1
|
Yeager CE, Garg RK. Advances and Future Trends in the Diagnosis and Management of Intracerebral Hemorrhage. Neurol Clin 2024; 42:689-703. [PMID: 38937036 DOI: 10.1016/j.ncl.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
Spontaneous intracerebral hemorrhage accounts for approximately 10% to 15% of all strokes in the United States and remains one of the deadliest. Of concern is the increasing prevalence, especially in younger populations. This article reviews the following: epidemiology, risk factors, outcomes, imaging findings, medical management, and updates to surgical management.
Collapse
Affiliation(s)
- Christine E Yeager
- Division of Critical Care Neurology, Rush University Medical Center, 1725 W Harrison Street, Suite 1106, Chicago, IL, USA.
| | - Rajeev K Garg
- Division of Critical Care Neurology, Section of Cognitive Neurosciences, Rush University Medical Center, 1725 W Harrison Street, Suite 1106, Chicago, IL, USA
| |
Collapse
|
2
|
Xu M, Fu X, Jin H, Yu X, Xu G, Ma Z, Pan C, Liu B. Intracerebral Hemorrhage Prognosis Classification via Joint-Attention Cross-Modal Network. Brain Sci 2024; 14:618. [PMID: 38928618 PMCID: PMC11201659 DOI: 10.3390/brainsci14060618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/28/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024] Open
Abstract
Intracerebral hemorrhage (ICH) is a critical condition characterized by a high prevalence, substantial mortality rates, and unpredictable clinical outcomes, which results in a serious threat to human health. Improving the timeliness and accuracy of prognosis assessment is crucial to minimizing mortality and long-term disability associated with ICH. Due to the complexity of ICH, the diagnosis of ICH in clinical practice heavily relies on the professional expertise and clinical experience of physicians. Traditional prognostic methods largely depend on the specialized knowledge and subjective judgment of healthcare professionals. Meanwhile, existing artificial intelligence (AI) methodologies, which predominantly utilize features derived from computed tomography (CT) scans, fall short of capturing the multifaceted nature of ICH. Although existing methods are capable of integrating clinical information and CT images for prognosis, the effectiveness of this fusion process still requires improvement. To surmount these limitations, the present study introduces a novel AI framework, termed the ICH Network (ICH-Net), which employs a joint-attention cross-modal network to synergize clinical textual data with CT imaging features. The architecture of ICH-Net consists of three integral components: the Feature Extraction Module, which processes and abstracts salient characteristics from the clinical and imaging data, the Feature Fusion Module, which amalgamates the diverse data streams, and the Classification Module, which interprets the fused features to deliver prognostic predictions. Our evaluation, conducted through a rigorous five-fold cross-validation process, demonstrates that ICH-Net achieves a commendable accuracy of up to 87.77%, outperforming other state-of-the-art methods detailed within our research. This evidence underscores the potential of ICH-Net as a formidable tool in prognosticating ICH, promising a significant advancement in clinical decision-making and patient care.
Collapse
Affiliation(s)
- Manli Xu
- The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310053, China;
| | - Xianjun Fu
- School of Artificial Intelligence, Zhejiang College of Security Technology, Wenzhou 325016, China;
| | - Hui Jin
- School of Computer, Hangzhou Dianzi University, Hangzhou 310018, China; (H.J.); (X.Y.)
| | - Xinlei Yu
- School of Computer, Hangzhou Dianzi University, Hangzhou 310018, China; (H.J.); (X.Y.)
