Subsequent Ultrasound Vascular Targeting Therapy of Hepatocellular Carcinoma Improves the Treatment Efficacy

Nanomedicine as a multimodal therapeutic paradigm against cancer: on the way forward in advancing precision therapy

Recent years have witnessed dramatic improvements in nanotechnology-based cancer therapeutics, and it continues to evolve from the use of conventional therapies (chemotherapy, surgery, and radiotherapy) to increasingly multi-complex approaches incorporating thermal energy-based tumor ablation (e.g. magnetic hyperthermia and photothermal therapy), dynamic therapy (e.g. photodynamic therapy), gene therapy, sonodynamic therapy (e.g. ultrasound), immunotherapy, and more recently real-time treatment efficacy monitoring (e.g. theranostic MRI-sensitive nanoparticles). Unlike monotherapy, these multimodal therapies (bimodal, i.e., a combination of two therapies, and trimodal, i.e., a combination of more than two therapies) incorporating nanoplatforms have tremendous potential to improve the tumor tissue penetration and retention of therapeutic agents through selective active/passive targeting effects. These combinatorial therapies can correspondingly alleviate drug response against hypoxic/acidic and immunosuppressive tumor microenvironments and promote/induce tumor cell death through various multi-mechanisms such as apoptosis, autophagy, and reactive oxygen-based cytotoxicity, e.g., ferroptosis, etc. These multi-faced approaches such as targeting the tumor vasculature, neoangiogenic vessels, drug-resistant cancer stem cells (CSCs), preventing intra/extravasation to reduce metastatic growth, and modulation of antitumor immune responses work complementary to each other, enhancing treatment efficacy. In this review, we discuss recent advances in different nanotechnology-mediated synergistic/additive combination therapies, emphasizing their underlying mechanisms for improving cancer prognosis and survival outcomes. Additionally, significant challenges such as CSCs, hypoxia, immunosuppression, and distant/local metastasis associated with therapy resistance and tumor recurrences are reviewed. Furthermore, to improve the clinical precision of these multimodal nanoplatforms in cancer treatment, their successful bench-to-clinic translation with controlled and localized drug-release kinetics, maximizing the therapeutic window while addressing safety and regulatory concerns are discussed. As we advance further, exploiting these strategies in clinically more relevant models such as patient-derived xenografts and 3D organoids will pave the way for the application of precision therapy.

Mechanobiological Strategies to Augment Cancer Treatment

Cancer cells exhibit aberrant extracellular matrix mechanosensing due to the altered expression of mechanosensory cytoskeletal proteins. Such aberrant mechanosensing of the tumor microenvironment (TME) by cancer cells is associated with disease development and progression. In addition, recent studies show that such mechanosensing changes the mechanobiological properties of cells, and in turn cells become susceptible to mechanical perturbations. Due to an increasing understanding of cell biomechanics and cellular machinery, several approaches have emerged to target the mechanobiological properties of cancer cells and cancer-associated cells to inhibit cancer growth and progression. In this Perspective, we summarize the progress in developing mechano-based approaches to target cancer by interfering with the cellular mechanosensing machinery and overall TME.

Hydralazine-augmented contrast ultrasound imaging improves the detection of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) detection with B-mode and contrast-enhanced ultrasound (CUS) imaging often varies between subjects, especially in patients with background cirrhosis. Various factors contribute to this variability, including the tumor blood flow, tumor size, internal echoes, and its location in livers with diffuse fibro-cirrhotic changes.

OBJECTIVE

Towards improving lesion detection, this study evaluates a vasodilator, hydralazine, to enhance the visibility of HCC by reducing its blood flow relative to the surrounding liver tissue.

METHODS

HCC were analyzed for tumor visibility measured for B-mode, CUS, and hydralazine-augmented-contrast ultrasound (HyCUS) in an autochthonous HCC rat model. 21 tumors from 12 rats were studied. B-mode and CUS images were acquired before hydralazine injection. Rats received an intravenous hydralazine injection of 5 mg/kg, then images were acquired 20 min later. Four rats were used as controls. The difference in echo intensity of the lesion and the surrounding tissue was used to determine the visibility index (VI).

