New calibration setup for quantitative DCE-US imaging protocol: Toward standardization.

BACKGROUND: The DCE-US (Dynamic Contrast-Enhanced Ultrasonography) imaging protocol predicts the vascular modifications compared with Response Evaluation Criteria in Solid Tumors (RECIST) based mainly on morphological changes. A quantitative biomarker has been validated through the DCE-US multi-centric study for early monitoring of the efficiency of anti-angiogenic cancer treatments. In this context, the question of transposing the use of this biomarker to other types of ultrasound scanners, probes and settings has arisen to maintain the follow-up of patients under anti-angiogenic treatments. As a consequence, radiologists encounter standardization issues between the different generations of ultrasound scanners to perform quantitative imaging protocols. PURPOSE: The aim of this study was to develop a new calibration setup to transpose the DCE-US imaging protocol to the new generation of ultrasound scanners using both abdominal and linear probes. METHODS: This calibration method has been designed to be easily reproducible and optimized, reducing the time required and cost incurred. It is based on an original set-up that includes using a concentration splitter to measure the variation of the harmonic signal intensity, obtained from the Area Under the time-intensity Curve (AUC) as a function of various contrast-agent concentrations. The splitter provided four different concentrations simultaneously ranging from 12.5% to 100% of the initial concentration of the SonoVue contrast agent (Bracco Imaging S.p.A., Milan, Italy), therefore, measuring four AUCs in a single injection. The plot of the AUC as a function of the four contrast agent concentrations represents the intensity variation of the harmonic signal: the slope being the calibration parameter. The standardization through this method implied that both generations of ultrasound scanners had to have the same slopes to be considered as calibrated. This method was tested on two ultrasound scanners from the same manufacturer (Aplio500, Aplioi900, Canon Medical Systems, Tokyo, Japan). The Aplio500 used the settings defined by the initial multicenter DCE-US study. The Mechanical Index (MI) and the Color Gain (CG) of the Aplioi900 have been adjusted to match those of the Aplio500. The reliability of the new setup was evaluated in terms of measurement repeatability, and reproducibility with the agreement between the measurements obtained once the two ultrasound scanners were calibrated. RESULTS: The new setup provided excellent repeatability measurements with a value of 96.8%. Once the two ultrasound scanners have been calibrated for both types of probes, the reproducibility was excellent with the agreement between their respective quantitative measurement was at the lowest 95.4% and at the best 98.8%. The settings of the Aplioi900 (Canon Medical Systems) were adjusted to match those of the Aplio500 (Canon Medical Systems) and these validated settings were for the abdominal probe: MI = 0.13 and CG = 34 dB; and for the linear probe: MI = 0.10 and CG = 38 dB. CONCLUSION: This new calibration setup provided reliable measurements and enabled the rapid transfer and the use of the DCE-US imaging protocol on new ultrasound scanners, thus permitting a continuation of the therapeutic evaluation of patients through quantitative imaging.

Influence of Different Measurement Methods of Arterial Input Function on Quantitative Dynamic Contrast-Enhanced MRI Parameters in Head and Neck Cancer.

