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The multifunctional ultrasound scanner MyLabX90 is used to collect, display, and analyze ultrasound images during ultrasound imaging procedures in combination with supported echographic probes.

Virtual Navigator option supports a radiological clinical ultrasound examination (first modality) by providing additional image information from a second imaging modality. As second imaging modality it is intended any image coming from CT, MR, US, PET,XA and NM. The second modality provides additional security in assessing the morphology of the real time ultrasound image.

The upgraded 6440 systems, MyLabX90 is a mainframe systems equipped with wheels allowing to move the system.

MyLabX90 scanners are based on a mainframe easily movable platform.

MyLabX90 scanners have four swiveling wheels. they have a range of height adjustments for onetime installation, the main screen can be easily moved due to an optional articulated arm. Due to their small footprint they can fit in any real-world clinical environment.

The possibility to adjust both the main screen. control panel and touchscreen brightness enables the use of MyLab in any environment even with really different lighting conditions:

from the really bright scenario of the operative room, to the dark scenario of the examination room, passing through the medium-light environment of the bed-side examination setting.

The primary modes of operation are for both models: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler, Color Flow Mapping (CFM), Amplitude Doppler (AD), Tissue Velocity Mapping (TVM), 3D and 4D. Model 6440 manages Qualitative Elastosonography (ElaXto).

Model 6440 can drive Phased array, Convex array, Linear array, Doppler probes and Volumetric probes (Bi-Scan probes). The control panel is equipped with a pull-out Qwerty alphanumeric keyboard that allows data entry.

Model 6440 has the Virtual Navigator software option integrated, designed to support a radiological clinical ultrasound examination (first modality) and follow a percutaneous procedure providing additional image information from a 2nd imaging modality (CT, MR, US and PET). The user is helped in assessing the patient anatomy by displaying the image generated by the 2nd modality.

Model 6440 is equipped with wireless capability.

Model 6440 is already cleared via K173291.

The marketing name for new devices of Model 6440 will be:

MyLabX90 ●

MyLabX90, defined herein, combines the cleared features of 6440 system with new capabilities, listed below:

• 1. Cardio Package with new AUTO E.F. The AutoEF, based on Artificial Intelligence, detects and track, automatically, the LV endocardial border to calculate LV Volumes (Diastolic Volume - Systolic Volume) and EF (Ejection Fraction). The software module (powered with A.I.) is registered by Pie Medical Imaging B.V. as Caas Qardia (K212376)
• 2. eDetect for Breast Lesions contouring function supports the operator by detecting the lesion contour (with A.I. algorithm) in Breast measurements, after that the operator has identified the region, with suspicious lesions, and applied the ROI marker. At the end of the detection the operator can confirm/edit the proposed contour or redraw it completely. In addition, several morphologic parameters (following Bi-Rads : shape, orientation and circumscribed) are automatically proposed to the customer and upon validation is inserted in the final report. The tool is available in Breast application.
• 3. XStrain allows clinicians to quantify endocardial velocities of contraction and relaxation and local deformation of the heart (Strain rate). Based on 2D speckle tracking technology with Angle-independent technology. A.I. Powered for auto border detection of left ventricle (LV).
• 4. The QAI (Quality Attenuation Imaging) application allows to perform a Colored Quantitative Attenuation analysis of tissues in Real-time. Based on the attenuation analysis along the ROI. In QAI attenuation parameter values are converted and color coded and displayed inside the Region Of Interest (ROI). A different set of palettes is available, with dynamic control and transparency.
• The Prostate Biopsy Stepper is enabling the compatibility with CIVCO Classic and GfM 5. MST50 steppers displaying a Grid Template overlays for precise guided-biopsies. The Stepper help stabilizes and follows accurate needle path during transperineal procedure. Stepper functionality is available in Fusion imaging / UroFusion environment.
• HyperDoppler, based on Color Doppler Flow Mapping (CDFM) technology, provides different 6. map representation to highlight the intracardiac flow properties
• 7. Transducer Element Check
• 8. New transducers 2CWL, 5CWL, CX 1-8, LX 3-15, LMX 4-20, PX 1-5 and TE 3-8
• 9. New biopsy kits JSM-198 and JSM-113.

Here's a breakdown of the acceptance criteria and study details for the "eDetect for Breast Lesions contouring" and "Endocardium border segmentation" AI features, based on the provided document:

eDetect for Breast Lesions Contouring

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document provides example values for "Absolute Difference [mm²]" and "Absolute Difference [mm]" for the image contouring, which are then converted to "Percentage Error (%)". The "Average Error < 0.15" acceptance criteria refers to the contouring accuracy, specifically the "Average Error" metric in relation to the contour. For the BIRADS parameters, only success rates are provided as criteria, without specific numerical results in the example given.

