Tissue Imaging


The foundation for much of the field of pathology is the analysis of images derived from cells and tissues using microscopy.  Pathology is based on taking small tissue samples from patients and then typically staining the samples and then visualizing them using either visible or fluorescent light.  These images are then examined by an experienced pathologist who will render a diagnosis.

The Department of Pathology at the University of Illinois at Chicago is focused on developing and applying advanced imaging capabilities towards the goals of improving disease detection and prediction of patient outcome.  Current activities include the following:



Spectral Imaging

The Spectral Pathology Lab (spectral-pathology.uic.edu), directed by Dr. Michael Walsh, is focused on developing new label free-imaging approaches that allow pathologists to ‘see’ additional biochemical information embedded within tissues.  The lab is using Fourier Transform Infrared (FTIR) spectroscopy and other spectral imaging approaches to address translational research questions, such as the prediction of early organ failure in kidney and heart transplants.


Computational Pathology

Research in the laboratory of Dr. Peter Gann is developing computation-intensive methods for extracting informative features from tissue specimens that are not perceptible to a human pathologist.

The lab uses Definiens Developer XD® and other software tools to mine high-dimensional libraries of visual features in order to create new models for clinical prediction and biological discovery.  Most current work is focused on nuclear and architectural characteristics of prostate cancer.  The images shown here illustrate the initial mapping of an H&E-stained sample, which allows for the definition of key objects and their hierarchical and spatial relations (e.g., nuclei within epithelium, nucleoli within nuclei, etc.).


Advanced Imaging Methods for Predicting Prostate Cancer Outcomes

Dr. Andre Balla is the lead pathologist on research projects investigating the use of infrared spectroscopy and spatial light interference microscopy (SLIM) for predicting prostate cancer recurrence.  Through collaboration with Drs. Rohit Bhargava and Gabriel Popescu from the Beckman Institute at the University of Illinois Urbana-Champaign, research teams have been able to show that both the infrared spectral signature and SLIM interrogation of the path of visible light through tissue can be used to improve upon current models for predicting recurrence.  This work has also revealed insights into the role of tumor-associated stroma.



Peter H. Gann, MD, ScD
Digital microscopy and image analysis for prostate cancer prognosis and chemoprevention
Quantification of brightfield and fluorescence images 
Nuclear morphometry

Grace Guzman, MD
Image analysis of liver and colon tissues

Andre Kajdacsy-Balla, MD, PhD
New imaging modalities for improving pathology

Suman Setty, MBBS, PhD
Digital imaging of disease states in renal biopsies

Michael J. Walsh, PhD
Infrared spectroscopy towards improved disease detection and prediction of disease outcome