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Automatic PredICtion of Edema After Stroke (APICES)

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ClinicalTrials.gov Identifier: NCT04057690
Recruitment Status : Recruiting
First Posted : August 15, 2019
Last Update Posted : August 15, 2019
Sponsor:
Information provided by (Responsible Party):
University Hospital Tuebingen

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

Condition or disease
Stroke, Acute Brain Edema

Detailed 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.


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Study Type : Observational
Estimated Enrollment : 1500 participants
Observational Model: Other
Time Perspective: Retrospective
Official Title: Automatic Prediction of Malignant Brain Edema After Middle Cerebral Artery Ischemic -Stroke
Actual Study Start Date : April 1, 2019
Estimated Primary Completion Date : March 31, 2020
Estimated Study Completion Date : March 31, 2022

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Anthrax Edema

Group/Cohort
MCA ischemia without malignant edema
MCA ischemia without malignant edema
MCA ischemia with malignant edema
MCA ischemia without malignant edema w/o surgical treatment



Primary Outcome Measures :
  1. Number of patients with stroke-related malignant edema after recanalization treatment detected by deep learning algorithms [ Time Frame: 4/2019-3/2022 ]
    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.


Secondary Outcome Measures :
  1. Number of correctly identified specific imaging findings for early detection of malignant edema [ Time Frame: 4/2019-3/2022 ]
    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.



Information from the National Library of Medicine

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Ages Eligible for Study:   Child, Adult, Older Adult
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
1500 retrospective datasets will be collected from 5 large German stroke units. Data sets include imaging data and clinical data from patients with subtotal MCA infarcts (M1-M2 occlusion), with or without malignant brain swelling, with or without reperfusion therapy, with or without neurosurgical decompression, and with or without death following malignant brain edema. Data sets from patients who have died following malignant brain edema will be included. Each data set consists of initial NCCT, CTA, (DSA if available), and follow-up NCCT until 14 days after stroke onset as well as clinical data.
Criteria

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04057690


Contacts
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Contact: Sven Poli, MD MSc +497071290 ext 83269 sven.poli@uni-tuebingen.de
Contact: Julia Zeller, MBA +497071290 ext 68293 julia.zeller@med.uni-tuebingen.de

Locations
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Germany
University Hospital Tuebingen Recruiting
Tuebingen, Germany, 72076
Contact: Sven Poli, MD MSc    +497071290 ext 83269    sven.poli@uni-tuebingen.de   
Contact: Julia Zeller, MBA    +497071290 ext 68293    julia.zeller@med.uni-tuebingen.de   
Sponsors and Collaborators
University Hospital Tuebingen

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Responsible Party: University Hospital Tuebingen
ClinicalTrials.gov Identifier: NCT04057690     History of Changes
Other Study ID Numbers: APICES
First Posted: August 15, 2019    Key Record Dates
Last Update Posted: August 15, 2019
Last Verified: April 2019

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by University Hospital Tuebingen:
Malignant Brain Edema
Stroke, Acute
Prediction
Additional relevant MeSH terms:
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Stroke
Brain Edema
Edema
Cerebrovascular Disorders
Brain Diseases
Central Nervous System Diseases
Nervous System Diseases
Vascular Diseases
Cardiovascular Diseases
Signs and Symptoms