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The ClearPetra Suction-Evacuation Sheath is used to establish a conduit during endoscopic urological procedures facilitating the passage of endoscopes and other instruments into the urinary tract. It is designed to establish a conduit for the treatment of urinary stones or other urinary diseases during endoscopic procedures.

The ClearPetra Suction-Evacuation Sheath consists of a straight distal tube and a proximal bifurcated tube. The distal straight tube of the ureteral access sheath is reinforced with metal wires for torque resistance. One segment of the proximal bifurcated tube is straight and is contiguous with the distal tube. The other is constructed in an oblique angle with a longitudinal pressure control vent. An obturator is included for the insertion of the sheath. The obturator can be locked to the proximal end of the straight tube using a luer lock mechanism. A rubber cap with central aperture is included as an accessory. It is to be placed at the proximal end of the straight tube after the removal of the obturator. The oblique tube is to be connected directly to a negative pressure aspirator with a clear tube or alternatively, connected to a specimen collector (packed separately) then onto a negative pressure aspirator.

The provided document is a 510(k) Summary for a medical device called the "ClearPetra Suction-Evacuation Sheath." It primarily focuses on demonstrating substantial equivalence to a predicate device (K161110 - ClearPetra Suction-Evacuation Sheath) rather than presenting a performance study against specific acceptance criteria for a new AI/software device.

Therefore, many of the requested sections about acceptance criteria, study details, expert involvement, and ground truth are not applicable in this context, as this submission is for a modified hardware device, not an AI software.

Here's an analysis based on the information provided in the document:

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

The document does not specify quantitative acceptance criteria in terms of clinical performance metrics (like sensitivity, specificity, etc.) for a diagnostic or AI device. Instead, it relies on comparison to a predicate device and bench testing to demonstrate that the modifications do not negatively impact safety and effectiveness.

The "acceptance criteria" can be inferred from the "Verdict" column in the comparison table and the subsequent non-clinical testing. These broadly aim to demonstrate that the modified device performs as well as or similarly to the predicate device, or within acceptable safety parameters for the new specifications.

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

This information is not provided in the document. The studies mentioned are primarily "Non-Clinical Testing" and "Bench Testing" rather than clinical studies with human participants. Therefore, concepts like "test set," "data provenance," and "retrospective/prospective" as they relate to clinical data are not applicable here. The testing would have likely involved physical samples of the device components.

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)

This information is not applicable as the document describes a hardware device modification and bench testing, not a study requiring expert-established ground truth for diagnostic accuracy (e.g., for an AI system evaluating medical images).

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

This information is not applicable for the same reasons as above. No clinical expert adjudication is mentioned or implied for the non-clinical testing performed.

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

A multi-reader multi-case (MRMC) comparative effectiveness study is not applicable and was not performed. This type of study is relevant for AI-powered diagnostic aids, not for the modification of a physical medical device like a suction-evacuation sheath.

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

A standalone performance study of an algorithm is not applicable as this submission is for a physical medical device, not an algorithm or AI software.

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

The concept of "ground truth" (in the context of expert consensus, pathology, or outcomes data) is not applicable here. The ground for determination of "acceptance" or "substantial equivalence" relies on:

• Physical/material specifications comparison.
• Biocompatibility testing against ISO standards.
• Performance bench testing results demonstrating functional equivalence and intended performance.
• Sterilization validation.

8. The sample size for the training set

This information is not applicable as there is no AI algorithm or software being trained.

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

This information is not applicable as there is no AI algorithm or software being trained.

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The ClearPetra Suction-Evacuation Sheath is used to establish a conduit during endoscopic urological procedures facilitating the passage of endoscopes and other instruments into the urinary tract. It is designed to establish a conduit for the treatment of urinary stones or other urinary diseases during the endoscopic procedures.

The ClearPetra Suction-Evacuation Sheath is designed to establish a conduit for the treatment of urinary stones or other urinary diseases during the endoscopic procedures. The intended use is for the passage of endoscopes and other urological devices for the purpose of performing diagnostic and surgical procedures such as, nephroscopy, ureteroscopy, or cystoscopy. It is used for the treatment of stones and for the removal of foreign bodies in the urinary tract.

The ClearPetra Suction-Evacuation Sheath comes in three models: ClearPetra Ureteral Access Sheath, ClearPetra Cystoscope Sheath and ClearPetra Nephrostomy Sheath. The Ureteral Access Sheath includes two versions: Access Sheath for the Semi-rigid Ureteroscope and Access Sheath for the Flexible Ureteroscope.

The ClearPetra Suction-Evacuation Sheath is comprised of the following components:

• Sheath
• Obturator
• Luer Connector
• Y Connector
• Rubber Cap

The sheath is fitted with a Y connector on the proximal end. The Y connector is bifurcated: straight tube and oblique tube, The distal straight tube of the ureteral access sheath is reinforced with metal wires for torque resistance.

one seqment of the Y connector is straight and is contiguous with the sheath: The other is constructed in an oblique angle with a longitudinal pressure control vent. The oblique tube is to be connected to a negative pressure aspirator with clear tube or alternatively, connected to a specimen collector then onto a negative pressure aspirator, then to collect stones or foreign bodies during the endoscopic procedure.

An obturator is included for the insertion of the sheath. The obturator is radiopaque and is fitted with a luer connector on the proximal end. The obturator can be locked to the proximal end of the straight tube using a luer lock mechanism. A rubber cap with central aperture is included as an accessory. It is to be placed at the proximal end of the straight tube after the removal of the obturator.

The device is offered in French size ranging from 10Fr to 22Fr and length 13cm to 55cm. The device is composed of biologically safe materials. It is supplied sterile and intended for single use only.

The provided text is a 510(k) Summary for the ClearPetra Suction-Evacuation Sheath. This document focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria through a standalone study with human readers or AI.

Therefore, many of the requested elements for describing an AI/CADe device's acceptance criteria and study are not applicable to this document. The document describes a traditional medical device and its non-clinical performance testing.

Here's a breakdown based on the information available:

Acceptance Criteria and Device Performance

Study Details (Based on the provided document)

Since this is a 510(k) for a physical medical device and not an AI/CADe system, much of the requested information regarding AI/CADe studies is not present.

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

   • Not applicable for a clinical study of an AI/CADe device. The document refers to "testing datas and results" for general performance and "Biocompatibility testing reports" for biocompatibility. The specific sample sizes for these non-clinical tests are not detailed in this summary. Data provenance for such engineering and biocompatibility tests typically refers to the testing lab and materials, not patient data.

2. 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. This document describes non-clinical performance testing (e.g., connection strength, bending resistance, biocompatibility), not a study requiring expert-established ground truth on patient data.

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

   • Not applicable. This pertains to clinical studies often involving discrepancy resolution among human readers, which is not described here.

4. 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/CADe device, and no MRMC study is mentioned.

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

   • Not applicable. This is a physical medical device.

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

   • Not applicable in the context of expert-derived ground truth for patient data. For the non-clinical performance tests, the "ground truth" or acceptance criteria would be defined by engineering specifications, regulatory standards (like ISO 10993 for biocompatibility), and internal product design requirements.

7. The sample size for the training set:

   • Not applicable. This is not an AI/CADe device that undergoes machine learning training.

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

   • Not applicable. This is not an AI/CADe device that undergoes machine learning training.

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