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LVivo platform is intended for non-invasive processing of ultrasound images to detect, measure, and calculate relevant medical parameters of structures and function of patients with suspected disease. In addition, it has the ability to provide Quality Score feedback.

The LVivo platform is a software system for automated analysis of ultrasound examinations. Automated analysis of echocardiographic examinations is done using DICOM movies. The LVivo platform supports global and segmental evaluation of the left ventricle (LV) of the heart. The global LV function is evaluated from two of the apical views: four-chamber (4CH) and two-chamber (2CH) by ejection fraction (EF). The segmental LV function is done from three apical views 4CH, 2CH and three chamber (3CH) and supports wall motion evaluation and strain. LVivo CE-EF (Contrast EF) extends the current toolbox of the LVivo platform by providing the ability to process Ultrasonic DICOM images which acquire by Ultrasound Equipment in which the patient was prescribed a contrast agent. In addition to the LV analysis, the cardiology toolbox includes a module for automated evaluation of the Right Ventricular function. The LVivo platform includes one additional non-cardiac module for the measurement of the bladder volume.

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

Acceptance Criteria and Reported Device Performance

Study Information

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

   • Sample Size: 101 patient exams.
   • Data Provenance: The data was collected from multiple sources: Beth Israel, Soroka, Hadassah (presumably Israel, based on the manufacturer's location), and UCMC (likely a US center given the race information collection). The text indicates that 69 of the 101 patients were collected from the US. The study is retrospective, as it refers to collected "patient exams."

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

   • Number of Experts: 3 sonographers.
   • Qualifications: The text explicitly states "3 sonographers" were used. While their specific years of experience are not mentioned, the implication is that they are qualified medical professionals capable of performing and interpreting ultrasound measurements. The subsequent review by a cardiologist also suggests oversight and validation of their measurements.

3. Adjudication method for the test set:

   • The ground truth was "comprised of the measurements by the 3 sonographers." This suggests a consensus or averaging approach among the three sonographers. It further states, "No further changes by the cardiologist to the measurements were needed following the cardiologist's review," implying the cardiologist reviewed and implicitly approved the sonographers' consensus measurements. This could be interpreted as a form of expert consensus adjudication, where the sonographers' measurements formed the basis, and a cardiologist provided final validation.

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, a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not described. This study directly compared the algorithm's performance to human (sonographer) ground truth measurements rather than assessing human reader improvement with AI assistance.

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

   • Yes, a standalone performance evaluation of the algorithm was done. The study compares the "automated results" of the LVivo Software Application to the established "manual measurements" (ground truth). The fact that the algorithm "processed automatically 91/101 (90%) of the exams" and these automated results were compared to the manually derived ground truth confirms a standalone evaluation.

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

   • The ground truth used was expert consensus based on "manual measurements" performed by "3 sonographers," which were then reviewed and confirmed by a cardiologist.

7. The sample size for the training set:

   • The document does not provide the sample size for the training set. It only discusses the performance evaluation using the test set of 101 patient exams.

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

   • The document does not provide any information on how the ground truth for the training set was established. The focus of this submission is on the performance evaluation of the final device using a designated test set.

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The ACUSON Redwood ultrasound imaging system is intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Fetal, Abdominal, Pediatric, Small Parts, OB/GYN (useful for visualization of the ovaries, follicles, uterus, and other pelvic structures), Adult, Pediatric and Neonatal Cardiac, Pelvic, Neonatal Cephalic, Adult Cephalic, Vascular, Musculoskeletal, Superficial Musculoskeletal, Transcranial, and Peripheral Vascular.

The system supports the Ultrasound-Derived Fat Fraction (UDFF) measurement tool to report an index that can be useful as an aid to a physician managing adult patients with hepatic steatosis.

The system also provides the ability to measure anatomical structures: fetal, abdominal, pediatric, small organ, neonatal cephalic, adult cephalic, cardiac (adult, pediatric and neonatal), transesophageal, transrectal, transvaginal, peripheral vessel, musculoskeletal (conventional), musculoskeletal (superficial), and calculation packages that provide information to the clinician that may be used adjunctively with other medical data obtained by a physician for clinical diagnosis purposes.

