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Computer-based self-training for CT colonography with and without CAD

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To determine whether (1) computer-based self-training for CT colonography (CTC) improves interpretation performance of novice readers; (2) computer-aided detection (CAD) use during training affects learning.

Methods

Institutional review board approval and patients’ informed consent were obtained for all cases included in this study. Twenty readers (17 radiology residents, 3 radiologists) with no experience in CTC interpretation were recruited in three centres. After an introductory course, readers performed a baseline assessment test (37 cases) using CAD as second reader. Then they were randomized (1:1) to perform either a computer-based self-training (150 cases verified at colonoscopy) with CAD as second reader or the same training without CAD. The same assessment test was repeated after completion of the training programs. Main outcome was per lesion sensitivity (≥ 6 mm). A generalized estimating equation model was applied to evaluate readers’ performance and the impact of CAD use during training.

Results

After training, there was a significant improvement in average per lesion sensitivity in the unassisted phase, from 74% (356/480) to 83% (396/480) (p < 0.001), and in the CAD-assisted phase, from 83% (399/480) to 87% (417/480) (p = 0.021), but not in average per patient sensitivity, from 93% (390/420) to 94% (395/420) (p = 0.41), and specificity, from 81% (260/320) to 86% (276/320) (p = 0.15). No significant effect of CAD use during training was observed on per patient sensitivity and specificity, nor on per lesion sensitivity.

Conclusions

A computer-based self-training program for CTC improves readers’ per lesion sensitivity. CAD as second reader does not have a significant impact on learning if used during training.

Key Points

• Computer-based self-training for CT colonography improves per lesion sensitivity of novice readers.

• Self-training program does not increase per patient specificity of novice readers.

• CAD used during training does not have significant impact on learning.

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Abbreviations

2D:

Two-dimensional

3D:

Three-dimensional

CAD:

Computer-aided detection

CI :

Confidence interval

CTC:

CT colonography

ESGAR:

European Society of Gastrointestinal and Abdominal Radiology

GEE:

Generalized estimating equation

OR:

Odds ratio

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Acknowledgements

im3D (Turin, Italy) provided the CTC training software, six workstations with CAD and technical support for the study.

We acknowledge the CTC readers of the study who are radiologists and radiology residents from Radiology Units of Florence, Rome and Turin: Lina Bartolini, Rosanna Candreva, Federica Ciolina, Giacomo Gabbani, Marco Gatti, Angela Grasso, Maria Luisa Grognardi, Nicholas Landini, Simone Liberali, Viorica Maldur, Simona Martinello, Antonella Masserelli, Maria Antonietta Napoli, Vincenzo Noce, Giulia Scarpini, Giulia Schivazappa, Gian Giacomo Taliani, Virginia Vegni, Andrea Wlderk, Stefania Zuccherelli.

Funding

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

Author information

Author notes

  1. Mario Mascalchi and Daniele Regge contributed equally to this work.

Authors and Affiliations

  1. Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, University of Florence, Viale Morgani 50, 50134, Florence, Italy

    Lapo Sali, Massimo Falchini, Giulia Grazzini & Mario Mascalchi

  2. im3D S.p.A., Via Livorno 60, 10153, Turin, Italy

    Silvia Delsanto, Daniela Sacchetto, Loredana Correale & Lia Morra

  3. Department of Surgical Science, University of Turin, 10124, Turin, Italy

    Andrea Ferraris, Giovanni Gandini & Daniele Regge

  4. Radiology Unit, Department of Radiological Sciences, Oncology and Pathology, University of Rome “Sapienza”, Viale del Policlinico 155, 00161, Rome, Italy

    Franco Iafrate

  5. Radiology Unit, Sant’Anna Hospital, Via Sant’Anna 1, 6924, Sorengo, Switzerland

    Gabriella Iussich

  6. Department of Radiological Sciences, Oncology and Pathology, University of Rome “Sapienza”, Sant’Andrea University Hospital, Via di Grottarossa 1035, 00189, Rome, Italy

    Andrea Laghi

  7. Imaging Unit, Candiolo Cancer Institute FPO-IRCCS, 10060, Candiolo, Turin, Italy

    Daniele Regge

Authors
  1. Lapo Sali
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  2. Silvia Delsanto
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  3. Daniela Sacchetto
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  4. Loredana Correale
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  5. Massimo Falchini
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  6. Andrea Ferraris
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  7. Giovanni Gandini
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  8. Giulia Grazzini
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  9. Franco Iafrate
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  10. Gabriella Iussich
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  11. Lia Morra
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  12. Andrea Laghi
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  13. Mario Mascalchi
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  14. Daniele Regge
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Corresponding author

Correspondence to Lapo Sali.

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Guarantor

The scientific guarantor of this publication is Professor Daniele Regge.

Conflict of interest

Four authors of this manuscript (Loredanda Correale, Silvia Delsanto, Lia Morra, Daniela Sacchetto) declare relationships with the following company: im3D, Turin, Italy.

All other 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.

Informed consent

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

Ethical approval

Institutional review board approval was obtained.

Study subjects or cohorts overlap

CTC cases for the assessment tests in this study were extracted from a previously published study (Iussich G, et al. Computer-aided detection for computed tomographic colonography screening: a prospective comparison of a double-reading paradigm with first-reader computer-aided detection against second-reader computer-aided detection. Invest Radiol. 2014;49:173–182).

Methodology

• prospective

• pmulticentre study

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Sali, L., Delsanto, S., Sacchetto, D. et al. Computer-based self-training for CT colonography with and without CAD. Eur Radiol 28, 4783–4791 (2018). https://doi.org/10.1007/s00330-018-5480-5

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  • DOI: https://doi.org/10.1007/s00330-018-5480-5

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