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QLAB Advanced Quantification Software is a software application package. It is designed to view and quantify image data acquired on Philips ultrasound systems.

Philips QLAB Advanced Quantification software (QLAB) is designed to view and quantify image data acquired on Philips ultrasound systems. QLAB is available either as a stand-alone product that can function on a standard PC, a dedicated workstation, and on-board Philips' ultrasound systems. It can be used for the off-line review and quantification of ultrasound studies.

QLAB software provides basic and advanced quantification capabilities across a family of PC and cart based platforms. QLAB software functions through Q-App modules, each of which provides specific capabilities.

QLAB builds upon a simple and thoroughly modular design to provide smaller and more easily leveraged products.

Philips Ultrasound is submitting this 510(k) to address QLAB 11.0 modifications which include:

• Dynamic Heart Model (DHM) an enhancement to the Heart Model Quantification ● application that provides tracking of the entire cardiac cycle
• QLAB functionality upgraded to the HSDP Platform 2 from the HSDP Platform 1 ●
• O-Store Shared central database supporting multiple clients. .

The document provided is a 510(k) premarket notification for the Philips QLAB Advanced Quantification Software. It states that the submission is for modifications to an existing device (QLAB 10.8 K171314) and does not introduce new indications, modes, features, or technologies that require clinical testing. Therefore, there is no detailed study described that definitively calculates specific acceptance criteria and device performance metrics in the traditional sense of a clinical trial for a novel device.

However, based on the information provided, we can infer the approach to acceptance criteria and "performance" from the perspective of software verification and validation for modifications to an already cleared device.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a submission for modifications to an existing cleared device, the "acceptance criteria" revolve around ensuring the modified software functions as intended and does not negatively impact the safety and effectiveness of the previously cleared predicate device. Performance is demonstrated through software verification and validation against internal requirements.

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

The document does not specify a "test set" in the context of patient data or clinical images for evaluating the diagnostic performance of the algorithms. Instead, the testing described is focused on software verification and validation. This typically involves:

• Test Cases: Software testing would involve a suite of test cases designed to cover all functionalities, new and existing, and boundary conditions. The number of these test cases is not specified.
• Data Provenance: The document does not mention the use of patient data for performance evaluation in terms of diagnostic accuracy. The testing is focused on the software's functional and technical aspects. Since this is an upgrade to an existing quantification software, it is likely that existing image data (possibly de-identified, potentially from various sources including internal datasets or public datasets for software testing purposes) would have been used to validate the functions of the application, but this is not explicitly stated. The document strongly emphasizes that no new indications or technologies requiring clinical testing are introduced.

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

Given that no clinical testing requiring a "ground truth" established by external experts is detailed, this information is not provided. The "ground truth" for software verification and validation is defined by the product's functional and technical requirements.

4. Adjudication Method for the Test Set

Not applicable, as no external expert adjudication for a "test set" (in the clinical sense) is described.

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

No. The document explicitly states: "QLAB 11.0 introduces no new indications for use, modes, features, or technologies relative to the predicate device (QLAB 10.8 K171314) that require clinical testing." Therefore, an MRMC study comparing human readers with and without AI assistance was not performed.

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

The QLAB Advanced Quantification Software is described as a "software application package" designed to "view and quantify image data." It functions as an "off-line review and quantification" tool. While its primary function is quantification, the context implies it's a tool used by a human to assist in diagnosis or assessment. The mention of "tracking of the entire cardiac cycle" and "expanding the measurements" for the Dynamic Heart Model suggests algorithmic quantification, but it is not presented as a standalone diagnostic AI system that operates without human review or interaction. The performance data focuses on the software fulfilling its functional requirements within the existing framework of the predicate device.

7. The Type of Ground Truth Used

The "ground truth" for the software verification and validation activities is based on the defined software requirements and specifications. This is a functional "ground truth" rather than a clinical ground truth (like pathology, expert consensus on patient outcomes). The goal was to demonstrate that the software modifications (Dynamic Heart Model, HSDP Platform 2, Q-Store) work as designed.

