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The LOGIQ E10s and LOGIQ Fortis are intended for use by a qualified physician for ultrasound evaluation.
Specific clinical applications and exam types include: Fetal / Obstetrics; Abdominal (including Renal, Gynecology/Pelvic); Pediatric; Small Organ (Breast, Testes, Thyroid); Neonatal Cephalic; Adult Cephalic; Cardiac (Adult and Pediatric); Peripheral Vascular; Musculo-skeletal Conventional and Superficial; Urology (including Prostate); Transrectal; Transvaginal; Transesophageal and Intraoperative (Abdominal, Vascular).
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, Attenuation Imaging and Combined modes: B/M, B/Color, B/PWD, B/Color/PWD, B/Power/PWD.
The LOGIQ E10s and LOGIQ Fortis are intended to be used in a hospital or medical clinic.

Device Description

The LOGIQ E10s is a full featured, Track 3, general purpose diagnostic ultrasound system which consists of a mobile console approximately 585 mm wide (keyboard), 991 mm deep and 1300 mm high that provides digital acquisition, processing and display capability. The user interface includes a computer keyboard, specialized controls, 12-inch high-resolution color touch screen and 23.8-inch High Contrast LED LCD monitor.
The LOGIQ Fortis is a full featured, Track 3, general purpose diagnostic ultrasound system which consists of a mobile console approximately 575 mm wide (keyboard). 925 mm deep and 1300 mm high that provides digital acquisition, processing and display capability. The user interface includes a digital keyboard (physical keyboard as an option), specialized controls, 12inch high-resolution color touch screen and 23.8-inch High Contrast LED LCD monitor (or 23.8inch High Resolution LED LCD monitor as an option).

AI/ML Overview

The provided text describes three AI features of the LOGIQ E10s and LOGIQ Fortis systems: Auto Renal Measure Assistant, Auto Abdominal Color Assistant, and Auto Preset Assistant. The information provided for each feature allows for a detailed breakdown of their acceptance criteria and the studies conducted to prove they meet these criteria.

Here's the requested information structured for clarity:

1. Table of Acceptance Criteria and Reported Device Performance

AI Feature	Acceptance Criteria	Reported Device Performance
Auto Renal Measure Assistant	Longitudinal model accuracy for length measurements expected to be > 80%. Transverse model accuracy for width measurements expected to be > 70%.	Longitudinal model for length measurements: Average accuracy of 96.45% (95% CI: ±1.26%), average absolute error of 0.35cm (95% CI: ±0.12 cm).
Transverse model for width measurements (first mention): Average accuracy of 92.94% (95% CI: ±3.02%), average absolute error of 0.38cm (95% CI: ±0.14 cm).
Transverse model for width measurements (second mention, likely a typo/repetition): Average accuracy of 93.13% (95% CI: ±3.63%), average absolute error of 0.37cm (95% CI: ±0.14 cm).
Auto Abdominal Color Assistant	Overall model success rate for Aorta, Kidney, Liver, GB, and Pancreas view suggestion expected to be 80% or higher.	Specific accuracy percentages for each view are not individually reported in the summary, but the success rate is implied to have met or exceeded the 80% threshold, as the device is deemed substantially equivalent. The summary states "Calculated the accuracies of the algorithm against each class," which suggests these were evaluated.
Auto Preset Assistant	Overall model success rate for Abdomen, Air, Breast, Carotid, Leg, MSK, Scrotal, Thyroid, and Carotid/Thyroid (Mixed) view suggestion expected to be 80% or higher.	Specific accuracy percentages for each view are not individually reported in the summary, but the success rate is implied to have met or exceeded the 80% threshold, as the device is deemed substantially equivalent. The summary states "Calculated the accuracies of the algorithm against each class," which suggests these were evaluated.

2. Sample Sizes and Data Provenance for Test Sets

Auto Renal Measure Assistant:
- Test Set Sample Size: 30 patients, resulting in 60 samples (30 longitudinal views, 30 transverse views).
- Data Provenance: Prospective collection. Data from USA (58%) and Japan (42%).
Auto Abdominal Color Assistant:
- Test Set Sample Size: 50+ patients, resulting in 1100+ images.
- Data Provenance: Not explicitly stated as retrospective or prospective, but collected from USA (77%) and Australia (23%).
Auto Preset Assistant:
- Test Set Sample Size: 110+ patients, resulting in 2600+ images.
- Data Provenance: Not explicitly stated as retrospective or prospective, but collected from USA (41.2%), Austria (3.8%), Australia (1.1%), Japan (41.3%), Italy (0.7%), and Greece (12%).

3. Number of Experts and Qualifications for Ground Truth

Auto Renal Measure Assistant:
- Number of Experts: 2 "Readers" and 1 "Board Certified Nephrologist" for arbitration.
- Qualifications: "certified sonographer/Clinician" for the two readers. "Board Certified Nephrologist" for the arbitrator.
Auto Abdominal Color Assistant:
- Number of Experts: Unspecified number of "Readers".
- Qualifications: "certified sonographer/Clinician" for the readers.
Auto Preset Assistant:
- Number of Experts: Unspecified number of "Readers".
- Qualifications: "certified sonographer/Clinician" for the readers.

