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The intended use of EPIQ Ultrasound Diagnostic System is diagnostic ultrasound imaging and fluid flow analysis of the human body, with the following indications for use:

Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal), Fetal/Obstetric, Gynecological, Intraoperative (Vascular), Intraoperative (Cardiac), intra-luminal, intra-cardiac echo, Musculoskeletal (Conventional), Musculoskeletal (Superficial), Ophthalmic, Other: Urology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transvaginal, Lung.

The clinical environments where EPIQ Series Diagnostic Ultrasound Systems can be used include clinics, hospitals, and clinical point-of-care for diagnosis of patients.

When integrated with Philips EchoNavigator, the systems can assist the interventionalist and surgeon with image quidance during treatment of cardiovascular disease in which the procedure uses both live X-ray and live echo guidance.

The systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating instructions given in the product user information. Systems are to be operated only by appropriately trained healthcare professionals for the purposes for which they were designed. However, nothing stated in the user information reduces your responsibility for sound clinical judgement and best clinical procedure.

Affiniti:
The intended use of Affiniti Series Diagnostic Ultrasound Systems is diagnostic ultrasound imaging and fluid flow analysis of the human body, with the following indications for use:

Abdominal, Cardiac Adult, Cardiac Other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal), Fetal/Obstetric, Gynecological, Intraoperative (Vascular), Intraoperative (Cardiac), Musculoskeletal (Conventional), Musculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transrectal, Transvaginal, Lung.

The clinical environments where the Affiniti diagnostic ultrasound systems can be used include clinics, hospitals, and clinical point-of-care for diagnosis of patients.

The systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating instructions given in the product user information. Systems are to be operated only by appropriately trained healthcare professionals for the purposes for which they were designed. However, nothing stated in the user information reduces your responsibility for sound clinical judgement and best clinical procedure.

The purpose of this Special 510(k) Pre-Market Notification is to introduce the Smart View Select (SVS) software application onto the EPIQ Series Diagnostic Ultrasound Systems and to introduce the Segmental Wall Motion software application onto both the EPIQ and Affiniti Series Diagnostic Ultrasound Systems.

Smart View Select is an automated software feature that assists the user in selection of images for analysis with the existing Philips AutoStrain LV or 2D Auto LV application in Adult Echo Transthoracic (TTE) examination. This feature automatically classifies each acquired image by view and selects an appropriate set of images for left ventricle (LV) analysis. The classification is based on a Deep Learning Al interface engine; the selection is a non-Al algorithm that considers the view classification and image depth to select the optimal set of images.

The Segmental Wall Motion software automatically evaluates the segmental (regional) function of the left ventricle (LV) from adult TTE echo examinations. For input, the SWM algorithm uses 3 apical views (A4C, A2C and A3C) and performs border detection and tracking to identify each of the LV segments based on the three views. The application then provides segmental wall motion scores for each of the 17 segments of the LV by using machine learning algorithms and an overall wall motion score index (WMSI) is calculated as the average of the segmental scores.

No hardware changes to the EPIQ or Affiniti systems are required when using SVS or SWM, and existing, cleared Philips TTE transducers are used with these software applications.

The SVS feature is supported by all EPIQ models running software version 11.0 or higher including EPIQ CVx/CVxi, EPIQ Elite Advanced, EPIQ Elite, EPIQ 7, EPIQ 5. The SWM feature is supported by the same EPIQ models running software version VM11.0 or higher, as well as all Affiniti models including Affiniti CVx, Affiniti 70, Affiniti 50, and Affiniti 30. The SVS and SWM software are associated with the cardiac adult indication.

The provided FDA 510(k) clearance letter and summary describe the acceptance criteria and a study conducted to prove that the Philips EPIQ Series and Affiniti Series Diagnostic Ultrasound Systems, with the new Smart View Select (SVS) and Segmental Wall Motion (SWM) software applications, meet these criteria for substantial equivalence.

Here's a breakdown of the requested information:

1. A table of acceptance criteria and the reported device performance

Device Under Evaluation: Philips EPIQ Series and Affiniti Series Diagnostic Ultrasound Systems with Smart View Select (SVS) and Segmental Wall Motion (SWM) software applications.

2. Sample size used for the test set and the data provenance

The document does not explicitly state the exact numerical sample size (number of subjects/exams) for the test sets in either study. It mentions the studies were retrospective.

• Data Provenance: Retrospective (from existing subject exams). The country of origin of the data is not specified in the provided text.

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

• Number of Experts: Three (3) reviewers participated in establishing ground truth for both studies.
• Qualifications of Experts: Described as "clinical experts." No further specific qualifications (e.g., years of experience, subspecialty) are provided in the document.

4. Adjudication method for the test set

• Adjudication Method: For both the SVS and SWM studies, the ground truth was established as the "average across reviewers" for each output (GLS and EF for SVS; WMSI for SWM). This implies a consensus or averaging approach rather than a specific hierarchical adjudication process (like 2+1 or 3+1).

5. 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

• MRMC Study: The studies described are not MRMC comparative effectiveness studies designed to evaluate the improvement of human readers with AI assistance. Instead, they are analytical validity studies evaluating the agreement of the AI-powered workflows (SVS and SWM) with an established ground truth or reference (manual clip selection and LVivo SWM, respectively).
• Effect Size of Human Improvement: Therefore, no effect size related to how much human readers improve with AI vs. without AI assistance is reported. The focus is on the performance of the AI-assisted workflow compared to a manual or reference workflow.

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

• Standalone Performance: For the SVS study, the "automatically obtained GLS and EF results with SVS selected clips" were compared against the ground truth. This suggests a form of standalone evaluation of the SVS algorithm's selection capability and its impact on the subsequent automated analysis. The SWM algorithm, while described as "semi-automated" where users are expected to review and concur, was also tested in an "un-edited" fashion for comparison in the SVS workflow path, which leans towards evaluating its automated output. However, the overall claims and clinical use imply human review (semi-automated).

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

• Smart View Select (SVS) Study Ground Truth: "Manual selection of clips from subject exam and subsequent semi-automated processing of the clips with AutoStrain LV software to evaluate GLS and EF, which served as ground truth (average across reviewers for each output)." This is based on expert consensus (average across reviewers) following a manual workflow using a previously cleared software (AutoStrain LV).
• Segmental Wall Motion (SWM) Study Ground Truth: "Processing of the clips with LVivo application for WMSI output, which served as ground truth in the study (average across reviewers)." This is also based on expert consensus using a previously cleared or referenced software (LVivo SWM, which is the reference device K161382).

8. The sample size for the training set

• The document does not provide any information about the sample size used for training the Deep Learning AI interface engine for SVS or the machine learning algorithms for SWM. It only mentions the retrospective data analysis studies for performance evaluation (test set).

9. How the ground truth for the training set was established

• As the document does not provide information on the training set, details about how its ground truth was established are also not available in the provided text.

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L Vivo 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.

The LVivo System analyzes echocardiographic patient examination DICOM movies for Global ejection fraction (EF) evaluation. EF is evaluated using two orthogonal planes, four-chamber (4CH) and two-chamber (2CH) views, to provide fully automated analyses of LV function from the echo examination movies. It also has the ability to measure strain and to evaluate the Right Ventricle and well as to measure the bladder.

This document describes the acceptance criteria and study results for DiA Imaging Analysis Ltd's LVivo Software Application, specifically focusing on its LVivoRV (Right Ventricular) and LVivo Bladder modules.

1. Table of Acceptance Criteria and Reported Device Performance

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