Photoacoustics

This study presents the use of sub-micron nanobubbles (NBs) as contrast agents for ultrasound localization microscopy (ULM), a super-resolution imaging technique that visualizes microvascular structure and flow beyond the acoustic diffraction limit. While ULM has traditionally relied on micron-sized microbubbles (MBs), the reduced dimensions and prolonged circulation times of NBs make them attractive candidates for localization-based imaging. However, their weaker acoustic responses present significant challenges for reliable detection and tracking. To address this challenge, we developed the ULM Master GUI, an interactive framework for optimization of the complete ULM processing pipeline. Using custom ultrasound-compatible wall-less gelatin flow phantoms containing vessel-mimicking channels and bifurcations ranging from 100 to 500 m, we demonstrate that NB-based ULM achieves velocity reconstruction and flow partitioning measurements comparable to conventional MB-based ULM. Across all investigated geometries, NBs faithfully reproduced the underlying flow patterns and hemodynamic behavior despite their substantially reduced acoustic scattering. These findings establish the feasibility of NB-based ULM, expand the range of contrast agents available for localization microscopy, and provide a foundation for future super-resolution ultrasound imaging using nanoscale acoustic contrast agents. The ULM processing GUI is publicly available at https://github.com/grisha1998/ulm-super-resolution-toolbox.

In vivo infrared thermography is limited by the inherently poor spatial resolution at long wavelengths, low contrast, and the lack of biocompatible contrast agents. Here, we present 3-5 m mid-wave infrared (MWIR) thermography enhanced by an artificial intelligence (AI) network and cold phosphate-buffered saline (PBS) as a thermal contrast agent for noninvasive in vivo imaging with high contrast and resolution. MWIR imaging enabled high thermal sensitivity with microscale spatial resolution, strong relative thermal contrast, and facilitated visualization of the subcutaneous vasculature in the human arm, hand, ankle, the femoral artery and vein in rats, and the femoral vessels in mice, with image contrast further enhanced by AI networks. In a 4T1 tumor-bearing mouse model, AI-enhanced MWIR resolved early-stage tumors of ~2.3 mm and metastases as small as ~1.7 mm. Using cold PBS as a MWIR thermal contrast agent, we achieved precise tumor boundary visualization and real-time imaging-guided tumor resection. AI-enhanced MWIR offers a promising solution for early diagnosis and improved surgical precision.

Objective: This study aims to develop and validate a quantitative, depth-resolved anisotropy imaging framework that extends ARFI-based focal degree-of-anisotropy (DoA) estimation into two-dimensional mapping by modeling the depth-dependent relationship between shear modulus ratio (SMR) and peak displacement ratio (PDR). Methods: We propose APRIL (Adaptive Polynomial Regression for anisotropy Imaging via ARFI-induced DispLacements), a framework for quantitative, depth-resolved DoA imaging that adaptively selects polynomial regression or shape-preserving spline interpolation based on excitation PSF asymmetry. Training data were generated using an LS-DYNA3D + Field II simulation pipeline in homogeneous transversely isotropic media (SMR 0.9-4.9). Testing included shifted SMRs under varied acoustic conditions and three heterogeneous inclusion configurations (anisotropic inclusion in isotropic background and vice versa). Experimental validation was performed in an in-vivo murine tumor model over the time, ex-vivo chicken breast, and tissue-mimicking gelatin phantoms, using a Verasonics system with an L11-5v transducer. Results: APRIL achieved depth-resolved SMR prediction errors below 9% over 10-30 mm, with highest accuracy in the focal region (MAE 2.3%, RMSE < 0.1) and stable performance across PSF transition zones. In heterogeneous phantoms, it reconstructed anisotropy maps with SSIM up to 86% and MPE below 7%, accurately delineating inclusion boundaries. Under acoustic parameter variations, mean absolute errors remained below 10%, demonstrating robustness to system and tissue heterogeneity. Conclusion: APRIL enables robust, two-dimensional anisotropy imaging beyond focal estimates. Significance: The method provides a physically grounded and generalizable framework for clinically viable anisotropy biomarkers in muscle, tendon, kidney, tumor and breast tissues.

