Diagnostic accuracy of dual-energy CT-based nomograms to predict lymph node metastasis in gastric cancer (original) (raw)

Abstract

Objectives

To develop and validate a dual-energy CT based nomogram for the preoperative prediction of lymph node metastasis (LNM) in patients with gastric cancer (GC).

Methods

A total of 210 surgically confirmed GC patients (159 males, 51 females; mean age: 59.8 ± 7.7 years, range: 28-79 years) who underwent spectral CT scans were retrospectively enrolled and split into a primary cohort (n = 140) and validation cohort (n = 70). Clinical information and follow-up data including overall survival (OS) and progression-free survival (PFS) were collected. The iodine concentration (IC) of the primary tumors at the arterial phase (AP) and venous phase (VP) were measured and then normalized to the aorta (nICs). Univariate, multivariable logistic regression and Cox regression analyses were performed to screen predictive indicators for LNM and outcome. A nomogram for risk factors of LNM was developed, and its performance was measured using the ROC, accuracy and Harrell’s concordance index (C-index).

Results

Tumor thickness, Borrmann classification and ICVP were independent predictors of LNM. The nomogram was significantly associated with LN status (p < 0.001). It yielded an AUC of 0.793 [95% confidence interval (95% CI), 0.678-0.908] and an accuracy of 0.757 (95% CI, 0.640-0.852) in the internal-validation cohort. The nomogram also exhibited a prognostic ability with C-indices of 0.675 (95% CI, 0.571-0.779; p < 0.001) for PFS and 0.643 (95% CI, 0.518-0.768; p = 0.025) for OS.

Conclusion

This study presented a dual-energy quantification-based nomogram, which can be used to facilitate the preoperative individualized prediction of LNM in patients with GC.

Key Points

• This study first developed and internally validated a dual-energy CT-based nomogram to predict lymph node metastasis in patients with gastric cancer.

• The nomogram incorporated the clinical risk factors and iodine concentration, which would enable superior preoperative individual prediction of lymph node metastasis and add more information for the optimal therapeutic strategy.

• The nomogram also exhibited a significant prognostic ability for progression-free and overall survival.

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Abbreviations

AP:

Arterial phase

AUC:

Area under the curve

EUS:

Endoscopic ultrasonography

GC:

Gastric cancer

GSI:

Gem spectral imaging

IC:

Iodine concentration

LNM:

Lymph node metastasis

MRI:

Magnetic resonance imaging

MVD:

Microvessel density

NCCN:

National Comprehensive Cancer Network

PET/CT:

Positron emission tomography/computed tomography

PNR:

Positive node ratio

ROI:

Region of interest

T:

Tumor

VEGF:

Vascular endothelial growth factor

VP:

