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The Platinum dRF Imaging System is intended to be used as a universal diagnostic imaging system for radiographic and fluoroscopic studies. Using a digital flat detector, it can perform a range of applications including general R/F, diagnostic fluoroscopy, conventional linear tomography, angiography and pediatric examinations.

The Platinum dRF is a device intended to visualize anatomical structures by converting a pattern of X-ray into a visible image. The system has medical applications ranging from but not limited to gastrointestinal examinations, cranial, skeletal, thoracic and lung exposures as well as examination of the urogenital tract. The units may also be used in lymphography, endoscopy, myelography, venography, pediatrics, arthrography, digital angiography and digital subtraction angiography (DSA).

The Platinum dRF may be used for outpatient and emergency treatment, as well as for mobile transport (wheelchair and bed) examinations.

The Platinum dRF is not indicated for use in interventional radiology.

The Apelem-DMS Platinum dRF Imaging System (Platinum) is not a stand-alone device, but functions as a platform for FDA cleared or registered components (i.e. generator, panel detector, detector collimator. X-ray tube and software imaging packages), that are installed with a Apelem-DMS manufactured radiological examination table, control panel with system controller software. and electrical panel.

The Platinum dRF remote controlled table is a radiologic table equipped with a flat panel electronic detector. This table is used to perform general digital radiological, fluoroscopy and peripheral angiography. This device allows for treatment on the whole body, using all angles. It allows the user dynamic acquisition for the whole body, to target the zones to analyze, and to be able to track contrast media.

Here's a breakdown of the acceptance criteria and the study information for the Apelem-DMS Platinum dRF Imaging System, based on the provided text:

Important Note: The provided document is a 510(k) summary for a medical device seeking substantial equivalence to a predicate device. This type of submission often focuses on demonstrating that the new device is as safe and effective as a legally marketed device, rather than performing extensive novel clinical trials as might be seen for entirely new technologies. Therefore, some detailed information about performance comparisons or AI assistance might not be present as it's not typically required for this type of submission.

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a quantitative, measurable format with specific thresholds. Instead, it relies on demonstrating substantial equivalence to a predicate device (Siemens AXIOM Luminos dRF). The performance is discussed in terms of similarities and improvements compared to the predicate, with the underlying assumption that if it's equivalent or better in relevant aspects, it meets necessary performance standards.

The table below summarizes the comparison:

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The Luminos Agile is intended to be used as a universal diagnostic imaging system for radiographic and fluoroscopic studies. Using either film cassettes or a digital mobile flat detector, it can perform a range of applications including general R/F, angiography and pediatric examinations.

Luminos Agile may be used for emergency treatment on an outpatient basis, as well as for bedside examinations.

Luminos Agile is a floor-mounted universal fluoroscopic x-ray diagnostic system (R/F system), that was developed for tableside examinations in combination with an Explorator. The modification is to replace the Image Intensifier / TV Camera with a solid state detector (flat panel/digital imager). The Explorator houses the flat panel solid state detector.

This modified AXIOM SIRESKOP SD will be marketed under the trade name Luminos Agile. The modification does not affect the intended use of the device nor does it alter its fundamental scientific technology.

Luminos Agile may be configured as a single tube system, with an under table tube or a dual tube system which features an additional 3D overhead tube crane, that can be moved longitudinally and laterally as well as vertically. The dual x-ray tube configuration provides a quick change between under table and over table exposure modes. The under table tube is used for fluoroscopy and radiographic exposures taken with the Digital Imaging System. The over table tube is suspended from an overhead tube support for exposures with a table Bucky or Bucky wall stand, either with film cassettes or solid state detector. The digital images produced by the solid state detector are recorded and displayed by the Fluorospot COMPACT digital imaging system. The table design remains unchanged while the new imaging chain is based on the AXIOM Luminos dRF described in premarket notification K062623 which received FDA Clearance on August 22. 2007.

The provided text describes the Siemens Luminos Agile, a floor-mounted universal fluoroscopic x-ray diagnostic system. This document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study with specific acceptance criteria and performance metrics.

Therefore, much of the requested information regarding acceptance criteria, specific performance metrics, sample sizes, expert qualifications, and study methodologies (MRMC, standalone, training set details) is not available in the provided text. The document is primarily a regulatory submission to establish equivalence for market clearance.

