The creation of sharp, detailed images of thick biological samples, such as those of human tissue, are now possible using an optical microscopy method developed by researchers at the Italian Institute of Technology (IIT). The team aimed to achieve the full resolution and signal to noise (SNR) benefits of image scanning microscopy (ISM). At the same time, it wanted to improve optical sectioning for complex, high-density samples.
The resulting imaging technique, which the researchers named superresolution sectioning image scanning microscopy (s2ISM), could help scientists gain insight into the aging process and the origin of certain diseases by studying the biomolecular processes inside living cells.
The technique reconstructs an image with digital and optical superresolution, high SNR, and enhanced optical sectioning from single-plane acquisition. It provides superresolution and optical sectioning simultaneously.
An instrument that acts like a light scalpel penetrates the sample deeply and observes the sample without damaging it. A small array of sensors captures the light at the point where it hits, and captures the various ways the light spreads in the sample. Once this information is recorded, a reconstruction algorithm processes the information, identifying the path of the light through the sample and producing sharper, better-sectioned images, without losing signal quality.
“The optical microscope used is equipped with an array of [single-photon avalanche diode] detectors, capable of detecting the arrival of individual photons with very high spatial and temporal precision,” researcher Alessandro Zunino said. “This characteristic not only improves the resolution and optical sectioning, but also enables advanced techniques such as fluorescence lifetime, which are fundamental to explore molecular dynamics in living tissues and to provide functional as well as structural information.”
Previous approaches to optical microscopy made it difficult to observe thick samples in detail, because the contrast in the image was hindered by the high density of the samples’ structures.
“What we did was rethink the way microscopes measure the light that hits the samples under observation, improving both the spatial resolution and the contrast when studying thick tissues, where background light would normally overpower their structure, creating noise in the images,” researcher Giuseppe Vicidomini, who coordinated the study, said.
The researchers formulated a comprehensive theoretical framework for their approach and validated the approach with images of biological samples captured using a custom setup equipped with a SPAD array detector. They demonstrated the s2ISM technique by exciting fluorescence emission in both linear and nonlinear regimes. Also, they generalized the reconstruction algorithm for fluorescence lifetime imaging.
The s2 microscopy method requires no changes in the optical system and can be extended to any laser scanning microscopy technique.
The new microscopy technique has many potential applications. For example, it could be used to study brain tissue, tumors, organoids, and other biological systems and observe the processes of living cells to better understand disease progression. In the pharmaceutical field, the technique could be used to visualize in real time how drugs interact with living biological tissues, speeding the discovery of new treatments.
The s2 technique is open-access and the code is provided as an open-source Python package; any laboratory can adopt, modify, and apply this technique at no cost and without the need for complex equipment. To simplify the application of s2ISM, the researchers have proposed a rigorous strategy to automatically extract the relevant parameters needed to run the algorithm.
The team hopes that making the software and data available for broad, rapid dissemination will encourage further innovation within the scientific community, especially in the fields of optical microscopy and life sciences.
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The resulting imaging technique, which the researchers named superresolution sectioning image scanning microscopy (s2ISM), could help scientists gain insight into the aging process and the origin of certain diseases by studying the biomolecular processes inside living cells.
The technique reconstructs an image with digital and optical superresolution, high SNR, and enhanced optical sectioning from single-plane acquisition. It provides superresolution and optical sectioning simultaneously.
An instrument that acts like a light scalpel penetrates the sample deeply and observes the sample without damaging it. A small array of sensors captures the light at the point where it hits, and captures the various ways the light spreads in the sample. Once this information is recorded, a reconstruction algorithm processes the information, identifying the path of the light through the sample and producing sharper, better-sectioned images, without losing signal quality.
“The optical microscope used is equipped with an array of [single-photon avalanche diode] detectors, capable of detecting the arrival of individual photons with very high spatial and temporal precision,” researcher Alessandro Zunino said. “This characteristic not only improves the resolution and optical sectioning, but also enables advanced techniques such as fluorescence lifetime, which are fundamental to explore molecular dynamics in living tissues and to provide functional as well as structural information.”
Previous approaches to optical microscopy made it difficult to observe thick samples in detail, because the contrast in the image was hindered by the high density of the samples’ structures.
“What we did was rethink the way microscopes measure the light that hits the samples under observation, improving both the spatial resolution and the contrast when studying thick tissues, where background light would normally overpower their structure, creating noise in the images,” researcher Giuseppe Vicidomini, who coordinated the study, said.
The researchers formulated a comprehensive theoretical framework for their approach and validated the approach with images of biological samples captured using a custom setup equipped with a SPAD array detector. They demonstrated the s2ISM technique by exciting fluorescence emission in both linear and nonlinear regimes. Also, they generalized the reconstruction algorithm for fluorescence lifetime imaging.
The s2 microscopy method requires no changes in the optical system and can be extended to any laser scanning microscopy technique.
The new microscopy technique has many potential applications. For example, it could be used to study brain tissue, tumors, organoids, and other biological systems and observe the processes of living cells to better understand disease progression. In the pharmaceutical field, the technique could be used to visualize in real time how drugs interact with living biological tissues, speeding the discovery of new treatments.
The s2 technique is open-access and the code is provided as an open-source Python package; any laboratory can adopt, modify, and apply this technique at no cost and without the need for complex equipment. To simplify the application of s2ISM, the researchers have proposed a rigorous strategy to automatically extract the relevant parameters needed to run the algorithm.
The team hopes that making the software and data available for broad, rapid dissemination will encourage further innovation within the scientific community, especially in the fields of optical microscopy and life sciences.
Bio Photonics Research Award
Visit: biophotonicsresearch.com
Nominate Now: https://biophotonicsresearch.com/award-nomination/?ecategory=Awards&rcategory=Awardee
#MeatAnalysis #FluorescenceTech #FoodQuality #FoodSafety #SpectroscopyInFood #MeatAuthentication #RapidDetection #FoodScience #MeatFreshness #MolecularDetection #FoodIndustryInnovation #NonDestructiveTesting #FoodMonitoring #SpectroscopyApplications #QualityControl #AdvancedSpectroscopy #MeatSpoilageDetection #FoodIntegrity #SmartFoodTesting #RealTimeAnalysis #FoodAuthenticity #FoodSafetyInnovation #SpectroscopyResearch #NextGenFoodSafety #InnovativeFoodScience,
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