Automatic PredICtion of Edema After Stroke

Stroke, Acute Clinical Trial

— APICES  

Official title:

Automatic Prediction of Malignant Brain Edema After Middle Cerebral Artery Ischemic -Stroke

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04057690
• Other study ID #: APICES
• Status: Recruiting
• Start date: April 1, 2019
• Est. completion date: March 31, 2023

Study information

• Verified date: November 2020
• Source: University Hospital Tuebingen
• Contact: Sven Poli, MD MSc
• Phone: +497071290
• Email: sven.poli[@]uni-tuebingen.de
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

To use machine learning for early detection of malignant brain edema in patients with MCA ischemia

Description:

Malignant cerebral edema following large ischemic strokes account for up to 10% of all ischemic strokes. Mortality rates are high and most of the survivors are left severely disabled. Although decompressive craniectomy has been shown to significantly decrease mortality, high morbidity rates among survivors are reported. The optimal timepoint when neurosurgical decompression should be performed in the individual patient varies and is a subject of debate. Early prediction of malignant brain edema to identify those patients who benefit from surgical treatment is a clinical challenge. The aim of this study is to use machine learning for comprehensive analysis of CT images as well as clinical data from 1500 patients with large ischemic MCA strokes in oder to develop a model for early prediction of malignant brain edema. In a first step algorithms automatically identify characteristic imaging features and clinical data of 1400 retrospective data sets to create a multistage model (learning phase). This is followed by a validation phase where the model is tested with 100 other retrospective data sets.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1500
• Est. completion date: March 31, 2023
• Est. primary completion date: December 31, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Acute = subtotal MCA infarct (M1-M2 occlusion)
• with or without malignant brain swelling
• with or without reperfusion therapy
• with or without neurosurgical decompression
• with or without death following malignant brain edema

Exclusion Criteria:

• Non-acute MCA infarct
• < subtotal MCA infarct

Related Conditions & MeSH terms

• Brain Edema
• Edema
• Stroke
• Stroke, Acute

Locations

Country	Name	City	State
Germany	University Hospital Tuebingen	Tuebingen

Sponsors (1)

Lead Sponsor	Collaborator
University Hospital Tuebingen

Country where clinical trial is conducted

Germany, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Number of patients with stroke-related malignant edema after recanalization treatment detected by deep learning algorithms	Deep learning algorithms will be used for automatic identification of specific image findings and specific clinical data that indicate a stroke-related malignant edema. Primary outcome measures are Sensitivity/Specificity/negative predictive value/positive predictive value of early detection of patients developing stroke-related malignant edema based on initial CT and 24 hour follow up CT and clinical parameters.	4/2019-3/2022
Secondary	Number of correctly identified specific imaging findings for early detection of malignant edema	Used specific imaging findings for early detection of malignant brain edema are Collateral status, Clot Burden Score, Vein Score, Change in CSF volume. In this study the specific image findings are manually annotated and also automatically detected using deep learning algorithms. Secondary outcome measures are Sensitivity/Specificity/NPV/PPV of specific imaging findings identified by deep learning algorithms.	4/2019-3/2022