Journal of Biomedical Optics

SignificanceCollagen autofluorescence provides valuable intrinsic contrast for assessing tissue structure, composition, and pathology. However, a comprehensive understanding of the fluorescence properties across different collagen types remains limited. This knowledge gap may limit the development of advanced label-free fluorescence spectroscopy and imaging techniques for specific tissue characterization and diagnostic applications. AimThis study aims to comprehensively characterize the fluorescence intensity excitation-emission matrices (I-EEMs) and time-resolved excitation-emission matrices (TR-EEMs) of collagen standards from Types I, II, III, IV, and V obtained from various organ sources under both dry and hydrated conditions, to identify optimal excitation-emission parameters for each collagen type discrimination, and to establish a reference dataset that supports future research in label-free tissue characterization. ApproachWe employed a time-resolved fluorescence spectroscopy system equipped with an optical parametric oscillator laser (excitation: 200-2000 nm, pulse width: 30 ps) as an excitation source to generate I-EEMs and TR-EEMs of human and bovine collagen Types I-V. The fluorescence light was obtained by a multichannel plate photomultiplier tube through a monochromator (spectral range: 200-1000 nm). Measurements were conducted using collagen standards, under both dry and hydrated states. Additionally, photobleaching effects were assessed to ensure the reliability and reproducibility of fluorescence data. ResultsEach collagen type exhibited distinct I-EEM and TR-EEM signatures, with fluorescence lifetimes ranging from 2.5 ns (Type III, bovine skin) to 5.3 ns (Types II and V). Fibrillar collagens (Types I and V) displayed broader I-EEMs, whereas basement membrane collagen (Type IV) showed the narrowest spectral distribution. Organ-source-dependent variations were evident within the same collagen type. Type I collagen from human placenta exhibited an inverse lifetime-emission wavelength relationship compared to bovine sources. Hydration consistently red-shifted emission peaks into the 395-420 nm range and reduced fluorescence lifetimes across all collagen types (e.g., Type I bovine Achilles tendon: 3.2-5.0 ns dry vs. 3.0-4.5 ns hydrated). Despite excitation wavelength- and fluence-dependent photobleaching of fluorescence intensity, fluorescence lifetimes remained relatively stable, confirming the robustness of lifetime-based measurements. ConclusionsThis study establishes a comprehensive reference dataset for the fluorescence properties of collagen Types I-V and demonstrates the potential of combined I-EEMs and TR-EEMs analysis for tissue characterization. The results highlight species-, organ-, type-, and environment-specific optical fingerprints of similar collagens, which must be considered before implementing more in-depth studies on how the optical properties of collagen change in different medical applications.

Cerebral blood volume (CBV) and blood flow (CBF) constitute key metrics for cerebrovascular monitoring, enabling assessment of stroke severity and risk-prediction, aging-related changes, and neurological diseases. CBF and CBV monitoring are key aspects in diagnosis, treatment triage, and clinical outcome of ischemic and hemorrhagic strokes. In recent years, there have been ongoing efforts toward the development of optical devices for noninvasive monitoring of CBV and CBF. Speckle contrast optical spectroscopy (SCOS) has recently emerged as a strong candidate for clinical translation in monitoring CBF and CBV, due to its affordability, compact and wearable design, and noninvasive nature. However, experimental demonstrations that SCOS can effectively monitor brain hemodynamics remain sparse. This is primarily due to challenges in design experiments that isolate cerebral blood dynamics from those in the scalp and skull. In this paper, we report experiments using SCOS to monitor cerebral hemodynamics in rats during intracerebral blood flow modulation. To modify cerebral blood dynamics, a surgical procedure was performed to insert a catheter for direct injection of flow modulation fluids into the brain. Using the SCOS device, we monitored changes in CBV during deliberate CBF interventions into the brains of five rats. A saline solution was also injected as a sham control of the flow intervention. The results show a significant decrease in CBV during injection, followed by a return to baseline. This behavior is consistent with physiological expectations, as the injected fluids dilute the blood, leading to a transient reduction in blood volume. Notably, the CBV decrease induced by the flow modulation fluid solution required more than twice as long to recover to baseline compared with the saline solution, which is consistent with the delayed clearance of the flow modulation fluid by design. These experimental results demonstrate the effectiveness of SCOS for monitoring cerebral hemodynamics in animal models and highlight its potential for translation to human studies. Moreover, this work paves the way for the testing and characterization of cerebral therapeutic agents intended for blood flow modulation in animal models.

