Investigating Low-Velocity Fluid Flow in Tumors with Convection-MRI

Extended Pharmacokinetics Improve Site-Specific Prodrug Activation Using Radiation

Radiotherapy is commonly used to treat cancer, and localized energy deposited by radiotherapy has the potential to chemically uncage prodrugs; however, it has been challenging to demonstrate prodrug activation that is both sustained in vivo and truly localized to tumors without affecting off-target tissues. To address this, we developed a series of novel phenyl-azide-caged, radiation-activated chemotherapy drug-conjugates alongside a computational framework for understanding corresponding pharmacokinetic and pharmacodynamic (PK/PD) behaviors. We especially focused on an albumin-bound prodrug of monomethyl auristatin E (MMAE) and found it blocked tumor growth in mice, delivered a 130-fold greater amount of activated drug to irradiated tumor versus unirradiated tissue, was 7.5-fold more efficient than a non albumin-bound prodrug, and showed no appreciable toxicity compared to free or cathepsin-activatable drugs. These data guided computational modeling of drug action, which indicated that extended pharmacokinetics can improve localized and cumulative drug activation, especially for payloads with low vascular permeability and diffusivity and particularly in patients receiving daily treatments of conventional radiotherapy for weeks. This work thus offers a quantitative PK/PD framework and proof-of-principle experimental demonstration of how extending prodrug circulation can improve its localized activity in vivo.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Biomechanical Aspects in Bone Tumor Engineering

In the past decades, anticancer drug development brought the field of tumor engineering to a new level by the need of robust test systems. Simulating tumor microenvironment in vitro remains a challenge, and osteosarcoma-the most common primary bone cancer-is no exception. The growing evidence points to the inevitable connection between biomechanical stimuli and tumor chemosensitivity and aggressiveness, thus making this component of the microenvironment a mandatory requirement to the developed models. In this review, we addressed the question: is the "in vivo - in vitro" gap in osteosarcoma engineering bridged from the perspective of biomechanical stimuli? The most notable biomechanical cues in the tumor cell microenvironment are observed and compared in the contexts of in vivo conditions and engineered three-dimensional in vitro models. Impact statement The importance of biomechanical stimuli in three-dimensional in vitro models for drug testing is becoming more pronounced nowadays. This review might assist in understanding the key players of the biophysical environment of primary bone cancer and the current state of bone tumor engineering from this perspective.

Engineering Mesoscopic 3D Tumor Models with a Self-Organizing Vascularized Matrix

Advanced in vitro systems such as multicellular spheroids and lab-on-a-chip devices have been developed, but often fall short in reproducing the tissue scale and self-organization of human diseases. A bioprinted artificial tumor model is introduced with endothelial and stromal cells self-organizing into perfusable and functional vascular structures. This model uses 3D hydrogel matrices to embed multicellular tumor spheroids, allowing them to grow to mesoscopic scales and to interact with endothelial cells. It is shown that angiogenic multicellular tumor spheroids promote the growth of a vascular network, which in turn further enhances the growth of cocultivated tumor spheroids. The self-developed vascular structure infiltrates the tumor spheroids, forms functional connections with the bioprinted endothelium, and can be perfused by erythrocytes and polystyrene microspheres. Moreover, cancer cells migrate spontaneously from the tumor spheroid through the self-assembled vascular network into the fluid flow. Additionally, tumor type specific characteristics of desmoplasia, angiogenesis, and metastatic propensity are preserved between patient-derived samples and tumors derived from this same material growing in the bioreactors. Overall, this modular approach opens up new avenues for studying tumor pathophysiology and cellular interactions in vitro, providing a platform for advanced drug testing while reducing the need for in vivo experimentation.

