Automated Image Analysis for Characterization of Circulating Tumor Cells and Clusters Sorted by Magnetic Levitation.

Magnetic levitation-based sorting technologies have revolutionized the detection and isolation of rare cells, including circulating tumor cells (CTCs) and circulating tumor cell clusters (CTCCs). Manual counting and quantification of these cells are prone to time-consuming processes, human error, and inter-observer variability, particularly challenging when heterogeneous cell types in 3D clusters are present. To overcome these challenges, we developed "Fastcount," an in-house MATLAB-based algorithm for precise, automated quantification and phenotypic characterization of CTCs and CTCCs, in both 2D and 3D. Fastcount is 120 times faster than manual counting and produces reliable results with a ±7.3% deviation compared to a trained laboratory technician. By analyzing 400 GB of fluorescence imaging data, we showed that Fastcount outperforms manual counting and commercial software when cells are aggregated in 3D or staining artifacts are present, delivering more accurate results. We further employed Fastcount for automated analysis of 3D image stacks obtained from CTCCs isolated from colorectal adenocarcinoma and renal cell carcinoma blood samples. Interestingly, we observed a highly heterogeneous spatial cellular composition within CTCCs, even among clusters from the same patient. Overall, Fastcount can be employed for various applications with lab-chip devices, such as CTC detection, CTCC analysis in 3D and cell detection in biosensors.

Characterization of spatially mapped volumetric molecular ultrasound signals for predicting response to anti-vascular therapy.

Quantitative three-dimensional molecular ultrasound is a promising technology for longitudinal imaging applications such as therapy monitoring; the risk profile is favorable compared to positron emission tomography and computed tomography. However, clinical translation of quantitative methods for this technology are limited in that they assume that tumor tissues are homogeneous, and often depend on contrast-destruction events that can produce unintended bioeffects. Here, we develop quantitative features (henceforth image features) that capture tumor spatial information, and that are extracted without contrast destruction. We compare these techniques with the contrast-destruction derived differential targeted enhancement parameter (dTE) in predicting response to therapy. We found thirty-three reproducible image features that predict response to antiangiogenic therapy, without the need for a contrast agent disruption pulse. Multiparametric analysis shows that several of these image features can differentiate treated versus control animals with comparable performance to post-destruction measurements, suggesting that these can potentially replace parameters such as the dTE. The highest performing pre-destruction image features showed strong linear correlations with conventional dTE parameters with less overall variance. Thus, our study suggests that image features obtained during the wash in of the molecular agent, pre-destruction, may replace conventional post-destruction image features or the dTE parameter.

Technical note: Noninvasive monitoring of normal tissue radiation damage using spectral quantitative ultrasound spectroscopy.

BACKGROUND: While radiation therapy (RT) is a critical component of breast cancer therapy and is known to decrease overall local recurrence rates, recent studies have shown that normal tissue radiation damage may increase recurrence risk. Fibrosis is a well-known consequence of RT, but the specific sequence of molecular and mechanical changes induced by RT remains poorly understood. PURPOSE: To improve cancer therapy outcomes, there is a need to understand the role of the irradiated tissue microenvironment in tumor recurrence. This study seeks to evaluate the use of spectral quantitative ultrasound (spectral QUS) for real time determination of the normal tissue characteristic radiation response and to correlate these results to molecular features in irradiated tissues. METHODS: Murine mammary fat pads (MFPs) were irradiated to 20 Gy, and spectral QUS was used to analyze tissue physical properties pre-irradiation as well as at 1, 5, and 10 days post-irradiation. Tissues were processed for scanning electron microscopy imaging as well as histological and immunohistochemical staining to evaluate morphology and structure. RESULTS: Tissue morphological and structural changes were observed non-invasively following radiation using mid-band fit (MBF), spectral slope (SS), and spectral intercept (SI) measurements obtained from spectral QUS. Statistically significant shifts in MBF and SI indicate structural tissue changes in real time, which matched histological observations. Radiation damage was indicated by increased adipose tissue density and extracellular matrix (ECM) deposition. CONCLUSIONS: Our findings demonstrate the potential of using spectral QUS to noninvasively evaluate normal tissue changes resulting from radiation damage. This supports further pre-clinical studies to determine how the tissue microenvironment and physical properties change in response to therapy, which may be important for improving treatment strategies.

