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Quantitative assessment of tumor angiogenesis using real-time motion-compensated contrast-enhanced ultrasound imaging

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Abstract

Purpose

To develop and test a real-time motion compensation algorithm for contrast-enhanced ultrasound imaging of tumor angiogenesis on a clinical ultrasound system.

Materials and methods

The Administrative Institutional Panel on Laboratory Animal Care approved all experiments. A new motion correction algorithm measuring the sum of absolute differences in pixel displacements within a designated tracking box was implemented in a clinical ultrasound machine. In vivo angiogenesis measurements (expressed as percent contrast area) with and without motion compensated maximum intensity persistence (MIP) ultrasound imaging were analyzed in human colon cancer xenografts (n = 64) in mice. Differences in MIP ultrasound imaging signal with and without motion compensation were compared and correlated with displacements in x- and y-directions. The algorithm was tested in an additional twelve colon cancer xenograft-bearing mice with (n = 6) and without (n = 6) anti-vascular therapy (ASA-404). In vivo MIP percent contrast area measurements were quantitatively correlated with ex vivo microvessel density (MVD) analysis.

Results

MIP percent contrast area was significantly different (P < 0.001) with and without motion compensation. Differences in percent contrast area correlated significantly (P < 0.001) with x- and y-displacements. MIP percent contrast area measurements were more reproducible with motion compensation (ICC = 0.69) than without (ICC = 0.51) on two consecutive ultrasound scans. Following anti-vascular therapy, motion-compensated MIP percent contrast area significantly (P = 0.03) decreased by 39.4 ± 14.6 % compared to non-treated mice and correlated well with ex vivo MVD analysis (Rho = 0.70; P = 0.05).

Conclusion

Real-time motion-compensated MIP ultrasound imaging allows reliable and accurate quantification and monitoring of angiogenesis in tumors exposed to breathing-induced motion artifacts.

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References

  1. Wilson SR, Burns PN (2010) Microbubble-enhanced US in body imaging: what role? Radiology 257:24–39

    Article  PubMed  Google Scholar 

  2. Lassau N, Chami L, Chebil M, Benatsou B, Bidault S, Girard E, Abboud G, Roche A (2011) Dynamic contrast-enhanced ultrasonography (DCE-US) and anti-angiogenic treatments. Discov Med 11:18–24

    PubMed  Google Scholar 

  3. Wilson SR, Jang HJ, Kim TK, Iijima H, Kamiyama N, Burns PN (2008) Real-time temporal maximum-intensity-projection imaging of hepatic lesions with contrast-enhanced sonography. AJR Am J Roentgenol 190:691–695

    Article  PubMed  Google Scholar 

  4. Aigner F, Mitterberger M, Rehder P, Pallwein L, Junker D, Horninger W, Frauscher F (2010) Status of transrectal ultrasound imaging of the prostate. J Endourol 24:685–691

    Article  PubMed  Google Scholar 

  5. Aigner F, Pallwein L, Mitterberger M, Pinggera GM, Mikuz G, Horninger W, Frauscher F (2009) Contrast-enhanced ultrasonography using cadence-contrast pulse sequencing technology for targeted biopsy of the prostate. BJU Int 103:458–463

    Article  PubMed  Google Scholar 

  6. DePriest PD, DeSimone CP (2003) Ultrasound screening for the early detection of ovarian cancer. J Clin Oncol 21:194s–199s

    Article  PubMed  Google Scholar 

  7. Fleischer AC, Lyshchik A, Andreotti RF, Hwang M, Jones HW III, Fishman DA (2010) Advances in sonographic detection of ovarian cancer: depiction of tumor neovascularity with microbubbles. AJR Am J Roentgenol 194:343–348

    Article  PubMed  Google Scholar 

  8. Fleischer AC, Lyshchik A, Jones HW III, Crispens MA, Andreotti RF, Williams PK, Fishman DA (2009) Diagnostic parameters to differentiate benign from malignant ovarian masses with contrast-enhanced transvaginal sonography. J Ultrasound Med 28:1273–1280

