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Multitom Rax is a device intended to visualize anatomical structures by converting an X-ray pattern into a visible image. The system has medical applications ranging from gastrointestinations to cranial, skeletal, thoracic and lung exposures as well as examinations of the urogenital tract. The unit may also be used in emergency applications, lymphography, endoscopy, myelography, arthrography, interventional radiology, digital angiography, and digital subtraction angiography (DSA). The system may be used on pediatric patients. The Multitom Rax is not for mammography examinations.

The True2scale Body Scan functionality (ie., slot-scanning-based acquisition and reconstruction technique) of the Multitom Rax is intended to be used for the generation of a geometrically accurate (in scanning direction) 2-D representation of the spine, the lower limbs or the full body which may be used for the assessment of body axes and skeletal alignment. The True2scale Body Scan feature is not intended to be used for interventional purposes.

The Multitom Rax is a stationary X-ray system for radiography and fluoroscopy. The Multitom Rax consists of a floor mounted patient table (option) and ceiling suspended Xray tube and a ceiling suspended Solid State X-ray Imager (SSXI). Together with an X-ray generator and a digital imaging system, the Multitom Rax provides comprehensive image acquisition modes to support radiographic and fluoroscopic imaging procedures. X-ray tube and SSXI suspension movements are synchronized to provide rotation around a center. Series imaging acquired during the rotation are provided to 3D post-processing workstations.

With the new True2scale Body Scan technology, the Multitom Rax performs a continuous scan that moves along the patient's vertical axis with a highly collimated radiation beam along a line trajectory using the system's two telescopic arms. The projections, which are acquired during the scanning process, form the basis for a reconstruction to obtain a 2D representation of the scanned object.

The provided text describes the acceptance criteria and a study to prove the device, Multitom Rax with True2scale Body Scan Option, meets those criteria. However, it does not contain a typical "acceptance criteria table" with numerical metrics and their corresponding performance. Instead, it focuses on the equivalence to a predicate device and clinical image quality.

Here's an attempt to extract and synthesize the information based on the provided text:

Acceptance Criteria and Device Performance

Study Details:

1. A table of acceptance criteria and the reported device performance: See table above. The document emphasizes the new True2scale Body Scan technology's ability to provide "geometrically accurate (in scanning direction) 2-D representation of the spine, the lower limbs or the full body which may be used for the assessment of body axes and skeletal alignment." The primary "acceptance criteria" for the clinical evaluation, therefore, was the subjective assessment of image quality for enabling this assessment.

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

   • Sample Size: Ten (10) anonymized clinical image sets.
   • Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective. It only states "anonymized clinical image sets."

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

   • Number of Experts: Not explicitly stated, but referred to as "expert, board-certified radiologists" (plural).
   • Qualifications: "expert, board-certified radiologists." No detail on years of experience is provided.

4. Adjudication method for the test set: Not explicitly detailed. The statement "all image sets were found to be of acceptable clinical image quality" suggests a consensus or majority opinion, but the specific adjudication method (e.g., 2+1, 3+1) is not provided.

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 performed as described. The clinical evaluation was focused on the image quality of the new technology itself, without comparing human readers with and without AI assistance. The True2scale Body Scan is described as a "slot-scanning-based acquisition and reconstruction technique" for generating images, not an AI-assisted diagnostic tool for interpretation.

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

   • The study was effectively a standalone performance assessment of the image generation capability of the True2scale Body Scan technology. The focus was on the machine's output (image quality) rather than a diagnostic algorithm's performance. The "human experts" were evaluating the output of the device itself.

7. The type of ground truth used:

   • Expert Consensus/Subjective Assessment: The ground truth for the clinical image evaluation was established through the subjective assessment of "expert, board-certified radiologists" who determined if the images were of "acceptable clinical image quality" for vertebral alignment detection and evaluation. It's not based on pathology or outcomes data.

8. The sample size for the training set:

   • The document does not mention a training set or machine learning model training in the context of the True2scale Body Scan clinical evaluation. The "software VF11 design was completed in accordance with Siemens Quality Management System Design Controls and verification and validation testing were successfully conducted" but it does not specify if this included a machine learning component requiring a training set. The True2scale Body Scan is described as an "acquisition and reconstruction technique," suggesting image processing rather than AI-driven interpretation.

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

   • Not applicable, as no training set for a machine learning model is mentioned in the context of this premarket submission.

