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The Zap-X Radiosurgery System is intended to provide treatment planning and image-guided stereotactic radiosurgery and precision radiotherapy for tumors, lesions and conditions in the brain, head and neck when radiation treatment is indicated.

The subject device, a modification to the previously cleared Zap-X Radiosurgery System, is a computer-controlled system for performing non-invasive stereotactic radiosurgery that is selfshielded for ionizing radiation. A gantry-mounted linear accelerator provides the modified Zap-X System with a therapeutic radiation source, and a kV imaging system is used to locate the treatment target accurately. At the start of treatment, X-ray images of the patient skeletal anatomy serve to align the treatment target with respect to the system isocenter. During radiosurgical treatment, the kV imaging system of the modified Zap-X System tracks patient movement and adjusts the table precisely to compensate for such movement.

The subject device for which this submission is being made improves the patient tracking/alignment throughout treatment. This is the only new feature which has been implemented on the subject device differentiating it from the predicate device. There is no change to the system specifications as a result of this improvement in patient alignment - the overall system patient positioning is still within 1 mm as with the predicate device.

The provided document is an FDA 510(k) clearance letter and summary for the Zap-X® Radiosurgery System. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than proving clinical effectiveness through a standalone study with defined acceptance criteria and performance metrics.

Therefore, the document does not contain the following information typically found in a study designed to prove a device meets specific acceptance criteria:

• A table of acceptance criteria and reported device performance (in terms of clinical outcomes or diagnostic accuracy).
• Sample size used for a test set in a performance study, or data provenance for such a set.
• Number of experts used to establish ground truth for a test set, or their qualifications.
• Adjudication method for a test set.
• Multi-reader multi-case (MRMC) comparative effectiveness study, nor its effect size.
• Standalone (algorithm only without human-in-the-loop performance) study results.
• Type of ground truth used for a performance study (e.g., pathology, outcomes data).
• Sample size for a training set (as this is a medical device, not an AI/ML algorithm in the traditional sense, though it uses software).
• How ground truth for a training set was established.

What the document does describe is that the modified Zap-X Radiosurgery System was evaluated through non-clinical bench testing to demonstrate that it performed as intended and was substantially equivalent to its predicate device.

Here's an overview of the "acceptance criteria" and "study" as presented in this 510(k) submission:

1. Acceptance Criteria and Reported Device Performance:

The "acceptance criteria" in this context are primarily conformance to established design specifications and relevant industry standards, as well as demonstration of substantial equivalence to a predicate device. The "reported device performance" is that these specifications and standards were met.

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

• Sample Size: Not applicable in the context of clinical data for performance evaluation. The "tests" refer to engineering bench tests and validations of device components and software.
• Data Provenance: Not applicable for a typical "test set" as defined for clinical performance. The testing was internal ("Internal testing performed confirmed...") and focused on engineering validation.

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

• Not applicable. This submission doesn't describe a study involving expert-established ground truth for a clinical test set. The validation was against engineering specifications and industry standards.

4. Adjudication method for the test set:

• Not applicable, as there was no clinical test set requiring expert adjudication.

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, an MRMC comparative effectiveness study was not done. The device is a radiosurgery system for treatment delivery, not an AI-assisted diagnostic or interpretation tool for human readers.

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

• The device itself is a standalone system for radiosurgery. The "study" described is the non-clinical bench testing of this system. It is not an algorithm being assessed in isolation from a human-in-the-loop context. The enhancement is an "improvement in patient alignment during treatment" within the system itself.

7. The type of ground truth used:

• The "ground truth" for the non-clinical testing was defined by engineering design specifications, performance metrics derived from the predicate device, and the requirements of various industry standards (e.g., IEC 60601-1, IEC 62304).

8. The sample size for the training set:

• Not applicable. This is not a submission for an AI/Machine Learning algorithm that requires a "training set" in the common sense. The system is a medical device incorporating software and hardware.

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

• Not applicable, as there was no training set in the context of an AI/ML algorithm.

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The Zap-X Radiosurgery System is intended to provide treatment planning and image-guided stereotactic radiosurgery and precision radiotherapy for tumors, lesions and conditions in the brain, head and neck when radiation treatment is indicated.

The modified Zap-X Radiosurgery System ("Zap-X System") is a computer-controlled system for performing non-invasive stereotactic radiosurgery that is self-shielded for ionizing radiation. A gantry-mounted linear accelerator provides the modified Zap-X System with a source of therapeutic radiation and a kV imaging system is used to accurately locate the treatment target. At the start of treatment, X-ray images of patient skeletal anatomy serve to align the treatment target with respect to the system isocenter. During radiosurgical treatment, the kV imaging system of the modified Zap-X System tracks patient movement and adjusts the table precisely to compensate for such movement.

