Motion correction of 3D dynamic contrast-enhanced ultrasound imaging without anatomical B-Mode images: Pilot evaluation in eight patients.

BACKGROUND: Dynamic contrast-enhanced ultrasound (DCE-US) is highly susceptible to motion artifacts arising from patient movement, respiration, and operator handling and experience. Motion artifacts can be especially problematic in the context of perfusion quantification. In conventional 2D DCE-US, motion correction (MC) algorithms take advantage of accompanying side-by-side anatomical B-Mode images that contain time-stable features. However, current commercial models of 3D DCE-US do not provide side-by-side B-Mode images, which makes MC challenging. PURPOSE: This work introduces a novel MC algorithm for 3D DCE-US and assesses its efficacy when handling clinical data sets. METHODS: In brief, the algorithm uses a pyramidal approach whereby short temporal windows consisting of three consecutive frames are created to perform local registrations, which are then registered to a master reference derived from a weighted average of all frames. We applied the algorithm to imaging studies from eight patients with metastatic lesions in the liver and assessed improvements in original versus motion corrected 3D DCE-US cine using: (i) frame-to-frame volumetric overlap of segmented lesions, (ii) normalized correlation coefficient (NCC) between frames (similarity analysis), and (iii) sum of squared errors (SSE), root-mean-squared error (RMSE), and r-squared (R2 ) quality-of-fit from fitted time-intensity curves (TIC) extracted from a segmented lesion. RESULTS: We noted improvements in frame-to-frame lesion overlap across all patients, from 68% ± 13% without correction to 83% ± 3% with MC (p = 0.023). Frame-to-frame similarity as assessed by NCC also improved on two different sets of time points from 0.694 ± 0.057 (original cine) to 0.862 ± 0.049 (corresponding MC cine) and 0.723 ± 0.066 to 0.886 ± 0.036 (p ≤ 0.001 for both). TIC analysis displayed a significant decrease in RMSE (p = 0.018) and a significant increase in R2 goodness-of-fit (p = 0.029) for the patient cohort. CONCLUSIONS: Overall, results suggest decreases in 3D DCE-US motion after applying the proposed algorithm.

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.

Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

The question of whether ultrasound point shear wave elastography can differentiate renal cell carcinoma (RCC) from angiomyolipoma (AML) is controversial. This study prospectively enrolled 51 patients with 52 renal tumors (42 RCCs, 10 AMLs). We obtained 10 measurements of shear wave velocity (SWV) in the renal tumor, cortex and medulla. Median SWV was first used to classify RCC versus AML. Next, the prediction accuracy of 4 machine learning algorithms-logistic regression, naïve Bayes, quadratic discriminant analysis and support vector machines (SVMs)-was evaluated, using statistical inputs from the tumor, cortex and combined statistical inputs from tumor, cortex and medulla. After leave-one-out cross validation, models were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). Tumor median SWV performed poorly (AUC = 0.62; p = 0.23). Except logistic regression, all machine learning algorithms reached statistical significance using combined statistical inputs (AUC = 0.78-0.98; p < 7.1 × 10-3). SVMs demonstrated 94% accuracy (AUC = 0.98; p = 3.13 × 10-6) and clearly outperformed median SWV in differentiating RCC from AML (p = 2.8 × 10-4).

Multimodality Hyperpolarized C-13 MRS/PET/Multiparametric MR Imaging for Detection and Image-Guided Biopsy of Prostate Cancer: First Experience in a Canine Prostate Cancer Model.

PURPOSE: To assess whether simultaneous hyperpolarized C-13 magnetic resonance spectroscopy (MRS)/positron emission tomography (PET)/multiparametric magnetic resonance (mpMR) imaging is feasible in an orthotopic canine prostate cancer (PCa) model using a clinical PET/MR system and whether the combined imaging datasets can be fused with transrectal ultrasound (TRUS) in real time for multimodal image fusion-guided targeted biopsy of PCa. PROCEDURES: Institutional Animal Care and Use Committee approval was obtained for this study. Canine prostate adenocarcinoma (Ace-1) cells were orthotopically injected into the prostate of four dogs. Once tumor engraftment was confirmed by TRUS, simultaneous hyperpolarized C-13 MRS of [1-13C]pyruvate, PET (2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), [68Ga]NODAGA-SCH1), and mpMR (T2W, DWI) imaging was performed using a clinical PET/MR system. Multimodality imaging data sets were then fused with TRUS and image-guided targeted biopsy was performed. Imaging results were then correlated with histological findings. RESULTS: Successful tumor engraftment was histologically confirmed in three of the four dogs (dogs 2, 3, and 4) and simultaneous C-13 MRS/PET/mpMR was feasible in all three. In dog 2, C-13 MRS showed increased lactate signal in the tumor (lactate/totalC = 0.47) whereas mpMR did not show any signal changes. In dog 3, [18F]FDG-PET (SUVmean = 1.90) and C-13 MRS (lactate/totalC = 0.59) showed elevated metabolic activity in the tumor. In dog 4, [18F]FDG (SUVmean = 2.43), [68Ga]NODAGA-SCH1 (SUVmean = 0.75), and C-13 MRS (Lac/totalC = 0.53) showed elevated uptake in tumor compared to control tissue and multimodal image fusion-guided biopsy of the tumor was successfully performed. CONCLUSION: Simultaneous C-13 MRS/PET/mpMR imaging and multimodal image fusion-guided biopsy is feasible in a canine PCa model.

