Quantitative CT Densitometry for Predicting Intracerebral Hemorrhage Growth

C.D. Barras; B.M. Tress; S. Christensen; M. Collins; P.M. Desmond; B.E. Skolnick; S.A. Mayer; S.M. Davis

doi:10.3174/ajnr.A3375

Research ArticleBrain

Quantitative CT Densitometry for Predicting Intracerebral Hemorrhage Growth

C.D. Barras, B.M. Tress, S. Christensen, M. Collins, P.M. Desmond, B.E. Skolnick, S.A. Mayer and S.M. Davis for the Recombinant Activated Factor VII Intracerebral Hemorrhage Trial Investigators

American Journal of Neuroradiology June 2013, 34 (6) 1139-1144; DOI: https://doi.org/10.3174/ajnr.A3375

C.D. Barras

aFrom the Departments of Radiology (C.D.B., B.M.T., S.C., P.M.D.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

B.M. Tress

aFrom the Departments of Radiology (C.D.B., B.M.T., S.C., P.M.D.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

S. Christensen

aFrom the Departments of Radiology (C.D.B., B.M.T., S.C., P.M.D.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

M. Collins

cDepartment of Mathematics and Statistics (M.C.), The University of Melbourne, Melbourne, Australia

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

P.M. Desmond

aFrom the Departments of Radiology (C.D.B., B.M.T., S.C., P.M.D.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

B.E. Skolnick

dNovo Nordisk Inc (B.E.S.), Princeton, New Jersey

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

S.A. Mayer

eDepartment of Neurology (S.A.M.), Columbia University Medical Center, New York, New York.

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

S.M. Davis

bNeurology (S.M.D.), Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Article
Figures & Data
Supplemental
Info & Metrics
Responses
References
PDF

Article Information

vol. 34 no. 6 1139-1144

DOI

https://doi.org/10.3174/ajnr.A3375

PubMed

23306009

Published By

American Journal of Neuroradiology

Print ISSN

0195-6108

Online ISSN

1936-959X

Altmetrics

Cited By...

45 Citations
Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

Black Hole Sign

Qi Li, Gang Zhang, Xin Xiong, Xing-Chen Wang, Wen-Song Yang, Ke-Wei Li, Xiao Wei, Peng Xie

Stroke 2016 47 7
Noncontrast Computed Tomography Markers of Intracerebral Hemorrhage Expansion

Gregoire Boulouis, Andrea Morotti, Andreas Charidimou, Dar Dowlatshahi, Joshua N. Goldstein

Stroke 2017 48 4
Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine

Jinjin Liu, Haoli Xu, Qian Chen, Tingting Zhang, Wenshuang Sheng, Qun Huang, Jiawen Song, Dingpin Huang, Li Lan, Yanxuan Li, Weijian Chen, Yunjun Yang

EBioMedicine 2019 43
Noncontrast Computed Tomography Hypodensities Predict Poor Outcome in Intracerebral Hemorrhage Patients

Gregoire Boulouis, Andrea Morotti, H. Bart Brouwers, Andreas Charidimou, Michael J. Jessel, Eitan Auriel, Octavio Pontes-Neto, Alison Ayres, Anastasia Vashkevich, Kristin M. Schwab, Jonathan Rosand, Anand Viswanathan, Mahmut E. Gurol, Steven M. Greenberg, Joshua N. Goldstein

Stroke 2016 47 10
Progressing haemorrhagic stroke: categories, causes, mechanisms and managements

Shiyu Chen, Liuwang Zeng, Zhiping Hu

Journal of Neurology 2014 261 11
Noncontrast computer tomography–based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model

Huihui Xie, Shuai Ma, Xiaoying Wang, Xiaodong Zhang

European Radiology 2020 30 1
Radiomics in Stroke Neuroimaging: Techniques, Applications, and Challenges

Qian Chen, Tianyi Xia, Mingyue Zhang, Nengzhi Xia, Jinjin Liu, Yunjun Yang

Aging and disease 2021 12 1
Clinical and Radiographic Predictors of Intracerebral Hemorrhage Outcome

Fawaz Al-Mufti, Ahmad M. Thabet, Tarundeep Singh, Mohammad El-Ghanem, Krishna Amuluru, Chirag D. Gandhi

Interventional Neurology 2018 7 1-2
Critical Care Neurology Part I

A.M. Thabet, M. Kottapally, J. Claude Hemphill

2017 140
Quantitative parameters of CT texture analysis as potential markers for early prediction of spontaneous intracranial hemorrhage enlargement

