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Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs)

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Abstract

Purpose

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features.

Methods

Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared.

Results

Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10–25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50–78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18–0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004).

Conclusion

Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

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References

  1. Kim SH, Lee JM, Lee ES, et al. (2015) Intraductal papillary mucinous neoplasms of the pancreas: evaluation of malignant potential and surgical resectability by using MR imaging with MR cholangiography. Radiology 274:723–733. doi:10.1148/radiol.14132960

    Article  PubMed  Google Scholar 

  2. Lim JH, Lee G, Oh YL (2001) Radiologic spectrum of intraductal papillary mucinous tumor of the pancreas. Radiographics 21:323–337. doi:10.1148/radiographics.21.2.g01mr01323

    Article  CAS  PubMed  Google Scholar 

  3. Campbell NM, Katz SS, Escalon JG, Do RK (2015) Imaging patterns of intraductal papillary mucinous neoplasms of the pancreas: an illustrated discussion of the International Consensus Guidelines for the Management of IPMN. Abdom Imaging 40:663–677. doi:10.1007/s00261-014-0236-4

    Article  PubMed  Google Scholar 

  4. Tanaka M, Fernandez-del Castillo C, Adsay V, et al. (2012) International consensus guidelines 2012 for the management of IPMN and MCN of the pancreas. Pancreatology 12:183–197. doi:10.1016/j.pan.2012.04.004

    Article  PubMed  Google Scholar 

  5. Jang DK, Ryu JK, Chung KH, et al. (2015) Risk factors for progression or malignancy in main-duct and mixed-type intraductal papillary mucinous neoplasm of the pancreas. Pancreas 45:1027–1031. doi:10.1097/MPA.0000000000000592

    Article  Google Scholar 

  6. Hackert T, Fritz S, Klauss M, et al. (2015) Main-duct intraductal papillary mucinous neoplasm: high cancer risk in duct diameter of 5 to 9 mm. Ann Surg 262:875–880. doi:10.1097/SLA.0000000000001462

    Article  PubMed  Google Scholar 

  7. Kawamoto S, Horton KM, Lawler LP, Hruban RH, Fishman EK (2005) Intraductal papillary mucinous neoplasm of the pancreas: can benign lesions be differentiated from malignant lesions with multidetector CT? Radiographics 25:1451–1468. doi:10.1148/rg.256055036

    Article  PubMed  Google Scholar 

  8. Tang RS, Weinberg B, Dawson DW, et al. (2008) Evaluation of the guidelines for management of pancreatic branch-duct intraductal papillary mucinous neoplasm. Clin Gastroenterol H 6:815–819. doi:10.1016/j.cgh.2008.04.005

    Article  Google Scholar 

  9. Pelaez-Luna M, Chari S, Smyrk TC, et al. (2007) Do consensus indications for resection in branch duct intraductal papillary mucinous neoplasm predict malignancy? A study of 147 patients. Am J Gastroenterol 102(8):1759–1764. doi:10.1111/j.1572-0241.2007.01224.x

    Article  PubMed  Google Scholar 

  10. Koh DM, Collins DJ (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188:1622–1635. doi:10.2214/AJR.06.1403

    Article  PubMed  Google Scholar 

  11. Padhani AR, Liu G, Koh DM, et al. (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125. doi:10.1593/neo.81328

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kwee TC, Takahara T, Ochiai R, et al. (2009) Whole-body diffusion-weighted magnetic resonance imaging. Eur J Radiol 70:409–417. doi:10.1016/j.ejrad.2009.03.054

    Article  PubMed  Google Scholar 

  13. Barral M, Taouli B, Guiu B, et al. (2015) Diffusion-weighted MR imaging of the pancreas: current status and recommendations. Radiology 274:45–63. doi:10.1148/radiol.14130778

    Article  PubMed  Google Scholar 

  14. Kang KM, Lee JM, Shin CI, et al. (2013) Added value of diffusion-weighted imaging to MR cholangiopancreatography with unenhanced mr imaging for predicting malignancy or invasiveness of intraductal papillary mucinous neoplasm of the pancreas. J Magn Reson Imaging 38:555–563. doi:10.1002/jmri.24022

    Article  PubMed  Google Scholar 

  15. Ogawa T, Horaguchi J, Fujita N, et al. (2014) Diffusion-weighted magnetic resonance imaging for evaluating the histological degree of malignancy in patients with intraductal papillary mucinous neoplasm. J Hepatobiliary Panreat Sci 21:801–808. doi:10.1002/jhbp.135

    Article  Google Scholar 

  16. Fatima Z, Ichikawa T, Motosugi U, et al. (2011) Magnetic resonance diffusion-weighted imaging in the characterization of pancreatic mucinous cystic lesions. Clin Radiol 66:108–111. doi:10.1016/j.crad.2010.10.004

    Article  CAS  PubMed  Google Scholar 

  17. Sandrasegaran K, Akisik FM, Patel AA, et al. (2011) Diffusion-weighted imaging in characterization of cystic pancreatic lesions. Clin Radiol 66:808–814. doi:10.1016/j.crad.2011.01.016

