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Ligence Heart is a fully automated software platform that processes, analyses and makes measurements on acquired transthoracic cardiac ultrasound images, automatically producing a full report with measurements of several key cardiac structural and functional parameters. The data produced by this software is intended to be used to support qualified cardiologists or sonographers for clinical decision making. Ligence Heart is indicated for use in adult patients. Ligence Heart has not been validated for the assessment of congenital heart disease, valve disease, pericardial disease, and/or intra-cardiac lesions (e.g., tumors, thrombi).

Ligence Heart is an image post-processing software used for viewing and quantifying adult cardiac ultrasound DICOM studies. The device is intended to generate structured measurement reports for echocardiography analysis and aid qualified sonographers and cardiologists in their decision-making process.

Ligence Heart automatically identifies standard transthoracic echo views with machine-learning–based view classification, cardiac cycle selection, and border detection, then generates reproducible quantitative left-ventricular volumetric and functional measurements. The results are inserted into a PACS-compatible report that the reviewing cardiologist or sonographer can accept, edit, supplement with additional manual measurements, or entirely replace with manual measurements. The software also organizes, displays, and compares each measurement with reference-guideline ranges. Completed reports are exported in PDF, streamlining routine echocardiography workflow while leaving final diagnostic responsibility with the clinician.

Here's a breakdown of the acceptance criteria and the study proving Ligence Heart meets them, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Reported Device Performance

Study Details

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

• Sample Size: 524 echocardiographic studies. (Initially, 600 were acquired, but 76 were excluded).
• Data Provenance: Retrospective, acquired from a U.S.-based independent Echocardiography Core Laboratory.

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

• Number of Experts: Three independent expert sonographers.
• Qualifications of Experts: The document explicitly states "expert sonographers." No further specific details (e.g., years of experience, board certification) are provided in this excerpt.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

• The document states, "524 echocardiographic studies were assessed by all three human readers..." This implies that all three contributed to the ground truth, but it doesn't explicitly state an adjudication method like 2+1 or 3+1. Given the use of "agreement between Ligence Heart and three independent expert sonographers...quantified using the reference-scaled IEC," it suggests that each expert's measurements were compared against the device, rather than a consensus ground truth being established before comparison with the device.

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:

• No, an MRMC comparative effectiveness study was not explicitly done to measure human reader improvement with AI assistance. The study focused on the standalone performance of the Ligence Heart device and its interchangeability with expert human measurements. It did not directly assess how human readers' performance would change when using the AI as an assistant.

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

• Yes, a standalone performance study was done. The primary clinical performance endpoint measured the agreement between "Ligence Heart" (the automated measurements) and "three independent expert sonographers." This evaluates the device's output independently against expert human measurements.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Expert measurements/readings. The ground truth for the comparison was established by the measurements from "three independent expert sonographers."

7. The sample size for the training set:

• The document explicitly states, "Test datasets were strictly segregated from algorithm training datasets, as they are from completely separate cohorts." However, the sample size for the training set is not provided in this excerpt.

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

• The document states that the test datasets were "strictly segregated from algorithm training datasets." However, how the ground truth for the training set was established is not described in this excerpt. It can be inferred that it likely involved expert annotations or measurements, similar to the test set, but the details are not available here.

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