Hippocampal Sclerosis Detection with NeuroQuant Compared with Neuroradiologists

Abstract

BACKGROUND AND PURPOSE: NeuroQuant is an FDA-approved software that performs automated MR imaging quantitative volumetric analysis. This study aimed to compare the accuracy of NeuroQuant analysis with visual MR imaging analysis by neuroradiologists with expertise in epilepsy in identifying hippocampal sclerosis. MATERIALS AND METHODS: We reviewed 144 adult patients who underwent presurgical evaluation for temporal lobe epilepsy. The reference standard for hippocampal sclerosis was defined by having hippocampal sclerosis on pathology (n ¼ 61) or not having hippocampal sclerosis on pathology (n ¼ 83). Sensitivities, specificities, positive predictive values, and negative predictive values were compared between NeuroQuant analysis and visual MR imaging analysis by using a McNemar paired test of proportions and the Bayes theorem. RESULTS: NeuroQuant analysis had a similar specificity to neuroradiologist visual MR imaging analysis (90.4% versus 91.6%; P ¼ .99) but a lower sensitivity (69.0% versus 93.0%, P , .001). The positive predictive value of NeuroQuant analysis was comparable with visual MR imaging analysis (84.0% versus 89.1%), whereas the negative predictive value was not comparable (79.8% versus 95.0%). CONCLUSIONS: Visual MR imaging analysis by a neuroradiologist with expertise in epilepsy had a higher sensitivity than did NeuroQuant analysis, likely due to the inability of NeuroQuant to evaluate changes in hippocampal T2 signal or architecture. Given that there was no significant difference in specificity between NeuroQuant analysis and visual MR imaging analysis, NeuroQuant can be a valuable tool when the results are positive, particularly in centers that lack neuroradiologists with expertise in epilepsy, to help identify and refer candidates for temporal lobe epilepsy resection. In contrast, a negative test could justify a case referral for further evaluation to ensure that false-negatives are detected.

Diagnostic Performance of MRI Volumetry in Epilepsy Patients With Hippocampal Sclerosis Supported Through a Random Forest Automatic Classification Algorithm

“…We calculated mean volumes, confidence intervals, and cutoff estimations to recognize a regional sample of patients with confirmed unilateral mesial sclerosis and temporal lobe epilepsy with high sensitivity and specificity. Hippocampal asymmetry degree was the most accurate measure for classification regardless of the volumetry method used, as previously reported by others ( 3 , 23 , 31 ).…”

“…However, validation results from FreeSurfer v6.0 developers indicate that subfield volumes still carry useful information, even when T1 images usually display limited contrast on the internal subregion boundaries ( 75 ). Equivalent methodology was also successfully implemented in previous studies on cognitive function and epilepsy ( 3 , 4 , 22 , 23 , 91 , 93 ) with satisfactory results.…”

Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis—a systematic review

“…co. kr/) recently compared their results to NeuroQuant [54]. Clinical: NeuroQuant has been used by radiologists in the context of traumatic brain injury [25,91], temporal lobe epilepsy [92][93][94] and AD [58,59,87]. The prognostic value of NeuroQuant has been assessed in MCI patients [39,57].…”

Automated analysis of cortical volume loss predicts seizure outcomes after frontal lobectomy

“…12 NeuroQuant can process most 1.5 T and 3 T T1-weighted MR images and create comprehensive volumetric reports in about 10 minutes. 13 NeuroQuant segments T1-weighted MRI data sets into 71 distinct brain regions, which are further delineated by laterality, and calculates volume percentiles compared to brain volumes of a normative database. Percentile data for each region of the brain is provided in a succinct report (Figure 1).…”