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European Journal of Nuclear Medicine and Molecular Imaging

Erschienen in:

23.02.2018 | Original Article

Multiparametric PET/MR imaging biomarkers are associated with overall survival in patients with pancreatic cancer

verfasst von: Bang-Bin Chen, Yu-Wen Tien, Ming-Chu Chang, Mei-Fang Cheng, Yu-Ting Chang, Shih-Hung Yang, Chih-Horng Wu, Ting-Chun Kuo, I-Lun Shih, Ruoh-Fang Yen, Tiffany Ting-Fang Shih

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 7/2018

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Abstract

Purpose

To correlate the overall survival (OS) with the imaging biomarkers of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy, and glucose metabolic activity derived from integrated fluorine 18 fluorodeoxyglucose positron emission tomography (¹⁸F–FDG PET)/MRI in patients with pancreatic cancer.

Methods

This prospective study was approved by the institutional review board and informed consent was obtained from all participants. Sixty-three consecutive patients (mean age, 62.7 ± 12 y; men/women, 40/23) with pancreatic cancer underwent PET/MRI before treatment. The imaging biomarkers were comprised of DCE-MRI parameters (peak, IAUC₆₀, K^trans, k_ep, v_e), the minimum apparent diffusion coefficient (ADC_min), choline level, standardized uptake values, metabolic tumor volume, and total lesion glycolysis (TLG) of the tumors. The relationships between these imaging biomarkers with OS were evaluated with the Kaplan-Meier and Cox proportional hazard models.

Results

Seventeen (27%) patients received curative surgery, with the median follow-up duration being 638 days. Univariate analysis showed that patients at a low TNM stage (≦3, P = 0.041), high peak (P = 0.006), high ADC_min (P = 0.002) and low TLG (P = 0.01) had better OS. Moreover, high TLG/peak ratio was associated with poor OS (P = 0.016). Multivariate analysis indicated that ADC_min (P = 0.011) and TLG/peak ratio (P = 0.006) were independent predictors of OS after adjustment for age, gender, tumor size, and TNM stage. The TLG/peak ratio was an independent predictor of OS in a subgroup of patients who did not receive curative surgery (P = 0.013).

Conclusion

The flow-metabolism mismatch reflected by the TLG/peak ratio may better predict OS than other imaging biomarkers from PET/MRI in pancreatic cancer patients.

Ryan DP, Hong TS, Bardeesy N. Pancreatic adenocarcinoma. N Engl J Med. 2014;371:2140–1. https://doi.org/10.1056/NEJMc1412266.CrossRefPubMed

Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67:7–30. https://doi.org/10.3322/caac.21387.CrossRefPubMed

O'Connor JP, Aboagye EO, Adams JE, Aerts HJ, Barrington SF, Beer AJ, et al. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol. 2017;14:169–86. https://doi.org/10.1038/nrclinonc.2016.162.CrossRefPubMed

Rosenkrantz AB, Friedman K, Chandarana H, Melsaether A, Moy L, Ding YS, et al. Current status of hybrid PET/MRI in oncologic imaging. AJR Am J Roentgenol. 2016;206:162–72. https://doi.org/10.2214/AJR.15.14968.CrossRefPubMed

Torigian DA, Zaidi H, Kwee TC, Saboury B, Udupa JK, Cho ZH, et al. PET/MR imaging: technical aspects and potential clinical applications. Radiology. 2013;267:26–44. https://doi.org/10.1148/radiol.13121038.CrossRefPubMed

Wang J, Shih TT, Yen RF. Multiparametric evaluation of treatment response to Neoadjuvant chemotherapy in breast cancer using integrated PET/MR. Clin Nucl Med. 2017;42:506–13. https://doi.org/10.1097/RLU.0000000000001684.CrossRefPubMed

Joo I, Lee JM, Lee DH, Lee ES, Paeng JC, Lee SJ, et al. Preoperative assessment of pancreatic cancer with FDG PET/MR imaging versus FDG PET/CT plus contrast-enhanced multidetector CT: a prospective preliminary study. Radiology. 2017;282:149–59. https://doi.org/10.1148/radiol.2016152798.CrossRefPubMed

Miles KA, Williams RE. Warburg revisited: imaging tumour blood flow and metabolism. Cancer Imaging : Off Publ Int Cancer Imaging Soc. 2008;8:81–6. https://doi.org/10.1102/1470-7330.2008.0011.CrossRef

Komar G, Kauhanen S, Liukko K, Seppanen M, Kajander S, Ovaska J, et al. Decreased blood flow with increased metabolic activity: a novel sign of pancreatic tumor aggressiveness. Clin Canc Res : Off J Am Assoc Canc Res. 2009;15:5511–7. https://doi.org/10.1158/1078-0432.CCR-09-0414.CrossRef

10.

