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The Nano Series Diagnostic Ultrasound System is intended for use by an appropriately trained and qualified healthcare professional for ultrasound evaluation in hospitals, clinics, road ambulances or at home. Nano Series Diagnostic Ultrasound System clinical applications include Abdominal, Gynecology, Obstetric, Small parts, Musculoskeletal, Urology, Peripheral vascular, Pediatric, Pleural/Thoracic and Cardiac.

The Modes of Operation for Nano Series include B mode, M mode, Doppler modes, Harmonic Imaging and their combination modes.

The Nano series ultrasound diagnostic system consists of an app which can be installed on iOS or Android devices, and convex and linear transducers which use wired or wireless technology for communication.

The Nano series diagnostic ultrasound systems transducers are available in four models: Nano C5, Nano C5 EXP, Nano L12 and Nano L12 EXP. Nano C5 and Nano C5 EXP are convex transducers, and Nano L12 and Nano L12 EXP are linear transducers.

The system also supports various software features, including: Dual imaging, Speckle Reduction Imaging (eSRI), Auto Trace, Zoom, ECG Wave, eVocal, eWorks, Remote Diagnosis, etc.

This system is a Track 3 device to acquire and display ultrasound data in various imaging modes.

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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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BioticsAI is intended to analyze fetal ultrasound images and frames (DICOM instances) using machine learning techniques to automatically detect views, detect anatomical structures within the views and to facilitate quality criteria verification and characteristics of the views.

The device is intended for use by Healthcare Professionals as a concurrent reading aid during and after the acquisition and interpretation of fetal ultrasound images.

BioticsAI is a software used by OB/GYN care centers for prenatal ultrasound review and reporting. BioticsAI uses artificial intelligence (A.I.) to automatically annotate ultrasound images with fetal anatomical planes and structures to facilitate ultrasound review and report generation for fetal ultrasound anatomical scans. It serves as concurrent reading aid for ultrasound images both during and after a fetal anatomical ultrasound examination.

BioticsAI is a Software as a Service (SaaS) solution that aims at helping sonographers, OB/GYNs, MFMs and Fetal surgeons (all three designated as healthcare professionals i.e. HCP) to perform their routine fetal ultrasound examinations in real-time.

BioticsAI can be used by Healthcare Professionals HCPs during fetal ultrasound exams for Trimester 2 of the fetus, during which a fetal anatomy exam is typically captured (typically conducted between 18-22 weeks but can be captured on gestational ages ranging from 18 up to 39 weeks). The software is intended to assist HCPs in assuring during and after their examination that the examination is complete and all images were collected according to their protocol

BioticsAI requires the following SaaS accessibility from internet browser.

BioticsAI receives DICOM instances, which consist of still fetal ultrasound images (in the form still image captures or individual frames from a multi-frame instance) from the ultrasound machine, which are submitted by the performing healthcare professional from the clinic's network, either during the screening or post-screening and performs the following:

• Automatically detect fetal anatomical planes (2D ultrasound views).
• Automatically flag high-level anatomical features (e.g., "head", "thorax", "limb detected in image", etc).
• Automatically detect specific anatomical structures within supported planes/views (i.e. "cerebellum, csp, and cisterna magna found in transcerebellar plane image").
• Facilitate quality verification of supported planes by determining whether the expected anatomical structures, as informed by the latest ISUOG and AIUM guidelines, are present in the ultrasound image. The quality assessment focuses on the presence or absence of these anatomical structures.

BioticsAI automatically identifies fetal anatomical views and anatomical structures captured during the screening. It uses green highlights to indicate successfully detected planes and structures. Red highlights are used to flag instances where the model could not detect an expected anatomical view or structure, even though it is a supported feature. Yellow highlights indicate views or structures that require manual verification (when the AI cannot determine whether anatomical features are present or absent because it is not yet supported by our product).

The end user can interact with the software to override BioticsAI's outputs. Specifically, users can unassign or assign an image to a plane or high level anatomical feature, and update the status of quality criteria for structures by changing it from "found" to "not found" or vice versa. Users have the flexibility to review and edit these assignments at any point during or after the exam.