| | - Gang Xu
- School of Artificial Intelligence, Zhejiang College of Security Technology, Wenzhou 325016, China;
| | - Zishuo Ma
- International Business School, Jinan University, Zhuhai 510632, China;
| | - Cheng Pan
- School of General Education, Sanda University, Shanghai 201209, China;
| | - Bo Liu
- The 39th Research Institute of China Electronics Technology Group Corporation, Xi’an 710065, China;
- Key Laboratory of Antenna and Control Technology of Shanxi Province, Xi’an 710068, China
- School of Management, Xi’an Jiaotong University, Xi’an 710049, China
| |
Collapse
|
3
|
Zheng H, Tang Y, Zhou H, Ji X. The rate-pressure product combined model within 24 h on admission predicts the 30-day mortality rate in conservatively treated patients with intracerebral hemorrhage. Front Neurol 2024; 15:1377843. [PMID: 38911585 PMCID: PMC11190339 DOI: 10.3389/fneur.2024.1377843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 05/21/2024] [Indexed: 06/25/2024] Open
Abstract
Background and objectives Recently, some literature has proposed new indicators such as rate-pressure product, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, etc. However, there has been no literature that has utilized these new indicators to establish a predictive model for assessing the risk of mortality in patients within 24 h on admission. Therefore, this study aims to build a predictive model that can rapidly assess the likelihood of mortality in patients within 24 h of admission. Methods The datasets used in this study are available from the corresponding author upon reasonable request. Patients were randomly assigned to the training or validation cohort based on a ratio of 7:3, which was implemented as internal validations for the final predictive models. In the training set, least absolute shrinkage and selection operator (LASSO) regression was employed to select predictive factors, followed by both univariate and subsequent multivariate analysis. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve. Results A total of 428 patients were included in our research. The final model included 4 independent predictors (Glasgow Coma Scale, hematoma volume, rate-pressure product, c-reactive protein) and was developed as a simple-to-use nomogram. The training set and internal validation set model's C-index are 0.933 and 0.954, demonstrating moderate predictive ability with regard to risks of mortality. Compared to ICH score (AUC: 0.910 and 0.925), the net reclassification index (NRI) is 0.298 (CI = -0.105 to 0.701, p: 0.147) and integrated discrimination improvement (IDI) is 0.089 (CI = -0.049 to 0.228, p: 0.209). Our model is equally excellent as the classic ICH score model. Conclusion We developed a model with four independent risk factors to predict the mortality of ICH patients. Our predictive model is effective in assessing the risk of mortality in patients within 24 h on admission, which might be worth considering in clinical settings after further external validation.
Collapse
Affiliation(s)
| | | | | | - Xiang Ji
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| |
Collapse
|
4
|
Deng L, Zhang JT, Lv XN, Li ZQ, Chen C, Hu X, Yin H, Yang TN, Zhang ZH, Li Q. Optimal intraventricular hemorrhage volume cutoff for predicting poor outcome in patients with intracerebral hemorrhage. J Stroke Cerebrovasc Dis 2024; 33:107683. [PMID: 38513767 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 03/15/2024] [Accepted: 03/18/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND AND OBJECTIVES The prognosis of patients with spontaneous intracerebral hemorrhage (ICH) is often influenced by hematoma volume, a well-established predictor of poor outcome. However, the optimal intraventricular hemorrhage (IVH) volume cutoff for predicting poor outcome remains unknown. METHODS We analyzed 313 patients with spontaneous ICH not undergoing evacuation, including 7 cases with external ventricular drainage (EVD). These patients underwent a baseline CT scan, followed by a 24-hour CT scan for measurement of both hematoma and IVH volume. We defined hematoma growth as hematoma growth > 33 % or 6 mL at follow-up CT, and poor outcome as modified Rankin Scale score≥3 at three months. Cutoffs with optimal sensitivity and specificity for predicting poor outcome were identified using receiver operating curves. RESULTS The receiver operating characteristic analysis identified 6 mL as the optimal cutoff for predicting poor outcome. IVH volume> 6 mL was observed in 53 (16.9 %) of 313 patients. Patients with IVH volume>6 mL were more likely to be older and had higher NIHSS score and lower GCS score than those without. IVH volume>6 mL (adjusted OR 2.43, 95 % CI 1.13-5.30; P = 0.026) was found to be an independent predictor of poor clinical outcome at three months in multivariable regression analysis. CONCLUSIONS Optimal IVH volume cutoff represents a powerful tool for improving the prediction of poor outcome in patients with ICH, particularly in the absence of clot evacuation or common use of EVD. Small amounts of intraventricular blood are not independently associated with poor outcome in patients with intracerebral hemorrhage. The utilization of optimal IVH volume cutoffs may improve the clinical trial design by targeting ICH patients that will obtain maximal benefit from therapies.
