Interaction of ultrasonically driven bubble with a soft tissue-like boundary.

This study investigates the size-dependent dynamics of bubbles and their interaction with soft boundaries under various ultrasound (US) conditions. We found that bubble behavior is influenced by size, with smaller bubbles displaying reduced inertial motion in similar ultrasound environments. Detailed analyses of three bubble sizes (1.5 µm, 15 µm, and 150 µm) next to a soft 1 kPa boundary revealed distinct patterns in radial oscillation, bubble center displacement, and boundary deflection for different ultrasound frequencies (5 kHz - 4 MHz). The smallest bubble maintained a spherical shape, while the largest experienced significant shape changes, indicative of impending jet formation. Investigating interactions at various frequencies highlighted the collapse tendency of the larger bubbles, showcasing maximum radial amplitude, displacement, and bubble wall velocity around its natural frequency. The presence of a soft boundary minimally affected radial amplitude and velocity, while the bubble displacement was contingent on the soft boundary modulus. Furthermore, boundary responses demonstrated that softer boundaries experienced less stress during bubble oscillations, exhibiting sharper peaks at resonance frequencies for larger bubbles. These findings provide valuable insights into optimizing ultrasound conditions for a variety of applications, highlighting the influence of bubble size and boundary properties on outcomes.

Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study.

Background: In patients with locally advanced breast cancer (LABC) receiving neoadjuvant chemotherapy (NAC), quantitative ultrasound (QUS) radiomics can predict final responses early within 4 of 16-18 weeks of treatment. The current study was planned to study the feasibility of a QUS-radiomics model-guided adaptive chemotherapy. Methods: The phase 2 open-label randomized controlled trial included patients with LABC planned for NAC. Patients were randomly allocated in 1:1 ratio to a standard arm or experimental arm stratified by hormonal receptor status. All patients were planned for standard anthracycline and taxane-based NAC as decided by their medical oncologist. Patients underwent QUS imaging using a clinical ultrasound device before the initiation of NAC and after the 1st and 4th weeks of treatment. A support vector machine-based radiomics model developed from an earlier cohort of patients was used to predict treatment response at the 4th week of NAC. In the standard arm, patients continued to receive planned chemotherapy with the treating oncologists blinded to results. In the experimental arm, the QUS-based prediction was conveyed to the responsible oncologist, and any changes to the planned chemotherapy for predicted non-responders were made by the responsible oncologist. All patients underwent surgery following NAC, and the final response was evaluated based on histopathological examination. Results: Between June 2018 and July 2021, 60 patients were accrued in the study arm, with 28 patients in each arm available for final analysis. In patients without a change in chemotherapy regimen (53 of 56 patients total), the QUS-radiomics model at week 4 of NAC that was used demonstrated an accuracy of 97%, respectively, in predicting the final treatment response. Seven patients were predicted to be non-responders (observational arm (n=2), experimental arm (n=5)). Three of 5 non-responders in the experimental arm had chemotherapy regimens adapted with an early initiation of taxane therapy or chemotherapy intensification, or early surgery and ended up as responders on final evaluation. Conclusion: The study demonstrates the feasibility of QUS-radiomics adapted guided NAC for patients with breast cancer. The ability of a QUS-based model in the early prediction of treatment response was prospectively validated in the current study. Clinical trial registration: clinicaltrials.gov, ID NCT04050228.

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning.

Objective: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT). Materials and methods: Several deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes. Results: Amongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network. Conclusion: Deep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism.

Numerical investigation of the effect of bubble properties on the linear resonance frequency shift due to inter-bubble interactions in ultrasonically excited lipid coated microbubbles.