Ultrasound-mediated multifunctional magnetic microbubbles for drug delivery of celastrol in VX2 liver transplant tumors

Celastrol (CST) has positive pharmacological effects on various cancers, but clinical application is limited because of poor water solubility and systemic toxicity. Ferric oxide (Fe3O4) has a large specific surface area and can be functionalized by inorganic modification to form complex magnetic drug delivery systems. Herein, Fe3O4 was surface-modified with citric acid and polyethylene glycol (PEG) (via) the Mitsunobu reaction and then covalently bound to CST. Finally, magnetic microbubbles (MMBs) containing perfluoropropane (C3F8) and Fe3O4-PEG2K-CST particles were constructed with poly(lactic-co-glycolic acid) (PLGA) as the shell membrane. In vitro studies showed that ultrasound-mediated MMBs exhibited improved inhibition of VX2 cell proliferation compared to inhibition achieved using MMBs without ultrasound mediation, blank MMBs, or free CST. In ultrasound mode, MMBs have favorable imaging properties. After the application of a high mechanical index, MMBs collapse through the cavitation effect, releasing their internal Fe3O4-PEG2K-CST. The CST is then delivered to the tumor microenvironment under acidic conditions. In magnetic resonance imaging T2 mode, a specific hypointense signal was observed in the tumor area compared with that before treatment, whereas no significant change occurred in the signal intensity of the surrounding organs. After treatment, pathological examination of tumor-bearing rabbit tissues showed that iron elements accumulated in several apoptosis cells in the tumor area, with no apparent abnormalities found in other areas. Thus, ultrasound-mediated MMBs could significantly improve the drug uptake of solid tumors and inhibit tumor growth with favorable biological safety.

MRI-Based Interstitial Fluid Velocity Analysis for Drug Delivery Efficiency Evaluation in Tumor

There are many flow behaviors in solid tumors, including intravascular, bloodstream, and interstitial convection. Studies have shown that tumor interstitial fluid (TIF) is an important part of tumor microenvironment regulation and affects drug delivery and metabolism between tumor cells. Magnetic resonance imaging (MRI) is suitable for detecting the flow rates of liquids in tissues. Clinical phase contrast PC-MRI technology has been designed to observe the blood flow in large vessels such as arteries and veins; however, it is not sensitive enough to deal with slow flow velocity. Our previously developed vertical plane echo PC-MRI technology, the Velocity Mapping sequence, improved the signal-to-noise ratio (SNR) for measuring slow interstitial fluid rate. In this study, this sequence was used to determine the TIF flow rate in MDA-MB-231 human breast tumor cells used in BALB/c nude male mice. Two different sizes of contrast agents were intravenously injected, and the relationship between their distribution and the TIF flow rate was studied for the first time. Combining the results of clinical scanning showed that small-molecule DTPA-Gd (diethylenetriaminepentaacetic acid-gadolinium) was distributed immediately around the tumor margin after the injection. This distribution was positively correlated to the high flow rate area of the TIF before administration. In contrast, nanoparticles NaGdF4-PEG (polyethylene glycol) entered the tumor and reached their peak at 3 h. Drug distribution was negatively correlated with the high-flow-rate region of the TIF. Investigation of the TIF velocity can help better understand the fluid behavior in tumors and its role in drug delivery.

Key Biophysical and Physiological Properties Impacting the Oxygenation Status of Breast Cancers During Thermo-radiotherapy

