Anatomical accuracy of interactive and automated rigid registration between X-ray CT and FDG-PET

Comparison of anatomical accuracy of software-based interactive (IRR) and automated rigid registration (ARR) of separately acquired CT and FDG-PET data sets.

Independently acquired PET and helical CT data from 22 tumour patients were registered manually using the Syngo advanced Fusion VC20H tool. IRR was performed separately for the thorax and the abdomen using physiological FDG uptake in several organs as a reference. In addition, ARR was performed with the commercially available software tool Mirada 7D on all of the patients. For both methods, the distances between the representation of 53 malignant lesions on PET and CT were measured in X-, Y-, and Z-direction with reference to a common coordinate system (X-, Y-, Z-distances).

The percentage of lesions misregistered by less than 1.5 cm was in X-direction 91% for IRR and 89% for ARR; in Y-direction 85% and 68%; in Z-direction 72% and 51%, respectively. The average X-, Y- and Z-distances for IRR ranged from 0.58 +/- 0.55 cm (X-direction) to 1.17 +/- 1.66 cm (Z-direction). For ARR, the average X-, Y- and Z-distances varied between 0.66 +/- 0.61 cm (X-direction) and 1.81 +/- 1.37 cm (Z-direction). Mixed effects analysis of the absolute X-, Y- and Z-distances revealed a significantly better alignment for IRR compared to ARR in Z-direction (p < 0.01). Lesion size and localization either in thorax or abdomen had no significant influence on the accuracy of registration.

For the majority of malignant lesions, manual image registration with the possibility to separately align different body segments was more accurate than the automated approach. Current software for ARR does not reach the anatomical accuracy reported for PET/CT hybrid scanners.