Stroke, AcuteAPICESNCT04057690
Automatic PredICtion of Edema After Stroke
An observational study of Stroke, Acute and Brain Edema, run by University Hospital Tuebingen at 19 sites in 3 countries.
Trial summary
To use machine learning for early detection of malignant brain edema in patients with MCA ischemia Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Stroke, Acute, Brain Edema
- How many people
- 1,687 participants
- Where
- 19 sitesin 3 countries
- Study dates
- 1 Apr 2019to 31 Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
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.
Who may be able to join
- 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
Who cannot join
- Non-acute MCA infarct
- < subtotal MCA infarct
Trial locations and contacts
19 sites in 3 countries.
19 sites in 3 countries
Germany17 sites
Charité Universitätsmedizin Berlin
Berlin
Universitätsklinikum Bonn
Bonn
Fraunhofer- Gesellschaft zur Förderung der angewandten Forschung e.V., Fraunhofer MEVIS
Bremen
Universitätsklinikum Düsseldorf
Düsseldorf
Universitätsklinikum Hamburg-Eppendorf
Hamburg
Klinikum der Medizinischen Hochschule Hannover
Hanover
Universitätsklinikum Heidelberg
Heidelberg
Universitätsklinikum Leipzig
Leipzig
Klinikum der Ludwig-Maximilians-Universität München
Munich
Technische Universität München
Munich
Universitätsklinikum Münster
Münster
Universitätsklinikum Regensburg
Regensburg
Klinikum Stuttgart
Stuttgart
University Hospital Tuebingen
Tübingen, 72076
Hertie Institute for AI in Brain Health
Tübingen
Universitätsklinikum Ulm
Ulm
Universitätsklinikum Würzburg
Würzburg
About this study
Official title: Automatic Prediction of Malignant Brain Edema After Middle Cerebral Artery Ischemic -Stroke
To use machine learning for early detection of malignant brain edema in patients with MCA ischemia
Read the 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.
- Conditions
- Stroke, Acute, Brain Edema
- Keywords
- Malignant Brain Edema, Stroke, Acute, Prediction
- Medical subject headings
- Stroke, Brain Edema
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| MCA ischemia without malignant edema | MCA ischemia without malignant edema | |
| MCA ischemia with malignant edema | MCA ischemia without malignant edema w/o surgical treatment |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 4/2019-3/2022
Secondary outcomes (1)
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.
Measured: 4/2019-3/2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Aug 2019
- Study start1 Apr 2019
- Primary completion30 Sep 2023
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Stroke, AcuteStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 1,687 participants (actual)
Sponsor and investigators
- Lead sponsor
- University Hospital Tuebingen
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Sven Poli, MD MSc, Principal investigator, sven.poli@uni-tuebingen.de
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04057690
- Sponsor's protocol ID
- APICES
- Acronym
- APICES
- Status last verified
- Sep 2025
- First submitted
- 25 Apr 2019
- Last updated
- 10 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 10 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Automatic Prediction of Malignant Brain Edema After Middle Cerebral Artery Ischemic -Stroke
- ClinicalTrials.gov ID
- NCT04057690
- Acronym / sponsor ID
- APICES / APICES
- Conditions
- Stroke, Acute, Brain Edema
- Keywords
- Malignant Brain Edema, Stroke, Acute, Prediction
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 1,687 participants (actual)
- Lead sponsor
- University Hospital TuebingenUniversity, hospital or other
- Study start
- 1 Apr 2019 (actual)
- Primary completion
- 30 Sep 2023 (actual)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 15 Aug 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
To use machine learning for early detection of malignant brain edema in patients with MCA ischemia
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.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| MCA ischemia without malignant edema | – | –MCA ischemia without malignant edema |
| MCA ischemia with malignant edema | – | –MCA ischemia without malignant edema w/o surgical treatment |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- 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.
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (2 listed)
- Non-acute MCA infarct
- < subtotal MCA infarct
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
1 secondary outcome
Number of correctly identified specific imaging findings for early detection of malignant edema
Time frame: 4/2019-3/2022
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Sep 2025.
Related trials for Stroke, Acute
Recruiting
Connectomic Alterations Following Acute Ischemic Stroke in the MCA Territory
Ischemic Stroke
RecruitingObservational study
Clevidipine for the Antihypertensive Treatment of Acute Intracerebral Hemorrhage
Intracerebral Hemorrhage, Stroke
Active, not recruitingPhase 4
A Study Testing How Well the Drug Extract of Ginkgo Biloba Leaves Tablets Works for People With Memory or Thinking Problems After a Stroke When Added to Standard Treatment
Ischemic Stroke Hospitalized, Impairment, Cognitive
Not yet recruitingPhase 4
Anti-inflammatory and Anti-thrombotic Therapy With colcHicine and Low Dose Rivaroxaban for Major Adverse Cardiovascular Events Reduction in Ischemic Stroke
Ischemic Stroke
Not yet recruitingPhase 3
INTRA-ARTERIAL MeVO TREATMENT (IMP-ACT) Within the ACT-GLOBAL Adaptive Platform Trial-NCT06352632
Stroke, Acute Ischemic, Medium Vessel Occlusion
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Sven Poli, MD MSc principal investigator
sven.poli@uni-tuebingen.de
19 sites in 3 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Stroke, Acute and Brain Edema, run by University Hospital Tuebingen at 19 sites in 3 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 10 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 19 sites in Germany, Austria, United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of patients with stroke-related malignant edema after recanalization treatment detected by deep learning algorithms (time frame: 4/2019-3/2022). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Sep 2025.