Mild hyperthermia at 39-43 °C for 30-60 min is applied locoregionally to improve the oxygenation status of recurrent breast cancers, thus enhancing the efficacy of radio-, chemo-, and immunotherapy. In this context, estimated (or even conflicting) data are often used in computational modelling of tumour oxygenation and simulation of O2 transport. In this chapter, we present information that may help to improve adjuvant thermotherapy delivered immediately prior to radiotherapy of recurrent breast cancers. Data are preferentially derived from clinical investigations; in some cases, measurements in experimental breast cancers are included.The biophysical properties presented for healthy, mostly postmenopausal, human breast (composite glandular-adipose-fibrous tissue) measured under normothermic (NT) conditions and in therapeutically heated breast cancers include tissue water content and tissue density. In general, averaged values of parameters reported for NT conditions are higher in breast cancers than in normal breast tissue, i.e., all ratios breast cancer/normal breast are >1. Mean values observed in breast cancers during mild hyperthermia (mHT) are consistently higher than those in NT tumours. Parameters determining convective transports in healthy breast tissue and breast cancer include blood flow rates, blood volume, exchanging water space, arterio-venous shunt flow, interstitial fluid flow rate, interstitial fluid pressure, microvascular permeability, interstitial hydraulic conductivity, and interstitial flow velocity. In general, averaged values of parameters measured under NT conditions are higher in breast cancers than in healthy breast. Except for interstitial fluid pressure, these values increase upon mHT treatment of cancers. Prime factors determining and describing the oxygenation status of the healthy breast, and in NT- versus mHT-treated breast cancers, include: oxygen (O2) delivery rates, O2- extractions, O2- consumption rates, subepidermal microvascular HbO2, tissue oxygen solubility, oxygen diffusion coefficients, mean O2 partial pressures pO2, hypoxic fractions HF <5 mmHg, oxygen enhancement ratio, and mitochondrial ROS production. With the exception of the mean pO2, O2 extraction rate and tissue O2 saturation all parameters listed are distinctly higher in breast cancers under NT conditions compared to normal breast. Mild hyperthermia results in therapeutically relevant improvements of the oxygenation status of cancers and enhances mitochondrial ROS production, thus improving radiosensitivity. Note: The oxygenation status of the healthy (postmenopausal) breast is very similar to that of the normal human subcutis.

Model discovery approach enables non-invasive measurement of intra-tumoral fluid transport in dynamic MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to non-invasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that it will contribute to the better understanding of cancer progression and therapeutic response.

Interstitial fluid pressure as an emerging biomarker in solid tumors

The physical microenvironment of cancer is characterized by elevated stiffness and tissue pressure, the main component of which is the interstitial fluid pressure (IFP). Elevated IFP is an established negative predictive and prognostic parameter, directly affecting malignant behavior and therapy response. As such, measurement of the IFP would allow to develop strategies aimed at engineering the physical microenvironment of cancer. Traditionally, IFP measurement required the use of invasive methods. Recent progress in dynamic and functional imaging methods such as dynamic contrast enhanced (DCE) magnetic resonance imaging and elastography, combined with numerical models and simulation, allows to comprehensively assess the biomechanical landscape of cancer, and may help to overcome physical barriers to drug delivery and immune cell infiltration. Here, we provide a comprehensive overview of the origin of elevated IFP, and its role in the malignant phenotype. Also, we review the methods used to measure IFP using invasive and imaging based methods, and highlight remaining obstacles and potential areas of progress in order to implement IFP measurement in clinical practice.

Ultrasonic Microbubble Cavitation Enhanced Tissue Permeability and Drug Diffusion in Solid Tumor Therapy

Chemotherapy has an essential role not only in advanced solid tumor therapy intervention but also in society's health at large. Chemoresistance, however, seriously restricts the efficiency and sensitivity of chemotherapeutic agents, representing a significant threat to patients' quality of life and life expectancy. How to reverse chemoresistance, improve efficacy sensitization response, and reduce adverse side effects need to be tackled urgently. Recently, studies on the effect of ultrasonic microbubble cavitation on enhanced tissue permeability and retention (EPR) have attracted the attention of researchers. Compared with the traditional targeted drug delivery regimen, the microbubble cavitation effect, which can be used to enhance the EPR effect, has the advantages of less trauma, low cost, and good sensitization effect, and has significant application prospects. This article reviews the research progress of ultrasound-mediated microbubble cavitation in the treatment of solid tumors and discusses its mechanism of action to provide new ideas for better treatment strategies.

Assessing pulsatile waveforms of paravascular cerebrospinal fluid dynamics using dynamic diffusion-weighted imaging (dDWI)

