Hybrid light transport model based bioluminescence tomography reconstruction for early gastric cancer detection

Gastric cancer is the second cause of cancer-related death in the world, and it remains difficult to cure because it has been in late-stage once that is found. Early gastric cancer detection becomes an effective approach to decrease the gastric cancer mortality. Bioluminescence tomography (BLT) has been applied to detect early liver cancer and prostate cancer metastasis. However, the gastric cancer commonly originates from the gastric mucosa and grows outwards. The bioluminescent light will pass through a non-scattering region constructed by gastric pouch when it transports in tissues. Thus, the current BLT reconstruction algorithms based on the approximation model of radiative transfer equation are not optimal to handle this problem. To address the gastric cancer specific problem, this paper presents a novel reconstruction algorithm that uses a hybrid light transport model to describe the bioluminescent light propagation in tissues. The radiosity theory integrated with the diffusion equation to form the hybrid light transport model is utilized to describe light propagation in the non-scattering region. After the finite element discretization, the hybrid light transport model is converted into a minimization problem which fuses an l1 norm based regularization term to reveal the sparsity of bioluminescent source distribution. The performance of the reconstruction algorithm is first demonstrated with a digital mouse based simulation with the reconstruction error less than 1mm. An in situ gastric cancer-bearing nude mouse based experiment is then conducted. The primary result reveals the ability of the novel BLT reconstruction algorithm in early gastric cancer detection.

[1]  Xin Yang,et al.  Dual-Modality Monitoring of Tumor Response to Cyclophosphamide Therapy in Mice with Bioluminescence Imaging and Small-Animal Positron Emission Tomography , 2011, Molecular imaging.

[2]  Xiaochao Qu,et al.  3D reconstruction of light flux distribution on arbitrary surfaces from 2D multi-photographic images. , 2010, Optics express.

[3]  P. Tsao,et al.  In Vivo Bioluminescence Imaging of Inducible Nitric Oxide Synthase Gene Expression in Vascular Inflammation , 2011, Molecular Imaging and Biology.

[4]  W. Han,et al.  Recent Development in Bioluminescence Tomography , 2006 .

[5]  R. Leahy,et al.  Digimouse: a 3D whole body mouse atlas from CT and cryosection data , 2007, Physics in medicine and biology.

[6]  Ge Wang,et al.  A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method. , 2004, Academic radiology.

[7]  Zhenhua Hu,et al.  Source sparsity based primal-dual interior-point method for three-dimensional bioluminescence tomography , 2011 .

[8]  Jimin Liang,et al.  Real-time bioluminescence and tomographic imaging of gastric cancer in a novel orthotopic mouse model. , 2012, Oncology reports.

[9]  A. Chatziioannou,et al.  Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study , 2005, Physics in medicine and biology.

[10]  Jae Hoon Lee,et al.  Modeling of diffuse-diffuse photon coupling via a nonscattering region: a comparative study. , 2004, Applied optics.

[11]  E. Hoffman,et al.  In vivo mouse studies with bioluminescence tomography. , 2006, Optics express.

[12]  Vasilis Ntziachristos,et al.  Looking and listening to light: the evolution of whole-body photonic imaging , 2005, Nature Biotechnology.

[13]  Christopher H. Contag,et al.  In vivo imaging using bioluminescence: a tool for probing graft-versus-host disease , 2006, Nature Reviews Immunology.

[14]  Jie Tian,et al.  Multimodality Molecular Imaging , 2008, IEEE Engineering in Medicine and Biology Magazine.

[15]  Geoffrey McLennan,et al.  Practical reconstruction method for bioluminescence tomography. , 2005, Optics express.

[16]  Jie Tian,et al.  In vivo quantitative bioluminescence tomography using heterogeneous and homogeneous mouse models. , 2010, Optics express.

[17]  A. Jemal,et al.  Global Cancer Statistics , 2011 .

[18]  Jie Tian,et al.  GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues. , 2010, Optics express.

[19]  Jie Tian,et al.  Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method. , 2010, Optics express.

[20]  Hamid Dehghani,et al.  In vivo bioluminescence tomography with a blocking-off finite-difference SP3 method and MRI/CT coregistration. , 2009, Medical physics.