The end user then has the ability to include the information gathered during quality and image review automatically in a final report via a button called "Confirm Screening Results", automatically filling out a report template with identified planes and structures. The report can then be further exported to the clinic's PACS over DIMSE via a populated DICOM SR.

BioticsAI also provides a standard DICOM Viewer for viewing DICOM instances, and obstetrics ultrasound report templates for manually creating ultrasound reports without the AI based functionality as described above.

To further explain the AI-driven outputs provided by the device, we describe the three primary AI components below:

• AI-1: High-Level Anatomy Classification

  Provides a multi-label classification of the general anatomical region depicted in the image (e.g., head/brain, face, thorax/chest, abdomen, limbs). These categories correspond to standard high-level anatomy groupings used in fetal ultrasound interpretation.

• AI-2: Per-Class Top-1 Fetal Plane Classification

  Provides fetal anatomical plane classifications using a per-class Top-1 approach. A fetal "plane" refers to a standardized cross-sectional view defined by ISUOG and aligned with AIUM guidance for mid-trimester fetal anatomy scans. For each anatomical plane category, the model outputs the image with the single highest-confidence prediction (Top-1) associated with that class.

• AI-3: Fetal Anatomical Structure Classification

  Provides multi-label identification of fetal anatomical structures (e.g., cerebellum, cisterna magna, cerebral peduncles), generated from the model's segmentation head and refined through post-processing filters that enforce plane-structure consistency and remove non-intended labels.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) clearance letter for BioticsAI:

Please note that the document primarily provides the results of standalone performance testing and verification/validation activities. It does not detail specific acceptance criteria values that were established prior to testing for each metric (e.g., "The device must achieve a sensitivity of at least X"). Instead, the tables present the achieved performance of the device from its standalone testing. Based on the clearance letter, it is implied that these reported performance metrics were deemed acceptable by the FDA for substantial equivalence.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 11,186 fetal ultrasound images across 296 patients.
• Data Provenance:
  • Country of Origin: United States.
  • Retrospective or Prospective: Not explicitly stated as retrospective or prospective, but described as "independent of the data used during model development" and collected "from a single site (across multiple ultrasound screening units and machine instances) in the United States." This typically implies a retrospective collection for model validation.
  • Diversity: Data represented varying ethnicities, patient BMIs, patient ages (18-44 years), gestational ages (18-39 weeks), twin pregnancies, and presence of abnormalities, designed to be "representative of the intended use population."

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

The document does not explicitly state the number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience") used to establish the ground truth for the test set. It only states that the ground truth was "independent of the data used during model development."

4. Adjudication method for the test set

The document does not specify the adjudication method (e.g., 2+1, 3+1, none) used for establishing the ground truth of the test set.

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

A MRMC comparative effectiveness study was not explicitly mentioned or detailed in the provided document. The performance data presented is for standalone device performance.

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

Yes, a standalone performance testing (algorithm only without human-in-the-loop performance) was done. The document states: "BioticsAI conducted a standalone performance testing on a dataset of 11,186 fetal ultrasound images..." The tables present the Sensitivity and Specificity of the AI model.

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

The document does not explicitly state the precise type of ground truth used (e.g., expert consensus, pathology, outcomes data). However, for image analysis tasks like detecting planes and structures in ultrasound images, ground truth is typically established by expert annotation or consensus by qualified medical professionals (e.g., sonographers, OB/GYN, MFMs, Fetal surgeons, or radiologists) interpreting the images. The context describes the device as verifying guidelines and determining presence/absence of structures, implying a gold standard based on established medical interpretation.

8. The sample size for the training set

The document does not provide the exact sample size for the training set. It only mentions that the test set was "independent of the data used during model development (training/fine tuning/internal validation) and establishment of device operating points."

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 mentions the data was used for "model development (training/fine tuning/internal validation)." Typically, similar to the test set, this would involve expert annotation and labeling.

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The LIA Console is indicated for use as an imaging tool in the evaluation of human tissue microstructure in the tracheobronchial tree by providing two-dimensional, cross-sectional, real-time depth visualization using Optical Coherence Tomography (OCT).

The safety and effectiveness of this device for diagnostic analysis (i.e., differentiating normal versus specific abnormalities) in any tissue microstructure or specific disease has not been evaluated.

