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The device is designed to sample targeted submucosal and extraluminal gastrointestinal lesions through the accessory channel of suitable ultrasound videoendoscope in adult patients only.

The proposed Endoscopic Ultrasound Aspiration Needle is a sterile single-use device, designed to sample targeted submucosal and extraluminal gastrointestinal lesions through the accessory channel of suitable ultrasound videoendoscope. The Endoscopic Ultrasound Aspiration Needle consists of an Aspiration Needle and negative suction device. The proposed devices are EO sterilized to achieve the Sterility Assurance Level (SAL) of 10-6 and placed in a sterility maintenance package to ensure a shelf life of 2 years.

The provided text describes a 510(k) summary for a medical device and does not contain information about acceptance criteria, device performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, or training set details for an AI/ML powered device.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device through:

• Comparison of technological characteristics: This involves a table (Table 7.1) comparing various features of the proposed device (Adapt Endoscopic Ultrasound Aspiration Needle) and the predicate device (Endoscopic Ultrasound Aspiration Needle, K172309).
• Performance data (bench testing): A list of bench tests performed to ensure the device works as intended. These tests are:
  • Smooth Actuation of Handle
  • Leakage
  • Ultrasound Visibility
  • Puncture Force
  • Stiffness
  • Durability
  • Stylet Removal Force
  • Locking Force of Handle
  • Tensile Strength
• Shelf-life and packaging integrity testing: Based on accelerated aging and ISO standards.
• Sterilization validation: In accordance with ISO 11135.
• Biocompatibility evaluation: In accordance with ISO 10993-1 and FDA guidance, including tests for Cytotoxicity, Sensitization, Irritation, Acute Systemic Toxicity, Material Mediated Pyrogenicity, and Hemolysis.

The text explicitly states that no animal study and no clinical study were included in the submission. This implies that no human-in-the-loop performance, standalone algorithm performance, or clinical effectiveness data would be available from this document.

Therefore, I cannot fulfill your request for the specific information you asked for, as the provided text pertains to a traditional medical device (an aspiration needle) and its regulatory submission, not an AI/ML powered device with related performance metrics.

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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 looks like a 510(k) summary for a medical device (an aspiration needle), not an AI/ML algorithm. Therefore, many of the requested criteria related to AI/ML software validation (like MRMC studies, training/test set ground truth, expert adjudication, etc.) are not applicable and are not present in the provided text.

The document discusses substantial equivalence to a predicate device, focusing on "technological characteristics" and "performance data" that appear to be related to physical device performance rather than software performance.

Based on the provided text, here's what can be extracted:

• Device: Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle
• Purpose: To sample targeted submucosal and extramural gastrointestinal lesions through an echoendoscope, and for delivery of injectable materials (fluids) or fiducials, or passage of accessory devices.
• Key Change: The only change to the device is an increase in the allowable fiducial marker size that is compatible with the Expect Slimline 22ga Needle, from 0.35mm OD to 0.46mm OD. The physical device itself remains unchanged from its predicate.

Here's an attempt to answer your questions based only on the provided text, noting where information is not present or relevant to this type of device:

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

The document states that "additional performance testing was conducted to evaluate the ability of the device design to support the proposed change" (i.e., increased fiducial size). It also mentions "Bench Testing includes simulated use testing."

However, no specific acceptance criteria values or reported performance metrics (e.g., flow rates, force requirements, successful delivery rates, etc.) are detailed in the provided K173184 summary. The summary simply concludes that "Boston Scientific Corporation has demonstrated that the proposed Expect™ Slimline (SL) is substantially equivalent to the Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle (K163058)." This implies that the performance met the internal criteria used to establish substantial equivalence for the altered fiducial size, but the specifics are not disclosed in this summary.