Venous phase

References

  1. Ferlay J, Soerjomataram I, Dikshit R et al (2015) Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 136:E359–E386
    Article CAS Google Scholar
  2. GLOBOCAN (2012) Stomach Cancer: Estimated Incidence, Mortality and Prevalence Worldwide in 2012. Available at: http://globocan.iarc.fr/old/FactSheets/cancers/stomach-new.asp Accessed November 4, 2014
  3. Shen L, Shan Y, Hu H et al (2013) Management of gastric cancer in Asia: resource-stratified guidelines. Lancet Oncology 14:e535–e547
    Article Google Scholar
  4. Chen W, Zheng R, Baade PD et al (2016) Cancer statistics in China, 2015. CA Cancer J Clin 66:115–132
    Article Google Scholar
  5. Kim JP, Hur YS, Yang HK (1995) Lymph node metastasis as a significant prognostic factor in early gastric cancer: analysis of 1,136 early gastric cancers. Ann Surg Oncol 2:308–313
    Article CAS Google Scholar
  6. Oka S, Tanaka S, Kaneko I et al (2006) Advantage of endoscopic submucosal dissection compared with EMR for early gastric cancer. Gastrointest Endosc 64:877–883
    Article Google Scholar
  7. Ajani JA, Bentrem DJ, Besh S et al (2013) Gastric cancer, version 2.2013: featured updates to the NCCN Guidelines. J Natl Compr Canc Netw 11:531–546
    Article CAS Google Scholar
  8. Hyung WJ, Cheong JH, Kim J, Chen J, Choi SH, Noh SH (2004) Application of minimally invasive treatment for early gastric cancer. J Surg Oncol 85:181–185
    Article Google Scholar
  9. Yamashita K, Hosoda K, Ema A, Watanabe M (2016) Lymph node ratio as a novel and simple prognostic factor in advanced gastric cancer. Eur J Surg Oncol 42:1253–1260
    Article CAS Google Scholar
  10. Persiani R, Rausei S, Biondi A, Boccia S, Cananzi F, D'Ugo D (2008) Ratio of metastatic lymph nodes: impact on staging and survival of gastric cancer. Eur J Surg Oncol 34:519–524
    Article CAS Google Scholar
  11. National Comprehensive Cancer Network (NCCN) guidelines. Available online: http://www.nccn.org/ (accessed on 26 July 2017).
  12. Kwee RM, Kwee TC (2016) Imaging in local staging of gastric cancer: a systematic review. J Clin Oncol 25:2107–2116
    Article Google Scholar
  13. Sussman SK, Halvorsen RA Jr, Illescas FF et al (1988) Gastric adenocarcinoma: CT versus surgical staging. Radiology 167:335–340
    Article CAS Google Scholar
  14. Botet JF, Lightdale CJ, Zauber AG et al (1991) Preoperative staging of gastric cancer: comparison of endoscopic US and dynamic CT. Radiology 181:426–432
    Article CAS Google Scholar
  15. Ziegler K, Sanft C, Zimmer T (1994) Comparison of computed tomography, endosonography, and intraoperative assessment in TN staging of gastric carcinoma. Gut 35:287–288
    Google Scholar
  16. Lv P, Lin X, Gao J, Chen K (2012) Spectral CT: preliminary studies in the liver cirrhosis. Korean J Radiol 13:434–442
    Article Google Scholar
  17. Zhang XF, Lu Q, Wu LM, Zou AH, Hua XL, Xu JR (2013) Quantitative iodine-based material decomposition images with spectral CT imaging for differentiating prostatic carcinoma from benign prostatic hyperplasia. Acad Radiol 20:947–956
    Article CAS Google Scholar
  18. Lv P, Lin XZ, Li J, Li W, Chen K (2011) Differentiation of small hepatic hemangioma from small hepatocellular carcinoma: recently introduced spectral CT method. Radiology 259:720–729
    Article Google Scholar
  19. Tang L, Li ZY, Li ZW et al (2015) Evaluating the response of gastric carcinomas to neoadjuvant chemotherapy using iodine concentration on spectral CT: a comparison with pathological regression. Clin Radiol 70:1198–1204
    Article CAS Google Scholar
  20. Pan Z, Pang L, Ding B et al (2013) Gastric cancer staging with dual energy spectral CT imaging. PLoS One 8:e53651
    Article CAS Google Scholar
  21. Klar M, Jochmann A, Foeldi M et al (2008) The MSKCC nomogram for prediction the likelihood of non-sentinel node involvement in a German breast cancer population. Breast Cancer Res Treat. 112:523–531
    Article CAS Google Scholar
  22. Briganti A, Larcher A, Abdollah F et al (2012) Updated nomogram predicting lymph node invasion in patients with prostate cancer undergoing extended pelvic lymph node dissection: the essential importance of percentage of positive cores. Eur Urol 61:480–487
    Article Google Scholar
  23. Zheng Z, Zhang Y, Zhang L et al (2016) A nomogram for predicting the likelihood of lymph node metastasis in early gastric patients. BMC Cancer 16:92–99
    Article Google Scholar
  24. Jin EH, Lee DH, Jung SA et al (2015) Clinicopathologic factors and molecular markers related to lymph node metastasis in early gastric cancer. World J Gastroenterol 21:571–577
    Article Google Scholar
  25. Liu S, Zhang Y, Chen L et al (2017) Whole-lesion apparent diffusion coefficient histogram analysis: significance in T and N staging of gastric cancers. BMC Cancer 17:665–674
    Article Google Scholar
  26. Gotoda T, Yanagisawa A, Sasako M et al (2000) Incidence of lymph node metastasis from early gastric cancer: estimation with a large number of cases at two large centers. Gastric Cancer 3:219–225
    Article Google Scholar
  27. Sekiguchi M, Oda I, Taniguchi H et al (2016) Risk stratification and predictive risk-scoring model for lymph node metastasis in early gastric cancer. J Gastroenterol 51:961–970
    Article CAS Google Scholar
  28. Ahmad R, Setia N, Schmidt BH et al (2016) Predictors of lymph node metastasis in Western early gastric cancer. J Gastrointest Surg 20:531–538
    Article Google Scholar
  29. Chen XH, Ken K, Liang P, Chai YR, Chen KS, Gao JB (2017) Spectral computed tomography in advanced gastric cancer: can iodine concentration non-invasively assess angiogenesis? World J Gastroenterol 23:1666–1675
    Article CAS Google Scholar
  30. Lv P, Liu J, Yan X et al (2017) CT spectral imaging for monitoring the therapeutic efficacy of VEGF receptor kinase inhibitor AG-013736 in rabbit VX2 liver tumours. Eur Radiol 27:918–926
    Article Google Scholar
  31. Hu S, Huang W, Chen Y et al (2014) Spectral CT evaluation of interstitial brachytherapy in pancreatic carcinoma xenografts: preliminary animal experience. Eur Radiol 24:2167–2173
    Article Google Scholar
  32. Thaiss WM, Haberland U, Kaufmann S et al (2016) Iodine concentration as a perfusion surrogate marker in oncology: further elucidation of the underlying mechanisms using volume perfusion CT with 80 kVp. Eur Radiol 26:2929–2936
    Article Google Scholar
  33. Matsui H, Anno H, Uyama I et al (2007) Relatively small size linitis plastica of the stomach: multislice CT detection of tissue fibrosis. Abdom Imaging 32:694–697
    Article Google Scholar
  34. Silva AC, Morse BG, Hara AK, Paden RG, Hongo N, Pavlicek W (2011) Dual-energy (spectral) CT: applications in abdominal imaging. Radiographics 31:1031–1046
    Article Google Scholar