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.

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.

Point Shear Wave Elastography for Grading Liver Fibrosis: Can the Number of Measurements Be Reduced?

The aim of this study was to assess whether the number of liver point shear wave elastography (pSWE) measurements could be reduced compared with the currently recommended 10 valid measurements. Three thousand four hundred one pSWE examinations in patients with liver disease were performed with 10 consecutive valid measurements in liver segment 8. Liver fibrosis grading using published cutoff values were compared retrospectively using the median of 10 versus the first 1-9 measurements with Kendall's τ coefficient. Overall and binary (clinically significant [≥F2] versus non-significant [F0/F1]) fibrosis grading highly correlated when using 5-9 versus 10 valid measurements (τ = 0.96/0.95, p < 0.001). With the use of 5 valid measurements, a change in binary grading was observed in 87 of 3401 (2.6%) exams and only when velocities measured between 1.1 and 1.5 m/s. Therefore, using 5-9 valid measurements in pSWE of the liver results in a small portion of liver fibrosis grading misclassifications compared with use of 10 measurements and could help decrease scanning time, cost and discomfort in sonographers and patients.

US Molecular Imaging of Acute Ileitis: Anti-Inflammatory Treatment Response Monitored with Targeted Microbubbles in a Preclinical Model.

Purpose To evaluate whether dual-selectin-targeted US molecular imaging allows longitudinal monitoring of anti-inflammatory treatment effects in an acute terminal ileitis model in swine. Materials and Methods The Institutional Animal Care and Use Committee approved all animal studies. Fourteen swine with chemically induced acute terminal ileitis (day 0) were randomized into the following groups: (a) an anti-inflammatory treatment group (n = 8; meloxicam, 0.25 mg per kilogram of body weight; prednisone, 0.5 mg/kg) and (b) a control group (n = 6; saline). US molecular imaging was performed with a clinical US machine after intravenous injection of clinically translatable dual P- and E-selectin-targeted microbubbles (5 × 108/kg). Three inflamed bowel segments per swine were imaged at baseline, as well as on days 1, 3, and 6 after treatment initiation. At day 6, bowel segments were analyzed ex vivo for selectin expression levels by using quantitative immunofluorescence. Results After induction of inflammation, US molecular imaging signal increased at day 1 in both animal groups (P < .001). At day 3, signal in the treatment group decreased (P < .001 vs day 1), while signal in control animals did not significantly change (P = .18 vs day 1) and was higher (P = .001) compared with that in the treatment group. At day 6, signal in the treatment group further decreased and remained lower (P = .02) compared with that in the control group. Immunofluorescence confirmed significant (P ≤ .04) downregulation of both P- and E-selectin expression levels in treated versus control bowel segments. Conclusion Dual-selectin-targeted US molecular imaging allows longitudinal monitoring of anti-inflammatory treatment effects in a large-animal model of acute ileitis. This supports further clinical development of this quantitative and radiation-free technique for monitoring inflammatory bowel disease. © RSNA, 2018 Online supplemental material is available for this article.

Ultrasound-guided delivery of thymidine kinase-nitroreductase dual therapeutic genes by PEGylated-PLGA/PIE nanoparticles for enhanced triple negative breast cancer therapy.