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

• Sample Size: Not specified. The document only states "Bench testing has been performed on the proposed Expect™ Slimline (SL) device."
• Data Provenance: Not specified. "Bench testing" would typically be conducted in a lab setting, not on patient data from a specific country, and would be prospective in nature (designed and executed tests).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. This is a physical medical device, not an AI/ML system requiring expert interpretation or ground truth establishment in the manner of medical imaging.

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

Not applicable. This is not a study involving human reader interpretation or clinical adjudication.

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/ML device.

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

Not applicable. This is not an AI/ML algorithm.

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

Not applicable. For a physical device, "ground truth" would relate to its physical and functional performance specifications (e.g., successful passage of fiducials of a certain size, structural integrity, ability to aspirate, etc.), which would be verified by engineering tests and measurements, not clinical ground truth in the AI sense.

8. The sample size for the training set

Not applicable. This is not an AI/ML device that requires a training set.

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

Not applicable. This is not an AI/ML device.

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The Endoscopic Ultrasound Aspiration Needle is designed to sample targeted submucosal and extraluminal gastrointestinal lesions through the accessory channel of suitable ultrasound videoendoscope in adult patients only.

The proposed Endoscopic Ultrasound Aspiration Needle is a sterile single-use device, designed to sample targeted submucosal and extraluminal gastrointestinal lesions through the accessory channel of suitable ultrasound videoendoscope.

It consists of three parts, Aspiration Needle, Syringe and Stopcock. The aspiration needle is offered with multiple types with different dimension, needle tip design and needle material. Syringe and stopcock are accessories to provide and control the vacuum suction to aspirate the sample.

There are 12 specifications, the difference is the diameter, material and tip design of needle.

The proposed devices are EO sterilized to achieve the Sterility Assurance Level (SAL) of 10t and placed in a sterility maintenance package to ensure a shelf life of 2 years.

This document is a 510(k) summary for the Endoscopic Ultrasound Aspiration Needle, which is a medical device. It does not contain information about the acceptance criteria or a study proving the device meets performance criteria for an AI/ML powered device. The document focuses on regulatory approval for this specific type of medical device by demonstrating substantial equivalence to predicate devices, not on proving performance through specific metrics associated with AI/ML.

Therefore, I cannot provide the requested information. The document does not describe:

• Acceptance criteria in terms of AI/ML performance metrics (e.g., sensitivity, specificity, AUC).
• A study that proves the device meets such acceptance criteria.
• Sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or ground truth types related to an AI/ML algorithm.
• Training set sample size or how ground truth for a training set was established.

This document describes a traditional medical device approval process based on comparison to existing legally marketed devices, not an AI/ML product.

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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.

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The Expect™ Slimline (SL) Needle is designed to sample targeted submucosal and extramural gastrointestinal lesions through the accessory channel of a curvilinear echoendoscope.

The Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle is an 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 aspiration 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.

This 510(k) summary describes a medical device called the Expect™ Slimline (SL) Endoscopic Ultrasound Aspiration Needle. This submission is for a modified version of an already cleared device, focusing on a new handle design. Therefore, the performance data provided relates to the mechanical and physical characteristics of this new design rather than clinical performance (e.g., diagnostic accuracy or clinical outcomes). The document explicitly states that "Bench Testing has been performed... which demonstrates that the modified handle design met the required specifications for completed design verification tests." This indicates that the acceptance criteria are based on engineering specifications and the study is bench testing.

Here's the information extracted from the provided text, structured according to your request:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• Sample Size for Test Set: Not explicitly stated. The document refers to "Bench Testing" but does not provide details on the number of units tested for each criterion.
• Data Provenance: The study was "Bench Testing" conducted by Boston Scientific Corporation. This is a controlled laboratory environment, not human or animal data.

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. The ground truth for this type of bench testing is based on engineering specifications and objective measurements (e.g., force, length, durability tests) rather than expert interpretation.

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

• Not applicable. This is bench testing against objective engineering specifications, not a subjective assessment requiring adjudication.

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 device is a mechanical medical instrument (an aspiration needle), and the study described is bench testing of its mechanical characteristics. It does not involve AI or human readers for diagnostic interpretation.

