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The Digital ClarusScope System and Digital NeuroPEN System are intended for use in neurosurgery, endoscopic neurosurgery, and ventriculoscopy for visualization of ventricles and structures within the brain during neurological surgical procedures, diagnostic and/or therapeutic procedures such as ventriculostomies, biopsies and removal of cysts, tumors and other obstructions.

The Digital ClarusScope System and Digital NeuroPEN System are neurological endoscopes which provide a light source, camera, and HDMI output for visualization. Irrigation is provided for flushing during the procedure. The working channel facilitates the use of tools necessary for neurological procedures (Digital ClarusScope versions only). The Digital ClarusScope and Digital NeuroPEN are intended to be used with the non-sterile, reusable Clarus Digital Control Module with standard HDMI video output. The proximal end of the Digital ClarusScope and Digital NeuroPEN terminate in two fittings: the endoscope connector attaches to the Clarus Digital Control Module, which interfaces to a standard off-the-shelf HDMI video monitor which is not provided by Clarus and is not part of this 510(k) application: the other fitting is an irrigation extension tube with a female Luerlock connector.

The provided text describes the regulatory clearance of the Clarus Medical Digital ClarusScope System and Digital NeuroPEN System, but it does not contain the specific acceptance criteria or a study proving that the device meets those criteria, as typically found in clinical performance study results.

The document details non-clinical performance data and a comparison to predicate and reference devices to establish substantial equivalence. It lists various tests performed, such as dimensional verification, mechanical strength, functional tests like fluid patency and image output, simulated use, sterility validation, shelf-life, environmental conditioning, distribution, biocompatibility, electrical safety, and electromagnetic compatibility.

However, it explicitly states:
"H. Non-Clinical Performance Data: The Digital ClarusScope, Digital NeuroPEN, and Digital Control Module have been thoroughly tested through verification of product specifications and user requirements. The following quality assurance and performance measures were applied during the development of the systems:
...

• Performance Testing (Verification):
  • Endoscope dimensional verification
  • o Mechanical strength requirements
• Functional Tests
  • Endoscope fluid patency o
  • O System image output
• Simulated Use Test
  • o Interconnection testing between endoscope and control module and accessories
  • Compatibility with introducer O
  • Compatibility of endoscope working channel with accessory devices O"

This section indicates that performance testing was conducted for verification, but it does not provide:

1. A table of acceptance criteria and reported device performance against those criteria.
2. Details of a clinical study with patient data, ground truth establishment, or expert reviews, which would be typical for proving performance in a diagnostic or image-interpretation context (e.g., accuracy, sensitivity, specificity).
3. Information regarding sample sizes for test sets, data provenance, number or qualifications of experts, or adjudication methods for establishing clinical ground truth.
4. Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done to assess human reader improvement with AI assistance (the device is a visualization system and not explicitly described as an AI-enabled diagnostic aid in this document).
5. Details on standalone algorithm performance.
6. The type of ground truth used for performance evaluation in a clinical context.
7. Sample size or ground truth establishment for a training set, as this document focuses on the device performance and not the performance of an embedded AI algorithm that would typically require such training data.

Based on the provided text, the device primarily focuses on visualization and mechanical/electrical safety and functionality, not on diagnostic accuracy based on image interpretation by an algorithm. Therefore, the information requested regarding acceptance criteria and clinical study details for diagnostic performance is not present in this document.

The document's conclusion of "Substantial Equivalence" is based on "performance testing, design and non-clinical testing," which aligns with the details provided in section H.

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The KARL STORZ Slim Nasopharyngoscope System is indicated to provide visualization and access of the nasal lumens and airway anatomy (including nasopharyngeal and trachea) during diagnostic and therapeutic procedures in adult and pediatric patients.

The KARL STORZ Slim Nasopharyngolaryngoscope (Model Number: 11161V) is a reusable, flexible videoscope used for examination of the nasal lumens and airway anatomy. The KARL STORZ Slim Nasopharyngolaryngoscope System is identical to the KARL STORZ Flexible Video-Neuro-Endoscope System, which is currently distributed under K161112.

This document pertains to the 510(k) premarket notification for the KARL STORZ Slim Nasopharyngolaryngoscope System (K171402). This device is a flexible videoscope used for visualization during ENT diagnostic and therapeutic procedures.

Important Note: This submission is for a device that is identical in design and performance to a previously cleared device (KARL STORZ Flexible Video-Neuro-Endoscope System, K161112), with the exception of an additional High-Level Disinfection (HLD) method being supported. Therefore, the majority of the acceptance criteria and study data relate to demonstrating this equivalence and validating the new HLD method, rather than a de novo clinical performance study of the device's efficacy.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a submission for a device largely identical to a predicate, the "acceptance criteria" here primarily refer to demonstrating equivalence to the predicate and compliance with relevant standards. No performance metrics like sensitivity, specificity, or accuracy (typical for AI/Algorithm-driven devices) are applicable here, as this is an endoscopic visualization device, not an AI diagnostic tool.

The "acceptance criteria" are thus implicitly met by demonstrating that the device is identical in design and performance to the predicate (K161112), and that the new HLD method is validated.