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The DigiX FDX radiographic systems are used in hospitals, clinics and medical practices. DigiX FDX enables radiographic exposure of the whole body including: Skull, chest, abdomen, and extremities and may be used on pediatric, adult and bariatic patients. It can also be used for intravenous, small interventions (like biopsy, punctures, etc.) and emergency (trauma critical ill) applications. Exposure may be taken with the Patient's sitting, standing, or in the prone/ supine position.

The DigiX FDX System is not meant for mammography.

The DigiX FDX uses an integrated or portable or fixed or wi-fi digital detector for generating diagnostic images by converting X-Ray into electronics signals. DigiX FDX is also designed to be used with conventional film/screen or Computed Radiography (CR) Cassettes.

The DigiX FDX system is a diagnostic X-Ray system intended for general purpose radiographic imaging of the human body. It is not intended for mammographic imaqing.

The DigiX FDX system is comprised of a combination of devices that include a ceiling mounted X-Ray tube suspension, vertical Bucky stand, fixed or mobile patient Bucky table, X-Ray generator, X-Ray tube, beam limiting device, and a solid-state image receptor.

The DigiX FDX systems are not intended to be operated with any other cleared devices, or to be integrated with other software/hardware devices via direct or indirect connections.

Here's a breakdown of the acceptance criteria and study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document focuses on demonstrating substantial equivalence to predicate devices rather than defining specific quantitative performance metrics as "acceptance criteria" for a new AI/software feature in the way clinical performance studies usually do. Instead, the "acceptance criteria" are implied to be that the modifications do not negatively impact safety or effectiveness, and that the device performs comparably to the predicate devices and meets relevant safety standards.

For the new features explicitly mentioned (Automatic Stitching and Dual Energy Subtraction), the document states they add functionality without affecting patient safety or effectiveness. For the other components, the criteria are often "Same" or "Similar functionality with same imaging results" or "doesn't affect the safety or effectiveness."

To represent this in a table, we'll extract performance comparisons from the "Functional and Specification Differences" table (Table 4) and the "Justification for Differences" (Table 5).

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

The document states:

• "Non-clinical testing included verification and validation testing, image evaluation, testing, and safety testing."
• "Performance testing included functional testing of all motions of the system(s) with respect to the design specifications. Image performance testing was conducted and results included in the submission."
• "Clinical testing is not applicable due to the fact that no new clinical applications were introduced to the system."

The document does NOT specify a sample size for any test set (clinical or otherwise) in terms of patient data or images used for validation of the radiographic system itself, nor does it mention data provenance (country of origin, retrospective/prospective). It primarily relies on hardware and software equivalence, and compliance with industry standards.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. The document explicitly states "Clinical testing is not applicable." Therefore, there was no clinical study conducted that would necessitate expert readers to establish ground truth for a test set. The evaluation focuses on technical performance and equivalence to predicate devices.

4. Adjudication Method for the Test Set

Not applicable. As no clinical test set requiring expert adjudication was performed, no adjudication method is mentioned.

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

No MRMC comparative effectiveness study was done. The document states "Clinical testing is not applicable due to the fact that no new clinical applications were introduced to the system." Therefore, there is no information on how much human readers improve with or without AI assistance. The new software features (Automatic Stitching, Dual Energy Subtraction) are presented as additional functionalities that don't affect safety or effectiveness, not as AI-assisted diagnostic tools requiring a comparative effectiveness study.

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

Not applicable. The device is a radiographic system, not an AI algorithm intended for standalone diagnostic performance. While it includes new software features (Automatic Stitching, Dual Energy Subtraction), these are integrated functionalities of the imaging system and not described as standalone diagnostic algorithms requiring independent performance evaluation without human interaction.

7. Type of Ground Truth Used

The "ground truth" for the evaluation is primarily based on:

• Compliance with technical specifications and design requirements: Functional testing, image performance testing.
• Adherence to safety and performance standards: IEC 60601 series, EN ISO 14971, IEC 62366-1, IEC 62304, 21 CFR 1020.30, 21 CFR 1020.31.
• Substantial equivalence to predicate devices: Demonstration that the new device has the same intended use, fundamental technological characteristics, and that any differences do not raise new questions of safety or effectiveness.
• Software documentation assessment: For the software components, including the new features, documentation was provided for a "Moderate Level of Concern" software as per FDA guidance.

No clinical ground truth (e.g., expert consensus, pathology, outcomes data) was used or required given the nature of this submission.

8. Sample Size for the Training Set

Not applicable. The document describes an X-ray imaging system, not an AI/ML device that requires a training set of data. The new software features (Automatic Stitching, Dual Energy Subtraction) are described as functionalities, not adaptive algorithms that learn from data.

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

Not applicable. As there was no training set, there was no ground truth to establish for it.

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