Abstract
PurposeAutomated analysis of neuroimaging data is commonly based on magnetic resonance imaging (MRI), but sometimes the availability is limited or a patient might have contradictions to MRI. Therefore, automated analyses of computed tomography (CT) images would be beneficial.MethodsWe developed an automated method to evaluate medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and the severity of white matter lesions (WMLs) from a CT scan and compared the results to those obtained from MRI in a cohort of 214 subjects gathered from Kuopio and Helsinki University Hospital registers from 2005 - 2016.ResultsThe correlation coefficients of computational measures between CT and MRI were 0.9 (MTA), 0.82 (GCA), and 0.86 (Fazekas). CT-based measures were identical to MRI-based measures in 60% (MTA), 62% (GCA) and 60% (Fazekas) of cases when the measures were rounded to the nearest full grade variable. However, the difference in measures was 1 or less in 97–98% of cases. Similar results were obtained for cortical atrophy ratings, especially in the frontal and temporal lobes, when assessing the brain lobes separately. Bland–Altman plots and weighted kappa values demonstrated high agreement regarding measures based on CT and MRI.ConclusionsMTA, GCA, and Fazekas grades can also be assessed reliably from a CT scan with our method. Even though the measures obtained with the different imaging modalities were not identical in a relatively extensive cohort, the differences were minor. This expands the possibility of using this automated analysis method when MRI is inaccessible or contraindicated.
Highlights
Throughout its existence, brain imaging has been a key element in the diagnostic workup of neurodegenerative diseases
According to the European Federation of Neurological Societies (EFNS) guidelines [6] regarding the diagnosis of neurodegenerative disorders, brain atrophy can be evaluated with visual rating scales in temporal areas [7], posterior areas [8], and globally in the whole brain [9], while white matter lesions (WMLs) relating to vascular pathologies are usually evaluated by the
All subjects from the University of Eastern Finland (UEF) biomarker register were assessed and imaged at Kuopio University Hospital (KUH) between 2004 and 2017 and were referred to the participating outpatient clinic due to suspected cognitive decline; these patients were examined in accordance with the national Finnish guidelines for the diagnosis of neurodegenerative diseases [24]
Summary
Throughout its existence, brain imaging has been a key element in the diagnostic workup of neurodegenerative diseases. Neuroradiology scale developed for magnetic resonance imaging (MRI) by Fazekas et al [10] These kinds of visual rating scales are fast and straightforward to use in clinical practice. They require the expertise of a neuroradiologist and are still relatively coarse, subjective and might be prone to floor and ceiling effects [11] and dependent on the experience of the image reader. These issues have been shown to cause significant intra- and interrater variability in the results [7]. The quantification of brain structures based on manual delineation is considered the ground truth, but it is very time-consuming and still partly subjective regardless of the application of carefully planned procedures [12, 13]
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