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

Nature Communications - Tập 9 Số 1
Tatjana Opacic1, Stefanie Dencks2, Benjamin Theek1, Marion Piepenbrock2, Dimitri Ackermann2, Anne Rix1, Twan Lammers1, Elmar Stickeler3, Stefan Delorme4, Georg Schmitz2, Fabian Kießling1
1Institute for Experimental Molecular Imaging, University Clinic Aachen, RWTH Aachen University, CMBS, Forckenbeckstr. 55, 52074, Aachen, Germany
2Chair for Medical Engineering, Department of Electrical Engineering and Information Technology, Ruhr University Bochum, Universitätsstr. 150, 44780, Bochum, Germany
3Department of Obstetrics and Gynecology, University Clinic Aachen, RWTH Aachen University, Pauwelsstr. 30, 52074, Aachen, Germany
4Department of Radiology, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

Tóm tắt

AbstractSuper-resolution imaging methods promote tissue characterization beyond the spatial resolution limits of the devices and bridge the gap between histopathological analysis and non-invasive imaging. Here, we introduce motion model ultrasound localization microscopy (mULM) as an easily applicable and robust new tool to morphologically and functionally characterize fine vascular networks in tumors at super-resolution. In tumor-bearing mice and for the first time in patients, we demonstrate that within less than 1 min scan time mULM can be realized using conventional preclinical and clinical ultrasound devices. In this context, next to highly detailed images of tumor microvascularization and the reliable quantification of relative blood volume and perfusion, mULM provides multiple new functional and morphological parameters that discriminate tumors with different vascular phenotypes. Furthermore, our initial patient data indicate that mULM can be applied in a clinical ultrasound setting opening avenues for the multiparametric characterization of tumors and the assessment of therapy response.

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Tài liệu tham khảo

Lindner, J. R. Microbubbles in medical imaging: current applications and future directions. Nat. Rev. Drug Discov. 3, 527–532 (2004).

Padhani, A. R., Harvey, C. J. & Cosgrove, D. O. Angiogenesis imaging in the management of prostate cancer. Nat. Clin. Pract. Urol. 2, 596–607 (2005).

Hamer, O. W., Schlottmann, K., Sirlin, C. B. & Feuerbach, S. Technology insight: advances in liver imaging. Nat. Clin. Pract. Gastroenterol. Hepatol. 4, 215–228 (2007).

Dimastromatteo, J., Brentnall, T. & Kelly, K. A. Imaging in pancreatic disease. Nat. Rev. Gastroenterol. Hepatol. 14, 97–109 (2017).

Birner, P. et al. Vascular patterns in glioblastoma influence clinical outcome and associate with variable expression of angiogenic proteins: evidence for distinct angiogenic subtypes. Brain Pathol. 13, 133–143 (2003).

Jia, W. R. et al. Three-dimensional contrast-enhanced ultrasound in response assessment for breast cancer: a comparison with dynamic contrast-enhanced magnetic resonance imaging and pathology. Sci. Rep. 6, 33832 (2016).

Lassau, N. et al. Validation of dynamic contrast-enhanced ultrasound in predicting outcomes of antiangiogenic therapy for solid tumors: the French multicenter support for innovative and expensive techniques study. Invest. Radiol. 49, 794–800 (2014).

Tolaney, S. M. et al. Role of vascular density and normalization in response to neoadjuvant bevacizumab and chemotherapy in breast cancer patients. Proc. Natl Acad. Sci. USA 112, 14325–14330 (2015).

O’Connor, J. P. et al. Imaging biomarker roadmap for cancer studies. Nat. Rev. Clin. Oncol. 14, 169–186 (2017).

Mirnezami, R., Nicholson, J. & Darzi, A. Preparing for precision medicine. N. Engl. J. Med. 366, 489–491 (2012).

Pitre-Champagnat, S. et al. Dynamic contrast-enhanced ultrasound parametric maps to evaluate intratumoral vascularization. Invest. Radiol. 50, 212–217 (2015).

Pysz, M. A. et al. Assessment and monitoring tumor vascularity with contrast-enhanced ultrasound maximum intensity persistence imaging. Invest. Radiol. 46, 187–195 (2011).

Wei, K. et al. Quantification of myocardial blood flow with ultrasound-induced destruction of microbubbles administered as a constant venous infusion. Circulation 97, 473–483 (1998).

Konerding, M. A., Miodonski, A. J. & Lametschwandtner, A. Microvascular corrosion casting in the study of tumor vascularity: a review. Scanning Microsc. 9, 1233–1243 (1995). discussion 1243-1234.

Siepmann M., Schmitz G., Bzyl J., Palmowski M., Kiessling F. Imaging tumor vascularity by tracing single microbubbles. Proc 2011 IEEE International Ultrasonics Symposium, 1906–1909 (2011).

Theek, B. et al. Automated generation of reliable blood velocity parameter maps from contrast-enhanced ultrasound data. Contrast Media Mol. Imaging 2017, 2098324 (2017).

Errico, C. et al. Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging. Nature 527, 499–502 (2015).

Christensen-Jeffries, K., Browning, R. J., Tang, M. X., Dunsby, C. & Eckersley, R. J. In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles. IEEE Trans. Med. Imaging 34, 433–440 (2015).

