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OSCAR 15 & OSCAR 15i are a mobile fluoroscopy system designed to provide fluoroscopic and spot film images of the patient during diagnostic, surgical and interventional procedures. Examples of clinical application may include cholangiography, endoscopy, urologic, neurologic, vascular, cardiac and critical care. The system may be used for other imaging applications at the physician's discretion. OSCAR 15i are indicated only for adult patients.

The OSCAR 15 & OSCAR 15i, C-Arm Mobile are used for providing fluoroscopic and radiographic images of patient anatomy, especially during special procedures in a hospital or medical clinics. The fluoroscopic mode of operation is very useful to the attending physician to see the images on real time without the need to develop individual films. These devices are intended to visualize anatomical structures by converting a pattern of x-radiation into a visible image through electronic amplification. The OSCAR 15 & OSCAR 15i consist of the X-ray tube assembly, X-ray controller, Image receptor and some accessories with no wireless function. The difference between OSCAR 15 and OSCAR 15i is only image acquisition parts. (An Flat Panel Detector (FPD) is applied to OSCAR 15, and an Image instensifier is applied to OSCAR 15i.)

The provided text is a 510(k) Pre-Market Notification for the OSCAR 15 & OSCAR 15i mobile fluoroscopy systems. It asserts substantial equivalence to a predicate device (OSCAR 15, K172180) and describes non-clinical performance and safety testing. However, it does not include specific acceptance criteria or a study that directly quantifies device performance against those criteria in a format applicable to AI/CADe devices (e.g., sensitivity, specificity, FROC analysis).

The document is concerned with demonstrating that the devices (OSCAR 15 and the newly added OSCAR 15i) function safely and effectively as fluoroscopic X-ray systems, primarily through comparison to a previously cleared predicate device and compliance with relevant IEC and CFR standards. It describes physical and technical specifications and differences, particularly in the image acquisition parts (Flat Panel Detector vs. Image Intensifier).

Therefore, based on the provided text, I cannot complete the requested tables and information for acceptance criteria and a study proving the device meets those criteria in the way typically expected for AI/CADe devices, as this information is not present. The document focuses on regulatory compliance and substantial equivalence for an imaging hardware device, not an AI/CADe algorithm.

Here's what can be extracted and what is missing based on your request:

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

• Acceptance Criteria: Not explicitly stated in terms of specific performance metrics (like sensitivity, specificity, accuracy) that would be common for AI/CADe devices. The acceptance criteria for this type of device are primarily compliance with safety and performance standards (e.g., IEC 60601 series, 21 CFR 1020.30, 1020.31, 1020.32) and demonstrating "substantial equivalence" to a predicate device.
• Reported Device Performance: The document states that "the performance related to image quality was also different" due to the detector change, and "The image performance was evaluated according to the IEC standard through performance bench testing demonstrated that these differences do not matter and effectiveness in comparison with the predicate device." It also mentions "clinical images have been evaluated by a licensed radiologist confirmed the sufficient diagnostic quality to provide accurate information." However, no quantified performance metrics are provided.

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

• Test Set Sample Size: Not specified. The document mentions "performance bench testing" and evaluation of "clinical images" but does not give a number for images or cases used in these evaluations.
• Data Provenance: Not specified.

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)

• Number of Experts: One ("a licensed radiologist") is mentioned for evaluating clinical images.
• Qualifications of Experts: Only "a licensed radiologist" is mentioned; no specific experience level or sub-specialty is provided.

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

• Adjudication Method: Not specified. Only one radiologist is mentioned for evaluation, implying no consensus/adjudication process was detailed.

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

• MRMC Study: No, an MRMC study targeting human reader improvement with AI assistance was not mentioned. The device is a fluoroscopy system, not an AI/CADe tool for interpreting images.

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

• Standalone Performance: No, this does not apply. The device is a fluoroscopy system, a hardware imaging device, not an algorithm being evaluated in a standalone capacity.

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

• Type of Ground Truth: For the "clinical images," the "sufficient diagnostic quality" was confirmed by a "licensed radiologist." This implies a form of expert opinion/judgment, but it's not explicitly framed as establishing a ground truth for a diagnostic algorithm. For the hardware performance, ground truth would be adherence to physical and electrical specifications verified through bench testing.

