Literature DB >> 12002599

Extension of breast cancer: comparison of CT and MRI.

Hiroshi Nakahara1, Kiyoshi Namba, Hideyuki Wakamatsu, Ryoji Watanabe, Hidemi Furusawa, Mitsunori Shirouzu, Takafumi Matsu, Chiaki Tanaka, Futoshi Akiyama, Hiromi Ifuku, Mayumi Nakahara, Shozo Tamura.   

Abstract

PURPOSE: To compare three-dimensional (3D) helical CT with 3D MRI in the evaluation of intraductal spread of breast cancer.
METHODS: Fifty patients with breast cancer were examined. Tumor size ranged from Tis to T2. The whole breast was scanned by both breath-holding helical CT and MRI with contrast media. Linear or segmental enhancement, and spotty enhancement around the main tumor were considered to indicate ductal carcinoma in situ (DCIS) or ductal spread. These findings were compared with thin section histopathologic data.
RESULTS: Seventeen of 35 patients had intraductal spread with invasive cancer and 15 patients had DCIS. The sensitivity, specificity, and accuracy of 3D CT in detecting intraductal spread or DCIS were 71.9%, 83.3%, and 76.0%, respectively, and those of 3D MRI were 87.5%, 61.1%, and 78.0%. Overestimations numbered three (6.0%) on CT and seven (14.0%) on MRI, and underestimations numbered nine (18.0%) on CT and four (8.0%) on MRI.
CONCLUSION: 3D helical CT can provide good information about the spread of breast cancer and could be an alternative to 3D MRI for preoperative examination of breast cancer.

Entities:  

Mesh:

Year:  2002        PMID: 12002599

Source DB:  PubMed          Journal:  Radiat Med        ISSN: 0288-2043


  6 in total

Review 1.  Comparison of magnetic resonance imaging and multidetector computed tomography for evaluating intraductal tumor extension of breast cancer.

Authors:  Takayoshi Uematsu
Journal:  Jpn J Radiol       Date:  2010-10-24       Impact factor: 2.374

2.  Usefulness of lesion image mapping with multidetector-row helical computed tomography using a dedicated skin marker in breast-conserving surgery.

Authors:  Narumi Harada-Shoji; Takayuki Yamada; Takanori Ishida; Masakazu Amari; Akihiko Suzuki; Takuya Moriya; Noriaki Ohuchi
Journal:  Eur Radiol       Date:  2008-11-15       Impact factor: 5.315

3.  Detection of intraductal component around invasive breast cancer using ultrasound: correlation with MRI and histopathological findings.

Authors:  Sangeetha Sundararajan; Eriko Tohno; Hiroshi Kamma; Ei Ueno; Manabu Minami
Journal:  Radiat Med       Date:  2006-02

4.  Deep Learning Classification of Breast Cancer Tissue from Terahertz Imaging Through Wavelet Synchro-Squeezed Transformation and Transfer Learning.

Authors:  Haoyan Liu; Nagma Vohra; Keith Bailey; Magda El-Shenawee; Alexander H Nelson
Journal:  J Infrared Millim Terahertz Waves       Date:  2022-01       Impact factor: 2.647

5.  The value of chest CT for prediction of breast tumor size: comparison with pathology measurement.

Authors:  Su Joa Ahn; Young Saing Kim; Eun Young Kim; Heung Kyu Park; Eun Kyung Cho; Yoon Kyung Kim; Yon Mi Sung; Hye-Young Choi
Journal:  World J Surg Oncol       Date:  2013-06-06       Impact factor: 2.754

6.  A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning.

Authors:  Hadi Moghadas-Dastjerdi; Hira Rahman Sha-E-Tallat; Lakshmanan Sannachi; Ali Sadeghi-Naini; Gregory J Czarnota
Journal:  Sci Rep       Date:  2020-07-02       Impact factor: 4.379

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.