Alzheimer Disease: Lehéricy S

Lehéricy S, Delmaire C, Galanaud D, Dormont D. · Inserm U610, Service de neuroradiologie et Centre de NeuroImagerie de Recherche, Centre hospitalo-universitaire Pitié-Salpêtrière, Paris (75). · Presse Med. · Pubmed #17611066 No free full text.

Abstract: Imaging is a part of the work-up for all types of dementia. X-ray computed tomography (CT) is a first-line examination to rule out causes of surgical, and thus reversible, dementia (for example, subdural hematoma or normal pressure hydrocephalus). MRI (magnetic resonance imaging) is preferred for work-ups of dementia. In the neurodegenerative dementias, the topography of the atrophy provides information about the specific type: atrophy of the medial temporal lobe is predominant in Alzheimer disease, while atrophy of the frontal and anterior temporal lobes is seen in frontotemporal dementia, with less medial temporal atrophy than in Alzheimer disease for frontotemporal dementia; vascular dementia is marked by infarction, lacuna, and signal abnormalities in the white matter and sometimes microbleeding. Single photon emission computed tomography (SPECT) and positron emission tomography (PET) are used in clinically atypical forms. Study of the dopamine transporter (DATscan) is used to distinguish Lewy body dementia from Alzheimer disease. Numerous studies are underway to identifying specific imaging markers for different types of dementia, including cerebral volumetric measurements, diffusion imaging, spectroscopy, very-high-field MRI scans of senile plaques, and PET markers of senile plaques.

Lehéricy S, Marjanska M, Mesrob L, Sarazin M, Kinkingnehun S. · Department of Neuroradiology, Université Pierre et Marie Curie-Paris 6, Groupe Hospitalier Pitié-Salpêtrière, 47-83 boulevard de l'Hôpital, Paris 75651, Cedex 13, France. · Eur Radiol. · Pubmed #16865367 No free full text.

Abstract: A modern challenge for neuroimaging techniques is to contribute to the early diagnosis of neurodegenerative diseases, such as Alzheimer's disease (AD). Early diagnosis includes recognition of pre-demented conditions, such as mild cognitive impairment (MCI) or having a high risk of developing AD. The role of neuroimaging therefore extends beyond its traditional role of excluding other conditions such as neurosurgical lesions. In addition, early diagnosis would allow early treatment using currently available therapies or new therapies in the future. Structural imaging can detect and follow the time course of subtle brain atrophy as a surrogate marker for pathological processes. New MR techniques and image analysis software can detect subtle brain microstructural, perfusion or metabolic changes that provide new tools to study the pathological processes and detect pre-demented conditions. This review focuses on markers of macro- and microstructural, perfusion, diffusion and metabolic MR imaging and spectroscopy in AD.

Krainik A, Rubin C, Grand S, David O, Baciu M, Jaillard A, Troprès I, Lamalle L, Duffau H, Le Bas JF, Segebarth C, Lehéricy S. · Service de Neuroradiologie - Unité IRM, CHU Grenoble. · J Radiol. · Pubmed #16788535 links to  free full text

Abstract: In the last decade, functional MRI (fMRI) has become one of the most widely used functional imaging technique in neurosciences. However, its clinical applications remain limited. Despite methodological and practical issues, fMRI data has been validated by different techniques (magnetoencephalography, Wada test, electrical and magnetic stimulations, and surgical resections). In neurosurgical practice, fMRI can identify eloquent areas involved in motor and language functions, and may evaluate characteristics of postoperative neurological deficit including its occurrence, clinical presentation and duration. This may help to inform patients and to prepare postoperative care. fMRI may also identify epileptic foci. In neurological practice, fMRI may help to determine prognosis of recovery after stroke, appropriate medication, and rehabilitation. fMRI may help to identify patients at risk of developing Alzheimer disease. Finally, cerebrovascular reactivity imaging is an interesting approach that might provide new radiological insights of vascular function.

Magnin B, Mesrob L, Kinkingnéhun S, Pélégrini-Issac M, Colliot O, Sarazin M, Dubois B, Lehéricy S, Benali H. · UMR-S 678, Inserm, Paris, France. · Neuroradiology. · Pubmed #18846369 No free full text.

