Utility of Ultrasound Imaging for Diagnosis of Focal Liver Lesions: A Radiomics Analysis

Sponsor
Chinese PLA General Hospital (Other)
Overall Status
Unknown status
CT.gov ID
NCT03871140
Collaborator
(none)
10,000
1
59.9
166.9

Study Details

Study Description

Brief Summary

Ultrasound (US) as first-line imaging technology in detecting focal liver lesions,also plays a crucial role in evaluating image and guiding ablation which is the main treatment for liver lesions. However, the effect of US in diagnosing liver lesions is challenged by several factors including being highly dependent on doctor's experience, low signal-to-noise ratio, low resolution for lesion feature,large error from thermal field evaluation during the process of ablation and so on. Therefore, it is of great significance to construct an intelligent US analysis system depending on the digital information technology. Basing on these problems,the following research will be involved in our project: 1) US database of liver lesions with seamless connection to Picture Archiving and Communication Systems (PACS) will be developed, with the aim to provide standard data for intelligent US analysis. 2) Deep learning model for accurate segmentation, detection and classification of liver lesions on US images will be studied. Then automatic extraction, selection and analysis of liver lesion ultrasound features and the intelligent US diagnosis for liver lesions will be realized. 3) Proposing a clustering model with deep image features, and depicting the similarity measurement of liver cancer, which can be furthered used to link the liver cancer feature to optimal ablation parameters. The intelligent decision-making system for quantifying thermal ablation will be established. 4) Regression algorithm and Generative Adversarial Nets will be developed to extract the image features of liver cancer which will predict risk factors after US-guided thermal ablation.Based on the above researches, it is of great value to establish an intelligent focal liver lesion US diagnosis system involving intelligent diagnosis,personalized ablation strategy and accurate prognosis evaluation, improving the level of accurate diagnosis and treatment of liver lesions.

Condition or Disease Intervention/Treatment Phase
  • Other: diagnosis

Study Design

Study Type:
Observational
Anticipated Enrollment :
10000 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Intelligent Diagnosis of Focal Liver Lesions and Thermal Ablation Zone of Liver Cancer Based on Ultrasound Imaging
Actual Study Start Date :
Jan 1, 2017
Anticipated Primary Completion Date :
Dec 30, 2020
Anticipated Study Completion Date :
Dec 30, 2021

Outcome Measures

Primary Outcome Measures

  1. AUC value [through study completion, an average of 3 year]

    Area under the receiver operating characteristic (ROC) curve (AUC)

  2. specificity [through study completion, an average of 3 year]

    diagnosis specificity of intelligent ultrasound analysis

  3. sensitivity [through study completion, an average of 3 year]

    diagnosis sensitivity of intelligent ultrasound analysis

Eligibility Criteria

Criteria

Ages Eligible for Study:
N/A and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
Yes
Inclusion Criteria:
  1. clear ultrasound imaging of focal liver lesions including malignant liver tumors such as hepatocellular carcinoma, metastatic liver cancer and benigh liver tumors such as hemangioma and focal nodular hyperplasia and so on can be acquired.

  2. clear ultrasound imaging of liver tissues backgroud without lesions can be acquired.

  3. disease history and pathological diagnosis of the lesions can be acquired.

Exclusion Criteria:
  1. patients unsuitable for ultrasound san

  2. patients counldn't provide disease history such as hepatitis, alcohol intake and so on

  3. patients without pathological results

Contacts and Locations

Locations

Site City State Country Postal Code
1 Chinese PLA General Hospital Beijing Beijing China 100853

Sponsors and Collaborators

  • Chinese PLA General Hospital

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Ping Liang, Prof, Chinese PLA General Hospital
ClinicalTrials.gov Identifier:
NCT03871140
Other Study ID Numbers:
  • 301jrcsk3
First Posted:
Mar 12, 2019
Last Update Posted:
Mar 12, 2019
Last Verified:
Apr 1, 2018
Individual Participant Data (IPD) Sharing Statement:
Undecided
Plan to Share IPD:
Undecided
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Mar 12, 2019