Label-free molecular imaging

2014 ◽  
Author(s):  
Junqi Zhang ◽  
Qi Li ◽  
Rongxin Fu ◽  
Tongzhou Wang ◽  
Ruliang Wang ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Label Free

scholarly journals Coarse Raman and optical diffraction tomographic imaging enable label-free phenotyping of isogenic breast cancer cells of varying metastatic potential

2020 ◽  
Author(s):  
Santosh Kumar Paidi ◽  
Vaani Shah ◽  
Piyush Raj ◽  
Kristine Glunde ◽  
Rishikesh Pandey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Molecular Imaging ◽  
Single Cell ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Metastatic Potential ◽  
Optical Diffraction ◽  
Multivariate Curve Resolution ◽  
Label Free

AbstractIdentification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive underscoring the need to marry emerging imaging techniques with tumor biology. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging the molecular specificity of Raman spectroscopy, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also leverage multivariate curve resolution – alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.

scholarly journals Introduction to Infrared and Raman-Based Biomedical Molecular Imaging and Comparison with Other Modalities

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5547
Author(s):  
Carlos F. G. C. Geraldes
Keyword(s):  
Computed Tomography ◽  
Molecular Imaging ◽  
Single Photon ◽  
Ex Vivo ◽  
Photon Emission ◽  
Raman Imaging ◽  
Emission Computed Tomography ◽  
Label Free ◽  
Advantages And Disadvantages

Molecular imaging has rapidly developed to answer the need of image contrast in medical diagnostic imaging to go beyond morphological information to include functional differences in imaged tissues at the cellular and molecular levels. Vibrational (infrared (IR) and Raman) imaging has rapidly emerged among the molecular imaging modalities available, due to its label-free combination of high spatial resolution with chemical specificity. This article presents the physical basis of vibrational spectroscopy and imaging, followed by illustration of their preclinical in vitro applications in body fluids and cells, ex vivo tissues and in vivo small animals and ending with a brief discussion of their clinical translation. After comparing the advantages and disadvantages of IR/Raman imaging with the other main modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography/single-photon emission-computed tomography (PET/SPECT), ultrasound (US) and photoacoustic imaging (PAI), the design of multimodal probes combining vibrational imaging with other modalities is discussed, illustrated by some preclinical proof-of-concept examples.

Label-free molecular imaging of immunological synapses between dendritic and T cells by Raman micro-spectroscopy

The Analyst ◽  
2010 ◽  
Vol 135 (12) ◽  
pp. 3205 ◽  
Author(s):  
Alina Bogumila Zoladek ◽  
Ramneek Kaur Johal ◽  
Samuel Garcia-Nieto ◽  
Flavius Pascut ◽  
Kevin M. Shakesheff ◽  
...  
Keyword(s):  
T Cells ◽  
Molecular Imaging ◽  
Label Free ◽  
Immunological Synapses

scholarly journals Label-free in vivo molecular imaging of underglycosylated mucin-1 expression in tumour cells

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Xiaolei Song ◽  
Raag D. Airan ◽  
Dian R. Arifin ◽  
Amnon Bar-Shir ◽  
Deepak K. Kadayakkara ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Tumour Cells ◽  
Label Free ◽  
Mucin 1

scholarly journals Label-free molecular imaging of bacterial communities of the opportunistic pathogen Pseudomonas aeruginosa

2016 ◽  
Author(s):  
Nameera Baig ◽  
Sneha Polisetti ◽  
Nydia Morales-Soto ◽  
Sage J. B. Dunham ◽  
Jonathan V. Sweedler ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Molecular Imaging ◽  
Bacterial Communities ◽  
Opportunistic Pathogen ◽  
Label Free

scholarly journals Label-free Molecular Imaging and Analysis by Raman Spectroscopy

2018 ◽  
Vol 51 (3) ◽  
pp. 101-110 ◽  
Author(s):  
Yasuaki Kumamoto ◽  
Yoshinori Harada ◽  
Tetsuro Takamatsu ◽  
Hideo Tanaka
Keyword(s):  
Raman Spectroscopy ◽  
Molecular Imaging ◽  
Label Free

scholarly journals Quantitative temporal interrogation in 3D of bioengineered human cartilage using multimodal label-free imaging

2018 ◽  
Vol 10 (10) ◽  
pp. 635-645 ◽  
Author(s):  
Catarina Costa Moura ◽  
Stuart A. Lanham ◽  
Tual Monfort ◽  
Konstantinos N. Bourdakos ◽  
Rahul S. Tare ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Label Free ◽  
Human Cartilage ◽  
Phenotypic Characterisation

Multimodal label-free molecular imaging allows 3D phenotypic characterisation and quantitation of bioengineered cartilage non-invasively and non-destructively.

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