Self-guided reconstruction for time-domain fluorescence molecular lifetime tomography

Chuangjian Cai; Wenjuan Cai; Jiaju Cheng; Yuxuan Yang; Jianwen Luo

doi:10.1117/1.JBO.21.12.126012

21 December 2016 Self-guided reconstruction for time-domain fluorescence molecular lifetime tomography

Chuangjian Cai, Wenjuan Cai, Jiaju Cheng, Yuxuan Yang, Jianwen Luo

Author Affiliations +

Journal of Biomedical Optics, Vol. 21, Issue 12, 126012 (December 2016). https://doi.org/10.1117/1.JBO.21.12.126012

Abstract

Fluorescence probes have distinct yields and lifetimes when located in different environments, which makes the reconstruction of fluorescence molecular lifetime tomography (FMLT) challenging. To enhance the reconstruction performance of time-domain (TD) FMLT with heterogeneous targets, a self-guided L1 regularization projected steepest descent (SGL1PSD) algorithm is proposed. Different from other algorithms performed in time domain, SGL1PSD introduces a time-resolved strategy into fluorescence yield reconstruction. The algorithm consists of four steps. Step 1 reconstructs the initial yield map with full time gate strategy; steps 2–4 reconstruct the inverse lifetime map, the yield map, and the inverse lifetime map again with time-resolved strategy, respectively. The reconstruction result of each step is used as a priori for the reconstruction of the next step. Projected iterated Tikhonov regularization algorithm is adopted for the yield map reconstructions in steps 1 and 3 to provide a solution with iterative refinement and nonnegative constraint. The inverse lifetime map reconstructions in steps 2 and 4 are based on L1 regularization projected steepest descent algorithm, which employ the L1 regularization to reduce the ill-posedness of the high-dimensional nonlinear problem. Phantom experiments with heterogeneous targets at different edge-to-edge distances demonstrate that SGL1PSD can provide high resolution and quantification accuracy for TD FMLT.

References

1.

E. M. Sevick-Muraca et al., “Fluorescence-enhanced, near infrared diagnostic imaging with contrast agents,” Curr. Opin. Chem. Biol., 6 (5), 642 –650 (2002). http://dx.doi.org/10.1016/S1367-5931(02)00356-3 COCBF4 1367-5931 Google Scholar

2.

A. B. Milstein et al., “Fluorescence optical diffusion tomography,” Appl. Opt., 42 (16), 3081 –3094 (2003). http://dx.doi.org/10.1364/AO.42.003081 APOPAI 0003-6935 Google Scholar

3.

V. Ntziachristos et al., “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol., 23 (3), 313 –320 (2005). http://dx.doi.org/10.1038/nbt1074 NABIF9 1087-0156 Google Scholar

4.

J. K. Willmann et al., “Molecular imaging in drug development,” Nat. Rev. Drug Discovery, 7 (7), 591 –607 (2008). http://dx.doi.org/10.1038/nrd2290 NRDDAG 1474-1776 Google Scholar

5.

V. Ntziachristos et al., “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med., 8 (7), 757 –761 (2002). http://dx.doi.org/10.1038/nm729 1078-8956 Google Scholar

6.

J. Lee et al., “Three-dimensional fluorescence enhanced optical tomography using referenced frequency-domain photon migration measurements at emission and excitation wavelengths,” J. Opt. Soc. Am. A, 19 (4), 759 –771 (2002). http://dx.doi.org/10.1364/JOSAA.19.000759 JOAOD6 0740-3232 Google Scholar

7.

R. Roy et al., “Tomographic fluorescence imaging in tissue phantoms: a novel reconstruction algorithm and imaging geometry,” IEEE Trans. Med. Imaging, 24 (2), 137 –154 (2005). http://dx.doi.org/10.1109/TMI.2004.839359 ITMID4 0278-0062 Google Scholar

8.

V. Y. Soloviev et al., “Fluorescence lifetime imaging by using time-gated data acquisition,” Appl. Opt., 46 (30), 7384 –7391 (2007). http://dx.doi.org/10.1364/AO.46.007384 APOPAI 0003-6935 Google Scholar

9.

S. V. Patwardhan et al., “Quantitative diffuse optical tomography for small animals using an ultrafast gated image intensifier,” J. Biomed. Opt., 13 (1), 011009 (2008). http://dx.doi.org/10.1117/1.2830656 JBOPFO 1083-3668 Google Scholar

10.

M. Brambilla et al., “Time-resolved scanning system for double reflectance and transmittance fluorescence imaging of diffusive media,” Rev. Sci. Instrum., 79 (1), 013103 (2008). http://dx.doi.org/10.1063/1.2828054 RSINAK 0034-6748 Google Scholar

11.

M. A. O’Leary et al., “Fluorescence lifetime imaging in turbid media,” Opt. Lett., 21 (2), 158 –160 (1996). http://dx.doi.org/10.1364/OL.21.000158 OPLEDP 0146-9592 Google Scholar

12.

J. McGinty et al., “In vivo fluorescence lifetime tomography of a FRET probe expressed in mouse,” Biomed. Opt. Express, 2 (7), 1907 –1917 (2011). http://dx.doi.org/10.1364/BOE.2.001907 BOEICL 2156-7085 Google Scholar

13.

