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.

Radiation enhancement using focussed ultrasound-stimulated microbubbles for breast cancer: A Phase 1 clinical trial.

BACKGROUND: Preclinical studies have demonstrated that tumour cell death can be enhanced 10- to 40-fold when radiotherapy is combined with focussed ultrasound-stimulated microbubble (FUS-MB) treatment. The acoustic exposure of microbubbles (intravascular gas microspheres) within the target volume causes bubble cavitation, which induces perturbation of tumour vasculature and activates endothelial cell apoptotic pathways responsible for the ablative effect of stereotactic body radiotherapy. Subsequent irradiation of a microbubble-sensitised tumour causes rapid increased tumour death. The study here presents the mature safety and efficacy outcomes of magnetic resonance (MR)-guided FUS-MB (MRgFUS-MB) treatment, a radioenhancement therapy for breast cancer. METHODS AND FINDINGS: This prospective, single-center, single-arm Phase 1 clinical trial included patients with stages I-IV breast cancer with in situ tumours for whom breast or chest wall radiotherapy was deemed adequate by a multidisciplinary team (clinicaltrials.gov identifier: NCT04431674). Patients were excluded if they had contraindications for contrast-enhanced MR or microbubble administration. Patients underwent 2 to 3 MRgFUS-MB treatments throughout radiotherapy. An MR-coupled focussed ultrasound device operating at 800 kHz and 570 kPa peak negative pressure was used to sonicate intravenously administrated microbubbles within the MR-guided target volume. The primary outcome was acute toxicity per Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Secondary outcomes were tumour response at 3 months and local control (LC). A total of 21 female patients presenting with 23 primary breast tumours were enrolled and allocated to intervention between August/2020 and November/2022. Three patients subsequently withdrew consent and, therefore, 18 patients with 20 tumours were included in the safety and LC analyses. Two patients died due to progressive metastatic disease before 3 months following treatment completion and were excluded from the tumour response analysis. The prescribed radiation doses were 20 Gy/5 fractions (40%, n = 8/20), 30 to 35 Gy/5 fractions (35%, n = 7/20), 30 to 40 Gy/10 fractions (15%, n = 3/20), and 66 Gy/33 fractions (10%, n = 2/20). The median follow-up was 9 months (range, 0.3 to 29). Radiation dermatitis was the most common acute toxicity (Grade 1 in 16/20, Grade 2 in 1/20, and Grade 3 in 2/20). One patient developed grade 1 allergic reaction possibly related to microbubbles administration. At 3 months, 18 tumours were evaluated for response: 9 exhibited complete response (50%, n = 9/18), 6 partial response (33%, n = 6/18), 2 stable disease (11%, n = 2/18), and 1 progressive disease (6%, n = 1/18). Further follow-up of responses indicated that the 6-, 12-, and 24-month LC rates were 94% (95% confidence interval [CI] [84%, 100%]), 88% (95% CI [75%, 100%]), and 76% (95% CI [54%, 100%]), respectively. The study's limitations include variable tumour sizes and dose fractionation regimens and the anticipated small sample size typical for a Phase 1 clinical trial. CONCLUSIONS: MRgFUS-MB is an innovative radioenhancement therapy associated with a safe profile, potentially promising responses, and durable LC. These results warrant validation in Phase 2 clinical trials. TRIAL REGISTRATION: clinicaltrials.gov, identifier NCT04431674.

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.

Development of an ultrasound-mediated nano-sized drug-delivery system for cancer treatment: from theory to experiment.

Aim: To establish a methodology for understanding how ultrasound (US) induces drug release from nano-sized drug-delivery systems (NSDDSs) and enhances drug penetration and uptake in tumors. This aims to advance cancer treatment strategies. Materials & methods: We developed a multi-physics mathematical model to elucidate and understand the intricate mechanisms governing drug release, transport and delivery. Unique in vitro models (monolayer, multilayer, spheroid) and a tailored US exposure setup were introduced to evaluate drug penetration and uptake. Results: The results highlight the potential advantages of US-mediated NSDDSs over conventional NSDDSs and chemotherapy, notably in enhancing drug release and inducing cell death. Conclusion: Our sophisticated numerical and experimental methods aid in determining and quantifying drug penetration and uptake into solid tumors.

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.

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.

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.

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.

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.

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.

Quantification of extravasation and binding of PSMA-targeted nanobubbles by modelling the second-wave phenomenon.

PURPOSE: With about ten-fold smaller diameter than MBs, nanobubbles (NBs) were developed as new-generation ultrasound contrast agents (UCA) able to extravasate and target specific receptors expressed on extravascular cancer cells, such as the prostate-specific membrane antigen (PSMA). It has been shown that PSMA-targeted NBs (PSMA-NBs) can bind to specific prostate cancer (PCa) cells and exhibit a prolonged retention effect (PRE), observable by NB-based CEUS (NB-CEUS). However, previous analyses of PRE were mainly limited to the semi-quantitative assessment of the time-intensity curve (TIC) in an entire tumor ROI, possibly losing information on tumor spatial heterogeneity and local characteristics. When analyzing the pixel-level TICs of free NB-based CEUS, we observed a unique second-wave phenomenon: The first pass of the NB wave (bolus) is usually accompanied by a second wave in the time range of 3 to 15 min after the bolus injection. Such a phenomenon was shown to be potentially valuable in supporting the diagnostics of cancerous lesions. PROCEDURES: Seven male athymic nude mice were included and implanted with a tumor expressing PSMA (PSMA+) and tumors not expressing PSMA (PSMA-) on two flanks. Using either free NBs or PSMA-NBs, the characteristics of pixel-level TICs were estimated by a specialized model accounting for the two-wave phenomenon, compared with a conventional model describing only one wave. The estimated parameters by the two models were presented as parametric maps to visualize the PRE of PSMA-NBs in a dual-tumor mouse model. The effectiveness of the two models were also assessed by comparing the estimated parameters in the PSMA+ and PSMA- tumors through Mann-Whitney U test and quartile difference. RESULTS: Two parameters, the peak time and residual factor of the second wave, by the second-wave model were significantly different between PSMA+ and PSMA- tumors when using PSMA-NBs. Compared with the TICs of free NBs, TICs of PSMA-NBs present higher peak intensity and a more delayed second wave, especially in the PSMA+ tumor. CONCLUSIONS: The estimation of parametric maps allows the estimation and visualization of specific binding of PSMA-NBs in PCa. The incorporation of the second-wave phenomenon enrich our understanding of NB kinetics in vivo and can possibly contribute to improved diagnostics of PCa in the future.

