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The intended use of EPIQ Ultrasound Diagnostic Series 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(3D/4D), 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.

The intended use of Affiniti Series Diagnostic Ultrasound 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), 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 (3D/4D), 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 Traditional 510(k) Pre-Market Notification is to introduce the addition of the Artificial Intelligence (AI) Auto Measure Abdomen feature software application onto the EPIQ Series Diagnostic Ultrasound Systems and Affiniti Series Diagnostic Ultrasound Systems.

The Auto Measure Abdomen feature on Philips EPIQ and Affiniti Series Diagnostic Ultrasound System aims to improve workflow efficiency by automating selected measurements required for routine abdominal and renal exams. The Auto Measure feature is designed to provide semi-automated and editable measures of abdominal organs such as kidney and spleen. The software provides a semi‑automated measurement capability. Users may adjust the position of the caliper end points for measurement refinement or perform additional manual measurements. The Auto Measure Abdomen feature is available in C5-1 and C9-2 transducers only.

The software applications are supported by all EPIQ and Affiniti models running software version 14.0 or higher.

Here's a breakdown of the acceptance criteria and the study details for the Auto Measure Abdomen feature, based on the provided FDA 510(k) clearance letter (K253595):

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Number of subjects: 150 subjects (i.e., 150 ultrasound exams).
• Number of images (samples):
  • 292 images for kidney longitudinal view (for kidney length measurement).
  • 271 images for kidney transverse view (for kidney width and height measurement).
  • 145 images for spleen sagittal view (for spleen length measurement).
• Data Provenance: Images were collected from adults (≥18 years) enrolled at three clinical sites. The data included both patients referred for abdominal or renal ultrasound and healthy volunteers. The letter does not explicitly state the country of origin, but "three clinical sites" implies a multi-site collection, likely within the US, given the FDA context. The data appears to be previously collected ("ultrasound images previously collected"). It's a retrospective study for the AI evaluation, using prospectively collected patient data.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Number of experts: 3 clinical experts.
• Qualifications of experts: All three experts are registered clinical sonographers with ten or more years of experience in general imaging and abdominal imaging, and each holds active certification by the American Registry for Diagnostic Medical Sonography (ARDMS).

4. Adjudication Method for the Test Set

• Method: The three clinical experts independently carried out manual measurements. The average values obtained from their measurements served as the ground truth. This is a form of expert consensus (averaging), without a specific 2+1 or 3+1 rule mentioned beyond averaging the three independent measurements. The experts also reviewed the AI algorithm-generated measurements to either accept or edit them, implying an expert-in-the-loop validation process for the AI output against their manual measurements.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, a formal MRMC comparative effectiveness study comparing human readers with and without AI assistance to measure a specific improvement effect size was not explicitly described in this document. The study focused on comparing the AI's measurements directly against expert ground truth. While experts were involved in generating ground truth and reviewing AI output, the study's primary endpoint was the concordance between AI measurements and expert measurements, not the increase in human reader performance with AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, the primary evaluation was a standalone performance test of the AI algorithm. The study evaluated the "AI algorithm performance" by comparing its "algorithm-generated measurements" to the expert-derived ground truth. Although experts could edit the AI measurements, the core evaluation reported in the tables (AI Auto Measure (cm) Mean ± SD (Min, Max)) represents the algorithm's raw output before any human modification.

7. The Type of Ground Truth Used

• Type: Expert consensus (average values of measurements from three experienced clinical sonographers).

8. The Sample Size for the Training Set

• The document states, "The datasets used in the validation study and for regulatory clearance were distinct from those employed during algorithm training." However, the exact sample size for the training set is not provided in this document.

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

• The document states, "The datasets used in the validation study and for regulatory clearance were distinct from those employed during algorithm training." However, the method for establishing ground truth for the training set is not provided in this document. It only confirms independence from the validation set's ground truth.

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The Philips Lumify Diagnostic Ultrasound System is intended for diagnostic ultrasound imaging in B (2D), Color Doppler, Combined (B+Color), Pulsed Wave Doppler (PWD), and M-modes.

It is indicated for diagnostic ultrasound imaging and fluid flow analysis in the following applications: Fetal/Obstetric, Abdominal, Pediatric, Cephalic, Urology, Gynecological, Cardiac Fetal Echo, Small Organ, Musculoskeletal, Peripheral Vessel, Carotid, Cardiac, Lung.

The Lumify system is a transportable ultrasound system intended for use in environments where healthcare is provided by healthcare professionals.

The Lung Application 3 is intended to assist healthcare professionals by providing automated image processing to analyze ultrasound images for lung-related conditions. Specifically, it evaluates the adequacy of ultrasound frames for clinical interpretation and assesses the appearance of pleural lines as normal or irregular.

