Combined Evaluation of FDG-PET and MRI Improves Detection and Differentiation of Dementia

Abstract

IntroductionVarious biomarkers have been reported in recent literature regarding imaging abnormalities in different types of dementia. These biomarkers have helped to significantly improve early detection and also differentiation of various dementia syndromes. In this study, we systematically applied whole-brain and region-of-interest (ROI) based support vector machine classification separately and on combined information from different imaging modalities to improve the detection and differentiation of different types of dementia.MethodsPatients with clinically diagnosed Alzheimer's disease (AD: n = 21), with frontotemporal lobar degeneration (FTLD: n = 14) and control subjects (n = 13) underwent both [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) scanning and magnetic resonance imaging (MRI), together with clinical and behavioral assessment. FDG-PET and MRI data were commonly processed to get a precise overlap of all regions in both modalities. Support vector machine classification was applied with varying parameters separately for both modalities and to combined information obtained from MR and FDG-PET images. ROIs were extracted from comprehensive systematic and quantitative meta-analyses investigating both disorders.ResultsUsing single-modality whole-brain and ROI information FDG-PET provided highest accuracy rates for both, detection and differentiation of AD and FTLD compared to structural information from MRI. The ROI-based multimodal classification, combining FDG-PET and MRI information, was highly superior to the unimodal approach and to the whole-brain pattern classification. With this method, accuracy rate of up to 92% for the differentiation of the three groups and an accuracy of 94% for the differentiation of AD and FTLD patients was obtained.ConclusionAccuracy rate obtained using combined information from both imaging modalities is the highest reported up to now for differentiation of both types of dementia. Our results indicate a substantial gain in accuracy using combined FDG-PET and MRI information and suggest the incorporation of such approaches to clinical diagnosis and to differential diagnostic procedures of neurodegenerative disorders.

Molecular neuroimaging with PET/MRI

“…Figure 2 shows a representative case of frontotemporal dementia with concordant PET and MRI data. This finding is consistent with previous literature data [35,36].…”

Diagnostic utility of ASL‐MRI and FDG‐PET in the behavioral variant of FTD and AD

“…The classification accuracies in our study are generally consistent with prior studies using FDG‐PET, which have achieved accuracy rates of around 80–95%. However, it should be noted that most prior studies assessing classification accuracy in FTLD have used a mixed group of FTLD cases, including cases with the semantic and nonfluent variants of primary progressive aphasia (the exception is the European study referenced above12, 50). Therefore, direct comparison of our classification outcomes with those of prior studies must be done with caution.…”

“…Diagnosis of bvFTD remains difficult, with patients being erroneously diagnosed with Alzheimer's disease (AD) or psychiatric disorders 5, 6, 7. A large body of work has demonstrated that brain imaging, in particular structural magnetic resonance imaging (MRI) and functional imaging of cerebral blood flow (CBF) with SPECT or cerebral metabolic rate of glucose (CMRgl) with fluorodeoxyglucose (FDG) positron emission tomography (PET), can improve the accuracy of differential diagnosis in bvFTD 8, 9, 10, 11, 12, 13, 14, 15, 16, 17. These findings led the Center for Medicare and Medicaid Services (CMS) to approve FDG‐PET as a diagnostic test for differentiating bvFTD from AD (https://www.cms.gov/medicare-coverage-database/details/ncd-details.aspx?NCDId=288&ncdver=3&bc=BAABAAAAAAAA&).…”

Based on the Network Degeneration Hypothesis: Separating Individual Patients with Different Neurodegenerative Syndromes in a Preliminary Hybrid PET/MR Study

“…For example, 18 F-FDG PET and structural MRI, respectively, detect regional hypometabolism, which reflects lowered regional neural activity, and atrophy, which reflects neurodegeneration, and both procedures are used for individual diagnostics (17)(18)(19). Restingstate functional MRI (rs-fMRI) facilitates the measurement of coherent ongoing brain activity, which reflects patterns of intrinsic functional connectivity including those of intrinsic brain networks (8,20).…”