Hippocampal Subfield Segmentation Research Articles

Optimization and validation of automated hippocampal subfield segmentation across the lifespan.

Automated segmentation of hippocampal (HC) subfields from magnetic resonance imaging (MRI) is gaining popularity, but automated procedures that afford high speed and reproducibility have yet to be extensively validated against the standard, manual morphometry. We evaluated the concurrent validity of an automated method for hippocampal subfields segmentation (automated segmentation of hippocampal subfields, ASHS; Yushkevich et al., ) using a customized atlas of the HC body, with manual morphometry as a standard. We built a series of customized atlases comprising the entorhinal cortex (ERC) and subfields of the HC body from manually segmented images, and evaluated the correspondence of automated segmentations with manual morphometry. In samples with age ranges of 6-24 and 62-79 years, 20 participants each, we obtained validity coefficients (intraclass correlations, ICC) and spatial overlap measures (dice similarity coefficient) that varied substantially across subfields. Anterior and posterior HC body evidenced the greatest discrepancies between automated and manual segmentations. Adding anterior and posterior slices for atlas creation and truncating automated output to the ranges manually defined by multiple neuroanatomical landmarks substantially improved the validity of automated segmentation, yielding ICC above 0.90 for all subfields and alleviating systematic bias. We cross-validated the developed atlas on an independent sample of 30 healthy adults (age 31-84) and obtained good to excellent agreement: ICC (2) = 0.70-0.92. Thus, with described customization steps implemented by experts trained in MRI neuroanatomy, ASHS shows excellent concurrent validity, and can become a promising method for studying age-related changes in HC subfield volumes.

HIPS: A new hippocampus subfield segmentation method

The importance of the hippocampus in the study of several neurodegenerative diseases such as Alzheimer's disease makes it a structure of great interest in neuroimaging. However, few segmentation methods have been proposed to measure its subfields due to its complex structure and the lack of high resolution magnetic resonance (MR) data. In this work, we present a new pipeline for automatic hippocampus subfield segmentation using two available hippocampus subfield delineation protocols that can work with both high and standard resolution data. The proposed method is based on multi-atlas label fusion technology that benefits from a novel multi-contrast patch match search process (using high resolution T1-weighted and T2-weighted images). The proposed method also includes as post-processing a new neural network-based error correction step to minimize systematic segmentation errors. The method has been evaluated on both high and standard resolution images and compared to other state-of-the-art methods showing better results in terms of accuracy and execution time.

Segmenting hippocampal subfields from 3T MRI with multi-modality images.

Hippocampal subfields play important roles in many brain activities. However, due to the small structural size, low signal contrast, and insufficient image resolution of 3T MR, automatic hippocampal subfields segmentation is less explored. In this paper, we propose an automatic learning-based hippocampal subfields segmentation method using 3T multi-modality MR images, including structural MRI (T1, T2) and resting state fMRI (rs-fMRI). The appearance features and relationship features are both extracted to capture the appearance patterns in structural MR images and also the connectivity patterns in rs-fMRI, respectively. In the training stage, these extracted features are adopted to train a structured random forest classifier, which is further iteratively refined in an auto-context model by adopting the context features and the updated relationship features. In the testing stage, the extracted features are fed into the trained classifiers to predict the segmentation for each hippocampal subfield, and the predicted segmentation is iteratively refined by the trained auto-context model. To our best knowledge, this is the first work that addresses the challenging automatic hippocampal subfields segmentation using relationship features from rs-fMRI, which is designed to capture the connectivity patterns of different hippocampal subfields. The proposed method is validated on two datasets and the segmentation results are quantitatively compared with manual labels using the leave-one-out strategy, which shows the effectiveness of our method. From experiments, we find a) multi-modality features can significantly increase subfields segmentation performance compared to those only using one modality; b) automatic segmentation results using 3T multi-modality MR images could be partially comparable to those using 7T T1 MRI.