Dynamic Contrast-Enhanced Ultrasound Modeling of an Analog to Pseudo-Diffusivity in Intravoxel Incoherent Motion Magnetic Resonance Imaging.

Tumor perfusion and vascular properties are important determinants of cancer response to therapy and thus various approaches for imaging perfusion are being explored. In particular, Intravoxel Incoherent Motion (IVIM) MRI has been actively researched as an alternative to Dynamic-Contrast-Enhanced (DCE) CT and DCE-MRI as it offers non-ionizing, non-contrast-based perfusion imaging. However, for repetitive treatment assessment in a short time period, high cost, limited access, and inability to scan at the bedside remain disadvantages of IVIM MRI. We propose an analysis framework that may enable 3D DCE Ultrasound (DCE-US) - low cost, bedside imaging with excellent safety record - as an alternative modality to IVIM MRI for the generation of DCE-US based pseudo-diffusivity maps in acoustically accessible anatomy and tumors. Modelling intravascular contrast propagation as a convective-diffusive process, we reconstruct parametric maps of pseudo-diffusivity by solving a large-scale fully coupled inverse problem without any assumptions regarding local constancy of the reconstructed parameters. In a mouse tumor model, we demonstrate that the 3D DCE-US pseudo-diffusivity is repeatable, sensitive to treatment with an antiangiogenic agent, and moderately correlated to histological measures of perfusion and angiogenesis.

Contrast-enhanced ultrasound imaging for assessing organ perfusion in rainbow trout (Oncorhynchus mykiss).

Contrast-enhanced ultrasound (CEUS) imaging has great potential as a non-lethal, inexpensive monitoring tool in aquatic toxicology. It is a well-established clinical imaging approach that combines real-time, quantitative assessment of organ blood flow, with morphological data. In humans, it has been extensively used to measure changes in blood flow that can be attributed to cancer, inflammation, and other biological abnormalities. However, it has yet to be explored as a tool for fish physiology or environmental toxicology. In this study, our goal was to determine if CEUS could be used to visualize and measure blood flow in the liver of a rainbow trout. All rainbow trout received two injections of an ultrasound contrast agent, microbubbles. A subset received a third injection after administration of propranolol, a non-specific beta1 & 2-blocker, to determine if changes in blood flow could be detected. Ultrasound contrast time-intensity curves (TIC) were obtained, fit to a lognormal model, and different perfusion parameters were calculated. Contrast enhancement was observed in all rainbow trout livers, with high percentage between repeated measurements, including blood flow (80.6 ± 27.3%), area under the curve (73.2 ± 14%), blood volume (84 ± 14.2%) and peak enhancement (86.7 ± 7.5%). After administration of propranolol, we detected a non-significant (p > 0.05) increase in area under the curve (102.6 ± 44.2%), peak enhancement (77.3 ± 106.4), blood volume (48.2 ± 74.5%), and decrease in hepatic blood flow (-17.3 ± 37.1%). These data suggest that CEUS imaging is suitable to measure organ blood flow in fish, and demonstrates tremendous potential for exploring different organs, fish species, and effects of chemical contaminants in future studies.

Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease is a major global health concern with increasing prevalence, associated with obesity and metabolic syndrome. Recently, quantitative ultrasound-based imaging techniques have dramatically improved the ability of ultrasound to detect and quantify hepatic steatosis. These newer ultrasound techniques possess many inherent advantages similar to conventional ultrasound such as universal availability, real-time capability, and relatively low cost along with quantitative rather than a qualitative assessment of liver fat. In addition, quantitative ultrasound-based imaging techniques are less operator dependent than traditional ultrasound. Here we review several different emerging quantitative ultrasound-based approaches used for detection and quantification of hepatic steatosis in patients at risk for nonalcoholic fatty liver disease. We also briefly summarize other clinically available imaging modalities for evaluating hepatic steatosis such as MRI, CT, and serum analysis.

Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.

