Toward a noninvasive estimate of interstitial fluid pressure by dynamic contrast-enhanced MRI in a rat model of cerebral tumor

Characterization of Indeterminate Breast Lesions Based on Pressure Estimates by Noninvasive 3D Contrast-Enhanced Ultrasound

OBJECTIVE

To assess the ability of the pressure gradient between breast lesions and adjacent normal tissue estimated by 3D subharmonic-aided pressure estimation (SHAPE) to characterize indeterminate breast lesions.

METHODS

This prospective study enrolled patients scheduled for ultrasound-guided needle biopsies of a breast lesion. Before the biopsy, 3D SHAPE data were collected from the breast lesion during the infusion of an ultrasound contrast agent (Definity) as well as after clearance of the agent. Direct, invasive pressure measurements in the lesion and adjacent normal tissue were then obtained using an intracompartmental pressure monitoring system (C2DX) before tissue sampling as part of the biopsy procedure. The mean SHAPE gradient and invasive measurement gradient between the lesion and adjacent normal tissue were compared to the biopsy results. The SHAPE gradients were also compared to the invasive pressure gradients.

RESULTS

There were 8 malignant and 13 benign lesions studied. The SHAPE gradients and invasive pressure gradients were significantly different between the benign and malignant lesions (2.86 ± 3.24 vs. -0.03 ± 1.72 a.u.; p = 0.03 and 9.9 ± 8.5 vs. 20.9 ± 8.0 mmHg; p = 0.008, respectively). The area under the curves, specificities, and sensitivities for detecting malignancy by SHAPE gradients and invasive pressure gradients were 0.79 and 0.88, 77% and 92%, and 88% and 50%, respectively. A weak negative correlation was found between the SHAPE and invasive pressure gradients (r = -0.2).

CONCLUSION

The pressure gradient between a breast lesion and adjacent normal tissue estimated by 3D SHAPE shows potential for characterizing indeterminate breast lesions.

Heterogeneous Mechanical Stress and Interstitial Fluid Flow Predictions Derived from DCE-MRI for Rat U251N Orthotopic Gliomas

Mechanical stress and fluid flow influence glioma cell phenotype in vitro, but measuring these quantities in vivo continues to be challenging. The purpose of this study was to predict these quantities in vivo, thus providing insight into glioma physiology and potential mechanical biomarkers that may improve glioma detection, diagnosis, and treatment. Image-based finite element models of human U251N orthotopic glioma in athymic rats were developed to predict structural stress and interstitial flow in and around each animal's tumor. In addition to accounting for structural stress caused by tumor growth, our approach has the advantage of capturing fluid pressure-induced structural stress, which was informed by in vivo interstitial fluid pressure (IFP) measurements. Because gliomas and the brain are soft, elevated IFP contributed substantially to tumor structural stress, even inverting this stress from compressive to tensile in the most compliant cases. The combination of tumor growth and elevated IFP resulted in a concentration of structural stress near the tumor boundary where it has the greatest potential to influence cell proliferation and invasion. MRI-derived anatomical geometries and tissue property distributions resulted in heterogeneous interstitial fluid flow with local maxima near cerebrospinal fluid spaces, which may promote tumor invasion and hinder drug delivery. In addition, predicted structural stress and interstitial flow varied markedly between irradiated and radiation-naïve animals. Our modeling suggests that relative to tumors in stiffer tissues, gliomas experience unusual mechanical conditions with potentially important biological (e.g., proliferation and invasion) and clinical consequences (e.g., drug delivery and treatment monitoring).

Hydraulic conductivity of human cancer tissue: A hybrid study

Background

Elevated tumor tissue interstitial fluid pressure (IFP) is an adverse biomechanical biomarker that predicts poor therapy response and an aggressive phenotype. Advances in functional imaging have opened the prospect of measuring IFP non-invasively. Image-based estimation of the IFP requires knowledge of the tissue hydraulic conductivity (K), a measure for the ease of bulk flow through the interstitium. However, data on the magnitude of K in human cancer tissue are not available.

