Improving SUVR quantification by correcting for radiotracer clearance in tissue

• Published in: Journal of cerebral blood flow and metabolism Vol. 44; no. 2; pp. 296 - 309
• Main Authors: Honhar, Praveen, Matuskey, David, Carson, Richard E, Hillmer, Ansel T
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.02.2024
• Subjects: Alzheimer Disease - metabolism; Brain - diagnostic imaging; Brain - metabolism; Humans; Kinetics; Positron-Emission Tomography - methods; Radiopharmaceuticals - metabolism; SUVR; PET quantification; tissue clearance correction
• ISSN: 0271-678X; 1559-7016; 1559-7016
• DOI: 10.1177/0271678X231196804

Abstract Standardized Uptake Value Ratio (SUVR) is a widely reported semi-quantitative positron emission tomography (PET) outcome measure, partly because of its ease of measurement from short scan durations. However, in brain, SUVR is often a biased estimator of the gold-standard distribution volume ratio (DVR) due to non-equilibrium conditions, i.e., clearance of the radiotracer in relevant tissues. Factors that affect radiotracer metabolism and clearance such as medication or subject groups could lead to artificial differences in SUVR. This work developed a correction that reduces the bias in SUVR (estimated from a short 15–30 min PET imaging session) by accounting for the effects of tracer clearance observed during the late SUVR time window. The proposed correction takes the form of a one-step non-linear algebraic transform of SUVR that is a function of radiotracer dependent parameters such as clearance rates from the reference and target tissues, and population averaged reference region clearance rate ( k 2 , ref ). An important observation was the need for accurate estimation of radiotracer clearance rate in target tissue, which was addressed with a regression based model. Simulations and human data from two different radiotracers (healthy controls for [11C]LSN3172176, healthy controls and Parkinson’s disease subjects for [18F]FE-PE2I) were used to validate the correction and evaluate its benefits and limitations. SUVR correction in human data significantly reduced mean SUVR bias across brain regions and subjects (from ∼25% for SUVR to <10% for corrected SUVR). This correction also significantly reduced the variability of this bias across brain regions for both tracers (approximately 50% for [11C]LSN3172176, 20% for [18F]FE-PE2I). Future work should investigate the benefits of using corrected SUVR in other populations and with different tracers.