Diagnostic accuracy of inverted grayscale mode in radiographs: a systematic review and meta-analysis

Mohammad Eftekhari; Mohammad Jalili; Amirhossein Karim; Amin  Doosti-Irani; Hadi Mirfazaelian

doi:10.18502/fem.v7i3.13825

Mohammad Eftekhari Department of Emergency Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad Jalili Department of Emergency Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Amirhossein Karim Department of Emergency Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Amin Doosti-Irani Department of Epidemiology, School of Public Health and Modeling of Non-communicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran.
Hadi Mirfazaelian Department of Emergency Medicine, Tehran University of Medical Sciences, Tehran, Iran.

DOI: https://doi.org/10.18502/fem.v7i3.13825

Keywords: Accuracy; Image Processing; Radiograph

Abstract

X-rays are routinely utilized for different diagnostic purposes but there is always the risk of an inaccurate diagnosis. This systematic review was designed to investigate whether inverse grayscale mode increased diagnostic accuracy. From inception to February 2022, MEDLINE, Embase, Scopus, Web of Science, and CENTRAL were searched for studies comparing grayscale inversion diagnostic accuracy to the conventional method. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) tool. Eighteen studies were included with an overall patient population of 1704. The number of studies investigating each lesion are as follows, lung masses: 13, pneumothoraces: 4, bony lesions: 3, interstitial lung diseases: 3, orthopedic studies: 2, bullous lung disease: 1, pleural effusion: 1, urinary calculus: 1, and large vascular occlusion: 1. Two studies had an overall moderate risk of bias and the remainders had low risk. The combined mode, featuring the conventional mode with the addition of the inverse grayscale, demonstrated better performance or insignificant difference in comparison with the conventional mode in all studies except one, which showed lower sensitivity in detecting pulmonary nodules. Also, meta-analysis of 250 patients in four pulmonary nodule studies showed better area under the ROC curve (AUC) of inverse mode (0.83, 95% CI: 0.75,0.90) in comparison with conventional mode (0.80, 95% CI: 0.72,0.88).

Application of inverse mode when using radiography for detection of pulmonary nodules might improve diagnostic accuracy. Also, the inverse/combined mode showed better performance for lesions other than pulmonary nodule in some studies. However, there was insufficient evidence to draw a consistent conclusion.