Mobile Medical Imaging Configuration for Higher Throughput
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Solution Overview
Problem
Current medical imaging systems are inefficient in throughput, require costly logistical patient transportation, and are not optimally designed for flexible operation, leading to sub-optimal utilization and frequent workflow interruptions.
Innovation Solution
A framework for distributed medical image acquisition using mobile imaging systems that autonomously or semi-autonomously move to patients, cooperate with each other, and assemble to optimally address clinical tasks, allowing for simultaneous assessment and minimizing workflow disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single imaging system is assigned to one imaging suite for imaging one patient at a time, then the system can provide dedicated imaging service, but the throughput cannot be increased beyond the imaging performance of the specific imaging system and utilization is less than 50% per day
Solution Approach 1:
The imaging system is transformed from a static, fixed-location installation to a mobile, dynamically deployable unit. The mobile imaging system can move between different imaging suites and be repositioned as needed, allowing the system to dynamically adapt to varying patient loads and clinical priorities across multiple locations, thereby increasing both throughput and utilization flexibility
Solution Approach 2:
The mobile imaging system is designed to provide universal imaging services across multiple imaging suites rather than being dedicated to a single location. This multi-functional capability allows one imaging system to serve multiple clinical areas, increasing overall system utilization and throughput while maintaining adaptability to different imaging needs
2Productivity
If the patient is transported from the injection room to the imaging suite, then the imaging process can be completed, but costly logistical problems arise as patients must be scheduled and transported from room to room
Solution Approach 1:
Instead of moving the patient from the injection room to a distant imaging suite, the imaging system is brought to the patient's location. This inversion of the traditional workflow eliminates the need for patient transportation and scheduling coordination between multiple rooms, reducing logistical complexity while maintaining imaging productivity
Solution Approach 2:
The mobile imaging system acts as an intermediary that bridges the injection room and imaging suite functions. By positioning the imaging system at the patient's location, it mediates between the injection process and image acquisition, eliminating the need for patient transport while maintaining the complete imaging workflow
3Ease of repair
If the imaging system is shut down for maintenance service, then the system can be serviced, but the service typically occurs in patient space and therefore interrupts the workflow
Solution Approach 1:
The mobile imaging system can be dynamically repositioned to separate maintenance activities from patient care areas. When servicing is needed, the system can be moved to a maintenance area or staged location, allowing technicians to perform repairs without interrupting patient workflows in the clinical areas, thus maintaining both ease of repair and workflow continuity
Solution Approach 2:
The imaging system's mobility creates a separation between the patient care function and the maintenance function. The system can be segmented in space and time - operating in patient areas during clinical hours and being moved to maintenance areas during non-clinical hours, allowing both workflow continuity and ease of repair
Data Source
AI summary
A framework for distributed medical image acquisition. An optimal configuration of one or more mobile imaging systems to address a clinical task is determined. The one or more mobile imaging systems may be dispatched in accordance with the optimal configuration to perform medical image acquisition of a patient to generate medical image data. Image reconstruction may then be performed based on the medical image data.