John M. Hudson

Reprint of: Outcomes in patients with metastatic renal cell cancer treated with individualized sunitinib therapy: Correlation with dynamic microbubble ultrasound data and review of the literature.

BACKGROUND Increased sunitinib exposure (area under the curve) is associated with better outcome in metastatic renal cell cancer. Recommendations for dose modification do not take this into account. A treatment strategy, based on individual patient toxicity, was developed to maximize dose and minimize time without therapy for patients who could not tolerate the standard sunitinib schedule of 50mg given for 28 days with a 14-day break (50mg, 28/14). METHODS A single-center retrospective review was conducted on patients with metastatic renal cell cancer treated from October 2005 to March 2010. Dose/schedule modifications (DSM) were done to keep toxicity (hematological, fatigue, skin, and gastrointestinal) at ≤ grade 2. DSM-1 was 50mg, 14 days on/7 days off with individualized increases in days on treatment. DSM-2 was 50mg, 7 days on/7 days off with individualized increase in days on treatment. DSM-3 was 37.5mg with individualized 7-day breaks. DSM-4 was 25mg with individualized 7-day breaks. Multivariable analysis was performed for outcome as a function of patient and treatment variables. RESULTS Overall, 172 patients were included in the analysis. Most patients had clear cell histology (79.1%) with sunitinib given as a first-line therapy in 59%. The DSM-1 and 2 and DSM-3 and 4 groups had a progression-free survival (PFS) (10.9-11.9 mo) and overall survival (OS) (23.4-24.5 mo) that was significantly better than the PFS (5.3 mo; P<0.001) and OS (14.4 mo; P = 0.03 and 0.003) for the standard schedule (50mg, 28/14). DCE-US in a subset of patients showed that maximum antiangiogenic activity was achieved after 14 days on therapy. CONCLUSIONS Individualized sunitinib scheduling based on toxicity may improve PFS and OS. This hypothesis is supported by several other respective data that are reviewed. A confirmatory prospective trial is ongoing.

Dynamic contrast enhanced ultrasound for therapy monitoring

Quantitative imaging is a crucial component of the assessment of therapies that target the vasculature of angiogenic or inflamed tissue. Dynamic contrast-enhanced ultrasound (DCE-US) using microbubble contrast offers the advantages of being sensitive to perfusion, non-invasive, cost effective and well suited to repeated use at the bedside. Uniquely, it employs an agent that is truly intravascular. This papers reviews the principles and methodology of DCE-US, especially as applied to anti-angiogenic cancer therapies. Reproducibility is an important attribute of such a monitoring method: results are discussed. More recent technical advances in parametric and 3D DCE-US imaging are also summarised and illustrated.

The Lognormal Perfusion Model for Disruption Replenishment Measurements of Blood Flow: In Vivo Validation

Dynamic contrast enhanced ultrasound (DCE-US) is evolving as a promising tool to noninvasively quantify relative tissue perfusion in organs and solid tumours. Quantification using the method of disruption replenishment is best performed using a model that accurately describes the replenishment of microbubble contrast agents through the ultrasound imaging plane. In this study, the lognormal perfusion model was validated using an exposed in vivo rabbit kidney model. Compared against an implanted transit time flow meter, longitudinal relative flow measurement was (×3) less variable and correlated better when quantification was performed with the lognormal perfusion model (Spearman r = 0.90, 95% confidence interval [CI] = 0.05) vs. the prevailing mono-exponential model (Spearman r = 0.54, 95% CI = 0.18). Disruption-replenishment measurements using the lognormal perfusion model were reproducible in vivo to within 12%.

A novel, flat, electronically-steered phased array transducer for tissue ablation: preliminary results

Flat, λ/2-spaced phased arrays for therapeutic ultrasound were examined in silico and in vitro. All arrays were made by combining modules made of 64 square elements with 1.5 mm inter-element spacing along both major axes. The arrays were designed to accommodate integrated, co-aligned diagnostic transducers for targeting and monitoring. Six arrays of 1024 elements (16 modules) and four arrays of 6144 elements (96 modules) were modelled and compared according to metrics such as peak pressure amplitude, focal size, ability to be electronically-steered far off-axis and grating lobe amplitude. Two 1024 element prototypes were built and measured in vitro, producing over 100 W of acoustic power. In both cases, the simulation model of the pressure amplitude field was in good agreement with values measured by hydrophone. Using one of the arrays, it was shown that the peak pressure amplitude dropped by only 24% and 25% of the on-axis peak pressure amplitude when steered to the edge of the array (40 mm) at depths of 30 mm and 50 mm. For the 6144 element arrays studied in in silico only, similarly high steerability was found: even when steered 100 mm off-axis, the pressure amplitude decrease at the focus was less than 20%, while the maximum pressure grating lobe was only 20%. Thermal simulations indicate that the modules produce more than enough acoustic power to perform rapid ablations at physiologically relevant depths and steering angles. Arrays such as proposed and tested in this study have enormous potential: their high electronic steerability suggests that they will be able to perform ablations of large volumes without the need for any mechanical translation.

