Towards Translation of Discrete Frequency Infrared Spectroscopic Imaging for Digital Histopathology of Clinical Biopsy Samples.
Fourier transform infrared (FT-IR) spectroscopic imaging has been widely tested as a tool for stainless digital histology of biomedical specimens, including for the identification of infiltration and fibrosis in endomyocardial biopsy samples to assess transplant rejection. A major barrier in clinical translation has been the slow speed of imaging. To address this need, we tested and report here the viability of using high speed discrete frequency infrared (DFIR) imaging to obtain stain-free biochemical imaging in cardiovascular samples collected from patients. Images obtained by this method were classified with high accuracy by a Bayesian classification algorithm trained on FT-IR imaging data as well as on DFIR data. A single spectral feature correlated with instances of fibrosis, as identified by the pathologist, highlights the advantage of the DFIR imaging approach for rapid detection. The speed of digital pathologic recognition was at least 16 times faster than the fastest FT-IR imaging instrument. These results indicate that a fast, on-site identification of fibrosis using IR imaging has potential for real time assistance during surgeries. Further, the work describes development and applications of supervised classifiers on DFIR imaging data, comparing classifiers developed on FT-IR and DFIR imaging modalities and identifying specific spectral features for accurate identification of fibrosis. This addresses a topic of much debate on the use of training data and cross-modality validity of IR measurements. Together, the work is a step toward addressing a clinical diagnostic need at acquisition time scales that make IR imaging technology practical for medical use.
Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Saumya
S
Tiwari
Knight Cardiovascular Institute, Oregon Health & Science University , 3181 SW Sam Jackson Park Road, Portland, Oregon 97201, United States.
Jai
J
Raman
Department of Pathology, Rush University Medical Center , 1725 West Harrison Street, Chicago, Illinois 60612, United States.
Vijaya
V
Reddy
California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States.
Andrew
A
Ghetler
California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States.
Richard P
RP
Tella
California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States.
Yang
Y
Han
California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States.
Christopher R
CR
Moon
California Research Center, Spectroscopy and Vacuum Solutions Division, Agilent Technologies, Inc. , 5301 Stevens Creek Blvd., Santa Clara, California 95051 United States.
Charles D
CD
Hoke
Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.|Departments of Chemistry, Mechanical Science and Engineering, Chemical and Biomolecular Engineering, Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Rohit
R
Bhargava
D001499:Bayes Theorem; D005355:Fibrosis / Q000000981:diagnostic imaging; D006801:Humans; D009206:Myocardium / Q000473:pathology*; D013055:Spectrophotometry, Infrared / Q000379:methods*; D017550:Spectroscopy, Fourier Transform Infrared