Here's a breakdown of the information that can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated as quantifiable metrics. The acceptance criteria for a 510(k) submission generally revolve around demonstrating "substantial equivalence" to a legally marketed predicate device in terms of intended use, technology, and safety/effectiveness. This does not involve setting specific performance thresholds (e.g., sensitivity, specificity) for a new clinical study.
• Reported Device Performance: Not provided in terms of quantitative clinical performance metrics (e.g., diagnostic accuracy, image quality scores). The document states that the modification (replacing an Image Intensifier/TV Camera with a solid state detector) "does not affect the intended use of the device nor does it alter its fundamental scientific technology." It also mentions that "the Luminos Agile is continually monitored, and if an error occurs, the system functions will be blocked and an error message will be displayed," and that Siemens adheres to industry practices to minimize hazards. This is general safety and functionality assurance rather than quantifiable performance for acceptance.

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

• Not Applicable/Not Provided. The document is a 510(k) submission asserting substantial equivalence. It does not describe a new clinical study with a "test set" in the context of diagnostic performance. The testing mentioned (final performance testing) refers to engineering/system validation, not a clinical trial with patient data for performance evaluation.

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)

• Not Applicable/Not Provided. As there is no described clinical test set for diagnostic performance, there is no mention of experts establishing ground truth for such a set.

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

• Not Applicable/Not Provided. See point 3.

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. This document describes an X-ray system, not an AI-powered diagnostic algorithm. An MRMC study would not be relevant in this context.

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

• No. This is a hardware system, not a standalone algorithm.

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

• Not Applicable/Not Provided. No clinical ground truth is described as having been established for testing diagnostic performance in this document. The ground truth for regulatory clearance in a 510(k) is typically the established safety and effectiveness of the existing predicate device(s).

8. The sample size for the training set

• Not Applicable/Not Provided. This is a hardware system, not a machine learning algorithm that requires a training set.

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

• Not Applicable/Not Provided. See point 8.

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The URS-50RF is indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic and interventional procedures. It is also indicated for generating fluoroscopic images of human anatomy for cardiology, diagnostic, and interventional procedures. It is intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The Canon Dynamic/Static DR URS-50RF is a portable digital radiography that can take images of any part of the body. It directly converts the X-ray images captured by the LANMIT (Large Area New MIS Sensor and TFT) sensor into a high-resolution digital images. The instrument is suited for use inside a patient environment. This unit converts the X-rays into digital signals. The unit can acquire still and moving images.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Canon Dynamic/Static DR Model URS-50RF Fluoroscopic Digital X-Ray System:

Summary of Device and Study Information (K093688)

This 510(k) summary describes a fluoroscopic digital X-ray system, the Canon Dynamic/Static DR URS-50RF, intended to generate fluoroscopic images for vascular angiography, diagnostic and interventional procedures, and cardiology. It aims to replace image intensifier technology. The submission focuses on demonstrating substantial equivalence to predicate devices, primarily through performance testing and software validation.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided document is a 510(k) summary. For medical devices, particularly those establishing substantial equivalence, explicit "acceptance criteria" are often phrased in terms of meeting or exceeding the performance of legally marketed predicate devices, or complying with relevant standards. The document does not list specific numerical acceptance criteria for image quality, diagnostic accuracy, or clinical endpoints. Instead, it makes a general statement about performance.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not explicitly stated. The document mentions "Tests were performed on the device," but does not specify the number of cases, images, or subjects used for performance testing.
• Data Provenance: Not specified. It's unclear if the testing involved human subjects, phantoms, or simulated data, or the country of origin of any data used. Given the nature of a 510(k) for an imaging device, it's highly probable that bench testing with phantoms and potentially some limited clinical evaluation (if required to show equivalence for image quality) was involved, but details are absent.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified. With no mention of expert review or ground truth establishment, no adjudication method is detailed.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not specifically mentioned or implied in the provided 510(k) summary. The summary focuses on demonstrating substantial equivalence to already marketed devices based on technological characteristics and general performance testing, rather than a direct comparison of physician performance with and without AI assistance.
• Effect Size of Human Reader Improvement: Not applicable, as no MRMC study (or AI assistance) was described.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: This device is a hardware fluoroscopic digital X-ray system, not an AI algorithm. Therefore, the concept of a "standalone (algorithm only)" performance study does not apply in this context. The performance described relates to the entire system's ability to acquire and process images.