AIM: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype. Since no targeted therapy is available, gene-directed enzyme prodrug therapy (GDEPT) could be an attractive strategy for treating TNBC. MATERIALS & METHODS: Polyethylene glycol (PEG)ylated-poly(lactic-co-glycolic acid)/polyethyleneimine nanoparticles (PLGA/PEI NPs) were synthesized and complexed with TK-NTR fusion gene. Ultrasound (US) and microbubble (MB) mediated sonoporation was used for efficient delivery of the TK-NTR-DNA-NP complex to TNBC tumor in vivo for cancer therapy. Therapeutic effect was evaluated by treating TNBC cells in vitro and tumor xenograft in vivo by using prodrugs ganciclovir (GCV) and CB1954. RESULTS: TNBC cells treated with GCV/CB1954 prodrugs after transfection of TK-NTR-DNA by PEGylated-PLGA/PEI NP resulted in high apoptotic-index. US-MB image-guided delivery of TK-NTR-DNA-NP complex displayed significant expression level of TK-NTR protein and showed tumor reduction when treated with GCV/CB1954 prodrugs in TNBC xenograft in vivo. CONCLUSION: US-MB image-guided delivery of TK-NTR gene by PEGylated-PLGA/PEI NPs could be a potential prodrug therapy for TNBC in the clinic.

Intraoperative Resection Guidance with Photoacoustic and Fluorescence Molecular Imaging Using an Anti-B7-H3 Antibody-Indocyanine Green Dual Contrast Agent.

Purpose: Breast cancer often requires surgical treatment including breast-conserving surgical resection. However, with current postsurgical histologic margin analysis, one quarter of breast cancer patients undergo reexcision to achieve negative margins corresponding to decreased local recurrence and better outcomes. Therefore, a method with high resolution and specificity for intraoperative margin assessment is needed.Experimental Design: First, quantitative immunofluorescence staining of B7-H3 expression was assessed in four pathologic stages of breast cancer progression of the MMTV-PyMT transgenic murine model. Next, an antibody-dye contrast agent, B7-H3-ICG, was injected into mice prior to surgical resection of breast cancer. Anatomic ultrasound, spectroscopic photoacoustic (sPA), and fluorescence imaging were used to guide resection of mammary glands suspected of containing cancer. Resected tissues were processed for H&E staining and pathologic assessment and compared with sPA and fluorescence imaging signals.Results: Tissue containing DCIS (46.0 ± 4.8 a.u.) or invasive carcinoma (91.7 ± 21.4 a.u.) showed significantly higher (P < 0.05) B7-H3 expression than normal and hyperplastic tissues (1.3 ± 0.8 a.u.). During image-guided surgical resection, tissue pieces assessed as normal or hyperplastic (n = 17) showed lower average sPA (3.17 ± 0.48 a.u.) and fluorescence signal [6.83E07 ± 2.00E06 (p/s)/(µW/cm²)] than DCIS and invasive carcinoma tissue (n = 63) with an average sPA signal of 23.98 ± 4.88 a.u. and an average fluorescence signal of 7.56E07 ± 1.44E06 (p/s)/(µW/cm²) with AUCs of 0.93 [95% confidence interval (CI), 0.87-0.99] and 0.71 (95% CI, 0.57-0.85), respectively.Conclusions: It was demonstrated that sPA and fluorescence molecular imaging combined with B7-H3-ICG agent can assess the disease status of tissues with high diagnostic accuracy, intraoperatively, with high resolution, sensitivity, and specificity. Clin Cancer Res; 24(15); 3572-82. ©2018 AACR.

Thy1-Targeted Microbubbles for Ultrasound Molecular Imaging of Pancreatic Ductal Adenocarcinoma.

Purpose: To engineer a dual human and murine Thy1-binding single-chain-antibody ligand (Thy1-scFv) for contrast microbubble-enhanced ultrasound molecular imaging of pancreatic ductal adenocarcinoma (PDAC).Experimental Design: Thy1-scFv were engineered using yeast-surface-display techniques. Binding to soluble human and murine Thy1 and to Thy1-expressing cells was assessed by flow cytometry. Thy1-scFv was then attached to gas-filled microbubbles to create MBThy1-scFv Thy1 binding of MBThy1-scFv to Thy1-expressing cells was evaluated under flow shear stress conditions in flow-chamber experiments. MBscFv-scrambled and MBNon-targeted were used as negative controls. All microbubble types were tested in both orthotopic human PDAC xenografts and transgenic PDAC mice in vivoResults: Thy1-scFv had a KD of 3.4 ± 0.36 nmol/L for human and 9.2 ± 1.7 nmol/L for murine Thy1 and showed binding to both soluble and cellularly expressed Thy1. MBThy1-scFv was attached to Thy1 with high affinity compared with negative control microbubbles (P < 0.01) as assessed by flow cytometry. Similarly, flow-chamber studies showed significantly (P < 0.01) higher binding of MBThy1-scFv (3.0 ± 0.81 MB/cell) to Thy1-expressing cells than MBscFv-scrambled (0.57 ± 0.53) and MBNon-targeted (0.43 ± 0.53). In vivo ultrasound molecular imaging using MBThy1-scFv demonstrated significantly higher signal (P < 0.01) in both orthotopic (5.32 ± 1.59 a.u.) and transgenic PDAC (5.68 ± 2.5 a.u.) mice compared with chronic pancreatitis (0.84 ± 0.6 a.u.) and normal pancreas (0.67 ± 0.71 a.u.). Ex vivo immunofluorescence confirmed significantly (P < 0.01) increased Thy1 expression in PDAC compared with chronic pancreatitis and normal pancreas tissue.Conclusions: A dual human and murine Thy1-binding scFv was designed to generate contrast microbubbles to allow PDAC detection with ultrasound. Clin Cancer Res; 24(7); 1574-85. ©2018 AACR.