Abstract: PURPOSE: We present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients with Alzheimer's disease (AD) and elderly control subjects. MATERIALS AND METHODS: We studied 16 patients with AD [mean age +/- standard deviation (SD) = 74.1 +/- 5.2 years, mini-mental score examination (MMSE) = 23.1 +/- 2.9] and 22 elderly controls (72.3 +/- 5.0 years, MMSE = 28.5 +/- 1.3). Three-dimensional T1-weighted MR images of each subject were automatically parcellated into regions of interest (ROIs). Based upon the characteristics of gray matter extracted from each ROI, we used an SVM algorithm to classify the subjects and statistical procedures based on bootstrap resampling to ensure the robustness of the results. RESULTS: We obtained 94.5% mean correct classification for AD and control subjects (mean specificity, 96.6%; mean sensitivity, 91.5%). CONCLUSIONS: Our method has the potential in distinguishing patients with AD from elderly controls and therefore may help in the early diagnosis of AD.

Colliot O, Chételat G, Chupin M, Desgranges B, Magnin B, Benali H, Dubois B, Garnero L, Eustache F, Lehéricy S. · Cognitive Neuroscience and Brain Imaging Laboratory, Centre National de la Recherche Scientifique, UPR640-LENA, Université Pierre et Marie Curie-Paris 6, Hôpital de la Pitié-Salpêtrière, Paris, France. · Radiology. · Pubmed #18458242 links to  free full text

Abstract: PURPOSE: To prospectively evaluate the accuracy of automated hippocampal volumetry to help distinguish between patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and elderly controls, by using established criteria for patients with AD and MCI as the reference standard. MATERIALS AND METHODS: The regional ethics committee approved the study and written informed consent was obtained from all participants. The study included 25 patients with AD (11 men, 14 women; mean age +/- standard deviation [SD], 73 years +/- 6; Mini-Mental State Examination (MMSE) score, 24.4 +/- 2.7), 24 patients with amnestic MCI (10 men, 14 women; mean age +/- SD, 74 years +/- 8; MMSE score, 27.2 +/- 1.4) and 25 elderly healthy controls (13 men, 12 women; mean age +/- SD, 64 years +/- 8). For each participant, the hippocampi were automatically segmented on three-dimensional T1-weighted magnetic resonance (MR) images with high spatial resolution. Segmentation was performed by using recently developed software that allows fast segmentation with minimal user input. Group differences in hippocampal volume were assessed by using Student t tests. To obtain robust estimates of P values, the correct classification rate, sensitivity, and specificity, bootstrap methods were used. RESULTS: Significant hippocampal volume reductions were detected in all groups of patients (-32% in AD patients vs controls, P < .001; -19% in MCI patients vs controls, P < .001; and -15% in AD patients vs MCI patients, P < .01). 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. CONCLUSION: This automated method can serve as an alternative to manual tracing and may thus prove useful in assisting with the diagnosis of AD.

Kinkingnéhun S, Sarazin M, Lehéricy S, Guichart-Gomez E, Hergueta T, Dubois B. · INSERM U610, Paris, France. · Neurology. · Pubmed #18448872 No free full text.

Abstract: OBJECTIVE: To determine whether regional atrophy or neuropsychological factors can predict the rate of decline in patients with mild Alzheimer disease (AD). BACKGROUND: Despite important implications for planning the care and treatment strategy, few prognostic factors of severe AD progression are known. METHODS: Twenty-three patients with mild AD were followed up every 6 months over the course of 3 years. At baseline, patients with AD and 18 controls underwent a neuropsychological battery and a brain MRI. At the end of the 3 years, patients with AD were dichotomized into slow decliners (SLD) or fast decliners (FD) groups on the basis of their decline in Mini-Mental State Examination score over time. We compared baseline cognitive performance and imaging data using voxel-based morphometry (VBM). RESULTS: SLD and FD groups did not differ in age, gender, level of education, mean estimated duration of illness, and standard neuropsychological data at inclusion, except for the Attentional Battery of the Cambridge Neuropsychological Tests Automated Battery (speed processing in shifting condition). VBM comparison between SLD and FD groups demonstrated more gray matter tissue loss in the FD group in the medial occipitoparietal areas, especially in the precuneus, the lingual gyrus, the cuneus, and the surrounding cortex of the parieto-occipital sulcus bilaterally. CONCLUSION: Voxel-based morphometry analysis demonstrated that patients who will have a faster decline at 3 years already had a more extensive cortical atrophy than SLD patients, especially in the medial occipitoparietal areas, which was not yet detected by clinical and neuropsychological assessment.