ArticleAJNR. American journal of neuroradiology2019
Improved Detection of Subtle Mesial Temporal Sclerosis: Validation of a Commercially Available Software for Automated Segmentation of Hippocampal Volume.
Article in AJNR. American journal of neuroradiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review.Neuroradiology · 2021Pooled it
- Article
- Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist.Current neurology and neuroscience reports · 2023Review
- Automated detection of hippocampal sclerosis using real-world clinical MRI images.Frontiers in neuroscience · 2023Article
- Quantification of amyloid PET for future clinical use: a state-of-the-art review.European journal of nuclear medicine and molecular imaging · 2022Review
- Automated Segmentation of Hippocampal Volume: The Next Step in Neuroradiologic Diagnosis of Mesial Temporal Sclerosis.AJNR. American journal of neuroradiology · 2019Article
- MRI Volumetric Quantification in Persons with a History of Traumatic Brain Injury and Cognitive Impairment.Journal of Alzheimer's disease : JAD · 2019Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeIdentification of mesial temporal sclerosis is critical in the evaluation of individuals with temporal lobe epilepsy. Our aim was to assess the performance of FDA-approved software measures of hippocampal volume to identify mesial temporal sclerosis in patients with medically refractory temporal lobe epilepsy compared with the initial clinical interpretation of a neuroradiologist. MATERIALS AND
methodsPreoperative MRIs of 75 consecutive patients who underwent a temporal resection for temporal lobe epilepsy from 2011 to 2016 were retrospectively reviewed, and 71 were analyzed using Neuroreader, a commercially available automated segmentation and volumetric analysis package. Volume measures, including hippocampal volume as a percentage of total intracranial volume and the Neuroreader Index, were calculated. Radiologic interpretations of the MR imaging and pathology from subsequent resections were classified as either mesial temporal sclerosis or other, including normal findings. These measures of hippocampal volume were evaluated by receiver operating characteristic curves on the basis of pathologic confirmation of mesial temporal sclerosis in the resected temporal lobe. Sensitivity and specificity were calculated for each method and compared by means of the McNemar test using the optimal threshold as determined by the Youden J point.
resultsOptimized thresholds of hippocampal percentage of a structural volume relative to total intracranial volume (<0.19%) and the Neuroreader Index (≤-3.8) were selected to optimize sensitivity and specificity (89%/71% and 89%/78%, respectively) for the identification of mesial temporal sclerosis in temporal lobe epilepsy compared with the initial clinical interpretation of the neuroradiologist (50% and 87%). Automated measures of hippocampal volume predicted mesial temporal sclerosis more accurately than radiologic interpretation (McNemar test,
conclusionsCommercially available automated segmentation and volume analysis of the hippocampus accurately identifies mesial temporal sclerosis and performs significantly better than the interpretation of the radiologist.
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