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The Radionics DGP-HP Single Use Ground Pad is to be used with the Radionics Cooltip™ RF System.

The Radionics Disposable Grounding Pad, DGP-HP, is a dispersive electrode that self adheres to the patients skin. The pad consists of an electrode element made up of a rubberized foam backing, a conducting plate, and a conductive gel. The electrode element is joined to a cable and standard connector that interfaces with an RF generator.

This document describes the Radionics Single Use Grounding Pad (DGP-HP). The submission is a 510(k) summary, which indicates that the manufacturer is demonstrating substantial equivalence to a predicate device, rather than providing extensive de novo clinical trial data for new device approval. As such, the information typically requested in your prompt (e.g., detailed acceptance criteria, specific study designs, sample sizes for test and training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth establishment) is generally not included in a 510(k) summary for this type of device.

510(k) submissions for accessories like grounding pads primarily focus on demonstrating that the new device performs as intended and is as safe and effective as a legally marketed predicate device. This is often achieved through engineering testing, biocompatibility testing, electrical safety testing, and performance testing against recognized standards rather than extensive clinical efficacy studies with human subjects.

Here's a breakdown of the available information in relation to your request, with an emphasis on what is not present as per the nature of the document:

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

• Acceptance Criteria: The document states that the grounding pad is designed to conform to "applicable sections of ANSI/AAMI HF18-1993, IEC 60601-2-2, 1998, and ISO 10993-1." However, the specific acceptance criteria (e.g., maximum impedance allowed, specific temperature rise limits, adhesion strength, biocompatibility results) from these standards, and the reported device performance against them, are not detailed in this 510(k) summary. These details would typically be in a more comprehensive technical report submitted to the FDA, but not in the public 510(k) summary.
• Reported Device Performance: No specific quantitative performance metrics are provided in this summary. The summary only generally states that the device is a "dispersive electrode that self adheres to the patient's skin" and "interfaces with an RF generator."

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

• Not applicable/Not provided in this summary. For this type of device (electrosurgical grounding pad), a "test set" in the context of clinical performance data is not typically relevant in a 510(k) submission. Testing usually involves laboratory-based engineering and performance testing on physical units of the device, not clinical data sets.

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 in this summary. "Ground truth" established by human experts is relevant for diagnostic or AI-driven devices assessing images or patient data. This device is an accessory that performs a physical function.

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

• Not applicable/Not provided in this summary. Adjudication methods are used to resolve disagreements among experts interpreting data, which is not relevant for this device.

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

• No, this was not done. MRMC studies are specific to diagnostic devices, particularly those involving human interpretation of data, often with AI assistance. This device is a medical accessory, not a diagnostic tool with AI.

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

• No, this was not done. Standalone algorithm performance is relevant for AI/software devices. This is a physical medical device.

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

• Not applicable/Not provided in this summary. The "truth" for this device would be its adherence to engineering and safety standards, and its physical performance (e.g., maintaining safe temperature, proper electrical dispersion), rather than a clinical ground truth.

8. The sample size for the training set

• Not applicable/Not provided in this summary. Training sets are for AI/machine learning models.

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

• Not applicable/Not provided in this summary.

Summary of Device Acceptance and Study as described in the provided text (within the context of a 510(k) for an accessory):

The acceptance criteria for the Radionics Single Use Grounding Pad (DGP-HP) are based on the device conforming to applicable sections of recognized international and national standards:

• ANSI/AAMI HF18-1993
• IEC 60601-2-2, 1998
• ISO 10993-1

The "study" demonstrating the device meets these criteria is an internal performance and safety evaluation, the details of which are not public in this summary. Instead, the 510(k) process relies on the assertion of substantial equivalence to predicate devices (Radionics RFG-DGP Disposable Grounding Pad K923647 and Nikopad Electrosurgical Grounding Pad Model 4777M K000079) which presumably met similar standards and demonstrated safe and effective use. The FDA's clearance (K030697) indicates that they reviewed the manufacturer's submission (which would contain detailed test reports) and agreed that the new device is substantially equivalent to the predicates.

