Thin-section CT findings in flock worker's lung, a work-related interstitial lung disease.
OBJECTIVE
To characterize the thin-section computed tomographic (CT) features of flock worker's lung (FWL) and to determine whether these features may be used to distinguish workers with FWL from flock workers who do not fulfill diagnostic criteria for FWL.


METHODS
Thin-section CT images obtained in 43 flock workers (including 11 with FWL) were reviewed independently by radiologists blinded to occupational and clinical details. CT features recorded included ground-glass opacities, consolidation, micronodules, reticular abnormality, and septal thickening. Thirty-five of the CT scans (including nine obtained in patients with FWL) were also studied by using quantitative image analysis. The Student t test was used to compare mean lung attenuation between the workers with FWL and those without it.


RESULTS
Every patient with FWL and 19 (59%) of the 32 exposed flock workers who did not meet criteria for the disease had an abnormal thin-section CT scan. The most common findings in FWL were ground-glass opacities and micronodules. Quantitative analysis showed a mean lung attenuation of -736.4 HU in patients with FWL, compared with -775.0 HU in workers without the disease (P <.05).


CONCLUSIONS
While ground-glass opacities, micronodules, or both were found in all cases of FWL, these abnormalities were also present in a substantial proportion of symptomatic flock workers who did not satisfy current criteria for FWL. Although nonspecific, these findings should suggest the diagnosis of FWL in exposed individuals.
Weiland
David A
DA
Department of Radiology, University of Colorado Health Sciences Center, 4200 E Ninth Ave, Denver, CO 80262, USA.
Lynch
David A
DA
Jensen
Steven P
SP
Newell
John D
JD
Miller
David E
DE
Crausman
Robert S
RS
Kuhn
Charles
C
Kern
David G
DG
D000328:Adult; D000368:Aged; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D017563:Lung Diseases, Interstitial / Q000209:etiology*; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000209:etiology*; D013783:Textile Industry; D014057:Tomography, X-Ray Computed / Q000379:methods*