Cerebrospinal fluid (CSF) in the paravascular spaces of the surface arteries (sPVS) is a vital pathway in brain waste clearance. Arterial pulsations may be the driving force of the paravascular flow, but its pulsatile pattern remains poorly characterized, and no clinically practical method for measuring its dynamics in the human brain is available. In this work, we introduce an imaging and quantification framework for in-vivo non-invasive assessment of pulsatile fluid dynamics in the sPVS. It used dynamic Diffusion-Weighted Imaging (dDWI) at a lower b-values of 150s/mm² and retrospective gating to detect the slow flow of CSF while suppressing the fast flow of adjacent arterial blood. The waveform of CSF flow over a cardiac cycle was revealed by synchronizing the measurements with the heartbeat. A data-driven approach was developed to identify sPVS and allow automatic quantification of the whole-brain fluid waveforms. We applied dDWI to twenty-five participants aged 18–82 y/o. Results demonstrated that the fluid waveforms across the brain showed an explicit cardiac-cycle dependency, in good agreement with the vascular pumping hypothesis. Furthermore, the shape of the CSF waveforms closely resembled the pressure waveforms of the artery wall, suggesting that CSF dynamics is tightly related to artery wall mechanics. Finally, the CSF waveforms in aging participants revealed a strong age effect, with a significantly wider systolic peak observed in the older relative to younger participants. The peak widening may be associated with compromised vascular compliance and vessel wall stiffening in the older brain. Overall, the results demonstrate the feasibility, reproducibility, and sensitivity of dDWI for detecting sPVS fluid dynamics of the human brain. Our preliminary data suggest age-related alterations of the paravascular pumping. With an acquisition time of under six minutes, dDWI can be readily applied to study fluid dynamics in normal physiological conditions and cerebrovascular/neurodegenerative diseases.

Deep GRU-CNN Model for COVID-19 Detection From Chest X-Rays Data

In the current era, data is growing exponentially due to advancements in smart devices. Data scientists apply a variety of learning-based techniques to identify underlying patterns in the medical data to address various health-related issues. In this context, automated disease detection has now become a central concern in medical science. Such approaches can reduce the mortality rate through accurate and timely diagnosis. COVID-19 is a modern virus that has spread all over the world and is affecting millions of people. Many countries are facing a shortage of testing kits, vaccines, and other resources due to significant and rapid growth in cases. In order to accelerate the testing process, scientists around the world have sought to create novel methods for the detection of the virus. In this paper, we propose a hybrid deep learning model based on a convolutional neural network (CNN) and gated recurrent unit (GRU) to detect the viral disease from chest X-rays (CXRs). In the proposed model, a CNN is used to extract features, and a GRU is used as a classifier. The model has been trained on 424 CXR images with 3 classes (COVID-19, Pneumonia, and Normal). The proposed model achieves encouraging results of 0.96, 0.96, and 0.95 in terms of precision, recall, and f1-score, respectively. These findings indicate how deep learning can significantly contribute to the early detection of COVID-19 in patients through the analysis of X-ray scans. Such indications can pave the way to mitigate the impact of the disease. We believe that this model can be an effective tool for medical practitioners for early diagnosis.

3D tumor angiogenesis models: recent advances and challenges

The development of blood vessels, referred to as angiogenesis, is an intricate process regulated spatially and temporally through a delicate balance between the qualitative and quantitative expression of pro and anti-angiogenic molecules. As angiogenesis is a prerequisite for solid tumors to grow and metastasize, a variety of tumor angiogenesis models have been formulated to better understand the underlying mechanisms and associated clinical applications. Studies have demonstrated independent mechanisms inducing angiogenesis in tumors such as (a) HIF-1/VEGF mediated paracrine interactions between a cancer cell and endothelial cells, (b) recruitment of progenitor endothelial cells, and (c) vasculogenic mimicry. Moreover, single-cell sequencing technologies have indicated endothelial cell heterogeneity among organ systems including tumor tissues. However, existing angiogenesis models often rely upon normal endothelial cells which significantly differ from tumor endothelial cells exhibiting distinct (epi)genetic and metabolic signatures. Besides, the existence of intra-individual variations necessitates the development of improved tumor vascular model systems for personalized medicine. In the present review, we summarize recent advancements of 3D tumor vascular model systems which include (a) tissue engineering-based tumor models; (b) vascular organoid models, and (c) organ-on-chips and their importance in replicating the tumor angiogenesis along with the associated challenges to design improved models.