    PubMed  Google Scholar 

  9. Gorg C (2007) The forgotten organ: contrast enhanced sonography of the spleen. Eur J Radiol 64:189–201

    Article  PubMed  Google Scholar 

  10. Fusaroli P, Spada A, Mancino MG, Caletti G (2010) Contrast harmonic echo-endoscopic ultrasound improves accuracy in diagnosis of solid pancreatic masses. Clin Gastroenterol Hepatol 8(629–634):e621–e622

    Google Scholar 

  11. Helmstaedter L, Riemann JF (2008) Pancreatic cancer—EUS and early diagnosis. Langenbecks Arch Surg 393:923–927

    Article  PubMed  Google Scholar 

  12. Hohl C, Schmidt T, Honnef D, Gunther RW, Haage P (2007) Ultrasonography of the pancreas. 2. Harmonic imaging. Abdom Imaging 32:150–160

    Article  PubMed  CAS  Google Scholar 

  13. Rickes S, Rauh P, Uhle C, Ensberg D, Monkemuller K, Malfertheiner P (2007) Contrast-enhanced sonography in pancreatic diseases. Eur J Radiol 64:183–188

    Article  PubMed  Google Scholar 

  14. Correas JM, Claudon M, Tranquart F, Helenon AO (2006) The kidney: imaging with microbubble contrast agents. Ultrasound Q 22:53–66

    PubMed  Google Scholar 

  15. Xu ZF, Xu HX, Xie XY, Liu GJ, Zheng YL, Lu MD (2010) Renal cell carcinoma and renal angiomyolipoma: differential diagnosis with real-time contrast-enhanced ultrasonography. J Ultrasound Med 29:709–717

    PubMed  Google Scholar 

  16. Doust BD (1976) The use of ultrasound in the diagnosis of gastroenterological disease. Gastroenterology 70:602–610

    PubMed  CAS  Google Scholar 

  17. Nylund K, Hausken T, Gilja OH (2010) Ultrasound and inflammatory bowel disease. Ultrasound Q 26:3–15

    Article  PubMed  Google Scholar 

  18. Nylund K, Odegaard S, Hausken T, Folvik G, Lied GA, Viola I, Hauser H, Gilja OH (2009) Sonography of the small intestine. World J Gastroenterol 15:1319–1330

    Article  PubMed  Google Scholar 

  19. Contamin H, Rioufol G, Bettinger T, Helbert A, Portier KG, Lepage OM, Thomas R, Broillet A, Tranquart F, Schneider M (2012) A minimally-invasive closed chest myocardial occlusion-reperfusion model in rhesus monkeys (Macaca mulatta): monitoring by contrast-enhanced ultrasound imaging. Int J Cardiovasc Imaging 28:531–542

    Google Scholar 

  20. Staub D, Partovi S, Schinkel AF, Coll B, Uthoff H, Aschwanden M, Jaeger KA, Feinstein SB (2011) Correlation of carotid artery atherosclerotic lesion echogenicity and severity at standard US with intraplaque neovascularization detected at contrast-enhanced US. Radiology 258:618–626

    Article  PubMed  Google Scholar 

  21. Staub D, Schinkel AF, Coll B, Coli S, van der Steen AF, Reed JD, Krueger C, Thomenius KE, Adam D, Sijbrands EJ, ten Cate FJ, Feinstein SB (2010) Contrast-enhanced ultrasound imaging of the vasa vasorum: from early atherosclerosis to the identification of unstable plaques. JACC Cardiovasc Imaging 3:761–771

    Article  PubMed  Google Scholar 

  22. Balleyguier C, Opolon P, Mathieu MC, Athanasiou A, Garbay JR, Delaloge S, Dromain C (2009) New potential and applications of contrast-enhanced ultrasound of the breast: Own investigations and review of the literature. Eur J Radiol 69:14–23

    Article  PubMed  Google Scholar 

  23. Caproni N, Marchisio F, Pecchi A, Canossi B, Battista R, D’Alimonte P, Torricelli P (2010) Contrast-enhanced ultrasound in the characterisation of breast masses: utility of quantitative analysis in comparison with MRI. Eur Radiol 20:1384–1395

    Article  PubMed  Google Scholar 

  24. Hooley RJ, Andrejeva L, Scoutt LM (2011) Breast cancer screening and problem solving using mammography, ultrasound, and magnetic resonance imaging. Ultrasound Q 27:23–47

