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As a disposable medical device, the product is used along with the company's image processor, to enter human body through the urethra and provide images via video monitor, and realize endoscopy inspection or operation to the patient's ureter and renal pelvis.

The Single-Use Digital Flexible Ureteroscope (Model: PUR12-1, PUR12-2, PUR12-3, PUR12-4, PUR12-5, PUR12-6, PUR12-S, PUR12-S1, PUR12-S2) is an endoscope which is used with the Monitor for Single-Use Endoscopy (Model:P1-D) produced by ENDOSO LIFE TECHNOLOGY for providing endoscopic imaging of the ureter and the renal pelvis for the purpose of diagnosis and treatment. The Single-Use Digital Flexible Ureteroscope is integrated with a working channel which allowing the use of flexible endoscopic accessories (e.g. stone basket, forceps, laser fibers for lithotripsy, etc.). The insertion portion of the endoscope is flexible, and the shape changes corresponding to the shape of the cavity. Anatomical images are captured by a CMOS chip at the distal end of the endoscope and the electronic signals are transmitted to the Monitor. Then, the resulting picture images are sent to and shown on a visual display.

The provided document is a 510(k) Summary for a medical device called "Single-Use Digital Flexible Ureteroscope". This document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study that proves the device meets specific acceptance criteria via clinical performance data (like sensitivity, specificity, or reader improvement with AI).

The document details the device's technical specifications and compares them to a predicate device. It also outlines the non-clinical testing performed to ensure safety and performance, which is typical for 510(k) submissions seeking substantial equivalence.

Therefore, many of the requested items related to clinical performance studies, such as sample size for test sets, number of experts for ground truth, MRMC studies, standalone performance, and ground truth establishment for training sets, are not applicable or not explicitly stated in this type of submission.

Here's a breakdown of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

For this specific device, the "acceptance criteria" are primarily related to meeting performance standards and showing similarity to the predicate device, rather than specific clinical performance metrics. The "reported device performance" is largely based on non-clinical tests.

Study Proving Device Meets Acceptance Criteria:

The document states: "The subject of this premarket submission, did not require clinical studies to support substantial equivalence." This means the "study" proving the device meets acceptance criteria is primarily a series of non-clinical (benchtop) tests and comparisons to a predicate device, demonstrating that the new device is as safe and effective as the legally marketed predicate.

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

• Sample Size: Not applicable. The document describes non-clinical tests. For example, for biocompatibility, specific tests were performed on "patient contacting components," but no sample size for a clinical "test set" is mentioned as clinical studies were not required.
• Data Provenance: The tests appear to be conducted by the manufacturer or their designated testing facilities, likely in China (Hunan, where the manufacturer is located). The data is generated retrospectively as part of the device development and submission process.

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

• Not applicable, as no clinical test set with corresponding ground truth established by experts is described. The "ground truth" for this submission are the established engineering standards, biocompatibility standards, and the performance characteristics of the predicate device.

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

• Not applicable, as no clinical test set requiring adjudication of findings is described.

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 ureteroscope (an
  endoscope), not an AI diagnostic/assistive tool for human readers. No MRMC study was conducted.

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

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

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

• The "ground truth" for this submission is based on:
  • Validated engineering and medical device standards (e.g., ISO 8600, IEC 62471, ISO 10993, ISO 11135, ASTM F1980, ISO 11607, ASTM D4169, IEC 60601 series).
  • Performance characteristics of the legally marketed predicate device (K230200).
  • Pass/fail criteria for the various non-clinical tests performed.

8. The sample size for the training set

• Not applicable. There is no mention of a training set for an AI algorithm.

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

• Not applicable. There is no mention of a training set for an AI algorithm within this document.

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The Single-use Bronchoscopes have been designed to be used with the Monitor for Single-Use Endoscopy, endotherapy accessories and other ancillary equipment for endoscopy within the airways and tracheobronchial tree. The Bronchoscope System is for use in a hospital environment.

The Single-use Bronchoscope is a disposable device designed for use in adults.

The Bronchoscope System consists of Single-use Bronchoscope (Model: BC12-1, BC12-2, BC20-1, BC20-2, BC22-1, BC22-2, BC22-3, BC28-1, BC28-2, BC28-3) to be introduced within the airways or tracheobronchial tree and Monitor for Single-Use Endoscopy (Model: P1-A, P1-C, P1-C, P1-D, P1-E, P2-A, P2-B, P2-C, P2-D, P2-E) for clinical image processing. The Single-use Bronchoscope is inserted through the airways and tracheobronchial tree during Bronchoscopy. The Monitor provides power and processes the images for medical electronic endoscope.

The Single-use Bronchoscope is a sterile single use flexible bronchoscope. The Monitor for Single-Use Endoscopy is a reusable monitor.

