Combination of chemotherapy and focused ultrasound for the treatment of unresectable pancreatic cancer: a proof-of-concept study

Pancreatic ductal adenocarcinoma cells reshape the immune microenvironment: Molecular mechanisms and therapeutic targets

Pancreatic ductal adenocarcinoma (PDAC) is a digestive system malignancy characterized by challenging early detection, limited treatment alternatives, and generally poor prognosis. Although there have been significant advancements in immunotherapy for hematological malignancies and various solid tumors in recent decades, with impressive outcomes in recent preclinical and clinical trials, the effectiveness of these therapies in treating PDAC continues to be modest. The unique immunological microenvironment of PDAC, especially the abnormal distribution, complex composition, and variable activation states of tumor-infiltrating immune cells, greatly restricts the effectiveness of immunotherapy. Undoubtedly, integrating data from both preclinical models and human studies helps accelerate the identification of reliable molecules and pathways responsive to targeted biological therapies and immunotherapies, thereby continuously optimizing therapeutic combinations. In this review, we delve deeply into how PDAC cells regulate the immune microenvironment through complex signaling networks, affecting the quantity and functional status of immune cells to promote immune escape and tumor progression. Furthermore, we explore the multi-modal immunotherapeutic strategies currently under development, emphasizing the transformation of the immunosuppressive environment into an anti-tumor milieu by targeting specific molecular and cellular pathways, providing insights for the development of novel treatment strategies.

Dynamic mode decomposition based Doppler monitoring of de novo cavitation induced by pulsed HIFU: an in vivo feasibility study

Pulsed high-intensity focused ultrasound (pHIFU) has the capability to induce de novo cavitation bubbles, offering potential applications for enhancing drug delivery and modulating tissue microenvironments. However, imaging and monitoring these cavitation bubbles during the treatment presents a challenge due to their transient nature immediately following pHIFU pulses. A planewave bubble Doppler technique demonstrated its potential, yet this Doppler technique used conventional clutter filter that was originally designed for blood flow imaging. Our recent study introduced a new approach employing dynamic mode decomposition (DMD) to address this in an ex vivo setting. This study demonstrates the feasibility of the application of DMD for in vivo Doppler monitoring of the cavitation bubbles in porcine liver and identifies the candidate monitoring metrics for pHIFU treatment. We propose a fully automated bubble mode identification method using k-means clustering and an image contrast-based algorithm, leading to the generation of DMD-filtered bubble images and corresponding Doppler power maps after each HIFU pulse. These power Doppler maps are then correlated with the extent of tissue damage determined by histological analysis. The results indicate that DMD-enhanced power Doppler map can effectively visualize the bubble distribution with high contrast, and the Doppler power level correlates with the severity of tissue damage by cavitation. Further, the temporal characteristics of the bubble modes, specifically the decay rates derived from DMD, provide information of the bubble dissolution rate, which are correlated with tissue damage level-slower rates imply more severe tissue damage.

Dynamic Mode Decomposition for Transient Cavitation Bubbles Imaging in Pulsed High-Intensity Focused Ultrasound Therapy

Pulsed high-intensity focused ultrasound (pHIFU) can induce sparse de novo inertial cavitation without the introduction of exogenous contrast agents, promoting mild mechanical disruption in targeted tissue. Because the bubbles are small and rapidly dissolve after each HIFU pulse, mapping transient bubbles and obtaining real-time quantitative metrics correlated with tissue damage are challenging. Prior work introduced Bubble Doppler, an ultrafast power Doppler imaging method as a sensitive means to map cavitation bubbles. The main limitation of that method was its reliance on conventional wall filters used in Doppler imaging and its optimization for imaging blood flow rather than transient scatterers. This study explores Bubble Doppler enhancement using dynamic mode decomposition (DMD) of a matrix created from a Doppler ensemble for mapping and extracting the characteristics of transient cavitation bubbles. DMD was first tested in silico with a numerical dataset mimicking the spatiotemporal characteristics of backscattered signal from tissue and bubbles. The performance of DMD filter was compared to other widely used Doppler wall filter-singular value decomposition (SVD) and infinite impulse response (IIR) high-pass filter. DMD was then applied to an ex vivo tissue dataset where each HIFU pulse was immediately followed by a plane wave Doppler ensemble. In silico DMD outperformed SVD and IIR high-pass filter and ex vivo provided physically interpretable images of the modes associated with bubbles and their corresponding temporal decay rates. These DMD modes can be trackable over the duration of pHIFU treatment using k-means clustering method, resulting in quantitative indicators of treatment progression.