The provided text is a 510(k) premarket notification for the Zap-X Radiosurgery System. The purpose of this document is to demonstrate "substantial equivalence" to a legally marketed predicate device, not necessarily to establish acceptance criteria for de novo performance or to report on a study directly proving such criteria.

Therefore, the information requested about acceptance criteria and a study proving the device meets them, particularly regarding AI performance metrics, is largely not present in this document. This document focuses on demonstrating that the modified Zap-X System is equivalent to an existing device and thus does not require new acceptance criteria to be established or proven in the same way an entirely novel device might.

However, I can extract information related to the device's performance characteristics, safety, and testing methods that would implicitly serve as "acceptance criteria" for a substantial equivalence determination.

Here's a breakdown of the available information based on your request:

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

Since this is a substantial equivalence submission, the "acceptance criteria" are implicitly met by demonstrating similarity to the predicate device and conforming to relevant standards. The performance data is primarily bench testing and compliance with recognized standards.

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 for clinical data. The document explicitly states: "No clinical testing was performed to support this premarket notification." The testing performed was "nonclinical, bench testing." Therefore, there is no clinical test set, sample size, or data provenance in the context of human patients.

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. Since no clinical testing was performed, there was no clinical ground truth established by experts for human patient data. The ground truth for bench testing would be based on engineering specifications and physical measurements.

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

• Not Applicable. No clinical test set or human expert review/adjudication was conducted as part of this submission.

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 not an AI-assisted diagnostic or interpretation device that would involve human readers performing tasks. It is a radiosurgery system. The document does not mention any MRMC studies or AI assistance in the context of human interpretation improvement.

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

• This refers to the performance of the system itself, which is what the "nonclinical, bench testing" covers. The device, being a radiosurgery system, operates as a standalone system (with human planning and oversight, but the delivery itself is automated based on the plan). The performance data cited from bench testing (electrical safety, software V&V, system validation, standards conformance) demonstrates the standalone performance of the device's components and integrated system.

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

• For the nonclinical testing, the "ground truth" would be established through:
  • Engineering specifications and design requirements: To which the system and its components were verified and validated.
  • Physical measurements and dosimetry: For characteristics like dose rate, beam sizes, and depth at maximum dose.
  • Standard compliance: Verification against the requirements of international and national standards (e.g., IEC 60601 series).

8. The sample size for the training set

• Not provided/Not applicable in a clinical sense. This document pertains to a medical device for radiation therapy delivery, not an AI/ML algorithm that requires a "training set" of patient data in the typical sense. While the software within the system would have undergone development and testing (software V&V), the document does not specify a "training set" size for any internal algorithms.

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

• Not provided/Not applicable. As above, a "training set" in the context of AI/ML is not discussed. The "ground truth" for the device's operational parameters would be established by physics principles, engineering design, and quality control processes.

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The Precision™ treatment planning system is indicated for creation and assessment of external photon beam irradiation treatment plans for radiation therapy, stereotactic radiotherapy or stereotactic radiosurgery for lesions, tumors and conditions anywhere in the body when radiation treatment is indicated. A treatment plan provides an estimate of the dose distribution and the parameters utilized by the radiation delivery system. Plans must be reviewed and approved by qualified medical practitioners prior to delivery.

The Precision™ Treatment Planning System is a radiation therapy planning system used for creation and assessment of treatment plans for delivery by radiation therapy, stereotactic radiotherapy or stereotactic radiosurgery treatment systems. It includes the planning system features of both the currently marketed predicate devices: CyberKnife MultiPlan Treatment Planning System (K150873) and the TomoTherapy Planning Station (K121934). Hence, the Precision Treatment Planning System is intended for treatment planning for multiple platforms:

• · Accuray's robotic radiosurgery systems, including but not limited to the CyberKnife® Treatment Delivery System (last cleared K150873).
• · Accuray's ring gantry systems, including but not limited to the Radixact™ Treatment Delivery System which is a next generation TomoTherapy® Treatment System (last cleared K121934).

The provided document is a 510(k) summary for the Accuray Precision™ Treatment Planning System. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not explicitly state acceptance criteria or provide a detailed study report that proves the device meets specific performance criteria through quantitative metrics.

