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European Radiology

, Volume 30, Issue 2, pp 1088–1095 | Cite as

Learning curve of liver stiffness measurement using a new hybrid machine composed of transient elastography interfaced with ultrasound

  • Christophe CassinottoEmail author
  • Marie-Ange Pierredon-Foulongne
  • Ali Belgour
  • Julien Delicque
  • Laure Escal
  • Nicolas Molinari
  • Sophie Anselme
  • Tony Jacq
  • Ugo Chamard-Champliaud
  • Bastien Nicolan
  • Carole Allimant
  • Boris Guiu
Ultrasound

Abstract

Objectives

To assess the learning curve for performing reliable liver stiffness measurements using a new hybrid machine composed of transient elastography (TE) interfaced with an ultrasound device for radiographers and radiologists with different levels of expertise in ultrasound imaging.

Methods

Ten novice operators who had never performed TE measurements were prospectively evaluated from April to October 2018: senior radiologists, young radiologists, fellows, radiographers, and residents, with different levels of experience in abdominal ultrasound imaging. All operators had a short theoretical training followed by a training session under supervision in three patients. Then, each operator had to perform TE in 50 consecutive patients with chronic liver disease, using beforehand ultrasound examination to select measurement area in the right liver lobe, and if needed, the XL probe. Percentages of failures and reliable measurements were compared.

Results

The rates of failures of measurements, poorly reliable, reliable, and very reliable results, were of 4.2% (21/500), 2.4% (12/500), 47.6% (238/500), and 45.8% (229/500), respectively. The rates of reliable plus very reliable results were excellent, ranging from 91 to 96% among all the subgroups. The rates of very reliable, reliable, and unreliable results did not differ between operator subgroups and especially between junior radiologists, senior radiologists, and radiographers. No breaking point was observed in the interquartile range/median values over time.

Conclusion

TE interfaced with ultrasound in this hybrid machine presents no learning curve effect. After a short initial training session, a novice observer is able to perform high rates of reliable and very reliable TE measurements.

Key Points

• When performing liver stiffness measurements using a new hybrid machine composed of transient elastography interfaced with ultrasound, the rate of failures of measurements is very low, below 5%.

• After a short training session and using ultrasound planning, a novice operator, whatever its expertise in ultrasound imaging, is capable of performing high rates of reliable and very reliable measurements.

• No learning curve is needed for performing reliable liver stiffness measurements using this new hybrid machine.

Keywords

Liver fibrosis Elasticity imaging techniques Ultrasonography Learning curve Clinical competence 

Abbreviations

BMI

Body mass index

ICC

Intra-class correlation coefficient

IQR/M

Interquartile range-to-liver stiffness median ratio

LSM

Liver stiffness measurement

TE

Transient elastography

Notes

Funding

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Dr. Christophe Cassinotto.

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

One of the authors has significant statistical expertise (Dr Molinari Nicolas).

Informed consent

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

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Prospective

• Observational

• Performed at one institution

Supplementary material

330_2019_6388_MOESM1_ESM.docx (27 kb)
Supplementary Table 1 (DOCX 26 kb)

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Christophe Cassinotto
    • 1
    Email author
  • Marie-Ange Pierredon-Foulongne
    • 1
  • Ali Belgour
    • 1
  • Julien Delicque
    • 1
  • Laure Escal
    • 1
  • Nicolas Molinari
    • 2
  • Sophie Anselme
    • 1
  • Tony Jacq
    • 1
  • Ugo Chamard-Champliaud
    • 1
  • Bastien Nicolan
    • 1
  • Carole Allimant
    • 1
  • Boris Guiu
    • 1
  1. 1.Department of Diagnostic and Interventional Radiology, Saint-Eloi HospitalUniversity Hospital of MontpellierMontpellier cedexFrance
  2. 2.Department of Medical InformationUniversity Hospital of MontpellierMontpellierFrance

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