Quantitative analysis of computed tomography images and early detection of cerebral edema for pediatric traumatic brain injury patients: retrospective study
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 …
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 …
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.
Springer
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