Study on the Prognostic Prediction Model of Patients With Acute Intracerebral Hemorrhage by Artificial Intelligence

NCT ID: NCT05424614

Last Updated: 2022-06-21

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 150 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-05-13
• Study Completion Date: 2024-12-30

Brief Summary

Spontaneous intracerebral hemorrhage(SICH) is the most lethal and disabling stroke. Timely and accurate assessment of patient prognosis could facilitate clinical decision making and stratified management of patients and is important for improving patient clinical prognosis. However, current studies on the prediction of prognosis of patients with SICH are limited and only include a single variable, with less precise results and inconvenient clinical application, which may lead to delays in effective patient treatment. Our group's previous studies on SICH showed that hematoma heterogeneity and the degree of contrast extravasation within the hematoma are closely related to the clinical outcome of patients, but they are difficult to describe quantitatively based on imaging signs. Based on this, we propose to use radiomics to quantitatively extract hematoma features from NCCT and CTA images, combine them with patients' clinical information and laboratory tests, study their relationship with the prognosis of cerebral hemorrhage, and use artificial intelligence to establish a rapid and accurate prognostic prediction model for patients with SICH, which is of great significance to guide clinical individualized treatment.

Conditions

Cerebral Hemorrhage; Prognosis; Artificial Intelligence

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

intracerebral hemorrhage group

Patients with the intracerebral hemorrhage who presented to the hospital within 24 hours of symptom onset

Functional outcome follow-up of patients

Intervention Type: OTHER

Patients were followed up by telephone after discharge, every 4 weeks, until the end of the 3-month follow-up. Their functional status was determined based on the MRS score (modified Rankin Scale). Those with less than 3 points were defined as having a good prognosis, and those with more than 3 points were defined as having a poor prognosis

Interventions

Functional outcome follow-up of patients

Patients were followed up by telephone after discharge, every 4 weeks, until the end of the 3-month follow-up. Their functional status was determined based on the MRS score (modified Rankin Scale). Those with less than 3 points were defined as having a good prognosis, and those with more than 3 points were defined as having a poor prognosis

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• 1. aged 18-80 years; 2. patients diagnosed with acute cerebral hemorrhage by CT examination; 3. complete non-contrast CT and CTA images; 4. the time interval from onset to the first baseline CT and CTA examination is less than 6 hours; 5. follow-up data within 3 months; 6. agree and sign a written document.

Exclusion Criteria

• 1. Patients with secondary aneurysm hemorrhage; 2. Patients with secondary hemorrhage of cerebrovascular malformation; 3. Patients with dissecting aneurysm hemorrhage; 4. Patients with cerebral infarction hemorrhage transformation; 5. Patients lost to follow-up within 3 months; 6. CT or CTA images have a heavy artefact.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Beijing Neurosurgical Institute

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Shengjun Sun

Role: PRINCIPAL_INVESTIGATOR

Beijing Neurosurgical Instuitute

Locations

Beijing Tiantan Hospital, Capital Medical University

Beijing, Beijing Municipality, China

Site Status: RECRUITING

Countries

China

Central Contacts

Shengjun Sun

Role: CONTACT

sunshengjun0212@163.com

13611293369

References

Pszczolkowski S, Manzano-Patron JP, Law ZK, Krishnan K, Ali A, Bath PM, Sprigg N, Dineen RA. Quantitative CT radiomics-based models for prediction of haematoma expansion and poor functional outcome in primary intracerebral haemorrhage. Eur Radiol. 2021 Oct;31(10):7945-7959. doi: 10.1007/s00330-021-07826-9. Epub 2021 Apr 16.

Reference Type: BACKGROUND

PMID: 33860831 (View on PubMed)

Xie H, Ma S, Wang X, Zhang X. Noncontrast computer tomography-based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model. Eur Radiol. 2020 Jan;30(1):87-98. doi: 10.1007/s00330-019-06378-3. Epub 2019 Aug 5.

Reference Type: BACKGROUND

PMID: 31385050 (View on PubMed)

Guo R, Zhang R, Liu R, Liu Y, Li H, Ma L, He M, You C, Tian R. Machine Learning-Based Approaches for Prediction of Patients' Functional Outcome and Mortality after Spontaneous Intracerebral Hemorrhage. J Pers Med. 2022 Jan 14;12(1):112. doi: 10.3390/jpm12010112.

Reference Type: BACKGROUND

PMID: 35055424 (View on PubMed)

Gregorio T, Pipa S, Cavaleiro P, Atanasio G, Albuquerque I, Chaves PC, Azevedo L. Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis. BMC Med Res Methodol. 2018 Nov 20;18(1):145. doi: 10.1186/s12874-018-0613-8.

Reference Type: BACKGROUND

PMID: 30458727 (View on PubMed)

Fu F, Sun S, Liu L, Gu H, Su Y, Li Y. Iodine Sign as a Novel Predictor of Hematoma Expansion and Poor Outcomes in Primary Intracerebral Hemorrhage Patients. Stroke. 2018 Sep;49(9):2074-2080. doi: 10.1161/STROKEAHA.118.022017.

Reference Type: BACKGROUND

PMID: 30354984 (View on PubMed)

Wang J, Wang W, Liu Y, Zhao X. Associations Between Levels of High-Sensitivity C-Reactive Protein and Outcome After Intracerebral Hemorrhage. Front Neurol. 2020 Oct 6;11:535068. doi: 10.3389/fneur.2020.535068. eCollection 2020.

Reference Type: BACKGROUND

PMID: 33123072 (View on PubMed)

Menon G, Johnson SE, Hegde A, Rathod S, Nayak R, Nair R. Neutrophil to lymphocyte ratio - A novel prognostic marker following spontaneous intracerebral haemorrhage. Clin Neurol Neurosurg. 2021 Jan;200:106339. doi: 10.1016/j.clineuro.2020.106339. Epub 2020 Oct 28.

Reference Type: BACKGROUND

PMID: 33183885 (View on PubMed)

Morotti A, Arba F, Boulouis G, Charidimou A. Noncontrast CT markers of intracerebral hemorrhage expansion and poor outcome: A meta-analysis. Neurology. 2020 Oct 6;95(14):632-643. doi: 10.1212/WNL.0000000000010660. Epub 2020 Aug 26.

Reference Type: BACKGROUND

PMID: 32847959 (View on PubMed)

Tseng WC, Wang YF, Wang TG, Hsiao MY. Early spot sign is associated with functional outcomes in primary intracerebral hemorrhage survivors. BMC Neurol. 2021 Mar 20;21(1):131. doi: 10.1186/s12883-021-02146-3.

Reference Type: BACKGROUND

PMID: 33743639 (View on PubMed)

Other Identifiers

2022-2-1074

Identifier Type: -

Identifier Source: org_study_id