2. Sample Size and Data Provenance

• Test Set Sample Size: 100 images collected from 20 different patients.
• Data Provenance: The document states that both training and test datasets are based on female patients and report US images of breast examinations. The country of origin is not explicitly stated. It is a retrospective collection as the images were "saved during exam".

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Two certified radiologists.
• Qualifications: Certified radiologists who performed data evaluation for border contouring. Their experience matured within different structures, where they operated independently and at different times.

4. Adjudication Method for Test Set

• Method: Consensus reading. The two radiologists each contributed to the annotation and then reviewed the annotations of the other. They discussed their agreement or disagreement to reach a consensus.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study was explicitly mentioned or described for this AI feature. The study focuses on evaluating the AI's performance against human annotations, not on human readers with and without AI assistance.

6. Standalone Performance (Algorithm Only)

• Yes, the acceptance criteria and reported performance are for the standalone algorithm, comparing its output to expert annotations.

7. Type of Ground Truth Used

• Expert Consensus: The ground truth for the test set was established by the consensus of two certified radiologists.

8. Sample Size for Training Set

• Training Set Sample Size: 828 images collected from 450 different patients.

9. How Ground Truth for Training Set Was Established

• Data Annotation was performed by operators, including information about lesion size, morphology, position, vascularization, and diagnosis given by a physician. The specifics of how this annotation was established (e.g., single expert, consensus) are not detailed for the training set, but it implies human annotation.

Endocardium Border Segmentation (Auto E.F.)

This AI feature is part of the "Cardio Package with new AUTO E.F.", which is based on AI algorithms registered by Pie Medical Imaging B.V. as Caas Qardia (K212376). The provided document summarizes the testing for this component but directs to the full report in section 1.7.5 for complete details.

1. Table of Acceptance Criteria and Reported Device Performance

The table in the document provides more granular results for A2C, A4C, and combined measures, all falling within the acceptance criteria.

2. Sample Size and Data Provenance

• Test Set Sample Size: 200 individually segmented frames.
• Data Provenance: The echocardiographic images were collected from patients of varying age and gender. The total dataset (training, validation, test) originated from 399 patients. The data was collected from different institutions using different echocardiographic systems (Esaote Mylab Alpha system and another ultrasound scanner, not Esaote). The country of origin is not explicitly stated. It is considered retrospective as annotations were performed on received ultrasound images.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Three cardiologists and one clinical researcher.
• Qualifications: The three cardiologists had "more than 20 years of experience," and the clinical researcher had "more than 5 years of experience with the analysis of cardiac ultrasound."

4. Adjudication Method for Test Set

• Method: An internal guideline for annotation of the LV blood pool endocardium contour was developed using information gathered from "external experts" (the cardiologists and clinical researcher mentioned above). This implies that a consensus or expert-derived guideline was used to establish the ground truth, rather than an explicit multi-reader adjudication process on each case in the test set.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study was explicitly mentioned or described for this AI feature. The study focuses on evaluating the AI's performance against expert-defined ground truth, not on human readers with and without AI assistance.

6. Standalone Performance (Algorithm Only)

• Yes, the acceptance criteria and reported performance are for the standalone algorithm, comparing its segmentation output to the ground truth.

7. Type of Ground Truth Used

• Expert-Derived Guidelines: The ground truth was established by using an internal guideline developed from information gathered from expert cardiologists and a clinical researcher. This implies a standardized annotation process based on expert knowledge.

8. Sample Size for Training Set

• Training Set Sample Size: 1221 image frames
• Validation Set Sample Size: 306 image frames
• Total for training/validation: 1527 image frames (A2C, A3C, and A4C combined).

9. How Ground Truth for Training Set Was Established

• Annotations on the received ultrasound images were performed using a customized CAAS Qardia 1.0 application. The basis for these annotations would have been the internal guideline developed by the experts (three cardiologists with >20 years of experience and one clinical researcher with >5 years of experience mentioned in the "Truthing" process).

