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The p.d software is used by radiation therapy professionals to assist in the design, manufacturing, and quality assurance testing of various radiation therapy devices used for cancer patients. The p.d software performs three distinct, primary functions which each are described below.

1. The p.d software takes a design of a compensating filter from a Treatment Planning System and converts the Treatment Planning System compensator filter files into a .decimal file format. This file can then be electronically submitted to .decimal through the software, so that we can manufacture the device.
2. The p.d software can design a beam shaping and compensating filters based on Treatment Planning System and other user supplied data. The device designs for compensating filters will be transferred back into the Treatment Planning System for final dose verification before devices are ordered and used for patient treatment.
3. The p.d software can perform quality assurance testing of the physical characteristics of treatment devices using data from various types of scanned images, including computed tomography images.

The .decimal p.d device is a software application that will enable users of various radiation treatment planning systems (TPS) to design, measure, and order beam shaping and modulating devices used in the delivery of various types of radiotherapy, including photon, electron, and particle therapy. The input from the treatment planning systems to the p.d product is generally received in DICOM file format. but other vendor specific or generic file formats are also utilized. p.d will also provide a simplified radiation dose calculator for the purpose of improving its ability to accurately create/modify patientspecific radiation beam modifying devices without the need for iteration with other treatment planning systems. However, all modulating devices will have final dose verification performed in a commissioned Treatment Planning System before devices are used for patient treatment. Additionally, the p.d software contains tools for analyzing scanned image data that aids users in performing quality assurance measurement and testing of radiotherapy devices.

The provided text describes the p.d 5.1 software, a device used in radiation therapy. However, it does not contain the detailed information required to fully answer your request regarding acceptance criteria and a specific study proving the device meets them. This document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a performance study with detailed acceptance criteria.

While the document indicates some testing was done, it doesn't provide the specifics you're asking for. Here's what can be inferred and what's missing:

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

Missing Information: The document does not provide a table of acceptance criteria with specific quantitative thresholds or reported device performance metrics. The testing described is more qualitative and focused on comparing to predicate devices and general software validation.

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

Missing Information:

• Sample Size: Not specified.
• Data Provenance: Not specified. The document mentions "hospital-based testing partners" but doesn't detail the origin or nature of the data used in validation.
• Retrospective/Prospective: Not specified.

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)

Missing Information: The document does not specify the number or qualifications of experts used for establishing ground truth in the test set. It mentions "Clinically oriented validation tests were written and executed by .decimal personnel and hospital-based testing partners," but this doesn't detail specific expert involvement for ground truth adjudication.

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

Missing Information: The document does not describe any specific adjudication method for establishing ground truth for the 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

Missing Information:

• MRMC Study: No MRMC comparative effectiveness study is mentioned.
• Effect Size: Not applicable, as no MRMC study was described. The focus is on demonstrating substantial equivalence of the software's functionality to existing tools. This device is an aid to radiation therapy professionals, not an AI to improve human reader performance in a diagnostic context.

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

Information Available (Inferred): The testing seems to have been primarily standalone, focusing on the software's ability to perform its functions (design filters, convert files, perform QA measurements) and comparing its output to predicate devices. The document states "Clinical testing was not performed... since testing can be performed such that no human subjects are exposed to risk." This suggests the validation was primarily of the software's internal logic and output, rather than its performance in conjunction with a human user in a clinical setting with real patient outcomes.

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

Information Available: The ground truth for the validation tests was established by:

• Comparing results to those of known predicate devices (p.d software version 5.0 and Eclipse TPS).
• Performing quality assurance measurements on devices of known quality.

This implies a form of "reference standard" or "known truth" derived from established systems and manufactured devices, rather than clinical pathology or patient outcomes.

8. The sample size for the training set

Not Applicable/Missing Information: The document describes software validation and verification, not the training of a machine learning model. Therefore, there is no "training set" in the context of AI/ML. If the "p.d software" incorporates algorithms that are based on machine learning, this information is not provided. The phrasing "using nearly identical algorithms and processes" to the predicate software suggests it's more of a deterministic software rather than a trained AI model.

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

Not Applicable/Missing Information: As there's no mention of a training set for an AI/ML model, this question is not applicable.

Summary of Device Performance (from the document):

The document concludes with: "These tests show that the p.d software performed equivalently to the predicate device when appropriate and that the software is deemed safe and effective for clinical use."

