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The QV-9000 Universal System is a stationary radiographic imaging system used for acquiring radiographic images of various anatomical regions of the human body.

The QV-9000 Universal System is a stationary, general purpose, X-ray imaging system used for acquiring radiographic exposures of various parts of the body including the skull, spinal column, chest, thorax, abdomen and extremities. The QV-9000 Universal System incorporates a floor-mounted vertical support column, with an attached rotating 'C' arm, an image receptor, an X-ray tube and collimator. The QV-9000 Universal System is compatible for use with either a digital or non-digital (film type) image receptor cabinet

The provided text does not contain detailed information about acceptance criteria for device performance, nor does it describe a specific study proving the device meets particular acceptance criteria.

The document is a 510(k) summary for a Special 510(k): Device Modification for the QV-9000 Universal System, an X-ray imaging system. The key information provided focuses on the device description, indications for use, and a general statement about safety and performance based on compliance with design control requirements, risk analysis, and verification/validation testing.

Here's why the requested information cannot be extracted from the given text:

• No specific performance metrics are listed: The document states "A description and summary of the verification and validation testing methods and results utilized to qualify the device modifications is also included in this submission," but these details are not present in the provided text.
• No detailed study description: There is no mention of a clinical study, reader study, or any specific test protocol with sample sizes, ground truth establishment, or expert involvement. The submission appears to rely on compliance with regulations and internal testing rather than a comparative effectiveness study or standalone performance study.

Therefore, I cannot populate the table or answer the subsequent questions about sample sizes, experts, adjudication, MRMC studies, standalone performance, or ground truth establishment based on the provided text.

The document primarily focuses on regulatory compliance (510(k) process, substantial equivalence to a predicate device K023008, and general controls) rather than detailed performance reporting as typically found in clinical study summaries.

Summary of available information regarding acceptance criteria and studies:

• Acceptance Criteria & Reported Device Performance: Not specified in the provided text. The document refers to "verification and validation testing methods and results" as being included in the submission, but these details are not provided here.
• Sample size for test set and data provenance: Not specified.
• Number of experts and qualifications: Not specified.
• Adjudication method: Not specified.
• Multi-reader multi-case (MRMC) comparative effectiveness study: Not mentioned.
• Standalone performance study: Not mentioned. The device's approval is based on substantial equivalence to a predicate and compliance with design controls and internal testing.
• Type of ground truth used: Not specified.
• Sample size for the training set: Not applicable, as this is an X-ray imaging system, not an AI/CAD system, and no "training set" for an algorithm is mentioned.
• How the ground truth for the training set was established: Not applicable.

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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

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.

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The Quantum DiRex System provides diagnostic quality images to aid the physician with diagnosis. The DiRex can be used to perform radiographic exposures of the skeleton (including skull, spinal column and extremities), chest, abdomen and other body parts. The DiRex is not indicated for use in mammography.

The Quantum DiRex System is an integrated digital imaging system that combines the currently marketed Quantum Q-Rad Radiographic System with the currently marketed Agfa DX-S CR System (digitizer with NX workstation). The Quantum DiRex System is a combination of these previously cleared systems that have been combined and will be marketed as a single system.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Quantum DiRex System:

Based on the provided text, the Quantum DiRex System is an integrated digital imaging system that combines the Quantum Q-Rad Radiographic System with the Agfa DX-S CR System. The primary acceptance criteria for this submission revolve around demonstrating substantial equivalence to predicate devices and meeting pre-determined performance criteria.

Here's a breakdown of the requested information:

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

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

The document does not specify a sample size for any test set or data provenance. The descriptions are general statements about "performance data" and "performance testing."

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

The document does not mention any expert review committee, experts used to establish ground truth, or their qualifications. The testing appears to be focused on technical performance and equivalence, rather than clinical efficacy studies requiring expert reader consensus on diagnostic images.

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

The document does not mention any adjudication method.

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 conducted. This submission is for a digital X-ray system, not an AI-powered diagnostic device, hence, there is no mention of human readers improving with AI assistance.

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

This question is not applicable as the device is a medical imaging system (hardware and associated software for image acquisition), not a standalone diagnostic algorithm. The performance described relates to the system's ability to produce diagnostic quality images, not an automated reading of those images.

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

The document does not explicitly state the type of ground truth used. Given the nature of the device (an imaging system, not a diagnostic algorithm), the "performance testing" likely involved evaluating image quality metrics, dose, system functionality, and compliance with pre-determined technical specifications (e.g., spatial resolution, contrast resolution, noise, consistency) rather than clinical ground truth diagnoses.

8. The sample size for the training set

The document does not mention a training set sample size. This is expected as the device is an imaging system, not a machine learning model that requires a training set.

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

This question is not applicable as the device is an imaging system and not an AI/ML model requiring a training set with established ground truth.

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The Quantum Medical Imaging, LLC Universal System is a stationary radiographic imaging system used for acquiring radiographic images of various anatomical regions of the human body.

The QV-800 Universal System is a walland floor-mounted column with an attached "swivel-arm". The QV-800 Universal System's "swivel-arm" design allows the x-ray tube and image receptor to remain in constant alignment as the arm is rotated and as the image receptor is anqulated. The QV-800 Universal System is designed for use in hospitals, imaging centers, and clinics.

The provided document is a 510(k) summary for the QV-800 Universal System, a stationary X-ray system. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, this document does not contain information about acceptance criteria, device performance studies, sample sizes for test/training sets, ground truth establishment, or expert involvement for AI/algorithmic performance evaluation.

The 510(k) summary focuses on the regulatory process of establishing substantial equivalence for a conventional medical device (an X-ray system) to legally marketed predicate devices, rather than on the performance evaluation of an AI-based or algorithmic device against specific acceptance criteria.

Therefore, I cannot extract the requested information as it is not present in the provided text.

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