Dr. Greg M. Palmer Profile

Dr. Greg M. Palmer

Associate Professor at Duke Univ

SPIE Involvement:

Author

SPIE Journal Paper | 23 November 2020 Open Access

Dual-emissive, oxygen-sensing boron nanoparticles quantify oxygen consumption rate in breast cancer cells

Ashlyn G. Rickard, Meng Zhuang, Christopher DeRosa, Xiaojie Zhang, Mark Dewhirst, Cassandra Fraser, Gregory Palmer

JBO, Vol. 25, Issue 11, 116504, (November 2020) https://doi.org/10.1117/12.10.1117/1.JBO.25.11.116504

KEYWORDS: Optical character recognition, Oxygen, Nanoparticles, Tumors, Boron, Luminescence, Diffusion, Phosphorescence, Microscopes, Calibration

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Proceedings Article | 21 February 2020 Paper

Nanostar probes: a golden platform for Synergistic Immuno Photothermal Nanotherapy (SYMPHONY) for the treatment of metastatic cancer

Vanessa Cupil-Garcia, Yang Liu, Bridget Crawford, Pakawat Chongsathidkiet, Gregory Palmer, Paolo Maccarini, Peter Fecci, Brant Inman, Tuan Vo-Dinh

Proceedings Volume 11257, 1125714 (2020) https://doi.org/10.1117/12.2552995

KEYWORDS: Tumors, Cancer, Oncology, Bladder cancer, Gold, Nanoparticles, Nanotherapeutics, Near infrared, Tumor growth modeling, Computed tomography

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Proceedings Article | 7 March 2019 Paper

Implantable "smart tattoo" SERS nanosensors for in vivo detection of nucleic acid biotargets in a large animal model

Hsin-Neng Wang, Janna Register, Andrew Fales, Naveen Gandra, Pietro Strobbia, Eugenia Cho, Alina Boico, Gregory Palmer, Bruce Klitzman, Tuan Vo-Dinh

Proceedings Volume 10894, 108941J (2019) https://doi.org/10.1117/12.2514634

KEYWORDS: Nanosensors, Animal model studies, Sensors, Raman spectroscopy, Plasmonics

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SPIE Journal Paper | 15 May 2018 Open Access

Assessing effects of pressure on tumor and normal tissue physiology using an automated self-calibrated, pressure-sensing probe for diffuse reflectance spectroscopy

Gregory Palmer, Hengtao Zhang, Chen-Ting Lee, Husam Mikati, Joseph Herbert, Marlee Krieger, Jesko von Windheim, Dave Koester, Daniel Stevenson, Daniel Rocke, Ramon Esclamado, Alaatin Erkanli, Nirmala Ramanujam, Mark Dewhirst, Walter Lee

JBO, Vol. 23, Issue 05, 057004, (May 2018) https://doi.org/10.1117/12.10.1117/1.JBO.23.5.057004

KEYWORDS: Calibration, Tumors, Tissue optics, Tissues, Diffuse reflectance spectroscopy, Scattering, Lamps, Sensors, Data modeling, Statistical modeling

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Proceedings Article | 12 February 2018 Paper

Synergistic immuno photothermal nanotherapy (SYMPHONY) to treat unresectable and metastatic cancers and produce and cancer vaccine effect

Tuan Vo-Dinh, Brant Inman, Paolo Maccarini, Gregory Palmer, Yang Liu

Proceedings Volume 10484, 1048408 (2018) https://doi.org/10.1117/12.2300089

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SPIE Journal Paper | 22 February 2017 Open Access

Miniature spectral imaging device for wide-field quantitative functional imaging of the morphological landscape of breast tumor margins

Brandon Nichols, Antonio Llopis, Gregory Palmer, Samuel McCachren, Ozlem Senlik, David Miller, Martin Brooke, Nan Jokerst, Joseph Geradts, Rachel Greenup, Nimmi Ramanujam

JBO, Vol. 22, Issue 02, 026007, (February 2017) https://doi.org/10.1117/12.10.1117/1.JBO.22.2.026007

KEYWORDS: Tissues, Tissue optics, Optical properties, Breast, Photodiodes, Personal digital assistants, Imaging spectroscopy, Tumors, Imaging devices, Functional imaging

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Proceedings Article | 25 March 2013 Paper

Monitoring of cycling hypoxia and angiogenesis in FaDu head and neck tumors using a side-firing sensor

Bing Yu, Amy Shah, Bingqing Wang, Narasimhan Rajaram, Quanli Wang, Nirmala Ramanujam, Gregory Palmer, Mark Dewhirst

Proceedings Volume 8578, 85781E (2013) https://doi.org/10.1117/12.2002837

KEYWORDS: Tumors, Hypoxia, Tissues, Oxygen, Sensors, Head, Neck, Blood vessels, Absorption, Data modeling

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SPIE Journal Paper | 31 July 2012 Open Access

Publisher's Note: Experimental validation of an inverse fluorescence Monte Carlo model to extract concentrations of metabolically relevant fluorophores from turbid phantoms and a murine tumor model

Chengbo Liu, Narasimhan Rajaram, Karthik Vishwanath, Tony Jiang, Nirmala Ramanujam, Gregory Palmer

JBO, Vol. 17, Issue 7, 079805, (July 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.7.079805

KEYWORDS: Luminescence, Monte Carlo methods, Tumors, Instrument modeling, Biomedical optics, Biomedical engineering, Biological research, Life sciences, Roads, Radiation oncology

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SPIE Journal Paper | 24 July 2012 Open Access

Experimental validation of an inverse fluorescence Monte Carlo model to extract concentrations of metabolically relevant fluorophores from turbid phantoms and a murine tumor model

