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For endometrial sampling for histologic biopsy of the uterine mucosal lining including post menopausal patients.

The RI. MOS. s.r.l. curette operates manually by applied vacuum suction and is a sterile single-use disposable device.

The provided text describes a 510(k) summary for the RI. MOS. s.r.l. GINRAM® Endocic device, an endometrial suction curette. Based on the provided sections, here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document mentions "A clinical sampling study was conducted" but does not specify the sample size used for this study. It also does not explicitly state the data provenance (e.g., country of origin, retrospective or prospective).

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

The document does not provide information regarding the number of experts used or their qualifications for establishing ground truth. The nature of the study (tissue collection) implies pathology experts would be involved in assessing tissue grade, but this is not stated.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The study described is a clinical sampling study to evaluate the device's design.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

This device is a manual medical instrument (curette), not an AI algorithm. Therefore, no standalone algorithm performance study was done as it's not applicable.

7. The Type of Ground Truth Used

The ground truth used would implicitly be histologic biopsy results to assess the "amount and grade of tissue collection."

8. The Sample Size for the Training Set

This device is a manual instrument; therefore, there is no "training set" in the context of an algorithm or AI. The clinical sampling study served as the evaluation or test set for the device's performance.

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

As there is no training set for a manual device, this question is not applicable. The "ground truth" for the device's performance on the clinical sampling study would have been established by histopathological examination of the collected endometrial tissue.

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For endometrial sampling for histologic biopsy of the uterine mucosal lining.

The RI.MOS. s.r.l. curette operates by negative pressure and is a sterile, single-use, disposable device.

The provided text describes a 510(k) submission for the RI.MOS. s.r.l. Rampipella, an endometrial suction curette. It's important to note that this is a traditional medical device, not an AI/ML powered device, so many of the requested fields (especially those related to AI/ML specific studies, ground truth, and expert involvement) are not applicable or not detailed in this type of submission.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified. The document only states "Comparative clinical performance evaluations were conducted."
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). It is a clinical performance evaluation, implying prospective, but detailed information is not provided.

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

• Not Applicable / Not Specified: The study focuses on the physical collection of tissue and safety, not on the interpretation of results by experts in a diagnostic context for an AI/ML device. The ground truth would inherently be the tissue itself, which would then be analyzed (presumably by pathologists, though not explicitly stated) to determine "histological grade tissue collection."

4. Adjudication Method for the Test Set:

• Not Applicable / Not Specified: This concept typically applies to studies where human interpreters are making subjective assessments that need to be reconciled (e.g., in AI/ML validation). The reported study is a clinical performance evaluation of a physical device.

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: This is not an AI/ML device. Therefore, no MRMC study or AI assistance evaluation would have been conducted or is applicable.

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

• No: This is not an AI/ML device.

7. The Type of Ground Truth Used:

• Histological Examination (Implied): The study evaluated "adequate histological grade tissue collection." This implies that the tissue samples collected by the device were subsequently examined histologically (likely by pathologists) to confirm their quality and suitability for diagnosis. The "ground truth" here is the actual quality and diagnostic utility of the collected tissue as determined by standard pathology practices.

8. The Sample Size for the Training Set:

• Not Applicable: This is a physical medical device, not an AI/ML algorithm. There is no concept of a "training set" in this context.

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

• Not Applicable: As above, there is no training set for a physical medical device.

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The RI MOS. s.r.l. Cuscovag, Specuvag and Specuvag AS devices are used to expose the interior of the vagina. The Cuscovag is indicated as an aid for routine examination in adolescent and geriatric women, the Specuvag as an aid for routine examination and the Specuvag AS as an aid for routine examination and procedures where smoke must be evacuated from the vaginal canal.

The RI. MOS. s.r.l. speculae line are sterile, single-use, disposable devices.

This document describes a 510(k) submission for gynecological specula (GINRAM® Cuscovag, Specuvag, and Specuvag AS). The submission aims to demonstrate substantial equivalence to a predicate device, the KleenSpec® Specula marketed by Welch Allyn (K941272).

