BIOE: “Label-free quantitative histopathology of breast tissue using quantitative phase imaging” and “Inherently therapeutic hafnium oxide nanoparticles with potential for inherent anti-microbial properties against dental biofilm”

Speaker Hassaan Majeed (Popescu Lab) and Fatemeh Ostadhossein (Pan Lab), Illinois Bioengineering Graduate Students
Date: 11/14/2017
Time: 11 a.m. - 12 p.m.

2240 Digital Computer Lab, 1304 W Springfield Avenue, Urbana, IL

Event Contact: Lisa Leininger

Department of Bioengineering

Event Type: Seminar/Symposium

“Label-free quantitative histopathology of breast tissue using quantitative phase imaging”


Hassaan Majeed, Bioengineering Graduate Student, Popescu Lab


According to the World Health Organization (WHO), breast cancer is the most prevalent form of cancer among women in both the developed and developing world. The WHO has also emphasized that early detection and treatment is essential in improving outcomes. The standard method for breast histopathology relies on manual microscopic examination of stained tissue morphology by a pathologist. This standard method not only suffers from inter-observer variation and low-throughput, due to qualitative assessment, but also results in high work-loads for clinicians world-wide. In this work, we demonstrate that optical path-length maps can be used to screen breast tissue biopsies i.e flag malignant areas within breast tissue. We imaged a tissue microarray comprising 68 different cases (34 malignant and 34 tumor adjacent normal) using Spatial Light Interference Microscopy. We then extracted the mean scattering length, glandular curvature and texture parameters from epithelial tissue areas in these phase images to generate a feature vector for each case. A Linear discriminant analysis (LDA) classifier was then trained toseparate benign feature vectors from malignant ones. Three-fold cross-validation results for the classification had an average sensitivity and specificity of 94% and 85%, respectively. Relying on quantitative information, our method removes observer subjectivity from the diagnostic process and lends itself to automated analysis. Designed for minimizing false negatives during screening, a tool based on this method can rapidly flag areas requiring further investigation by pathologists, reducing caseloads and allowing early detection.




“Inherently therapeutic hafnium oxide nanoparticles with potential for inherent anti-microbial properties against dental biofilm”


Fatemeh Ostadhossein, Illinois Bioengineering Graduate Student, Pan Lab


The utilization of particles at the nanoscale has emerged as an interdisciplinary area for early detection, diagnosis and therapy of diseases, which shows promise to understand the components, processes, and dynamics of a disease at a molecular level. The integration of diagnosis and therapy in tandem is known as ‘theranostic’ to tackle the bewildering conundrum of debilitating diseases such as cancer. The high surface to volume ratio of nanoparticles have conferred them with the potential to ferry multiple therapeutic agents, target a specific biomarker or serve as beacons to shed light on the biological entities from minute molecular level to anatomical features. In this talk the synthesis and characterization of novel nanoparticle developed as inherently therapeutic Xray contrast materials for periodontal disease will be discussed. In addition, the follow up studies explored the potential for this novel system for bone imaging, traumatic brain injury via “hard” and “soft” particle approach. The other part of the talk will be devoted to discuss application of carbon dots as a drug delivery platform for the inhibition of cancer stem cells which was recently published in the journal Small (DOI: 10.1002/smll.201601161). Rigorous physicochemical characterization is performed using analytical tools in both hydrated and de-hydrated state. In vitro and in vivo ecacy and imaging studies with these particles will be highlighted, reaching sparse biological epitopes such as stem like cancer cells and others.


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University of Illinois at Urbana-Champaign
1270 Digital Computer Laboratory, MC-278
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Urbana, IL 61801, USA

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