Evaluation of SUVlean consistency in FDG and PSMA PET/MR with Dixon-, James-, and Janma-based lean body mass correction
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Abstract
Purpose: To systematically evaluate the consistency of various standardized uptake value (SUV) lean body mass (LBM) normalization methods in a clinical positron emission tomography/magnetic resonance imaging (PET/MR) setting. Methods: SUV of brain, liver, prostate, parotid, blood, and muscle were measured in 90 18 F-FDG and 28 18 F-PSMA PET/MR scans and corrected for LBM using the James, Janma (short for Janmahasatian), and Dixon approaches. The prospective study was performed from December 2018 to August 2020 at Shanghai East Hospital. Forty dual energy X-ray absorptiometry (DXA) measurements of non-fat mass were used as the reference standard. Agreement between different LBM methods was assessed by linear regression and Bland-Altman statistics. SUV’s dependency on BMI was evaluated by means of linear regression and Pearson correlation. Results: Compared to DXA, the Dixon approach presented the least bias in LBM/weight% than James and Janma models (bias 0.4±7.3%, − 8.0±9.4%, and − 3.3±8.3% respectively). SUV normalized by body weight (SUVbw) was positively correlated with body mass index (BMI) for both FDG (e.g., liver: r = 0.45, p < 0.001) and PSMA scans ( r = 0.20, p = 0.31), while SUV normalized by lean body mass (SUVlean) revealed a decreased dependency on BMI ( r = 0.22, 0.08, 0.14, p = 0.04, 0.46, 0.18 for Dixon, James, and Janma models, respectively). The liver SUVbw of obese/overweight patients was significantly larger ( p < 0.001) than that of normal patients, whereas the bias was mostly eliminated in SUVlean. One-way ANOVA showed significant difference ( p < 0.001) between SUVlean in major organs measured using Dixon method vs James and Janma models. Conclusion: Significant systematic variation was found using different approaches to calculate SUVlean. A consistent correction method should be applied for serial PET/MR scans. The Dixon method provides the most accurate measure of LBM, yielding the least bias of all approaches when compared to DXA.
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[18F]FDG-PET SUV is more closely correlated with BMI than PSMA-PET SUV.
“However, when compared to SUV in prostate-specific membrane antigen (PSMA)-PET, those in [18F]FDG-PET are more closely correlated with BMI [5].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [5]
The Results section (‘Liver SUV among four BMI subgroups’; page unavailable) reports a significant positive association between BMI and body-weight-normalized liver SUV in the FDG group. The Discussion (page unavailable) says SUV–BMI correlations in the PSMA group were not statistically significant for most organs, except the blood pool. These findings support a narrower comparison, but not the unqualified claim that FDG-PET SUV is more closely correlated with BMI than PSMA-PET SUV across sites or SUV measures. (LLM, conf=0.78)
Experimental — accuracy not yet measuredThe correlation between SUV and BMI can be partly explained mathematically by incorrect estimation of distribution volume in obese patients if total body mass is used instead of lean body mass.
“This correlation can be partly explained mathematically by the incorrect estimation of the distribution volume in obese patients if total body mass is used instead of lean body mass (due to the relatively low [18F]FDG accumulation in fat tissue [4]) [5].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [5]
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Cites
From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors
Wahl, R. L., Jacene, H., Kasamon, Y., & Lodge, M. A. (2009) · Journal of Nuclear Medicine · doi:10.2967/jnumed.108.057307 · Cited by 3,777 · see citing works
Functional Brown Adipose Tissue in Healthy Adults
Virtanen, K. A., Lidell, M. E., Orava, J., Heglind, M., Westergren, R., Niemi, T., Taittonen, M., Laine, J., Savisto, N.-J., Enerbäck, S., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0808949 · Cited by 3,058 · see citing works
Simple proton spectroscopic imaging.
Dixon, W. T. (1984) · Radiology · doi:10.1148/radiology.153.1.6089263 · Cited by 2,261 · see citing works
Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index
Gallagher, D., Heymsfield, S. B., Heo, M., Jebb, S. A., Murgatroyd, P. R., & Sakamoto, Y. (2000) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/72.3.694 · Cited by 2,139 · see citing works
Mazess, R., Barden, H. S., Bisek, J., & Hanson, J. (1990) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/51.6.1106 · Cited by 1,465 · see citing works
Quantification of Lean Bodyweight
Janmahasatian, S., Duffull, S. B., Ash, S., Ward, L. C., Byrne, N. M., & Green, B. (2005) · Clinical Pharmacokinetics · doi:10.2165/00003088-200544100-00004 · Cited by 902 · see citing works
The applications of PET in clinical oncology.
