Impact of Simulation Training on Radiology Resident Performance in Neonatal Head Ultrasound

Published:August 04, 2020DOI:

      Rationale and Objectives

      The aim of this study was to determine whether resident performance in head ultrasound on neonates improves following brain phantom simulation training.

      Materials and Methods

      Ten junior radiology residents with at least one year of radiology training were divided into two equal groups. Both groups received a detailed head ultrasound protocol sheet and observed a technologist perform a head ultrasound on a neonatal patient at the beginning of their first pediatric radiology rotation. Both groups of residents also received teaching with a brain phantom model. Group A residents independently performed one head ultrasound exam, subsequently received phantom simulation training, and then performed a post-training head ultrasound exam. Group B residents received phantom simulation training prior to their first head ultrasound exam. Three pediatric radiologists independently and blindly reviewed the ultrasound images of each head ultrasound exam for proficiency of image acquisition using a validated scoring system. Scores of Group A residents prior to phantom training were compared to their scores after phantom training as well as to scores of Group B residents using simple linear regression.


      There was a statistically significant improvement in the performance of head ultrasound on neonates when comparing the same residents pre- and postphantom training (p = 0.003). Residents who initially trained with the phantom performed significantly better on their first head ultrasound examination on a neonate than those residents who did not (p = 0.005).


      Our novel head ultrasound phantom training model significantly improves radiology resident performance of head ultrasound on neonates and may, therefore, be beneficial for residency education.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Academic Radiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Riccabona M
        Neonatal neurosonography.
        Eur J Radiol. 2014; 83: 1495-1506
        • Davis PJ
        • Cox RM
        • Brooks J
        Training in neonatal cranial ultrasound: a questionnaire survey.
        Br J Radiol. 2005; 78: 55-56
      1. The Royal College of Radiologists. Appendix 7. Cranial ultrasound. Ultrasound training recommendations for medical and surgical specialties. 3 ed. UK2017:63-68.

        • Patel R
        • Dennick R.
        Simulation based teaching in interventional radiology training: is it effective.
        Clin Radiol. 2017; 72:266 (266.e214): e267
        • Mooney JJ
        • Sarwani N
        • Coleman ML
        • Fotos JS
        Evaluation of Three-dimensional printed materials for simulation by computed tomography and ultrasound imaging.
        Simul Healthc. 2017; 12: 182-188
        • Tsai A
        • Barnewolt CE
        • Prahbu SP
        • et al.
        Creation and validation of a simulator for neonatal brain ultrasonography: a pilot study.
        Acad Radiol. 2017; 24: 76-83
        • Cignoni Paolo
        • Callieri
        • et al.
        MeshLab: an open-source mesh processing tool.
        The Eurographics Association, 2008
        • Chen SJ
        • Hellier P
        • Marchal M
        • et al.
        An anthropomorphic polyvinyl alcohol brain phantom based on Colin27 for use in multimodal imaging.
        Med Phys. 2012; 39: 554-561
        • Gorelik N
        • Khumalo Z
        • Saint-Martin C
        • Bure L
        • Faingold R
        Poster #: SCI-066 development of an objective scoring system to assess resident proficiency at performing head ultrasound in infants. The International Pediatric Radiology 7th Conjoint Meeting & Exhibition.
        Pediatr Radiol. 2016; 46: S320-S321
        • R Core Team
        R: A language and environment for statistical computing.
        R Foundation for Statistical Computing, Vienna, Austria2019
        • Sidhu HS
        • Olubaniyi BO
        • Bhatnagar G
        • Shuen V
        • Dubbins P
        Role of simulation-based education in ultrasound practice training.
        J Ultrasound Med. 2012; 31: 785-791
        • Fulton N
        • Buethe J
        • Gollamudi J
        • Robbin M
        Simulation-based training may improve resident skill in ultrasound-guided biopsy.
        AJR Am J Roentgenol. 2016; 207: 1329-1333
        • Ballard DH
        • Trace AP
        • Ali S
        • et al.
        Clinical applications of 3d printing: primer for radiologists.
        Acad Radiol. 2018; 25: 52-65