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Special Issue "Advanced Spectroscopy, Imaging and Sensing in Biomedicine"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Guest Editor
Dr. Anna Chiara De Luca

Biophotonics and Advanced Microscopies Lab, Institute of Protein Biochemistry-IBP, National Research Council (CNR), Via Pietro Castellino n.111, 80131 Napoli, Italy
Website | E-Mail
Interests: biophotonics, Raman spectroscopy, SERS, bioimaging, correlative microscopy, cell imaging and sensing, cancer, biosensors
Guest Editor
Dr. Stefano Managò

Biophotonics and Advanced Microscopies Lab, Institute of Protein Biochemistry-IBP, National Research Council (CNR), Via Pietro Castellino n.111, 80131 Napoli, Italy
Website | E-Mail
Interests: biophotonics, Raman spectroscopy, SERS, bioimaging, cancer, biosensors
Guest Editor
Dr. Ilaria Rea

Functional Nanomaterials and Interfaces Lab, Institute for Microelectronics and Microsystems - IMM, National Research Council (CNR), Via Pietro Castellino n.111, 80131 Napoli, Italy
Website | E-Mail
Interests: nanomaterials; hybrid interfaces; photoluminescence; optical biosensing; drug delivery

Special Issue Information

Dear Colleagues,

Now, and even more in the future, spectroscopy and photonics will be a strong key enabler for many techniques that can be exploited for high-resolution bioimaging and biosensing at cellular, intracellular, and bulk tissue levels. This Special Issue intends to capitalize on the recent progress in advanced spectroscopy, imaging, and sensing for the investigation of biological systems. Biophotonics spectroscopic and imaging approaches are ideally suited for the early detection of diseases and sensing applications including biomarkers detection, quantification, or mapping; cells’ identification and sorting; and to assess response to therapy. The physical principles behind each technique are emphasized on examining the advantages and limitations of each for biomedical applications. Fluorescence microscopy, Raman/SERS imaging, and single molecule microscopy are but a few of the advanced photonic techniques emerging as powerful tools to study the response of biosystems at the level of single cells, or even single molecules, because they are non-invasive, offer high detection sensitivity, and allow functional imaging at micro- or nano-scale resolution. Additionally, a variety of molecular and nanoparticle probes capable of tagging and highlighting the location of biological components that would otherwise be invisible under the microscope have been recently proposed.

To promote the latest advances in exploring spectroscopic/imaging approaches for the identification, understanding, and treatment of diseases, from the cellular/molecular level to macroscopic applications, we invite the submission of original research or review articles to this Special Issue.

Topics of the Special Issue are listed below, but other topics related to bioimaging and biosensing are also welcome. 

Dr. Anna Chiara De Luca
Dr. Stefano Managò
Dr. Ilaria Rea
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Advanced microscopy in biomedical imaging and sensing
  • Raman/SERS spectroscopic imaging and sensing
  • Optical sensors for biomarkers
  • Optical fibers and sensors for biomedicine
  • Multimodality optical diagnostic systems
  • Fluorescence and super resolution in biomedical imaging and sensing
  • Nanomaterials for intracellular imaging
  • Nanomaterials for optical sensing
  • Biophotonics

Published Papers (3 papers)