This is a general statement of performance, but it lacks the specific, quantifiable acceptance criteria and corresponding reported performance metrics that your request specifies. The 510(k) process primarily aims to demonstrate substantial equivalence, and the provided document reflects that focus.

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The p.d software is used by radiation therapy professionals to assist in the treatment of cancer patients. The p.d software takes a Treatment Planning System design of a compensating filter which contains steep, narrow, and unmachinable areas and then smoothes them out into a machinable surface. And the software converts Treatment Planning System compensator filter file into a .decimal file format.

Optionally the user may elect to design a beam shaping compensator filter based on Treatment Planning System's data which will be transferred back into the Treatment Planning System for final dose verification. The customer uses the software in-house before sending the file to .decimal to be manufactured. Each filter must be QA'd and approved by a radiation therapy professional prior to use on a patient.

The p.d software is used by radiation therapy professionals to assist in the treatment of cancer patients. The p.d software takes a Treatment Planning System design of a compensating filter which contains steep, narrow, and unmachinable areas and then smoothes them out into a machinable surface. And the software converts Treatment Planning System compensator filter file into a .decimal file format.

Optionally the user may elect to design a beam shaping compensator filter based on Treatment Planning System's data which will be transferred back into the Treatment Planning System for final dose verification. The customer uses the software in-house before sending the file to .decimal to be manufactured. Each filter must be QA'd and approved by a radiation therapy professional prior to use on a patient.

This document is related to a 510(k) premarket notification for the ".decimal p.d" software, which assists in radiation therapy. The provided text does not contain acceptance criteria for device performance, nor does it detail a study proving the device meets specific acceptance criteria using statistical metrics like sensitivity, specificity, or accuracy.

The document states:

• "Clinical testing is not required to demonstrate substantial equivalence or safety and effectiveness of this device." This explicitly indicates that a clinical study, as typically understood for evaluating device performance against acceptance criteria using patient data, was not performed.
• Instead, "Clinically oriented validation test cases were written and executed by in house .decimal customer support personnel including Board Certified Medical Physicists." This suggests an internal validation process focused on functional and technical correctness, rather than a statistical evaluation of clinical performance.

Therefore, I cannot provide the requested information regarding acceptance criteria, reported device performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth establishment in the context of a clinical performance study. The provided text does not support such an analysis.

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The p.d software takes a Treatment Planning System design of a compensating filter used for radiation therapy which contains steep, narrow, and unmachinable areas and then smoothes them out into a machinable surface. The customer will use the software in-house before sending the file to .decimal to be manufactured. Each filter must be QA'd by the customer before use on a patient.

.decimal created a software translator to be used with a Radiation Therapy Treatment Planning Systems (TPS). The software takes the TPS design of a compensating filter used for radiation therapy which contains steep, narrow, and unmachinable areas and then smoothes them out into a machinable surface.

The provided text, K061440, describes a software translator called "p.d" designed to smooth out unmachinable areas in radiation therapy compensating filters. The document is a 510(k) summary for a premarket notification to the FDA in 2006.

However, the K061440 document does not contain the detailed acceptance criteria or a study that addresses the specific points requested in the prompt. It provides general information about the device, its intended use, and substantial equivalence to a predicate device, but lacks the specific performance data, sample sizes, expert qualifications, or study methodologies that would typically be found in a comprehensive validation or clinical study report.

Here's an analysis of what is and is not present in the provided text in relation to your request:

1. Table of acceptance criteria and the reported device performance:

• Not present. The document states that "p.d Software Validation" (PD-11) is attached in Section 11 and "Summary of Clinical Testing" is in Section 12, but these sections are not included in the provided text. Therefore, specific acceptance criteria (e.g., maximum deviation from original design, smoothing parameters, processing time) and quantitative performance metrics are not available.

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

• Not present. The document mentions "clinical testing" but does not provide any details about the test set size, data origin (country), or whether it was retrospective or prospective.

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

• Not present. There is no mention of experts, ground truth establishment, or their qualifications. The intended use states the customer verifies the filters, but this is an operational process, not a ground truth methodology for a study.

4. Adjudication method for the test set:

• Not present. Without details of a test set or ground truth establishment, an adjudication method is not mentioned.

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:

• Not present. This type of study is not mentioned. The device is a software translator for manufacturing, not an AI-assisted diagnostic tool that human readers would interpret.

