Volume 29 Issue S2 | Journal of Biomedical Optics

Journal of Biomedical Optics

VOL. 29 · NO. S2 | June 2024

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Special Issue Honoring Gabriel Popescu, Pioneer in Biomedical Optics (17)

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Special Issue Honoring Gabriel Popescu, Pioneer in Biomedical Optics

Introducing the Special Issue on Label-Free Quantitative Phase Imaging Honoring Prof. Gabriel Popescu, a Pioneer in Biomedical Optics

Stephen Boppart, Catherine Best-Popescu, Randy Bartels, Kevin Eliceiri

Journal of Biomedical Optics, Vol. 29, Issue S2, S22701, (December 2024) https://doi.org/10.1117/1.JBO.29.S2.S22701

TOPICS: Biomedical optics, Phase imaging, Biological imaging, Biomedical applications, Microscopy, Light emitting diodes, Tissues, Reflection, Optical imaging, Engineering

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Perspectives on label-free microscopy of heterogeneous and dynamic biological systems

Dan Pham, Amani Gillette, Jeremiah Riendeau, Kasia Wiech, Emmanuel Contreras Guzman, Rupsa Datta, Melissa Skala

Journal of Biomedical Optics, Vol. 29, Issue S2, S22702, (February 2024) https://doi.org/10.1117/1.JBO.29.S2.S22702

TOPICS: Microscopy, Tissues, Diseases and disorders, Imaging systems, Image analysis, Raman spectroscopy, Cancer, Tumors, Image segmentation, Image resolution

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Swept-source Raman spectroscopy of chemical and biological materials

Jeonggeun Song, Peter T. So, Hongki Yoo, Jeon Woong Kang

Journal of Biomedical Optics, Vol. 29, Issue S2, S22703, (April 2024) https://doi.org/10.1117/1.JBO.29.S2.S22703

TOPICS: Raman spectroscopy, Spectroscopy, Biological samples, Bandpass filters, Tissues, Tunable filters, Spectral resolution, Signal processing, Optical filters, Glucose

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Significance

Raman spectroscopy has been used as a powerful tool for chemical analysis, enabling the noninvasive acquisition of molecular fingerprints from various samples. Raman spectroscopy has proven to be valuable in numerous fields, including pharmaceutical, materials science, and biomedicine. Active research and development efforts are currently underway to bring this analytical instrument into the field, enabling in situ Raman measurements for a wider range of applications. Dispersive Raman spectroscopy using a fixed, narrowband source is a common method for acquiring Raman spectra. However, dispersive Raman spectroscopy requires a bulky spectrometer, which limits its field applicability. Therefore, there has been a tremendous need to develop a portable and sensitive Raman system.

Aim

We developed a compact swept-source Raman (SS-Raman) spectroscopy system and proposed a signal processing method to mitigate hardware limitations. We demonstrated the capabilities of the SS-Raman spectroscopy by acquiring Raman spectra from both chemical and biological samples. These spectra were then compared with Raman spectra obtained using a conventional dispersive Raman spectroscopy system.

Approach

The SS-Raman spectroscopy system used a wavelength-swept source laser (822 to 842 nm), a bandpass filter with a bandwidth of 1.5 nm, and a low-noise silicon photoreceiver. Raman spectra were acquired from various chemical samples, including phenylalanine, hydroxyapatite, glucose, and acetaminophen. A comparative analysis with the conventional dispersive Raman spectroscopy was conducted by calculating the correlation coefficients between the spectra from the SS-Raman spectroscopy and those from the conventional system. Furthermore, Raman mapping was obtained from cross-sections of swine tissue, demonstrating the applicability of the SS-Raman spectroscopy in biological samples.

Results

We developed a compact SS-Raman system and validated its performance by acquiring Raman spectra from both chemical and biological materials. Our straightforward signal processing method enhanced the quality of the Raman spectra without incurring high costs. Raman spectra in the range of 900 to 1200 cm−1 were observed for phenylalanine, hydroxyapatite, glucose, and acetaminophen. The results were validated with correlation coefficients of 0.88, 0.84, 0.87, and 0.73, respectively, compared with those obtained from dispersive Raman spectroscopy. Furthermore, we performed scans across the cross-section of swine tissue to generate a biological tissue mapping plot, providing information about the composition of swine tissue.

Conclusions

We demonstrate the capabilities of the proposed compact SS-Raman spectroscopy system by obtaining Raman spectra of chemical and biological materials, utilizing straightforward signal processing. We anticipate that the SS-Raman spectroscopy will be utilized in various fields, including biomedical and chemical applications.

