K Number
K133589
Device Name
SOMATOM FORCE
Date Cleared
2014-04-17

(146 days)

Product Code
Regulation Number
892.1750
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data. The images delivered by the system can be used by a trained physician as an aid in diagnosis.

Device Description

The SOMATOM Force is a whole body X-ray Computed Tomography System which features two continuously rotating tube-detector systems and functions according to the fan beam principle. The SOMATOM Force produces CT images in DICOM format, which can be used by postprocessing applications commercially distributed by Siemens and other vendors.

The system software is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.

The computer system delivered with the CT scanner is able to run the post processing applications optionally.

AI/ML Overview

The Siemens SOMATOM Force is a whole-body X-ray Computed Tomography System.

1. Acceptance Criteria and Device Performance:

The provided document does not contain a specific table of acceptance criteria with corresponding device performance metrics for diagnostic accuracy or clinical effectiveness. Instead, the submission focuses on demonstrating safety, technical equivalence, and compliance with recognized standards.

The acceptance criteria for the SOMATOM Force appear to be primarily based on conformance to established safety and performance standards and substantial equivalence to a legally marketed predicate device (SOMATOM Definition Flash). The performance is assessed through nonclinical testing (integration and functional), phantom testing, and verification/validation testing.

Acceptance Criteria CategorySpecific Criteria (Implied)Reported Device Performance (Summary)
SafetyAdherence to IEC and other recognized safety standards (e.g., electrical, mechanical, radiation hazards).Fulfilled requirements of listed safety standards (e.g., IEC 60601 series, ISO 14971 for risk management). Risk analysis completed and controls implemented. EMC/electrical safety evaluated.
Performance/FunctionalityGeneration and processing of cross-sectional images; computer reconstruction of X-ray transmission data. Image quality.Nonclinical tests (integration and functional) and phantom testing conducted. IBHC feature designed to improve image quality.
Substantial EquivalenceComparable indications for use, design, material, functionality, technology, and energy source to the predicate device.Considered substantially equivalent to SOMATOM Definition Flash (K121072). Intended use, materials, energy source, and fundamental scientific technology are similar.
Software IntegrityConformance with special controls for medical devices containing software; all software specifications meet acceptance criteria.Performance data submitted for special controls. Software verification and validation found acceptable. Software documentation for a moderate level of concern included.
Risk ManagementIdentification and mitigation of potential hazards.Risk analysis completed, and risk controls implemented. Testing results support mitigation of identified hazards.

2. Sample Size for Test Set and Data Provenance:

The document does not specify a "test set" in the context of clinical images or patient data for validating diagnostic performance. The testing described is primarily technical and phantom-based.

  • Sample Size for Test Set: Not applicable in the context of diagnostic accuracy assessment with patient data in this submission. The tests mentioned are "nonclinical tests (integration and functional) and phantom testing."
  • Data Provenance: Not applicable in the context of patient data. The nonclinical tests would have been performed by Siemens as part of product development.

3. Number of Experts for Ground Truth and Qualifications:

Not applicable. This submission focuses on the technical safety and performance of the CT scanner itself, not on the diagnostic performance of a software algorithm requiring expert ground truth for interpretation of patient images.

4. Adjudication Method:

Not applicable, as no external expert independent review of diagnostic performance with patient images is described.

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

No MRMC comparative effectiveness study is mentioned in the provided document. The submission focuses on the technical capabilities and safety of the CT scanner, not on comparing diagnostic accuracy with or without AI assistance.

6. Standalone (Algorithm Only) Performance:

Not applicable. The SOMATOM Force is a physical CT scanner, not a standalone algorithm. The "Iterative Beam Hardening Correction (IBHC)" is a feature within the system to improve image quality, not a separate diagnostic algorithm.

7. Type of Ground Truth Used:

For the evaluation described:

  • Technical Performance: Likely based on physical phantom measurements, engineering specifications, and established scientific principles for image quality metrics (e.g., resolution, noise, contrast).
  • Safety Compliance: Based on compliance with international and national safety standards (e.g., IEC standards for electrical safety, radiation protection, and medical device software).
  • Substantial Equivalence: Based on comparison of technical characteristics and intended use with a legally marketed predicate device.

8. Sample Size for the Training Set:

Not applicable. The SOMATOM Force is a hardware system with integrated software for image acquisition and reconstruction. It is not an AI/ML-based diagnostic algorithm that undergoes a distinct "training phase" on a dataset in the manner described for typical AI submissions. The IBHC feature is a predefined algorithm rather than a continuously learning system.

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

Not applicable, as there isn't a "training set" in the context of a machine learning model for diagnostic interpretation. The algorithms (like IBHC) are developed based on physics principles and engineering.

§ 892.1750 Computed tomography x-ray system.

(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.