Power Doppler Quantification in Assessing Gestational Trophoblastic Neoplasia.

PURPOSE: The FIGO score cannot accurately stratify low-risk gestational trophoblastic neoplasia (GTN) patients who develop chemoresistance to single agent methotrexate chemotherapy. Tumour vascularisation is a key risk factor and its quantification may provide non-invasive way of complementing risk assessment. MATERIALS AND METHODS: 187 FIGO-staged, low-risk GTN patients were prospectively recruited. Power Doppler ultrasound was analysed using a quantification program. Four diagnostic indicators were obtained comprising the number of colour pixels (NCP), mean dB, power Doppler quantification (PDQ), and percentage of colour pixels (%CP). Each indicator performance was assessed to determine if they could distinguish the subset of low-risk patients who became chemoresistant. RESULTS: There were 111 non-resistant and 76 resistant patients. NCP performed best at distinguishing these two groups where the non-resistant group had an average 3435 (±â€Š2060) pixels and the resistant group 6151 (±â€Š3192) pixels (p < 0.001). PDQ and %CP showed significant differences (p < 0.001) but had poorer performance (area under ROC curves were 72 % and 67 % respectively compared with 75 % for NCP). The mean dB index was not significantly different (p = 0.133). CONCLUSION: Power Doppler ultrasound quantification shows potential for non-invasive assessment of tumour vascularity and can distinguish low-risk GTN patients who become chemoresistant from those who have an uncomplicated course with first line treatment.

Monitoring Dual VEGF Inhibition in Human Pancreatic Tumor Xenografts With Dynamic Contrast-Enhanced Ultrasound.

BACKGROUND: Association of drugs acting against different antiangiogenic mechanisms may increase therapeutic effect and reduce resistance. Noninvasive monitoring of changes in the antiangiogenic response of individual tumors could guide selection and administration of drug combinations. Noninvasive detection of early therapeutic response during dual, vertical targeting of the vascular endothelial growth factor pathway was investigated in an ectopic subcutaneous xenograft model for human pancreatic tumor. METHODS: Dynamic contrast-enhanced ultrasound 12 MHz was used to monitor tumor-bearing Naval Medical Research Institute mice beginning 15 days after tumor implantation. Mice received therapy from 15 to 29 days with sorafenib (N = 9), ziv-aflibercept (N = 11), combined antiangiogenic agents (N = 11), and placebo control (N = 14). Sorafenib (BAY 43-9006; Nexavar), a multikinase inhibitor acting on Raf kinase and receptor tyrosine kinases-including vascular endothelial growth factor receptors 2 and 3-was administered daily (60 mg/kg, per os). Ziv-aflibercept (ZALTRAP), a high-affinity ligand trap blocking the activity of vascular endothelial growth factor A, vascular endothelial growth factor B, and placental growth factor was administered twice per week (40 mg/kg, intraperitoneally). RESULTS: Functional evaluation with dynamic contrast-enhanced ultrasound indicated stable tumor vascularization for the control group while revealing significant and sustained reduction after 1 day of therapy in the combined group (P = .007). There was no survival benefit or penalty due to drug combination. The functional progression-free survival assessed with dynamic contrast-enhanced ultrasound was significantly higher for the 3 treated groups; whereas, the progression-free survival based on tumor size did not discriminate therapeutic effect. CONCLUSIONS: Dynamic contrast-enhanced ultrasound, therefore, presents strong potential to monitor microvascular modifications during antiangiogenic therapy, a key role to monitoring antiangiogenic combining therapy to adapt dose range drug.

3-D Longitudinal Imaging of Tumor Angiogenesis in Mice in Vivo Using Ultrafast Doppler Tomography.

Angiogenesis, the formation of new vessels, is one of the key mechanisms in tumor development and an appealing target for therapy. Non-invasive, high-resolution, high-sensitivity, quantitative 3-D imaging techniques are required to correctly depict tumor heterogeneous vasculature over time. Ultrafast Doppler was recently introduced and provides an unprecedented combination of resolution, penetration depth and sensitivity without requiring any contrast agents. The technique was further extended to three dimensions with ultrafast Doppler tomography (UFD-T). In this work, UFD-T was applied to the monitoring of tumor angiogenesis in vivo, providing structural and functional information at different stages of development. UFD-T volume renderings revealed that our murine model's vasculature stems from pre-existing vessels and sprouts to perfuse the whole volume as the tumor grows until a critical size is reached. Then, as the network becomes insufficient, the tumor core is no longer irrigated because the vasculature is concentrated mainly in the periphery. In addition to spatial distribution and growth patterns, UFD-T allowed a quantitative analysis of vessel size and length, revealing that the diameter distribution of vessels remained relatively constant throughout tumor growth. The network is dominated by small vessels at all stages of tumor development, with more than 74% of the vessels less than 200 µm in diameter. This study also found that cumulative vessel length is more closely related to tumor radius than volume, indicating that the vascularization becomes insufficient when a critical mass is reached. UFD-T was also compared with dynamic contrast-enhanced ultrasound and found to provide complementary information regarding the link between structure and perfusion. In conclusion, UFD-T is capable of in vivo quantitative assessment of the development of tumor vasculature (vessels with blood speed >1 mm/s [sensitivity limit] assessed with a resolution limit of 80 µm) in 3 dimensions. The technique has very interesting potential as a tool for treatment monitoring, response assessment and treatment planning for optimal drug efficiency.

