%0 Journal Article %J J Alzheimers Dis %D 2018 %T Prediction of Alzheimer's Dementia in Patients with Amnestic Mild Cognitive Impairment in Clinical Routine: Incremental Value of Biomarkers of Neurodegeneration and Brain Amyloidosis Added Stepwise to Cognitive Status. %A Lange, Catharina %A Suppa, Per %A Pietrzyk, Uwe %A Makowski, Marcus R %A Spies, Lothar %A Peters, Oliver %A Buchert, Ralph %K Aged %K Aged, 80 and over %K Alzheimer Disease %K Amyloidosis %K Brain %K Cognitive Dysfunction %K Female %K Fluorodeoxyglucose F18 %K Humans %K Imaging, Three-Dimensional %K Longitudinal Studies %K Magnetic Resonance Imaging %K Male %K Middle Aged %K Neuropsychological Tests %K Positron-Emission Tomography %K Survival Analysis %K tau Proteins %X

The aim of this study was to evaluate the incremental benefit of biomarkers for prediction of Alzheimer's disease dementia (ADD) in patients with mild cognitive impairment (MCI) when added stepwise in the order of their collection in clinical routine. The model started with cognitive status characterized by the ADAS-13 score. Hippocampus volume (HV), cerebrospinal fluid (CSF) phospho-tau (pTau), and the FDG t-sum score in an AD meta-region-of-interest were compared as neurodegeneration markers. CSF-Aβ1-42 was used as amyloidosis marker. The incremental prognostic benefit from these markers was assessed by stepwise Kaplan-Meier survival analysis in 402 ADNI MCI subjects. Predefined cutoffs were used to dichotomize patients as 'negative' or 'positive' for AD characteristic alteration with respect to each marker. Among the neurodegeneration markers, CSF-pTau provided the best incremental risk stratification when added to ADAS-13. FDG PET outperformed HV only in MCI subjects with relatively preserved cognition. Adding CSF-Aβ provided further risk stratification in pTau-positive subjects, independent of their cognitive status. Stepwise integration of biomarkers allows stepwise refinement of risk estimates for MCI-to-ADD progression. Incremental benefit strongly depends on the patient's status according to the preceding diagnostic steps. The stepwise Kaplan-Meier curves might be useful to optimize diagnostic workflow in individual patients.

%B J Alzheimers Dis %V 61 %P 373-388 %8 2018 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/29154285?dopt=Abstract %R 10.3233/JAD-170705 %0 Journal Article %J J Alzheimers Dis %D 2017 %T Alzheimer's Disease Diagnosis Relies on a Twofold Clinical-Biological Algorithm: Three Memory Clinic Case Reports. %A Levy Nogueira, Marcel %A Samri, Dalila %A Epelbaum, Stéphane %A Lista, Simone %A Suppa, Per %A Spies, Lothar %A Hampel, Harald %A Dubois, Bruno %A Teichmann, Marc %X

The International Working Group recently provided revised criteria of Alzheimer's disease (AD) proposing that the diagnosis of typical amnesic AD should be established by a clinical-biological signature, defined by the phenotype of an "amnesic syndrome of the hippocampal type" (ASHT) combined with positive in vivo evidence of AD pathophysiology in the cerebrospinal fluid (CSF) or on amyloid PET imaging. The application and clinical value of this refined diagnostic algorithm, initially intended for research purposes, is explored in three memory clinic cases presenting with different cognitive profiles including an ASHT, hippocampal atrophy, and CSF AD-biomarker data. The case reports highlight that the isolated occurrence of one of the two proposed AD criteria, ASHT or positive pathophysiological markers, does not provide a reliable diagnosis of typical AD. It is proposed that the twofold diagnostic IWG algorithm can be applied and operationalized in memory clinic settings to improve the diagnostic accuracy of typical amnesic AD in clinical practice.

%B J Alzheimers Dis %V 60 %P 577-583 %8 2017 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/28869481?dopt=Abstract %R 10.3233/JAD-170574 %0 Journal Article %J J Alzheimers Dis %D 2017 %T Fully Automatic MRI-Based Hippocampus Volumetry Using FSL-FIRST: Intra-Scanner Test-Retest Stability, Inter-Field Strength Variability, and Performance as Enrichment Biomarker for Clinical Trials Using Prodromal Target Populations at Risk for Alzheimer's %A Cavedo, Enrica %A Suppa, Per %A Lange, Catharina %A Opfer, Roland %A Lista, Simone %A Galluzzi, Samantha %A Schwarz, Adam J %A Spies, Lothar %A Buchert, Ralph %A Hampel, Harald %X

BACKGROUND: MRI-based hippocampus volume is a core clinical biomarker for identification of Alzheimer's disease (AD).

