Literature DB >> 9536897

Radiology's Achilles' heel: error and variation in the interpretation of the Röntgen image.

P J Robinson1.   

Abstract

The performance of the human eye and brain has failed to keep pace with the enormous technical progress in the first full century of radiology. Errors and variations in interpretation now represent the weakest aspect of clinical imaging. Those interpretations which differ from the consensus view of a panel of "experts" may be regarded as errors; where experts fail to achieve consensus, differing reports are regarded as "observer variation". Errors arise from poor technique, failures of perception, lack of knowledge and misjudgments. Observer variation is substantial and should be taken into account when different diagnostic methods are compared; in many cases the difference between observers outweighs the difference between techniques. Strategies for reducing error include attention to viewing conditions, training of the observers, availability of previous films and relevant clinical data, dual or multiple reporting, standardization of terminology and report format, and assistance from computers. Digital acquisition and display will probably not affect observer variation but the performance of radiologists, as measured by receiver operating characteristic (ROC) analysis, may be improved by computer-directed search for specific image features. Other current developments show that where image features can be comprehensively described, computer analysis can replace the perception function of the observer, whilst the function of interpretation can in some cases be performed better by artificial neural networks. However, computer-assisted diagnosis is still in its infancy and complete replacement of the human observer is as yet a remote possibility.

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Year:  1997        PMID: 9536897     DOI: 10.1259/bjr.70.839.9536897

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  49 in total

1.  Adverse events in British hospitals. Preventive strategies, not epidemiological studies, are needed.

Authors:  T V Nguyen; K M Hillman; M D Buist
Journal:  BMJ       Date:  2001-06-09

2.  Consensus versus disagreement in imaging research: a case study using the LIDC database.

Authors:  Dmitriy Zinovev; Yujie Duo; Daniela S Raicu; Jacob Furst; Samuel G Armato
Journal:  J Digit Imaging       Date:  2012-06       Impact factor: 4.056

3.  Reliability of change in lumbar MRI findings over time in patients with and without disc prosthesis--comparing two different image evaluation methods.

Authors:  Linda Berg; Oivind Gjertsen; Christian Hellum; Gesche Neckelmann; Lars G Johnsen; Geir E Eide; Ansgar Espeland
Journal:  Skeletal Radiol       Date:  2012-03-20       Impact factor: 2.199

4.  Reducing error in radiographic interpretation.

Authors:  Kate Alexander
Journal:  Can Vet J       Date:  2010-05       Impact factor: 1.008

5.  Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results.

Authors:  Sandy A Napel; Christopher F Beaulieu; Cesar Rodriguez; Jingyu Cui; Jiajing Xu; Ankit Gupta; Daniel Korenblum; Hayit Greenspan; Yongjun Ma; Daniel L Rubin
Journal:  Radiology       Date:  2010-05-26       Impact factor: 11.105

6.  Spectrum of diagnostic errors in radiology.

Authors:  Antonio Pinto; Luca Brunese
Journal:  World J Radiol       Date:  2010-10-28

Review 7.  Errors in imaging patients in the emergency setting.

Authors:  Antonio Pinto; Alfonso Reginelli; Fabio Pinto; Giuseppe Lo Re; Federico Midiri; Carlo Muzj; Luigia Romano; Luca Brunese
Journal:  Br J Radiol       Date:  2016-02-03       Impact factor: 3.039

8.  Radiological error: analysis, standard setting, targeted instruction and teamworking.

Authors:  Richard FitzGerald
Journal:  Eur Radiol       Date:  2005-02-23       Impact factor: 5.315

9.  Peri-acetabular radiolucent lines: inter- and intra-observer agreement on post-operative radiographs.

Authors:  D Kneif; M Downing; G P Ashcroft; P Gibson; D Knight; W Ledingham; J Hutchison
Journal:  Int Orthop       Date:  2005-04-02       Impact factor: 3.075

10.  Predicting visual semantic descriptive terms from radiological image data: preliminary results with liver lesions in CT.

Authors:  Adrien Depeursinge; Camille Kurtz; Christopher Beaulieu; Sandy Napel; Daniel Rubin
Journal:  IEEE Trans Med Imaging       Date:  2014-05-01       Impact factor: 10.048

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