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Introduction: Feature Issue on Optical Imaging and Spectroscopy

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Abstract

The editors introduce the Biomedical Optics Express feature issue, “Optical Imaging and Spectroscopy,” which was a technical area at the 2010 Optical Society of America (OSA), Biomedical Optics (BIOMED) Topical Meeting held on 11–14 April in Miami, Florida. The feature issue includes 23 contributions from conference attendees.

©2010 Optical Society of America

This feature issue of Biomedical Optics Express showcases contributions made to the 2010 Optical Society of America (OSA), Biomedical Optics (BIOMED) Topical Meeting held on 11 – 14 April in Miami, Florida. It focuses on the technical area of Optical Imaging and Spectroscopy, which was chaired by Arjun Yodh, Univ. of Pennsylvania. More than 60 papers were presented in 9 sessions that covered topics such as Cancer Imaging and Monitoring, Brain Imaging and Monitoring, Imaging and Spectroscopy Theory, Clinical Application of Imaging and Clinical Applications of Diffuse Optics.

For this feature issue 23 papers were selected that represent a cross-section of topics covered at this conference. Papers that deal with theoretical aspects of diffuse optical tomography (DOT) continue to have a major presence at this topical meeting and hence 8 manuscripts address the latest developments in this area. Both Srinivasan et al. [1] and Fan et al. [2] focus on issues related to combining optical tomographic imaging methods with other imaging modalities; an approach that has gained increasing interest in recent years. Tarvainen et al. [3] and Tian et al. [4] propose methods that correct linear image reconstruction approaches. In their papers they demonstrate how errors introduced by the linearization can be reduced, while maintaining the speed advantage that linear reconstruction methods offer over more complex non-linear algorithms. Also addressing the speed of the DOT reconstruction, Montejo et al. [5] and Kim et al. [6] introduce novel ways on how to solve the equation of radiative transfer and the related inverse problem in an economical fashion. An increasing number of groups study now the use of spatially modulated light for DOT. D’Andrea et al. [7] shows how this approach can be used to reduce the computation times in DOT. Finally Jacques et al. [8] introduces a novel approach for rapid spectral analysis for spectral imaging.

The BIOMED meeting has also always been a forum to present novel experimental methods and instruments for tissue diagnostics. Within this feature issue a total of 9 papers fall into this category. Erickson et al. [9] present a general-purpose hand-held optical fluorescence imager that provides co-registration facilities. Their system allows to image different tissue volumes and curvatures in near real-time. Another system that allows to rapidly acquire fluorescence wavelength-time matrices of biological tissues is introduced by Lloyd et al. [10]. Sun et al. [11] focus in their work on the software aspects of a high-speed, multispectral in-vivo optical imaging system that make use of commercially available scientific cameras. Qui et al. [12] discuss the potential of gold nanorods as labels for differential light scattering measurements for the detection of human disease through several centimeters of tissue. Looking for ways to improve current systems for sentinel lymph node detection, Tellier et al. [13] explore in their paper a new near-infrared optical probe based on the recording of scattered photons. Robles et al. [14] investigate the ability to measure tissue hemoglobin concentration and oxygen saturation levels using spectroscopic optical coherence tomography. They characterize their system by analyzing data obtained from oxygenated and deoxygenated hemoglobin phantoms. A more complex tissue phantom that enables EEG and near-infrared optical tomography to be performed simultaneously over the same volume is described by Cooper et al. [15]. In a study by Wood et al. [16], the polarization properties of two commercial laparoscopes were characterized and found to exhibit birefringence effects. The authors conclude that this complicates endoscopic polarization imaging, which, in recent years, has been found to reveal diagnostic information about tissue morphology. In an impressive comprehensive work, Venugopal et al. [17] describe the design and characterization of a time-resolved small animal imager that is based on a wide-field excitation scheme. They show that their system can be used for whole-body molecular and functional imaging.

Pre-Clinical and Clinical Applications are the focus of 4 papers. Using a rodent model for stepped hypercapnia, Carp et al. [18] measured cerebral blood flow (CBF) with near-infrared diffuse correlation spectroscopy (DCS) and arterial spin labeling MRI (ASL), simultaneously. They found that DCS and ASL CBF values show a high correlation. Chen et al. [19] report on a study of the spatial and spectral dependence of the optical signals induced by stimulation of the human median and sural nerves. In a companion paper by the same group of researchers, Erb et al. [20] focuses on the contribution of non-artifactual vascular motion induced by muscle contraction to the biological origin of the same signal. The influence of muscle fiber motion during exercise on diffuse correlation spectroscopy (DCS) measurements of skeletal muscle blood flow is explored by Shang et al. [21].

Leaving the realm of tissue imaging, two final studies address issues related to imaging of sub-cellular structures and function. Antkowiak et al. [22] study the quantitative phase of the dynamic cellular response in femtosecond laser photoporation and Pasternack et al. [23] elucidate the effects of two-dimensional Gabor filters on the quantification of sub-cellular dynamics in apoptotic cells.