There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor blood flow, and identified repeatable quantitative features to use in machine-learning models to capture subtle multi-parametric perfusion properties, including heterogeneity. Models were developed and trained in mice data and tested in a separate mouse cohort, as well as early validation clinical data consisting of patients receiving therapy for liver metastases. Models had excellent (ROC-AUC > 0.9) prediction of response in pre-clinical data, as well as proof-of-concept clinical data. Significant correlations with histological assessments of tumor vasculature were noted (Spearman R > 0.70) in pre-clinical data. Our approach can identify responders based on early perfusion changes, using perfusion properties correlated to gold-standard vascular properties.

Quantitative Ultrasound Spectroscopy for Differentiation of Hepatocellular Carcinoma from At-Risk and Normal Liver Parenchyma.

PURPOSE: Quantitative ultrasound approaches can capture tissue morphologic properties to augment clinical diagnostics. This study aims to clinically assess whether quantitative ultrasound spectroscopy (QUS) parameters measured in hepatocellular carcinoma (HCC) tissues can be differentiated from those measured in at-risk or healthy liver parenchyma. EXPERIMENTAL DESIGN: This prospective Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Fifteen patients with HCC, 15 non-HCC patients with chronic liver disease, and 15 healthy volunteers were included (31.1% women; 68.9% men). Ultrasound radiofrequency data were acquired in each patient in both liver lobes at two focal depths (3/9 cm). Region of interests (ROIs) were drawn on HCC and liver parenchyma. The average normalized power spectrum for each ROI was extracted, and a linear regression was fit within the -6 dB bandwidth, from which the midband fit (MBF), spectral intercept (SI), and spectral slope (SS) were extracted. Differences in QUS parameters between the ROIs were tested by a mixed-effects regression. RESULTS: There was a significant intraindividual difference in MBF, SS, and SI between HCC and adjacent liver parenchyma (P < 0.001), and a significant interindividual difference between HCC and at-risk and healthy non-HCC parenchyma (P < 0.001). In patients with HCC, cirrhosis (n = 13) did not significantly change any of the three parameters (P > 0.8) in differentiating HCC from non-HCC parenchyma. MBF (P = 0.12), SI (P = 0.33), and SS (P = 0.57) were not significantly different in non-HCC tissue among the groups. CONCLUSIONS: The QUS parameters are significantly different in HCC versus non-HCC liver parenchyma, independent of underlying cirrhosis. This could be leveraged for improved HCC detection with ultrasound in the future.

Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography.

Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy.

A multi-model framework to estimate perfusion parameters using contrast-enhanced ultrasound imaging.

PURPOSE: Contrast-enhanced ultrasound imaging has expanded the diagnostic potential of ultrasound by enabling real-time imaging and quantification of tissue perfusion. Several perfusion models and curve fitting methods have been developed to quantify the temporal behavior of tracer signal and standardize perfusion quantification. While the least-squares approach has traditionally been applied for curve fitting, it can be inadequate for noisy and complex data. Moreover, previous research suggests that certain perfusion models may be more relevant depending on the organ or tissue imaged. We propose a multi-model framework to select the most appropriate perfusion model and curve fitting method for each diagnostic application. METHODS: Our multi-model approach uses a system identification method, which estimates perfusion parameters from the model with the best fit to a given time-intensity curve. We compared current perfusion quantification methods that use a single perfusion model and curve fitting method and our proposed multi-model framework on bolus 3D dynamic contrast-enhanced ultrasound (DCE-US) in vivo images obtained in mice implanted with a colon cancer, as well as on simulation data. The quality of fit in estimating perfusion parameters was evaluated using the Spearman correlation coefficient, the coefficient of determination (R2 ), and the normalized root-mean-square error (NRMSE) to ensure that the multi-model framework finds the best perfusion model and curve fitting algorithm. RESULTS: Our multi-model framework outperforms conventional single perfusion model approaches with least-squares optimization, providing more robust perfusion parameter estimation. R2 and NRMSE are 0.98 and 0.18, respectively, for our proposed method. By comparison, the performance of the traditional approach is much more dependent upon the selection of the appropriate model. The R2 and NRMSE are 0.91 and 0.31, respectively. CONCLUSIONS: The proposed multi-model framework for perfusion modeling outperforms the current approach of single perfusion modeling using least-squares optimization and more robustly estimates perfusion parameters when using empiric data labeled by an expert as the gold standard. Our technique is minimally sensitive to issues affecting the accuracy of perfusion parameter estimation, including rise time, noise, region of interest size, and frame rate. This framework could be of key utility in modeling different perfusion systems in different tissues and organs.

