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Handbook of Photonics for Biomedical Engineering pp 179–220Cite as

Monitoring Cancer Therapy with Diffuse Optical Methods

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Abstract

This review focuses on noninvasive monitoring of the therapeutic responses of tumors via assessment of tumor vascular and hemodynamic parameters. The diffuse optical techniques provide a promising means for noninvasive imaging of deep tissues. During the last few years, researchers have focused on developing diffuse optical techniques to provide complementary information with multiple parameters. These techniques permit real-time, noninvasive quantification of tissue hemoglobin concentration, blood oxygen saturation, blood flow, and drug concentration in vivo. Multiparameter approach increases sensitivity and specificity along with providing a more complete picture of physiological mechanisms and ultimately prediction of the response. The instrumentation is portable and rapid, and it has enabled the study of tissue responses in a variety of settings of monitoring cancer treatments in preclinical and clinical settings.

After presenting the niche for the diffuse optical methods in the Introduction section, the basic principles of photon propagation in tissue will be provided in section “Theoretical Background.” After several instrumentation, examples will be presented in section “Instruments,” preclinical applications will be provided in section “Preclinical Applications.” In preclinical cases, examples of antivascular therapy and photodynamic therapy (PDT) in small animals will be provided. The effects of an antivascular drug, combretastatin, were monitored continuously and were found to induce substantial reduction of blood flow and tissue oxygen. The observations of blood flow and oxygenation were then correlated with power Doppler ultrasound and hypoxia biomarker techniques, respectively. Then PDT fluence rate effects on skin and head and neck cancer models for superficial and deep tissue imaging are provided. As clinical applications in section “Clinical Applications,” PDT and chemoradiation monitoring in patients with head and neck cancer and chemotherapy monitoring in breast cancer patients will be presented. Pilot studies revealed that early changes in diffuse optical parameters correlate well with the end-point clinical responses. Total hemoglobin concentration, blood oxygen saturation, blood flow, and drug consumption during treatment showed variable sensitivity to the therapy for different individuals, thus emphasizing the need for simultaneous monitoring of multiple tissue parameters for individualized treatment planning.

This book chapter was invited by Professor Donghyun Kim.

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References

  1. McCarthy K, Pearson K, Fulton R, Hewitt J (2012) Pre-operative chemoradiation for non-metastatic locally advanced rectal cancer. Cochrane Database Syst Rev 12, CD008368

    Google Scholar 

  2. Rydzewska L, Tierney J, Vale CL, Symonds PR (2012) Neoadjuvant chemotherapy plus surgery versus surgery for cervical cancer. Cochrane Database Syst Rev 12, CD007406

    Google Scholar 

  3. Ueda S, Roblyer D, Cerussi A et al (2012) Baseline tumor oxygen saturation correlates with a pathologic complete response in breast cancer patients undergoing neoadjuvant chemotherapy. Cancer Res 72:4318–4328

    Article  Google Scholar 

  4. Garland ML, Vather R, Bunkley N et al (2014) Clinical tumour size and nodal status predict pathologic complete response following neoadjuvant chemoradiotherapy for rectal cancer. Int J Colorectal Dis 29:301–307

    Article  Google Scholar 

  5. Jiang S, Pogue BW, Kaufman PA et al (2014) Predicting breast tumor response to neoadjuvant chemotherapy with diffuse optical spectroscopic tomography prior to treatment. Clin Cancer Res 20:6006–6015

    Article  Google Scholar 

  6. Vaupel P, Kallinowski F, Okunieff P (1989) Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res 49:6449–6465

    Google Scholar 

  7. Tromberg BJ, Pogue BW, Paulsen KD et al (2008) Assessing the future of diffuse optical imaging technologies for breast cancer management. Med Phys 35:2443–2451

    Article  Google Scholar 

  8. Lehtio K, Eskola O, Viljanen T et al (2004) Imaging perfusion and hypoxia with PET to predict radiotherapy response in head-and-neck cancer. Int J Radiat Oncol Biol Phys 59:971–982

    Article  Google Scholar 

  9. Jacobson O, Chen X (2013) Interrogating tumor metabolism and tumor microenvironments using molecular positron emission tomography imaging. Theranostic approaches to improve therapeutics. Pharmacol Rev 65:1214–1256

    Article  Google Scholar 

  10. DeVries AF, Kremser C, Hein PA et al (2003) Tumor microcirculation and diffusion predict therapy outcome for primary rectal carcinoma. Int J Radiat Oncol Biol Phys 56:958–965

    Article  Google Scholar 

  11. Hermans R, Lambin P, Van der Goten A et al (1999) Tumoural perfusion as measured by dynamic computed tomography in head and neck carcinoma. Radiother Oncol 53:105–111

    Article  Google Scholar 

  12. Preda L, Calloni SF, Moscatelli ME et al (2014) Role of CT perfusion in monitoring and prediction of response to therapy of head and neck squamous cell carcinoma. Biomed Res Int 2014:917150

    Article  Google Scholar 

  13. Anderson H, Price P, Blomley M et al (2001) Measuring changes in human tumour vasculature in response to therapy using functional imaging techniques. Br J Cancer 85:1085–1093