Development of a histologically validated segmentation protocol for the hippocampal body

BackgroundRecent findings have demonstrated that hippocampal subfields can be selectively affected in different disease states, which has led to efforts to segment the human hippocampus with in vivo magnetic resonance imaging (MRI). However, no studies have examined the histological accuracy of subfield segmentation protocols. The presence of MRI-visible anatomical landmarks with known correspondence to histology represents a fundamental prerequisite for in vivo hippocampal subfield segmentation. In the present study, we aimed to: 1) develop a novel method for hippocampal body segmentation, based on two MRI-visible anatomical landmarks (stratum lacunosum moleculare [SLM] & dentate gyrus [DG]), and assess its accuracy in comparison to the gold standard direct histological measurements; 2) quantify the accuracy of two published segmentation strategies in comparison to the histological gold standard; and 3) apply the novel method to ex vivo MRI and correlate the results with histology. MethodsUltra-high resolution ex vivo MRI was performed on six whole cadaveric hippocampal specimens, which were then divided into 22 blocks and histologically processed. The hippocampal bodies were segmented into subfields based on histological criteria and subfield boundaries and areas were directly measured. A novel method was developed using mean percentage of the total SLM distance to define subfield boundaries. Boundary distances and subfield areas on histology were then determined using the novel method and compared to the gold standard histological measurements. The novel method was then used to determine ex vivo MRI measures of subfield boundaries and areas, which were compared to histological measurements. ResultsFor direct histological measurements, the mean percentages of total SLM distance were: Subiculum/CA1 = 9.7%, CA1/CA2 = 78.4%, CA2/CA3 = 97.5%. When applied to histology, the novel method provided accurate measures for CA1/CA2 (ICC = 0.93) and CA2/CA3 (ICC = 0.97) boundaries, but not for the Subiculum/CA1 (ICC = −0.04) boundary. Accuracy was poorer using previous techniques for CA1/CA2 (maximum ICC = 0.85) and CA2/CA3 (maximum ICC = 0.88), with the previously reported techniques also performing poorly in defining the Subiculum/CA1 boundary (maximum ICC = 0.00). Ex vivo MRI measurements using the novel method were linearly related to direct measurements of SLM length (r2 = 0.58), CA1/CA2 boundary (r2 = 0.39) and CA2/CA3 boundary (r2 = 0.47), but not for Subiculum/CA1 boundary (r2 = 0.01). Subfield areas measured with the novel method on histology and ex vivo MRI were linearly related to gold standard histological measures for CA1, CA2, and CA3/CA4/DG. ConclusionsIn this initial proof of concept study, we used ex vivo MRI and histology of cadaveric hippocampi to develop a novel segmentation protocol for the hippocampal body. The novel method utilized two anatomical landmarks, SLM & DG, and provided accurate measurements of CA1, CA2, and CA3/CA4/DG subfields in comparison to the gold standard histological measurements. The relationships demonstrated between histology and ex vivo MRI supports the potential feasibility of applying this method to in vivo MRI studies.

Regional tau deposition and subregion atrophy of medial temporal structures in early Alzheimer's disease: A combined positron emission tomography/magnetic resonance imaging study

IntroductionMolecular imaging and selective hippocampal subfield atrophy are a focus of recent Alzheimer's disease (AD) research. Here, we investigated correlations between molecular imaging and hippocampal subfields in early AD. MethodsWe investigated 18 patients with early AD and 18 healthy control subjects using 11C-Pittsburgh compound-B (PIB) positron emission tomography (PET) and 18F-THK5351 PET and automatic segmentation of hippocampal subfields with high-resolution T2-weighted magnetic resonance imaging. The PET images were normalized and underwent voxelwise regression analysis with each subregion volumes using SPM12. ResultsAs for 18F-THK5351 PET, the bilateral perirhinal cortex volumes were significantly associated with the ipsilateral or bilateral temporal lobar uptakes, whereas hippocampal subfields showed no correlations. 11C-PIB PET showed relatively broad negative correlation with the right cornu ammonis 3 volumes. DiscussionRegional tau deposition was correlated with extrahippocampal subregional atrophy and not with hippocampal subfields, possibly reflecting different underlying mechanisms of atrophy in early AD. Amyloid might be associated with right cornu ammonis 3 atrophy.

