Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks
Objectives: This study aimed to investigate the usefulness of a new non-contrast CT scan (NCCT) sign called the dHU, which represented the difference in mean Hounsfield unit values between follow-up and the initial NCCT for predicting 90-day poor functional outcomes in acute supratentorial spontaneo...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | NeuroImage: Clinical |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158223000670 |
| _version_ | 1797803966512234496 |
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| author | Xiaona Xia Xiaoqian Zhang Jiufa Cui Qingjun Jiang Shuai Guan Kongming Liang Hao Wang Chao Wang Chencui Huang Hao Dong Kai Han Xiangshui Meng |
| author_facet | Xiaona Xia Xiaoqian Zhang Jiufa Cui Qingjun Jiang Shuai Guan Kongming Liang Hao Wang Chao Wang Chencui Huang Hao Dong Kai Han Xiangshui Meng |
| author_sort | Xiaona Xia |
| collection | DOAJ |
| description | Objectives: This study aimed to investigate the usefulness of a new non-contrast CT scan (NCCT) sign called the dHU, which represented the difference in mean Hounsfield unit values between follow-up and the initial NCCT for predicting 90-day poor functional outcomes in acute supratentorial spontaneous intracerebral hemorrhage(sICH) using deep convolutional neural networks. Methods: A total of 377 consecutive patients with sICH from center 1 and 91 patients from center 2 (external validation set) were included. A receiver operating characteristic (ROC) analysis was performed to determine the critical value of dHU for predicting poor outcome at 90 days. Modified Rankin score (mRS) >3 or >2 was defined as the primary and secondary poor outcome, respectively. Two multivariate models were developed to test whether dHU was an independent predictor of the two unfavorable functional outcomes. Results: The ROC analysis showed that a dHU >2.5 was a critical value to predict the poor outcomes (mRS >3) in sICH. The sensitivity, specificity, and accuracy of dHU >2.5 for poor outcome prediction were 37.5%, 86.0%, and 70.6%, respectively. In multivariate models developed after adjusting for all elements of the ICH score and hematoma expansion, dHU >2.5 was an independent predictor of both primary and secondary poor outcomes (OR = 2.61, 95% CI [1.32,5.13], P = 0.006; OR = 2.63, 95% CI [1.36,5.10], P = 0.004, respectively). After adjustment for all possible significant predictors (p < 0.05) by univariate analysis, dHU >2.5 had a positive association with primary and secondary poor outcomes (OR = 3.25, 95% CI [1.52,6.98], P = 0.002; OR = 3.42, 95% CI [1.64,7.15], P = 0.001). Conclusions: The dHU of hematoma based on serial CT scans is independently associated with poor outcomes after acute sICH, which may help predict clinical evolution and guide therapy for sICH patients. |
| first_indexed | 2024-03-13T05:28:59Z |
| format | Article |
| id | doaj.art-f90dffe1945f41a897493d918f49630c |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-03-13T05:28:59Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-f90dffe1945f41a897493d918f49630c2023-06-15T04:55:44ZengElsevierNeuroImage: Clinical2213-15822023-01-0138103378Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networksXiaona Xia0Xiaoqian Zhang1Jiufa Cui2Qingjun Jiang3Shuai Guan4Kongming Liang5Hao Wang6Chao Wang7Chencui Huang8Hao Dong9Kai Han10Xiangshui Meng11Department of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, ChinaDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, ChinaDepartment of Radiology, the Affiliated Hospital of Qingdao University, Qingdao, Shandong, ChinaDepartment of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, ChinaDepartment of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, ChinaDepartment of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing 100080, ChinaDepartment of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing 100080, ChinaDepartment of Radiology, Jiaozhou People’s Hospital, Qingdao, ChinaDepartment of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing 100080, ChinaDepartment of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing 100080, ChinaDepartment of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing 100080, ChinaDepartment of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China; Corresponding author.Objectives: This study aimed to investigate the usefulness of a new non-contrast CT scan (NCCT) sign called the dHU, which represented the difference in mean Hounsfield unit values between follow-up and the initial NCCT for predicting 90-day poor functional outcomes in acute supratentorial spontaneous intracerebral hemorrhage(sICH) using deep convolutional neural networks. Methods: A total of 377 consecutive patients with sICH from center 1 and 91 patients from center 2 (external validation set) were included. A receiver operating characteristic (ROC) analysis was performed to determine the critical value of dHU for predicting poor outcome at 90 days. Modified Rankin score (mRS) >3 or >2 was defined as the primary and secondary poor outcome, respectively. Two multivariate models were developed to test whether dHU was an independent predictor of the two unfavorable functional outcomes. Results: The ROC analysis showed that a dHU >2.5 was a critical value to predict the poor outcomes (mRS >3) in sICH. The sensitivity, specificity, and accuracy of dHU >2.5 for poor outcome prediction were 37.5%, 86.0%, and 70.6%, respectively. In multivariate models developed after adjusting for all elements of the ICH score and hematoma expansion, dHU >2.5 was an independent predictor of both primary and secondary poor outcomes (OR = 2.61, 95% CI [1.32,5.13], P = 0.006; OR = 2.63, 95% CI [1.36,5.10], P = 0.004, respectively). After adjustment for all possible significant predictors (p < 0.05) by univariate analysis, dHU >2.5 had a positive association with primary and secondary poor outcomes (OR = 3.25, 95% CI [1.52,6.98], P = 0.002; OR = 3.42, 95% CI [1.64,7.15], P = 0.001). Conclusions: The dHU of hematoma based on serial CT scans is independently associated with poor outcomes after acute sICH, which may help predict clinical evolution and guide therapy for sICH patients.http://www.sciencedirect.com/science/article/pii/S2213158223000670Spontaneous intracranial hemorrhageDifference of mean Hounsfield units (dHU)Non-contrast computed tomographyOutcomeDeep convolutional neural networks |
| spellingShingle | Xiaona Xia Xiaoqian Zhang Jiufa Cui Qingjun Jiang Shuai Guan Kongming Liang Hao Wang Chao Wang Chencui Huang Hao Dong Kai Han Xiangshui Meng Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks NeuroImage: Clinical Spontaneous intracranial hemorrhage Difference of mean Hounsfield units (dHU) Non-contrast computed tomography Outcome Deep convolutional neural networks |
| title | Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks |
| title_full | Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks |
| title_fullStr | Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks |
| title_full_unstemmed | Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks |
| title_short | Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks |
| title_sort | difference of mean hounsfield units dhu between follow up and initial noncontrast ct scan predicts 90 day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks |
| topic | Spontaneous intracranial hemorrhage Difference of mean Hounsfield units (dHU) Non-contrast computed tomography Outcome Deep convolutional neural networks |
| url | http://www.sciencedirect.com/science/article/pii/S2213158223000670 |
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