Pharmacokinetic Modeling of Targeted Ultrasound Contrast Agents for Quantitative Assessment of Anti-Angiogenic Therapy: a Longitudinal Case-Control Study in Colon Cancer.

PURPOSE: To evaluate quantitative and semi-quantitative ultrasound molecular imaging (USMI) for antiangiogenic therapy monitoring in human colon cancer xenografts in mice. PROCEDURES: Colon cancer was established in 17 mice by injection of LS174T (Nr = 9) or CT26 (Nn = 8) cancer cells to simulate clinical responders and non-responders, respectively. Antiangiogenic treatment (bevacizumab; Nrt = Nnt = 5) or control treatment (saline; Nrc = 4, Nnc = 3) was administered at days 0, 3, and 7. Three-dimensional USMI was performed by injection at days 0, 1, 3, 7, and 10 of microbubbles targeted to the vascular endothelial growth factor receptor 2 (VEGFR2). Microbubble binding rate (kb), estimated by first-pass binding model fitting, and semi-quantitative parameters late enhancement (LE) and differential targeted enhancement (dTE) were compared at each day to evaluate their ability to assess and predict the response to therapy. Correlation analysis with the ex-vivo immunohistological quantification of VEGFR2 expression and the percentage blood vessel area was also performed. RESULTS: Significant changes in the USMI parameters during treatment were observed only in the responders treated with bevacizumab (p-value < 0.05). Prediction of the response to therapy as early as 1 day after treatment was achieved by the quantitative parameter kb (p-value < 0.01), earlier than possible by tumor volume quantification. USMI parameters could significantly distinguish between clinical responders and non-responders (p-value << 0.01) and correlated well with the ex-vivo quantification of VEGFR2 expression and the percentage blood vessels area (p-value << 0.01). CONCLUSION: USMI (semi)quantitative parameters provide earlier assessment of the response to therapy compared to tumor volume, permit early prediction of non-responders, and correlate well with ex-vivo angiogenesis biomarkers.

Role of Acid Sphingomyelinase and Ceramide in Mechano-Acoustic Enhancement of Tumor Radiation Responses.

Background: High-dose radiotherapy (>8-10 Gy) causes rapid endothelial cell death via acid sphingomyelinase (ASMase)-induced ceramide production, resulting in biologically significant enhancement of tumor responses. To further augment or solicit similar effects at low radiation doses, we used genetic and chemical approaches to evaluate mechano-acoustic activation of the ASMase-ceramide pathway by ultrasound-stimulated microbubbles (USMB). Methods: Experiments were carried out in wild-type and acid sphingomyelinase (asmase) knockout mice implanted with fibrosarcoma xenografts. A cohort of wild-type mice received the ASMase-ceramide pathway inhibitor sphingosine-1-phosphate (S1P). Mice were treated with varying radiation doses, with or without a priori USMB exposure at different microbubble concentrations. Treatment response was assessed with quantitative 3D Doppler ultrasound and immunohistochemistry at baseline, and at three, 24, and 72 hours after treatment, with three to five mice per treatment group at each time point. All statistical tests were two-sided. Results: Results confirmed an interaction between USMB and ionizing radiation at 24 hours (P < .001), with a decrease in tumor perfusion of up to 46.5% by three hours following radiation and USMB. This peaked at 24 hours, persisting for up to 72 hours, and was accompanied by extensive tumor cell death. In contrast, statistically nonsignificant and minimal tumor responses were noted in S1P-treated and asmase knockout mice for all treatments. Conclusions: This work is the first to confirm the involvement of the ASMase-ceramide pathway in mechanotransductive vascular targeting using USMB. Results also confirm that an acute vascular effect is driving this form of enhanced radiation response, and that it can be elicited at low radiation doses (<8-10 Gy) by a priori USMB exposure.