Strauss, L. G., & Conti, P. S. (1991) · PubMed · Cited by 844 · see citing works
Zasadny, K. R., & Wahl, R. L. (1993) · Radiology · doi:10.1148/radiology.189.3.8234714 · Cited by 633 · see citing works
Advanced Body Composition Assessment: From Body Mass Index to Body Composition Profiling
Borga, M., West, J., Bell, J. D., Harvey, N. C., Romu, T., Heymsfield, S. B., & Leinhard, O. D. (2018) · Journal of Investigative Medicine · doi:10.1136/jim-2018-000722 · Cited by 626 · see citing works
Metal-Induced Artifacts in MRI
Hargreaves, B. A., Worters, P. W., Pauly, K. B., Pauly, J. M., Koch, K. M., & Gold, G. E. (2011) · American Journal of Roentgenology · doi:10.2214/ajr.11.7364 · Cited by 559 · see citing works
Prospective investigation of positron emission tomography in lung nodules.
Lowe, V. J., Fletcher, J. W., Gobar, L. S., Lawson, M. A., Kirchner, P. T., Valk, P. E., Karis, J. P., Hübner, K. F., Delbeke, D., Heiberg, E. V., et al. (1998) · Journal of Clinical Oncology · doi:10.1200/jco.1998.16.3.1075 · Cited by 547 · see citing works
YEUNG, H. W. D., Grewal, R. K., Gönen, M., Schöder, H. M., & Larson, S. M. (2003) · PubMed · Cited by 370 · see citing works
In vivo validation of whole body composition estimates from dual-energy X-ray absorptiometry
Prior, B. M., Cureton, K. J., Modlesky, C. M., Evans, E. M., Sloniger, M. A., Saunders, M., & Lewis, R. D. (1997) · Journal of Applied Physiology · doi:10.1152/jappl.1997.83.2.623 · Cited by 317 · see citing works
Sugawara, Y., Zasadny, K. R., Neuhoff, A. W., & Wahl, R. L. (1999) · Radiology · doi:10.1148/radiology.213.2.r99nv37521 · Cited by 265 · see citing works
Hoekstra, C. J., Paglianiti, I., Hoekstra, O. S., Smit, E. F., Postmus, P. E., Teule, G. J. J., & Lammertsma, A. A. (2000) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s002590050570 · Cited by 248 · see citing works
Kim, C. K., Gupta, N. C., Chandramouli, B., & Alavi, A. A. (1994) · PubMed · Cited by 229 · see citing works
Karlsson, A., Rosander, J., Romu, T., Tallberg, J., Grönqvist, A., Borga, M., & Leinhard, O. D. (2014) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24726 · Cited by 215 · see citing works
Neeland, I. J., Grundy, S. M., Li, X., ADAMS-HUET, B. A., & Vega, G. L. (2016) · Nutrition and Diabetes · doi:10.1038/nutd.2016.28 · Cited by 140 · see citing works
Gallium 68 PSMA-11 PET/MR Imaging in Patients with Intermediate- or High-Risk Prostate Cancer
Park, S. Y., Zacharias, C., Harrison, C. M., Fan, R. E., Kunder, C. A., Hatami, N., Giesel, F. L., Ghanouni, P., Daniel, B. L., Loening, A. M., et al. (2018) · Radiology · doi:10.1148/radiol.2018172232 · Cited by 130 · see citing works
James, W. P. T. (1977) · Nutrition Bulletin · doi:10.1111/j.1467-3010.1977.tb00966.x · Cited by 129 · see citing works
Optimum Lean Body Formulation for Correction of Standardized Uptake Value in PET Imaging
Tahari, A. K., Chien, D. C., Azadi, J. R., & Wahl, R. L. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.136986 · Cited by 123 · see citing works
Antibiotic Utilization Trends in Two State Hospitals of Mongolia from 2013 to 2017
Dorj, G., Blix, H. S., Sunderland, B., Gankhulug, B., Tegshee, O., Purevkhuu, M., Shirnen, G., Sanjjav, T., Dorj, G., & Gendenragchaa, B. (2019) · BioMed Research International · doi:10.1155/2019/9160296 · Cited by 114 · see citing works
Segmentation and quantification of adipose tissue by magnetic resonance imaging
Hu, H. H., Chen, J., & Shen, W. (2016) · Magnetic Resonance Materials in Physics, Biology and Medicine · doi:10.1007/s10334-015-0498-z · Cited by 90 · see citing works
Revisiting Weight-Normalized SUV and Lean-Body-Mass–Normalized SUV in PET Studies
Sarikaya, İ., Albatineh, A. N., & Sarıkaya, A. (2019) · Journal of Nuclear Medicine Technology · doi:10.2967/jnmt.119.233353 · Cited by 72 · see citing works
Menda, Y., Bushnell, D. L., Madsen, M. T., McLaughlin, K. A., Kahn, D. J., & Kernstine, K. H. (2001) · Nuclear Medicine Communications · doi:10.1097/00006231-200110000-00004 · Cited by 58 · see citing works
