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The Lodox whole-body x-ray scanner is mainly intended for use in trauma wards where multiple injuries can be medically diagnosed in a very short time. It can also be used for normal x-ray examinations as is currently practised with general-purpose single-shot x-ray machines. A full image area is 1800 mm by 680 mm, and can be reduced to any size down to 100 mm by 100 mm anywhere within the image area.

Lodox is a whole-body x-ray scanner that produces x-ray images that can be used for diagnostic purposes. It is an optical-based digital x-ray imager. It works by converting incident x-ray energy to visible light by use of a fluorescent screen optically coupled to a number of CCD cameras, which produce a digital image. The captured diagnostic image is stored in a database and is displayed on a highresolution, medical-quality monitor, where the diagnosis can be performed. The diagnostic image can be transmitted through a DICOM 3.0 compatible digital network for printing. The imaging area can be set from 100 mm x 100 mm x 680 mm on a special purpose patient trolley.

Here's a breakdown of the acceptance criteria and study information for the Lodox Digital Radiography System, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally framed around achieving "substantial equivalence" to predicate devices (film radiography and an existing CT system) in terms of image quality and intended use. The performance metrics reported are primarily physical characteristics and a subjective clinical assessment.

Reported Device Performance (Specific Technological Characteristics):

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

• Sample Size: 39 human subjects
• Data Provenance: Not explicitly stated, but the company is based in South Africa. The phrasing "a range of anatomy was covered representative of general radiography" suggests these were clinical cases, likely prospective, where subjects were x-rayed by both methods.

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

• Number of Experts: Two radiologists.
• Qualifications: "a panel of two radiologists" - no further specific qualifications (e.g., years of experience) are provided in this document.

4. Adjudication Method for the Test Set

• The document states, "The results were examined by a panel of two radiologists and found substantially equivalent to film." This implies a consensus-based adjudication or individual review leading to a uniform conclusion, but a specific method like 2+1 or 3+1 is not detailed. It's possible they independently reviewed and then discussed to reach consensus, or reviewed together.

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

• No, an MRMC comparative effectiveness study was not done in the context of AI assistance. This device is a diagnostic imaging system, not an AI-assisted diagnostic tool. The study compared the image quality of the Lodox system against conventional film radiography.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• This question is not applicable. The Lodox system is an X-ray imager, not an algorithm, and its performance is inherently linked to human interpretation of the images it produces. The study described is a comparison of the device's output (images) to conventional methods, which are then evaluated by human experts.

7. The Type of Ground Truth Used

• The ground truth used was expert consensus (the findings of the two radiologists) which compared the diagnostic quality of images from the Lodox system to images from conventional film radiography. Since the predicate is film radiography, the "ground truth" to which Lodox images were compared was essentially "diagnostically acceptable images from conventional film radiography" as assessed by experts.

8. The Sample Size for the Training Set

• The document does not provide information regarding a training set. This is consistent with the nature of the device; it's an imaging capture system, not an AI model that requires a discrete training phase. The "clinical testing" described serves as the validation of its performance, not a training set for an algorithm.

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

• This question is not applicable as no training set or AI model is described as part of the Lodox Digital Radiography System's development or evaluation in this document.

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