The ACUSON Redwood Diagnostic Ultrasound System is multi-purpose, mobile, softwarecontrolled, diagnostic ultrasound system with an on-screen display for thermal and mechanical indices related to potential bio-effect mechanisms. Its function is to acquire harmonic ultrasound echo data and display it in B-Mode, M-Mode, Pulsed (PW) Doppler Mode, Continuous (CW) Doppler Mode, Color Doppler Mode, Color M mode, Doppler Tissue Image mode, Amplitude Doppler Mode, Combination modes, Harmonic Imaging and 3D Imaging modes, and 4D imaging modes on a flat panel display for diagnostic ultrasound imaging.

Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:

Preamble: The provided document is a 510(k) summary for the ACUSON Redwood Diagnostic Ultrasound System. The core of the study described focuses on the new "Ultrasound-Derived Fat Fraction (UDFF)" feature. The general diagnostic ultrasound system itself is noted to use "the same technology and principles as existing predicate devices" and therefore "clinical studies were not required to support substantial equivalence" for its broader functionality. The following information pertains specifically to the UDFF feature.

Acceptance Criteria and Device Performance (UDFF Feature)

Further Study Details for UDFF Feature:

1. Sample Sizes Used for the Test Set and Data Provenance:

   • Study 1: N = 30 subjects
     • Ethnicity/Country: 15 from USA, 15 from Korea
     • Sex: 15 Male, 15 Female
     • Retrospective or Prospective: Not explicitly stated, but the description of "To verify the clinical reliability...To record the UDFF measurement acquisition time" suggests it was a prospective data collection for this study.
   • Study 2: N = 28 subjects
     • Ethnicity/Country: 28 from Korea
     • Sex: 20 Male, 8 Female
     • Retrospective or Prospective: Not explicitly stated, but given the objective "To verify that UDFF of ACUSON Redwood shows good agreement with MRI-PDFF" and "To verify the clinical accuracy...", it implies prospective data collection where both UDFF and MRI-PDFF were acquired for correlation.

2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

   • Study 1: This study primarily focused on comparing the ACUSON Redwood UDFF to the ACUSON Sequoia UDFF and internal consistency (test-retest reliability). Ground truth, in the sense of a definitive diagnostic outcome, was not the primary endpoint that would require expert adjudication. The "ground truth" here is the measurement from the established predicate device (ACUSON Sequoia UDFF) and the consistency of the Redwood's own measurements.
   • Study 2: The ground truth for this study was MRI-PDFF (Magnetic Resonance Imaging Proton Density Fat Fraction). This MRI-PDFF is considered a quantitative reference standard for liver fat quantification. The document does not specify the number of human readers/experts directly involved in establishing the MRI-PDFF values for the study, as MRI-PDFF is typically an objective, quantitative measurement derived from MRI sequences and software, rather than a subjective expert read needing adjudication.

3. Adjudication Method for the Test Set:

   • Not applicable as the ground truths (predicate device measurements and MRI-PDFF) are presented as objective measurements and not subjective expert interpretations requiring adjudication.

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 involving human readers and AI assistance was not mentioned or performed for the UDFF feature as described. The UDFF is a standalone software tool for measurement.

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

   • Yes, the studies evaluate the performance of the UDFF software tool itself in its ability to quantify fat fraction, either compared to a predicate device's software tool (Study 1) or to MRI-PDFF as a reference standard (Study 2). The results (Pearson Correlation, ICC, bland-Altman, AUROC) are metrics of the algorithm's performance.

6. The type of ground truth used:

   • Study 1: The ground truth was the Ultrasound-Derived Fat Fraction (UDFF) measurement obtained from the predicate device (ACUSON Sequoia), and the internal consistency of the ACUSON Redwood UDFF measurements (test-retest).
   • Study 2: The ground truth was MRI-PDFF (Magnetic Resonance Imaging Proton Density Fat Fraction), which is a quantitative imaging biomarker considered a non-invasive gold standard for liver fat content.

7. The sample size for the training set:

   • The document does not provide information regarding the sample size of any training set used for the UDFF algorithm. This section focuses on validation studies.

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

   • The document does not provide information regarding how the ground truth for any potential training set was established.

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