Collapse
Affiliation(s)
- Lan Deng
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jiang-Tao Zhang
- Department of Neurology, Chengde Central Hospital, Chengde 067000, Hebei, China
| | - Xin-Ni Lv
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Zuo-Qiao Li
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Chu Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Xiao Hu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Hao Yin
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Tian-Nan Yang
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Zhe-Hao Zhang
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Qi Li
- Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Anhui 230601, China.
| |
Collapse
|
5
|
Morotti A, Nawabi J, Pilotto A, Toffali M, Busto G, Mazzacane F, Cavallini A, Laudisi M, Gentile L, Viola MM, Schlunk F, Bartolini D, Paciaroni M, Magoni M, Bassi C, Simonetti L, Fainardi E, Casetta I, Zini A, Padovani A. Functional outcome improvement from 3 to 12 months after intracerebral hemorrhage. Eur Stroke J 2024; 9:391-397. [PMID: 38183279 PMCID: PMC11318429 DOI: 10.1177/23969873231222782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 12/09/2023] [Indexed: 01/08/2024] Open
Abstract
INTRODUCTION Most intracerebral hemorrhage (ICH) trials assessed outcome at 3 months but the recovery trajectory of ICH survivors may continue up to 1 year after the index event. We aimed to describe the predictors of functional outcome improvement from 3 to 12 months after ICH. MATERIALS AND METHODS Retrospective analysis of patients admitted to six European Stroke Centers for supratentorial ICH. Functional outcome was measured with the modified Rankin Scale (mRS) at 3 and 12 months. Predictors of functional outcome improvement were explored with binary logistic regression. RESULTS We included 703 patients, of whom 245 (34.9%) died within 3 months. Among survivors, 131 (28.6%) had an mRS improvement, 78 (17.0%) had a worse mRS and 249 (54.4%) had a stable functional status at 12 months. Older age and the presence of baseline disability (defined as pre-stroke mRS > 1), were associated with lower odds of functional outcome improvement (Odds Ratio (OR) 0.98 per year increase, 95% Confidence Interval (CI) 0.96-1.00, p = 0.017 and OR 0.45, 95% CI 0.25-0.81, p = 0.008 respectively). Conversely, deep ICH location increased the probability of long term mRS improvement (OR 1.67, 95% CI, 1.07-2.61, p = 0.023). Patients with mild-moderate disability at 3 months (mRS 2-3) had the highest odds of improvement at 12 months (OR 8.76, 95% CI 3.68-20.86, p < 0.001). DISCUSSION AND CONCLUSION Long term recovery is common after ICH and associated with age, baseline functional status, mRS at 3 months and hematoma location. Our findings might inform future trials and improve long-term prognostication in clinical practice.