Tumour Vascular Shutdown and Cell Death Following Ultrasound-Microbubble Enhanced Radiation Therapy.

High-dose radiotherapy effects are regulated by acute tumour endothelial cell death followed by rapid tumour cell death instead of canonical DNA break damage. Pre-treatment with ultrasound-stimulated microbubbles (USMB) has enabled higher-dose radiation effects with conventional radiation doses. This study aimed to confirm acute and longitudinal relationships between vascular shutdown and tumour cell death following radiation and USMB in a wild type murine fibrosarcoma model using in vivo imaging. Methods: Tumour xenografts were treated with single radiation doses of 2 or 8 Gy alone, or in combination with low-/high-concentration USMB. Vascular changes and tumour cell death were evaluated at 3, 24 and 72 h following therapy, using high-frequency 3D power Doppler and quantitative ultrasound spectroscopy (QUS) methods, respectively. Staining using in situ end labelling (ISEL) and cluster of differentiation 31 (CD31) of tumour sections were used to assess cell death and vascular distributions, respectively, as gold standard histological methods. Results: Results indicated a decrease in the power Doppler signal of up to 50%, and an increase of more than 5 dBr in cell-death linked QUS parameters at 24 h for tumours treated with combined USMB and radiotherapy. Power Doppler and quantitative ultrasound results were significantly correlated with CD31 and ISEL staining results (p < 0.05), respectively. Moreover, a relationship was found between ultrasound power Doppler and QUS results, as well as between micro-vascular densities (CD31) and the percentage of cell death (ISEL) (R2 0.5-0.9). Conclusions: This study demonstrated, for the first time, the link between acute vascular shutdown and acute tumour cell death using in vivo longitudinal imaging, contributing to the development of theoretical models that incorporate vascular effects in radiation therapy. Overall, this study paves the way for theranostic use of ultrasound in radiation oncology as a diagnostic modality to characterize vascular and tumour response effects simultaneously, as well as a therapeutic modality to complement radiation therapy.

Quantitative Three-Dimensional Dynamic Contrast-Enhanced Ultrasound Imaging: First-In-Human Pilot Study in Patients with Liver Metastases.

Purpose: To perform a clinical assessment of quantitative three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) feasibility and repeatability in patients with liver metastasis, and to evaluate the extent of quantitative perfusion parameter sampling errors in 2D compared to 3D DCE-US imaging. Materials and Methods: Twenty consecutive 3D DCE-US scans of liver metastases were performed in 11 patients (45% women; mean age, 54.5 years; range, 48-60 years; 55% men; mean age, 57.6 years; range, 47-68 years). Pairs of repeated disruption-replenishment and bolus DCE-US images were acquired to determine repeatability of parameters. Disruption-replenishment was carried out by infusing 0.9 mL of microbubbles (Definity; Latheus Medical Imaging) diluted in 35.1 mL of saline over 8 min. Bolus consisted of intravenous injection of 0.2 mL microbubbles. Volumes-of-interest (VOI) and regions-or-interest (ROI) were segmented by two different readers in images to extract 3D and 2D perfusion parameters, respectively. Disruption-replenishment parameters were: relative blood volume (rBV), relative blood flow (rBF). Bolus parameters included: time-to-peak (TP), peak enhancement (PE), area-under-the-curve (AUC), and mean-transit-time (MTT). Results: Clinical feasibility and repeatability of 3D DCE-US using both the destruction-replenishment and bolus technique was demonstrated. The repeatability of 3D measurements between pairs of repeated acquisitions was assessed with the concordance correlation coefficient (CCC), and found to be excellent for all parameters (CCC > 0.80), except for the TP (0.74) and MTT (0.30) parameters. The CCC between readers was found to be excellent (CCC > 0.80) for all parameters except for TP (0.71) and MTT (0.52). There was a large Coefficient of Variation (COV) in intra-tumor measurements for 2D parameters (0.18-0.52). Same-tumor measurements made in 3D were significantly different (P = 0.001) than measurements made in 2D; a percent difference of up to 86% was observed between measurements made in 2D compared to 3D in the same tumor. Conclusions: 3D DCE-US imaging of liver metastases with a matrix array transducer is feasible and repeatable in the clinic. Results support 3D instead of 2D DCE US imaging to minimize sampling errors due to tumor heterogeneity.

Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging.

Due to spatial tumor heterogeneity and consecutive sampling errors, it is critically important to assess treatment response following antiangiogenic therapy in three dimensions as two-dimensional assessment has been shown to substantially over- and underestimate treatment response. In this study, we evaluated whether three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) imaging allows assessing early changes in tumor perfusion following antiangiogenic treatment (bevacizumab administered at a dose of 10 mg/kg b.w.), and whether these changes could predict treatment response in colon cancer tumors that either are responsive (LS174T tumors) or none responsive (CT26) to the proposed treatment. Our results showed that the perfusion parameters of 3D DCE-US including peak enhancement (PE) and area under curve (AUC) significantly decreased by up to 69 and 77%, respectively, in LS174T tumors within 1 day after antiangiogenic treatment (P = 0.005), but not in CT26 tumors (P > 0.05). Similarly, the percentage area of neovasculature significantly decreased in treated versus control LS174T tumors (P < 0.001), but not in treated versus control CT26 tumors (P = 0.796). Early decrease in both PE and AUC by 45-50% was predictive of treatment response in 100% (95% CI 69.2, 100%) of responding tumors, and in 100% (95% CI 88.4, 100%) and 86.7% (95% CI 69.3, 96.2%), respectively, of nonresponding tumors. In conclusion, 3D DCE-US provides clinically relevant information on the variability of tumor response to antiangiogenic therapy and may be further developed as biomarker for predicting treatment outcomes.

Erratum: Breast tumor response to ultrasound mediated excitation of microbubbles and radiation therapy in vivo.

[This corrects the article DOI: 10.18632/oncoscience.299.].

Molecular Contrast-Enhanced Ultrasound Imaging of Radiation-Induced P-Selectin Expression in Healthy Mice Colon.

PURPOSE: To evaluate the feasibility of using molecular contrast-enhanced ultrasound (mCEUS) to image radiation (XRT)-induced expression of cell adhesion molecules that mediate inflammatory response to XRT in healthy mouse colon tissue. METHODS AND MATERIALS: The colons of male BALB/c mice (aged 6-8 weeks, n=9) were irradiated with 14 Gy using a Kimtron IC-225 x-ray irradiator operating at 225 kV/13.0 mA at a dose rate of 0.985 Gy/min. The head and thorax regions were shielded during irradiation. A second control cohort of mice was left untreated (n=6). Molecular CEUS was carried out before and 24 hours after irradiation using a VEVO2100 system and MS250 21-MHz center frequency transducer. Each imaging session comprised mCEUS imaging with P-selectin targeted microbubbles and control microbubbles targeted with an isotype control IgG. Quantification of mCEUS was carried out by measuring the differential targeted enhancement (dTE) parameter. The perfusion parameters peak enhancement and area under the curve were also extracted from the initial injection bolus. Animals were sacrificed at 24 hours and the colon was resected for immunohistochemistry analysis (P-selectin/CD31-stained vessel). RESULTS: For P-selectin targeted microbubble, a significant increase (40 a.u.; P=.013) in dTE (P-dTE) was observed in irradiated mice over 24 hours. In contrast, a nonsignificant change in P-selectin dTE was observed in control mice. For control microbubbles, no significant difference in the IgG dTE parameter was noted in treated and control animals over 24 hours. A nonsignificant increase in the peak enhancement and area under the curve perfusion parameters associated with blood volume was noted in animals treated with radiation. Quantitative histology indicated significantly elevated P-selectin expression per blood vessel (36% in treated; 14% in control). CONCLUSION: Our results confirm the feasibility of using mCEUS for imaging of XRT-induced expression of P-selectin as a potential approach to monitoring healthy tissue inflammatory damage during radiation therapy.

Breast tumor response to ultrasound mediated excitation of microbubbles and radiation therapy in vivo.

