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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.

Main application	Districts	Invasive access
Cardiac	Cardiac Adult, Cardiac Pediatric	Transesophageal
Vascular	Neonatal, Adult Cephalic, Vascular	Not applicable
General Imaging	Abdominal, Breast, Musculo-skeletal, Neonatal, Pediatric, SmallOrgans (Testicles), Thyroid,Urological	Intraoperative (Abdominal),Laparoscopic,Transrectal
Women Health	OB/Fetal, Gynecology	Transrectal, Transvaginal

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.

Device Description

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)
1. 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.
1. 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).
1. 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
1. Transducer Element Check
1. New transducers 2CWL, 5CWL, CX 1-8, LX 3-15, LMX 4-20, PX 1-5 and TE 3-8
1. New biopsy kits JSM-198 and JSM-113.

AI/ML Overview

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

Criteria	Acceptance Threshold	Reported Device Performance (L 4-15 Probe Example)
IOU Contour	Average Error < 0.15	A1: 0.14, A2: 1.57, A3: 3.27 (mm²)
BIRADS Parameters (Success Rate)
- Shape	> 80%	Not explicitly reported numerically, but states "The test results are in line with the acceptance criteria."
- Orientation	> 90%	Not explicitly reported numerically, but states "The test results are in line with the acceptance criteria."
- Circumscribed	> 75%	Not explicitly reported numerically, but states "The test results are in line with the acceptance criteria."

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

Criteria	Acceptance Threshold	Reported Device Performance (Average Dice Coefficient)
Mean Dice Coefficient	> 0.9	0.95
Standard Deviation	< 0.03	0.02

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