Publications

Journal Publications

March 19, 2013
S. Uttam, S. Alexandrov, R. K. Bista, and Y. Liu,
Abstract

Three-dimensional optical tomographic imaging plays an important role in biomedical research and clinical applications. We introduce spectral tomographic imaging (STI) via spectral encoding of spatial frequency principle that not only has the capability for visualizing the three-dimensional object at sub-micron resolution but also providing spatially-resolved quantitative characterization of its structure with nanoscale accuracy for any volume of interest within the object. The theoretical basis and the proof-of-concept numerical simulations are presented to demonstrate the feasibility of spectral tomographic imaging.

July 17, 2012
S. Alexandrov, S. Uttam, R. K. Bista, and Y. Liu
Abstract

An approach to acquire axial structural information at nanoscale is demonstrated. It is based on spectral encoding of spatial frequency principle to reconstruct the structural information about the axial profile of the three-dimensional (3D) spatial frequency for each image point. This approach overcomes the fundamental limitations of current optical techniques and provides nanoscale accuracy and sensitivity in characterizing axial structures. Numerical simulation and experimental results are presented.

June 16, 2012
R. Bista, P. Wang, R. Bhargava, S. Uttam, R. E. Brand, and Y. Liu
Abstract

Accurate detection of breast malignancy from histologically normal cells (“field effect”) has significant clinical implications in a broad base of breast cancer management, such as high-risk lesion management, personalized risk assessment, breast tumor recurrence, and tumor margin management. More accurate and clinically applicable tools to detect markers characteristic of breast cancer “field effect” that are able to guide the clinical management are urgently needed. We have recently developed a novel optical microscope, spatial-domain low-coherence quantitative phase microscopy, which extracts the nanoscale structural characteristics of cell nuclei (i.e., nuclear nano-morphology markers), using standard histology slides. In this proof-of-concept study, we present the use of these highly sensitive nuclear nano-morphology markers to identify breast malignancy from histologically normal cells. We investigated the nano-morphology markers from 154 patients with a broad spectrum of breast pathology entities, including normal breast tissue, non-proliferative benign lesions, proliferative lesions (without and with atypia), “malignant-adjacent” normal tissue, and invasive carcinoma. Our results show that the nuclear nano-morphology markers of “malignant-adjacent” normal tissue can detect the presence of invasive breast carcinoma with high accuracy and do not reflect normal aging. Further, we found that a progressive change in nuclear nano-morphology markers that parallel breast cancer risk, suggesting its potential use for risk stratification. These novel nano-morphology markers that detect breast cancerous changes from nanoscale structural characteristics of histologically normal cells could potentially benefit the diagnosis, risk assessment, prognosis, prevention, and treatment of breast cancer.

June 4, 2012
R. Bista, S. Uttam, D. Hartman, W. Qiu, L. Zhang, R. Brand, and Y. Liu
Abstract

The development of accurate and clinically applicable tools to assess cancer risk is essential to define candidates to undergo screening for early-stage cancers at a curable stage or provide a novel method to monitor chemoprevention treatments. With the use of our recently developed optical technology—spatial-domain low-coherence quantitative phase microscopy (SL-QPM), we have derived a novel optical biomarker characterized by structure-derived optical path length (OPL) properties from the cell nucleus on the standard histology and cytology specimens, which quantifies the nano-structural alterations within the cell nucleus at the nanoscale sensitivity, referred to as nano-morphology marker. The aim of this study is to evaluate the feasibility of the nuclear nano-morphology marker from histologically normal cells, extracted directly from the standard histology specimens, to detect early-stage carcinogenesis, assess cancer risk, and monitor the effect of chemopreventive treatment. We used a well-established mouse model of spontaneous carcinogenesis—ApcMin mice, which develop multiple intestinal adenomas (Min) due to a germline mutation in the adenomatous polyposis coli (Apc) gene. We found that the nuclear nano-morphology marker quantified by OPL detects the development of carcinogenesis from histologically normal intestinal epithelial cells, even at an early pre-adenomatous stage (six weeks). It also exhibits a good temporal correlation with the small intestine that parallels the development of carcinogenesis and cancer risk. To further assess its ability to monitor the efficacy of chemopreventive agents, we used an established chemopreventive agent, sulindac. The nuclear nano-morphology marker is reversed toward normal after a prolonged treatment. Therefore, our proof-of-concept study establishes the feasibility of the SL-QPM derived nuclear nano-morphology marker OPL as a promising, simple and clinically applicable biomarker for cancer risk assessment and evaluation of chemopreventive treatment.

April 5, 2012
S. Alexandrov, S. Uttam, R. Bista, R Zhao, and Y. Liu
Abstract

We demonstrate a novel approach for the real time visualization and quantification of the 3D spatial frequencies in an image domain. Our approach is based on the spectral encoding of spatial frequency principle and permits the formation of an image as a color map in which spatially separated spectral wavelengths correspond to the dominant 3D spatial frequencies of the object. We demonstrate that our approach can visualize and analyze the dominant axial internal structure for each image point in real time and with nanoscale sensitivity to structural changes. Computer modeling and experimental results of instantaneous color visualization and quantification of 3D structures of a model system and biological samples are presented.

