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510(k) Data Aggregation
(73 days)
EPIQ Series Diagnostic Ultrasound System: 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), Transrectal, Transvaginal, Lung.
Modes of operation include: B Mode, M Mode, PW Doppler, CW Doppler, Color Doppler, Color M Mode, Power Doppler, and Harmonic Imaging.
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 guidance 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 Series Diagnostic Ultrasound Systems: 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.
Modes of operation include: B Mode, M Mode, PW Doppler, CW Doppler, Color Doppler, Color M Mode, Power Doppler, and Harmonic Imaging.
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 510(k) Pre-market Notification is to introduce the SVS v2 Contrast software application with the EPIQ and Affiniti Series Diagnostic Ultrasound Systems as part of the VM13.0 program.
SVS v2 Contrast is an automated software feature that assists in the selection of images for analysis with the new Philips license options 2D Auto EF Advanced (Adv) developed by DiA Imaging Analysis (K243235), now part of Philips Ultrasound LLC, and existing Philips license options AutoStrain LV; or 2D Auto LV (both K240850) license application in Adult Echo Transthoracic (TTE) examinations.
As described in 510(k) K240850, 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 AI inference engine; the selection is a non-AI algorithm that considers the view classification and image depth to select the optimal set of images. The difference in SVS v2 Contrast from the predicate SVS v1 (K240850) is that the algorithm is revised to include the selection of optimal images for analysis when contrast is used in routine TTE exams.
Users can launch existing 2D Auto EF; 2D Auto EF Adv; AutoStrain LV; or 2D Auto LV with the set of images that have been automatically selected without the need to review the acquired images and manually select the views. Users may select 2D Auto EF Adv, to process the selected views by SVS v2 Contrast. SVS v2 Contrast prioritizes the contrast image pair; however, if an appropriate pair of contrast images is not found, then Auto EF Adv may select non-contrast images. The manual approach to select views is still available and the user can override automatically selected images from SVS v2 Contrast.
No hardware changes to the EPIQ or Affiniti Series Diagnostic Ultrasound Systems are required when using SVS v2 Contrast, and existing, cleared Philips TTE transducers.
The SVS v2 Contrast feature is supported by all EPIQ models running software version 13.0 or higher including EPIQ CVx/CVxi, EPIQ Elite Advanced, EPIQ Elite, EPIQ 7, EPIQ 5. The SVS v2 Contrast feature is supported by the Affiniti models running software version VM13.0 or higher, including Affiniti CVx, Affiniti 70, Affiniti 50, and Affiniti 30. The SVS v2 Contrast feature is associated with the cardiac adult indication.
Acceptance Criteria and Study Details for SVS v2 Contrast Software
This document outlines the acceptance criteria and details of the study conducted to demonstrate that the Philips Ultrasound systems (EPIQ and Affiniti Series Diagnostic Ultrasound System) with the SVS v2 Contrast software application meet the established performance benchmarks.
1. Table of Acceptance Criteria and Reported Device Performance
| Criteria | Acceptance Criteria | Reported Device Performance (SVS Selected vs Manually Selected Ground Truth) |
|---|---|---|
| Primary Endpoint: Pearson's correlation coefficient (r) for Biplane EF (Automated Selection vs. Manual Selection) | Lower Confidence Bound for the Pearson's correlation coefficient (r) to be > 0.8. (Informed by published literature (Maret, E. B. (2008)) and previous regulatory submissions (K130779, K232500)). Note: The manual selection here refers to "manual contrast clip selection," which was automatically processed within the Contrast EF application, with the automated EF results serving as ground truth. | N = 46: r = 0.953 (95% CI: 0.917, 0.974), p-value < 0.0001. The lower bound of the 95% CI (0.917) is > 0.8, meeting the acceptance criteria. |
| Agreement Assessment: Bland-Altman Analysis for Biplane EF (Automated Selection vs. Manual Selection) | Acceptable performance for automatic selection of appropriate clips by SVS software and subsequent output of Contrast Enhanced Biplane EF feature compared to the results of Contrast Enhanced Biplane EF from manually selected contrast clips. (No specific numerical thresholds provided for Bland-Altman, but indicated as demonstrating "acceptable performance" if the primary endpoint is met). | N = 46: Mean Difference ± SD = 0.71 ± 4.36 (95% CI for Mean Difference: -0.58, 2.01). Lower LoA = -7.83 (95% CI: -10.06, -5.60), Upper LoA = 9.26 (95% CI: 7.03, 11.49). Reported as demonstrating acceptable performance. |
| Agreement Assessment: Pearson's correlation coefficient (r) for Biplane EF (Automated Selection vs. Manual Tracing Ground Truth) | No explicit independent acceptance criterion for this comparison; serves as an additional supporting analysis. | N = 46: r = 0.938 (95% CI: 0.890, 0.965), p-value < 0.0001. |
| Agreement Assessment: Bland-Altman Analysis for Biplane EF (Automated Selection vs. Manual Tracing Ground Truth) | No explicit independent acceptance criterion for this comparison; serves as an additional supporting analysis. | N = 46: Mean Difference ± SD = 1.22 ± 5.22 (95% CI for Mean Difference: -0.33, 2.77). Lower LoA = -9.01 (95% CI: -11.67, -6.34), Upper LoA = 11.45 (95% CI: 8.78, 14.11). |
2. Sample Size Used for the Test Set and Data Provenance
- Initial Cohort: 60 subjects
- Evaluable Study Sample (Test Set): 46 subjects (after 10 samples were non-reportable)
- Data Provenance: Retrospective data study, utilizing previously acquired exams (including contrast and non-contrast clips) with TTE transducers.
