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The OEC Elite mobile fluoroscopy system is designed to provide fluoroscopic and digital spot images of adult and pediatric patient populations during diagnostic, interventional, and surgical procedures. Examples of a clinical application may include: orthopedic, gastrointestinal, endoscopic, urologic, vascular, cardiac, critical care, and emergency procedures.

The OEC Elite is a Mobile Fluoroscopic C-arm Imaging system used to assist trained surgeons and other qualified physicians. The system is used to provide fluoroscopic X-Ray images during diagnostic, interventional, and surgical procedures. These images help the physician visualize the patient's anatomy and interventional tools. This visualization helps to localize clinical regions of interest and pathology. The images provide real-time visualization and records of pre-procedure anatomy, in vivo-clinical activity and post-procedure outcomes.

The C-arm is a stable mobile platform capable of performing linear motions (vertical, horizontal) and rotational motions (orbital, lateral, wig-wag) that allow the user to position the X-Ray image chain at various angles and distances with respect to the patient anatomy to be imaged. The C - arm is mechanically balanced allowing for ease of movement and capable of being "locked" in place using a manually activated lock. The C-Arm is comprised of the high voltage generator, software. X-ray control, and a "C" shaped image gantry, which supports an X-ray tube and a Flat Panel Detector or Image Intensifier, depending on the choice of detector configuration desired.

The workstation is a stable mobile platform with an articulating arm supporting a color image, high resolution, LCD display monitor. It also includes image processing equipment/software, recording devices, data input/output devices and power control systems.

GE is submitting this pre-market notification for proposed labeling changes (quantitative performance claims) related to a previously-released feature, Enhanced Noise Reduction.

The provided text describes a 510(k) premarket notification for the GE OEC Elite mobile fluoroscopy system with "Enhanced Noise Reduction" claims. However, it does not contain the specific acceptance criteria or an explicit study proving the device meets those criteria in the format requested. The document focuses on demonstrating substantial equivalence to a predicate device through non-clinical testing and engineering bench testing, rather than reporting on a clinical study against predefined performance metrics.

Therefore, I cannot populate the table and answer all questions directly from the provided input. However, I can extract the information related to the non-clinical testing and the claims being made for the Enhanced Noise Reduction feature.

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

Information that can be extracted or inferred:

• Device Name: OEC Elite with Enhanced Noise Reduction
• Purpose of the Submission: Proposed labeling changes (quantitative performance claims) related to the Enhanced Noise Reduction feature, demonstrating substantial equivalence to the predicate device.
• Nature of Enhanced Noise Reduction: It's a user-selectable, augmented image processing pathway for Cardiac and Vascular acquisition profiles. It "reduces image noise in a manner characteristic of the reduction in noise resulting from an increase in photon flux" while maintaining "spatial and temporal resolution." It does not change the tube output (dose).
• Claim: "Claims for equivalence to a higher power system without an increase in radiation dose for both cardiac and vascular applications."
• Testing Conducted: Non-clinical testing, engineering bench testing, risk analysis, required reviews, design reviews, integration testing, performance testing, safety testing, simulated use testing. Specific mention of "image quality and dose performance using standard IQ metrics and QA phantoms" and "a wide variety of anthropomorphic phantoms."
• Conclusion: The scientific engineering bench testing methods "demonstrate substantial equivalence." Clinical data was not required.

Missing Information (Crucial for the requested table and questions):

• Specific Acceptance Criteria: The document mentions "quantitative performance claims" but does not detail what these exact criteria are (e.g., specific SNR improvement percentages, resolution metrics, dose reduction targets).
• Reported Device Performance: Without explicit acceptance criteria, the "reported performance" cannot be formally assessed against them. The claim itself implies performance ("equivalence to a higher power system without an increase in radiation dose"), but specific metrics are absent.
• Sample Size (Test Set): Not specified for any performance testing. Phantoms are mentioned.
• Data Provenance (Test Set): Phantoms are artificial, so no country of origin or retrospective/prospective status.
• Number of Experts for Ground Truth (Test Set): Not applicable as no human interpretation of test set images is mentioned as part of performance evaluation.
• Qualifications of Experts for Ground Truth: Not applicable.
• Adjudication Method: Not applicable.
• MRMC Comparative Effectiveness Study: Explicitly stated that "clinical data is not required to demonstrate substantial equivalence." Therefore, no MRMC study with human readers comparing AI vs. without AI assistance was performed or reported.
• Standalone Performance: The testing described is for the algorithm (Enhanced Noise Reduction) as part of the device (OEC Elite C-arm) but without human-in-the-loop performance reported.
• Type of Ground Truth: For the "quantitative performance claims," the ground truth would typically be objective physical measurements of image quality parameters derived from phantoms.
• Sample Size (Training Set): Not mentioned.
• Ground Truth for Training Set: Not mentioned.

