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Multix Fusion Max system is a radiographic system used in hospitals, clinics, and medical practices. Multix Fusion Max enables radiographic exposures of the whole body including: skull, chest, abdomen, and extremities and may be used on pediatric, adult and bariatric patients. Exposures may be taken with the patient sitting, standing, or in the prone position. The Multix Fusion Max system is not meant for mammography.

Multix Fusion Max uses a mobile (wired), or a fixed (integrated) or wireless digital detector for generating diagnostic images by converting x-rays into image signals. The Multix Fusion Max is also designed to be used with conventional film/screen or Computed Radiography (CR) cassettes.

The Multix Fusion Max Radiography X-ray system is a modular system of x-ray components (ceiling suspension with x-ray tube, bucky wall stand, bucky table, x-ray generator, portable wireless and integrated detectors) which is the same as the predicate device, the Multix Fusion Max (K162971). The portable wireless and integrated detectors used with Multix Fusion Max are imported from the cleared predicate device, Multix Fusion Max (K162971). There are no new imaging detectors added to the subject x-ray system. The Multix Fusion Max software is being used unchanged from the reference device, Ysio Max (K181279). This 510(k) submission describes modifications to the predicate device, the Multix Fusion Max, cleared via K162971.

The purpose of this submission is for the following modifications to Multix Fusion Max:

• Updated operating system from Windows 7 to Windows 10 and software version upgrade from VE21 to VF10
• New cybersecurity features
• Additional pediatric exposure technique factors
• A new 80-line grid with a 15:1 ratio
• The image processing algorithms (DiamondView MAX) will be used for exposures without grid
• The Multix Fusion Max with VF10 has been tested according to the currently recognized voluntary standards.

The provided document is a 510(k) summary for the Multix Fusion Max X-ray system. It describes modifications to an existing device (Multix Fusion Max, K162971) and claims substantial equivalence to that predicate device. The changes include an updated operating system (Windows 7 to Windows 10), software version upgrade, new cybersecurity features, additional pediatric exposure technique factors, and a new 80-line grid.

Crucially, this document does not contain information about a study that proves the device meets specific performance acceptance criteria for diagnostic accuracy, sensitivity, or specificity, especially not in the context of an AI-assisted diagnostic device or a multi-reader, multi-case study. The performance testing mentioned is primarily "non-clinical performance testing" for device functionality, safety (electrical, mechanical, radiation), and software verification/validation, rather than clinical performance for diagnostic effectiveness. The document states:

• "Non-clinical tests were conducted for the Multix Fusion Max during product development. The modifications described in this Premarket Notification are supported with verification and validation testing."
• "The testing results indicate that all the software specifications have met the acceptance criteria. Verification and validation testing was found acceptable to support the claim of substantial equivalence."
• "The non-clinical test data demonstrate that the Multix Fusion Max device performance is comparable to the predicate device that is currently marketed for the same intended use."

The entire premise of the 510(k) submission for this device is to demonstrate substantial equivalence to a previously cleared device, not to prove new or improved clinical effectiveness through a diagnostic performance study. The device is a radiographic system for generating images, not an AI or CAD system that provides diagnostic interpretations or assists human readers in making diagnoses.

Therefore, many of the requested details about acceptance criteria for diagnostic performance, sample size for test sets (in a clinical sense), ground truth establishment, expert readers, MRMC studies, or standalone AI performance do not apply to the information presented in this 510(k) summary.

However, I can extract information related to what was studied to support the 510(k) clearance based on substantial equivalence.

Here's the closest answer based on the provided text, highlighting what is (and isn't) present:

Acceptance Criteria and Study for Multix Fusion Max (K191418)

The provided 510(k) summary for the Multix Fusion Max (K191418) focuses on demonstrating substantial equivalence to a predicate device (Multix Fusion Max, K162971) following modifications primarily related to software (operating system upgrade, cybersecurity), and minor hardware changes (new grid, expanded pediatric technique factors). The "study" described is a series of non-clinical verification and validation tests rather than a clinical diagnostic performance study. As such, many of the requested criteria related to AI or diagnostic accuracy studies are not applicable to the content of this document.

1. Table of Acceptance Criteria and Reported Device Performance

General acceptance criteria are related to safety, functionality, and compliance with standards. The document does not provide specific quantitative acceptance criteria for diagnostic performance (e.g., sensitivity, specificity) for a clinical study of images, as this was not a submission for an AI/CAD device.

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

• Sample Size: Not applicable in the context of a clinical test set of patient images for diagnostic accuracy. The testing performed was non-clinical verification and validation of system functionality and safety.
• Data Provenance: Not applicable for a clinical test set. The document refers to its manufacturing sites in Shanghai, China, and Forchheim, Germany, and the applicant is Siemens Medical Solutions USA, Inc. The testing described is intrinsic to the device's engineering and software.

