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Item does not contain fulltext BACKGROUND: Mood disorders are familial psychiatric diseases, in which patients show reduced white matter (WM) integrity. We sought to determine whether WM integrity was affected in young offspring at high-familial risk of mood disorder before they go on to develop major depressive disorder (MDD). METHODS: The Bipolar Family study is a prospective longitudinal study examining young individuals (age 16-25 years) at familial risk of mood disorder on three occasions 2 years apart. This study used baseline imaging data, categorizing groups according to clinical outcome at follow-up. Diffusion tensor MRI data were acquired for 61 controls and 106 high-risk individuals, the latter divided into 78 high-risk subjects who remained well throughout the study ('high-risk well') and 28 individuals who subsequently developed MDD ('high-risk MDD'). Voxel-wise between-group comparison of fractional anisotropy (FA) based on diagnostic status was performed using tract-based spatial statistics (TBSS). RESULTS: Compared to controls, both high-risk groups showed widespread decreases in FA (pcorr < .05) at baseline. Although FA in the high-risk MDD group negatively correlated with subthreshold depressive symptoms at the time of scanning (pcorr < .05), there were no statistically significant differences at p-corrected levels between the two high-risk groups. CONCLUSIONS: These results suggest that decreased FA is related to the presence of familial risk for mood disorder along with subdiagnostic symptoms at the time of scanning rather than predictive of subsequent diagnosis. Due to the difficulties performing such longitudinal prospective studies, we note, however, that this latter analysis may be underpowered due to sample size within the high-risk MDD group. Further clinical follow-up may clarify these findings.

Objective We present a retrospective meta-analysis of voxel-based morphometry (VBM) of gray (GM) and white matter (WM) differences between patients with bipolar disorder (BD) and behaviorally healthy controls. Methods We used the activation likelihood estimation and Sleuth software for our meta-analysis, considering P-value maps at the cluster level inference of .05 with uncorrected P

Background Studies have reported hippocampal and amygdala volume abnormalities in schizophrenic patients. It is necessary to explore the potential for these structures as early disease markers in subjects at high risk (HR) of schizophrenia. Methods We performed a review of 29 magnetic resonance imaging (MRI) studies measuring hippocampal and amygdala volumes in subjects at HR for schizophrenia. We reclassified subjects in 3 new HR categories: presence of only risk symptoms (psychotic moderate symptoms), presence of only risk factors (genetic, developmental or environmental), and presence of combined risk symptoms/factors. Results Hippocampal volume reductions were detected in subjects with first episode (FE) of psychosis, in all young adults and in adolescents at HR of schizophrenia. The loss of tissue was mainly located in the posterior part of hippocampus and the right side seems more vulnerable in young adults with only risk symptoms. Instead, the anterior sector seems more involved in HR subjects with genetic risks. Abnormal amygdala volumes were found in FE subjects, in children with combined risk symptoms/factors and in older subjects using different inclusion criteria, but not in young adults. Conclusion Hippocampal and amygdala abnormalities may be present before schizophrenia onset. Further studies should be conducted to clarify whether these abnormalities are causally or effectually related to neurodevelopment. Shape analysis could clarify the impact of environmental, genetic, and developmental factors on the medial temporal structures during the evolution of this disease.

Background Hippocampal volumetry on magnetic resonance imaging is recognized as an Alzheimer's disease (AD) biomarker, and manual segmentation is the gold standard for measurement. However, a standard procedure is lacking. We operationalize and quantitate landmark differences to help a Delphi panel converge on a set of landmarks. Methods One hundred percent of anatomic landmark variability across 12 different protocols for manual segmentation was reduced into four segmentation units (the minimum hippocampus, the alveus/fimbria, the tail, and the subiculum), which were segmented on magnetic resonance images by expert raters to estimate reliability and AD-related atrophy. Results Intra- and interrater reliability were more than 0.96 and 0.92, respectively, except for the alveus/fimbria, which were 0.86 and 0.77, respectively. Of all AD-related atrophy, the minimum hippocampus contributed to 67%; tail, 24%; alveus/fimbria, 4%; and the subiculum, 5%. Conclusions Anatomic landmark variability in available protocols can be reduced to four discrete and measurable segmentation units. Their quantitative assessment will help a Delphi panel to define a set of landmarks for a harmonized protocol.