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Research

Open AccessArticle
Multispectral Depth-Resolved Fluorescence Lifetime Spectroscopy Using SPAD Array Detectors and Fiber Probes
Sensors 2019, 19(12), 2678; https://doi.org/10.3390/s19122678
Received: 27 May 2019 / Revised: 10 June 2019 / Accepted: 12 June 2019 / Published: 13 June 2019
PDF Full-text (1687 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Single Photon Avalanche Diode (SPAD) arrays are increasingly exploited and have demonstrated potential in biochemical and biomedical research, both for imaging and single-point spectroscopy applications. In this study, we explore the application of SPADs together with fiber-optic-based delivery and collection geometry to realize [...] Read more.
Single Photon Avalanche Diode (SPAD) arrays are increasingly exploited and have demonstrated potential in biochemical and biomedical research, both for imaging and single-point spectroscopy applications. In this study, we explore the application of SPADs together with fiber-optic-based delivery and collection geometry to realize fast and simultaneous single-point time-, spectral-, and depth-resolved fluorescence measurements at 375 nm excitation light. Spectral information is encoded across the columns of the array through grating-based dispersion, while depth information is encoded across the rows thanks to a linear arrangement of probe collecting fibers. The initial characterization and validation were realized against layered fluorescent agarose-based phantoms. To verify the practicality and feasibility of this approach in biological specimens, we measured the fluorescence signature of formalin-fixed rabbit aorta samples derived from an animal model of atherosclerosis. The initial results demonstrate that this detection configuration can report fluorescence spectral and lifetime contrast originating at different depths within the specimens. We believe that our optical scheme, based on SPAD array detectors and fiber-optic probes, constitute a powerful and versatile approach for the deployment of multidimensional fluorescence spectroscopy in clinical applications where information from deeper tissue layers is important for diagnosis. Full article
(This article belongs to the Special Issue Advanced Spectroscopy, Imaging and Sensing in Biomedicine)
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Open AccessArticle
In-Cell Determination of Lactate Dehydrogenase Activity in a Luminal Breast Cancer Model – ex vivo Investigation of Excised Xenograft Tumor Slices Using dDNP Hyperpolarized [1-13C]pyruvate
Sensors 2019, 19(9), 2089; https://doi.org/10.3390/s19092089
Received: 22 March 2019 / Revised: 18 April 2019 / Accepted: 30 April 2019 / Published: 5 May 2019
PDF Full-text (2857 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
[1-13C]pyruvate, the most widely used compound in dissolution-dynamic nuclear polarization (dDNP) magnetic resonance (MR), enables the visualization of lactate dehydrogenase (LDH) activity. This activity had been demonstrated in a wide variety of cancer models, ranging from cultured cells, to xenograft models, [...] Read more.
[1-13C]pyruvate, the most widely used compound in dissolution-dynamic nuclear polarization (dDNP) magnetic resonance (MR), enables the visualization of lactate dehydrogenase (LDH) activity. This activity had been demonstrated in a wide variety of cancer models, ranging from cultured cells, to xenograft models, to human tumors in situ. Here we quantified the LDH activity in precision cut tumor slices (PCTS) of breast cancer xenografts. The Michigan Cancer Foundation-7 (MCF7) cell-line was chosen as a model for the luminal breast cancer type which is hormone responsive and is highly prevalent. The LDH activity, which was manifested as [1-13C]lactate production in the tumor slices, ranged between 3.8 and 6.1 nmole/nmole adenosine tri-phosphate (ATP) in 1 min (average 4.6 ± 1.0) on three different experimental set-ups consisting of arrested vs. continuous perfusion and non-selective and selective RF pulsation schemes and combinations thereof. This rate was converted to an expected LDH activity in a mass ranging between 3.3 and 5.2 µmole/g in 1 min, using the ATP level of these tumors. This indicated the likely utility of this approach in clinical dDNP of the human breast and may be useful as guidance for treatment response assessment in a large number of tumor types and therapies ex vivo. Full article
(This article belongs to the Special Issue Advanced Spectroscopy, Imaging and Sensing in Biomedicine)
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Open AccessArticle
Deep Learning-Based Framework for In Vivo Identification of Glioblastoma Tumor using Hyperspectral Images of Human Brain
Sensors 2019, 19(4), 920; https://doi.org/10.3390/s19040920
Received: 24 January 2019 / Revised: 18 February 2019 / Accepted: 20 February 2019 / Published: 22 February 2019
Cited by 2 | PDF Full-text (10305 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor resection in [...] Read more.
The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor resection in real-time during neurosurgical procedures is a current clinical need. Hyperspectral imaging is a non-contact, non-ionizing, and label-free imaging modality that can assist surgeons during this challenging task without using any contrast agent. In this work, we present a deep learning-based framework for processing hyperspectral images of in vivo human brain tissue. The proposed framework was evaluated by our human image database, which includes 26 in vivo hyperspectral cubes from 16 different patients, among which 258,810 pixels were labeled. The proposed framework is able to generate a thematic map where the parenchymal area of the brain is delineated and the location of the tumor is identified, providing guidance to the operating surgeon for a successful and precise tumor resection. The deep learning pipeline achieves an overall accuracy of 80% for multiclass classification, improving the results obtained with traditional support vector machine (SVM)-based approaches. In addition, an aid visualization system is presented, where the final thematic map can be adjusted by the operating surgeon to find the optimal classification threshold for the current situation during the surgical procedure. Full article
(This article belongs to the Special Issue Advanced Spectroscopy, Imaging and Sensing in Biomedicine)
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