Feasibility study of clinical target volume definition for soft-tissue sarcoma using muscle fiber orientations derived from diffusion tensor imaging

被引:7
作者
Shusharina, Nadya [1 ,2 ]
Liu, Xiaofeng [2 ,3 ]
Coll-Font, Jaume [2 ,4 ,5 ]
Foster, Anna [4 ,5 ]
El Fakhri, Georges [2 ,3 ]
Woo, Jonghye [2 ,3 ]
Bortfeld, Thomas [1 ,2 ]
Nguyen, Christopher [2 ,4 ,5 ,6 ,7 ]
机构
[1] Massachusetts Gen Hosp, Div Radiat Biophys, Dept Radiat Oncol, Boston, MA 02114 USA
[2] Harvard Med Sch, Boston, MA 02114 USA
[3] Massachusetts Gen Hosp, Dept Radiol, Gordon Ctr Med Imaging, Boston, MA 02114 USA
[4] Massachusetts Gen Hosp, Cardiovasc Res Ctr, Charlestown, MA 02129 USA
[5] Massachusetts Gen Hosp, AA Martinos Ctr Biomed Imaging, Charlestown, MA 02129 USA
[6] MIT, Div Hlth Sci Technol, Cambridge, MA USA
[7] Cleveland Clin, Heart Vasc & Thorac Inst, Cardiovasc Innovat Res Ctr, Cleveland, OH USA
关键词
clinical target volume; soft-tissue sarcoma; diffusion weighted imaging; RADIOTHERAPY; VARIABILITY; EXTREMITY; TRACKING; IMAGES;
D O I
10.1088/1361-6560/ac8045
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective. Soft-tissue sarcoma spreads preferentially along muscle fibers. We explore the utility of deriving muscle fiber orientations from diffusion tensor MRI (DT-MRI) for defining the boundary of the clinical target volume (CTV) in muscle tissue. Approach. We recruited eight healthy volunteers to acquire MR images of the left and right thigh. The imaging session consisted of (a) two MRI spin-echo-based scans, T1- and T2-weighted; (b) a diffusion weighted (DW) spin-echo-based scan using an echo planar acquisition with fat suppression. The thigh muscles were auto-segmented using the convolutional neural network. DT-MRI data were used as a geometry encoding input to solve the anisotropic Eikonal equation with the Hamiltonian Fast-Marching method. The isosurfaces of the solution modeled the CTV boundary. Main results. The auto-segmented muscles of the thigh agreed with manually delineated with the Dice score ranging from 0.8 to 0.94 for different muscles. To validate our method of deriving muscle fiber orientations, we compared anisotropy of the isosurfaces across muscles with different anatomical orientations within a thigh, between muscles in the left and right thighs of each subject, and between different subjects. The fiber orientations were identified reproducibly across all comparisons. We identified two controlling parameters, the distance from the gross tumor volume to the isosurface and the eigenvalues ratio, to tailor the proposed CTV to the satisfaction of the clinician. Significance. Our feasibility study with healthy volunteers shows the promise of using muscle fiber orientations derived from DW MRI data for automated generation of anisotropic CTV boundary in soft tissue sarcoma. Our contribution is significant as it serves as a proof of principle for combining DT-MRI information with tumor spread modeling, in contrast to using moderately informative 2D CT planes for the CTV delineation. Such improvements will positively impact the cancer centers with a small volume of sarcoma patients.
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页数:10
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