S. S. Hou et al., “Tomographic lifetime imaging using combined early-and late-arriving photons,” Opt. Lett., 39 (5), 1165 –1168 (2014). http://dx.doi.org/10.1364/OL.39.001165 OPLEDP 0146-9592 Google Scholar

14.

W. L. Rice et al., “Resolution below the point spread function for diffuse optical imaging using fluorescence lifetime multiplexing,” Opt. Lett., 38 (12), 2038 –2040 (2013). http://dx.doi.org/10.1364/OL.38.002038 OPLEDP 0146-9592 Google Scholar

15.

R. E. Nothdurft et al., “In vivo fluorescence lifetime tomography,” J. Biomed. Opt., 14 (2), 024004 (2009). http://dx.doi.org/10.1117/1.3086607 JBOPFO 1083-3668 Google Scholar

16.

L. Zhang et al., “Three-dimensional scheme for time-domain fluorescence molecular tomography based on Laplace transforms with noise-robust factors,” Opt. Express, 16 (10), 7214 –7223 (2008). http://dx.doi.org/10.1364/OE.16.007214 OPEXFF 1094-4087 Google Scholar

17.

F. Gao et al., “Simultaneous fluorescence yield and lifetime tomography from time-resolved transmittances of small-animal-sized phantom,” Appl. Opt., 49 (16), 3163 –3172 (2010). http://dx.doi.org/10.1364/AO.49.003163 APOPAI 0003-6935 Google Scholar

18.

C. Cai et al., “Direct reconstruction method for time-domain fluorescence molecular lifetime tomography,” Opt. Lett., 40 (17), 4038 –4041 (2015). http://dx.doi.org/10.1364/OL.40.004038 OPLEDP 0146-9592 Google Scholar

19.

C. Cai et al., “Nonlinear greedy sparsity-constrained algorithm for direct reconstruction of fluorescence molecular lifetime tomography,” Biomed. Opt. Express, 7 (4), 1210 –1226 (2016). http://dx.doi.org/10.1364/BOE.7.001210 BOEICL 2156-7085 Google Scholar

20.

F. Gao et al., “A self-normalized, full time-resolved method for fluorescence diffuse optical tomography,” Opt. Express, 16 (17), 13104 –13121 (2008). http://dx.doi.org/10.1364/OE.16.013104 OPEXFF 1094-4087 Google Scholar

21.

C. Qin et al., “Galerkin-based meshless methods for photon transport in the biological tissue,” Opt. Express, 16 (25), 20317 –20333 (2008). http://dx.doi.org/10.1364/OE.16.020317 OPEXFF 1094-4087 Google Scholar

22.

B. Zhang et al., “Early-photon fluorescence tomography of a heterogeneous mouse model with the telegraph equation,” Appl. Opt., 50 (28), 5397 –5407 (2011). http://dx.doi.org/10.1364/AO.50.005397 APOPAI 0003-6935 Google Scholar

23.

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl., 15 (2), R41 (1999). http://dx.doi.org/10.1088/0266-5611/15/2/022 INPEEY 0266-5611 Google Scholar

24.

A. Neumaier, “Solving ill-conditioned and singular linear systems: a tutorial on regularization,” SIAM Rev., 40 (3), 636 –666 (1998). http://dx.doi.org/10.1137/S0036144597321909 SIREAD 0036-1445 Google Scholar

25.

H. Lee et al., “Fluorescence lifetime properties of near-infrared cyanine dyes in relation to their structures,” J. Photochem. Photobiol., A, 200 (2), 438 –444 (2008). http://dx.doi.org/10.1016/j.jphotochem.2008.09.008 JPPCEJ 1010-6030 Google Scholar

26.

H. Pu et al., “Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis,” Phys. Med. Biol., 59 (17), 5025 –5042 (2014). http://dx.doi.org/10.1088/0031-9155/59/17/5025 PHMBA7 0031-9155 Google Scholar

27.

M. Y. Berezin et al., “Long fluorescence lifetime molecular probes based on near infrared pyrrolopyrrole cyanine fluorophores for in vivo imaging,” Biophys. J., 97 (9), L22 –L24 (2009). http://dx.doi.org/10.1016/j.bpj.2009.08.022 BIOJAU 0006-3495 Google Scholar

28.

J. Chamorro-Servent et al., “Feasibility of U-curve method to select the regularization parameter for fluorescence diffuse optical tomography in phantom and small animal studies,” Opt. Express, 19 (12), 11490 –11506 (2011). http://dx.doi.org/10.1364/OE.19.011490 OPEXFF 1094-4087 Google Scholar

Citation Download Citation

Chuangjian Cai, Wenjuan Cai, Jiaju Cheng, Yuxuan Yang, and Jianwen Luo "Self-guided reconstruction for time-domain fluorescence molecular lifetime tomography," Journal of Biomedical Optics 21(12), 126012 (21 December 2016). https://doi.org/10.1117/1.JBO.21.12.126012

Received: 11 September 2016; Accepted: 30 November 2016; Published: 21 December 2016

Access the abstract

JOURNAL ARTICLE
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY