second-look ultrasonography for mri-detected suspicious breast lesions in patients with breast cancer

second-look ultrasonography for mri-detected suspicious breast lesions in patients with breast cancer

;Min Ji Hong;Joo Hee Cha;Hak Hee Kim;Hee Jung Shin;Eun Young Chae;Ji Eun Shin;Woo Jung Choi
materials research society symposium proceedings 2015 Vol. 34 pp. 125-132
171
hong2015ultrasonographysecond-look

Abstract

Purpose: The purpose of this study is to evaluate the use of second-look ultrasonography (US) for investigating additional suspicious lesions detected on preoperative staging magnetic resonance imaging (MRI) for breast cancer. Methods: Between September 2008 and August 2010, 1,970 breast MRIs were performed at our medical institution for the evaluation of breast cancer before surgery. Second-look US was recommended for 135 patients with 149 suspicious lesions, following the MRI interpretation, and 108 patients with 121 lesions were included in this study. The detection rate on second-look US, according to the lesion type, diameter, and histopathological outcome, was analyzed. Results: Of the 121 lesions considered in this study, 97 (80.2%) were diagnosed on MRI as masses and 24 (19.8%) as non-mass-like lesions; 105 lesions (86.8%) were correlated and 16 (13.2%) were not correlated with the findings of second-look US. Of the 105 correlated lesions, 29 (27.6%) were proven to be malignant and 76 (72.4%) were benign. Although a greater number of large malignant lesions were correlated on second-look US than small benign lesions, there was no statistically significant difference according to lesion diameter or type, as seen on MRI or pathology. Conclusion: We have concluded that second-look US is a useful diagnostic tool for lesions incidentally detected on breast MRI, as in this study, it could identify 86.8% of the MRI-detected breast lesions.

Citation

ID: 237908
Ref Key: hong2015ultrasonographysecond-look
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
237908
Unique Identifier:
10.14366/usg.14046
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