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Pediatric PET/MRI Neuroimaging: Overview

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Hybrid PET/MR Neuroimaging

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Abstract

Modern pediatric imaging seeks not only to provide exceptional anatomic but also to provide physiologic and metabolic information of the pathology in question with as little radiation penalty as possible. 18F-FDG (FDG) PET/MRI attempts to combine exquisite soft tissue information obtained with MRI with metabolic information provided by PET. In pediatric neuro-oncology, PET/MRI is in many ways ideal for follow-up compared to PET/CT, given superiority of MRI in neuroradiology compared to CT and lower radiation dose, which is especially relevant in serial imaging of pediatric patients. PET/MRI has proven especially useful for diagnosis and follow-up in pediatric sarcomas and lymphomas and appears promising for a number of other malignancies. Major limitation of PET/MRI is evaluation of lung metastases, although there is extensive research into development of novel tools in this area. This chapter covers pediatric applications of PET/MRI in addition to considerations regarding tracer and protocols and current challenges to clinical implementation.

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References

  1. Kleis M, Daldrup-Link H, Matthay K, et al. Diagnostic value of PET/CT for the staging and restaging of pediatric tumors. Eur J Nucl Med Mol Imaging. 2009;36(1):23–36.

    Article  Google Scholar 

  2. Gelfand MJ, Sharp SE, Treves ST, Fahey FH, Parisi MT, Alessio AM. Estimated cumulative radiation dose from PET/CT in children with malignancies. Pediatr Radiol. 2010;40(10):1712–3; author reply 4–5.

    Article  Google Scholar 

  3. Chawla SC, Federman N, Zhang D, et al. Estimated cumulative radiation dose from PET/CT in children with malignancies: a 5-year retrospective review. Pediatr Radiol. 2010;40(5):681–6.

    Article  Google Scholar 

  4. Mathews JD, Forsythe AV, Brady Z, et al. Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians. BMJ. 2013;f2360:346.

    Google Scholar 

  5. Pearce MS, Salotti JA, Little MP, et al. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet. 2012;380(9840):499–505.

    Article  Google Scholar 

  6. Daldrup-Link H. How PET/MR can add value for children with cancer. Curr Radiol Rep. 2017;5(3):15.

    Google Scholar 

  7. Bezrukov I, Schmidt H, Gatidis S, et al. Quantitative evaluation of segmentation- and atlas-based attenuation correction for PET/MR on pediatric patients. J Nucl Med. 2015;56(7):1067–74.

    Article  Google Scholar 

  8. Hirsch FW, Sattler B, Sorge I, et al. PET/MR in children. Initial clinical experience in paediatric oncology using an integrated PET/MR scanner. Pediatr Radiol. 2013;43(7):860–75.

    Article  Google Scholar 

  9. Ponisio MR, McConathy J, Laforest R, Khanna G. Evaluation of diagnostic performance of whole-body simultaneous PET/MRI in pediatric lymphoma. Pediatr Radiol. 2016;46(9):1258–68.

    Article  Google Scholar 

  10. Purz S, Sabri O, Viehweger A, et al. Potential pediatric applications of PET/MR. J Nucl Med. 2014;55:32s–9s.

    Article  CAS  Google Scholar 

  11. Schafer JF, Gatidis S, Schmidt H, et al. Simultaneous whole-body PET/MR imaging in comparison to PET/CT in pediatric oncology: initial results. Radiology. 2014;273(1):220–31.

    Article  Google Scholar 

  12. Schmall JP, Surti S, Otero H, Servaes S, Karp JS, States LJ. Investigating low-dose image quality in whole-body pediatric (18)F-FDG scans using TOF-PET/MRI. J Nucl Med. 2021;62:123–30.

    Google Scholar 

  13. Chen KT, Gong E, de Carvalho Macruz FB, et al. Ultra-low-dose (18)F-Florbetaben amyloid PET imaging using deep learning with multi-contrast MRI inputs. Radiology. 2019;290(3):649–56.

