Search Results

The Expect™ Slimline (SL) Needle is designed to sample targeted submucosal and extramural gastrointestinal lesions through the accessory channel of a curvilinear echoendoscope. It can also be used for delivery of injectable materials (fluids) or fiducials into tissue or for passage of accessory devices.

The Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle is and endoscopic ultrasound aspiration needle that can be coupled to the biopsy channel of a Curvilinear Array (CLA) Echoendoscope with a standard luer connection and delivered into the digestive tract. The needle is used to acquire samples from lesions within and adjacent to the digestive system's major lumens that can be identified and targeted using the echoendoscope. An aspiration sample is obtained by penetrating the lesion with the needle while applying suction. Per manufacturer's instructions, the Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle can also be used for delivery of injectable materials (fluids) or fiducials into tissue or for passage of accessory devices.

This document is a 510(k) summary for the Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a study report for the device's performance.

Therefore, much of the requested information regarding acceptance criteria, specific study details, and AI-related aspects (like MRMC studies) is not present in the provided text. The document refers to "bench testing" but does not provide details about its acceptance criteria or results.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Cannot be provided. The document states that "additional performance criteria were introduced to evaluate the ability of the device design to support the proposed indications for use" and lists "Bench Testing" including "Simulated Use Test Method" and "Fluid Injection Capability." However, it does not provide the specific acceptance criteria for these tests or the quantitative results of the device's performance against those criteria.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cannot be provided. The document mentions "Bench testing" but does not specify the sample sizes used for these tests, nor does it provide information on data provenance (country, retrospective/prospective).

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 / Cannot be provided. This device is an aspiration needle, not an interpretive AI system. The concept of "experts establishing ground truth for a test set" with qualifications like "radiologist with 10 years of experience" is relevant for diagnostic imaging AI studies, but not for the mechanical performance testing of an aspiration needle described here.

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

• Not applicable / Cannot be provided. Similar to point 3, adjudication methods (like 2+1, 3+1 consensus) are typically used in studies involving human interpretation or decision-making, especially in evaluating diagnostic AI. This is not mentioned or implied for the bench testing of an aspiration needle.

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 / Cannot be provided. The device is an endoscopic ultrasound aspiration needle, not an AI system or an AI-assisted diagnostic tool. Therefore, an MRMC comparative effectiveness study comparing human readers with and without AI assistance is irrelevant to this device.

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

• Not applicable / Cannot be provided. This device is a physical medical instrument, not an algorithm or AI.

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

• Not applicable / Cannot be provided. For the bench testing of an aspiration needle, "ground truth" would likely refer to objective measurements of physical properties (e.g., needle tip sharpness, material strength, fluid flow rate, penetration force) against engineering specifications, rather than clinical "expert consensus, pathology, or outcomes data." The document does not specify these objective measurements or criteria.

8. The sample size for the training set

• Not applicable / Cannot be provided. The concept of a "training set" specifically refers to data used to train machine learning models. This document describes a physical medical device, not an AI model, so a training set as typically understood in AI is not relevant.

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

• Not applicable / Cannot be provided. See point 8.

Ask a specific question about this device