Literature DB >> 25275834

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

Stephanie Pitre-Champagnat1, Ingrid Leguerney, Jacques Bosq, Pierre Peronneau, Fabian Kiessling, Lucie Calmels, Jeremy Coulot, Nathalie Lassau.   

Abstract

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.

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Year:  2015        PMID: 25275834     DOI: 10.1097/RLI.0000000000000101

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  13 in total

1.  Perfusion contrast-enhanced ultrasound to predict early lymph-node metastasis in breast cancer.

Authors:  Naoko Mori; Shunji Mugikura; Minoru Miyashita; Yumiko Kudo; Mikiko Suzuki; Li Li; Yu Mori; Shoki Takahashi; Kei Takase
Journal:  Jpn J Radiol       Date:  2018-11-20       Impact factor: 2.374

2.  Three-dimensional Dynamic Contrast-enhanced US Imaging for Early Antiangiogenic Treatment Assessment in a Mouse Colon Cancer Model.

Authors:  Huaijun Wang; Dimitre Hristov; Jiale Qin; Lu Tian; Jürgen K Willmann
Journal:  Radiology       Date:  2015-05-22       Impact factor: 11.105

Review 3.  Ultrasound in Radiology: From Anatomic, Functional, Molecular Imaging to Drug Delivery and Image-Guided Therapy.

Authors:  Alexander L Klibanov; John A Hossack
Journal:  Invest Radiol       Date:  2015-09       Impact factor: 6.016

4.  Dynamic contrast-enhanced ultrasonography (D-CEUS) for the early prediction of bevacizumab efficacy in patients with metastatic colorectal cancer.

Authors:  Michele Amadori; Domenico Barone; Emanuela Scarpi; Devil Oboldi; Elena Amadori; Gianfranco Bandi; Alice Rossi; Fabio Ferroni; Angela Ragazzini; Andrea Casadei Gardini; Giovanni Luca Frassineti; Giampaolo Gavelli; Alessandro Passardi
Journal:  Eur Radiol       Date:  2018-02-07       Impact factor: 5.315

5.  Contrast-Enhanced Ultrasonography with Quantitative Analysis allows Differentiation of Renal Tumor Histotypes.

Authors:  Di Sun; Cong Wei; Yi Li; Qijie Lu; Wei Zhang; Bing Hu
Journal:  Sci Rep       Date:  2016-10-11       Impact factor: 4.379

6.  Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization.

Authors:  Tatjana Opacic; Stefanie Dencks; Benjamin Theek; Marion Piepenbrock; Dimitri Ackermann; Anne Rix; Twan Lammers; Elmar Stickeler; Stefan Delorme; Georg Schmitz; Fabian Kiessling
Journal:  Nat Commun       Date:  2018-04-18       Impact factor: 14.919

7.  Automated Generation of Reliable Blood Velocity Parameter Maps from Contrast-Enhanced Ultrasound Data.

Authors:  Benjamin Theek; Tatjana Opacic; Diana Möckel; Georg Schmitz; Twan Lammers; Fabian Kiessling
Journal:  Contrast Media Mol Imaging       Date:  2017-05-30       Impact factor: 3.161

8.  Ultrasound molecular imaging as a non-invasive companion diagnostic for netrin-1 interference therapy in breast cancer.

Authors:  Jennifer Wischhusen; Katheryne E Wilson; Jean-Guy Delcros; Rodolfo Molina-Peña; Benjamin Gibert; Shan Jiang; Jacqueline Ngo; David Goldschneider; Patrick Mehlen; Juergen K Willmann; Frederic Padilla
Journal:  Theranostics       Date:  2018-10-06       Impact factor: 11.556

9.  A Prospective Study on the Value of Ultrasound Microflow Assessment to Distinguish Malignant from Benign Solid Breast Masses: Association between Ultrasound Parameters and Histologic Microvessel Densities.

Authors:  Ah Young Park; Myoungae Kwon; Ok Hee Woo; Kyu Ran Cho; Eun Kyung Park; Sang Hoon Cha; Sung Eun Song; Ju Han Lee; JaeHyung Cha; Gil Soo Son; Bo Kyoung Seo
Journal:  Korean J Radiol       Date:  2019-05       Impact factor: 3.500

10.  Construction of ultrasonic nanobubbles carrying CAIX polypeptides to target carcinoma cells derived from various organs.

Authors:  Lianhua Zhu; Yanli Guo; Luofu Wang; Xiaozhou Fan; Xingyu Xiong; Kejing Fang; Dan Xu
Journal:  J Nanobiotechnology       Date:  2017-09-29       Impact factor: 10.435

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