Conference Presentations

S. Uttam
Sampling and scrambling in compressive sensing based spectral domain optical coherence tomography
CLEO Laser Science to Photonic Applications (Optical Society of America, 2020) JTu2F.7.
May 10, 2020
S. Uttam and Y. Liu
Three-dimensional nanoscale nuclear architecture mapping for improved cancer risk stratification
SPIE/OSA European Conferences on Biomedical Optics (ECBO) 2019, 23-27 June 2019, Munich, Germany; Paper 11076-38 (2019). [Invited paper]
June 23, 2019
S. Uttam, A.M. Stern, S. A. Furman, F. Pullara, F. Ginty, D. L. Taylor, S. C. Chennubhotla
Spatial proteomics with hyperplexed fluorescence imaging predicts risk of colorectal cancer recurrence and infers recurrence-specific protein-protein networks
Cancer Res; 79 (13 Supplement): 1642 (2019). [AACR Annual Meeting 2019, March 29-April 3 2019, Atlanta, Georgia.]
March 29, 2019
S. Uttam
Hyperplexed immunofluorescence imaging based on spatial proteomics predicts risk of colorectal cancer recurrence and infers recurrence-specific protein networks
Joint Immunology and Computational and Systems Biology Workshop, Jan 23, 2019, University of Pittsburgh, Pittsburgh, PA, USA (2019
January 23, 2019
R. C. Burgess and S. Uttam
Modeling the impact of chromatin modifications on the DNA damage response in yeast
Find Your Inner Modeler workshop, Aug 16-17, 2018, University of Illinois at Chicago, Chicago, Illinois, USA (2018). [Travel award]
August 16, 2018
F. Pullara, N. Bouhenni, S. Uttam, and S. C. Chennubhotla
Integrative strategies for probing energy landscapes and dynamics of IDPs
Workshop on Intrinsically Disordered Proteins, TSRC 2017, July 11--14, 2017; Telluride, Colorado, USA (2017)
July 11, 2017

