title: Quantification of image contrast of infarcts on computed tomography scans.
abstract: Introduction Accurate identification of infarcts in non-contrast computed tomography (NC-CT) scans of the brain is fundamental in the diagnosis and management of patients with stroke. Quantification of image contrast properties at the boundaries of ischemic infarct regions in NC-CT can contribute to a more precise manual or automatic delineation of these regions. Here we explore these properties quantitatively. Methods We retrospectively investigated 519 NC-CT studies of 425 patients with clinically confirmed ischemic strokes. The average and standard deviation (SD) of patients' age was 67.5 ± 12.4 years and the average(median)±SD time from symptoms onset to NC-CT examination was 27.4(12)±35.7 h. For every scan with an ischemic lesion identified by experts, the image contrast of the lesion vs. normal surrounding parenchyma was calculated as a difference of mean Hounsfield Unit (HU) of 1-5 consecutive voxels (the contrast window width) belonging to the lesion and to the parenchyma. This contrast was calculated at each single voxel of ischemic lesion boundaries (previously delineated by the experts) in horizontal and vertical directions in each image. The distributions of obtained horizontal, vertical and both contrasts combined were calculated among all 519 NC-CTs. Results The highest applicative contrast window width was identified as 5 voxels. The ischemic infarcts were found to be characterized by 6.60 HU, 8.28 HU and 7.55 HU mean values for distributions of horizontal, vertical and combined contrasts. Approximately 40-50% of the infarct boundary voxels were found to refer to the image contrast below 5 HU. Conclusion Low image contrast of ischemic lesions prevents accurate delineation of the infarcts in NC-CT.
authors.affiliation: 1 The Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland.
authors.forename: R S
authors.initials: RS
authors.lastname: Gomolka
authors.affiliation: 2 Department of Radiology, Jagiellonian University, The Cracow University Hospital, Krakow, Poland.
authors.forename: R M
authors.initials: RM
authors.lastname: Chrzan
authors.affiliation: 2 Department of Radiology, Jagiellonian University, The Cracow University Hospital, Krakow, Poland.
authors.forename: A
authors.initials: A
authors.lastname: Urbanik
authors.affiliation: 3 Department of Neurology and Cerebrovascular Diseases, Poznan University of Medical Sciences, Poznan, Poland.
authors.forename: R
authors.initials: R
authors.lastname: Kazmierski
authors.affiliation: 1 The Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland.
authors.forename: A D
authors.initials: AD
authors.lastname: Grzanka
authors.affiliation: 4 John Paul II Center for Virtual Anatomy and Surgical Simulation, Cardinal Stefan Wyszynski, Warsaw, Poland.
authors.forename: W L
authors.initials: WL
authors.lastname: Nowinski
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D020520:Brain Infarction / Q000000981:diagnostic imaging* / Q000209:etiology; D002545:Brain Ischemia / Q000150:complications*; D003287:Contrast Media / Q000378:metabolism; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D013223:Statistics as Topic; D020521:Stroke / Q000150:complications / Q000000981:diagnostic imaging / Q000209:etiology; D013997:Time Factors; D014057:Tomography, X-Ray Computed
chemical_list: D003287:Contrast Media
keywords: NC-CT; Stroke; computer-aided diagnosis; tissue contrast