Correlation of diffusion MRI with the Ki-67 index in non-small cell lung cancer

1. Yabuuchi H, Hatakenaka M, Takayama K, Matsuo Y, Sunami S, Kamitani T, et al. Non-small cell lung cancer: detection of early response to chemotherapy by using contrast-enhanced dynamic and diffusion-weighted MR imaging. Radiology 2011; 26: 598-604.10.1148/radiol.11101503Search in Google Scholar

2. Wang Y, Chen ZE, Yaghmai V, Nikolaidis P, McCarthy RJ, Merrick L, et al. Diffusion-weighted MR imaging in pancreatic endocrine tumors correlated with histopathologic characteristics. J Magn Reson Imaging 2011; 33: 1071-9.10.1002/jmri.22541Search in Google Scholar

3. Zhang J, Cui LB, Tang X, Ren XL, Shi JR, Yang HN, et al. DW MRI at 3.0 T versus FDG PET/CT for detection of malignant pulmonary tumors. Int J Cancer 2014; 134: 606-11.10.1002/ijc.28394Search in Google Scholar

4. Li F, Yu T, Li W, Zhang C, Cao Y, Su D, et al. Correlation of apparent diffusion coefficient with histologic type and grade of lung cancer. Zhongguo Fei Ai Za Zhi 2012; 15: 646-51.Search in Google Scholar

5. Xu L, Tian J, Liu Y, Li C. Accuracy of diffusion-weighted (DW) MRI with background signal suppression (MR-DWIBS) in diagnosis of mediastinal lymph node metastasis of nonsmall-cell lung cancer (NSCLC). J Magn Reson Imaging 2014; 40: 200-5.10.1002/jmri.24343Search in Google Scholar

6. Usuda K, Sagawa M, Motono N, Ueno M, Tanaka M, Machida Y, et al. Diagnostic performance of diffusion weighted imaging of malignant and benign pulmonary nodules and masses: comparison with positron emission tomography. Asian Pac J Cancer Prev 2014; 15: 4629-35.10.7314/APJCP.2014.15.11.4629Search in Google Scholar

7. Türkbey B, Aras Ö, Karabulut N, Turgut AT, Akpinar E, Alibek S, et al. Diffusion-weighted MRI for detecting and monitoring cancer: a review of current applications in body imaging. Diagn Interv Radiol 2012; 18: 46-59.Search in Google Scholar

8. Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 2007; 188: 1622-35.10.2214/AJR.06.1403Search in Google Scholar

9. Padhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009; 11: 102-25.10.1593/neo.81328Search in Google Scholar

10. Scholzen T, Gerdes J. The Ki-67 protein: from the known and the unknown. J Cell Physiol 2000; 182: 311-22.10.1002/(SICI)1097-4652(200003)182:3<311::AID-JCP1>3.0.CO;2-9Search in Google Scholar

11. Raĭkhlin NT, Bukaeva IA, Smirnova EA, Gurevich LE, Delektorskaia VV, Polotskiĭ BE, et al. Significance of the expression of nucleolar argyrophilic proteins and antigen Ki-67 in the evaluation of cell proliferative activity and in the prediction of minimal (T1) lung cancer. Arkh Patol 2008; 70: 15-18.Search in Google Scholar

12. Gerdes J, Lemke H, Baisch H, Wacker HH, Schwab U, Stein H. Cell cycle analysis of a cell proliferation-associated human nuclear antigen defined by the monoclonal antibody Ki-67. J Immunol 1984; 133: 1710-15.10.4049/jimmunol.133.4.1710Search in Google Scholar

13. Zhu L, Ren G, Li K, Liang ZH, Tang WJ, Ji YM, et al. Pineal parenchymal tumours: minimum apparent diffusion coefficient in prediction of tumour grading. J Int Med Res 2011; 39: 1456-63.10.1177/147323001103900434Search in Google Scholar

14. Choi SY, Chang YW, Park HJ, Kim HJ, Hong SS, Seo DY. Correlation of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer. Br J Radiol 2012; 85(1016): e474-9.10.1259/bjr/79381464Search in Google Scholar

