Background While non-rigid fusion is by definition expected to alter the information of positron emission tomography (PET) data, we assessed whether rigid transformation also influences metabolic tumor volume (MTV) determination. Methods The PET/computed tomography (CT) data of 28 solid pulmonary lesions of 20 tumor patients examined with 18F-Fluordeoxyglucose (FDG) was retrospectively analyzed. The original (OR) hardware-coregistered PET images were fused with contrast-enhanced diagnostic CT (CT1, 1 mm slices) and low dose CT (CT5, 5 mm slices). After automatic rigid transformation (Mirada Fusion7D) using two algorithms (rigid fast (RF), rigid slow (RS)), MTV and maximal standardized uptake value (SUVmax) were determined applying four different segmentation methods with either fixed or background-adapted thresholding and compared to OR-PET data. Results Relative differences in SUVmax compared to OR data revealed no significant differences for RF (median, -0.1%; interquartile range (IQR), -1.1% to 0.9%; p = 0.75) and RS (median, 0.5%; IQR, -0.6% to 1.3%; p = 0.19) in CT1, whereas in CT5 significant deviations were observed for RF (median, -9.0%; IQR, -10.9 to -6.1; p < 0.001) and RS (median, -8.4%; IQR, -11.1 to -5.6; p < 0.001). Relative MTV differences were 0.7% (IQR, -3.0% to 2.7%; p = 0.76) for RF and -1.3% (IQR, -3.6% to 0.9%; p = 0.12) for RS in CT1. Coregistration led to significant MTV differences in RF (median, 10.4%; IQR, 7.4% to 16.7%; p < 0.001) and RS (median, 10.6%; IQR, 5.4% to 17.7%; p < 0.001) in CT5. Conclusions Rigid coregistration of PET data allows a quantitative evaluation with reasonable accuracy in most cases. However, in some cases, it can result in substantial deviations of MTV and SUVmax. Therefore, it is recommended to perform quantitative evaluation in the original PET data rather than in coregistered PET data. © 2013 Steffen et al.
CITATION STYLE
Steffen, I. G., Hofheinz, F., Rogasch, J. M. M., Furth, C., Amthauer, H., & Ruf, J. (2013). Influence of rigid coregistration of PET and CT data on metabolic volumetry: A user’s perspective. EJNMMI Research, 3(1). https://doi.org/10.1186/2191-219X-3-85
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