3D Dynamic Contrast-enhanced Ultrasound Research Articles

Can 3D Multiparametric Ultrasound Imaging Predict Prostate Biopsy Outcome?

ObjectivesTo assess the value of 3D multiparametric ultrasound imaging, combining hemodynamic and tissue stiffness quantifications by machine learning, for the prediction of prostate biopsy outcomes. MethodsAfter signing informed consent, 54 biopsy-naïve patients underwent a 3D dynamic contrast-enhanced ultrasound (DCE-US) recording, a multi-plane 2D shear-wave elastography (SWE) scan with manual sweeping from base to apex of the prostate, and received 12-core systematic biopsies (SBx). 3D maps of 18 hemodynamic parameters were extracted from the 3D DCE-US quantification and a 3D SWE elasticity map was reconstructed based on the multi-plane 2D SWE acquisitions. Subsequently, all the 3D maps were segmented and subdivided into 12 regions corresponding to the SBx locations. Per region, the set of 19 computed parameters was further extended by derivation of eight radiomic features per parameter. Based on this feature set, a multiparametric ultrasound approach was implemented using five different classifiers together with a sequential floating forward selection method and hyperparameter tuning. The classification accuracy with respect to the biopsy reference was assessed by a group-k-fold cross-validation procedure, and the performance was evaluated by the Area Under the Receiver Operating Characteristics Curve (AUC). ResultsOf the 54 patients, 20 were found with clinically significant prostate cancer (csPCa) based on SBx. The 18 hemodynamic parameters showed mean AUC values varying from 0.63 to 0.75, and SWE elasticity showed an AUC of 0.66. The multiparametric approach using radiomic features derived from hemodynamic parameters only produced an AUC of 0.81, while the combination of hemodynamic and tissue-stiffness quantifications yielded a significantly improved AUC of 0.85 for csPCa detection (p-value < 0.05) using the Gradient Boosting classifier. ConclusionsOur results suggest 3D multiparametric ultrasound imaging combining hemodynamic and tissue-stiffness features to represent a promising diagnostic tool for biopsy outcome prediction, aiding in csPCa localization.

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

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. This work introduces a novel MC algorithm for 3D DCE-US and assesses its efficacy when handling clinical data sets. 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. 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. Overall, results suggest decreases in 3D DCE-US motion after applying the proposed algorithm.

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.

Blood flow patterns estimation in the left ventricle with low-rate 2D and 3D dynamic contrast-enhanced ultrasound

Background and Objective: Left ventricle (LV) dysfunction always occurs at early heart-failure stages, producing variations in the LV flow patterns. Cardiac diagnostics may therefore benefit from flow-pattern analysis. Several visualization tools have been proposed that require ultrafast ultrasound acquisitions. However, ultrafast ultrasound is not standard in clinical scanners. Meanwhile techniques that can handle low frame rates are still lacking. As a result, the clinical translation of these techniques remains limited, especially for 3D acquisitions where the volume rates are intrinsically low.Methods: To overcome these limitations, we propose a novel technique for the estimation of LV blood velocity and relative-pressure fields from dynamic contrast-enhanced ultrasound (DCE-US) at low frame rates. Different from other methods, our method is based on the time-delays between time-intensity curves measured at neighbor pixels in the DCE-US loops. Using Navier-Stokes equation, we regularize the obtained velocity fields and derive relative-pressure estimates. Blood flow patterns were characterized with regard to their vorticity, relative-pressure changes (dp/dt) in the LV outflow tract, and viscous energy loss, as these reflect the ejection efficiency.Results: We evaluated the proposed method on 18 patients (9 responders and 9 non-responders) who underwent cardiac resynchronization therapy (CRT). After CRT, the responder group evidenced a significant (p<0.05) increase in vorticity and peak dp/dt, and a non-significant decrease in viscous energy loss. No significant difference was found in the non-responder group. Relative feature variation before and after CRT evidenced a significant difference (p<0.05) between responders and non-responders for vorticity and peak dp/dt. Finally, the method feasibility is also shown with 3D DCE-US.Conclusions: Using the proposed method, adequate visualization and quantification of blood flow patterns are successfully enabled based on low-rate DCE-US of the LV, facilitating the clinical adoption of the method using standard ultrasound scanners. The clinical value of the method in the context of CRT is also shown.