Bichromatic tetraphasic full-field optical coherence microscopy

Rishyashring Iyer, Mantas Žurauskas, Yug Rao, Eric Chaney, Stephen Boppart

Journal of Biomedical Optics, Vol. 29, Issue S2, S22704, (March 2024) https://doi.org/10.1117/1.JBO.29.S2.S22704

TOPICS: Biological samples, Phase reconstruction, Optical coherence tomography, Scattering, Biological imaging, Optical coherence microscopy, Spectroscopy, Biomedical optics, Phase shifts, Beam splitters

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Perspective on quantitative phase imaging to improve precision cancer medicine

Yang Liu, Shikhar Uttam

Journal of Biomedical Optics, Vol. 29, Issue S2, S22705, (March 2024) https://doi.org/10.1117/1.JBO.29.S2.S22705

TOPICS: Cancer, Refractive index, Reflection, Biological samples, Tissues, Phase imaging, Tumors, 3D image processing, Medicine, Oncology

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Significance

Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states.

Aim

This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection.

Approach

We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI’s applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging.

Results

QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research.

Conclusions

QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI’s capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging

Piyush Raj, Santosh Kumar Paidi, Lauren Conway, Arnab Chatterjee, Ishan Barman

Journal of Biomedical Optics, Vol. 29, Issue S2, S22706, (April 2024) https://doi.org/10.1117/1.JBO.29.S2.S22706

TOPICS: Image segmentation, 3D image processing, Image processing algorithms and systems, Evolutionary algorithms, Biological imaging, Education and training, 3D mask effects, Phase imaging, Matrices, Tomography

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Significance

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms.

Aim

We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images.

Approach

The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the x-y plane. Leveraging cell continuity in consecutive z-stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process.

Results

The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2 s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools.

Conclusion

Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Multispectral label-free in vivo cellular imaging of human retinal pigment epithelium using adaptive optics fluorescence lifetime ophthalmoscopy improves feasibility for low emission analysis and increases sensitivity for detecting changes with age and eccentricity

Karteek Kunala, Janet Hrdina Tang, Keith Parkins, Jennifer Hunter

Journal of Biomedical Optics, Vol. 29, Issue S2, S22707, (July 2024) https://doi.org/10.1117/1.JBO.29.S2.S22707

TOPICS: In vivo imaging, Fluorescence, Image segmentation, Retinal scanning, Histograms, Fluorescence intensity, Biomedical optics, Photons, Diseases and disorders, Autofluorescence

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Significance

Adaptive optics fluorescence lifetime ophthalmoscopy (AOFLIO) provides a label-free approach to observe functional and molecular changes at cellular scale in vivo. Adding multispectral capabilities improves interpretation of lifetime fluctuations due to individual fluorophores in the retinal pigment epithelium (RPE).

Aim

To quantify the cellular-scale changes in autofluorescence with age and eccentricity due to variations in lipofuscin, melanin, and melanolipofuscin in RPE using multispectral AOFLIO.

Approach

AOFLIO was performed on six subjects at seven eccentricities. Four imaging channels (λex/λem) were used: 473/SSC, 473/LSC, 532/LSC, and 765/NIR. Cells were segmented and the timing signals of each pixel in a cell were combined into a single histogram, which were then used to compute the lifetime and phasor parameters. An ANOVA was performed to investigate eccentricity and spectral effects on each parameter.

Results

A repeatability analysis revealed <11.8% change in lifetime parameters in repeat visits for 532/LSC. The 765/NIR and 532/LSC had eccentricity and age effects similar to previous reports. The 473/LSC had a change in eccentricity with mean lifetime and a phasor component. Both the 473/LSC and 473/SSC had changes in eccentricity in the short lifetime component and its relative contribution. The 473/SSC had no trend in eccentricity in phasor. The comparison across the four channels showed differences in lifetime and phasor parameters.

Conclusions

Multispectral AOFLIO can provide a more comprehensive picture of changes with age and eccentricity. These results indicate that cell segmentation has the potential to allow investigations in low-photon scenarios such as in older or diseased subjects with the co-capture of an NIR channel (such as 765/NIR) with the desired spectral channel. This work represents the first multispectral, cellular-scale fluorescence lifetime comparison in vivo in the human RPE and may be a useful method for tracking diseases.