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

• This is not applicable as the submission describes non-clinical engineering and software validation, not a diagnostic performance study where human experts establish ground truth for image interpretation.

4. Adjudication Method for the Test Set

• Not applicable for the type of non-clinical testing described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, an MRMC study was not done or described in this 510(k) summary. This device is a basic X-ray system, not an AI or CAD system designed to assist human readers in diagnosis.

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

• Not applicable. This device is an X-ray imaging system, not an AI algorithm intended for standalone diagnostic interpretation.

7. The Type of Ground Truth Used

• Not applicable in the context of diagnostic image interpretation. For functional testing, "ground truth" would be established through engineering specifications, direct measurement, and known physical principles.

8. The Sample Size for the Training Set

• Not applicable. This document describes a conventional X-ray system, not a machine learning or AI algorithm that requires a training set of data.

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

• Not applicable, as no training set for an AI/ML algorithm is described.

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Multix Fusion Max system is a radiographic system used in hospitals, clinics, and medical practices. Multix Fusion Max enables radiographic exposures of the whole body including: skull, chest, abdomen, and extremities and may be used on pediatic, adult and bariatic patients. Exposures may be taken with the patient sitting, standing, or in the prone position. The Multix Fusion Max system is not meant for mammography.

Multix Fusion Max uses a mobile(wired), or a fixed (integrated) or wireless digital detector for generating diagnostic images by converting x-rays into image signals. The Multix Fusion Max is also designed to be used with conventional film/screen or Computed Radiography (CR) cassettes.

The Multix Fusion Max Radiography X-ray system is a modular system of x-ray components (ceiling suspension with X-ray tube, Bucky wall stand, Bucky table, X-ray generator, portable wireless and integrated detectors) same as the predicate the Multix Fusion. This 510(k) submission describes modifications to the predicate device the Multix Fusion cleared via K142049.

The provided text is a 510(k) summary for the Siemens Multix Fusion Max X-ray system. This document is a premarket notification to the FDA to demonstrate that the new device is substantially equivalent to a legally marketed predicate device. As such, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" refer to demonstrating substantial equivalence, not typically a clinical performance study with specific metrics like sensitivity or specificity for an AI-powered diagnostic device.

This document describes the device as a radiographic system with various hardware and software modifications compared to its predicate. The "acceptance criteria" here are primarily about demonstrating that the new modifications do not introduce new safety concerns and that the device performs functionally similarly to its predicates.

Here's an analysis of the provided information, framed within your request, but acknowledging the nature of a 510(k) for a general radiography system rather than an AI diagnostic algorithm:

1. Table of Acceptance Criteria (as implied by a 510(k) for an X-ray system) and Reported Device Performance

For an X-ray system like the Multix Fusion Max, "acceptance criteria" are defined by its substantial equivalence to predicate devices, focusing on technical specifications, safety, and operational performance. The "performance" is the demonstration that these are met or that differences are not significant and do not raise new safety/effectiveness questions.

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

This is an X-ray system submission, not a study of an AI-powered diagnostic device. Therefore, there isn't a "test set" in the sense of a dataset of patient images for an AI algorithm. The testing described is primarily non-clinical, focusing on system function, image quality a phantom/test environment, and safety standards compliance.

• Sample Size: Not applicable in the context of clinical "test set" for an AI algorithm. Non-clinical tests were conducted at the product development stage, but specific "sample sizes" of components or tests are not detailed.
• Data Provenance: Not applicable. The "data" are internal testing results, not patient data from a specific country or collected retrospectively/prospectively.

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

Not applicable. There is no mention of expert readers or ground truth establishment in this type of 510(k) submission for a general X-ray system. The performance demonstration is based on technical specifications and engineering tests.

4. Adjudication Method for the Test Set

Not applicable.

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

Not applicable. This is not an AI-powered diagnostic device, and no MRMC study is mentioned or required for this type of submission.

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

Not applicable. This is an X-ray imaging system, not an AI algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

Not applicable in the context of clinical ground truth. The "ground truth" for this device's performance demonstration relies on engineering specifications, adherence to international standards (e.g., IEC, ISO), and performance metrics like DQE and MTF measured in a controlled environment, not clinical outcomes or expert labels.

8. The Sample Size for the Training Set

Not applicable. This is an X-ray system, not an AI algorithm requiring a "training set."

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

Not applicable.

In summary, the provided document
describes a 510(k) premarket notification for a conventional X-ray system, not an AI-powered diagnostic device. Therefore, the questions related to AI algorithm development, clinical datasets, expert ground truth, and reader studies are not addressed and are not applicable to this type of device submission. The acceptance criteria are based on demonstrating substantial equivalence to predicate devices through non-clinical performance testing and compliance with recognized standards.

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