RESUMO
BACKGROUND AND PURPOSE: The Brain Tumor Reporting and Data System (BT-RADS) is a structured radiology reporting algorithm that was introduced to provide uniformity in post-treatment primary brain tumor follow-up and reporting, but its interrater reliability (IRR) assessment has not been widely studied. Our goal is to evaluate the IRR among neuroradiologists and radiology residents in the use of BT-RADS. MATERIALS AND METHODS: This retrospective study reviewed 103 consecutive MR studies in 98 adult patients previously diagnosed with and treated for primary brain tumor (January 2019 to February 2019). Six readers with varied experience (4 neuroradiologists and 2 radiology residents) independently evaluated each case and assigned a BT-RADS score. Readers were blinded to the original score reports and the reports from other readers. Cases in which at least one neuroradiologist scored differently were subjected to consensus scoring. After the study, a post-hoc reference score was also assigned by 2 readers using future imaging and clinical information previously unavailable to readers. The interrater reliabilities were assessed using Gwet's AC2 index with ordinal weights and percent agreement. RESULTS: Of the 98 patients evaluated (median age, 53 years; interquartile range, 41-66 years), 53% were males. The most common tumor type was astrocytoma (77%) of which 56% were grade 4 glioblastoma. Gwet's index for interrater reliability among all six readers was 0.83 (95% CI: 0.78, 0.87). The Gwet's index for the neuroradiologists' group (0.84 [95% CI: 0.79, 0.89]) was not statistically different from that for the residents' group (0.79 [95% CI: 0.72, 0.86]) (χ2 = 0.85; p = 0.36). All four neuroradiologists agreed on the same BT-RADS score in 57 of the 103 studies, three neuroradiologists agreed in 21 of the 103 studies, and two neuroradiologists agreed in 21 of the 103 studies. Percent agreement between neuroradiologist blinded scores and post-hoc reference scores ranged from 41%-52%. CONCLUSIONS: A very good interrater agreement was found when tumor reports were interpreted by independent blinded readers using BT-RADS criteria. Further study is needed to determine if this high overall agreement can translate into greater consistency in clinical care. ABBREVIATIONS: BI-RADS = Breast Imaging Reporting and Data System; BT-RADS = Brain Tumor Reporting and Data System; IQR = interquartile range; IRR = interrater reliability; NI-RADS = Neck Imaging Reporting and Data System.
RESUMO
BACKGROUND AND PURPOSE: Brain imaging plays an important role in investigating patients with cognitive decline and ruling out secondary causes of dementia. This study compares the diagnostic value of quantitative hippocampal volumes derived from automated volumetric software and structured scoring scales in differentiating Alzheimer disease, mild cognitive impairment, and subjective cognitive decline. MATERIALS AND METHODS: Retrospectively, we reviewed images and medical records of adult patients who underwent MR imaging with a dementia protocol (2018-2021). Patients with postscanning diagnoses of Alzheimer disease, mild cognitive impairment, and subjective cognitive decline based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision, were included. Diagnostic performances of automated normalized total hippocampal volume and structured manually assigned medial temporal atrophy and entorhinal cortical atrophy scores were assessed using multivariate logistic regression and receiver operating characteristic curve analysis. RESULTS: We evaluated 328 patients (Alzheimer disease, n = 118; mild cognitive impairment, n = 172; subjective cognitive decline, n = 38). Patients with Alzheimer disease had lower normalized total hippocampal volume (median, 0.35%), higher medial temporal atrophy (median, 3), and higher entorhinal cortical atrophy (median, 2) scores than those with subjective cognitive decline (P < .001) and mild cognitive impairment (P < .001). For discriminating Alzheimer disease from subjective cognitive decline, an entorhinal cortical atrophy cutoff value of 2 had a higher specificity (87%) compared with normalized total hippocampal volume (74%) and medial temporal atrophy (66%), but a lower sensitivity (69%) than normalized total hippocampal volume (84%) and medial temporal atrophy (84%). In discriminating Alzheimer disease from mild cognitive impairment, an entorhinal cortical atrophy cutoff value of 3 had a specificity (66%), similar to that of normalized total hippocampal volume (67%) but higher than medial temporal atrophy (54%), and its sensitivity (69%) was also similar to that of normalized total hippocampal volume (71%) but lower than that of medial temporal atrophy (84%). CONCLUSIONS: Entorhinal cortical atrophy and medial temporal atrophy may be useful adjuncts in discriminating Alzheimer disease from subjective cognitive decline, with reduced cost and implementation challenges compared with automated volumetric software.