ArticleEuropean radiology2018
Computer-based self-training for CT colonography with and without CAD.
Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Local Recurrences in Rectal Cancer: MRI vs. CT.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- Single CT Appointment for Double Lung and Colorectal Cancer Screening: Is the Time Ripe?Diagnostics (Basel, Switzerland) · 2022Review
- Computer-Aided Diagnosis Improves the Detection of Clinically Significant Prostate Cancer on Multiparametric-MRI: A Multi-Observer Performance Study Involving Inexperienced Readers.Diagnostics (Basel, Switzerland) · 2021Article
- Developing Sustainable Classification of Diseases via Deep Learning and Semi-Supervised Learning.Healthcare (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo 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.
methodsInstitutional 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.
resultsAfter 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.
conclusionsA 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.