Comparison of polystyrene and hydrogel microcarriers for optical imaging of adherent cells

Oscar Benavides, Berkley White, Holly Gibbs, Roland Kaunas, Carl Gregory, Kristen Maitland, Alex Walsh

Journal of Biomedical Optics, Vol. 29, Issue S2, S22708, (June 2024) https://doi.org/10.1117/1.JBO.29.S2.S22708

TOPICS: Polystyrene, Visualization, Fluorescence intensity, Simulations, Hydrogels, Fluorescence, Elasticity, Optical surfaces, Mie scattering, Wavefront errors

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Label-free fluorescence lifetime imaging for the assessment of cell viability in living tumor fragments

Jason T. Smith, Chao J. Liu, Jeannine Degnan, Jonathan N. Ouellette, Matthew W. Conklin, Anna V. Kellner, Christina M. Scribano, Laura Hrycyniak, Jonathan D. Oliner, Chris Zahm, Eric Wait, Kevin W. Eliceiri, John Rafter

Journal of Biomedical Optics, Vol. 29, Issue S2, S22709, (June 2024) https://doi.org/10.1117/1.JBO.29.S2.S22709

TOPICS: Cell death, Tumors, Fluorescence lifetime imaging, Tissues, Cancer, Chemotherapy, Fluorescence, Tumor growth modeling, Autofluorescence, Photons

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Utilizing convolutional neural networks for discriminating cancer and stromal cells in three-dimensional cell culture images with nuclei counterstain

Huu Tuan Nguyen, Nicholas Pietraszek, Sarah Shelton, Kwabena Arthur, Roger Kamm

Journal of Biomedical Optics, Vol. 29, Issue S2, S22710, (August 2024) https://doi.org/10.1117/1.JBO.29.S2.S22710

TOPICS: Image segmentation, 3D image processing, Education and training, Machine learning, Tumors, Reflectivity, Image classification, 3D modeling, Cancer, Image processing

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Vibrational imaging of metabolites for improved microbial cell strains

Adam Hanninen

Journal of Biomedical Optics, Vol. 29, Issue S2, S22711, (July 2024) https://doi.org/10.1117/1.JBO.29.S2.S22711

TOPICS: Vibration, Infrared imaging, Biomolecules, Biological imaging, Microscopy, Raman spectroscopy, Biological research, Microfluidics, Light absorption, Infrared spectroscopy

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Capturing cell morphology dynamics with high temporal resolution using single-shot quantitative phase gradient imaging

Sun Woong Hur, MinSung Kwon, Revathi Manoharaan, Melika Haji Mohammadi, Ashok Zachariah Samuel, Michael Mulligan, Paul Hergenrother, Rohit Bhargava

Journal of Biomedical Optics, Vol. 29, Issue S2, S22712, (July 2024) https://doi.org/10.1117/1.JBO.29.S2.S22712

TOPICS: Cell death, Polarization, Microscopes, Tunable filters, Temporal resolution, Fluorescence, Phase reconstruction, Image restoration, Fluorescence imaging, Digital image correlation

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Significance

Label-free quantitative phase imaging can potentially measure cellular dynamics with minimal perturbation, motivating efforts to develop faster and more sensitive instrumentation. We characterize fast, single-shot quantitative phase gradient microscopy (ss-QPGM) that simultaneously acquires multiple polarization components required to reconstruct phase images. We integrate a computationally efficient least squares algorithm to provide real-time, video-rate imaging (up to 75 frames/s). The developed instrument was used to observe changes in cellular morphology and correlate these to molecular measures commonly obtained by staining.

Aim

We aim to characterize a fast approach to ss-QPGM and record morphological changes in single-cell phase images. We also correlate these with biochemical changes indicating cell death using concurrently acquired fluorescence images.

Approach

Here, we examine nutrient deprivation and anticancer drug-induced cell death in two different breast cell lines, viz., M2 and MCF7. Our approach involves in-line measurements of ss-QPGM and fluorescence imaging of the cells biochemically labeled for viability.

Results

We validate the accuracy of the phase measurement using a USAF1951 pattern phase target. The ss-QPGM system resolves 912.3 lp/mm, and our analysis scheme accurately retrieves the phase with a high correlation coefficient (∼0.99), as measured by calibrated sample thicknesses. Analyzing the contrast in phase, we estimate the spatial resolution achievable to be 0.55 μm for this microscope. ss-QPGM time-lapse live-cell imaging reveals multiple intracellular and morphological changes during biochemically induced cell death. Inferences from co-registered images of quantitative phase and fluorescence suggest the possibility of necrosis, which agrees with previous findings.

