Add like
Add dislike
Add to saved papers

Non-tuberculous mycobacterial lung disease: diagnosis based on computed tomography of the chest.

European Radiology 2016 December
OBJECTIVES: To elucidate the accuracy and inter-observer agreement of non-tuberculous mycobacterial lung disease (NTM-LD) diagnosis based on chest CT findings.

METHODS: Two chest radiologists and two pulmonologists interpreted chest CTs of 66 patients with NTM-LD, 33 with pulmonary tuberculosis and 33 with non-cystic fibrosis bronchiectasis. These observers selected one of these diagnoses for each case without knowing any clinical information except age and sex. Sensitivity and specificity were calculated according to degree of observer confidence. Inter-observer agreement was assessed using Fleiss' κ values. Multiple logistic regression was performed to elucidate which radiological features led to the correct diagnosis.

RESULTS: The sensitivity of NTM-LD diagnosis was 56.4 % (95 % CI 47.9-64.7) and specificity 80.3 % (73.1-86.0). The specificity of NTM-LD diagnosis increased with confidence: 44.4 % (20.5-71.3) for possible, 77.4 % (67.4-85.0) for probable, 95.2 % (87.2-98.2) for definite (P < 0.001) diagnoses. Inter-observer agreement for NTM-LD diagnosis was moderate (κ = 0.453). Tree-in-bud pattern (adjusted odds ratio [aOR] 6.24, P < 0.001), consolidation (aOR 1.92, P = 0.036) and atelectasis (aOR 3.73, P < 0.001) were associated with correct NTM-LD diagnoses, whereas presence of pleural effusion (aOR 0.05, P < 0.001) led to false diagnoses.

CONCLUSIONS: NTM-LD diagnosis based on chest CT findings is specific but not sensitive.

KEY POINTS: • Diagnosis of NTM-LD based on radiological findings showed high specificity. • Sensitivity of NTM-LD diagnosis was around 50 %. • Inter- observer agreement was moderate. • Identification of tree-in-bud pattern, consolidation and atelectasis led to correct diagnoses.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app