The aim of this study was to retrospectively investigate the impact of the number of iterations performed during OSEM reconstruction on the sensitivity and specificity of 18F-FDG PET for predicting surgical candidacy and surgical outcomes in TLE. This was done with a blinded reader study comparing two OSEM reconstructions, differing in the number of iterations performed. The ability of 18F-FDG PET to predict surgical candidacy was evaluated with a ROC analysis of the two reconstructions, and the sensitivities of the two reconstructions for predicting surgical outcomes were compared. In the cases studied here, the number of iterations performed during OSEM reconstruction had no statistically significant impact on the sensitivity and specificity of 18F-FDG PET for predicting surgical candidacy, or its sensitivity for predicting surgical outcome. The nuclear medicine physicians’ interpretations of the PET studies were essentially unchanged by the different reconstructions, illustrated by the consistency with which they interpreted the images between the two reconstructions studied. Therefore using physician preference to determine reconstruction parameters seems justified and acceptable in this case. These results should be tempered by the limited statistical power of our data.
The hypometabolic regions identified by nuclear medicine physicians tended to be more global decreases in FDG uptake in the temporal lobe (). Smaller lesions may not have been identified in either reconstruction, as they may have remained too blurred in the original reconstructions, and obscured by noise in the reconstructions with more iterations. It is possible that reconstructing with a number of iterations between 2 and 5 would be more optimal and would result in a better trade-off between image sharpness and noise variance.
We did not consider partial volume correction methods that aim to increase image sharpness while suppressing noise to improve the identification of small hypometabolic regions on 18
F-FDG-PET or on SPECT studies [5
]. Such methods are not yet available as clinical tools, whereas changing the number of iterations used in OSEM reconstructions can readily be performed and therefore may have a more immediate impact. Given that our results do not indicate any benefit to using the sharper but noisier images obtained with more iterations, more advanced partial volume correction methods might be needed to identify smaller regions of hypometabolism. However, if physicians rely on identifying a pattern of globally reduced 18
F-FDG uptake, such methods may make little difference in subjective interpretation. If this is the case, one of the more objective methods of detecting small regions of hypometabolism might be required [20
We have focused on the number of iterations performed during OSEM reconstruction in order to study the tradeoff between bias and variance (resolution and noise in this case), but there are a number of other factors that will influence resolution and noise. The most notable extraneous factors in this study are the two PET cameras that were used, the GE Advance and the Discovery VCT, and the different acquisitions and reconstruction used for each scanner, 2D acquisition with 2D OSEM reconstruction for the Advance and a shorter 3D acquisition with 3D OSEM reconstruction using more subsets (35 versus 28) for the Discovery VCT (). The overall impact of these differences on the images from the two scanners is difficult to determine. The 3D acquisition and reconstruction of the Discovery VCT images should result in better noise properties in the images, but this may be offset by the shorter acquisition time. Likewise, the greater number of subsets used during reconstruction should give sharper images for the same number of iterations, though image sharpness is also likely influenced by the 3D acquisition. We do not attempt to address each of these issues, but instead try and focus only on the impact of iteration number by demonstrating that excluding the Discovery VCT scans does not significantly alter the results. In addition, the smooth, clinically standard reconstructions from the two scanners are qualitatively closer to each other in their resolution and noise properties than to the corresponding sharper reconstructions ().
All reconstructions used for PET imaging have parameters that will affect the tradeoff between bias and variance. While these parameters are frequently determined by physician and institutional preference, it is possible that they could have an impact on diagnostic outcomes. Our investigation here indicates that this may not be the case with OSEM reconstructions of 18F-FDG PET images acquired for the diagnosis of TLE, as we found little difference between the two reconstructions studied. Our results are limited by their statistical power, by extraneous variables such as the two PET cameras used, and in that we only examined two possible numbers of iterations. However, the consistency with which the readers interpreted the images indicates that a substantial number of scans would have to be read to identify any difference between reconstructions. Different reconstruction parameters, such as an intermediate number of iterations between 2 and 5, may have made a greater impact on the interpretation of scans, but the consistency of the interpretations makes this unlikely as well. If changing the number of iterations performed in reconstruction had potential to change interpretations, less consistency would be expected in the data presented here, even if the area under the ROC curves and the sensitivities are nearly equivalent. As such it appears perfectly reasonable to use images that nuclear medicine physicians are most familiar and comfortable with. Nevertheless, such studies could be helpful in validating and optimizing the reconstruction and image processing methods used in different clinical imaging tasks. And in the case of 18F-FDG PET for the diagnosis of TLE a more rigorous study could be performed with more patients and varying more reconstruction parameters to validate the results presented here.