Accurate knowledge of tissue absorption (a) and reduced scattering [Formula] parameters are required to plan and monitor laparoscopic chemophototherapy (CPT) in ovarian cancer, including light dosimetry and quantitative fluorescence mapping of porphyrin-phospholipid (PoP) photobleaching and light-triggered doxorubicin (Dox) release. We implemented a depth-sensitive, multi-frequency laparoscopic spatial frequency domain imaging (SFDI) framework to improve optical-property estimation in layered tissue. A DMD-based laparoscope imaged two-layer phantoms with controlled optical contrasts and superficial thicknesses. Spatial-frequency subsets associated with different penetration depths were independently fit to recover a and [Formula], and compared with a two-layer diffusion model. Recovered [Formula] values remained bounded by the known layer references and shifted monotonically toward the superficial value as spatial frequency and top-layer thickness increased, approaching a single-layer response at high frequency/thick layers. Quantitative model comparison showed {delta}-P1 variants outperformed the standard diffusion approximation, reducing RMSPE between modeled and measured [Formula] to 0.8-6.5% (silicone/silicone) and 1.6-8.3% (silicone/intralipid), whereas SDA errors reached [~]13.8% and 21.1%, respectively. This approach demonstrates multi-frequency laparoscopic SFDI as a practical initial step for depth-sensitive fluorescence correction for individualized CPT treatment planning and monitoring.

Collagen remodeling in the uterine cervix is a vital process in pregnancy that allows for timely fetal delivery, yet its spatio-temporal details are still not fully understood. In this study, we measured collagen reorganization at different stages of murine gestation and at various cervical depths. We used polarization-resolved Second Harmonic Generation microscopy to specifically detect fibrillar collagen and assess its orientation with sub-micrometer resolution. We imaged large cervical areas using automated mosaicking and implemented an analysis pipeline that showed significant region-dependent changes in collagen quantity, porosity, and orientation disorder. Notably, we found that collagen disorganization begins in the lower cervix at gestation day 12 and extends throughout the entire cervix by day 15. Additionally, we demonstrated that the temporal dynamics of disorganization, without spatial sensitivity, can also be tracked using Mueller Matrix imaging, which is a clinically deployable method. These findings should improve understanding and diagnosis of gestation-related issues such as premature birth.

This study uses two different quantitative phase imaging techniques (QPI) and for the first time measures the height, volume, and mass dynamics of Madin-Darby Canine Kidney (MDCK) monolayers. We demonstrate novel methods to determine the height of confluent monolayers of cells from 2D and 3D QPI data and validate that the two methods agree. We developed a novel cell segmentation method adapted to QPI images of confluent cell layers and present a robust measure of relative error. We also demonstrate that height statistics of cells can be obtained without segmenting the images. We obtain the following precisions of cell density (1 %), height (3 %), area (5 %) and volume (6 %). Cell height varies 15-25 % over a monolayer and increases 50-100 % when cell density doubles. The average refractive index and the dry mass fraction of the cells, on the other hand, are constant over the entire density range.