8. The Sample Size for the Training Set

No training set is mentioned. This submission is for modifications to quantification software, not a de novo AI model that requires training on a dataset. The "Dynamic Heart Model" is described as an "enhancement" to an existing application providing "tracking" and "expanding measurements," suggesting algorithmic improvements rather than a new discriminative AI model requiring a separate training set.

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

Not applicable, as no training set for a de novo AI model is mentioned.

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QLAB Advanced Quantification Software is a software application package. It is designed to view and quantify image data acquired on Philips Healthcare Ultrasound systems.

Philips QLAB Advanced Quantification software (OLAB) is designed to view and quantify image data acquired on Philips ultrasound products. QLAB is available either as a stand-alone product that can function on a standard PC, a dedicated workstation, and on-board Philips' ultrasound systems. It can be used for the off-line review and quantification of ultrasound studies.

QLAB software provides basic and advanced quantification capabilities across a family of PC and cart based platforms. QLAB software functions through Q-App modules, each of which provides specific capabilities.

The provided FDA 510(k) summary for Philips' QLAB Advanced Quantification Software (K171314) focuses on modifications to existing Q-Apps (a2DQ and aCMQ/CMQ Stress) and primarily addresses software verification and validation, rather than a clinical study establishing new acceptance criteria or device performance through a comparative effectiveness study.

Therefore, much of the requested information (such as specific performance metrics, sample sizes for test sets, expert qualifications, adjudication methods, and MRMC study details) is not explicitly detailed in this document in the typical format of a clinical performance study. The document emphasizes equivalence to a predicate device and internal testing.

However, based on the provided text, here's an attempt to answer the questions, highlighting where information is not available:

Acceptance Criteria and Device Performance Study Details

1. Table of Acceptance Criteria and Reported Device Performance

The document does not specify quantitative acceptance criteria or a "reported device performance" in terms of clinical metrics (e.g., sensitivity, specificity, accuracy) from a comparative study. Instead, the acceptance is based on the device meeting its defined requirements and performance claims during internal software verification and validation.

Acceptance Criteria (Implied from the document): The modified QLAB a2DQ and aCMQ/CMQ Stress Q-Apps are safe and effective and introduce no new risks, meeting defined requirements and performance claims validated through internal processes.

Reported Device Performance:

• The modifications to the a2DQ and aCMQ/CMQ Stress Q-Apps were tested in accordance with Philips internal processes.
• Verification and software validation data support the proposed modified QLAB a2DQ/aCMQ/CMQ Stress software relative to the currently marketed unmodified QLAB software.
• Testing demonstrated that the proposed QLAB Advanced Quantification Software, with modified Q-Apps, meets defined requirements and performance claims.

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

• Sample Size: Not specified. The document refers to "software verification and validation data," but does not provide details on the number of cases or images used in this testing.
• Data Provenance: Not specified. It only mentions "Philips internal processes" for testing. Specifics like country of origin or retrospective/prospective nature of data are not mentioned.

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

• This information is not provided. The document focuses on software validation and does not detail an expert-based ground truth establishment process for a clinical test set.

4. Adjudication method for the test set

• This information is not provided, as the nature of the "test set" described is for software verification/validation rather than a clinical adjudication process.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study is not mentioned in this document. The submission focuses on device equivalence and software modifications, not an assessment of human reader improvement with AI assistance.

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

• The document implies that "Software Verification and Validation testing" was performed for the algorithms. While it doesn't explicitly state "standalone performance study," the entire context of "software only device" and "modification to software application package" suggests that the functional testing would inherently be of the algorithm's performance. However, there are no specific performance metrics (e.g., accuracy, precision) reported for this standalone performance.

7. The type of ground truth used

• The document does not explicitly state the type of "ground truth" in a clinical sense (e.g., pathology, outcomes data, expert consensus). Given it's a software modification submission, the "ground truth" for validation would likely be based on established reference values or measurements within the existing QLAB system, against which the modified algorithms were compared for consistent and accurate computation in "Requirements Review," "Design Review," "Risk Management," and "Software Verification and Validation" activities.