15. Onishi N, Kanao S, Kataoka M, Iima M, Sakaguchi R, Kawai M, et al. Apparent diffusion coefficient as a potential surrogate marker for Ki-67 index in mucinous breast carcinoma, J Magn Reson Imaging 2015; 41: 610-5.Search in Google Scholar

16. Mesko S, Kupelian P, Demanes DJ, Huang J, Wang PC, Kamrava M. Quantifying the ki-67 heterogeneity profile in prostate cancer. Prostate Cancer 2013: 2013: 717080.10.1155/2013/717080381607124222860Search in Google Scholar

17. Kobayashi S, Koga F, Kajino K, Yoshita S, Ishii C, Tanaka H, et al. Apparent diffusion coefficient value reflects invasive and proliferative potential of bladder cancer. J Magn Reson Imaging 2014; 39: 172-8.10.1002/jmri.2414823589321Search in Google Scholar

18. Tang Y, Dundamadappa SK, Thangasamy S, Flood T, Moser R, Smith T, et al. Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma. AJR Am J Roentgenol 2014; 202: 1303-8.10.2214/AJR.13.1163724848829Search in Google Scholar

19. Martin B, Paesmans M, Mascaux C, Berghmans T, Lothaire P, Meert AP, et al. Ki-67 expression and patients survival in lung cancer: systematic review of the literature with meta-analysis. Br J Cancer 2004; 91: 2018-25.10.1038/sj.bjc.6602233240978615545971Search in Google Scholar

20. Usuda K, Zhao XT, Sagawa M, Aikawa H, Ueno M, Tanaka M, et al. Diffusion-weighted imaging (DWI) signal intensity and distribution represent the amount of cancer cells and their distribution in primary lung cancer. Clin Imaging 2013; 37: 265-72.10.1016/j.clinimag.2012.04.02623465978Search in Google Scholar

21. Ohno Y, Koyama H, Yoshikawa T, Matsumoto K, Aoyama N, Onishi Y, et al. Diffusion-weighted MRI versus 18F-FDG PET/CT: performance as predictors of tumor treatment response and patient survival in patients with nonsmall cell lung cancer receiving chemoradiotherapy. AJR Am J Roentgenol 2012; 198: 75-82.10.2214/AJR.11.652522194481Search in Google Scholar

22. Tanaka R, Horikoshi H, Nakazato Y, Seki E, Minato K, Iijima M, et al. Magnetic resonance imaging in peripheral lung adenocarcinoma: correlation with histopathologic features. J Thorac Imaging 2009; 24: 4-9.10.1097/RTI.0b013e31818703b719242296Search in Google Scholar

23. Matoba M, Tonami H, Kondou T, Yokota H, Higashi K, Toga H, et al. Lung carcinoma: diffusion-weighted MR imaging—preliminary evaluation with apparent diffusion coefficient. Radiology 2007; 243: 570-7.10.1148/radiol.243206013117400757Search in Google Scholar

24. Martin B, Paesmans M, Mascaux C, Berghmans T, Lothaire P, Meert AP, et al. Ki-67 expression and patients survival in lung cancer: systematic review of the literature with meta-analysis. Br J Cancer 2004; 91: 2018-25.10.1038/sj.bjc.6602233Search in Google Scholar

25. Warth A, Cortis J, Soltermann A, Meister M, Budczies J, Stenzinger A, et al. Tumour cell proliferation (Ki-67) in non-small cell lung cancer: a critical reappraisal of its prognostic role. Br J Cancer 2014; 111: 1222-9.10.1038/bjc.2014.402445384725051406Search in Google Scholar

26. Tabata K, Tanaka T, Hayashi T, Hori T, Nunomura S, Yonezawa S, et al. Ki-67 is a strong prognostic marker of non-small cell lung cancer when tissue heterogeneity is considered. BMC Clin Pathol 2014; 14: 23-30.10.1186/1472-6890-14-23403234624860257Search in Google Scholar

27. Ahn HK, Jung M, Ha SY, Lee JI, Park I, Kim YS, et al. Clinical significance of Ki-67 and p53 expression in curatively resected non-small cell lung cancer. Tumour Biol 2014; 35: 5735-40.10.1007/s13277-014-1760-024737581Search in Google Scholar