BACKGROUND: Head and neck cancer (HNC) is the sixth most prevalent cancer worldwide. Dynamic contrast-enhanced MRI (DCE-MRI) helps in diagnosis and prognosis. Quantitative DCE-MRI requires an arterial input function (AIF), which affects the values of pharmacokinetic parameters (PKP). PURPOSE: To evaluate influence of four individual AIF measurement methods on quantitative DCE-MRI parameters values (Ktrans , ve , kep , and vp ), for HNC and muscle. STUDY TYPE: Prospective. POPULATION: A total of 34 HNC patients (23 males, 11 females, age range 24-91) FIELD STRENGTH/SEQUENCE: A 3 T; 3D SPGR gradient echo sequence with partial saturation of inflowing spins. ASSESSMENT: Four AIF methods were applied: automatic AIF (AIFa) with up to 50 voxels selected from the whole FOV, manual AIF (AIFm) with four voxels selected from the internal carotid artery, both conditions without (Mc-) or with (Mc+) motion correction. Comparison endpoints were peak AIF values, PKP values in tumor and muscle, and tumor/muscle PKP ratios. STATISTICAL TESTS: Nonparametric Friedman test for multiple comparisons. Nonparametric Wilcoxon test, without and with Benjamini Hochberg correction, for pairwise comparison of AIF peak values and PKP values for tumor, muscle and tumor/muscle ratio, P value ≤ 0.05 was considered statistically significant. RESULTS: Peak AIF values differed significantly for all AIF methods, with mean AIFmMc+ peaks being up to 66.4% higher than those for AIFaMc+. Almost all PKP values were significantly higher for AIFa in both, tumor and muscle, up to 76% for mean Ktrans values. Motion correction effect was smaller. Considering tumor/muscle parameter ratios, most differences were not significant (0.068 ≤ Wilcoxon P value ≤ 0.8). DATA CONCLUSION: We observed important differences in PKP values when using either AIFa or AIFm, consequently choice of a standardized AIF method is mandatory for DCE-MRI on HNC. From the study findings, AIFm and inflow compensation are recommended. The use of the tumor/muscle PKP ratio should be of interest for multicenter studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

New method for quantification of intratumoral heterogeneity: a feasibility study on Ktrans maps from preclinical DCE-MRI.

OBJECT: To develop new imaging biomarkers of therapeutic efficacy through the quantification of intratumoral microvascular heterogeneity. MATERIALS AND METHODS: The described method was a combination of non-supervised clustering and extraction of intratumoral complexity features (ICF): number of non-connected objects, volume fraction. It was applied to a set of 3D DCE-MRI Ktrans maps acquired previously on tumor bearing mice prior to and on day 4 of anti-angiogenic treatment. Evolutions of ICF were compared to conventional summary statistics (CSS) and to heterogeneity related whole tumor texture features (TF) on treated (n = 9) and control (n = 6) mice. RESULTS: Computed optimal number of clusters per tumor was 4. Several intratumoral features extracted from the clusters were able to monitor a therapy effect. Whereas no feature significantly changed for the control group, 6 features significantly changed for the treated group (4 ICF, 2 CSS). Among these, 5 also significantly differentiated the two groups (3 ICF, 2 CSS). TF failed in demonstrating differences within and between the two groups. DISCUSSION: ICF are potential imaging biomarkers for anti-angiogenic therapy assessment. The presented method may be expected to have advantages with respect to texture analysis-based methods regarding interpretability of results and setup of standardized image analysis protocols.

Methodological Study to Investigate the Potential of Ultrasound-Based Elastography and Texture as Biomarkers to Monitor Liver Tumors.

AIMS AND OBJECTIVES: In order to evaluate the responses of hepatic lesions to treatment in terms of tissue stiffness and heterogeneity, this work investigated the robustness of 2D shear-wave elastography (2D SWE) stiffness measurements and texture analyses in vitro and in vivo in terms of repeatability and variability. METHODS AND MATERIALS: A multioperator (n = 5) study was performed with an ultrasonic elastography device on two sets of phantoms. For the first set of phantoms, 10 measurements for each of the eight inclusions were performed by each observer, whereas the second set of phantoms was used to evaluate the influence of depth on the stiffness measurements. Variability of the stiffness measurements was evaluated in vivo on 10 healthy livers, with 10 measurements for each hepatic segment. Texture analyses were performed in B-mode, obtaining elastography images for every hepatic segment. RESULTS: Stiffness measurements were influenced by depth, particularly when exceeding 7 cm. In vivo measurements demonstrated that measurements of segments I, VII, and VIII were less reliable, mainly due to their deeper locations. The protocols used were more flexible in terms of acquisition setup and probe placement than those currently used with Fibroscan®. For texture analysis on the B-mode images, 12 features showed low variability regardless of the evaluated hepatic segment. On elastogram, only two features showed low variability, but not in every segment. CONCLUSION: We demonstrated the robustness of two methodologies for the quantification of liver stiffness and heterogeneity. Further clinical studies should evaluate whether these techniques can assess tumor responses to treatment and, therefore, have the potential to be used as imaging biomarkers.