    Article  Google Scholar 

  14. Pirhonen JP, Grenman SA, Bredbacka AB et al (1995) Effects of external radiotherapy on uterine blood flow in patients with advanced cervical carcinoma assessed by color Doppler ultrasonography. Cancer 76:67–71

    Article  Google Scholar 

  15. Chen B, Pogue BW, Goodwin IA et al (2003) Blood flow dynamics after photodynamic therapy with verteporfin in the RIF-1 tumor. Radiat Res 160:452–459

    Article  Google Scholar 

  16. Huilgol NG, Khan MM, Puniyani R (1995) Capillary perfusion – a study in two groups of radiated patients for cancer of head and neck. Indian J Cancer 32:59–62

    Google Scholar 

  17. Goertz DE, Yu JL, Kerbel RS et al (2002) High-frequency Doppler ultrasound monitors the effects of antivascular therapy on tumor blood flow. Cancer Res 62:6371–6375

    Google Scholar 

  18. Stone HB, Brown JM, Phillips TL, Sutherland RM (1993) Oxygen in human tumors: correlations between methods of measurement and response to therapy. Summary of a workshop held November 19–20, 1992, at the National Cancer Institute, Bethesda, Maryland. Radiat Res 136:422–434

    Article  Google Scholar 

  19. Sunar U, Rohrbach D, Rigual N et al (2010) Monitoring photobleaching and hemodynamic responses to HPPH-mediated photodynamic therapy of head and neck cancer: a case report. Opt Express 18:14969–14978

    Article  Google Scholar 

  20. Cerussi A, Hsiang D, Shah N et al (2007) Predicting response to breast cancer neoadjuvant chemotherapy using diffuse optical spectroscopy. Proc Natl Acad Sci U S A 104:4014–4019

    Article  Google Scholar 

  21. Cutler M (1929) Transillumination of the breast. Surg Gynecol Obstet 48:721–727

    Google Scholar 

  22. Jobsis FF (1977) Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science 198:1264–1267

    Article  Google Scholar 

  23. Bank W, Chance B (1997) Diagnosis of defects in oxidative muscle metabolism by non-invasive tissue oximetry. Mol Cell Biochem 174:7–10

    Article  Google Scholar 

  24. Jacques SL (1996) Origins of tissue optical properties in the UVA, visible, and NIR regions. In: Advances in optical imaging and photon migration. OSA trends in optics and photonics, vol 2, pp 364–371

    Google Scholar 

  25. Mourant JR, Freyer JP, Hielscher AH et al (1998) Mechanisms of light scattering from biological cells relevant to noninvasive optical-tissue diagnostics. Appl Opt 37:3586–3593

    Article  Google Scholar 

  26. Mourant JR, Fuselier T, Boyer J et al (1997) Predictions and measurements of scattering and absorption over broad wavelength ranges in tissue phantoms. Appl Opt 36:949–957

    Article  Google Scholar 

  27. Laughney AM, Krishnaswamy V, Rizzo EJ et al (2012) Scatter spectroscopic imaging distinguishes between breast pathologies in tissues relevant to surgical margin assessment. Clin Cancer Res 18:6315–6325

    Article  Google Scholar 

  28. Cheung C, Culver JP, Takahashi K et al (2001) In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies. Phys Med Biol 46:2053–2065

    Article  Google Scholar 

  29. Boas DA, Campbell LE, Yodh AG (1995) Scattering and imaging with diffusing temporal field correlations. Phys Rev Lett 75:1855–1858

    Article  Google Scholar 

  30. Boas DA, Yodh AG (1997) Spatially varying dynamical properties of turbid media probed with diffusing temporal light correlation. J Opt Soc Am A 14:192–215

    Article  Google Scholar 

  31. Bussink J, Kaanders JH, Rijken PF et al (2000) Changes in blood perfusion and hypoxia after irradiation of a human squamous cell carcinoma xenograft tumor line. Radiat Res 153:398–404

    Article  Google Scholar 

  32. Fenton BM, Lord EM, Paoni SF (2001) Effects of radiation on tumor intravascular oxygenation, vascular configuration, development of hypoxia, and clonogenic survival. Radiat Res 155:360–368

    Article  Google Scholar 

  33. Busch TM (2006) Local physiological changes during photodynamic therapy. Lasers Surg Med 38:494–499

    Article  Google Scholar 

  34. Busch TM (2010) Hypoxia and perfusion labeling during photodynamic therapy. Methods Mol Biol 635:107–120

    Article  Google Scholar 

  35. Gibbs-Strauss SL, O’Hara JA, Hoopes PJ et al (2009) Noninvasive measurement of aminolevulinic acid-induced protoporphyrin IX fluorescence allowing detection of murine glioma in vivo. J Biomed Opt 14:014007

    Article  Google Scholar 

  36. Rollakanti KR, Kanick SC, Davis SC et al (2013) Techniques for fluorescence detection of protoporphyrin IX in skin cancers associated with photodynamic therapy. Photonics Lasers Med 2:287–303

    Article  Google Scholar 

  37. Warren CB, Lohser S, Wene LC et al (2010) Noninvasive fluorescence monitoring of protoporphyrin IX production and clinical outcomes in actinic keratoses following short-contact application of 5-aminolevulinate. J Biomed Opt 15:051607