SignificanceQuantifying lipid droplet (LD) remodeling in 3D hepatic organoids is often limited to endpoint staining or phototoxic live fluorescence imaging, thereby obscuring droplet-level kinetics. AimWe aimed to develop a label-free method to track LD dynamics in living hepatic organoids under different fatty-acid loads. ApproachTime-lapse 3D refractive-index tomograms were acquired using holotomography and analyzed with a depth-adaptive, multi-threshold segmentation pipeline to quantify LD number, volume, sphericity, and refractive-index-derived concentration and dry mass at single-droplet resolution. ResultsOleic acid and linoleic acid induced LD accumulation while preserving organoid integrity, whereas palmitic acid triggered rapid structural collapse. Despite increases in total LD burden under both oleic acid and linoleic acid, droplet-level dynamics diverged: oleic acid produced volume-dominated accumulation via enlargement of fewer LDs and increased size heterogeneity, whereas linoleic acid produced number-dominated accumulation via sustained increases in LD number, yielding a more uniform population of small droplets. ConclusionsLabel-free holotomography with depth-adaptive analysis enables non-invasive, longitudinal, and multi-scale quantification of LD dynamics in intact organoids and reveals fatty-acid- dependent temporal modes of lipid storage. Statement of DiscoveryWe developed a label-free, longitudinal 3D holotomography framework with depth-adaptive lipid droplet segmentation that quantifies single-droplet dynamics in living mouse hepatic organoids. Using this platform, we found that oleic acid and linoleic acid induce LD accumulation via distinct strategies--oleic acid via droplet enlargement and linoleic acid via sustained increases in droplet number--while palmitic acid rapidly compromises organoid integrity.

Peritoneal micrometastases (micromets) remain a major barrier to durable cytoreduction in ovarian and other intra-abdominal cancers, because lesions can be difficult to visualize and are often resistant to systemic therapy. Liposomal doxorubicin (Dox) improves pharmacokinetics but can be limited by slow intratumoral release. Porphyrin-phospholipid (PoP) liposomes enable near-infrared light-triggered release of Dox (chemophototherapy (CPT)), creating an opportunity for intraoperative, fluorescence-guided treatment planning and monitoring. Here, we evaluate a laparoscopic fluorescence imaging platform for quantifying light-triggered drug delivery in 2D monolayers and 3D spheroid cluster models. Dox fluorescence increased linearly with administered LC-Dox-PoP concentration in both SCC2095sc and SKOV-3 cultures (R2 = 0.97-0.98 in 2D; R2 = 0.98 in spheroid clusters over 1-9 {micro}g/mL). Laparoscope-derived fluorescence measurements agreed with standard well-plate reader measurements (R2 = 0.89-0.96). Porphyrin fluorescence provided stronger, complementary contrast for localizing spheroid constructs and decreased after activation light exposure, consistent with photobleaching during triggered release. Together, these results support a quantitative imaging framework for fluorescence-guided monitoring of light-triggered liposomal drug release, with potential to inform individualized CPT dosimetry for peritoneal micrometastases. These findings in SCC2095sc (oral squamous cell carcinoma) additionally suggest relevance of fluorescence-guided CPT for head and neck/oral cancer, where localized post-resection adjuvant treatment may improve control of residual disease.

PurposeTo investigate the interplay between biomechanics, fluid dynamics, and solute transport in Diabetic Macular Oedema (DMO) using a mechanics-based computational model, aiming to elucidate mechanisms behind variable treatment outcomes. MethodsWe developed a multiphysics model of the retina within a porous media framework. The model integrates OCT-derived geometry, vascular leakage, retinal biomechanics (including Muller cell fibre architecture), retinal pigment epithelium (RPE) function, and anti-VEGF transport. We simulated oedema development and therapeutic response by varying these parameters systematically. ResultsModel results showed that active RPE pumping is essential for maintaining retinal dehydration. Our simulations revealed a critical trade-off related to Muller cell architecture: the physiological z-shaped orientation protects against oedema but impedes anti-VEGF drug delivery to leaky vessels. In contrast, a pathological, vertical Muller cell alignment increases oedema susceptibility but allows for a faster therapeutic response due to improved drug diffusion. ConclusionsMuller cell orientation presents a trade-off between biomechanical protection and therapeutic efficacy, offering a novel mechanistic explanation for the variable patient responses to anti-VEGF therapy observed clinically. This in-silico framework is a powerful tool for dissecting DMO pathophysiology and has the potential to guide the development of personalised treatment strategies.