Ultrasonically excited microbubbles (MBs) have numerous applications in various fields, such as drug delivery, and imaging. Ultrasonically excited MBs are known to be nonlinear oscillators that generate secondary acoustic emissions in the media when excited by a primary ultrasound wave. The propagation of acoustic waves in the liquid is limited to the speed of sound, resulting in each MB receiving the primary and secondary waves at different times depending on their distance from the ultrasound source and the distance between MBs. These delays are referred to as primary and secondary delays, respectively. A previous study demonstrated that the inclusion of secondary delays in a model describing the interactions between MBs exposed to ultrasound results in an increase in the linear resonance frequency of MBs as they approach each other. This work investigates the impact of various MB properties on the change in linear resonance frequency resulting from changes in inter-bubble distances. The effects of shell properties, including the initial surface tension, surface dilatational viscosity of the shell monolayer, elastic compression modulus of the shell, and the initial radius of the MBs, are examined. MB size is a significant factor influencing the rate of linear resonance frequency increase with increasing concentration. Moreover, it is found that the shell properties of MBs play a negligible role in the rate of change in linear resonance frequency of MBs as the inter-bubble distances change.The findings of this study have implications for various applications of MBs in the biomedical field. By understanding the impact of inter-bubble distances and shell properties on the linear resonance frequency of MBs, the utilization of MBs in applications reliant on their resonant behavior can be optimized.

Decorrelation Time Mapping as an Analysis Tool for Nanobubble-Based Contrast Enhanced Ultrasound Imaging.

Nanobubbles (NBs; ~100-500 nm diameter) are preclinical ultrasound (US) contrast agents that expand applications of contrast enhanced US (CEUS). Due to their sub-micron size, high particle density, and deformable shell, NBs in pathological states of heightened vascular permeability (e.g. in tumors) extravasate, enabling applications not possible with microbubbles (~1000-10,000 nm diameter). A method that can separate intravascular versus extravascular NB signal is needed as an imaging biomarker for improved tumor detection. We present a demonstration of decorrelation time (DT) mapping for enhanced tumor NB-CEUS imaging. In vitro models validated the sensitivity of DT to agent motion. Prostate cancer mouse models validated in vivo imaging potential and sensitivity to cancerous tissue. Our findings show that DT is inversely related to NB motion, offering enhanced detail of NB dynamics in tumors, and highlighting the heterogeneity of the tumor environment. Average DT was high in tumor regions (~9 s) compared to surrounding normal tissue (~1 s) with higher sensitivity to tumor tissue compared to other mapping techniques. Molecular NB targeting to tumors further extended DT (11 s) over non-targeted NBs (6 s), demonstrating sensitivity to NB adherence. From DT mapping of in vivo NB dynamics we demonstrate the heterogeneity of tumor tissue while quantifying extravascular NB kinetics and delineating intra-tumoral vasculature. This new NB-CEUS-based biomarker can be powerful in molecular US imaging, with improved sensitivity and specificity to diseased tissue and potential for use as an estimator of vascular permeability and the enhanced permeability and retention (EPR) effect in tumors.

Efficient ultrasound-mediated drug delivery to orthotopic liver tumors - Direct comparison of doxorubicin-loaded nanobubbles and microbubbles.

Liver metastasis is a major obstacle in treating aggressive cancers, and current therapeutic options often prove insufficient. To overcome these challenges, there has been growing interest in ultrasound-mediated drug delivery using lipid-shelled microbubbles (MBs) and nanobubbles (NBs) as promising strategies for enhancing drug delivery to tumors. Our previous work demonstrated the potential of Doxorubicin-loaded C3F8 NBs (hDox-NB, 280 ± 123 nm) in improving cancer treatment in vitro using low-frequency unfocused therapeutic ultrasound (TUS). In this study, we investigated the pharmacokinetics and biodistribution of sonicated hDox-NBs in orthotopic rat liver tumors. We compared their delivery and therapeutic efficiency with size-isolated MBs (hDox-MB, 1104 ± 373 nm) made from identical shell material and core gas. Results showed a similar accumulation of hDox in tumors treated with hDox-MBs and unfocused therapeutic ultrasound (hDox-MB + TUS) and hDox-NB + TUS. However, significantly increased apoptotic cell death in the tumor and fewer off-target apoptotic cells in the normal liver were found upon the treatment with hDox-NB + TUS. The tumor-to-liver apoptotic ratio was elevated 9.4-fold following treatment with hDox-NB + TUS compared to hDox-MB + TUS, suggesting that the therapeutic efficacy and specificity are significantly increased when using hDox-NB + TUS. These findings highlight the potential of this approach as a viable treatment modality for liver tumors. By elucidating the behavior of drug-loaded bubbles in vivo, we aim to contribute to developing more effective liver cancer treatments that could ultimately improve patient outcomes and decrease off-target side effects.

