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The ELPH Injection System is a contrast delivery system which is designed to inject radiopaque contrast media into a patient's vascular system to obtain diagnostic images when used with computed tomography (i.e. "CT") equipment.

The ELPH Injection System will deliver radiographic contrast media at a controlled flow rate and volume into a patient's vascular system for the purpose of obtaining enhanced diagnostic images. The ELPH is made up of the following major components: Power Head, Power Pack, Remote Console (Optional), Syringes.

The provided document is a 510(k) summary for the ELPH Injection System. It describes the device, its intended use, and argues for its substantial equivalence to a predicate device (CT 8000 Digital Injection System, later marketed as CT 9000ADV).

However, this document does not contain acceptance criteria or detailed study information that would typically be found in a performance evaluation or clinical study report. It is a regulatory submission focused on demonstrating equivalence rather than proving performance against specific criteria through a dedicated study.

Therefore, many of your requested points cannot be answered from the provided text. The document primarily focuses on a comparison of features between the new device and the predicate device to argue for substantial equivalence.

Here's how much can be extracted from the provided text based on your request:

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

The document does not explicitly state "acceptance criteria" for the ELPH Injection System in the way a performance study would. Instead, it compares the features and performance specifications of the ELPH system to its predicate device, the CT 8000 Digital Injection System. The "reported device performance" is essentially the listed specifications for the ELPH.

Note: The "acceptance criteria" here are implied by the performance of the predicate device. The submission makes a case that the ELPH system is "less expensive, smaller and less complicated to operate" and meets "only the ordinary needs," which sometimes results in lower specifications compared to the predicate, but is still considered substantially equivalent for its intended, more focused purpose.

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

This information is not provided in the document. The document presents a comparison of device features and specifications, not data from a test set or provenance of data.

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)

This information is not provided in the document, as it does not detail a study involving expert assessment or ground truth establishment.

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

This information is not provided in the document.

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

This information is not provided in the document. The device is an injection system, not an AI-powered diagnostic tool.

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

This information is not provided in the document. The device is a hardware injection system and does not appear to involve algorithms in the context of diagnostic performance.

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

This information is not provided in the document, as it does not detail a study where ground truth would be established for evaluating diagnostic performance.

8. The sample size for the training set

This information is not provided in the document. The device is a hardware injection system and the submission does not mention a training set in the context of machine learning.

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

This information is not provided in the document.

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The Angiomat Illumena is designed to inject a radiopaque contrast medium into the vascular system for Angiographic or CT procedures as prescribed by qualified health care professionals.

The Angiomat Illumena is designed to inject a radiopaque contrast medium into the vascular system for Angiographic or CT procedures as prescribed by qualified health care professionals. The system is designed to be configured as cither an Angiographic injector or as a CT injector.

The system includes a microprocessor controlled DC servo motor which drives a lead serve ram against the piston of a single use syringe. The operation of the servo is programmed by the operator using a touch screen on an electroluments on display. The system is powered by AC line voltage at 100 Volts, 130 Volts, or 240 Volts. System power is less than 1500 Walls.

A typical Angiomat Illumena system includes a power pack, console, powerhead, syringe holder assembly, ac power cable assembly, start cable assembly, and console cable assembly. Other options include ECCG trigger systems, syringe heater, air detection and warning system, pedestal mounting system. wall/rack/ceiling mounting systems, interface cabling, powerhead and console extension cabling. Start switch variations, and printer system.

The system is designed to deliver contrast from either a prefilled syringe or an unfilled wringe which is filled at the start of the procedure. A reusable, sterilizable syringe is also available.

The system will interface with an X-ray system allowing either the start of injection initiated by the X-ray system or start of X-ray initiated by the injector.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Angiomat Illumena Injector:

Note: The provided document is a 510(k) summary for a medical device. This type of document focuses on demonstrating substantial equivalence to predicate devices rather than deeply detailed, statistically rigorous clinical trials common for novel devices or software. As such, some of the requested information (like specific sample sizes for test sets, the number of experts for ground truth, or MRMC studies) is not typically included in this type of submission and is therefore not present in the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the device's ability to perform "to specification within ranges equivalent to the predicate devices with accuracy and precision superior to the predicate devices." The performance reported is that the device meets these specifications.

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

• Sample Size: Not explicitly stated in terms of number of injections or individual tests. The document refers to "a comprehensive set of tests" and "tests were performed using extremes of operating parameters."
• Data Provenance: The tests directly involve the physical device (Angiomat Illumena Injector) delivering water. This implies the data is prospective as it's generated during the testing phase of the new device. The country of origin for the testing is not specified, but given the company's address and the FDA 510(k) submission, it would likely be in the United States.

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

• Number of Experts: Not applicable. The "ground truth" for these performance tests is based on direct physical measurements using calibrated equipment (e.g., for volume, pressure, time) and comparison against the device's own specifications and programmed parameters. There are no human "experts" establishing a subjective ground truth for these engineering performance metrics.
• Qualifications of Experts: N/A.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The "adjudication" is based on objective measurements from calibrated equipment compared against predefined specifications. These are not subjective assessments requiring multiple reviewers.

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 comparative effectiveness study was not done. This device is an injector, not an imaging analysis or diagnostic AI tool. Its performance is measured by its mechanical and electronic accuracy in delivering contrast medium, not its impact on human reader interpretation of medical images.

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

• Standalone Performance: Yes, the described performance tests essentially are standalone performance tests. The device's ability to accurately deliver programmed flow, volume, and pressure is evaluated directly, without a human operator's influence on the measured output (beyond programming the device). The tests verify the device's inherent mechanical and electronic accuracy.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth used for these performance tests is objective physical measurement derived from calibrated reference equipment. For example:
  • For volume accuracy: Measured delivered volume using calibrated equipment.
  • For pressure accuracy: Measured back pressure using calibrated equipment.
  • For flow rate accuracy: Verification of algorithms, timing with measurement equipment, and measured delivered volume over time using calibrated equipment.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This device is a hardware injector with embedded software for control, not a machine learning or AI algorithm that "trains" on data in the conventional sense. The "training" for such a system would involve engineering design, calibration, and iterative development rather than a dataset of clinical cases with established ground truth.

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

• Ground Truth for Training Set: Not applicable. As mentioned above, this is not an AI/ML device that uses a "training set" with ground truth in the typical sense. The "ground truth" for its development would be based on engineering specifications, physical laws, and performance requirements derived from its intended use and predicate devices.

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