AimsTo characterize subtype-associated heterogeneity in type 2 diabetes mellitus (T2DM), particularly normal-weight diabetes, using extracellular vesicle (EV)-associated molecular features in a clinically stratified cohort. MethodsEVs were isolated from plasma using ExoTIC and validated by transmission electron microscopy, nanoparticle tracking analysis, flow cytometry, and Western blotting. EVs from Asian normal-weight (A-NWD), Asian overweight (A-OWD), Non-Hispanic White normal-weight (W-NWD), and Non-Hispanic White overweight (W-OWD) T2DM patients were analyzed by multimodal surface-enhanced Raman spectroscopy (SERS; n=65) and EV-RNA sequencing (n=39). ResultsSERS identified subgroup-associated spectral fingerprints that distinguished the four BMI- and race/ethnicity-defined groups in this cohort. EV-RNA sequencing revealed differential microRNA expression across subgroups, with higher miR-208a and miR-132 in A-OWD and higher miR-484 in A-NWD. Unsupervised analyses also showed partially overlapping EV-associated molecular features between A-NWD and W-OWD, suggesting that BMI-based subgrouping alone may not fully capture shared metabolic states. ConclusionsMultimodal EV profiling identified subgroup-associated spectral and miRNA features in clinically stratified T2DM and provides a framework for studying diabetes heterogeneity, including molecular patterns associated with normal-weight diabetes.

BackgroundTranscranial photobiomodulation (tPBM) utilizes near-infrared light to penetrate the skull to stimulate neural tissue. However, the in vivo physiological response and the factors influencing this response in the human brain have yet to be understood. MethodsIn this study, we utilize functional magnetic resonance imaging (fMRI) to evaluate the effect of tPBM on the blood-oxygenation (BOLD) and cerebral blood flow (CBF), while varying stimulation parameters such as wavelength, irradiance, and frequency. We further examine the influence of skin tone and sex. We further model the neurovascular interactions underlying the response. ResultsOur results show that the fMRI responses to tPBM is not restrained to the site of irradiation, but quickly spreads to distal sites. Certain regions display an fMRI response sustained after tPBM cessation. Importantly, the responses are dependent on biological and stimulation parameters. Lastly, biophysical modeling revealed a consistent neurovascular coupling-like behaviour underlying these responses. ConclusionEmpirical characterizations of dose dependence are critically important to brain stimulation methods in general but have yet to be demonstrated in most cases. This is the first tPBM study to do just that, establishing the foundation for precision medicine using tPBM, and sets a valuable precedent for the field of brain stimulation.

We established a photoacoustic tomography and ultrasound imaging system capable of resolving visually evoked hemodynamic responses in the cortical and subcortical visual regions of the brains of freely behaving mice. By searching for anatomical landmarks in the US imaging planes, we can locate brain regions of interest and continuously record HR in these regions. The system was examined using a 100-minute-long vision research protocol in wild-type mice and mice with vision deficits. We found that: 1) visually evoked HR amplitudes increase as visual stimulation intensity increases in both scotopic and photopic conditions; and 2) HR amplitudes increase during the light adaptation time course.

