Observer agreement in the diagnosis of interstitial lung diseases based on HRCT scans.
OBJECTIVE
To determine the interobserver and intraobserver agreement in the diagnosis of interstitial lung diseases (ILDs) based on HRCT scans and the impact of observer expertise, clinical data and confidence level on such agreement.


METHODS
Two thoracic radiologists and two general radiologists independently reviewed the HRCT images of 58 patients with ILDs on two distinct occasions: prior to and after the clinical anamnesis. The radiologists selected up to three diagnostic hypotheses for each patient and defined the confidence level for these hypotheses. One of the thoracic and one of the general radiologists re-evaluated the same images up to three months after the first readings. In the coefficient analyses, the kappa statistic was used.


RESULTS
The thoracic and general radiologists, respectively, agreed on at least one diagnosis for each patient in 91.4% and 82.8% of the patients. The thoracic radiologists agreed on the most likely diagnosis in 48.3% (kappa = 0.42) and 62.1% (kappa = 0.58) of the cases, respectively, prior to and after the clinical anamnesis; likewise, the general radiologists agreed on the most likely diagnosis in 37.9% (kappa = 0.32) and 36.2% (kappa = 0.30) of the cases. For the thoracic radiologist, the intraobserver agreement on the most likely diagnosis was 0.73 and 0.63 prior to and after the clinical anamnesis, respectively. That for the general radiologist was 0.38 and 0.42.The thoracic radiologists presented almost perfect agreement for the diagnostic hypotheses defined with the high confidence level.


CONCLUSIONS
Interobserver and intraobserver agreement in the diagnosis of ILDs based on HRCT scans ranged from fair to almost perfect and was influenced by radiologist expertise, clinical history and confidence level.
Antunes
Viviane Baptista
VB
Department of Diagnostic Imaging, São Paulo Hospital, Federal University of São Paulo, São Paulo (SP), Brazil. antunes.viviane@gmail.com
Meirelles
Gustavo de Souza Portes
GS
Jasinowodolinski
Dany
D
Pereira
Carlos Alberto de Castro
CA
Verrastro
Carlos Gustavo Yuji
CG
Torlai
Fabíola Goda
FG
D'Ippolito
Giuseppe
G
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002983:Clinical Competence; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D017563:Lung Diseases, Interstitial / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011871:Radiology / Q000193:education*; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*