A strategy to prevent a temperature-induced MRI artifact in warm liquid phantoms due to convection currents

MRI phantom studies often fail to mimic the temperature of the human body, which can negatively impact accuracy. An artifact induced by increasing temperature in liquid phantoms was observed, presenting a significant challenge to temperature-controlled experiments. In this study we characterize and provide a solution to eliminate this temperature-induced MRI artifact. Low concentration (0.5-2.5 mM) agar phantoms were prepared. Utilizing a temperature-controlled phantom holder, T₁ - and T₂ -weighted structural images were acquired at 7 T along with quantitative B₀ , B₁ , T₁ , T₂ and ADC maps at both 25 and 37°C. Additionally, computer simulations were conducted to demonstrate the fluid flow and thermal flux patterns in water to provide an insight into the origins of the artifact. Evidence from computer simulation and quantitative MRI strongly suggest the artifact was caused by heat transfer in the form of natural convection leading to structured patterns of signal loss in MR images. The artifact was present up to agar concentrations of 1.5 mM (T₁ = 3068 ± 16 ms, T₂ = 1052 ± 20 ms, ADC = 2.29 ± 0.36 × 10^-3 mm² /s at 25°C; T₁ = 3928 ± 44 ms, T₂ = 1122 ± 24 ms, ADC = 2.64 ± 0.49 × 10^-3 mm² /s at 37°C), above which point increased sample viscosity no longer allows for convection currents, thereby eliminating the artifact. The methodology described in this work simplifies quantitative MR acquisition of liquid phantoms at physiological temperature by suppressing convection currents with relatively small changes to intrinsic MR parameters (T₁ increased by 1.4% and T₂ decreased by 17% for 1.5 mM agar at 25°C).

Limits to flow detection in phase contrast MRI

Pulsed gradient spin echo (PGSE) complex signal behavior becomes dominated by attenuation rather than oscillation when displacements due to flow are similar or less than diffusive displacements. In this "slow-flow" regime, the optimal displacement encoding parameter q for phase contrast velocimetry depends on the diffusive length scale q s l o w = 1 / l D = 1 / 2 D Δ rather than the velocity encoding parameter v _enc = π/(qΔ). The minimum detectable mean velocity using the difference between the phase at +q _slow and -q _slow is 〈 v m i n 〉 = 1 / SNR D / Δ . These theories are then validated and applied to MRI by performing PGSE echo planar imaging experiments on water flowing through a column with a bulk region and a beadpack region at controlled flow rates. Velocities as slow as 6 μm/s are detected with velocimetry. Theories, MRI experimental protocols, and validation on a controlled phantom help to bridge the gap between porous media NMR and pre-clinical phase contrast and diffusion MRI.

Investigating the Contribution of Collagen to the Tumor Biomechanical Phenotype with Noninvasive Magnetic Resonance Elastography

Increased stiffness in the extracellular matrix (ECM) contributes to tumor progression and metastasis. Therefore, stromal modulating therapies and accompanying biomarkers are being developed to target ECM stiffness. Magnetic resonance (MR) elastography can noninvasively and quantitatively map the viscoelastic properties of tumors in vivo and thus has clear clinical applications. Herein, we used MR elastography, coupled with computational histopathology, to interrogate the contribution of collagen to the tumor biomechanical phenotype and to evaluate its sensitivity to collagenase-induced stromal modulation. Elasticity (G d) and viscosity (G l) were significantly greater for orthotopic BT-474 (G d = 5.9 ± 0.2 kPa, G l = 4.7 ± 0.2 kPa, n = 7) and luc-MDA-MB-231-LM2-4 (G d = 7.9 ± 0.4 kPa, G l = 6.0 ± 0.2 kPa, n = 6) breast cancer xenografts, and luc-PANC1 (G d = 6.9 ± 0.3 kPa, G l = 6.2 ± 0.2 kPa, n = 7) pancreatic cancer xenografts, compared with tumors associated with the nervous system, including GTML/Trp53KI/KI medulloblastoma (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 7), orthotopic luc-D-212-MG (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 7), luc-RG2 (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 5), and luc-U-87-MG (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 8) glioblastoma xenografts, intracranially propagated luc-MDA-MB-231-LM2-4 (G d = 3.7 ± 0.2 kPa, G l = 2.2 ± 0.1 kPa, n = 7) breast cancer xenografts, and Th-MYCN neuroblastomas (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 5). Positive correlations between both elasticity (r = 0.72, P < 0.0001) and viscosity (r = 0.78, P < 0.0001) were determined with collagen fraction, but not with cellular or vascular density. Treatment with collagenase significantly reduced G d (P = 0.002) and G l (P = 0.0006) in orthotopic breast tumors. Texture analysis of extracted images of picrosirius red staining revealed significant negative correlations of entropy with G d (r = -0.69, P < 0.0001) and G l (r = -0.76, P < 0.0001), and positive correlations of fractal dimension with G d (r = 0.75, P < 0.0001) and G l (r = 0.78, P < 0.0001). MR elastography can thus provide sensitive imaging biomarkers of tumor collagen deposition and its therapeutic modulation. SIGNIFICANCE: MR elastography enables noninvasive detection of tumor stiffness and will aid in the development of ECM-targeting therapies.