The Lung Application 3 is a software-only functionality integrated into the Philips Lumify Diagnostic Ultrasound System, designed to support lung ultrasound examinations. It introduces two key features: pleural line assessment and lung image view quality assessment. The Pleural Line feature identifies and assesses the appearance of pleural lines as normal or irregular (defined as thickened, interrupted, fragmented, jagged, uneven, or otherwise non-smooth appearance on ultrasound). The lung view quality tool assesses the adequacy of ultrasound frames based on overall image appearance and the presence of any pleural lines. The application operates on a compatible Android-based commercial off-the-shelf device (e.g., tablet or smartphone) connected to Lumify transducers (C5-2, S4-1, and L12-4 models). It utilizes machine learning algorithms trained on a large dataset of expert-annotated lung ultrasound images to ensure accurate analysis. The workflow includes zone selection, image acquisition, navigation, review, and editing of results, with real-time feedback provided via visual indicators for image quality and pleural line analysis. The Lung Application 3 is intended for use by trained professionals in clinical settings to assist in evaluations of adult patients (18 years and older) with various pulmonary conditions. It does not introduce any new contraindications and is designed to comply with existing safety and operational standards.

Key Features:

• Software-based functionality for lung ultrasound enhancement.
• Pleural line classification as normal or irregular appearance.
• Lung view quality assessment for diagnostic adequacy.
• Real-time feedback via visual indicators.
• Machine learning-based algorithms for accurate image analysis.
• Compatibility with existing Lumify transducers and Android devices.

The Philips Lumify Diagnostic Ultrasound System (Lumify) is a mobile, durable, and reusable, software-controlled medical device, which is intended to acquire high-resolution ultrasound data and to display the data in B mode (2D), Pulsed Wave Doppler, Color Doppler, Combined (B+ Color), and M modes. The Lumify system is compatible with iOS and Android operating systems.

The Lumify Diagnostic Ultrasound System (iOS) utilizes:

1. A commercial off-the-shelf (COTS) iOS mobile item (smart phone or tablet)
2. The Philips Ultrasound Lumify software running as a medical device application on the COTS device
3. The Philips C5-2 Curved array USB transducer
4. The Philips L12-4 Linear array USB transducer
5. The Philips S4-1 Sector array USB transducer
6. Lumify Micro B Transducer Cable
7. Lumify Micro C Transducer Cable
8. Lumify USB-C to USB-C Transducer Cable
9. Lumify Power Module

Here's a breakdown of the acceptance criteria and the study proving the device's adherence, based on the provided FDA 510(k) clearance letter for the Philips Lumify Diagnostic Ultrasound System with Lung Application 3:

Acceptance Criteria and Reported Device Performance

Study Details

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

• Test Set Sample Size: The document does not explicitly state the exact numerical sample size for the test set. It mentions that the machine learning algorithms were trained on a "large dataset of expert-annotated lung ultrasound images" and that the retrospective data analysis evaluated the performance on a set of images to assess agreement with ground truth. More specific numbers for the test set are not provided.
• Data Provenance: The data was described as "retrospective data analysis study evaluated the performance of two artificial intelligence algorithms integrated into the Philips Lumify Diagnostic Ultrasound System for automated classification of lung view quality and pleural line appearance during clinical LUS examinations." The country of origin for the data is not specified.

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

• Number of Experts: The document does not explicitly state the number of experts used to establish ground truth. It refers to "expert-annotated lung ultrasound images" and "qualified clinical experts" when establishing acceptance criteria based on inter-rater agreement.
• Qualifications of Experts: The experts are referred to as "qualified clinical experts." Specific qualifications (e.g., "radiologist with 10 years of experience") are not provided.

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

• The document does not specify the adjudication method used for establishing ground truth for the test set. It mentions "expert-annotated," implying multiple experts, but the process for resolving disagreements (if any) is not detailed.

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:

• A MRMC comparative effectiveness study involving human readers with vs. without AI assistance was not explicitly described in this document as part of the performance evaluation for this 510(k) clearance. The study focused on the standalone performance of the AI algorithms against expert-established ground truth.

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

• Yes, a standalone study was done. The performance evaluation described in Section 8, "Non-Clinical Performance Data," is a standalone assessment of the AI algorithms. It evaluated "algorithm agreement with ground truth labels." The results presented for PABAK, concordance, and Kappa are all measures of the algorithm's performance independent of real-time human interaction.

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

• The ground truth was established by expert annotation/consensus. The document states, "machine learning algorithms trained on a large dataset of expert-annotated lung ultrasound images" and "evaluated algorithm agreement with ground truth labels." The acceptance criteria were also "established based on published inter-rater agreement ranges for lung view quality and pleural line irregularity among qualified clinical experts."

7. The sample size for the training set:

• The document states, "It utilizes machine learning algorithms trained on a large dataset of expert-annotated lung ultrasound images." A specific numerical sample size for the training set is not provided.

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

• The ground truth for the training set was established through expert annotation. The document explicitly mentions "machine learning algorithms trained on a large dataset of expert-annotated lung ultrasound images."

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