Collapse
Affiliation(s)
- Andrea Morotti
- Department of Continuity of Care and Frailty, Neurology Unit, ASST-Spedali Civili, Brescia, Italy
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Jawed Nawabi
- Department of Neuroradiology, Charité - Universitätsmedizin Berlin, Campus Mitte, Humboldt-Universität zu Berlin, Freie Universität Berlin, Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), BIH Biomedical Innovation Academy, Berlin, Germany
| | - Andrea Pilotto
- Department of Continuity of Care and Frailty, Neurology Unit, ASST-Spedali Civili, Brescia, Italy
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Maddalena Toffali
- Department of Continuity of Care and Frailty, Neurology Unit, ASST-Spedali Civili, Brescia, Italy
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Giorgio Busto
- Department of Experimental and Clinical Biomedical Sciences, Neuroradiology Unit, University of Firenze, AOU Careggi, Firenze, Italy
| | - Federico Mazzacane
- U.C. Malattie Cerebrovascolari e Stroke Unit, IRCCS Fondazione Mondino, Pavia, Italia
| | - Anna Cavallini
- U.C. Malattie Cerebrovascolari e Stroke Unit, IRCCS Fondazione Mondino, Pavia, Italia
| | - Michele Laudisi
- Clinica Neurologica, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Università degli studi di Ferrara, Ospedale Universitario S. Anna, Ferrara, Italia
| | - Luana Gentile
- IRCCS Istituto delle Scienze Neurologiche di Bologna,UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italia
| | - Maria Maddalena Viola
- IRCCS Istituto delle Scienze Neurologiche di Bologna,UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italia
| | - Frieder Schlunk
- Department of Neuroradiology, Medical Centre, University of Freiburg, Freiburg, Germany
| | - Diletta Bartolini
- Cardiovascular and Emergency Medicine, Stroke Unit, University of Perugia/Azienda Ospedaliera Santa Maria Della Misericordia, Perugia, Italy
| | - Maurizio Paciaroni
- Cardiovascular and Emergency Medicine, Stroke Unit, University of Perugia/Azienda Ospedaliera Santa Maria Della Misericordia, Perugia, Italy
| | - Mauro Magoni
- Stroke Unit, Neurologia Vascolare, ASST Spedali Civili di Brescia, Brescia, Italy
| | - Chiara Bassi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Luigi Simonetti
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Neuroradiology Unit, Maggiore Hospital, Bologna, Italy
| | - Enrico Fainardi
- Department of Experimental and Clinical Biomedical Sciences, Neuroradiology Unit, University of Firenze, AOU Careggi, Firenze, Italy
| | - Ilaria Casetta
- Clinica Neurologica, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Università degli studi di Ferrara, Ospedale Universitario S. Anna, Ferrara, Italia
| | - Andrea Zini
- IRCCS Istituto delle Scienze Neurologiche di Bologna,UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italia
| | - Alessandro Padovani
- Department of Continuity of Care and Frailty, Neurology Unit, ASST-Spedali Civili, Brescia, Italy
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| |
Collapse
|
6
|
Duskin J, Yechoor N, Singh S, Mora S, Senff J, Kourkoulis C, Anderson CD, Rosand J. Nutrition markers and discharge outcome in deep and lobar intracerebral hemorrhage. Eur Stroke J 2024:23969873241253048. [PMID: 38738882 DOI: 10.1177/23969873241253048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024] Open
Abstract
INTRODUCTION Malnutrition is common in stroke patients and has been associated with poor functional outcomes and increased mortality after stroke. Previous research on nutrition status and post-intracerebral hemorrhage (ICH) outcomes, however, is limited and conflicting. PATIENTS AND METHODS Monocenter study of patients with spontaneous deep or lobar ICH from a longitudinal cohort enrolling consecutive patients between 1994 and 2022. Nutrition status was assessed using admission body mass index (BMI), albumin, total bilirubin, cholesterol, c-reactive protein, hemoglobin a1c, high-density lipoprotein, hemoglobin, low-density lipoprotein, mean corpuscular volume, alanine transaminase, and triglycerides. Main outcome was favorable discharge outcome (mRS 0-2). Multivariable logistic regression was conducted with adjustment for baseline differences. RESULTS Among 2170 patients, 1152 had deep and 1018 had lobar ICH. Overweight BMI was associated with higher odds of favorable discharge outcome in all (aOR = 3.01, 95% CI 1.59-5.69, p = 0.001) and lobar (aOR = 3.26, 95% CI 1.32-8.08, p = 0.011) ICH after adjustment for baseline differences. This association did not reach statistical significance in deep (aOR = 2.77, 95% CI 0.99-7.72, p = 0.052) ICH. No lab values were associated with functional outcome in all, deep, or lobar ICH after adjustment. DISCUSSION AND CONCLUSION Overweight BMI was associated with favorable discharge status after ICH. These findings could inform future studies to determine whether overweight BMI has a protective effect in ICH patients.
