Multimodal Breast Parenchymal Patterns Correlation Using a Patient-Specific Biomechanical Model

被引:4
|
作者
Garcia, Eloy [1 ]
Diez, Yago [2 ]
Diaz, Oliver [1 ]
Llado, Xavier [1 ]
Gubern-Merida, Albert [3 ]
Marti, Robert [1 ]
Marti, Joan [1 ]
Oliver, Arnau [1 ]
机构
[1] Univ Girona, Inst Comp Vis & Robot, Girona 17071, Spain
[2] Tohoku Univ, Tokuyama Lab GSIS, Sendai, Miyagi 9808577, Japan
[3] Radboud Univ Nijmegen, Med Ctr, NL-6525 GA Nijmegen, Netherlands
基金
欧盟地平线“2020”;
关键词
Breast cancer; parenchymal patterns; cross-modality; subject-specific biomechanical models; X-RAY MAMMOGRAPHY; MR-IMAGES; DENSITY SEGMENTATION; REGISTRATION; CLASSIFICATION; OPTIMIZATION; COMPRESSION; VALIDATION;
D O I
10.1109/TMI.2017.2749685
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we aim to produce a realistic 2-D projection of the breast parenchymal distribution from a 3-D breast magnetic resonance image (MRI). To evaluate the accuracy of our simulation, we compare our results with the local breast density (i.e., density map) obtained from the complementary full-field digital mammogram. To achieve this goal, we have developed a fully automatic framework, which registers MRI volumes to X-ray mammograms using a subject-specific biomechanical model of the breast. The optimization step modifies the position, orientation, and elastic parameters of the breast model to perform the alignment between the images. When the model reaches an optimal solution, the MRI glandular tissue is projected and compared with the one obtained from the corresponding mammograms. To reduce the loss of information during the ray-casting, we introduce a new approach that avoids resampling the MRI volume. In the results, we focus our efforts on evaluating the agreement of the distributions of glandular tissue, the degree of structural similarity, and the correlation between the real and synthetic density maps. Our approach obtained a high-structural agreement regardless the glandularity of the breast, whilst the similarity of the glandular tissue distributions and correlation between both images increase in denser breasts. Furthermore, the synthetic images show continuity with respect to large structures in the density maps.
引用
收藏
页码:712 / 723
页数:12
相关论文
共 50 条
  • [21] Landmark Detection for Fusion of Fundus and MRI Toward a Patient-Specific Multimodal Eye Model
    De Zanet, Sandro I.
    Ciller, Carlos
    Rudolph, Tobias
    Maeder, Philippe
    Munier, Francis
    Balmer, Aubin
    Cuadra, Meritxell Bach
    Kowal, Jens H.
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2015, 62 (02) : 532 - 540
  • [22] PRESURGERY DESIGN AND BIOMECHANICAL EVALUATION OF PATIENT-SPECIFIC KNEE IMPLANT
    Rong, Qiguo
    Bai, Jianfeng
    Huang, Yongling
    Lin, Jianhao
    JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY, 2015, 15 (06)
  • [23] Patient-Specific Biomechanical Modeling of the Lung Tumor for Radiation Therapy
    Giroux, M.
    Ladjal, H.
    Beuve, M.
    Giraud, P.
    Shariat, B.
    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, 2017, 20 : 95 - 96
  • [24] Patient-Specific Biomechanical Modeling of Cardiac Amyloidosis - A Case Study
    Chapelle, D.
    Felder, A.
    Chabiniok, R.
    Guellich, A.
    Deux, J. -F.
    Damy, T.
    FUNCTIONAL IMAGING AND MODELING OF THE HEART (FIMH 2015), 2015, 9126 : 295 - 303
  • [25] Additive manufacturing and biomechanical validation of a patient-specific diabetic insole
    Peker, Ayfer
    Aydin, Levent
    Kucuk, Serdar
    Ozkoc, Guralp
    Cetinarslan, Berrin
    Canturk, Zeynep
    Selek, Alev
    POLYMERS FOR ADVANCED TECHNOLOGIES, 2020, 31 (05) : 988 - 996
  • [26] Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues
    Lago, M. A.
    Ruperez, M. J.
    Martinez-Martinez, F.
    Martinez-Sanchis, S.
    Bakic, P. R.
    Monserrat, C.
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (21) : 7942 - 7950
  • [27] Classification of TNBC using a patient-specific ErbB network model
    Yamashiro, Sawa
    Imoto, Hiroaki
    Okada, Mariko
    CANCER SCIENCE, 2022, 113 : 1666 - 1666
  • [28] A hybrid patient-specific biomechanical model based image registration method for the motion estimation of lungs
    Han, Lianghao
    Dong, Hua
    McClelland, Jamie R.
    Han, Liangxiu
    Hawkes, David J.
    Barratt, Dean C.
    MEDICAL IMAGE ANALYSIS, 2017, 39 : 87 - 100
  • [29] Optimizing Radiotherapy for Glioblastoma Using A Patient-Specific Mathematical Model
    Corwin, D.
    Holdsworth, C.
    Rockne, R.
    Stewart, R.
    Phillips, M.
    Swanson, K.
    MEDICAL PHYSICS, 2013, 40 (06)
  • [30] A Patient-Specific Model for Collision Prediction Using an Azure Kinect
    Simpson, Z.
    Sperling, N.
    MEDICAL PHYSICS, 2020, 47 (06) : E572 - E572