Fusion of high b-value diffusion-weighted and unenhanced T1-weighted images to diagnose invasive breast cancer: factors associated with false-negative results

被引:14
作者
Kim, Jin Joo [1 ]
Kim, Jin You [1 ]
机构
[1] Pusan Natl Univ, Sch Med, Dept Radiol, Med Res Inst,Pusan Natl Univ Hosp, 1-10 Ami Dong, Busan 602739, South Korea
关键词
Magnetic resonance imaging; Diffusion magnetic resonance imaging; Breast neoplasm; Diagnosis;
D O I
10.1007/s00330-020-07644-5
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objectives: We sought factors associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast breast magnetic resonance imaging (MRI) using fused high b-value diffusion-weighted imaging (DWI) and unenhanced T1-weighted images (T1WI). Methods: Between 2018 and 2019, 316 consecutive women (mean age, 54.6 years) with invasive breast cancer who underwent preoperative breast MRI, including fused high b-value DWI and unenhanced T1WI, were retrospectively evaluated. Malignancy confidence ratings of the most suspicious breast lesions evident on fused DWI were derived by two radiologists using a 6-point Likert-type scale. Both clinicopathological and imaging features were analyzed. Multivariate regression analysis was performed to identify factors associated with false-negative DWI results in the diagnosis of invasive breast cancer. Results: Of the 316 breast cancers, fused DWI yielded 289 (91.5%) true-positive and 27 (8.5%) false-negative results. Multivariate analysis showed that small tumor size (<= 1 cm) (odds ratio [OR], 5.95; 95% confidence interval [CI], 2.11, 16.81; p = 0.001), presence of calcifications in the tumor (OR, 3.41; 95% CI, 1.27, 9.15; p = 0.015), and a moderate/marked background diffusion signal (ORs, 4.23 and 19.18; 95% CI, 1.31, 13.67 and 6.51, 56.46; p = 0.016 and p < 0.001, respectively) were significantly associated with false-negative results. In subgroup analysis of 141 screening-detected cancers, a marked background diffusion signal (OR, 7.94; 95% CI, 2.30, 27.35; p = 0.001) remained significantly associated with false-negative results in the multivariate analysis. Conclusions: In addition to histopathological features, a higher background diffusion signal was associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast MRI using fused high b-value DWI and unenhanced T1WI.
引用
收藏
页码:4860 / 4871
页数:12
相关论文
共 30 条
  • [1] Allred DC, 1998, MODERN PATHOL, V11, P155
  • [2] American College of Radiology, 2013, ACR BI RADS ATLAS BR
  • [3] Visibility of mammographically occult breast cancer on diffusion-weighted MRI versus ultrasound
    Amornsiripanitch, Nita
    Rahbar, Habib
    Kitsch, Averi E.
    Lam, Diana L.
    Weitzel, Brett
    Partridge, Savannah C.
    [J]. CLINICAL IMAGING, 2018, 49 : 37 - 43
  • [4] Fast and Noninvasive Characterization of Suspicious Lesions Detected at Breast Cancer X-Ray Screening: Capability of Diffusion-weighted MR Imaging with MIPs
    Bickelhaupt, Sebastian
    Laun, Frederik B.
    Tesdorff, Jana
    Lederer, Wolfgang
    Daniel, Heidi
    Stieber, Anne
    Delorme, Stefan
    Schlemmer, Heinz-Peter
    [J]. RADIOLOGY, 2016, 278 (03) : 689 - 697
  • [5] Readout-segmented Echo-pIanar Imaging Improves the Diagnostic Performance of Diffusion-weighted MR Breast Examinations at 3.0 T
    Bogner, Wolfgang
    Pinker-Domenig, Katja
    Bickel, Hubert
    Chmelik, Marek
    Weber, Michael
    Helbich, Thomas H.
    Trattnig, Siegfried
    Gruber, Stephan
    [J]. RADIOLOGY, 2012, 263 (01) : 64 - 76
  • [6] Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions
    Chen, Xin
    Li, Wen-ling
    Zhang, Yi-li
    Wu, Qian
    Guo, You-min
    Bai, Zhi-lan
    [J]. BMC CANCER, 2010, 10
  • [7] Ernster VL, 2002, JNCI-J NATL CANCER I, V94, P1546
  • [8] Analysis of factors influencing the degree of detectability on diffusion-weighted MRI and diffusion background signals in patients with invasive breast cancer
    Hahn, Soo Yeon
    Ko, Eun Sook
    Han, Boo-Kyung
    Lim, Yaeji
    Gu, Seonhye
    Ko, Eun Young
    [J]. MEDICINE, 2016, 95 (27)
  • [9] Quantitative assessment of background parenchymal enhancement in breast magnetic resonance images predicts the risk of breast cancer
    Hu, Xiaoxin
    Jiang, Luan
    Li, Qiang
    Gu, Yajia
    [J]. ONCOTARGET, 2017, 8 (06) : 10620 - 10627
  • [10] Unenhanced magnetic resonance screening using fused diffusion-weighted imaging and maximum-intensity projection in patients with a personal history of breast cancer: role of fused DWI for postoperative screening
    Kang, Ji Won
    Shin, Hee Jung
    Shin, Ki Chang
    Chae, Eun Young
    Choi, Woo Jung
    Cha, Joo Hee
    Kim, Hak Hee
    [J]. BREAST CANCER RESEARCH AND TREATMENT, 2017, 165 (01) : 119 - 128