Literature DB >> 17428687

Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: a proof-of-principle study.

Alexander Hammers1, Rolf Heckemann, Matthias J Koepp, John S Duncan, Jo V Hajnal, Daniel Rueckert, Paul Aljabar.   

Abstract

In temporal lobe epilepsy (TLE), hippocampal atrophy (HA) is a marker of poor prognosis regarding seizure remission, but predicts success of anterior temporal lobe resection. Manual quantification of HA on MRI is time-consuming and limited by investigator availability. Normal ranges of hippocampal volumes, both in absolute terms and relative to intracranial volume, and of hippocampal asymmetry were defined using an automatic label propagation and decision fusion technique based on thirty manually derived atlases of healthy controls. Manual test-retest reliability and overlaps of automatically and manually determined hippocampal volumes were quantified with similarity indices (SIs). Correct clinical identification of ipsilateral HA, and contralaterally normal hippocampal volumes, was determined in nine patients with histologically confirmed hippocampal sclerosis in terms of volumes and asymmetry indices (AIs) for standard statistical thresholds and with receiver operating characteristic (ROC) analysis. Manual test-retest reliability was very high, with SIs between 0.87 and 0.90. Manual and automatic hippocampus labels overlapped with a SI of 0.83 on the unaffected but with 0.76 on the atrophic side. Accuracy was higher for less atrophic hippocampi. The automatic method correctly identified 6/9 HAs in terms of absolute volume, 7/9 in terms of relative volume at a standard 2 SD threshold, and 9/9 for AIs. ROC-determined thresholds allowed clinically desirable correct identification of all HAs (100% sensitivity) with 85-100% specificity for volumes, and 100% specificity for AIs. The method has the potential to automatically detect unilateral HA, but further work is needed to determine its performance in detecting clinically important bilateral disease.

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Year:  2007        PMID: 17428687     DOI: 10.1016/j.neuroimage.2007.02.031

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  35 in total

1.  Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

Authors:  Nikdokht Farid; Holly M Girard; Nobuko Kemmotsu; Michael E Smith; Sebastian W Magda; Wei Y Lim; Roland R Lee; Carrie R McDonald
Journal:  Radiology       Date:  2012-06-21       Impact factor: 11.105

2.  Voxel-Based Morphometry-from Hype to Hope. A Study on Hippocampal Atrophy in Mesial Temporal Lobe Epilepsy.

Authors:  F Riederer; R Seiger; R Lanzenberger; E Pataraia; G Kasprian; L Michels; J Beiersdorf; S Kollias; T Czech; J Hainfellner; C Baumgartner
Journal:  AJNR Am J Neuroradiol       Date:  2020-06       Impact factor: 3.825

3.  FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping.

Authors:  Ali R Khan; Lei Wang; Mirza Faisal Beg
Journal:  Neuroimage       Date:  2008-03-26       Impact factor: 6.556

4.  A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease.

Authors:  Sean M Nestor; Erin Gibson; Fu-Qiang Gao; Alex Kiss; Sandra E Black
Journal:  Neuroimage       Date:  2012-11-07       Impact factor: 6.556

5.  Mesial Temporal Sclerosis: Accuracy of NeuroQuant versus Neuroradiologist.

Authors:  M Azab; M Carone; S H Ying; D M Yousem
Journal:  AJNR Am J Neuroradiol       Date:  2015-04-23       Impact factor: 3.825

6.  A learning-based wrapper method to correct systematic errors in automatic image segmentation: consistently improved performance in hippocampus, cortex and brain segmentation.

Authors:  Hongzhi Wang; Sandhitsu R Das; Jung Wook Suh; Murat Altinay; John Pluta; Caryne Craige; Brian Avants; Paul A Yushkevich
Journal:  Neuroimage       Date:  2011-01-13       Impact factor: 6.556

Review 7.  Defining the human hippocampus in cerebral magnetic resonance images--an overview of current segmentation protocols.

Authors:  C Konrad; T Ukas; C Nebel; V Arolt; A W Toga; K L Narr
Journal:  Neuroimage       Date:  2009-05-15       Impact factor: 6.556

8.  Subcortical and cerebellar atrophy in mesial temporal lobe epilepsy revealed by automatic segmentation.

Authors:  Carrie R McDonald; Donald J Hagler; Mazyar E Ahmadi; Evelyn Tecoma; Vicente Iragui; Anders M Dale; Eric Halgren
Journal:  Epilepsy Res       Date:  2008-03-21       Impact factor: 3.045

9.  On the estimation of the location of the hippocampus in the context of hippocampal avoidance whole brain radiotherapy treatment planning.

Authors:  Edward T Bender; Minesh P Mehta; Wolfgang A A Tomé
Journal:  Technol Cancer Res Treat       Date:  2009-12

10.  Automatic segmentation of the hippocampus and the amygdala driven by hybrid constraints: method and validation.

Authors:  M Chupin; A Hammers; R S N Liu; O Colliot; J Burdett; E Bardinet; J S Duncan; L Garnero; L Lemieux
Journal:  Neuroimage       Date:  2009-02-21       Impact factor: 6.556

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