8. The sample size for the training set

• Not applicable/Not specified. The document describes modifications to existing software ("QLAB builds upon a simple and thoroughly modular design"). It does not describe the development of a de novo AI algorithm that would typically involve a separate "training set." The focus is on the verification of modified functionalities within an existing proven system.

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

• Not applicable/Not specified, as no training set for a new AI algorithm is discussed.

Summary of Document Focus:

This FDA 510(k) summary is for a software modification to an existing device (QLAB Advanced Quantification Software). The primary goal is to demonstrate "substantial equivalence" to a predicate device and to show that the modifications do not introduce new safety or effectiveness risks. The "study" referenced is internal software verification and validation, not a clinical trial or comparative effectiveness study. Therefore, the details requested for clinical performance metrics, reader studies, and explicit ground truth establishment for clinical data sets are largely absent from this particular type of submission.

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Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal), Fetabl/Obstetric, Gynecological, Intraoperative (Vascular), Intraoperative (Cardiac), Musculoskeletal (Conventional), Musculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transvaginal.

The clinical environments where the EPIQ 5, EPIQ 7, Affiniti 50 Diagnostic Ultrasound Systems can be used include Clinics, Hospitals, and clinical point-of-care for diagnosis of patients.

The proposed EPIO and Affiniti Diagnostic Ultrasound Systems, which includes EPIO 5. EPIQ 7, Affiniti 50 and Affiniti 70 systems, are general purpose, software controlled, diagnostic ultrasound systems. Their function is to acquire ultrasound data and to display the data in various modes of operation.

The devices consist of two parts: the system console and the transducers. The system console contains the user interface, a display, system electronics and optional peripherals (ECG, printers). In addition to the physical knobs and buttons of the main control panel, the user interface consists of a touch screen with soft key controls. EPIO also has a QWERTY keyboard.

The removable transducers are connected to the system using a standard technology, multipin connectors. The proposed EPIQ and Affiniti systems use standard transducer technology, and supports phased, linear, curved linear array, TEE, motorized 3D curved linear arrays as well as non-imaging (pencil) probes.

Clinical data storage consists of a local repository as well as off-line image storage via the network, DVR, DVD, and USB storage devices. The images are stored in industry-standard formats (e.g. JPEG. AVI, DICOM) and are intended to be readable using industry-standard hardware and software. On-line review of the images is available. Secure access tools are provided to restrict and log access to the clinical data repository according to HIPAA.

The system circuitry generates an electronic voltage pulse, which is transmitted to the transducer. In the transducer, a piezo electric array converts the electronic pulse into an ultrasonic pressure wave. When coupled to the body, the pressure wave transmits through body tissues. The Doppler functions of the system process the Doppler shift frequencies from the echoes of moving targets such as blood to detect and graphically display the Doppler shifts of these tissues as flow.

The proposed EPIQ and Affiniti systems give the operator the ability to measure anatomical structures and offer analysis packages that provide information used by competent healthcare professionals to make a diagnosis. The proposed EPIQ and Affiniti systems enable image guided navigation and image fusion via the optional PercuNav feature (K121498).

The document describes the Philips EPIQ 5 and EPIQ 7 Diagnostic Ultrasound Systems, and Affiniti 50 and Affiniti 70 Diagnostic Ultrasound Systems. It primarily details their indications for use and compares their technological characteristics to a previously cleared predicate device (Philips EPIQ Diagnostic Ultrasound System K132304).

Based on the provided text, a "study that proves the device meets the acceptance criteria" in terms of clinical performance or specific statistical metrics is not explicitly described. The document explicitly states: "Clinical data was not required to demonstrate safety and effectiveness of the proposed EPIQ and Affiniti Diagnostic Ultrasound Systems since the proposed EPIQ or Affiniti system introduces no new indications for use, modes or features that have not been previously cleared with the predicate device EPIQ system (K132304). The clinical safety and effectiveness of ultrasound systems with these characteristics are well accepted for both predicate and subject devices."

Therefore, the acceptance criteria are demonstrated through substantial equivalence to a predicate device, and compliance with recognized safety and performance standards, rather than a de novo clinical study for this specific submission.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria (from Standards) and Reported Device Performance (Compliance Statement)

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