Green synthesis of anti-cancer drug-loaded gold nanoparticles for low-intensity pulsed ultrasound targeted drug release.

In the present work, we have designed a one-pot green protocol in which anti-cancer drugs (curcumin and doxorubicin) can be directly loaded on the surface of gold nanoparticles during their formation. We have further demonstrated that low-intensity pulsed ultrasound (LIPUS) can be used to effectively induce the release of anti-cancer drugs from the surface of gold nanoparticles in an ex vivo tissue model. With this protocol, gold nanoparticles can be easily loaded with different types of anticancer drugs, irrespective of their affinity towards water, and even hydrophobic molecules, like curcumin, can be attached onto the gold nanoparticles in an aqueous medium. The method is very simple and straightforward and does not require stirring or mechanical shaking. The drug molecules interact with the gold seeds formed during the reduction and growth process and modulate the final morphology into a spherical shape. A black-colored colloidal solution of gold nanowire networks is formed in the absence of these anti-cancer drug molecules in the reaction mixture. We used hyperspectral-enhanced dark field microscopy to examine the uptake of gold nanoparticles by breast cancer cells. Upon exposure to LIPUS, the release of the anti-cancer drug from the particle surface can be quantified by fluorescence measurements. This release of drug molecules along with trisodium citrate from the surface of gold nanoparticles by ultrasound resulted in their destabilization and subsequent aggregation, which could be visually observed through the change in the color of colloidal sol. Cancer cell viability was studied by MTT assay to examine the efficacy of this nanoparticle-based drug delivery system. Ultraviolet-visible spectroscopy, dynamic light scattering (DLS), and transmission electron microscope (TEM) analysis were used to characterize the nanoparticles and quantify anti-cancer drug release.

Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy.

Locally advanced breast cancer (LABC) is a severe type of cancer with a poor prognosis, despite advancements in therapy. As the disease is often inoperable, current guidelines suggest upfront aggressive neoadjuvant chemotherapy (NAC). Complete pathological response to chemotherapy is linked to improved survival, but conventional clinical assessments like physical exams, mammography, and imaging are limited in detecting early response. Early detection of tissue response can improve complete pathological response and patient survival while reducing exposure to ineffective and potentially harmful treatments. A rapid, cost-effective modality without the need for exogenous contrast agents would be valuable for evaluating neoadjuvant therapy response. Conventional ultrasound provides information about tissue echogenicity, but image comparisons are difficult due to instrument-dependent settings and imaging parameters. Quantitative ultrasound (QUS) overcomes this by using normalized power spectra to calculate quantitative metrics. This study used a novel transfer learning-based approach to predict LABC response to neoadjuvant chemotherapy using QUS imaging at pre-treatment. Using data from 174 patients, QUS parametric images of breast tumors with margins were generated. The ground truth response to therapy for each patient was based on standard clinical and pathological criteria. The Residual Network (ResNet) deep learning architecture was used to extract features from the parametric QUS maps. This was followed by SelectKBest and Synthetic Minority Oversampling (SMOTE) techniques for feature selection and data balancing, respectively. The Support Vector Machine (SVM) algorithm was employed to classify patients into two distinct categories: nonresponders (NR) and responders (RR). Evaluation results on an unseen test set demonstrate that the transfer learning-based approach using spectral slope parametric maps had the best performance in the identification of nonresponders with precision, recall, F1-score, and balanced accuracy of 100, 71, 83, and 86%, respectively. The transfer learning-based approach has many advantages over conventional deep learning methods since it reduces the need for large image datasets for training and shortens the training time. The results of this study demonstrate the potential of transfer learning in predicting LABC response to neoadjuvant chemotherapy before the start of treatment using quantitative ultrasound imaging. Prediction of NAC response before treatment can aid clinicians in customizing ineffectual treatment regimens for individual patients.