Computational modelling suggests complex interactions between interstitial flow and tumour angiogenesis

Angiogenesis, the growth of capillaries from pre-existing ones, plays a key role in cancer progression. Tumours release tumour angiogenic factors (TAFs) into the extracellular matrix (ECM) that trigger angiogenesis once they reach the vasculature. The neovasculature provides nutrients and oxygen to the tumour. In the ECM, the interstitial fluid moves driven by pressure differences and may affect the distribution of tumour TAFs, and, in turn, tumour vascularization. In this work, we propose a hybrid mathematical model to investigate the influence of fluid flow in tumour angiogenesis. Our model shows the impact of interstitial flow in a time-evolving capillary network using a continuous approach. The flow model is coupled to a model of angiogenesis that includes tip endothelial cells, filopodia, capillaries and TAFs. The TAF transport equation considers not only diffusive mechanisms but also the convective transport produced by interstitial flow. Our simulations predict a significant alteration of the new vascular networks, which tend to grow more prominently against the flow. The model suggests that interstitial flow may produce increased tumour malignancies and hindered treatments.

Remarkable Boron Delivery Of iRGD-Modified Polymeric Nanoparticles For Boron Neutron Capture Therapy

Purpose

Boron neutron capture therapy (BNCT) is an emerging binary radiotherapy, which is limited for application due to the challenge of targeted delivery into tumor nowadays. Here, we propose the use of iRGD-modified polymeric nanoparticles for active targeted delivery of boron and doxorubicin (DOX) in BNCT.

Methods

¹⁰B-enriched BSH was covalently grafted to PEG-PCCL to prepare ¹⁰B-polymer, then surface-modified with iRGD. And, DOX was physically incorporated into polymers afterwards. Characterization of prepared polymers and in vitro release profile of DOX from polymers were determined by several methods. Cellular uptake of DOX was observed by confocal microscope. Accumulation of boron in cells and tissues was analyzed by ICP-MS. Biodistribution of DOX was studied by ex vivo fluorescence imaging and quantitative measurement. Tumor vascular normalization of Endostar for promoting delivery efficiency of boron on refractory B16F10 tumor was also studied.

Results

The polymers were monodisperse and spheroidal in water with an average diameter of 24.97 nm, which were relatively stable at physiological pH and showed a sustained release of DOX, especially at endolysosomal pH. Enhanced cellular delivery of DOX was found in iRGD-modified polymer group. Cellular boron uptake of iRGD-modified polymers in A549 cells was remarkably raised fivefold (209.83 ng ¹⁰B/10⁶ cells) compared with BSH. The polymers represented prolonged blood circulation, enhanced tumor accumulation of ¹⁰B against BSH, and favorable tumor:normal tissue boron concentration ratios (tumor:blood = 14.11, tumor:muscle = 19.49) in A549 tumor-bearing mice 24 hrs after injection. Both fluorescence imaging and quantitative measurement showed the highest tumor accumulation of DOX at 24 hrs after injecting of iRGD-modified polymers. Improvement of vascular integrity and reduction of vascular mimicries were found after Endostar injection, and raised tumor accumulation of boron as well.

Conclusion

The developed nanoparticle is an inspiring candidate for the safe clinical application for BNCT.