    Article  Google Scholar 

  38. Cerussi AE, Tanamai VW, Mehta RS et al (2010) Frequent optical imaging during breast cancer neoadjuvant chemotherapy reveals dynamic tumor physiology in an individual patient. Acad Radiol 17:1031–1039

    Article  Google Scholar 

  39. Jakubowski DB, Cerussi AE, Bevilacqua F et al (2004) Monitoring neoadjuvant chemotherapy in breast cancer using quantitative diffuse optical spectroscopy: a case study. J Biomed Opt 9:230–238

    Article  Google Scholar 

  40. Vishwanath K, Klein D, Chang K et al (2009) Quantitative optical spectroscopy can identify long-term local tumor control in irradiated murine head and neck xenografts. J Biomed Opt 14:054051

    Article  Google Scholar 

  41. Yu G, Durduran T, Zhou C et al (2006) Real-time in situ monitoring of human prostate photodynamic therapy with diffuse light. Photochem Photobiol 82:1279–1284

    Article  Google Scholar 

  42. Yodh AG, Boas DA (2003) Functional imaging with diffusing light. In: Vo-Dinh T (ed) Biomedical diagnostics. CRC Press, Boca Raton, Florida, pp 311–356

    Google Scholar 

  43. Boas DA (1996) Diffuse photon probes of structural and dynamical properties of turbid media: theory and biomedical applications. University of Pennsylvania, Philadelphia

    Google Scholar 

  44. O’Leary MA (1996) Imaging with diffuse photon density waves. In: Physics and astronomy. University of Pennsylvania, Philadelphia

    Google Scholar 

  45. Haskell RC, Svaasand LO, Tsay TT et al (1994) Boundary conditions for the diffusion equation in radiative transfer. J Opt Soc Am A Opt Image Sci Vis 11:2727–2741

    Article  Google Scholar 

  46. Kienle A, Patterson MS (1997) Improved solutions of the steady-state and the time-resolved diffusion equations for reflectance from a semi-infinite turbid medium. J. Opt. Soc.Am.A Opt. Image Sci. Vis 14:246–254

    Google Scholar 

  47. Tseng SH, Bargo P, Durkin A, Kollias N (2009) Chromophore concentrations, absorption and scattering properties of human skin in-vivo. Opt Express 17:14599–14617

    Article  Google Scholar 

  48. Bard MP, Amelink A, Skurichina M et al (2006) Optical spectroscopy for the classification of malignant lesions of the bronchial tree. Chest 129:995–1001

    Article  Google Scholar 

  49. Gamm UA, Kanick SC, Sterenborg HJ et al (2011) Measurement of tissue scattering properties using multi-diameter single fiber reflectance spectroscopy: in silico sensitivity analysis. Biomed Opt Express 2:3150–3166

    Article  Google Scholar 

  50. Kanick SC, Gamm UA, Schouten M et al (2011) Measurement of the reduced scattering coefficient of turbid media using single fiber reflectance spectroscopy: fiber diameter and phase function dependence. Biomed Opt Express 2:1687–1702

    Article  Google Scholar 

  51. Middelburg TA, Kanick SC, de Haas ER et al (2011) Monitoring blood volume and saturation using superficial fibre optic reflectance spectroscopy during PDT of actinic keratosis. J Biophotonics 4:721–730

    Article  Google Scholar 

  52. Finlay JC, Foster TH (2004) Hemoglobin oxygen saturations in phantoms and in vivo from measurements of steady-state diffuse reflectance at a single, short source-detector separation. Med Phys 31:1949–1959

    Article  Google Scholar 

  53. Hull EL, Nichols MG, Foster TH (1998) Quantitative broadband near-infrared spectroscopy of tissue-simulating phantoms containing erythrocytes. Phys Med Biol 43:3381–3404

    Article  Google Scholar 

  54. Brown W (1993) Dynamic light scattering: the method and some applications. Oxford University Press, Oxford, England

    Google Scholar 

  55. Berne BJ, Pecora R (1990) Dynamic light scattering: with applications to chemistry, biology, and physics. R.E. Krieger, Malabar

    Google Scholar 

  56. Pine DJ, Weitz DA, Chaikin PM, Herbolzheimer E (1988) Diffusing wave spectroscopy. Phys Rev Lett 60:1134–1137

    Article  Google Scholar 

  57. Mesquita RC, Durduran T, Yu G et al (2011) Direct measurement of tissue blood flow and metabolism with diffuse optics. Philos Trans A Math Phys Eng Sci 369:4390–4406

    Article  MathSciNet  MATH  Google Scholar 

  58. Yu G, Durduran T, Zhou C et al (2011) Near-infrared diffuse correlation spectroscopy (DCS) for assessment of tissue blood flow. In: Boas DA, Pitris C, Ramanujam N (eds) Handbook of biomedical optics. Taylor & Francis Books, Florence, Kentucky, pp 195–216

    Google Scholar 

  59. Sunar U, Quon H, Durduran T et al (2006) Noninvasive diffuse optical measurement of blood flow and blood oxygenation for monitoring radiation therapy in patients with head and neck tumors: a pilot study. J Biomed Opt 11:064021