SignificanceCerebral autoregulation (CA) reflects the dynamic coupling among cerebral blood flow (CBF), intracranial pressure (ICP), and arterial blood pressure (ABP); its failure contributes to secondary brain injury. Existing bedside methods rely on indirect or spatially limited CBF surrogates and cannot resolve microvascular flow dynamics across space, depth, and time. AimTo develop, optimize, and apply a scalable, noncontact time-resolved laser speckle contrast imaging (TR-LSCI) platform for depth-sensitive, high-speed, wide-field CBF imaging during controlled ICP perturbations. ApproachTR-LSCI synchronizes a 20-MHz pulsed laser with a time-gated, single-photon avalanche diode (SPAD) camera (512 x 512 pixels) to detect diffuse photons at varying path lengths, enabling depth-resolved microvascular CBF imaging. Benchtop and mobile TR-LSCI systems were applied in adult rats and a neonatal piglet with synchronized invasive ICP and ABP measurements. ResultsTR-LSCI captured spatially heterogeneous, pulsatile CBF dynamics at up to 52 Hz over large cortical fields of view, with heart rate estimates statistically equivalent to those from ICP and ABP. Multivariable analysis identified reproducible, phase-dependent CA transitions encompassing preserved autoregulation, ABP-driven compensation, and ICP-constrained CBF suppression; notably, CBF alone exhibited distinct phase signatures. ConclusionsTR-LSCI enables dynamic, physiology-informed neurovascular monitoring and supports future bedside CA assessment.

Polarization-resolved second harmonic generation microscopy provides structural information about non-centrosymmetric biological samples such as collagen. It involves illuminating the sample with a focused laser beam having a variable linear polarization angle and recording the second harmonic signal as a function of this angle. However, accurate linear polarization control is challenging due to ellipticity introduced by reflections from mirrors and dichroic mirrors in the optical path. Waveplate-based compensation has emerged as the standard approach to address these distortions, but its effectiveness for quantitative measurements remains incompletely characterized. Here, we attempt to fill this gap by implementing an established automated waveplate compensation method based on a rotating half-waveplate in combination with a compensating quarter-waveplate. This was done on a commercial Leica TCS SP8 MP multiphoton microscope, making various hardware improvements and carefully documenting important experimental details. Despite significant effort, we consistently observed substantial unwanted residual polarization ellipticity, with amplitudes up to 0.25, persisting under optimal waveplate configurations. Our simulation analysis provides evidence that this limitation may arise from wavelength-dependent dichroic mirror birefringence combined with the broad spectral bandwidth (10nm to 20nm full width at half maximum) of femtosecond laser pulses. While the approach investigated here can compensate a single wavelength, different spectral components within the pulse experience different phase retardations from wavelength-dependent optical elements, potentially resulting in residual ellipticity that cannot be eliminated. Our simulations qualitatively reproduced key features of the experimental observations. These findings have important implications for quantitative polarization-resolved second harmonic generation microscopy and suggest that alternative approaches, including specimen rotation or picosecond laser sources with narrower bandwidth, should be investigated for applications requiring precise polarization control. To facilitate community investigation of these effects, we provide open-source analysis code and simulation files.

Optical coherence tomography (OCT) has transformed clinical eye care by providing high-resolution volumetric imaging of the retina. Recently, ultrawide-field-of-view (FOV) OCT played an increasingly significant clinical role; however, most clinical OCT systems offer only a rather limited FOV. We increased the FOV of clinical OCT by volumetrically montaging multiple OCT datasets in three dimensions (3D). We performed volumetric montaging by representing the internal limiting membrane (ILM) and retinal pigment epithelium (RPE) in each volume as point clouds and using these point clouds to compute transformations that map each volume to a common reference frame. We validated our methodology using datasets from three institutions with different OCT hardware and data-acquisition procedures. Using the mean surface distance between point clouds, we found the error in montaging was less than the lateral pixel size. Our method enabled existing clinical OCT to achieve ultrawide FOV imaging without any hardware modification.

