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The use of pretest probability increases the value of high-resolution CT in diagnosing usual interstitial pneumonia.

ABSTRACT: BACKGROUND:Recent studies have suggested that non-definitive patterns on high-resolution CT (HRCT) scan provide sufficient diagnostic specificity to forgo surgical lung biopsy in the diagnosis of idiopathic pulmonary fibrosis (IPF). The objective of this study was to determine test characteristics of non-definitive HRCT patterns for identifying histopathological usual interstitial pneumonia (UIP). METHODS:Patients with biopsy-proven interstitial lung disease (ILD) and non-definitive HRCT scans were identified from two academic ILD centres. Test characteristics for HRCT patterns as predictors of UIP on surgical lung biopsy were derived and validated in independent cohorts. RESULTS:In the derivation cohort, 64/385 (17%) had possible UIP pattern on HRCT; 321/385 (83%) had inconsistent with UIP pattern. 113/385 (29%) patients had histopathological UIP pattern in the derivation cohort. Possible UIP pattern had a specificity of 91.2% (95% CI 87.2% to 94.3%) and a positive predictive value (PPV) of 62.5% (95% CI 49.5% to 74.3%) for UIP pattern on surgical lung biopsy. The addition of age, sex and total traction bronchiectasis score improved the PPV. Inconsistent with UIP pattern demonstrated poor PPV (22.7%, 95% CI 18.3% to 27.7%). HRCT pattern specificity was nearly identical in the validation cohort (92.7%, 95% CI 82.4% to 98.0%). The substantially higher prevalence of UIP pattern in the validation cohort improved the PPV of HRCT patterns. CONCLUSIONS:A possible UIP pattern on HRCT has high specificity for UIP on surgical lung biopsy, but PPV is highly dependent on underlying prevalence. Adding clinical and radiographic features to possible UIP pattern on HRCT may provide sufficient probability of histopathological UIP across prevalence ranges to change clinical decision-making.

SUBMITTER: Brownell R

PROVIDER: S-EPMC5555580 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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The use of pretest probability increases the value of high-resolution CT in diagnosing usual interstitial pneumonia.

Brownell Robert R Moua Teng T Henry Travis S TS Elicker Brett M BM White Darin D Vittinghoff Eric E Jones Kirk D KD Urisman Anatoly A Aravena Carlos C Johannson Kerri A KA Golden Jeffrey A JA King Talmadge E TE Wolters Paul J PJ Collard Harold R HR Ley Brett B

Thorax 20170112 5

<h4>Background</h4>Recent studies have suggested that non-definitive patterns on high-resolution CT (HRCT) scan provide sufficient diagnostic specificity to forgo surgical lung biopsy in the diagnosis of idiopathic pulmonary fibrosis (IPF). The objective of this study was to determine test characteristics of non-definitive HRCT patterns for identifying histopathological usual interstitial pneumonia (UIP).<h4>Methods</h4>Patients with biopsy-proven interstitial lung disease (ILD) and non-definiti ...[more]

PMID: 28082530

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Project description:OBJECTIVES:We propose a novel computational approach for the automated classification of classic versus atypical usual interstitial pneumonia (UIP). MATERIALS AND METHODS:Thirty-three patients with UIP were enrolled in this study. They were classified as classic versus atypical UIP by a consensus of 2 thoracic radiologists with more than 15 years of experience using the American Thoracic Society evidence-based guidelines for computed tomography diagnosis of UIP. Two cardiothoracic fellows with 1 year of subspecialty training provided independent readings. The system is based on regional characterization of the morphological tissue properties of lung using volumetric texture analysis of multiple-detector computed tomography images. A simple digital atlas with 36 lung subregions is used to locate texture properties, from which the responses of multidirectional Riesz wavelets are obtained. Machine learning is used to aggregate and to map the regional texture attributes to a simple score that can be used to stratify patients with UIP into classic and atypical subtypes. RESULTS:We compared the predictions on the basis of regional volumetric texture analysis with the ground truth established by expert consensus. The area under the receiver operating characteristic curve of the proposed score was estimated to be 0.81 using a leave-one-patient-out cross-validation, with high specificity for classic UIP. The performance of our automated method was found to be similar to that of the 2 fellows and to the agreement between experienced chest radiologists reported in the literature. However, the errors of our method and the fellows occurred on different cases, which suggests that combining human and computerized evaluations may be synergistic. CONCLUSIONS:Our results are encouraging and suggest that an automated system may be useful in routine clinical practice as a diagnostic aid for identifying patients with complex lung disease such as classic UIP, obviating the need for invasive surgical lung biopsy and its associated risks.

Project description:PURPOSE:To conduct a meta-analysis to determine specific computed tomography (CT) patterns and clinical features that discriminate between nonspecific interstitial pneumonia (NSIP) and usual interstitial pneumonia (UIP). MATERIALS AND METHODS:The PubMed/Medline and Embase databases were searched for studies describing the radiological patterns of UIP and NSIP in chest CT images. Only studies involving histologically confirmed diagnoses and a consensus diagnosis by an interstitial lung disease (ILD) board were included in this analysis. The radiological patterns and patient demographics were extracted from suitable articles. We used random-effects meta-analysis by DerSimonian & Laird and calculated pooled odds ratios for binary data and pooled mean differences for continuous data. RESULTS:Of the 794 search results, 33 articles describing 2,318 patients met the inclusion criteria. Twelve of these studies included both NSIP (338 patients) and UIP (447 patients). NSIP-patients were significantly younger (NSIP: median age 54.8 years, UIP: 59.7 years; mean difference (MD) -4.4; p = 0.001; 95% CI: -6.97 to -1.77), less often male (NSIP: median 52.8%, UIP: 73.6%; pooled odds ratio (OR) 0.32; p<0.001; 95% CI: 0.17 to 0.60), and less often smokers (NSIP: median 55.1%, UIP: 73.9%; OR 0.42; p = 0.005; 95% CI: 0.23 to 0.77) than patients with UIP. The CT findings from patients with NSIP revealed significantly lower levels of the honeycombing pattern (NSIP: median 28.9%, UIP: 73.4%; OR 0.07; p<0.001; 95% CI: 0.02 to 0.30) with less peripheral predominance (NSIP: median 41.8%, UIP: 83.3%; OR 0.21; p<0.001; 95% CI: 0.11 to 0.38) and more subpleural sparing (NSIP: median 40.7%, UIP: 4.3%; OR 16.3; p = 0.005; 95% CI: 2.28 to 117). CONCLUSION:Honeycombing with a peripheral predominance was significantly associated with a diagnosis of UIP. The NSIP pattern showed more subpleural sparing. The UIP pattern was predominantly observed in elderly males with a history of smoking, whereas NSIP occurred in a younger patient population.

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The use of pretest probability increases the value of high-resolution CT in diagnosing usual interstitial pneumonia.

Publications

The use of pretest probability increases the value of high-resolution CT in diagnosing usual interstitial pneumonia.

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