BACKGROUND AND PURPOSE: Alzheimer disease is a prevalent neurodegenerative disease. Computer assessment of brain atrophy patterns can help predict conversion to Alzheimer disease. Our aim was to assess the prognostic efficacy of individual-versus-combined regional volumetrics in 2 commercially available brain volumetric software packages for predicting conversion of patients with mild cognitive impairment to Alzheimer disease. MATERIALS AND METHODS: Data were obtained through the Alzheimer9s Disease Neuroimaging Initiative. One hundred ninety-two subjects (mean age, 74.8 years; 39% female) diagnosed with mild cognitive impairment at baseline were studied. All had T1-weighted MR imaging sequences at baseline and 3-year clinical follow-up. Analysis was performed with NeuroQuant and Neuroreader. Receiver operating characteristic curves assessing the prognostic efficacy of each software package were generated by using a univariable approach using individual regional brain volumes and 2 multivariable approaches (multiple regression and random forest), combining multiple volumes. RESULTS: On univariable analysis of 11 NeuroQuant and 11 Neuroreader regional volumes, hippocampal volume had the highest area under the curve for both software packages (0.69, NeuroQuant; 0.68, Neuroreader) and was not significantly different ( P > .05) between packages. Multivariable analysis did not increase the area under the curve for either package (0.63, logistic regression; 0.60, random forest NeuroQuant; 0.65, logistic regression; 0.62, random forest Neuroreader). CONCLUSIONS: Of the multiple regional volume measures available in FDA-cleared brain volumetric software packages, hippocampal volume remains the best single predictor of conversion of mild cognitive impairment to Alzheimer disease at 3-year follow-up. Combining volumetrics did not add additional prognostic efficacy. Therefore, future prognostic studies in mild cognitive impairment, combining such tools with demographic and other biomarker measures, are justified in using hippocampal volume as the only volumetric biomarker.
Last. Hugo Vrenken(VUmc: VU University Medical Center)H-Index: 59
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Objective To investigate whether subcortical grey matter atrophy predicts progression from mild cognitive impairment (MCI) to Alzheimer9s disease (AD), and to compare subcortical volumes between AD, MCI and controls. To assess the correlation between subcortical grey matter volumes and severity of cognitive impairment. Methods We included 773 participants with three-dimensional T1-weighted MRI at 3 T, made up of 181 controls, who had subjective memory symptoms with normal cognition, 201 MCIs and...
Last. Oscar L. Lopez(University of Pittsburgh)H-Index: 111
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Background: Multiple neurological disorders including Alzheimer’s disease (AD), mesial temporal sclerosis, and mild traumatic brain injury manifest with volume loss on brain MRI. Subtle volume loss is particularly seen early in AD. While prior research has demonstrated the value of this additional information from quantitative neuroimaging, very few applications have been approved for clinical use. Here we describe a US FDA cleared software program, Neuroreader TM , for assessment of clinical hi...
Objective This study aims to determine the clinical utility of visual ratings and volumetric measurements of medial temporal atrophy among subjects from the Alzheimer's Disease Neurorimaging Initiative (ADNI) cohort. Methods A sample of 189 subjects from the ADNI, Phase 1 (ADNI-1), was chosen as follows: 49 cognitively normal (CN), 89 with mild cognitive impairment (MCI), and 50 with Alzheimer's disease (AD). Structural MRI images were downloaded from the ADNI website, and a visual rating system...
Last. Xiaojuan Guo(BNU: Beijing Normal University)H-Index: 14
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Alzheimer's disease (AD) is one of the most serious progressive neurodegenerative diseases among the elderly, therefore the identification of conversion to AD at the earlier stage has become a crucial issue. In this study, we applied multimodal support vector machine to identify the conversion from normal elderly cognition to mild cognitive impairment (MCI) or AD based on magnetic resonance imaging and positron emission tomography data. The participants included two independent cohorts (Training...
Last. Jussi Tohka(TUT: Tampere University of Technology)H-Index: 27
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Abstract Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this study, we present a novel magnetic resonance imaging (MRI)-based method for predicting the MCI-to-AD conversion from one to three years before the clinical diagnosis. First, we developed a novel MRI biomarker of MCI-to-AD conversion using sem...
Background: Regulatory qualification of a biomarker for a defined context of use provides scientifically robustassurances to sponsors and regulators that accelerate appropriate adoption of biomarkers into drug development. Methods: The Coalition Against Major Diseases submitted a dossier to the Scientific Advice Working Party of the European Medicines Agency requesting a qualification opinion on the use of hippocampalvolumeasabiomarkerforenrichingclinicaltrialsinsubjectswithmildcognitiveimpairme...