Clarification of Definitions of Hyperprogressive Disease During Immunotherapy for Non-Small Cell Lung Cancer.

Importance: Hyperprogressive disease (HPD) is an aggressive pattern of progression reported for patients treated with programmed cell death 1 (PD-1)/programmed cell death 1 ligand (PD-L1) inhibitors as a single agent in several studies. However, the use of different definitions of HPD introduces the risk of describing different tumoral behaviors. Objective: To assess the accuracy of each HPD definition to identify the frequency of HPD and the association with poorer outcomes of immune-checkpoint inhibitor (ICI) treatment in patients with advanced non-small cell lung cancer (NSCLC) and to provide an optimized and homogenized definition based on all previous criteria for identifying HPD. Design, Setting, and Participants: This retrospective cohort study included 406 patients with advanced NSCLC treated with PD-1/PD-L1 inhibitors from November 1, 2012, to April 5, 2017, in 8 French institutions. Measurable lesions were defined using the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria on at least 2 computed tomographic scans before the initiation of ICI therapy and 1 computed tomographic scan during treatment. Data were analyzed from November 1, 2012, to August 1, 2019. Exposures: Advanced NSCLC and treatment with PD-1/PD-L1 inhibitors. Main Outcomes and Measures: Association of the definition with the related incidence and the HPD subset constitution and the association between each HPD definition and overall survival. All dynamic indexes used in the previous proposed definitions, such as the tumor growth rate (TGR) or tumor growth kinetics (TGK), were calculated before and during treatment. Results: Among the 406 patients with NSCLC included in the analysis (259 male [63.8%]; median age at start of ICI treatment, 64 [range, 30-91] years), the different definitions resulted in incidences of the HPD phenomenon varying from 5.4% (n = 22; definition based on a progression pace >2-fold and a time to treatment failure of <2 months) to 18.5% (n = 75; definition based on the TGR ratio). The concordance between these different definitions (using the Jaccard similarity index) varied from 33.3% to 69.3%. For every definition, HPD was associated with poorer survival (range of median overall survival, 3.4 [95% CI, 1.9-8.4] to 6.0 [95% CI, 3.7-9.4] months). The difference between TGR before and during therapy (ΔTGR) was the most correlated with poor overall survival with an initial plateau for a larger number of patients and a slower increase, and it had the highest ability to distinguish patients with HPD from those with progressive disease not classified as HPD. In addition, an optimal threshold of ΔTGR of greater than 100 was identified for this distinction. Conclusions and Relevance: The findings of this retrospective cohort study of patients with NSCLC suggest that the previous 5 definitions of HPD were not associated with the same tumor behavior. A new definition, based on ΔTGR of greater than 100, appeared to be associated with the characteristics expected with HPD (increase of the tumor kinetics and poor survival). Additional studies on larger groups of patients are necessary to confirm the accuracy and validate this proposed definition.

Ultrasound Molecular Imaging of Renal Cell Carcinoma: VEGFR targeted therapy monitored with VEGFR1 and FSHR targeted microbubbles.