The LIA Console is indicated for use as an imaging tool in the evaluation of human tissue microstructure in the tracheobronchial tree by providing two-dimensional, cross-sectional, real-time depth visualization using Optical Coherence Tomography (OCT).

The LIA Console is intended to be used only in conjunction with the LIA-1 Catheter in order to function as intended.

LIA Console consists of the following main parts:

1. Monitor: 24-inch multi-touch display monitor allowing software user interface.

2. Catheter Driving Unit (CDU): Electromechanical and optical interface between the LIA Console and the LIA-1 Catheter. A rotary motor inside drives the LIA-1 Catheter to form 360-degree side view real-time imaging.

3. Catheter Driving Arm (CDA): A supporting arm allowing CDU positioning, mobility and flexibility during the procedure.

4. Image Engine: The main body of the LIA Console contains laser source, computing unit, data acquisition and power distribution module and other components.

5. Caster: Four caster wheels installed at the base provide mobility for the LIA Console. Each caster is equipped with a brake that can lock the LIA Console in place as needed.

6. OCTICA Software: A proprietary GUI-based software that controls data acquisition, rotary motor and other hardware components to enable real-time OCT imaging of tissue microstructure.

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The HyperVue™ Imaging System - Integrated with compatible HyperVue™ Software and Starlight™ Imaging Catheter is intended for the imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures.

The Starlight Imaging Catheter is intended for use in vessels 2.0 to 5.2 mm in diameter.

The Starlight Imaging Catheter is not intended for use in a target vessel which has undergone a previous bypass procedure.

The NIRS capability of the HyperVue Imaging System - Integrated is intended for the detection of lipid core containing plaques of interest.

The NIRS capability of the HyperVue Imaging System - Integrated is intended for the assessment of coronary artery lipid core burden.

The NIRS capability of the HyperVue Imaging System - Integrated is intended for the identification of patients and plaques at increased risk of major adverse cardiac events.

The HyperVue Imaging System – Integrated is a stationary, capital equipment platform intended for intravascular optical imaging of coronary arteries. HyperVue Imaging System – Integrated with the HyperVue Software and the Starlight Imaging Catheter is used as an intravascular imaging device with the ability to simultaneously assess vessel composition and structure by combining Optical Coherence Tomography (OCT) and Near Infrared Spectroscopy (NIRS).

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The Digital Color Doppler Ultrasound System is a general-purpose ultrasonic imaging system intended for use by sufficiently trained healthcare professionals for ultrasound imaging, measurement, and analysis of the human body, which is intended to be used in a hospital or medical clinic.

The system is intended for use in the following clinical applications: Fetal, Abdominal, Pediatric, Small Organ (breast, testes, thyroid), Cephalic (neonatal and adult), Trans-rectal, Trans-vaginal, Peripheral Vascular, Cerebral Vascular, Musculo-skeletal (Conventional and Superficial), Cardiac (pediatric and adult), OB/Gyn and Urology.

Modes of operation include: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power Doppler, Directional Power Doppler, Tissue Harmonic Imaging, Tissue Doppler Imaging, 3D/4D Imaging mode, Strain Elastography, Contrast imaging and Combined modes: B/M, B/PWD, B/THI, M/Color M, B/Color Doppler, B/Color Doppler/PWD, B/Power Doppler/PWD.

This X11 Exp/X11 Elite/X11 Pro/X11 Plus/X11 Super/X11 Senior/X11/E11/E11 Pro/E11 Plus/E11 Elite/X11T/X11U/X11R/X11i/X11s/E11T/E11i/E11s/XR1/XR2/XR3/ER1/ER2/ER3/X10 Exp/X10 Elite/X10 Pro/X10 Plus/X10 Super/X10 Senior/X10/X10T/X10U/X10R/X10i/X10s/E10/E10 Pro/E10 Plus/E10T/E10i/E10s/SU11A EXP/SU11A PRO/SU11A AD/SU11A CU/SU11B EXP/SU11B PRO/SU11B AD/SU11B CU/SU11C EXP/SU11C PRO/SU11C AD/SU11C CU Digital Color Doppler Ultrasound System (hereafter as "X11 Exp Series Digital Color Doppler Ultrasound System") is an integrated preprogrammed color ultrasound imaging system, capable of producing high detail resolution intended for clinical diagnostic imaging applications.

