Infusion Planning Simulation for Medical Liquid Distribution

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Current methods for planning medical liquid infusions lack precision in determining the amount of medical liquid delivered to target versus non-target regions, affecting the efficacy and efficiency of the infusion process.

Innovation Solution

A computer program that uses planning scan data to determine the optimal position and parameters for an infusion device, incorporating medical imaging and simulation techniques to predict the distribution of the medical liquid within the body, ensuring maximum delivery to the target tissue while minimizing delivery to non-target tissue.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional infusion planning methods are used, then the infusion process is simple and quick to plan, but the precision in determining the amount of medical liquid delivered to target versus non-target regions is insufficient

Engineering Contradiction:
Improveprecision in determining medical liquid distributionVSAvoidcomplexity of infusion planning system
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary simulation of medical liquid distribution before the actual infusion procedure. Planning scan data is acquired and processed in advance to create a virtual model that predicts liquid distribution patterns, allowing optimization of infusion parameters before clinical application.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system creates a virtual copy or simulation model of the patient's anatomy using planning scan data. This digital twin allows for testing and optimization of infusion parameters without affecting the actual patient, enabling precise prediction of medical liquid distribution patterns.

Inventive Principle:
Principle #26Copying

2Reliability

If infusion parameters are optimized for maximum target tissue delivery, then treatment efficacy is improved, but the amount of medical liquid introduced into non-target regions may increase

Engineering Contradiction:
Improvetreatment efficacyVSAvoidmedical liquid delivery to non-target tissue
Core Design Contradiction:
ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system determines different infusion parameters for different spatial regions. By analyzing the virtual model, it identifies optimal flow rates, pressures, and durations that maximize delivery to target tissue while minimizing infiltration into non-target regions, applying localized quality control to different anatomical areas.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The simulation provides feedback on predicted medical liquid distribution patterns before actual infusion. This allows adjustment of infusion parameters based on predicted outcomes, optimizing the balance between target tissue delivery and non-target tissue protection.

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP2681679B1Computer-assisted infusion planning and simulation
Publication Date: 2017.07.26 BRAINLAB AG
  • EP2681679B1 patent drawingFigure 1a~1b
  • EP2681679B1 patent drawingFigure 2
  • EP2681679B1 patent drawingFigure 3~4

AI summary

A method for planning an infusion of a medical liquid by an infusion apparatus comprising an infusion device, wherein the method comprises the steps of: acquiring planning scan data which represent a medical image of at least a body region (3) of a patient and are obtained by a planning scan before the infusion device is positioned; determining a planned device position from the planning scan data; acquiring verification scan data which represent a medical image of the region of the patient after the infusion device has been positioned; determining a source volume of the liquid from the verification scan data; and determining infusion parameters from the verification scan data and the source volume.