Recent treatment developments for metastatic renal cell carcinoma offer combinations of immunotherapies or immunotherapy associated with tyrosine kinase inhibitors (TKI). There is currently no argument to choose one solution or another. Easy-to-use markers to assess longitudinal responses to TKI are necessary to determine when to switch to immunotherapies. These new markers will enable an earlier adaptation of therapeutic strategy in order to prevent tumor development, unnecessary toxicity and financial costs. This study evaluates the potential of ultrasound molecular imaging to track the response to sunitinib in a clear cell renal carcinoma model (ccRCC). We used a patient-derived xenograft model for this imaging study. Mice harboring human ccRCC were randomized for sunitinib treatment vs. control. The tumors were imaged at days 0, 7, 14 and 28 with ultrasound molecular imaging. Signal enhancement was quantified and compared between the two groups after injections of non-targeted microbubbles and microbubbles targeting VEGFR1 and FSHR. The tumor growth of the sunitinib group was significantly slower. There was a significantly lower expression of both VEGFR-1 and FSHR molecular ultrasound imaging signals in the sunitinib group at all times of treatment (Days 7, 14 and 28). These results confirm the study hypothesis. There was no significant difference between the 2 groups for the non-targeted microbubble ultrasound signal. This study demonstrated for the first time the potential of VEGFR1 and FSHR, by ultrasound-based molecular imaging, to follow-up the longitudinal response to sunitinib in ccRCC. These results should trigger developments for clinical applications.

CT Texture Analysis Challenges: Influence of Acquisition and Reconstruction Parameters: A Comprehensive Review.

Texture analysis in medical imaging is a promising tool that is designed to improve the characterization of abnormal images from patients, to ultimately serve as a predictive or prognostic biomarker. However, the nature of image acquisition itself implies variability in each pixel/voxel value that could jeopardize the usefulness of texture analysis in the medical field. In this review, a search was performed to identify current published data for computed tomography (CT) texture reproducibility and variability. On the basis of this analysis, the critical steps were identified with a view of using texture analysis as a reliable tool in medical imaging. The need to specify the CT scanners used and the associated parameters in published studies is highlighted. Harmonizing acquisition parameters between studies is a crucial step for future texture analysis.

Influence of Magnetic Field Strength on Magnetic Resonance Imaging Radiomics Features in Brain Imaging, an In Vitro and In Vivo Study.

BACKGROUND: The development and clinical adoption of quantitative imaging biomarkers (radiomics) has established the need for the identification of parameters altering radiomics reproducibility. The aim of this study was to assess the impact of magnetic field strength on magnetic resonance imaging (MRI) radiomics features in neuroradiology clinical practice. METHODS: T1 3D SPGR sequence was acquired on two phantoms and 10 healthy volunteers with two clinical MR devices from the same manufacturer using two different magnetic fields (1.5 and 3T). Phantoms varied in terms of gadolinium concentrations and textural heterogeneity. 27 regions of interest were segmented (phantom: 21, volunteers: 6) using the LIFEX software. 34 features were analyzed. RESULTS: In the phantom dataset, 10 (67%) out of 15 radiomics features were significantly different when measured at 1.5T or 3T (student's t-test, p < 0.05). Gray levels resampling, and pixel size also influence part of texture features. These findings were validated in healthy volunteers. CONCLUSIONS: According to daily used protocols for clinical examinations, radiomic features extracted on 1.5T should not be used interchangeably with 3T when evaluating texture features. Such confounding factor should be adjusted when adapting the results of a study to a different platform, or when designing a multicentric trial.

Reduced-order modeling of hemodynamics across macroscopic through mesoscopic circulation scales.

We propose a hemodynamic reduced-order model bridging macroscopic and mesoscopic blood flow circulation scales from arteries to capillaries. In silico tree-like vascular geometries, mathematically described by graphs, are synthetically generated by means of stochastic growth algorithms constrained by statistical morphological and topological principles. Scale-specific pruning gradation of the tree is then proposed in order to fit computational budget requirement. Different compliant structural models with respect to pressure loads are used depending on vessel walls thicknesses and structures, which vary considerably from macroscopic to mesoscopic circulation scales. Nonlinear rheological properties of blood are also included, and microcirculation network responses are computed for different rheologies. Numerical results are in very good agreement with available experimental measurements. The computational model captures the dynamic transition between large- to small-scale flow pulsatility speeds and magnitudes and wall shear stresses, which have wide-ranging physiological influences.

