Chemical Imaging and Printed Structures for Simulation in Pathology

bhargavaRohit Bhargava

Figure 1: Conventional histopathologic images (left) and images indicating histology (middle) and pathology (right) of prostate tissue using chemical imaging and computational visualization.

Department of Bioengineering
Beckman Institute for Advanced Science and Technology
Histopathology is essential to diagnosing most health conditions involving tissue changes. We are developing technologies that can provide conventional histopathologic views without the need to stain or use dyes, while using new concepts to harness the microenvironment; we can now improve disease diagnosis well beyond human capability.1 We are doing so by co-developing theory, simulations, and equipment designed to extract the best possible performance from imaging systems.2 Recently, we have also developed nonlinear Raman imaging systems that permit 3D visualization of intact tissues and cell cultures. Here we show how the development of technology can lead to better pathology outcomes tomorrow by simulation and computer referencing. That technology,3 in conjunction with computational methods,4 can be used to translate the expertise of leading academic centers and consensus estimates to serve low-resource settings and community healthcare systems. Next, we show how cell culture systems can be developed in an increasingly sophisticated manner to mimic tissues and their biological processes.5 In particular, the use of multiple cells in the same culture, with carefully developed relative cell positioning, can be used to understand molecular signaling that is relevant to simulation and prediction of breast cancer progression under different conditions. Finally, we have developed a 3D printer to allow sophisticated investigations into cellular processes by precise control of chemical and physical cues.


  1. J. T. Kwak, et al. “Improving Prediction of Disease Recurrence using Chemical Imaging,” submitted (2014)
  2. M. J. Nasse, et al. “High-resolution Fourier Transform Infrared Chemical Imaging with Multiple Synchrotron Beams,” Nature Methods, 8, 413-416 (2011)
  3. R. Bhargava. “Infrared Spectroscopic Imaging: The Next Generation,” Appl. Spectrosc. 66, 1091-1120 (2012)
  4. M. J. Baker, et al. “Using Fourier Transform IR Spectroscopy to Analyze Biological Materials,” Nature Protocols 9, 1771–1791 (2014)
  5. S. E. Holton, et al. “Integration of Molecular Profiling and Chemical Imaging to Elucidate Fibroblast-Microenvironment Impact on Cancer Cell Phenotype and Endocrine Resistance in Breast Cancer,” PLoS One 9, 5, e96878 (2014)



Rohit Bhargava received his Ph.D. from Case Western Reserve University in 2000 and his undergraduate degree from the Indian Institute of Technology, New Delhi, in 1996. He is a professor in the UIUC Department of Bioengineering and a full-time faculty member in the Beckman Institute Bioimaging Science and Technology group. His fields of professional interest are infrared spectroscopic imaging, cancer pathology, probes for molecular imaging, polymer structure, and numerical methods for image processing.