Publications

Journal Publications

November 1, 2011
S. Uttam, R. Bista, D. Hartman, R. Brand, and Y. Liu
Abstract

For any technique to be adopted into a clinical setting, it is imperative that it seamlessly integrates with well-established clinical diagnostic workflow. We recently developed an optical microscopy technique-spatial-domain low-coherence quantitative phase microscopy (SL-QPM) that can extract the refractive index of the cell nucleus from the standard histology specimens on glass slides prepared via standard clinical protocols. This technique has shown great potential in detecting cancer with a better sensitivity than conventional pathology. A major hurdle in the clinical translation of this technique is the intrinsic variation among staining agents used in histology specimens, which limits the accuracy of refractive index measurements of clinical samples. In this paper, we present a simple and easily generalizable method to remove the effect of variations in staining levels on nuclear refractive index obtained with SL-QPM. We illustrate the efficacy of our correction method by applying it to variously stained histology samples from animal model and clinical specimens.

August 22, 2011
IEEE Trans Image Process; 21(2): 638-652 (2012).
Feature-specific difference imaging
S. Uttam, N. Goodman, and M. Neifeld
Abstract

Difference images quantify changes in the object scene over time. In this paper, we use the feature-specific imaging paradigm to present methods for estimating a sequence of difference images from a sequence of compressive measurements of the object scene. Our goal is twofold. First is to design, where possible, the optimal sensing matrix for taking compressive measurements. In scenarios where such sensing matrices are not tractable, we consider plausible candidate sensing matrices that either use the available a priori information or are nonadaptive. Second, we develop closed-form and iterative techniques for estimating the difference images. We specifically look at l 2 - and l 1 -based methods. We show that l 2 -based techniques can directly estimate the difference image from the measurements without first reconstructing the object scene. This direct estimation exploits the spatial and temporal correlations between the object scene at two consecutive time instants. We further develop a method to estimate a generalized difference image from multiple measurements and use it to estimate the sequence of difference images. For l 1 -based estimation, we consider modified forms of the total-variation method and basis pursuit denoising. We also look at a third method that directly exploits the sparsity of the difference image. We present results to show the efficacy of these techniques and discuss the advantages of each

August 19, 2011
Opt. Lett.; 36: 3323-3325 (2011).
Spectral contrast imaging microscopy
S. Alexandrov, S. Uttam, R. Bista, and Y. Liu
Abstract

We introduce a new technique, spectral contrast imaging microscopy (SCIM), for super-resolution microscopic imaging. Based on a novel contrast mechanism that encodes each local spatial frequency with a corresponding optical wavelength, SCIM provides a real-time high-resolution spectral contrast microscopic image with superior contrast. We show that two microscopic objects, separated by a distance smaller than the diffraction limit of the optical system, can be spatially resolved in the SCIM image as different colors. Results with numerical simulation and experiments using a high-resolution United States Air Force target are presented. The ability of SCIM for imaging biological cells is also demonstrated.

July 1, 2011
R. Bista, S. Uttam, P. Wang, L. Staton, S. Choi, C. Bakkenist, D. Hartman, R. Brand, and Y. Liu
Abstract

Intrigued by our recent finding that the nuclear refractive index is significantly increased in malignant cells and histologically normal cells in clinical histology specimens derived from cancer patients, we sought to identify potential biological mechanisms underlying the observed phenomena. The cell cycle is an ordered series of events that describes the intervals of cell growth, DNA replication, and mitosis that precede cell division. Since abnormal cell cycles and increased proliferation are characteristic of many human cancer cells, we hypothesized that the observed increase in nuclear refractive index could be related to an abundance or accumulation of cells derived from cancer patients at a specific point or phase(s) of the cell cycle. Here we show that changes in nuclear refractive index of fixed cells are seen as synchronized populations of cells that proceed through the cell cycle, and that increased nuclear refractive index is strongly correlated with increased DNA content. We therefore propose that an abundance of cells undergoing DNA replication and mitosis may explain the increase in nuclear refractive index observed in both malignant and histologically normal cells from cancer patients. Our findings suggest that nuclear refractive index may be a novel physical parameter for early cancer detection and risk stratification.

November 1, 2010
P. Wang, R. Bista, W. Khalbuss, W. Qiu, S. Uttam, K. Staton, L. Zhang, T. Brentnall, R. Brand, and Y. Liu
Abstract

Definitive diagnosis of malignancy is often challenging due to limited availability of human cell or tissue samples and morphological similarity with certain benign conditions. Our recently developed novel technology-spatial-domain low-coherence quantitative phase microscopy (SL-QPM)-overcomes the technical difficulties and enables us to obtain quantitative information about cell nuclear architectural characteristics with nanoscale sensitivity. We explore its ability to improve the identification of malignancy, especially in cytopathologically non-cancerous-appearing cells. We perform proof-of-concept experiments with an animal model of colorectal carcinogenesis-APC(Min) mouse model and human cytology specimens of colorectal cancer. We show the ability of in situ nanoscale nuclear architectural characteristics in identifying cancerous cells, especially in those labeled as "indeterminate or normal" by expert cytopathologists. Our approach is based on the quantitative analysis of the cell nucleus on the original cytology slides without additional processing, which can be readily applied in a conventional clinical setting. Our simple and practical optical microscopy technique may lead to the development of novel methods for early detection of cancer.

Conference Presentations

D. Brokl, D. Lo, W. Khalbuss, P. Wang, R. Bista, S. Uttam, Y. Liu, and R. Brand
Spatial-Domain Low-Coherence Quantitative Phase Microscopy to Improve the Cytological Diagnosis of Pancreatic Cancer
Gastroenterology - Orlando, 2011; 140(1):S-53. [Plenary talk]
May 1, 2011
S. Uttam, J. Xu, and Y. Liu
Nanoscale nuclear architecture mapping captures chromatin reorganization in epithelial cells undergoing malignant transformation
SPIE Photonics West (BIOS), 6-11 March 2021, San Francisco, USA; Conference Proceedings volume 11653, Quantitative Phase Imaging VII; 1165318 (2021).
March 6, 2011
S. Uttam, N. Goodman, and M. Neifeld
Direct reconstruction of difference images from optimal spatial-domain projections
in Proc. SPIE Conference on Optics & Photonics, San Diego, CA, Aug. 2008.
August 1, 2008
S. Uttam, N. Goodman, M. Neifeld, D. Brady, J. Kim, and C. Kim
Optically multiplexed imaging with superposition-space tracking
in Proc. SPIE Conference on Optics & Photonics, San Diego, CA, Aug. 2008.
August 1, 2008
S. Uttam, N. Goodman, and M. Neifeld
Difference imaging from linear spatial-domain projections
SIAM Conference on Imaging Science, San Diego, CA July 2008
July 1, 2008

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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