OBJECTIVE: To assess robustness of automatic hippocampus volumetry with the freely available FSL-FIRST software with respect to short-term repeat and across field strength imaging. FSL-FIRST hippocampus volume (FIRST-HV) was also evaluated as enrichment biomarker for mild cognitive impairment (MCI) trials.

METHODS: Robustness of FIRST-HV was assessed in 51 healthy controls (HC), 74 MCI subjects, and 28 patients with AD dementia from ADNI1, each with two pairs of back-to-back scans, one at 1.5T one at 3T. Enrichment performance was tested in a second sample of 287 ADNI MCI subjects.

RESULTS: FSL-FIRST worked properly in all four scans in 147 out of 153 subjects of the first sample (49 HC, 72 MCI, 26 AD). In these subjects, FIRST-HV did not differ between the first and the second scan within an imaging session, neither at 1.5T nor at 3T (p≥0.302). FIRST-HV was on average 0.78% larger at 3T compared to 1.5T (p = 0.012). The variance of the FIRST-HV difference was larger in the inter-field strength setting than in the intra-scanner settings (p < 0.0005). Computer simulations suggested that the additional variability encountered in the inter-field strength scenario does not cause a relevant degradation of FIRST-HV's prognostic performance in MCI. FIRST-HV based enrichment resulted in considerably increased effect size of the 2-years change of cognitive measures.

CONCLUSION: The impact of intra-scanner test-retest and inter-field strength variability of FIRST-HV on clinical tasks is negligible. In addition, FIRST-HV is useful for enrichment in clinical MCI trials.

%B J Alzheimers Dis %V 60 %P 151-164 %8 2017 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/28777748?dopt=Abstract %R 10.3233/JAD-161108 %0 Journal Article %J J Alzheimers Dis %D 2016 %T Combination of Structural MRI and FDG-PET of the Brain Improves Diagnostic Accuracy in Newly Manifested Cognitive Impairment in Geriatric Inpatients. %A Ritter, Kerstin %A Lange, Catharina %A Weygandt, Martin %A Mäurer, Anja %A Roberts, Anna %A Estrella, Melanie %A Suppa, Per %A Spies, Lothar %A Prasad, Vikas %A Steffen, Ingo %A Apostolova, Ivayla %A Bittner, Daniel %A Gövercin, Mehmet %A Brenner, Winfried %A Mende, Christine %A Peters, Oliver %A Seybold, Joachim %A Fiebach, Jochen B %A Steinhagen-Thiessen, Elisabeth %A Hampel, Harald %A Haynes, John-Dylan %A Buchert, Ralph %X

BACKGROUND: The cause of cognitive impairment in acutely hospitalized geriatric patients is often unclear. The diagnostic process is challenging but important in order to treat potentially life-threatening etiologies or identify underlying neurodegenerative disease.

OBJECTIVE: To evaluate the add-on diagnostic value of structural and metabolic neuroimaging in newly manifested cognitive impairment in elderly geriatric inpatients.

METHODS: Eighty-one inpatients (55 females, 81.6±5.5 y) without history of cognitive complaints prior to hospitalization were recruited in 10 acute geriatrics clinics. Primary inclusion criterion was a clinical hypothesis of Alzheimer's disease (AD), cerebrovascular disease (CVD), or mixed AD+CVD etiology (MD), which remained uncertain after standard diagnostic workup. Additional procedures performed after enrollment included detailed neuropsychological testing and structural MRI and FDG-PET of the brain. An interdisciplinary expert team established the most probable etiologic diagnosis (non-neurodegenerative, AD, CVD, or MD) integrating all available data. Automatic multimodal classification based on Random Undersampling Boosting was used for rater-independent assessment of the complementary contribution of the additional diagnostic procedures to the etiologic diagnosis.

RESULTS: Automatic 4-class classification based on all diagnostic routine standard procedures combined reproduced the etiologic expert diagnosis in 31% of the patients (p = 0.100, chance level 25%). Highest accuracy by a single modality was achieved by MRI or FDG-PET (both 45%, p≤0.001). Integration of all modalities resulted in 76% accuracy (p≤0.001).

CONCLUSION: These results indicate substantial improvement of diagnostic accuracy in uncertain de novo cognitive impairment in acutely hospitalized geriatric patients with the integration of structural MRI and brain FDG-PET into the diagnostic process.