Acoustically stimulated microbubbles have been demonstrated to perturb endothelial cells of the vasculature resulting in biological effects. In the present study, vascular and tumor response to ultrasound-stimulated microbubble and radiation treatment was investigated in vivo to identify effects on the blood vessel endothelium. Mice bearing breast cancer tumors (MDA-MB-231) were exposed to ultrasound after intravenous injection of microbubbles at different concentrations, and radiation at different doses (0, 2, and 8 Gy). Mice were sacrificed 12 and 24 hours after treatment for histopathological analysis. Tumor growth delay was assessed for up to 28 days after treatment. The results demonstrated additive antitumor and antivascular effects when ultrasound stimulated microbubbles were combined with radiation. Results indicated tumor cell apoptosis, vascular leakage, a decrease in tumor vasculature, a delay in tumor growth and an overall tumor disruption. When coupled with radiation, ultrasound-stimulated microbubbles elicited synergistic anti-tumor and antivascular effects by acting as a radioenhancing agent in breast tumor blood vessels. The present study demonstrates ultrasound driven microbubbles as a novel form of targeted antiangiogenic therapy in a breast cancer xenograft model that can potentiate additive effects to radiation in vivo.

Quantitative ultrasound imaging of therapy response in bladder cancer in vivo.

BACKGROUND AND AIMS: Quantitative ultrasound (QUS) was investigated to monitor bladder cancer treatment response in vivo and to evaluate tumor cell death from combined treatments using ultrasound-stimulated microbubbles and radiation therapy. METHODS: Tumor-bearing mice (n=45), with bladder cancer xenografts (HT- 1376) were exposed to 9 treatment conditions consisting of variable concentrations of ultrasound-stimulated Definity microbubbles [nil, low (1%), high (3%)], combined with single fractionated doses of radiation (0 Gy, 2 Gy, 8 Gy). High frequency (25 MHz) ultrasound was used to collect the raw radiofrequency (RF) data of the backscatter signal from tumors prior to, and 24 hours after treatment in order to obtain QUS parameters. The calculated QUS spectral parameters included the mid-band fit (MBF), and 0-MHz intercept (SI) using a linear regression analysis of the normalized power spectrum. RESULTS AND CONCLUSIONS: There were maximal increases in QUS parameters following treatments with high concentration microbubbles combined with 8 Gy radiation: (ΔMBF = +6.41 ± 1.40 (±SD) dBr and SI= + 7.01 ± 1.20 (±SD) dBr. Histological data revealed increased cell death, and a reduction in nuclear size with treatments, which was mirrored by changes in quantitative ultrasound parameters. QUS demonstrated markers to detect treatment effects in bladder tumors in vivo.

Multiparametric monitoring of chemotherapy treatment response in locally advanced breast cancer using quantitative ultrasound and diffuse optical spectroscopy.

PURPOSE: This study evaluated pathological response to neoadjuvant chemotherapy using quantitative ultrasound (QUS) and diffuse optical spectroscopy imaging (DOSI) biomarkers in locally advanced breast cancer (LABC). MATERIALS AND METHODS: The institution's ethics review board approved this study. Subjects (n = 22) gave written informed consent prior to participating. US and DOSI data were acquired, relative to the start of neoadjuvant chemotherapy, at weeks 0, 1, 4, 8 and preoperatively. QUS parameters including the mid-band fit (MBF), 0-MHz intercept (SI), and the spectral slope (SS) were determined from tumor ultrasound data using spectral analysis. In the same patients, DOSI was used to measure parameters relating to tumor hemoglobin and composition. Discriminant analysis and receiver-operating characteristic (ROC) analysis was used to classify clinical and pathological response during treatment and to estimate the area under the curve (AUC). Additionally, multivariate analysis was carried out for pairwise QUS/DOSI parameter combinations using a logistic regression model. RESULTS: Individual QUS and DOSI parameters, including the (SI), oxy-hemoglobin (HbO2), and total hemoglobin (HbT) were significant markers for response after one week of treatment (p < 0.01). Multivariate (pairwise) combinations increased the sensitivity, specificity and AUC at this time; the SI + HbO2 showed a sensitivity/specificity of 100%, and an AUC of 1.0. CONCLUSIONS: QUS and DOSI demonstrated potential as coincident markers for treatment response and may potentially facilitate response-guided therapies. Multivariate QUS and DOSI parameters increased the sensitivity and specificity of classifying LABC patients as early as one week after treatment.