Viscoelastic characterization of tissue has significant diagnostic value in oncology, as tumor progression alters both elasticity and viscosity in ways that neither property alone can fully capture. Existing acoustic radiation force (ARF)-based methods such as Viscoelastic Response (VisR) ultrasound estimate relative elasticity and viscosity through per-A-line nonlinear model fitting, which is computationally intensive and requires auxiliary simulations to correct elasticity-dependent bias. This work presents VESTA (Machine Learning-Enabled Estimation of ViscoElastic Ratios from On-Axis Spatio-Temporal ARFI Features), a two-stage data-driven pipeline that predicts elasticity ratio (ER) and viscosity ratio (VR) directly from seven normalized ARFI displacement features at the A-line level, without model fitting or compensation. Stage~1 is an MLP classifier that detects inclusion boundaries from normalized peak displacement and negative peak velocity ratios; Stage~2 is a dilated Conv1D regression model that estimates ER and VR along the full axial sequence using the predicted mask alongside displacement features. The pipeline was trained on 500 simulated inclusion scenarios spanning three geometries, five focal depths, two F-numbers, and a broad range of material contrasts. In silico, mean predicted ER and VR were within 12\% of ground truth across all geometries, with performance best when ER and VR were moderate or decoupled. Experimental validation on a chicken breast phantom demonstrated plausible generalization to real tissue heterogeneity. Applied to an in vivo murine 4T1 breast cancer model, the pipeline tracked treatment-related attenuation of mechanical contrast in paclitaxel-treated tumors relative to controls over a 36-day imaging period, supporting its relevance for tumor monitoring.

PurposeIn this work, we aimed to establish a flow phantom for multi-modal PET and spectral CT imaging to improve blood flow quantification. MethodsA modular flow phantom was built with materials compatible with both PET and spectral CT. A peristaltic pump was used to allow for recirculation. Pores were installed through the aorta to allow for tissue exchange between the blood and tissue compartments, and valves were placed in line with the aorta to control the pressure gradient between compartments. We characterized the system using saline bolus experiments, dynamic PET imaging, and iodine-based spectral CT acquisitions. A blood flow (K1) of 1.0 mL/min/mL with a pressure range of approximately 1.0-3.0 psi was targeted. Using compartmental modeling, we estimate K1 across phantom configurations and evaluate the consistency of perfusion-related parameters derived from saline, PET, and spectral CT measurements. ResultsWith the four pore, two valve configuration, target K1 of 1.0 mL/min/mL was achieved with a physiologic pressure range (2.2-3.5 psi) and a pump speed of 150 rpm. Further, the flow phantom was also able to recapitulate K1 across a range of values through adjustable modifications to the phantom configuration. ConclusionsWe present a modular multimodal flow phantom with a tissue-mimicking compartment, vascular tubing with an adjustable number of pores and valves, and 3D-printed components to support tunable exchange between blood-pool and tissue compartments and controlled dynamic perfusion imaging with same-session PET and spectral CT. Such a setup will enable the development of multi-modal approaches for evaluating tissue perfusion.

Understanding processes such as blood-brain barrier (BBB) disruption and tumor progression can greatly benefit from simultaneous molecular, functional, and hemodynamic imaging in deep tissue, yet few existing imaging modalities can provide all three in a single system. Here, we present an integrated imaging platform that combines 3D photoacoustic tomography with ultrasound localization microscopy (3D-PAULM) to enable intrinsically co-registered, multiparametric imaging. 3D-PAULM unifies multispectral photoacoustic molecular imaging, ultrasound B-mode imaging, microbubble-enhanced power Doppler, and ultrasound localization microscopy, and concurrently measures blood oxygenation, blood perfusion, microvascular flow dynamics, and molecular probes from near-infrared dyes and photoswitchable phytochromes. We apply 3D-PAULM to quantify BBB leakage in focal ischemia and systemic inflammation, and to perform high-sensitivity molecular imaging of solid tumors alongside functional mapping of tumor hypoxia and super-resolved vascular remodeling. Together, these results establish 3D-PAULM as a versatile platform for integrated functional and molecular imaging in deep tissue.

