Share：
Share this content in WeChat
X
[Chinese][PDF]85368
• Clinical Article •
The evaluation of the infiltration range of breast cancer tissue in vitro using 7.0 T MRI: a comparative study between MRI and histological examination
CHEN Ye-xi  ZHONG Xiao-ping  LI Zhi-yang  CAI Dao-quan  WU Ren-hua  SHEN Zhi-wei 

CHEN Ye-xi, ZHONG Xiao-ping for common first author DOI:10.3969/j.issn.1674-8034.2015.01.006.


[Abstract] Objectives: To evaluate the accuracy of infiltration range of breast cancer tissue in vitro using 7.0 T magnetic resonance imaging(MRI), and to verify the possible value of determining the breast tumor margin before surgery by MRI.Materials and Methods: Fresh breast cancer tissue in vitro (n=17) were underwent 7.0 T MRI and histological examination. After acquisition of diffusion weighted imaging (DWI)、apparent diffusion coefficient (ADC) and fractional anisotropy (FA) imaging on the 7.0 T MRI machines, the edge of lesion was drawn out manually and the area of tumor was calculated by VnmrJ 4.0. The HE dyeing slice of pathology was observed under a microscope. The edge of lesion was drawn out manually and the area was calculated by Photoshop software. The correlation between the area of tumor from MRI and the histological slice was analyzed using Pearson correlation test of SPSS version 19.0.Results: In all specimens, there were 14 cases of breast infiltrative ductal carcinoma, 2 cases breast papillary carcinoma and 1 case of mucinous breast carcinoma confirmed pathologically. Significant correlation was found between the area of breast tumor on DWI, ADC, FA mapping and histological result (4.32±1.28) cm2 in DWI vs. (3.81±1.12) cm2 in histological slice, Pearson correlation coefficient r=0.966, P=0.00, (4.68±1.43) cm2 in ADC vs. (3.81±1.12) cm2 in histological slice, Pearson correlation coefficient r=0.976, P=0.00, (4.74±1.53) cm2 in FA vs. (3.81±1.12) cm2 in histological slice, Pearson correlation coefficient r=0.964, P=0.00).Conclusions: Although all of the areas acquired by MRI were larger than those by histological results, there was significant correlation between them. Thus, useful information for evaluating the infiltration range of breast tumor may be provided by MRI.
[Keywords] Breast neoplasms；Magnetic resonance imaging；Infiltration range；Pthology

CHEN Ye-xi Department of Surgery, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, China

ZHONG Xiao-ping Department of Surgery, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, China

LI Zhi-yang Department of Surgery, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, China

CAI Dao-quan Department of Surgery, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, China

WU Ren-hua* Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, China

SHEN Zhi-wei* Department of Radiology, the Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, China

*Correspondence to: Wu RH, E-mail: rhwu@stu.edu.cn. Shen ZW, E-mail: zwshen@stu.edu.cn

Conflicts of interest   None.

Received  2014-09-01
Accepted  2014-11-06
DOI: 10.3969/j.issn.1674-8034.2015.01.006
CHEN Ye-xi, ZHONG Xiao-ping for common first author DOI:10.3969/j.issn.1674-8034.2015.01.006.

