Clinical evaluation of automated quantitative MRI reports for assessment of hippocampal sclerosis

Abstract

Objectives Hippocampal sclerosis (HS) is a common cause of temporal lobe epilepsy. Neuroradiological practice relies on visual assessment, but quantification of HS imaging biomarkers-hippocampal volume loss and T2 elevation-could improve detection. We tested whether quantitative measures, contextualised with normative data, improve rater accuracy and confidence. Methods Quantitative reports (QReports) were generated for 43 individuals with epilepsy (mean age ± SD 40.0 ± 14.8 years, 22 men; 15 histologically unilateral HS; 5 bilateral; 23 MR-negative). Normative data was generated from 111 healthy individuals (age 40.0 ± 12.8 years, 52 men). Nine raters with different experience (neuroradiologists, trainees, and image analysts) assessed subjects' imaging with and without QReports. Raters assigned imaging normal, right, left, or bilateral HS. Confidence was rated on a 5-point scale. Results Correct designation (normal/abnormal) was high and showed further trend-level improvement with QReports, from 87.5 to 92.5% (p = 0.07, effect size d = 0.69). Largest magnitude improvement (84.5 to 93.8%) was for image analysts (d = 0.87). For bilateral HS, QReports significantly improved overall accuracy, from 74.4 to 91.1% (p = 0.042, d = 0.7). Agreement with the correct diagnosis (kappa) tended to increase from 0.74 ('fair') to 0.86 ('excellent') with the report (p = 0.06, d = 0.81). Confidence increased when correctly assessing scans with the QReport (p < 0.001, η 2 p = 0.945).

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

“…These patient populations may have more subtle patterns of atrophy and QReports are likely to provide the greatest benefit to raters by flagging patients who require more regular follow-ups and reducing inter-rater variability. The results of diagnostic accuracy studies are ideally published in peer-reviewed journals [19][20][21][116][117][118]. Several companies provide lists of publications on their website.…”

A Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis Derived From Deep Learning-Based Segmentation of T1w-MRI

“…The reliabilities of the measures were assessed using repeated scans. Finally, we propose this metric as an imaging biomarker for HS along with a quantitative report to communicate the result of an individual assessment (30).…”

Editorial for “MRI Findings of Arachnoiditis, Revisited. Is Classification Needed?”

“…Neuroradiological studies involving raters from different specialities and experience levels have been on the rise in recent years. [2][3][4][5][6][7] Since the advent of MRI, lumbosacral arachnoiditis classification has been based on a three-group system pertaining to the T2-weighted appearance of nerve roots: group 1, the nerve roots clump in the center of the thecal sac; in group 2, the nerve roots adhere to the periphery of the thecal sac; in group 3, the nerve roots form a mass in the thecal sac. However, this paper, the first in the literature to examine radiological classification of lumbosacral arachnoiditis, provides further evidence of heterogeneous imaging findings and encourages moving beyond the traditional three-group classification.…”

“…The use of five radiologists from two different specialties with varying experience level is a comprehensive approach. This sort of rigorous imaging assessment across specialties and experience levels is the first of its kind in lumbosacral arachnoiditis but similar methods have been used in radiological assessment of several neurological disorders, including epilepsy, 4 traumatic brain injury, 7 and dementia. 2,3,5,6 The impact of this work is quite evident, determining the high prevalence of synechiae and standardizing their diagnostic criteria could make radiological assessment and diagnosis of arachnoiditis faster and more accurate.…”

“…Everyday, there are more neuro‐professionals and consequently there is an increasing interest in harmonizing diagnostics independent of the raters' speciality. Neuroradiological studies involving raters from different specialities and experience levels have been on the rise in recent years 2–7 …”