Ultrasound-mediated nano-sized drug delivery systems for cancer treatment: Multi-scale and multi-physics computational modeling.

Computational modeling enables researchers to study and understand various complex biological phenomena in anticancer drug delivery systems (DDSs), especially nano-sized DDSs (NSDDSs). The combination of NSDDSs and therapeutic ultrasound (TUS), that is, focused ultrasound and low-intensity pulsed ultrasound, has made significant progress in recent years, opening many opportunities for cancer treatment. Multiple parameters require tuning and optimization to develop effective DDSs, such as NSDDSs, in which mathematical modeling can prove advantageous. In silico computational modeling of ultrasound-responsive DDS typically involves a complex framework of acoustic interactions, heat transfer, drug release from nanoparticles, fluid flow, mass transport, and pharmacodynamic governing equations. Owing to the rapid development of computational tools, modeling the different phenomena in multi-scale complex problems involved in drug delivery to tumors has become possible. In the present study, we present an in-depth review of recent advances in the mathematical modeling of TUS-mediated DDSs for cancer treatment. A detailed discussion is also provided on applying these computational models to improve the clinical translation for applications in cancer treatment. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Noninvasive Quantification of Contractile Dynamics in Cardiac Cells, Spheroids, and Organs-on-a-Chip Using High-Frequency Ultrasound.

Cell-based models that mimic in vivo heart physiology are poised to make significant advances in cardiac disease modeling and drug discovery. In these systems, cardiomyocyte (CM) contractility is an important functional metric, but current measurement methods are inaccurate and low-throughput or require complex setups. To address this need, we developed a standalone noninvasive, label-free ultrasound technique operating at 40-200 MHz to measure the contractile kinetics of cardiac models, ranging from single adult CMs to 3D microtissue constructs in standard cell culture formats. The high temporal resolution of 1000 fps resolved the beat profile of single mouse CMs paced at up to 9 Hz, revealing limitations of lower speed optical based measurements to resolve beat kinetics or characterize aberrant beats. Coupling of ultrasound with traction force microscopy enabled the measurement of the CM longitudinal modulus and facile estimation of adult mouse CM contractile forces of 2.34 ± 1.40 µN, comparable to more complex measurement techniques. Similarly, the beat rate, rhythm, and drug responses of CM spheroid and microtissue models were measured, including in configurations without optical access. In conclusion, ultrasound can be used for the rapid characterization of CM contractile function in a wide range of commonly studied configurations ranging from single cells to 3D tissue constructs using standard well plates and custom microdevices, with applications in cardiac drug discovery and cardiotoxicity evaluation.

Synchronous Intravital Imaging and Cavitation Monitoring of Antivascular Focused Ultrasound in Tumor Microvasculature Using Monodisperse Low Boiling Point Nanodroplets.

Focused ultrasound-stimulated microbubbles can induce blood flow shutdown and ischemic necrosis at higher pressures in an approach termed antivascular ultrasound. Combined with conventional therapies of chemotherapy, immunotherapy, and radiation therapy, this approach has demonstrated tumor growth inhibition and profound synergistic antitumor effects. However, the lower cavitation threshold of microbubbles can potentially yield off-target damage that the polydispersity of clinical agent may further exacerbate. Here we investigate the use of a monodisperse nanodroplet formulation for achieving antivascular effects in tumors. We first develop stable low boiling point monodisperse lipid nanodroplets and examine them as an alternative agent to mediate antivascular ultrasound. With synchronous intravital imaging and ultrasound monitoring of focused ultrasound-stimulated nanodroplets in tumor microvasculature, we show that nanodroplets can trigger blood flow shutdown and do so with a sharper pressure threshold and with fewer additional events than conventionally used microbubbles. We further leverage the smaller size and prolonged pharmacokinetic profile of nanodroplets to allow for potential passive accumulation in tumor tissue prior to antivascular ultrasound, which may be a means by which to promote selective tumor targeting. We find that vascular shutdown is accompanied by inertial cavitation and complex-order sub- and ultraharmonic acoustic signatures, presenting an opportunity for effective feedback control of antivascular ultrasound.