    Article  Google Scholar 

  60. Sunar U, Makonnen S, Zhou C et al (2007) Hemodynamic responses to antivascular therapy and ionizing radiation assessed by diffuse optical spectroscopies. Opt Express 15:15507–15516

    Article  Google Scholar 

  61. Durduran T, Choe R, Baker WB, Yodh AG (2010) Diffuse optics for tissue monitoring and tomography. Rep Prog Phys 73:43

    Article  Google Scholar 

  62. Carp SA, Dai GP, Boas DA et al (2010) 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 1:553–565

    Article  Google Scholar 

  63. Culver JP, Durduran T, Furuya D et al (2003) Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia. J Cereb Blood Flow Metab 23:911–924

    Article  Google Scholar 

  64. Li J, Dietsche G, Iftime D et al (2005) Noninvasive detection of functional brain activity with near-infrared diffusing-wave spectroscopy. J Biomed Opt 10:44002

    Article  Google Scholar 

  65. de Visscher SA, Witjes MJ, van der Vegt B et al (2013) Localization of liposomal mTHPC formulations within normal epithelium, dysplastic tissue, and carcinoma of oral epithelium in the 4NQO-carcinogenesis rat model. Lasers Surg Med 45:668–678

    Article  Google Scholar 

  66. van Leeuwen-van Zaane F, van Driel PB, Gamm UA et al (2014) Microscopic analysis of the localization of two chlorin-based photosensitizers in OSC19 tumors in the mouse oral cavity. Lasers Surg Med 46:224–234

    Article  Google Scholar 

  67. Ramanujam N (2000) Fluorescence spectroscopy of neoplastic and non-neoplastic tissues. Neoplasia 2:89–117

    Article  Google Scholar 

  68. Kasischke KA, Lambert EM, Panepento B et al (2011) Two-photon NADH imaging exposes boundaries of oxygen diffusion in cortical vascular supply regions. J Cereb Blood Flow Metab 31:68–81

    Article  Google Scholar 

  69. Manjunath BK, Kurein J, Rao L et al (2004) Autofluorescence of oral tissue for optical pathology in oral malignancy. J Photochem Photobiol B 73:49–58

    Article  Google Scholar 

  70. Brancaleon L, Durkin AJ, Tu JH et al (2001) In vivo fluorescence spectroscopy of nonmelanoma skin cancer. Photochem Photobiol 73:178–183

    Article  Google Scholar 

  71. Bogaards A, Sterenborg HJ, Wilson B (2007) In vivo quantification of fluorescent molecular markers in real-time: a review to evaluate the performance of five existing methods. Photodiagnosis Photodynamic Ther 4:170–178

    Article  Google Scholar 

  72. Fisher CJ, Niu CJ, Lai B et al (2013) Modulation of PPIX synthesis and accumulation in various normal and glioma cell lines by modification of the cellular signaling and temperature. Lasers Surg Med 45:460–468

    Article  Google Scholar 

  73. Casas A, Fukuda H, Meiss R, Batlle AM (1999) Topical and intratumoral photodynamic therapy with 5-aminolevulinic acid in a subcutaneous murine mammary adenocarcinoma. Cancer Lett 141:29–38

    Article  Google Scholar 

  74. Johansson J, Berg R, Svanberg K, Svanberg S (1997) Laser-induced fluorescence studies of normal and malignant tumour tissue of rat following intravenous injection of delta-amino levulinic acid. Lasers Surg Med 20:272–279

    Article  Google Scholar 

  75. Kobuchi H, Moriya K, Ogino T et al (2012) Mitochondrial localization of ABC transporter ABCG2 and its function in 5-aminolevulinic acid-mediated protoporphyrin IX accumulation. PLoS One 7, e50082

    Article  Google Scholar 

  76. Korbelik M, Krosl G (1995) Accumulation of benzoporphyrin derivative in malignant and host cell populations of the murine RIF tumor. Cancer Lett 97:249–254

    Article  Google Scholar 

  77. Korbelik M, Krosl G (1995) Photofrin accumulation in malignant and host cell populations of a murine fibrosarcoma. Photochem Photobiol 62:162–168

    Article  Google Scholar 

  78. Millon SR, Ostrander JH, Yazdanfar S et al (2010) Preferential accumulation of 5-aminolevulinic acid-induced protoporphyrin IX in breast cancer: a comprehensive study on six breast cell lines with varying phenotypes. J Biomed Opt 15:018002

    Article  Google Scholar 

  79. Saczko J, Mazurkiewicz M, Chwilkowska A et al (2007) Intracellular distribution of Photofrin in malignant and normal endothelial cell lines. Folia Biol (Praha) 53:7–12

    Google Scholar 

  80. Uekusa M, Omura K, Nakajima Y et al (2010) Uptake and kinetics of 5-aminolevulinic acid in oral squamous cell carcinoma. Int J Oral Maxillofac Surg 39:802–805

    Article  Google Scholar 

  81. Wang C, Chen X, Wu J et al (2013) Low-dose arsenic trioxide enhances 5-aminolevulinic acid-induced PpIX accumulation and efficacy of photodynamic therapy in human glioma. J Photochem Photobiol B 127:61–67

