Background: The introduction of quantitative SPECT/CT allows more objective assessments of tracer accumulation in SPECT. However standardized uptake values (SUV) still do not play a big role for orthopedic or oncologic questions. With a more reliable normalization, the use of quantitative measures might also be of use for a more objective assessment of lesions. We retrospectively included patients that received a quantitative [Tc]-HDP bone SPECT/CT scan of the lumbar spine for 4 body weight (BW) categories. Measurements of bone activity (kBq/cc) and bone density in Hounsfield Units (HU) in a standard volume of interest in the femur, the first and the fifth lumbar vertebra of all patients, without active disease within these regions was made. Correlations between tracer uptake and clinical parameters (BW, height, age, gender) were assessed with a multiple regression and based on the model coefficients, a correction formula was calculated and applied.

Results: The strongest correlation between measured activity in L1 and patient parameters was found for BW (r= -0.64, p < 0.001), compared to height (r = -0.28, p = 0.002) and age (r = -0.34, p = 0.001). Furthermore, there was a weak positive correlation between tracer accumulation and bone density (r: 0.35, p < 0.001). Using standard normalization with BW there was a very weak positive correlation between SUV at L1 and BW with a slight overestimation in heavier subjects (r = 0.15, p = 0.09). The calculated correction based on the multiple regression of activity as dependent variable, and weight, age and bone density as significant predictors resulted in more robust uptake values with non-significant associations to BW, height, age or density. However, there was still a wide interindividual range of values for normalized bone activity.

Conclusion: Using an age, bone density and weight-based normalization significantly decreased the interindividual variability of normal uptake on quantitative SPECT/CT compared to the regularly used BW adjusted SUV. However, a generalized normalization is difficult in the presence of strong patient effects, not attributable to the measured clinical variables.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11576713PMC
http://dx.doi.org/10.1186/s13550-024-01167-6DOI Listing

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