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Allows for drainage and monitoring of cerebrospinal fluid (CSF) from the lateral ventricles of the brain and the lumbar subarachnoid space in selected patients to reduce intracranial pressure (ICP), to monitor CSF, to provide temporary drainage of CSF in patients with infected CSF shunts, and the monitoring of ICP.

The XDS provides a simple to use, closed loop system for the drainage of cerebrospinal fluid (CSF) and allows for pressure monitoring. XDS consists of a disposable drainage bag attached to a drainage tubing set that incorporates a calibrated scale and a graduated drip chamber used for estimation of drainage fluids. The systems will be provided sterile and will be labeled for single use only.

This looks like a 510(k) summary for a medical device. Based on the provided text, there is no study described that demonstrates the device meets acceptance criteria. The document mainly focuses on establishing substantial equivalence to a predicate device for regulatory approval.

Specifically, the document states:

• Description: "The XDS provides a simple to use, closed loop system for the drainage of cerebrospinal fluid (CSF) and allows for pressure monitoring. XDS consists of a disposable drainage bag attached to a drainage tubing set that incorporates a calibrated scale and a graduated drip chamber used for estimation of drainage fluids. The systems will be provided sterile and will be labeled for single use only."
• Intended Use: "The XDS allows for drainage and monitoring of CSF from the lateral ventricles of the brain and the lumbar subarachnoid space in selected patients to reduce intracranial pressure (ICP), to monitor CSF, to provide temporary drainage of CSF in patients with infected CSF shunts, and the monitoring of ICP."
• Predicate Device: Medtronic Becker External Drainage and Monitoring System, K984053

A 510(k) summary typically includes a declaration that the device is substantially equivalent to a legally marketed predicate device. This often means that the device has similar technological characteristics and/or that differences in technological characteristics do not raise different questions of safety and effectiveness. It does not necessarily require the submission of extensive clinical performance studies comparing the new device against specific acceptance criteria in the same way a new drug or novel device might.

Therefore, I cannot extract the requested information regarding acceptance criteria and a study proving the device meets them from the provided text. The document is solely a regulatory filing for substantial equivalence based on a predicate device.

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The MMLC is intended to assist the radiation oncologist team in the delivery of radiation to well defined target volumes while sparing surrounding normal tissue and critical organs from excess radiation. This is accomplished through 31 pairs of opposing tungsten leaves, which allow the MMLC to shape the x-ray beam according to a treatment plan generated by a planning system such as the RSA XPlan software.

The MMLC is intended to assist the radiation oncologist team in the delivery of radiation to well defined target volumes while sparing surrounding normal tissue and critical organs from excess radiation. With Radionics' XPlan Conformal Treatment Planning Software or any treatment planning system, the MMLC enables static conformal treatments to be performed with finely shaped field patterns. In this application, the MMLC performs the same function as customized beam shaping blocks, and circular or cut block collimators, which have been used for many years.

The Mini Multi-Leaf Collimator (MMLC) is a complete system consisting of an independent device that attaches to a Siemens linear accelerator (LINAC) for small field conformal radiosurgery or radiotherapy. Along with XPlan Conformal Treatment Planning Software, the MMLC enables static conformal treatments to be performed with finely shaped field patterns created by independently actuated leaves.

The subject of this submission, the software modifications for the MMLC VR1, is for use in an installation of a Siemens LINAC with the Lantis Verify and Record system and the PrimeView front end. This program coordinates MMLC settings with the Siemens software and hardware and assures that the MMLC is set correctly to the same field as the LINAC setting, and can abort treatment if the MMLC cannot be set correctly.

Here's an analysis of the provided text regarding acceptance criteria and the study performed, structured as requested. It's important to note that the provided text is a 510(k) summary and approval letter, which typically focuses on substantial equivalence rather than detailed performance studies with quantified acceptance criteria in the manner often sought for AI/ML device evaluations. As such, some of the requested information may not be explicitly present.

Acceptance Criteria and Study for MMLC VR1

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not contain a formalized table of acceptance criteria with corresponding performance metrics in the way one might find for an AI/ML diagnostic device (e.g., sensitivity, specificity thresholds). Instead, the "performance" described relates to the system's functionality and its ability to correctly interface and coordinate with the Siemens LINAC.

