David D. Nolte

Networks of intersecting fractures often provide the flow paths through subsurface reservoirs. Assessing network connectivity is challenging because fracture intersections compose a vanishingly small fraction of the network void volume. In this paper, motivated by 3D X‐ray imaging of the simplest element of fracture network, that is, two orthogonal fractures, we perform a percolation and finite‐size scaling analysis to study the connectivity provided by fracture intersections. The conditions when an intersection enhances connectivity across a sample depend on spatial correlations in the fracture aperture distributions, on the stress state, and on the direction of flow. Here we consider three flow directions: (a) across intersections, (b) parallel to intersections and (c) around corners. For (a), intersections provide minimal enhancement of connectivity because they contribute little additional void area. For (b), intersections increase the probability of a connected path near threshold by enabling 3D connected pathways that are not possible in parallel fractures. Flow around corners, (c), is fundamentally the result of the intersection connecting two fractures in series and spatial correlations are broken around corners, suppressing the connectivity relative to (a). When the connected fractures are stressed equally, a joint percolation threshold emerges that continues to have scale invariance. However, when the fractures are stressed unequally, the system has mixed percolation without clearly defined percolation thresholds. In all cases, percolation probabilities are found to be scale dependent which has important consequences for the connectivity of larger fracture networks composed of the fundamental element studied here.

Fractures evolve in time through thermal‐hydraulic‐mechanical‐chemical (THMC) processes that alter their long‐range hydraulic transport properties and modify subsurface behavior and activities. The location of subsurface fractures makes it necessary to use remote sensing techniques such as passive or active seismic monitoring for fracture characterization. In this paper, we develop a machine learning approach to monitor the evolution of fracture properties using passive seismic sources in a laboratory setting and using active seismic monitoring from the Sanford Underground Research Facility in Lead, South Dakota, at a depth of 1.25 km in amphibolite rock during stimulation of natural fractures as well as during induced fracturing. The unsupervised metric learning technique applies tandem neural networks (twin (Siamese) or triplet) with contrastive loss and adaptive margins to track slowly varying systems for which class or similarity labels are not available. The approach adopts locality‐sensitive hashing to divide time‐ordered contiguous data into an arbitrary number of pseudo‐classes. Contrastive‐loss training with many hash bins generates an evolving latent‐space trajectory. This approach enables unsupervised metric learning for seismic data stacks under the condition of contiguous state sampling and slowly varying fracture properties. The displacement discontinuity theory provides a mechanistic foundation for the fracture‐dependent trajectories that are related to relaxation of fractures with time‐dependent specific stiffness responding to changes in stress or fluid saturation.

Living organisms are frequently used as sentinels to monitor changes in the environment, and organoids can serve a similar function as in vitro sentinels detecting microbiological processes. One such process of great interest is pathogenic infection, which causes alterations in the cellular dynamics of the sentinels. Doppler light scattering is well suited to measure such changes, as it is sensitive to the intracellular dynamics of the organoids even when the microbe density is too dilute to detect directly. In this paper, we present measurements of the endogenous changes of intracellular dynamics of DLD organoids (microclusters) in response to bacterial infection, detected using a long-coherence form of biodynamic imaging (BDI), a dynamic-contrast digital holography technique that captures the Doppler shifts encoded in the dynamic speckles. With a stable common-path digital holography system and using small in-vitro tissue microclusters, clinically relevant inoculum doses as low as 100 cfu/mL cause detectable changes in intracellular Doppler spectra within hours of infection and several hours before the proliferating bacteria population causes direct light scattering. Because it can measure effects for small bacterial populations, the method shows promise as a fast diagnostic tool to detect the presence of bacteria in patient fluid samples faster than traditional methods.

The global pandemic at the start of this decade reminded us that viral infection remains a significant health threat across the globe. A major difficulty in suppressing the spread of infections is that detecting the infection is very difficult in the early stages of the epidemic, before targeted tests like PCR becomes available, when there is very little information available about the virus. Moreover, virus boasts extremely high rate of mutation, creating the need for new tests constantly. We report our preliminary work on the use of Biodynamic Imaging (BDI), a dynamic-contrast full field OCT technique, in attempts to detect the infection of Crandell-Rees Feline Kidney (CRFK) spheroids with Canine Parvovirus (CPV).

Doppler frequency shifts associated with the motions in cells range from mHz to Hz, requiring ultra-stable interferometry to capture frequency offsets at several parts in 10¹⁸. Common-path interferometers minimize the influence of mechanical disturbances when the signal and reference share common optical elements. In this paper, multi-mode speckle self-referencing via a Fresnel biprism demonstrates frequency stability down to 1 mHz. A low-coherence NIR source creates an OCT-like pseudo-coherence-gate in Fourier-domain holography without phase stepping, and the Fourier reconstruction of the self-referencing speckle fields produces an image-domain autocorrelation of the target. Fluctuation spectroscopy of dynamic speckle is performed on a semi-solid lipid emulsion that captures Brownian thermal signatures and on feline tissue culture that measures active intracellular transport. The extension of biodynamic imaging to lower frequencies opens the opportunity for studies of cell crawling in macroscopic living tissues.