Methods

We measured the hydraulic conductivity of tumor tissue using modified Ussing chambers in surgical resection specimens. The effect of the tumor microenvironment (TME) on K was investigated by quantifying the collagen content, cell density, and fibroblast density of the tested samples using quantitative immune histochemistry. Also, we developed a computational fluid dynamics (CFD) model to evaluate the role of K on interstitial fluid flow and drug transport in solid tumors.

Results

The results show that the hydraulic conductivity of human tumor tissues is very limited, ranging from approximately 10-15 to 10-14 m2/Pa∙s. Moreover, K values varied significantly between tumor types and between different samples from the same tumor. A significant inverse correlation was found between collagen fiber density and hydraulic conductivity values. However, no correlation was detected between K and cancer cell or fibroblast densities. The computational model demonstrated the impact of K on the interstitial fluid flow and the drug concentration profile: higher K values led to a lower IFP and deeper drug penetration.

Conclusions

Human tumor tissue is characterized by a very limited hydraulic conductivity, representing a barrier to effective drug transport. The results of this study can inform the development of realistic computational models, facilitate non-invasive IFP estimation, and contribute to stromal targeting anticancer therapies.

Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI

Here, we investigate radiomics-based characterization of tumor vascular and microenvironmental properties in an orthotopic rat brain tumor model measured using dynamic-contrast-enhanced (DCE) MRI. Thirty-two immune compromised-RNU rats implanted with human U-251N cancer cells were imaged using DCE-MRI (7Tesla, Dual-Gradient-Echo). The aim was to perform pharmacokinetic analysis using a nested model (NM) selection technique to classify brain regions according to vasculature properties considered as the source of truth. A two-dimensional convolutional-based radiomics analysis was performed on the raw-DCE-MRI of the rat brains to generate dynamic radiomics maps. The raw-DCE-MRI and respective radiomics maps were used to build 28 unsupervised Kohonen self-organizing-maps (K-SOMs). A Silhouette-Coefficient (SC), k-fold Nested-Cross-Validation (k-fold-NCV), and feature engineering analyses were performed on the K-SOMs' feature spaces to quantify the distinction power of radiomics features compared to raw-DCE-MRI for classification of different Nested Models. Results showed that eight radiomics features outperformed respective raw-DCE-MRI in prediction of the three nested models. The average percent difference in SCs between radiomics features and raw-DCE-MRI was: 29.875% ± 12.922%, p < 0.001. This work establishes an important first step toward spatiotemporal characterization of brain regions using radiomics signatures, which is fundamental toward staging of tumors and evaluation of tumor response to different treatments.

Dynamic contrast enhanced (DCE) MRI estimation of vascular parameters using knowledge-based adaptive models

We introduce and validate four adaptive models (AMs) to perform a physiologically based Nested-Model-Selection (NMS) estimation of such microvascular parameters as forward volumetric transfer constant, Ktrans, plasma volume fraction, vp, and extravascular, extracellular space, ve, directly from Dynamic Contrast-Enhanced (DCE) MRI raw information without the need for an Arterial-Input Function (AIF). In sixty-six immune-compromised-RNU rats implanted with human U-251 cancer cells, DCE-MRI studies estimated pharmacokinetic (PK) parameters using a group-averaged radiological AIF and an extended Patlak-based NMS paradigm. One-hundred-ninety features extracted from raw DCE-MRI information were used to construct and validate (nested-cross-validation, NCV) four AMs for estimation of model-based regions and their three PK parameters. An NMS-based a priori knowledge was used to fine-tune the AMs to improve their performance. Compared to the conventional analysis, AMs produced stable maps of vascular parameters and nested-model regions less impacted by AIF-dispersion. The performance (Correlation coefficient and Adjusted R-squared for NCV test cohorts) of the AMs were: 0.914/0.834, 0.825/0.720, 0.938/0.880, and 0.890/0.792 for predictions of nested model regions, vp, Ktrans, and ve, respectively. This study demonstrates an application of AMs that quickens and improves DCE-MRI based quantification of microvasculature properties of tumors and normal tissues relative to conventional approaches.