Qijun Shen, Yanna Shan, Zhengyu Hu, Wenhui Chen, Bing Yang, Jing Han, Yanfang Huang, Wen Xu, Zhan Feng

European Radiology 2018 28 10
Imaging-Based Outcome Prediction of Acute Intracerebral Hemorrhage

Jawed Nawabi, Helge Kniep, Sarah Elsayed, Constanze Friedrich, Peter Sporns, Thilo Rusche, Maik Böhmer, Andrea Morotti, Frieder Schlunk, Lasse Dührsen, Gabriel Broocks, Gerhard Schön, Fanny Quandt, Götz Thomalla, Jens Fiehler, Uta Hanning

Translational Stroke Research 2021 12 6
Critical Care Management of Intracerebral Hemorrhage

Sheila Chan, J. Claude Hemphill

Critical Care Clinics 2014 30 4
Radiomics for predicting hematoma expansion in patients with hypertensive intraparenchymal hematomas

Chao Ma, Yupeng Zhang, Tuerdialimu Niyazi, Jian Wei, Guo Guocai, Jianan Liu, Shikai Liang, Fei Liang, Peng Yan, Kun Wang, Chuhan Jiang

European Journal of Radiology 2019 115
Quantitative analysis of orbital soft tissues on computed tomography to assess the activity of thyroid-associated orbitopathy

Jun Soo Byun, Nam Ju Moon, Jeong Kyu Lee

Graefe's Archive for Clinical and Experimental Ophthalmology 2017 255 2
Glyceryl Trinitrate for Acute Intracerebral Hemorrhage

Kailash Krishnan, Polly Scutt, Lisa Woodhouse, Alessandro Adami, Jennifer L. Becker, Eivind Berge, Lesley A. Cala, Ana M. Casado, Valeria Caso, Christopher Chen, Hanna Christensen, Ronan Collins, Anna Czlonkowska, Robert A. Dineen, John Gommans, Panos Koumellis, Kennedy R. Lees, George Ntaios, Serefnur Ozturk, Stephen J. Phillips, Stuart J. Pocock, Asita de Silva, Nikola Sprigg, Szabolcs Szatmari, Joanna M. Wardlaw, Philip M. Bath

Stroke 2016 47 1
Performance characteristics of methods for quantifying spontaneous intracerebral haemorrhage: data from the Efficacy of Nitric Oxide in Stroke (ENOS) trial

Kailash Krishnan, Siti F Mukhtar, James Lingard, Aimee Houlton, Elizabeth Walker, Tanya Jones, Nikola Sprigg, Lesley A Cala, Jennifer L Becker, Robert A Dineen, Panos Koumellis, Alessandro Adami, Ana M Casado, Philip M W Bath, Joanna M Wardlaw

Journal of Neurology, Neurosurgery & Psychiatry 2015 86 11
Quantitative analysis of computed tomography images and early detection of cerebral edema for pediatric traumatic brain injury patients: retrospective study

Hakseung Kim, Gwang-dong Kim, Byung C Yoon, Keewon Kim, Byung-Jo Kim, Young Hun Choi, Marek Czosnyka, Byung-Mo Oh, Dong-Joo Kim

BMC Medicine 2014 12 1
Prediction of Intracerebral Haemorrhage Expansion with Clinical, Laboratory, Pharmacologic, and Noncontrast Radiographic Variables

Sheila Chan, Carol Conell, Kaivalya T. Veerina, Vivek A. Rao, Alexander C. Flint

International Journal of Stroke 2015 10 7
Computed Tomographic Black Hole Sign Predicts Postoperative Rehemorrhage in Patients with Spontaneous Intracranial Hemorrhage Following Stereotactic Minimally Invasive Surgery

Zhengkui Shen, Likun Wang, Guofeng Wu, Qi Li, Siying Ren, Yuanhong Mao

World Neurosurgery 2018 120
A nomogram to predict early hematoma expansion of hypertensive cerebral hemorrhage

Si Hu, WenGuo Sheng, Yi Hu, Qiang Ma, Bin Li, RuiZhang Han

Medicine 2021 100 7
Swirls and spots: relationship between qualitative and quantitative hematoma heterogeneity, hematoma expansion, and the spot sign

Dale Connor, Thien J. Huynh, Andrew M. Demchuk, Dar Dowlatshahi, David J. Gladstone, Sivaniya Subramaniapillai, Sean P. Symons, Richard I. Aviv

Neurovascular Imaging 2015 1 1
Predictores de mortalidad y mal resultado funcional en la hemorragia intraparenquimatosa espontánea grave: estudio prospectivo observacional