Erselcan, T., Turgut, B., Doğan, D. Ö., & Özdemir, S. (2002) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-002-0974-3 · Cited by 44 · see citing works
Summary of the First ISMRM–SNMMI Workshop on PET/MRI: Applications and Limitations
Hope, T. A., Fayad, Z. A., Fowler, K. J., Holley, D., Iagaru, A. H., McMillan, A. B., Veit-Haiback, P., Witte, R. J., Zaharchuk, G., & Catana, C. (2019) · Journal of Nuclear Medicine · doi:10.2967/jnumed.119.227231 · Cited by 42 · see citing works
Ulbrich, E. J., Nanz, D., Leinhard, O. D., Marcon, M., & Fischer, M. A. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26676 · Cited by 38 · see citing works
Evaluation of SUV normalized by lean body mass (SUL) in 68Ga-PSMA11 PET/CT: a bi-centric analysis
Gafita, A., Calais, J., Franz, C., Rauscher, I., Wang, H., Roberstson, A., Czernin, J. G., Weber, W., & Eiber, M. (2019) · EJNMMI Research · doi:10.1186/s13550-019-0572-z · Cited by 29 · see citing works
Ruiz‐Orta, C., Fernandéz‐Blázquez, J. P., Pereira, E., & Alamo, R. G. (2011) · Polymer · doi:10.1016/j.polymer.2011.04.018 · Cited by 29 · see citing works
Liu, G., Cao, T., Hu, L., Zheng, J., Pang, L., Hu, P., Gu, Y., & Shi, H. (2019) · BioMed Research International · doi:10.1155/2019/8213215 · Cited by 27 · see citing works
Self-citationChan, T. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.089292 · Cited by 23 · see citing works
Vriens, D., de Geus‐Oei, L., van Laarhoven, H. W. M., Timmer-Bonte, J. N. H., Krabbe, P. F. M., Visser, E. P., & Oyen, W. J. G. (2009) · Nuclear Medicine Communications · doi:10.1097/mnm.0b013e32832bdc80 · Cited by 20 · see citing works
Kim, W. H., Kim, C. G., & Kim, D. (2012) · Nuclear Medicine and Molecular Imaging · doi:10.1007/s13139-012-0146-8 · Cited by 20 · see citing works
Rausch, I., Rust, P., DiFranco, M. D., Lassen, M. L., Stadlbauer, A., Mayerhoefer, M. E., Hartenbach, M., Hacker, M., & Beyer, T. (2016) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.168294 · Cited by 19 · see citing works
Decazes, P., Métivier, D., Rouquette, A., Talbot, J., & Kerrou, K. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.164913 · Cited by 16 · see citing works
Multimedia Communications Technology in Diagnostic Imaging
McGarty, T. P. (1991) · Investigative Radiology · doi:10.1097/00004424-199104000-00018 · Cited by 14 · see citing works
Jochimsen, T. H., Schulz, J., Busse, H., Werner, P., Schaudinn, A., Zeisig, V., Kurch, L., Seese, A., Barthel, H., Sattler, B., et al. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/12/4651 · Cited by 13 · see citing works
Devriese, J., Beels, L., Maes, A. F., Wiele, C. V. D., Gheysens, O. S., & Pottel, H. (2016) · PubMed · Cited by 11 · see citing works
Halsne, T., Müller, E. G., Spiten, A.-E., Sherwani, A. G., Mikalsen, L. T. G., Revheim, M.-E. R., & Stokke, C. (2018) · Journal of Nuclear Medicine Technology · doi:10.2967/jnmt.117.204586 · Cited by 9 · see citing works
Evaluation of CT-based SUV normalization
Devriese, J., Beels, L., Maes, A., de Wiele, C. V., & Pottel, H. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/17/6369 · Cited by 9 · see citing works
The knowledge base for nuclear cardiology training
Cerqueira, M. D., & Wackers, F. J. T. (1994) · Journal of Nuclear Cardiology · doi:10.1007/bf02940018 · Cited by 9 · see citing works
Narita, A., Shiomi, S., Katayama, Y., Yamanaga, T., Daisaki, H., Hamada, K., & Watanabe, Y. (2016) · Radiological Physics and Technology · doi:10.1007/s12194-016-0346-5 · Cited by 7 · see citing works
Webber, C. E. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1788-1_8 · Cited by 7 · see citing works
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Influences on PET Quantification and Interpretation
Rogasch, J. M. M., Hofheinz, F., van Heek, L., Voltin, C.-A., Boellaard, R., & Kobe, C. (2022) · Diagnostics · doi:10.3390/diagnostics12020451 · Cited by 50 · see citing works
“In a number of normal organs, the SUV corrected for body mass is positively correlated with the body mass index (BMI) [1–3].”