8. The sample size for the training set

• Training Set Sample Size: Not applicable/not mentioned. This device is a hardware fluoroscopy system, not an AI model requiring a training set.

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

• Ground Truth for Training Set: Not applicable/not mentioned, as there is no AI model or training set described.

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The FLUSION-9001 fluoroscopic C-arm Mobile X-ray System is intended to provide fluoroscopic and radiographic imaging of the patient during diagnostic, surgical and interventional procedures. Clinical applications may include but are not limited to digital subtraction angiography, orthopedical, abdominal, vascular, cardias, critical care and emergency room procedures.

The FLUSION-9001 fluoroscopic C-arm Mobile X-ray System consists of a high voltage (HV) inverter generator, a tube support unit, an X-ray beam limiting device, mobile cart, a detector, operating software, and a tube, and is primarily used in a hospital for diagnosis of diseases in skeletal. respiratory and urinary systems such as the skull, spinal column, chest, abdomen, extremities, and other body parts. This device is not intended to be used for mammography applications.

FLUSION-9001 fluoroscopic C-arm Mobile X-ray System is a solution to produce radiological images of patient during medical operations. This inverter control X-ray unit visualizes the anatomical structure on screen, which is obtained by X-ray fluoroscopy and a flat panel detector. This system can be applied in emergency room, operation room, cast room or etc. of a hospital.

The provided document is a 510(k) summary for the FLUSION-9001 Fluoroscopic C-arm Mobile X-ray System. It focuses on demonstrating substantial equivalence to predicate devices based on technical specifications and adherence to recognized standards.

Therefore, the document does not contain information about acceptance criteria for device performance in a clinical study, or a study specifically designed to prove the device meets such criteria in terms of diagnostic accuracy or impact on human readers.

The information provided describes the device's technical specifications and compares them to predicate and reference devices, along with compliance with relevant industry standards and regulations for medical devices.

Here's a breakdown of what is available and what is not:

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

• Not Available: The document does not provide a table of acceptance criteria for diagnostic performance outcomes (e.g., sensitivity, specificity, accuracy) or reported performance metrics from a clinical study. The tables present technical specifications of the device and its comparators (e.g., X-ray tube heat capacity, detector DQE, pixel matrix).

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

• Not Available: There is no mention of a test set, sample size, or data provenance related to a clinical performance study. The testing performed focuses on non-clinical aspects like electrical, mechanical, software, and risk management.

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 Available: Since there is no mention of a clinical test set or ground truth establishment, this information is not provided.

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

• Not Available: There is no information on any adjudication method for a clinical test set.

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 Available: The document describes a fluoroscopic C-arm Mobile X-ray system, which is an imaging device, not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study involving AI assistance for human readers would not be applicable or expected for this device nor is it mentioned.

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

• Not Available: As noted above, this is an imaging acquisition device, not an algorithm, so standalone performance is not relevant in the context of diagnostic algorithms.

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

• Not Available: There is no mention of ground truth as it pertains to clinical diagnostic performance.

8. The sample size for the training set

• Not Available: This device is a hardware system, not a machine learning model, so there is no training set in the context of AI/ML.

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

• Not Available: See point 8.

What the document does describe (Non-clinical testing for substantial equivalence):

The document details the non-clinical testing performed to establish substantial equivalence (refer to section VIII. Non clinical testing and IX. Conclusion):

• Standards Adherence: The device successfully underwent testing according to various IEC and EN standards related to medical electrical equipment, including safety, electromagnetic compatibility, and specific requirements for X-ray equipment (e.g., EN 60601-1, EN 60601-1-2, IEC 60601-1-3, IEC 60601-2-43, IEC 60601-2-54).
• Guidance Document Utilization: The development informed by FDA guidance documents regarding software in medical devices, 510(k) submissions for solid-state X-ray imaging devices, cybersecurity, and pediatric information for X-ray imaging devices.
• Regulatory Compliance: Conformance to 21 CFR 1020 Subchapter J (Performance Standards for Ionizing Radiation Emitting Products), 21 CFR 1020.30 (Diagnostic x-ray system and their major components), and 21 CFR 1020.32 (Fluoroscopic Equipment).

