Skip to main content
SpringerLink
Log in

Risk stratification of abdominal tumors in children with amide proton transfer imaging

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To evaluate the potential of molecular amide proton transfer (APT) MRI for predicting the risk group of abdominal tumors in children, and compare it with quantitative T1 and T2 mapping.

Methods

This prospective study enrolled 133 untreated pediatric patients with suspected abdominal tumors from February 2019 to September 2020. APT-weighted (APTw) imaging and quantitative relaxation time mapping sequences were executed for each subject. The region of interest (ROI) was generated with automatic artifact detection and ROI-shrinking algorithms, within which the APTw, T1, and T2 indices were calculated and compared between different risk groups. The prediction performance of different imaging parameters was assessed with the receiver operating characteristics (ROC) analysis and Student’s t-test.

Results

Fifty-seven patients were included in the final analysis, including 24 neuroblastomas (NB), 18 Wilms’ tumors (WT), and 15 hepatoblastomas (HB). The APTw signal was significantly (p < .001) higher in patients with high-risk NB than those with low-risk NB, while the difference between patients with low-risk and high-risk WT (p = .69) or HB (p = .35) was not statistically significant. The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk NB, WT, and HB were 0.93, 0.58, and 0.71, respectively. The quantitative T1 and T2 values generated AUCs of 0.61–0.70 for the risk stratification of abdominal tumors.

Conclusions

APT MRI is a potential imaging biomarker for stratifying the risk group of pediatric neuroblastoma in the abdomen preoperatively and provides added value to structural MRI.

Key Points

• Amide proton transfer (APT) imaging showed significantly (p < .001) higher values in pediatric patients with high-risk neuroblastoma than those with low-risk neuroblastoma, but did not demonstrate a significant difference in patients with Wilms’ tumor (p = .69) or hepatoblastoma (p = .35).

• The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk neuroblastoma, Wilms’ tumor, and hepatoblastoma were 0.93, 0.58, and 0.71, respectively.

• The quantitative T1 and T2 indices generated AUCs of 0.61–0.70 for dichotomizing the risk group of abdominal tumors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

APT:

Amide proton transfer

APTw:

Amide proton transfer-weighted

CEST:

Chemical exchange saturation transfer

HB:

Hepatoblastoma

MIX:

Interleaved T1 and T2 mapping sequence

NB:

Neuroblastoma

T1w:

T1-weighted

T2w:

T2-weighted

WT:

Wilms’ tumor

References

  1. Steliarova-Foucher E, Colombet M, Ries LAG et al (2017) International incidence of childhood cancer, 2001–10: a population-based registry study. Lancet Oncol 18:719–731

    Article  Google Scholar 

  2. Maris JM, Hogarty MD, Bagatell R, Cohn SL (2007) Neuroblastoma. Lancet 369:2106–2120

    Article  CAS  Google Scholar 

  3. Hiorns M, Owens C (2001) Radiology of neuroblastoma in children. Eur Radiol 11:2071–2081

    Article  CAS  Google Scholar 

  4. Davidoff AM (2012) Wilms tumor. Adv Pediatr 59:247–267

    Article  Google Scholar 

  5. Herzog CE, Andrassy RJ, Eftekhari F (2000) Childhood cancers: hepatoblastoma. Oncologist 5:445–453

    Article  CAS  Google Scholar 

  6. Cohn SL, Pearson ADJ, London WB et al (2009) The International Neuroblastoma Risk Group (INRG) Classification System: an INRG Task Force report. J Clin Oncol 27:289–297

    Article  Google Scholar 

  7. Vujanic GM, Sandstedt B, Harms D et al (2002) Revised International Society of Paediatric Oncology (SIOP) working classification of renal tumors of childhood. Med Pediatr Oncol 38:79–82

    Article  Google Scholar 

  8. Meyers RL, Maibach R, Hiyama E et al (2017) Risk-stratified staging in paediatric hepatoblastoma: a unified analysis from the Children’s Hepatic tumors International Collaboration. Lancet Oncol 18:122–131

    Article  Google Scholar 

  9. Van Zijl PCM, Yadav NN (2011) Chemical exchange saturation transfer (CEST): What is in a name and what isn’t? Magn Reson Med 65:927–948

    Article  Google Scholar 

  10. Zhou J, Payen J-F, Wilson DA, Traystman RJ, van Zijl PC (2003) Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med 9:1085–1090

    Article  CAS  Google Scholar 

  11. Zhou JY, Tryggestad E, Wen ZB et al (2011) Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides. Nat Med 17:130-U308

    Article  CAS  Google Scholar 

  12. Togao O, Yoshiura T, Keupp J et al (2014) Amide proton transfer imaging of adult diffuse gliomas: correlation with histopathological grades. Neuro Oncol 16:441–448

    Article  CAS  Google Scholar 

  13. Kamitani T, Sagiyama K, Togao O et al (2020) Amide proton transfer (APT) imaging of parotid tumors: differentiation of malignant and benign tumors. Eur J Radiol 129:109047

    Article  Google Scholar 

  14. Ohno Y, Yui M, Koyama H et al (2016) Chemical exchange saturation transfer MR imaging: preliminary results for differentiation of malignant and benign thoracic lesions. Radiology 279:578–589

    Article  Google Scholar 

  15. Liu R, Zhang H, Niu W et al (2019) Improved chemical exchange saturation transfer imaging with real-time frequency drift correction. Magn Reson Med 81:2915–2923

    Article  CAS  Google Scholar 

  16. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P (1999) SENSE: sensitivity encoding for fast MRI. Magn Reson Med 42:952–962

    Article  CAS  Google Scholar 

  17. Zhou J, Zhu H, Lim M et al (2013) Three-dimensional amide proton transfer MR imaging of gliomas: initial experience and comparison with gadolinium enhancement. J Magn Reson Imaging 38:1119–1128

