K Number
K981055
Device Name
XKNIFE-4
Manufacturer
Date Cleared
1998-09-29

(190 days)

Product Code
Regulation Number
892.5050
Panel
RA
Reference & Predicate Devices
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

XKnife-4 is intended for use in stereotactic, collimated beam, computer planned, LINAC (linear accelerator) based radiosurgery and radiotherapy treatment.

Device Description

The XKnife-4 system has similar technical characteristics as the commercially available XKnife-3 system. Both systems consist of treatment planning software, stereotactic hardware and a protocol of extensive verification and QA procedures to ensure proper transfer of the treatment parameters to the clinical delivery system. The XKnife-4 system also has similar technical characteristics as the commercially available XPlan-1 system. Both systems support the use of the LINAC jaws, in addition to a circular collimator, to further shape the radiation beam.

AI/ML Overview

The provided text is a 510(k) summary for the Radionics Software Applications, Inc. XKnife-4, a radiation treatment planning system. However, it does not contain the detailed information required to answer all the questions about acceptance criteria and the study proving the device meets them.

Specifically, the document primarily focuses on establishing substantial equivalence to predicate devices (XKnife-3 and XPlan-1) based on similar technical characteristics and general safety/effectiveness. It mentions "Nonclinical tests were conducted to demonstrate that the XKnife-4 software meets all product requirements" but does not provide any specific acceptance criteria, performance metrics, or details about these tests.

Therefore, I can only address the questions for which information is present.


Summary of Available Information from the Provided Text:

The Radionics Software Applications, Inc. XKnife-4 is a radiation treatment planning system intended for stereotactic, collimated beam, computer-planned, LINAC-based radiosurgery and radiotherapy treatment.

The 510(k) process for this device focused on demonstrating substantial equivalence to existing predicate devices (Radionics Software Applications, Inc. XKnife-3 System and XPlan-1 System). The justification for substantial equivalence was based on:

  • Similar technical characteristics: Both XKnife-4 and XKnife-3 consist of treatment planning software, stereotactic hardware, and a protocol for verification and QA. XKnife-4 and XPlan-1 both support the use of LINAC jaws.
  • Nonclinical tests: "Nonclinical tests were conducted to demonstrate that the XKnife-4 software meets all product requirements." These tests also aimed to show that the performance is substantially equivalent to the predicate devices.

Missing Information:

The document explicitly lacks:

  • A table of acceptance criteria and reported device performance.
  • Sample sizes for test sets or training sets.
  • Data provenance.
  • Details about expert involvement (number, qualifications, adjudication method).
  • Information on MRMC comparative effectiveness studies.
  • Effect size for human readers' improvement with AI assistance.
  • Details about standalone algorithm performance studies.
  • Specific types of ground truth used (beyond a general statement of "product requirements").
  • How ground truth was established for any training or test sets.

Attempt to Answer Based on Provided Text (highlighting what is absent):

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

    • Acceptance Criteria: Not explicitly stated. The document broadly mentions "meets all product requirements" and demonstrates "performance is substantially equivalent to the predicate devices." No specific numerical or qualitative criteria are provided.
    • Reported Device Performance: Not explicitly stated. The document implies performance is on par with the predicate devices through the substantial equivalence claim, but no specific metrics or results from the nonclinical tests are detailed.
  2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Sample Size: Not mentioned.
    • Data Provenance: Not 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)

    • Experts: Not mentioned.
    • Qualifications: Not mentioned.
  4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    • Adjudication Method: Not 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

    • MRMC Study: Not mentioned as being conducted. The device is a "radiation treatment planning system," not typically assessed via MRMC studies in the way a diagnostic AI might be.
    • Effect Size: Not applicable/not mentioned.
  6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    • Standalone Performance: The document states "Nonclinical tests were conducted to demonstrate that the XKnife-4 software meets all product requirements." This implies some form of standalone testing was performed to verify the software's functionality, but no specific performance metrics (e.g., accuracy, precision) or a detailed study description are provided. The context suggests product validation rather than a standalone performance study as understood for AI diagnostics.
  7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

    • Type of Ground Truth: Not explicitly stated. The phrase "meets all product requirements" implies ground truth was established by adherence to design specifications and expected computational outcomes for treatment planning, rather than clinical ground truth like pathology or outcomes.
  8. The sample size for the training set

    • Training Set Sample Size: Not mentioned. The document does not describe a machine learning or AI training process in the modern sense. It refers to a "software application" for treatment planning.
  9. How the ground truth for the training set was established

    • Ground Truth for Training Set: Not mentioned. As above, this document does not describe a machine learning training paradigm.

§ 892.5050 Medical charged-particle radiation therapy system.

(a)
Identification. A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.(b)
Classification. Class II. When intended for use as a quality control system, the film dosimetry system (film scanning system) included as an accessory to the device described in paragraph (a) of this section, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.