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Methinks NCCT Stroke is a radiological computer aided triage and notification software indicated for use in the analysis of (1) non-contrast head CT (NCCT) images. The device is intended to assist hospital networks and trained physicians in workflow triage by flagging and communicating suspected positive findings of (1) Intracranial Hemorrhage (ICH) and (2) Large Vessel Occlusion (LVO) of the ICA, MCA-M1 and MCA-M2.

Methinks NCCT Stroke uses an artificial intelligence algorithm to analyze images and highlight cases with suspected (1) ICH and (2) LVO in the cloud in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected ICH or LVO findings via PACS and/or notifications. Notifications include preview images that are meant for informational purposes only, and are not intended for diagnostic use beyond notification.

The device does not alter the original medical image, and it is not intended to be used as a primary diagnostic device. The results of Methinks NCCT Stroke are intended to be used in conjunction with other patient information and based on professional judgment to assist with triage/prioritization of medical images. Notified clinicians are ultimately responsible for reviewing full images per the standard of care. Methinks NCCT Stroke is for adults only.

Methinks NCCT Stroke is a radiological computer-assisted triage and notification software device. The device receives Non-Contrast Computed Tomography (NCCT) images and processes them to provide triage and notification prioritization of suspected Intracranial Hemorrhage (ICH) and Large Vessel Occlusion (LVO) of the ICA, MCA-M1 and MCA-M2. The Methinks NCCT Stroke device is an AI/ML Software as a Medical Device. The outputs of the device are intended to be used by trained clinicians in the prioritization of patients with suspected ICH and/or LVO.

The provided FDA 510(k) clearance letter for the Methinks NCCT Stroke device details the acceptance criteria and the study that proves the device meets these criteria. Here's a breakdown of the requested information:

Acceptance Criteria and Reported Device Performance

Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the reported performance metrics, primarily sensitivity (Se) and specificity (Sp), for both Intracranial Hemorrhage (ICH) and Large Vessel Occlusion (LVO) detection. The document states that "Sensitivity and specificity exceed the pre-specified performance goals for ICH and LVO," although the exact numerical "goals" are not explicitly stated. The performance of the device against human readers is also an implicit acceptance criterion.

Study Information

1. Sample sizes used for the test set and the data provenance:

   • ICH Test Set: 358 cases (132 ICH Positive, 226 ICH Negative)
   • LVO Test Set: 335 cases (110 LVO Positive, 225 LVO Negative)
   • Data Provenance: Retrospective, blinded, multicenter, multinational study.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • The document implies that ground truth for the initial performance evaluation (Se and Sp for ICH and LVO) was established through "expert reader truthing of the data." The number and qualifications of these specific experts for ground truth establishment are not explicitly stated beyond "expert reader."
   • For the reader study, there were 4 readers involved: 2 "expert neuroradiologists" and 2 "general radiologists (non-experts)." Their specific years of experience or other detailed qualifications are not provided beyond these labels.

3. Adjudication method for the test set:

   • The document mentions "expert reader truthing of the data" for establishing ground truth but does not specify a detailed adjudication method (e.g., 2+1, 3+1). For the reader study, the individual performance of the readers is provided, implying that their interpretations were compared against the established ground truth, but not that they formally adjudicated for the ground truth itself within the study.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • A MRMC comparative study was done comparing the device's performance to human readers (radiologists) without AI assistance.
   • Effect Size of AI vs. Human Readers (Standalone AI vs. Human Alone):
     • LVO Sensitivity:
       • Methinks NCCT-LVO: 73.6%
       • Expert Neuroradiologists (R1 + R2): 50.0%
       • General Radiologists (R3 + R4): 37.7%
     • Difference in Sensitivity (Effect Size):
       • Methinks NCCT-LVO vs. Experts: 23.6% (95%CI: 8.5% - 38.7%), showing superiority of the device.
       • Methinks NCCT-LVO vs. Non-experts: 35.9% (95%CI: 16.0% - 42.9%), also showing superiority of the device.
   • The study does not report how much human readers improve with AI assistance (i.e., human-in-the-loop performance). It focuses on the standalone performance of the AI compared to human readers working without AI.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, a standalone performance evaluation of the Methinks NCCT Stroke algorithm was done for both ICH and LVO detection. The reported sensitivity and specificity metrics (e.g., ICH Se: 94.7%, Sp: 99.5%; LVO Se: 76.4%, Sp: 91.1%) are for the algorithm only.

6. The type of ground truth used:

   • The ground truth for the test set was established by "expert reader truthing of the data." This implies a consensus of medical experts, likely radiologists or neuroradiologists, reviewing the images. It is not explicitly stated if pathology, surgical findings, or long-term clinical outcomes were used to confirm the ground truth.

7. The sample size for the training set:

   • The document does not specify the sample size for the training set. It only mentions the test set sizes.

8. How the ground truth for the training set was established:

   • The document does not specify how the ground truth for the training set was established. It only mentions the "expert reader truthing of the data" in the context of the performance validation (test set).

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