7. Type of Ground Truth Used

• Type of Ground Truth: Not explicitly stated. The performance testing is generally described as validating that the device is "safe and effective" and "performs comparably" to predicate devices. For an imaging system, ground truth might involve:
  • Physical Measurements: Using phantoms to verify spatial resolution, contrast resolution, noise, dose efficiency, etc.
  • Clinical Image Quality Assessment: Expert review of images to ensure diagnostic interpretability, though this isn't detailed as "ground truth" establishment in the psychological sense.
  • Comparison to Predicate: Performance is often benchmarked against images from the predicate device.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This device is a hardware imaging system, not an AI or machine learning algorithm that requires a "training set."

9. How the Ground Truth for the Training Set Was Established

• Ground Truth for Training Set Establishment: Not applicable, as there is no training set for a hardware device.

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The CXDI-50RF is indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic and interventional procedures. It is also indicated for generating fluoroscopic images of human anatomy for cardiology, diagnostic, and interventional procedures. It is intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The Canon Dynamic/Static DR CXDI-50RF is a portable digital radiography that can take images of any part of the body. It directly converts the X-ray images captured by the LANMIT (Large Area New MIS Sensor and TFT) sensor into a high-resolution digital images. The instrument is suited for use inside a patient environment. This unit converts the X-rays into digital signals. The unit can acquire still and moving images.

The Canon Dynamic/Static DR Fluoroscopic Digital X-Ray Receptor Panel (Model CXDI-50RF) is indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic, and interventional procedures, as well as for cardiology, diagnostic, and interventional procedures. It is intended to replace fluoroscopic images obtained through image intensifier technology and is not intended for mammography applications.

Here's an analysis of the provided information regarding acceptance criteria and the study:

Details of the Study:

The provided 510(k) summary (K092439) for the Canon Dynamic/Static DR Model CXDI-50RF Fluoroscopic Digital X-Ray Receptor Panel primarily relies on showing substantial equivalence to predicate devices rather than a detailed clinical performance study with specific metrics like sensitivity, specificity, or AUC based on expert reads.

Here's what can be inferred from the document:

1. Sample size used for the test set and the data provenance:

   • The document does not specify a sample size for a test set in the context of an accuracy or performance study involving image interpretation.
   • The data provenance is not described in terms of country of origin or whether it was retrospective or prospective.
   • The "Performance Testing/Data" section mentions "Tests were performed on the device," but these tests appear to be primarily technical and safety assessments (e.g., electrical safety, EMC, software validation) and comparative assessments against predicate devices' technological characteristics, not a clinical study on diagnostic accuracy.

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

   • This information is not provided. The submission focuses on technical equivalence and safety, not on evaluating human reader performance with the device against a ground truth established by experts.

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

   • This information is not provided, as there is no described clinical test set requiring expert adjudication for diagnostic accuracy.

4. 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 done. This submission predates the widespread regulatory requirement for such studies for AI-powered devices. The device described is a digital X-ray receptor panel, an imaging hardware component, not an AI diagnostic algorithm. Therefore, the concept of "human readers improve with AI vs without AI assistance" is not applicable here.

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

   • No, a standalone algorithm performance study was not done. The device is an image acquisition component, not a diagnostic algorithm.

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

   • This information is not provided for a clinical diagnostic performance study. The "ground truth" implied in the submission relates to technical specifications, safety standards, and functional equivalence to predicate devices.

7. The sample size for the training set:

   • There is no mention of a training set in the context of machine learning or AI models. The device is a hardware component for imaging, not a software algorithm that requires a training set.

8. How the ground truth for the training set was established:

   • This information is not applicable as there is no training set for an AI/machine learning model described.

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The HDR Vision is intended to be used as a universal diagnostic imaging system for radiographic and fluoroscopic studies. Using a digital flat detector, it can perform a range of applications including general RIF, angiography and pediativ examinations.

The HDR Vision is a device intended to visualize anatomical structures by converting a pattern of X-ray into a visible image. The system has medical applications ranging from but not limited to gastroninal examinations, cramil, skeletal, procecc and hing exposures as well as examination of the units may also be used in lymphography, endocony, myelography, venggraphy, pediatrics, arthrography, interventional radiology, digital angiocraphy and digital subtaction angiography (DSA).

