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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 does not contain specific acceptance criteria or an analytical study proving the device meets those criteria. Instead, it describes a 510(k) submission for the DVS (Dose Verification System) focusing on its substantial equivalence to predicate devices and the modifications made.

However, based on the text, we can infer some general acceptance criteria and the type of study conducted, though not its detailed results.

Inferred Acceptance Criteria and Device Performance (based on general statements in the document):

Study Information Based on the Text:

Since the provided text is a 510(k) summary, it details the submission for substantial equivalence rather than a detailed clinical or performance study with raw data and statistical analysis. The text 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 efficacv and demonstrated that the device met 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)."

This indicates that internal verification and validation testing was performed. However, the document does not provide the specific details requested for the study, such as:

1. Sample size used for the test set and the data provenance: Not mentioned.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
3. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not mentioned.
4. 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 mentioned. The device is a dosimeter, not an AI-assisted diagnostic tool.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not explicitly stated as a "standalone" study in the context of an algorithm, but the "verification and validation testing" would have assessed the device's inherent performance.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not mentioned. For a dosimeter, ground truth would typically refer to highly accurate reference dosimetry measurements (e.g., from ion chambers or calibrated phantoms).
7. The sample size for the training set: Not mentioned. Dosimeters are typically calibrated, not "trained" in the machine learning sense.
8. How the ground truth for the training set was established: Not mentioned. Calibration would be against known radiation doses from a calibrated source.

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The OneDose Patient Dosimetry System is intended to measure a patient's dose during radiotherapy application.

The OneDose Patient Dosimetry System consists of the following components and accessories: (1) disposable, single use, pre-calibrated radiation dosiments, (2) a hand held, battery powered reader, (3) a reader calibration test strip and (4) reader download software. The dosimeters use a MOSFET, metal oxide semiconductor field effect transistor as a sensing mechanism. The dosimeters are inserted into the Reader and zeroed, then positioned onto a patient. The dosimeters are small and have no wires. They have a medical grade adhesive and liner on the back. The liner is removed and the adhesive side of the dosimeter is adhered to the patient. Following radiotherapy, the dosimeters are removed from the patient, re-inserted into the Reader, and the patient's dose is read and reported by the Reader. The patient's records are stored on the dosimeter for future reference and in the Reader's memory.

The provided text states that "verification and validation testing provided information sufficient to determine that the modifications did not have an effect on safety or effectiveness and demonstrated that the device met pre-determined acceptance criteria based on performance specifications." However, specific details about the acceptance criteria, the study design, and the reported device performance are not explicitly provided in the furnished document.

Therefore, I cannot populate the table or answer the specific questions about the study that proves the device meets the acceptance criteria with the information given. The document mentions that the primary difference between the predicate and modified device is a "change in the accuracy specification," which implies that accuracy was an acceptance criterion, but the exact target and achieved performance are not listed.

Despite this, I can extract the following relevant information:

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

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

• Test Set Sample Size: Not specified.
• Data Provenance: 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)

• Not applicable as this is a dosimetry device, not an imaging analysis device requiring expert interpretation for ground truth. The ground truth would typically be established by physical measurements or established radiation dosimetry standards. Details of such ground truth establishment are not provided.

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

• Not applicable for this type of device and study as described.

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 radiation dosimetry system, not an AI-assisted diagnostic imaging device requiring human reader studies.

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

• The device is a "standalone" dosimetry system in the sense that it measures dose directly. The testing mentioned in the document would have evaluated the device's accuracy and performance independently.
• The document states: "Furthermore, verification and validation testing provided information sufficient to determine that the modifications did not have an effect on safety or effectiveness and demonstrated that the device met pre-determined acceptance criteria based on performance specifications." This implies standalone testing of the device's performance.

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

• Not explicitly stated, but for a radiation dosimeter, the ground truth would typically be established through physical measurements using calibrated reference dosimeters or by calculations based on known radiation fields, rather than expert consensus, pathology, or outcomes data.

