Literature DB >> 29796918

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

Lapo Sali1, Silvia Delsanto2, Daniela Sacchetto2, Loredana Correale2, Massimo Falchini3, Andrea Ferraris4, Giovanni Gandini4, Giulia Grazzini3, Franco Iafrate5, Gabriella Iussich6, Lia Morra2, Andrea Laghi7, Mario Mascalchi3, Daniele Regge4,8.   

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.

Entities:  

Keywords:  CT colonography; Education; Learning; Virtual colonoscopy

Mesh:

Year:  2018        PMID: 29796918     DOI: 10.1007/s00330-018-5480-5

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  22 in total

1.  Use of resampling to select among alternative error structure specifications for GLMM analyses of repeated measurements.

Authors:  Scott Tonidandel; John E Overall; Fraser Smith
Journal:  Int J Methods Psychiatr Res       Date:  2004       Impact factor: 4.035

2.  CT colonography: effect of experience and training on reader performance.

Authors:  Stuart A Taylor; Steve Halligan; David Burling; Simon Morley; Paul Bassett; Wendy Atkin; Clive I Bartram
Journal:  Eur Radiol       Date:  2004-02-10       Impact factor: 5.315

3.  Sample size tables for computer-aided detection studies.

Authors:  Nancy A Obuchowski; Stephen L Hillis
Journal:  AJR Am J Roentgenol       Date:  2011-11       Impact factor: 3.959

4.  Efficacy of computer-aided detection as a second reader for 6-9-mm lesions at CT colonography: multicenter prospective trial.

Authors:  Daniele Regge; Patrizia Della Monica; Giovanni Galatola; Cristiana Laudi; Antonella Zambon; Loredana Correale; Roberto Asnaghi; Brunella Barbaro; Claudia Borghi; Delia Campanella; Maria Carla Cassinis; Riccardo Ferrari; Andrea Ferraris; Cesare Hassan; Rita Golfieri; Franco Iafrate; Gabriella Iussich; Andrea Laghi; Roberto Massara; Emanuele Neri; Lapo Sali; Silvia Venturini; Giovanni Gandini
Journal:  Radiology       Date:  2012-11-14       Impact factor: 11.105

5.  Formative evaluation of standardized training for CT colonographic image interpretation by novice readers.

Authors:  Abraham H Dachman; Katherine B Kelly; Michael P Zintsmaster; Rich Rana; Shweta Khankari; Joseph D Novak; Arif N Ali; Adnan Qalbani; Joel G Fletcher
Journal:  Radiology       Date:  2008-10       Impact factor: 11.105

6.  Computer-aided detection of colorectal polyps: can it improve sensitivity of less-experienced readers? Preliminary findings.

Authors:  Mark E Baker; Luca Bogoni; Nancy A Obuchowski; Chandra Dass; Renee M Kendzierski; Erick M Remer; David M Einstein; Pascal Cathier; Anna Jerebko; Sarang Lakare; Andrew Blum; Dina F Caroline; Michael Macari
Journal:  Radiology       Date:  2007-10       Impact factor: 11.105

Review 7.  Evaluation of use of e-Learning in undergraduate radiology education: a review.

Authors:  Saad Zafar; Saima Safdar; Aasma N Zafar
Journal:  Eur J Radiol       Date:  2014-09-06       Impact factor: 3.528

8.  CT colonography: preliminary assessment of a double-read paradigm that uses computer-aided detection as the first reader.

Authors:  Gabriella Iussich; Loredana Correale; Carlo Senore; Nereo Segnan; Andrea Laghi; Franco Iafrate; Delia Campanella; Emanuele Neri; Francesca Cerri; Cesare Hassan; Daniele Regge
Journal:  Radiology       Date:  2013-04-29       Impact factor: 11.105

9.  Computer-aided detection (CAD) as a second reader using perspective filet view at CT colonography: effect on performance of inexperienced readers.

Authors:  V A Fisichella; F Jäderling; S Horvath; P-O Stotzer; A Kilander; M Båth; M Hellström
Journal:  Clin Radiol       Date:  2009-08-13       Impact factor: 2.350

10.  The second ESGAR consensus statement on CT colonography.

Authors:  Emanuele Neri; Steve Halligan; Mikael Hellström; Philippe Lefere; Thomas Mang; Daniele Regge; Jaap Stoker; Stuart Taylor; Andrea Laghi
Journal:  Eur Radiol       Date:  2012-09-15       Impact factor: 5.315

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  1 in total

1.  Computer-Aided Diagnosis Improves the Detection of Clinically Significant Prostate Cancer on Multiparametric-MRI: A Multi-Observer Performance Study Involving Inexperienced Readers.

Authors:  Valentina Giannini; Simone Mazzetti; Giovanni Cappello; Valeria Maria Doronzio; Lorenzo Vassallo; Filippo Russo; Alessandro Giacobbe; Giovanni Muto; Daniele Regge
Journal:  Diagnostics (Basel)       Date:  2021-05-28
  1 in total

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