Feasibility and performance of novel software to quantify metabolically active volumes and 3D partial volume corrected SUV and metabolic volumetric products of spinal bone marrow metastases on ¹⁸F-FDG-PET/CT.

Our aim was to assess feasibility and performance of novel semi-automated image analysis software called ROVER to quantify metabolically active volume (MAV), maximum standardized uptake value-maximum (SUV_max), 3D partial volume corrected mean SUV (cSUV_mean), and 3D partial volume corrected mean MVP (cMVP_mean) of spinal bone marrow metastases on fluorine-18 fluorodeoxyglucose-positron emission tomography/computerized tomography (¹⁸F-FDG-PET/CT). We retrospectively studied 16 subjects with 31 spinal metastases on FDG-PET/CT and MRI. Manual and ROVER determinations of lesional MAV and SUV_max, and repeated ROVER measurements of MAV, SUV_max, cSUV_mean and cMVP_mean were made. Bland-Altman and correlation analyses were performed to assess reproducibility and agreement. Our results showed that analyses of repeated ROVER measurements revealed MAV mean difference (D)=-0.03±0.53cc (95% CI(-0.22, 0.16)), lower limit of agreement (LLOA)=-1.07cc, and upper limit of agreement (ULOA)=1.01cc; SUV_max D=0.00±0.00 with LOAs=0.00; cSUV_mean D=-0.01±0.39 (95% CI(-0.15, 0.13)), LLOA=-0.76, and ULOA=0.75; cMVP_mean D=-0.52±4.78cc (95% CI(-2.23, 1.23)), LLOA=-9.89cc, and ULOA=8.86cc. Comparisons between ROVER and manual measurements revealed volume D= -0.39±1.37cc (95% CI (-0.89, 0.11)), LLOA=-3.08cc, and ULOA=2.30cc; SUV_max D=0.00±0.00 with LOAs=0.00. Mean percent increase in lesional SUV_mean and MVP_mean following partial volume correction using ROVER was 84.25±36.00% and 84.45±35.94% , respectively. In conclusion, it is feasible to estimate MAV, SUV_max, cSUV_mean, and cMVP_mean of spinal bone marrow metastases from ¹⁸F-FDG-PET/CT quickly and easily with good reproducibility via ROVER software. Partial volume correction is imperative, as uncorrected SUV_mean and MVP_mean are significantly underestimated, even for large lesions. This novel approach has great potential for practical, accurate, and precise combined structural-functional PET quantification of disease before and after therapeutic intervention.