Study on the Performance of a Machine Learning Algorithm Recognizing and Triaging Large Vessel Occlusions Using Non-contrast CT Scans

NCT06216457 | Not Yet Recruiting FDA Device

• 1 other identifier: SMART-LVO Registry
• Study Type: observational
• Target: 5,000
• Locations: 0 countries
• Sites: N/A

Brief Summary

The goal of this prospective observational study is to assess the effectiveness and performance of Methinks AI stroke imaging software platform in acute Code Stroke patients, and as a comparator to study sites utilizing existing AI imaging stroke platforms. The main question\[s\] it aims to answer is: • Performance of and outcomes associated with the use of the Methinks AI stroke imaging medical device in real-world clinical practice.

Conditions

Stroke, Ischemic; Stroke Hemorrhagic; Stroke, Acute; Brain Ischemia

Outcome Measures

Primary Outcomes (1)

• Evaluate the sensitivity and specificity of the following Methinks AI modules:

  1. Methinks NCCT algorithm detecting ICA, M1, and M2 occlusions. 2. Methinks NCCT algorithm detecting ICHs. 3. Methinks CTA algorithm detecting ICA, M1, and M2 occlusions.

  Baseline, pre-intervention (Code Stroke presentation and screening), During Code Stroke treatment, Immediately After the stroke treatment, Up to Discharge or 7 Days (whichever is sooner).

Secondary Outcomes (3)

• Time Potential time reduction - difference in speed to LVO notification between Methinks NCCT-LVO and competitor CTA-LVO.

  Baseline, pre-intervention (Code Stroke presentation and screening), During Code Stroke treatment, Immediately After the stroke treatment, Up to Discharge or 7 Days (whichever is sooner).

• Time for NCCT-LVO Notification.

  Baseline, pre-intervention (Code Stroke presentation and screening), During Code Stroke treatment, Immediately After the stroke treatment, Up to Discharge or 7 Days (whichever is sooner).

• User experience.

  1 day (Questionnaire completed at individual site enrollment completion.)

Study Arms (3)

Group 1: LVO

Subjects with Methinks NCCT algorithm detecting ICA, M1, and M2 occlusions.

Device: AI software for Stroke

Group 2: ICH

Subjects with Methinks NCCT algorithm detecting ICHs.

Device: AI software for Stroke

Group 3: Controls

Subjects with final diagnosis confirmed not to be Stroke (i.e. stroke mimic) or any type of stroke not determined to be: LVO (ICA, M1 or M2) or ICH.

Device: AI software for Stroke

Interventions

AI software for Stroke DEVICE

AI Software for Non-Contrast Head CT (Computed Tomography) and CT Angiography, utilized for Code Stroke screening, notification and triage.

Also known as: Methinks AI Software

Group 1: LVO; Group 2: ICH; Group 3: Controls

Eligibility Criteria

• Age: 22 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Consecutive Code Stroke patients, aged 22 or older, regardless of presence or absence of ultimate diagnosis of Ischemic Stroke or Hemorrhagic Stroke.

You may qualify if:

• Subjects with acute neurological symptoms suggestive of Stroke, ischemic or hemorrhagic ("Code Stroke"), regardless of presence or absence of final Stroke diagnosis.
• Subjects aged 22 years or older.
• NCCT performed for Code Stroke screening.
• If the patient does not have a hemorrhage, a CTA (head and neck, performed for Code Stroke screening) should also be performed.
• NCCT and CTA have been processed by Methinks AI software.

You may not qualify if:

• ● Subject imaging does not meet Image Acquisition and DICOM Tag Requirements

Sponsors & Collaborators

• Methinks Software SL: lead
• Santiago Ortega- global PI: collaborator

Related Links

• Sponsor website

MeSH Terms

Conditions

Ischemic Stroke; Hemorrhagic Stroke; Stroke; Brain Ischemia

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases

Central Study Contacts

Carlotta Calvi

CONTACT

+34639041147; research@methinks.ai

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 4, 2024
• First Posted: January 22, 2024
• Study Start: July 1, 2024
• Primary Completion: July 30, 2024
• Study Completion: October 31, 2024
• Last Updated: May 29, 2024

Record last verified: 2024-05

Data Sharing

• IPD Sharing: Will not share