3D pediatric cranial bone imaging using high-resolution MRI for visualizing cranial sutures: a pilot study

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  • 1 Division of Plastic and Reconstructive Surgery,
  • 2 Mallinckrodt Institute of Radiology, and
  • 3 Department of Neurosurgery, Washington University in St. Louis, Missouri
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OBJECTIVE

There is an unmet need to perform imaging in young children and obtain CT-equivalent cranial bone images without subjecting the patients to radiation. In this study, the authors propose using a high-resolution fast low-angle shot golden-angle 3D stack-of-stars radial volumetric interpolated breath-hold examination (GA-VIBE) MRI sequence that is intrinsically robust to motion and has enhanced bone versus soft-tissue contrast.

METHODS

Patients younger than 11 years of age, who underwent clinical head CT scanning for craniosynostosis or other cranial malformations, were eligible for the study. 3D reconstructed images created from the GA-VIBE MRI sequence and the gold-standard CT scan were randomized and presented to 3 blinded reviewers. For all image sets, each reviewer noted the presence or absence of the 6 primary cranial sutures and recorded on 5-point Likert scales whether they recommended a second scan be performed.

RESULTS

Eleven patients (median age 1.8 years) underwent MRI after clinical head CT scanning was performed. Five of the 11 patients were sedated. Three clinicians reviewed the images, and there were no cases, either with CT scans or MR images, in which a reviewer agreed a repeat scan was required for diagnosis or surgical planning. The reviewers reported clear imaging of the regions of interest on 99% of the CT reviews and 96% of the MRI reviews. With CT as the standard, the sensitivity and specificity of the GA-VIBE MRI sequence to detect suture closure were 97% and 96%, respectively (n = 198 sutures read).

CONCLUSIONS

The 3D reconstructed images using the GA-VIBE sequence in comparison to the CT scans created clinically acceptable cranial images capable of detecting cranial sutures. Future directions include reducing the scan time, improving motion correction, and automating postprocessing for clinical utility.

ABBREVIATIONS GA = golden angle; ICC = intraclass correlation coefficient; PETRA = pointwise encoding time reduction with radial acquisition; VIBE = volumetric interpolated breath-hold examination.

Supplementary Materials

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Contributor Notes

Correspondence Kamlesh B. Patel: Washington University in St. Louis, MO. kamlesh.patel@wustl.edu.

INCLUDE WHEN CITING Published online June 12, 2020; DOI: 10.3171/2020.4.PEDS20131.

Disclosures Dr. Patel reports being a consultant for Stryker.

  • 1

    Doumit GD, Papay FA, Moores N, Zins JE. Management of sagittal synostosis: a solution to equipoise. J Craniofac Surg. 2014;25(4):12601265.

    • Search Google Scholar
    • Export Citation
  • 2

    Kestle JRW, Lee A, Anderson RCE, Variation in the management of isolated craniosynostosis: a survey of the Synostosis Research Group. J Neurosurg Pediatr. 2018;22(6):627631.

    • Search Google Scholar
    • Export Citation
  • 3

    Domeshek LF, Mukundan S Jr, Yoshizumi T, Marcus JR. Increasing concern regarding computed tomography irradiation in craniofacial surgery. Plast Reconstr Surg. 2009;123(4):13131320.

    • Search Google Scholar
    • Export Citation
  • 4

    Fearon JA, Singh DJ, Beals SP, Yu JC. The diagnosis and treatment of single-sutural synostoses: are computed tomographic scans necessary? Plast Reconstr Surg. 2007;120(5):13271331.

    • Search Google Scholar
    • Export Citation
  • 5

    Binning M, Ragel B, Brockmeyer DL, Evaluation of the necessity of postoperative imaging after craniosynostosis surgery. J Neurosurg. 2007;107(1)(suppl):4345.

    • Search Google Scholar
    • Export Citation
  • 6

    Stewart NM, Hallac RR, Chou PY, Craniofacial flash: minimizing radiation dose in pediatric craniofacial computed tomography. J Craniofac Surg. 2018;29(7):17511754.

