Aimen Kasasbeh, Edward C. Hwang, Karen Steger-May, S. Kathleen Bandt, Amy Oberhelman, David Limbrick, Michelle M. Miller-Thomas, Joshua S. Shimony and Matthew D. Smyth
Mesial temporal sclerosis (MTS) is widely recognized as a significant underlying cause of temporal lobe epilepsy. Magnetic resonance imaging is routinely used in the preoperative evaluation of children with epilepsy. The purpose of this study was to evaluate the prevalence, reliability, and prognostic value of MRI identification of MTS and MRI findings indicative of MTS in a series of patients who underwent resection of the medial temporal lobe for medically refractory epilepsy.
The authors reviewed the medical records and preoperative MRI reports of 25 patients who had undergone medial temporal resections (anterior temporal lobectomy or functional hemispherotomy) for medically intractable epilepsy. The preoperative MRI studies were presented for blinded review by 2 neuroradiologists who independently evaluated the radiographs for selected MTS features and provided a final interpretation. To quantify interrater agreement and accuracy, the findings of the 2 blinded neuroradiologists, the nonblinded clinical preoperative radiology report, and the final pathology interpretation were compared.
The preoperative MRI studies revealed MTS in 6 patients (24%), and histopathological analysis verified MTS in 8 (32%) of 25 specimens. Six MRI features of MTS were specifically evaluated: 1) increased hippocampal signal intensity, 2) reduced hippocampal size, 3) atrophy of the ipsilateral hippocampal collateral white matter, 4) enlarged ipsilateral temporal horn, 5) reduced gray-white matter demarcation in the temporal lobe, and 6) decreased temporal lobe size. The most prevalent feature of MTS identified on MRI was a reduced hippocampal size, found in 11 of the MRI studies (44%). Analysis revealed moderate interrater agreement for MRI identification of MTS between the 2 blinded neuroradiologists and the nonblinded preoperative report (Cohen κ 0.40–0.59). Interrater agreement was highly variable for different MTS features indicative of MTS, ranging from poor to near perfect. Agreement was highest for increased hippocampal signal and decreased temporal lobe size and was consistently poor for reduced gray-white matter demarcation. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and proportion perfect agreement were highest for increased hippocampal signal and reduced hippocampal size. An MRI finding of MTS was not predictive of seizure outcome in this small series.
Mesial temporal sclerosis identification on brain MRI in children evaluated for medial temporal resections has a PPV of 55%–67% and an NPV of 79%–87%. Increased hippocampal signal and reduced hippocampal size were associated with high predictive values, while gray-white differentiation and an enlarged temporal horn were not predictive of MTS. Seizure outcome following medial temporal resections was not associated with MRI findings of MTS or MRI abnormalities indicative of MTS in this small sample size.
Gloria J. Guzmán Pérez-Carrillo, Christopher Owen, Katherine E. Schwetye, Spencer McFarlane, Ananth K. Vellimana, Soe Mar, Michelle M. Miller-Thomas, Joshua S. Shimony, Matthew D. Smyth and Tammie L. S. Benzinger
Many patients with medically intractable epilepsy have mesial temporal sclerosis (MTS), which significantly affects their quality of life. The surgical excision of MTS lesions can result in marked improvement or even complete resolution of the epileptic episodes. Reliable radiological diagnosis of MTS is a clinical challenge. The purpose of this study was to evaluate the utility of volumetric mapping of the hippocampi for the identification of MTS in a case-controlled series of pediatric patients who underwent resection for medically refractory epilepsy, using pathology as a gold standard.
A cohort of 57 pediatric patients who underwent resection for medically intractable epilepsy between 2005 and 2015 was evaluated. On pathological investigation, this group included 24 patients with MTS and 33 patients with non-MTS findings. Retrospective quantitative volumetric measurements of the hippocampi were acquired for 37 of these 57 patients. Two neuroradiologists with more than 10 years of experience who were blinded to the patients' MTS status performed the retrospective review of MR images. To produce the volumetric data, MR scans were parcellated and segmented using the FreeSurfer software suite. Hippocampal regions of interest were compared against an age-weighted local regression curve generated with data from the pediatric normal cohort. Standard deviations and percentiles of specific subjects were calculated. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined for the original clinical read and the expert readers. Receiver operating characteristic curves were generated for the methods of classification to compare results from the readers with the authors' results, and an optimal threshold was determined. From that threshold the sensitivity, specificity, PPV, and NPV were calculated for the volumetric analysis.
With the use of quantitative volumetry, a sensitivity of 72%, a specificity of 95%, a PPV of 93%, an NPV of 78%, and an area under the curve of 0.84 were obtained using a percentage difference of normalized hippocampal volume. The resulting specificity (95%) and PPV (93%) are superior to the original clinical read and to Reader A and Reader B's findings (range for specificity 74%–86% and for PPV 64%–71%). The sensitivity (72%) and NPV (78%) are comparable to Reader A's findings (73% and 81%, respectively) and are better than those of the original clinical read and of Reader B (sensitivity 45% and 63% and NPV 71% and 70%, respectively).
Volumetric measurement of the hippocampi outperforms expert readers in specificity and PPV, and it demonstrates comparable to superior sensitivity and NPV. Volumetric measurements can complement anatomical imaging for the identification of MTS, much like a computer-aided detection tool would. The implementation of this approach in the daily clinical workflow could significantly improve diagnostic accuracy.