References and links

1. S. Srinivasan, H. R. Ghadyani, B. W. Pogue, and K. D. Paulsen, “A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging,” Biomed. Opt. Express 1(2), 398–413 (2010). [CrossRef]  

2. Q. Fang, R. H. Moore, D. B. Kopans, and D. A. Boas, “Compositional-prior-guided image reconstruction algorithm for multi-modality imaging,” Biomed. Opt. Express 1(1), 223–235 (2010). [CrossRef]  

3. T. Tarvainen, V. Kolehmainen, J. P. Kaipio, and S. R. Arridge, “Corrections to linear methods for diffuse optical tomography using approximation error modeling,” Biomed. Opt. Express 1(1), 209–222 (2010). [CrossRef]  

4. F. Tian, H. Niu, S. Khadka, Z.-J. Lin, and H. Liu, “Algorithmic depth compensation improves quantification and noise suppression in functional diffuse optical tomography,” Biomed. Opt. Express 1(2), 441–452 (2010). [CrossRef]  

5. L. D. Montejo, A. D. Klose, and A. H. Hielscher, “Implementation of the equation of radiative transfer on block-structured grids for modeling light propagation in tissue,” Biomed. Opt. Express 1(3), 861–878 (2010). [CrossRef]  

6. H. K. Kim, M. Flexman, D. J. Yamashiro, J. J. Kandel, and A. H. Hielscher, “PDE-constrained multispectral imaging of tissue chromophores with the equation of radiative transfer,” Biomed. Opt. Express 1(3), 812–824 (2010). [CrossRef]  

7. C. D’Andrea, N. Ducros, A. Bassi, S. Arridge, and G. Valentini, “Fast 3D optical reconstruction in turbid media using spatially modulated light,” Biomed. Opt. Express 1(2), 471–481 (2010). [CrossRef]  

8. S. L. Jacques, R. Samatham, and N. Choudhury, “Rapid spectral analysis for spectral imaging,” Biomed. Opt. Express 1(1), 157–164 (2010). [CrossRef]  

9. S. J. Erickson, S. L. Martinez, J. Gonzalez, L. Caldera, and A. Godavarty, “Improved detection limits using a hand-held optical imager with coregistration capabilities,” Biomed. Opt. Express 1(1), 126–134 (2010). [CrossRef]  

10. W. R. Lloyd, R. H. Wilson, C.-W. Chang, G. D. Gillispie, and M.-A. Mycek, “Instrumentation to rapidly acquire fluorescence wavelength-time matrices of biological tissues,” Biomed. Opt. Express 1(2), 574–586 (2010). [CrossRef]  

11. R. Sun, M. B. Bouchard, and E. M. C. Hillman, “SPLASSH: Open source software for camera-based high-speed, multispectral in-vivo optical image acquisition,” Biomed. Opt. Express 1(2), 385–397 (2010). [CrossRef]  

12. L. Qiu, T. A. Larson, E. Vitkin, L. Guo, E. B. Hanlon, I. Itzkan, K. V. Sokolov, and L. T. Perelman, “Gold nanorod light scattering labels for biomedical imaging,” Biomed. Opt. Express 1(1), 135–142 (2010). [CrossRef]  

13. F. Tellier, R. Ravelo, H. Simon, R. Chabrier, J. Steibel, and P. Poulet, “Sentinel lymph node detection by an optical method using scattered photons,” Biomed. Opt. Express 1(3), 902–910 (2010). [CrossRef]  

14. F. E. Robles, S. Chowdhury, and A. Wax, “Assessing hemoglobin concentration using spectroscopic optical coherence tomography for feasibility of tissue diagnostics,” Biomed. Opt. Express 1(1), 310–317 (2010). [CrossRef]  

15. R. J. Cooper, R. Eames, J. Brunker, L. C. Enfield, A. P. Gibson, and J. C. Hebden, “A tissue equivalent phantom for simultaneous near-infrared optical tomography and EEG,” Biomed. Opt. Express 1(2), 425–430 (2010). [CrossRef]  

16. T. C. Wood and D. S. Elson, “Polarization response measurement and simulation of rigid endoscopes,” Biomed. Opt. Express 1(2), 463–470 (2010). [CrossRef]  

17. V. Venugopal, J. Chen, and X. Intes, “Development of an optical imaging platform for functional imaging of small animals using wide-field excitation,” Biomed. Opt. Express 1(1), 143–156 (2010). [CrossRef]  

18. S. A. Carp, G. P. Dai, D. A. Boas, M. A. Franceschini, and Y. R. Kim, “Validation of diffuse correlation spectroscopy measurements of rodent cerebral blood flow with simultaneous arterial spin labeling MRI; towards MRI-optical continuous cerebral metabolic monitoring,” Biomed. Opt. Express 1(2), 553–565 (2010). [CrossRef]  

19. D. K. Chen, M. K. Erb, Y. Tong, Y. Yu, A. Sassaroli, P. R. Bergethon, and S. Fantini, “Spectral and spatial dependence of diffuse optical signals in response to peripheral nerve stimulation,” Biomed. Opt. Express 1(3), 923–942 (2010). [CrossRef]  

20. M. K. Erb, D. K. Chen, A. Sassaroli, S. Fantini, and P. R. Bergethon, “Diffuse optical signals in response to peripheral nerve stimulation reflect skeletal muscle kinematics,” Biomed. Opt. Express 1(3), 943–954 (2010). [CrossRef]  

21. Yu. Shang, T. B. Symons, T. Durduran, A. G. Yodh, and G. Yu, “Effects of muscle fiber motion on diffuse correlation spectroscopy blood flow measurements during exercise,” Biomed. Opt. Express 1(2), 500–511 (2010). [CrossRef]  

22. M. Antkowiak, M. L. Torres-Mapa, K. Dholakia, and F. J. Gunn-Moore, “Quantitative phase study of the dynamic cellular response in femtosecond laser photoporation,” Biomed. Opt. Express 1(2), 414–424 (2010). [CrossRef]  

23. R. M. Pasternack, B. Rabin, J.-Y. Zheng, and N. N. Boustany, “Quantifying subcellular dynamics in apoptotic cells with two-dimensional Gabor filters,” Biomed. Opt. Express 1(2), 720–728 (2010) (Invited). [CrossRef]  

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