    • Search Google Scholar
    • Export Citation
  • 7

    Radiation risks and pediatric computed tomography (CT): a guide for health care providers. National Cancer Institute. September 4, 2018. Accessed April 23, 2020. https://www.cancer.gov/about-cancer/causes-prevention/risk/radiation/pediatric-ct-scans

    • Search Google Scholar
    • Export Citation
  • 8

    Miglioretti DL, Johnson E, Williams A, The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk. JAMA Pediatr. 2013;167(8):700707.

    • Search Google Scholar
    • Export Citation
  • 9

    Brenner DJ, Elliston CD, Hall EJ, Berdon WE. Estimates of the cancer risks from pediatric CT radiation are not merely theoretical: comment on “Point/counterpoint: in x-ray computed tomography, technique factors should be selected appropriate to patient size. Against the proposition.” Med Phys. 2001;28(11):23872388.

    • Search Google Scholar
    • Export Citation
  • 10

    Parker L. Computed tomography scanning in children: radiation risks. Pediatr Hematol Oncol. 2001;18(5):307308.

  • 11

    Pearce MS, Salotti JA, Little MP, Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet. 2012;380(9840):499505.

    • Search Google Scholar
    • Export Citation
  • 12

    Smyth MD, Narayan P, Tubbs RS, Cumulative diagnostic radiation exposure in children with ventriculoperitoneal shunts: a review. Childs Nerv Syst. 2008;24(4):493497.

    • Search Google Scholar
    • Export Citation
  • 13

    Brenner DJ, Hall EJ. Computed tomography—an increasing source of radiation exposure. N Engl J Med. 2007;357(22):22772284.

  • 14

    Coté CJ, Karl HW, Notterman DA, Adverse sedation events in pediatrics: analysis of medications used for sedation. Pediatrics. 2000;106(4):633644.

    • Search Google Scholar
    • Export Citation
  • 15

    Kannikeswaran N, Mahajan PV, Sethuraman U, Sedation medication received and adverse events related to sedation for brain MRI in children with and without developmental disabilities. Paediatr Anaesth. 2009;19(3):250256.

    • Search Google Scholar
    • Export Citation
  • 16

    Malviya S, Voepel-Lewis T, Eldevik OP, Sedation and general anaesthesia in children undergoing MRI and CT: adverse events and outcomes. Br J Anaesth. 2000;84(6):743748.

    • Search Google Scholar
    • Export Citation
  • 17

    Eley KA, McIntyre AG, Watt-Smith SR, Golding SJ. “Black bone” MRI: a partial flip angle technique for radiation reduction in craniofacial imaging. Br J Radiol. 2012;85(1011):272278.

    • Search Google Scholar
    • Export Citation
  • 18

    Eley KA, Watt-Smith SR, Golding SJ. “Black bone” MRI: a potential alternative to CT when imaging the head and neck: report of eight clinical cases and review of the Oxford experience. Br J Radiol. 2012;85(1019):14571464.

    • Search Google Scholar
    • Export Citation
  • 19

    Eley KA, Watt-Smith SR, Golding SJ. Three-dimensional reconstruction of the craniofacial skeleton with gradient echo magnetic resonance imaging (“black bone”): what is currently possible? J Craniofac Surg. 2017;28(2):463467.

    • Search Google Scholar
    • Export Citation
  • 20

    Rofsky NM, Lee VS, Laub G, Abdominal MR imaging with a volumetric interpolated breath-hold examination. Radiology. 1999;212(3):876884.

    • Search Google Scholar
    • Export Citation
  • 21

    Winkelmann S, Schaeffter T, Koehler T, An optimal radial profile order based on the Golden Ratio for time-resolved MRI. IEEE Trans Med Imaging. 2007;26(1):6876.

    • Search Google Scholar
    • Export Citation
  • 22

    Grimm R, Fürst S, Souvatzoglou M, Self-gated MRI motion modeling for respiratory motion compensation in integrated PET/MRI. Med Image Anal. 2015;19(1):110120.

    • Search Google Scholar
    • Export Citation
  • 23

    Peters DC, Korosec FR, Grist TM, Undersampled projection reconstruction applied to MR angiography. Magn Reson Med. 2000;43(1):91101.

  • 24

    Fedorov A, Beichel R, Kalpathy-Cramer J, 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012;30(9):13231341.

