(30 days)
AccuLeaf is intended to assist the radiation oncologist in the delivery of radiation to well defined target volumes while sparing surrounding normal tissue and critical organs from excess radiation.
In this application AccuLeaf performs the same function as customized beam shaping blocks, and circular or cut blocks collimators, which have been used for many years.
AccuLeaf is a LINAC based Micro-Multi-Leaf-Collimator (MMLC), used in radiation treatment.
It enables shaping the Linac beam according to target geometrical and clinical requirements.
The device is composed of the MMLC module, the Linac interface module, the Workstation (with AccuLeaf Control Software), and the Distribution module.
The device operates in conjunction with a Linac, a treatment couch, and any additional equipment required in radiation treatment.
The MMLC apertures, (defined in treatment data file), are generated by positioning the motor-driven leaves. The motors, controlled by AccuLeaf, bring the leaves to specified positions. The AccuLeaf control operates as a sequential linear process, where the apertures are performed one by one.
To form a desired aperture, AccuLeaf calculates leaves motion from knowledge of their current positions (measured) and desired destination (delivered by treatment plan).
AccuLeaf displays an image reflecting the leaves current position. Numeric indication of each leaf position is available.
AccuLeaf two operation modes are Step-and-Shoot and Dynamic Arc:
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Step-and-Shoot: MMLC modifies the apertures prior to irradiation.
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Dynamic Arc: Irradiating Linac forms an arc while AccuLeaf forms apertures at a set of Gantry angles.
This document is a 510(k) summary for the AccuLeaf device, which is a Micro-Multi-Leaf-Collimator (MMLC) used in radiation treatment. The document focuses on establishing substantial equivalence to previously cleared devices and does not contain detailed information about acceptance criteria or specific studies to prove device performance in the way a clinical trial report would.
Therefore, many of the requested fields cannot be filled from the provided text.
Here's a breakdown of what can and cannot be extracted:
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A table of acceptance criteria and the reported device performance
- Not found. This document is a 510(k) summary, which focuses on regulatory clearance based on substantial equivalence. It does not detail specific engineering or clinical acceptance criteria for performance, nor does it provide a table of measured device performance against such criteria.
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Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
- Not found. The document does not describe any specific test set or clinical study involving patient data.
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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 found. No test set or ground truth establishment is described.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set
- Not found. No test set or adjudication is described.
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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 found. The AccuLeaf device is a hardware component (MMLC) for radiation therapy delivery, not an AI or diagnostic imaging device that would typically involve human readers or MRMC studies. It assists radiation oncologists in delivering radiation, performing functions akin to physical beam shaping blocks.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
- Not found. This is not applicable. The device is a physical system that shapes radiation beams under the control of software and in conjunction with a linear accelerator; it's not a standalone algorithm in the sense of AI.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Not found. No ground truth for performance evaluation is described. The "ground truth" for its function would be the intended radiation field shape as defined by the treatment plan.
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The sample size for the training set
- Not found. The document does not describe the development of a machine learning model that would require a training set.
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How the ground truth for the training set was established
- Not found. Not applicable as no training set is described.
Summary of available information related to acceptance criteria and study:
The provided text is a 510(k) summary, which is a premarket notification to the FDA. It primarily focuses on demonstrating "substantial equivalence" to existing legally marketed devices, rather than detailed performance study results against specific criteria.
Key points from the document:
- Predicate Devices: The device establishes substantial equivalence to:
- Performance Standards: No specific performance standards have been established by Section 514 of the Federal Food, Drug, and Cosmetic Act for this type of device.
- Voluntary Standards: The AccuLeaf complies with the following voluntary standards, which serve as a form of "acceptance criteria" for safety and general performance characteristics:
- IEC 60601-1 (1990) +A1 (1993) +A2 (1995)
- IEC 60601-1-1 (2000)
- IEC 60601-1-2 (1993)
- IEC 60601-1-4, Ed.1.1 (2000)
- Device Function: The device "enables shaping the Linac beam according to target geometrical and clinical requirements." It "calculates leaves motion from knowledge of their current positions (measured) and desired destination (delivered by treatment plan)." The core performance is the accurate positioning of leaves to achieve the desired aperture.
- The document implies that the device "meets the acceptance criteria" by being substantially equivalent to its predicates and complying with recognized voluntary standards. The "study" proving this is the 510(k) submission itself, where the manufacturer provides documentation to the FDA to demonstrate equivalence, which typically involves comparing technical specifications, operating principles, and intended use with the predicate devices. It does not refer to a separate clinical or performance study with a test set of data points as would be done for a diagnostic AI device.
§ 892.5710 Radiation therapy beam-shaping block.
(a)
Identification. A radiation therapy beam-shaping block is a device made of a highly attenuating material (such as lead) intended for medical purposes to modify the shape of a beam from a radiation therapy source.(b)
Classification. Class II.