Artificial Intelligence-Assisted Magnetic Resonance Imaging Diagnostic Strategy in a Tertiary Stroke Center (AID-STROKE)

An Artificial Intelligence-Assisted Magnetic Resonance Imaging Diagnostic Strategy in a Tertiary Stroke Center-a Diagnostic Accuracy Study

Quality improvement study with prospective observational design. The study monitors the diagnostic accuracy of an AI-assisted resident radiologist-termed the AI-ResRad diagnostic strategy-compared to an on-call specialist neuroradiologist-termed the SpecNeuroRad strategy-in interpreting stroke MRIs in patients with known onset.

The study includes a pre-planned sub-study evaluating the diagnostic accuracy of neurologists and AI-assisted neurologists.

Study Overview

• Status: Not yet recruiting
• Conditions: Stroke; Stroke Assessment
• Intervention / Treatment: Diagnostic test: Index test (AI-ResRad); Diagnostic test: Reference test (SpecNeuroRad); Diagnostic test: Comparative Index tests: ResRad and AI-SpecNeuroRad; Diagnostic test: Neurologist Diagnostic Accuracy (Sub-study outcome)

Detailed Description

Current clinical practice and the supporting evidence base rely on interpretations by specialist neuroradiologists. Modern radiology departments face increasing imaging demands while contending with limited resources-including a shortage of specialist neuroradiologists. In the ideal setting, patients are evaluated in real time by a vascular neurologist and a neuroradiologist, who synchronously integrate clinical and imaging findings. In such cases, thrombolysis decisions can be re-evaluated concurrently with MRI acquisition, initiating treatment within minutes of scan completion. Although modern stroke MRI protocols can be completed in as little as 10 minutes, these rapid-response team activations often consume a disproportionate share of specialist time and availability. Consequently, real-world clinical practice frequently involves alternative team configurations, including resident radiologists, resident neurologists, and remote specialist consultations-compositions that vary depending on the on-call team's experience, time of day, and day of the week.

Artificial intelligence (AI) can support the team with image interpretation, potentially optimizing time and resources. Recent studies have explored the role of AI-assisted stroke workflows and its ability to accurately detect ischemic lesions and hemorrhagic stroke-demonstrating promising encouraging diagnostic performance. However, there remains a need for prospective studies evaluating the real-world diagnostic accuracy of AI assistance as applied within its intended clinical use context To further understand the potential contributions of AI-assistance and resident radiologist interpretations, we designed the AID-STROKE accuracy study, under the Danish Quality Improvement legal and design framework.

Sub-study: An Artificial Intelligence-Assisted Neurologist-based Diagnostic Strategy in Magnetic Resonance Imaging of Acute Stroke Patients with Known Onset-a Diagnostic Accuracy Study

This pre-specified sub-study will be conducted in patients received at one of the hospitals (Gødstrup Regional Hospital)

• Study Type: Observational
• Enrollment (Estimated): 500

Contacts and Locations

Study Locations

• Denmark
  • Aarhus, Denmark, 8200
    • Aarhus University Hospital
    • Contact: Stig Holm Ovesen, MD, PhD; Phone Number: 0045 + 29426696; Email: stigje@rm.dk
  • Gødstrup, Denmark
    • Gødstrup Regional Hospital
    • Contact: Stig Holm Ovesen, MD, PhD; Phone Number: 0045 + 29426696; Email: stigje@rm.dk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Adult patients suspected of stroke with known onset who meet the rapid response stroke activation and MRI criteria at Aarhus University Hospital and Gødstrup Regional Hospital will be included consecutively.

Description

Inclusion Criteria:

• Age ≥ 18 years
• Stroke team activation
• Thrombolysis candidate
• Known symptom onset
• MRI candidate

Exclusion Criteria:

• Prior inclusion
• Previous MRI in the same course of hospitalization
• No resident radiologist on call

Participation in the neurologists' sub-study is limited to participants enrolled at one of the two participating sites at Gødstrup Regional Hospital.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Acute stroke with known onset; Adult patients suspected of stroke with known onset who meet the rapid response stroke activation and MRI criteria at Aarhus University Hospital and Gødstrup Regional Hospital will be included consecutively.

