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Vesair Cystoscopes are indicated to provide the user with the means for endoscopic diagnostic and therapeutic surgical procedures. Examples for the devices include the visualization and manipulation of anatomy as the surgeon deems appropriate. Vesair Cystoscopes are intended to be used in general urological surgery through a minimally invasive approach by utilizing natural orifices to access the surgical site.

The Vesair Cystoscopes described in this submission are rigid reusable endoscopes for visualization of the operating site during cystoscopic minimally invasive procedures in conjunction with a commercially available light guide, light source, video camera, monitor, and printer. Light that is created by an external light source is transmitted from the endoscope's light guide connector through the endoscope itself to the tip via a fiber optic system. Images are transferred the other way back through a rigid lens system.

Technical parameters of the Vesair Cystoscopes that characterize the optical view are the Direction of View (0°, 30°, 70°) and the Field of View (105°). The image can be displayed by a camera/monitor system which can be connected to the endoscope eyepiece. The Vesair Cystoscopes have the same diameter (4mm), and are available in different lengths of the insertion tube (0° - 280mm length, 30° - 185mm or 278mm length, 70° - 185mm or 281mm length). None of the cystoscope models have a working channel. Like other currently marketed rigid cystoscopes, all models have patient-contacting outer surfaces mainly made from metal (304 stainless steel) and incorporate fiber optics for light transmission and rigid lenses for image transmission.

Each cystoscope model is provided non-sterile and requires cleaning and steam sterilization prior to use and between subsequent uses.

The provided text describes the Vesair Cystoscopes, which are rigid reusable endoscopes, and details their comparison to predicate and reference devices for a 510(k) submission. However, it does not describe an AI/ML device or a study that establishes ground truth through expert consensus, pathology, or outcomes data, nor does it include information on a multi-reader multi-case (MRMC) comparative effectiveness study, standalone algorithm performance, or training set details.

Therefore, most of the requested information regarding AI device acceptance criteria and study details cannot be extracted from this document.

The document focuses on demonstrating substantial equivalence to legally marketed predicate devices based on technological characteristics and performance testing relevant to an endoscope, not an AI/ML system.

Here's a breakdown of what can be extracted and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" in the context of an AI/ML device's performance metrics (e.g., sensitivity, specificity, AUC). Instead, it lists performance tests conducted for a medical device (endoscope) and reports that these tests met the required specifications.

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

• Test set sample size: Not applicable/Not provided. The performance testing described (reprocessing, biocompatibility, safety, shelf-life, optical quality) relates to the physical and functional characteristics of the endoscope, not an AI model evaluated on a data set.
• Data Provenance: Not applicable/Not provided. The tests described are bench tests or laboratory analyses on the device itself, not data derived from patients or clinical sources.

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

• Not applicable/Not provided. Ground truth in the context of expert consensus for AI/ML performance is not relevant to this device's submission which is for an endoscope. The tests performed would have relied on standard testing methodologies and equipment, not clinical experts establishing ground truth for data interpretation.

4. Adjudication method for the test set:

• Not applicable/Not provided. Adjudication methods (e.g., 2+1, 3+1) are used for resolving discrepancies in expert interpretations to establish ground truth for AI/ML models. This is not relevant to the described device testing.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

• No, a MRMC comparative effectiveness study was not done. This type of study is specific to evaluating diagnostic AI/ML devices in conjunction with human readers, which is not what the Vesair Cystoscopes are.

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

• No, a standalone algorithm performance study was not done. The Vesair Cystoscopes are physical medical devices (endoscopes) and do not involve an algorithm.

7. The type of ground truth used:

• Not applicable/Not provided. The concept of "ground truth" (expert consensus, pathology, outcomes data) as it applies to AI/ML device validation is not relevant here. The "truth" for the performance tests would be established by reference standards, validated methods, and compliance with specifications.

8. The sample size for the training set:

• Not applicable/Not provided. This device is not an AI/ML system and therefore does not have a training set.

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

• Not applicable/Not provided. As there is no AI component, there is no training set or associated ground truth establishment.

In summary, the provided text describes a traditional medical device (cystoscope) submission and its performance testing, which does not involve AI or the associated methodologies for validating AI/ML performance.

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The Vesair Cystoscopic Sheath is intended to facilitate the introduction of catheters or instruments into the urethra. The Vesair Cystoscopic Sheath is indicated for use as a guide for urological catheters or instruments inserted into the urethra and as a lubricious barrier between the urethral tissue and the catheter or instrument.

The Vesair Cystoscopic Sheath is intended for use in visualizing the urethra and bladder as well as the establishment of a protective tract into the bladder to facilitate atraumatic insertion of catheters and instruments through the urethra.