    Article  Google Scholar 

  82. Zaak D, Sroka R, Khoder W et al (2008) Photodynamic diagnosis of prostate cancer using 5-aminolevulinic acid – first clinical experiences. Urology 72:345–348

    Article  Google Scholar 

  83. Bellnier DA, Greco WR, Loewen GM et al (2003) Population pharmacokinetics of the photodynamic therapy agent 2-[1-hexyloxyethyl]-2-devinyl pyropheophorbide-a in cancer patients. Cancer Res 63:1806–1813

    Google Scholar 

  84. Sunar U, Rohrbach D, Morgan J et al (2013) Quantification of PpIX concentration in basal cell carcinoma and squamous cell carcinoma models using spatial frequency domain imaging. Biomed Opt Express 4:531–537

    Article  Google Scholar 

  85. Saager RB, Cuccia DJ, Saggese S et al (2011) Quantitative fluorescence imaging of protoporphyrin IX through determination of tissue optical properties in the spatial frequency domain. J Biomed Opt 16:126013

    Article  Google Scholar 

  86. O’Leary MA, Boas DA, Li XD et al (1996) Fluorescence lifetime imaging in turbid media. Opt Lett 21:158–160

    Article  Google Scholar 

  87. Gardner CM, Jacques SL, Welch AJ (1996) Fluorescence spectroscopy of tissue: recovery of intrinsic fluorescence from measured fluorescence. Appl Opt 35:1780–1792

    Article  Google Scholar 

  88. Welch AJ, Gardner C, Richards-Kortum R et al (1997) Propagation of fluorescent light. Lasers Surg Med 21:166–178

    Article  Google Scholar 

  89. Kanick SC, Davis SC, Zhao Y et al (2014) Dual-channel red/blue fluorescence dosimetry with broadband reflectance spectroscopic correction measures protoporphyrin IX production during photodynamic therapy of actinic keratosis. J Biomed Opt 19:75002

    Article  Google Scholar 

  90. Finlay JC, Conover DL, Hull EL, Foster TH (2001) Porphyrin bleaching and PDT-induced spectral changes are irradiance dependent in ALA-sensitized normal rat skin in vivo. Photochem Photobiol 73:54–63

    Article  Google Scholar 

  91. Montan S, Svanberg K, Svanberg S (1985) Multicolor imaging and contrast enhancement in cancer-tumor localization using laser-induced fluorescence in hematoporphyrin-derivative-bearing tissue. Opt Lett 10:56–58

    Article  Google Scholar 

  92. Sterenborg HJ, Saarnak AE, Frank R, Motamedi M (1996) Evaluation of spectral correction techniques for fluorescence measurements on pigmented lesions in vivo. J Photochem Photobiol B 35:159–165

    Article  Google Scholar 

  93. Pogue BW, Burke G (1998) Fiber-optic bundle design for quantitative fluorescence measurement from tissue. Appl Opt 37:7429–7436

    Article  Google Scholar 

  94. Busch DR, Guo W, Choe R et al (2010) Computer aided automatic detection of malignant lesions in diffuse optical mammography. Med Phys 37:1840–1849

    Article  Google Scholar 

  95. Choe R, Yodh A (2008) Diffuse optical tomography of the breast. In: Suri J, Rangayyan R, Laxminarayan S (eds) Emerging technology in breast imaging and mammography. American Scientific Publishers, Valencia, California, pp 317–342

    Google Scholar 

  96. Culver JP, Ntziachristos V, Holboke MJ, Yodh AG (2001) Optimization of optode arrangements for diffuse optical tomography: a singular-value analysis. Opt Lett 26:701–703

    Article  Google Scholar 

  97. Gu X, Zhang Q, Bartlett M et al (2004) Differentiation of cysts from solid tumors in the breast with diffuse optical tomography. Acad Radiol 11:53–60

    Article  Google Scholar 

  98. Herve L, Koenig A, Da Silva A et al (2007) Noncontact fluorescence diffuse optical tomography of heterogeneous media. Appl Opt 46:4896–4906

    Article  Google Scholar 

  99. Ntziachristos V, Hielscher AH, Yodh AG, Chance B (2001) Diffuse optical tomography of highly heterogeneous media. IEEE Trans Med Imaging 20:470–478

    Article  Google Scholar 

  100. Pogue BW, Davis SC, Song X et al (2006) Image analysis methods for diffuse optical tomography. J Biomed Opt 11(3):33001

    Google Scholar 

  101. Srinivasan S, Pogue BW, Dehghani H et al (2004) Improved quantification of small objects in near-infrared diffuse optical tomography. J Biomed Opt 9:1161–1171

    Article  Google Scholar 

  102. Konecky SD, Panasyuk GY, Lee K et al (2008) Imaging complex structures with diffuse light. Opt Express 16:5048–5060

    Article  Google Scholar 

  103. Gridelli C, Rossi A, Maione P et al (2009) Vascular disrupting agents: a novel mechanism of action in the battle against non-small cell lung cancer. Oncologist 14:612–620

