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The Insufflator is a device intended to facilitate the use of the laparoscope by filling the peritoneal cavity with gas to distend it.

The subject device consists of an insufflator, a high pressure tube and a pneumoperitoneum tube. The insufflator is a microprocessor-controlled CO2 insufflator that consists of the following major components and features: housing, power supply, pressure reducers, venting system, fluid sensor, gas heater, various setting keys and display elements. The insufflator is not intended to enter the field and cannot be sterilized. The pneumoperitoneum tube shall be cleaned, disinfected, and sterilized prior to subsequent use.

The provided document is a 510(k) summary for an Insufflator (K222812), intended to facilitate the use of a laparoscope by distending the peritoneal cavity with gas. It primarily focuses on demonstrating substantial equivalence to a predicate device (K030837) and a reference device (K153513) through non-clinical performance testing.

Based on the provided information, here's an analysis of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly present a table of "acceptance criteria" for specific performance metrics in a pass/fail format alongside the device's reported performance. Instead, it lists the standards and the types of comparative non-clinical performance testing performed, implying that meeting these standards and showing comparable performance to the predicate device would be the acceptance criteria.

However, we can infer some criteria from the "General Comparison" table (Table 2) and the "Performance Specifications" in Table 3 (which is incomplete in the provided text).

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

The document mentions "non clinical tests were conducted" and "comparative performance testing was also conducted on the subject and predicate devices." However, it does not specify the sample sizes used for these tests. The tests are non-clinical, meaning they involve lab testing of the devices themselves, not patient data. Therefore, questions of country of origin of data or retrospective/prospective are not applicable for this non-clinical submission.

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

This information is not applicable as the studies are entirely non-clinical performance and safety tests of a medical device (insufflator). There is no "ground truth" to be established by clinical experts for a test set in the context of this 510(k) submission.

4. Adjudication Method for the Test Set:

This information is not applicable for the same reason as above. Non-clinical engineering tests do not involve expert adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC comparative effectiveness study was not done. The submission is for a medical device (insufflator) and relies on non-clinical performance and safety testing. There are no human readers or cases involved in the presented studies.

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

This question is not applicable in the traditional sense for this device. The device is hardware with embedded software, not an AI algorithm performing diagnostic or therapeutic functions needing standalone performance evaluation in the context of AI/ML. The software verification and validation were performed as an integral part of the device's functionality.

7. The Type of Ground Truth Used:

As the studies are non-clinical performance tests, the "ground truth" would be established by:

• Engineering specifications and standards: Adherence to standards like IEC 60601-1, IEC 60601-1-2, ASTM D4169, AAMI TIR 30, AAMI TIR 12, ISO 15883-2, ISO 17665-1, ISO 14971, and IEC 60601-2-18.
• Expected physical and functional performance: Measured parameters like flow rate, pressure accuracy, temperature, and warning thresholds are compared against design specifications and the performance of the predicate device.

8. The Sample Size for the Training Set:

This information is not applicable. The device is an insufflator, not a machine learning or AI model that requires a training set of data. The software within the device is likely deterministic control software, subject to standard software verification and validation, not machine learning model training.

9. How the Ground Truth for the Training Set was Established:

This information is not applicable as there is no training set mentioned or implied for this device.

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The EVA 15 Insufflator is intended for use in diagnostic endoscopic and laparoscopic procedures to distend the abdomen, rectum, colon, esophagus, stomach or thoracic cavity with up to 25 mmHg pressure, by filling it with gas and to evacuate surgical smoke.

The EVA15 insufflator is intended for use in diagnostic and/or therapeutic endoscopic and laparoscopic procedures to distend a cavity by filling it with gas and to evacuate surgical smoke. It is indicated to facilitate the use of various endoscopic instruments by filling the abdominal cavity or rectum with gas to distend it, and by evacuating surgical smoke. The EVA 15 Insufflator is used in an operating room or endoscopic suite. It consists of the following major components: (1) a micro-processor-controlled insufflation and smoke evacuation unit and (2) a disposable tube set.

The laparoscopic tube set is a sterile, single-use product. The EVA15 Insufflator is an active medical device, nonsterile and reusable and is intended to insufflate a body cavity up to 25mmHg and with up to 40 SLPM instantaneous flow. The EVA15 is powered by AC and uses compressed 50 psi CO2 and air gas supply the pneumatic circuitry for insufflation and smoke evacuation respectively.

This document describes the 510(k) submission for the EVA15 Insufflator, emphasizing the modifications and the non-clinical testing performed to demonstrate substantial equivalence to its predicate device (K202799 - Palliare EVA15).

Here’s a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document explicitly states that the device met its acceptance criteria, which were the "same acceptance criteria as applied to the predicate" (K202799). However, specific numerical acceptance criteria are not detailed for all tests. The performance reported indicates successful completion of these tests.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify a "test set" in terms of subject data (e.g., patient data for an AI algorithm). The testing described is non-clinical performance testing of the device itself (hardware and software). Therefore, specific sample sizes for a data-driven test set are not applicable here. The provenance of any data used for testing (e.g., country of origin, retrospective/prospective) is not mentioned as the testing focuses on device function.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of those Experts

This information is not applicable as the document describes non-clinical performance testing of a medical device (an insufflator), not an AI algorithm that requires expert-established ground truth from images or patient data.

4. Adjudication Method for the Test Set

This information is not applicable for the same reasons as point 3.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC study was performed or mentioned. This type of study focuses on human reader performance with and without AI assistance, which is not relevant for an insufflator device.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study of the device was performed in the form of non-clinical testing (static and dynamic conditions). This is not an "algorithm only" study in the typical AI context; rather, it refers to the performance of the integrated device system. The document states: "Performance testing of the insufflator in the revised pressure range demonstrated that the subject device met its acceptance criteria... Testing included: Static condition (Pressure accuracy), Dynamic condition (Simulated leak, Smoke evacuation)."

7. Type of Ground Truth Used

The "ground truth" for this device's performance testing would be the engineering specifications and established functional requirements for insufflators. For example, pressure accuracy would be compared against a calibrated standard, and smoke evacuation effectiveness against predefined thresholds. It's not expert consensus, pathology, or outcomes data.

8. Sample Size for the Training Set

This information is not applicable as the device is a hardware/software system, not a machine learning or AI algorithm that requires a "training set" in the conventional sense.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable for the same reasons as point 8.

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The OpClear® System consists of a reusable control unit and a range of disposable sterile single-use accessories intended to remove visual obstructions such as condensation, blood and other tissue particulates from the distal lens of a laparoscope during surgery and therefore maintaining a clear image of the surgical site.

OpClear® System is a laparoscopic lens cleaning device which is intended to be used during any laparoscopic surgical procedure where there is a potential for contamination of the distal lens. Consisting of a reusable control unit and a range of sterile, invasive, single use disposables, it is intended to maintain surgical vision by removing contaminants such as condensation, blood, peritoneal fluid, smoke, fat and tissue smears that have contaminated the distal lens of the laparoscope during surgical procedures.

OpClear® System is composed of a control unit and a range of disposable accessories as shown below.

This document describes the OpClear® System, a laparoscopic lens cleaning device, and its FDA 510(k) submission (K171637). The information provided focuses on device description, indications for use, operating principles, and a summary of non-clinical testing. It does not contain a detailed study with specific acceptance criteria, reported device performance metrics, or information on sample sizes, expert ground truth, adjudication methods, or MRMC studies.

Therefore, many of the requested elements cannot be extracted from the provided text.

Based on the available text:

1. A table of acceptance criteria and the reported device performance
   The document mentions that "Performance validation has been performed following improvement in the operating parameters for the Device" but does not provide a table of acceptance criteria or specific reported device performance metrics.

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 for Test Set: Not provided. The document refers to "a simulated human abdominal cavity environment" for testing.
   • Data Provenance: The testing described is "non-clinical testing" conducted in a "simulated human abdominal cavity environment" in a "laboratory." This implies the data is prospective from an in vitro or benchtop study, not human subject data. The submitter is UK-based (Cipher Surgical Limited, Coventry, UK), suggesting the laboratory testing was likely conducted in the UK.

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/Not provided. The ground truth for the non-clinical testing appears to be based on the validated "simulated human abdominal cavity environment" and optimizing device parameters, not expert consensus on diagnostic images.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
   Not applicable/Not provided, as the testing was non-clinical and did not involve human interpretation or diagnostic 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. The OpClear® System is a physical medical device (laparoscopic lens cleaning device), not an AI-powered diagnostic or assistive tool. Its function is to maintain clear vision during surgery, reducing the need for human readers (surgeons) to interrupt their work for cleaning. The document does not describe any MRMC study or AI components.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
   Not applicable. This is a physical device, not an algorithm. Its performance is inherent to its mechanical and fluid delivery functions as operated by a surgeon.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
   The ground truth for the "Performance validation" in the non-clinical testing was based on the "suitability" of the "simulated human abdominal cavity environment...as a simulation of the operating environment for the device." This implies an engineered definition of cleanliness or obstruction removal within the simulated environment.

8. The sample size for the training set
   Not applicable. The OpClear® System is a physical device, not a machine learning algorithm that requires a "training set."

9. How the ground truth for the training set was established
   Not applicable, as there is no training set for this physical device.

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