Dentate gyrus-cornu ammonis (CA) 4 volume is decreased and associated with depressive episodes and lipid peroxidation in bipolar II disorder: Longitudinal and cross-sectional analyses.

Reduced dentate gyrus volume and increased oxidative stress have emerged as potential pathophysiological mechanisms in bipolar disorder. However, the relationship between dentate gyrus volume and peripheral oxidative stress markers remains unknown. Here, we examined dentate gyrus-cornu ammonis (CA) 4 volume longitudinally in patients with bipolar II disorder (BD-II) and healthy controls and investigated whether BD-II is associated with elevated peripheral levels of oxidative stress. We acquired high-resolution structural 3T-magnetic resonance imaging (MRI) images and quantified hippocampal subfield volumes using an automated segmentation algorithm in individuals with BD-II (n=29) and controls (n=33). The participants were scanned twice, at study inclusion and on average 2.4years later. In addition, we measured peripheral levels of two lipid peroxidation markers (4-hydroxy-2-nonenal [4-HNE] and lipid hydroperoxides [LPH]). First, we demonstrated that the automated hippocampal subfield segmentation technique employed in this work reliably measured dentate gyrus-CA4 volume. Second, we found a decreased left dentate gyrus-CA4 volume in patients and that a larger number of depressive episodes between T1 and T2 predicted greater volume decline. Finally, we showed that 4-HNE was elevated in BD-II and that 4-HNE was negatively associated with left and right dentate gyrus-CA4 volumes in patients. These results are consistent with a role for the dentate gyrus in the pathophysiology of bipolar disorder and suggest that depressive episodes and elevated oxidative stress might contribute to hippocampal volume decreases. In addition, these findings provide further support for the hypothesis that peripheral lipid peroxidation markers may reflect brain alterations in bipolar disorders.

Structural differences in hippocampal subfields among schizophrenia patients, major depressive disorder patients, and healthy subjects

Many MRI studies have reported a volume reduction of the hippocampus in psychiatric diseases. However, disease-related volume differences in hippocampus subfields remain unclear. Here we compared the volumes of hippocampus subfields in patients with schizophrenia, patients with major depressive disorder (MDD), and healthy subjects as controls. T2-weighted images were acquired in 20 patients with schizophrenia, 36 with MDD, and 35 healthy volunteers by 3-Tesla MRI. Hippocampal subfields were segmented using an automatic algorithm, Automatic Segmentation of Hippocampal Subfields (ASHS). Schizophrenia patients exhibited significant volume reductions in the cornu ammonis (CA)1 compared to the controls, and in the dentate gyrus compared to the controls and MDD patients without medication, whereas there was no significant difference between the MDD patients and controls. There was a nominal negative correlation between the perirhinal cortex volume and depression severity in the MDD patients without medication, whereas there were negative correlations between CA2 volume and both negative symptoms and the duration of illness in the schizophrenia patients. We identified differing volume reductions in hippocampal subfields and varying correlations between disease severity and subfield volumes depending on diagnosis, suggesting that volume differences in hippocampus subfields may provide important information regarding the pathophysiology of schizophrenia and MDD.

Depressive symptoms modify age effects on hippocampal subfields in older adults.