Modelling the transport of fluid through heterogeneous, whole tumours in silico

Cancers exhibit spatially heterogeneous, unique vascular architectures across individual samples, cell-lines and patients. This inherently disorganised collection of leaky blood vessels contribute significantly to suboptimal treatment efficacy. Preclinical tools are urgently required which incorporate the inherent variability and heterogeneity of tumours to optimise and engineer anti-cancer therapies. In this study, we present a novel computational framework which incorporates whole, realistic tumours extracted ex vivo to efficiently simulate vascular blood flow and interstitial fluid transport in silico for validation against in vivo biomedical imaging. Our model couples Poiseuille and Darcy descriptions of vascular and interstitial flow, respectively, and incorporates spatially heterogeneous blood vessel lumen and interstitial permeabilities to generate accurate predictions of tumour fluid dynamics. Our platform enables highly-controlled experiments to be performed which provide insight into how tumour vascular heterogeneity contributes to tumour fluid transport. We detail the application of our framework to an orthotopic murine glioma (GL261) and a human colorectal carcinoma (LS147T), and perform sensitivity analysis to gain an understanding of the key biological mechanisms which determine tumour fluid transport. Finally we mimic vascular normalization by modifying parameters, such as vascular and interstitial permeabilities, and show that incorporating realistic vasculatures is key to modelling the contrasting fluid dynamic response between tumour samples. Contrary to literature, we show that reducing tumour interstitial fluid pressure is not essential to increase interstitial perfusion and that therapies should seek to develop an interstitial fluid pressure gradient. We also hypothesise that stabilising vessel diameters and permeabilities are not key responses following vascular normalization and that therapy may alter interstitial hydraulic conductivity. Consequently, we suggest that normalizing the interstitial microenvironment may provide a more effective means to increase interstitial perfusion within tumours.

The structure of tumours varies widely, with dense and chaotically-formed networks of blood vessels that differ between each individual tumour and even between different regions of the same tumour. This atypical environment can inhibit the delivery of anti-cancer therapies. Computational tools are urgently required which facilitate a deeper understanding of the relationship between blood vessel architectures and therapeutic response. We have developed a computational framework which integrates the complex tumour vascular architecture to predict fluid transport across all lengths scales in whole tumours. We apply our model to two tumour cell-lines and show that differences in their inherent vascular structures influence flow through cancerous tissue. We also use our platform to predict the fluid dynamic response following vascular normalization therapy in realistic, static tumour networks and show that the response is dependent on tumour vascular architecture. We hypothesise that therapy may alter the permeability of interstitial tissue to fluid transport and show that lowering interstitial fluid pressure is not a necessary therapeutic outcome to increase tumour perfusion.

Measurement of Tumor Pressure and Strategies of Imaging Tumor Pressure for Radioimmunotherapy

Tumor interstitial pressure is a fundamental feature of cancer biology. Elevation in tumor pressure affects the efficacy of cancer treatment and results in the heterogenous intratumoral distribution of drugs and macromolecules. Monoclonal antibodies (mAb) play a prominent role in cancer therapy and molecular nuclear imaging. Therapy using mAb labeled with radionuclides—also known as radioimmunotherapy (RIT)—is an effective form of cancer treatment. RIT is clinically effective for the treatment of lymphoma and other blood cancers; however, its clinical use for solid tumor was limited because their high interstitial pressure prevents mAb from penetrating into the tumor. This pressure can be decreased using anti-cancer drugs or additional external therapy. In this paper, we reviewed the intratumoral pressure using direct tumor-pressure measurement strategies, such as the wick-in-needle and pressure catheter transducer method, and indirect tumor-pressure measurement strategies via magnetic resonance.

