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The Insertion Tool is used to facilitate the introduction of a guidewire during general intravascular procedures.

The Insertion Tool is a sterile accessory device indicated to facilitate the introduction of a guidewire into the lumen of a guiding catheter, without damage to the guidewire's distal tip.

It is designed to accommodate guidewires with diameters from 0.010" to 0.018" and is composed of a rigid funnel known as the hub which is attached to a stainless steel hypotube. The interior of the hub is designed to allow a guidewire with multiple bends at the distal tip to be directed easily into the smaller diameter stainless steel hypotube.

This document is a 510(k) summary for an "Insertion Tool" and does not relate to an AI/ML device. Therefore, the requested information about acceptance criteria, study details, human-in-the-loop performance, and training/test set specifics for an AI/ML model is not applicable and cannot be extracted from the provided text.

The document describes a medical device, its intended use, and comparison to predicate devices, focusing on design verification and validation through bench tests. There is no mention of AI/ML algorithms or their performance in this submission.

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Intended Use

The DVS (Dose Verification System) is intended for use in radiation therapy to verify treatment planning and radiation dose to tissue and organs in or near the irradiated areas of a patient.

Indications for Use

The DVS system is specifically indicated for breast and prostate cancer to measure photon beam therapy and as an adjunct to treatment planning to permit measurement of the in vivo radiation dose received at the tumor periphery, tumor bed and/or surrounding normal tissues for validation of the prescribed dose.

The DVS, Dose Verification System consists of four sub-systems: the DVS Implantable Dosimeter for measuring radiation dose in vivo, the DVS Insertion Tool for implanting the dosimeter during percutaneous procedures, the DVS Reader System (Wand and Base Station) for powering the dosimeter and providing a user interface when taking dose measurements, and the DVS Data System (Plan and Review Software and Dosimetery Database) for storing and reporting patient data and for storing dosimeter information. The dosimeters use a MOSFET, Metal Oxide Semiconductor Field Effect Transistor, as a sensing mechanism. The dosimeter is factory calibrated and powered by the Reader Wand utilizing electromagnetic energy. The dosimeter contains a transmitter, to transmit threshold voltage readings to the reader. It is radioopaque and thus registers on computed tomography scans as a point of interest whereby a point dose may be determined. Patients are implanted prior to radiotherapy. Information on the patient's therapy, dose planning, point dose at the dosimeter, dosimeter serial number and calibration files are entered into the Plan and Review software and stored in the Dosimetry Database. At each therapy fraction the dosimeter is read pre- and post-therapy using the Reader Wand and Base Station. This translates into a daily fractional dose. The patient's daily and cumulative dose may be reviewed via the Plan and Review software. Because the Plan and Review software and Dosimetry Database are designed to be stored on a server, multiple users may be logged into the system at any one time. Reports on the patient's daily and cumulative dose history may be printed using the Plan and Review software.

The provided 510(k) summary for the Sicel Technologies, Inc. DVS (Dose Verification System) describes the device, its intended use, and its comparison to predicate devices, but it does not contain the specific details required to answer all of your questions regarding acceptance criteria and the comprehensive study that proves the device meets those criteria.

Specifically, the document states: "Furthermore, verification and validation testing based on the risk analysis, provided information sufficient to determine that the modifications did not have an effect on safety or efficacy and demonstrated that the device met pre-determined acceptance criteria based on performance specifications. The testing demonstrated that the modified device is substantially equivalent to the predicate device and performs as well as the predicate device. The verification and validation results are provided within the 510(k)." However, these detailed results are not included in the provided text extract.

Therefore, many of your questions cannot be answered with the given information.

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

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

• Cannot fully answer. While the document mentions "pre-determined acceptance criteria based on performance specifications" and a "change in the accuracy specification" for the modified device, the actual numerical acceptance criteria and the reported device performance against these criteria are not provided.

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

• Cannot answer. This information is not present in the provided text.