8. The sample size for the training set

• Not applicable. This device is a measurement system, not a machine learning algorithm that requires a "training set" in the conventional sense. Its calibration and performance are based on physical principles and engineering, not data training.

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

• Not applicable for the same reason as in point 8.

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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.

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 is a 510(k) summary for the DVS (Dose Verification System) and discusses its substantial equivalence to a predicate device. It does not contain detailed information about specific acceptance criteria, device performance metrics (other than stating "the dosimeter performance specifications are the same and have not changed"), sample sizes for testing, ground truth establishment, or clinical study designs (such as MRMC studies).

Therefore, I cannot populate the table or answer most of the questions based on the provided text.

Here is what can be inferred or stated about the information requested:

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

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

• Sample size: Not specified.
• Data provenance: Not specified (e.g., country of origin, retrospective or prospective). The document mentions "verification and validation testing" but does not detail the nature of the test set.

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

• Not specified. The document does not describe the establishment of a "ground truth" using human experts for the test set.

4. Adjudication method for the test set:

• Not specified, as no expert adjudication of a test set is mentioned.

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 MRMC comparative effectiveness study is mentioned. This device is a hardware/software system for dose verification, not an AI-assisted diagnostic tool for human readers.

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

• This device is not an algorithm-only system. It's a physical dosimeter and reader system with accompanying software. The document states "verification and validation testing... demonstrated that the device met pre-determined acceptance criteria based on performance specifications," which implies standalone testing of the system's performance.

7. The type of ground truth used:

• The document implies that the device's measurements are validated against established physical dosimetry principles and potentially against existing clinical dose measurement standards (given its use for "verification of the prescribed dose"). However, the specific type of ground truth (e.g., gold standard phantom measurements, comparison to other validated dosimetry systems) is not explicitly detailed.

8. The sample size for the training set:

• Not applicable. This device is not an AI/ML model that requires a training set in the typical sense. It is a measurement device.

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

• Not applicable, as there is no training set for an AI/ML model for this device.

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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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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 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 radioopague 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, up to 25 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 does not contain detailed information about acceptance criteria or a specific study proving the device meets acceptance criteria. The document is a 510(k) summary for regulatory submission, focusing on device description, predicate device comparison, and indications for use. It mentions performance studies and preclinical studies were conducted, and that the performance data demonstrates that calibrated devices perform within the stated performance specifications of the labeling, but does not provide the specifics of these studies or the quantitative acceptance criteria.

Therefore, many of the requested sections cannot be filled from the provided text.

Here's a breakdown of what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size (Test Set): Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions "performance studies, pre-clinical studies, and clinical studies" were conducted, but gives no details about them.

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

• Not specified. The device is a dosimeter, so the "ground truth" would likely be a known radiation dose, rather than expert interpretation of images.

4. Adjudication method for the test set

• Not specified. This is typically relevant for studies involving human interpretation or subjective assessments, which isn't directly applicable to a dosimeter's primary function as described.

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 device is a patient radiation dosimeter, not an AI-assisted diagnostic tool for human readers.

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

• No specific standalone algorithm performance study is detailed. The device itself (the DVS implantable dosimeter and reader system) performs the measurement and relies on factory calibration. The text states "performance data section demonstrates that calibrated devices perform within the stated performance specifications of the labeling." This implies internal testing of the device's accuracy.

7. The type of ground truth used

• The ground truth would be precise, known radiation dose values, provided by calibrated radiation sources. The text mentions "The DVS, Dose Verification System is calibrated at the factory using the same method as the Thomson Nielsen for evaluating radiation units/volts" and that an external ADCL lab verifies factory calibration for similar devices. This suggests a rigorous calibration process against established standards.

8. The sample size for the training set

• Not applicable. This device is a hardware dosimeter with associated software; it's not described as a machine learning algorithm that requires a "training set" in the conventional sense. Its "training" is its factory calibration.

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

• Not applicable as it's not an ML system. For its calibration (analogous to training), the ground truth is established through "controlled conditions at the factory" using methods similar to predicate devices, and potentially validated by an "external ADCL lab." The "factory calibration procedure is described in sufficient detail within the 510(k) to demonstrate the methods used to assure calibration."