Anatomical Road Mapping Using CT and MR Enterography for Ultrasound Molecular Imaging of Small Bowel Inflammation in Swine.

OBJECTIVES: To evaluate the feasibility and time saving of fusing CT and MR enterography with ultrasound for ultrasound molecular imaging (USMI) of inflammation in an acute small bowel inflammation of swine. METHODS: Nine swine with ileitis were scanned with either CT (n = 3) or MR (n = 6) enterography. Imaging times to load CT/MR images onto a clinical ultrasound machine, fuse them to ultrasound with an anatomical landmark-based approach, and identify ileitis were compared to the imaging times without anatomical road mapping. Inflammation was then assessed by USMI using dual selectin-targeted (MBSelectin) and control (MBControl) contrast agents in diseased and healthy control bowel segments, followed by ex vivo histology. RESULTS: Cross-sectional image fusion with ultrasound was feasible with an alignment error of 13.9 ± 9.7 mm. Anatomical road mapping significantly reduced (P < 0.001) scanning times by 40%. Localising ileitis was achieved within 1.0 min. Subsequently performed USMI demonstrated significantly (P < 0.001) higher imaging signal using MBSelectin compared to MBControl and histology confirmed a significantly higher inflammation score (P = 0.006) and P- and E-selectin expression (P ≤ 0.02) in inflamed vs. healthy bowel. CONCLUSIONS: Fusion of CT and MR enterography data sets with ultrasound in real time is feasible and allows rapid anatomical localisation of ileitis for subsequent quantification of inflammation using USMI. KEY POINTS: • Real-time fusion of CT/MRI with ultrasound to localise ileitis is feasible. • Anatomical road mapping using CT/MRI significantly decreases the scanning time for USMI. • USMI allows quantification of inflammation in swine, verified with ex vivo histology.

Contrast-enhanced ultrasound of malignant liver lesions.

Contrast-enhanced ultrasound (CEUS) is a safe, relatively inexpensive, and widely available imaging technique using dedicated imaging ultrasound sequences and FDA-approved contrast microbubbles that allow detection and characterization of malignant focal liver lesions with high diagnostic accuracy. CEUS provides dynamic real-time imaging with high spatial and temporal capability, allowing for unique contributions to the already established protocols for diagnosing focal liver lesions using CT and MR imaging. In patients with lesions indeterminate on CT and MRI, CEUS is a helpful problem-solving complementary tool that improves patient management. Furthermore, CEUS assists guidance of liver biopsies and local treatment. Variations of CEUS such as DCE-US and ultrasound molecular imaging are emerging for quantitative monitoring of treatment effects and possible earlier detection of cancer. In this review, basic principles of CEUS techniques and ultrasound contrast agents along with a description of the enhancement patterns of malignant liver lesions are summarized. Also, a discussion of the role of CEUS for treatment guidance and monitoring, intraoperative CEUS, and an outlook on emerging applications is provided.

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.

Intra-Individual Comparison between 2-D Shear Wave Elastography (GE System) and Virtual Touch Tissue Quantification (Siemens System) in Grading Liver Fibrosis.

