Abstract

Many patients with dementia may have comorbid or misdiagnosed normal pressure hydrocephalus, a treatable neurologic disorder. The callosal angle is a validated biomarker for normal pressure hydrocephalus with 93% diagnostic accuracy. Our purpose was to develop and evaluate an algorithm for automatically computing callosal angles from MR images of the brain. This article reports the results of analyzing callosal angles from 1856 subjects with 5264 MR images from the Open Access Series of Imaging Studies and the Alzheimer's Disease Neuroimaging Initiative databases. Measurement variability was examined between 2 neuroradiologists (n = 50) and between manual and automatic measurements (n = 281); from differences in simulated head orientation; and from real-world changes in patients with multiple examinations (n = 906). We evaluated the effectiveness of the automatic callosal angle to differentiate normal pressure hydrocephalus from Alzheimer disease in a simulated cohort. The algorithm identified that 12.4% of subjects from these carefully screened cohorts had callosal angles of <90°, a published threshold for possible normal pressure hydrocephalus. The intraclass correlation coefficient was 0.97 for agreement between neuroradiologists and 0.90 for agreement between manual and automatic measurement. The method was robust to different head orientations. The median coefficient of variation for repeat examinations was 4.2% (Q1 = 3.1%, Q3 = 5.8%). The simulated classification of normal pressure hydrocephalus versus Alzheimer using the automatic callosal angle had an accuracy, sensitivity, and specificity of 0.87 each. In even the most pristine research databases, analyses of the callosal angle indicate that some patients may have normal pressure hydrocephalus. The automatic callosal angle measurement can rapidly and objectively screen for normal pressure hydrocephalus in patients who would otherwise be misdiagnosed.

Highlights

  • ObjectivesOur objective was to automate callosal angle (CA) measurements and do the following: 1) assess the agreement between 2 neuroradiologists measuring the CA and between manual and automatic measurements; 2) evaluate the variation of automated CA under both simulated and real-world conditions; 3) use the algorithm to analyze MR images to identify patients with possible Normal pressure hydrocephalus (NPH) in studies with different scanners, vendors, and imaging parameters; and 4) characterize the performance of the automated measurement for the differentiation of NPH from other dementia

  • BACKGROUND AND PURPOSEMany patients with dementia may have comorbid or misdiagnosed normal pressure hydrocephalus, a treatable neurologic disorder

  • The algorithm identified that 12.4% of subjects from these carefully screened cohorts had callosal angles of,90°, a published threshold for possible normal pressure hydrocephalus

Read more

Summary

Objectives

Our objective was to automate CA measurements and do the following: 1) assess the agreement between 2 neuroradiologists measuring the CA and between manual and automatic measurements; 2) evaluate the variation of automated CA under both simulated and real-world conditions; 3) use the algorithm to analyze MR images to identify patients with possible NPH in studies with different scanners, vendors, and imaging parameters; and 4) characterize the performance of the automated measurement for the differentiation of NPH from other dementia

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call