Standardization of Radiological Evaluation of Dynamic Contrast Enhanced MRI: Application in Breast Cancer Diagnosis

被引:1
|
作者
Furman-Haran, E. [1 ]
Feinberg, M. Shapiro [2 ]
Badikhi, D. [1 ]
Eyal, E. [1 ]
Zehavi, T. [2 ]
Degani, H. [1 ]
机构
[1] Weizmann Inst Sci, IL-76100 Rehovot, Israel
[2] Meir Med Ctr, Kefar Sava, Israel
关键词
Breast cancer diagnosis; Breast MRI; Dynamic contrast enhanced MRI; Three time point; Principal component analysis; INDEPENDENT COMPONENT ANALYSIS; HIGH-SPATIAL-RESOLUTION; DCE-MRI; PARAMETRIC ANALYSIS; TUMOR ANGIOGENESIS; PROSTATE-CANCER; 3-TIME-POINT; MANAGEMENT;
D O I
10.7785/tcrt.2013.600263
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Dynamic contrast enhanced MRI is applied as an adjuvant tool for breast cancer detection, diagnosis, and follow-up of therapy. Despite improvements through the years in achieving higher spatial and temporal resolution, it still suffers from lack of scanning and processing standardization, and consequently, high variability in the radiological evaluation, particularly differentiating malignant from benign lesions. We describe here a hybrid method for achieving standardization of the radiological evaluation of breast dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) protocols, based on integrating the model based three time point (3TP) method with principal component analysis (PCA). The scanning and image processing procedures consisted of three main steps: 1. 3TP standardization of the MRI acquisition parameters according to a kinetic model, 2. Applying PCA to test cases and constructing an eigenvectors' base related to the contrast-enhancement kinetics and 3. Projecting all new cases on the eigenvectors' base and evaluating the clinical outcome. Datasets of overall 96 malignant and 26 benign breast lesions were recorded on 1.5T and 3T scanners, using three different MRI acquisition parameters optimized by the 3TP method. The final radiological evaluation showed similar detection and diagnostic ability for the three different MRI acquisition parameters. The area under the curve of receiver operating characteristic analysis yielded a value of 0.88 +/- 0.034 for differentiating malignant from benign lesions. This 3TP+PCA hybrid method is fast and can be readily applied as a computer aided diagnostic tool of breast cancer. The underlying principles of this method can be extended to standardize the evaluation of malignancies in other organs.
引用
收藏
页码:445 / 454
页数:10
相关论文
共 50 条
  • [31] Comparison of Dynamic Contrast-Enhanced MRI and Dynamic Contrast-Enhanced CT Biomarkers in Bladder Cancer
    Naish, J. H.
    McGrath, D. M.
    Bains, L. J.
    Passera, K.
    Roberts, C.
    Watson, Y.
    Cheung, S.
    Taylor, M. B.
    Logue, J. P.
    Buckley, D. L.
    Tessier, J.
    Young, H.
    Waterton, J. C.
    Parker, G. J. M.
    MAGNETIC RESONANCE IN MEDICINE, 2011, 66 (01) : 219 - 226
  • [32] Combined diffusion-weighted and dynamic contrast-enhanced MRI for prostate cancer diagnosis - Correlation with biopsy and histopathology
    Kozlowski, Piotr
    Chang, Silvia D.
    Jones, Edward C.
    Berean, Kenneth W.
    Chen, Henry
    Goldenberg, S. Larry
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2006, 24 (01) : 108 - 113
  • [33] Association between rim enhancement of breast cancer on dynamic contrast-enhanced MRI and patient outcome: impact of subtype
    Schmitz, Alexander M. Th
    Loo, Claudette E.
    Wesseling, Jelle
    Pijnappel, Ruud M.
    Gilhuijs, Kenneth G. A.
    BREAST CANCER RESEARCH AND TREATMENT, 2014, 148 (03) : 541 - 551
  • [34] Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy
    Zhang, Michelle
    Horvat, Joao V.
    Bernard-Davila, Blanca
    Marino, Maria Adele
    Leithner, Doris
    Ochoa-Albiztegui, R. Elena
    Helbich, Thomas H.
    Morris, Elizabeth A.
    Thakur, Sunitha
    Pinker, Katja
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2019, 49 (03) : 864 - 874
  • [35] AUTOMATIC LIVER TUMOR DIAGNOSIS WITH DYNAMIC-CONTRAST ENHANCED MRI
    Caldeira, Liliana
    Silva, Isabela
    Sanches, Joao
    2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5, 2008, : 2256 - 2259
  • [36] Dynamic contrast enhanced MRI in the differential diagnosis of soft tissue tumors
    Tuncbilek, N
    Karakas, HM
    Okten, OO
    EUROPEAN JOURNAL OF RADIOLOGY, 2005, 53 (03) : 500 - 505
  • [37] Ultrafast Dynamic Contrast-enhanced MRI of the Breast: How Is It Used?
    Kataoka, Masako
    Honda, Maya
    Ohashi, Akane
    Yamaguchi, Ken
    Mori, Naoko
    Goto, Mariko
    Fujioka, Tomoyuki
    Mori, Mio
    Kato, Yutaka
    Satake, Hiroko
    Iima, Mami
    Kubota, Kazunori
    MAGNETIC RESONANCE IN MEDICAL SCIENCES, 2022, 21 (01) : 83 - 94
  • [38] Dynamic contrast-enhanced MRI in oncology: how we do it
    Petralia, Giuseppe
    Summers, Paul E.
    Agostini, Andrea
    Ambrosini, Roberta
    Cianci, Roberta
    Cristel, Giulia
    Calistri, Linda
    Colagrande, Stefano
    RADIOLOGIA MEDICA, 2020, 125 (12): : 1288 - 1300
  • [39] Role of MRI in Differentiating Benign from Malignant Breast Lesions Using Dynamic Contrast Enhanced MRI and Diffusion Weighted MRI
    Ahluwalia, Kunal Singh
    Narula, Harneet
    Jain, Amit
    Arora, Anshul
    Vohra, Aditi
    Bansal, Tanu
    Gakhar, Akshit
    JOURNAL OF EVOLUTION OF MEDICAL AND DENTAL SCIENCES-JEMDS, 2021, 10 (19): : 1422 - 1428
  • [40] Dynamic Contrast-Enhanced MRI in the Evaluation of Carotid Space Paraganglioma versus Schwannoma
    Gaddikeri, Santhosh
    Hippe, Daniel S.
    Anzai, Yoshimi
    JOURNAL OF NEUROIMAGING, 2016, 26 (06) : 618 - 625