The light emitted by the LED cold light source at the distal tip of the disposable video Bronchoscope is irradiated into the body cavity, and the light reflected from the cavity enters the optical system and is captured by the CMOS image sensor. The CMOS acquisition image is controlled by the CMOS drive circuit, and the RGB video signal is output to the Monitor for Single-Use Endoscopy via the VI circuit. The Monitor receives video signals from the endoscope, processes the video signals and outputs the processed video signal. The Monitor also controls the brightness of the LEDs on the endoscope.

The provided document is a 510(k) Premarket Notification and primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study report for a novel AI/ML-driven medical device. Therefore, it does not contain the specific information required to answer many of the questions about acceptance criteria, detailed study design, ground truth establishment, or human-in-the-loop performance.

This document describes a "Bronchoscope System," which includes a "Single-use Bronchoscope" and a "Monitor for Single-Use Endoscopy." The core technology described involves an optical system with a CMOS sensor to capture images for display, which is a common technology for endoscopes, not necessarily an AI/ML device in the sense of image analysis/decision support.

Here's an attempt to answer the questions based only on the provided text, highlighting what is not available:

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

The document does not present a formal table of acceptance criteria with reported quantitative performance metrics in the format usually seen for AI/ML device studies (e.g., sensitivity, specificity, AUC). Instead, it relies on demonstrating equivalence through various non-clinical tests compared to a predicate device.

The "Summary of Testing" section lists the types of tests performed. The acceptance criteria are implicitly that the device performs "as well as" the predicate or meets established ISO standards.

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

The document states: "Based on the similarities of the device specifications, intended use, indications for use between the Bronchoscope System and its predicate device, no clinical studies were needed to support this 510(k) Premarket Notification."

This means there was no clinical test set in the traditional sense for evaluating something like diagnostic accuracy of an AI/ML model. The evaluation was done through non-clinical bench testing, electrical safety, biocompatibility, and software V&V. Therefore, information on sample size, data provenance (country, retrospective/prospective) for a clinical test set is not applicable to this submission.

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)

Since no clinical studies were performed, no expert ground truth establishment for a clinical test set was required or conducted.

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

Not applicable as no clinical test set using expert adjudication was conducted.

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, as this is not an AI-assisted diagnostic device submission requiring MRMC studies. The device is a bronchoscope system for visualization.

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

This refers to an AI algorithm's performance. The Bronchoscope System is a hardware device for direct visualization, not an AI algorithm. Therefore, "standalone performance" in the AI sense is not applicable.

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

For the non-clinical tests, the "ground truth" was established by engineering specifications, validated test methods (e.g., ISO standards), and comparisons against the predicate device's established performance parameters. For example:

• Electrical Safety/EMC: Compliance to IEC standards.
• Optical Performance: Measurement against ISO 8600 series specifications.
• Biocompatibility: Results of standard biological tests (e.g., cytotoxicity, sensitization) against established safe thresholds.

8. The sample size for the training set

The document does not mention a "training set" because it is not an AI/ML device that requires machine learning training.

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

Not applicable, as no training set for an AI/ML model was used.

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It is used in medical institutions for observation and imaging in abdominal surgery by entering the human body through the wound.

The Laparoscope (Model: 4KA0、4KA0R、4KA30、4KA30R、4KA45、4KA45R) is used in medical institutions. Laparoscopes are tubular optical instruments used to visualize or image a patient's anatomy during minimally invasive, endoscopic procedures for examination, diagnosis or therapy. The Laparoscope transmits light in both the visible and near infrared spectrum to illuminate and image the anatomy, then forms and relays the image of the surgical site to a camera system for processing and display.

The provided document is a 510(k) summary for a Laparoscope, which is a medical device for observation and imaging in abdominal surgery. It's a submission to the FDA demonstrating substantial equivalence to a legally marketed predicate device. This document describes the device's technical specifications and the tests conducted to prove its performance and safety, aligning them with the predicate device and relevant standards.

However, the document does not contain information related to an AI/ML-driven medical device. Specifically, there is no mention of a "study that proves the device meets the acceptance criteria" in the context of AI/ML performance metrics, or human reader performance with and without AI assistance. The tests described are for a physical medical device (laparoscope), focusing on electrical safety, packaging, biocompatibility, cleaning/disinfection/sterilization, and bench performance (optical and mechanical verification).

Therefore, I cannot provide the requested information regarding acceptance criteria and study details for an AI-driven device, as the provided text does not describe such a device or study. The information requested (acceptance criteria, sample size, ground truth, experts, MRMC studies, etc.) is typically associated with the validation of AI/ML software as a medical device (SaMD) or AI-assisted medical devices, which is not the subject of this 510(k) submission.

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