The document focuses on demonstrating substantial equivalence to existing predicate devices (CyberKnife MultiPlan Treatment Planning System (K150873) and TomoTherapy Planning Station (K121934)) rather than presenting a standalone performance study against pre-defined acceptance criteria.

Therefore, many of the requested details such as specific acceptance criteria thresholds, sample sizes for test/training sets, expert qualifications for ground truth, adjudication methods, or MRMC study results are not available in the provided text.

Here's what can be extracted based on the information given, and where information is missing:

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

The document does not provide a table with explicit numerical acceptance criteria. Instead, it states:

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions "performance test data" but does not detail its composition.

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 specified. The document states that "Plans must be reviewed and approved by qualified medical practitioners prior to delivery," implying expert review is part of the clinical workflow, but it doesn't detail their role in establishing ground truth for testing.

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

• Not specified.

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 or comparative effectiveness study involving human readers with and without AI assistance is mentioned. The device is a "Treatment Planning System," not an AI-assisted diagnostic tool for human readers. Its primary output is a treatment plan (dose distribution and parameters), not a diagnostic interpretation.

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

• The document implies that the system's performance was evaluated standalone in comparison to the predicate systems, without explicitly calling it an "algorithm only" study. It states, "The performance test data for Precision Treatment Planning System demonstrates that the user will be able to create, save, review and modify treatment plans with the same or higher level of quality as currently produced by each of the individual predicate treatment planning systems." The focus is on the system's ability to generate treatment plans.

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

• Not explicitly stated. Given it's a treatment planning system, the "ground truth" for its performance would likely relate to the accuracy of dose calculations and the ability to generate plans that meet established clinical objectives and physics models, which are typically validated against physical measurements (phantoms) and clinical expert review. The document mentions "review and evaluation against the treatment prescription and established physics models."

8. The sample size for the training set

• The document focuses on the performance of the system as a whole rather than a specific AI component that would require a separate training set. While the system may employ algorithms, the 510(k) summary doesn't detail distinct training sets for machine learning models. Therefore, this information is not provided.

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

• As above, details regarding training sets and their ground truth establishment are not provided in this 510(k) summary.

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The iDMST™ Data Management System is indicated for the storage, retrieval, and processing of data utilized in the practice of radiotherapy, stereotactic radiotherapy and stereotactic radiosurgery.

The subject device, iDMS™ Data Management System, is essentially the CyberKnife® Data Management System (CDMS) cleared in the predicate device, the CyberKnife® Robotic Radiosurgery System. This submission simply establishes the iDMS™ System as a stand-alone data management system and reflects its integration with Accuray's robotic radiosurgery and ring gantry systems, including but not limited to the CyberKnife® System and Radixact™ Treatment Delivery System which is a next generation TomoTherapy® Treatment System. As such, modifications are limited to those required to integrate the iDMS™ System with the Radixact™ System which is a next generation TomoTherapy® Treatment System.

The iDMS™ System is a data management system that provides storage, applications and interfaces to access, add, modify, export, delete, and validate patient, user and system data for Accuray's radiotherapy, stereotactic radiotherapy, and stereotactic radiosurgery delivery systems, including but not limited to the CyberKnife® System and Radixact™ Treatment Delivery System which is a next generation TomoTherapy® Treatment System, as well as treatment planning systems, including the Precision™ Treatment Planning System. The IDMS™ System can store and retrieve treatment plans and delivery data for multiple systems.

I am sorry, but the provided text does not contain detailed information about the acceptance criteria and study results for the iDMS™ Data Management System. The document is a 510(k) summary for FDA clearance and primarily focuses on establishing substantial equivalence to a predicate device.

While it mentions "Testing was completed to verify that all hardware and software perform as designed, as well as regression testing to verify the integrity of existing features. Testing demonstrated that the iDMS™ System performance is equivalent to the predicate, the CDMS features," it does not provide:

• A table of acceptance criteria and reported device performance.
• Sample sizes used for the test set or data provenance.
• Number of experts and their qualifications for ground truth.
• Adjudication method.
• Details about multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance.
• Type of ground truth used.
• Sample size for the training set.
• How ground truth for the training set was established.

The document states that the iDMS™ Data Management System is "essentially the CyberKnife® Data Management System (CDMS) cleared in the predicate device, the CyberKnife® Robotic Radiosurgery System," and that "modifications are limited to those required to integrate the iDMS™ System with the Radixact™ System." This suggests that the system's performance might be considered equivalent to the predicate device without requiring a new, extensive clinical study if the modifications are minor and do not alter fundamental performance characteristics.

Therefore,Based on the provided text, I cannot answer your request.

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