Jain, R. K., Martin, J. D. & Stylianopoulos, T. The role of mechanical forces in tumor growth and therapy. Annu. Rev. Biomed. Eng. 16, 321–346 (2014).

Fernandez-Sanchez, M. E. et al. Mechanical induction of the tumorigenic beta-catenin pathway by tumour growth pressure. Nature 523, 92–95 (2015).

Stylianopoulos, T. & Jain, R. K. Combining two strategies to improve perfusion and drug delivery in solid tumors. Proc. Natl Acad. Sci. USA 110, 18632–18637 (2013).

Ruoslahti, E. Specialization of tumour vasculature. Nat. Rev. Cancer 2, 83–90 (2002).

Carmeliet, P. & Jain, R. K. Molecular mechanisms and clinical applications of angiogenesis. Nature 473, 298–307 (2011).

Kashani-Sabet, M., Sagebiel, R. W., Ferreira, C. M., Nosrati, M. & Miller, J. R. 3rd Tumor vascularity in the prognostic assessment of primary cutaneous melanoma. J. Clin. Oncol. 20, 1826–1831 (2002).

Chow, K. L. et al. Prognostic factors in recurrent glioblastoma multiforme and anaplastic astrocytoma treated with selective intra-arterial chemotherapy. Ajnr. Am. J. Neuroradiol. 21, 471–478 (2000).

Palmowski, M. et al. Comparison of conventional time-intensity curves vs. maximum intensity over time for post-processing of dynamic contrast-enhanced ultrasound. Eur. J. Radiol. 75, e149–e153 (2010).

Boonstra, H., Oosterhuis, J. W., Oosterhuis, A. M. & Fleuren, G. J. Cervical tissue shrinkage by formaldehyde fixation, paraffin wax embedding, section cutting and mounting. Virchows. Arch. A. Pathol. Anat. Histopathol. 402, 195–201 (1983).

Hsu, P. K. et al. Effect of formalin fixation on tumor size determination in stage i non-small cell lung cancer. Ann. Thorac. Surg. 84, 1825–1829 (2007).

Kamoun, W. S. et al. Simultaneous measurement of rbc velocity, flux, hematocrit and shear rate in vascular networks. Nat. Methods 7, 655–660 (2010).

Hudson, J. M. K. R. & Burns, P. N. Quantification of flow using ultrasound and microbubbles: a disruption replenishment model based on physical principles. Ultrasound Med. Biol. 35, 2007–2020 (2010).

Krix, M. et al. A multivessel model describing replenishment kinetics of ultrasound contrast agent for quantification of tissue perfusion. Ultrasound Med. Biol. 29, 1421–1430 (2003).

Demené, C. et al. Spatiotemporal clutter filtering of ultrafast ultrasound data highly increases Doppler and fUltrasound sensitivity. IEEE Trans. Med. Imaging 34, 2271–2285 (2015).

Claudon, M. et al. Guidelines and good clinical practice recommendations for contrast enhanced ultrasound (CEUS) in the liver—update 2012: a wfumb-efsumb initiative in cooperation with representatives of afsumb, aium, asum, flaus and icus. Ultrasound Med. Biol. 39, 187–210 (2013).

Lin, F. et al. 3-d ultrasound localization microscopy for identifying microvascular morphology features of tumor angiogenesis at a resolution beyond the diffraction limit of conventional ultrasound. Theranostics 7, 196–204 (2017).

Wang, H., Lutz, A. M., Hristov, D., Tian, L. & Willmann, J. K. Intra-animal comparison between three-dimensional molecularly targeted us and three-dimensional dynamic contrast-enhanced us for early antiangiogenic treatment assessment in colon cancer. Radiology 282, 443–452 (2017).

Ehling, J. et al. Micro-ct imaging of tumor angiogenesis: quantitative measures describing micromorphology and vascularization. Am. J. Pathol. 184, 431–441 (2014).

Fokong, S. et al. Advanced characterization and refinement of poly n-butyl cyanoacrylate microbubbles for ultrasound imaging. Ultrasound Med. Biol. 37, 1622–1634 (2011).

Foiret, J. et al. Ultrasound localization microscopy to image and assess microvasculature in a rat kidney. Sci. Rep. 7, 13662 (2017).

Hingot, V., Errico, C., Tanter, M. & Couture, O. Subwavelength motion-correction for ultrafast ultrasound localization microscopy. Ultrasonics 77, 17–21 (2017).

Ackermann, D. S. G. Detection and tracking of multiple microbubbles in ultrasound b-mode images. IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 63, 72–82 (2016).

Viessmann, O. M., Eckersley, R. J., Christensen-Jeffries, K., Tang, M. X. & Dunsby, C. Acoustic super-resolution with ultrasound and microbubbles. Phys. Med. Biol. 58, 6447–6458 (2013).

Desailly, Y., Pierre, J., Couture, O. & Tanter, M. Resolution limits of ultrafast ultrasound localization microscopy. Phys. Med. Biol. 60, 8723–8740 (2015).

Gremse, F. et al. Imalytics preclinical: interactive analysis of biomedical volume data. Theranostics 6, 328–341 (2016).

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Tập 9 Số 1

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