Application of Automated Medial Temporal Lobe Atrophy Scale to Alzheimer Disease

Ridha, Basil H.; Barnes, Josephine; Pol, Laura A. van de; Schott, Jonathan M.; Boyes, Richard G.; Siddique, Musib; Rossor, Martin N.; Scheltens, Philip; Fox, Nick C.

doi:10.1001/archneur.64.6.849

Cited by 58 publications

(27 citation statements)

References 22 publications

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“…Individual classification on the basis of hippocampal volume resulted in 84% correct classification ͑sensitivity, 84%; specificity, 84%͒ between AD patients and controls and 73% correct classification ͑sensitivity, 75%; specificity, 70%͒ between MCI patients and controls. Ridha et al 21 compared an automated intensity-based measure of medial temporal lobe atrophy ͑ATLAS͒ with volumetric and visually based methods. Their measure differentiates patients with AD from controls at cross-sectional and longitudinal levels.…”

Section: Discussionmentioning

confidence: 99%

“…20 Visual rating scales, although simple to use and suitable for a clinical application, were not designed to detect atrophy progression on serial imaging; their quantized nature makes them insensitive to change over time. 21 To accelerate and spread epidemiological studies and clinical trials, some automated systems have been proposed for hippocampal segmentation, [22][23][24][25][26][27][28] but none is yet widely used 29 due to the high computational burden, 30 unsatisfactory results, 31 or poor generalization capability. 24 In order to overcome these difficulties, in this work we describe the development of a simple, quick, and operatorindependent method to extract two fixed size ͑30ϫ 70 ϫ 30 mm 3 ͒, parallelepiped-shaped subimages from a MR image.…”

Section: 2mentioning

confidence: 99%

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Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease

et al. 2009

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The purpose of this study is to develop a software for the extraction of the hippocampus and surrounding medial temporal lobe ͑MTL͒ regions from T1-weighted magnetic resonance ͑MR͒ images with no interactive input from the user, to introduce a novel statistical indicator, computed on the intensities in the automatically extracted MTL regions, which measures atrophy, and to evaluate the accuracy of the newly developed intensity-based measure of MTL atrophy to ͑a͒ distinguish between patients with Alzheimer disease ͑AD͒, patients with amnestic mild cognitive impairment ͑aMCI͒, and elderly controls by using established criteria for patients with AD and aMCI as the reference standard and ͑b͒ infer about the clinical outcome of aMCI patients. For the development of the software, the study included 61 patients with mild AD ͑17 men, 44 women; mean ageϮ standard deviation ͑SD͒, 75.8 yearsϮ 7.8; Mini Mental State Examination ͑MMSE͒ score, 24.1Ϯ 3.1͒, 42 patients with aMCI ͑11 men, 31 women; mean ageϮ SD, 75.2 yearsϮ 4.9; MMSE score, 27.9Ϯ 1.9͒, and 30 elderly healthy controls ͑10 men, 20 women; mean ageϮ SD, 74.7 yearsϮ 5.2; MMSE score, 29.1Ϯ 0.8͒. For the evaluation of the statistical indicator, 150 patients with mild AD ͑62 men, 88 women; mean ageϮ SD, 76.3 yearsϮ 5.8; MMSE score, 23.2Ϯ 4.1͒, 247 patients with aMCI ͑143 men, 104 women; mean ageϮ SD, 75.3 yearsϮ 6.7; MMSE score, 27.0Ϯ 1.8͒, and 135 elderly healthy controls ͑61 men, 74 women; mean ageϮ SD, 76.4 yearsϮ 6.1͒. Fifty aMCI patients were evaluated every 6 months over a 3 year period to assess conversion to AD. For each participant, two subimages of the MTL regions were automatically extracted from T1-weighted MR images with high spatial resolution. An intensity-based MTL atrophy measure was found to separate control, MCI, and AD cohorts. Group differences were assessed by using two-sample t test. Individual classification was analyzed by using receiver operating characteristic ͑ROC͒ curves. Compared to controls, significant differences in the intensitybased MTL atrophy measure were detected in both groups of patients ͑AD vs controls, 0.28Ϯ 0.03 vs 0.34Ϯ 0.03, P Ͻ 0.001; aMCI vs controls, 0.31Ϯ 0.03 vs 0.34Ϯ 0.03, P Ͻ 0.001͒. Moreover, the subgroup of aMCI converters was significantly different from controls ͑0.27Ϯ 0.034 vs 0.34Ϯ 0.03, P Ͻ 0.001͒. Regarding the ROC curve for intergroup discrimination, the area under the curve was 0.863 for AD patients vs controls, 0.746 for all aMCI patients vs controls, and 0.880 for aMCI converters vs controls. With specificity set at 85%, the sensitivity was 74% for AD vs controls, 45% for aMCI vs controls, and 83% for aMCI converters vs controls. The automated analysis of MTL atrophy in the segmented volume is applied to the early assessment of AD, leading to the discrimination of aMCI converters with an average 3 year follow-up. This procedure can provide additional useful information in the early diagnosis of AD.