Major depression is associated with hippocampal volume changes, especially in late-life depression. These changes usually consist of volume reductions, but depression-related increases in hippocampal volume have also been reported. Subfield analysis has identified structural changes primarily in the cornu ammonis (CA) 1, CA2-3 and subiculum of the hippocampus in individuals with major depression; however, it is unclear whether lower levels of depressive symptoms are also associated volume reduction, or if depressive symptoms interact with age to impact hippocampal subfields. The current study addressed these questions. A total of 43 community-dwelling older adults completed the Center for Epidemiologic Studies Depression Scale and underwent magnetic resonance imaging. Hippocampal subfield segmentation was carried out using an automated procedure, and left and right volumes from CA1, CA2-3, and the subiculum served as outcome measures. Multiple hierarchical regressions were carried out with age, Center for Epidemiologic Studies Depression Scale scores and their interaction as the independent variables, and sex and total intracranial volume as covariates. Higher Center for Epidemiologic Studies Depression Scale scores were associated with less age-related volumetric decreases in the right subiculum and right CA1. Age-related atrophy in the hippocampus might be counteracted by depressive symptom-related enlargement of CA1 and the subiculum. More research is required to better understand the functional significance of this relationship. Geriatr Gerontol Int 2017; 17: 1494-1500.

Building a Surface Atlas of Hippocampal Subfields From High Resolution T2-weighted MRI Scans Using Landmark-free Surface Registration.

The hippocampus is widely studied in neuroimaging field as it plays important roles in memory and learning. However, the critical subfield information is often not explored in most hippocampal studies. We previously proposed a method for hippocampal subfield morphometry by integrating FreeSurfer, FSL, and SPHARM tools. But this method had some limitations, including the analysis of T1-weighted MRI scans without detailed subfield information and hippocampal registration without using important subfield information. To bridge these gaps, in this work, we propose a new framework for building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans by integrating state-of-the-art methods for automated segmentation of hippocampal subfields and landmark-free, subfield-aware registration of hippocampal surfaces. Our experimental results have shown the promise of the new framework.

Dissociated Accumbens and Hippocampal Structural Abnormalities across Obesity and Alcohol Dependence.

Background:Processing of food and drug rewards involves specific neurocircuitry, and emerging evidence implicates subcortical abnormalities, particularly the nucleus accumbens and hippocampus. We specifically hypothesized that these 2 established regions in addiction neurocircuitry are associated with distinctive in vivo structural abnormalities in obesity and alcohol dependence.Methods:To specifically investigate anatomically discrete volumetric changes associated with overconsumption of different rewards, we acquired T1 MRI data from 118 subjects in 3 groups comprising obesity (n=42), alcohol dependence (n=32), and healthy volunteer controls (n=44). To exploit novel methods of automated hippocampal subfield segmentation, we used Freesurfer software to generate volumetric data in subject groups for the hippocampal subiculum and its major striatal efferent target, the nucleus accumbens. Hypothesis-led, selective group difference comparisons were analyzed.Results:We found markedly greater accumbens volumes (P=.002) and relatively preserved hippocampal subfield volumes in obesity. Conversely, in alcohol dependence, we found preserved accumbens volumes but atrophy of specific ventral hippocampal subfields, the subiculum and presubiculum. Smaller global subcortical gray-matter volume was found in the alcohol dependence group only.Conclusions:Reward neurocircuitry including the accumbens and ventral hippocampus may show key structural abnormalities in disorders involving processing of both food and drug rewards, although the foci of disruption may vary as a function of reward modality. Structural differences may subserve altered reward and motivational processes in obesity and alcohol dependence and represent a potential biomarker for therapeutic targeting in key public health disorders.

Hippocampal subfield volumetry in patients with subcortical vascular mild cognitive impairment.

Memory impairment is a typical characteristic of patients with subcortical vascular mild cognitive impairment (svMCI) or with amnestic mild cognitive impairment (aMCI). The hippocampus, which plays an important role in the consolidation of information from short-term memory to long-term memory, is a heterogeneous structure that consists of several anatomically and functionally distinct subfields. However, whether distinct hippocampal subfields are differentially and selectively affected by svMCI pathology and whether these abnormal changes in hippocampal subfields are different between svMCI and aMCI patients are largely unknown. A total of 26 svMCI patients, 26 aMCI patients and 26 healthy controls matched according to age, gender and years of education were enrolled in this study. We utilized an automated hippocampal subfield segmentation method provided by FreeSurfer to estimate the volume of several hippocampal subfields, including the cornu ammonis (CA) areas, the dentate gyrus (DG), the subiculum and the presubiculum. Compared with controls, the left subiculum and presubiculum and the right CA4/DG displayed significant atrophy in patients with svMCI. Interestingly, we also found significant differences in the volume of the right CA1 between the svMCI and aMCI groups. Taken together, our results reveal region-specific vulnerability of hippocampal subfields to svMCI pathology and identify distinct hippocampal subfield atrophy patterns between svMCI and aMCI patients.