Collapse
Affiliation(s)
- Jonathan Duskin
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Nirupama Yechoor
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Sanjula Singh
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, NL, USA
| | - Samantha Mora
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jasper Senff
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, NL, USA
| | - Christina Kourkoulis
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Christopher D Anderson
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Jonathan Rosand
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| |
Collapse
|
7
|
Okumura M, Sato T, Takahashi J, Kokubu T, Nakada R, Kitagawa T, Tanabe M, Takatsu H, Onda A, Komatsu T, Sakuta K, Sakai K, Umehara T, Mitsumura H, Iguchi Y. Small ischemic lesions accompanying intracerebral hemorrhage: The underlying influence of old lacunes and polyunsaturated fatty acids. Nutr Metab Cardiovasc Dis 2024; 34:1157-1165. [PMID: 38331645 DOI: 10.1016/j.numecd.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 09/23/2023] [Accepted: 01/03/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND AND AIMS Small ischemic lesions (SILs) accompanying intracerebral hemorrhage (ICH) might be induced by small-vessel vulnerability and hypercoagulation. Some polyunsaturated fatty acids (PUFAs) have been associated with hypercoagulation in cardiovascular diseases. Our aim here is to determine how pre-existing small-vessel disease (SVD) and PUFAs may affect SILs. METHODS AND RESULTS We screened consecutive ICH patients (October 2012-December 2021) meeting two inclusion criteria: (1) the patients were hospitalized for acute ICH and were undergoing magnetic resonance imaging and (2) the patients' PUFA measurements were available. After excluding patients with isolated intraventricular hemorrhage, we evaluated whether three SVD markers (white matter hyperintensities, old lacunes, cerebral microbleeds) and PUFAs might be associated with the development of SILs. We selected 319 participants from 377 screened consecutive ICH patients (median age = 64, males = 207 [65 %]). Of the 319 patients, 45 patients (14 %) developed SILs. In a multivariable logistic regression analysis, the factors associated with SILs were old lacunes (OR 3.255, 95 % CI 1.101-9.622, p = 0.033) and DHA/AA ratio (OR 0.180, 95 % CI 0.046-0.704, p = 0.013). Furthermore, in our multivariable analysis using DHA/AA ratio tertiles with and without SILs, we observed a linear trend between SILs and the Higher Tertile of the DHA/AA ratio (DHA/AA ratio Mid-Tertile: OR 1.330, 95%CI 0.557-3.177, p = 0.521, and DHA/AA ratio Lower Tertile: OR 2.632, 95%CI 1.124-6.162, p = 0.026). CONCLUSION The presence of old lacunes and lower DHA/AA ratios might be associated with SILs accompanying ICH.