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

• Not applicable. This device is a mechanical medical instrument, not an algorithm.

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

• The ground truth for the bench testing was engineering specifications and objective measurements. The device's performance was compared against predetermined design requirements for its mechanical functions.

8. The sample size for the training set:

• Not applicable. This device is a mechanical medical instrument, not a machine learning model requiring a training set. The "design verification tests" are likely derived from historical data and industry standards, but there isn't a "training set" in the AI sense.

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

• Not applicable. As noted above, there is no training set in the context of this device and study. The "ground truth" for the acceptance criteria (required specifications) would have been established through device design processes, engineering standards, and potentially regulatory benchmarks for similar devices.

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The Expect™ EUS-FNA device is intended for sampling targeted submucosal and extramural gastrointestinal lesions through the accessory channel of a curvilinear echoendoscope.

The Expect™ Endoscopic Ultrasound Aspiration Needle (EUS-FNA) is an 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 aspiration 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.

The provided document describes a 510(k) premarket notification for a medical device, the Expect™ Endoscopic Aspiration Needle, and not a study assessing the device's diagnostic performance for an AI/ML product. The document focuses on demonstrating substantial equivalence to a predicate device through bench testing rather than clinical performance data typical of AI/ML software.

Therefore, many of the requested categories in your prompt related to clinical study design, AI/ML performance metrics, ground truth, and expert evaluation cannot be extracted from this document.

Here's an analysis of what can be extracted based on the provided text, and where information is not available:

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

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

• Sample Size for Test Set: Not applicable. This was a bench test of a physical device component, not an AI/ML diagnostic test with a "test set" of clinical data.
• Data Provenance: Not applicable.

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 as typically defined for AI/ML diagnostic studies is not relevant here as it's a bench test of mechanical and material properties.

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

• Not applicable. No expert adjudication process was described for the bench testing.

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

• No. An MRMC study was not conducted as this is a physical medical device, not an AI/ML diagnostic software.

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

• Not applicable. No algorithm is involved.

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

• Not applicable. The "ground truth" for this device's performance relies on engineering specifications and validated test methods for mechanical and material properties (design verification) and biocompatibility, not clinical data or expert consensus on diagnosis.

8. The sample size for the training set

• Not applicable. There is no training set mentioned, as this is not an AI/ML device.

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

• Not applicable. No training set was used.

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The Resound EUS-FNA device is intended for sampling targeted submucosal and extramural gastrointestinal lesions through the accessory channel of a curvilinear echoendoscope.

The Resound Endoscopic Ultrasound Aspiration Needle (EUS-FNA) is an 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 aspiration 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.

The provided text describes a medical device, the Resound™ Endoscopic Ultrasound Aspiration Needle (EUS-FNA), and its 510(k) submission for substantial equivalence. However, the document does not contain information related to specific acceptance criteria, studies proving the device meets those criteria, or details regarding performance data in the structured format requested (e.g., sample sizes, expert qualifications, MRMC studies, ground truth establishment methods).

The "Performance Data" section explicitly states:

• "Bench Testing has been performed on the finished Resound EUS-FNA device to demonstrate that the proposed device is substantially equivalent to the predicate devices."

This indicates that the main type of study conducted was bench testing (physical and/or mechanical testing), not clinical performance studies involving human subjects or AI algorithms, which are typically where the detailed performance metrics, sample sizes, and expert adjudications mentioned in your request would originate.

The submission focuses on demonstrating substantial equivalence to predicate devices (Wilson-Cook EchoTip Ultrasound Needle and Olympus Single-Use Aspiration Needle) based on technological characteristics and bench testing, rather than establishing specific clinical performance metrics against a defined set of acceptance criteria.

Therefore, I cannot provide the requested information from the given text because it is not present. The document focuses on regulatory approval through substantial equivalence, which often relies on non-clinical data for devices of this type (biopsy needles used for aspiration).

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