The basic principle is that system transmits ultrasonic energy into patient body and implements post processing of received echoes to generate onscreen display of anatomic structures and fluid flow within the body.

This system is a Track 3 device that employs a wide array of probes that include linear array, convex array phased array and etc.

This system consists of a console with touch screen and keyboard control panel, power supply module, color LCD monitor and optional probes.

This system is a portable, general purpose, software controlled, color diagnostic ultrasound system. Its basic function is to acquire ultrasound data and to display the image in B-Mode (including Tissue Harmonic Image), M-Mode, TDI, Color-Flow Doppler, Pulsed Wave Doppler, Continued Wave Doppler and Power Doppler, or the combination of these modes, Elastography, contrast, 3D/4D.

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The ASUS Ultrasound Imaging System (Model: LU800 Series) is a software-based imaging system and accessories intended for use by qualified and trained healthcare professionals who has the ability to conduct ultrasound scan process for evaluation by ultrasound imaging system or fluid flow analysis of the human body.

The modes of operation include B mode, M mode, PWD mode, Color Doppler (CD) mode, Power Doppler mode, and the combined mode (B+M, B+CD, B+PWD). Specific clinical applications and exam types including:

LU800L
General abdominal imaging, Pediatric, Small organ (thyroid, prostate, scrotum, breast), Neonatal cephalic, Musculoskeletal (conventional), Musculoskeletal (superficial), Peripheral vessel, Other(Carotid), Pulmonary, interventional guidance(includes free hand needle/ catheter)

LU800C
Fetal, General abdominal imaging, Pediatric, Small organ (thyroid, prostate, scrotum, breast), Urology, Musculoskeletal (conventional), OB/Gyn, Cardiac (adult), Cardiac(pediatric), Peripheral vessel, interventional guidance(includes free hand needle/ catheter)

LU800M
Fetal, General abdominal imaging, Pediatric, Small organ (thyroid, prostate, scrotum, breast), Neonatal cephalic, Urology, Musculoskeletal (conventional), OB/Gyn, Cardiac(adult), Cardiac (pediatric), Peripheral vessel

LU800PA
Fetal, General abdominal imaging, Pediatric, Cardiac (adult), Cardiac (pediatric), Pulmonary

LU800E
Fetal, General abdominal imaging, Pediatric, Small organ (thyroid, prostate, scrotum, breast), Trans-rectal, Trans-vaginal, Urology, OB/Gyn, interventional guidance(includes free hand needle/ catheter)

The clinical environments where the system can be used include physician offices, clinics, hospitals, and clinical point-of-care for diagnosis of patients.

The ASUS Ultrasound Imaging System (Model: LU800 Series) is a portable, software controlled, handheld ultrasound system used to acquire and display hi-resolution, real-time ultrasound data through a commercial off-the-shelf (COTS) mobile device.

I. The imaging system software runs as an app on a mobile device.

II. The imaging system software can be download to a commercial off-the-shelf (COTS) mobile device and utilizes an icon touch-based user interface.

III. The imaging system consists of a series of wireless transducers employing Wi-Fi-based technology to communicate with traditional tablet/smartphone devices via direct Wi-Fi. This allows the user to export ultrasound images and display them across a range portable personal device.

IV. The imaging system houses a built-in battery, multichannel beamformer, prescan converter and Wi-Fi components

The device is intended for use in environments where healthcare is provided by qualified and trained healthcare professionals, but not intended for use in emergency medical service, ambulance, or aircraft.

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Hepatus 7/Hepatus 6/Hepatus 5/Hepatus 7S/Hepatus 6S/Hepatus 5S/Hepatus 7T/Hepatus 6T/Hepatus 5T/Fibrous 7/Fibrous 6/Fibrous 5 Diagnostic Ultrasound System is applicable for adults, pregnant women, pediatric patients and neonates. It is intended for use in fetal, abdominal, Pediatric, small organ (breast, thyroid, testes), Neonatal Cephalic, Adult Cephalic, musculo-skeletal (conventional), musculo- skeletal (superficial), thoracic/pleural, Cardiac Adult, Cardiac Pediatric and Peripheral vessel exams.