- Country of Origin: The sample included data from two sites: one outside the USA and one in the USA.
- 7 patient exams collected from the first site (outside USA).
- Remaning 39 patient exams from the second site (USA).
- Country of Origin: The sample included data from two sites: one outside the USA and one in the USA.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
- Ground Truth (Primary): The ground truth for the primary endpoint (Biplane EF - Manually Selected (Ground Truth)) was generated by one sonographer (reviewer) who manually selected contrast clips from subject exams. These clips were then automatically processed within the Contrast EF application, with the automated EF results serving as this ground truth. This ground truth was created as part of the K243235 submission.
- Ground Truth (Supporting): For the comparison against "Manual Tracing (Ground Truth)," three sonographers manually measured the previously selected clips (by the single sonographer) following a physician's review. This clinical ground truth was also created as part of the K243235 submission.
- Qualifications of Experts: The document specifies "sonographer" for those involved in manual clip selection and measurements, and "physicians review" for the support ground truth. Specific details on years of experience or board certification are not provided within this document.
4. Adjudication Method for the Test Set
The document does not explicitly state an adjudication method (e.g., 2+1, 3+1).
- For the primary ground truth, it appears one sonographer made the manual selection, which then fed into an automated process.
- For the supporting ground truth ("Manual Tracing"), three sonographers performed measurements following a physician's review. It is not clear if these three sonographer measurements were averaged, or if disagreements were arbitrated by the physician or another expert.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was explicitly mentioned in the provided text, nor was an effect size of human readers improving with AI vs. without AI assistance. The study focused on the agreement between the device's automated selection and manually established ground truth, rather than human reader performance.
6. Standalone (Algorithm Only) Performance
Yes, a standalone performance of the algorithm (SVS v2 Contrast) was performed. The study evaluates the algorithm's ability to automatically select appropriate clips and its subsequent impact on Biplane EF calculation. The comparison is made between the "Biplane EF - SVS Selected (Automated)" and the "Biplane EF - Manually Selected (Ground Truth)," where the latter represents a ground truth derived with manual input for clip selection but still using an automated EF calculation. Additionally, a comparison was made against "Biplane EF – by Manual Tracing (Ground Truth)," which reflects a more direct human-traced ground truth reference.
7. Type of Ground Truth Used
The ground truth used was primarily a hybrid approach:
- Expert consensus/manual selection combined with automated processing: For the primary ground truth, a single sonographer manually selected clips, which were then processed by the Contrast EF application to yield the ground truth EF.
- Expert manual tracing (with physician review): For the supporting analysis, three sonographers performed manual tracings/measurements following a physician's review.
This suggests a "clinical ground truth" established by human experts, sometimes in conjunction with other software tools. It is not pathology or direct outcomes data.
8. Sample Size for the Training Set
The document does not specify the sample size for the training set. It mentions "To ensure data separation between development and testing data, the data set to which each exam belongs was identified," indicating that there were distinct training and test sets, but the training set size is not provided.
9. How the Ground Truth for the Training Set Was Established
The document does not provide details on how the ground truth for the training set was established. It only refers to the test set's ground truth and mentions that the algorithm is based on a Deep Learning AI inference engine, implying the use of a training set.
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