Incorporating MRI structural information into bioluminescence tomography: system, heterogeneous reconstruction and in vivo quantification

Zhang, Jun; Chen, Duofang; Liang, Jimin; Xue, Huadan; Lei, Jing; Wang, Qin; Chen, Dongmei; Meng, Ming; Jin, Zhengyu; Hui, Hui

doi:10.1364/boe.5.001861

Cited by 23 publications

(12 citation statements)

References 54 publications

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“…A fusion of both BLT and MRI has the potential to compensate for the shortcomings of each method. One approach to fuse BLI/BLT images with other imaging modalities has been to use the coregistered information in an attempt to improve BLT reconstruction accuracy ( 28 – 31 ) or validate BLT results ( 32 ). While a growing body of work has examined the coregistration of BLI and MRI in these feasibility studies, an underdeveloped area is the application of coregistered BLT in preclinical or discovery research ( 33 , 34 ).…”

Section: Introductionmentioning

confidence: 99%

Co-Registration of Bioluminescence Tomography, Computed Tomography, and Magnetic Resonance Imaging for Multimodal In Vivo Stem Cell Tracking

2016

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We present a practical approach for coregistration of bioluminescence tomography (BLT), computed tomography (CT), and magnetic resonance (MR) images. For this, we developed a customized animal shuttle composed of nonfluorescent, MR-compatible Delrin plastic that fits a commercially available MR surface coil. Mouse embryonic stem cells were transfected with the luciferase gene and labeled with superparamagnetic iron oxide nanoparticles. Cells were stereotaxically implanted in the mouse brain and imaged weekly for 4 weeks with bioluminescent imaging (IVIS Spectrum CT scanner) and magnetic resonance imaging (MRI; 11.7 T horizontal bore scanner). Without the use of software coregistration, in vitro phantom studies yielded root-mean-square errors of 7.6 × 10−3, 0.93 mm, and 0.78 mm along the medial–lateral (ML), dorsal–ventral (DV), and anterior–posterior (AP) axes, respectively. Rotation errors were negligible. Software coregistration by translation along the DV and AP axes resulted in consistent agreement between the CT and MR images, without the need for rotation or warping. In vivo coregistered BLT/MRI mouse brain data sets showed a single diffuse region of bioluminescent imaging photon signal and MRI hypointensity. Over time, the transplanted cells formed tumors as histopathologically validated. Disagreement between BLT and MRI tumor location was greatest along the DV axis (1.4 ± 0.2 mm) than along the ML (0.5 ± 0.3 mm) and the AP axes (0.6 mm) because of the uncertainty of the depth of origin of the BLT signal. Combining the high spatial anatomical information of MRI with the cell viability/proliferation data from BLT should facilitate preclinical evaluation of novel therapeutic candidate stem cells.

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Section: Introductionmentioning

confidence: 99%

Co-Registration of Bioluminescence Tomography, Computed Tomography, and Magnetic Resonance Imaging for Multimodal In Vivo Stem Cell Tracking

2016

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“…31 and 32) or MRI. 33,34 The CT or MRI images can be segmented into different organs which are then assigned corresponding optical property values. Consequently, the anatomical and optical information obtained from CT or MRI serves as a prior knowledge for the BLT reconstruction.…”

Section: Discussionmentioning

confidence: 99%

Systematic calibration of an integrated x‐ray and optical tomography system for preclinical radiation research