4. Adjudication Method for Test Sets

Auto Renal Measure Assistant:
- Method: A "Board Certified Nephrologist arbitrated the ground truth between the above two readers to establish the reference standard". This implies a 2+1 (two readers, one arbitrator) method.
Auto Abdominal Color Assistant & Auto Preset Assistant:
- Method: The text states, "Readers (certified sonographer/Clinician) to ground truth the 'anatomy' visible in static B-Mode image." There is no mention of multiple readers or an arbitration process, implying no explicit inter-reader adjudication method was described beyond individual expert annotation.

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

No MRMC comparative effectiveness study was explicitly described in the provided text. The studies focus on the standalone performance of the AI algorithms against a derived ground truth, rather than comparing human reader performance with and without AI assistance. Therefore, no effect size for human readers' improvement with AI assistance is reported.

6. Standalone (Algorithm Only) Performance Study

Yes, standalone (algorithm only) performance studies were done for all three AI features listed. The studies evaluate the accuracy or success rate of the AI algorithms in performing their intended functions (measurement, view suggestion) against an established ground truth, without a human-in-the-loop component being explicitly tested or reported.

7. Type of Ground Truth Used

Auto Renal Measure Assistant: Expert Consensus, as it involved two readers and an arbitrator to establish the reference standard for measurements.
Auto Abdominal Color Assistant & Auto Preset Assistant: Expert Annotation/Consensus, established by "Readers (certified sonographer/Clinician) to ground truth the 'anatomy'visible in static B-Mode image." While not explicitly stated as consensus among multiple readers, it is established by qualified experts.

8. Sample Size for Training Sets

The training set sample sizes are not explicitly provided in the summaries for any of the AI features. The document only mentions that the "verification data was acquired independently during validation process after the development of the model," and "The exams used for test/training validation purpose are separated from the ones used during training process." This implies training data existed but its size is not detailed.

9. How Ground Truth for Training Sets Was Established

The document does not explicitly describe how the ground truth for the training sets was established. It focuses primarily on the process for the test/validation sets. However, it can be inferred that a similar process involving expert clinicians/sonographers would have been used to establish ground truth for training data, as is common practice in medical imaging AI development.

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K Number

K211524

Device Name

LOGIQ E10s, LOGIQ Fortis

Manufacturer

GE Healthcare

Date Cleared

2021-08-27

(102 days)

Product Code

Regulation Number

Type

Panel

Reference & Predicate Devices

K200158,K202658,K200119

Intended Use

The LOGIQ E10s and LOGIQ Fortis are general-purpose diagnostic ultrasound systems intended for use by qualified and trained healthcare professionals for ultrasound imaging, measurement, display and analysis of the human body and fluid. LOGIQ E10s and LOGIQ Fortis clinical applications include: Fetal / Obstetrics; Abdominal (including Renal, Gynecology/Pelvic); Pediatric; Small Organ (Breast, Testes, Thyroid); Neonatal Cephalic; Cardiac (Adult and Pediatric); Peripheral Vascular; Musculo- skeletal Conventional and Superficial; Urology (including Prostate); Transrectal; Transvaginal; Transesophageal and Intraoperative (Vascular). Modes of operation include: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Harmonic Imaging, Coded Pulse, 3D/4D Imaging mode, Elastography, Shear Wave Elastography, Attenuation Imaging and Combined modes: B/M, B/Color, B/ PWD, B/Color/PWD, B/Power/PWD. The LOGIQ E10s and LOGIQ Fortis are intended to be used in a hospital or medical clinic.

Device Description

The LOGIQ Fortis is a full featured, Track 3, general purpose diagnostic ultrasound system which consists of a mobile console approximately 575 mm wide (keyboard), 925 mm deep and 1300 mm high that provides digital acquisition, processing and display capability. The user interface includes a digital keyboard (physical keyboard as an option), specialized controls, 12-inch high-resolution color touch screen and 23.8-inch High Contrast LED LCD monitor (or 23.8-inch High Resolution LED LCD monitor as an option).

AI/ML Overview

The provided text is a 510(k) Premarket Notification from the FDA for GE Healthcare's LOGIQ E10s and LOGIQ Fortis diagnostic ultrasound systems. This document primarily focuses on establishing substantial equivalence to a predicate device and does not contain detailed information about specific clinical studies with acceptance criteria, sample sizes, or ground truth establishment in the way typically found for AI/ML-driven medical devices that require such studies for de novo or PMA applications.

Therefore, most of the requested information cannot be extracted from this document as it explicitly states: "The subject of this premarket submission, LOGIQ E10s, LOGIQ Fortis, did not require clinical studies to support substantial equivalence."

However, I can provide available information:

1. Table of acceptance criteria and the reported device performance:

This document does not specify quantitative acceptance criteria or reported device performance in terms of diagnostic accuracy metrics (e.g., sensitivity, specificity, AUC) for clinical applications. Instead, it relies on demonstrating substantial equivalence to a predicate device by comparing intended use, technology, imaging modes, safety, and functionality.

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