[1]
杨玲，李连弟，陈育德，等．中国乳腺癌发病死亡趋势的估计与预测．中华肿瘤杂志, 2006, 28(6): 438-440.
[2]
Smith RA. The evolving role of MRI in the detection and evaluation of breast cancer. N Engl J Med, 2007, 356(13): 1362-1364.
[3]
Alsharif S, Daghistani R, Kamberoğlu EA, et al. Mammographic, sonographic and MR imaging features of invasive micropapillary breast cancer. Eur J Radiol, 2014, 83(8): 1375-1380.
[4]
Baltzer PA, Schafer A, Dietzel M, et al. Diffusion tensor magnetic resonance imaging of the breast: a pilot study. Eur Radiol, 2011, 21(1): 1-10.
[5]
Cakir O, Arslan A, Inan N, et al. Comparison of the diagnostic performances of diffusion parameters in diffusion weighted imaging and diffusion tensor imaging of breast lesions. Eur J Radiol, 2013, 82(12): e801-806.
[6]
Woodhams R, Ramadan S, Stanwell P, et al. Diffusion-weighted imaging of the breast: principles and clinical applications. Radiographics, 2011, 31(4): 1059-1084.
[7]
赵莉芸，周纯武，李静. 2012年北美放射学年会乳腺影像学研究进展．磁共振成像, 2013, (02): 156-160.
[8]
陈对梅，汪青山，王峻，等．乳腺叶状肿瘤的MRI表现分析．磁共振成像, 2013, (01): 24-28.
[9]
Zhai G, Kim H, Sarver D, et al. Early therapy assessment of combined anti-DR5 antibody and carboplatin in triple-negative breast cancer xenografts in mice using diffusion-weighted imaging and (1)H MR spectroscopy. J Magn Reson Imaging, 2014, 39(6): 1588-1594.
[10]
Yoo H, Shin HJ, Baek S, et al. Diagnostic performance of apparent diffusion coefficient and quantitative kinetic parameters for predicting additional malignancy in patients with newly diagnosed breast cancer. Magn Reson Imaging, 2014, 32(7): 867-874.
[11]
Schnall MD, Blume J, Bluemke DA, et al. Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology, 2006, 238(1): 42-53.
[12]
Tan SL, Rahmat K, Rozalli FI, et al. Differentiation between benign and malignant breast lesions using quantitative diffusion-weighted sequence on 3 T MRI. Clin Radiol, 2014, 69(1): 63-71.
[13]
Pinker K, Helbich TH, Magometschnigg H, et al. Molecular breast imaging: an update. Radiologe, 2014, 54(3): 241-253.
[14]
Gutierrez RL, Demartini WB, Silbergeld JJ, et al. High cancer yield and positive predictive value: outcomes at a center routinely using preoperative breast MRI for staging. AJR Am J Roentgenol, 2011, 196(1): W93-99.
[15]
Biglia N, Bounous VE, Martincich L, et al. Role of MRI (magnetic resonance imaging) versus conventional imaging for breast cancer presurgical staging in young women or with dense breast. Eur J Surg Oncol, 2011, 37(3): 199-204.
[16]
Trimboli RM, Verardi N, Cartia F, et al. Breast cancer detection using double reading of unenhanced MRI including T1-weighted, T2-weighted STIR, and diffusion-weighted imaging: a proof of concept study. Am J Roentgenol, 2014, 203(3): 674-681.
[17]
Ouyang Z, Ouyang Y, Zhu M. et al. Diffusion-weighted imaging with fat suppression using short-tau inversion recovery: clinical utility for diagnosis of breast lesions. Clin Radiol, 2014, 69(8): 337-344.
[18]
Kang BJ, Lipson JA, Planey KR, et al. Rim sign in breast lesions on diffusion-weighted magnetic resonance imaging: diagnostic accuracy and clinical usefulness. J Magn Reson Imaging, 2014. DOI:
[19]
Janka R, Hammon M, Geppert C, et al. Diffusion-weighted MR imaging of benign and malignant breast lesions before and after contrast enhancement. Rofo, 2014, 186(2): 130-135.
[20]
Nogueira L, Brandao S, Matos E, et al. Diffusion-weighted breast imaging at 3 T: preliminary experience. Clin Radiol, 2014, 69(4): 378-384.
[21]
Zhai G, Grubbs CJ, Stockard CR, et al. Diffusion weighted imaging evaluated the early therapy effect of tamoxifen in an MNU-induced mammary cancer rat model. PLoS One, 2013, 8(5): e64445.
[22]
韦苇，黄仲奎，龙莉玲，等．乳腺浸润性导管癌的3.0 T MRI诊断．磁共振成像, 2012, (6): 434-439.
[23]
汪登斌．乳腺MRI检查最佳序列选择及扫描参数优化．磁共振成像, 2011, 2(3): 177-181.
[24]
De Felice C, Cipolla V, Guerrieri D, et al. Apparent diffusion coefficient on 3.0 Tesla magnetic resonance imaging and prognostic factors in breast cancer. Eur J Gynaecol Oncol, 2014, 35(4): 408-414.
[25]
Mcdonald ES, Schopp JG, Peacock S, et al. Diffusion-weighted MRI: association between patient characteristics and apparent diffusion coefficients of normal breast fibroglandular tissue at 3 T. AJR Am J Roentgenol, 2014, 202(5): W496-502.
[26]
Mclaughlin RL, Newitt DC, Wilmes LJ, et al. High resolution in vivo characterization of apparent diffusion coefficient at the tumor-stromal boundary of breast carcinomas: a pilot study to assess treatment response using proximity-dependent diffusion-weighted imaging. J Magn Reson Imaging, 2014, 39(5): 1308-1313.
[27]
Kim EJ, Kim SH, Kang BJ, et al. Diagnostic value of breast MRI for predicting metastatic axillary lymph nodes in breast cancer patients: diffusion-weighted MRI and conventional MRI. Magn Reson Imaging, 2014, 32(10): 1230-1236.
[28]
Iwasa H, Kubota K, Hamada N, et al. Early prediction of response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and gray-scale ultrasonography. Oncol Rep, 2014, 31(4): 1555-1560.
[29]
Hahn SY, Ko EY, Han BK, et al. Role of diffusion-weighted imaging as an adjunct to contrast-enhanced breast MRI in evaluating residual breast cancer following neoadjuvant chemotherapy. Eur J Radiol, 2014, 83(2): 283-288.
[30]
Hagmann P, Jonasson L, Maeder P, et al. Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics, 2006, 26(Suppl 1): 205-223.

PREV The morphological study of brain cortical in chronic obstructive pulmonary disease
NEXT The application of conventional MRI, DWI and DCEI in focal liver lesions
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn