Development and clinical validation of CT-based regional modified Centiloid method for amyloid PET.

BACKGROUND: The standard Centiloid (CL) method was proposed to harmonize and quantify global 18F-labeled amyloid beta (Aß) PET ligands using MRI as an anatomical reference. However, there is need for harmonizing and quantifying regional Aß uptakes between ligands using CT as an anatomical reference. In the present study, we developed and validated a CT-based regional direct comparison of 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) Centiloid (rdcCL). METHODS: For development of MRI-based or CT-based rdcCLs, the cohort consisted of 63 subjects (20 young controls (YC) and 18 old controls (OC), and 25 participants with Alzheimer's disease dementia (ADD)). We performed a direct comparison of the FMM-FBB rdcCL method using MRI and CT images to define a common target region and the six regional VOIs of frontal, temporal, parietal, posterior cingulate, occipital, and striatal regions. Global and regional rdcCL scales were compared between MRI-based and CT-based methods. For clinical validation, the cohort consisted of 2245 subjects (627 CN, 933 MCI, and 685 ADD). RESULTS: Both MRI-based and CT-based rdcCL scales showed that FMM and FBB were highly correlated with each other, globally and regionally (R2 = 0.96~0.99). Both FMM and FBB showed that CT-based rdcCL scales were highly correlated with MRI-based rdcCL scales (R2 = 0.97~0.99). Regarding the absolute difference of rdcCLs between FMM and FBB, the CT-based method was not different from the MRI-based method, globally or regionally (p value = 0.07~0.95). In our clinical validation study, the global negative group showed that the regional positive subgroup had worse neuropsychological performance than the regional negative subgroup (p < 0.05). The global positive group also showed that the striatal positive subgroup had worse neuropsychological performance than the striatal negative subgroup (p < 0.05). CONCLUSIONS: Our findings suggest that it is feasible to convert regional FMM or FBB rdcSUVR values into rdcCL scales without additional MRI scans. This allows a more easily accessible method for researchers that can be applicable to a variety of different conditions.

Predicting conversion of brain ß-amyloid positivity in amyloid-negative individuals.

BACKGROUND: Cortical deposition of ß-amyloid (Aß) plaque is one of the main hallmarks of Alzheimer's disease (AD). While Aß positivity has been the main concern so far, predicting whether Aß (-) individuals will convert to Aß (+) has become crucial in clinical and research aspects. In this study, we aimed to develop a classifier that predicts the conversion from Aß (-) to Aß (+) using artificial intelligence. METHODS: Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort regarding patients who were initially Aß (-). We developed an artificial neural network-based classifier with baseline age, gender, APOE ε4 genotype, and global and regional standardized uptake value ratios (SUVRs) from positron emission tomography. Ten times repeated 10-fold cross-validation was performed for model measurement, and the feature importance was assessed. To validate the prediction model, we recruited subjects at the Samsung Medical Center (SMC). RESULTS: A total of 229 participants (53 converters) from the ADNI dataset and a total of 40 subjects (10 converters) from the SMC dataset were included. The average area under the receiver operating characteristic values of three developed models are as follows: Model 1 (age, gender, APOE ε4) of 0.674, Model 2 (age, gender, APOE ε4, global SUVR) of 0.814, and Model 3 (age, gender, APOE ε4, global and regional SUVR) of 0.841. External validation result showed an AUROC of 0.900. CONCLUSION: We developed prediction models regarding Aß positivity conversion. With the growing recognition of the need for earlier intervention in AD, the results of this study are expected to contribute to the screening of early treatment candidates.

Prognostic value of amyloid PET scan in normal pressure hydrocephalus.

Amyloid positron emission tomography ([18F] florbetaben (FBB) PET) can be used to determine concomitant Alzheimer's disease (AD) in idiopathic normal pressure hydrocephalus (iNPH) patients. FBB PET scans and the tap test were performed in 31 patients with clinically suspected iNPH, and amyloid positive (iNPH/FBB+) and negative (iNPH/FBB-) groups were compared with respect to clinical characteristics. We evaluated prognostic value of FBB PET scans by analyzing the response to the tap test using a linear mixed model. We also performed a multivariable regression analysis to investigate whether amyloid PET positivity can predict the positive tap test response independent of other AD biomarkers. The results showed that the iNPH/FBB+ group (7/31, 22.6%) had a higher percentage of APOE4 carriers, lower Aß42, higher CSF t-tau, and p-tau/Aß42 ratio than the iNPH/FBB- group (24/31, 77.4%), while the two groups did not differ in imaging characteristics. The iNPH/FBB- group had a higher percentage of tap responders and showed a greater improvement in gait scores after the tap test than the iNPH/FBB+ group (group-tap test effect interaction, p = 0.035). A multivariable logistic regression analysis showed that amyloid positivity on PET scans (OR 0.03, p = 0.029) and CSF p-tau (OR 0.87, p = 0.044) were independently associated with the positive tap test response. Among 21 tap responders in the iNPH/FBB- group, 14 patients received shunt surgery and 12/14 (85.7%) patients showed symptom improvement. Our findings suggest that amyloid PET scans can help determine which iNPH patients will benefit from shunt surgery by discriminating concomitant AD.