28. Alper F, Kurt AT, Aydin Y, Ozgokce M, Akgun M. The role of dynamic magnetic resonance imaging in the evaluation of pulmonary nodules and masses. Med Princ Pract 2013; 22: 80-6.10.1159/000339475558670222797711Search in Google Scholar

29. Karaman A, Kahraman M, Bozdoğan E, Alper F, Akgün M. Diffusion magnetic resonance imaging of thorax. Tuberk Toraks 2014; 62: 215-30.Search in Google Scholar

30. Araz O, Demirci E, Ucar EY, Calik M, Karaman A, Durur-Subasi I, et al. Roles of Ki-67, p53, transforming growth factor-β and lysyl oxidase in the metastasis of lung cancer. Respirology 2014; 19: 1034-9.10.1111/resp.1234524995672Search in Google Scholar

31. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin 2013; 63: 11-30.10.3322/caac.2116623335087Search in Google Scholar

32. Zhang Z, Zhou Y, Qian H, Shao G, Lu X, Chen Q, et al. Stemness and inducing differentiation of small cell lung cancer NCI-H446 cells. Cell Death Dis 2013; 16: e633.10.1038/cddis.2013.152367436023681228Search in Google Scholar

33. Schaarschmidt BM, Buchbender C, Nensa F, Grueneien J, Gomez B, Köhler J, et al. Correlation of the apparent diffusion coefficient (ADC) with the standardized uptake value (SUV) in lymph node metastases of non-small cell lung cancer (NSCLC) patients using hybrid 18F-FDG PET/MRI. PLoS One 2015; 10(1): e0116277.10.1371/journal.pone.0116277428906625574968Search in Google Scholar

34. Yoshida S, Kobayashi S, Koga F, Ishioka J, Ishii C, Tanaka H, et al. Apparent diffusion coefficient as a prognostic biomarker of upper urinary tract cancer: a preliminary report. Eur Radiol 2013; 23: 2206-14.10.1007/s00330-013-2805-223494496Search in Google Scholar

35. Yoshida S, Koga F, Kobayashi S, Ishii C, Tanaka H, Tanaka H, et al. Role of diffusion weighted magnetic resonance imaging in predicting sensitivity to chemoradiotherapy in muscle-invasive bladder cancer. Int J Radiat Oncol Biol Phys 2012; 83: e21-e7.10.1016/j.ijrobp.2011.11.06522414281Search in Google Scholar

36. Wieduwilt MJ, Valles F, Issa S, Behler CM, Hwang J, McDermott M, et al. Immunochemotherapy with intensive consolidation for primary CNS lymphoma: a pilot study and prognostic assessment by diffusion-weighted MRI. Clin Cancer Res 2012; 18: 1146-55.10.1158/1078-0432.CCR-11-0625328820422228634Search in Google Scholar

37. Srinivasan A, Chenevert TL, Dwamena BA, Eisbruch A, Watcharotone K, Myles JD, et al. Utility of pretreatment mean apparent diffusion coefficient and apparent diffusion coefficient histograms in prediction of outcome to chemoradiation in head and neck squamous cell carcinoma. J Comput Assist Tomogr 2012; 36: 131-7.10.1097/RCT.0b013e318240543522261783Search in Google Scholar

38. Pope WB, Lai A, Mehta R, Qiao J, Young JR, Xue X, et al. Apparent diffusion coefficient histogram analysis stratifies progression-free survival in newly diagnosed bevacizumab-treated glioblastoma. AJNR Am J Neuroradiol 2011; 32: 882-9.10.3174/ajnr.A2385796554821330401Search in Google Scholar

39. Kıvrak AS, Paksoy Y, Erol C, Koplay M, Özbek S, Kara F. Comparison of apparent diffusion coefficient values among different MRI platforms: a multi-center phantom study. Diagn Interv Radiol 2013; 19: 433-7.10.5152/dir.2013.1303424004973Search in Google Scholar

40. Rosenkrantz AB, Oei M, Babb JS, Niver BE, Taouli B. Diffusion-weighted imaging of the abdomen at 3.0 Tesla: image quality and apparent diffusion coefficient reproducibility compared with 1.5 Tesla. J Magn Reson Imaging 2011; 33: 128-35.10.1002/jmri.2239521182130Search in Google Scholar