A fast approach for hippocampal segmentation from T1-MRI for predicting progression in Alzheimer's disease from elderly controls

Platero, Carlos A.; Tobar, M. Carmen

doi:10.1016/j.jneumeth.2016.06.013

Cited by 25 publications

(7 citation statements)

References 67 publications

(97 reference statements)

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“…To compare our segmentation accuracy of the whole hippocampus with the current literature, we also generated a binary segmentation of the hippocampus by merging the hippocampal subfield labels. The average DSCs of the whole hippocampus throughout all the experiments (including the ones that did not survive quality control) were 0.89±0.01 for 7T and 0.89±0.03 for 3T, which are comparable to the state-of-the-art methods [11, 22–25]. The DSC/GDSC values reported here for the subregions for 3T and 7T are similar to previously reported results in overlapping datasets [9, 19] but are slightly lower for some of the subregions, likely due to smaller overall atlas size in the experiments above.…”

Section: Discussionmentioning

confidence: 69%

Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer’s Disease at 3T and 7T: What Atlas Composition Works Best?

Xie

Shinohara

Ittyerah

et al. 2018

JAD

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Section: Discussionmentioning

confidence: 69%

Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer’s Disease at 3T and 7T: What Atlas Composition Works Best?

Xie

Shinohara

Ittyerah

et al. 2018

JAD

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“…Two other studies performed an evaluation of MTL cortices in younger adults and patients with temporal lobe epilepsy and reported DSC values in the same range (Hu, Coupé, Pruessner, & Collins, 2014; Kim, Caldairou, Bernasconi, & Bernasconi, 2018). With regard to hippocampus, our pipeline performs comparable to state-of-the-art methods (Collins & Pruessner, 2010; Coupé et al, 2011; Leung et al, 2010; Platero & Tobar, 2016; Wang et al, 2013). …”

Section: Discussionmentioning

confidence: 87%

Automated segmentation of medial temporal lobe subregions on in vivo T1‐weighted MRI in early stages of Alzheimer's disease

Xie

Wisse

Pluta

et al. 2019

Human Brain Mapping

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Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology—and thus are promising biomarkers for Alzheimer’s disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.

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“…Previous studies reported that earlier versions of FreeSurfer agree more closely with manual methods than other common tools, FSL/FIRST [Morey et al, 2009; Schoemaker et al, 2016] or IBASPM [Tae et al, 2008]. Some hippocampus-specific classification systems [Tangaro et al, 2014; Platero and Tobar, 2016] and the Automatic Brain Segmentation System [Hosseini et al, 2016] have outperformed FreeSurfer in hippocampus-specific segmentations. FreeSurfer has also been shown to be more sensitive to the atrophy coincident with MDD than alternatives [Morey et al, 2009].…”

Section: Discussionmentioning

confidence: 99%

“…Determining hippocampal volume from MRI has been accomplished through varied manual [Boccardi et al, 2011; Jack, 1994; Konrad et al, 2009] and automated [Alemán-Gómez et al, 2006; Fischl et al, 2002; Moghaddam and Soltanian-Zadeh, 2009; Platero and Tobar 2016; Smith et al, 2004] methods. Manual tracing has long been considered the gold standard, allowing for flexible quantification without many of the assumptions built into algorithms.…”

Section: Introductionmentioning

confidence: 99%

A comparison of manual tracing and FreeSurfer for estimating hippocampal volume over the adult lifespan

Schmidt

Storrs

Freeman

et al. 2018

Human Brain Mapping

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MRI has become an indispensable tool for brain volumetric studies, with the hippocampus an important region of interest. Automation of the MRI segmentation process has helped advance the field by facilitating the volumetric analysis of larger cohorts and more studies. FreeSurfer has emerged as the de facto standard tool for these analyses, but studies validating its output are all based on older versions. To characterize FreeSurfer's validity, we compare several versions of FreeSurfer software with traditional hand-tracing. Using MRI images of 262 males and 402 females aged 38 to 84, we directly compare estimates of hippocampal volume from multiple versions of FreeSurfer, its hippocampal subfield routines, and our manual tracing protocol. We then use those estimates to assess asymmetry and atrophy, comparing performance of different estimators with each other and with brain atrophy measures. FreeSurfer consistently reports larger volumes than manual tracing. This difference is smaller in larger hippocampi or older people, with these biases weaker in version 6.0.0 than prior versions. All methods tested agree qualitatively on rightward asymmetry and increasing atrophy in older people. FreeSurfer saves time and money, and approximates the same atrophy measures as manual tracing, but it introduces biases that could require statistical adjustments in some studies.

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A fast approach for hippocampal segmentation from T1-MRI for predicting progression in Alzheimer's disease from elderly controls

Cited by 25 publications

References 67 publications

Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer’s Disease at 3T and 7T: What Atlas Composition Works Best?

Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer’s Disease at 3T and 7T: What Atlas Composition Works Best?

Automated segmentation of medial temporal lobe subregions on in vivo T1‐weighted MRI in early stages of Alzheimer's disease

A comparison of manual tracing and FreeSurfer for estimating hippocampal volume over the adult lifespan

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