%B J Alzheimers Dis %V 54 %P 1319-1331 %8 2016 Oct 18 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/27567842?dopt=Abstract %R 10.3233/JAD-160380 %0 Journal Article %J J Alzheimers Dis %D 2016 %T Optimization of Statistical Single Subject Analysis of Brain FDG PET for the Prognosis of Mild Cognitive Impairment-to-Alzheimer's Disease Conversion. %A Lange, Catharina %A Suppa, Per %A Frings, Lars %A Brenner, Winfried %A Spies, Lothar %A Buchert, Ralph %K Aged %K Alzheimer Disease %K Area Under Curve %K Brain %K Cognitive Dysfunction %K Disease Progression %K Female %K Fluorodeoxyglucose F18 %K Follow-Up Studies %K Glucose %K Humans %K Image Interpretation, Computer-Assisted %K Male %K Positron-Emission Tomography %K Prognosis %K Radiopharmaceuticals %K ROC Curve %X

BACKGROUND: Positron emission tomography (PET) with the glucose analog F-18-fluorodeoxyglucose (FDG) is widely used in the diagnosis of neurodegenerative diseases. Guidelines recommend voxel-based statistical testing to support visual evaluation of the PET images. However, the performance of voxel-based testing strongly depends on each single preprocessing step involved.

OBJECTIVE: To optimize the processing pipeline of voxel-based testing for the prognosis of dementia in subjects with amnestic mild cognitive impairment (MCI).

METHODS: The study included 108 ADNI MCI subjects grouped as 'stable MCI' (n = 77) or 'MCI-to-AD converter' according to their diagnostic trajectory over 3 years. Thirty-two ADNI normals served as controls. Voxel-based testing was performed with the statistical parametric mapping software (SPM8) starting with default settings. The following modifications were added step-by-step: (i) motion correction, (ii) custom-made FDG template, (iii) different reference regions for intensity scaling, and (iv) smoothing was varied between 8 and 18 mm. The t-sum score for hypometabolism within a predefined AD mask was compared between the different settings using receiver operating characteristic (ROC) analysis with respect to differentiation between 'stable MCI' and 'MCI-to-AD converter'. The area (AUC) under the ROC curve was used as performance measure.

RESULTS: The default setting provided an AUC of 0.728. The modifications of the processing pipeline improved the AUC up to 0.832 (p = 0.046). Improvement of the AUC was confirmed in an independent validation sample of 241 ADNI MCI subjects (p = 0.048).

CONCLUSION: The prognostic value of voxel-based single subject analysis of brain FDG PET in MCI subjects can be improved considerably by optimizing the processing pipeline.

%B J Alzheimers Dis %V 49 %P 945-59 %8 2016 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/26577523?dopt=Abstract %R 10.3233/JAD-150814 %0 Journal Article %J J Alzheimers Dis %D 2016 %T Performance of Hippocampus Volumetry with FSL-FIRST for Prediction of Alzheimer's Disease Dementia in at Risk Subjects with Amnestic Mild Cognitive Impairment. %A Suppa, Per %A Hampel, Harald %A Kepp, Timo %A Lange, Catharina %A Spies, Lothar %A Fiebach, Jochen B %A Dubois, Bruno %A Buchert, Ralph %K Aged %K Aging %K Alzheimer Disease %K Area Under Curve %K Cognitive Dysfunction %K Databases, Factual %K Disease Progression %K Hippocampus %K Humans %K Image Interpretation, Computer-Assisted %K Magnetic Resonance Imaging %K Neuropsychological Tests %K Organ Size %K Pattern Recognition, Automated %K Prognosis %K Reproducibility of Results %K Risk %K ROC Curve %K Sensitivity and Specificity %K Time Factors %X

MRI-based hippocampus volume, a core feasible biomarker of Alzheimer's disease (AD), is not yet widely used in clinical patient care, partly due to lack of validation of software tools for hippocampal volumetry that are compatible with routine workflow. Here, we evaluate fully-automated and computationally efficient hippocampal volumetry with FSL-FIRST for prediction of AD dementia (ADD) in subjects with amnestic mild cognitive impairment (aMCI) from phase 1 of the Alzheimer's Disease Neuroimaging Initiative. Receiver operating characteristic analysis of FSL-FIRST hippocampal volume (corrected for head size and age) revealed an area under the curve of 0.79, 0.70, and 0.70 for prediction of aMCI-to-ADD conversion within 12, 24, or 36 months, respectively. Thus, FSL-FIRST provides about the same power for prediction of progression to ADD in aMCI as other volumetry methods.

%B J Alzheimers Dis %V 51 %P 867-73 %8 2016 %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/26923010?dopt=Abstract %R 10.3233/JAD-150804