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

• Implicitly yes, but no details of the study. The device is a "software translator" that takes a TPS design and smoothes it out. Its function is inherently standalone in that it performs an automated transformation of a digital design. However, there is no study described that evaluates its standalone performance against specific metrics. The "clinical testing" summary is referenced but not provided.

7. The type of ground truth used:

• Not explicitly stated, but inferred to be a comparison against the original "steep, narrow, and unmachinable areas" and the requirement for a "machinable surface." For this type of device, ground truth would likely involve geometric accuracy, smoothness criteria, and mechanical machinability assessments. However, the document does not specify how this ground truth was established for study purposes.

8. The sample size for the training set:

• Not present. As this is from 2006 and the device is described as a "software translator" to smooth designs, it's less likely to be a deep learning model requiring a large training set in the modern sense. It's more likely rule-based or algorithmic. Regardless, no training set size is mentioned.

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

• Not present.

In summary, the provided document K061440 primarily focuses on the regulatory submission for substantial equivalence. It points to validation and clinical testing summaries (Sections 11 and 12) which are not included in the provided text. Therefore, the specific details regarding acceptance criteria and study methodologies, as requested, cannot be extracted from this document alone.

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P.D. Access Device: Is intended for use when blood flow must be detected for percutaneous vessel cannulation. The vessel must be of a caliber which would normally be punctured with a needle and introducer of this size or larger. These additional probe/needle models are being incorporated to broaden the product line in order to accommodate both user preference and patient anatomies for all age groups.

P.D. Access Monitor: Is intended for use to audibly indicate the doppler response of blood flow within an artery or vein. It is intended for use only in conjunction with the P.D. Access Vascular Access Device.

The P.D. Access™ device is intended to be used in conjunction with the P.D. Access Dual Frequency Monitor for general vascular use. The P.D. Access device is intended for general vascular use for audibly indicating the Doppler response to blood flow within an artery or vein. The indications and intended use for the P.D. Access device is the same as the predicate devices manufactured by CardioVascular Dynamics (i.e., P.D. Access/SmartNeedle). Product technology, performance characteristics, specifications, components and materials of the P.D. Access device are similar to those of predicate devices.

The CardioVascular Dynamics, Inc. P.D. Access™ Vascular Access Device and P.D. Access™ Dual Frequency Monitor received 510(k) clearance based on substantial equivalence to predicate devices, rather than a study demonstrating meeting specific acceptance criteria with performance metrics. The submission focuses on comparing the new device's characteristics to already legally marketed devices.

Here's an analysis based on the provided documents:

1. Table of Acceptance Criteria and Reported Device Performance

The provided documents do not define specific quantitative acceptance criteria or present performance metrics in a manner typical for a study proving device efficacy or accuracy like sensitivity, specificity, or AUC. Instead, the acceptance is based on demonstrating substantial equivalence in design, materials, indications, and overall safety and effectiveness compared to predicate devices.

The "reported device performance" is described qualitatively as:

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

• The documents do not mention a specific "test set" in the context of an accuracy or performance study involving patient data or clinical outcomes.
• The testing described ("dimensional, strength, ultrasonic performance and biocompatibility testing") would have involved physical samples of the device components, not patient data.
• No information on provenance (country of origin, retrospective/prospective) of data is provided, as no clinical study data is presented for performance evaluation against ground truth.

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

• Not applicable. No clinical test set requiring expert ground truth establishment is described. The evaluation was primarily based on engineering and biocompatibility testing against predefined specifications, and a comparison to predicate devices, not an expert-adjudicated test set for diagnostic accuracy.

4. Adjudication Method for the Test Set

• Not applicable. No clinical test set requiring adjudication is described.

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

• No, an MRMC comparative effectiveness study was not done. The submission solely focuses on demonstrating substantial equivalence to predicate devices, not on comparing performance with and without AI assistance or evaluating human reader improvement. This device is a diagnostic tool (Doppler monitor and access device), not an AI-powered image analysis system.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• No, a standalone performance study in the context of an algorithm or AI is not applicable. The P.D. Access device is a physical medical device (vascular access and Doppler monitor) that audibly indicates blood flow, designed for human clinical use, not a standalone algorithm. The "ultrasonic performance" testing would have verified its function, but this is distinct from AI algorithm performance.

7. Type of Ground Truth Used

• The "ground truth" for the engineering and biocompatibility tests would be the established device specifications and regulatory standards for material properties, dimensions, ultrasonic output, and biocompatibility.
• For the substantial equivalence claim, the "ground truth" is effectively the performance and safety profiles of the predicate devices, against which the new device was compared.