OBJECTIVES: Previous neuroimaging studies have reported abnormalities in white matter (WM) pathways in subjects at high familial risk of mood disorders. In the current study, we examined the trajectory of these abnormalities during the early stages of illness development using longitudinal diffusion tensor imaging (DTI) data.METHODS: Subjects (16-28 years old) were recruited in the Scottish Bipolar Family Study, a prospective longitudinal study that has examined individuals at familial risk of mood disorder on three occasions, 2 years apart. The current study concerns imaging data from the first and second assessments. We analysed DTI data for 43 controls and 69 high-risk individuals who were further subdivided into a group of 53 high-risk subjects who remained well (high-risk well) and 16 who met diagnostic criteria for major depressive disorder (high-risk MDD) at follow-up. Longitudinal differences in fractional anisotropy (FA) between groups based on diagnostic status were investigated using the tract-based spatial statistics technique (TBSS).RESULTS: We found a significant reduction in FA (Pcorr CONCLUSIONS: These results suggest that there are similar trajectories of FA reductions for controls and high-risk young adults, despite high-risk individuals being at a disadvantaged starting point considering their reduced WM integrity detected at baseline in previous studies. Difference in WM integrity between high-risk individuals and controls could therefore occur in earlier childhood and be a necessary but not sufficient condition to develop future mood disorders.

Diffusion tensor MRI‐based tractography was used to investigate white matter (WM) changes in the major limbic (i.e., fornix and cingulum) and cortico‐cortical association pathways [i.e., the uncinate fasciculus, the inferior fronto‐occipital fasciculus, the inferior longitudinal fasciculus (ILF), the superior longitudinal fasciculus, and the corpus callosum] in 25 Alzheimer's disease (AD) patients, 19 amnestic mild cognitive impairment (aMCI) patients, and 15 healthy controls (HC). Mean diffusivity (MD), fractional anisotropy (FA), as well as axial (DA) and radial (DR) diffusivities were measured for each tract, using an atlas‐based tractography approach. The association of WM tract integrity with hippocampal volume was also assessed. MD values were significantly different among groups in all WM tracts (P values ranging from 0.002 to 0.03), except in the fornix (P = 0.06) and the inferior fronto‐occipital fasciculus (P = 0.09). Conversely, FA was significantly different among groups in the fornix only (P = 0.02). DA values were significantly different among groups in all WM tracts (P values ranging from 0.001 to 0.01), except in the fornix (P = 0.13) and the cingulum (P = 0.29). Significantly different DR values among groups were found in the fornix (P = 0.02) and the ILF (P = 0.01). In the fornix and cingulum, DR was significantly more increased than DA in both patient groups compared to HC. No difference in DA versus DR was found in cortico‐cortical WM tracts. DA values in the fornix were significantly correlated with the hippocampal volume. This study demonstrates a different pattern of WM involvement in the limbic and cortico‐cortical association pathways in aMCI and AD patients. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.

The use of hippocampal volumetry as a biomarker for Alzheimer's disease (AD) requires that tracers from different laboratories comply with the same segmentation method. Here we present a platform for training and qualifying new tracers to perform the manual segmentation of the hippocampus on magnetic resonance images (MRI) following the European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (EADC-ADNI) Harmonized Protocol (HarP). Our objective was to demonstrate that the training process embedded in the platform leads to increased compliance and qualification with the HarP.Thirteen new tracers' segmentations were compared with benchmark images with respect to: (a) absolute segmentation volume; (b) spatial overlap of contour with the reference using the Jaccard similarity index; and (c) spatial distance of contour with the reference. Point by point visual feedback was provided through three training phases on 10 MRI. Tracers were then tested on 10 different MRIs in the qualification phase.Statistical testing of training over three phases showed a significant increase of Jaccard (i.e. mean Jaccard overlap P .001) between phases on average for all raters, demonstrating that training positively increased compliance with the HarP. Based on these results we defined qualification thresholds which all tracers were able to meet.This platform is an adequate infrastructure allowing standardized training and evaluation of tracers' compliance with the HarP. This is a necessary step allowing the use of hippocampal volumetry as a biomarker for AD in clinical and research centers.