The conclusion states that based on these tests and comparisons to predicate devices, the FLUSION-9001 system is considered substantially equivalent in its design, mechanical and electrical performance, making it suitable for its intended use.

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Intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for obtaining fluoroscopic radiographic images of the skull, spinal column, chest, abdomen, extremities, and other body parts.

The Insight Enhanced™ DRF Digital Imaging System is designed to provide an additional imaging acquisition device to the existing image intensifier, camera and user interface with a dynamic flat-panel detector (dFPD) on the following FDA approved R&F fluoroscopic imaging systems employing an image intensifier: GE Advantx, GE Legacy, GE P500 and Shimadzu YSF300. The subject fluoro system Insight Enhanced is based on the predicate Insight Essentials. The following dynamic digital detectors are added to the predicate system: Vivix-D 1212G and Vivix-D 1717G. The x-ray generator, beam-limiting device and patient positioner, necessary for a full fluoroscopy system are not part of the subject device software stays unchanged from the predicate Insight Essentials DRF.

The Insight Enhanced™ DRF Digital Imaging System allows the operator to view and enhance high-definition fluoroscopy images. High resolution digital spot images may also be acquired at single or rapid acquisition rates, up to 30 fps. Images may be viewed and enhanced enabling the operator to bring out diagnostic details difficult or impossible to see using conventional imaging techniques. Images can be stored locally for short term storage. The Insight Enhanced™ DRF Digital Imaging System enables the operator to produce hardcopy images with a laser printer or send images over a network for longer-term storage. The major system components include: a fluoroscopic video camera, monitors, and an image processor PC.

The provided text is a 510(k) summary for the Insight Enhanced™ DRF Digital Imaging System. It describes a device that adds dynamic flat-panel detectors (dFPD) to an existing, already cleared fluoroscopic imaging system. The submission argues for substantial equivalence to a predicate device, the Insight Essentials™ DRF Digital Imaging System (K191310).

Based on the provided text, the device does not have acceptance criteria related to its performance in terms of diagnostic effectiveness that would be proven by a clinical study. Instead, the "acceptance criteria" here relate to demonstrating substantial equivalence to a predicate device, primarily through non-clinical bench testing.

Here's a breakdown of the information requested, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not explicitly stated in terms of patient images. The "test set" described consists of phantom images. The document mentions that "Phantom images were acquired with the subject device and compared to the predicate device, also installed on the same GE Legacy R&F system." The number of phantom images acquired or the specifics of the phantom used are not provided.
• Data Provenance: The data is from non-clinical bench testing rather than human subjects. No country of origin is specified for these bench tests, but they were conducted to support a U.S. FDA submission.

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

• This information is not applicable as the test involved non-clinical bench testing with phantoms and direct comparison to a predicate device, not diagnostic performance with human readers against a human-established ground truth.

4. Adjudication Method for the Test Set

• This information is not applicable as the test involved non-clinical bench testing with phantoms. The comparison was based on analysis of the acquired phantom images and doses, not expert adjudication of diagnostic outcomes.

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

• No, an MRMC comparative effectiveness study was not done. The submission explicitly states: "No clinical data is necessary to evaluate safety or effectiveness for purposes of determining substantial equivalence of the proposed modification. Bench testing was performed to assess the device safety and effectiveness."

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

• The device described is an imaging system component (dynamic flat-panel detectors added to a fluoroscopic imaging system), not an AI algorithm. Its performance is evaluated as part of the overall imaging system's ability to acquire images comparable to a predicate device. Therefore, the concept of a "standalone algorithm" performance study is not applicable in the context of this submission. The "algorithm" if any, is likely for image processing, which is stated to be "unchanged from the predicate Insight Essentials DRF."

7. The Type of Ground Truth Used

• For the non-clinical bench testing, the "ground truth" was effectively the performance of the legally marketed predicate device (Insight Essentials™ DRF Digital Imaging System) and its ability to produce comparable phantom images and use similar doses.

8. The Sample Size for the Training Set

• This information is not applicable. The device is an imaging system component, not an AI model that requires a training set. The software for image processing and workflow functions is stated to be "unchanged from the predicate Insight Essentials DRF."

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

• This information is not applicable as there is no mention of an AI model with a training set.

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