Conclusions

Label-free ss-QPGM with high-temporal resolution and high spatial fidelity is demonstrated. Its application for monitoring dynamic changes in live cells offers promising prospects.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review—part I

Neha Goswami, Mark A. Anastasio, Gabriel Popescu

Journal of Biomedical Optics, Vol. 29, Issue S2, S22713, (July 2024) https://doi.org/10.1117/1.JBO.29.S2.S22713

TOPICS: Scattering, Tissues, Phase measurement, Phase imaging, Refractive index, Light scattering, Scatter measurement, Microscopy, Biological samples, Reflection

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Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review–part II

Neha Goswami, Mark A. Anastasio, Gabriel Popescu

Journal of Biomedical Optics, Vol. 29, Issue S2, S22714, (July 2024) https://doi.org/10.1117/1.JBO.29.S2.S22714

TOPICS: Biological samples, Light sources and illumination, Scattering, Phase imaging, Red blood cells, Optical coherence tomography, Tomography, 3D metrology, Double positive medium, Autocorrelation

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Off-axis digital lensless holographic microscopy based on spatially multiplexed interferometry

José Ángel Picazo-Bueno, Steffi Ketelhut, Jürgen Schnekenburger, Vicente Micó, Björn Kemper

Journal of Biomedical Optics, Vol. 29, Issue S2, S22715, (August 2024) https://doi.org/10.1117/1.JBO.29.S2.S22715

TOPICS: Digital holography, Holograms, Microscopy, Holography, Holographic interferometry, 3D image reconstruction, Microfluidics, Biomedical optics, Multiplexing, Microspheres

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Significance

Digital holographic microscopy (DHM) is a label-free microscopy technique that provides time-resolved quantitative phase imaging (QPI) by measuring the optical path delay of light induced by transparent biological samples. DHM has been utilized for various biomedical applications, such as cancer research and sperm cell assessment, as well as for in vitro drug or toxicity testing. Its lensless version, digital lensless holographic microscopy (DLHM), is an emerging technology that offers size-reduced, lightweight, and cost-effective imaging systems. These features make DLHM applicable, for example, in limited resource laboratories, remote areas, and point-of-care applications.

Aim

In addition to the abovementioned advantages, in-line arrangements for DLHM also include the limitation of the twin-image presence, which can restrict accurate QPI. We therefore propose a compact lensless common-path interferometric off-axis approach that is capable of quantitative imaging of fast-moving biological specimens, such as living cells in flow.

Approach

We suggest lensless spatially multiplexed interferometric microscopy (LESSMIM) as a lens-free variant of the previously reported spatially multiplexed interferometric microscopy (SMIM) concept. LESSMIM comprises a common-path interferometric architecture that is based on a single diffraction grating to achieve digital off-axis holography. From a series of single-shot off-axis holograms, twin-image free and time-resolved QPI is achieved by commonly used methods for Fourier filtering-based reconstruction, aberration compensation, and numerical propagation.

Results

Initially, the LESSMIM concept is experimentally demonstrated by results from a resolution test chart and investigations on temporal stability. Then, the accuracy of QPI and capabilities for imaging of living adherent cell cultures is characterized. Finally, utilizing a microfluidic channel, the cytometry of suspended cells in flow is evaluated.

Conclusions

LESSMIM overcomes several limitations of in-line DLHM and provides fast time-resolved QPI in a compact optical arrangement. In summary, LESSMIM represents a promising technique with potential biomedical applications for fast imaging such as in imaging flow cytometry or sperm cell analysis.

Statistical estimation theory detection limits for label-free imaging

Lang Wang, Maxine Varughese, Ali Pezeshki, Randy Bartels

Journal of Biomedical Optics, Vol. 29, Issue S2, S22716, (September 2024) https://doi.org/10.1117/1.JBO.29.S2.S22716

TOPICS: Molecules, Signal detection, Biomedical optics, Raman scattering, Molecular interactions, Vibration, Absorption, Detection theory, Estimation theory, Polarizability

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To label or not: the need for validation in label-free imaging

Joseph M. Szulczewski, Filiz Yesilkoy, Tyler K. Ulland, Randy Bartels, Bryan A. Millis, Stephen A. Boppart, Kevin W. Eliceiri

Journal of Biomedical Optics, Vol. 29, Issue S2, S22717, (December 2024) https://doi.org/10.1117/1.JBO.29.S2.S22717

TOPICS: Biological imaging, Biomedical optics, Imaging spectroscopy, Raman spectroscopy, Spectroscopy, Vibration, Autofluorescence, Fluorescence, Tissues, Nicotinamide adenine dinucleotide

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