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The Sonosite LX Ultrasound System is a general-purpose ultrasound system intended for use by qualified physicians and healthcare professionals for evaluation by ultrasound imaging or fluid flow analysis of the human body. Specific clinical applications and exam types include:

• Abdominal
• Adult Cephalic
• Neonatal Cephalic
• Cardiac Adult
• Cardiac Pediatric
• Dermatological
• Fetal OB/GYN
• Musculo-skeletal (Conventional)
• Musculo-skeletal (Superficial)
• Ophthalmic
• Pediatric
• Peripheral vessel
• Small Organ (breast, thyroid, testicles, prostate)
• Transesophageal (cardiac)
• Transrectal
• Transvaginal
• Needle Guidance

Modes of operation include: B Mode (B), M-Mode (M) (including simultaneous M-mode and anatomical M Mode), PW Doppler (PWD) (including Pulsed Wave Tissue Doppler), Continuous Wave Doppler (CWD), Color Power Doppler (including Velocity Color Doppler), Tissue Harmonic Imaging (THI), Tissue Doppler Imaging (TDI), and Combined modes, including Triplex imaging: B+M, B+PWD, B+CWD, B+C, (B+C)+PWD, (B+C)+CWD.

This device is indicated for Prescription Use Only.

The Sonosite LX Ultrasound System is intended to be used in medical practices, clinical environments, including Healthcare facilities, Hospitals, Clinics and clinical point-of-care for diagnosis of patients.

The Sonosite LX Ultrasound System is a full featured, general purpose, software controlled, diagnostic ultrasound system used to acquire and display high-resolution, real-time ultrasound data in 2D, M Mode, Pulsed Wave (PW) Doppler, Continuous Wave (CW) Doppler, Color Power Doppler (CPD), and color Doppler (Color) or in a combination of these modes. The Sonosite LX is designed as an integrated unit with its kiosk-style stand.

The system includes a variety of accessories including needle guide starter kits. The system includes USB host support for peripherals such as input devices, storage devices, and an Ethernet port. Input devices include wired and wireless devices. The system also includes an ECG-specific port to support the ECG feature. The non-diagnostic ECG module provides ECG tracing of the cardiac signal synchronized with the ultrasound image.

The provided FDA 510(k) clearance letter for the Sonosite LX Ultrasound System (K251830) describes a general-purpose ultrasound system. As such, the clearance does not detail specific acceptance criteria for diagnostic performance metrics (e.g., sensitivity, specificity, accuracy) that would typically be associated with AI-powered diagnostic devices. Instead, the submission focuses on demonstrating substantial equivalence to predicate devices through technical characteristics and compliance with general safety and performance standards.

However, based on the information provided, we can infer some "acceptance criteria" related to the device's technical specifications and safety, and how the study addresses them.

Here's an analysis based on your requested information:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a general-purpose ultrasound system and not an AI/diagnostic algorithm, the acceptance criteria are not in the form of diagnostic performance metrics. Instead, they are related to equivalence with predicate devices, safety, and general performance standards.

Regarding specific AI-related questions (2-9), this clearance letter does not pertain to an AI/ML device for diagnostic interpretation. It's for a general-purpose ultrasound system. Therefore, most of these questions are not applicable to the information provided.

However, I will address them to indicate their non-applicability or provide any remotely relevant information.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable. This submission is for a general-purpose ultrasound system, not an AI/ML algorithm requiring a specific test set for diagnostic performance. The evaluation was primarily based on engineering testing (electrical, thermal, mechanical, EMC safety, biocompatibility, acoustic output, standards compliance) and comparison to predicate devices, rather than a dataset of patient cases.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not Applicable. No ground truth (in the context of diagnostic accuracy) was established for a test set in this submission, as it's not an AI/ML diagnostic algorithm.

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

• Not Applicable. No test set requiring expert adjudication for diagnostic ground truth.

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. This is not an AI-assisted diagnostic device, so no MRMC study comparing human readers with and without AI assistance was performed or reported.

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

• Not Applicable. This is a hardware device (ultrasound system), not a standalone algorithm.

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

• Not Applicable. The "ground truth" here relates to engineering specifications and safety standards, such as:
  • Biocompatibility confirmed by ISO 10993-1 standards (chemical testing, etc.)
  • Acoustic output confirmed by IEC 62359 standards.
  • Electrical safety confirmed by IEC 60601-1 standards.
  • Functional "ground truth" confirmed by successful testing in a clinical environment, meaning it operates as intended for imaging and fluid flow analysis.

8. The sample size for the training set

• Not Applicable. This clearance is not for an AI/ML device that requires a training set.

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

• Not Applicable. No training set for an AI/ML device.

In summary, the FDA 510(k) clearance for the Sonosite LX Ultrasound System is focused on demonstrating substantial equivalence to pre-existing, legally marketed predicate ultrasound systems and compliance with international safety and performance standards. The "study" proving it meets acceptance criteria primarily involves comprehensive engineering validation and verification testing (electrical, thermal, mechanical, EMC, acoustic output, biocompatibility, cleaning/disinfection) and documented adherence to a robust Quality System, rather than a clinical study evaluating diagnostic accuracy with a patient dataset or the performance of an AI algorithm.

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The diagnostic ultrasound system and probes are designed to obtain ultrasound images and analyze body fluids.

The clinical applications include: Fetal/Obstetrics, Abdominal, Gynecology, Pediatric, Small Organ, Neonatal Cephalic, Adult Cephalic, Trans-rectal, Muscular-Skeletal (Conventional, Superficial), Urology, Cardiac Adult, Cardiac Pediatric, Trans-esophageal (Cardiac), Peripheral vessel, Lung and Dermatology.