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Funding

This study has received funding by National Natural and Science Fund of China (no. 81271573).

Author information

Author notes

  1. Jing Li and Mengjie Fang contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital of Zhengzhou University, No. 1, East Jianshe Road, Zhengzhou, 450052, Henan, China
    Jing Li, Rui Wang, Pan Liang, Jie Liu & Jianbo Gao
  2. Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou, 450008, Henan, China
    Jing Li
  3. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
    Mengjie Fang, Di Dong & Jie Tian
  4. University of Chinese Academy of Sciences, Beijing, 100190, China
    Mengjie Fang, Di Dong & Jie Tian

Authors

  1. Jing Li
  2. Mengjie Fang
  3. Rui Wang
  4. Di Dong
  5. Jie Tian
  6. Pan Liang
  7. Jie Liu
  8. Jianbo Gao

Corresponding author

Correspondence toJianbo Gao.

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Guarantor

The scientific guarantor of this publication is Jianbo Gao.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Written informed consent was waived by the Institutional Review Board of Zhengzhou University.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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Li, J., Fang, M., Wang, R. et al. Diagnostic accuracy of dual-energy CT-based nomograms to predict lymph node metastasis in gastric cancer.Eur Radiol 28, 5241–5249 (2018). https://doi.org/10.1007/s00330-018-5483-2

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