Diffusion-weighted imaging or dynamic contrast-enhanced curve: a retrospective analysis of contrast-enhanced magnetic resonance imaging-based differential diagnoses of benign and malignant breast lesions

被引:27
作者
Yang, Xiaoping [1 ]
Dong, Mengshi [1 ]
Li, Shu [1 ]
Chai, Ruimei [1 ]
Zhang, Zheng [1 ]
Li, Nan [1 ]
Zhang, Lina [1 ]
机构
[1] China Med Univ, Dept Radiol, Affiliated Hosp 1, 155 Nanjing St, Shenyang 110001, Liaoning, Peoples R China
关键词
Breast neoplasms; Diffusion magnetic resonance imaging; Magnetic resonance imaging; KINETIC-ANALYSIS; CATEGORY; 4; MRI; ACCURACY; CRITERIA; CANCER; TIME;
D O I
10.1007/s00330-020-06883-w
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
Objective To compare the diagnostic performance of models based on a combination of contrast-enhanced (CE) magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI) or time-intensity curves (TIC) in diagnosing malignancies of breast lesions. Methods A double-blind retrospective study was conducted in 328 patients (254 for training and the following 74 for validation) who underwent dynamic contrast-enhanced MRI (DCE-MRI) of the breast with pathological results. Two score models, the DWI model (apparent diffusion coefficient (ADC) + morphology + enhanced information) and the TIC model (TIC + morphology + enhanced information), were established with binary logistic regression for mass and non-mass enhancements (NMEs) in the training set. The sensitivity, specificity, and area under the curve (AUC) were compared between the two models (DWI model vs. TIC model); p < 0.05 was considered as statistically different. External validation was used. Results In the training set, the sensitivities, specificities, and AUCs of the DWI/TIC model were 95.2%/95.8%, 70.8%/47.9%, and 0.932/0.891 for masses, and 94.2%/90.4%, 47.4%/47.4%, and 0.798 (95% CI, 0.686-0.884)/0.802 (95% CI, 0.691-0.887) for NMEs, respectively. The AUC of the DWI model was significantly higher than that of the TIC model (p < 0.05) for masses. In the validation set, the AUCs of the DWI/TIC model were 0.896/0.861 for masses (p < 0.05) and 0.936/0.836 for NMEs (p > 0.05). Conclusions Combined with CE MRI, the DWI model was superior or equal to the TIC model in differentiating benign and malignant breast lesions.
引用
收藏
页码:4795 / 4805
页数:11
相关论文
共 50 条
[1]   Diffusion-weighted imaging or dynamic contrast-enhanced curve: a retrospective analysis of contrast-enhanced magnetic resonance imaging–based differential diagnoses of benign and malignant breast lesions [J].
Xiaoping Yang ;
Mengshi Dong ;
Shu Li ;
Ruimei Chai ;
Zheng Zhang ;
Nan Li ;
Lina Zhang .
European Radiology, 2020, 30 :4795-4805
[2]   Effectivity of combined diffusion-weighted imaging and contrast-enhanced MRI in malignant and benign breast lesions [J].
Yadav, Pratiksha ;
Chauhan, Surbhi .
POLISH JOURNAL OF RADIOLOGY, 2018, 83 :E82-E93
[3]   Investigation of imaging features in contrast-enhanced magnetic resonance imaging of benign and malignant breast lesions [J].
Kubota, Kazunori ;
Fujioka, Tomoyuki ;
Tateishi, Ukihide ;
Mori, Mio ;
Yashima, Yuka ;
Yamaga, Emi ;
Katsuta, Leona ;
Yamaguchi, Ken ;
Tozaki, Mitsuhiro ;
Sasaki, Michiro ;
Uematsu, Takayoshi ;
Monzawa, Shuichi ;
Isomoto, Ichiro ;
Suzuki, Mizuka ;
Satake, Hiroko ;
Nakahara, Hiroshi ;
Goto, Mariko ;
Kikuchi, Mari .
JAPANESE JOURNAL OF RADIOLOGY, 2024, 42 (07) :720-730
[4]   Potential of Noncontrast Magnetic Resonance Imaging With Diffusion-Weighted Imaging in Characterization of Breast Lesions Intraindividual Comparison With Dynamic Contrast-Enhanced Magnetic Resonance Imaging [J].
Baltzer, Pascal A. T. ;
Bickel, Hubert ;
Spick, Claudio ;
Wengert, Georg ;
Woitek, Ramona ;
Kapetas, Panagiotis ;
Clauser, Paola ;
Helbich, Thomas H. ;
Pinker, Katja .
INVESTIGATIVE RADIOLOGY, 2018, 53 (04) :229-235
[5]   Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning [J].
Zhang, Ming ;
He, Guangyuan ;
Pan, Changjie ;
Yun, Bing ;
Shen, Dong ;
Meng, Mingzhu .
JOURNAL OF CANCER RESEARCH AND THERAPEUTICS, 2023, 19 (06) :1589-1596
[6]   Accuracy of combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging for breast cancer detection: a meta-analysis [J].
Zhang, Li ;
Tang, Min ;
Min, Zhiqian ;
Lu, Jun ;
Lei, Xiaoyan ;
Zhang, Xiaoling .
ACTA RADIOLOGICA, 2016, 57 (06) :651-660
[7]   Evaluation of the efficacy of neoadjuvant chemotherapy for breast cancer using diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging [J].
Xu, H. D. ;
Zhang, Y. Q. .
NEOPLASMA, 2017, 64 (03) :430-436
[8]   Contrast-enhanced and unenhanced diffusion-weighted imaging of the breast at 3 T [J].
Fanariotis, M. ;
Tsougos, I ;
Vlychou, M. ;
Fezoulidis, I ;
Vassiou, K. .
CLINICAL RADIOLOGY, 2018, 73 (11) :928-935
[9]   Validity of dynamic contrast-enhanced magnetic resonance imaging of the breast versus diffusion-weighted imaging and magnetic resonance spectroscopy in predicting the malignant nature of non-mass enhancement lesions [J].
Bayoumi, Dalia ;
Shokeir, Farah Ahmed ;
Karam, Rasha ;
Elboghdady, Aya .
EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE, 2024, 55 (01)
[10]   Contribution of Diffusion-Weighted Imaging to Dynamic Contrast-Enhanced MRI in the Characterization of Breast Tumors [J].
Kul, Sibel ;
Cansu, Aysegul ;
Alhan, Etem ;
Dinc, Hasan ;
Gunes, Gurbuz ;
Reis, Abdulkadir .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2011, 196 (01) :210-217