BackgroundInfluentialWhole-body tumor burden in PET/CT expert review
dos Santos, D. F., Takahashi, M. E. S., Camacho, M., Lima, M., Amorim, B. J., ROHREN, E. M., & Etchebehere, E. (2022) · Clinical and Translational Imaging · doi:10.1007/s40336-022-00517-5 · Cited by 8 · see citing works
Zamanian, A., Rousseau, É., Buteau, F.-A., Arsenault, F., Beaulieu, A., April, G., Juneau, D., Plouznikoff, N., Turcotte, É. E., Allard, C., et al. (2025) · Cancer Imaging · doi:10.1186/s40644-025-00910-z · Cited by 6 · see citing works
Dosing Therapeutic Radiopharmaceuticals in Obese Patients
van Nuland, M., Ververs, T. F., & Lam, M. G. E. H. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23020818 · Cited by 5 · see citing works
Fenner, J., Samim, M., Raad, R. A., Shankar, D. S., & Burke, C. J. (2025) · Clinical Imaging · doi:10.1016/j.clinimag.2025.110437 · Cited by 2 · see citing works
Ahmed, M., Gandhi, O. H., Singh, S. B., Gujral, J., Park, P. K., Shrestha, B., Niazi, S. K., Ismoilov, M., Motamedi, N., Werner, T. J., et al. (2025) · Nuclear Medicine Communications · doi:10.1097/mnm.0000000000002038 · Cited by 2 · see citing works
Impact of Uptake Period on 18F-DCFPyL-PSMA PET/CT Maximum Standardised Uptake Value
Nassour, A., Jain, A., Khanani, H., Hui, N., Thompson, N. J., Sørensen, B., Baskaranathan, S., Bergersen, P., Chalasani, V., Dean, T., et al. (2025) · Cancers · doi:10.3390/cancers17060960 · Cited by 1 · see citing works
Correction of Intensity of Bone Involvement (IBI) Index by Lean Body Mass and Body Surface Area
Santos, G. M. B. J., Takahashi, M. E. S., Mosci, C., SOUZA, S. R. S. D., Souza, C. A. D., Lorand-Metze, I. G. H., Carvalheira, J. B. C., & Ramos, C. D. (2024) · Revista Brasileira de Física Médica · doi:10.29384/rbfm.2024.v18.19849001754
Zhang, N., Huo, L., Zhang, Y., Yu, L., & Wang, H. (2023) · Digital Medicine · doi:10.1097/dm-2023-00018
Liu, Y., Tang, R., Yang, H., Tang, S.-J., Chen, Y., Huang, Z.-W., & Qiu, L. (2026) · EJNMMI Research · doi:10.1186/s13550-025-01370-z
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Mou, T., Lin, Y., Fan, F., Huang, J., Sun, T., Liu, E.-T., & Gao, Y. (2026) · Phenomics · doi:10.1007/s43657-025-00289-8
Sanghera, B., Lowe, G. J., Sanghera, S., & Wong, W. (2026) · Journal of Medical Physics · doi:10.4103/jmp.jmp_56_26
- Authors
- Zhao, J., Xue, Q., Chen, X., You, Z., Wang, Z., Yuan, J., Liu, H., & Hu, L.
- Affiliations
- Tongji University (CN)
- United Imaging Healthcare (China) (CN)
- Corresponding author
- Zhao, Jun
- Venue
- EJNMMI Physics
- Published
- 2021-02-17
- Volume
- 8
- Issue
- 1
- Pages
- 17-17
- ISSN
- 2197-7364 (ISSN-L)
- PMC
- PMC7889776
- OpenAlex
- W3102510319
- Cited by
- 12
- References
- 44
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 1 · 2023: 1 · 2022: 3
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- EJNMMI Physics (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Key Specialty Construction Project of Pudong Health and Family Planning Commission of Shanghai (PWZzk2017-24)
- Project of Science and Technology Commission of Shanghai Municipality (19DZ1930703)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiopharmaceutical Chemistry and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- standardized uptake value, PET/MR, FDG-PET, PSMA PET, Dixon method, body mass index, obesity, liver SUV, dual-energy X-ray absorptiometry
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