    Article  Google Scholar 

  14. Chen KT, Gong E, de Carvalho Macruz FB, et al. Ultra-low-dose (18)F-florbetaben amyloid PET imaging using deep learning with multi-contrast MRI inputs. Radiology. 2020;296(3):E195.

    Article  Google Scholar 

  15. Kaplan S, Zhu YM. Full-dose PET image estimation from low-dose PET image using deep learning: a pilot study. J Digit Imaging. 2019;32(5):773–8.

    Article  Google Scholar 

  16. Liu H, Wu J, Lu W, Onofrey JA, Liu YH, Liu C. Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET. Phys Med Biol. 2020;65(18):185006.

    Article  CAS  Google Scholar 

  17. Muehe AM, Theruvath AJ, Lai L, et al. How to provide gadolinium-free PET/MR cancer staging of children and young adults in less than 1 h: the Stanford approach. Mol Imaging Biol. 2018;20(2):324–35.

    Article  CAS  Google Scholar 

  18. Punwani S, Taylor SA, Bainbridge A, et al. Pediatric and adolescent lymphoma: comparison of whole-body STIR half-Fourier RARE MR imaging with an enhanced PET/CT reference for initial staging. Radiology. 2010;255(1):182–90.

    Article  Google Scholar 

  19. Kwee TC, van Ufford HM, Beek FJ, et al. Whole-body MRI, including diffusion-weighted imaging, for the initial staging of malignant lymphoma: comparison to computed tomography. Investig Radiol. 2009;44(10):683–90.

    Article  Google Scholar 

  20. Kwee TC, Takahara T, Ochiai R, et al. Whole-body diffusion-weighted magnetic resonance imaging. Eur J Radiol. 2009;70(3):409–17.

    Article  Google Scholar 

  21. Krohmer S, Sorge I, Krausse A, et al. Whole-body MRI for primary evaluation of malignant disease in children. Eur J Radiol. 2010;74(1):256–61.

    Article  CAS  Google Scholar 

  22. Klenk C, Gawande R, Uslu L, et al. Ionising radiation-free whole-body MRI versus F-18-fluorodeoxyglucose PET/CT scans for children and young adults with cancer: a prospective, non-randomised, single-centre study. Lancet Oncol. 2014;15(3):275–85.

    Article  Google Scholar 

  23. Ishiguchi H, Ito S, Kato K, et al. Diagnostic performance of (18)F-FDG PET/CT and whole-body diffusion-weighted imaging with background body suppression (DWIBS) in detection of lymph node and bone metastases from pediatric neuroblastoma. Ann Nucl Med. 2018;32(5):348–62.

    Article  CAS  Google Scholar 

  24. Maggialetti N, Ferrari C, Minoia C, et al. Role of WB-MR/DWIBS compared to 18F-FDG PET/CT in the therapy response assessment of lymphoma. Radiol Med. 2016;121(2):132–43.

    Article  Google Scholar 

  25. Pareek A, Muehe AM, Theruvath AJ, Gulaka PK, Spunt SL, Daldrup-Link HE. Whole-body PET/MRI of pediatric patients: the details that matter. J Vis Exp. 2017;130:57128.

    Google Scholar 

  26. Mecheter I, Alic L, Abbod M, Amira A, Ji J. MR image-based attenuation correction of brain PET imaging: review of literature on machine learning approaches for segmentation. J Digit Imaging. 2020;33(5):1224–41.

    Article  Google Scholar 

  27. Sekine T, Buck A, Delso G, et al. The impact of atlas-based MR attenuation correction on the diagnosis of FDG-PET/MR for Alzheimer’s diseases- a simulation study combining multi-center data and ADNI-data. PLoS One. 2020;15(6):e0233886.

    Google Scholar 

  28. Broski SM, Goenka AH, Kemp BJ, Johnson GB. Clinical PET/MRI: 2018 update. AJR Am J Roentgenol. 2018;211(2):295–313.

    Article  Google Scholar 

  29. Tudisca C, Nasoodi A, Fraioli F. PET-MRI: clinical application of the new hybrid technology. Nucl Med Commun. 2015;36(7):666–78.