Automated subfield volumetric analysis of hippocampus in temporal lobe epilepsy using high-resolution T2-weighed MR imaging.

Background and purposeAutomated subfield volumetry of hippocampus is desirable for use in temporal lobe epilepsy (TLE), but its utility has not been established. Automatic segmentation of hippocampal subfields (ASHS) and the new version of FreeSurfer software (ver.6.0) using high-resolution T2-weighted MR imaging are candidates for this volumetry. The aim of this study was to evaluate hippocampal subfields in TLE patients using ASHS as well as the old and new versions of FreeSurfer.Materials and methodsWe recruited 50 consecutive unilateral TLE patients including 25 with hippocampal sclerosis (TLE-HS) and 25 without obvious etiology (TLE-nonHS). All patients and 45 healthy controls underwent high-resolution T2-weighted and 3D-volume T1-weighted MRI scanning. We analyzed all of their MR images by FreeSurfer ver.5.3, ver.6.0 and ASHS. For each subfield, normalized z-scores were calculated and compared among groups.ResultsIn TLE-HS groups, ASHS and FreeSurfer ver.6.0 revealed maximal z-scores in ipsilateral cornu ammonis (CA) 1, CA4 and dentate gyrus (DG), whereas in FreeSurfer ver.5.3 ipsilateral subiculum showed maximal z-scores. In TLE-nonHS group, there was no significant volume reduction by either ASHS or FreeSurfer.ConclusionsASHS and the new version of FreeSurfer may have an advantage in compatibility with existing histopathological knowledge in TLE patients with HS compared to the old version of FreeSurfer (ver.5.3), although further investigations with pathological findings and/or surgical outcomes are desirable.

Detailed segmentation of human hippocampal and subicular subfields using a combined approach

Hippocampal and subicular subfields (dentate gyrus, CA4, CA3, CA2, CA1, prosubiculum, subiculum, presubiculum and parasubiculum) of human brains have become the major targets of extensive ex vivo and in vivo neuroimaging studies. The subfield segmentation in previous studies relied heavily on parcellation based on conventional Nissl stains. Our recent study (Ding and Van Hoesen, J Comp Neurol, 523:2233-2253, 2015), however, has revealed significantly more reliable and accurate parcellation of all the subfields in both hippocampal head and body regions using a combined approach. This approach combines traditional Nissl staining and modern neurochemical labeling on closely adjacent sections. The resulting atlases of human hippocampi in our recent study are further supported by gene expression patterns in each subfield and thus will provide a very helpful guide for hippocampal and subicular segmentation on neuroimaging scans. A comparison of our recent results with those in previous studies is also discussed.

Automatic Hippocampal Subfield Segmentation from 3T Multi-modality Images.

Hippocampal subfields play important and divergent roles in both memory formation and early diagnosis of many neurological diseases, but automatic subfield segmentation is less explored due to its small size and poor image contrast. In this paper, we propose an automatic learning-based hippocampal subfields segmentation framework using multi-modality 3TMR images, including T1 MRI and resting-state fMRI (rs-fMRI). To do this, we first acquire both 3T and 7T T1 MRIs for each training subject, and then the 7T T1 MRI are linearly registered onto the 3T T1 MRI. Six hippocampal subfields are manually labeled on the aligned 7T T1 MRI, which has the 7T image contrast but sits in the 3T T1 space. Next, corresponding appearance and relationship features from both 3T T1 MRI and rs-fMRI are extracted to train a structured random forest as a multi-label classifier to conduct the segmentation. Finally, the subfield segmentation is further refined iteratively by additional context features and updated relationship features. To our knowledge, this is the first work that addresses the challenging automatic hippocampal subfields segmentation using 3T routine T1 MRI and rs-fMRI. The quantitative comparison between our results and manual ground truth demonstrates the effectiveness of our method. Besides, we also find that (a) multi-modality features significantly improved subfield segmentation performance due to the complementary information among modalities; (b) automatic segmentation results using 3T multimodality images are partially comparable to those on 7T T1 MRI.

