Quantitative PET/CT in clinical practice: assessing the agreement of PET tumor indices using different clinical reading platforms.

OBJECTIVE

The aim of this study was to determine whether various fluorine-18-fluorodeoxyglucose PET/CT-derived parameters used in oncology vary significantly depending on the interpretation software systems used in clinical practice for multiple human solid tumors.

PATIENTS AND METHODS

A total of 120 fluorine-18-fluorodeoxyglucose PET/CT studies carried out in patients with pancreatic, lung, colorectal, and head and neck cancers were evaluated retrospectively on two different vendor software platforms including Mirada and MIMVista. Regions of interest were placed on the liver to determine the liver mean standardized uptake value at lean body mass (SUL) and on each tumor to determine the SULmax, SULpeak. Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) were determined using fixed thresholds of 50% of SULmax and SULpeak. Inter-reader, intersystem intraclass correlations, systematic bias, and variability reflected by the 95% limits of agreement, and precision were determined.

RESULTS

There was excellent inter-reader reliability between the readers and the two software systems, with intraclass correlations more than 0.9 for all PET metrics, with P values less than 0.0001. The bias and SD on Bland-Altman analysis between the two software platforms for tumor SULmax, SULpeak, Max50MTV, and Peak50MTV, respectively, for Reader 1 were -1.52±2.24, 0.80±3.67, -0.80±13.01, and -4.49±20.6. For Reader 2, the biases were -1.62±1.95, 0.18±3.60, -0.27±4.64, and -3.13±8.30. The precision between the two systems was better for SULmax and SULpeak, with less variance observed, than for volume-based metrics such as Max50MTV and Peak50MTV or TLG.

CONCLUSION

Excellent correlation has been found between two tested software reading platforms for all PET-derived metrics in a dual-reader analysis. Overall, the SULmax and SULpeak values had less bias and better precision compared with the MTV and TLG.