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The multifunctional ultrasound scanner MyLabX75 Family is used to collect, display, and analyze ultrasound images during ultrasound imaging procedures in combination with supported echographic probes
-Cardiac [Adult and Pediatric]
-Vascular [Neonatal, Adult Cephalic, Vascular generic] -General Imaging [Abdominal, Breast, Musculo-skeletal, Neonatal, Pediatric, Small Organs (Testicles), Thyroid, Urological ] with invasive access Intraoperative (Abdominal), Laparoscopic, Transrectal. -Women Health [OB/Fetal, Gynecology with invasive access (Transrectal, Transvaginal)]
The equipment provides imaging for guidance of biopsy and imaging to assist in the placement of needles and catheters in vascular or other anatomical structures as well as peripheral nerve blocks in Musculoskeletal applications. The ultrasonic medical diagnostic equipment is intended to mechanical and electronic ultrasound probes (convex array, linear array and phased array) and Doppler probes.
The Fiber Guidance option assists ultrasound guidance in the phases of insertion and positioning of the introducer needle and optical fiber and procedure monitoring.

Model 6430, commercial names MyLabX75 and MyLab XPro75, is a mainframe ultrasound system used to perform diagnostic general ultrasound studies. The primary modes of operation are: B-Mode, Tissue Enhancement Imaging (TEI), M-Mode, Multi View (MView), Doppler (both PW and CW), Color Flow Mapping (CFM), Amplitude Doppler (AD), Tissue Velocity Mapping (TVM), 3D and 4D, Qualitative Elastosonography (ElaXto) and Quantitative Elastosonography (QElaXto).
Model 6430 has a software option integrated, called PLA, designed to support a radiological clinical ultrasound examination (first modality) and follow a percutaneous procedure providing additional image information from a second imaging modality (CT, MR, US and PET). The user is helped in assessing the patient anatomy by displaying the image generated by the 2nd modality.
Model 6430 is equipped with a LCD color display where acquired images and advanced image features are shown. Model 6430 control panel is equipped with a pull-out Qwerty alphanumeric keyboard that allows data entry. The touchscreen has an emulation of the Qwerty alphanumeric keyboard that allows data entry and has additional controls and mode-depending keys, integrated in the touchscreen.
Model 6430 can drive Phased Array (PA), Convex Array (LA), Linear Array (LA), Doppler and Volumetric probes.
Model 6430 is equipped with an internal Hard Disk Drive. Data can also be stored directly to external archiving media (Hard-Disk, PC, on server) via a LAN/USB port.
6430 project is mainly design change of 6450 devoted to reducing cost and to differentiate design and performances, 6430 will introduce in the Esaote's Mid-ultrasound tier functionalities that, at the moment are present only in our High -End Ultrasound tier, such as 2D Shear Wave Elastography (2D-SWE) and Virtual Navigator.
The marketing names for Model 6430 will be MyLabX75 and MyLab XPro75.
The difference between MyLab XPro75 is only in the licenses configuration: on MyLab XPro75 all the options are included while in the MyLabX75 some licenses can be ordered by customer.

The provided text is a 510(k) summary for the Esaote MyLabX75 and MyLab XPro75 ultrasound systems. It explicitly states that no clinical tests were performed to demonstrate that the device meets acceptance criteria. The submission relies entirely on non-clinical data and equivalence to a predicate device.

Therefore, many of the requested details about acceptance criteria and study design are not applicable or cannot be extracted from this document.

Here's what can be extracted based on the information provided:

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

The document does not specify quantitative acceptance criteria for performance; rather, it focuses on safety and technological equivalence.

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

• Not Applicable. No clinical test set was used as "No clinical tests were performed." The submission relies on non-clinical data, typically engineering verification and validation.

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

• Not Applicable. No clinical test set was used, and thus no expert ground truth establishment for a clinical study.

4. Adjudication method for the test set

• Not Applicable. No clinical test set was used.

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

• Not Applicable. No clinical effectiveness study, and specifically no MRMC study, was performed. This device is an ultrasound system, not an AI-assisted diagnostic tool in the context of human reader improvement.

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

• Not Applicable. This is an ultrasound imaging system, not a standalone diagnostic algorithm. The performance evaluation was based on non-clinical engineering tests and comparison to a predicate device's technological characteristics and safety standards.

7. The type of ground truth used

• Not Applicable. As no clinical studies were performed, there was no ground truth for patient outcomes or expert consensus on diagnostic accuracy required in this submission. The "ground truth" for the non-clinical tests would be the compliance with engineering specifications and safety standards.

8. The sample size for the training set

• Not Applicable. This document does not describe the development or training of any machine learning algorithms. It is a traditional 510(k) for an ultrasound imaging system.

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

• Not Applicable. As no machine learning training set is mentioned.

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