Significance: Continuous, noninvasive, and depth-resolved monitoring of blood-flow-related tissue dynamics remains an important unmet need. Speckle-contrast optical spectroscopy (SCOS), including interferometric implementations such as iSCOS, provides a scalable optical route to blood-flow sensing, but conventional continuous-wave approaches lack intrinsic depth selectivity. Time-of-flight (TOF) gating offers a way to separate superficial and deeper dynamic contributions in layered tissues, such as skin-muscle or scalp-cortex, by resolving photon path lengths. Aim: We introduce a swept-source, single-channel implementation of interferometric speckle-contrast optical spectroscopy (iSCOS) to obtain TOF-resolved temporal speckle contrast, {kappa}^2, from the measured field autocorrelation g_1, and evaluate its feasibility for depth-resolved blood-flow sensing. Approach: A swept-source iNIRS system operating at 780 nm acquired interferometric signals, which were Fourier-transformed along the optical-frequency axis to recover complex TOF-resolved speckle fields. Temporal speckle contrast was then estimated at each TOF gate indirectly from g_1 using the speckle-visibility relation. Diffusion-based numerical simulations were first used to compare the direct variance-based estimator and the indirect g_1-based estimator under varying reduced scattering coefficient, diffusion coefficient, additive noise level, and bi-layer geometry. Because the simulations showed that the g_1-derived {kappa}^2 estimator was substantially less sensitive to additive noise than the direct estimator, this estimator was used for the main phantom and in vivo analyses, while the direct estimator served as a simulation comparator. The g_1-derived estimator was then applied to liquid and bi-layer phantoms, followed by proof-of-concept in vivo measurements on the human forearm during cuff occlusion and on the forehead during a Sudoku task. Results: TOF-resolved kappa2 curves recovered with the g_1-derived estimator matched DWS theory across scattering coefficients, photon path lengths, and exposure times. The estimator preserved theoretical accuracy for additive noise amplitudes up to 50% of the field amplitude, whereas the direct variance estimator showed substantial noise-induced bias and required correction. Bi-layer simulations and phantom experiments reproduced the predicted direction and onset of TOF-dependent decorrelation-rate trends in layered media. In vivo, the recovered blood-flow index tracked the expected TOF-dependent cuff-occlusion and reactive-hyperemia response in the forearm. During the single-subject Sudoku task, the left-forehead recording showed a TOF-dependent relative blood-flow-index increase of +0.8 {+/-} 1.9% at TOF = 400 ps, +9.8 {+/-} 2.2% at TOF = 600 ps, and +15.2 {+/-} 5.6% at TOF = 800 ps. This pattern is consistent with increased sensitivity to deeper tissue at longer photon path lengths, but requires cohort-level validation before quantitative interpretation as cognitive activation. Conclusions: Coupling temporal speckle-contrast analysis with swept-source iNIRS yields a proof-of-concept, depth-resolved platform for blood-flow sensing. By estimating TOF-resolved speckle contrast through the g_1-derived {kappa}^2 route, TOF-iSCOS suppresses additive-noise bias while preserving sensitivity to deeper dynamic tissue layers. The present single-channel results bridge continuous-wave iSCOS, interferometric NIRS and time-domain diffuse correlation spectroscopy (TD-DCS), and motivate future multi-channel and cohort studies for scalable cortical hemodynamic monitoring.

Short-wave infrared (SWIR) sensors promise to expand the capabilities of optical sensing technologies but the lack of robust data characterising tissue-constituent optical properties in the SWIR makes instrument design challenging. We characterise and evaluate the optical properties of the dominant chromophores in tissue and tissue-mimicking phantoms, from visible to SWIR wavelengths. Using single-integrating sphere systems, we measured the optical properties of single-component chromophores (H2O, haemoglobin, corn oil, synthetic melanin) and multi-component tissues (whole blood, lard), to decouple contributions from optical scattering, H2O absorption and other contributing chromophores; we also characterised commonly-used phantom materials and investigated their potential to mimic soft tissues in the SWIR range using simulations. We provide a consistent dataset of absorption and reduced scattering coefficients that characterise the dominant tissue chromophores from 450 nm out to 1600 nm. These results were shown to be consistent with literature data, where available. We integrate these data into an open-source Python toolkit, SIMPA, for optical modelling and demonstrate soft tissue simulations that can be probed continuously from visible to SWIR wavelengths. Our findings are compared with tissue-mimicking phantoms, highlighting a need for additives for polymer-based phantoms that mimic SWIR water absorption. By providing this open-source dataset, we aim to enable future studies exploring SWIR light-tissue interactions that facilitate rapid assessment and prototyping of next-generation spectroscopy and imaging techniques.