Characterization of the Response of 9L and U-251N Orthotopic Brain Tumors to 3D Conformal Radiation Therapy

In a study employing MRI-guided stereotactic radiotherapy (SRS) in two orthotopic rodent brain tumor models, the radiation dose yielding 50% survival (the TCD50) was sought. Syngeneic 9L cells, or human U-251N cells, were implanted stereotactically in 136 Fischer 344 rats or 98 RNU athymic rats, respectively. At approximately 7 days after implantation for 9L, and 18 days for U-251N, rats were imaged with contrast-enhanced MRI (CE-MRI) and then irradiated using a Small Animal Radiation Research Platform (SARRP) operating at 220 kV and 13 mA with an effective energy of ∼70 keV and dose rate of ∼2.5 Gy per min. Radiation doses were delivered as single fractions. Cone-beam CT images were acquired before irradiation, and tumor volumes were defined using co-registered CE-MRI images. Treatment planning using MuriPlan software defined four non-coplanar arcs with an identical isocenter, subsequently accomplished by the SARRP. Thus, the treatment workflow emulated that of current clinical practice. The study endpoint was animal survival to 200 days. The TCD50 inferred from Kaplan-Meier survival estimation was approximately 25 Gy for 9L tumors and below 20 Gy, but within the 95% confidence interval in U-251N tumors. Cox proportional-hazards modeling did not suggest an effect of sex, with the caveat of wide confidence intervals. Having identified the radiation dose at which approximately half of a group of animals was cured, the biological parameters that accompany radiation response can be examined.

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.

Estimation of Mechanical and Transport Parameters in Cancers Using Short Time Poroelastography

Mechanical and transport properties of cancers such as Young's modulus (YM), Poisson's ratio (PR), and vascular permeability (VP) have great clinical importance in cancer diagnosis, prognosis, and treatment. However, non-invasive estimation of these parameters in vivo is challenged by many practical factors. Elasticity imaging methods, such as "poroelastography", require prolonged data acquisition, which can limit their clinical applicability. In this paper, we investigate a new method to perform poroelastography experiments, which results in shorter temporal acquisition windows. This method is referred to as "short-time poroelastography" (STPE). Finite element (FE) and ultrasound simulations demonstrate that, using STPE, it is possible to accurately estimate YM, PR (within 10% error) using windows of observation (WoOs) of length as short as 1 underlying strain Time Constant (TC). The error was found to be almost negligible (< 3%) when using WoOs longer than 2 strain TCs. In the case of VP estimation, WoOs of at least 2 strain TCs are required to obtain an error < 8% (in simulations). The stricter requirement for the estimation of VP with respect to YM and PR is due its reliance on the transient strain behavior while YM and PR depend on the steady state strain values only. In vivo experimental data are used as a proof-of-principle of the potential applicability of the proposed methodology in vivo. The use of STPE may provide a means to efficiently perform poroelastography experiments without compromising the accuracy of the estimated tissue properties.

Adaptation of laser interstitial thermal therapy for tumor ablation under MRI monitoring in a rat orthotopic model of glioblastoma

BACKGROUND

Laser interstitial thermal therapy (LITT) under magnetic resonance imaging (MRI) monitoring is being increasingly used in cytoreductive surgery of recurrent brain tumors and tumors located in eloquent brain areas. The objective of this study was to adapt this technique to an animal glioma model.

METHODS

A rat model of U251 glioblastoma (GBM) was employed. Tumor location and extent were determined by MRI and dynamic contrast-enhanced (DCE) MRI. A day after assessing tumor appearance, tumors were ablated during diffusion-weighted imaging (DWI)-MRI using a Visualase LITT system (n = 5). Brain images were obtained immediately after ablation and again at 24 h post-ablation to confirm the efficacy of tumor cytoablation. Untreated tumors served as controls (n = 3). Rats were injected with fluorescent isothiocyanate (FITC) dextran and Evans blue that circulated for 10 min after post-LITT MRI. The brains were then removed for fluorescence microscopy and histopathology evaluations using hematoxylin and eosin (H&E) and major histocompatibility complex (MHC) staining.