A.M. Ferrete-Araujo, J.J. Egea-Guerrero, Á. Vilches-Arenas, D.A. Godoy, F. Murillo-Cabezas

Medicina Intensiva 2015 39 7
Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion

Chongfeng Duan, Fang Liu, Song Gao, Jiping Zhao, Lei Niu, Nan Li, Song Liu, Gang Wang, Xiaoming Zhou, Yande Ren, Wenjian Xu, Xuejun Liu

Clinical Neuroradiology 2022 32 1
Exploration of Multiparameter Hematoma 3D Image Analysis for Predicting Outcome After Intracerebral Hemorrhage

Pascal Salazar, Mario Di Napoli, Mostafa Jafari, Alibay Jafarli, Wendy Ziai, Alexander Petersen, Stephan A. Mayer, Eric M. Bershad, Rahul Damani, Afshin A. Divani

Neurocritical Care 2020 32 2
Radiomics Features on Computed Tomography Combined With Clinical-Radiological Factors Predicting Progressive Hemorrhage of Cerebral Contusion

Qingning Yang, Jun Sun, Yi Guo, Ping Zeng, Ke Jin, Chencui Huang, Jingxu Xu, Liran Hou, Chuanming Li, Junbang Feng

Frontiers in Neurology 2022 13
Continuing versus Stopping Prestroke Antihypertensive Therapy in Acute Intracerebral Hemorrhage: A Subgroup Analysis of the Efficacy of Nitric Oxide in Stroke Trial

Kailash Krishnan, Polly Scutt, Lisa Woodhouse, Alessandro Adami, Jennifer L. Becker, Lesley A. Cala, Ana M. Casado, Christopher Chen, Robert A. Dineen, John Gommans, Panos Koumellis, Hanna Christensen, Ronan Collins, Anna Czlonkowska, Kennedy R. Lees, George Ntaios, Serefnur Ozturk, Stephen J. Phillips, Nikola Sprigg, Szabolcs Szatmari, Joanna M. Wardlaw, Philip M. Bath

Journal of Stroke and Cerebrovascular Diseases 2016 25 5
An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1

Rajiv Gupta, Sanjith Prahas Krishnam, Pamela W. Schaefer, Michael H. Lev, R. Gilberto Gonzalez

Neuroimaging Clinics of North America 2020 30 4
Are computed-tomography-based hematoma radiomics features reproducible and predictive of intracerebral hemorrhage expansion? an in vitro experiment and clinical study

Kai Chen, Lijing Deng, Qing Li, Liangping Luo

The British Journal of Radiology 2021 94 1121
Establishment and validation of a prediction model for intraparenchymal hematoma expansion in patients with cerebral contusion: A reliable Nomogram

Yufeng Zhu, Lulu Xu, Shengwu Lin, Yunxiao Chen, Pei Han, Zhongsheng Lu

Clinical Neurology and Neurosurgery 2022 212
Occurrence of spot signs from hypodensity areas on precontrast CT in intracerebral hemorrhage

Jun Nishiyama, Takatoshi Sorimachi, Rie Aoki, Go Inoue, Mitsunori Matsumae

Neurological Research 2017 39 5
Abilities of a Densitometric Analysis of Computed Tomography Images and Hemorrhagic Parameters to Predict Outcome Favorability in Patients With Intracerebral Hemorrhage

Hakseung Kim, Xiaoke Yang, Young Hun Choi, Byung C Yoon, Keewon Kim, Dong-Joo Kim

Neurosurgery 2018 83 2
Is the CT Blend Sign Composed of Two Parts of Blood with Different Age?

Yinghui Li, Siying Ren, Likun Wang, Yuanhong Mao, Guofeng Wu, Qi Li, Zhouping Tang

Neurocritical Care 2021 35 2
Audit of CT reporting standards in cases of intracerebral haemorrhage at a comprehensive stroke centre in Australia

Christen D Barras, Hamed Asadi, Pramit M Phal, Brian M Tress, Stephen M Davis, Patricia M Desmond

Journal of Medical Imaging and Radiation Oncology 2016 60 6
Monitoring and Predicting Treatment Response of Extraocular Muscles in Grave's Orbitopathy by 99mTc-DTPA SPECT/CT

Chengzhi Jiang, Zilong Deng, Jin Huang, Haoyu Deng, Jia Tan, Xinhui Li, Min Zhao

Frontiers in Medicine 2021 8
Association of Satellite Sign with Postoperative Rebleeding in Patients Undergoing Stereotactic Minimally Invasive Surgery for Hypertensive Intracerebral Haemorrhage

