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Related Experiment Video

Updated: Jun 20, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

Classifying diagnostic pitfalls in juxtapleural CT lesions: A root cause.

Kunquan Lai¹, Xinhuan Huang¹, Huan Lai¹

¹Department of Computed Tomography, Shicheng County People's Hospital, Ganzhou, Jiangxi 342700, China.

European Journal of Radiology Open

|June 19, 2026

Summary

A root-cause analysis framework was developed to classify diagnostic pitfalls in computed tomography (CT) interpretation of juxtapleural lesions. The study identified three main error types, showing a feasible classification system for challenging cases.

Keywords:

Diagnostic errors Patient safety Pleural diseases Root cause analysis Tomography, X-ray computed

Related Experiment Videos

Last Updated: Jun 20, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

Area of Science:

Radiology and Medical Imaging
Diagnostic Accuracy
Medical Error Analysis

Background:

Interpreting juxtapleural lesions on computed tomography (CT) scans can present diagnostic challenges.
Diagnostic errors in radiology can stem from various underlying mechanisms, impacting patient care.
A systematic approach is needed to understand and categorize these diagnostic pitfalls.

Purpose of the Study:

To develop and assess the feasibility of a root-cause analysis (RCA) framework.
To classify diagnostic pitfalls encountered in CT interpretation of juxtapleural lesions.
To identify underlying mechanisms of diagnostic failure in challenging cases.

Main Methods:

A retrospective, exploratory taxonomy-development study was conducted.
A cohort enriched for diagnostic difficulty (20 patients) was analyzed.
Non-concordant cases underwent structured RCA, with errors categorized by two radiologists into pitfall types.

Main Results:

Major or moderate diagnostic discordance was found in 90% of cases within the selected cohort.
Three distinct pitfall types were identified: Misleading Features (66.7%), Perceptual Errors (16.7%), and Errors of Integration (16.7%).
Substantial inter-rater agreement (Cohen's κ = 0.68) was observed for the categorization.

Conclusions:

Diagnostic errors in challenging CT interpretations of juxtapleural lesions follow systematic patterns.
A novel three-pitfall taxonomy demonstrates feasibility and initial reliability for analyzing these errors.
Further validation in larger, prospective studies is necessary for clinical implementation.