8. Sample Size for the Training Set

• Not applicable. This device is not an AI/ML algorithm that requires a training set.

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

• Not applicable. As the device does not involve AI/ML, there is no training set and therefore no ground truth establishment for one.

Summary based on the 510(k) submission:

The 510(k) cleared the P.D. Access™ Vascular Access Device and Dual Frequency Monitor based on its substantial equivalence to existing predicate devices. The evidence provided included:

• Engineering and material testing (dimensional, strength, ultrasonic performance, biocompatibility) demonstrating the device met its own specifications and performed without failures.
• A detailed comparison chart showing product technology, performance characteristics, specifications, components, and materials were "similar" to predicate devices.
• An assertion that its indications for use and intended use were "the same" as predicate devices.

The FDA decision letter confirms this, stating the device is "substantially equivalent (for the indications for use stated in the enclosure) to devices marketed in interstate commerce prior to May 28, 1976... or to devices that have been reclassified." There were no clinical studies or performance accuracy studies against a "ground truth" as would be seen for new diagnostic algorithms or complex AI devices.

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The P.D. Access™ / SmartNeedle® Device is intended to be used in conjunction with the SmanNeedle® Monitor for general vascular use. The SmanNeedle® Monitor will also be marketed as the P.D. Access™ Monitor; and the Monitor graphics and labeling will be changed to reflect the name. Other than the name, the Monitors will be equivalent. There will be no change in safety and efficacy.

The P.D. Access™ / SmartNeedle® Device is indicated and intended for general vascular use for monitoring the flow of blood within the vasculature. The indications and intended use for of the P.D. Access™ / SmartNeedle® Device are the same as predicate devices manufactured by CardioVascular Dynamics (the SmartNeedle").

The P.D. Access™ / SmartNeedle® Device is intended to be used in conjunction with the SmanNeedle® Monitor for general vascular use. The SmanNeedle® Monitor will also be marketed as the P.D. Access™ Monitor; and the Monitor graphics and labeling will be changed to reflect the name. Other than the name, the Monitors will be equivalent. There will be no change in safety and efficacy. Product specifications, components and materials of the P.D. Access™ / SmartNeedle® Device are similar to those of predicate devices.

This 510(k) notification describes the P.D. Access™ / SmartNeedle® Device, a vascular access device intended for monitoring blood flow. The submission primarily focuses on demonstrating substantial equivalence to previously cleared predicate devices.

Here's an analysis based on your requested information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states: "Testing of the P.D. Access™ / SmartNeedle® Device included dimensional, strength, ultrasonic performance and biocompatibility testing. These tests demonstrated that the all items tested were within specification tolerances. There were no failures during these tests."

However, the specific quantitative "acceptance criteria" and "reported device performance" are not detailed in this summary. The summary only provides a qualitative statement of compliance. For example, it doesn't list a specific "strength tolerance" in Newtons and then a "reported strength" of X Newtons.

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

The document does not specify the sample sizes used for the dimensional, strength, ultrasonic performance, or biocompatibility tests. It also does not mention the country of origin of the data or whether the data was retrospective or prospective.

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

This information is not applicable and not provided. The study described focuses on device performance against engineering specifications (dimensional, strength, ultrasonic, biocompatibility) rather than a diagnostic performance where expert ground truth would be required.

4. Adjudication Method for the Test Set:

This information is not applicable and not provided, as the testing was against engineering specifications.

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

No. An MRMC comparative effectiveness study was not done. The device is a vascular access device with a monitoring function (audible blood flow). Its effectiveness is judged by meeting engineering specifications and being substantially equivalent to predicate devices, not by radiologists' diagnostic performance.

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

The concept of "standalone performance" as it applies to AI algorithms is not relevant here. This is a physical medical device. The "ultrasonic performance" testing would be considered the standalone performance of its monitoring capability. The document states this performance was within specification tolerances.

7. The Type of Ground Truth Used:

The "ground truth" for the tests described would be the pre-defined engineering specifications for dimensions, strength, ultrasonic output characteristics, and biocompatibility standards. These are objective measures rather than expert consensus, pathology, or outcomes data in the typical sense of diagnostic performance.

8. The Sample Size for the Training Set:

This information is not applicable and not provided. This device does not involve a "training set" in the context of machine learning or AI algorithms.

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

This information is not applicable and not provided, as there is no training set for this type of device.

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