(187 days)
The Diagnostic Ultrasound System Aplio a550 Model CUS-AA550, Aplio a450 Model CUSAA450 and Aplio a Model CUS-AA000 is indicated for the visualization of structures, and dynamic processes with the human body using ultrasound and to provide image information for diagnosis in the following clinical applications: fetal, abdominal, intra-operative (abdominal), pediatric, small organs (including thyroid, breast, testicle), trans-vaginal, trans-rectal, neonatal cephalic, adult cephalic, cardiac (both adult and pediatric), peripheral vascular, transesophageal, musculo-skeletal (both conventional and superficial), laparoscopic and thoracic/pleural.
This system provides high-quality ultrasound images in the following modes of operation: B (2D), M, Color Doppler (blood-flow imaging), Doppler (PWD, Power) (blood-flow spectrum), Combined (B/M; B/PWD; BDF/PWD; BDF/MDF; BDF/MDF/PWD; 2D/CWD; BDF/CWD), Precision lmaging, Apli Pure, Micro Pure, BEAM, TDI, Shear wave, Elastography, SMI (ADF), 2D Wall Motion Tracking, Smart 3D, Smart Sensor3D, 3D Color (Volume color), 4D, STIC, STIC Color, Fusion, Smart Navigation, ATI, CHI (Per FDA approved contrast agent prescribing information), Shadow Glass. This system is suitable for use in hospital and clinical settings by physicians or legally qualified persons who have received the appropriate training.
The Aplio a550 Model CUS-AA550, Aplio a450 Model CUS-AA450, and Aplio a Model CUS-AA000, V6.5 are mobile diagnostic ultrasound systems. These systems are Track 3 devices that employ a wide array of probes including flat linear array, convex linear array, and sector array with frequency ranges between approximately 2MHz to 20 MHz.
This document describes the premarket notification for the Aplio a550, Aplio a450, and Aplio a Diagnostic Ultrasound System, Software V6.5 (K212960).
The provided information focuses on substantial equivalence to a predicate device (Aplio a550, Aplio a450, and Aplio a, V5.1, K202364) and improvements to existing features. Crucially, the document states: "No clinical studies were required to demonstrate safety and efficacy of the Aplio a550, and Aplio a, V6.5 system." This implies that formal acceptance criteria with reported device performance based on a new clinical study are not directly applicable in the traditional sense for this submission as a standalone device.
However, the document does mention "Additional performance testing, using phantoms and volunteer data, were conducted in order to demonstrate that the requirements for the improved features were met." It also discusses the expansion of marketing language for features supported by Artificial Intelligence (AI) and Machine Learning (ML), such as "2D Wall Motion Tracking for left ventricle (2D WMT) and Auto Ejection Fraction for left ventricle (Auto EF), marketed by Canon as 2D WMT with Full-assist function and Auto EF with Full-assist function."
Given the information provided, it's not possible to extract specific acceptance criteria and detailed device performance metrics from a dedicated clinical study for this 510(k) submission. The substantial equivalence argument relies on the predicate device's existing clearance and improvements to its features, with performance demonstrated through technical testing rather than a new clinical trial with pre-defined acceptance criteria.
Therefore, the following points address the questions based on the available text:
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A table of acceptance criteria and the reported device performance:
- This information is not provided in the document as part of a formal clinical study with pre-defined acceptance criteria for the new submission. The submission is based on demonstrating substantial equivalence to a predicate device and showing improvements through technical testing.
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Sample size used for the test set and the data provenance:
- The document mentions "additional performance testing, using phantoms and volunteer data." However, the specific sample size (number of phantoms or volunteers) and the provenance of this data are not provided in the document.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This information is not provided in the document. As no clinical study is explicitly described for establishing ground truth, the involvement of experts for this purpose is not mentioned.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- This information is not provided in the document.
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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:
- An MRMC comparative effectiveness study is not explicitly mentioned as being performed for this submission. While the document talks about "promotion of the support by artificial intelligence (AI) and/or machine learning (ML) of the automated initial contour tracing capability of 2D Wall Motion Tracking for left ventricle (2D WMT) and Auto Ejection Fraction for left ventricle (Auto EF)," it does not detail a study demonstrating the effect size of human reader improvement with AI assistance. The AI/ML aspects are presented as improvements to existing functionalities rather than a new comparative effectiveness claim requiring an MRMC study in this context.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The document implies that AI/ML capabilities are for "automated initial contour tracing" and "Auto Ejection Fraction." While this suggests algorithmic performance, the document does not present a standalone performance study with specific metrics for the algorithm only. The context is generally about supporting existing features.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The type of ground truth used for "additional performance testing, using phantoms and volunteer data" is not explicitly stated. For phantom data, the "ground truth" would typically be derived from the known properties of the phantom. For volunteer data, it is not specified how ground truth was established, particularly for the AI/ML features in question.
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The sample size for the training set:
- The document does not provide information regarding the sample size for any training set used for the AI/ML features mentioned.
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How the ground truth for the training set was established:
- The document does not provide information on how ground truth was established for any training set.
§ 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.