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The device is a general-purpose ultrasonic imstrument intended for use by a qualified clinician for evaluation of Fetal , Abdominal, Pediatric, Small Organ (breast, thyroid,testes ), Neonatal Cephalic, Cardiac (adult , pediatric),Musculo-skeletal (Conventional , Superficial) ,Peripheral Vascular,Trans-esophageal,Trans-rectal, Trans-vaginal, OB/GYN and Urology.

The CBit Series Digital Color Doppler Ultrasound System is an integrated preprogrammed color doppler ultrasound imaging system, capable of producing high detail resolution intended for clinical diagnostic imaging applications. This system is a Track 3 device that employs a wide array of probes that include linear array, convex array and phased array . This system consists of a mobile console with keyboard control panel, power supply module, color LCD monitor and optional probes. This system is a mobile, general purpose, software controlled, color diagnostic ultrasound system. Its basic function is to acquire ultrasound echo data and to display the image B-Mode (including Fusion Harmonic Imaging). M-Mode, Pulsed (PW) Doppler Mode, Continuous (CW) Doppler Mode, Color Doppler Mode, Power Doppler Mode, Directional Power Doppler Mode, TDI Mode or a combination of these modes, Elastography, 3D/4D.

The provided text is a 510(k) Summary for the CHISON CBit Series Digital Color Doppler Ultrasound System. It describes the device, its intended use, non-clinical tests conducted, and a comparison to predicate devices to establish substantial equivalence. However, it does not contain a study that proves the device meets specific acceptance criteria in terms of quantitative performance metrics for AI algorithms. Instead, the document focuses on regulatory compliance and substantial equivalence to previously cleared devices.

Therefore, many of the requested details about acceptance criteria, their proof, and study specifics for AI performance cannot be extracted from this document as it does not describe such a study.

Here's a breakdown of what can be extracted:

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria with reported device performance in terms of AI algorithm accuracy, sensitivity, specificity, or other quantitative metrics. The "acceptance criteria" presented are primarily regulatory compliance standards and substantial equivalence to predicate devices, rather than performance benchmarks for AI features.

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. The document explicitly states: "No clinical testing was required." Therefore, there is no test set for AI performance, sample size, or data provenance mentioned.

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, as no clinical testing and no test set with ground truth establishment for AI performance is described.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable, as no clinical testing and no test set with ground truth establishment for AI performance is described.

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. No MRMC study involving AI assistance is mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Not applicable. The document does not describe a standalone AI algorithm performance study. The device is a diagnostic ultrasound system with several operating modes and features, some of which are likely enhanced by AI (features like "Auto IMT," "Auto NT," "Stress Echo," "Strain," "Q-Image," "Q-flow," "Q-beam," "AIO," and "LV tracking" hint at AI analysis or automation), but no specific standalone performance metrics for these AI components are provided.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

Not applicable, as no clinical testing with ground truth establishment for AI performance is described.

8. The sample size for the training set

Not applicable. The document does not describe the development or training of any AI algorithms, therefore no training set sample size is provided.

9. How the ground truth for the training set was established

Not applicable, as no training set or its ground truth establishment is mentioned.

Summary of Device Features and Non-Clinical Tests (as presented in the document):

The CHISON CBit Series Digital Color Doppler Ultrasound System is a general-purpose ultrasonic imaging instrument. It is noted to include features like "Elastography," "3D/4D," "TDI Mode," "Auto IMT," "Stress Echo," "Strain," "Q-Image," "Q-flow," "Q-beam," "AIO," and "LV tracking," which often imply some level of algorithmic or AI-assisted processing.

The study presented focuses on non-clinical tests to ensure safety and performance equivalence to predicate devices. These tests evaluated:

• Electrical safety (according to IEC 60601-1: 2005)
• Electromagnetic compatibility (according to IEC 60601-1-2: 2014)
• Basic safety and essential performance of ultrasonic medical diagnostic equipment (according to IEC 60601-2-37: 2007)
• Acoustic output measurements (according to NEMA UD 2:2004)
• Real-time display of thermal and mechanical acoustic output indices (according to NEMA UD3: 2004)
• Biocompatibility (according to ISO 10993-1:2009, ISO 10993-5, ISO 10993-10)
• Software Documentation for a Moderate Level of Concern.

The document states that "The device has been found to conform to applicable medical device safety standards in regards to thermal, mechanical and electrical safety as well as biocompatibility."

The "Substantially Equivalent Conclusion" is reached based on:

• Favorable comparison of Indications for Use with predicate devices.
• Similar operation modes and controls (with some differences in value range, or additional features like LV tracking, LGC, Breast measurement package, which are deemed not to raise new safety or effectiveness concerns as they align with existing functionalities or general measurement packages of predicate devices).
• Compliance with the same safety standards as predicate devices.

The document does not detail any performance studies that would typically involve specific acceptance criteria for AI algorithm performance or metrics derived from clinical data. The focus is on regulatory equivalence concerning the device's overall functionality and safety, not on specific AI performance evaluation against ground truth data.

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