Evaluation of a Simplified Intravoxel Incoherent Motion (IVIM) Analysis of Diffusion-Weighted Imaging for Prediction of Tumor Size Changes and Imaging Response in Breast Cancer Liver Metastases Undergoing Radioembolization

Medicine (United States)

Volumn 95, Issue 14, 2016, Pages

  Pieper, Claus C ^a   Sprinkart, Alois M ^a   Meyer, Carsten ^a   König, Roy ^a   Schild, Hans H ^a   Kukuk, Guido M ^a   Mürtz, Petra ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

MACROSALB TC 99M; TECHNETIUM 99M; YTTRIUM 90;

ADULT; AGED; AREA UNDER THE CURVE; ARTICLE; BREAST CANCER; CANCER RADIOTHERAPY; CHEMOEMBOLIZATION; CLINICAL ARTICLE; DIFFUSION COEFFICIENT; DIFFUSION WEIGHTED IMAGING; DISEASE COURSE; FEMALE; HUMAN; LIVER CANCER; MALE; METASTASIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; RESPONSE EVALUATION CRITERIA IN SOLID TUMORS; SINGLE PHOTON EMISSION COMPUTER TOMOGRAPHY; TREATMENT DURATION; TREATMENT RESPONSE; TUMOR VOLUME; VOXEL BASED MORPHOMETRY; ARTIFICIAL EMBOLIZATION; BRACHYTHERAPY; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; LIVER NEOPLASMS; MIDDLE AGED; PATHOLOGY; PROCEDURES; RETROSPECTIVE STUDY; SECONDARY;

ADULT; AGED; BRACHYTHERAPY; BREAST NEOPLASMS; DIFFUSION MAGNETIC RESONANCE IMAGING; EMBOLIZATION, THERAPEUTIC; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LIVER NEOPLASMS; MIDDLE AGED; RETROSPECTIVE STUDIES;

EID: 84964692175     PISSN: 00257974     EISSN: 15365964     Source Type: Journal    
DOI: 10.1097/MD.0000000000003275     Document Type: Article

References (56)

1. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228-247.
2. Li SP, Padhani AR. Tumor response assessments with diffusion and perfusion MRI. J Magn Reson Imaging. 2012;35:745-763.
3. Thoeny HC, Ross BD. Predicting and monitoring cancer treatment response with diffusion-weighted MRI. J Magn Reson Imaging. 2010;32:2-16.
4. Husband JE, Schwartz LH, Spencer J, et al. Evaluation of the response to treatment of solid tumours-A consensus statement of the International Cancer Imaging Society. Br J Cancer. 2004;90:2256-2260.
5. Kennedy AS, Salem R. Radioembolization (yttrium-90 microspheres) for primary and metastatic hepatic malignancies. Cancer J. 2010;16:163-175.
6. Bester L, Hobbins PG, Wang S-C, et al. Imaging characteristics following 90yttrium microsphere treatment for unresectable liver cancer. J Med Imaging Radiat Oncol. 2011;55:111-118.
7. 18F-FDG uptake and tumour size on PET/CT. Eur J Nucl Med Mol Imaging. 2005;32:778-787.
8. Szyszko T, Al-Nahhas A, Canelo R, et al. Assessment of response to treatment of unresectable liver tumours with 90Y microspheres: value of FDG PET versus computed tomography. Nucl Med Commun. 2007;28:15-20.
9. Sabet A, Meyer C, Aouf A, et al. Early post-treatment FDG PET predicts survival after (90)Y microsphere radioembolization in liver-dominant metastatic colorectal cancer. Eur J Nucl Med Mol Imaging. 2015;42:370-376.
10. Morsbach F, Sah B-R, Spring L, et al. Perfusion CT best predicts outcome after radioembolization of liver metastases: a comparison of radionuclide and CT imaging techniques. Eur Radiol. 2014;24:1455-1465.
11. Vandecaveye V, Michielsen K, De Keyzer F, et al. Chemoemboliza-tion for hepatocellular carcinoma: 1-month response determined with apparent diffusion coefficient is an independent predictor of outcome. Radiology. 2014;270:747-757.
12. Dudeck O, Zeile M, Wybranski C, et al. Early prediction of anticancer effects with diffusion-weighted MR imaging in patients with colorectal liver metastases following selective internal radiotherapy. Eur Radiol. 2010;20:2699-2706.
13. Chiaradia M, Baranes L, Van Nhieu JT, et al. Intravoxel incoherent motion (IVIM) MR imaging of colorectal liver metastases: are we only looking at tumor necrosis? J Magn Reson Imaging. 2014;39:317-325.
14. Padhani AR, Koh DM. Diffusion MR imaging for monitoring of treatment response. Magn Reson Imaging Clin N Am. 2011;19:181-209.
15. Padhani AR, Liu G, Koh DM, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11:102-125.
16. Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. Am J Roentgenol. 2007;188:1622-1635.
17. Theilmann RJ, Borders R, Trouard TP, et al. Changes in water mobility measured by diffusion MRI predict response of metastatic breast cancer to chemotherapy. Neoplasia. 2004;6:831-837.
18. Heijmen L, ter Voert EEGW, Oyen WJG, et al. Multimodality imaging to predict response to systemic treatment in patients with advanced colorectal cancer. PLoS ONE. 2015;10:http://www.ncbi.nlm. nih.gov/pmc/articles/PMC4382283/. Accessed September 18, 2015.
19. Le Bihan D, Breton E, Lallemand D, et al. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology. 1988;168:497-505.
20. Koh DM, Collins DJ, Orton MR. Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. Am J Roent-genol. 2011;196:1351-1361.
21. Kukuk GM, Mürtz P, Träber F, et al. Diffusion-weighted imaging with acquisition of three b-values for response evaluation of neuroendocrine liver metastases undergoing selective internal radiotherapy. Eur Radiol. 2014;24:267-276.
22. Lewin M, Fartoux L, Vignaud A, et al. The diffusion-weighted imaging perfusion fraction f is a potential marker of sorafenib treatment in advanced hepatocellular carcinoma: a pilot study. Eur Radiol. 2011;21:281-290.
23. ter Voert EEGW, Delso G, Porto M, et al. Intravoxel incoherent motion protocol evaluation and data quality in normal and malignant liver tissue and comparison to the literature. Invest Radiol. 2015. DOI: 10.1097/RLI.0000000000000207. http://www.ncbi.nlm.nih.gov/pubmed/26405835.
24. Cohen AD, Schieke MC, Hohenwalter MD, et al. The effect of low b-values on the intravoxel incoherent motion derived pseudodiffusion parameter in liver. Magn Reson Med. 2015;73:306-311.
25. Leporq B, Saint-Jalmes H, Rabrait C, et al. Optimization of intra-voxel incoherent motion imaging at 3.0 Tesla for fast liver examination. J Magn Reson Imaging. 2015;41:1209-1217.
26. Chung SR, Lee SS, Kim N, et al. Intravoxel incoherent motion MRI for liver fibrosis assessment: a pilot study. Acta Radiol. 2014 DOI: 10.1177/0284185114559763. http://acr.sagepub.com/con tent/early/2014/11/20/0284185114559763.
27. Guiu B, Petit JM, Capitan V, et al. Intravoxel incoherent motion diffusion-weighted imaging in nonalcoholic fatty liver disease: a 3.0-T MR study. Radiology. 2012;265:96-103.
28. Luciani A, Vignaud A, Cavet M, et al. Liver cirrhosis: intravoxel incoherent motion MR imaging-pilot study. Radiology. 2008;249:891-899.
29. Kakite S, Dyvorne H, Besa C, et al. Hepatocellular carcinoma: short-term reproducibility of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0T. J Magn Reson Imaging. 2015;41:149-156.