Summary of Missing Information:

The document is a high-level regulatory summary and does not delve into the specifics of the actual performance studies, including:

• Quantitative acceptance criteria (e.g., accuracy percentages, dose deviation limits).
• Detailed results of the performance studies.
• Protocols and methodologies of the pre-clinical and clinical studies.
• Sample sizes for any testing or validation.
• Specific ground truth methodologies beyond general statements about calibration.

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The OneDose Patient Dosimetry System is intended to measure a patient's dose during radiotherapy applications.

The OneDose Patient Dosimetry System consists of the following components and accessories: (1) disposable, single use, pre-calibrated radiation dosimeters, (2) a hand held, battery powered, reader, and (3) a reader calibration test strip. The dosimeters use a metal oxide semiconductor field effect transistor as a sensing mechanism. The dosimeters are inserted into the Reader and calibrated prior to use on a patient. The dosimeters are small and have no wires. They have a medical grade adhesive and liner on the back. The adhesive side of the dosimeter is adhered to the patient. Following radiotherapy, the dosimeters are removed from the patient, re-inserted into the Reader, and the patient's dose is read and reported by the Reader. The dose records are stored on the dosimeter for future reference and in the Reader's memory.

The provided document K040687 is a 510(k) summary for the Sicel Technologies, Inc. OneDose Patient Dosimetry System. This document describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not contain a detailed study proving the device meets specific acceptance criteria in the format typically expected from a clinical performance study.

510(k) submissions primarily focus on demonstrating substantial equivalence to a legally marketed predicate device, rather than providing independent clinical performance data against pre-defined acceptance criteria for a novel device. The document states that the "data contained with the methods section demonstrates that calibrated devices perform within the stated performance specifications of the labeling." This implies that performance data was submitted, but the specific acceptance criteria and detailed study results are not explicitly provided within this summary.

Therefore, many of the requested fields cannot be filled directly from the provided text.

Here's an attempt to answer based on the available information and highlighting what is not present:

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

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

• Sample Size: Not specified in this 510(k) summary.
• Data Provenance: Not specified. It can be inferred that testing was conducted by the manufacturer, Sicel Technologies, Inc., likely at their facilities in Morrisville, NC, but the specific country of origin or whether it was retrospective or prospective is not mentioned for the performance data.

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

• Number of experts: Not applicable. For dosimetry devices, "ground truth" is typically established by physical measurements using highly accurate reference equipment or established radiation physics principles, not by human expert opinion.
• Qualifications of experts: Not applicable.

4. Adjudication method for the test set:

• Not applicable. Adjudication methods like 2+1 or 3+1 are used for subjective interpretations (e.g., image reading), not for objective physical measurements from a dosimetry 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 is a dosimetry device, not an AI-assisted diagnostic tool. MRMC studies are not relevant here.

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

• Yes, implicitly. The OneDose Patient Dosimetry System is a standalone device that measures and reports patient dose. Its performance would be evaluated as such. The device's function is to objectively measure a dose, not to assist humans in interpretation.

7. The type of ground truth used:

• The ground truth would be established through highly accurate and traceable radiation measurements using established laboratory standards and reference dosimetry equipment. This could involve direct measurements in controlled radiation fields. The summary indirectly hints at this by mentioning "evaluating radiation factors" and "calibrated under controlled conditions at the factory."

8. The sample size for the training set:

• Not applicable in the typical sense for machine learning algorithms. This device is based on a MOSFET sensing mechanism, which relies on physical principles, not a "training set" in the context of AI/ML. The "calibration" performed at the factory might involve using a set of known radiation doses to ensure the device accurately converts the MOSFET response into a dose reading, but this is distinct from an AI training set.

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

• Not applicable for the reasons stated in point 8. The calibration process would involve exposing the devices to precisely known radiation doses and adjusting the device's internal parameters (or ensuring they meet specifications) to report these doses accurately.

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