    Article  Google Scholar 

  18. Zhu H, Jones CK, Van Zijl PCM, Barker PB, Zhou J (2010) Fast 3D chemical exchange saturation transfer (CEST) imaging of the human brain. Magn Reson Med 64:638–644

    Article  Google Scholar 

  19. Heo HY, Zhang Y, Jiang S, Lee DH, Zhou J (2016) Quantitative assessment of amide proton transfer (APT) and nuclear overhauser enhancement (NOE) imaging with extrapolated semisolid magnetization transfer reference (EMR) signals: II. Comparison of three EMR models and application to human brain glioma at 3 Tesla. Magn Reson Med 75:1630–1639

    Article  CAS  Google Scholar 

  20. In Den Kleef JJE, Cuppen JJM (1987) RLSQ:T1, T2, and ρ calculations, combining ratios and least squares. Magn Reson Med 5:513–524

    Article  CAS  Google Scholar 

  21. Zhang H, Lai C, Liu R et al (2019) Age-specific optimization of T1-weighted brain MRI throughout infancy. Neuroimage 199:387–395

    Article  Google Scholar 

  22. Zhang Y, Heo HY, Lee DH et al (2016) Selecting the reference image for registration of CEST series. J Magn Reson Imaging 43:756–761

    Article  Google Scholar 

  23. Jenkinson M (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17:825–841

    Article  Google Scholar 

  24. Kim M, Gillen J, Landman BA, Zhou J, van Zijl P (2009) Water saturation shift referencing (WASSR) for chemical exchange saturation transfer (CEST) experiments. Magn Reson Med 61:1441–1450

    Article  Google Scholar 

  25. Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29–36

    Article  CAS  Google Scholar 

  26. Hanley JA, McNeil BJ (1983) A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 148:839–843

    Article  CAS  Google Scholar 

  27. Pinto NR, Applebaum MA, Volchenboum SL et al (2015) Advances in risk classification and treatment strategies for neuroblastoma. J Clin Oncol 33:3008–3017

    Article  CAS  Google Scholar 

  28. von Schweinitz D (2012) Hepatoblastoma: recent developments in research and treatment. Semin Pediatr Surg 21:21–30

    Article  Google Scholar 

  29. D’Angio GJ, Breslow N, Beckwith JB et al (1989) Treatment of Wilms’ tumor. Results of the third national Wilms’ tumor study. Cancer 64:349–360

    Article  CAS  Google Scholar 

  30. Zaiss M, Windschuh J, Paech D et al (2015) Relaxation-compensated CEST-MRI of the human brain at 7 T: unbiased insight into NOE and amide signal changes in human glioblastoma. Neuroimage 112:180–188

    Article  Google Scholar 

  31. Park JE, Kim HS, Park KJ, Choi CG, Kim SJ (2015) Histogram analysis of amide proton transfer imaging to identify contrast-enhancing low-grade brain tumor that mimics high-grade tumor: increased accuracy of MR perfusion. Radiology 277:151–161

    Article  Google Scholar 

  32. Wen Z, Hu S, Huang F et al (2010) MR imaging of high-grade brain tumors using endogenous protein and peptide-based contrast. Neuroimage 51:616–622

    Article  Google Scholar 

  33. Sagiyama K, Mashimo T, Togao O et al (2014) In vivo chemical exchange saturation transfer imaging allows early detection of a therapeutic response in glioblastoma. Proc Natl Acad Sci U S A 111:4542–4547

  34. Park JR, Eggert A, Caron H (2008) Neuroblastoma: biology, prognosis, and treatment. Pediatr Clin North Am 55:97–120

    Article  Google Scholar 

  35. Aherne W, Buck P (1971) The potential cell population doubling time in neuroblastoma and nephroblastoma. Br J Cancer 25:691–696

    Article  CAS  Google Scholar 

  36. Liu CJ, Lu MY, Liu YL et al (2017) Risk stratification of pediatric patients with neuroblastoma using volumetric parameters of 18F-FDG and 18F-DOPA PET/CT. Clin Nucl Med 42:e142–e148

    Article  Google Scholar 

  37. Zhang Y, Yong X, Liu R et al (2020) Whole-brain chemical exchange saturation transfer imaging with optimized turbo spin echo readout. Magn Reson Med 84:1161–1172

    Article  CAS  Google Scholar 

Download references

Funding

This study has received funding by National Natural Science Foundation of China (grant number: 81971605, 61801421, 61801424, and 91859201) and Ministry of Science and Technology of the People’s Republic of China (grant number: 2018YFE0114600). Leading Innovation and Entrepreneurship Team of Zhejiang Province: 2020R01003. This work was supported by the MOE Frontier Science Center for Brain Science & Brain-Machine Integration, Zhejiang University.

Author information

Author notes

  1. Xuan Jia and Wenqi Wang contributed equally to this work

Authors and Affiliations

  1. Department of Radiology, Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

    Xuan Jia, Jiawei Liang, Xiaohui Ma & Can Lai

  2. Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China

    Wenqi Wang, Dan Wu & Yi Zhang

  3. Philips Healthcare, Shanghai, China

    Weibo Chen

Authors
  1. Xuan Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenqi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiawei Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaohui Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Weibo Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Can Lai
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yi Zhang.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Yi Zhang.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Philips Healthcare (employee: Weibo Chen).

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• diagnostic or prognostic study

• performed at one institution

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 1.40 MB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jia, X., Wang, W., Liang, J. et al. Risk stratification of abdominal tumors in children with amide proton transfer imaging. Eur Radiol 32, 2158–2167 (2022). https://doi.org/10.1007/s00330-021-08376-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-021-08376-w

Keywords

Search

Navigation