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JLK-SDH is a notification-only, parallel workflow tool that is intended to assist trained radiologists to identify and communicate images of specific patients to a specialist, independent of the standard of care workflow.

JLK-SDH uses an artificial intelligence algorithm to analyze images for findings suggestive of a prespecified clinical condition and to notify an appropriate user of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes non-contrast CT images of the head for subdural hemorrhage (SDH) and sends notifications to a clinician that a suspected SDH has been identified and recommends a review of those images. Images can be previewed and compressed through PACS and mobile applications.

Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests.

JLK-SDH is limited to the analysis of imaging data and should not be used in lieu of full patient evaluation or relied upon to make or confirm the diagnosis.

JLK-SDH is a radiological computer-assisted triage and notification (CADt) software package compliant with the DICOM standard. The device functions as a Non-Contrast Computed Tomography (NCCT) processing module, providing triage and notification for suspected hemispheric subdural hemorrhage (SDH). It serves as a notification-only, parallel workflow tool for hospital networks and trained clinicians. The device helps to identify and communicate specific patient images to trained radiologists, independent of the standard of care workflow. Utilizing an artificial intelligence algorithm, the system automatically receives and analyzes NCCT studies for image features indicating the presence of SDH and sends a notification to alert a radiologist of the case.

This algorithm, hosted on JLK servers, is designed to analyze non-contrast CT images of the head acquired on CT scanners and forwarded to JLK servers. The mobile software module that enables user to receive and toggle notifications for suspected subdural hemorrhages identified by the JLK-SDH Image Analysis Algorithm. Users can view a patient list, and nondiagnostic CT scans through the mobile application. Image viewing through the mobile application interface is for non-diagnostic purposes only.

Here's a detailed breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

• Sample Size: 560 NCCT scans
  • 174 SDH positive cases
  • 386 SDH negative cases
• Data Provenance: Retrospective study. Scans were obtained from various regions in the U.S.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Three.
• Qualifications: All truthers were US board-certified neuroradiologists.

4. Adjudication Method for the Test Set

• Adjudication Method: 2+1 truther scheme. Ground truth was determined by two neuroradiologists, with a third neuroradiologist intervening in cases of disagreement. (28 cases were sent to the third truther).

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No, the text describes a standalone performance evaluation of the device's AI algorithm.

6. Standalone (Algorithm Only) Performance

• Was a standalone performance study done? Yes. The performance data section explicitly states, "JLK, Inc. performed a standalone performance in accordance with the §892.2080 special controls to demonstrate adequate clinical performance of the JLK-SDH module."

7. Type of Ground Truth Used

• Type of Ground Truth: Expert consensus of US board-certified neuroradiologists.

8. Sample Size for the Training Set

• Sample Size: 29,524 non-contrast CT (NCCT) scans
  • 3,330 patients had SDH
  • 11,732 had different kinds of intracranial hemorrhage (IPH, IVH, SAH, or EDH)
  • 14,462 patients did not have any intracranial hemorrhage

9. How the Ground Truth for the Training Set Was Established

• The document does not explicitly detail the exact method for establishing ground truth for the training set. It only mentions that the images "had been obtained in patients with and without intracranial hemorrhage" and categorizes them by the type of hemorrhage. While it suggests clinical diagnoses, the specific process (e.g., expert review, clinical reports, pathology) used to label these training cases is not described.

Clarification on "Acceptance Criteria"
The document states that the "primary endpoints, sensitivity and specificity, both exceeded 80%." This implies that >80% for both sensitivity and specificity served as the acceptance criteria for the standalone performance study. For time-to-notification, the acceptance criterion was to 'meet the target' established by the predicate device.

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