Diagnostic test: Index test (AI-ResRad); Eligible residents will review MRI sequences from the local PACS as they become available. During this process, they will maintain real-time communication-in person or via phone-with the treating neurologist, who will provide relevant clinical information. Simultaneously, the resident will have access to the AI output. Residents will have full access to the patient's electronic medical record and prior imaging. After integrating these inputs, the resident will complete an AI-assisted MRI interpretation using a predefined survey structure.; Diagnostic test: Reference test (SpecNeuroRad); Before any MRI sequences have been finalized, the resident will notify the on-call specialist neuroradiologist and pass on the clinical information received from the neurologist. The neuroradiologist will then independently review the MRI sequences as they become available in PACS, without access to the resident's interpretation or the AI results. They will also access the patient's electronic medical record and prior imaging. Once both parties have completed their respective surveys, the resident will call the neuroradiologist to jointly deliver an oral MRI interpretation to the neurologist. The radiologic information system's written radiology report may be completed by the neuroradiologist or the resident, with final sign-off by the neuroradiologist.; Diagnostic test: Comparative Index tests: ResRad and AI-SpecNeuroRad; Two additional comparative test strategies will be evaluated: ResRad: Prior to accessing AI results, residents will complete a non-assisted MRI interpretation.; AI-SpecNeuroRad: After completing their initial non-assisted interpretation (SpecNeuroRad), the specialist neuroradiologist will be granted access to the AI output. They will then submit a second interpretation (AI-assisted) using the same survey platform. To enforce internal blinding between non-assisted and AI-assisted interpretations, AI outputs are only revealed upon manual activation, which is timestamped by the system. Interpretation surveys are also timestamped at submission. All non-assisted interpretations must be submitted prior to AI output activation to be considered valid. Cases that violate this timestamp sequence will be excluded from final analyses to ensure methodological integrity.; Diagnostic test: Neurologist Diagnostic Accuracy (Sub-study outcome); Simultaneously with the radiologists' MRI interpretations with and without AI assistance according to the study workflow, the neurologist responsible for patient management will complete a similar MRI interpretation survey. The neurologist will first interpret the MRI without AI assistance and subsequently with AI assistance, mirroring the radiologist study workflow. The neurologist will be blinded to the radiologists' interpretations while completing their assessments, and likewise, the radiologists will be blinded to the neurologist's interpretations.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Composite agreement	Overall agreement is defined as the proportion of patients for whom the AI-ResRad and SpecNeuroRad agree on all MRI pattern items included in the MRI interpretation survey: (1) DWI lesion and (2) hemorrhage.	Immediately after the procedure

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic Accuracy	The diagnostic accuracy of the AI-ResRad and ResRad strategies will be reported in terms of sensitivity, specificity, and positive and negative predictive values, using SpecNeuroRad as the reference standard. This will be assessed separately for each of the imaging patterns: 1) DWI lesion; and 2) hemorrhage.	immediately after the procedure
Comparative Diagnostic Accuracy	Comparative diagnostic accuracy outcomes will be explored between the AI-ResRad and ResRad strategies, using SpecNeuroRad as the reference standard, including the net reclassification index, net benefit, and absolute difference in overall agreement (defined as described above for the primary outcome).	immediately after the procedure
Concordance SpecNeuroRad	For the AI-SpecNeuroRad strategy, outcomes will include pairwise agreement with the original SpecNeuroRad interpretation, characterization of disagreement cases, and identification of AI-induced reclassifications.	immediately after the procedure

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Neurologists' Diagnostic Accuracy (Sub-study)	The diagnostic accuracy of the neurologist's interpretations, both without AI assistance and with AI assistance, will be reported in terms of sensitivity, specificity, and positive and negative predictive values, using SpecNeuroRad as the reference standard. Accuracy will be assessed separately for each imaging pattern: (1) DWI lesion and (2) hemorrhage.	Immediately after the procedure
Neurologists' Composite Agreement (Sub-study)	Overall agreement will be defined as the proportion of patients for whom the neurologist's interpretations (with and without AI assistance) agree with the SpecNeuroRad on all MRI pattern items included in the MRI interpretation survey: (1) DWI lesion and (2) hemorrhage.	Immediately after the procedure

Collaborators and Investigators

• Sponsor: Aarhus University Hospital

Study record dates

Study Major Dates

• Study Start (Estimated): February 16, 2026
• Primary Completion (Estimated): July 1, 2027
• Study Completion (Estimated): July 1, 2027

Study Registration Dates

• First Submitted: January 29, 2026
• First Submitted That Met QC Criteria: January 29, 2026
• First Posted (Actual): February 5, 2026

Study Record Updates

• Last Update Posted (Actual): February 9, 2026
• Last Update Submitted That Met QC Criteria: February 5, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Keywords: MRI; stroke; Artificial Intelligence
• Additional Relevant MeSH Terms: Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases; Stroke
• Other Study ID Numbers: AID-STROKE

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The datasets will not be shared due to legal and privacy restrictions associated with data approved for use in a quality improvement study.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No