Extensive learning is associated with gray matter changes in the right hippocampus

Longitudinal voxel-based morphometry studies have demonstrated increases in gray matter volume in hippocampal areas following extensive cognitive learning. Moreover, there is increasing evidence for the relevance of the subiculum in the context of learning and memory. Using longitudinal FreeSurfer analyses and hippocampus subfield segmentation the present study investigated the effects of 14weeks of intensive learning on hippocampal and subicular gray matter volume in a sample of medical students compared to control subjects not engaged in any cognitive learning activities. We found that extensive learning resulted in a significant increase of right hippocampal volume. Volume of the left hippocampus and the subiculum remained unchanged. The current findings emphasize the role of the hippocampus in semantic learning and memory processes and provide further evidence for the neuroplastic ability of the hippocampus in the context of cognitive learning.

Assessment of PET & ASL metabolism in the hippocampal subfields of MCI and AD using simultaneous PET-MR.

Alzheimer’s disease (AD) has been reported to show decreased metabolic activity in the hippocampus using FDG PET-MR. Histological data suggests that the hippocampal subfields are selectively affected in AD. Given the simultaneous imaging nature of integrated PET-MR scanners and the multimodal capabilities of PET-MR, our purpose here is to assess FDG activity, as well as ASL perfusion in the subfields of MCI and AD patients. 10 consecutive subjects were recruited for this study 3 MCI, 3 AD patients and 4 age-matched controls. The scanning was performed on a simultaneous 3T PET/MR scanner. To delineate the hippocampal subfields, automatic segmentation of hippocampal subfields (ASHS) was employed. Static FDG-PET series were reconstructed for analysis at 45-75 min for all subjects. All imaging sequences were automatically registered to the oblique coronal T2-weighted images (segmentation space). PET standardized uptake values (SUV) in the hippocampal subfields were normalized by the pons. FDG PET metabolism was reduced significantly in AD, as well as MCI patients as compared to controls, with the highest effect demonstrated in the CA3/DG and CA1/2 (p = 0.047, subfields. Patients (MCI and AD combined) had decreased metabolism as compared to controls in CA1/2 and significantly smaller volumes the Subiculum. When assessing CBF across groups, a significant decrease in CBF was found in the Subiculum. Our preliminary results demonstrate that PET-MRI may potentially be a sensitive biomarker and tool for early diagnosis of AD. They also confirm the importance of assessing metabolic and structural changes of neurodegenerative diseases at the subfield level.

Amyloid Burden in Cognitively Normal Elderly is Associated with Preferential Hippocampal Subfield Volume Loss

The earliest sites of brain atrophy in Alzheimer's disease are in the medial temporal lobe, following widespread cerebral cortical amyloid deposition. We assessed 74 cognitively normal participants with clinical measurements, amyloid-β-PET imaging, MRI, and a newly developed technique for MRI-based hippocampal subfield segmentation to determine the differential association of amyloid deposition and hippocampal subfield volume. Compared to amyloid-negative participants, amyloid-positive participants had significantly smaller hippocampal tail, presubiculum, subiculum, and total hippocampal gray matter volumes. We conclude that, prior to the development of cognitive impairment, atrophy in particular hippocampal subfields occurs preferentially with amyloid-β accumulation.

A Critical Appraisal of the Hippocampal Subfield Segmentation Package in FreeSurfer.

A Critical Appraisal of the Hippocampal Subfield Segmentation Package in FreeSurfer.

