(106 days)
The Quantum / Canon CXDI Integration System provides diagnostic quality images to aid the physician with diagnosis. The System can be used to perform radiographic exposures of the skeleton (including skull, spinal column and extremities), chest, abdomen and other body parts. The System is not indicated for use in mammography.
The Quantum / Canon CXDI Integration System consists of add-on software that will allow the use of the currently marketed Quantum Q-Rad Radiographic System with the currently marketed Canon CXDI Series System, including models CXDI-40EG or CXDI-50G, as a fully integrated digital imaging system.
The provided text describes the Quantum / Canon CXDI Integration System, an add-on software designed to integrate existing Quantum Q-Rad Radiographic Systems with Canon CXDI Series Systems to form a fully integrated digital imaging system.
Here's an analysis of the acceptance criteria and study information, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Generation of "diagnostic quality images" | "Performance data demonstrated that the Quantum / Canon CXDI Integration System...met pre-determined acceptance criteria." |
| Safety and effectiveness | "The Quantum / Canon CXDI Integration System meets all the pre-determined acceptance criteria of the testing performed to confirm safety and effectiveness" |
| Substantial equivalence to predicate devices | "Performance data demonstrated that the Quantum / Canon CXDI Integration System is substantially equivalent to the predicate devices" and "The System is substantially equivalent to the predicate devices." |
| Acceptable risks | "The risks associated with use of the new device were found acceptable when evaluated by standardized risk/hazard analysis techniques." |
| Biocompatibility (for patient-contacting materials) | "No biocompatibility testing was conducted...all patient-contacting materials...have been previously cleared for similar devices." |
Note: The document states that the device "met pre-determined acceptance criteria" and "meets all the pre-determined acceptance criteria." It does not provide specific quantitative metrics or thresholds for these criteria. The primary "performance" articulated is substantial equivalence to the predicate devices and the ability to produce diagnostic quality images.
2. Sample Size Used for the Test Set and Data Provenance
The provided text does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It broadly mentions "Performance testing was successfully completed on the system in accordance with predetermined protocols based on the system design inputs."
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
The provided text does not specify the number of experts used or their qualifications for establishing ground truth for any test set.
4. Adjudication Method for the Test Set
The provided text does not specify any adjudication method (e.g., 2+1, 3+1, none) for a test set.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
The provided text does not mention an MRMC comparative effectiveness study, nor does it provide an effect size for human readers improving with AI vs. without AI assistance. The device is an integration system for digital radiography, not an AI-powered diagnostic tool in the sense of offering independent assessments. It focuses on the technical integration and "diagnostic quality images."
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was Done
The device itself is an "integration system" that enables existing hardware to function as a "fully integrated digital imaging system." It's not described as an algorithm performing diagnostic tasks standalone. The focus is on the system providing "diagnostic quality images to aid the physician with diagnosis," implying human interpretation. Therefore, a standalone performance study in the sense of an AI algorithm making diagnoses without a human is not applicable and not described.
7. The Type of Ground Truth Used
The provided text does not specify the type of ground truth used for any performance testing beyond stating that diagnostic quality images are produced. The context suggests that the "ground truth" would be the clinical acceptability of the x-ray images for diagnosis, likely evaluated by medical professionals, but this is not explicitly detailed.
8. The Sample Size for the Training Set
The provided text does not specify a training set size. As the device is primarily an integration system for existing hardware and software to produce digital images, the concept of a "training set" in the context of machine learning is not explicitly detailed or relevant based on the information provided. The "performance testing" seems to be related to the system's ability to operate correctly and produce images comparable to predicate devices.
9. How the Ground Truth for the Training Set Was Established
Since a training set is not mentioned or implied by the nature of the device (an integration system), the method for establishing its ground truth is not applicable and not described in the provided text.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).