Validation of automatic MRI hippocampal subfield segmentation by histopathological evaluation in patients with temporal lobe epilepsy.

OBJECTIVE The present study validates the results of automated hippocampal subfield segmentation with histopathology in epilepsy patients undergoing epilepsy surgery. METHODS We performed an automated hippocampal subfield segmentation on presurgical three-dimensional, T1-weighted magnetization Prepared Rapid Acquisition of Gradient Echoes Magnetic Resonance Imaging (MRI) data of 25 patients with unilateral mesial temporal lobe epilepsy due to hippocampal sclerosis (HS), using Freesurfer Version 6.0. The resulting volumes of cornu ammonis (CA) subfields CA1, CA2/3, CA4 and the dentate gyrus (DG) were compared to the histopathological cell count. RESULTS We found a significant correlation between histopathology in subregion CA2 and automated segmentation of subregion CA1 (p = 0.0062), CA2/3 (p = 0.004), CA4 (p = 0.0062) and the DG (p = 0.0054), between histopathology in CA3 and automated segmentation of CA1 (p = 0.0132), CA2/3 (p = 0.0004), CA4 (p = 0.0032) and the DG (p = 0.0037), as well as between histopathology in the DG and automated segmentation of CA1 (p = 0.0115), CA2/3 (p < 0.0001), CA4 (p < 0.0001) and the DG (p = 0.0001). The histopathological finding of HS type 1 could correctly be classified in all cases on MRI. SIGNIFICANCE The present study shows significant correlations between histopathological evaluation and results of the automated segmentation of the hippocampus, thereby validating the automated segmentation method. As the differential involvement of different hippocampal subfields may be associated with clinical parameters and the outcome after epilepsy surgery, the automated segmentation is also promising for prognostic purposes.

• Publication year

  2021

• Venue

  Seizure

• Publication date

  2021-03-12

• Fields of study

  Medicine

• Identifiers
  DOI 10.1016/j.seizure.2021.03.007PMID 33752160
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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