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

• Test Set Sample Size: The document does not specify a numerical sample size for the test set. It mentions "a rigorous test of the functionality of the MMLC-Siemens interface was conducted using a Siemens LINAC." This implies physical testing with at least one LINAC setup.
• Data Provenance: The testing was conducted using a "Siemens LINAC, equipped with PrimeView and Lantis" and "Radionics MMLC interface hardware (BCI box)." This suggests a controlled, prospective testing environment rather than retrospective data analysis from patient studies. There is no information about the country of origin of the data beyond the company's location (Burlington, MA, USA).

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

This type of information is not provided in a 510(k) summary for a device like the MMLC. The "ground truth" for this device is not based on expert interpretation of medical images or patient outcomes, but rather on the correct mechanical and software functioning of the radiotherapy equipment. The "experts" involved would likely be engineers, physicists, and radiotherapy professionals conducting the functional tests, but their specific number or qualifications are not detailed.

4. Adjudication Method for the Test Set

Not applicable. The testing described is functional verification of mechanical and software interfaces, not expert adjudication of clinical findings.

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

No, an MRMC comparative effectiveness study was not done. The MMLC is for beam shaping in radiotherapy, not for diagnostic interpretation by human readers. Its "effectiveness" is in its ability to accurately and safely shape radiation beams, not in improving human diagnostic performance.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

The MMLC VR1's performance is inherently tied to its interaction with the LINAC and the treatment planning software, and ultimately, human operators oversee its use. The testing described is a standalone functional verification of the software and hardware integration, ensuring the algorithm (software modifications) correctly coordinates MMLC settings and safety functions. It's not a standalone diagnostic algorithm in the typical sense of AI/ML.

7. The Type of Ground Truth Used

The ground truth used for this device's validation is based on the correct and safe operational functionality and physical accuracy of the MMLC in shaping the X-ray beam as intended by the treatment plan and in coordination with the LINAC. This includes:

• Accurate setting of the MMLC leaves.
• Correct coordination between MMLC settings and LINAC settings.
• Effective abortion of treatment if MMLC settings are incorrect.

This is a technical ground truth rather than a medical/clinical ground truth (like pathology, expert consensus, or outcomes data).

8. The Sample Size for the Training Set

The document is a 510(k) summary for a hardware/software device primarily focused on mechanical functionality and software integration, not an AI/ML algorithm that learns from a "training set" of medical data. Therefore, the concept of a training set sample size, as typically understood for machine learning, does not apply here. The software modifications likely underwent traditional software development and testing cycles rather than machine learning training.

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

As noted above, the concept of a "training set" and its associated ground truth is not applicable to this type of device and its submission. The software was likely developed against functional specifications and tested against expected operational behaviors, not 'trained' on patient data.

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For recording, stimulating and lesioning nervous tissue for functional neurosurgical procedures such as but not limited to: cordotomies, tractotomies, myelotomies, thalamotomies and pallidotomies.

The above device consists of a recording electrode, sheath, adaptor bushing, spacer and passing cannula. It is used with the Nueromap System, CRW Stereotaxtic frame and lesion generator to record signals in determining the placement of lesions.

The provided text does not contain information about acceptance criteria or a study that proves the device meets those criteria. This 510(k) summary (K991399) primarily addresses the substantial equivalence of the Radionics Microelectrode Kit (MEK) to a predicate device based on its intended use and technological characteristics.

Therefore, I cannot provide the requested information, including:

1. A table of acceptance criteria and the reported device performance: No such criteria or performance data are mentioned.
2. Sample size used for the test set and the data provenance: No test set is described.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: No ground truth establishment is described.
4. Adjudication method: Not applicable as there is no described test set.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: No such study is mentioned.
6. Standalone (algorithm only without human-in-the-loop performance) study: This device is a physical electrode kit, not an algorithm.
7. The type of ground truth used: Not applicable as there is no described test set.
8. The sample size for the training set: This device is a physical electrode kit, not a machine learning model.
9. How the ground truth for the training set was established: Not applicable.

The submission focuses on basic device description, intended use, and comparison to a pre-amendments predicate device to demonstrate substantial equivalence, and not on performance studies with specific statistical endpoints or acceptance criteria.

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