Search Results

The LANDAUER® microSTAR®ii Medical Dosimetry System provides an accurate, reliable and easy-to-use dosimeter and reader intended for use in measuring dose on-phantom or on-patient in medical dosimetry applications, such as radiotherapy and diagnostic radiology. When used to measure patient dose, the system is used to provide a secondary verification of radiation dose as a means of Quality Control for the primary dose calculation method. The output of the microSTAR®ii system is not used to adjust the dose to the patient.

The LANDAUER® microSTARii Medical Dosimetry System consists of the following components to provide secondary verification of dose from various radiotherapy and diagnostic imaging devices: Dosimeter (nanoDot) to record radiation during radiation exposure. Reading device (microSTARii Reader) for reading the radiation dose recorded by the dosimeter. microSTARii Software Application, a simple software tool that the user interacts with for radiation dose calculation, dose reporting, managing and storing data. 2D barcode scanner. Calibration Dosimeter Set (nanoDots) for QC/Calibration.

The provided text is a 510(k) summary for the microSTARii Medical Dosimetry System. It is an application for a medical device that measures radiation dose, not an AI/ML device that requires typical acceptance criteria and validation studies as outlined in the prompt.

Therefore, many of the requested details about acceptance criteria, study methodologies (like data provenance, expert ground truth, MRMC studies, standalone performance, training sets, etc.), which are standard for AI/ML device submissions, are not applicable to this document. This document describes a physical dosimetry system (hardware and software) used for quality control in medical dosimetry, not an AI algorithm that makes diagnostic or prognostic predictions.

Specifically, the document states:

• "No mandatory performance standards have been established for this device (Section 514 of the Act)."
• "Clinical testing was not necessary to support substantial equivalence of the proposed device to the predicate device."

This indicates that the validation approach focuses on non-clinical performance (bench testing, software testing, EMC) to demonstrate substantial equivalence to a predicate, rather than human-in-the-loop or standalone AI performance.

Given this, I cannot extract the information required by the prompt regarding acceptance criteria and study methodologies as they relate to an AI/ML device. The acceptance criteria and study described are for a traditional medical device's performance, safety, and effectiveness.

Ask a specific question about this device