Translation of infrared spectroscopic imaging for digital histopathology of clinical specimens

Over the past several decades, infrared (IR) spectroscopic imaging has been widely proposed as a potential diagnostic tool for histopathological studies in research and for human disease evaluation. This imaging technique couples the chemical information provided by the absorbance of IR light and the structural information provided by optical microscopy. This information can be used as a molecular and spatial barcode of the measured sample. Since the IR absorption provides image contrast and uniquely identifies the sample’s chemistry without dyes or prior knowledge of composition, it enables a systematic analysis with enhanced ability to extract diagnostic information. However, most IR spectroscopic imaging approaches require significant time for data acquisition and processing. Limiting the amount of spectral data needed has significantly reduced the acquisition time, but its clinical feasibility is yet to be demonstrated. Therefore, the major goal of my dissertation work is carefully designing a measurement protocol with a high signal-to-noise ratio (SNR) and adequate pixel sizes that are sufficient for digital assessment of clinical samples in an intraoperative time frame. The work addresses two key clinical problems by developing a non-destructive technique (1) for intraoperative imaging of cavity shave margins (CSM) in breast conserving surgery (BCS) and (2) for detection and subtyping of cardiac amyloidosis with high sensitivity.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Bioengineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Mittal, Anirudh

Contributors dc:contributor

• Bhargava, Rohit
• Irudayaraj, Joseph
• Nie, Shuming
• Higham, Anna

• Infrared spectroscopic imaging
• Digital histopathology

Statement dc:rights

• Copyright 2022 Anirudh Mittal

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/117520

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F117520