Here's an analysis of the provided text in relation to your questions:

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

The provided text does not contain a table of acceptance criteria or specific device performance metrics in the way one would expect for an AI/CADe device. This submission is for a physical medical device (specula), not a software-based diagnostic tool. The "acceptance criteria" here are based on demonstrating substantial equivalence to a predicate device, primarily through technological characteristics and safety testing.

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 applicable or not provided in the context of this 510(k) summary for a physical medical device. There is no "test set" of patient data in the typical sense for evaluating an AI algorithm's diagnostic performance. The evaluation is focused on the device's physical and material properties and its intended use.

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 or not provided. Since there's no diagnostic AI algorithm being described, there's no "ground truth" derived from expert consensus on medical images or data.

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

This information is not applicable or not provided. No "adjudication method" for a test set is mentioned because there's no diagnostic performance being evaluated in this manner.

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

This information is not applicable. The device is a speculum, not an AI-assisted diagnostic tool. Therefore, no MRMC study or evaluation of human reader improvement with AI assistance would be relevant or performed.

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

This information is not applicable. The device is a physical instrument, not an algorithm.

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

This information is not applicable. No "ground truth" for diagnostic purposes is discussed or needed for a speculum 510(k) submission. The "truth" here relates to the device meeting safety standards and performing its intended mechanical function.

8. The sample size for the training set

This information is not applicable. There is no "training set" for a physical medical device like a speculum.

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

This information is not applicable. As there is no training set, there is no ground truth establishment for it.

In summary: The provided document is a 510(k) summary for a physical medical device (gynecological specula). It focuses on demonstrating substantial equivalence to a predicate device through shared technological characteristics and compliance with safety standards (ISO 10993). The questions you've posed are primarily relevant to the evaluation of AI/CADe (Computer-Aided Detection/Diagnosis) systems, which process and interpret data, and therefore, most of the answers are "not applicable" in this context.

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The RI. MOS. Cervical and Intracervical Anaesthesia Needles are used to apply cervical and intracervical anesthesia block.

The RI. MOS. s.r.l. cervical and intracervical needles operate with standard medical syringes are are sterile, single-use, disposable devices.

The provided text is a 510(k) summary for a medical device: "RI. MOS. s.r.l. cervical anesthesia needle and intracervical anesthesia needle." This document focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting a study that establishes performance against specific acceptance criteria.

Therefore, most of the requested information regarding acceptance criteria and performance studies is not available in the provided text. The 510(k) process for devices like needles primarily relies on showing that the new device has the same intended use, technological characteristics, and performance as an existing, legally marketed device.

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

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

• Not Available. The document does not define specific acceptance criteria (e.g., in terms of mechanical strength, sterility, or anesthesia efficacy) nor does it report the device's performance against such criteria. The submission is a claim of substantial equivalence.

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

• Not Available. No test study or data provenance is mentioned.

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 Available. There is no mention of a test set, experts, or ground truth establishment.

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

• Not Available. No adjudication method is mentioned as there is no test set or study.

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 is a medical needle, not an AI-assisted diagnostic device. No MRMC study was performed.

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

• Not Applicable. This is a medical needle, not an algorithm.

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

• Not Available. No ground truth is established or mentioned in the context of a performance study. For a 510(k) submission of this type, the "ground truth" for regulatory review is the substantial equivalence to a predicate device based on its intended use and technological characteristics.

8. The sample size for the training set

• Not Applicable. This is not a machine learning or AI device that would require a training set.

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

• Not Applicable. As above, no training set or associated ground truth establishment.

Summary of available information from the document:

• Device Name: RI. MOS. s.r.l. cervical anesthesia needle and intracervical anesthesia needle.
• Intended Use: Applying cervical and intracervical anesthesia block.
• Predicate Device: Potocky Needle® marketed by CooperSurgical.
• Basis for Acceptance: Substantial equivalence to the predicate device, meaning the new device has "the same or similar technological characteristics" and intended use as the predicate. The FDA's letter (FEB 1 1999) explicitly states that the device is "substantially equivalent" for the stated indications for use.
• Device Characteristics: Sterile, single-use, disposable devices that operate with standard medical syringes.

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