Correlated Multimodal Imaging (CMI) combines two or more imaging modalities to gather information about the same specimen. It creates a composite view of the sample with multidimensional information about its macro-, meso- and microscopic structure, dynamics, function and chemical composition. Since no single imaging technique can reveal all these details, CMI is the only way to understand biomedical processes and diseases mechanistically and holistically. CMI relies on the joint multidisciplinary expertise of biologists, physicists, chemists, clinicians and computer scientists, and depends on coordinated activities and knowledge transfer between academia and industry, and instrument developers and users. Due to its inherently multidisciplinary and cross-functional nature, the interdisciplinary network and EU-funded COST Action COMULIS (Correlated Multimodal Imaging in Life Sciences) was founded to raise awareness for CMI, train researchers in multimodal approaches, and work towards a scientific mindset that is enthusiastic about interdisciplinary imaging approaches in life sciences.
The field of bioimaging is experiencing several major boosts: The resolution revolution in electron cryo-microscopy (cryo-EM) leads to an exponential increase in resolved single particle structures and is accompanied by a ‘volume resolution’ that allows scanning big volumes at high resolution using for example focused ion beams and scanning electron microscopy (FIB/SEM). The same holds true for advanced light microscopy which routinely resolves subcellular structures both below the diffraction limit (superresolution) and in thick tissue with increased penetration depth (light sheet and multiphoton microscopy). Additionally, frontiers of bioimaging are currently being pushed towards the integration and correlation of several modalities to tackle biomedical research questions holistically and across multiple scales (correlative multimodal imaging, CMI). CMI combines two or more imaging modalities to gather information about the same specimen. It creates a composite view of the sample with multidimensional information about its macro-, meso- and microscopic structure, dynamics, function and chemical composition. Since no single imaging technique can reveal all these details, CMI is the only way to understand biomedical processes and diseases mechanistically and holistically. The goal of this research topic is hence to introduce CMI as a versatile approach in research and diagnostics that can significantly advance life sciences, specifically bridging biological and clinical imaging approaches. At the same time, the field is still in its infancy and it will be an important goal to define quality standards and guidelines for correlation and data handling.
In this context, it is of great interest to highlight these efforts of imaging across scales in a dedicated collection, present commonly-accepted protocols and quality standards for existing CMI approaches, and showcase novel CMI pipelines across scales and their potential to tackle exciting biomedical research questions. This edition will specifically highlight approaches that aim at bridging the gap between preclinical (i.e. micro MRI, microPET, micro CT or OCT) and biological imaging and at promoting corresponding correlation software and open databases. Submissions can be both reviews and original research papers that can cover technical, computational or biomedical aspects of multimodal imaging across scales, and are welcome both from COMULIS members and scientists that are new to the field. We expect submissions from the field of correlative microscopies, such as advanced CLEM approaches including volume electron microscopy, from computational sciences for co-registration of datasets and multimodal data handling strategies, and from the preclinical imaging field.
Correlated Multimodal Imaging (CMI) combines two or more imaging modalities to gather information about the same specimen. It creates a composite view of the sample with multidimensional information about its macro-, meso- and microscopic structure, dynamics, function and chemical composition. Since no single imaging technique can reveal all these details, CMI is the only way to understand biomedical processes and diseases mechanistically and holistically. CMI relies on the joint multidisciplinary expertise of biologists, physicists, chemists, clinicians and computer scientists, and depends on coordinated activities and knowledge transfer between academia and industry, and instrument developers and users. Due to its inherently multidisciplinary and cross-functional nature, the interdisciplinary network and EU-funded COST Action COMULIS (Correlated Multimodal Imaging in Life Sciences) was founded to raise awareness for CMI, train researchers in multimodal approaches, and work towards a scientific mindset that is enthusiastic about interdisciplinary imaging approaches in life sciences.
The field of bioimaging is experiencing several major boosts: The resolution revolution in electron cryo-microscopy (cryo-EM) leads to an exponential increase in resolved single particle structures and is accompanied by a ‘volume resolution’ that allows scanning big volumes at high resolution using for example focused ion beams and scanning electron microscopy (FIB/SEM). The same holds true for advanced light microscopy which routinely resolves subcellular structures both below the diffraction limit (superresolution) and in thick tissue with increased penetration depth (light sheet and multiphoton microscopy). Additionally, frontiers of bioimaging are currently being pushed towards the integration and correlation of several modalities to tackle biomedical research questions holistically and across multiple scales (correlative multimodal imaging, CMI). CMI combines two or more imaging modalities to gather information about the same specimen. It creates a composite view of the sample with multidimensional information about its macro-, meso- and microscopic structure, dynamics, function and chemical composition. Since no single imaging technique can reveal all these details, CMI is the only way to understand biomedical processes and diseases mechanistically and holistically. The goal of this research topic is hence to introduce CMI as a versatile approach in research and diagnostics that can significantly advance life sciences, specifically bridging biological and clinical imaging approaches. At the same time, the field is still in its infancy and it will be an important goal to define quality standards and guidelines for correlation and data handling.
In this context, it is of great interest to highlight these efforts of imaging across scales in a dedicated collection, present commonly-accepted protocols and quality standards for existing CMI approaches, and showcase novel CMI pipelines across scales and their potential to tackle exciting biomedical research questions. This edition will specifically highlight approaches that aim at bridging the gap between preclinical (i.e. micro MRI, microPET, micro CT or OCT) and biological imaging and at promoting corresponding correlation software and open databases. Submissions can be both reviews and original research papers that can cover technical, computational or biomedical aspects of multimodal imaging across scales, and are welcome both from COMULIS members and scientists that are new to the field. We expect submissions from the field of correlative microscopies, such as advanced CLEM approaches including volume electron microscopy, from computational sciences for co-registration of datasets and multimodal data handling strategies, and from the preclinical imaging field.