Based on the available information, here's what can be provided:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size: Not specified. Testing involved "standard IQ metrics and QA phantoms" and "a wide variety of anthropomorphic phantoms."
• Data provenance: Not applicable in the traditional sense, as testing was performed using phantoms and engineering bench tests. This is non-clinical, in-house testing by the manufacturer.

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

• Not applicable. The claims are based on objective, quantifiable physical measurements using phantoms, not on expert human interpretation of images for ground truth.

4. Adjudication method for the test set

• Not applicable, as ground truth was established through physical measurements rather than human consensus or adjudication.

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. The document explicitly states: "The new performance claims and the accumulated changes did not require clinical data in order to establish safety or efficacy." And "clinical data is not required to demonstrate substantial equivalence." Therefore, no MRMC study was performed or reported.

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

• Yes, implicitly. The "Enhanced Noise Reduction" is an algorithm (an "augmented image processing pathway"). The "additional engineering bench testing was performed to substantiate the quantitative performance claims related to Enhanced Noise Reduction" and to demonstrate "overall imaging performance... using a wide variety of anthropomorphic phantoms." This describes testing the algorithm's effect on image quality metrics without human interpretation as part of the core evaluation for these particular claims.

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

• For the non-clinical performance claims, the ground truth was established through objective physical measurements using "standard IQ metrics and QA phantoms" and "anthropomorphic phantoms." This involves measuring parameters like signal-to-noise ratio, spatial resolution, and potentially dose, against expected or ideal values from the phantoms.

8. The sample size for the training set

• Not specified in the provided text.

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

• Not specified in the provided text, as details on the training set or its ground truth are absent.

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The OEC Elite mobile fluoroscopy system is designed to provide fluoroscopic and digital spot images of adult and pediatric patient populations during diagnostic, interventional, and surgical procedures. Examples of a clinical application may include: orthopedic, gastrointestinal, endoscopic, urologic, vasular, cardiac, critical care, and emergency procedures.

The OEC Elite is a Mobile Fluoroscopic C-arm Imaging system used to assist trained surgeons and other qualified physicians. The system is used to provide fluoroscopic X-Ray images during diagnostic, interventional, and surgical procedures. These images help the physician visualize the patient's anatomy and interventional tools. This visualization helps to localize clinical regions of interest and pathology. The images provide real-time visualization and records of pre-procedure anatomy, in vivo-clinical activity and post-procedure outcomes. The system is composed of two primary physical components. The first is referred to as the "C - Arm" because of its "C" shaped image gantry; the second is referred to as the "Workstation", which is the primary interface for the user to interact with the system.

The C-arm is a stable mobile platform capable of performing linear motions (vertical, horizontal) and rotational motions (orbital, lateral, wig-wag) that allow the user to position the X-Ray image chain at various and distances with respect to the patient anatomy to be imaged. The C - arm is mechanically balanced allowing for ease of movement and capable of being "locked" in place using a manually activated lock. The C-Arm is comprised of the high voltage generator, software, X-ray control, and a "C" shaped image gantry, which supports an X-ray tube and a Flat Panel Detector or Image Intensifier, depending on the choice of detector configuration desired.

The workstation is a stable mobile platform with an articulating arm supporting a color image, high resolution, LCD display monitor. It also includes image processing equipment/software, recording devices, data input/output devices and power control systems.

The primary purpose of the mobile fluoroscopy system is to provide fluoroscopic images of the patient during diagnostic, interventional, and surgical procedures such as orthopedic, gastrointestinal, endoscopic, urologic, neurologic, vascular, cardiac, critical care and emergency procedures.

This document (K172550) is a 510(k) summary for a medical device (OEC Elite fluoroscopy system) and does not describe a study related to an AI/ML-based device.

