scholarly journals Label-free digital pathology by infrared imaging

2020 ◽  
Vol 9 (1-2) ◽  
pp. 5-12 ◽  
Author(s):  
Frederik Großerueschkamp ◽  
Klaus Gerwert
Keyword(s):  
Infrared Imaging ◽  
Digital Pathology ◽  
Label Free

Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging

2021 ◽  
pp. 1-9
Author(s):  
Frederik Großerueschkamp ◽  
Hendrik Jütte ◽  
Klaus Gerwert ◽  
Andrea Tannapfel
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Infrared Imaging ◽  
Digital Pathology ◽  
Human Observer ◽  
Label Free ◽  
Mathematical Methods ◽  
Thin Sections ◽  
Innovative Methods ◽  
Primary Meaning

<b><i>Background:</i></b> Digital pathology, in its primary meaning, describes the utilization of computer screens to view scanned histology slides. Digitized tissue sections can be easily shared for a second opinion. In addition, it allows tissue image analysis using specialized software to identify and measure events previously observed by a human observer. These tissue-based readouts were highly reproducible and precise. Digital pathology has developed over the years through new technologies. Currently, the most discussed development is the application of artificial intelligence to automatically analyze tissue images. However, even new label-free imaging technologies are being developed to allow imaging of tissues by means of their molecular composition. <b><i>Summary:</i></b> This review provides a summary of the current state-of-the-art and future digital pathologies. Developments in the last few years have been presented and discussed. In particular, the review provides an outlook on interesting new technologies (e.g., infrared imaging), which would allow for deeper understanding and analysis of tissue thin sections beyond conventional histopathology. <b><i>Key Messages:</i></b> In digital pathology, mathematical methods are used to analyze images and draw conclusions about diseases and their progression. New innovative methods and techniques (e.g., label-free infrared imaging) will bring significant changes in the field in the coming years.

scholarly journals Label free technologies 3: infrared imaging applied to paraffinized tissue microarrays for colon cancer diagnosis

2013 ◽  
Vol 8 (S1) ◽  
Author(s):  
Ganesh D Sockalingum ◽  
Jayakrupakar Nallala ◽  
Marie-Danièle Diebold ◽  
Cyril Gobinet ◽  
Olivier Piot ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Diagnosis ◽  
Infrared Imaging ◽  
Tissue Microarrays ◽  
Label Free

scholarly journals Liquid-Phase Peak Force Infrared Microscopy for Chemical Nano-imaging and Spectroscopy of Soft Matters

2020 ◽  
Author(s):  
Haomin Wang ◽  
Joseph M. González-Fialkowski ◽  
Wenqian Li ◽  
Qing Xie ◽  
Yan Yu ◽  
...  
Keyword(s):  
Liquid Phase ◽  
Infrared Imaging ◽  
Polymer Surface ◽  
Fluid Phase ◽  
Peak Force ◽  
Label Free ◽  
Imaging And Spectroscopy ◽  
Nano Imaging ◽  
Solid Liquid Interface ◽  
Soft Matters

<a>Peak force infrared (PFIR) microscopy is an emerging atomic force microscopy that bypasses Abbe’s diffraction limit in achieving chemical nano-imaging and spectroscopy. The PFIR microscopy mechanically detects the infrared photothermal responses in the dynamic tip-sample contact of peak force tapping mode, and has been applied for a variety of samples, ranging from soft matters, photovoltaics heterojunctions, to polaritonic materials under the air conditions. In this article, we develop and demonstrate the PFIR microscopy in the liquid phase for soft matters and biological samples. With the capability of controlling fluid compositions on demand, the liquid-phase peak force infrared (LiPFIR) microscopy enables <i>in situ </i>tracking the polymer surface reorganization in fluids and detecting the product of click chemical reaction in the aqueous phase. Both broadband spectroscopy and infrared imaging with ~ 10 nm spatial resolution are benchmarked in the fluid phase, together with complementary mechanical information. We also demonstrate the LiPFIR microscopy on revealing the chemical composition of a budding site of yeast cell wall particles in water as an application on biological structures. The label-free, non-destructive chemical nano-imaging and spectroscopic capabilities of the LiPFIR microscopy will facilitate the investigations of soft matters and their transformations at the solid/liquid interface.</a>

scholarly journals Biochemical Changes in Irradiated Oral Mucosa: A FTIR Spectroscopic Study

Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
Helena Ukkonen ◽  
Simo Vuokila ◽  
Jopi Mikkonen ◽  
Hannah Dekker ◽  
Engelbert Schulten ◽  
...  
Keyword(s):  
Oral Mucosa ◽  
Infrared Imaging ◽  
Objective Assessment ◽  
Principal Component ◽  
Superficial Layer ◽  
Label Free ◽  
Differential Distribution ◽  
Biochemical Alterations ◽  
Patient Groups ◽  
Therapeutic Irradiation

Radiation exposure during the course of treatment in head and neck cancer (HNC) patients can induce both structural and biochemical anomalies. The present study is focused on utilizing infrared imaging for the identification of the minor biochemical alterations in the oral mucosa. Chemical maps generated using glycoprotein band indicates its differential distribution along the superficial layer. Spectra extracted from this layer suggests changes in overall nucleic acid and protein content in response to the therapeutic irradiation. Discrimination among control and irradiated groups have been achieved using principal component analysis. Findings of this preliminary study further support prospective utilization of Fourier Transform InfraRed (FTIR) imaging as a non-destructive, label-free tool for objective assessment of the oral mucosa in patient groups with or without radiation therapy.

scholarly journals Label-free SARS-CoV-2 detection and classification using phase imaging with computational specificity

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Neha Goswami ◽  
Yuchen R. He ◽  
Yu-Heng Deng ◽  
Chamteut Oh ◽  
Nahil Sobh ◽  
...  
Keyword(s):  
Neural Network ◽  
Influenza A ◽  
Digital Pathology ◽  
Ground Truth ◽  
Optical Path Length ◽  
Phase Imaging ◽  
Processing Unit ◽  
Label Free ◽  
Interferometric Method ◽  
Viral Particles

AbstractEfforts to mitigate the COVID-19 crisis revealed that fast, accurate, and scalable testing is crucial for curbing the current impact and that of future pandemics. We propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and classification. An ultrasensitive interferometric method was used to image four virus types with nanoscale optical path-length sensitivity. Pairing these data with fluorescence images for ground truth, we trained semantic segmentation models based on U-Net, a particular type of convolutional neural network. The trained network was applied to classify the viruses from the interferometric images only, containing simultaneously SARS-CoV-2, H1N1 (influenza-A virus), HAdV (adenovirus), and ZIKV (Zika virus). Remarkably, due to the nanoscale sensitivity in the input data, the neural network was able to identify SARS-CoV-2 vs. the other viruses with 96% accuracy. The inference time for each image is 60 ms, on a common graphic-processing unit. This approach of directly imaging unlabeled viral particles may provide an extremely fast test, of less than a minute per patient. As the imaging instrument operates on regular glass slides, we envision this method as potentially testing on patient breath condensates. The necessary high throughput can be achieved by translating concepts from digital pathology, where a microscope can scan hundreds of slides automatically.

scholarly journals Liquid-Phase Peak Force Infrared Microscopy for Chemical Nano-imaging and Spectroscopy of Soft Matters

2020 ◽  
Author(s):  
Haomin Wang ◽  
Joseph M. González-Fialkowski ◽  
Wenqian Li ◽  
Qing Xie ◽  
Yan Yu ◽  
...  
Keyword(s):  
Liquid Phase ◽  
Infrared Imaging ◽  
Polymer Surface ◽  
Fluid Phase ◽  
Peak Force ◽  
Label Free ◽  
Imaging And Spectroscopy ◽  
Nano Imaging ◽  
Solid Liquid Interface ◽  
Soft Matters