    Article  Google Scholar 

  104. Kim S, Peshkin L, Mitchison TJ (2012) Vascular disrupting agent drug classes differ in effects on the cytoskeleton. PLoS One 7, e40177

    Article  Google Scholar 

  105. Tozer GM (2003) Measuring tumour vascular response to antivascular and antiangiogenic drugs. Br J Radiol 76(Spec No 1):S23–S35

    Article  MathSciNet  Google Scholar 

  106. Rossi A, Maione P, Ferrara ML et al (2009) Angiogenesis inhibitors and vascular disrupting agents in non-small cell lung cancer. Curr Med Chem 16:3919–3930

    Article  Google Scholar 

  107. Ding X, Zhang Z, Li S, Wang A (2011) Combretastatin A4 phosphate induces programmed cell death in vascular endothelial cells. Oncol Res 19:303–309

    Article  Google Scholar 

  108. Greene LM, O’Boyle NM, Nolan DP et al (2012) The vascular targeting agent Combretastatin-A4 directly induces autophagy in adenocarcinoma-derived colon cancer cells. Biochem Pharmacol 84:612–624

    Article  Google Scholar 

  109. Li J, Cona MM, Chen F et al (2013) Sequential systemic administrations of combretastatin A4 Phosphate and radioiodinated hypericin exert synergistic targeted theranostic effects with prolonged survival on SCID mice carrying bifocal tumor xenografts. Theranostics 3:127–137

    Article  Google Scholar 

  110. Kessel D, Oleinick NL (2010) Photodynamic therapy and cell death pathways. Methods Mol Biol 635:35–46

    Article  Google Scholar 

  111. Dougherty TJ, Gomer CJ, Henderson BW et al (1998) Photodynamic therapy. J Natl Cancer Inst 90:889–905

    Article  Google Scholar 

  112. Wilson BC, Patterson MS (2008) The physics, biophysics and technology of photodynamic therapy. Phys Med Biol 53:R61–R109

    Article  Google Scholar 

  113. Zhu TC, Finlay JC (2008) The role of photodynamic therapy (PDT) physics. Med Phys 35:3127–3136

    Article  Google Scholar 

  114. Maas AL, Carter SL, Wileyto EP et al (2012) Tumor vascular microenvironment determines responsiveness to photodynamic therapy. Cancer Res 72:2079–2088

    Article  Google Scholar 

  115. Chen B, Pogue BW, Zhou X et al (2005) Effect of tumor host microenvironment on photodynamic therapy in a rat prostate tumor model. Clin Cancer Res 11:720–727

    Google Scholar 

  116. Foster TH, Murant RS, Bryant RG et al (1991) Oxygen consumption and diffusion effects in photodynamic therapy. Radiat Res 126:296–303

    Article  Google Scholar 

  117. Zhou X, Pogue BW, Chen B et al (2006) Pretreatment photosensitizer dosimetry reduces variation in tumor response. Int J Radiat Oncol Biol Phys 64:1211–1220

    Article  Google Scholar 

  118. Wilson BC, Patterson MS, Lilge L (1997) Implicit and explicit dosimetry in photodynamic therapy:a new paradigm. Lasers Med Sci 12:182–199

    Article  Google Scholar 

  119. Sheng C, Hoopes PJ, Hasan T, Pogue BW (2007) Photobleaching-based dosimetry predicts deposited dose in ALA-PpIX PDT of rodent esophagus. Photochem Photobiol 83:738–748

    Article  Google Scholar 

  120. Sunar U (2013) Monitoring photodynamic therapy of head and neck malignancies with optical spectroscopies. World J Clin Cases 1:96–105

    Article  Google Scholar 

  121. Rogers HW, Weinstock MA, Harris AR et al (2010) Incidence estimate of nonmelanoma skin cancer in the United States, 2006. Arch Dermatol 146:283–287

    Article  Google Scholar 

  122. Goldberg LH, Landau JM, Moody MN et al (2012) Evaluation of the chemopreventative effects of ALA PDT in patients with multiple actinic keratoses and a history of skin cancer. J Drugs Dermatol 11:593–597

    Google Scholar 

  123. Lehmann P (2007) Methyl aminolaevulinate-photodynamic therapy: a review of clinical trials in the treatment of actinic keratoses and nonmelanoma skin cancer. Br J Dermatol 156:793–801

    Article  Google Scholar 

  124. Biel M (2006) Advances in photodynamic therapy for the treatment of head and neck cancers. Lasers Surg Med 38:349–355

    Article  Google Scholar 

  125. Biel MA (2010) Photodynamic therapy of head and neck cancers. Methods Mol Biol 635:281–293

    Article  Google Scholar 

  126. D’Cruz AK, Robinson MH, Biel MA (2004) mTHPC-mediated photodynamic therapy in patients with advanced, incurable head and neck cancer: a multicenter study of 128 patients. Head Neck 26:232–240

    Article  Google Scholar 

  127. Quon H, Finlay J, Cengel K et al (2011) Transoral robotic photodynamic therapy for the oropharynx. Photodiagnosis Photodyn Ther 8:64–67

