Image-based modeling of tumor shrinkage in head and neck radiation therapy.
OBJECTIVE
Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases.


METHODS
Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique.


RESULTS
The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the "ground truth" with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%.


CONCLUSIONS
An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.
Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847, USA. mchao@uams.edu
Ming
M
Chao
Yaoqin
Y
Xie
Eduardo G
EG
Moros
Quynh-Thu
QT
Le
Lei
L
Xing
D054893:Cone-Beam Computed Tomography; D003952:Diagnostic Imaging; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology* / Q000532:radiotherapy*; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D019047:Phantoms, Imaging; D012984:Software; D047368:Tumor Burden