Study of the reliability of quantification methods of dynamic contrast-enhanced ultrasonography: numerical modeling of blood flow in tumor microvascularization.

Dynamic contrast-enhanced ultrasonography is a recent functional dynamic imaging technique that allows evaluation of the efficacy of anti-angiogenic treatments by quantifying changes in specific parameters of the tumor vasculature. Preclinical and clinical experimental studies now reveal the existence of sources of variability in the quantitative methods. In order to study the reliability of quantification methods (both semi-quantitative and quantitative), we have developed the first numerical model of blood flow and contrast agents in vascular networks with computational fluid dynamics Fluent software version 15.0 (ANSYS, France). We studied four vascular networks (1.84 × 10-3, 2.28 × 10-3, 2.4 × 10-3 and 2.54 × 10-3 ml) and four blood velocities (0.01, 0.02, 0.03 and 0.05 m s-1). For variations in tumor vascular volume the quantitative method is more sensitive, with variations of parameter perfusion of 25.7%, in contrast to variations of the semi-quantitative parameters between 14.9 and 19.5%. For changes in blood velocity the semi-quantitative method is more sensitive, with variation of the area under the enhancement curve (64%), the maximum of the enhancement curve (60%), and the slope of the enhancement curve (73%). The transit time parameters from the two quantitative methods were weakly sensitive to both blood volume and blood flow variations. This study is hopeful and may be extended to the treatment of more complex vascular networks, to approach clinical conditions, and to the evaluation of quantification methods in contrast imaging.

A Novel Microflow Phantom Dedicated to Ultrasound Microvascular Measurements.

Tumor microvascularization is a biomarker of response to antiangiogenic treatments and is accurately assessed by ultrasound imaging. Imaging modes used to visualize slow flows include Power Doppler imaging, dynamic contrast-enhanced ultrasonography, and more recently, microvascular Doppler. Flow phantoms are used to evaluate the performance of Doppler imaging techniques, but they do not have a steady flow and sufficiently small channels. We report a novel device for robust and stable microflow measurements and the study of the microvascularization. Based on microfluidics technology, the prototype features wall-less cylindrical channels of diameters ranging from as small as 147 up to 436 µm, cast in a soft silicone polymer and perfused via a microfluidic flow pressure controller. The device was assessed using flow rates from 49 to 146 µL/min, with less than 1% coefficient of variation over three minutes, corresponding to velocities of 6 to 142 mm/s. This enabled us to evaluate and confirm the reliability of the Superb Microvascular Imaging Doppler mode compared with the Power Doppler mode at these flow rates in the presence of vibrations mimicking physiological motion.

Can we trust the calculation of texture indices of CT images? A phantom study.

PURPOSE: Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. METHODS: For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. RESULTS: Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). CONCLUSIONS: Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images.

Molecular Imaging to Predict Response to Targeted Therapies in Renal Cell Carcinoma.

Molecular magnetic resonance imaging targeted to an endothelial integrin involved in neoangiogenesis was compared to DCE-US and immunochemistry to assess the early response of three different therapeutic agents in renal cell carcinoma. Human A498 renal cells carcinoma was subcutaneously inoculated into 24 nude mice. Mice received either phosphate-buffered saline solution, sunitinib, everolimus, or bevacizumab during 4 days. DCE-US and molecular MRI targeting αvß3 were performed at baseline and 4 days after treatment initiation. PI, AUC, relaxation rate variations ΔR2⁎, and percentage of vessels area quantified on CD31-stained microvessels were compared. Significant decreases were observed for PI and AUC parameters measured by DCE-US for bevacizumab group as early as 4 days, whereas molecular αvß3-targeted MRI was able to detect significant changes in both bevacizumab and everolimus groups. Percentage of CD31-stained microvessels was significantly correlated with DCE-US parameters, PI (R = 0.87, p = 0.0003) and AUC (R = 0.81, p = 0.0013). The percentage of vessel tissue area was significantly reduced (p < 0.01) in both sunitinib and bevacizumab groups. We report an early detection of neoangiogenesis modification after induction of targeted therapies, using DCE-US or αvß3-targeted MRI. We consider these outcomes should encourage clinical trial developments to further evaluate the potential of this molecular MRI technique.