    Article  Google Scholar 

  128. Quon H, Grossman CE, Finlay JC et al (2011) Photodynamic therapy in the management of pre-malignant head and neck mucosal dysplasia and microinvasive carcinoma. Photodiagnosis Photodyn Ther 8:75–85

    Article  Google Scholar 

  129. Rigual NR, Thankappan K, Cooper M et al (2009) Photodynamic therapy for head and neck dysplasia and cancer. Arch Otolaryngol Head Neck Surg 135:784–788

    Article  Google Scholar 

  130. Jerjes W, Hamdoon Z, Hopper C (2012) Photodynamic therapy in the management of potentially malignant and malignant oral disorders. Head Neck Oncol 4:16

    Article  Google Scholar 

  131. Jerjes W, Upile T, Betz CS et al (2007) The application of photodynamic therapy in the head and neck. Dent Update 34:478–480, 483–474, 486

    Google Scholar 

  132. Baran TM, Wilson JD, Mitra S et al (2012) Optical property measurements establish the feasibility of photodynamic therapy as a minimally invasive intervention for tumors of the kidney. J Biomed Opt 17:98002-1

    Article  Google Scholar 

  133. Johansson A, Axelsson J, Andersson-Engels S, Swartling J (2007) Realtime light dosimetry software tools for interstitial photodynamic therapy of the human prostate. Med Phys 34:4309–4321

    Article  Google Scholar 

  134. Oakley E, Wrazen B, Bellnier DA et al (2015) A new finite element approach for near real-time simulation of light propagation in locally advanced head and neck tumors. Lasers Surg Med 47:60–67

    Article  Google Scholar 

  135. Rendon A, Beck JC, Lilge L (2008) Treatment planning using tailored and standard cylindrical light diffusers for photodynamic therapy of the prostate. Phys Med Biol 53:1131–1149

    Article  Google Scholar 

  136. Thompson MS, Johansson A, Johansson T et al (2005) Clinical system for interstitial photodynamic therapy with combined on-line dosimetry measurements. Appl Opt 44:4023–4031

    Article  Google Scholar 

  137. Kruijt B, van der Ploeg-van den Heuvel A, de Bruijn HS et al (2009) Monitoring interstitial m-THPC-PDT in vivo using fluorescence and reflectance spectroscopy. Lasers Surg Med 41:653–664

    Article  Google Scholar 

  138. Samkoe KS, Chen A, Rizvi I et al (2010) Imaging tumor variation in response to photodynamic therapy in pancreatic cancer xenograft models. Int J Radiat Oncol Biol Phys 76:251–259

    Article  Google Scholar 

  139. Becker TL, Paquette AD, Keymel KR et al (2010) Monitoring blood flow responses during topical ALA-PDT. Biomed Opt Express 2:123–130

    Article  Google Scholar 

  140. Busch TM, Wang HW, Wileyto EP et al (2010) Increasing damage to tumor blood vessels during motexafin lutetium-PDT through use of low fluence rate. Radiat Res 174:331–340

    Article  Google Scholar 

  141. Busch TM, Wileyto EP, Emanuele MJ et al (2002) Photodynamic therapy creates fluence rate-dependent gradients in the intratumoral spatial distribution of oxygen. Cancer Res 62:7273–7279

    Google Scholar 

  142. Ericson MB, Sandberg C, Stenquist B et al (2004) Photodynamic therapy of actinic keratosis at varying fluence rates: assessment of photobleaching, pain and primary clinical outcome. Br J Dermatol 151:1204–1212

    Article  Google Scholar 

  143. Henderson BW, Busch TM, Snyder JW (2006) Fluence rate as a modulator of PDT mechanisms. Lasers Surg Med 38:489–493

    Article  Google Scholar 

  144. Sitnik TM, Hampton JA, Henderson BW (1998) Reduction of tumour oxygenation during and after photodynamic therapy in vivo: effects of fluence rate. Br J Cancer 77:1386–1394

    Article  Google Scholar 

  145. Sitnik TM, Henderson BW (1998) The effect of fluence rate on tumor and normal tissue responses to photodynamic therapy. Photochem Photobiol 67:462–466

    Article  Google Scholar 

  146. Henderson BW, Sitnik-Busch TM, Vaughan LA (1999) Potentiation of photodynamic therapy antitumor activity in mice by nitric oxide synthase inhibition is fluence rate dependent. Photochem Photobiol 70:64–71

    Article  Google Scholar 

  147. Yu G, Durduran T, Zhou C et al (2005) Noninvasive monitoring of murine tumor blood flow during and after photodynamic therapy provides early assessment of therapeutic efficacy. Clin Cancer Res 11:3543–3552

    Article  Google Scholar 

  148. Rohrbach DJ, Tracy EC, Walker J et al (2015) Blood flow dynamics during local photoreaction in a head and neck tumor model. Frontiers in Physics 3

    Google Scholar 

  149. Jerjes W, Upile T, Hamdoon Z et al (2011) Photodynamic therapy: the minimally invasive surgical intervention for advanced and/or recurrent tongue base carcinoma. Lasers Surg Med 43:283–292

    Article  Google Scholar 

  150. Story W, Sultan AA, Bottini G et al (2013) Strategies of airway management for head and neck photo-dynamic therapy. Lasers Surg Med 45:370–376

