(182 days)
The SQNOLINE Elegra ultrasound imaging system is intended for the following applications: General Radiology, Abdominal, Intraoperative, Small Parts, Transcranial, OB/GYN, Pelvic, Neonatal/Adult Cephalic, Urology, Vascular, Musculoskeletal. Superficial Musculoskeletal, and Peripheral Vascular applications. The addition of contrast agent imaging will not add any new applications or intended uses.
The system also provides for the measurement of anatomical structures and for analysis packages that provide information that is used for clinical diagnosis purposes.
The SONOLINE Elegra is a general purpose, mobile, software-controlled, diagnostic ultrasound system with an on-screen display for thermal and mechanical indices related to potential bioeffect mechanisms. Its function is to acquire ultrasound data and display it in B-Mode, M-Mode, Color Mode, Pulsed (PW) Doppler Mode, Continuous (CW) Doppler Mode, or in a combination of modes, on a CRT display.
The Siemens SONOLINE Elegra diagnostic ultrasound system, with the addition of Contrast Agent Imaging (CAI), did not involve specific acceptance criteria and performance data like a typical AI/ML medical device. This 510(k) submission (K981528) focuses on demonstrating substantial equivalence to a predicate device for an updated functionality (CAI and Harmonic Imaging) on an existing ultrasound system.
Therefore, many of the requested elements for AI/ML device studies are not applicable to this submission.
Here's a breakdown of what can be extracted and why other parts are not available:
1. A table of acceptance criteria and the reported device performance
This information is not provided in the 510(k) summary. For a traditional medical device like an ultrasound system, the "acceptance criteria" are typically related to meeting performance standards specified by the FDA (e.g., image quality, safety, acoustic output levels) rather than statistical performance metrics like sensitivity/specificity for a diagnostic AI algorithm. The 510(k) process focuses on demonstrating equivalence to a legally marketed predicate device.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable. This device is an imaging system, not an AI/ML algorithm that processes data for diagnostic output based on a test set of cases. The "testing" for such a system would involve validating its functionality and safety according to engineering and performance specifications, likely using phantoms and potentially clinical images, but not in the format of a "test set" for diagnostic performance validation.
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. Ground truth establishment for a test set of diagnostic cases is relevant for AI/ML devices, not for the core functionality of an ultrasound imaging system in this context.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. This pertains to AI/ML diagnostic performance evaluation.
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, but rather an imaging system with an enhanced imaging mode (Contrast Agent Imaging). The submission does not describe a MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not a standalone algorithm; it's a feature integrated into an ultrasound system, used by a human operator.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable. Ground truth for diagnostic performance is not the focus of this submission. The "ground truth" for an ultrasound system's performance typically refers to physical measurements and imaging of known structures (e.g., phantoms) to verify image quality and system accuracy.
8. The sample size for the training set
Not applicable. This refers to AI/ML model training data.
9. How the ground truth for the training set was established
Not applicable. This refers to AI/ML model training data.
Summary of the Study and Device Information Provided (relevant to the 510(k) submission):
Device Name: SONOLINE Elegra Advanced / SONOLINE Elegra Diagnostic Ultrasound system (with Addition of Contrast Agent Imaging)
Study/Evaluation: The submission is a 510(k) Premarket Notification to demonstrate substantial equivalence to predicate devices for the addition of Contrast Agent Imaging (CAI) and Harmonic Imaging to an existing ultrasound system.
Predicate Devices:
- Acuson Sequoia™ Ultrasound System and Harmonic Imaging with Contrast Option (K973767, 12/23/97)
- SONOLINE Elegra (K945072, 11/21/95)
Technological Comparison (indicating how it meets implicit "acceptance criteria" for substantial equivalence):
The document states that both the SONOLINE Elegra and the predicate Acuson system are "full-featured, high-end diagnostic ultrasound systems capable of B-mode, M-mode, CW Doppler, Color Doppler, Amplitude Doppler, and combined imaging modes utilizing a number of transducers with varying center frequencies."
Crucially, "Both systems are modified to optimize images obtained with the use of diagnostic ultrasound and ultrasound contrast agents. Both systems employ modified transmit/receive functions which allow for enhanced imaging of tissues and structures which reflect the transmitted ultrasound at a harmonic, or multiple, of the transmit frequency."
This direct comparison of technological features and functions demonstrates that the new functionality of the SONOLINE Elegra (Contrast Agent Imaging and Harmonic Imaging) is substantially equivalent to that already cleared in a predicate device (Acuson Sequoia). The "acceptance criteria" here are essentially meeting the safety and efficacy profiles of the predicate device.
Safety Standards Endorsed:
The SONOLINE Elegra is designed to meet several safety standards, which implicitly serve as acceptance criteria for its overall operation:
- UL 2601-1. Safety Requirements for Medical Equipment
- CSA 22.2 No. 601-1, Safety Requirements for Medical Equipment
- Standard for Real Time Display of Thermal and Mechanical Indices on Diagnostic Ultrasound Equipment, AIUM/NEMA, 1992.
- 93/42/EEC Medical Devices Directive EN60601 = (IEC 601-1+ IEC 601-1-2). Safety and EMC Requirements for Medical Equipment
Post-Clearance Requirement:
The FDA's clearance letter includes a condition that the manufacturer submit a post-clearance special report with "complete information, including acoustic output measurements based on production line devices." This indicates that safety (specifically acoustic output) is a key performance metric that must be continuously met, acting as an ongoing acceptance criterion.
This submission is a regulatory filing for an incremental upgrade to an existing ultrasound system, focusing on equivalence rather than detailed performance metrics for a novel diagnostic accuracy claim.
§ 892.1560 Ultrasonic pulsed echo imaging system.
(a)
Identification. An ultrasonic pulsed echo imaging system is a device intended to project a pulsed sound beam into body tissue to determine the depth or location of the tissue interfaces and to measure the duration of an acoustic pulse from the transmitter to the tissue interface and back to the receiver. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II (special controls). A biopsy needle guide kit intended for use with an ultrasonic pulsed echo imaging system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.