Therefore, many of the requested details, such as "number of experts used to establish ground truth", "adjudication method", "MRMC study", "standalone performance", "training set size", and "ground truth for training set", are completely irrelevant to this document.

The document discusses the substantial equivalence of an updated version of a fluoroscopy system (OEC Elite with Cardiac option) to its predicate device. This is a hardware/software update to an imaging device, not an AI/ML diagnostic or assistive tool.

Based on the provided text, here's what can be extracted regarding acceptance criteria and performance, focusing on the device's performance rather than an AI's performance:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are based on demonstrating that the updated OEC Elite with Cardiac option maintains the performance of the predicate device and meets established industry standards for X-ray imaging systems. The "reported device performance" are statements of compliance and successful testing rather than specific numerical results for all metrics.

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

The document explicitly states that no clinical images or human studies were used to demonstrate substantial equivalence for the cardiac option. The testing conducted was "engineering (non-Clinical) testing," "engineering bench testing," and "imaging performance evaluation using anthropomorphic phantoms."

Therefore, there is no "test set" in the sense of clinical patient data, nor is there data provenance (country of origin, retrospective/prospective). The "sample size" would refer to the number of phantom tests or bench tests, which are not specified in numerical terms beyond "successful verification and validation testing" and "additional engineering bench testing."

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

Not applicable. No ground truth was established by human experts for a clinical dataset because no clinical dataset was used for demonstration of substantial equivalence.

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

Not applicable. No clinical test set requiring adjudication was used.

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

Not applicable. This is not an AI device, and no MRMC study was performed.

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

Not applicable. This is a fluoroscopy imaging system, not an AI algorithm.

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

The "ground truth" for the device's technical performance was established by measurement against established engineering standards and phantom studies, rather than clinical ground truth (e.g., pathology). The "truth" was defined by what parameters an X-ray imaging system should meet.

8. The sample size for the training set

Not applicable. This is not an AI/ML device that requires a "training set" of data. The software changes were built upon an existing architecture and followed a standard software development lifecycle.

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

Not applicable. No training set was used in the context of AI/ML.

Ask a specific question about this device

The OEC Elite mobile fluoroscopy system is designed to provide fluoroscopic and digital spot images of adult and pediatric patient populations during diagnostic, interventional, and surgical procedures. Examples of a clinical application may include orthopedic, gastrointestinal, endoscopic, urologic, vascular, critical care, and emergency procedures.

The OEC Elite is a Mobile Fluoroscopic C-arm Imaging system used to assist trained surgeons and other qualified physicians. The system is used to provide fluoroscopic X-Ray images during diagnostic, interventional, and surgical procedures. These images help the physician visualize the patient's anatomy and interventional tools. This visualization helps to localize clinical regions of interest and pathology. The images provide real-time visualization and records of pre-procedure anatomy, in vivo-clinical activity and post-procedure outcomes. The system is composed of two primary physical components. The first is referred to as the "C - Arm" because of its "C" shaped image gantry; the second is referred to as the "Workstation", which is the primary interface for the user to interact with the system.

The provided document describes the OEC Elite mobile fluoroscopy system, which is a medical imaging device. The document is submitted as a 510(k) premarket notification to the FDA to demonstrate substantial equivalence to a legally marketed predicate device.

However, the document specifically states: "Clinical images are not required to demonstrate the substantial equivalence to the predicate device." This means that there was no clinical study involving human patients or human readers performed to prove the device meets acceptance criteria related to clinical performance (e.g., diagnostic accuracy, reader improvement with AI assistance).

The acceptance criteria and proof of performance are based on non-clinical testing (engineering bench testing and phantom studies).

Here's a breakdown of the requested information based on the provided text, while acknowledging the absence of a clinical study:

1. Table of Acceptance Criteria and Reported Device Performance (Non-Clinical):

The acceptance criteria are implied by compliance with various industry standards and guidance documents for X-ray imaging devices. The document asserts that the device met these criteria.

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

• Test Set Sample Size: Not applicable in the context of a clinical test set. The document refers to "engineering bench testing" and "imaging performance evaluation using anthropomorphic phantoms." The specific number of phantoms or tests is not provided.
• Data Provenance: Not applicable for clinical data. The tests were performed internally by the manufacturer (GE OEC Medical Systems, Inc.) in Salt Lake City, Utah, USA. The data is from non-clinical sources (bench tests, phantom studies).