    Article  PubMed  Google Scholar 

  25. Molinari F, Mantovani A, Deandrea M, Limone P, Garberoglio R, Suri JS (2010) Characterization of single thyroid nodules by contrast-enhanced 3-D ultrasound. Ultrasound Med Biol 36:1616–1625

    Article  PubMed  Google Scholar 

  26. Zengel P, Siedek V, Berghaus A, Clevert DA (2010) Intraductally applied contrast-enhanced ultrasound (IA-CEUS) for improved visualization of obstructive diseases of the salivary glands, primary results. Clin Hemorheol Microcirc 45:193–205

    PubMed  CAS  Google Scholar 

  27. de Lange C, Brabrand K, Emblem KE, Bjornerud A, Loberg EM, Saugstad OD, Munkeby BH (2011) Cerebral perfusion in perinatal hypoxia and resuscitation assessed by transcranial contrast-enhanced ultrasound and 3 T MRI in newborn pigs. Invest Radiol 46:686–696

    Google Scholar 

  28. Lamuraglia M, Bridal SL, Santin M, Izzi G, Rixe O, Paradiso A, Lucidarme O (2010) Clinical relevance of contrast-enhanced ultrasound in monitoring anti-angiogenic therapy of cancer: current status and perspectives. Crit Rev Oncol Hematol 73:202–212

    Article  PubMed  Google Scholar 

  29. Yoshida K, Hirokawa T, Moriyasu F, Liu L, Liu GJ, Yamada M, Imai Y (2010) Arterial-phase contrast-enhanced ultrasonography for evaluating anti-angiogenesis treatment: a pilot study. World J Gastroenterol 17:1045–1050

    Article  Google Scholar 

  30. Palmowski M, Lederle W, Gaetjens J, Socher M, Hauff P, Bzyl J, Semmler W, Gunther RW, Kiessling F (2010) 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

    Article  PubMed  Google Scholar 

  31. Hoyt K, Warram JM, Umphrey H, Belt L, Lockhart ME, Robbin ML, Zinn KR (2010) Determination of breast cancer response to bevacizumab therapy using contrast-enhanced ultrasound and artificial neural networks. J Ultrasound Med 29:577–585

    PubMed  Google Scholar 

  32. Pollard RE, Sadlowski AR, Bloch SH, Murray L, Wisner ER, Griffey S, Ferrara KW (2002) Contrast-assisted destruction-replenishment ultrasound for the assessment of tumor microvasculature in a rat model. Technol Cancer Res Treat 1:459–470

    PubMed  Google Scholar 

  33. Watson KD, Hu X, Lai CY, Lindfors HA, Hu-Lowe DD, Tuthill TA, Shalinsky DR, Ferrara KW (2011) Novel ultrasound and DCE-MRI analyses after antiangiogenic treatment with a selective VEGF receptor inhibitor. Ultrasound Med Biol 37:909–921

    Article  PubMed  Google Scholar 

  34. Zhou JH, Cao LH, Liu JB, Zheng W, Liu M, Luo RZ, Han F, Li AH (2011) Quantitative assessment of tumor blood flow in mice after treatment with different doses of an antiangiogenic agent with contrast-enhanced destruction-replenishment US. Radiology 259:406–413

    Article  PubMed  Google Scholar 

  35. Arditi M, Frinking PJ, Zhou X, Rognin NG (2006) A new formalism for the quantification of tissue perfusion by the destruction-replenishment method in contrast ultrasound imaging. IEEE Trans Ultrason Ferroelectr Freq Control 53:1118–1129

    Article  PubMed  Google Scholar 

  36. Wei K, Jayaweera AR, Firoozan S, Linka A, Skyba DM, Kaul S (1998) Quantification of myocardial blood flow with ultrasound-induced destruction of microbubbles administered as a constant venous infusion. Circulation 97:473–483

    Article  PubMed  CAS  Google Scholar 

  37. Pysz MA, Foygel K, Panje CM, Needles A, Tian L, Willmann JK (2011) Assessment and monitoring tumor vascularity with contrast-enhanced ultrasound maximum intensity persistence imaging. Invest Radiol 46:187–195

