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510(k) Data Aggregation
(125 days)
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.
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).
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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(102 days)
The LOGIQ e is a general purpose diagnostic ultrasound system for use by qualified and trained healthcare professionals for ultrasound imaging, measurement, display and analysis of the human body and fluid.
LOGIQ e is intended to be used in a hospital or medical clinic.
LOGIQ e clinical application include: Ophthalmic, fetal/ob; abdominal (gyn & urology); pediatric; small organ (breast, testes, thyroid); neonatal and adult cephalic; cardiac (adult & pediatric); peripheral vascular; musculoskeletal conventional & superficial; transrectal; transvaginal; transesophageal; intraoperative (abdominal, thoracic and peripheral); thoracic/pleural for motion and fluid detection and imaging guidance of interventional procedures (e.g. Nerve block; vascular access). Mode of operation include: B, M, PW Doppler, CW Doppler, Color Doppler, Color M Doppler, Power Doppler, Harmonic Imaging, Coded Pulse and Combined modes: B/M, B/PWD, B/Color/PWD, B/Power/PWD.
The proposed LOGIQ e system is a general-purpose, Track 3, diagnostic ultrasound device, intended for ultrasound imaging, measurement, display and analysis of the human body and fluid.
It is an ultrasound imaging & analysis system, consisting of a compact console with LCD, and control panel with new keyboard.
The system has digital acquisition, processing and display capability and operates from an integrated battery or AC/DC power adapter. It has one battery pack as standard configuration and also with an optional battery pack to be provided for additional power for longer scanning time.
The system also has an optional height-adjustable cart for comfortable standing and sitting positions. The cart is approx. 510mm length, 510mm width and adjustable height from 830 to 1130mm with optional battery box consisting of a charger box and 4pcs battery Packs to supply the system power from the cart.
LOGIQ e utilizes a variety of electronic array transducers operating in linear, curved, sector/phased array, TEE.
The system includes electronics for transmit and receive of ultrasound data, ultrasound signal processing, software computing, hardware for image storage, printing, and network access to the facility through both LAN and wireless (supported by use of a wireless LAN USB-adapter) connection.
The system supports electronic delivery of software. The system allows the user, in addition to service personnel, to update the SW by logging into a GEHC website to download SW available to them and install it on the system. Download from the GEHC website requires an account.
The provided text does NOT contain information about acceptance criteria or a study proving that an AI device meets acceptance criteria. The document is a 510(k) premarket notification for a GE Medical Systems Ultrasound device, the LOGIQ e. It primarily focuses on demonstrating substantial equivalence to a predicate device and other reference devices, not on the performance of a new AI-powered feature with specific acceptance criteria.
The document discusses:
- Device Name: LOGIQ e
- Regulation Number/Name: 21 CFR 892.1550, Ultrasonic Pulsed Doppler Imaging System
- Regulatory Class: Class II
- Product Codes: IYN, IYO, ITX
- Indications for Use: General purpose diagnostic ultrasound for various clinical applications.
- Predicate Device: LOGIQ e (K151028)
- Reference Devices: Vivid iq (K221148), Versana Premier (K210438), Venue Go (K202233)
- Changes/Additions: New transducers, software features (AutoEF, Scan assistant, Strain Elastography, Probe check, Imaging Insights, Tricefy Uplink), hardware (new industrial design, secondary battery option, thermal solution), and accessories.
- Non-Clinical Tests: Acoustic output, biocompatibility, cleaning/disinfection, thermal, electromagnetic, and mechanical safety, compliance with various IEC, ISO, AAMI, and NEMA standards. Quality assurance measures like risk analysis, design reviews, and testing are mentioned.
- Clinical Tests: The document explicitly states: "The subject of this premarket submission, LOGIQ e, did not require clinical studies to support substantial equivalence."
Therefore, I cannot provide the requested information regarding acceptance criteria, device performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth for the test and training sets, as these details are not present in the provided context. The submission is for a general diagnostic ultrasound system and not for a specific AI algorithm with performance metrics.
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