Conference Presentations

S. Uttam
Nanoscale nuclear architecture mapping of early carcinogenesis
Paper 12389-32, Quantitative Phase Imaging IX, SPIE Photonics West, San Francisco (January 27 - Feb 1, 2023) [Invited]
February 1, 2023
S. Uttam
Label-free nanoscale nuclear architecture mapping of early carcinogenesis
2023 Biophysics and Quantitative Biology in the AI Era, NSF AI Planning Institute at Carnegie Mellon University (Jan 12-13, 2023)
January 25, 2023
S. Uttam
Overcoming the segmentation barrier in in multiplexed spatial proteomic images
UPMC Hillman Cancer Center, Spatial Omics and Computational Imaging in Human Diseases Symposium, Nov 14, 2022. [Invited]
December 1, 2022
S. Uttam
Cancer systems biology in space and scale
UPMC Hillman Cancer Center, Cancer Biology Program Retreat, Oct 24, 2022 [Invited]
November 20, 2022
B. Raymond, D. J. Hartman, and S. Uttam
Spatial Analysis of Cytotoxic T Lymphocyte Infiltration in Colorectal Tumors for Predicting Stage-independent Relapse and Death
2022 Biomedical Engineering Society (BMES) Annual Meeting, Oct 12-15, 2022
October 1, 2022
C. Newman, B. Kochetov, R. Raphael, L. Zhang, and S. Uttam
Understanding the Cellular Landscape of Preclinical Models of Colorectal Cancer
2022 Biomedical Engineering Society (BMES) Annual Meeting, Oct 12-15, 2022
October 1, 2022
K. Yadav, R. Pawar, A. Singhi, and S. Uttam
Characterizing the Three-Dimensional Nuclear Morphology of Normal Appearing, Immune, and Cancer Cells in Cancer Tumor Microenvironment
2022 Biomedical Engineering Society (BMES) Annual Meeting, Oct 12-15, 2022
October 1, 2022
P. N. Thota, J. Nasibli, P. Kumar, M.R. Sanaka, A. Chak, X. Zhang, X. Liu, S. Uttam, and Y. Liu
Nanoscale nuclear architecture mapping predicts neoplastic progression in Barrett’s esophagus: a proof-of-concept study
in Gastrointest. Endosc.; 95(6) Supplement, AB230-AB231
September 1, 2022
B. Kochetov, P.D. Bell, R. Raphael, B.J. Raymond, B.J. Leibowitz, J. Tong, B. Diergaarde , J. Yu, R.K. Pai, R.E. Schoen, L. Zhang, A. Singhi, and S. Uttam
Unsupervised sub-cellular segmentation of complex tissue and cell samples using highly multiplexed imaging-derived a priori knowledge
Abstract 1930. Cancer Res 15 June 2022; 82 (12_Supplement): 1930
June 1, 2022
B. Kochetov, R. Raphael, and S. Uttam
Unsupervised segmentation of complex tissue using multiplexed imaging-derived a priori knowledge
Biomedical Engineering Society (BMES) 2021 Annual Meeting; Oct 6 - 9, 2021; Orlando, Florida; Abstract 074 - 841 (2021)
October 6, 2021
S. Leng, J. Xu, Y. Liu, and S. Uttam
Demonstration of ability of nanoscale nuclear architecture mapping to study chromatin alteration
Biomedical Engineering Society (BMES) 2021 Annual Meeting; Oct 6 - 9, 2021; Orlando, Florida; Abstract reu-011-3129 (2021).
October 6, 2021
D. Pitlor, R. E. Brand, B. Dudley, E. Karlowski, A. Zyhowski, E. J. Metter, R. M. Brand, and S. Uttam
Coefficient of variation based multiplexed ELISA biomarker selection in HNPCC Syndrome Patients
Biomedical Engineering Society (BMES) 2021 Annual Meeting; Oct 6 - 9, 2021; Orlando, Florida; Abstract reu-007-3147 (2021)
October 6, 2021
S. Uttam
Sampling and scrambling in compressive sensing based spectral domain optical coherence tomography
CLEO Laser Science to Photonic Applications (Optical Society of America, 2020) JTu2F.7.
May 10, 2020
S. Uttam and Y. Liu
Three-dimensional nanoscale nuclear architecture mapping for improved cancer risk stratification
SPIE/OSA European Conferences on Biomedical Optics (ECBO) 2019, 23-27 June 2019, Munich, Germany; Paper 11076-38 (2019). [Invited paper]
June 23, 2019
S. Uttam, A.M. Stern, S. A. Furman, F. Pullara, F. Ginty, D. L. Taylor, S. C. Chennubhotla
Spatial proteomics with hyperplexed fluorescence imaging predicts risk of colorectal cancer recurrence and infers recurrence-specific protein-protein networks
Cancer Res; 79 (13 Supplement): 1642 (2019). [AACR Annual Meeting 2019, March 29-April 3 2019, Atlanta, Georgia.]
March 29, 2019
S. Uttam
Hyperplexed immunofluorescence imaging based on spatial proteomics predicts risk of colorectal cancer recurrence and infers recurrence-specific protein networks
Joint Immunology and Computational and Systems Biology Workshop, Jan 23, 2019, University of Pittsburgh, Pittsburgh, PA, USA (2019
January 23, 2019
R. C. Burgess and S. Uttam
Modeling the impact of chromatin modifications on the DNA damage response in yeast
Find Your Inner Modeler workshop, Aug 16-17, 2018, University of Illinois at Chicago, Chicago, Illinois, USA (2018). [Travel award]
August 16, 2018
F. Pullara, N. Bouhenni, S. Uttam, and S. C. Chennubhotla
Integrative strategies for probing energy landscapes and dynamics of IDPs
Workshop on Intrinsically Disordered Proteins, TSRC 2017, July 11--14, 2017; Telluride, Colorado, USA (2017)
July 11, 2017
S. Uttam, F. Pullara, and S. C. Chennubhotla
Comparative dynamics - An information theoretic perspective
Biomolecular Machines Conference - Protein Flexibility and Allostery, May 18-21, 2017, Banff, Alberta, Canada (2017)
May 17, 2017
S. Uttam
Nanoscale nuclear architecture mapping for cancer-risk stratification and prediction
Computational Pathology Lecture Series, April 14, 2017; Computational Pathology Interest Group and Lecture Series, University of Pittsburgh, Pittsburgh, Pennsylvania, USA (2017). [Invited talk]
April 17, 2017
Y. Liu, S. Uttam, H. V. Pham, and D. J. Hartman
Improved cancer risk stratification and diagnosis via quantitative phase microscopy
SPIE Photonics West (BIOS), Jan 28 -- Feb 2, 2017, San Francisco, USA; Conference: Quantitative Phase Imaging III, Paper 10074-40 (2017).[Invited paper]
February 2, 2017
R. Bista, S. Uttam, D. Hartman, W. Qiu, J. Yu, L. Zhang, R. Brand, and Y. Liu
Investigation of nuclear nano-morphology markers as a novel biomarker for cancer risk assessment using a mouse model
Gastroenterology - San Diego, 2012; 142(5):S-532.
May 1, 2012
S. Uttam, S. Alexandrov, R. Bista, and Y. Liu
Model-based demonstration of spectral tomographic imaging
in Biomedical Optics, OSA Technical Digest (Optical Society of America, 2012), paper BSu3A.61.
February 28, 2012
Y. Liu, S. Alexandrov, S. Uttam, and R. Bista
Probing Cell Nanoscale Structural Properties Using Intrinsic Contrast of Light Scattering
Biophysical Journal, Vol. 102, Issue 3, S1 (2012). [Invited talk ]
February 25, 2012
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