Ajith Bernardin Raj, Li-fei Lian, Feng Xu, Guo Li, Shan-shan Huang, Qi-ming Liang, Kai Lu, Jian-ling Zhao, Fu-rong Wang

Current Medical Science 2021 41 3
Advances in CT for prediction of hematoma expansion in acute intracerebral hemorrhage

Thien J Huynh, Sean P Symons, Richard I Aviv

Imaging in Medicine 2013 5 6
CT radiomics combined with clinical and radiological factors predict hematoma expansion in hypertensive intracerebral hemorrhage

Fei Yu, Mingguang Yang, Cheng He, Yanli Yang, Ying Peng, Hua Yang, Hong Lu, Heng Liu

European Radiology 2024 35 1
Intracranial Densitometry-Augmented Machine Learning Enhances the Prognostic Value of Brain CT in Pediatric Patients With Traumatic Brain Injury: A Retrospective Pilot Study

Young-Tak Kim, Hakseung Kim, Choel-Hui Lee, Byung C. Yoon, Jung Bin Kim, Young Hun Choi, Won-Sang Cho, Byung-Mo Oh, Dong-Joo Kim

Frontiers in Pediatrics 2021 9
CT-based radiomics models predict spontaneous intracerebral hemorrhage expansion and are comparable with CT angiography spot sign

Qingrun Li, Feng Li, Hao Liu, Yan Li, Hongri Chen, Wenrui Yang, Shaofeng Duan, Hongying Zhang

Frontiers in Neurology 2024 15
Predictors of mortality and poor functional outcome in severe spontaneous intracerebral hemorrhage: A prospective observational study

A.M. Ferrete-Araujo, J.J. Egea-Guerrero, Á. Vilches-Arenas, D.A. Godoy, F. Murillo-Cabezas

Medicina Intensiva (English Edition) 2015 39 7
Systematic Evaluation of Hematoma Expansion Models in Spontaneous Intracerebral Hemorrhage: A Meta-Analysis and Meta-Regression Approach

Ruoru Wu, Tao Hong, Ye Li

Cerebrovascular Diseases 2024
The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage

Te-Chang Wu, Yan-Lin Liu, Jeon-Hor Chen, Yang Zhang, Tai-Yuan Chen, Ching-Chung Ko, Min-Ying Su

Diagnostics 2022 12 11
The Attenuation Value Within the Non-hypodense Region on Non-contrast Computed Tomography of Spontaneous Cerebral Hemorrhage: A Long-Neglected Predictor of Hematoma Expansion

Yong Chen, Dan Cao, Zheng-Qian Guo, Xiao-Ling Ma, Yi-Bo Ou, Yue He, Xu Chen, Jian Chen

Frontiers in Neurology 2022 13
Predicting the 90-day prognosis of stereotactic brain hemorrhage patients by multiple machine learning using radiomic features combined with clinical features

Jinwei Li, Cong Liang, Junsun Dang, Yang Zhang, Hongmou Chen, Xianlei Yan, Quan Liu

Frontiers in Surgery 2024 11
Prediction of Basal Ganglia Hematoma Expansion Based on Radiomics and Clinical Characteristics: A Novel Multivariate Predictive Nomogram

Bin Luo, Lin Ma, Yubo Wang, Hecheng Ren, MingSheng Yu, YuXiang Ma, Long Yin, Ying Huang, Nicola Tambasco

Acta Neurologica Scandinavica 2023 2023

PreviousNext

In this issue

American Journal of Neuroradiology

Vol. 34, Issue 6

1 Jun 2013

Table of Contents
Index by author

Download PDF

Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Your Email *

Your Name *

Send To *

Enter multiple addresses on separate lines or separate them with commas.

You are going to email the following Quantitative CT Densitometry for Predicting Intracerebral Hemorrhage Growth

Message Subject (Your Name) has sent you a message from American Journal of Neuroradiology

Message Body (Your Name) thought you would like to see the American Journal of Neuroradiology web site.

Your Personal Message

CAPTCHA

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Cite this article

C.D. Barras, B.M. Tress, S. Christensen, M. Collins, P.M. Desmond, B.E. Skolnick, S.A. Mayer, S.M. Davis

Quantitative CT Densitometry for Predicting Intracerebral Hemorrhage Growth

American Journal of Neuroradiology Jun 2013, 34 (6) 1139-1144; DOI: 10.3174/ajnr.A3375

Citation Manager Formats

BibTeX
Bookends
EasyBib
EndNote (tagged)
EndNote 8 (xml)
Medlars
Mendeley
Papers
RefWorks Tagged
Ref Manager
RIS
Zotero

0 Responses

Respond to this article

Bookmark this article

User Name *

Password *

Remember my user name & password.

