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Intended for use by a qualified/trained physician or technician for the purpose of acquiring X-ray images of the desired parts of patient's anatomy (including head, cervical spine, chest, abdomen, lumbar spine, pelvis and extremities).This device is not intended for mammography.

This SR-2300/SR-2300S Portable DR Imaging System is a portable digital device developed, designed and manufactured by SIUI. The device consists of the following major components: a portable X-ray unit, a flat panel detector, and workstation. The difference between SR-2300 and SR-2300S is the operation interface of the portable X-ray Unit only, while the flat panel detector and the workstation are the same for SR-2300 and SR-2300S. The SR-2300S has the display interface with button-operation digital tube, while the SR-2300 has the display interface with touch screen operation.

The provided text describes a 510(k) premarket notification for the SR-2300/SR-2300S Portable DR Imaging System. This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific acceptance criteria through a clinical performance study for an AI/ML-enabled medical device.

Therefore, many of the requested details about acceptance criteria, study design (sample size, ground truth, experts, adjudication, MRMC), and training set information for an AI/ML device are not present in this document. This submission is for a traditional medical device (portable X-ray system), not an AI/ML diagnostic software.

Here's a breakdown of the available information based on your request, highlighting what is not applicable (N/A) or not provided in this type of submission:

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

• Acceptance Criteria: N/A. This submission focuses on demonstrating substantial equivalence to a predicate device through technical specifications and compliance with established performance standards for X-ray systems, rather than meeting specific performance metrics for a diagnostic or AI algorithm.
• Reported Device Performance: The document provides a comparison of technical characteristics between the subject device and the predicate device (Table 1 on page 6-7). This table serves to show that the new device's specifications meet or exceed those of the predicate, or that any differences do not impact safety or efficacy. For example:
  • X-ray Generator Peak Power: Predicate: 2kW; Subject: 3.2kW (implied from "Tube voltage 40-125kV, Tube current 10-100mA")
  • Tube Voltage Adjustable Range: Predicate: 40-100kV; Subject: 40-125kV
  • mAs Range: Predicate: 0.4mAs-50mAs; Subject: 0.4mAs-200mAs
  • DQE: Predicate: 25% at 1.0 lp/mm, 5% at 3.0 lp/mm; Subject: 36% at 1.0 lp/mm, 13% at 3.0 lp/mm
  • MTF: Predicate: 35% at 2.0 lp/mm; Subject: 38% at 2.0 lp/mm

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

• Sample Size for Test Set: N/A. No clinical test set data is reported as "Clinical testing is not necessary for the SR-2300/SR-2300S Portable DR Imaging System in order to demonstrate substantial equivalence to the predicate device." (Page 10, Section 5.9).
• Data Provenance: N/A for clinical performance. The document states "Clinical images were provided; these images were not necessary to establish substantial equivalence based on the modifications to the predicate device, but they provide further evidence in addition to bench testing data to show that the complete system works as intended." (Page 10, Section 5.7). No details on the number or origin of these "clinical images" are given.

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

• N/A. No clinical test set with expert-established ground truth was required or performed for this 510(k) submission.

4. Adjudication method for the test set

• N/A. No 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

• N/A. This is not an AI/ML-enabled device, and no MRMC study was conducted.

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

• N/A. This is a hardware device (portable X-ray system), not a standalone algorithm.

7. The type of ground truth used

• N/A. No clinical performance study requiring ground truth was conducted. The "ground truth" for this type of device is typically established through engineering specifications, phantom testing, and comparisons to established performance standards for X-ray imaging, as well as the predicate device's characteristics.

8. The sample size for the training set

• N/A. This is a traditional medical device, not an AI/ML device that requires a training set.

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

• N/A. No training set for an AI/ML algorithm.

Summary of what the document does provide regarding device performance proof:

The document primarily relies on non-clinical testing and compliance with established standards to demonstrate substantial equivalence and ensure safety and effectiveness.

• Non-clinical Testing Summary (pages 8-10, Section 5.7):
  • The device complies with and was tested in accordance with numerous international standards for medical electrical equipment, X-ray equipment, electromagnetic compatibility, radiation protection, risk management, biological evaluation, software life cycle processes, usability, and symbols.
  • Examples of standards: IEC 60601-1, IEC 60601-1-2, IEC 60601-2-54, IEC 60601-1-3, ISO 14971, ISO 10993 (various parts), IEC 62304, IEC 60601-1-6, IEC 62366-1, ISO 15223-1, ISO 13485.
  • Proof: "The test results showed compliance with the above standards. Validation was performed for overall operation by taking and reviewing test images. Clinical images were provided; these images were not necessary to establish substantial equivalence based on the modifications to the predicate device, but they provide further evidence in addition to bench testing data to show that the complete system works as intended. The non-clinical tests demonstrate that the device is as safe, as effective, and performs as well as the predicate." (Page 10, Section 5.7).
• Comparison to Predicate Device (Table 1, pages 6-7): Shows that the subject device's technical specifications are comparable or superior to the predicate, and any differences do not raise new safety or effectiveness concerns.

In conclusion, this 510(k) submission is for a conventional X-ray system, and therefore, the detailed criteria for an AI/ML device performance study are not applicable or provided. The "proof" of meeting acceptance criteria for this device rests on demonstrating adherence to recognized performance standards for X-ray equipment and showing substantial equivalence to a legally marketed predicate device through technical comparisons and non-clinical bench testing.

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