Background A globally harmonized protocol (HarP) for manual hippocampal segmentation based on magnetic resonance has been recently developed by a task force from European Alzheimer's Disease Consortium (EADC) and Alzheimer's Disease Neuroimaging Initiative (ADNI). Our aim was to produce benchmark labels based on the HarP for manual segmentation. Methods Five experts of manual hippocampal segmentation underwent specific training on the HarP and segmented 40 right and left hippocampi from 10 ADNI subjects on both 1.5 T and 3 T scans. An independent expert visually checked segmentations for compliance with the HarP. Descriptive measures of agreement between tracers were intraclass correlation coefficients (ICCs) of crude volumes and similarity coefficients of three-dimensional volumes. Results Two hundred labels have been provided for the 20 magnetic resonance images. Intra- and interrater ICCs were >0.94, and mean similarity coefficients were 1.5 T, 0.73 (95% confidence interval [CI], 0.71–0.75); 3 T, 0.75 (95% CI, 0.74–0.76). Conclusion Certified benchmark labels have been produced based on the HarP to be used for tracers' training and qualification.

BackgroundThis study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation.MethodsThe panel received a questionnaire regarding whole hippocampus boundaries and segmentation procedures. Quantitative information was supplied to allow evidence-based answers. A recursive and anonymous Delphi procedure was used to achieve convergence. Significance of agreement among panelists was assessed by exact probability on Fisher's and binomial tests.ResultsAgreement was significant on the inclusion of alveus/fimbria (P = .021), whole hippocampal tail (P = .013), medial border of the body according to visible morphology (P = .0006), and on this combined set of features (P = .001). This definition captures 100% of hippocampal tissue, 100% of Alzheimer’s disease-related atrophy, and demonstrated good reliability on preliminary intrarater (0.98) and inter-rater (0.94) estimates.DiscussionConsensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol. published

Manual segmentation from magnetic resonance imaging (MR) is the gold standard for evaluating hippocampal atrophy in Alzheimer's disease (AD). Nonetheless, different segmentation protocols provide up to 2.5-fold volume differences. Here we surveyed the most frequently used segmentation protocols in the AD literature as a preliminary step for international harmonization. The anatomical landmarks (anteriormost and posteriormost slices, superior, inferior, medial, and lateral borders) were identified from 12 published protocols for hippocampal manual segmentation ([Abbreviation] first author, publication year: [B] Bartzokis, 1998; [C] Convit, 1997; [dTM] deToledo-Morrell, 2004; [H] Haller, 1997; [J] Jack, 1994; [K] Killiany, 1993; [L] Lehericy, 1994; [M] Malykhin, 2007; [Pa] Pantel, 2000; [Pr] Pruessner, 2000; [S] Soininen, 1994; [W] Watson, 1992). The hippocampi of one healthy control and one AD patient taken from the 1.5T MR ADNI database were segmented by a single rater according to each protocol. The accuracy of the protocols' interpretation and translation into practice was checked with lead authors of protocols through individual interactive web conferences. Semantically harmonized landmarks and differences were then extracted, regarding: (a) the posteriormost slice, protocol [B] being the most restrictive, and [H, M, Pa, Pr, S] the most inclusive; (b) inclusion [C, dTM, J, L, M, Pr, W] or exclusion [B, H, K, Pa, S] of alveus/fimbria; (c) separation from the parahippocampal gyrus, [C] being the most restrictive, [B, dTM, H, J, Pa, S] the most inclusive. There were no substantial differences in the definition of the anteriormost slice. This survey will allow us to operationalize differences among protocols into tracing units, measure their impact on the repeatability and diagnostic accuracy of manual hippocampal segmentation, and finally develop a harmonized protocol.

Histologic studies show that the amygdala is affected by Alzheimer disease (AD) pathology, and its medial aspect is the most involved. We aimed to assess in vivo local structural differences in the amygdala of patients with AD using high-field MRI.A total of 19 patients with AD (mean age 76, SD 6 years, mean Mini-Mental State Examination score [MMSE] 13, SD 4) and 19 healthy elderly controls (age 74, SD 5, MMSE 29, SD 1) were enrolled. The radial atrophy mapping technique was used to reconstruct the 3-dimensional surface of the amygdala. Maps of surface tissue loss in patients with AD vs controls were computed and statistically tested with permutation tests thresholded at p0.05, to correct for multiple comparisons. A digital atlas of the amygdalar nuclei was used to infer which nuclei were involved.Both amygdalar volumes were significantly smaller in patients with AD (right 1,508 mm³, SD 418; left 1,646, SD 419) than controls (right 2,129 mm³, SD 316; left 2,077, SD 376; p0.002). In the dorsomedial part, significant local tissue loss (20%-30%) was mapped in the medial and central nuclei. Ventrally, the lateral nucleus (La) and the basolateral ventral medial nucleus (BLVM) were also involved (20%-30% loss).We found in vivo local structural differences in the amygdala of patients with AD. The nuclei involved have known connections to the hippocampus (BLVM, La) and olfactory system (medial nucleus) and with cholinergic pathways (central nucleus). This pattern is consistent with the known pathophysiology of neural systems affected by AD.