• Type of Scope: Flexible
• Distal Tip Diameter: 8.5 Fr, 2.83 mm (elliptical: 3.2 mm x 2.4 mm)
• Working Shaft Length: 350 mm
• Working Channel Diameter: 1.2 mm
• Deflection: Up: 270°, Down: 270° |
  | Optical Characteristics | The device's optical characteristics (Type of Imager, Field of View, Direction of View, Light Source) must be identical or substantially equivalent to the predicate devices, ensuring equivalent visualization quality. | Identical to Reference Device (K161112):
• Type of Imager: CMOS chip
• Field of View: 90°
• Direction of View: 0°
• Light Source: Internal LED |
  | Electrical Safety and EMC | Compliance with recognized electrical safety and electromagnetic compatibility (EMC) standards. | Device design for electrical safety and EMC is unchanged from reference device (K161112). Data from K161112 complied with:
• ANSI/AAMI ES 60601-1:2005 (Recognition Number: 19-4)
• IEC 60601-1-2:2007 (Recognition Number: 19-8)
  No additional data needed. |
  | Bench Testing (Performance) | Compliance with recognized performance standards for endoscopes (e.g., image quality, durability). | Device design for performance is unchanged from reference device (K161112). Data from K161112 complied with:
• ISO 8600-1:2015 (Recognition Number: 9-110)
• ISO 8600-3:1997 (Recognition Number: 9-84)
• ISO 8600-4:2014 (Recognition Number: 9-94)
  No additional data needed. |
  | Biocompatibility | Compliance with recognized biocompatibility standards for medical devices based on patient contact. | Device design for materials is unchanged from reference device (K161112). Data from K161112 complied with:
• ISO 10993-1:2009/(R) 2013 (Recognition Number: 2-156)
• ISO 10993-5:2009/(R) 2014 (Recognition Number: 2-153)
• ISO 10993-10:2010 (Recognition Number: 2-173)
• ISO 10993-11:2006/(R) 2010 (Recognition Number: 2-118)
  No additional data needed. |
  | High Level Disinfection (HLD) Safety & Efficacy | Validation of the safety and efficacy of the additional HLD method (CIDEX) for the semi-critical device, demonstrating effective disinfection and device material compatibility. This is crucial as the device's Spaulding classification changed from "critical" (requiring sterilization) to "semi-critical" (allowing HLD). Compliance with relevant standards for HLD validation. | New HLD validation study performed for CIDEX on a representative device. Data complied with:
• AAMI TIR12:2010
• ISO 15883-5:2005
• AAMI TIR30:2011
• AAMI/ANSI/ISO 11737-1:2006/ (R)2011 (Recognition Number: 14-227)
• ASTM E1837-96:2014
  This supports the use of CIDEX as an HLD method for the device. |

Specific Study Information (as applicable to this type of device submission):

For this 510(k) submission, the primary "study" is demonstrating substantial equivalence to the predicate and validating the new HLD method. Clinical performance data was not required because non-clinical bench testing was deemed sufficient to establish substantial equivalence. This is not an AI/Algorithm device, so many of the requested points do not apply.

1. Sample Size Used for the Test Set and Data Provenance:

   • Test Set (for HLD validation): The document states an "HLD validation study was performed using a representative device." It does not specify the exact sample size (number of devices or test cycles) but implies rigorous testing in compliance with the listed standards (e.g., AAMI TIR12, ISO 15883-5).
   • Data Provenance: Not explicitly stated, but typically such validation studies are done in a controlled laboratory environment by the manufacturer or a contracted lab. The document implies it's a prospective validation study to support the new HLD method for this specific device. Country of origin for the HLD study data is not provided.

2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

   • Not applicable. For this type of device and submission, "ground truth" as it relates to clinical diagnosis or imagery (like in AI/Algorithm studies) is not established by expert readers. The "ground truth" for HLD validation is established through microbiological testing (e.g., absence of viable microorganisms after disinfection) and material compatibility testing, which are performed by qualified lab personnel following validated protocols, not clinical experts.

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

   • Not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical image interpretation studies, typically for AI where there's a need to reconcile discordant expert reads against a reference standard. Here, the "test set" is for HLD validation, not for image interpretation.

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 device is an endoscope for direct human visualization, not an AI-assisted diagnostic tool. No MRMC study was performed or required.

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

   • Not applicable. This device is a manual endoscopic instrument; it does not have a standalone algorithm component.

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

   • For the HLD validation, the "ground truth" for efficacy is the microbiological sterility or reduction level achieved, as determined by validated laboratory methods (e.g., culture, spore count reduction). For material compatibility, the "ground truth" is the absence of degradation or adverse effects on device components after repeated HLD cycles.

7. The sample size for the training set:

   • Not applicable. This device does not have a "training set" in the context of an AI/machine learning algorithm. The design of the existing predicate device (K161112) served as the "base" or "trained" design, and this submission focuses on demonstrating equivalence and validating a new cleaning process.

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

   • Not applicable. (Same reasoning as above).

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