The Vesair Cystoscopic Sheath Assembly includes a Visual Obturator, Sheath and the Vesair Single-Use Sterile Seal. The Sheath is provided non-sterile and requires cleaning and steam sterilization prior to use.

The provided text is a 510(k) premarket notification document for the "Vesair Cystoscopic Sheath." It primarily focuses on demonstrating substantial equivalence to a predicate device ("Guardian Urethral Sheath") rather than providing detailed acceptance criteria and study results for a new, AI-powered medical device.

Therefore, the document does not contain the information requested regarding:

1. A table of acceptance criteria and reported device performance: The document mentions "in vitro performance tests" but does not provide specific acceptance criteria (e.g., specific thresholds for success in a test) or the quantitative results of these tests.
2. Sample size used for the test set and data provenance: No information is given about sample sizes for any "test set" in the context of device performance, nor is there any mention of data provenance (e.g., country of origin, retrospective/prospective).
3. Number of experts and their qualifications for ground truth: This is irrelevant as the device isn't an AI/imaging device requiring expert ground truth for interpretation.
4. Adjudication method: Not applicable for this type of device and study.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: Not applicable, as this is a medical device, not an AI-assisted diagnostic tool.
6. Standalone (algorithm only) performance: Not applicable, as there is no algorithm or AI component mentioned.
7. Type of ground truth used: Not applicable in the context of a new AI/imaging device. The "performance data" mentioned are for mechanical and material properties.
8. Sample size for the training set: Not applicable, as there's no machine learning or AI training involved.
9. How ground truth for the training set was established: Not applicable for the same reason.

The document lists "In Vitro Performance Testing" as part of the performance data, including:

• Design Verification Testing / Simulated Use Testing
• Ship Testing
• Repeat Steam Sterilization Testing
• Accelerated Aging

However, it does not provide the details of these tests, their acceptance criteria, or the results. It concludes by stating that "Based upon the in vitro performance tests, the Vesair Cystoscopic Sheath has been shown to be substantially equivalent to the currently marketed Guardian Urethral Sheath K141252."

To summarize, the provided text describes a regulatory submission for a medical device (a cystoscopic sheath) and its claim of substantial equivalence to a predicate device, focusing on material, design, and sterilization comparisons. It is not an AI/software device and therefore does not have the types of performance data, ground truth establishment, or study methodologies that would be relevant to the questions posed.

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The Guardian Urethral Sheath is intended to facilitate the introduction of catheters or instruments into the Guardian Urethral Sheath is indicated for use as a guide for urological catheters or instruments inserted into the uneticious barrier between the urethral tissue and the catheter or instrument.

Not Found

This document is a 510(k) premarket notification from the FDA for a device called the "Guardian Urethral Sheath." It does not contain information about acceptance criteria or a study proving the device meets acceptance criteria in the way you've described for an AI/software-based medical device.

The information provided is a letter from the FDA to the manufacturer, Solace Therapeutics, stating that their device, the Guardian Urethral Sheath, has been found substantially equivalent to a legally marketed predicate device. This is a common regulatory pathway for medical devices that are similar to existing ones.

Therefore, I cannot extract the requested information from this document because it is not present. The document focuses on regulatory approval based on substantial equivalence, not on performance criteria and studies demonstrating that a device (especially an AI-driven one) meets those criteria.

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The Guardian Urethral Sheath is intended to facilitate the introduction of catheters or instruments into the urethra. The Guardian Urethral Sheath is indicated for use as a guide for urological catheters or instruments inserted into the urethra and as a lubricious barrier between the urethral tissue and the catheter or instrument.

The Solace Guardian Urethral Sheath is an everting sleeve sheath with a backflow valve for the establishment of a protective tract to the bladder to facilitate atraumatic insertion of catheters and instruments through the urethra. The sheath consists of a thin-walled rigid plastic tube, an obturator, and an everting sleeve that deploys from the obturator during insertion to reduce friction. Improvements from the Generation I sheath include a silicone disc to improve patient comfort at the external contact point, a single handed fluid management system, and independent fill and waste lines.

The Urethral Sheath is supplied sterile and is single use. The working channel is sized to accommodate instruments up to 19 French. The sheath outside size is 24 French with a working length of 4.7 cm.

The Sheath helps the patient by protecting the urethra and reducing abrasion or tenderness resulting from instruments passing through the urethra.

This 510(k) summary describes a medical device, the Guardian Urethral Sheath, and its testing for substantial equivalence to a predicate device. However, it does not involve an AI/ML device, and therefore, many of the requested criteria related to AI/ML performance studies, such as sample sizes for test and training sets, ground truth establishment, expert adjudication, and MRMC studies, are not applicable.