Intratumor Heterogeneity in Interstitial Fluid Pressure in Cervical and Pancreatic Carcinoma Xenografts

Preclinical studies have suggested that interstitial fluid pressure (IFP) is uniformly elevated in the central region of tumors, whereas clinical studies have revealed that IFP may vary among different measurement sites in the tumor center. IFP measurements are technically difficult, and it has been claimed that the intratumor heterogeneity in IFP reported for human tumors is due to technical problems. The main purpose of this study was to determine conclusively whether IFP may be heterogeneously elevated in the central tumor region, and if so, to reveal possible mechanisms and possible consequences. Tumors of two xenograft models were included in the study: HL-16 cervical carcinoma and Panc-1 pancreatic carcinoma. IFP was measured with Millar SPC 320 catheters in two positions in each tumor and related to tumor histology or the metastatic status of the host mouse. Some tumors of both models showed significant intratumor heterogeneity in IFP, and this heterogeneity was associated with a compartmentalized histological appearance (i.e., the tissue was divided into compartments separated by thick connective tissue bands) in HL-16 tumors and with a dense collagen-I-rich extracellular matrix in Panc-1 tumors, suggesting that these connective tissue structures prevented efficient interstitial convection. Furthermore, some tumors of both models developed lymph node metastases, and of the two IFP values measured in each tumor, only the higher value was significantly higher in metastatic than in non-metastatic tumors, suggesting that metastatic propensity was determined by the tumor region having the highest IFP.

Phase contrast MRI of creeping flows using stimulated echo

Creeping flows govern many important physiological phenomena such as elevated interstitial fluid flows in tumors, glymphatic flows in the brain, among other applications. However, few methods exist to measure such slow flows non-invasively in optically opaque biological tissues in vivo. Phase-contrast MRI is a velocimetry technique routinely used in the clinic to measure fast flows in biological tissues, such as blood and cerebrospinal fluid (CSF), in the order of cm/s. Use of this technique to encode slower flows is hampered by diffusion weighting and phase error introduced by gradient hardware imperfections. In this study, a new PC-MRI technique is developed using stimulated echo preparation to overcome these challenges. Flows as slow as 1 μm/s are measured and validated using controlled water flow through a pipe at 4.7 T. The error in measured flow rate obtained by integrating the measured velocity over the cross-sectional area of the pipe is less than 10%. The developed method was also able to capture slow natural convection flows appearing in liquids placed inside a horizontal bore magnet. Monitoring the 4D velocity vector field revealed that the natural convection flows decay exponentially with time. This method could be applied in future to study creeping flows, e.g. in tissue.

Magnetic resonance imaging of catalytically relevant processes

The main aim of this article is to provide a state-of-the-art review of the magnetic resonance imaging (MRI) utilization in heterogeneous catalysis. MRI is capable to provide very useful information about both living and nonliving objects in a noninvasive way. The studies of an internal heterogeneous reactor structure by MRI help to understand the mass transport and chemical processes inside the working catalytic reactor that can significantly improve its efficiency. However, one of the serious disadvantages of MRI is low sensitivity, and this obstacle dramatically limits possible MRI application. Fortunately, there are hyperpolarization methods that eliminate this problem. Parahydrogen-induced polarization approach, for instance, can increase the nuclear magnetic resonance signal intensity by four to five orders of magnitude; moreover, the obtained polarization can be stored in long-lived spin states and then transferred into an observable signal in MRI. An in-depth account of the studies on both thermal and hyperpolarized MRI for the investigation of heterogeneous catalytic processes is provided in this review as part of the special issue emphasizing the research performed to date in Russia/USSR.

Computational fluid dynamics with imaging of cleared tissue and of in vivo perfusion predicts drug uptake and treatment responses in tumours

Understanding the uptake of a drug by diseased tissue, and the drug's subsequent spatiotemporal distribution, are central factors in the development of effective targeted therapies. However, the interaction between the pathophysiology of diseased tissue and individual therapeutic agents can be complex, and can vary across tissue types and across subjects. Here, we show that the combination of mathematical modelling, high-resolution optical imaging of intact and optically cleared tumour tissue from animal models, and in vivo imaging of vascular perfusion predicts the heterogeneous uptake, by large tissue samples, of specific therapeutic agents, as well as their spatiotemporal distribution. In particular, by using murine models of colorectal cancer and glioma, we report and validate predictions of steady-state blood flow and intravascular and interstitial fluid pressure in tumours, of the spatially heterogeneous uptake of chelated gadolinium by tumours, and of the effect of a vascular disrupting agent on tumour vasculature.