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)

• Cannot answer. This information is not present in the provided text. The DVS is a dosimeter for measuring physical radiation dose, not an imaging device requiring expert interpretation for ground truth. Its ground truth would likely be established from known radiation sources and measurement standards.

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

• Cannot answer. This information is not present in the provided text. Given the nature of a dosimeter, "adjudication" in the context of expert consensus on image interpretation is not applicable.

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

• Cannot answer. This information is not present in the provided text. The DVS is a diagnostic tool for measuring radiation dose, not an AI-assisted diagnostic imaging system that would typically undergo an MRMC study. There's no mention of AI integration for human reader improvement.

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

• Partially Answerable (by inference but no direct statement). The DVS is a physical device (dosimeter) that measures radiation. Its performance would inherently be "standalone" in terms of its measurement accuracy, as it directly detects and quantifies radiation. The human interaction is with reading the device output and integrating it into treatment planning, not in performing the measurement itself. The "verification and validation testing" mentioned would have evaluated the device's accuracy in a standalone manner.

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

• Partially Answerable (by inference). For a radiation dosimeter, the ground truth would typically be established by:
  • Known radiation sources: Measuring reference radiation fields with well-established and traceable dose rates.
  • Comparison to other validated dosimeters/standards: Comparing the DVS readings to those of other highly accurate and calibrated dosimeters.
  • This would involve physical measurements and calibration against international standards, not expert consensus or pathology data.

8. The sample size for the training set

• Cannot answer. This information is not present. As a physical measurement device, it's not "trained" in the typical machine learning sense with a training set. It is factory calibrated.

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

• Cannot answer definitively. As explained above, the device is "factory calibrated." This means its response to known radiation doses is characterized and stored. The methods for establishing the ground truth for this factory calibration (e.g., using primary or secondary standard dosimetry systems) are not detailed in the provided text.

In summary, the provided 510(k) summary serves as an administrative document for regulatory submission and does not contain the detailed technical study results you are seeking. These details would typically be found in the full 510(k) submission documentation, including specific test reports and performance data.

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Intended Use: The DVS (Dose Verification System) is intended for use in radiation therapy to verify treatment planning and radiation dose to tissue and organs in or near the irradiated areas of a patient.

Indications for Use: The DVS system is specifically indicated for breast and prostate cancer to measure photon beam therapy and as an adjunct to treatment planning to permit measurement of the in vivo radiation dose received at the tumor periphery, tumor bed and/or surrounding normal tissues for validation of the prescribed dose.

The DVS, Dose Verification System consists of four sub-systems: the DVS Implantable Dosimeter for measuring radiation dose in vivo, the DVS Insertion Tool for implanting the dosimeter during percutaneous procedures, the DVS Reader System (Wand and Base Station) for powering the dosimeter and providing a user interface when taking dose measurements, and the DVS Data System (Plan and Review Software and Dosimetery Database) for storing and reporting patient data and for storing dosimeter information. The dosimeters use a MOSFET, Metal Oxide Semiconductor Field Effect Transistor, as a sensing mechanism. The dosimeter is factory calibrated and powered by the Reader Wand utilizing electromagnetic energy. The dosimeter contains a transmitter, to transmit threshold voltage readings to the reader. It is radioopaque and thus registers on computed tomography scans as a point of interest whereby a point dose may be determined. Patients are implanted prior to radiotherapy. Information on the patient's therapy, dose planning, point dose at the dosimeter, dosimeter serial number and calibration files are entered into the Plan and Review software and stored in the Dosimetry Database. At each therapy fraction the dosimeter is read pre- and post-therapy using the Reader Wand and Base Station. This translates into a daily fractional dose. The patient's daily and cumulative dose may be reviewed via the Plan and Review software. Because the Plan and Review software and Dosimetry Database are designed to be stored on a server, multiple users may be logged into the system at any one time. Reports on the patient's daily and cumulative dose history may be printed using the Plan and Review software.

The provided text describes a medical device, the DVS (Dose Verification System), and its regulatory submission. However, it does not contain specific information about acceptance criteria for performance, a study proving those criteria were met, or details related to an AI/ML device.