RESULTS

The visibility index for HCC was found to be significantly improved with the use of HyCUS imaging compared to traditional B-mode and CUS imaging. The visibility index for HCC was 16.5 ± 2.8 for HyCUS, compared to 5.3 ± 4.8 for B-mode and 4.1 ± 3.8 for CUS. The differences between HyCUS and the other imaging modalities were statistically significant, with p-values of 0.001 and 0.02, respectively. Additionally, when compared to control cases, HyCUS showed higher discrimination of HCC (VI = 6.4 ± 1.2) with a p-value of 0.003, while B-mode (VI = 6.7 ± 1.4, p = 0.5) and CUS (VI = 6.4 ± 1.2, p = 0.3) showed lower discrimination.

CONCLUSION

Vascular blood flow modulation by hydralazine enhances the visibility of HCC. HyCUS offers a potential problem-solving method for detecting HCC when B-mode and CUS are unsuccessful, especially with background fibro-cirrhotic liver disease. Future evaluation of the approach in humans will determine its translatability for clinical applications.

Ultrasound Radiomics for the Detection of Early-Stage Liver Fibrosis

Objective: The study evaluates quantitative ultrasound (QUS) texture features with machine learning (ML) to enhance the sensitivity of B-mode ultrasound (US) for the detection of fibrosis at an early stage and distinguish it from advanced fibrosis. Different ML methods were evaluated to determine the best diagnostic model. Methods: 233 B-mode images of liver lobes with early and advanced-stage fibrosis induced in a rat model were analyzed. Sixteen features describing liver texture were measured from regions of interest (ROIs) drawn on B-mode images. The texture features included a first-order statistics run length (RL) and gray-level co-occurrence matrix (GLCM). The features discriminating between early and advanced fibrosis were used to build diagnostic models with logistic regression (LR), naïve Bayes (nB), and multi-class perceptron (MLP). The diagnostic performances of the models were compared by ROC analysis using different train-test sampling approaches, including leave-one-out, 10-fold cross-validation, and varying percentage splits. METAVIR scoring was used for histological fibrosis staging of the liver. Results: 15 features showed a significant difference between the advanced and early liver fibrosis groups, p < 0.05. Among the individual features, first-order statics features led to the best classification with a sensitivity of 82.1−90.5% and a specificity of 87.1−89.8%. For the features combined, the diagnostic performances of nB and MLP were high, with the area under the ROC curve (AUC) approaching 0.95−0.96. LR also yielded high diagnostic performance (AUC = 0.91−0.92) but was lower than nB and MLP. The diagnostic variability between test-train trials, measured by the coefficient-of-variation (CV), was higher for LR (3−5%) than nB and MLP (1−2%). Conclusion: Quantitative ultrasound with machine learning differentiated early and advanced fibrosis. Ultrasound B-mode images contain a high level of information to enable accurate diagnosis with relatively straightforward machine learning methods like naïve Bayes and logistic regression. Implementing simple ML approaches with QUS features in clinical settings could reduce the user-dependent limitation of ultrasound in detecting early-stage liver fibrosis.

Contrast-enhanced ultrasound for assessing blood flow modulation of hepatocellular carcinoma by hydralazine

Modulating aberrant tumor microvasculature provides unique opportunities for enhancing ultrasound imaging of hepatocellular carcinoma (HCC). This study aims to use contrast-enhanced ultrasound to evaluate the potential of a potent vasodilator, hydralazine, to attenuate blood flow in HCC while enhancing it in the surrounding liver tissue. The "steel effect," where blood flow is diverted from the lesion to the surrounding tissue aims to enhance lesion-tissue contrast. Methods: HCC was induced in six rats by oral ingestion of diethylnitrosamine for 12 weeks. 10 tumors were studied to assess the enhancement in HCC tumors and surrounding tissue. Contrast-enhanced ultrasound images (CEUS) of each tumor were acquired before and after hydralazine injection. The enhancement of images was analyzed for the qualitative and quantitative assessment of HCC enhancement. Peak enhancement (PE) was calculated, representing the maximum signal intensity reached during the transit of the contrast bolus for both the tumor and the surrounding tissue. Intravenous administration of hydralazine significantly reduced CEUS signals in HCC tumors. The visual examination of images showed that the enhancement of tumors dramatically decreased after hydralazine injection. On the other hand, the surrounding tissue showed an increased enhancement. PE for the HCC changed from (71.8 ± 5) pre hydralazine to (28.7± 4.9), a 61.7% reduction after hydralazine injection, p=0.01. Future studies validating the technique in clinical settings for enhancing lesion-tissue contrast may allow physicians greater precision and accuracy in HCC surveillance for early detection of small tumors.