Kinetic modelling of ultrasound-triggered chemotherapeutic drug release from the surface of gold nanoparticles.

Therapeutic ultrasound can be used to trigger the on-demand release of chemotherapeutic drugs from gold nanoparticles (GNPs). In the previous work, our group achieved doxorubicin (DOX) release from the surface of GNPS under low-intensity pulsed ultrasound (LIPUS) exposure. However, the specific release kinetics of ultrasound-triggered DOX release from GNPs is not known. Here, we present a release kinetics study of DOX from GNPs under ultrasound exposure for the first time. A novel dialysis membrane setup was designed to quantify DOX release from LIPUS-activated GNPs at 37.0 °C and 43.4 °C (hyperthermia temperature range). Contributions of thermal and non-thermal mechanisms of LIPUS-triggered DOX release were also quantified. Non-thermal mechanisms accounted for 40 ± 7% and 34 ± 5% of DOX release for 37.0 °C and 43.4 °C trials, respectively. DOX release under LIPUS exposure was found to follow Korsmeyer-Peppas (K-P) kinetics, suggesting a shift from a Fickian (static) to a non-Fickian (dynamic) release profile with the addition of non-thermal interactions. DOX release was attributed to an anomalous diffusion release mechanism from the GNP surface. A finite element model was also developed to quantify the acoustic radiation force, believed to be the driving force of non-thermal DOX release inside the dialysis bag.

Assessing Tumor Microenvironment Characteristics and Stratifying EPR with a Nanobubble Companion Nanoparticle via Contrast-Enhanced Ultrasound Imaging.

The tumor microenvironment is characterized by dysfunctional endothelial cells, resulting in heightened vascular permeability. Many nanoparticle-based drug delivery systems attempt to use this enhanced permeability combined with impaired lymphatic drainage (a concept known as the 'enhanced permeability and retention effect' or EPR effect) as the primary strategy for drug delivery, but this has not proven to be as clinically effective as anticipated. The specific mechanisms behind the inconsistent clinical outcomes of nanotherapeutics have not been clearly articulated, and the field has been hampered by a lack of accessible tools to study EPR-associated phenomena in clinically relevant scenarios. While medical imaging has tremendous potential to contribute to this area, it has not been broadly explored. This work examines, for the first time, the use of multiparametric dynamic contrast-enhanced ultrasound (CEUS) with a novel nanoscale contrast agent to examine tumor microenvironment characteristics noninvasively and in real-time. We demonstrate that CEUS imaging can: (1) evaluate tumor microenvironment features and (2) be used to help predict the distribution of doxorubicin-loaded liposomes in the tumor parenchyma. CEUS using nanobubbles (NBs) was carried out in two tumor types of high (LS174T) and low (U87) vascular permeability, and time-intensity curve (TIC) parameters were evaluated in both models prior to injection of doxorubicin liposomes. Consistently, LS174T tumors showed significantly different TIC parameters, including area under the rising curve (2.7x), time to peak intensity (1.9x) and decorrelation time (DT, 1.9x) compared to U87 tumors. Importantly, the DT parameter successfully predicted tumoral nanoparticle distribution (r = 0.86 ± 0.13). Ultimately, substantial differences in NB-CEUS generated parameters between LS174T and U87 tumors suggest that this method may be useful in determining tumor vascular permeability and could be used as a biomarker for identifying tumor characteristics and predicting sensitivity to nanoparticle-based therapies. These findings could ultimately be applied to predicting treatment efficacy and to evaluating EPR in other diseases with pathologically permeable vasculature.

A priori prediction of breast cancer response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivative and molecular subtype.