Reproducibility of Contrast-Enhanced Ultrasound in Mice with Controlled Injection.

PURPOSE: Sensitivity of contrast-enhanced ultrasound (CEUS) to microvascular flow modifications can be limited by intra-injection variability (injected dose, rate, volume). PROCEDURES: To evaluate the effect of injection variability on microvascular flow evaluation, CEUS was compared between controlled and manual injections where enhancement was assessed in vitro within a flow phantom, in normal murine kidney (N = 12) and in murine ectopic tumors (N = 10). RESULTS: For both in vitro and in vivo measurements in the renal cortex, controlled injections significantly improved reproducibility of functional parameter estimation. Their coefficient of variation (CV) in the renal cortex ranged from 4 to 19 % for controlled injection vs. 5 to 43 % for manual injections. For measurements in tumors, controlled injection only decreased the CV significantly for the mean transit time. In tumors, multiple injections of contrast agent with a 15-min delay between each were shown to strongly modify contrast uptake by facilitating penetration of microbubbles. CONCLUSION: Improved reproducibility of CEUS assessments in murine models should provide more robust quantification of flow parameters and more sensitive evaluation of tumor modifications in therapeutic models.

Automatic motion estimation using flow parameters for dynamic contrast-enhanced ultrasound.

Dynamic contrast-enhanced ultrasound (DCE-US) sequences are subject to motion which can disturb functional flow quantification. This can make estimated parameters more variable or unreliable. Methods that compensate for motion are therefore desirable. The most commonly used motion correction techniques in DCE-US register the images in the sequence with respect to a user-selected reference image. However, this image may not include all features that are representative of the whole sequence. Moreover, image-based registration neglects pertinent, functional-flow information contained in the DCE-US sequence. An operator-free method is proposed that combines the motion estimation and flow-parameter quantification (M/Q method) in a single mathematical framework. This method is based on a realistic multiplicative model of the DCE-US noise. By computing likelihood in this model, motion and flow parameters are both estimated iteratively. First, the maximization is accomplished by estimating functional and motion parameters. Then, a final registration based on a non-parametric temporal smoothing of the sequence is performed. This method is compared to a conventional (mutual information) registration method where all the images of the sequence are registered with respect to a reference image chosen by an expert. The two methods are evaluated on simulated sequences and DCE-US sequences acquired in patients (N = 15). The M/Q method demonstrates significantly (p < 0.05) lower Dice coefficients and Hausdorff distance than the conventional method on the simulated data sets. On the in vivo sequences analysed, the M/Q methods outperformed the conventional method in terms of mean Dice and Hausdorff distance on 80% of the sequences, and in terms of standard deviation of Dice and Hausdorff distance on 87% of the sequences.

Dual-mode registration of dynamic contrast-enhanced ultrasound combining tissue and contrast sequences.

This study proposes a new method for automatic, iterative image registration in the context of dynamic contrast-enhanced ultrasound (DCE-US) imaging. By constructing a cost function of image registration using a combination of the tissue and contrast-microbubble responses, this new method, referred to as dual-mode registration, performs alignment based on both tissue and vascular structures. Data from five focal liver lesions (FLLs) were used for the evaluation. Automatic registration based on the dual-mode registration technique and tissue-mode registration obtained using the linear response image sequence alone were compared to manual alignment of the sequence by an expert. Comparison of the maximum distance between the transformations applied by the automatic registration techniques and those from expert manual registration reference showed that the dual-mode registration provided better precision than the tissue-mode registration for all cases. The reduction of maximum distance ranged from 0.25 to 9.3mm. Dual-mode registration is also significantly better than tissue-mode registration for the five sequences with p-values lower than 0.03. The improved sequence alignment is also demonstrated visually by comparison of images from the sequences and the video playbacks of the motion-corrected sequences. This new registration technique better maintains a selected region of interest (ROI) within a fixed position of the image plane throughout the DCE-US sequence. This should reduce motion-related variability of the echo-power estimations and, thus, contribute to more robust perfusion quantification with DCE-US.

A multiplicative model for improving microvascular flow estimation in dynamic contrast-enhanced ultrasound (DCE-US): theory and experimental validation.

Perfusion parameter estimation from dynamic contrast-enhanced ultrasound (DCE-US) data relies on fitting parametric models of flow to curves describing linear echo power as a function of time. The least squares criterion is generally used to fit these models to data. This criterion is optimal in the sense of maximum likelihood under the assumption of an additive white Gaussian noise. In the current work, it is demonstrated that this assumption is not held for DCEUS. A better-adapted maximum likelihood criterion based on a multiplicative model is proposed. It is tested on simulated bolus perfusion data and on 11 sequences acquired in vivo during bolus perfusion of contrast agent in the cortex of healthy murine kidney, an area where the perfusion is expected to be approximately homogeneous. Results on simulated data show a significant improvement (p < 0.05) of the precision and the accuracy for the estimations of perfusion parameters time to peak (TTP), wash-in rate (WiR), and mean transit time (MTT). On the 11 in vivo sequences, the new method leads to a significant reduction (p < 0.05) in the variation of parametric maps for 9 sequences for TTP and 10 sequences for WiR and MTT. The mean percent decreases of the coefficient of variation are 40%, 25%, and 59% for TTP, WiR, and MTT, respectively. This method should contribute to a more robust and accurate estimation of perfusion parameters and an improved resolution of parametric imaging.