HDR Vision may be used for outpatient and emergency treatment, as well as for mobile transport (wheelchair and bed) examinations.

The HDR Vision is intended to be used as a universal diagnostic imaging system for radiographic and fluoroscopic studies.

The HDR Vision is a device intended to visualize anatomical structures by converting a pattern of X-ray into a visible image. The system has medical applications ranging from but not limited to gastrointestinal examinations, cranial, skeletal, thoracic and lung exposures as well as examination of the urogenital tract. The units may also be used in lymphography, endoscopy, myelography, venography, pediatrics, arthrography, interventional radiology, digital angiography and digital subtraction angiography (DSA).

HDR Vision is a universal fluoroscopic x-ray diagnostic system (RIF system), with an overtable X-ray tube assembly. Using a digital flat detector, it can perform a range of applications including general R/F, angiography and pediatric examinations.

HDR Vision can be configured as a single tube system, with only an overtable tube or it can be combined with an additional 3D overhead tube crane, that can be moved longitudinally and laterally as well as vertically and a bucky wall stand.

This device employs similar materials and processes as found in the predicate device. The device produces ionizing radiation that is employed to generate radiographic and fluoroscopic images of the anatomy. HDR Vision is not a stand-alone device, but functions as the platform for specific X-ray components, X-ray tube and housing, flat detector, digital imaging system, Bucky wall stand, collimator, generator etc. Many of the components used in HDR Vision are either commercially available with current Pausch systems or include minor modifications to existing components.

This 510(k) premarket notification for the HDR Vision device does not include a detailed study with acceptance criteria and reported device performance in the way typically expected for AI/ML-based medical devices.

Instead, this submission claims substantial equivalence to a predicate device (Siemens Medical Systems AXIOM Luminos dRF, K062623), meaning it asserts that the new device is as safe and effective as a legally marketed device. The focus is on demonstrating similar technological characteristics and intended use, rather than presenting a de-novo study with quantitative acceptance criteria for diagnostic performance.

Therefore, many of the requested sections (1, 2, 3, 4, 5, 6, 7, 8, 9) cannot be fully answered with the provided text because these elements are typically associated with studies proving the performance of an AI algorithm, which is not the primary subject of this 2008 submission for a general fluoroscopic X-ray system.

However, I can extract the relevant information regarding the device itself and the basis of its clearance.

Description of Device and Substantial Equivalence Claim

The HDR Vision is a universal diagnostic imaging system for radiographic and fluoroscopic studies. It is intended to visualize anatomical structures by converting X-rays into a visible image. It can perform a range of applications including general R/F, angiography, and pediatric examinations.

The device claims substantial equivalence to the Siemens Medical Systems AXIOM Luminos dRF (K062623). The Flat Panel Detector Pixium RF 4343 in the HDR Vision is also claimed to be substantially equivalent to the Pixium 5100 in the predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

Not Applicable (N/A) in the context of this 510(k) submission.

This 510(k) submission primarily focuses on demonstrating substantial equivalence in terms of intended use and technological characteristics to a predicate device, rather than presenting specific quantitative acceptance criteria for diagnostic performance of an AI algorithm or a de novo clinical study with reported performance metrics. The submission states: "The HDR Vision complies with the same or equivalent standards and has the same intended use as the predicate device and does not raise new questions of safety or effectiveness and is substantially equivalent to the Siemens AXIOM Luminos dRF; K062623 (August 22, 2007)."

Therefore, there are no specific quantitative acceptance criteria or reported device performance metrics for diagnostic accuracy presented in this document. The "acceptance criteria" here are implicitly satisfied by demonstrating equivalence to the predicate device's established safety and effectiveness.

2. Sample Size Used for the Test Set and Data Provenance

Not Applicable (N/A).

As this is a substantial equivalence claim for a conventional imaging system, there is no "test set" in the context of an algorithmic performance evaluation described in the provided text. No patient data or images were used to test the diagnostic accuracy of the device as an AI/ML product.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts

Not Applicable (N/A).

No test set for diagnostic accuracy is described, therefore no experts were used to establish ground truth for such a set within this submission.

4. Adjudication Method for the Test Set

Not Applicable (N/A).