Toward a Standardization of Ultrasound Scanners for Dynamic Contrast-Enhanced Ultrasonography: Methodology and Phantoms.

The standardization of ultrasound scanners for dynamic contrast-enhanced ultrasonography (DCE-US) is mandatory for evaluation of clinical multicenter studies. We propose a robust method using a phantom for measuring the variation of the harmonic signal intensity obtained from the area under the time-intensity curve versus various contrast-agent concentrations. The slope of this measured curve is the calibration parameter. We tested our method on two devices from the same manufacturer (AplioXV and Aplio500, Toshiba, Tokyo, Japan) using the same settings as defined for a French multicenter study. The Aplio500's settings were adjusted to match the slopes of the AplioXV, resulting in the following settings on the Aplio500: at 3.5 MHz: MI = 0.15; CG = 35 dB and at 8 MHz: MI = 0.10; CG = 32 dB. This calibration method is very important for future DCE-US multicenter studies.

Study of Intrapatient Variability and Reproducibility of Quantitative Tumor Perfusion Parameters Evaluated With Dynamic Contrast-Enhanced Ultrasonography.

OBJECTIVES: Dynamic contrast-enhanced (DCE) ultrasonography (US) is a functional imaging technique enabling quantitative assessment of solid tumor perfusion in metastatic patients treated with antiangiogenic therapies.The objective of this prospective single-center study was to evaluate in real-life conditions (in routine clinical practice) the intrapatient variability and reproducibility of DCE-US parameters. MATERIALS AND METHODS: Each patient provided written informed consent and had 2 DCE-US examinations (preprandial and postprandial) at baseline, day 15, and 1 month after treatment initiation. Perfusion curves were recorded after Sonovue injections to determine 7 perfusion parameters. Dynamic contrast-enhanced US examinations were analyzed in pairs: preprandial and postprandial. Log transformed values were used to determine the variability of the pairs (within-subject coefficient of variation) and their reproducibility (Spearman correlation coefficient). RESULTS: We included 60 patients (23 colon cancers, 36 kidney cancers, and 1 breast cancer) treated with axitinib (26 patients), sunitinib (27 patients), and other antiangiogenic treatments (7 patients). The 60 patients included 38 men (63%) and 22 women (37%) with a median age of 62 (range, 25-82 years). Thirty patients had hepatic and 30 had extrahepatic target lesions. Data were analyzed for 128 pairs of DCE-US: 45 (baseline), 45 (day 15), and 38 (1 month). Preprandial and postprandial values were not significantly different. For area under the curve and area under the washout, the correlation coefficient between preprandial and postprandial values was 0.89; the associated within-subject coefficients of variation were 61% and 64%, respectively. However, the range of individual variations (postprandial value/preprandial value) was less than 2 logs for a range of parameter values of about 4 logs. Variability was independent of the metastatic site. CONCLUSIONS: This study showed that area under the curve and area under the washout are the 2 most reproducible DCE-US parameters.

Dynamic contrast-enhanced ultrasound parametric maps to evaluate intratumoral vascularization.

