Literature DB >> 28687168

Evidence-based anatomical review areas derived from systematic analysis of cases from a radiological departmental discrepancy meeting.

S C Chin1, J R Weir-McCall2, P M Yeap2, R D White3, M J Budak4, G Duncan2, T B Oliver2, I A Zealley2.   

Abstract

AIM: To produce short checklists of specific anatomical review sites for different regions of the body based on the frequency of radiological errors reviewed at radiology discrepancy meetings, thereby creating "evidence-based" review areas for radiology reporting.
MATERIALS AND METHODS: A single centre discrepancy database was retrospectively reviewed from a 5-year period. All errors were classified by type, modality, body system, and specific anatomical location. Errors were assigned to one of four body regions: chest, abdominopelvic, central nervous system (CNS), and musculoskeletal (MSK). Frequencies of errors in anatomical locations were then analysed.
RESULTS: There were 561 errors in 477 examinations; 290 (46%) errors occurred in the abdomen/pelvis, 99 (15.7%) in the chest, 117 (18.5%) in the CNS, and 125 (19.9%) in the MSK system. In each body system, the five most common location were chest: lung bases on computed tomography (CT), apices on radiography, pulmonary vasculature, bones, and mediastinum; abdominopelvic: vasculature, colon, kidneys, liver, and pancreas; CNS: intracranial vasculature, peripheral cerebral grey matter, bone, parafalcine, and the frontotemporal lobes surrounding the Sylvian fissure; and MSK: calvarium, sacrum, pelvis, chest, and spine.
CONCLUSION: The five listed locations accounted for >50% of all perceptual errors suggesting an avenue for focused review at the end of reporting. Crown
Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 28687168     DOI: 10.1016/j.crad.2017.06.001

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  2 in total

1.  Computational modeling of human reasoning processes for interpretable visual knowledge: a case study with radiographers.

Authors:  Yu Li; Hongfei Cao; Carla M Allen; Xin Wang; Sanda Erdelez; Chi-Ren Shyu
Journal:  Sci Rep       Date:  2020-12-10       Impact factor: 4.379

2.  The Back Alleys and Dark Corners of Abdomen and Pelvis Computed Tomography: The Most Frequent Sites of Missed Findings in the Multiplanar Era.

Authors:  Mark A Kliewer; Mikala R Brinkman; J Louis Hinshaw
Journal:  J Clin Imaging Sci       Date:  2020-11-02
  2 in total

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