    Article  Google Scholar 

  151. Mo W, Rohrbach D, Sunar U (2012) Imaging a photodynamic therapy photosensitizer in vivo with a time-gated fluorescence tomography system. J Biomed Opt 17:071306

    Article  Google Scholar 

  152. Rohrbach DJ, Rigual N, Tracy E et al (2012) Interlesion differences in the local photodynamic therapy response of oral cavity lesions assessed by diffuse optical spectroscopies. Biomed Opt Express 3:2142–2153

    Article  Google Scholar 

  153. Rigual N, Shafirstein G, Cooper MT et al (2013) Photodynamic therapy with 3-(1′-hexyloxyethyl) pyropheophorbide a for cancer of the oral cavity. Clin Cancer Res 19:6605–6613

    Article  Google Scholar 

  154. Henderson BW, Daroqui C, Tracy E et al (2007) Cross-linking of signal transducer and activator of transcription 3 – a molecular marker for the photodynamic reaction in cells and tumors. Clin Cancer Res 13:3156–3163

    Article  Google Scholar 

  155. Liu W, Oseroff AR, Baumann H (2004) Photodynamic therapy causes cross-linking of signal transducer and activator of transcription proteins and attenuation of interleukin-6 cytokine responsiveness in epithelial cells. Cancer Res 64:6579–6587

    Article  Google Scholar 

  156. Srivatsan A, Wang Y, Joshi P et al (2011) In vitro cellular uptake and dimerization of signal transducer and activator of transcription-3 (STAT3) identify the photosensitizing and imaging-potential of isomeric photosensitizers derived from chlorophyll-a and bacteriochlorophyll-a. J Med Chem 54:6859–6873

    Article  Google Scholar 

  157. Zhou C, Choe R, Shah N et al (2007) Diffuse optical monitoring of blood flow and oxygenation in human breast cancer during early stages of neoadjuvant chemotherapy. J Biomed Opt 12:051903

    Article  Google Scholar 

  158. Choe R, Corlu A, Lee K et al (2005) Diffuse optical tomography of breast cancer during neoadjuvant chemotherapy: a case study with comparison to MRI. Med Phys 32:1128–1139

    Article  Google Scholar 

  159. Schegerin M, Tosteson AN, Kaufman PA et al (2009) Prognostic imaging in neoadjuvant chemotherapy of locally-advanced breast cancer should be cost-effective. Breast Cancer Res Treat 114:537–547

    Article  Google Scholar 

  160. Shah N, Gibbs J, Wolverton D et al (2005) Combined diffuse optical spectroscopy and contrast-enhanced magnetic resonance imaging for monitoring breast cancer neoadjuvant chemotherapy: a case study. J Biomed Opt 10:051503

    Article  Google Scholar 

  161. Roblyer D, Ueda S, Cerussi A et al (2011) Optical imaging of breast cancer oxyhemoglobin flare correlates with neoadjuvant chemotherapy response one day after starting treatment. Proc Natl Acad Sci U S A 108:14626–14631

    Article  Google Scholar 

  162. Lee K (2011) Optical mammography: diffuse optical imaging of breast cancer. World J Clin Oncol 2:64–72

    Article  Google Scholar 

  163. Leproux A, van der Voort M, van der Mark MB et al (2011) Optical mammography combined with fluorescence imaging: lesion detection using scatterplots. Biomed Opt Express 2:1007–1020

    Article  Google Scholar 

  164. Choe R, Durduran T (2012) Diffuse Optical Monitoring of the Neoadjuvant Breast Cancer Therapy. IEEE J Sel Top Quantum Electron 18:1367–1386

    Article  Google Scholar 

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Acknowledgments

We would like to thank Dr. Arjun G. Yodh for providing supervisorship and mentorship at the University of Pennsylvania that initiated most of the work presented here. We also acknowledge Dr. Britton Chance for his excellent mentoring and guidance. We thank Shoko Nioka and Bruce J. Tromberg for their continuous support. Additional thanks go to current and past researchers of Yodh lab at Penn, particularly Turgut Durduran, Regine Choe, Guoqiang Yu, Chao Zhou, Soren D. Konecky, Kijoon Lee, Hsing-wen Wang, David R. Busch, Alper Corlu, and Leonid Zubkov. U. Sunar acknowledges the support from the NCI grants, P30CA16056 (Startup grant) and CA55791 (Program Project Grant).

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Authors and Affiliations

  1. Biomedical Engineering, University at Buffalo, Buffalo, NY, USA

    Ulas Sunar

  2. Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH, USA

    Ulas Sunar & Daniel J. Rohrbach

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  1. Ulas Sunar
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  2. Daniel J. Rohrbach
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Correspondence to Ulas Sunar .

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Editors and Affiliations

  1. Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

    Aaron Ho-Pui Ho

  2. School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea (Republic of)

    Donghyun Kim

  3. Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

    Michael G. Somekh

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Sunar, U., Rohrbach, D.J. (2017). Monitoring Cancer Therapy with Diffuse Optical Methods. In: Ho, AP., Kim, D., Somekh, M. (eds) Handbook of Photonics for Biomedical Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5052-4_26

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