The purpose of this study was to investigate the performances of the tumor response prediction prior to neoadjuvant chemotherapy based on quantitative ultrasound, tumour core-margin, texture derivative analyses, and molecular parameters in a large cohort of patients (n = 208) with locally advanced and earlier-stage breast cancer and combined them to best determine tumour responses with machine learning approach. Two multi-features response prediction algorithms using a k-nearest neighbour and support vector machine were developed with leave-one-out and hold-out cross-validation methods to evaluate the performance of the response prediction models. In a leave-one-out approach, the quantitative ultrasound-texture analysis based model attained good classification performance with 80% of accuracy and AUC of 0.83. Including molecular subtype in the model improved the performance to 83% of accuracy and 0.87 of AUC. Due to limited number of samples in the training process, a model developed with a hold-out approach exhibited a slightly higher bias error in classification performance. The most relevant features selected in predicting the response groups are core-to-margin, texture-derivative, and molecular subtype. These results imply that that baseline tumour-margin, texture derivative analysis methods combined with molecular subtype can potentially be used for the prediction of ultimate treatment response in patients prior to neoadjuvant chemotherapy.

Multi-Scale and Multi-Physics Models of the Transport of Therapeutic/Diagnostic Cancer Agents.

The effectiveness of tumor treatment heavily relies on the successful delivery of anticancer drugs [...].

Integrating Therapeutic Ultrasound With Nanosized Drug Delivery Systems in the Battle Against Cancer.

Controlled, localized, and timely activation of nanosized drug delivery systems (NSDDSs), using an external stimulus such as therapeutic ultrasound (TUS), can improve the efficacy of cancer treatments compared to either conventional chemotherapy methods or passive NSDDSs alone. Specifically, TUS induces thermal and mechanical effects that trigger drug release from NSDDSs and overcomes drug delivery barriers in tumor microenvironments to allow nanoparticle drug carriers to penetrate more deeply into tumor tissue while minimizing side effects. This review highlights recent advancements, contemplates future prospects, and addresses challenges in using TUS-mediated NSDDSs for cancer treatment, encompassing preclinical and clinical applications.

Controlled Tempering of Lipid Concentration and Microbubble Shrinkage as a Possible Mechanism for Fine-Tuning Microbubble Size and Shell Properties.

The acoustic response of microbubbles (MBs) depends on their resonance frequency, which is dependent on the MB size and shell properties. Monodisperse MBs with tunable shell properties are thus desirable for optimizing and controlling the MB behavior in acoustics applications. By utilizing a novel microfluidic method that uses lipid concentration to control MB shrinkage, we generated monodisperse MBs of four different initial diameters at three lipid concentrations (5.6, 10.0, and 16.0 mg/mL) in the aqueous phase. Following shrinkage, we measured the MB resonance frequency and determined its shell stiffness and viscosity. The study demonstrates that we can generate monodisperse MBs of specific sizes and tunable shell properties by controlling the MB initial diameter and aqueous phase lipid concentration. Our results indicate that the resonance frequency increases by 180-210% with increasing lipid concentration (from 5.6 to 16.0 mg/mL), while the bubble diameter is kept constant. Additionally, we find that the resonance frequency decreases by 260-300% with an increasing MB final diameter (from 5 to 12 µm), while the lipid concentration is held constant. For example, our results depict that the resonance frequency increases by ∼195% with increasing lipid concentration from 5.6 to 16.0 mg/mL, for ∼11 µm final diameter MBs. Additionally, we find that the resonance frequency decreases by ∼275% with increasing MB final diameter from 5 to 12 µm when we use a lipid concentration of 5.6 mg/mL. We also determine that MB shell viscosity and stiffness increase with increasing lipid concentration and MB final diameter, and the level of change depends on the degree of shrinkage experienced by the MB. Specifically, we find that by increasing the concentration of lipids from 5.6 to 16.0 mg/mL, the shell stiffness and viscosity of ∼11 µm final diameter MBs increase by ∼400 and ∼200%, respectively. This study demonstrates the feasibility of fine-tuning the MB acoustic response to ultrasound by tailoring the MB initial diameter and lipid concentration.