    Article  CAS  PubMed  Google Scholar 

  18. Rosenkrantz AB (2013) Histogram-based apparent diffusion coefficient analysis: an emerging tool for cervical cancer characterization? AJR Am J Roentgenol 200:311–313. doi:10.2214/AJR.12.9926

    Article  PubMed  Google Scholar 

  19. Rosenkrantz AB, Obele C, Rusinek H, et al. (2015) Whole-lesion diffusion metrics for assessment of bladder cancer aggressiveness. Abdom Imaging 40:327–332. doi:10.1007/s00261-014-0213-y

    Article  PubMed  Google Scholar 

  20. Cho SH, Kim GC, Jang YJ, et al. (2015) Locally advanced rectal cancer: post-chemoradiotherapy ADC histogram analysis for predicting a complete response. Acta Radiol 56:1042–1050. doi:10.1177/0284185114550193

    Article  PubMed  Google Scholar 

  21. Kierans AS, Bennet GL, Mussi TC, et al. (2013) Characterization of malignancy of adnexal lesions using ADC entropy: comparison with mean ADC and qualitative DWI assessment. J Magn Reson Imaging 37:164–171. doi:10.1002/jmri.23794

    Article  PubMed  Google Scholar 

  22. Donati OF, Mazaheri Y, Afaq A, et al. (2014) Prostate cancer aggressiveness: assessment with whole-lesion histogram analysis of the apparent diffusion coefficient. Radiology 271:143–152. doi:10.1148/radiol.13130973

    Article  PubMed  Google Scholar 

  23. Downey K, Riches SF, Morgan VA, et al. (2013) Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images. AJR Am J Roentgenol 200:314–320. doi:10.2214/AJR.12.9545

    Article  PubMed  Google Scholar 

  24. Poussaint TY, Vajapeyam S, Ricci KI, et al. (2016) Apparent diffusion coefficient histogram metrics correlate with survival in diffuse intrinsic pontine glioma: a report from the Pediatric Brain Tumor Consortium. Neuro Oncol 18:725–734. doi:10.1093/neuonc/nov256

    Article  PubMed  Google Scholar 

  25. Doric D, Nikolic-Doric E, Jevremovic V, Malisic J (2009) On measuring skewness and kurtosis. Qual Quant 43:481–493. doi:10.1007/s11135-007-9128-9

    Article  Google Scholar 

  26. DeCarlo LT (1997) On the meaning and use of kurtosis. Psychol Methods 3:292–307. doi:10.1037//1082-989x.2.3.292

    Article  Google Scholar 

  27. Foroutan P, Kreahling JM, Morse DL, et al. (2013) Diffusion MRI and novel texture analysis in osteosarcoma xenotransplants predicts response to anti-checkpoint therapy. PLoS ONE 12:e82875. doi:10.1371/journal.pone.0082875

    Article  Google Scholar 

  28. Gupta R, Mortele KJ, Tatli S, et al. (2008) Pancreatic intraductal papillary mucinous neoplasms: role of CT in predicting pathologic subtypes. AJR Am J Roentgenol 191:1458–1464. doi:10.2214/AJR.07.3302

    Article  PubMed  Google Scholar 

  29. Rosenkrantz AB, Ream JM, Nolan P, et al. (2015) Prostate cancer: utility of whole-lesion apparent diffusion coefficient metrics for prediction of biochemical recurrence after radical prostatectomy. AJR Am J Roentgenol 205:1208–1214. doi:10.2214/AJR.15.14482

    Article  PubMed  PubMed Central  Google Scholar 

  30. Farnell MB (2008) Surgical management of intraductal papillary mucinous neoplasm (IPMN) of the pancreas. J Gastrointest Surg 12:414–416. doi:10.1007/s11605-007-0349-y

    Article  PubMed  Google Scholar 

  31. Chang Y, Paul AK, Kim N, et al. (2016) Computer-aided diagnosis for classifying benign versus malignant thyroid nodules based on ultrasound images: a comparison with radiologist-based assessments. Med Phys 43:554. doi:10.1118/1.4939060

    Article  PubMed  Google Scholar 

  32. Barry B, Buch K, Soto JA, et al. (2014) Quantifying liver fibrosis through the application of texture analysis to diffusion weighted imaging. Magn Reson Imaging 32:84–90. doi:10.1016/j.mri.2013.04.006

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology, NYU School of Medicine, Center for Biomedical Imaging, NYU Langone Medical Center, 660 First Avenue, 3rd Floor, New York, NY, 10016, USA

    David H. Hoffman, Justin M. Ream & Andrew B. Rosenkrantz

  2. Department of Pathology, NYU Langone Medical Center, New York, NY, 10016, USA

    Christina H. Hajdu

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  1. David H. Hoffman
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  2. Justin M. Ream
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  4. Andrew B. Rosenkrantz
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Corresponding author

Correspondence to David H. Hoffman.

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No funding was received for this study.

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The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

The requirement for written informed consent was waived by the IRB.

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The NYU School of Medicine Institutional Review Board approved this study.

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Hoffman, D.H., Ream, J.M., Hajdu, C.H. et al. Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs). Abdom Radiol 42, 1222–1228 (2017). https://doi.org/10.1007/s00261-016-1001-7

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