Detecting morphological changes in the brain is important for a better understanding of normal aging and brain disorders. Growing and Adaptive MEshes (GAMEs) is a multi-dimensional method for modeling complex brain structures and highlight significant differences between groups, such as healthy subjects versus patients with Alzheimer disease (AD). In this work, we have extended the functionalities of GAMEs by introducing a multidimensional analysis of linear correlation between local morphological changes and other independent variables, thus allowing for epidemiological studies. The new algorithm has been validated on a challenging medical application: the correlation of morphological changes in hippocampi and thalamus with the MMSE score, in a population of healthy subjects and patients with AD.

In this study, we investigated the use of hippocampal shape-based markers for automatic detection of Alzheimer's disease (AD) and mild cognitive impairment converters (MCI-c). Three-dimensional T1-weighted magnetic resonance images of 50 AD subjects, 50 age-matched controls, 15 MCI-c, and 15 MCI-non-converters (MCI-nc) were taken. Manual delineations of both hippocampi were obtained from normalized images. Fully automatic shape modeling was used to generate comparable meshes for both structures. Repeated permutation tests, run over a randomly sub-sampled training set (25 controls and 25 ADs), highlighted shape-based markers, mostly located in the CA1 sector, which consistently discriminated ADs and controls. Support vector machines (SVMs) were trained, using markers from either one or both hippocampi, to automatically classify control and AD subjects. Leave-1-out cross-validations over the remaining 25 ADs and 25 controls resulted in an optimal accuracy of 90% (sensitivity 92%), for markers in the left hippocampus. The same morphological markers were used to train SVMs for MCI-c versus MCI-nc classification: markers in the right hippocampus reached an accuracy (and sensitivity) of 80%. Due to the pattern recognition framework, our results statistically represent the expected performances of clinical set-ups, and compare favorably to analyses based on hippocampal volumes.

Histological studies have suggested differing involvement of the hippocampal subfields in ageing and in Alzheimer's disease. The aim of this study was to assess in vivo local hippocampal changes in ageing and Alzheimer's disease based on high resolution MRI at 3 Tesla. T(1)-weighted images were acquired from 19 Alzheimer's disease patients [age 76 +/- 6 years, three males, Mini-Mental State Examination 13 +/- 4] and 19 controls (age 74 +/- 5 years, 11 males, Mini-Mental State Examination 29 +/- 1). The hippocampal formation was isolated by manual tracing. Radial atrophy mapping was used to assess group differences and correlations by averaging hippocampal shapes across subjects using 3D parametric surface mesh models. Percentage difference, Pearson's r, and significance maps were produced. Hippocampal volumes were inversely correlated with age in older healthy controls (r = 0.56 and 0.6 to the right and left, respectively, P < 0.05, corresponding to 14% lower volume for every 10 years of older age from ages 65 to 85 years). Ageing-associated atrophy mapped to medial and lateral areas of the tail and body corresponding to the CA1 subfield and ventral areas of the head corresponding to the presubiculum. Significantly increased volume with older age mapped to a few small spots mainly located to the CA1 sector of the right hippocampus. Volumes were 35% and 30% smaller in Alzheimer's disease patients to the right and left (P < 0.0005). Alzheimer's disease-associated atrophy mapped not only to CA1 areas of the body and tail corresponding to those also associated with age, but also to dorsal CA1 areas of the head unaffected by age. Regions corresponding to the CA2-3 fields were relatively spared in both ageing and Alzheimer's disease. Hippocampal atrophy in Alzheimer's disease maps to areas in the body and tail that partly overlap those affected by normal ageing. Specific areas in the anterior and dorsal CA1 subfield involved in Alzheimer's disease were not in normal ageing. These patterns might relate to differential neural systems involved in Alzheimer's disease and ageing.

