MRI Protocol Sequencing to Reduce Hardware Strain and Patient Discomfort
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Solution Overview
Problem
Magnetic resonance imaging (MRI) systems face hardware strain and patient interaction issues due to sequences with large-gradient waveforms and B1+ magnetic fields, leading to scanner failures and patient discomfort, with existing automatic protocols failing to adequately address these challenges.
Innovation Solution
An automatic protocolling system that intelligently orders MRI sequences to reduce hardware and patient interactions by spacing out high-interacting sequences with low-interacting ones, using artificial intelligence to select pulse sequence parameters and dynamically reorder protocols to minimize noise, heat, and acoustic energy, thereby reducing scan time and improving patient experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple sequences with large-gradient waveforms are run repeatedly, then imaging productivity is improved, but hardware reliability deteriorates due to gradient cooling system strain and magnet interactions
Solution Approach 1:
The system implements periodic cooling intervals between high-gradient sequences, inserting low-gradient sequences to allow gradient cooling system recovery. This periodic action prevents continuous strain on the gradient cooling system while maintaining imaging productivity through efficient sequence scheduling.
Solution Approach 2:
The system performs preliminary assessment of sequence hardware interactions and pre-calculates optimal sequencing that distributes high-gradient sequences with adequate spacing. This preliminary planning prevents hardware overload before it occurs, ensuring both productivity and reliability.
2Speed
If sequences with large B1+ magnetic fields are used, then imaging speed is improved, but patient safety deteriorates due to transmit-coil heating and implant heating
Solution Approach 1:
The system alternates between high B1+ sequences and low B1+ sequences, providing periodic intervals that allow transmit-coil cooling and reduce cumulative heating. This maintains imaging speed while preventing excessive temperature rise in the coil and patient tissues.
Solution Approach 2:
The system dynamically adjusts B1+ field parameters by selecting sequences with varying B1+ levels based on real-time thermal conditions and patient safety constraints. This parameter variation optimizes the balance between imaging speed and patient safety.
3Productivity
If high-acoustic-energy sequences are run continuously, then imaging productivity is improved, but patient comfort deteriorates due to excessive noise exposure
Solution Approach 1:
The system schedules high-acoustic-energy sequences periodically with intervals of low-acoustic-energy sequences, allowing patient auditory system recovery. This maintains productivity while reducing cumulative noise exposure and improving patient comfort.
4Reliability
If sequences are spaced out to reduce hardware interactions, then hardware reliability is improved, but scan time increases
Solution Approach 1:
The system pre-calculates optimal sequence spacing that achieves minimum cooling intervals while maximizing imaging productivity. This preliminary optimization ensures adequate hardware cooling without unnecessary scan time extension.
Solution Approach 2:
The system dynamically adjusts sequence timing parameters and spacing based on real-time hardware temperature feedback, optimizing the balance between reliability and scan time efficiency.
Data Source
AI summary
An automatic protocolling system and methods involving a processor operable by way of a set of executable instructions storable in relation to a nontransient memory device, the set of executable instructions configuring the processor to: receive information relating to an initial protocol comprising an initial ordering of a plurality of sequences, the information comprising data relating to an interaction extent value of at least one of an imaging system and a patient as a function of time corresponding to each sequence in the plurality of sequences, the data relating to a time-integrated effect of each sequence in the plurality of sequences; and dynamically determine an alternative protocol comprising an alternative ordering of the plurality of sequences based on the time-integrated effect, whereby an alternative protocol is provided.