    • Search Google Scholar
    • Export Citation
  • 25

    R: A language and environment for statistical computing. Version 3.3.2. R Foundation for Statistical Computing; 2019.

  • 26

    Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155163.

    • Search Google Scholar
    • Export Citation
  • 27

    Dorfman AL, Fazel R, Einstein AJ, Use of medical imaging procedures with ionizing radiation in children: a population-based study. Arch Pediatr Adolesc Med. 2011;165(5):458464.

    • Search Google Scholar
    • Export Citation
  • 28

    Eley KA, Watt-Smith SR, Sheerin F, Golding SJ. “Black Bone” MRI: a potential alternative to CT with three-dimensional reconstruction of the craniofacial skeleton in the diagnosis of craniosynostosis. Eur Radiol. 2014;24(10):24172426.

    • Search Google Scholar
    • Export Citation
  • 29

    Dremmen MHG, Wagner MW, Bosemani T, Does the addition of a “black bone” sequence to a fast multisequence trauma MR protocol allow MRI to replace CT after traumatic brain injury in children? AJNR Am J Neuroradiol. 2017;38(11):21872192.

    • Search Google Scholar
    • Export Citation
  • 30

    Kralik SF, Supakul N, Wu IC, Black bone MRI with 3D reconstruction for the detection of skull fractures in children with suspected abusive head trauma. Neuroradiology. 2019;61(1):8187.

    • Search Google Scholar
    • Export Citation
  • 31

    Goldwasser T, Bressan S, Oakley E, Use of sedation in children receiving computed tomography after head injuries. Eur J Emerg Med. 2015;22(6):413418.

    • Search Google Scholar
    • Export Citation
  • 32

    Uffman JC, Tumin D, Raman V, MRI utilization and the associated use of sedation and anesthesia in a pediatric ACO. J Am Coll Radiol. 2017;14(7):924930.

    • Search Google Scholar
    • Export Citation
  • 33

    Dong SZ, Zhu M, Bulas D. Techniques for minimizing sedation in pediatric MRI. J Magn Reson Imaging. 2019;50(4):10471054.

  • 34

    Lindberg DM, Stence NV, Grubenhoff JA, Feasibility and accuracy of fast MRI versus CT for traumatic brain injury in young children. Pediatrics. 2019;144(4):e20190419.

    • Search Google Scholar
    • Export Citation
  • 35

    Isaacs AM, Shimony JS, Morales DM, Feasibility of fast brain diffusion MRI to quantify white matter injury in pediatric hydrocephalus. J Neurosurg Pediatr. 2019;24(4):461468.

    • Search Google Scholar
    • Export Citation
  • 36

    Lin W, Guo J, Rosen MA, Song HK. Respiratory motion-compensated radial dynamic contrast-enhanced (DCE)-MRI of chest and abdominal lesions. Magn Reson Med. 2008;60(5):11351146.

    • Search Google Scholar
    • Export Citation
  • 37

    Paul J, Divkovic E, Wundrak S, High-resolution respiratory self-gated golden angle cardiac MRI: comparison of self-gating methods in combination with k-t SPARSE SENSE. Magn Reson Med. 2015;73(1):292298.

    • Search Google Scholar
    • Export Citation
  • 38

    Han X. MR-based synthetic CT generation using a deep convolutional neural network method. Med Phys. 2017;44(4):14081419.

  • 39

    Gong K, Yang J, Kim K, Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images. Phys Med Biol. 2018;63(12):125011.

    • Search Google Scholar
    • Export Citation
  • 40

    Barkovich MJ, Xu D, Desikan RS, Pediatric neuro MRI: tricks to minimize sedation. Pediatr Radiol. 2018;48(1):5055.

  • 41

    Dean DC III, Dirks H, O’Muircheartaigh J, Pediatric neuroimaging using magnetic resonance imaging during non-sedated sleep. Pediatr Radiol. 2014;44(1):6472.

    • Search Google Scholar
    • Export Citation
  • 42

    Ashley WW Jr, McKinstry RC, Leonard JR, Use of rapid-sequence magnetic resonance imaging for evaluation of hydrocephalus in children. J Neurosurg. 2005;103(2)(suppl):124130.

    • Search Google Scholar
    • Export Citation

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