Chengbo Liu, Narasimhan Rajaram, Karthik Vishwanath, Tony Jiang, Nirmala Ramanujam, Gregory Palmer

JBO, Vol. 17, Issue 7, 077012, (July 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.7.077012

KEYWORDS: Luminescence, Monte Carlo methods, Absorption, Calibration, Reflectivity, Tissues, Rhodamine, Scattering, Optical properties, Tissue optics

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SPIE Journal Paper | 1 November 2010 Open Access

Optical imaging of tumor hypoxia dynamics

Gregory Palmer, Andrew Fontanella, Guoqing Zhang, Gabi Hanna, Cassandra Fraser, Mark Dewhirst

JBO, Vol. 15, Issue 06, 066021, (November 2010) https://doi.org/10.1117/12.10.1117/1.3523363

KEYWORDS: Oxygen, Tumors, Tissues, Hypoxia, Optical imaging, Luminescence, Nanoparticles, Green fluorescent protein, Cancer, Skin

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SPIE Journal Paper | 1 March 2009 Open Access

Quantitative diffuse reflectance and fluorescence spectroscopy: tool to monitor tumor physiology in vivo

Gregory Palmer, Ronald Viola, Thies Schroeder, Pavel Yarmolenko, Mark Dewhirst, Nirmala Ramanujam

JBO, Vol. 14, Issue 02, 024010, (March 2009) https://doi.org/10.1117/12.10.1117/1.3103586

KEYWORDS: Tumors, Luminescence, Diffuse reflectance spectroscopy, Sensors, Absorption, Physiology, Tissue optics, Optical spectroscopy, Oxygen, Tissues

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SPIE Journal Paper | 1 November 2008 Open Access

Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo

Bing Yu, Justin Lo, Thomas Kuech, Gregory Palmer, Janelle Bender, Nirmala Ramanujam

JBO, Vol. 13, Issue 06, 060505, (November 2008) https://doi.org/10.1117/12.10.1117/1.3041500

KEYWORDS: Tissue optics, Scattering, Absorption, Photodiodes, Optical properties, Tissues, Imaging spectroscopy, In vivo imaging, Imaging systems, Diffuse reflectance spectroscopy

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SPIE Journal Paper | 1 May 2008 Open Access

Diagnosis of breast cancer using fluorescence and diffuse reflectance spectroscopy: a Monte-Carlo-model-based approach

Changfang Zhu, Gregory Palmer, Tara Breslin, Josephine Harter, Nirmala Ramanujam

JBO, Vol. 13, Issue 03, 034015, (May 2008) https://doi.org/10.1117/12.10.1117/1.2931078

KEYWORDS: Tissues, Luminescence, Breast, Scattering, Absorption, Diffuse reflectance spectroscopy, Breast cancer, Collagen, Tumor growth modeling, Monte Carlo methods

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We explore the use of Monte-Carlo-model-based approaches for the analysis of fluorescence and diffuse reflectance spectra measured ex vivo from breast tissues. These models are used to extract the absorption, scattering, and fluorescence properties of malignant and nonmalignant tissues and to diagnose breast cancer based on these intrinsic tissue properties. Absorption and scattering properties, including -carotene concentration, total hemoglobin concentration, hemoglobin saturation, and the mean reduced scattering coefficient are derived from diffuse reflectance spectra using a previously developed Monte Carlo model of diffuse reflectance. A Monte Carlo model of fluorescence described in an earlier manuscript was employed to retrieve the intrinsic fluorescence spectra. The intrinsic fluorescence spectra were decomposed into several contributing components, which we attribute to endogenous fluorophores that may present in breast tissues including collagen, NADH, and retinol/vitamin A. The model-based approaches removes any dependency on the instrument and probe geometry. The relative fluorescence contributions of individual fluorescing components, as well as -carotene concentration, hemoglobin saturation, and the mean reduced scattering coefficient display statistically significant differences between malignant and adipose breast tissues. The hemoglobin saturation and the reduced scattering coefficient display statistically significant differences between malignant and fibrous/benign breast tissues. A linear support vector machine classification using (1) fluorescence properties alone, (2) absorption and scattering properties alone, and (3) the combination of all tissue properties achieves comparable classification accuracies of 81 to 84% in sensitivity and 75 to 89% in specificity for discriminating malignant from nonmalignant breast tissues, suggesting each set of tissue properties are diagnostically useful for the discrimination of breast malignancy.

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SPIE Journal Paper | 1 March 2008 Open Access

Monte-Carlo-based model for the extraction of intrinsic fluorescence from turbid media

Gregory Palmer, Nirmala Ramanujam

JBO, Vol. 13, Issue 02, 024017, (March 2008) https://doi.org/10.1117/12.10.1117/1.2907161

KEYWORDS: Luminescence, Optical properties, Absorption, Scattering, Monte Carlo methods, Tissues, Optical spheres, Tissue optics, Diffuse reflectance spectroscopy, Refractive index

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SPIE Journal Paper | 1 March 2005 Open Access

Use of a multiseparation fiber optic probe for the optical diagnosis of breast cancer

Changfang Zhu, Gregory Palmer, Tara Breslin, Fushen Xu, Nirmala Ramanujam

JBO, Vol. 10, Issue 02, 024032, (March 2005) https://doi.org/10.1117/12.10.1117/1.1897398

KEYWORDS: Tissues, Luminescence, Diffuse reflectance spectroscopy, Breast, Fiber optics, Principal component analysis, Absorption, Statistical analysis, Breast cancer, Optical spectroscopy

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Showing 5 of 15 publications

Conference Committee Involvement (1)

Clinical and Biomedical Spectroscopy and Imaging II

24 May 2011 | Munich, Germany

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