Machine learning improves early detection of liver fibrosis by quantitative ultrasound radiomics

Progression of liver fibrosis to cirrhosis, a severe non-reversible process, is one of the most critical risk factors in developing hepatocellular carcinoma and liver failure. Detection of liver fibrosis at an early stage is therefore essential for better patient management. Ultrasound (US) imaging can provide a noninvasive alternative to biopsies. This study evaluates quantitative US texture features to improve early-stage versus advanced liver fibrosis detection. 157 B-mode US images of different liver lobes acquired from early and advanced fibrosis rat cases were used for analysis. 5-6 regions of interest were placed on each image. Twelve quantitative features that describe liver texture changes were extracted from the images, including first-order histogram, run length (RL), and gray level co-occurrence matrix (GLCM). The diagnostic performance of individual features was high with AUC ranging from 0.80 to 0.94. Logistic regression with leave-one-out cross-validation was used to evaluate the performance of the combined features. All features combined showed a slight improvement in performance with AUC = 0.95, sensitivity = 96.8%, and specificity = 93.7%. Quantitative US texture features characterize liver fibrosis changes with high accuracy and can differentiate early from advanced disease. Quantitative ultrasound, if validated in future clinical studies, can have a potential role in identifying fibrosis changes that are not easily detected by visual US image assessments.

Ultrasound and Nanomedicine for Cancer-Targeted Drug Delivery: Screening, Cellular Mechanisms and Therapeutic Opportunities

Cancer is a disease characterized by abnormal cell growth. According to a report published by the World Health Organization (WHO), cancer is the second leading cause of death globally, responsible for an estimated 9.6 million deaths in 2018. It should be noted that ultrasound is already widely used as a diagnostic procedure for detecting tumorigenesis. In addition, ultrasound energy can also be utilized effectively for treating cancer. By filling the interior of lipospheres with gas molecules, these particles can serve both as contrast agents for ultrasonic imaging and as delivery systems for drugs such as microbubbles and nanobubbles. Therefore, this review aims to describe the nanoparticle-assisted drug delivery system and how it can enhance image analysis and biomedicine. The formation characteristics of nanoparticles indicate that they will accumulate at the tumor site upon ultrasonic imaging, in accordance with their modification characteristics. As a result of changing the accumulation of materials, it is possible to examine the results by comparing images of other tumor cell lines. It is also possible to investigate ultrasound images for evidence of cellular effects. In combination with a precision ultrasound imaging system, drug-carrying lipospheres can precisely track tumor tissue and deliver drugs to tumor cells to enhance the ability of this nanocomposite to treat cancer.

Hydralazine augmented ultrasound hyperthermia for the treatment of hepatocellular carcinoma

This study investigates the use of hydralazine to enhance ultrasound hyperthermia for the treatment of hepatocellular carcinoma (HCC) by minimizing flow-mediated heat loss from the tumor. Murine HCC tumors were treated with a continuous mode ultrasound with or without an intravenous administration of hydralazine (5 mg/kg). Tumor blood flow and blood vessels were evaluated by contrast-enhanced ultrasound (CEUS) imaging and histology, respectively. Hydralazine markedly enhanced ultrasound hyperthermia through the disruption of tumor blood flow in HCC. Ultrasound treatment with hydralazine significantly reduced peak enhancement (PE), perfusion index (PI), and area under the curve (AUC) of the CEUS time-intensity curves by 91.9 ± 0.9%, 95.7 ± 0.7%, and 96.6 ± 0.5%, compared to 71.4 ± 1.9%, 84.7 ± 1.1%, and 85.6 ± 0.7% respectively without hydralazine. Tumor temperature measurements showed that the cumulative thermal dose delivered by ultrasound treatment with hydralazine (170.8 ± 11.8 min) was significantly higher than that without hydralazine (137.7 ± 10.7 min). Histological assessment of the ultrasound-treated tumors showed that hydralazine injection formed larger hemorrhagic pools and increased tumor vessel dilation consistent with CEUS observations illustrating the augmentation of hyperthermic effects by hydralazine. In conclusion, we demonstrated that ultrasound hyperthermia can be enhanced significantly by hydralazine in murine HCC tumors by modulating tumor blood flow. Future studies demonstrating the safety of the combined use of ultrasound and hydralazine would enable the clinical translation of the proposed technique.