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.

Assessment of angiogenesis in rabbit orthotropic liver tumors using three-dimensional dynamic contrast-enhanced ultrasound compared with two-dimensional DCE-US

To evaluate quantitative three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) in the assessment of tumor angiogenesis using an orthotropic liver tumor model. Nine New Zealand white rabbits with liver orthotropic VX2 tumors were established and imaged by two-dimensional (2D) and 3D DCE-US after SonoVue® bolus injections. The intraclass correlation coefficients of perfusion parameters, including peak intensity (PI), mean transit time, time to peak, and area under the curve, were calculated based on time-intensity curve. The percentage area of microvascular (PAMV) and the expression of vascular endothelial growth factor (VEGF) were both evaluated by immunohistochemical analysis and weighted by the tumor activity area ratio. Correlations between quantitative and histologic parameters were analyzed. The reproducibility of 3D DCE-US quantitative parameters was excellent (ICC 0.91-0.99); but only PI showed high reproducibility (ICC 0.97) in 2D. None of the parameters of quantitative 2D DCE-US were significantly correlated with weighted PAMV or VEGF. For 3D DCE-US, there was a positive correlation between PI and weighted PAMV (r = 0.74, P = 0.04) as well as VEGF (r = 0.79, P = 0.02). Quantitative parameters of 3D DCE-US show feasibility, higher reproducibility and accuracy for the assessment of tumor angiogenesis using an orthotropic liver tumor model compared with 2D DCE-US.

PT150 - 3D multiparametric contrast ultrasound predicts the histopathological outcome of systematic biopsy

Introduction & Objectives: A non-targeted 12-core systematic biopsy (SBx) procedure guided by transrectal ultrasound (TRUS) is currently guideline-recommended for prostate cancer (PCa) diagnosis. Despite the risk of complications, underdiagnosis, and overtreatment associated with SBx, until now image-based targeted biopsy has not proven sufficiently accurate to replace SBx. Three-dimensional (3D) dynamic contrastenhanced ultrasound (DCE-US) was recently introduced for prostate imaging, permitting to image the entire gland with a single bolus injection. Quantitative two-dimensional DCE-US has already shown promising for PCa localization. Here, we present a new method for PCa localization by multiparametric analysis of 3D DCE-US.

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 10mg/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 1day 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.

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

To evaluate whether three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) imaging allows assessing early changes in tumor perfusion following antiangiogenic treatment, and whether these changes could predict treatment response in two animal models of colon cancer that simulate clinical responders and nonresponders. Clinically responding (n=20; LS174T) and nonresponding (n=20; CT26) colon cancer xenografts were established in 40 mice. Ten mice from each group received either antiangiogenic therapy (anti-VEGF blocking with bevacizumab, 10mg/kg) or saline as controls and were imaged longitudinally with 3D DCE-US at baseline (day 0) and days 1, 3, 7, and 10 following treatment. The change in three perfusion parameters (peak enhancement [PE], area under curve [AUC], time to peak [TTP]) relative to baseline was compared to the percentage area of neovasculature on ex vivo quantitative immunofluorescence and with response at day 10 assessed by tumor volume. PE and AUC significantly decreased 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 on immunofluorescence significantly decreased in treated vs. control LS174T tumors (P<0.001), but not in treated vs. control CT26 tumors (P=0.796). Early decrease in both PE and AUC by 45-50% were 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. 3D DCE-US provides clinically relevant information on the variability of tumor response to antiangiogenic therapy and could eventually serve as a biomarker for predicting treatment outcomes.