It is intended for use by, or by the order of, and under the supervision of, an appropriately trained healthcare professional who is qualified for direct use of medical devices. It can be used in hospitals (includes emergency room), private practices, clinics and similar care environment for clinical diagnosis of patients.

Modes of Operation: 2D mode, Color Doppler mode, Power Doppler (PD) mode, M mode, Pulsed Wave (PW) Doppler mode, Continuous Wave (CW) Doppler mode, Tissue Doppler Imaging (TDI) mode, Tissue Doppler Wave (TDW) mode, ElastoScan Mode, Combined modes, Multi-Image mode(Dual, Quad), 3D/4D mode.

The HM70 EVO is a general purpose, mobile, software controlled, diagnostic ultrasound system. Its function is to acquire ultrasound data and to display the data as 2D mode. M mode, Color Doppler imaging, Power Doppler imaging (including Directional Power Doppler mode; S-Flow), PW Spectral Doppler mode, CW Spectral Doppler mode, Harmonic imaging(S-Harmonic), Tissue Doppler imaging, Tissue Doppler Wave, Panoramic Imaging, Freehand 3D, 3D imaging mode (real-time 4D imaging mode), Elastoscan Mode or as a combination of these modes. The HM70 EVO also gives the operator the ability to measure anatomical structures and offers analysis packages that provide information that is used to make a diagnosis by competent health care professionals. The HM70 EVO has real time acoustic output display with two basic indices, a mechanical index and a thermal index. which are both automatically displayed.

The provided text describes two AI-based features of the HM70 EVO Diagnostic Ultrasound System: UterineAssist and NerveTrack. The acceptance criteria and performance studies for each are detailed below.

UterineAssist

1. Table of Acceptance Criteria and Reported Device Performance

For UterineAssist, the document details performance for three areas: image segmentation, feature points extraction, and size measurement. While explicit acceptance criteria values (like a minimum percentage or maximum error) are not stated in a direct acceptance criteria table, the reported device performance serves as the evidence of meeting internal acceptance.

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

• Segmentation Test:

  • Sample Size: 450 sagittal uterus images and 150 transverse uterus images (total 600 images).
  • Data Provenance: Collected at three hospitals. Mix of retrospective and prospective data collection in clinical practice.
  • Country of Origin: All Koreans (implies South Korea).

• Feature Points Extraction Test & Size Measurement Test:

  • Sample Size: 45 sagittal and 41 transverse plane images of uterus (total 86 images).
  • Data Provenance: Collected at three hospitals. Mix of retrospective and prospective data collection in clinical practice.
  • Country of Origin: All Koreans (implies South Korea).

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

• Number of Experts: Three participating OB/GYN experts.
• Qualifications: Each had more than 10 years' experience.

4. Adjudication Method for the Test Set

• Method: The set of images (uterus and endometrium) were divided into 3 subsets. Each of the three OB/GYN experts drew the ground truths for one of the subsets. The ground truths drawn by one expert were then cross-checked by the other two experts. Any images not meeting inclusion/exclusion criteria were excluded. This can be described as a 1+2 cross-check adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No MRMC comparative effectiveness study is reported for UterineAssist, as this section only describes the standalone performance metrics.

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

• Yes, the reported performance metrics (Dice-score, error measurements) reflect the "standalone" performance of the algorithm.

7. The Type of Ground Truth Used

• The ground truth for both segmentation and feature points/size measurements was established by expert consensus/adjudication from three experienced OB/GYN experts.

8. The Sample Size for the Training Set

• The training data details (specific sample size) are not provided, but it is stated that it is independent of the test data.

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

• Not explicitly stated, but implicitly, similar expert labeling or other reliable methods would have been used, consistent with the independent test data approach. It is only mentioned that the training and test data sets are "completely separated" and there is "no overlap."

NerveTrack

1. Table of Acceptance Criteria and Reported Device Performance

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

• Number of Subjects: 18 (13 Females, 5 Males)
• Number of Images: 2,146
• Age Range: 22-68 years
• BMI Range: 16-31.5
• Data Provenance: Not explicitly stated as retrospective or prospective, but the description of gathering scan data and expert involvement suggests a prospective collection or a specifically designed retrospective collection process for validation.
• Country of Origin: All Koreans (implies South Korea).

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

• Number of Experts: Ten anesthesiologists and five sonographers (total 15 experts) for review and confirmation.
• Qualifications: All had more than 10 years of experience.
• Initial Ground Truth Drawing: One anesthesiologist who scanned the ultrasound directly drew the GT.

4. Adjudication Method for the Test Set

• Method: One anesthesiologist who directly scanned the ultrasound drew the initial ground truth (GT) for the nerve location. Then, "two or more other anesthesiologists and sonographers reviewed and confirmed that it was correct." If any mistake was identified during the review, it was revised. This indicates a 1 + (2 or more) consensus/adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, the document describes "standalone performance" validation of the NerveTrack algorithm, specifically focusing on accuracy and speed. It does not mention any MRMC study comparing human readers with and without AI assistance.

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

• Yes, the validation clearly states, "The standalone performance of NerveTrack was evaluated..." and provides performance metrics (accuracy and speed) for the algorithm itself.

7. The Type of Ground Truth Used

• The ground truth for the location of 10 different kinds of nerves was established by expert consensus/adjudication involving anesthesiologists and sonographers with significant experience.

8. The Sample Size for the Training Set

• The training data details (specific sample size) are not provided, but it is stated that it is independent of the test data.

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

• Not explicitly stated, but it is mentioned that the "training data used for the training of the NerveTrack algorithm are independent of the data used to test the NerveTrack algorithm." This implies a separate, established ground truth for the training set, likely using similar expert labeling methods.

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