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Section: Discussionmentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease

et al. 2009

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“…A number of studies were published where the visual rating scale was used in memory clinic population [40][41][42][43][44][45][46][47]. However, the scale, although simple to use and suitable for a clinical application, was not designed to detect atrophy progression on serial imaging; its quantized nature makes it insensitive to subtle changes over time [44].…”

Section: Automatic Methodsmentioning

confidence: 99%

“…Individual classification on the basis of hippocampal volume resulted in 84% correct classification (sensitivity, 84%; specificity, 84%) between AD patients and controls and 73% correct classification (sensitivity, 75%; specificity, 70%) between MCI patients and controls. Ridha et al [44] compared an automated intensity-based measure of MTL atrophy (ATLAS) with volumetric and visually based methods. Their measure differentiates patients with AD from controls at cross-sectional and longitudinal levels.…”

Section: Yushkevich Et Almentioning

confidence: 99%

Automatic Morphological Analysis of Medial Temporal Lobe

Chincarini¹,

Corosu²,

Gemme³

et al. 2010

TONMEDJ

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Abstract:Research in Alzheimer's disease (AD) has seen a tremendous growth of candidate biomarkers in the last decade. The role of such established or putative biomarkers is to allow an accurate diagnosis of AD, to infer about its prognosis, to monitor disease progression and evaluate changes induced by disease-modifying drugs. An ideal biomarker should detect a specific pathophysiological feature of AD, not present in the healthy condition, in other primary dementias, or in confounding conditions. Besides being reliable, a biomarker should be detectable by means of procedures which must be relatively non-invasive, simple to perform, widely available and not too expensive. At present, no candidate meets these requirements representing the high standards aimed at by researchers. Among others, various morphological brain measures performed by means of magnetic resonance imaging (MRI), ranging from the total brain volume to some restricted regions such as the hippocampal volume, have been proposed. Nowadays the efforts are directed toward finding an automated, unsupervised method of evaluating atrophy in some specific brain region, such as the medial temporal lobe (MTL). In this work we provide an extensive review of the state of the art on the automatic and semi-automatic image processing techniques for the early assessment of patients at risk of developing AD. Our main focus is the relevance of the morphological analysis of MTL, and in particular of the hippocampal formation, in making the diagnosis of AD and in distinguishing it from other dementias.

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“…[9,10] Moderne Magnetresonanztomographie(MRT)-Techniken bestätigten nicht nur die Volumenabnahme der grauen Substanz (Neurone), sondern wiesen auch eine Korrelation zwischen der Atrophie des entorhinalen Cortex und der Beeinträchtigung des episodischen Gedächtnisses bei AD-Patienten nach. [11][12][13] Neben der strukturabbildenden MRT werden heute Techniken wie die Positronenemissionstomographie (PET), mit der die Ab-Ablagerung mithilfe von 11 C-PIB oder anderen PETLiganden verfolgt wird, oder funktionelle Techniken wie Glucoseumsatz und fMRT (funktionelle Magnetresonanztomographie) eingesetzt, um das Fortschreiten der Krankheit zu verfolgen und möglicherweise eine Frühdiagnose zu ermöglichen (Abbildungen 2 und 3). [14][15][16][17] Vor allem mit Messungen des Magnetisierungstransferverhältnisses lassen sich sehr frühe Veränderungen im Gehirn von Patienten mit leichter kognitiver Beeinträchtigung (MCI; mild cognitive impairment), einem klinischen Risikofaktor für eine Demenzentwicklung, nachweisen.…”

Section: Bildgebung Struktureller Und Funktioneller Veränderungen Im unclassified

Die Alzheimer‐Demenz: von der Pathologie zu therapeutischen Ansätzen

Jakob‐Roetne

Jacobsen

2009

Angewandte Chemie

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Die gegenwärtigen Strategien zur Entwicklung von Alzheimer‐Therapien sind breit gefächert. Ein verstärktes Augenmerk gilt der Suche nach Hemmstoffen (siehe Bild für zwei Beispiele) der proteolytischen Enzyme β‐ und γ‐Secretase, die die Spaltung des Amyloid‐Vorläuferproteins in Amyloid‐β‐Peptide inhibieren, aus denen die krankheitstypischen Plaque‐Ablagerungen im Gehirn von Alzheimer‐Patienten entstehen.magnified imageDie Forschungen über Altersdemenz und die Alzheimersche Krankheit umfassen ein sehr breites Feld wissenschaftlicher Aktivitäten. So wurden etwa bei der letztjährigen internationalen Tagung der Alzheimer‐Gesellschaft (ICAD 2008 in Chicago) mehr als 2200 Einzelbeiträge präsentiert. Ziel dieses Aufsatzes ist es, einen zusammenhängenden Überblick über das Gebiet zu präsentieren und die wichtigsten Themen und Forschungstrends aufzuzeigen. Die Ausführungen beginnen mit einer Diskussion von Verhaltensabweichungen und sichtbaren pathologischen Befunden, bevor dann auf die molekularen Details der Pathologie eingegangen wird. Besonderes Augenmerk gilt der “Amyloidhypothese” der Alzheimer‐Krankheit, da sie das theoretische Fundament für die meisten der in der Entwicklung befindlichen therapeutischen Konzepte bildet.

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Application of Automated Medial Temporal Lobe Atrophy Scale to Alzheimer Disease

Cited by 58 publications

References 22 publications

Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease

Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease

Automatic Morphological Analysis of Medial Temporal Lobe

Die Alzheimer‐Demenz: von der Pathologie zu therapeutischen Ansätzen

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