    Article  PubMed  Google Scholar 

  38. Zhao H, Xu R, Ouyang Q, Chen L, Dong B, Huihua Y (2010) Contrast-enhanced ultrasound is helpful in the differentiation of malignant and benign breast lesions. Eur J Radiol 73:288–293

    Article  PubMed  Google Scholar 

  39. Dave JK, Forsberg F (2009) Novel automated motion compensation technique for producing cumulative maximum intensity subharmonic images. Ultrasound Med Biol 35:1555–1563

    Article  PubMed  Google Scholar 

  40. Bohs LN, Trahey GE (1991) A novel method for angle independent ultrasonic imaging of blood flow and tissue motion. IEEE Trans Biomed Eng 38:280–286

    Article  PubMed  CAS  Google Scholar 

  41. Weidner N (2008) Chapter 14. Measuring intratumoral microvessel density. Methods Enzymol 444:305–323

    Article  PubMed  Google Scholar 

  42. Faria JR, Aarao AR, Jimenez LM, Silva OH, Avelleira JC (2010) Inter-rater concordance study of the PASI (Psoriasis Area and Severity Index). An Bras Dermatol 85:625–629

    Article  PubMed  Google Scholar 

  43. Dindyal S, Kyriakides C (2011) Ultrasound microbubble contrast and current clinical applications. Recent Pat Cardiovasc Drug Discov 6:27–41

    Article  PubMed  CAS  Google Scholar 

  44. McCarville MB (2011) Contrast-enhanced sonography in pediatrics. Pediatr Radiol 41(Suppl 1):S238–S242

    Article  PubMed  Google Scholar 

  45. Xu HX (2009) Contrast-enhanced ultrasound: the evolving applications. World J Radiol 1:15–24

    Article  PubMed  Google Scholar 

  46. Pochon S, Tardy I, Bussat P, Bettinger T, Brochot J, von Wronski M, Passantino L, Schneider M (2010) BR55: a lipopeptide-based VEGFR2-targeted ultrasound contrast agent for molecular imaging of angiogenesis. Invest Radiol 45:89–95

    Article  PubMed  CAS  Google Scholar 

  47. Pysz MA, Foygel K, Rosenberg J, Gambhir SS, Schneider M, Willmann JK (2010) Antiangiogenic cancer therapy: monitoring with molecular US and a clinically translatable contrast agent (BR55). Radiology 256:519–527

    Article  PubMed  Google Scholar 

  48. Palmowski M, Huppert J, Ladewig G, Hauff P, Reinhardt M, Mueller MM, Woenne EC, Jenne JW, Maurer M, Kauffmann GW, Semmler W, Kiessling F (2008) Molecular profiling of angiogenesis with targeted ultrasound imaging: early assessment of antiangiogenic therapy effects. Mol Cancer Ther 7:101–109

    Article  PubMed  CAS  Google Scholar 

  49. Deshpande N, Ren Y, Foygel K, Rosenberg J, Willmann JK (2011) Tumor angiogenic marker expression levels during tumor growth: longitudinal assessment with molecularly targeted microbubbles and US imaging. Radiology 258:804–811

    Article  PubMed  Google Scholar 

  50. Lassau N, Koscielny S, Chami L, Chebil M, Benatsou B, Roche A, Ducreux M, Malka D, Boige V (2011) Advanced hepatocellular carcinoma: early evaluation of response to bevacizumab therapy at dynamic contrast-enhanced US with quantification—preliminary results. Radiology 258:291–300

    Article  PubMed  Google Scholar 

  51. Lavisse S, Lejeune P, Rouffiac V, Elie N, Bribes E, Demers B, Vrignaud P, Bissery MC, Brule A, Koscielny S, Peronneau P, Lassau N (2008) Early quantitative evaluation of a tumor vasculature disruptive agent AVE8062 using dynamic contrast-enhanced ultrasonography. Invest Radiol 43:100–111

    Article  PubMed  CAS  Google Scholar 

  52. Williams R, Hudson JM, Lloyd BA, Sureshkumar AR, Lueck G, Milot L, Atri M, Bjarnason GA, Burns PN (2011) Dynamic microbubble contrast-enhanced US to measure tumor response to targeted therapy: a proposed clinical protocol with results from renal cell carcinoma patients receiving antiangiogenic therapy. Radiology 260:581–590