et al. 2015

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Purpose: The cone beam computed tomography (CBCT) guided small animal radiation research platform (SARRP) has been developed for focal tumor irradiation, allowing laboratory researchers to test basic biological hypotheses that can modify radiotherapy outcomes in ways that were not feasible previously. CBCT provides excellent bone to soft tissue contrast, but is incapable of differentiating tumors from surrounding soft tissue. Bioluminescence tomography (BLT), in contrast, allows direct visualization of even subpalpable tumors and quantitative evaluation of tumor response. Integration of BLT with CBCT offers complementary image information, with CBCT delineating anatomic structures and BLT differentiating luminescent tumors. This study is to develop a systematic method to calibrate an integrated CBCT and BLT imaging system which can be adopted onboard the SARRP to guide focal tumor irradiation. Methods: The integrated imaging system consists of CBCT, diffuse optical tomography (DOT), and BLT. The anatomy acquired from CBCT and optical properties acquired from DOT serve as a priori information for the subsequent BLT reconstruction. Phantoms were designed and procedures were developed to calibrate the CBCT, DOT/BLT, and the entire integrated system. Geometrical calibration was performed to calibrate the CBCT system. Flat field correction was performed to correct the nonuniform response of the optical imaging system. Absolute emittance calibration was performed to convert the camera readout to the emittance at the phantom or animal surface, which enabled the direct reconstruction of the bioluminescence source strength. Phantom and mouse imaging were performed to validate the calibration. Results: All calibration procedures were successfully performed. Both CBCT of a thin wire and a euthanized mouse revealed no spatial artifact, validating the accuracy of the CBCT calibration. The absolute emittance calibration was validated with a 650 nm laser source, resulting in a 3.0% difference between simulated and measured signal. The calibration of the entire system was confirmed through the CBCT and BLT reconstruction of a bioluminescence source placed inside a tissue-simulating optical phantom. Using a spatial region constraint, the source position was reconstructed with less than 1 mm error and the source strength reconstructed with less than 24% error. Conclusions: A practical and systematic method has been developed to calibrate an integrated x-ray and optical tomography imaging system, including the respective CBCT and optical tomography system calibration and the geometrical calibration of the entire system. The method can be modified and adopted to calibrate CBCT and optical tomography systems that are operated independently or hybrid x-ray and optical tomography imaging systems. C 2015 American Association of Physicists in Medicine. [http://dx

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“…The relative intensity error can accurately reveal the intensity error between the actual source and the reconstructed one in the actual region and can be seen as a combination of the relative error of the power density and the measurement of overlapped region, both of which are used to reflect the real reconstruction performance in [35]. The smaller intensity error can indicate the better quantitative reconstruction results.…”

Section: Evaluation Standardmentioning

confidence: 99%

X-ray luminescence computed tomography imaging based on X-ray distribution model and adaptively split Bregman method

Chen

Zhu

Cao

et al. 2015

Biomed. Opt. Express

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Abstract:X-ray luminescence computed tomography (XLCT) has become a promising imaging technology for biological application based on phosphor nanoparticles. There are mainly three kinds of XLCT imaging systems: pencil beam XLCT, narrow beam XLCT and cone beam XLCT. Narrow beam XLCT can be regarded as a balance between the pencil beam mode and the cone-beam mode in terms of imaging efficiency and image quality. The collimated X-ray beams are assumed to be parallel ones in the traditional narrow beam XLCT. However, we observe that the cone beam X-rays are collimated into X-ray beams with fan-shaped broadening instead of parallel ones in our prototype narrow beam XLCT. Hence we incorporate the distribution of the X-ray beams in the physical model and collected the optical data from only two perpendicular directions to further speed up the scanning time. Meanwhile we propose a depth related adaptive regularized split Bregman (DARSB) method in reconstruction. The simulation experiments show that the proposed physical model and method can achieve better results in the location error, dice coefficient, mean square error and the intensity error than the traditional split Bregman method and validate the feasibility of method. The phantom experiment can obtain the location error less than 1.1 mm and validate that the incorporation of fan-shaped X-ray beams in our model can achieve better results than the parallel X-rays. Yang, and J. Tian, "A trust region method in adaptive finite element framework for bioluminescence tomography," Opt. Express 18(7), 6477-6491 (2010). 34. L. R. Dice, "Measures of the amount of ecologic association between species," Ecology 26(3), 297-302 (1945). 35. J. Zhang, D. Chen, J. Liang, H. Xue, J. Lei, Q. Wang, D. Chen, M. Meng, Z. Jin, and J. Tian, "Incorporating mri structural information into bioluminescence tomography: system, heterogeneous reconstruction and in vivo quantification," Biomed.

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Incorporating MRI structural information into bioluminescence tomography: system, heterogeneous reconstruction and in vivo quantification

Cited by 23 publications

References 54 publications

Co-Registration of Bioluminescence Tomography, Computed Tomography, and Magnetic Resonance Imaging for Multimodal In Vivo Stem Cell Tracking

Co-Registration of Bioluminescence Tomography, Computed Tomography, and Magnetic Resonance Imaging for Multimodal In Vivo Stem Cell Tracking

Systematic calibration of an integrated x‐ray and optical tomography system for preclinical radiation research

X-ray luminescence computed tomography imaging based on X-ray distribution model and adaptively split Bregman method

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