Quantitative analysis of computed tomography images and early detection of cerebral edema for pediatric traumatic brain injury patients: retrospective study
- Authors
- Kim, Hakseung; Kim, Gwang-dong; Yoon, Byung C.; Kim, Keewon; Kim, Byung-Jo; Choi, Young Hun; Czosnyka, Marek; Oh, Byung-Mo; Kim, Dong-Joo
- Issue Date
- 22-10월-2014
- Publisher
- BIOMED CENTRAL LTD
- Keywords
- Cerebral edema; Computed tomography; Densitometry; Traumatic brain injury; Pediatrics
- Citation
- BMC MEDICINE, v.12
- Indexed
- SCIE
SCOPUS
- Journal Title
- BMC MEDICINE
- Volume
- 12
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/97059
- DOI
- 10.1186/s12916-014-0186-2
- ISSN
- 1741-7015
- Abstract
- Background: The purpose of this study was to identify whether the distribution of Hounsfield Unit (HU) values across the intracranial area in computed tomography (CT) images can be used as an effective diagnostic tool for determining the severity of cerebral edema in pediatric traumatic brain injury (TBI) patients. Methods: CT images, medical records and radiology reports on 70 pediatric patients were collected. Based on radiology reports and the Marshall classification, the patients were grouped as mild edema patients (n = 37) or severe edema patients (n = 33). Automated quantitative analysis using unenhanced CT images was applied to eliminate artifacts and identify the difference in HU value distribution across the intracranial area between these groups. Results: The proportion of pixels with HU = 17 to 24 was highly correlated with the existence of severe cerebral edema (P < 0.01). This proportion was also able to differentiate patients who developed delayed cerebral edema from mild TBI patients. A significant difference between deceased patients and surviving patients in terms of the HU distribution came from the proportion of pixels with HU = 19 to HU = 23 (P < 0.01). Conclusions: The proportion of pixels with an HU value of 17 to 24 in the entire cerebral area of a non-enhanced CT image can be an effective basis for evaluating the severity of cerebral edema. Based on this result, we propose a novel approach for the early detection of severe cerebral edema.
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Collections - College of Medicine > Department of Medical Science > 1. Journal Articles
- Graduate School > Department of Brain and Cognitive Engineering > 1. Journal Articles
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