Simon Duchesne

Bio: Simon Duchesne is an academic researcher from Laval University. The author has contributed to research in topics: Cognitive decline & Hyperintensity. The author has an hindex of 32, co-authored 152 publications receiving 3399 citations. Previous affiliations of Simon Duchesne include University of Rennes & McGill University.

Steps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer's disease

Abstract: Background The promise of Alzheimer’s disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer’s disease and thus represents the most rational target for an initial effort at standardization. Methods and Results The authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer’s Disease Centers–Alzheimer’s Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer’s Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark. Conclusions Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity

Abstract: Background An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Methods Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. Results The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P P Conclusions The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

Steps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer's disease

Abstract: Background The promise of Alzheimer’s disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer’s disease and thus represents the most rational target for an initial effort at standardization. Methods and Results The authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer’s Disease Centers–Alzheimer’s Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer’s Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark. Conclusions Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.

Research Article The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity

Abstract: Background: An international Delphi panel has defined a harmonized protocol (HarP) for themanual segmentation of the hippocampus on MR. The aim of this study is to study the concurrentvalidity of the HarP toward local protocols, and its major sources of variance.Methods: Fourteen tracers segmented 10 Alzheimer’s Disease Neuroimaging Initiative (ADNI)cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on theHarP through a standard web-platform and resegmented following the HarP. The five most accuratetracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 Tand3T.Results: Theagreementamongtracerswasrelativelylowwiththelocalprotocols(absoluteleft/rightICC0.44/0.43)andmuchhigherwiththeHarP(absoluteleft/rightICC0.88/0.89).Onthelargersetof15cases,theHarPagreementwithin(left/rightICCrange:0.94/0.95to0.99/0.99)andamongtracers(left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates(3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variancedue to atrophy (33.5%, P ,.001), and physiological variability (49.2%, P ,.001).Conclusions: The HarP has high measurement stability compared with local segmentation proto-cols, and good reproducibility within and among human tracers. Hippocampi segmented with theHarP can be used as a reference for the qualification of human tracers and automated segmentationalgorithms. 2014 The Alzheimer’s Association. All rights reserved.

NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease

Abstract: In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

Statistical Parametric Mapping The Analysis Of Functional Brain Images

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Clinical Diagnosis of Alzheimer's Disease

Abstract: There are a number of ways in which a clinical diagnosis of dementia of the Alzheimer type can be made – the application of clinical criteria is the commonest but ancillary techniques such as neuroima