Despite improvements in the ability to treat cancer, first-line chemotherapy in standard-of-care treatments still fail to elicit a response from about half of cancer patients. This limitation signals a pressing need for practical methods to select personalized cancer therapies. Biodynamic imaging (BDI; a form of dynamic-contrast OCT with low-coherence digital holography) on living cancer biopsies from patients shows potential as a method to guide personalized selection of cancer therapy. However, building a library of signatures for different types of cancer has been a practical obstacle. Here, a comparative preclinical/clinical trial with two-species (human and canine) and two-cancers (esophageal carcinoma and B-cell lymphoma) demonstrates the general applicability of BDI as a method of chemoresistance prediction and as a viable tool for personalized medicine. This study identifies a set of drug response phenotypes that span species and cancer type, suggesting the existence of universal characteristics, which would reduce the burden of library construction needed for the method to be useful for doctors and their patients.

This review examines the biological physics of intracellular transport probed by the coherent optics of dynamic light scattering from optically thick living tissues. Cells and their constituents are in constant motion, composed of a broad range of speeds spanning many orders of magnitude that reflect the wide array of functions and mechanisms that maintain cellular health. From the organelle scale of tens of nanometers and upward in size, the motion inside living tissue is actively driven rather than thermal, propelled by the hydrolysis of bioenergetic molecules and the forces of molecular motors. Active transport can mimic the random walks of thermal Brownian motion, but mean-squared displacements are far from thermal equilibrium and can display anomalous diffusion through Lévy or fractional Brownian walks. Despite the average isotropic three-dimensional environment of cells and tissues, active cellular or intracellular transport of single light-scattering objects is often pseudo-one-dimensional, for instance as organelle displacement persists along cytoskeletal tracks or as membranes displace along the normal to cell surfaces, albeit isotropically oriented in three dimensions. Coherent light scattering is a natural tool to characterize such tissue dynamics because persistent directed transport induces Doppler shifts in the scattered light. The many frequency-shifted partial waves from the complex and dynamic media interfere to produce dynamic speckle that reveals tissue-scale processes through speckle contrast imaging and fluctuation spectroscopy. Low-coherence interferometry, dynamic optical coherence tomography, diffusing-wave spectroscopy, diffuse-correlation spectroscopy, differential dynamic microscopy and digital holography offer coherent detection methods that shed light on intracellular processes. In health-care applications, altered states of cellular health and disease display altered cellular motions that imprint on the statistical fluctuations of the scattered light. For instance, the efficacy of medical therapeutics can be monitored by measuring the changes they induce in the Doppler spectra of living ex vivo cancer biopsies.

Nearly half of cancer patients who receive standard-of-care treatments fail to respond to their first-line chemotherapy, demonstrating the pressing need for improved methods to select personalized cancer therapies. Low-coherence digital holography has the potential to fill this need by performing dynamic contrast OCT on living cancer biopsies treated ex vivo with anti-cancer therapeutics. Fluctuation spectroscopy of dynamic light scattering under conditions of holographic phase stability captures ultra-low Doppler frequency shifts down to 10 mHz caused by light scattering from intracellular motions. In the comparative preclinical/clinical trials presented here, a two-species (human and canine) and two-cancer (esophageal carcinoma and B-cell lymphoma) analysis of spectral phenotypes identifies a set of drug response characteristics that span species and cancer type. Spatial heterogeneity across a centimeter-scale patient biopsy sample is assessed by measuring multiple millimeter-scale sub-samples. Improved predictive performance is achieved for chemoresistance profiling by identifying red-shifted sub-samples that may indicate impaired metabolism and removing them from the prediction analysis. These results show potential for using biodynamic imaging for personalized selection of cancer therapy.

Doppler spectroscopy detects signatures of bacterial infection of in vitro tissue and can monitor their suppression upon antibiotic use. Such early detection may allow quick diagnosis and selection of effective therapy for patients.

Biophotonics is a research and technology field that sits at the interface of photonics and biomedical applications, which includes clinical diagnosis, therapeutics, biotechnology, and the environment. The integration of optics and biology has been one of the most active technology areas in the past three decades, not only in curiosity-driven research but also in terms of how these technologies are translated into practice with visible impacts within a relatively short time. A prominent example is the use of lasers and photonics technologies in ophthalmology applications such as laser vision correction, artificial lenses in cataract surgery, and retinal detachment repairs. The adoption of photonics technologies in medicine is significantly faster than other medical devices in a relatively cautious and heavily regulated area, mostly owing to its natural compatibility with minimally invasive procedures. Biophotonics is an interdisciplinary and multidisciplinary area at the same time. Even for a specific application, e.g., laser vision correction, many different photonics technologies may be used in combination: UV laser ablation in cornea reshaping, ultrafast laser ablation for cap cutting, image processing and modeling for procedure planning and design, and real time eye movement tracking. Many optical modalities do not require direct contact with the target, which allows several methods to be multiplexed, e.g., to provide additional sources of diagnostic contrasts or real-time feedback and guidance for therapy.