    Article  Google Scholar 

  30. Brendle CB, Schmidt H, Fleischer S, Braeuning UH, Pfannenberg CA, Schwenzer NF. Simultaneously acquired MR/PET images compared with sequential MR/PET and PET/CT: alignment quality. Radiology. 2013;268(1):190–9.

    Article  Google Scholar 

  31. Barkovich MJ, Xu D, Desikan RS, Williams C, Barkovich AJ. Pediatric neuro MRI: tricks to minimize sedation. Pediatr Radiol. 2018;48(1):50–5.

    Article  Google Scholar 

  32. Patel DM, Tubbs RS, Pate G, Johnston JM, Blount JP. Fast-sequence MRI studies for surveillance imaging in pediatric hydrocephalus. J Neurosurg Pediatr. 2014;13(4):440–7.

    Article  Google Scholar 

  33. Rozovsky K, Ventureyra ECG, Miller E. Fast-brain MRI in children is quick, without sedation, and radiation-free, but beware of limitations. J Clin Neurosci. 2013;20(3):400–5.

    Article  Google Scholar 

  34. Ramgopal S, Karim SA, Subramanian S, Furtado AD, Marin JR. Rapid brain MRI protocols reduce head computerized tomography use in the pediatric emergency department. BMC Pediatr. 2020; 20(1):1–14.

    Google Scholar 

  35. Andica C, Hagiwara A, Hori M, et al. Review of synthetic MRI in pediatric brains: basic principle of MR quantification, its features, clinical applications, and limitations. J Neuroradiol. 2019;46(4):268–75.

    Article  Google Scholar 

  36. Haacke EM, Chen Y, Utriainen D, et al. STrategically Acquired Gradient Echo (STAGE) imaging, part III: technical advances and clinical applications of a rapid multi-contrast multi-parametric brain imaging method. Magn Reson Imaging. 2020;65:15–26.

    Article  Google Scholar 

  37. Tanenbaum LN, Tsiouris AJ, Johnson AN, et al. Synthetic MRI for clinical neuroimaging: results of the Magnetic Resonance Image Compilation (MAGiC) prospective, multicenter, multireader trial. AJNR Am J Neuroradiol. 2017;38(6):1103–10.

    Article  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Mercy Catholic Medical Center, Trinity Health Mid- Atlantic, Department of Radiology, Darby, PA, USA

    Christian Pedersen

  2. Radiology (Division of Neuroradiology), Mayo Clinic, Rochester, MN, USA

    Steven Messina

  3. Department of Radiology and Molecular Imaging Program at Stanford (MIPS), Stanford School of Medicine, Stanford, CA, USA

    Heike Daldrup-Link

  4. Section of Neuroradiology and Nuclear Medicine, Yale School of Medicine, New Haven, CT, USA

    Mariam Aboian

Authors
  1. Christian Pedersen
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  2. Steven Messina
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  3. Mariam Aboian
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Corresponding author

Correspondence to Mariam Aboian .

Editor information

Editors and Affiliations

  1. Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, The Feinstein Institutes for Medical Research, Manhasset, NY, USA

    Ana M. Franceschi

  2. Stony Brook University Hospital, Stony Brook, NY, USA

    Dinko Franceschi

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Pedersen, C., Messina, S., Daldrup-Link, H., Aboian, M. (2022). Pediatric PET/MRI Neuroimaging: Overview. In: Franceschi, A.M., Franceschi, D. (eds) Hybrid PET/MR Neuroimaging. Springer, Cham. https://doi.org/10.1007/978-3-030-82367-2_62

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  • DOI: https://doi.org/10.1007/978-3-030-82367-2_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82366-5

  • Online ISBN: 978-3-030-82367-2

  • eBook Packages: MedicineMedicine (R0)

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