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510(k) Data Aggregation
(37 days)
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(55 days)
The XiScan Expert Imaging Systems are intended for fluoroscopic imaging of patient extremities.
The XiScan Expert Imaging Systems are compact, mobile, mini c-arm systems specifically designed for fluoroscopic imaging of patient extremities. Two versions are available: the XiScan Office Expert and the XiScan Surgical Expert. The systems can be operated in either manual or automatic exposure rate control (AERC) modes, with options of reduced radiation LOW DOSE and high resolution STANDARD DOSE when using AERC. Both systems offer a range of options for image manipulations. The Surgical Expert also features a remote, hand-held keypad to manage on-screen patient information and image storage.
The provided text is a 510(k) summary for the XiScan Expert Imaging Systems, which are mini c-arm systems for fluoroscopic imaging. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a dedicated study.
Therefore, many of the requested details about acceptance criteria, study design, and ground truth establishment are not present in this type of regulatory submission, as the requirement for 510(k) is to show equivalence.
However, I can extract the available information:
1. Table of Acceptance Criteria and Reported Device Performance:
No specific acceptance criteria or performance metrics (e.g., sensitivity, specificity, accuracy) are reported in this 510(k) summary. The document relies on a comparison to predicate devices.
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified directly in this document. The basis for substantial equivalence is listed below. | Not specified directly in this document. The basis for substantial equivalence is listed below. |
| Basis for Substantial Equivalence: | The XiScan Expert Imaging Systems have the same intended use and similar technical specifications compared to predicate devices (Fluoroscan Premier, Fluoroscan OfficeMate, OEC Mini 6600 Digital Mobile C-arm). |
| All devices are mini c-arm systems with similar technique factors, SIDs, field-of-view sizes, and image enhancement options. | |
| A bench test confirmed that patient X-ray exposure rates for imaging various anatomies are similar. |
2. Sample Size for the Test Set and Data Provenance:
No specific "test set" in the context of evaluating diagnostic performance is mentioned. The assessment was based on a "bench test comparison" of device specifications and X-ray exposure rates.
- Sample size for test set: Not applicable/not specified for a typical diagnostic performance study.
- Data provenance: The "bench test comparison" implies data was generated directly from the devices being compared, likely within a controlled test environment. Country of origin not specified. Retrospective/prospective not applicable in this context.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
Not applicable. This document describes a comparison of technical specifications and X-ray exposure, not a diagnostic performance study requiring expert ground truth for interpretation.
4. Adjudication Method for the Test Set:
Not applicable. No diagnostic interpretation or "test set" requiring adjudication is mentioned.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No. This document does not mention an MRMC study or any study evaluating the effect of AI assistance on human readers. The device itself is an imaging system, not an AI-based diagnostic tool.
6. Standalone (Algorithm Only) Performance Study:
No. The device is an imaging system, not an algorithm. Therefore, a standalone algorithm performance study is not applicable.
7. Type of Ground Truth Used:
Not applicable for a typical diagnostic performance study. The "ground truth" for the bench test comparison would be adherence to technical specifications and measured X-ray output, which would be objectively determined.
8. Sample Size for the Training Set:
Not applicable. This document describes a physical medical imaging device, not a machine learning algorithm that requires a training set.
9. How Ground Truth for the Training Set Was Established:
Not applicable, as there is no training set for a machine learning algorithm.
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