Microbubble contrast-enhanced ultrasound (CEUS) relies on discriminating nonlinear bubble signals from linear tissue backscattering. While Singular Value Decomposition (SVD) filtering improves this discrimination, existing techniques often fail to retain the slowly-moving microbubble signals from static clutter. Here, we present a novel multi-stage singular value decomposition (MS-SVD) framework for ultrafast CEUS imaging. Our method employs plane-wave transmissions at multiple angles and acoustic pressure levels (implemented via duty-cycle modulation) and alternating transmit polarity. The beamformed data are then processed by three sequential SVD filters: (1) spatial-angular SVD to extract coherent signals across all transmit angles, (2) spatial-pressure SVD to separate linear fundamental and nonlinear harmonic components, and (3) spatiotemporal SVD to isolate moving microbubble echoes from tissue clutter. In in vitro flow phantoms and in vivo rat brain through a cranial window, MS-SVD dramatically improves microbubble detection compared to conventional SVD filtering, MS-SVD yields much stronger vascular contrast and suppresses tissue clutter to a greater extent. The resulting power-Doppler and super-resolution maps are notably cleaner and more complete: MS-SVD detects substantially more microbubble events in ULM, revealing finer vessel details and more accurate flow speeds. By capturing the full acoustic signature of microbubbles (both fundamental and harmonic), MS-SVD achieves higher contrast-to-noise and sensitivity in CEUS. These gains make it a powerful front-end for super-resolution ultrasound localization microscopy and other high-sensitivity microvascular imaging applications.

Three-dimensional photoacoustic tomography (3D-PAT) enables noninvasive structural and functional imaging with optical absorption contrast and ultrasonic detection depth. However, its spatial resolution is limited by acoustic diffraction, and incomplete detection geometry can substantially degrade image fidelity and quantitative accuracy. Here, we present a ULM-guided model-based reconstruction framework, termed 3D-PAULMprior that incorporates sub-diffraction vascular priors from concurrent ultrasound localization microscopy (ULM) into 3D photoacoustic reconstruction. The method uses weighted regional Laplacian regularization to integrate high-resolution vascular information into the inverse problem, thereby enhancing vascular sharpness, suppressing limited-view artifacts, and improving blood oxygen saturation estimation. We validated 3D-PAULMprior using numerical simulations, tissue-mimicking phantoms, and in vivo mouse brain imaging. Compared with conventional reconstruction, 3D- PAULMprior improved spatial resolution by over 50%, increased contrast-to-noise ratio by 261.2%, and enhanced structural similarity index by 24.6%. In vivo, 3D-PAULMprior recovered vascular structures that were poorly resolved or missing in conventional reconstructions and produced more spatially confined sO2 maps. These results establish 3D-PAULMprior as a robust multimodal reconstruction strategy for high-resolution structural and functional photoacoustic imaging.

Point-of-care ultrasound has transformed bedside diagnostics, yet current systems remain limited by rigid form factors, bulky external electronics and the need for skilled operators. Here we report a conformable ultrasound imaging patch that integrates a 1024-channel CMOS ultrasound application-specific integrated circuit (ASIC) directly beneath a conformable piezocomposite transducer array. The 10 mm X 8 mm, 1024-element ASIC contains on-chip transmit and receive beamforming, reducing the effective off-chip channel count by 16X while preserving image fidelity. Fabricated on a flexible polyimide substrate and bonded using anisotropic conductive film, the patch operates untethered from conventional ultrasound consoles and requires only a laptop for control and data acquisition. The device supports focused, plane-wave and diverging-wave transmission with steering over {+/-}30{degrees} in azimuth and {+/-}15{degrees} in elevation, achieving peak-to-peak acoustic pressures up to 7 MPa at a 4.4-MHz center frequency (mechanical index of 1.7), within diagnostic safety limits. Phantom experiments demonstrate three-dimensional imaging with axial and lateral resolutions (in both XZ and YZ planes) of 0.5 mm and 2 mm, respectively, and accurate contrast reproduction in tissue-mimicking phantoms. Human studies further demonstrate three-dimensional (3D) visualization of the internal jugular vein and carotid artery, as well as rib-shadow-free imaging of pleural motion during respiration. This work establishes a scalable architecture for chronic, wearable ultrasound imaging and highlights the potential of CMOS-integrated, conformable ultrasound systems for continuous physiological monitoring and remote diagnostics.

