(35 days)
Esaote 7400, MyLabOmega, is a compact portable system intended to perform diagnostic general ultrasound studies including: Fetal, Abdominal, Intraoperative (Abdominal), Laparoscopic, Pediatric, Small organs, Neonatal, Neonatal Cephalic, Adult Cephalic, Transvaginal, Musculoskeletal (Conventional), Musculoskeletal (Superficial), Urological, Cardiovascular Adult, Cardiovascular Pediatric, Transoesophageal (cardiac), Peripheral Vessel.
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 be connected to mechanical and electronic ultrasound probes (convex array, linear array and phased array) and Doppler probes.
The upgraded 7400 system (MyLabOmega) is portable systems equipped with a handle. The system sizes and weights allow them to be carried using its handle. 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 7400 manages Qualitative Elastosonography. 7400 is equipped with a LCD color display where acquired images and advanced image features are shown. 7400 can drive Phased, Convex, Linear array, Doppler probes and Volumetric probes (Bi-Scan probes). On both models the touchscreen has an emulation of the Qwerty alphanumeric keyboard that allows data entry. 7400 model is equipped with wireless capability and has been designed to be powered by battery.
The upgraded 7400 system, defined herein, combines the cleared features of both the 6440 and 7400 systems with new capabilities, listed below:
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- Addition of Auto NT option.
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- Addition of MicroV option.
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- Addition of Qpack option.
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- Management of probe P 1-5.
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- Management of probe L 4-15
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- Addition of 4D Stic option.
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- Addition of Full screen option.
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- Operative system Windows 10
The provided text details a 510(k) premarket notification for the Esaote 7400 Ultrasound System, not an AI/ML medical device. Therefore, the traditional acceptance criteria and study designs typically associated with proving the performance of AI/ML devices (e.g., specific metrics like sensitivity/specificity, sample sizes for test/training sets, expert ground truth establishment, MRMC studies) are not applicable here.
The 510(k) submission for the Esaote 7400 Ultrasound System (K190447) focuses on demonstrating substantial equivalence to previously cleared predicate devices, primarily through technological characteristics and adherence to established medical device safety and performance standards.
Here's how the provided information relates to the request, reinterpreting "acceptance criteria" and "study" in the context of a traditional medical device 510(k):
1. A table of acceptance criteria and the reported device performance:
In the context of a 510(k) for a conventional ultrasound system, the "acceptance criteria" are compliance with relevant safety and performance standards, and demonstrating that the new device's technological characteristics are substantially equivalent to the predicate. Device performance is typically proven through a suite of non-clinical tests.
| Acceptance Criteria (in 510(k) Context) | Reported Device Performance (as per submission) |
|---|---|
| Safety and Performance Standards Compliance: | The upgraded 7400 (MyLabOmega) system has been evaluated for: |
- Acoustic output
- Biocompatibility
- Cleaning and disinfection effectiveness
- Thermal, electrical, electromagnetic, and mechanical safety
And found to conform to: - IEC 60601-1
- IEC 60601-1-2
- IEC 60601-2-37
- NEMA UD-3 (Standard for Real Time Display of Thermal and Mechanical Acoustic Output Indices on Diagnostic Ultrasound Equipment)
- NEMA UD-2 (Acoustic Output Measurement Standard for Diagnostic Ultrasound) |
| Technological Equivalence to Predicate Devices: | The 7400 upgrade employs the same fundamental technological characteristics as its predicate devices. - The upgraded system is substantially equivalent to Esaote 7400 (cleared via K111302 and K161359).
- Clinical uses from Esaote 7400 (K142008) and Esaote 6440 (K173291) are unchanged.
- Specific new features (Auto NT, Auto EF, Qpack, probes L 4-15 and P 1-5 management, Full screen mode, Windows 10 OS) are identical to those already cleared on the Esaote 6440 (K173291). |
| Manufacturing Quality System: | The 7400 new version is manufactured under an ISO 9001 and ISO 13485 certified quality system. |
2. Sample size used for the test set and the data provenance:
For this type of device (ultrasound system), the "test set" is not a dataset of images for an algorithm, but rather the device itself undergoing a series of engineering and performance verification tests. The document does not specify a "sample size" in the conventional sense of patient data.
- Test Sample Size: Not applicable in the context of an AI/ML algorithm. The "sample" is the physical device being tested against engineering specifications and regulatory standards.
- Data Provenance: Not applicable for an AI/ML algorithm test set. The data presented are engineering test results and compliance assessments. The document mentions previous clearances (K111302, K132231, K132466, K142008, K161359, K173291), indicating an iterative development and clearance process, but not specifically data provenance for an algorithm. This is a submission for a hardware system update.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts/Qualifications for Ground Truth: Not applicable. Ground truth, in the context of AI/ML, refers to expert-labeled data used to train and validate models. For a conventional ultrasound system, performance is assessed through objective engineering measurements and compliance testing, not through expert reading of images in a studies designed for AI model evaluation.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Adjudication Method: Not applicable. This concept belongs to the evaluation of AI/ML algorithms where multiple readers might disagree on a diagnosis, requiring an adjudication process to establish definitive ground truth. For an ultrasound system, performance is assessed against technical specifications and established standards, which don't typically involve reader adjudication.
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:
- MRMC Study: No, an MRMC study was not done, and it's not relevant for this type of device submission. This study design is specifically for evaluating the impact of AI on human reader performance. This submission is for the ultrasound system itself, not an integrated AI-powered diagnostic tool requiring such a study for its regulatory clearance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Standalone Performance: Not applicable. The device is an ultrasound system, which is inherently a human-in-the-loop diagnostic tool. The document does not describe any "algorithm only" component being evaluated in a standalone manner. The "options" mentioned (Auto NT, MicroV, Qpack, 4D Stic) are features of the ultrasound system, not independent AI algorithms with their own performance metrics being evaluated in isolation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Type of Ground Truth: Not applicable in the AI/ML sense. The "ground truth" for this device's performance is compliance with international and national safety and performance standards (e.g., IEC, NEMA) and demonstrating that its technological changes do not raise new questions of safety or effectiveness compared to predicate devices. This involves objective engineering measurements and verification, not diagnostic ground truth from medical cases.
8. The sample size for the training set:
- Training Set Sample Size: Not applicable. This refers to the data used to train an AI/ML model, which is not the subject of this 510(k) submission.
9. How the ground truth for the training set was established:
- Training Set Ground Truth Establishment: Not applicable, as there is no mention of an AI/ML training set in the provided document.
In summary: The provided document is a 510(k) premarket notification for a diagnostic ultrasound system, not an AI/ML medical device. Therefore, the criteria and study types requested in the prompt, which are standard for AI/ML device evaluations (e.g., test sets, training sets, ground truth, MRMC studies), are not present or applicable here. The focus of this 510(k) is on demonstrating substantial equivalence to predicate devices and adherence to established safety and performance standards for ultrasound equipment through non-clinical (engineering) testing.
§ 892.1550 Ultrasonic pulsed doppler imaging system.
(a)
Identification. An ultrasonic pulsed doppler imaging system is a device that combines the features of continuous wave doppler-effect technology with pulsed-echo effect technology and is intended to determine stationary body tissue characteristics, such as depth or location of tissue interfaces or dynamic tissue characteristics such as velocity of blood or tissue motion. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.