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

• Not applicable. As no clinical study was performed, there were no human experts establishing clinical ground truth for a test set. Ground truth for non-clinical performance (e.g., image quality metrics) is established through engineering and physics measurements against defined standards.

4. Adjudication Method for the Test Set:

• Not applicable, as no clinical study with human readers or AI performance evaluation was conducted.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No. The document explicitly states: "Clinical images are not required to demonstrate the substantial equivalence to the predicate device." Therefore, no MRMC study to compare human readers with and without AI assistance was performed.

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

• Yes, indirectly, in a non-clinical context. The device itself is an imaging system, not explicitly an "AI algorithm" in the modern sense of a diagnostic AI. However, the performance metrics listed (DOE, spatial resolution, contrast resolution, etc., and the functioning of new software features like subtraction or roadmapping) represent the "standalone" imaging performance of the device, without human interpretation as part of the validation study. The "algorithm" here refers to the underlying image processing and control software of the fluoroscopy system.

7. The Type of Ground Truth Used:

• Engineering specifications, physical measurements, and phantom imaging results. The ground truth for the non-clinical performance was based on:
  • Design input specifications.
  • Compliance with recognized standards (e.g., IEC 60601 series, FDA's "Information for Industry: X-ray Imaging Devices- Laboratory Image Quality and Dose Assessment, Tests and Standards", "Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices (SSXI)").
  • Measurements obtained from anthropomorphic phantoms that simulate human anatomy, rather than actual patient data or clinical outcomes.

8. The Sample Size for the Training Set:

• Not applicable. This device is a fluoroscopy system, not a machine learning model that undergoes "training" in the typical AI sense. The software development process mentioned (IEC 60324 compliant, design control, risk management) pertains to traditional software engineering, not AI model training with large datasets. The new vascular features were "built upon the existing robust and extensible software architecture."

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

• Not applicable, for the same reason as point 8.

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The OEC Elite™ MiniView™ (mobile mini C-Arm) is designed to provide physicians with real time general fluoroscopic visualization of patients of all ages. It is intended to aid physicians and surgeons during diagnostic or therapeutic treatment/surgical procedures of the limbs/extremities and shoulders including, but not limited to, orthopedics and emergency medicine.

The OEC Elite™ MiniView™ is a mobile fluoroscopic mini C-arm system that provides fluoroscopic images of patients of all ages during diagnostic, treatment, and surgical procedures of the shoulders, limbs, and extremities. The system consists of a C-arm attached to an image processing workstation. A CsI(TI) -CMOS flat panel detector and the identical X-ray source monoblock are used for image acquisition.

The C-arm supports the high-voltage generator, X-ray tube, X-ray controls, collimator, and the FPD. The C-arm is capable of performing linear (vertical, horizontal, orbital) and rotational motions that allow the user to position the X-Ray imaging components at various angles and distances with respect to the patient extremity anatomy to be imaged. The C and support arm are mechanically balanced allowing for ease of movement and capable of being "locked" in place using an electronically controlled braking system. The workstation is a stable mobile platform that supports the C-arm, image display monitor(s), image processing equipment/software, recording devices, data input/output devices and power control systems.

The primary technology change for the subject device compared to the unmodified predicate OEC Elite MiniView, was to add an optional wireless footswitch which provides identical functionalities as the wired footswitch to control X-ray on and off.

This document describes the 510(k) summary for the GE OEC Elite™ MiniView™ device, which is a mobile fluoroscopic mini C-arm system. The specific change being submitted for review is the addition of an optional wireless footswitch.

Here's an analysis of the provided text to answer your questions regarding acceptance criteria and the study proving the device meets them:

Crucially, this 510(k) submission states that no clinical studies were required to support substantial equivalence due to the nature of the modification (adding a wireless footswitch). Therefore, many of your questions related to clinical study design (sample size, expert ground truth, MRMC studies, standalone performance) will not be applicable or directly answerable from this document.

The primary method of demonstrating device performance and safety for this submission was through non-clinical testing, including design verification and validation, risk management activities, and compliance with recognized standards.

