Evidence map›Paper›PMID 34867703›Full record

ArticleFrontiers in neurology2021

Detection of Hippocampal Subfield Asymmetry at 7T With Automated Segmentation in Epilepsy Patients With Normal Clinical Strength MRIs.

Akila Pai, Lara V Marcuse, Judy Alper, Bradley N Delman, John W Rutland, Rebecca E Feldman, Patrick R Hof, Madeline Fields, James Young, Priti Balchandani

Abstract read
In one paragraph

Article in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Radiologic Classification of Hippocampal Sclerosis in Epilepsy.AJNR. American journal of neuroradiology · 2024
    Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Akila PaiIcahn School of Medicine at Mount Sinai, New York, NY, United States.
Lara V MarcuseDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Judy AlperBioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Bradley N DelmanDepartment of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
John W RutlandTranslational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Rebecca E FeldmanDepartment of Computer Science, Math, Physics, and Statistics, University of British Columbia, Okanagan, BC, Canada.
Patrick R HofNash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Madeline FieldsDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
James YoungDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Priti BalchandaniBioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States.

Funding

High Resolution Magnetic Resonance Imaging and Spectroscopy of Epilepsy at 7TK99NS070821 · NINDS · STANFORD UNIVERSITY · PI BALCHANDANI, PRITI · 2011 to 2012
$175k
NINDS NIH HHS K99 NS070821
6 · The paper itself

Abstract

While the etiology of hippocampal sclerosis (HS) in epilepsy patients remains unknown, distinct phenotypes of hippocampal subfield atrophy have been associated with different clinical presentations and surgical outcomes. The advent of novel techniques including ultra-high field 7T magnetic resonance imaging (MRI) and automated subfield volumetry have further enabled detection of hippocampal pathology in patients with epilepsy, however, studies combining both 7T MRI and automated segmentation in epilepsy patients with normal-appearing clinical MRI are limited. In this study, we present a novel application of the automated segmentation of hippocampal subfields (ASHS) software to determine subfield volumes of the CA1, CA2/3, CA4/DG, and the subiculum using ultra high-field 7T MRI scans, including T1-weighted MP2RAGE and T2-TSE sequences, in 27 patients with either mesial temporal lobe epilepsy (mTLE) or neocortical epilepsy (NE) compared to age and gender matched healthy controls. We found that 7T improved visualization of structural abnormalities not otherwise seen on clinical strength MRIs in patients with unilateral mTLE. Additionally, our automated segmentation algorithm was able to detect structural differences in volume and asymmetry across hippocampal subfields in unilateral mTLE patients compared to controls. Specifically, amongst unilateral mTLE patients with longer disease durations, volume loss was observed in the ipsilateral CA1 and CA2/3 subfields and contralateral CA1. There were no differences in subfield volumes in patients with NE compared to controls. We report the first application of 7T with automated segmentation to characterize the relationship between disease duration burden and asymmetry across specific hippocampal subfields in this population. Disease duration was found to have a statistically significant positive relationship with subfield asymmetry within the unilateral mTLE cohort. These findings highlight the ability of 7T MRI and automated segmentation to provide novel qualitative and quantitative information in epilepsy patients who are otherwise MRI-negative at clinical field strengths.

Indexed as

7T MRIasymmetryepilepsyhippocampussubfieldvolumetry

Identifiers

PMID34867703
PMCPMC8634833

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.