Here's an analysis of the provided text based on your prompt, highlighting the available information and noting where AI/ML-specific criteria are not met:

1. Table of Acceptance Criteria and Reported Device Performance

• Cytotoxicity
• Sensitization
• Irritation or Intracutaneous reactivity | Biocompatibility tests were conducted on the Guardian Urethral Sheath according to the requirements of ISO 10993:2009. The following were completed: Cytotoxicity, Sensitization, Irritation or Intracutaneous reactivity. (Implies satisfactory completion as it supports the conclusion of substantial equivalence). |
  | In Vitro Performance Testing:
• Simulated Use Testing
• Design Verification Testing
• Process Validation Testing | In vitro performance tests were performed on the Guardian Urethral Sheath. The following were performed: Simulated Use Testing, Design Verification Testing, Process Validation Testing. (Implies satisfactory completion as it supports the conclusion of substantial equivalence). |
  | Substantial Equivalence: Material, design, and function to the Generation 1 Guardian Urethral Sheath K052298. | "The Generation 2 Guardian Urethral Sheath is substantially equivalent in material, design and function to the Generation 1 Guardian Urethral Sheath K052298 (formerly CYSTOGLIDE INTRODUCER SHEATH)."
  "Based upon these biocompatibility and in vitro performance tests, the Guardian Urethral Sheath has been shown to be substantially equivalent to the currently marketed Guardian Urethral Sheath K052298." |

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

• Not Applicable (N/A) for AI/ML context. The testing described is for a conventional hardware medical device (a urethral sheath), not an AI/ML diagnostic or predictive algorithm. Therefore, there isn't a "test set" in the sense of a dataset for algorithm evaluation.
• The performance data provided are for physical and biological characteristics (biocompatibility, in vitro performance). The text does not specify sample sizes for these tests (e.g., number of devices tested for simulated use, number of animal subjects for biocompatibility, etc.).
• Data Provenance: Not specified for the general performance testing. Biocompatibility tests are standardized. "Simulated Use Testing" implies a lab setting.

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

• N/A for AI/ML context. Ground truth in the context of expert consensus for image or data interpretation is not relevant for this device. The "ground truth" for this device would be established by physical and chemical testing standards and clinical performance expectations. The text does not specify experts involved in establishing these test criteria or evaluating the results, beyond the implied expertise in conducting ISO standard tests.

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

• N/A for AI/ML context. Adjudication methods like 2+1 are used for resolving disagreements among human readers or labelers in AI/ML performance evaluation. This concept does not apply to the physical and biological testing of a conventional medical device.

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. This is not an AI/ML device, so an MRMC study comparing human readers with and without AI assistance is not relevant and was not performed or described.

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

• N/A. This is not an AI/ML algorithm.

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

• For Biocompatibility: The ground truth is established by adherence to the ISO 10993:2009 standards for material safety (cytotoxicity, sensitization, irritation).
• For In Vitro Performance: The ground truth is established by Design Verification Testing, Simulated Use Testing, and Process Validation Testing, which would compare the device's performance against pre-defined engineering specifications and functional requirements. These are objective measures based on engineering and manufacturing standards.

8. The sample size for the training set

• N/A for AI/ML context. This is not an AI/ML device, so there is no "training set."

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

• N/A for AI/ML context. As there is no training set for an AI/ML model, this question is not applicable.

Summary of the Study Proving Acceptance Criteria:

The study proving the device meets the acceptance criteria is a series of biocompatibility tests and in vitro performance tests.

• Biocompatibility Testing: Conducted according to ISO 10993:2009 standards, which include tests for Cytotoxicity, Sensitization, and Irritation or Intracutaneous reactivity. The positive outcome of these tests implies that the device materials are safe for their intended use.
• In Vitro Performance Testing: This encompassed Simulated Use Testing, Design Verification Testing, and Process Validation Testing. These tests would evaluate the device's functional integrity, design specifications, and manufacturing consistency under controlled, laboratory conditions. For instance, simulated use testing would assess how the sheath performs during insertion and withdrawal of instruments, and how well the backflow valve functions, within a simulated anatomical environment. Design verification would confirm that the device meets its specified dimensions, material properties, and operational characteristics. Process validation would ensure that the manufacturing process consistently produces devices that meet these specifications.

The conclusion drawn from these tests is that the Guardian Urethral Sheath (Generation 2) has been shown to be substantially equivalent to its predicate device (Guardian Urethral Sheath K052298) in terms of material, design, and function. The FDA's 510(k) clearance further confirms this determination of substantial equivalence, based on the provided data.

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