OBJECTIVES: The purposes of this study were to assess the reliability of parametric maps from dynamic contrast-enhanced ultrasound (DCE-US) to reflect the heterogeneous distribution of intratumoral vascularization and to predict the tissue features linked to vasculature. This study was designed to compare DCE-US parametric maps with histologic vascularity measurements. MATERIALS AND METHODS: Dynamic contrast-enhanced ultrasound was performed on 17 melanoma-bearing nude mice after a 0.1-mL bolus injection of SonoVue (Bracco SPA, Milan, Italy). The parametric maps were developed from raw linear data to extract pixelwise 2 semiquantitative parameters related to perfusion and blood volume, namely, area under the curve (AUC) and peak intensity (PI). The mathematical method to fit the time-intensity curve for each pixel was a polynomial model used in clinical routine and patented by the team. Regions of interest (ROIs) were drawn on DCE-US parametric maps for whole tumors and for several local areas of 15 mm within each tumor (iROI), the latter reflecting the heterogeneity of intratumoral blood volume. As the criterion standard correlation, microvessel densities (MVDs) were determined for both ROI categories. In detail, for all iROI of 15 mm, MVD and maturity were divided separately for vessels of 0 to 10 µm, 10 to 40 µm, and greater than 40 µm in diameter, and the results were correlated with the ultrasound findings. RESULTS: Among the 17 studied mice, a total of 64 iROIs were analyzed. For the whole-tumor ROI set, AUC and PI values significantly correlated with MVD (rAUC = 0.52 [P = 0.0408] and rPI = 0.70 [P = 0.0026]). In the case of multiple iROI, a strong linear correlation was observed between the DCE-US parameters and the density of vessels ranging in their diameter from 0 to 10 µm (rAUC = 0.68 [P < 0.0001]; rPI = 0.63 [P < 0.0001]), 10 to 40 µm (rAUC = 0.98 [P = 0.0003]; rPI = 0.98 [P = 0.0004]), and greater than 40 µm (rAUC = 0.86 [P = 0.0120]; rPI = 0.92 [P = 0.0034]), respectively. However, the DCE-US parameter values of perfusion and blood volume were not significantly different according to the diameters (AUC: P = 0.1731; PI: P = 0.2918) and maturity of blood vessels. CONCLUSIONS: Parametric maps of DCE-US can be reliably established from raw linear data and reflect the heterogeneous histological measures of vascularization within tumors. In contrast, the values of DCE-US parametric maps (AUC, PI) do not allow deduction of heterogeneous tissue features such as the diameters and maturity of vascular networks.

Impact of the arterial input function on microvascularization parameter measurements using dynamic contrast-enhanced ultrasonography.

AIM: To evaluate the sources of variation influencing the microvascularization parameters measured by dynamic contrast-enhanced ultrasonography (DCE-US). METHODS: Firstly, we evaluated, in vitro, the impact of the manual repositioning of the ultrasound probe and the variations in flow rates. Experiments were conducted using a custom-made phantom setup simulating a tumor and its associated arterial input. Secondly, we evaluated, in vivo, the impact of multiple contrast agent injections and of examination day, as well as the influence of the size of region of interest (ROI) associated with the arterial input function (AIF). Experiments were conducted on xenografted B16F10 female nude mice. For all of the experiments, an ultrasound scanner along with a linear transducer was used to perform pulse inversion imaging based on linear raw data throughout the experiments. Semi-quantitative and quantitative analyses were performed using two signal-processing methods. RESULTS: In vitro, no microvascularization parameters, whether semi-quantitative or quantitative, were significantly correlated (P values from 0.059 to 0.860) with the repositioning of the probe. In addition, all semi-quantitative microvascularization parameters were correlated with the flow variation while only one quantitative parameter, the tumor blood flow, exhibited P value lower than 0.05 (P = 0.004). In vivo, multiple contrast agent injections had no significant impact (P values from 0.060 to 0.885) on microvascularization parameters. In addition, it was demonstrated that semi-quantitative microvascularization parameters were correlated with the tumor growth while among the quantitative parameters, only the tissue blood flow exhibited P value lower than 0.05 (P = 0.015). Based on these results, it was demonstrated that the ROI size of the AIF had significant influence on microvascularization parameters: in the context of larger arterial ROI (from 1.17 ± 0.6 mm(3) to 3.65 ± 0.3 mm(3)), tumor blood flow and tumor blood volume were correlated with the tumor growth, exhibiting P values lower than 0.001. CONCLUSION: AIF selection is an essential aspect of the deconvolution process to validate the quantitative DCE-US method.