Optimal mass transport kinetic modeling for head and neck DCE-MRI: Initial analysis

被引:3
|
作者
Elkin, Rena [1 ]
Nadeem, Saad [2 ]
LoCastro, Eve [2 ]
Paudyal, Ramesh [2 ]
Hatzoglou, Vaios [3 ]
Lee, Nancy Y. [4 ]
Shukla-Dave, Amita [2 ,3 ]
Deasy, Joseph O. [2 ]
Tannenbaum, Allen [5 ]
机构
[1] SUNY Stony Brook, Appl Math & Stat, Stony Brook, NY 11794 USA
[2] Mem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10065 USA
[3] Mem Sloan Kettering Canc Ctr, Dept Radiol, 1275 York Ave, New York, NY 10021 USA
[4] Mem Sloan Kettering Canc Ctr, Dept Radiat Oncol, 1275 York Ave, New York, NY 10021 USA
[5] SUNY Stony Brook, Comp Sci & Appl Math & Stat, Stony Brook, NY 11794 USA
基金
美国国家卫生研究院;
关键词
advection; data-driven; DCE pharmacokinetic modeling; diffusion; optimal mass transport; CONTRAST-ENHANCED MRI; MONITOR TREATMENT RESPONSE; SQUAMOUS-CELL CARCINOMA; DISTANCE; BRAIN;
D O I
10.1002/mrm.27897
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
Purpose Current state-of-the-art models for estimating the pharmacokinetic parameters do not account for intervoxel movement of the contrast agent (CA). We introduce an optimal mass transport (OMT) formulation that naturally handles intervoxel CA movement and distinguishes between advective and diffusive flows. Method Ten patients with head and neck squamous cell carcinoma (HNSCC) were enrolled in the study between June 2014 and October 2015 and underwent DCE MRI imaging prior to beginning treatment. The CA tissue concentration information was taken as the input in the data-driven OMT model. The OMT approach was tested on HNSCC DCE data that provides quantitative information for forward flux (phi F) and backward flux (phi B). OMT-derived phi F was compared with the volume transfer constant for CA, Ktrans, derived from the Extended Tofts Model (ETM). Results The OMT-derived flows showed a consistent jump in the CA diffusive behavior across the images in accordance with the known CA dynamics. The mean forward flux was 0.0082 +/- 0.0091 (min-1) whereas the mean advective component was 0.0052 +/- 0.0086 (min-1) in the HNSCC patients. The diffusive percentages in forward and backward flux ranged from 8.67% to 18.76% and 12.76% to 30.36%, respectively. The OMT model accounts for intervoxel CA movement and results show that the forward flux (phi F) is comparable with the ETM-derived Ktrans. Conclusions This is a novel data-driven study based on optimal mass transport principles applied to patient DCE imaging to analyze CA flow in HNSCC.
引用
收藏
页码:2314 / 2325
页数:12
相关论文
共 50 条
  • [1] The Use of Dynamic Tracer Concentration in Veins for Quantitative DCE-MRI Kinetic Analysis in Head and Neck
    Yuan, Jing
    Chow, Steven Kwok Keung
    Zhang, Qinwei
    Yeung, David Ka Wai
    Ahuja, Anil T.
    King, Ann D.
    [J]. PLOS ONE, 2013, 8 (03):
  • [2] Influence of Parameterization on Tracer Kinetic Modeling in DCE-MRI
    Fusco, Roberta
    Sansone, Mario
    Petrillo, Mario
    Petrillo, Antonella
    [J]. JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING, 2014, 34 (02) : 157 - 163
  • [3] Comparison of DCE-MRI kinetic parameters and FMISO-PET uptake parameters in head and neck cancer patients
    Simoncic, Urban
    Leibfarth, Sara
    Welz, Stefan
    Schwenzer, Nina
    Schmidt, Holger
    Reischl, Gerald
    Pfannenberg, Christina
    la Fougere, Christian
    Nikolaou, Konstantin
    Zips, Daniel
    Thorwarth, Daniela
    [J]. MEDICAL PHYSICS, 2017, 44 (06) : 2358 - 2368
  • [4] Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) as a predictor of response in head and neck squamous cell carcinoma (HNSCC): Initial analysis
    Shukla-Dave, A.
    Lee, N.
    Wang, Y.
    Stambuk, H.
    Karinii, S.
    Shah, J. P.
    Pfister, D. G.
    Koutcher, J. A.
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2007, 69 (03): : S202 - S203
  • [5] CAD-System based on Kinetic Analysis for Non-Mass-Enhancing Lesions in DCE-MRI
    Goebl, Sebastian
    Plant, Claudia
    Lobbes, Marc
    Meyer-Baese, Anke
    [J]. INDEPENDENT COMPONENT ANALYSES, COMPRESSIVE SAMPLING, WAVELETS, NEURAL NET, BIOSYSTEMS, AND NANOENGINEERING XI, 2013, 8750
  • [6] A five-colour colour-coded mapping method for DCE-MRI analysis of head and neck tumours
    Yuan, J.
    Chow, S. K. K.
    Yeung, D. K. W.
    King, A. D.
    [J]. CLINICAL RADIOLOGY, 2012, 67 (03) : 216 - 223
  • [7] Quantification of Antiangiogenic and Antivascular Drug Activity by Kinetic Analysis of DCE-MRI Data
    Ferl, G. Z.
    Port, R. E.
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2012, 92 (01) : 118 - 124
  • [8] Characterizing fluid flows in breast tumor DCE-MRI studies using unbalanced regularized optimal mass transport methods
    Chen, Xinan
    Huang, Wei
    Tannenbaum, Allen R.
    Deasy, Joseph O.
    [J]. MEDICAL IMAGING 2024: IMAGE PROCESSING, 2024, 12926
  • [9] Quantitative evaluation of dual-flip-angle T-1 mapping on DCE-MRI kinetic parameter estimation in head and neck
    Yuan, Jing
    Chow, Steven Kwok Keung
    Yeung, David Ka Wai
    Ahuja, Anil T.
    King, Ann D.
    [J]. QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2012, 2 (04) : 245 - 253
  • [10] Histogram analysis parameters derived from DCE-MRI in head and neck squamous cell cancer - Associations with microvessel density
    Meyer, Hans-Jonas
    Hamerla, Gordian
    Leifels, Leonard
    Hoehn, Anne Kathrin
    Surov, Alexey
    [J]. EUROPEAN JOURNAL OF RADIOLOGY, 2019, 120