RESULTS

All rats showed a space-occupying tumor with T2 and T1 contrast-enhancement at pre-LITT imaging. The rats that underwent the LITT procedure showed a well-demarcated ablation zone with near-complete ablation of tumor tissue and with peri-ablation contrast enhancement at 24 h post-ablation. Tumor cytoreduction by ablation as seen on MRI was confirmed by H&E and MHC staining.

CONCLUSIONS

Data showed that tumor cytoablation using MRI-monitored LITT was possible in preclinical glioma models. Real-time MRI monitoring facilitated visualizing and controlling the area of ablation as it is otherwise performed in clinical applications.

Longitudinal Monitoring of Simulated Interstitial Fluid Pressure for Pancreatic Ductal Adenocarcinoma Patients Treated with Stereotactic Body Radiotherapy

Simple Summary

High vessel permeability, poor perfusion, low lymphatic drainage, and dense abundant stroma elevate interstitial fluid pressures (IFP) in pancreatic ductal adenocarcinoma (PDAC). The present study aims to monitor longitudinal changes in simulated tumor IFP and velocity (IFV) values using a dynamic contrast-enhanced (DCE)-MRI-based computational fluid modeling (CFM) approach in PDAC. Nine PDAC patients underwent DCE-MRI acquisition on a 3-Tesla MRI scanner at pre-treatment (TX (0)), immediately after the first fraction of stereotactic body radiotherapy (SBRT, (D1-TX)), and six weeks post-TX (D2-TX). The partial differential equation of IFP formulated from the continuity equation using the Starling Principle of fluid exchange and Darcy velocity–pressure relationship was solved in COMSOL Multiphysics software to generate IFP and IFV parametric maps using relevant tumor tissue physiological parameters. Initial results suggest that after validation, IFP and IFV can be imaging biomarkers of early response to therapy that may guide precision medicine in PDAC.

Abstract

The present study aims to monitor longitudinal changes in simulated tumor interstitial fluid pressure (IFP) and velocity (IFV) values using dynamic contrast-enhanced (DCE)-MRI-based computational fluid modeling (CFM) in pancreatic ductal adenocarcinoma (PDAC) patients. Nine PDAC patients underwent MRI, including DCE-MRI, on a 3-Tesla MRI scanner at pre-treatment (TX (0)), after the first fraction of stereotactic body radiotherapy (SBRT, (D1-TX)), and six weeks post-TX (D2-TX). The partial differential equation of IFP formulated from the continuity equation, incorporating the Starling Principle of fluid exchange, Darcy velocity, and volume transfer constant (K^trans), was solved in COMSOL Multiphysics software to generate IFP and IFV maps. Tumor volume (V_t), K^trans, IFP, and IFV values were compared (Wilcoxon and Spearman) between the time- points. D2-TX K^trans values were significantly different from pre-TX and D1-TX (p < 0.05). The D1-TX and pre-TX mean IFV values exhibited a borderline significant difference (p = 0.08). The IFP values varying <3.0% between the three time-points were not significantly different (p > 0.05). V_t and IFP values were strongly positively correlated at pre-TX (ρ = 0.90, p = 0.005), while IFV exhibited a strong negative correlation at D1-TX (ρ = −0.74, p = 0.045). V_t, K^trans, IFP, and IFV hold promise as imaging biomarkers of early response to therapy in PDAC.