    Article  PubMed  Google Scholar 

  53. Averkiou M, Lampaskis M, Kyriakopoulou K, Skarlos D, Klouvas G, Strouthos C, Leen E (2010) Quantification of tumor microvascularity with respiratory gated contrast enhanced ultrasound for monitoring therapy. Ultrasound Med Biol 36:68–77

    Article  PubMed  Google Scholar 

  54. Mule S, De Cesare A, Frouin F, Lucidarme O, Herment A (2007) An original methodology for quantitative assessment of perfusion in small animal studies using contrast-enhanced ultrasound. Conf Proc IEEE Eng Med Biol Soc 2007:347–350

    PubMed  Google Scholar 

  55. Frangi AF, Laclaustra M, Lamata P (2003) A registration-based approach to quantify flow-mediated dilation (FMD) of the brachial artery in ultrasound image sequences. IEEE Trans Med Imaging 22:1458–1469

    Article  PubMed  Google Scholar 

  56. de Oliveira PL, de Senneville BD, Dragonu I, Moonen CT (2010) Rapid motion correction in MR-guided high-intensity focused ultrasound heating using real-time ultrasound echo information. NMR Biomed 23:1103–1108

    Article  PubMed  Google Scholar 

  57. Mule S, Kachenoura N, Lucidarme O, De Oliveira A, Pellot-Barakat C, Herment A, Frouin F (2011) An automatic respiratory gating method for the improvement of microcirculation evaluation: application to contrast-enhanced ultrasound studies of focal liver lesions. Phys Med Biol 56:5153–5165

    Article  PubMed  CAS  Google Scholar 

  58. Pollard RE, Dayton PA, Watson KD, Hu X, Guracar IM, Ferrara KW (2009) Motion corrected cadence CPS ultrasound for quantifying response to vasoactive drugs in a rat kidney model. Urology 74:675–681

    Article  PubMed  Google Scholar 

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Acknowledgments

We would like to acknowledge the support by the NIH R21 CA139279 grant, the NCI ICMIC CA114747 P50 developmental grant, the SMIS NIH fellowship program, and the Canary Foundation. We also acknowledge Novartis (Basel, Switzerland) for provision of the ASA-404 VDA therapy, and Siemens for provision of the clinical ultrasound machine.

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Authors and Affiliations

  1. Molecular Imaging Program at Stanford, Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Room H1307, Stanford, CA, USA

    Marybeth A. Pysz, Kira Foygel & Jürgen K. Willmann

  2. Siemens Healthcare, Ultrasound Business Unit, Mountain View, CA, USA

    Ismayil Guracar

  3. Department of Health, Research and Policy, Stanford University, Stanford, CA, USA

    Lu Tian

Authors
  1. Marybeth A. Pysz
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  2. Ismayil Guracar
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  3. Kira Foygel
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  4. Lu Tian
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  5. Jürgen K. Willmann
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Corresponding author

Correspondence to Jürgen K. Willmann.

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Supplementary material 1 (DOC 30 kb)

10456_2012_9271_MOESM2_ESM.tif

Supplementary material 2 Supplementary Figure 1. Schematic showing the mechanism of calculation for real-time motion correction process. The first frame of the image acquisition is the (i) reference frame, and contains the (x, y) coordinates of the motion tracking box, (j, k). (ii) The B-mode image of the current frame with a new position of motion tracking box (a, b) following motion is compared with the reference frame, and (iii) the sum of absolute differences is used to calculate the positional movement of the tracking box (u, v) to obtain the highest similarity. The displacement (u, v) is then applied to the contrast image, and MIP is either suspended if large displacement occurred, or applied if minimal displacement occurred.(TIFF 1087 kb)

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Pysz, M.A., Guracar, I., Foygel, K. et al. Quantitative assessment of tumor angiogenesis using real-time motion-compensated contrast-enhanced ultrasound imaging. Angiogenesis 15, 433–442 (2012). https://doi.org/10.1007/s10456-012-9271-3

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  • DOI: https://doi.org/10.1007/s10456-012-9271-3

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