<i>In vivo</i>water state measurements in breast cancer using broadband diffuse optical spectroscopy

Chung, Sukmin; Cerussi, Albert E.; Klifa, Catherine; Baek, Hyeon‐Man; Birgül, Özlem; Gülşen, Gültekin; Merritt, Sean; Hsiang, David; Tromberg, Bruce J.

doi:10.1088/0031-9155/53/23/005

Cited by 116 publications

(113 citation statements)

References 70 publications

(111 reference statements)

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“…18 Previous reports using diffuse optical spectroscopy have suggested that malignant tumors have reduced lipid (∼20%) and increased water (>50%) contents compared to normal breast tissue. [19][20][21][22] In addition, other reports suggest a positive correlation between increased tissue water content and carcinogenesis. 23 Although the water content in benign lesions may vary significantly depending on the type of lesions, 24 the quantitative information of lesion composition can be used to improve the positive predictive value for cancer detection.…”

Section: Introductionmentioning

confidence: 99%

Breast tissue decomposition with spectral distortion correction: A postmortem study

et al. 2014

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Purpose: To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections. Methods: Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results. Results: The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections. Conclusions:The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique. C 2014 American Association of Physicists in Medicine. [http://dx

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Section: Introductionmentioning

confidence: 99%

Breast tissue decomposition with spectral distortion correction: A postmortem study

et al. 2014

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“…4 Leff et al 5 recently reviewed DOT breast tumor contrasts in Hb t and StO 2 . Some disagreements remain in the diffuse optics community about which optically measured parameters are the most important indicators of malignancy; recent work, for example, on water 6 and collagen 7 has opened up additional possibilities.…”

Section: Introduction Ia Diffuse Optics and Automated Cancer Diamentioning

confidence: 99%

Computer aided automatic detection of malignant lesions in diffuse optical mammography

et al. 2010

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Purpose:Computer aided detection ͑CAD͒ data analysis procedures are introduced and applied to derive composite diffuse optical tomography ͑DOT͒ signatures of malignancy in human breast tissue. In contrast to previous optical mammography analysis schemes, the new statistical approach utilizes optical property distributions across multiple subjects and across the many voxels of each subject. The methodology is tested in a population of 35 biopsy-confirmed malignant lesions. Methods: DOT CAD employs multiparameter, multivoxel, multisubject measurements to derive a simple function that transforms DOT images of tissue chromophores and scattering into a probability of malignancy tomogram. The formalism incorporates both intrasubject spatial heterogeneity and intersubject distributions of physiological properties derived from a population of cancercontaining breasts ͑the training set͒. A weighted combination of physiological parameters from the training set define a malignancy parameter ͑M͒, with the weighting factors optimized by logistic regression to separate training-set cancer voxels from training-set healthy voxels. The utility of M is examined, employing 3D DOT images from an additional subjects ͑the test set͒. Results: Initial results confirm that the automated technique can produce tomograms that distinguish healthy from malignant tissue. When compared to a gold standard tissue segmentation, this protocol produced an average true positive rate ͑sensitivity͒ of 89% and a true negative rate ͑speci-ficity͒ of 94% using an empirically chosen probability threshold. Conclusions: This study suggests that the automated multisubject, multivoxel, multiparameter statistical analysis of diffuse optical data is potentially quite useful, producing tomograms that distinguish healthy from malignant tissue. This type of data analysis may also prove useful for suppression of image artifacts.

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“…Both the transmitted light (transmission or transillumination spectroscopy) and the diffusely reflected radiation (reflectance or backscattering spectroscopy) are detected. [179,199,200,203,204,211] techniques. The near IR spectroscopy makes use of the same principles and the same methods of data recording, as the modern optical imaging methods, based on the detection of diffusely scattered light, and in this sense is their direct predecessor.…”

Section: Methods Based On the Detection Of Diffusely Scattered Lightmentioning

confidence: 99%

Diffuse optical mammotomography: state-of-the-art and prospects

Konovalov

Genina

Bashkatov

2016

JBPE

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Abstract:The principles of diffuse optical tomography (DOT) of tissues are presented. The DOT capabilities as a method of breast cancer diagnostics are analysed. The state-ofthe-art of the DOT instrumentation and methodological base in application to solving the mammography problems are described. The significant contribution of Russian scientists to the development of the DOT methodology is emphasised. Basing on the results of the analysis, the authors expect the possibility of soonest entry of diffuse optical mammotomographs to the market of medical imaging instrumentation, and the capability of Russian researchers to take part in the competition for this market. © 2016 Journal of Biomedical Photonics & Engineering.Key words: diffuse optical tomography, breast, optical and functional parameters, methods of determining optical parameters, methods of image reconstruction, perturbation model of reconstruction, temporal point spread function, spatial resolution, reconstruction time. University Press, Cambridge (2016). 7. S. R. Arridge, and M. Schweiger, "Inverse methods for optical tomography," in Information Processing in Medical Imaging, H.H. Barrett (ed.), Springer-Verlag, Flagstaff, 259-277 (1993). 8. J. C. Hebden, S. R. Arridge, and D. T. Delpy, "Optical imaging in medicine: I. Experimental techniques,"Phys. Med. Biol. 42, 825-840 (1997). 9. S. R. Arridge, and J. C. Hebden, "Optical imaging in medicine: II. Modelling and reconstruction," Phys. Med. Biol. 42, 841-853 (1997). 10. B. B. Das, F. Liu, and R. R. Alfano, "Time-resolved fluorescence and photon migration studies in biomedical and random media," Rep. Prog. Phys. 60, 227-292 (1997). 11. K. Michielsen, H. De'Raedt, J. Przeslawski, and N. Garcia, "Computer simulation of time-resolved optical imaging of objects hidden in turbid media," Phys. Rep. 304, 89-144 (1998). 12. S. R. Arridge, "Optical tomography in medical imaging," Inverse Problems 15, R41-R93 (1999). Darzi, "Diffuse optical imaging of the healthy and diseased breast: a systematic review," Breast Cancer Research and Treatment 108, 9-22 (2008). 19. S. L. Jacques, and B. W. Pogue, "Tutorial on diffuse light transport," J. Biomed. Opt. 13, 041302 (2008 Biol. 361, 171-179 (1994). 31. A. Yodh, and B. Chance, "Spectroscopy and imaging with diffusing light," Phys. Today 48, 34-40 (1995). 32. J. C. Hebden, S. R. Arridge, "Imaging through scattering media by the use of an analytical model of perturbation amplitudes in the time domain," Appl. Opt. 35, 6788-6796 (1996). 33. K. D. Paulsen, and H. Jiang, "Enhanced frequency-domain optical image reconstruction in tissues through total-variation minimization," Appl. Opt. 35, 3447-3458 (1996). 34. R. J. Grable, "Optical tomography improves mammography," Laser Focus World 32, 113-118 (1996). 35. V. V. Lyubimov, "The physical foundation of the strongly scattering media laser tomography," Proc. SPIE 2769SPIE , 107-110 (1996. 36. V. V. Lyubimov, "Optical tomography of highly scattering media by using the first transmitted photons of ultrashort pulses," Optics a...

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In vivowater state measurements in breast cancer using broadband diffuse optical spectroscopy

Cited by 116 publications

References 70 publications

Breast tissue decomposition with spectral distortion correction: A postmortem study

Breast tissue decomposition with spectral distortion correction: A postmortem study

Computer aided automatic detection of malignant lesions in diffuse optical mammography

Diffuse optical mammotomography: state-of-the-art and prospects

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