A computational model of glioma reveals opposing, stiffness-sensitive effects of leaky vasculature and tumor growth on tissue mechanical stress and porosity

A biphasic computational model of a growing, vascularized glioma within brain tissue was developed to account for unique features of gliomas, including soft surrounding brain tissue, their low stiffness relative to brain tissue, and a lack of draining lymphatics. This model is the first to couple nonlinear tissue deformation with porosity and tissue hydraulic conductivity to study the mechanical interaction of leaky vasculature and solid growth in an embedded glioma. The present model showed that leaky vasculature and elevated interstitial fluid pressure produce tensile stress within the tumor in opposition to the compressive stress produced by tumor growth. This tensile effect was more pronounced in softer tissue and resulted in a compressive stress concentration at the tumor rim that increased when tumor was softer than host. Aside from generating solid stress, fluid pressure-driven tissue deformation decreased the effective stiffness of the tumor while growth increased it, potentially leading to elevated stiffness in the tumor rim. A novel prediction of reduced porosity at the tumor rim was corroborated by direct comparison with estimates from our in vivo imaging studies. Antiangiogenic and radiation therapy were simulated by varying vascular leakiness and tissue hydraulic conductivity. These led to greater solid compression and interstitial pressure in the tumor, respectively, the former of which may promote tumor infiltration of the host. Our findings suggest that vascular leakiness has an important influence on in vivo solid stress, stiffness, and porosity fields in gliomas given their unique mechanical microenvironment.

Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma

The effect of a human vascular endothelial growth factor antibody on the vasculature of human tumor grown in rat brain was studied. Using dynamic contrast-enhanced magnetic resonance imaging, the effects of intravenous bevacizumab (Avastin; 10 mg/kg) were examined before and at postadministration times of 1, 2, 4, 8, 12 and 24 h (N = 26; 4-5 per time point) in a rat model of orthotopic, U251 glioblastoma (GBM). The commonly estimated vascular parameters for an MR contrast agent were: (i) plasma distribution volume (v_p ), (ii) forward volumetric transfer constant (K^trans ) and (iii) reverse transfer constant (k_ep ). In addition, extracellular distribution volume (V_D ) was estimated in the tumor (V_D-tumor ), tumor edge (V_D-edge ) and the mostly normal tumor periphery (V_D-peri ), along with tumor blood flow (TBF), peri-tumoral hydraulic conductivity (K) and interstitial flow (Flux) and tumor interstitial fluid pressure (TIFP). Studied as % changes from baseline, the 2-h post-treatment time point began showing significant decreases in v_p , V_D-tumor, V_D-edge and V_D-peri , as well as K, with these changes persisting at 4 and 8 h in v_p , K, V_{D-tumor, -edge} and _-peri (t-tests; p < 0.05-0.01). Decreases in K^trans were observed at the 2- and 4-h time points (p < 0.05), while interstitial volume fraction (v_e ; = K^trans /k_ep ) showed a significant decrease only at the 2-h time point (p < 0.05). Sustained decreases in Flux were observed from 2 to 24 h (p < 0.01) while TBF and TIFP showed delayed responses, increases in the former at 12 and 24 h and a decrease in the latter only at 12 h. These imaging biomarkers of tumor vascular kinetics describe the short-term temporal changes in physical spaces and fluid flows in a model of GBM after Avastin administration.

Cerebral microcirculation in glioblastoma: A major determinant of diagnosis, resection, and drug delivery

Glioblastoma (GBM) is the most common primary brain tumor with a dismal prognosis. Current standard of treatment is safe maximal tumor resection followed by chemotherapy and radiation. Altered cerebral microcirculation and elevated blood-tumor barrier (BTB) permeability in tumor periphery due to glioma-induced vascular dysregulation allow T1 contrast-enhanced visualization of resectable tumor boundaries. Newer tracers that label the tumor and its vasculature are being increasingly used for intraoperative delineation of glioma boundaries for even more precise resection. Fluorescent 5-aminolevulinic acid (5-ALA) and indocyanine green (ICG) are examples of such intraoperative tracers. Recently, magnetic resonance imaging (MRI)-based MR thermometry is being employed for laser interstitial thermal therapy (LITT) for glioma debulking. However, aggressive, fatal recurrence always occurs. Postsurgical chemotherapy is hampered by the inability of most drugs to cross the blood-brain barrier (BBB). Understanding postsurgical changes in brain microcirculation and permeability is crucial to improve chemotherapy delivery. It is important to understand whether any microcirculatory indices can differentiate between true recurrence and radiation necrosis. LITT leads to peri-ablation BBB opening that persists for several weeks. Whether it can be a conduit for chemotherapy delivery is yet to be explored. This review will address the role of cerebral microcirculation in such emerging ideas in GBM diagnosis and therapy.

