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The XRpad2 4336 HWC-M, when used with a radiographic imaging system, is indicated for use in generating radiographic images of human anatomy for diagnostic X-ray procedures, wherever conventional screen-film (SF), digital radiography (DR), or computed radiography (CR) systems may be used. It is not intended for mammographic use.

Device Description

The XRpad2 4336 HWC-M is a lightweight, cassette-sized, flat panel X-ray detector for digital radiography. The X-ray detector consists of an amorphous silicon flat panel with a directly deposited CsI:T1 scintillator and dedicated read-out, scan, and control electronics, all packaged in a carbon-fiber and aluminum enclosure. The outside dimensions of the detector are 460.0 mm × 383.6 mm × 15.5 mm, which fits into a standard X-ray cassette Bucky.

The detector can be integrated into a fixed room X-ray system to enable digital radiography.

AI/ML Overview

This document describes the 510(k) summary for the PerkinElmer XRpad2 4336 HWC-M Flat Panel Detector, which seeks to establish substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a quantitative table format with corresponding "reported device performance" values for the XRpad2 4336 HWC-M. Instead, it relies on demonstrating equivalence to a predicate device (PerkinElmer XRpad 4336 MED, K140551) through non-clinical testing and stating that the physical values are "comparable."

However, a comparison chart for device characteristics is provided (Page 5), which implicitly indicates the performance metrics considered for demonstrating equivalence. The "acceptance criteria" for the new device are essentially that its performance is equivalent to the predicate.

Characteristic	Predicate Device Performance (PerkinElmer XRpad 4336 MED, K140551)	Proposed Device Performance (PerkinElmer XRpad2 4336 HWC-M)	Reference/Comment (Implicit Acceptance Criteria)
Intended Use / Indications for Use	As described for predicate	Same	Must be the same as the predicate.
Panel	Single substrate amorphous silicon active TFT/diode array	Same	Must be the same.
Scintillator	Direct deposition CsI:Tl	Same	Must be the same.
Pixel pitch	100 µm	Same	Must be the same.
Pixel matrix	3556 × 4320 pixels	3524 × 4288 pixels	Slightly different, but not noted as impacting image quality or substantial equivalence.
Limiting resolution	5 lp/mm	Same	Must be the same.
Binning capable	2 × 2 binning for 200 µm	Same	Must be the same.
Data transmit area	355 mm × 432 mm	352 mm × 429 mm	Slightly different, corresponding to pixel matrix change, but not noted to impact image quality.
External dimensions (w×l×h)	384 mm × 460 mm × 15 mm	384 mm × 460 mm × 15.5 mm	Minimal difference, attributed to housing update.
Weight	3.8 kg	3.1 kg	Different, due to housing update, and stated not to impact image quality.
Housing material	Aluminum with carbon-fiber	Same	Must be the same.
Finish	Matte carbon-fiber front with white silk-screen active area markers	Same	Must be the same.
Communication interface	Gb Ethernet or 802.11n WiFi	Same	Must be the same.
WiFi band	5.1-5.3 GHz	5.1-5.9 GHz	Expanded, but considered equivalent for networking.
X-ray synchronization interface	Dedicated trigger in/out signal lines or Automatic Exposure Detection	Same	Must be the same.
Power	External power supply or battery	Same	Must be the same.
Software library	Windows OS	Windows and Linux OS	Expanded OS support, but functionality considered equivalent.
DQE and MTF	Not explicitly stated, but established for predicate	Comparable to predicate device	Must be comparable to the predicate device to demonstrate substantial equivalence (non-clinical test).

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

A new clinical study was not conducted for the XRpad2 4336 HWC-M device. The clinical data supporting the predicate device, XRpad 4336 MED, was derived from testing for K122495 (XRD 1622 AP3 MED). Therefore, no specific "test set" sample size or data provenance is provided for the current device's clinical performance. The current device relies on demonstrating that its differences "do not invalidate the applicability of the clinical study data submitted in K122495."

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

Since a new clinical study was not conducted for this device, and it relies on previous clinical data, this information is not provided in the document. The document refers to the predicate clearance (K140551) which itself references K122495 for clinical data. Details on experts and ground truth for K122495 are not in this document.

4. Adjudication Method for the Test Set

As no new clinical study test set was used for this device, a specific adjudication method is not described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done for the XRpad2 4336 HWC-M. The submission focuses on non-clinical equivalence to a predicate device.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

This device is a flat panel X-ray detector, not an AI algorithm. Therefore, a standalone (algorithm only) performance study as typically understood for AI/CAD systems is not applicable or performed. Its performance is measured by image quality metrics (like DQE, MTF) and compared to a predicate device.

7. Type of Ground Truth Used

For the current device, direct clinical ground truth (e.g., pathology, outcomes data) was not established in a new study. The device's "ground truth" for clinical performance is indirectly established by demonstrating its equivalence to a predicate device whose clinical effectiveness was previously established, likely through methods typical for X-ray detectors (e.g., image quality assessment, possibly expert consensus on diagnostic images from K122495).

8. Sample Size for the Training Set

This device is an X-ray detector, not a machine learning algorithm that requires a "training set" in the conventional sense. The document describes engineering, design, and performance validation, not algorithmic training.

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

As this is not an AI/ML device requiring a training set, this question is not applicable.

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