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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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The MULTIX Impact system is a radiographic system used in hospitals, clinics, and medical practices. MULTIX Impact 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 Impact system is not meant for mammography.

The MULTIX Impact uses digital detectors for generating diagnostic images by converting x-rays into image signals. The MULTIX Impact is also designed to be used with conventional film/screen or Computed Radiography (CR) cassettes.

The MULTIX Impact Radiography X-ray system is a modular system of X-ray components (floor-mounted X-ray tube, Bucky wall stand, Bucky table, X-ray generator, portable wireless detectors) similar to the predicate the Multix Fusion Max. This 510(k) submission describes modifications to the predicate device the Multix Fusion Max cleared via K162971. The following modifications have been made to the cleared predicate device and the new system will be branded the MULTIX Impact:

1. A new 43x35cm Wireless detector, 3543DR 1.
2. A new X-ray tube and a new generator
3. An optional 40 line grid with grid suppression algorithm
4. Wireless Remote Control Console
5. An optional All-in-one PC containing touch screen function
6. An optional positioning assistance camera
7. Upgrade software to VA10
8. Upgrade operator system from Windows XP to Windows 10

The Siemens MULTIX Impact X-ray system is a modification of the predicate device, the Multix Fusion Max (K162971). The submission focuses on demonstrating substantial equivalence rather than presenting an effectiveness study for a new clinical claim. Therefore, the information provided primarily concerns performance testing to confirm that the modifications do not negatively impact safety or effectiveness.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a submission demonstrating substantial equivalence to a predicate device for an X-ray system, the acceptance criteria are generally focused on demonstrating that various component modifications do not degrade performance below the predicate's established levels, and that the device meets relevant safety and performance standards. Formal "acceptance criteria" for a specific clinical task are not explicitly stated for the device as a whole in the way they would be for a diagnostic AI algorithm. Instead, the comparison is to the predicate and established standards.

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

The document describes modifications to an existing X-ray system and its components. The "test set" here refers to the actual physical device and its components undergoing verification and validation testing, rather than a dataset of medical images for a diagnostic algorithm.

• Sample Size for Test Set: Not applicable in the context of a dataset of cases. The testing was performed on the MULTIX Impact system itself and its components.
• Data Provenance: Not applicable in the clinical data sense. The testing is described as "Non-clinical tests... during product development" and "testing for verification and validation." This implies internal testing by the manufacturer.

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

Not applicable. This is not a study requiring expert clinical read-outs for ground truth. The "ground truth" for this submission is adherence to technical specifications, performance standards (like DQE, MTF), and safety requirements, which are evaluated by engineering and quality control processes.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of clinical image adjudication for ground truth establishment. Technical performance and safety are verified through engineering tests.

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 MRMC study was performed or is mentioned. This submission is for an X-ray system, not an AI-powered diagnostic device, and it focuses on demonstrating substantial equivalence of modified hardware and software components, not on comparative effectiveness with human readers.

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

Not applicable. The device is an X-ray system, which is inherently used with human operators. There is no "algorithm only" performance claim. The software modifications are part of the overall X-ray system's functionality.

7. The Type of Ground Truth Used

The "ground truth" for this submission relates to:

• Technical Specifications: Ensuring components meet their specified performance parameters (e.g., DQE, MTF for the detector, power output for the generator).
• Compliance with Standards: Verification that the device adheres to recognized national and international standards (IEC, ISO, NEMA).
• Safety and Effectiveness: Demonstration that modifications do not introduce new safety risks or degrade the overall effectiveness of the predicate device, as evaluated through risk analysis and functional testing.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/machine learning device that requires a training set of data.

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

Not applicable, as there is no training set for an AI algorithm.

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