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Poster Presentations: P2
clustering linkage method was performed. Each identified subgroup of subjects was compared to an age and gender-matched control group by general linear model. Results: With cluster analysis, we classified AD patients into three, four, five and six anatomical subtypes according to the number of clusters. The three clusters were 1) medial temporal dominant (MT) subtype (n¼52) in which the bilateral medial temporal lobes were involved dominantly; 2) parietal dominant (P) subtype (n¼28) in which bilateral parietal, dorsolateral frontal areas were involved as well as precuneus, with relatively sparing medial temporal area; and 3) diffuse atrophy (D) subtype (n¼72) in which nearly all cortical areas were involved (figure). The neuropsychological results of these three subtypes were consistent with their pattern of cortical atrophy. Cluster analysis with four and five clusters showed that D subtype was further divided into two and three subtypes, respectively. Cluster analysis with six clusters further divided P subtype into left dominant and right dominant ones (figure). Conclusions: Our findings showed that AD patients can be divided into various subtypes according to cortical atrophy pattern, which is in line with their neuropsychological results. These findings are important as they confirm with imaging study that AD is not homogeneous. P2-099
DISTRIBUTION OF AMYLOID BURDEN IN PIB(+) SUBCORTICAL VASCULAR COGNITIVE IMPAIRMENT COMPARED WITH ALZHEIMER’S DISEASE
morbid Alzheimer’s disease pathologies. We hypothesized that patients with PiB (+) SVCI have pattern differs from AD, and that the patterns of distribution of PiB differ according to severity of amyloid burden. Methods: We included 44 patients with SVCI and 44 patients with Alzheimer’s disease type cognitive impairment (ADCI) who had amyloid deposition assessed by PiB PET. We divided the SVCI and ADCI to tertiary groups according to global PiB retention ratio of SVCI. To compare the distribution of PiB retention, a voxel-based statistical analysis was performed using statistical parametric mapping (SPM) analyses. Lobar to global PiB retention ratios and asymmetry indices were also compared between SVCI and ADCI. Results: The characteristics of PiB distribution in PiB (+) SVCI compared to PiB (+) ADCI were 1) increased left-right asymmetry, 2) increased anterior-posterior asymmetry, 3) increased retention in occipital, precuneus (PC)-posterior cingulate cortices (PCC), 4) decreased retention in striatum and temporal areas. These features became clear with grouping according to severity of amyloid burden. Low PiB group revealed left-right asymmetry in parietal cortices distinctly; intermediate PiB group showed increased occipital retention and decreased striatum retention; high PiB group presented increased retention in parietal, PC-PCC, decreased retention in frontal, temporal and striatum, increased anterior-posterior asymmetry compared to ADCI. Conclusions: PiB PET presented the distribution of amyloid retention in PiB (+) SVCI may differ from that seen in ADCI. It might suggest the different pathomechanism of amyloid retention in SVCI. It is important to the point that the prevention of deterioration and management in SVCI patients may be different from those in the patients with AD. P2-100
IS HIPPOCAMPAL VOLUME A GOOD MARKER TO DIFFERENTIATE ALZHEIMER’S DISEASE FROM FRONTOTEMPORAL DEMENTIA?
Young Noh1, Sang Won Seo2, Jung-Hyun Kim1, Jae-Hong Lee3, Seun Jeon4, Jong Lee4, Geon Ha Kim1, Hanna Cho1, Cindy Yoon5, HeeJin Kim6, Byoung Seok Ye1, Yearn Seong Choe7, Kyung-Han Lee1, Jae Seung Kim8, Duk L. Na2, 1Samsung Medical Center, Seoul, South Korea; 2Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; 3Asan Medical Center, Seoul, South Korea; 4 Hanyang University, Seoul, South Korea; 5Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, 50 Ilwo, Seoul, South Korea; 6Samsung Medical Center, Seoul, Seoul, South Korea; 7Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, South Korea; 8Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea. Contact e-mail:
[email protected]
Leonardo de Souza1, Marie Chupin2, Maxime Bertoux3, Stephane Lehericy4, Bruno Dubois5, Foudil Lamari6, Isabelle Le Ber7, Michel Bottlaender8, Olivier Colliot2, Marie Sarazin2, 1Alzheimer Institute; Research and Resource Memory Centre; Centre de Reference des Demences Cogimage-CRICM, Paris, France; Rares, Paris, France; 2Equipe 3 Alzheimer Institute, AP-HP, Groupe Hospitalier Pitie-Salp^etriere, Paris, F-75013, France; 4Centre de NeuroImagerie de Recherche (CENIR), H^opital de la Pitie-Salp^etriere, Paris, France; 5Salp^etriere Hospital, Paris, A~Zle-de-France, France; 6H^opital de la Pitie-Salp^etriere, Paris, France; 7 CRCICM, IM2A, UMR-S975 AP-HP, Paris, A~Zle-de-France, France; 8 Service Hospitalier Frederic Joliot, Orsay, France. Contact e-mail:
[email protected]
Background: Subcortical vascular cognitive impairment (SVCI) refers to cognitive impairments due to cerebrovascular disease (CVD), which consists of subcortical vascular dementia (SVaD) and subcortical vascular mild cognitive impairment (svMCI). Previous pathological studies and imaging studies using Pittsburgh compound-B (PiB) PET demonstrated that patients who had been clinically diagnosed with SVaD proved to have co-
Background: To analyze the effectiveness of hippocampal volumetric measures to distinguish Alzheimer’s disease (AD) from behavioral variant frontotemporal dementia (bvFTD), using strict inclusion criteria based on clinical and pathophysiological markers. Methods: Seventy-two participants were included: 31 AD patients with predominant and progressive episodic memory deficits associated with typical AD CSF profile and/or
Poster Presentations: P2 positive amyloid imaging (PET with 11 C-labeled Pittsburgh Compound B [PiB]), 26 bvFTD patients diagnosed according to consensual clinical criteria and with no CSF AD profile, and 15 healthy controls without amyloid retention on PiB-PET exam. Hippocampal volumes (HV) were segmented with an automated method and were normalized to total intracranial volume (nHV). Results: Significant reductions in HV were found in both AD and bvFTD patients compared with controls, but there were no significant differences between AD and bvFTD patients. Mean nHV distinguished normal controls from either AD or bvFTD with high sensitivity (80.6% and 76.9%, respectively) and specificity (93.3% for both), but it
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was inefficient in differentiating AD from bvFTD. Logistic regression analyses r evealed that mean nHV correctly classified only 56.1% of patients into the AD group instead of the bvFTD group, while mean nHV accurately classified AD (82.6% accuracy) and bvFTD (75.6% accuracy) relative to controls. There were no differences in the clinical and neuropsychological profiles according to HV in bvFTD and AD patients. Conclusions: When considered alone, measures of HV are not good markers to differentiate AD from bvFTD. Hippocampal sclerosis associated with FTD may explain the high degree of overlap in nHV between both groups.