Accurate cell type classification is essential for a wide range of biomedical applications, including disease diagnosis, drug discovery, and the study of cellular processes. Holographic imaging flow cytometry (HIFC) provides label-free quantitative phase imaging (QPI) of individual cells, enabling classification based on phase images. However, reconstructing holograms into phase images involves multi-step image processing, which introduces substantial computational overhead. The availability of diverse image representations across holographic reconstruction stages allows for flexible analytical strategies, enabling the optimization of trade-off between classification accuracy and computational efficiency. Moreover, deep learning offers an efficient alternative, accelerating the reconstruction process while performing accurate classification. However, despite its importance, this optimization challenge remains largely unexplored in the current literature. Here, we present the first systematic evaluation aimed at balancing classification accuracy with computational efficiency, highlighting how different image representations affect overall performance. We focus on a binary classification task discriminating natural killer cells from breast cancer cells. Six distinct classification pipelines are evaluated: direct processing of raw holograms, analysis of demodulated complex fields (CFs), refocused CFs, unwrapped phase images, and two deep learning-based methods that either replace the automatic refocusing stage or perform end-to-end hologram-to-phase reconstruction. For each strategy, we assess both computational cost and classification performance. Our results reveal a clear trade-off: reconstructed phase images provide the highest accuracy, whereas simpler representations or accelerated reconstruction methods significantly reduce processing time with minimal loss of accuracy. A Pareto analysis identifies the optimal set of strategies, offering practical guidelines for selecting image representations and processing pipelines based on available hardware and desired performance. Thus, this work offers a systematic framework for high-throughput deep learning classification in HIFC, serving as a potential reference for future biomedical applications.

BackgroundPhotobiomodulation (PBM) therapy has demonstrated therapeutic potential in promoting cellular repair, modulating inflammation, and enhancing mitochondrial function. Platelet-rich plasma (PRP) is widely used in regenerative medicine due to its concentration of growth factors and cytokines. Very small embryonic-like stem cells (VSELs), a rare population of pluripotent stem cells present in adult tissues, have emerged as a potential contributor to tissue regeneration. While PBM and PRP are used in combination, how VSELs or Multi-lineage stress enduring (MUSE) cells are at play, and the biological mechanisms underlying their synergistic effects remain incompletely characterized. ObjectiveThis exploratory pilot study aimed to evaluate whether application of the MD Biophysics laser to autologous PRP is associated with measurable changes in VSEL-related antibody marker expression, and to identify directional trends to inform future controlled studies. MethodsPRP samples were collected from participants across seven test dates (July 2024 to February 2025), yielding 18 participant-session datasets. Samples were analyzed before (Pre) and after (Post) laser application using flow cytometry conducted at a UCLA Flow Cytometry Laboratory. Four VSEL-associated antibody markers were assessed: CD45-CD34+, CXCR4+, CD133+, and SSEA-4+. Analyses were descriptive and focused on paired differences and directional trends due to the exploratory design and absence of a control group. ResultsThree of four VSEL-associated markers (CXCR4+, CD133+, and SSEA-4+) demonstrated a group-level increase in median paired differences following laser application. Directional increases were observed in 12/18 sessions for CXCR4+, 10/18 for CD133+, and 9/18 for SSEA-4+. CD45-CD34+ showed a near-equal distribution of increases and decreases. Ki-67 positivity indicated the presence of viable, proliferative cells. While no findings reached statistical significance due to limited sample size, consistent directional trends were observed across multiple markers. ConclusionApplication of PBM to autologous PRP was associated with directional increases in multiple VSEL-associated antibody markers, suggesting a potential role for stem cell activation or mobilization in the mechanism of action. Although preliminary and not statistically powered, these findings provide hypothesis-generating evidence supporting further investigation. The observed trends informed iterative protocol refinement and establish a foundation for future controlled, adequately powered studies to evaluate clinical efficacy and underlying biological mechanisms.