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

Since this is a submission for a modification (wireless footswitch) and relies on non-clinical testing for substantial equivalence, the "acceptance criteria" are primarily related to product safety, effectiveness, and functional equivalence to the wired footswitch and predicate device.

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

• Sample Size for Test Set: Not applicable in the context of clinical data. The "test set" here refers to the device itself and its components undergoing engineering and functional verification/validation testing. This is not a patient-based test set.
• Data Provenance: The testing was conducted internally by GE Hualun Medical Systems Co. Ltd. in Beijing, China, as part of their design control processes. This is prospective engineering and quality assurance testing, not data collected from patients.

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. Ground truth in a clinical sense (e.g., disease presence) was not established. The "ground truth" for this engineering submission is functional correctness and safety established by engineering specifications, international standards, and internal quality processes.

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

• Not applicable. This was not a human reader adjudication study. The "adjudication" was based on successful completion of predetermined engineering tests and compliance with regulatory standards, as overseen by GE's quality management system.

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 MRMC study was done. The document explicitly states: "The subject of this premarket submission, OEC Elite MiniView with the addition of the wireless footswitch, did not require clinical studies to support substantial equivalence." This device is not an AI-assisted diagnostic tool.

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

• Not applicable. This device is a medical imaging system, and the submission is for a hardware control component (wireless footswitch), not a standalone algorithm or AI.

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

• The "ground truth" used for this submission is based on engineering specifications, functional requirements, and compliance with recognized industry and electrical safety standards. For example, the footswitch must reliably transmit an "X-ray ON/OFF" signal, and the device must maintain its safety characteristics as per IEC 60601 series standards. This is not a clinical ground truth.

8. The sample size for the training set

• Not applicable. This is not a machine learning/AI device, so there is no "training set."

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

• Not applicable. As there is no training set for an AI model, there is no ground truth established for one.

Ask a specific question about this device

The OEC Elite mobile fluoroscopy system is designed to provide fluoroscopic and digital spot images of adult and pediatric populations during diagnostic, interventional and surgical procedures. Examples of a clinical application may include: orthopedic, gastrointestinal, endoscopic, urologic, critical care and emergency procedures.

The OEC Elite is a Mobile Fluoroscopic C-arm Imaging system used to assist trained surgeons and other qualified physicians. The system is used to provide fluoroscopic X-Ray images during diagnostic, interventional, and surgical procedures. These images help the physician visualize the patient's anatomy and interventional tools. This visualization helps to localize clinical regions of interest and pathology. The images provide real-time visualization and records of pre-procedure anatomy, in vivo-clinical activity and post-procedure outcomes. The system is composed of two primary physical components. The first is referred to as the "C - Arm" because of its "C" shaped image gantry; the second is referred to as the "Workstation", which is the primary interface for the user to interact with the system.

The C-arm is a stable mobile platform capable of performing linear motions (vertical, horizontal) and rotational motions (orbital, lateral, wig-wag) that allow the user to position the X-Ray image chain at various angles and distances with respect to the patient anatomy to be imaged. The C - arm is mechanically balanced allowing for ease of movement and capable of being "locked" in place using a manually activated lock. The C-Arm is comprised of the high voltage generator, software, X-ray control, and a "C" shaped image gantry, which supports an X-ray tube and a Flat Panel Detector or Image Intensifier, depending on the choice of detector configuration desired.

The workstation is a stable mobile platform with an articulating arm supporting a color image, high resolution, LCD display monitor. It also includes image processing equipment/software, recording devices, data input/output devices and power control systems.

The primary purpose of the mobile fluoroscopy system is to provide fluoroscopic images of the patient during diagnostic, interventional, and surgical procedures such as orthopedic, gastrointestinal, endoscopic, urologic, neurologic, critical care and emergency procedures.

The OEC Elite comes with four image receptor (detector) options: the choice of 21x21 cm or 31x31 cm (new) Thallium-doped Cesium Iodide Cs] solid state flat panel X-ray detector with Complementary Metal Oxide Semiconductor (CMOS) light imager; or the choice of a 9 inch or 12 inch of the same existing image intensifier as in the OEC 9900 Elite.

This document describes the OEC Elite, a mobile fluoroscopy system. It does not contain information on human performance studies or the establishment of ground truth by expert consensus for evaluating clinical tasks. Instead, it focuses on non-clinical engineering and imaging performance testing against defined metrics.