It is intended to provide 50Hz shear wave speed measurements (ViTE: Visual Transient Elastography) and estimates of tissue stiffness as well as 3.5 MHz ultrasound coefficient of attenuation (LiSA: Liver Ultra-Sound Attenuation) in internal structures of the body.

It is also intended to measure spleen stiffness using ViTE at 100 Hz shear wave frequency.

The liver stiffness measurement by ViTE may aid the physician in determining the likelihood of cirrhosis and may be used, taken in context with other clinical and laboratory data, as an aid in the assessment of liver fibrosis.

The coefficient of attenuation measurement by LiSA may be used, taken in context with other clinical and laboratory data, as an aid in the assessment of hepatic steatosis.

ViTE and LiSA is indicated as a non-invasive aid for the clinical management, diagnosis, and monitoring of patients with liver disease, as part of an overall assessment of liver.

This device is a general purpose diagnostic ultrasound system intended for use by qualified and trained healthcare professionals for ultrasound imaging, measurement, display and analysis of the human body and fluid, which is intended to be used in a hospital or medical clinic.

Modes of operation include: B, M, PW Doppler, CWD, Color Doppler, Amplitude Doppler, Tissue Harmonic Imaging, Biopsy guidance, Color M, Contrast imaging (Contrast agent for Liver), ViTE, LiSA and Combined mode: B+M, PW+M, Color+B, Power+B, PW+Color+B, Power+PW+B, iScape View, TDI.

The Hepatus 7/Hepatus 6/Hepatus 5/Hepatus 7S/Hepatus 6S/Hepatus 5S/Hepatus7T/Hepatus 6T/Hepatus 5T/Fibrous 7/Fibrous 6/Fibrous 5 Diagnostic Ultrasound System is a general purpose, mobile, software controlled, ultrasonic diagnostic system. Its function is to acquire and display ultrasound images in Modes of operation include: B, M, PW Doppler, CWD, Color Doppler, Amplitude Doppler, Tissue Harmonic Imaging, Biopsy guidance, Color M, Contrast imaging (Contrast agent for Liver), ViTE, LiSA and Combined mode: B+M, PW+M, Color+B, Power+B, PW+Color+B, Power+PW+B, iScape View, TDI.

The Hepatus 7/Hepatus 6/Hepatus 5/Hepatus 7S/Hepatus 6S/Hepatus 5S/Hepatus7T/Hepatus 6T/Hepatus 5T/Fibrous 7/Fibrous 6/Fibrous 5 Diagnostic Ultrasound System can also measure anatomical structures and offer analysis packages to provide information based on which the competent health care professionals can make the diagnosis.

Compared to the predicate device Hepatus 7 (K200643), the new features of the subject device are listed in the table below.

Items: Indications for uses, New features: small organ (breast, thyroid, testes), Neonatal Cephalic, Adult Cephalic, musculo-skeletal (conventional), musculo-skeletal (superficial), thoracic/pleural, Cardiac Adult, Cardiac Pediatric.
Items: Indications for uses, New features: Spleen stiffness measurement using ViTE at 100 Hz.

The liver stiffness measurement by ViTE may aid the physician in determining the likelihood of cirrhosis and may be used, taken in context with other clinical and laboratory data, as an aid in the assessment of liver fibrosis.

The coefficient of attenuation measurement by LiSA may be used, taken in context with other clinical and laboratory data, as an aid in the assessment of hepatic steatosis.

ViTE and LiSA is indicated as a non-invasive aid for the clinical management, diagnosis, and monitoring of patients with liver disease, as part of an overall assessment of liver.

Probes: LFC5-1s, L9-3s, L15-3RCs, P4-2s
Needle-guided brackets: NGB-034, NGB-011, NGB-043
Functions: iScape View, CW, Tissue Doppler Imaging, Spleen ViTE, Small Parts Package, Pediatrics Package, Nerve Package, Cardiology Package, Emergency&Critical Package

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The multifunctional ultrasound scanner is used to collect, display, and analyze ultrasound images during ultrasound imaging procedures in combination with supported echographic probes.

