A novel CT‑based automated analysis method provides comparable results with MRI in measuring brain atrophy and white matter lesions

Purpose Automated 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. Methods We 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. Results The 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. Conclusions MTA, 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.Peer reviewe

Low Cerebrospinal Fluid Amyloid-Beta Concentration Is Associated with Poorer Delayed Memory Recall in Women

Background: Data on the association of memory performance with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are inconsistent. The Consortium to Establish a Registry for Alzheimer's Disease neuropsychological battery (CERAD-NB) is a commonly used validated cognitive tool; however, only few studies have examined its relationship with CSF biomarkers for AD. We studied the correlation of pathological changes in CSF biomarkers with various CERAD-NB subtests and total scores. Methods: Out of 79 subjects (36 men, mean age 70.5 years), 63 had undergone an assessment of cognitive status with CERAD-NB and a CSF biomarker analysis due to a suspected memory disorder, and 16 were controls with no memory complaint.Results: In women we found a significant correlation between CSF amyloid-beta (Aβ1-42) and several subtests measuring delayed recall. Word List Recall correlated with all markers: Aβ1-42 (r = 0.323, p = 0.035), tau (r = -0.304, p = 0.050) and hyperphosphorylated tau (r = -0.331, p = 0.046). No such correlations were found in men. Conclusions: CSF biomarkers correlate with delayed memory scores in CERAD-NB in women, and women may have more actual AD pathology at the time of the investigations than men

Cerebrospinal fluid and MRI biomarkers in neurodegenerative diseases:a retrospective memory clinic-based study

Abstract Background: Cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers of neurodegenerative diseases are relatively sensitive and specific in highly curated research cohorts, but proper validation for clinical use is mostly missing. Objective: We studied these biomarkers in a novel memory clinic cohort with a variety of different neurodegenerative diseases. Methods: This study consisted of 191 patients with subjective or objective cognitive impairment who underwent neurological, CSF biomarker (Aβ42, p-tau, and tau) and T1-weighted MRI examinations at Kuopio University Hospital. We assessed CSF and imaging biomarkers, including structural MRI focused on volumetric and cortical thickness analyses, across groups stratified based on different clinical diagnoses, including Alzheimer’s disease (AD), frontotemporal dementia, dementia with Lewy bodies, Parkinson’s disease, vascular dementia, and mild cognitive impairment (MCI), and subjects with no evidence of neurodegenerative disease underlying the cognitive symptoms. Imaging biomarkers were also studied by profiling subjects according to the novel amyloid, tau, and, neurodegeneration (AT(N)) classification. Results: Numerous imaging variables differed by clinical diagnosis, including hippocampal, amygdalar and inferior lateral ventricular volumes and entorhinal, lingual, inferior parietal and isthmus cingulate cortical thicknesses, at a false discovery rate (FDR)-corrected threshold for significance (analysis of covariance; p < 0.005). In volumetric comparisons by AT(N) profile, hippocampal volume significantly differed (p < 0.001) between patients with normal AD biomarkers and patients with amyloid pathology. Conclusion: Our analysis suggests that CSF and MRI biomarkers function well also in clinical practice across multiple clinical diagnostic groups in addition to AD, MCI, and cognitively normal groups