Here is an analysis based on the provided text, focusing on the acceptance criteria and the study proving the device meets them:

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

The document outlines acceptance criteria based on performance metrics for Solid State X-ray Imaging Devices (SSXI) and compares the OEC Elite to its predicate device, OEC 9900 Elite.

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

The document refers to "additional engineering bench testing" and "imaging performance evaluation using anthropomorphic phantoms." It does not specify a distinct "test set" in terms of clinical images or patient data, nor does it provide a sample size for such a set. It appears the performance evaluations were conducted on the device itself and phantoms.

The data provenance is through non-clinical testing using anthropomorphic phantoms in a laboratory setting at GE OEC Medical Systems, Inc. (GE Healthcare).

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

This information is not applicable as the evaluation was based on non-clinical engineering and imaging performance metrics, primarily using anthropomorphic phantoms and objective measurements. There was no mention of human experts establishing ground truth for a clinical test set in this context.

4. Adjudication method for the test set:

This information is not applicable as there was no clinical test set requiring human adjudication to establish ground truth. The evaluation focused on technical performance metrics against a predicate device.

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 MRMC comparative effectiveness study was done. The device described (OEC Elite) is a mobile fluoroscopy system, a medical imaging hardware device, not an AI-powered diagnostic tool that assists human readers. Therefore, the concept of "human readers improve with AI vs without AI assistance" does not apply to this submission.

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

This is not applicable in the context of an x-ray imaging system. The OEC Elite is a hardware device that produces images, not an algorithm, and the performance criteria relate to image quality and system functionality, not algorithmic output without human intervention.

7. The type of ground truth used:

The "ground truth" for the non-clinical testing was established by objective measurements of physical performance metrics (e.g., DQE, spatial resolution) on the OEC Elite and compared to the established performance of the predicate device (OEC 9900 Elite) and reference devices. Additionally, compliance with recognized standards (e.g., IEC 60601-1 Ed. 3 series, 21CFR Subchapter J) served as a form of "ground truth" for safety and efficacy.

8. The sample size for the training set:

This information is not applicable. The OEC Elite is a medical imaging hardware system, not a machine learning or AI algorithm that requires a "training set."

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

This information is not applicable as there was no training set.

Ask a specific question about this device

The OEC Elite MiniView (mobile mini C-Arm) is designed to provide physicians with real time goopic visualization of patients of all ages. It is intended to aid physicians and surgeons during diagnostic or therapeutic treatment/surgical procedures of the limbs/extremities and shoulders including, but not limited to, orthopedics and emergency medicine.

The OEC Elite™ MiniView™ is a mobile fluoroscopic mini C-arm system that provides fluoroscopic images of patients of all ages during diagnostic, treatment, and surgical procedures of the shoulders, limbs, and extremities. The system consists of a C-arm attached to an image processing workstation. A CsI(TI) - CMOS flat panel detector and the identical X-ray source monoblock are used for image acquisition.

The C-arm supports the high-voltage generator, X-ray tube, X-ray controls, collimator, and the FPD. The C-arm is capable of performing linear (vertical, horizontal, orbital) and rotational motions that allow the user to position the X-Ray imaging components at various angles and distances with respect to the patient extremity anatomy to be imaged. The C and support arm are mechanically balanced allowing for ease of movement and capable of being "locked" in place using an electronically controlled braking system. The workstation is a stable mobile platform that supports the C-arm, image display monitor(s), image processing equipment/software, recording devices, data input/output devices and power control systems.

The OEC Elite™ MiniView™ is a mobile fluoroscopic mini C-arm system. The provided document is a 510(k) Premarket Notification Submission, which focuses on demonstrating substantial equivalence to a predicate device, rather than defining and proving acceptance criteria in the typical sense of a clinical trial for a novel AI device. However, based on the information provided, we can extract details about the performance evaluation done to demonstrate this equivalence.

Here's an analysis based on the provided text, structured according to your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics like sensitivity, specificity, or AUC as one might find for an AI diagnostic algorithm. Instead, the evaluation focuses on demonstrating that the performance of the proposed device (OEC Elite™ MiniView™) is at least equivalent to the predicate device (OEC Mini 6800 Digital Mobile C-arm) and reference devices in terms of image quality and clinical capability.

