(224 days)
syngo.CT Brain Hemorrhage is designed to assist the radiologist in prioritizing cases of suspected intracranial hemorrhage, also in the subarachnoid space, on non-contrast CT examinations of the head. It makes case-level output available to a CT scanner or other PACS system for worklist prioritization. The output is intended for informational purposes only and is not intended for diagnostic use. The device does not alter the original medical image and is not intended to be used as a standalone diagnostic device.
The subject device syngo.CT Brain Hemorrhage is an image-processing software that uses an artificial intelligence algorithm to support qualified clinicians in the analysis and prioritization of non-contrast head CT images. It is a notification-only processing application that algorithmically identifies findings suspicious of acute intracranial hemorrhage (ICH) and acute subarachnoid hemorrhage (SAH). The subject device facilitates a parallel workflow, where cases suspected of presence of ICH or SAH are flagged. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue.
Here's a breakdown of the acceptance criteria and study details for the syngo.CT Brain Hemorrhage device, based on the provided text:
Acceptance Criteria and Device Performance
| Acceptance Criteria (Performance Goal) | Reported Device Performance (Intracranial Hemorrhage) | Reported Device Performance (Subarachnoid Hemorrhage) |
|---|---|---|
| Sensitivity ≥ 80% | 95.0% (95% CI: 92.5%-96.7%) | 86.1% (95% CI: 81.1%-90.0%) |
| Specificity ≥ 80% | 93.1% (95% CI: 90.5%-95.1%) | 85.2% (95% CI: 82.3%-87.7%) |
Study Details
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Sample size used for the test set and the data provenance:
- Sample Size: 900 anonymized head CT cases.
- Data Provenance: From 5 sites in the US and Europe. The distribution of positive (case with ICH) and negative (case without ICH) cases was approximately equal.
- Type: Retrospective (implied by "anonymized head CT cases from 5 sites").
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: 3
- Qualifications: US board-certified neuroradiologists with more than 10 years of experience.
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Adjudication method for the test set:
- Method: Majority read (e.g., 2 out of 3 experts agreed).
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If a multi-reader multi-case (MRMC) comparative effectiveness study was done: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned. The study described is a standalone performance study.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Yes, the document explicitly states: "The performance of the syngo.CT Brain Hemorrhage device has been va alone performance study."
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The type of ground truth used: Expert consensus, established by the majority read of 3 US board-certified neuroradiologists.
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The sample size for the training set: 29,713 cases.
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How the ground truth for the training set was established: The document does not explicitly state how the ground truth for the training set was established. It only mentions the training data size.
§ 892.2080 Radiological computer aided triage and notification software.
(a)
Identification. Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (
e.g., improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use;
(ii) A detailed description of the intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.