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

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Title: Computer-based self-training for CT colonography with and without CAD.
Authors: Sali, Lapo1 lapo.sali@unifi.it, Delsanto, Silvia2, Sacchetto, Daniela2, Correale, Loredana2, Falchini, Massimo1, Ferraris, Andrea3, Gandini, Giovanni3, Grazzini, Giulia1, Iafrate, Franco4, Iussich, Gabriella5, Morra, Lia2, Laghi, Andrea6, Mascalchi, Mario1, Regge, Daniele3,7
Source: European Radiology. Nov2018, Vol. 28 Issue 11, p4783-4791. 9p. 1 Diagram, 2 Charts, 3 Graphs.
Subjects: Virtual colonoscopy, CAD/CAM systems, Generalized estimating equations, Odds ratio, Tissue wounds, Algorithms, Clinical competence, Colon tumors, Colonoscopy, Comparative studies, Differential diagnosis, Research methodology, Medical cooperation, Medical education, Medical specialties & specialists, Rectum tumors, Research, Research evaluation, Evaluation research, Receiver operating characteristic curves, Colon polyps, Computer-aided diagnosis, Impact of Event Scale
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. [ABSTRACT FROM AUTHOR]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Computer-based self-training for CT colonography with and without CAD.
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22European+Radiology%22&quot;&gt;European Radiology&lt;/searchLink&gt;. Nov2018, Vol. 28 Issue 11, p4783-4791. 9p. 1 Diagram, 2 Charts, 3 Graphs.
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  Data: &lt;bold&gt;Objectives: &lt;/bold&gt;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.&lt;bold&gt;Methods: &lt;/bold&gt;Institutional review board approval and patients&#39; 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&#39; performance and the impact of CAD use during training.&lt;bold&gt;Results: &lt;/bold&gt;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 &lt; 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.&lt;bold&gt;Conclusions: &lt;/bold&gt;A computer-based self-training program for CTC improves readers&#39; per lesion sensitivity. CAD as second reader does not have a significant impact on learning if used during training.&lt;bold&gt;Key Points: &lt;/bold&gt;• 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. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00330-018-5480-5
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      – SubjectFull: Generalized estimating equations
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