Blood clot formation and thrombolysis are dynamic biological processes that play central roles in hemostasis, thrombosis, and thrombolytic therapy. Monitoring clot evolution is challenging, as existing approaches often rely on specialized hardware or complex acquisition protocols. This study presents dense speed-of-sound shift imaging (DSI), a noninvasive ultrasound framework for spatiotemporal monitoring of coagulation and lysis from ultrasound image sequences acquired with a single imaging transducer. DSI estimates interframe displacements using dense optical flow and reconstructs slowness-shift maps by solving a regularized inverse problem, from which relative speed-of-sound (SoS) shifts are derived. Using this approach, we quantified spatially localized acoustic signatures of material solidification, clot formation, and enzymatic clot dissolution across systems of increasing biological complexity, including thermally gelling gelatin, fibrin clots, and porcine and human whole blood. DSI detected composition-dependent clot properties, with fibrinogen primarily affecting SoS shift magnitude and thrombin primarily affecting clotting kinetics. In both porcine and human whole blood, DSI tracked the full transition from rapid clot formation to tPA-mediated thrombolysis, revealing markedly slower lysis kinetics and species-dependent differences in clotting amplitude and stabilization time. Together, these results establish DSI as a simple, ultrasound-based platform for quantitative monitoring of coagulation, thrombolysis, and related biological material transitions.

Hyperspectral imaging (HSI) has gained increasing attention for bone assessment because it captures rich wavelength dependent information associated with mineralised tissue. HSI provides detailed spectral information related to material composition, while 3D geometric information supports the analysis of surface morphology and structural detail. However, integrating spectral and geometric information remains challenging, particularly when conventional reconstruction pipelines depend on external pose estimation. To address this challenge, we propose BoNeRF-HS, a self-calibrated hyperspectral neural radiance field for 3D reconstruction. BoNeRF-HS jointly optimises camera intrinsics, volume density, and hyperspectral radiance, removing the need for COLMAP based poses. To improve spectral modelling, we incorporate a gated spectral adapter head that learns wavelength dependent radiance features for hyperspectral view synthesis. We evaluate BoNeRF-HS on a multi-view hyperspectral dataset containing mouse bone, trabecular bone analogue, and cortical bone analogue samples. Experimental results demonstrate that our framework achieves improved reconstruction quality, and better preservation of bone surface details compared with existing approaches.

PurposeTo enhance the SNR in MRI within a localized region of interest using a novel interventional wireless RF resonator probe combined with a dual-drive pTx system. MethodsA dual-drive body birdcage coil was operated in a linearly-polarized mode to decouple a passive RF resonator probe from the transmit field while maintaining the resonator in a receive-only coupled mode. The resonator was fabricated using standard microfabrication techniques and tuned to the Larmor frequency of a 3T MRI system. The 10-g specific absorption rate (SAR) distribution was simulated to identify potential hot spots around the resonator prior to heating experiments. To evaluate the interaction between the resonator probe and the linearly-polarized transmit field, SNR and flip-angle distributions were measured in a phantom. In vivo imaging studies were subsequently performed using the resonator probe in conjunction with the linearly-polarized dual-drive birdcage coil. ResultsTemperature measurements demonstrated a normalized temperature increase of less than 0.10{degrees}C, corresponding to a SAR value below 1.21 W/kg. Experimental flip-angle mapping confirmed effective magnetic decoupling of the resonator probe using linearly-polarized dual-drive transmission. An SNR enhancement factor of 1.6 was achieved within the region of interest in phantom experiments. In vivo imaging demonstrated a 2.0 {+/-} 0.2-fold SNR enhancement in the vicinity of the resonator probe. ConclusionA novel interventional approach for localized SNR enhancement in MRI was demonstrated using a wireless RF resonator probe and a dual-drive pTx system. The proposed technique enables local signal enhancement while minimizing transmit-field interactions, thereby facilitating safe interventional MRI and potentially improving image quality and diagnostic performance.

Minimally invasive surgery is a powerful technique that enables operations deep within the body while minimizing patient trauma and recovery time. Optical endoscopes are key to providing intraoperative vision but still face challenges due to the loss of essential senses, including depth perception and tactile feedback for tissue evaluation. Thus, it is critical to develop endoscopic imaging technologies that can augment operators with critical information. In this work, we explore a prototype multimodal 3D imaging endoscope that integrates volumetric light-field imaging with laser-speckle contrast imaging to simultaneously capture 3D structure and blood-flow information in a clinically relevant form factor.