Efficient ultrasound-mediated drug delivery to orthotopic liver tumors - Direct comparison of doxorubicin-loaded nanobubbles and microbubbles.

Liver metastasis is a major obstacle in treating aggressive cancers, and current therapeutic options often prove insufficient. To overcome these challenges, there has been growing interest in ultrasound-mediated drug delivery using lipid-shelled microbubbles (MBs) and nanobubbles (NBs) as promising strategies for enhancing drug delivery to tumors. Our previous work demonstrated the potential of Doxorubicin-loaded C3F8 NBs (hDox-NB, 280 ± 123 nm) in improving cancer treatment in vitro using low-frequency ultrasound. In this study, we investigated the pharmacokinetics and biodistribution of sonicated hDox-NBs in orthotopic rat liver tumors. We compared their delivery and therapeutic efficiency with size-isolated MBs (hDox-MB, 1104 ± 373 nm). Results showed a similar accumulation of hDox in tumors treated with hDox-MBs and unfocused therapeutic ultrasound (hDox-MB+TUS) and hDox-NB+TUS. However, significantly increased apoptotic cell death in the tumor and fewer off-target apoptotic cells in the normal liver were found upon the treatment with hDox-NB+TUS. The tumor-to-liver apoptotic ratio was elevated 9.4-fold following treatment with hDox-NB+TUS compared to hDox-MB+TUS, suggesting that the therapeutic efficacy and specificity are significantly increased when using hDox-NB+TUS. These findings highlight the potential of this approach as a viable treatment modality for liver tumors. By elucidating the behavior of drug-loaded bubbles in vivo, we aim to contribute to developing more effective liver cancer treatments that could ultimately improve patient outcomes and decrease off-target side effects.

Microfluidic nanobubbles: observations of a sudden contraction of microbubbles into nanobubbles.

Microfluidic devices are often utilized to generate uniform-size microbubbles. In most microfluidic bubble generation experiments, once the bubbles are formed the gas inside the bubbles begin to dissolve into the surrounding aqueous environment. The bubbles shrink until they attain an equilibrium size dictated by the concentration and type of amphiphilic molecules stabilizing the gas-liquid interface. Here, we exploit this shrinkage mechanism, and control the solution lipid concentration and microfluidic geometry, to make monodisperse bulk nanobubbles. Interestingly, we make the surprising observation of a critical microbubble diameter above and below which the scale of bubble shrinkage dramatically changes. Namely, microbubbles generated with an initial diameter larger than the critical diameter shrinks to a stable diameter that is consistent with previous literature. However, microbubbles that are initially smaller than the critical diameter experience a sudden contraction into nanobubbles whose size is at least an order-of-magnitude below expectations. We apply electron microscopy and resonance mass measurement methods to quantify the size and uniformity of the nanobubbles, and probe the dependence of the critical bubble diameter on the lipid concentration. We anticipate that further analysis of this unexpected microbubble sudden contraction regime can lead to more robust technologies for making monodisperse nanobubbles.

Detection of clot formation & lysis In-Vitro using high frequency photoacoustic imaging & frequency analysis.

Clotting is a physiological process that prevents blood loss after injury. An imbalance in clotting factors can lead to lethal consequences such as exsanguination or inappropriate thrombosis. Clinical methods to monitor clotting and fibrinolysis typically measure the viscoelasticity of whole blood or optical density of plasma over time. Though these methods provide insights into clotting and fibrinolysis, they require milliliters of blood which can worsen anemia or only provide partial information. To overcome these limitations, a high-frequency photoacoustic (HFPA) imaging system was developed to detect clotting and lysis in blood. Clotting was initiated in vitro in reconstituted blood using thrombin and lysed with urokinase plasminogen activator. Frequency spectra measured using HFPA signals (10-40 MHz) between non-clotted blood and clotted blood differed markedly, allowing tracking of clot initiation and lysis in volumes of blood as low as 25 µL/test. HFPA imaging shows potential as a point-of-care examination of coagulation and fibrinolysis.