Ultrasound-based shear wave elastography (SWE) has recently gained substantial attention for non-invasive assessment of liver fibrosis. The purpose of this study was to perform an intra-individual comparison between 2-D shear wave elastography (2-D-SWE with a GE system) and Virtual Touch Tissue Quantification (VTTQ with a Siemens system) to assess whether these can be used interchangeably to grade fibrosis. Ninety-three patients (51 men, 42 women; mean age, 54 y) with liver disease of various etiologies (hepatitis B virus = 47, hepatitis C virus = 22; alcohol = 6, non-alcoholic steatohepatitis = 5, other = 13) were included. Using published system-specific shear wave speed cutoff values, liver fibrosis was classified into clinically non-significant (F0/F1) and significant (≥F2) fibrosis. Results indicated that intra-modality repeatability was excellent for both techniques (GE 2-D-SWE: intra-class correlation coefficient = 0.89 [0.84-0.93]; VTTQ: intra-class correlation coefficient = 0.90 [0.86-0.93]). Intra-modality classification agreement for fibrosis grading was good to excellent (GE 2-D-SWE: κ = 0.65, VTTQ: κ = 0.82). However, inter-modality agreement for fibrosis grading was only fair (κ = 0.31) using published system-specific shear wave speed cutoff values of fibrosis. In conclusion, although both GE 2-D-SWE and Siemens VTTQ exhibit good to excellent intra-modality repeatability, inter-modality agreement is only fair, suggesting that these should not be used interchangeably.

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.

Ultrasound-guided drug delivery in cancer.

Recent advancements in ultrasound and microbubble (USMB) mediated drug delivery technology has shown that this approach can improve spatially confined delivery of drugs and genes to target tissues while reducing systemic dose and toxicity. The mechanism behind enhanced delivery of therapeutics is sonoporation, the formation of openings in the vasculature, induced by ultrasound-triggered oscillations and destruction of microbubbles. In this review, progress and challenges of USMB mediated drug delivery are summarized, with special focus on cancer therapy.

Spectroscopic Photoacoustic Molecular Imaging of Breast Cancer using a B7-H3-targeted ICG Contrast Agent.

Purpose: Breast cancer imaging methods lack diagnostic accuracy, in particular for patients with dense breast tissue, and improved techniques are critically needed. The purpose of this study was to evaluate antibody-indocyanine green (ICG) conjugates, which undergo dynamic absorption spectrum shifts after cellular endocytosis and degradation, and spectroscopic photoacoustic (sPA) imaging to differentiate normal breast tissue from breast cancer by imaging B7-H3, a novel breast cancer associated molecular target. Methods: Quantitative immunohistochemical staining of endothelial and epithelial B7-H3 expression was assessed in 279 human breast tissue samples, including normal (n=53), benign lesions (11 subtypes, n=129), and breast cancers (4 subtypes, n=97). After absorption spectra of intracellular and degraded B7-H3-ICG and Isotype control-ICG (Iso-ICG) were characterized, sPA imaging in a transgenic murine breast cancer model (FVB/N-Tg(MMTVPyMT)634Mul) was performed and compared to imaging of control conditions [B7-H3-ICG in tumor negative animals (n=60), Iso-ICG (n=30), blocking B7-H3+B7-H3-ICG (n=20), and free ICG (n=20)] and validated with ex vivo histological analysis. Results: Immunostaining showed differential B7-H3 expression on both the endothelium and tumor epithelium in human breast cancer with an area under the ROC curve of 0.93 to differentiate breast cancer vs non-cancer. Combined in vitro/in vivo imaging showed that sPA allowed specific B7-H3-ICG detection down to the 13 nM concentration and differentiation from Iso-ICG. sPA molecular imaging of B7-H3-ICG showed a 3.01-fold (P<0.01) increase in molecular B7-H3-ICG signal in tumors compared to control conditions. Conclusions: B7-H3 is a promising target for both vascular and epithelial sPA imaging of breast cancer. Leveraging antibody-ICG contrast agents and their dynamic optical absorption spectra allows for highly specific sPA imaging of breast cancer.

Reduced dose CT with model-based iterative reconstruction compared to standard dose CT of the chest, abdomen, and pelvis in oncology patients: intra-individual comparison study on image quality and lesion conspicuity.

PURPOSE: To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging. METHODS: Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales. RESULTS: Median radiation dose reduction was 46% using RD CT (P < 0.01). Median image noise across all measured tissue types was lower (P < 0.01) in RD CT. Subjective image quality for RD CT was higher (P < 0.01) in regard to image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P < 0.01). Lesion conspicuity was subjectively better in RD CT (P < 0.01). Repeated target lesion size measurements were highly reproducible both on SD CT (ICC = 0.987) and RD CT (ICC = 0.97). CONCLUSIONS: RD CT imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.