School of Medicine, Knoxville, Tennessee 37920

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First published: 13 August 2013
Citations: 10

Abstract

Purpose:

The authors introduce a novel method for defining standardized uptake values (SUVs) in PET/CT based on routinely collected CT data. The goal of the study is to reduce, if possible, the variability of SUV in a heterogeneous population. Two well established methods for defining SUV are based on body weight (BW) and lean body mass, calculated as a function of height, weight, and sex with an empirical formula (LBM). The authors investigate two novel models, CT1 and CT2, that estimate the lean mass from CT Hounsfield Unit values. The authors compare the four methods, assessing the variability of hepatic SUV in18F-FDG studies.

Methods:

CT images from 252 cancer patients were segmented into regions representing lean tissues, fat, and bone. The fraction of lean tissue in the scanned region was extrapolated to the entire body with a naive method (CT1) and a method that modeled typical FDG uptake patterns (CT2). For each method, SUV-based measurements of the liver were calculated for all patients and dependence on body weight was assessed. Coefficients of variation (CVs) were evaluated. Several sub-cohorts were analyzed, including those with low and high body mass index (BMI). The extrapolation technique was tested in 19 melanoma patients who received head to toe PET/CT scans. CT-based weight predictions were compared with actual patient weight in melanoma studies and in PET/CT scans of pigs.

Results:

Only the SUV based on BW method depended significantly on body weight. CVs for the BW, LBM, CT1, and CT2 methods were, respectively, 18.0%, 15.5%, 15.9%, and 14.9%. In the high-BMI cohort, CVs were 18.2%, 16.2%, 16.2%, and 15.1%. Mean SUV of the 14 most obese patients agreed most closely with mean SUV of 120 lean patients when the CT2 method was used. SUV based on truncated CT agreed with head to toe predictions within 5% for the CT1 method and 1% for the CT2 method. CT-based weight estimate recovered 97.4% of the weight in head to toe studies of humans and 99.7% in pig studies.

Conclusions:

The novel CT1 and CT2 methods were less variable than the BW method and were comparable to the LBM method. SUV were little affected by missing CT data.