Objective: To define a harmonized protocol for manual hippocampal segmentation from magnetic resonance scans. Background Heterogeneity of landmarks among protocols leads to different volume estimates, hampering comparison of studies and clinical use. Landmark differences among the 12 most common protocols were extracted, operationalized, and quantitatively investigated. The results were presented to the Delphi panel, consisting of seventeen researchers with substantial expertise in hippocampal segmentation, to reach an evidence-based consensus on segmentation landmarks. Design/Methods: The Delphi panel participated in recursive anonymous voting sessions where feedback from previous rounds was utilized to progressively facilitate panelists9 agreement. Panelists were presented with tracing alternatives, each associated with quantitative data relating: (i) reliability, (ii) impact on whole hippocampal volume, and (iii) correlation with AD pathology. Panelists were asked to choose among alternatives and provide justification and comments. Anonymous votes and comments, and voting statistics of the first round were fed into the second Delphi round. Exact probability on binomial test of the choice was computed. At the time of writing, two Delphi rounds were completed. Results: Sixteen panelists completed both Delphi rounds. Agreement was significant on inclusion of alveus and fimbria (81%, p=0.021), of the whole visible hippocampal tail (75%, p=0.035), and approached significance for the segmentation of the medial border of the body following visible morphology (69%, p=0.057). Agreement on including the minimum hippocampus, alveus, morphological subiculum, whole hippocampal tail in the final hippocampal tracing protocol was significant (88%, p=0.001). Based on the previous quantitative investigation of landmark differences, the hippocampus so defined covers 100% of hippocampal tissue, captures 100% of AD-related atrophy, and has good intra-rater (0.99) and inter-rater (0.94) reliability measured on volume statistics. Conclusions: The most “inclusive” landmarks were preferred by Delphi panelists. Further rounds will be run to seek statistically significant agreement for all aspects. Supported by: Alzheimer9s Association. Lilly International. Wyeth International (Pfizer Group). Disclosure: Dr. Boccardi has nothing to disclose. Dr. Bocchetta has nothing to disclose. Dr. Apostolova has nothing to disclose. Dr. Barnes has nothing to disclose. Dr. Bartzokis has received personal compensation for activities with Bristol-Myers Squibb Company and Novartis. Dr. Bartzokis has received research support from Novartis and Janssen Pharmaceutica. Dr. Corbetta has nothing to disclose. Dr. DeCarli has received personal compensation for activities wtih Merck Pharmaceutical, Avanir, Bayer Pharmaceuticals, and Pfizer as a consultant.Dr. DeCarli has received personal compensation in an editorial capacity for Alzheimer9s Disease and Associated Disorders.Dr. DeCarli has received research support from Merck. Dr. DeToledo-Morrell has nothing to disclose. Dr. Firbank has nothing to disclose. Dr. Ganzola has nothing to disclose. Dr. Gerritsen has nothing to disclose. Dr. Henneman has nothing to disclose. Dr. Killiany has received personal compensation for activities with Sunovion Pharmaceuticals Inc as a consultant. Dr. Killiany has received research support from The MRI Centers of New England and a clinical affiliation with Essex Neurological Associates. Dr. Malykhin has nothing to disclose. Dr. Pasqualetti has nothing to disclose. Dr. Pruessner has nothing to disclose. Dr. Redolfi has nothing to disclose. Dr. Robitaille has nothing to disclose. Dr. Soininen has received personal compensation for activities with ACImmune. Dr. Tolomeo has nothing to disclose. Dr. Wang has nothing to disclose. Dr. Watson has nothing to disclose. Dr. Wolf has nothing to disclose. Dr. Duchesne has received (royalty or license fee or contractual rights) payments from Screen Inc.Dr. Duchesne has received research support from Afga Healthcare Inc. Dr. Jack has received personal compensation for activities with Janssen Pharmaceutica, Eisai Inc, General Electric, Johnson and Johnson, and Eli Lilly & Company as a consultant.Dr. Jack has received research support from Pfizer Inc, Allon, and Baxter, Inc. Dr. Frisoni has received personal compensation for activities Eli Lilly & Company, Bristol-Myers Squibb Company, Bayer Healthcare, Lundbeck Research USA, Inc., Elan Corporation, AstraZeneca Pharmaceuticals, Pfizer Inc, Baxter, Taurx, and Wyeth Pharmaceuticals. Dr. Frisoni has received personal compensation in an editorial capacity for Lancet Neurology, Aging Clinical & Experimental Research, Neurobiology of Aging, Alzheimer9s Diseases and Associated Disorders, and Neurogenerative Diseases. Dr. Frisoni has received research support from Wyeth Corporation, Eli Lilly & Company, Lundbeck Research USA, Inc.