Michalski CW, Erkan M, Friess H, Kleeff J. Tumor metabolism to blood flow ratio in pancreatic cancer: helpful in patient stratification? Future Oncol. 2010;6:13–5. https://doi.org/10.2217/fon.09.151.CrossRefPubMed

11.

Mankoff DA, Dunnwald LK, Partridge SC, Specht JM. Blood flow-metabolism mismatch: good for the tumor, bad for the patient. Clin Canc Res : Off J Am Assoc Canc Res. 2009;15:5294–6. https://doi.org/10.1158/1078-0432.CCR-09-1448.CrossRef

12.

Padhani AR, Miles KA. Multiparametric imaging of tumor response to therapy. Radiology. 2010;256:348–64. https://doi.org/10.1148/radiol.10091760.CrossRefPubMed

13.

Shen G, Ma H, Liu B, Ren P, Kuang A. Correlation of the apparent diffusion coefficient and the standardized uptake value in neoplastic lesions: a meta-analysis. Nucl Med Commun. 20176; https://doi.org/10.1097/MNM.0000000000000746.

14.

Rakheja R, Chandarana H, DeMello L, Jackson K, Geppert C, Faul D, et al. Correlation between standardized uptake value and apparent diffusion coefficient of neoplastic lesions evaluated with whole-body simultaneous hybrid PET/MRI. AJR Am J Roentgenol. 2013;201:1115–9. https://doi.org/10.2214/AJR.13.11304.CrossRefPubMed

15.

Sakane M, Tatsumi M, Kim T, Hori M, Onishi H, Nakamoto A, et al. Correlation between apparent diffusion coefficients on diffusion-weighted MRI and standardized uptake value on FDG-PET/CT in pancreatic adenocarcinoma. Acta Radiol. 2015;56:1034–41. https://doi.org/10.1177/0284185114549825.CrossRefPubMed

16.

Chen BB, Tien YW, Chang MC, Cheng MF, Chang YT, Wu CH, et al. PET/MRI in pancreatic and periampullary cancer: correlating diffusion-weighted imaging, MR spectroscopy and glucose metabolic activity with clinical stage and prognosis. Eur J Nucl Med Mol Imaging. 2016;43:1753–64. https://doi.org/10.1007/s00259-016-3356-y.CrossRefPubMed

17.

Chen BB, Hsu CY, Yu CW, Liang PC, Hsu C, Hsu CH, et al. Dynamic contrast-enhanced MR imaging of advanced Hepatocellular carcinoma: comparison with the liver parenchyma and correlation with the survival of patients receiving systemic therapy. Radiology. 2016;281:454–64. https://doi.org/10.1148/radiol.2016152659.CrossRefPubMed

18.

Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magnet Res Imaging : JMRI. 1999;10:223–32.CrossRef

19.

Liu K, Xie P, Peng W, Zhou Z. Dynamic contrast-enhanced magnetic resonance imaging for pancreatic ductal adenocarcinoma at 3.0-T magnetic resonance: correlation with histopathology. J Comput Assist Tomography. 2015;39:13–8. https://doi.org/10.1097/RCT.0000000000000171.CrossRef

20.

Wu L, Lv P, Zhang H, Fu C, Yao X, Wang C, et al. Dynamic contrast-enhanced (DCE) MRI assessment of microvascular characteristics in the murine orthotopic pancreatic cancer model. Magn Reson Imaging. 2015;33:737–60. https://doi.org/10.1016/j.mri.2014.08.014.CrossRefPubMed

21.

Kim JH, Lee JM, Park JH, Kim SC, Joo I, Han JK, et al. Solid pancreatic lesions: characterization by using timing bolus dynamic contrast-enhanced MR imaging assessment--a preliminary study. Radiology. 2013;266:185–96. https://doi.org/10.1148/radiol.12120111.CrossRefPubMed

22.

Yao X, Zeng M, Wang H, Sun F, Rao S, Ji Y. Evaluation of pancreatic cancer by multiple breath-hold dynamic contrast-enhanced magnetic resonance imaging at 3.0T. Europe J Radiol. 2012;81:e917–22. https://doi.org/10.1016/j.ejrad.2012.05.011.CrossRef

23.

Akisik MF, Sandrasegaran K, Bu G, Lin C, Hutchins GD, Chiorean EG. Pancreatic cancer: utility of dynamic contrast-enhanced MR imaging in assessment of antiangiogenic therapy. Radiology. 2010;256:441–9. https://doi.org/10.1148/radiol.10091733.CrossRefPubMed

24.

Barral M, Taouli B, Guiu B, Koh DM, Luciani A, Manfredi R, et al. Diffusion-weighted MR imaging of the pancreas: current status and recommendations. Radiology. 2015;274:45–63. https://doi.org/10.1148/radiol.14130778.CrossRefPubMed

25.