Quantitative CT Densitometry for Predicting Intracerebral Hemorrhage Growth

C.D. Barras, B.M. Tress, S. Christensen, M. Collins, P.M. Desmond, B.E. Skolnick, S.A. Mayer, S.M. Davis

American Journal of Neuroradiology Jun 2013, 34 (6) 1139-1144; DOI: 10.3174/ajnr.A3375

Share This Article:

Tweet Widget
Facebook Like
Google Plus One

Purchase

Jump to section

Article
Figures & Data
Supplemental
Info & Metrics
Responses
References
PDF

PubMed
Google Scholar

Cited By...

Noncontrast Computed Tomography Markers of Intracerebral Hemorrhage Expansion
Noncontrast Computed Tomography Hypodensities Predict Poor Outcome in Intracerebral Hemorrhage Patients
Black Hole Sign: Novel Imaging Marker That Predicts Hematoma Growth in Patients With Intracerebral Hemorrhage
Glyceryl Trinitrate for Acute Intracerebral Hemorrhage: Results From the Efficacy of Nitric Oxide in Stroke (ENOS) Trial, a Subgroup Analysis

Crossref (45)
Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

Black Hole Sign

Qi Li, Gang Zhang, Xin Xiong, Xing-Chen Wang, Wen-Song Yang, Ke-Wei Li, Xiao Wei, Peng Xie

Stroke 2016 47 7
Noncontrast Computed Tomography Markers of Intracerebral Hemorrhage Expansion

Gregoire Boulouis, Andrea Morotti, Andreas Charidimou, Dar Dowlatshahi, Joshua N. Goldstein

Stroke 2017 48 4
Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine

Jinjin Liu, Haoli Xu, Qian Chen, Tingting Zhang, Wenshuang Sheng, Qun Huang, Jiawen Song, Dingpin Huang, Li Lan, Yanxuan Li, Weijian Chen, Yunjun Yang

EBioMedicine 2019 43
Noncontrast Computed Tomography Hypodensities Predict Poor Outcome in Intracerebral Hemorrhage Patients

Gregoire Boulouis, Andrea Morotti, H. Bart Brouwers, Andreas Charidimou, Michael J. Jessel, Eitan Auriel, Octavio Pontes-Neto, Alison Ayres, Anastasia Vashkevich, Kristin M. Schwab, Jonathan Rosand, Anand Viswanathan, Mahmut E. Gurol, Steven M. Greenberg, Joshua N. Goldstein

Stroke 2016 47 10
Progressing haemorrhagic stroke: categories, causes, mechanisms and managements

Shiyu Chen, Liuwang Zeng, Zhiping Hu

Journal of Neurology 2014 261 11
Noncontrast computer tomography–based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model

Huihui Xie, Shuai Ma, Xiaoying Wang, Xiaodong Zhang

European Radiology 2020 30 1
Radiomics in Stroke Neuroimaging: Techniques, Applications, and Challenges

Qian Chen, Tianyi Xia, Mingyue Zhang, Nengzhi Xia, Jinjin Liu, Yunjun Yang

Aging and disease 2021 12 1
Clinical and Radiographic Predictors of Intracerebral Hemorrhage Outcome

Fawaz Al-Mufti, Ahmad M. Thabet, Tarundeep Singh, Mohammad El-Ghanem, Krishna Amuluru, Chirag D. Gandhi

Interventional Neurology 2018 7 1-2
Critical Care Neurology Part I

A.M. Thabet, M. Kottapally, J. Claude Hemphill

2017 140
Quantitative parameters of CT texture analysis as potential markers for early prediction of spontaneous intracranial hemorrhage enlargement

Qijun Shen, Yanna Shan, Zhengyu Hu, Wenhui Chen, Bing Yang, Jing Han, Yanfang Huang, Wen Xu, Zhan Feng

European Radiology 2018 28 10

Main menu

User menu

Search

American Journal of Neuroradiology

Quantitative CT Densitometry for Predicting Intracerebral Hemorrhage Growth

Article Information

Altmetrics

Cited By...

In this issue

Citation Manager Formats

Related Articles

Cited By...

More in this TOC Section

Similar Articles

Indexed Content

Cases

Special Collections

Resources

Multimedia

About Us

American Society of Neuroradiology