<a>Peak force infrared (PFIR) microscopy is an emerging atomic force microscopy that bypasses Abbe’s diffraction limit in achieving chemical nano-imaging and spectroscopy. The PFIR microscopy mechanically detects the infrared photothermal responses in the dynamic tip-sample contact of peak force tapping mode, and has been applied for a variety of samples, ranging from soft matters, photovoltaics heterojunctions, to polaritonic materials under the air conditions. In this article, we develop and demonstrate the PFIR microscopy in the liquid phase for soft matters and biological samples. With the capability of controlling fluid compositions on demand, the liquid-phase peak force infrared (LiPFIR) microscopy enables <i>in situ </i>tracking the polymer surface reorganization in fluids and detecting the product of click chemical reaction in the aqueous phase. Both broadband spectroscopy and infrared imaging with ~ 10 nm spatial resolution are benchmarked in the fluid phase, together with complementary mechanical information. We also demonstrate the LiPFIR microscopy on revealing the chemical composition of a budding site of yeast cell wall particles in water as an application on biological structures. The label-free, non-destructive chemical nano-imaging and spectroscopic capabilities of the LiPFIR microscopy will facilitate the investigations of soft matters and their transformations at the solid/liquid interface.</a>

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.

Long-Wave Infrared Imaging for Intraoperative Cancer Detection—What is the True Temperature of a Cancer?

2021 ◽  
pp. 155335062110460
Author(s):  
Stephanie Vaughn ◽  
Robin Ruthazer ◽  
Andrew Rosenblatt ◽  
Roger L Jenkins ◽  
Andrea P Sorcini ◽  
...  
Keyword(s):  
Cancer Detection ◽  
Temperature Difference ◽  
Infrared Imaging ◽  
Surrounding Tissue ◽  
True Temperature ◽  
Diagnostic Study ◽  
Label Free ◽  
Long Wave ◽  
Long Wave Infrared

Background During cancer operations, the cancer itself is often hard to delineate—buried beneath healthy tissue and lacking discernable differences from the surrounding healthy organ. Long-wave infrared, or thermal, imaging poses a unique solution to this problem, allowing for the real-time label-free visualization of temperature deviations within the depth of tissues. The current study evaluated this technology for intraoperative cancer detection. Methods In this diagnostic study, patients with gastrointestinal, hepatobiliary, and renal cancers underwent long-wave infrared imaging of the malignancy during routine operations. Results It was found that 74% were clearly identifiable as hypothermic anomalies. The average temperature difference was 2.4°C (range 0.7 to 5.0) relative to the surrounding tissue. Cancers as deep as 3.3 cm from the surgical surface were visualized. Yet, 79% of the images had clinically relevant false positive signals [median 3 per image (range 0 to 10)] establishing an accuracy of 47%. Analysis suggests that the degree of temperature difference was primarily determined by features within the cancer and not peritumoral changes in the surrounding tissue. Conclusion These findings provide important information on the unexpected hypothermal properties of intra-abdominal cancers, directions for future use of intraoperative long-wave infrared imaging, and new knowledge about the in vivo thermal energy expenditure of cancers and peritumoral tissue.

Label-free phenotyping of peripheral blood lymphocytes by infrared imaging

The Analyst ◽  
2015 ◽  
Vol 140 (7) ◽  
pp. 2247-2256 ◽  
Author(s):  
M. Verdonck ◽  
S. Garaud ◽  
H. Duvillier ◽  
K. Willard-Gallo ◽  
E. Goormaghtigh
Keyword(s):  
Peripheral Blood ◽  
Infrared Imaging ◽  
Peripheral Blood Lymphocytes ◽  
Lymphocyte Subpopulations ◽  
Label Free ◽  
Ftir Imaging ◽  
Blood Lymphocytes ◽  
Antibody Labelling

FTIR imaging enables to effectively discriminate lymphocyte subpopulations without antibody labelling.

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