No test set for diagnostic accuracy or algorithmic performance is described, so no adjudication method is mentioned.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi Reader Multi Case (MRMC) comparative effectiveness study was not done.

This type of study is typically conducted for AI/ML-enabled devices to compare human reader performance with and without AI assistance. The HDR Vision is a conventional fluoroscopic X-ray system, and its premarket notification does not include such a study.

6. If a Standalone (i.e. Algorithm Only Without Human-in-the-Loop Performance) Was Done

No, a standalone performance study was not done.

The HDR Vision is an imaging system designed for human operators; it is not an algorithm-only device. Its premarket notification does not describe a standalone performance study in the context of AI/ML.

7. The Type of Ground Truth Used

Not Applicable (N/A).

No ground truth for an AI/ML algorithm or diagnostic performance study is mentioned in this submission. For a conventional imaging device like the HDR Vision, the "ground truth" is inherently the clinical diagnosis made by medical professionals using the images produced by the device, in conjunction with other clinical information.

8. The Sample Size for the Training Set

Not Applicable (N/A).

This document describes a conventional X-ray system, not an AI/ML-based device that would require a training set.

9. How the Ground Truth for the Training Set Was Established

Not Applicable (N/A).

As no training set is relevant for this conventional imaging device, no ground truth establishment method is described.

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The DRF 4343 is a digital image acquisition system to be used in conjunction with a solid-state detector during radiography or fluoroscopy x-ray examination to capture, digitalize, review images and format images according to DICOM protocol to be sent through network connection. This device is not intended for mammography use.

The DRF 4343 is Intended to capture digital images from a radiographic/fluoroscopic system through a dynamic digital flat panel, to digitalize, archive and review images and to provide a network connection via DICOM protocol to various output (e.g. hardcopy, softcopy and archive) devices which uses a device.

This 510(k) submission for the DRF 4343, an Operator Console and Imaging Workstation for Stationary Digital X-Ray Systems, does not contain information about acceptance criteria or a study that specifically proves the device meets such criteria. Instead, the submission focuses on demonstrating substantial equivalence to predicate devices based on shared indications for use and technological characteristics.

Therefore, many of the requested details cannot be extracted from the provided text.

Here is a breakdown of what can be inferred or what is explicitly missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• No specific acceptance criteria or reported device performance metrics are provided in the document. The submission relies on demonstrating substantial equivalence to predicate devices, implying that if it functions similarly to already approved devices, its performance is acceptable.

2. Sample size used for the test set and the data provenance:

• Not applicable. The document does not describe a performance study with a test set.

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

• Not applicable. No test set or ground truth establishment is described.

4. Adjudication method for the test set:

• Not applicable. No test set or adjudication method is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size:

• No MRMC comparative effectiveness study is mentioned. The submission focuses on device characteristics and substantial equivalence, not comparative effectiveness with human readers.

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

• Not applicable. This device is an operator console and imaging workstation for X-ray systems, not an AI algorithm performing diagnostic tasks. Its function is to capture, digitalize, archive, and review images, which implicitly involves human interaction.

7. The type of ground truth used:

• Not applicable. As there is no performance study or ground truth establishment described.

8. The sample size for the training set:

• Not applicable. This submission does not describe an AI model or a training set.

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

• Not applicable. As there is no AI model or training set described.

Summary of available information related to the device and its approval:

• Device Name: DRF 4343
• Common Name: Operator Console and Imaging Workstation for Stationary Digital X-Ray Systems
• Indication for Use: "The DRF 4343 is a digital image acquisition system to be used in conjunction with a solid-state detector during radiography or fluoroscopy x-ray examination to capture, digitalize, review images and format images according to DICOM protocol to be sent through network connection. This device is not intended for mammography use."
• Predicate Devices: Nical NDR+/DIVA-D (K053029), Siemens AXIOM Luminos dRF (K062623), Shimadzu DAR7000 RADspeed SAFIRE (K050925).
• Rationale for Substantial Equivalence: The DRF 4343 has the same indication for use and similar technological characteristics as the predicate devices, with minor differences not raising new questions regarding safety or effectiveness.

In conclusion, this 510(k) submission establishes substantial equivalence through comparison to existing predicate devices rather than through a dedicated performance study with acceptance criteria and a test set. Therefore, the specific details requested regarding acceptance criteria and study data are not present in the provided document.

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