Metal-Organic Framework-Mediated Synergistic Hypoxia-Activated Chemo-Immunotherapy Induced by High Intensity Focused Ultrasound for Enhanced Cancer Theranostics

High intensity focused ultrasound (HIFU) has attracted considerable attention as a noninvasive, efficient, and economic therapeutic modality for solid tumors. However, HIFU surgery has its intrinsic limitation in completely ablating tumors, leading to residual tumor tissue. Furthermore, the severely hypoxic environment ensuring after surgery can exacerbate the unrestricted proliferation and metabolism of residual tumor cells, leading to tumor recurrence and metastasis. To address these limitations, a versatile HIFU-specific metal-organic framework nanosystem (called ADMOFs) is developed by coordinating hypoxia-activated prodrug AQ4N, Mn2+, and DOX based on the postoperative response to changes in the tumor microenvironment. ADMOFs loaded with AQ4N/Mn2+ exhibited remarkable tumor-targeting behavior in vivo and enhanced photoacoustic/magnetic resonance imaging effects, enabling more accurate guidance for HIFU surgery. After surgery, the ADMOFs exploited the severely hypoxic tumor environment induced by HIFU, overcoming hypoxia-associated drug resistance, and inducing immunogenic cell death. Finally, it effectively inhibited tumor growth and eliminated lung metastasis. Transcriptome studies revealed that this strategy significantly up-regulated genes involved in apoptosis, cell cycle, and HIF-1 signaling pathway while downregulating genes related to tumor proliferation and metastasis. These findings suggest that combining hypoxia-activated chemo-immunotherapy with HIFU is a promising strategy for enhancing cancer theranostics.

Dynamic Mode Decomposition for Transient Cavitation Bubbles Imaging in Pulsed High Intensity Focused Ultrasound Therapy

Pulsed high-intensity focused ultrasound (pHIFU) can induce sparse de novo inertial cavitation without the introduction of exogenous contrast agents, promoting mild mechanical disruption in targeted tissue. Because the bubbles are small and rapidly dissolve after each HIFU pulse, mapping transient bubbles and obtaining real-time quantitative metrics correlated to tissue damage are challenging. Prior work introduced Bubble Doppler, an ultrafast power Doppler imaging method as a sensitive means to map cavitation bubbles. The main limitation of that method was its reliance on conventional wall filters used in Doppler imaging and optimized for imaging blood flow rather than transient scatterers. This study explores Bubble Doppler enhancement using dynamic mode decomposition (DMD) of a matrix created from a Doppler ensemble for mapping and extracting the characteristics of transient cavitation bubbles. DMD was first tested in silico with a numerical dataset mimicking the spatiotemporal characteristics of backscattered signal from tissue and bubbles. The performance of DMD filter was compared to other widely used Doppler wall filters - singular value decomposition (SVD) and infinite impulse response (IIR) highpass filter. DMD was then applied to an ex vivo tissue dataset where each HIFU pulse was immediately followed by a plane wave Doppler ensemble. In silico DMD outperformed SVD and IIR high pass filter and ex vivo provided physically interpretable images of the modes associated with bubbles and their corresponding temporal decay rates. These DMD modes can be trackable over the duration of pHIFU treatment using k-means clustering method, resulting in quantitative indicators of treatment progression.

High-Intensity Focused Ultrasound Surgery for Tumor Ablation: A Review of Current Applications

The management of cancer with alternative approaches is a matter of clinical interest worldwide. High-intensity focused ultrasound (HIFU) surgery is a noninvasive technique performed under US or MRI guidance. The most studied therapeutic uses of HIFU involve thermal tissue ablation, demonstrating both palliative and curative potential. However, concurrent mechanical bioeffects also provide opportunities in terms of augmented drug delivery and immunosensitization. The safety and efficacy of HIFU integration with current cancer treatment strategies are being actively investigated in managing primary and secondary tumors, including cancers of the breast, prostate, pancreas, liver, kidney, and bone. Current primary HIFU indications are pain palliation, complete ablation of localized earlystage tumors, or debulking of unresectable late-stage cancers. This review presents the latest HIFU applications, from investigational to clinically approved, in the field of tumor ablation. Keywords: Ultrasound, Ultrasound-High Intensity Focused (HIFU), Interventional-MSK, Interventional-Body, Oncology, Technology Assessment, Tumor Response, MR Imaging © RSNA, 2023.