Inverse-scattering methods enable label-free, quantitative visualization of a samples three-dimensional (3D) refractive index (RI), providing intrinsic and volumetric morphological contrast without exogenous labels. This is achieved by developing computational frameworks that reconstruct the samples 3D RI from a series of scattering measurements acquired under different data-capture conditions. Recent advances have demonstrated successful 3D RI reconstructions in multiple-scattering samples using angle-varying illuminations; however, these studies have primarily focused on non-absorptive samples. Here, we extend the multi-slice beam propagation (MSBP) inverse-scattering framework to reconstruct complex-valued RI, encompassing both the samples conventional RI (real part) and absorptivity (imaginary part). We show that reconstructing complex-valued RI makes the inverse problem ill-posed under angle-varying illumination alone, and that incorporating measurement diversity from both angle-varying illumination and sample defocus is necessary to ensure stable and accurate convergence. Experimental demonstrations were conducted on 1) dyed microsphere samples to characterize accuracy of reconstructed RI and absorptivity; and 2) diverse absorptive scattering samples to demonstrate biological utility. These results represent an important step for label-free volumetric imaging in biological tissue, which typically exhibits both scattering and absorption.

Transcranial focused ultrasound is an emerging noninvasive neuromodulation technique offering high spatial precision and deep penetration. However, in deep brain neuromodulation in mice, the skull base attenuates the signal, distorting the focal region and creating off-target peaks. This study presents a machine-learning-driven simulation framework to optimize a bowl-shaped phased-array transducer design for hypothalamic targeting and compares its performance with that of time-reversal phase conjugation and a single-element baseline. A computed tomography-based mouse head model was used for full-wave acoustic simulations with a fixed bowl geometry (10 mm aperture, 6 mm radius of curvature). Designs were evaluated across various parameters, including operating frequency (0.2-1.5 MHz), active element count (16, 32, 64, 128), and element diameter (300-550 m). The evaluation employed four metrics: the presence of a -3 dB focal region within the hypothalamic area, axial focal length defined by the -3 dB full-width at half maximum, focal fragmentation measured by the -3 dB blob count, and targeting displacement. Random Forest surrogate models were trained in simulation outputs and paired with the Non-dominated Sorting Genetic Algorithm II to reduce computational costs during multi-objective optimization. The forward-excitation-optimized phased-array design (0.73 MHz, 128 elements, 381 m element diameter) achieved a focal region at the hypothalamic target with a full width at half maximum of 0.67 mm, a blob count of 1, and a targeting displacement of 0.38 mm when placed 1 mm below the nominal position. Time-reversal phase conjugation further improved confinement and targeting (full width at half maximum: 0.59 mm; displacement: 0.37 mm). Limitations include reliance on a single mouse anatomy, and incorporating additional CT-derived anatomies should enhance generalizability across strains, ages, and sexes. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/727023v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@62de15org.highwire.dtl.DTLVardef@e26e57org.highwire.dtl.DTLVardef@1ba4893org.highwire.dtl.DTLVardef@f2c77a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA CT-based acoustic simulation and machine-learning framework was developed to optimize bowl-shaped phased-array transducers for mouse hypothalamic tFUS neuromodulation. C_LIO_LIRandom Forest surrogate models coupled with NSGA-II efficiently identified optimized array designs across frequency, element count, and element diameter. C_LIO_LIThe optimized phased-array design produced a compact hypothalamic focus with submillimeter targeting displacement, with further confinement achieved using time-reversal phase conjugation. C_LI