Main applications

• Cardiac
  • Districts: Cardiac Adult, Cardiac Pediatric (including newborns)
  • Invasive access: Transesophageal
• Vascular
  • Districts: Neonatal, Adult Cephalic, Vascular
  • Invasive access: Not applicable
• General Imaging
  • Districts: Abdominal, Musculo-skeletal, Neonatal, Pediatric, Small Organ (Testicles, Breast, Thyroid), Urologic
  • Invasive access: Intraoperative (Abdominal), Laparoscopic, Transrectal
• Women Health
  • Districts: OB/Fetal, Gynecology
  • Invasive access: Transrectal, Transvaginal

The primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both PW and CW), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes, Elastosonography, 3D/4D and CnTI.

The ultrasound scanner is suitable for use in health institutions and is designed for ultrasound practitioners.

7600 Ultrasound System is a portable based ultrasound device used to perform diagnostic general ultrasound studies.

7600 Ultrasound System is equipped with two LCD Color Displays. The first LCD Color Display is the main output device used to display the acquisition image, the acquisition configuration and the exam results. The second LCD is provided with Touch panel and is used as a flexible input control device because its easy configurability.

The device uses the physical properties of the ultrasound (i.e. sound waves with frequency above 20 kHz and that are not audible to the human ear) for the visualization of deep structures of the body by recording the reflections or echoes of ultrasonic pulses directed into the tissues and of the Doppler effect, i.e. the frequency-shifted ultrasound reflections produced by moving targets (usually red blood cells) in the bloodstream, to determine both direction and velocity of blood flow in the target organs.

The primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both PW and CW), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes. 7600 Ultrasound System also manages Elastosonography, 3D/4D and CnTI.

Several types of probes are used to cover different needs in terms of geometrical shape and frequency range.

7600 Ultrasound System can drive Phased array, Convex array, Linear array, Doppler probes and Volumetric probes (Bi-Scan probes).

7600 Ultrasound System is equipped with wireless capability.

7600 Ultrasound System will be available on the market in two models with the following commercial names: MyLabC25, MyLabC30.

The difference between MyLabC25 and MyLabC30 models is only in the licenses configuration.

7600 Ultrasound System, defined herein, is a new portable version of the cart-based 6600 Ultrasound System previously cleared under K243253.

The proposed 7600 Ultrasound System includes a new software version that combines features FDA-cleared and already available in the predicate and reference devices (K243253 and K241671). No new functionalities have been introduced in the current software release compared to the version previously cleared.

7600 Ultrasound System employs the same fundamental technological characteristics as its predicate device cleared via K243253.

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The device is a general purpose ultrasound system intended for use by qualified and trained healthcare professionals. Specific clinical applications remain the same as previously cleared: Fetal/OB; Abdominal (including GYN, pelvic and infertility monitoring/follicle development); Pediatric; Small Organ (breast, testes, thyroid etc.); Neonatal and Adult Cephalic; Cardiac (adult and pediatric); Musculo-skeletal Conventional and Superficial; Vascular; Transvaginal (including GYN); Transrectal

Modes of operation include: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power Doppler, Harmonic Imaging, Coded Pulse, 3D/4D Imaging mode, Elastography, Shear Wave Elastography and Combined modes: B/M, B/Color, B/PWD, B/Color/PWD, B/Power/ PWD, B/Elastography. The Voluson™ Expert 18, Voluson™ Expert 20, Voluson™ Expert 22 is intended to be used in a hospital or medical clinic.

The systems are full-featured Track 3 ultrasound systems, primarily for general radiology use and specialized for OB/GYN with particular features for real-time 3D/4D acquisition. They consist of a mobile console with keyboard control panel; color LCD/TFT touch panel, color video display and optional image storage and printing devices. They provide high performance ultrasound imaging and analysis and have comprehensive networking and DICOM capability. They utilize a variety of linear, curved linear, matrix phased array transducers including mechanical and electronic scanning transducers, which provide highly accurate real-time three-dimensional imaging supporting all standard acquisition modes.

The following probes are the same as the predicate: RIC5-9-D, IC5-9-D, RIC6-12-D, 9L-D, 11L-D, ML6-15-D, RAB6-D, C1-6-D, C2-9-D, M5Sc-D, RM7C, eM6CG3, RSP6-16-D , RIC10-D, 6S-D and L18-18iD, RIC12-D.