Effects of low-level sarin and cyclosarin exposure on hippocampal subfields in Gulf War Veterans

BackgroundMore than 100,000 US troops were potentially exposed to chemical warfare agents sarin (GB) and cyclosarin (GF) when an ammunition dump at Khamisiyah, Iraq was destroyed during the 1991 Gulf War (GW). We previously reported reduced hippocampal volume in GW veterans with suspected GB/GF exposure relative to matched, unexposed GW veterans estimated from 1.5T magnetic resonance images (MRI). Here we investigate, in a different cohort of GW veterans, whether low-level GB/GF exposure is associated with structural alterations in specific hippocampal subfields, estimated from 4T MRI. MethodsThe Automatic Segmentation of Hippocampal Subfields (ASHS) technique was used to quantify CA1, CA2, CA3 and dentate gyrus (DG), and subiculum (SUB) subfields volumes from high-resolution T2-weighted images acquired on a 4T MR scanner in 56 GW veterans with suspected GB/GF exposure and 56 “matched” unexposed GW veterans (mean age 49±7 years). ResultsGB/GF exposed veterans had smaller CA2 (p=0.003) and CA3/DG (p=0.01) subfield volumes compared to matched, unexposed GW veterans. There were no group difference in total hippocampal volume, quantified with FreeSurfer, and no dose–response relationship between estimated levels of GB/GF exposure and total hippocampal or subfield volume. ConclusionsThese findings extend our previous report of structural alterations in the hippocampi of GW veterans with suspected GB/GF exposure to volume changes in the CA2, CA3, and DG hippocampal subfields in a different cohort of GW veterans with suspected GB/GF exposure.

ALTERED FMRI ACTIVATION PATTERN DURING VISUAL SCENE ENCODING IN AFFECTED AND NON-AFFECTED CARRIERS OF PSEN1 AND APP MUTATIONS

Background: Several studies highlighted the differential effect of normal and pathological aging on hippocampal subfield volumes, suggesting that these measurements may be more accurate than global hippocampal volumetry to detect early Alzheimer’s disease (AD). For clinical application, validated automatic algorithms of hippocampal subfield segmentation are urgently needed. An increasing number of studies use the automatic segmentation algorithm implemented in FreeSurfer. However, this approach has not been validated so far on AD patients. This study aimed to compare the accuracy of T1-MRI-based FreeSurfer segmentation versus manual delineation on dedicated high-resolution scan in measuring hippocampal subfield volumes and the effects of age and AD on these volumes. Methods: Hippocampal subfields were segmented in 98 healthy individuals (aged 19 to 84), 17 MCI and 18 AD patients using both FreeSurfer (T1-MRI, resolution: 1*1*1mm) and manual delineation (proton density-MRI, resolution: 0.375*0.375*2mm). Intraclass correlation coefficients (ICC) and Bland-Altman plots were computed to assess the consistency between both methods, and the effects of age (regressions) and group (ANOVAs) were assessed for both Freesurfuer and manual measurements. Results: Moderate to high ICCs were found for the subiculum and other subfields as well as for the whole hippocampus, but the ICC was very low for CA1. Using manual delineation, age was found to have a linear effect on the subiculum and a nonlinear (later) effect on CA1 volumes. A graded effect of the pathology was found on CA1, subiculum and the other subfields volumes. FreeSurfer CA1 volumes were found to be lower than those obtained from manual segmentation. This bias was proportional to the volume of this structure so that no effect of age or AD could be detected on FreeSurfer CA1 volumes. Conclusions: This study highlights differences in the anatomic definition of the subfields, especially for CA1, between FreeSurfer and manual delineation based on histologic atlases. While FreeSurfer provides reasonable estimates of the subiculum and other subfields, it does not provide a reliable estimate of CA1 volume and fails in detecting normal aging and AD-related changes in this subfield. As earliest AD-related changes seem to occur in CA1, FreeSurfer needs to be improved especially for clinical application in early AD diagnosis.