Collapse
Affiliation(s)
- Motohiro Okumura
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Takeo Sato
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
| | - Junichiro Takahashi
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Tatsushi Kokubu
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Ryoji Nakada
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Tomomichi Kitagawa
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Maki Tanabe
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Hiroki Takatsu
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Asako Onda
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Teppei Komatsu
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Kenichi Sakuta
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Kenichiro Sakai
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Tadashi Umehara
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Hidetaka Mitsumura
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| | - Yasuyuki Iguchi
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan
| |
Collapse
|
8
|
Pezzini D, Nawabi J, Schlunk F, Li Q, Mazzacane F, Busto G, Scola E, Arba F, Brancaleoni L, Giacomozzi S, Simonetti L, Laudisi M, Cavallini A, Katsanos AH, Shoamanesh A, Zini A, Casetta I, Fainardi E, Morotti A, Padovani A. Predictors and Prognostic Impact of Hematoma Expansion in Infratentorial Cerebral Hemorrhage. Neurocrit Care 2024; 40:707-714. [PMID: 37667076 DOI: 10.1007/s12028-023-01819-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 07/24/2023] [Indexed: 09/06/2023]
Abstract
BACKGROUND Hematoma expansion (HE) is common and predicts poor outcome in patients with supratentorial intracerebral hemorrhage (ICH). We investigated the predictors and prognostic impact of HE in infratentorial ICH. METHODS We conducted a retrospective analysis of patients with brainstem and cerebellar ICH admitted at seven sites. Noncontrast computed tomography images were analyzed for the presence of hypodensities according to validated criteria, defined as any hypodense region strictly encapsulated within the hemorrhage with any shape, size, and density. Occurrence of HE (defined as > 33% and/or > 6-mL growth) and mortality at 90 days were the outcomes of interest. Their predictors were investigated using logistic regression with backward elimination at p < 0.1. Logistic regression models for HE were adjusted for baseline ICH volume, antiplatelet and anticoagulant treatment, onset to computed tomography time, and presence of hypodensities. The logistic regression model for mortality accounted for the ICH score and HE. RESULTS A total of 175 patients were included (median age 75 years, 40.0% male), of whom 38 (21.7%) had HE and 43 (24.6%) died within 90 days. Study participants with HE had a higher frequency of hypodensities (44.7 vs. 24.1%, p = 0.013), presentation within 3 h from onset (39.5 vs. 24.8%, p = 0.029), and 90-day mortality (44.7 vs. 19.0%, p = 0.001). Hypodensities remained independently associated with HE after adjustment for confounders (odds ratio 2.44, 95% confidence interval 1.13-5.25, p = 0.023). The association between HE and mortality remained significant in logistic regression (odds ratio 3.68, 95% confidence interval 1.65-8.23, p = 0.001). CONCLUSION Early presentation and presence of noncontrast computed tomography hypodensities were independent predictors of HE in infratentorial ICH, and the occurrence of HE had an independent prognostic impact in this population.
Collapse
Affiliation(s)
- Debora Pezzini
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy.
| | - Jawed Nawabi
- Department of Radiology (CCM), Charité-Universitätsmedizin Berlin, Campus Mitte, Berlin Institute of Health, Humboldt-Universitätzu Berlin, FreieUniversität Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), BIH Biomedical Innovation Academy, Berlin, Germany
| | - Frieder Schlunk
- Berlin Institute of Health (BIH), BIH Biomedical Innovation Academy, Berlin, Germany
- Department of Neuroradiology, Charité-Universitätsmedizin Berlin, FreieUniversität Berlin, Humboldt-Universitätz Berlin, Berlin, Germany
| | - Qi Li
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Federico Mazzacane
- U.C. Malattie Cerebrovascolari e Stroke Unit, IRCCS Fondazione Mondino, Pavia, Italy
| | - Giorgio Busto
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, Florence, Italy
