Evaluation of CT-based SUV normalization

Evaluation of SUVlean consistency in FDG and PSMA PET/MR with Dixon-, James-, and Janma-based lean body mass correction

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 18F-FDG and 28 18F-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.

Patient-specific lean body mass can be estimated from limited-coverage computed tomography images

OBJECTIVE

In PET/CT, quantitative evaluation of tumour metabolic activity is possible through standardized uptake values, usually normalized for body weight (BW) or lean body mass (LBM). Patient-specific LBM can be estimated from whole-body (WB) CT images. As most clinical indications only warrant PET/CT examinations covering head to midthigh, the aim of this study was to develop a simple and reliable method to estimate LBM from limited-coverage (LC) CT images and test its validity.

PATIENTS AND METHODS

Head-to-toe PET/CT examinations were retrospectively retrieved and semiautomatically segmented into tissue types based on thresholding of CT Hounsfield units. LC was obtained by omitting image slices. Image segmentation was validated on the WB CT examinations by comparing CT-estimated BW with actual BW, and LBM estimated from LC images were compared with LBM estimated from WB images. A direct method and an indirect method were developed and validated on an independent data set.

RESULTS

Comparing LBM estimated from LC examinations with estimates from WB examinations (LBMWB) showed a significant but limited bias of 1.2 kg (direct method) and nonsignificant bias of 0.05 kg (indirect method).

CONCLUSION

This study demonstrates that LBM can be estimated from LC CT images with no significant difference from LBMWB.