The impact of initial tumor microenvironment on imaging phenotype

Models of human cancer, to be useful, must replicate human disease with high fidelity. Our focus in this study is rat xenograft brain tumors as a model of human embedded cerebral tumors. A distinguishing signature of such tumors in humans, that of contrast-enhancement on imaging, is often not present when the human cells grow in rodents, despite the xenografts having nearly identical DNA signatures to the original tumor specimen. Although contrast enhancement was uniformly evident in all the human tumors from which the xenografts’ cells were derived, we show that long-term contrast enhancement in the model tumors may be determined conditionally by the tumor microenvironment at the time of cell implantation. We demonstrate this phenomenon in one of two patient-derived orthotopic xenograft (PDOX) models using cancer stem-like cell (CSC)-enriched neurospheres from human tumor resection specimens, transplanted to groups of immune-compromised rats in the presence or absence of a collagen/fibrin scaffolding matrix, Matrigel. The rats were imaged by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and their brains were examined by histopathology. Targeted proteomics of the PDOX tumor specimens grown from CSC implanted with and without Matrigel showed that while the levels of the majority of proteins and post-translational modifications were comparable between contrast-enhancing and non-enhancing tumors, phosphorylation of Fox038 showed a differential expression. The results suggest key proteins determine contrast enhancement and suggest a path toward the development of better animal models of human glioma. Future work is needed to elucidate fully the molecular determinants of contrast-enhancement.

Pulsed focused ultrasound lowers interstitial fluid pressure and increases nanoparticle delivery and penetration in head and neck squamous cell carcinoma xenograft tumors

Nanocarriers offer a promising approach to significantly improve therapeutic delivery to solid tumors as well as limit the side effects associated with anti-cancer agents. However, their relatively large size can negatively affect their ability to efficiently penetrate into more interior tumor regions, ultimately reducing therapeutic efficacy. Poor penetration of large agents such as nanocarriers is attributed to factors in the tumor microenvironment such as elevated interstitial fluid pressure (IFP) and fibrillar collagen in the extracellular matrix. Our previous studies reported that pretreatment of solid tumor xenografts with nondestructive pulsed focused ultrasound (pFUS) can improve the delivery and subsequent therapy of a variety of therapeutic formulations in different tumor models, where the results were associated with expanded extracellular spaces (ECS), an increase in hydraulic conductivity, and decrease in tissue stiffness. Here, we demonstrate the inverse relationship between IFP and the penetration of systemically administered nanoparticle (NP) probes, where IFP increased from the tumor periphery to their center. Furthermore, we show that pretreatment with pFUS can safely reduce IFP and improve NP delivery; especially into the center of the tumors. These results coincide with effects generated in the fibrillar collagen network microstructure in the ECS as determined by quantitative polarized light microscopy. Whole tumor and histomorphometric analysis, however, did not show significant differences in collagen area fraction or collagen feature solidity, as well as tumor cross-sectional area and aspect ratio, as a result of the treatments. We present a biophysical model connecting the experimental results, where pFUS-mediated cytoarchitectural changes are associated with improved redistribution of the interstitial fluid and lower IFP. The resulting improvement in NP delivery supports our previous therapeutic studies and may have implications for clinical applications to improve therapeutic outcomes in cancer therapy.