| | - Elisa Scola
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, Florence, Italy
| | - Francesco Arba
- Stroke Unit, Careggi University Hospital, Florence, Italy
| | - Laura Brancaleoni
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italy
| | - Sebastiano Giacomozzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italy
| | - Luigi Simonetti
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UO (SSI) di Neuroradiologia, Ospedale Maggiore, Bologna, Italy
| | - Michele Laudisi
- Clinica Neurologica, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Università degli Studi di Ferrara, Ospedale Universitario S. Anna, Ferrara, Italy
| | - Anna Cavallini
- U.C. Malattie Cerebrovascolari e Stroke Unit, IRCCS Fondazione Mondino, Pavia, Italy
| | - Aristeidis H Katsanos
- Division of Neurology, McMaster University/Population Health Research Institute, Hamilton, ON, Canada
- Second Department of Neurology, Attikon Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Ashkan Shoamanesh
- Division of Neurology, McMaster University/Population Health Research Institute, Hamilton, ON, Canada
| | - Andrea Zini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Neurologia e Rete Stroke Metropolitana, Ospedale Maggiore, Bologna, Italy
| | - Ilaria Casetta
- Clinica Neurologica, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Università degli Studi di Ferrara, Ospedale Universitario S. Anna, Ferrara, Italy
| | - Enrico Fainardi
- Neuroradiology Unit, Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy
| | - Andrea Morotti
- Neurology Unit, Department of Neurological Sciences and Vision, ASST Spedali Civili, Brescia, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Piazzale Spedali Civili, 1, 25123, Brescia, Italy
- Neurology Unit, Department of Neurological Sciences and Vision, ASST Spedali Civili, Brescia, Italy
| |
Collapse
|
9
|
Yang Y, Cheng Y, Wang P, Cai M, Ji X, Zhu H, Zhao X, Sun Y, Zhao P, Yin S. Functional outcome following spontaneous intracerebral hemorrhage between ultrasound guidance endoscopic surgery and conventional craniotomy: A retrospective population-based study. J Stroke Cerebrovasc Dis 2024; 33:107609. [PMID: 38331009 DOI: 10.1016/j.jstrokecerebrovasdis.2024.107609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 01/05/2024] [Accepted: 01/29/2024] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVES Ultrasound guidance endoscopic surgery (ES) has been widely used in the treatment of cerebral hemorrhage in recent years, but relevant research articles are still scarce. Our study aims to investigate the effect of ES compared with conventional craniotomy (CC) on the postoperative complications, and prognosis of patients with intracerebral hemorrhage. MATERIALS AND METHODS The clinical data of 1201 patients with ICH treated in our hospital from January 2017 to January 2020 were collected. The t-test, Chi-squared test and Fisher's exact test were used to analyze the clinical baseline data. Among 1021 spontaneous ICH patients, 193 patients who underwent hematoma evacuation were included in the present analysis. RESULTS The Glasgow Outcome Scale (GOS) score at 6 months had a favorable prognosis in ES group (p = 0.003). ES group had fewer postoperative complications compared with CC group. Operating time and intraoperative blood loss were significantly lower in ES group than CC group (p = 0.001 and p = 0.002). CONCLUSIONS Our study revealed that receiving ES improved the prognosis of ICH patients. Additionally, endoscopic surgery diminishes operative time, and intraoperative blood loss and reduces the incidence of postoperative complications.
Collapse
Affiliation(s)
- Yuefan Yang
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China.
| | - Yuefei Cheng
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - Peng Wang
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - Ming Cai
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - Xiaojun Ji
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - Hongyu Zhu
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - XiaoYun Zhao
- Department of Ultrasound Diagnosis, The Hospital of 81(st) Group Army PLA, PR China
| | - YinChen Sun
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - Peilin Zhao
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China
| | - ShangJiong Yin
- Department of Neurosurgery, The Hospital of 81(st) Group Army PLA, PR China.