The prognostic and predictive value of vascular response parameters measured by dynamic contrast-enhanced-CT, -MRI and -US in patients with metastatic renal cell carcinoma receiving sunitinib

ObjectivesTo identify dynamic contrast-enhanced (DCE) imaging parameters from MRI, CT and US that are prognostic and predictive in patients with metastatic renal cell cancer (mRCC) receiving sunitinib.MethodsThirty-four patients were monitored by DCE imaging on day 0 and 14 of the first course of sunitinib treatment. Additional scans were performed with DCE-US only (day 7 or 28 and 2 weeks after the treatment break). Perfusion parameters that demonstrated a significant correlation (Spearman p < 0.05) with progression-free survival (PFS) and overall survival (OS) were investigated using Cox proportional hazard models/ratios (HR) and Kaplan-Meier survival analysis.ResultsA higher baseline and day 14 value for Ktrans (DCE-MRI) and a lower pre-treatment vascular heterogeneity (DCE-US) were significantly associated with a longer PFS (HR, 0.62, 0.37 and 5.5, respectively). A larger per cent decrease in blood volume on day 14 (DCE-US) predicted a longer OS (HR, 1.45). We did not find significant correlations between any of the DCE-CT parameters and PFS/OS, unless a cut-off analysis was used.ConclusionsDCE-MRI, -CT and ultrasound produce complementary parameters that reflect the prognosis of patients receiving sunitinib for mRCC. Blood volume measured by DCE-US was the only parameter whose change during early anti-angiogenic therapy predicted for OS and PFS.Key Points• DCE-CT, -MRI and ultrasound are complementary modalities for monitoring anti-angiogenic therapy.• The change in blood volume measured by DCE-US was predictive of OS/PFS.• Baseline vascular heterogeneity by DCE-US has the strongest prognostic value for PFS.

Impact of Acquisition Method and Region of Interest Placement on Inter-observer Agreement and Measurement of Tumor Response to Targeted Therapy Using Dynamic Contrast-Enhanced Ultrasound.

This study evaluated the impact of different acquisition methods, user-directed region of interest placement and post-processing steps on the quantification of dynamic contrast-enhanced ultrasound measurements of blood volume in 29 patients with renal cancer, pre- and post-treatment. Specifically, we compared tumor quantification using multiple planes versus a single plane, breathhold versus free breathing and large region of interest versus a region targeting the area of highest vascularity. Performance was evaluated using area under the receiver operating characteristic curves to identify the method that best predicts progression-free survival. The intra-class correlation coefficient was also used to investigate how the same parameters affect inter-observer agreement. Of the different methods used to quantify blood volume in this study, the combination that had the highest level of inter-observer agreement (intra-class correlation coefficient = 0.8-0.97) and was the best predictor of progression-free survival was the change in blood volume measured (area under receiver operating characteristic curve = 0.77, p = 0.04) by a multiplane average, acquired during quiet breathing, quantified using a region of interest that encompassed the entire tumor.

P2B-5 Quantification of Flow Using Ultrasound and Microbubbles: A Disruption Replenishment Model Based on Physical Principles

With contrast agents, ultrasound can make hemodynamic measurements in microvascular networks with the technique of disruption replenishment. In its current form, the method suffers from poor reproducibility and accuracy, largely due to the inappropriate use of a mono-exponential model for fitting the time replenishment data. In reality, the time-intensity replenishment curve reflects the hemodynamics and morphology of the vascular system being measured, the ultrasound field distribution and microbubble properties. Here, we introduce an analytic replenishment model that attempts to account for these parameters and compare its performance to the established model in a flow phantom. Specifically, the proposed model 1) incorporates the hemodynamic properties of the flow system (velocity distribution and vascular cross section), 2) includes the elevation and axial plane pressure distributions and 3) accounts for the distinct high and low MI disruption and detection boundaries. Compared to the currently accepted mono-exponential model, the presented model shows better agreement in both the quality of the fit and estimation of velocity (~5-10% vs. 20% error) for the same flow and acoustic conditions