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.

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.

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.

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.

Novel MRI-guided focussed ultrasound stimulated microbubble radiation enhancement treatment for breast cancer.

Preclinical studies have demonstrated focused ultrasound (FUS) stimulated microbubble (MB) rupture leads to the activation of acid sphingomyelinase-ceramide pathway in the endothelial cells. When radiotherapy (RT) is delivered concurrently with FUS-MB, apoptotic pathway leads to increased cell death resulting in potent radiosensitization. Here we report the first human trial of using magnetic resonance imaging (MRI) guided FUS-MB treatment in the treatment of breast malignancies. In the phase 1 prospective interventional study, patients with breast cancer were treated with fractionated RT (5 or 10 fractions) to the disease involving breast or chest wall. FUS-MB treatment was delivered before 1st and 5th fractions of RT (within 1 h). Eight patients with 9 tumours were treated. All 7 evaluable patients with at least 3 months follow-up treated for 8 tumours had a complete response in the treated site. The maximum acute toxicity observed was grade 2 dermatitis in 1 site, and grade 1 in 8 treated sites, at one month post RT, which recovered at 3 months. No RT-related late effect or FUS-MB related toxicity was noted. This study demonstrated safety of combined FUS-MB and RT treatment. Promising response rates suggest potential strong radiosensitization effects of the investigational modality.Trial registration: clinicaltrials.gov, identifier NCT04431674.

A spatiotemporal computational model of focused ultrasound heat-induced nano-sized drug delivery system in solid tumors.

Focused Ultrasound (FUS)-triggered nano-sized drug delivery, as a smart stimuli-responsive system for treating solid tumors, is computationally investigated to enhance localized delivery of drug and treatment efficacy. Integration of thermosensitive liposome (TSL), as a doxorubicin (DOX)-loaded nanocarrier, and FUS, provides a promising drug delivery system. A fully coupled partial differential system of equations, including the Helmholtz equation for FUS propagation, bio-heat transfer, interstitial fluid flow, drug transport in tissue and cellular spaces, and a pharmacodynamic model is first presented for this treatment approach. Equations are then solved by finite element methods to calculate intracellular drug concentration and treatment efficacy. The main objective of this study is to present a multi-physics and multi-scale model to simulate drug release, transport, and delivery to solid tumors, followed by an analysis of how FUS exposure time and drug release rate affect these processes. Our findings not only show the capability of model to replicate this therapeutic approach, but also confirm the benefits of this treatment with an improvement of drug aggregation in tumor and reduction of drug delivery in healthy tissue. For instance, the survival fraction of tumor cells after this treatment dropped to 62.4%, because of a large amount of delivered drugs to cancer cells. Next, a combination of three release rates (ultrafast, fast, and slow) and FUS exposure times (10, 30, and 60 min) was examined. Area under curve (AUC) results show that the combination of 30 min FUS exposure and rapid drug release leads to a practical and effective therapeutic response.

A Quantitative Study of Thermal and Non-thermal Mechanisms in Ultrasound-Induced Nano-drug Delivery.

OBJECTIVE: The primary objective of this study was to quantify the contributions to drug release for thermal and non-thermal mechanisms in ultrasound-induced release from gold nanoparticles (GNPs) for the first time. METHODS: We studied doxorubicin (DOX) and curcumin release from the surface of GNPs using two different methods to induce drug release in an ex vivo tissue model: (i) localized tissue heating with a water bath and (ii) low-intensity pulsed ultrasound (LIPUS) exposure. Both methods have similar temperature profiles and can induce the release of both hydrophobic (curcumin) and hydrophilic (DOX) drugs from the surface of GNPs. Quantitative drug release in both cases was compared via fluorescence measurements. DISCUSSION: The water bath heating method induced drug release using thermal effects only, whereas LIPUS exposure induced drug release used a combination of thermal and non-thermal mechanisms. It was found that there were increases of 70 ± 16% (curcumin) and 127 ± 20% (DOX) in drug release when LIPUS was used to induce drug release (both thermal and non-thermal mechanisms) as compared with the water bath (thermal mechanisms only) mediated release. CONCLUSION: We determined that non-thermal mechanisms account for 41 ± 3% of curcumin release and 56 ± 4% of DOX release. It was concluded that in our ex vivo tissue model, the non-thermal mechanisms play a significant role in LIPUS-induced drug release from GNP drug carriers and that the contributions of non-thermal mechanisms to drug release depend on the type of anticancer drug loaded on the GNP surface.