Color-coded visualization of magnetic resonance imaging multiparametric maps

被引:12
作者
Kather, Jakob Nikolas [1 ,2 ]
Weidner, Anja [3 ]
Attenberger, Ulrike [3 ]
Bukschat, Yannick [2 ]
Weis, Cleo-Aron [4 ]
Weis, Meike [3 ]
Schad, Lothar R. [2 ]
Zoellner, Frank Gerrit [2 ]
机构
[1] Univ Heidelberg Hosp, Dept Med Oncol & Internal Med 6, Natl Ctr Tumor Dis, Heidelberg, Germany
[2] Heidelberg Univ, Med Fac Mannheim, Comp Assisted Clin Med, Mannheim, Germany
[3] Heidelberg Univ, Univ Med Ctr Mannheim, Inst Clin Radiol & Nucl Med, Mannheim, Germany
[4] Heidelberg Univ, Univ Med Ctr Mannheim, Inst Pathol, Mannheim, Germany
来源
SCIENTIFIC REPORTS | 2017年 / 7卷
关键词
COMPUTER-AIDED DIAGNOSIS; VISUAL-SEARCH; DATA SYSTEM; MRI; CLASSIFICATION; DISEASE; FUSION; CT;
D O I
10.1038/srep41107
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Multiparametric magnetic resonance imaging (mpMRI) data are emergingly used in the clinic e.g. for the diagnosis of prostate cancer. In contrast to conventional MR imaging data, multiparametric data typically include functional measurements such as diffusion and perfusion imaging sequences. Conventionally, these measurements are visualized with a one-dimensional color scale, allowing only for one-dimensional information to be encoded. Yet, human perception places visual information in a three-dimensional color space. In theory, each dimension of this space can be utilized to encode visual information. We addressed this issue and developed a new method for tri-variate color-coded visualization of mpMRI data sets. We showed the usefulness of our method in a preclinical and in a clinical setting: In imaging data of a rat model of acute kidney injury, the method yielded characteristic visual patterns. In a clinical data set of N = 13 prostate cancer mpMRI data, we assessed diagnostic performance in a blinded study with N = 5 observers. Compared to conventional radiological evaluation, color-coded visualization was comparable in terms of positive and negative predictive values. Thus, we showed that human observers can successfully make use of the novel method. This method can be broadly applied to visualize different types of multivariate MRI data.
引用
收藏
页数:11
相关论文
共 38 条
  • [31] 3D Multi-parametric Breast MRI Segmentation Using Hierarchical Support Vector Machine with Coil Sensitivity Correction
    Wang, Yi
    Morrell, Glen
    Heibrun, Marta E.
    Payne, Allison
    Parker, Dennis L.
    [J]. ACADEMIC RADIOLOGY, 2013, 20 (02) : 137 - 147
  • [32] Ware C., 2004, INFORM VISUALIZATION, P2
  • [33] Value of multiparametric prostate MRI of the peripheral zone
    Weidner, Anja M.
    Michaely, Henrik J.
    Lemke, Andreas
    Breitinger, Lutz
    Wenz, Frederik
    Marx, Alexander
    Schoenberg, Stefan O.
    Dinter, Dietmar J.
    [J]. ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK, 2011, 21 (03): : 198 - 205
  • [34] PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2
    Weinreb, Jeffrey C.
    Barentsz, Jelle O.
    Choyke, Peter L.
    Cornud, Francois
    Haider, Masoom A.
    Macura, Katarzyna J.
    Margolis, Daniel
    Schnall, Mitchell D.
    Shtern, Faina
    Tempany, Clare M.
    Thoeny, Harriet C.
    Verma, Sadna
    [J]. EUROPEAN UROLOGY, 2016, 69 (01) : 16 - 40
  • [35] Real-time MRI-TRUS fusion for guidance of targeted prostate biopsies
    Xu, Sheng
    Kruecker, Jochen
    Turkbey, Baris
    Glossop, Neil
    Singh, Anurag K.
    Choyke, Peter
    Pinto, Peter
    Wood, Bradford J.
    [J]. COMPUTER AIDED SURGERY, 2008, 13 (05) : 255 - 264
  • [36] An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited
    Zoellner, Frank G.
    Daab, Markus
    Sourbron, Steven P.
    Schad, Lothar R.
    Schoenberg, Stefan O.
    Weisser, Gerald
    [J]. BMC MEDICAL IMAGING, 2016, 16
  • [37] Functional imaging of acute kidney injury at 3 Tesla: Investigating multiple parameters using DCE-MRI and a two-compartment filtration model
    Zoellner, Frank G.
    Zimmer, Fabian
    Klotz, Sarah
    Hoeger, Simone
    Schad, Lothar R.
    [J]. ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK, 2015, 25 (01): : 58 - 65
  • [38] UMMPerfusion: an Open Source Software Tool Towards Quantitative MRI Perfusion Analysis in Clinical Routine
    Zoellner, Frank G.
    Weisser, Gerald
    Reich, Marcel
    Kaiser, Sven
    Schoenberg, Stefan O.
    Sourbron, Steven P.
    Schad, Lothar R.
    [J]. JOURNAL OF DIGITAL IMAGING, 2013, 26 (02) : 344 - 352