Infrared Spectroscopic Imaging for Label-free and Automated Histopathology

2010 ◽  
Author(s):  
Rohit Bhargava ◽  
Rohith K. Reddy ◽  
Jason Ip ◽  
Frances N. Pounder ◽  
Matthew V. Schulmerich ◽  
...  
Keyword(s):  
Spectroscopic Imaging ◽  
Label Free ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging

Infrared spectroscopic imaging: a label free approach for the detection of amyloidosis in human tissue biopsies

Amyloid ◽  
2017 ◽  
Vol 24 (sup1) ◽  
pp. 163-164
Author(s):  
David Martinez-Marin ◽  
Hari Sreedhar ◽  
Michael J. Walsh ◽  
Maria M. Picken
Keyword(s):  
Human Tissue ◽  
Spectroscopic Imaging ◽  
Label Free ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging

scholarly journals Automated osteosclerosis grading of clinical biopsies using infrared spectroscopic imaging

2019 ◽  
Author(s):  
Rupali Mankar ◽  
Carlos E. Bueso-Ramos ◽  
C. Cameron Yin ◽  
Juliana E. Hidalgo-Lopez ◽  
Sebastian Berisha ◽  
...  
Keyword(s):  
Treatment Effectiveness ◽  
Myeloproliferative Neoplasms ◽  
Spectroscopic Imaging ◽  
Response To Treatment ◽  
Label Free ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging ◽  
Bone Marrow Function ◽  
Hematoxylin And Eosin ◽  
Grading Standards

AbstractOsteosclerosis and myefibrosis are complications of myeloproliferative neoplasms. These disorders result in excess growth of trabecular bone and collagen fibers that replace hematopoietic cells, resulting in abnormal bone marrow function. Treatments using imatinib and JAK2 pathway inhibitors can be effective on osteosclerosis and fibrosis, therefore accurate grading is critical for tracking treatment effectiveness. Current grading standards use a four-class system based on analysis of biopsies stained with three histological stains: hematoxylin and eosin (H&E), Masson’s trichrome, and reticulin. However, conventional grading can be subjective and imprecise, impacting the effectiveness of treatment. In this paper, we demonstrate that mid-infrared spectroscopic imaging may serve as a quantitative diagnostic tool for quantitatively tracking disease progression and response to treatment. The proposed approach is label-free and provides automated quantitative analysis of osteosclerosis and collagen fibrosis.

scholarly journals A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression

2016 ◽  
Vol 89 (5) ◽  
pp. 1153-1159 ◽  
Author(s):  
Vishal K. Varma ◽  
Andre Kajdacsy-Balla ◽  
Sanjeev K. Akkina ◽  
Suman Setty ◽  
Michael J. Walsh
Keyword(s):  
Diabetic Nephropathy ◽  
Spectroscopic Imaging ◽  
Label Free ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging

scholarly journals Rapid and label-free classification of human glioma cells by infrared spectroscopic imaging

2008 ◽  
Vol 73A (12) ◽  
pp. 1158-1164 ◽  
Author(s):  
Gerald Steiner ◽  
Saskia Küchler ◽  
Andreas Hermann ◽  
Edmund Koch ◽  
Reiner Salzer ◽  
...  
Keyword(s):  
Glioma Cells ◽  
Spectroscopic Imaging ◽  
Label Free ◽  
Human Glioma ◽  
Human Glioma Cells ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging ◽  
Free Classification

scholarly journals Detection and Quantification of Myocardial Fibrosis Using Stain-Free Infrared Spectroscopic Imaging

2021 ◽  
Author(s):  
Eric Zimmermann ◽  
Sudipta S. Mukherjee ◽  
Kianoush Falahkheirkhah ◽  
Mark C. Gryka ◽  
Andre Kajdacsy-Balla ◽  
...  
Keyword(s):  
Myocardial Fibrosis ◽  
Cardiac Tissue ◽  
Infrared Imaging ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Spectroscopic Imaging ◽  
Quantitative Agreement ◽  
Label Free ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging

Context.— Myocardial fibrosis underpins a number of cardiovascular conditions and is difficult to identify with standard histologic techniques. Challenges include imaging, defining an objective threshold for classifying fibrosis as mild or severe, as well as understanding the molecular basis for these changes. Objective.— To develop a novel, rapid, label-free approach to accurately measure and quantify the extent of fibrosis in cardiac tissue using infrared spectroscopic imaging. Design.— We performed infrared spectroscopic imaging and combined that with advanced machine learning–based algorithms to assess fibrosis in 15 samples from patients belonging to the following 3 classes: (1) nonpathologic (control) donor hearts; (2) patients receiving transplant; and (3) tissue from patients undergoing implantation of ventricular assist device. Results.— Our results show excellent sensitivity and accuracy for detecting myocardial fibrosis as demonstrated by high area under the curve of 0.998 in the receiver-operating characteristic curve measured from infrared imaging. Fibrosis of various morphologic subtypes are then demonstrated with virtually generated picrosirius red images, which show good visual and quantitative agreement (correlation coefficient = 0.92, ρ = 7.76 × 10−15) with stained images of the same sections. Underlying molecular composition of the different subtypes were investigated with infrared spectra showing reproducible differences presumably arising from differences in collagen subtypes and/or crosslinking. Conclusions.— Infrared imaging can be a powerful tool in studying myocardial fibrosis and gleaning insights into the underlying chemical changes that accompany it. Emerging methods suggest that the proposed approach is compatible with conventional optical microscopy and its consistency makes it translatable to the clinical setting for real-time diagnoses as well as for objective and quantitative research.

scholarly journals Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis

2017 ◽  
Vol 92 ◽  
pp. 14-17 ◽  
Author(s):  
Shaiju S. Nazeer ◽  
Hari Sreedhar ◽  
Vishal K. Varma ◽  
David Martinez-Marin ◽  
Christine Massie ◽  
...  
Keyword(s):  
Biochemical Analysis ◽  
Spectroscopic Imaging ◽  
Label Free ◽  
Tissue Fibrosis ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging

scholarly journals Label-free Identification of Antibody-mediated Rejection in Cardiac Allograft Biopsies Using Infrared Spectroscopic Imaging

2019 ◽  
Vol 103 (4) ◽  
pp. 698-704
Author(s):  
Imran Uraizee ◽  
Vishal K. Varma ◽  
Hari Sreedhar ◽  
Francesca Gambacorta ◽  
Shaiju S. Nazeer ◽  
...  
Keyword(s):  
Spectroscopic Imaging ◽  
Cardiac Allograft ◽  
Label Free ◽  
Antibody Mediated Rejection ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging

Label-Free Infrared Spectroscopic Imaging Reveals Heterogeneity of β-Sheet Aggregates in Alzheimer’s Disease

2021 ◽  
pp. 9662-9671
Author(s):  
Matthew P. Confer ◽  
Brooke M. Holcombe ◽  
Abigail G. Foes ◽  
John M. Holmquist ◽  
Savannah C. Walker ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Spectroscopic Imaging ◽  
Label Free ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging ◽  
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