De Robertis R, Tinazzi Martini P, Demozzi E, Dal Corso F, Bassi C, Pederzoli P, et al. Diffusion-weighted imaging of pancreatic cancer. World J Radiol. 2015;7:319–28. https://doi.org/10.4329/wjr.v7.i10.319.CrossRefPubMedPubMedCentral

26.

Hecht EM, Liu MZ, Prince MR, Jambawalikar S, Remotti HE, Weisberg SW, et al. Can diffusion-weighted imaging serve as a biomarker of fibrosis in pancreatic adenocarcinoma? J Magnet Res Imaging : JMRI. 2017;46:393–402. https://doi.org/10.1002/jmri.25581.CrossRef

27.

Ma W, Li N, Zhao W, Ren J, Wei M, Yang Y, et al. Apparent diffusion coefficient and dynamic contrast-enhanced magnetic resonance imaging in pancreatic cancer: characteristics and correlation with Histopathologic parameters. J Comput Assist Tomogr. 2016;40:709–16. https://doi.org/10.1097/RCT.0000000000000434.CrossRefPubMed

28.

Niwa T, Ueno M, Ohkawa S, Yoshida T, Doiuchi T, Ito K, et al. Advanced pancreatic cancer: the use of the apparent diffusion coefficient to predict response to chemotherapy. Br J Radiol. 2009;82:28–34. https://doi.org/10.1259/bjr/43911400.CrossRefPubMed

29.

Kurosawa J, Tawada K, Mikata R, Ishihara T, Tsuyuguchi T, Saito M, et al. Prognostic relevance of apparent diffusion coefficient obtained by diffusion-weighted MRI in pancreatic cancer. J Magnet Res Imaging : JMRI. 2015; https://doi.org/10.1002/jmri.24939.

30.

Penet MF, Shah T, Bharti S, Krishnamachary B, Artemov D, Mironchik Y, et al. Metabolic imaging of pancreatic ductal adenocarcinoma detects altered choline metabolism. Clin Cancer Res : Off J Am Assoc Canc Res. 2015;21:386–95. https://doi.org/10.1158/1078-0432.CCR-14-0964.CrossRef

31.

Battini S, Faitot F, Imperiale A, Cicek AE, Heimburger C, Averous G, et al. Metabolomics approaches in pancreatic adenocarcinoma: tumor metabolism profiling predicts clinical outcome of patients. BMC Med. 2017;15:56. https://doi.org/10.1186/s12916-017-0810-z.CrossRefPubMedPubMedCentral

32.

Nunna P, Sheikhbahaei S, Ahn S, Young B, Subramaniam RM. The role of positron emission tomography/computed tomography in management and prediction of survival in pancreatic cancer. J Comput Assist Tomogr. 2016;40:142–51. https://doi.org/10.1097/RCT.0000000000000323.CrossRefPubMed

33.

Chaika NV, Gebregiworgis T, Lewallen ME, Purohit V, Radhakrishnan P, Liu X, et al. MUC1 mucin stabilizes and activates hypoxia-inducible factor 1 alpha to regulate metabolism in pancreatic cancer. Proc Natl Acad Sci U S A. 2012;109:13787–92. https://doi.org/10.1073/pnas.1203339109.CrossRefPubMedPubMedCentral

34.

Li N, Li Y, Li Z, Huang C, Yang Y, Lang M, et al. Hypoxia inducible factor 1 (HIF-1) recruits macrophage to activate pancreatic Stellate cells in pancreatic Ductal Adenocarcinoma. Int J Mol Sci. 2016;17 https://doi.org/10.3390/ijms17060799.

35.

Hoffmann AC, Mori R, Vallbohmer D, Brabender J, Klein E, Drebber U, et al. High expression of HIF1a is a predictor of clinical outcome in patients with pancreatic ductal adenocarcinomas and correlated to PDGFA, VEGF, and bFGF. Neoplasia. 2008;10:674–9.CrossRefPubMedPubMedCentral

36.

Bali MA, Metens T, Denolin V, Delhaye M, Demetter P, Closset J, et al. Tumoral and nontumoral pancreas: correlation between quantitative dynamic contrast-enhanced MR imaging and histopathologic parameters. Radiology. 2011;261:456–66. https://doi.org/10.1148/radiol.11103515.CrossRefPubMed

Titel: Multiparametric PET/MR imaging biomarkers are associated with overall survival in patients with pancreatic cancer
verfasst von: Bang-Bin Chen
Yu-Wen Tien
Ming-Chu Chang
Mei-Fang Cheng
Yu-Ting Chang
Shih-Hung Yang
Chih-Horng Wu
Ting-Chun Kuo
I-Lun Shih
Ruoh-Fang Yen
Tiffany Ting-Fang Shih
Publikationsdatum: 23.02.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 7/2018
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-018-3960-0

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Multiparametric PET/MR imaging biomarkers are associated with overall survival in patients with pancreatic cancer

Abstract

Purpose

Methods

Results

Conclusion

Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusion

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