The document is a 510(k) summary for a patient radiation dosimeter. It focuses on:

• Device Description: What the DVS is and how it works (MOSFET technology for in vivo radiation dose measurement).
• Intended Use/Indications for Use: To verify treatment planning and radiation dose in radiation therapy, specifically for breast and prostate cancer to measure photon beam therapy.
• Comparison to Predicate Device: Stating that the intended use and technological features are largely the same as a predicate device, with an additional indication for prostate cancer.
• Regulatory Information: Submitter details, FDA communication, and classification.

Therefore, I cannot provide the requested information about acceptance criteria, performance study details, or AI/ML-specific metrics because these details are not present in the provided text.

To address the prompt directly with the information available:

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

This information is not provided in the document. The document describes the device, its intended use, and its equivalence to a predicate device, but does not detail specific performance metrics, acceptance criteria, or results from a performance study.

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. No test set 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)

This information is not provided in the document. There is no mention of experts or ground truth establishment for a test set.

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

This information is not provided in the document. There is no mention of adjudication or a test set.

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 provided in the document. The DVS is a patient radiation dosimeter, not an AI/ML-assisted diagnostic device. Therefore, an MRMC study related to human reader improvement with AI assistance would not be applicable to this device and is not mentioned.

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

This information is not provided in the document. The DVS is a physical implantable device with a reader and software, not an algorithm in the sense of AI/ML. Its performance is inherent to its physical measurement capabilities.

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

This information is not provided in the document. For a radiation dosimeter, ground truth would typically refer to a known, accurately measured radiation dose from a reference instrument. However, the document does not elaborate on how this was established for validation.

8. The sample size for the training set

This information is not provided in the document. As this device is not described as an AI/ML device, a "training set" in that context would not apply.

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

This information is not provided in the document. (See point 8).

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For Plastic and Reconstructive Surgery* * This product is available by prescription only.

Softform® Implant Soft Tissuc Augmentation Tube with Insertion Tool - Size Modifications

{
"1. A table of acceptance criteria and the reported device performance": "The provided text is an FDA 510(k) clearance letter and an 'Indications for Use' page. It does not contain information about specific acceptance criteria or detailed device performance metrics. Its purpose is to declare substantial equivalence to a predicate device and outline the approved indications for use.",
"2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)": "The provided document does not contain information about a test set sample size or data provenance. This type of detail is typically found in the 510(k) submission itself, not in the clearance letter or indications for 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)": "The provided document does not contain information about experts used to establish ground truth or their qualifications. This is not typically part of an FDA clearance letter.",
"4. Adjudication method (e.g. 2+1, 3+1, none) for the test set": "The provided document does not contain information about an adjudication method for a test set. This detail would be found in the device's validation study, not in the regulatory clearance.",
"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": "The provided document does not contain information about a multi-reader multi-case (MRMC) comparative effectiveness study or any effect sizes related to human-AI collaboration. This type of study is more common for diagnostic AI tools, which doesn't seem to be the primary function of the 'Softform® Implant' mentioned.",
"6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done": "The provided document does not contain information about a standalone algorithm performance study. The device, 'Softform® Implant', is described as a 'Soft Tissue Augmentation Tube with Insertion Tool', suggesting it's a physical implant and not an algorithm-based device requiring standalone performance evaluation.",
"7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)": "The provided document does not contain information about the type of ground truth used. As a medical implant, 'ground truth' for its safety and effectiveness would likely come from pre-clinical testing, clinical trials, and material properties, rather than expert consensus on image interpretation or pathology in the context of an algorithm.",
"8. The sample size for the training set": "The provided document does not contain information about a training set sample size. Given the nature of the device ('Softform® Implant' - a soft tissue augmentation tube), it is highly unlikely that an AI training set would be relevant or discussed in its regulatory clearance.",
"9. How the ground truth for the training set was established": "The provided document does not contain information about how ground truth for a training set was established. As noted above, this device does not appear to be an AI/algorithm-based device for which a training set and its associated ground truth would be relevant."
}

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