The three main steps that are of paramount importance for the accurate and timely diagnosis of pathologies that reflect in tissular modifications, such as cancers or neurodegenerative diseases, are: ‘detection’, ‘characterization’ and ‘confirmation’. Histopathology plays an essential role concerning the latter two, approaches based on excisional biopsy and tissue staining being currently regarded as the golden standard. Over the past couple of decades, significant efforts have been placed on transferring laser scanning microscopy (LSM) to the realm of tissue characterization. The imaging techniques belonging to this family hold great potential for overcoming some of the important disadvantages of traditional histopathology approaches, namely long diagnosis time, invasiveness, artefacts, sampling error, time consumption, high costs, and interpretive variability. The ‘non-invasive’ character of LSM techniques derives from their capabilities to exploit various endogenous optical signals generated by the tissues upon interaction with a laser beam and to provide optical sections (virtual biopsies) that reflect the tissular architecture at controlled depths. LSM techniques can thus provide label-free information of similar pathologic relevance to the information collected for characterization/confirmation purposes with traditional histopathology approaches, being capable of probing optical properties of tissues with deep implications for resolving important anatomical and physiological aspects which represent hallmarks for disease predisposition and progression. To date techniques such as Confocal Laser Scanning Microscopy, Fluorescence Lifetime Imaging, Two-Photon Excitation Microscopy, Second Harmonic Generation Microscopy, Coherent Anti-Stokes Raman Scattering Microscopy, as well as other LSM variants, have already been demonstrated to be powerful tools for investigating tissue morphology, functionality and biochemical composition with high spatial and temporal resolution. In the opinion of many, they are likely to become at some point in the future the central element of the default tissue characterization frameworks for both ex- and in-vivo assays. However, a series of important challenges still lie en route concretizing this ambitious perspective, such as data interpretation problems, difficulty in collecting LSM datasets inside the human body or insufficient penetration depth to probe particular relevant regions in the tissue volume. Furthermore, combining the outputs of complementary imaging techniques used to investigate a specific region is not always easy.
This Research Topic welcomes original research articles, perspectives and reviews addressing the latest knowledge about relevant subjects that can promote the further translation of LSM techniques to clinical practice as tools that can enhance the diagnostic sensitivity and specificity for pathologies whose timely and accurate assessment currently suffers from the limitations of traditional histopathology approaches. Contributions on the following LSM topics will be particularly encouraged:
- Disease diagnostics based on optical signals generated by endogenous chromophores
- Tissue characterization based on label-free probing of collagen organization
- Pathology assessment using the vibrational signatures of molecules
- Multimodal LSM imaging and joint exploitation of complementary datasets for accurate tissue characterization
- Image processing methods for enhanced visualization of LSM data sets collected on tissues
- LSM oriented computer vision and machine learning methods for automated tissue screening and disease diagnostics
- LSM instrumentation developments that lead to faster, deeper and more reliable tissue imaging
The three main steps that are of paramount importance for the accurate and timely diagnosis of pathologies that reflect in tissular modifications, such as cancers or neurodegenerative diseases, are: ‘detection’, ‘characterization’ and ‘confirmation’. Histopathology plays an essential role concerning the latter two, approaches based on excisional biopsy and tissue staining being currently regarded as the golden standard. Over the past couple of decades, significant efforts have been placed on transferring laser scanning microscopy (LSM) to the realm of tissue characterization. The imaging techniques belonging to this family hold great potential for overcoming some of the important disadvantages of traditional histopathology approaches, namely long diagnosis time, invasiveness, artefacts, sampling error, time consumption, high costs, and interpretive variability. The ‘non-invasive’ character of LSM techniques derives from their capabilities to exploit various endogenous optical signals generated by the tissues upon interaction with a laser beam and to provide optical sections (virtual biopsies) that reflect the tissular architecture at controlled depths. LSM techniques can thus provide label-free information of similar pathologic relevance to the information collected for characterization/confirmation purposes with traditional histopathology approaches, being capable of probing optical properties of tissues with deep implications for resolving important anatomical and physiological aspects which represent hallmarks for disease predisposition and progression. To date techniques such as Confocal Laser Scanning Microscopy, Fluorescence Lifetime Imaging, Two-Photon Excitation Microscopy, Second Harmonic Generation Microscopy, Coherent Anti-Stokes Raman Scattering Microscopy, as well as other LSM variants, have already been demonstrated to be powerful tools for investigating tissue morphology, functionality and biochemical composition with high spatial and temporal resolution. In the opinion of many, they are likely to become at some point in the future the central element of the default tissue characterization frameworks for both ex- and in-vivo assays. However, a series of important challenges still lie en route concretizing this ambitious perspective, such as data interpretation problems, difficulty in collecting LSM datasets inside the human body or insufficient penetration depth to probe particular relevant regions in the tissue volume. Furthermore, combining the outputs of complementary imaging techniques used to investigate a specific region is not always easy.
This Research Topic welcomes original research articles, perspectives and reviews addressing the latest knowledge about relevant subjects that can promote the further translation of LSM techniques to clinical practice as tools that can enhance the diagnostic sensitivity and specificity for pathologies whose timely and accurate assessment currently suffers from the limitations of traditional histopathology approaches. Contributions on the following LSM topics will be particularly encouraged:
- Disease diagnostics based on optical signals generated by endogenous chromophores
- Tissue characterization based on label-free probing of collagen organization
- Pathology assessment using the vibrational signatures of molecules
- Multimodal LSM imaging and joint exploitation of complementary datasets for accurate tissue characterization
- Image processing methods for enhanced visualization of LSM data sets collected on tissues
- LSM oriented computer vision and machine learning methods for automated tissue screening and disease diagnostics
- LSM instrumentation developments that lead to faster, deeper and more reliable tissue imaging