| |
Collapse
|
10
|
MacIntosh BJ, Liu Q, Schellhorn T, Beyer MK, Groote IR, Morberg PC, Poulin JM, Selseth MN, Bakke RC, Naqvi A, Hillal A, Ullberg T, Wassélius J, Rønning OM, Selnes P, Kristoffersen ES, Emblem KE, Skogen K, Sandset EC, Bjørnerud A. Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury. Front Neurol 2023; 14:1244672. [PMID: 37840934 PMCID: PMC10568013 DOI: 10.3389/fneur.2023.1244672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 09/05/2023] [Indexed: 10/17/2023] Open
Abstract
Introduction Radiological assessment is necessary to diagnose spontaneous intracerebral hemorrhage (ICH) and traumatic brain injury intracranial hemorrhage (TBI-bleed). Artificial intelligence (AI) deep learning tools provide a means for decision support. This study evaluates the hemorrhage segmentations produced from three-dimensional deep learning AI model that was developed using non-contrast computed tomography (CT) imaging data external to the current study. Methods Non-contrast CT imaging data from 1263 patients were accessed across seven data sources (referred to as sites) in Norway and Sweden. Patients were included based on ICH, TBI-bleed, or mild TBI diagnosis. Initial non-contrast CT images were available for all participants. Hemorrhage location frequency maps were generated. The number of estimated haematoma clusters was correlated with the total haematoma volume. Ground truth expert annotations were available for one ICH site; hence, a comparison was made with the estimated haematoma volumes. Segmentation volume estimates were used in a receiver operator characteristics (ROC) analysis for all samples (i.e., bleed detected) and then specifically for one site with few TBI-bleed cases. Results The hemorrhage frequency maps showed spatial patterns of estimated lesions consistent with ICH or TBI-bleed presentations. There was a positive correlation between the estimated number of clusters and total haematoma volume for each site (correlation range: 0.45-0.74; each p-value < 0.01) and evidence of ICH between-site differences. Relative to hand-drawn annotations for one ICH site, the VIOLA-AI segmentation mask achieved a median Dice Similarity Coefficient of 0.82 (interquartile range: 0.78 and 0.83), resulting in a small overestimate in the haematoma volume by a median of 0.47 mL (interquartile range: 0.04 and 1.75 mL). The bleed detection ROC analysis for the whole sample gave a high area-under-the-curve (AUC) of 0.92 (with sensitivity and specificity of 83.28% and 95.41%); however, when considering only the mild head injury site, the TBI-bleed detection gave an AUC of 0.70. Discussion An open-source segmentation tool was used to visualize hemorrhage locations across multiple data sources and revealed quantitative hemorrhage site differences. The automated total hemorrhage volume estimate correlated with a per-participant hemorrhage cluster count. ROC results were moderate-to-high. The VIOLA-AI tool had promising results and might be useful for various types of intracranial hemorrhage.
Collapse
Affiliation(s)
- Bradley J. MacIntosh
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences, Sandra Black Centre for Brain Resilience & Recovery, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Oslo, Norway
| | - Qinghui Liu
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Till Schellhorn
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Mona K. Beyer
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Inge Rasmus Groote
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Department of Radiology, Vestfold Hospital Trust, Tønsberg, Norway
| | - Pål C. Morberg
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Department of Radiology and Department of Surgery, Vestfold Hospital Trust, Tønsberg, Norway
| | - Joshua M. Poulin
- Hurvitz Brain Sciences, Sandra Black Centre for Brain Resilience & Recovery, Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Oslo, Norway
| | - Maiken N. Selseth
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
- Department of Diagnostic Imaging, Akershus University Hospital, Lørenskog, Norway
| | - Ragnhild C. Bakke
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Aina Naqvi
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Amir Hillal
- Department of Diagnostic Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
| | - Teresa Ullberg
- Department of Diagnostic Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Johan Wassélius
- Department of Diagnostic Radiology, Neuroradiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Ole M. Rønning
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Espen S. Kristoffersen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
- Department of General Practice, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Kyrre Eeg Emblem
- Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Karoline Skogen
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Else C. Sandset
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Atle Bjørnerud
- Computational Radiology & Artificial Intelligence Unit, Department of Physics and Computational Radiology, Clinic for Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
| |
Collapse
|
11
|
Dowlatshahi D, Jamal M, Raposo N. Hematoma Tolerance: Location Matters. Stroke 2023; 54:1558-1559. [PMID: 37216454 DOI: 10.1161/strokeaha.123.043337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Affiliation(s)
- Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa and Ottawa Hospital Research Institute, Canada (D.D., M.J.)
| | - Mobin Jamal
- Department of Medicine (Neurology), University of Ottawa and Ottawa Hospital Research Institute, Canada (D.D., M.J.)
| | - Nicolas Raposo
- Department of Neurology, University Hospital of Toulouse, France (N.R.)
- Toulouse NeuroImaging Center, University of Toulouse, Inserm, UPS, France (N.R.)
| |
Collapse
|