Towards noninvasive estimation of tumour pressure by utilising MR elastography and nonlinear biomechanical models: a simulation and phantom study

The solid and fluid pressures of tumours are often elevated relative to surrounding tissue. This increased pressure is known to correlate with decreased treatment efficacy and potentially with tumour aggressiveness and therefore, accurate noninvasive estimates of tumour pressure would be of great value. We present a proof-of-concept method to infer the total tumour pressure, that is the sum of the fluid and solid parts, by examining stiffness in the peritumoural tissue with MR elastography and utilising nonlinear biomechanical models. The pressure from the tumour deforms the surrounding tissue leading to changes in stiffness. Understanding and accounting for these biases in stiffness has the potential to enable estimation of total tumour pressure. Simulations are used to validate the method with varying pressure levels, tumour shape, tumour size, and noise levels. Results show excellent matching in low noise cases and still correlate well with higher noise. Percent error remains near or below 10% for higher pressures in all noise level cases. Reconstructed pressures were also calculated from experiments with a catheter balloon embedded in a plastisol phantom at multiple inflation levels. Here the reconstructed pressures generally match the increases in pressure measured during the experiments. Percent errors between average reconstructed and measured pressures at four inflation states are 17.9%, 52%, 23.2%, and 0.9%. Future work will apply this method to in vivo data, potentially providing an important biomarker for cancer diagnosis and treatment.

Estimation of Vascular Permeability in Irregularly Shaped Cancers Using Ultrasound Poroelastography

OBJECTIVE

Vascular permeability (VP) is a mechanical parameter which plays an important role in cancer initiation, metastasis, and progression. To date, there are only a few non-invasive methods that can be used to image VP in solid tumors. Most of these methods require the use of contrast agents and are expensive, limiting widespread use.

METHODS

In this paper, we propose a new method to image VP in tumors, which is based on the use of ultrasound poroelastography. Estimation of VP by poroelastography requires knowledge of the Young's modulus (YM), Poisson's ratio (PR), and strain time constant (TC) in the tumors. In our method, we find the ellipse which best fits the tumor (regardless of its shape) using an eigen-system-based fitting technique and estimate the YM and PR using Eshelby's elliptic inclusion formulation. A Fourier method is used to estimate the axial strain TC, which does not require any initial guess and is highly robust to noise.

RESULTS

It is demonstrated that the proposed method can estimate VP in irregularly shaped tumors with an accuracy of above [Formula: see text] using ultrasound simulation data with signal-to-noise ratio of 20 dB or higher. In vivo feasibility of the proposed technique is demonstrated in an orthotopic mouse model of breast cancer.

CONCLUSION

The proposed imaging method can provide accurate and localized estimation of VP in cancers non-invasively and cost-effectively.

SIGNIFICANCE

Accurate and non-invasive assessment of VP can have a significant impact on diagnosis, prognosis, and treatment of cancers.

Estimation of mechanical parameters in cancers by empirical orthogonal function analysis of poroelastography data

Ultrasound poroelastography is a non-invasive imaging modality that has been shown to be capable of estimating mechanical parameters such as Young's modulus (YM), Poisson's ratio (PR) and vascular permeability (VP) in cancers. However, experimental poroelastographic data are inherently noisy because of the requirement of relatively long temporal data acquisitions often in hand-held mode conditions. In this paper, we propose a new method, which allows accurate estimation of YM and PR from denoised steady state axial and lateral strains by empirical orthogonal function (EOF) analysis of poroelastographic data. The method also allows estimation of VP from the time constant (TC) of the first expansion coefficient (EC) of the temporal axial strain, which has larger dynamic range and lower noise in comparison to the actual temporal axial strain curve. We validated our technique through finite element (FE) and ultrasound simulations and tested the in vivo feasibility in experimental data obtained from a cancer animal model. The percent relative errors (PRE) in the estimation of YM, PR and VP using the EOF analysis as applied to ultrasound simulation data were 3.27%, 3.10%, 14.22%, respectively (at SNR of 20 dB). Based on the high level of accuracy by EOF analysis, the proposed technique may become a useful signal processing technique for applications focusing on the estimation of the mechanical behavior of cancers.

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.