30. Woo S, Lee JM, Yoon JH, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade. Radiology. 2014;270:758-767.
31. Andreou A, Koh DM, Collins DJ, et al. Measurement reproduci-bility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases. Eur Radiol. 2013;23:428-434.
32. Lee JT, Liau J, Murphy P, et al. Cross-sectional investigation of correlation between hepatic steatosis and IVIM perfusion on MR imaging. Magn Reson Imaging. 2012;30: 572-578.
33. Cho GY, Kim S, Jensen JH, et al. A versatile flow phantom for intravoxel incoherent motion MRI. Magn Reson Med. 2012;67:1710-1720.
34. Lemke A, Stieltjes B, Schad LR, et al. Toward an optimal distribution of b values for intravoxel incoherent motion imaging. Magn Reson Imaging. 2011;29:766-776.
35. Kennedy A, Nag S, Salem R, et al. Recommendations for radio-embolization of hepatic malignancies using yttrium-90 microsphere brachytherapy: a consensus panel report from the radioembolization brachytherapy oncology consortium. Int J Radiat Oncol Biol Phys. 2007;68:13-23.
36. Mahnken AH, Spreafico C, Maleux G, et al. Standards of practice in transarterial radioembolization. Cardiovasc Intervent Radiol. 2013;36:613-622.
37. Concia M, Sprinkart AM, Penner A-H, et al. Diffusion-weighted magnetic resonance imaging of the pancreas: diagnostic benefit from an intravoxel incoherent motion model-based 3 b-value analysis. Invest Radiol. 2014;49:93-100.
38. Penner A-H, Sprinkart AM, Kukuk GM, et al. Intravoxel incoherent motion model-based liver lesion characterisation from three b-value diffusion-weighted MRI. Eur Radiol. 2013;23:2773-2783.
39. Koh DM. Science to practice: can intravoxel incoherent motion diffusion-weighted MR imaging be used to assess tumor response to antivascular drugs? Radiology. 2014;272:307-308.
40. Yamada I, Aung W, Himeno Y, et al. Diffusion coefficients in abdominal organs and hepatic lesions: evaluation with intravoxel incoherent motion echo-planar MR imaging. Radiology. 1999;210:617-623.
41. Lee HJ, Rha SY, Chung YE, et al. Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density. Magn Reson Med. 2014;71:1554-1558.
42. Bauerle T, Seyler L, Munter M, et al. Diffusion-weighted imaging in rectal carcinoma patients without and after chemoradiotherapy: a comparative study with histology. Eur J Radiol. 2013;82:444-452.
43. Kim S, Decarlo L, Cho GY, et al. Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model. NMR Biomed. 2012;25:787-794.
44. Gade TP, Buchanan IM, Motley MW, et al. Imaging intratumoral convection: pressure-dependent enhancement in chemotherapeutic delivery to solid tumors. Clin Cancer Res. 2009;15:247-255.
45. Wagner M, Doblas S, Daire JL, et al. Diffusion-weighted MR imaging for the regional characterization of liver tumors. Radiology. 2012;264:464-472.
46. Tam HH, Collins DJ, Brown G, et al. The role of pre-treatment diffusion-weighted MRI in predicting long-term outcome of color-ectal liver metastasis. Br J Radiol. 2013;86:1-8.
47. Lee Y, Lee SS, Kim N, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of the liver: effect of triggering methods on regional variability and measurement repeatability of quantitative parameters. Radiology. 2015;274:405-415.
48. Lemke A, Laun FB, Simon D, et al. An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen. Magn Reson Med. 2010;64:1580-1585.
49. Cui Y, Zhang XP, Sun YS, et al. Apparent diffusion coefficient: potential imaging biomarker for prediction and early detection of response to chemotherapy in hepatic metastases. Radiology. 2008;248:894-900.
50. Dzik-Jurasz A, Domenig C, George M, et al. Diffusion MRI for prediction of response of rectal cancer to chemoradiation. Lancet. 2002;360:307-308.
51. Trédan O, Galmarini CM, Patel K, et al. Drug resistance and the solid tumor microenvironment. J Natl Cancer Inst. 2007;99:1441-1454.
52. Brown JM. The hypoxic cell: a target for selective cancer therapy-eighteenth Bruce F. Cain Memorial Award lecture. Cancer Res. 1999;59:5863-5870.
53. Barabasch A, Kraemer NA, Ciritsis A, et al. Diagnostic accuracy of diffusion-weighted magnetic resonance imaging versus positron emission tomography/computed tomography for early response assessment of liver metastases to Y90-radioembolization. Invest Radiol. 2015 DOI: 10.1097/rli.0000000000000144. http://www.ncbi.nlm.nih.gov/pubmed/25763526.
54. Joo I, Lee JM, Han JK, et al. Intravoxel incoherent motion diffusion-weighted MR imaging for monitoring the therapeutic efficacy of the vascular disrupting agent CKD-516 in rabbit VX2 liver tumors. Radiology. 2014;272:417-426.
55. Morsbach F, Pfammatter T, Reiner CS, et al. Computed tomographic perfusion imaging for the prediction of response and survival to transarterial radioembolization of liver metastases. Invest Radiol. 2013;48:787-794.
56. Reiner CS, Morsbach F, Sah B-R, et al. Early treatment response evaluation after Yttrium-90 radioembolization of liver malignancy with CT perfusion. J Vasc Interv Radiol. 2014;25:747-759.