relationship between classification of doppler ultrasound blood flow signals and angiogenesis in primary hepatocellular carcinoma

relationship between classification of doppler ultrasound blood flow signals and angiogenesis in primary hepatocellular carcinoma

;MA Yanyan
lontar komputer 2014 Vol. 30 pp. 926-928
159
yanyan2014linchuangrelationship

Abstract

ObjectiveTo investigate the relationship of the classification of Doppler ultrasound blood flow signals with matrix metalloproteinase-9 (MMP-9) expression and microvessel density (MVD) in primary hepatocellular carcinoma (PHC). MethodsSixty patients with PHC, who underwent surgical resection in the Second Affiliated Hospital of Dalian Medical University from April 2008 to April 2013, were included in the study. These patients underwent ultrasound examination before operation. The classification of Doppler ultrasound blood flow signals in the focus was recorded. The expression of MMP-9 and CD31 in carcinoma tissues was detected by immunohistochemistry, and MVD was calculated. Continuous data were analyzed by t test, while categorical data by chi-square test; the relationship was evaluated by Spearman correlation analysis. ResultsThe classification of Doppler ultrasound blood flow signals was as follows: grade 0 (15 cases); grade 1 (20 cases); grade 2 (15 cases); grade 3 (10 cases). The positive rate of MMP-9 expression was 72.3%. The MVD was 43.2±5.4. The classification of Doppler ultrasound blood flow signals in the focus was positively correlated with MMP-9 expression and MVD (r=0.56, P<0.05). ConclusionThe classification of Doppler ultrasound blood flow signals can reveal vascular changes in the focus, and it can be used in the clinical evaluation of angiogenesis in tumor tissues and the clinical diagnosis and treatment of PHC.

Citation

ID: 233749
Ref Key: yanyan2014linchuangrelationship
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
233749
Unique Identifier:
10.3969/j.issn.1001-5256.2014.09.022
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet