Automated Tumor Trend Assessment System for Pseudo-Progression Detection
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Solution Overview
Problem
Current methods for assessing benign tumor development trends, particularly after radiation treatment, are inefficient and cause psychological stress due to subjective annotations, time-consuming processes, and inability to differentiate between actual tumor progression and pseudo-progression, leading to inadequate treatment advice for patients.
Innovation Solution
A benign tumor development trend assessment system using a server computing device with modules for image pre-processing, target extraction, feature extraction, and trend analysis, which automatically analyzes tumor images before and after radiation treatment to predict or determine tumor response and potential pseudo-progression, providing personalized treatment advice.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tumor contouring is performed by experienced surgeons reviewing tumor images, then treatment area and dose delivery can be determined, but the process is time consuming and subjective annotations are inevitable
Solution Approach 1:
The system performs preliminary automatic tumor contouring and feature extraction from medical images before radiation treatment planning, generating initial treatment area definitions and dose delivery parameters that can be reviewed and adjusted by surgeons, thereby reducing the time surgeons need to spend on manual contouring while maintaining accuracy
Solution Approach 2:
The system creates digital copies of tumor regions through automated image analysis and generates virtual treatment plans that can be replicated and reviewed, eliminating the need for surgeons to manually recreate contours from scratch and reducing subjective variability in annotations
2Reliability
If radiation treatment is administered without automated assessment, then treatment can proceed, but patients experience psychological stress and treatment efficacy is reduced due to inability to differentiate pseudo-progression from actual progression
Solution Approach 1:
The system implements automated feedback mechanisms that continuously monitor tumor response to radiation treatment by analyzing serial medical images, comparing actual progression against predicted progression patterns, and providing real-time assessments that differentiate pseudo-progression from true progression, enabling timely treatment adjustments and reducing patient anxiety through objective monitoring
Solution Approach 2:
The system performs preliminary assessment of tumor characteristics and predicts individual patient responses to radiation treatment before treatment begins, identifying patients at risk for pseudo-progression in advance, allowing for personalized treatment planning that improves efficacy and reduces psychological stress by setting realistic expectations
Data Source
AI summary
A benign tumor development trend assessment system includes an image outputting device and a server computing device. The image outputting device outputs first/second images captured from the same position in a benign tumor. The server computing device includes an image receiving module, an image pre-processing module, a target extracting module, a feature extracting module and a trend analyzing module. The image receiving module receives the first/second images. The image pre-processing module pre-processes the first/second images to obtain first/second local images. The target extracting module automatically detects and delineates tumor regions from the first/second local images to obtain first/second region of interest (ROI) images. The feature extracting module automatically identifies the first/second ROI images to obtain at least one first/second features. The trend analyzing module analyzes the first/second features to obtain a tumor development trend result.