Quantifying cells within intact three-dimensional biological specimens remains a major challenge, as standard optical and histological techniques are inherently two-dimensional, destructive, or constrained by light scattering. Optical clearing can extend imaging depth but is time-consuming, disruptive to tissue integrity, and often incompatible with downstream analyses, limiting its practical use for routine three-dimensional quantification. X-ray computed tomography can overcome these limitations, yet conventional micro-CT lacks the soft-tissue contrast required for cellular-scale analysis. Here, we introduce an integrated imaging framework in which propagation-based phase-contrast X-ray CT is combined with volumetric nuclear segmentation to enable three-dimensional cell quantification in unstained volumetric tissue. We imaged ex vivo human liver tissue and segmented nuclei throughout the reconstructed volume, extracting quantitative nuclear metrics and spatial organisation metrics, including equivalent diameter, minor-to-major axis ratio and nearest-neighbour distance. We assessed measurement consistency across two non-overlapping volumes of interest and benchmark slice-resolved nuclear metrics against haematoxylin and eosin histology. The resulting high-contrast volumetric datasets preserve tissue context, allowing quantitative measurements to be interpreted alongside surrounding architecture and microstructure. Together, these results show that laboratory phase-contrast X-ray CT supports nucleibased volumetric cell quantification in intact unstained tissue and provides a framework for context-preserving quantitative analysis in three dimensions.

Background. Ortho-positronium (o-Ps) lifetime, now measurable in vivo on long-axial-field-of-view (LAFOV) PET/CT, has been proposed as a biomarker of tissue oxygenation and hypoxia. Because o-Ps lifetime is dominated by tissue free-volume structure while the oxygen- specific contribution is small, whether an in-vivo lifetime contrast reflects oxygenation rather than anatomy is an open, identifiability-limited question. Aim. To test the oxygenation hypothesis directly using the heart's natural arterial/venous oxygenation contrast, with a built-in anatomical control. Methods. We re-analysed a public [82Rb]Cl human cardiac LAFOV PET/CT dataset (5.30 x 10^8 evaluated three-photon events). Per-compartment o-Ps lifetimes were extracted with a background-plus-two-component exponentially-modified-Gaussian (EMG) model. The list-mode to image mapping and right/left ventricle (RV/LV) identity were established lifetime-free (the mapping reproduces the provider's reconstructed image at block-correlation 0.998 and wins a joint multi-organ alignment panel). We applied a confound battery: registration stress test, blood-core vs wall, lung-air and wall-myocardium partial-volume, tissue density; and a structure/position-matched control (pulmonary artery, deoxygenated, vs aorta, oxygenated). An isotope-matched 82Rb uniform-quartz reference bounded the instrument's positional behaviour. All results were produced by two independent analysis pipelines. Results. RV o-Ps lifetime exceeded LV by delta tau = +0.304 ns (RV 1.700 +/- 0.172, LV 1.396 +/- 0.130 ns; about 1.4 sigma), in the oxygen-expected direction; the contrast was stable across +/-16 mm registration perturbation (sign preserved in 100% of 342 shifts) and resided in the blood core, not the wall. However, the matched-vessel control was null: pulmonary artery minus aorta = -0.011 +/- 0.344 ns. Lung-air and wall-myocardium partial-volume were disfavoured, and the effect fell within the isotope-matched 82Rb instrumental positional envelope (about 0.1-0.35 ns over 40 mm in uniform material). Conclusion. On this single subject, the cardiac o-Ps lifetime contrast does not provide a clean readout of blood oxygenation: an oxygenation effect of the observed (about 0.3 ns) magnitude is ruled out by the matched control, while a small physiological effect cannot be excluded. We provide a reusable confound-control battery for evaluating future in-vivo o-Ps oxygenation claims. Multi-subject replication with anatomy decoupled from oxygenation is required.

Urinary stone disease is a common urological condition with increasing incidence, particularly in developed countries. Laser lithotripsy (LL) has become a preferred minimally invasive treatment due to its high precision and low tissue damage. Recent studies suggest that cavitation plays a critical role in stone damage during LL, and three-dimensional passive cavitation mapping (3D-PCM) has emerged as a promising tool for detecting these events. However, clinical translation of 3D-PCM remains challenging due to limitations in imaging depth, field of view (FOV), and procedural compatibility. Here, we present a large-FOV dual-modality imaging system (3D-PCM and B-mode ultrasound) based on a large-aperture planar ultrasound array. Through array optimization and model-based reconstruction, our system achieves an expanded FOV of ~40*40mm^2 at a clinically relevant imaging depth of ~110mm, while maintaining high spatial resolution of ~0.6 mm laterally and ~0.4 mm axially. In vivo experiments in a porcine model demonstrate that the reconstructed cavitation distribution correlates well with stone damage. Our technology has the potential to provide real-time treatment feedback during LL without disrupting the standard workflow.