Lung metastasis prediction method for patients with limb soft tissue sarcoma

A soft tissue sarcoma, metastasis prediction technology, applied in image data processing, instrument, character and pattern recognition, etc., can solve the problem of tumor heterogeneity and other problems

Active Publication Date: 2019-08-02
SHANGHAI MARITIME UNIVERSITY
View PDF6 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, it is difficult to study ...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Lung metastasis prediction method for patients with limb soft tissue sarcoma

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The present invention will be further elaborated below by describing a preferred specific embodiment in detail in conjunction with the accompanying drawings.

[0032] Such as figure 1 As shown, a lung metastasis prediction method for patients with extremity soft tissue sarcoma, including:

[0033] Step 1: Collect the clinical data and PET image data of patients with soft tissue sarcoma of the extremities, where the PET image data is in DICOM format, including the data of 51 subjects, of which

[0034] Step 2: Fusion the collected image data with the pre-marked tumor area to obtain the region of interest (ROI), and calculate the standard uptake value (SUV value) at the same time, and merge and organize the clinical data;

[0035] In a specific embodiment, this step 2 includes:

[0036] Step 2.1, extract tumor area data from the collected data, the specific method is as follows, for each subject, use the tumor area outlined by a professional doctor to locate the tumor v...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a lung metastasis prediction method for patients with limb soft tissue sarcoma, and the method comprises the steps: S1, carrying out the feature extraction of all to-be-testedobjects through employing a standard shooting value of a PET image, wherein the features comprises an SUV feature and a texture feature; s2, carrying out feature extraction on all tested clinical information by using a one-hot encoding method; and S3, performing feature contribution degree sorting on all the features by using a random forest algorithm, fusing the high contribution degree features,and constructing a lung metastasis prediction model of the patient with the limb soft tissue sarcoma by using a BP neural network. The lung metastasis prediction method can predict the lung metastasis condition of patients with limb soft tissue sarcoma more accurately by using fewer patient characteristics.

Description

technical field [0001] The invention relates to a lung metastasis prediction system and method for patients with soft tissue sarcoma of extremities, specifically a system and method for predicting lung metastasis of patients with soft tissue sarcoma of extremities by fusing PET images and clinical features. Background technique [0002] Sarcomas are a group of highly heterogeneous tumors classified according to similar adult tissue types in histogenesis. It is characterized by invasive or destructive growth that can recur and spread distantly. As one of the sarcomas, soft tissue sarcomas (STSs) can occur anywhere in the body, and 59% of them originate from the limbs. Unfortunately, 10%-20% of patients with sarcoma or STS have distant metastases at diagnosis. During follow-up, the metastasis rate was about 30%-40%, of which lung metastasis accounted for about 90%. In addition, knowledge of the prognostic factors for resection of lung metastases is largely inadequate, with ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T7/00G06K9/62G06K9/32G06K9/46
CPCG06T7/0012G06T2207/10104G06T2207/30096G06V10/25G06V10/40G06F18/24323
Inventor 邓金曾卫明石玉虎李颖鲁佳
Owner SHANGHAI MARITIME UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products