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The MAMBA and MAMBA Flex Microcatheters are intended to provide support to facilitate the placement of guidewires in the coronary vasculature, and can be used to exchange one guidewire for another. The microcatheters are also intended to assist in the delivery of contrast media into the coronary vasculature.

The MAMBA™ and MAMBA™ Flex devices (referred to as the "MAMBA Microcatheters") are designed to provide a platform for the user to exchange quidewires without losing their position in the vasculature.

The MAMBA device is available in a 135cm length, while MAMBA Flex is available in 135cm and 150cm lengths.

The MAMBA Flex models have a smaller outer diameter and a more flexible distal portion than the MAMBA device.

Marks on the proximal portion of the catheter shaft and a radiopaque marker at the distal tip facilitate placement of the device.

The device's inner lumen permits the use of 0.014 in./0.36 mm or smaller quidewires. The shaft consists of a coil which allows the device to be torqued to assist in advancement. The distal portion of the shaft is coated hydrophilic coating to assist in advancement.

The proximal end has a single luer hub for flushing or injecting through the inner lumen and is for guide wire lumen access during a guidewire exchange.

The MAMBA Microcatheters are to be used in patients where vessel conditions require additional wire support to reach the lesion and will deliver radiopaque media and therapeutic agents to selected sites in coronary vasculature.

The provided text is a 510(k) Premarket Notification from the FDA regarding the Boston Scientific MAMBA and MAMBA Flex Microcatheters. This document specifically focuses on the substantial equivalence of these microcatheters to a legally marketed predicate device (MAMBA Microcatheters, K171452).

The information provided does not describe a study proving the device meets acceptance criteria in the context of an AI/ML medical device, particularly one involving ground truth derived from expert consensus, pathology, or outcomes data. It also does not involve human readers, multi-reader multi-case (MRMC) studies, or standalone algorithm performance. This document is for a physical medical device (microcatheter), not a software or AI-driven diagnostic tool.

Therefore, many of the requested categories are not applicable to the content provided. I will fill in the relevant information based on the document's content, and specify "Not Applicable" or explain why the information isn't present for the other categories.

Acceptance Criteria and Device Performance for MAMBA and MAMBA Flex Microcatheters

The FDA 510(k) summary for the Boston Scientific MAMBA and MAMBA Flex Microcatheters describes non-clinical performance data to establish substantial equivalence to a predicate device. The "acceptance criteria" here refer to the performance benchmarks that the new device had to meet during bench testing to demonstrate that it is as safe and effective as the predicate.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states "The results of these tests provide reasonable assurance that the proposed device has been designed and tested to assure conformance to the requirements for its intended use" and "No new safety or performance issues were raised during the testing." While specific numerical performance values are not provided in this summary, the implication is that the new device met the pre-defined acceptance thresholds for each test.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: The document does not specify the exact number of units or tests performed for each bench test. It generically states "Bench testing was performed."
• Data Provenance: The data is from non-clinical bench testing conducted by Boston Scientific Corporation. The country of origin for the testing is not specified, but the company is U.S.-based. This is retrospective data in the sense that it was conducted prior to the 510(k) submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts

• Not Applicable. This is a physical medical device. The "ground truth" and "performance" are established through engineering specifications, material science, and mechanical bench testing, not through expert human review of diagnostic images or clinical outcomes in the same way an AI/ML device would be evaluated. The "experts" involved would be engineers, QA personnel, and potentially biomaterials scientists.

4. Adjudication Method for the Test Set

• Not Applicable. As described above, this is about physical device performance rather than interpretation or classification that would require adjudication among multiple human reviewers. Test results are likely objectively measured (e.g., burst pressure, force to kink).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. This type of study (MRMC) is relevant for diagnostic imaging AI/ML devices where the AI assists human readers. This document describes a physical medical device.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done

• Not Applicable. This is a physical medical device, not a software algorithm.

7. The Type of Ground Truth Used

• The "ground truth" for this device's performance is established by engineering specifications, material properties, and pre-defined performance thresholds for physical and mechanical characteristics (e.g., dimensional accuracy, burst strength, flexibility, torqueability, guidewire exchange efficiency). It is based on objective, quantifiable measures of the device's physical attributes and functional capabilities as designed and manufactured.

8. The Sample Size for the Training Set

• Not Applicable. This document describes a physical medical device, not an AI/ML algorithm that requires a training set. The "training" for such a device largely refers to its design, material selection, and manufacturing processes, which are informed by engineering principles and previous device experience.

9. How the Ground Truth for the Training Set was Established

• Not Applicable. As per point 8, there is no "training set" in the context of an AI/ML algorithm for this physical device. The design and development of the microcatheters are based on established engineering principles, industry standards for medical devices, and performance requirements derived from extensive experience with similar predicate devices. The "ground truth" in this context would be the successful performance of existing, legally marketed devices that serve as benchmarks.

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