[Research on Reliability Index and Realization of Magnetic Resonance (MR) Based on Clinical Use Condition]

Area of Science:

• Biomedical Engineering
• Medical Imaging Technology
• Reliability Engineering

Background:

• Magnetic Resonance (MR) components require classification for effective reliability analysis.
• Clinical usage conditions in hospitals like Shanghai Sixth People's Hospital inform component categorization.
• Understanding loss forces is crucial for differentiating MR component types.

Purpose of the Study:

• To categorize MR components based on clinical application and primary loss forces.
• To develop a comprehensive framework for MR system reliability indexes and implementation.
• To provide methods for reliability prediction and verification, including MTBF calculation.

Main Methods:

• Classification of MR components into scanning type I, scanning type II, dynamic, and electric thermal types.
• Development of system reliability index determination, allocation, and realization methods.
• Application of reliability prediction and verification techniques, including MTBF calculation from clinical data.

Main Results:

• A structured categorization of MR components is presented.
• A complete set of MR system reliability indexes and their implementation methods are defined.
• Methods for reliability prediction, verification, and MTBF calculation using clinical data are established.

Conclusions:

• The proposed reliability framework enhances the understanding and management of MR systems.
• The classification and methods support improved MR system design and maintenance.
• Clinical data-driven MTBF calculation offers a practical approach to assessing MR system reliability.