The existing cleared Probe C1-6-D is being added to previously cleared SW- AI Feature Sonolyst 1st Trimester.

The provided text describes the FDA 510(k) clearance for the Voluson Expert Series ultrasound systems, specifically focusing on the AI feature "Sonolyst 1st Trimester" and the addition of the C1-6-D transducer to this feature.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

Additional Performance Data (Mean values across transabdominal and transvaginal scans):

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

• SonoLyst 1st Trim IR: 7970 images

• SonoLyst 1st Trim X: 4931 images

• SonoLyst 1st Trim Live: 9111 images

• SonoBiometry CRL: 243 images

• Specific to Probegroup CL2 (which includes C1-6-D Probe): Data was collected from 396 patients.

• Data Provenance: Data was collected from multiple geographical sites including the UK, Austria, India, and USA. The data was collected using different systems (GE Voluson V730, P8, S6/S8, E6, E8, E10, Expert 22, Philips Epiq 7G).

• Retrospective/Prospective: The document does not explicitly state whether the test data was retrospective or prospective. However, the mention of "data acquired with transabdominal vs transvaginal probes" and "patients within the dataset includes pregnancies between 11 and 14 weeks of gestation, with no known fetal abnormalities at the time of imaging" suggests that the images were pre-existing or collected specifically for this evaluation, implying a retrospective or a pre-defined prospective collection for the study.

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

• Initial Curation: A single sonographer curated (sorted and graded) the images initially.
• Review Panel for Graded Images: Where the system's grading differed from the initial ground truth, the images were reviewed by a 5-sonographer review panel to determine the grading accuracy of the system.
• Qualifications: The document identifies them as "sonographers." Specific years of experience or expertise in fetal ultrasound are not provided, other than their role in image curation and review.

4. Adjudication Method for the Test Set

• Initial Sorting and Grading: Images were initially curated (sorted and graded) by a single sonographer.
• Reclassification during Sorting: The SonoLyst IR/X First Trimester process resulted in some images being reclassified during sorting based on the majority view of the panel (after the step where the system had sorted them).
• Grading Accuracy Review: For graded images where the initial single sonographer's ground truth differed from the system, a 5-sonographer review panel was used to determine the accuracy. This suggests an adjudication process where the panel formed a consensus or majority opinion to establish the final ground truth when discrepancies arose. The exact method (e.g., simple majority, weighted vote) is not specified beyond "majority view of the panel."

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

• The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done to evaluate how much human readers improve with AI vs. without AI assistance. The testing focused on the standalone performance of the AI algorithm against a ground truth established by sonographers.
• The verification of SonoLystLive 1st Trim Trimester features was based on the "average agreement between a sonographer panel and the output of the algorithm regarding Traffic light quality," which involves human readers assessing traffic light quality in relation to the algorithm's output, but it's not a study designed to measure human improvement with AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Yes, a standalone performance evaluation was conducted. The performance metrics (SonoLystIR, SonoLystX, SonoLystLive, SonoBiometry CRL success rate) are reported as the accuracy of the algorithm comparing its output directly against the established ground truth. This is a measure of the algorithm's ability to perform its specified functions independently.

7. The Type of Ground Truth Used

• The ground truth was established through expert consensus/review by sonographers.
  • Initial curation by a single sonographer.
  • Review and reclassification during sorting based on the "majority view of the panel."
  • A 5-sonographer review panel was used to determine grading accuracy for discrepancies.
• The ground truth also adhered to standardized imaging protocols based on internationally recognized guidelines (AIUM Practice Parameter, AIUM Detailed Protocol, ISUOG Practice Guidelines, ISUOG Detailed Protocol, and the study by Yimei Liao et al.) which informed the quality and consistency of the expert review.

8. The Sample Size for the Training Set

• 122,711 labelled source images from 35,861 patients were used for training.

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

• The document states that "Data used for both training and validation has been collected across multiple geographical sites using different systems to represent the variations in target population."
• While the specific method for establishing ground truth for the training set is not explicitly detailed in the same way as the test set, it can be inferred that similar expert labeling and curation processes would have been applied given the emphasis on "labelled source images." The document focuses on the test set truthing process as part of verification, implying that the training data would have undergone a robust labeling process to ensure quality for machine learning.

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