Oblique plane microscopy (OPM) is a light sheet microscopy technique that uses a single high numerical aperture (NA) objective for both illuminating the sample and collecting emission fluorescence from a tilted plane within the specimen. OPM has become indispensable in biological and biomedical research, providing rapid, high-resolution volumetric fluorescence imaging of live cells and tissues while minimising phototoxicity and photobleaching. It also overcomes the sample mounting challenges associated with conventional light sheet microscopes that require two orthogonally placed objectives. However, the application of OPM has been limited by the complex design and the intricate optical alignment and characterisation needed, particularly with the remote-refocusing system (RFS) in the emission path. This protocol offers a detailed, step-by-step guide for constructing an OPM setup using commercially available components and for characterising its performance to ensure optimal imaging quality. We aim to deliver the unique merits of OPM to researchers in life science and medicine, enabling them to visualise the spatiotemporal organisation of key biomolecules, structures, and cells in 3D at high resolutions.

A wide variety of protocols have been proposed for optical clearing of tissues, whole-mount organs, and other bulky specimens to enable their volumetric fluorescence imaging. However, quantitative comparisons of tissue clearing protocols that take into account the fluorescence of the final specimens remain rare. Here, we propose a volumetric fluorescence image-based workflow for evaluating tissue clearing and fluorescence staining protocols. The workflow calculates depth-dependent fluorescence attenuation coefficients using data from entire 3D images, thereby avoiding spatial sampling bias and eliminating reliance on simple readouts, such as light transmittance, to predict fluorescence image quality. By combining autofluorescence signal with the signal from a specific fluorescence label, we independently evaluated transparency and the quality of fluorescence staining in cleared specimens. Using the proposed workflow, we systematically compared clearing and staining performance of three CUBIC-based protocols in murine liver, kidney, spleen, thymus, and intestine, and revealed differences in final fluorescence image quality across protocol-organ combinations.

It is increasingly necessary to both study biology in 3D and obtain quantitative measurements. Not all 3D-reconstructions are created equal, particularly when using the anatomical model as a basis for force calculations, i.e. computational modeling. Here, we compare 3D anatomical reconstructions from two emerging imaging modalities: 4D ultrasound (4DUS) and light sheet fluorescent microscopy (LSFM) against our previous nano-computed tomography (nanoCT) cohort data, using the tortuous highly intricate pharyngeal arch artery system of the chick embryo as a test bed. We highlight modality-specific morphological image acquisition discrepancies and their influence on subsequent computational fluid dynamics results. Overall, LSFM accurately captured quantitative volumetric measurements of small rapidly-changing vascular morphologies while 4DUS systematically inflated small tortuous vessels. Differences in image-based morphology changes led to significant changes in computationally-obtained force magnitudes and flow patterns linked to vessel angle and tortuosity. This validates LSFM as a comparative preclinical vascular quantitative imaging tool and suggests that 4DUS needs extensive 3D anatomical validation for non cardiac chamber vessels.

Epithelial ovarian cancer remains one of the most lethal malignancies among women, with late-stage diagnoses yielding 5-year survival rates below 30%. The metabolic heterogeneity of the tumor microenvironment (TME) highlights the need for methods capable of rapid, chemically specific phenotyping. Stimulated Raman scattering (SRS) microscopy when combined with deuterium labeled metabolites enables the non-invasive high contrast interrogation of cellular metabolic pathways. In this study, we used SRS microscopy to profile fatty acid and glycogen metabolism in epithelial ovarian cancer (SKOV-3) and cervical cancer (HeLa) cell models. Deuterium labeled glucose revealed striking differences in glycogen synthesis and intracellular distribution, with SKOV-3 cells exhibiting markedly greater single-cell heterogeneity than HeLa. Complementary measurements of lipid droplet (LD) synthesis and turnover under nutrient starvation further revealed cell-line-specific metabolic strategies, identifying LD and glycogen dynamics as a potential diagnostic marker of cancer metabolic phenotypes. These results demonstrate that SRS microscopy in the Raman silent region, paired with metabolic labeling, can sensitively resolve metabolic diversity across cancer cell subpopulations. Such metabolic phenotyping may inform both early diagnostic strategies and therapeutic approaches that combine cytotoxic treatment with targeted metabolic disruption.