Biomarkers, including neuroimaging, have great potential to increase the power of clinical trials through greater effect sizes by matching imaging methodology with therapeutic mechanism.
Computational anatomy with magnetic resonance imaging (MRI) is well established as a noninvasive biomarker of Alzheimer’s disease (AD); however, there is less certainty about its dependency on the staging of AD. We use classical group analyses and automated machine learning classification of standard structural MRI scans to investigate AD diagnostic accuracy from the preclinical phase to clinical dementia. Longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative were stratified int...
Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) three-dimensional T 1 -weighted magnetic resonance imaging (MRI) acquisitions provide a rich data set for developing and testing analysis techniques for extracting structural endpoints. To promote greater rigor in analysis and meaningful comparison of different algorithms, the ADNI MRI Core has created standardized analysis sets of data comprising scans that met minimum quality control requirements. We encourage researchers to test ...
Hippocampal pathology occurs early in Alzheimer disease (AD), and atrophy, measured by volumes and volume changes, may predict which subjects will develop AD. Measures of the temporal horn (TH), which is situated adjacent to the hippocampus, may also indicate early changes in AD. Previous studies suggest that these metrics can predict conversion from amnestic mild cognitive impairment (MCI) to AD with conversion and volume change measured concurrently. However, the ability of these metrics to pr...
Last. Meike W. Vernooij(EUR: Erasmus University Rotterdam)H-Index: 72
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Developments in neuroradiological MRI analysis offer promise in enhancing objectivity and consistency in dementia diagnosis through the use of quantitative volumetric reporting tools (QReports). Translation into clinical settings should follow a structured framework of development, including technical and clinical validation steps. However, published technical and clinical validation of the available commercial/proprietary tools is not always easy to find and pathways for successful integration ...
Alzheimer’s Disease (AD) exerts a significant worldwide impact. An estimated 44 million individuals currently live with this Major Neurocognitive Disorder. There are about 6.2 million Americans with AD dementia today and AD kills more people than breast cancer and prostate cancer combined. The National Institute on Aging estimates that the prevalence of AD doubles every five years beyond the age of 65 and as the population ages, a greater proportion of the population is affected. AD will cost th...
Last. Jonathan McConathy(UAB: University of Alabama at Birmingham)H-Index: 25
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PET/MR imaging is in routine clinical use and is at least as effective as PET/CT for oncologic and neurologic studies with advantages with certain PET radiopharmaceuticals and applications. In addition, whole body PET/MR imaging substantially reduces radiation dosages compared with PET/CT which is particularly relevant to pediatric and young adult population. For cancer imaging, assessment of hepatic, pelvic, and soft-tissue malignancies may benefit from PET/MR imaging. For neurologic imaging, v...
OBJECTIVES Mild cognitive impairment (MCI) types may have distinct neuropathological substrates with hippocampal atrophy particularly common in amnestic MCI (aMCI). However, depending on the MCI classification criteria applied to the sample (e.g., number of abnormal test scores considered or thresholds for impairment), volumetric findings between MCI types may change. Additionally, despite increased clinical use, no prior research has examined volumetric differences in MCI types using the automa...
SUMMARY: This article will familiarize neuroradiologists with the pathophysiology, clinical findings, and standard MR imaging and PET imaging features of multiple forms of dementia as well as new emerging techniques. Cases were compiled from multiple institutions with the goal of improved diagnostic accuracy and improved patient care as well as information about biomarkers on the horizon. Dementia topics addressed include the following: Alzheimer disease, frontotemporal dementia, cerebral amyloi...
OBJECTIVE To compare two clinically available MR volumetry software, NeuroQuant® (NQ) and Inbrain® (IB), and examine the inter-method reliabilities and differences between them. MATERIALS AND METHODS This study included 172 subjects (age range, 55-88 years; mean age, 71.2 years), comprising 45 normal healthy subjects, 85 patients with mild cognitive impairment, and 42 patients with Alzheimer's disease. Magnetic resonance imaging scans were analyzed with IB and NQ. Mean differences were compared ...
PURPOSE In mild cognitive impairment (MCI), identifying individuals at high risk for progressive cognitive deterioration can be useful for prognostication and intervention. This study quantitatively characterizes cognitive decline rates in MCI and tests whether volumetric data from baseline magnetic resonance imaging (MRI) can predict accelerated cognitive decline. METHODS The authors retrospectively examined Alzheimer Disease Neuroimaging Initiative data to obtain serial Mini-Mental Status Exam...
