Selection of SUV normalization and reference tissue for quantitative [68Ga]Ga-Pentixafor PET/CT analysis

[68Ga]Ga-Pentixafor PET/CT enables visualization of C-X-C chemokine receptor 4 expression, but quantitative accuracy depends on standardized uptake value (SUV) normalization and reference tissue selection. Body composition and variability across candidate organs may confound SUV interpretation.We retrospectively analyzed [68Ga]Ga-Pentixafor PET/CT scans from 40 patients without malignancy. Regions of interest were placed in the blood pool, liver, spleen, bone marrow, and muscle. Three SUV were calculated: SUV normalized by body weight (SUVbw) and SUV normalized by lean body mass (SUL), the latter derived using two methods—the conventional James formula and the Janmahasatian (Janma) formula, a revised method optimized for obese individuals. Correlations with body weight were quantified using Spearman correlation coefficients and the slope-to-intercept ratio (a/b) from linear regression analyses, while interobserver reproducibility and variability were evaluated using the intraclass correlation coefficient (ICC) and the coefficient of quartile variation (CQV), respectively. This study aimed to identify an optimal normalization strategy and reliable reference tissue for quantitative [68Ga]Ga-Pentixafor PET/CT. SUVmean, SULmean-James, and SULmean-Janma exhibited significant body-weight dependence in all candidate tissues except muscle, with the strongest association observed in the liver (right liver lobe: ρ = 0.635, 0.576, and 0.650, respectively). Compared with SUVbw, SUL derived from the James formula effectively reduced body-weight-related fluctuations in SUV measurements: a/b decreased from 0.065 to 0.034 in the right liver lobe, 0.036 to 0.021 in the left liver lobe, and 0.076 to 0.037 in the spleen. Across all normalization methods, SUV measurements demonstrated good repeatability in all candidate reference tissues (ICC > 0.7). Variability analysis showed that the liver and blood pool yielded the lowest dispersion for both SUVmean and SULmean-James (CQV: 9.4%-16.8%), identifying them as the most stable reference tissues. In contrast, splenic uptake exhibited substantial inter-individual variability (CQV: 19.9%-22.2%), suggesting it is unsuitable as a routine reference tissue. SUL-James normalization, together with the liver or blood pool as reference tissues, provides robust and reproducible quantification for [68Ga]Ga-Pentixafor PET/CT. These findings support standardized imaging frameworks and may facilitate treatment response evaluation, prognostic assessment, and harmonization across centers.

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Journal
EJNMMI Research
Published
2026-01-04
DOI
https://doi.org/10.1186/s13550-025-01370-z
Primary Topic
Medical Imaging Techniques and Applications
Type
article
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article

Selection of SUV normalization and reference tissue for quantitative [68Ga]Ga-Pentixafor PET/CT analysis

Shijie Tang, Hongyu Yang, Yanggang Liu, Zhanwen Huang et al.
EJNMMI Research
Medical Imaging Techniques and Applications
article

Selection of SUV normalization and reference tissue for quantitative [68Ga]Ga-Pentixafor PET/CT analysis

Shijie Tang, Hongyu Yang, Yanggang Liu, Zhanwen Huang, Ranbie Tang, Yue Chen, Lin Qiu
article en

Abstract

[68Ga]Ga-Pentixafor PET/CT enables visualization of C-X-C chemokine receptor 4 expression, but quantitative accuracy depends on standardized uptake value (SUV) normalization and reference tissue selection. Body composition and variability across candidate organs may confound SUV interpretation.We retrospectively analyzed [68Ga]Ga-Pentixafor PET/CT scans from 40 patients without malignancy. Regions of interest were placed in the blood pool, liver, spleen, bone marrow, and muscle. Three SUV were calculated: SUV normalized by body weight (SUVbw) and SUV normalized by lean body mass (SUL), the latter derived using two methods—the conventional James formula and the Janmahasatian (Janma) formula, a revised method optimized for obese individuals. Correlations with body weight were quantified using Spearman correlation coefficients and the slope-to-intercept ratio (a/b) from linear regression analyses, while interobserver reproducibility and variability were evaluated using the intraclass correlation coefficient (ICC) and the coefficient of quartile variation (CQV), respectively. This study aimed to identify an optimal normalization strategy and reliable reference tissue for quantitative [68Ga]Ga-Pentixafor PET/CT. SUVmean, SULmean-James, and SULmean-Janma exhibited significant body-weight dependence in all candidate tissues except muscle, with the strongest association observed in the liver (right liver lobe: ρ = 0.635, 0.576, and 0.650, respectively). Compared with SUVbw, SUL derived from the James formula effectively reduced body-weight-related fluctuations in SUV measurements: a/b decreased from 0.065 to 0.034 in the right liver lobe, 0.036 to 0.021 in the left liver lobe, and 0.076 to 0.037 in the spleen. Across all normalization methods, SUV measurements demonstrated good repeatability in all candidate reference tissues (ICC > 0.7). Variability analysis showed that the liver and blood pool yielded the lowest dispersion for both SUVmean and SULmean-James (CQV: 9.4%-16.8%), identifying them as the most stable reference tissues. In contrast, splenic uptake exhibited substantial inter-individual variability (CQV: 19.9%-22.2%), suggesting it is unsuitable as a routine reference tissue. SUL-James normalization, together with the liver or blood pool as reference tissues, provides robust and reproducible quantification for [68Ga]Ga-Pentixafor PET/CT. These findings support standardized imaging frameworks and may facilitate treatment response evaluation, prognostic assessment, and harmonization across centers.

EJNMMI ResearchVol. 16(1)
Target (United States) (US), Southwest Medical University (CN), Affiliated Hospital of Southwest Medical University (CN), Huzhou Vocational and Technical College (CN), First Affiliated Hospital of Sichuan Medical University (CN)
Openalex Percentile: Top 98%
Medical Imaging Techniques and Applications
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