Going against the norm: validation of a novel alternative to brain SPECT normative datasets

Aim: Quantitative analysis of brain single photon emission computed tomography (SPECT) perfusion imaging is dependent on normative datasets that are challenging to produce. This study investigated the combination of SPECT neuroimaging from a large clinical population rather than small numbers of controls. The authors hypothesized this "population template"would demonstrate noninferiority to a control dataset, providing a viable alternative for quantifying perfusion abnormalities in SPECT neuroimaging. Methods: A total of 2, 068 clinical SPECT scans were averaged to form the "population template". Validation was three-fold. First, the template was imported into SPECT brain analysis software, MIMneuro®, and compared against its control dataset of 90 individuals through its region and cluster analysis tools. Second, a cohort of 100 cognitively impaired subjects was evaluated against both the population template and MIMneuro®'s normative dataset to compute region-based metrics. Concordance and intraclass correlation coefficients, mean square deviations, total deviation indices, and limits of agreement were derived from these data to measure agreement and test for noninferiority. Finally, the same patients were clinically read in CereMetrix® to confirm that expected perfusion patterns appeared after comparison to the template. Results: MIMneuro®'s default threshold for normality is ± 1.65 z-score and this served as our noninferiority margin. Direct comparison of the template to controls produced no regions that exceeded this threshold and all clusters identified were far from statistically significant. Agreement measures revealed consistency between the softwares and that CereMetrix® results were noninferior to MIMneuro®, albeit with proportional bias. Visual analysis also confirmed that expected perfusion patterns appeared when individual scans were compared to the population template within CereMetrix®. Conclusions: The authors demonstrated a population template was noninferior to a smaller control dataset despite inclusion of abnormal scans. This suggests that our patient-based population template can serve as an alternative for identifying and quantifying perfusion abnormalities in brain SPECT.