The "acceptance criteria" here implicitly revolve around ensuring the safety and effectiveness of the updated device, which includes:

• Meeting design input and user needs.
• Compliance with regulatory standards (IEC 60601-1 Ed.3 series, IEC 60601-2-54, IEC 60601-2-43, and 21CFR Subchapter J performance standards).
• Image quality and clinical capability at least equivalent to the predicate device.

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

• Test Set Sample Size: The document mentions a cadaver study involving two cadavers on which nineteen orthopedic procedures were performed across a variety of extremity anatomies.
• Data Provenance: The cadaver study was performed as part of the submission process, implying it was a prospective evaluation specifically for this device. The country of origin of the cadavers is not specified in the provided text.

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

• Number of Experts: Two independent physicians were used to evaluate the images.
• Qualifications of Experts: The document states they were "two independent physicians", and given the nature of the device (fluoroscopic imaging for orthopedic procedures), it's highly probable these were orthopedic surgeons or radiologists with expertise in musculoskeletal imaging and procedures. However, their specific specializations or years of experience are not explicitly stated in the provided text.

4. Adjudication Method for the Test Set

The document states: "The performance of the subject device to the predicate was also performed by two independent physicians." It further states that the "study confirmed the clinical capability and overall quality of the images produced by the OEC Elite™ MiniView™ was at least equivalent to that of the Mini 6800 Digital Mobile C-Arm." This implies a consensus or comparative evaluation by the two physicians. However, a specific adjudication method (e.g., 2+1, 3+1, etc.) is not explicitly detailed. It's presented as a direct comparison where both physicians apparently agreed on the equivalence.

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

• Not a typical MRMC study: The evaluation described is not a traditional MRMC comparative effectiveness study focused on quantifying human reader improvement with AI assistance. This device is an imaging system (hardware and software for image acquisition and processing), not an AI-powered diagnostic aide designed to improve human reader performance for a specific task.
• Focus on System Equivalence: The study aimed to demonstrate the system's overall clinical capability and image quality equivalence to a predicate device, as evaluated by human readers (the two physicians), rather than measuring the effect size of AI assistance on human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Standalone "Algorithm" Performance: The device itself is an imaging system, not purely an algorithm. Its performance is inherent in the images it produces. Therefore, "standalone" in this context refers to the system's ability to produce diagnostically acceptable images.
• Bench Testing and Image Quality Tests: The document details extensive "engineering bench testing" and "image quality/performance testing" identified for fluoroscopy. These tests evaluate the system's technical image output without human interpretation as the primary endpoint. This can be considered the equivalent of "standalone" performance for an imaging device. Specifically mentioned are:
  • Demonstration of system performance.
  • Imaging performance evaluation using anthropomorphic phantoms (including a pediatric anthropomorphic phantom).
  • All image quality/performance testing identified for fluoroscopy in FDA's "Information for Industry: X-ray Imaging Devices - Laboratory Image Quality and Dose Assessment, Tests and Standards" was performed.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• For the Cadaver Study (Test Set): The ground truth for evaluating clinical capability and image quality seems to be based on expert consensus (or agreement) between the two independent physicians regarding the equivalence of the images produced by the OEC Elite™ MiniView™ compared to the predicate device for diagnostic and procedural guidance in the cadaveric setting. There is no mention of pathology or outcomes data for this specific evaluation, as it's a technical performance and clinical utility assessment on cadavers.
• For Bench Testing: The ground truth for bench testing and phantom studies would be defined by known physical properties of the phantoms and established engineering specifications and standards for image quality metrics.

8. The Sample Size for the Training Set

The document describes a medical imaging device (C-arm), not an AI algorithm that requires a separate training set. Therefore, the concept of a "training set sample size" as typically applied to machine learning models is not applicable here. The device's underlying technology and software architecture are based on existing, proven designs (predicate and reference devices), with modifications validated through engineering bench tests and the cadaver study.

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

As noted in point 8, there is no explicit "training set" in the context of an AI algorithm described in this document. The device's development involved standard engineering practices, which could be considered an iterative design and testing process that refines the system's performance. The "ground truth" during this development would be based on engineering specifications, performance targets, and established imaging principles, rather than a labeled dataset for training an AI model.

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