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Clinical Course and Changes in High-Resolution Computed Tomography Findings in Patients with Idiopathic Pulmonary Fibrosis without Honeycombing.

ABSTRACT: Some patients with idiopathic pulmonary fibrosis (IPF) do not have honeycombing on high-resolution computed tomography (HRCT) at their initial evaluation. The clinical course and sequential changes in HRCT findings in these patients are not fully understood. We reviewed the cases of 43 patients with IPF without honeycombing on initial HRCT from institutions throughout Japan. All patients were diagnosed with IPF based on a surgical lung biopsy. Multidisciplinary discussions were held five times between 2011 and 2014, to exclude alternative etiologies. We evaluated the sequential changes in HRCT findings in 30 patients with IPF. We classified these 30 patients into three groups based on their HRCT patterns and clarified the clinical characteristics and prognosis among the groups. The patterns of all 30 patients on initial HRCT corresponded to a possible usual interstitial pneumonia (UIP) pattern which was described in the 2011 International Statement. On long-term follow-up (71.0±38.7 standard deviation [SD] months), honeycombing was seen in 16 patients (53%, the HoneyCo group); traction bronchiectasis or cysts without honeycombing was observed in 12 patients (40%, the NoHoneyCo group), and two patients showed no interval change (7%, the NoChange group) on HRCT. The mean survival periods of the HoneyCo and NoHoneyCo groups were 67.1 and 61.2 months, respectively (p = 0.76). There are some patients with IPF whose conditions chronically progress without honeycombing on HRCT. The appearance of honeycombing on HRCT during the follow-up might not be related to prognosis.

SUBMITTER: Yamauchi H

PROVIDER: S-EPMC5102464 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Clinical Course and Changes in High-Resolution Computed Tomography Findings in Patients with Idiopathic Pulmonary Fibrosis without Honeycombing.

Yamauchi Hiroyoshi H Bando Masashi M Baba Tomohisa T Kataoka Kensuke K Yamada Yoshihito Y Yamamoto Hiroshi H Miyamoto Atsushi A Ikushima Soichiro S Johkoh Takeshi T Sakai Fumikazu F Terasaki Yasuhiro Y Hebisawa Akira A Kawabata Yoshinori Y Sugiyama Yukihiko Y Ogura Takashi T

PloS one 20161109 11

Some patients with idiopathic pulmonary fibrosis (IPF) do not have honeycombing on high-resolution computed tomography (HRCT) at their initial evaluation. The clinical course and sequential changes in HRCT findings in these patients are not fully understood. We reviewed the cases of 43 patients with IPF without honeycombing on initial HRCT from institutions throughout Japan. All patients were diagnosed with IPF based on a surgical lung biopsy. Multidisciplinary discussions were held five times b ...[more]

PMID: 27829068

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Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a fatal lung disease involving progressive degeneration of lung capacity. Current diagnosis of IPF heavily relies on visual evaluation of fibrotic features in high-resolution computed tomography (HRCT) images of the lungs. Although the characteristics of this disease have been studied at the molecular and cellular levels, little is known about the mechanical characteristics of IPF lungs inferred from HRCT images. To this end, we performed a pilot study to investigate the radiographic and volumetric characteristics of lungs in subjects with IPF.MethodsWe collected HRCT images of healthy (N = 13) and IPF (N = 9) lungs acquired at breath-holds after full inspiration (expanded state) and full expiration (contracted state). We performed statistical analyses on Hounsfield unit (HU) histograms, lobar volumes (V: lobe volume normalized by the lung volume), and lobar flows (Q: the difference in lobe volume divided by the difference in lung volume between the expanded and contracted states).ResultsParameters characterizing the HU histograms (i.e., mean, median, skewness, and kurtosis) significantly differed between healthy and IPF subjects, for all lobes in both expanded and contracted states. The distribution of V across lobes differed significantly between the groups in both states. The distribution of Q also differed significantly between the groups: Q values of the lower lobes for the IPF group were 33% (right) and 22% (left) smaller than those for the healthy group, consistent with the observation that radiographic scores were highest in the lower lung section in IPF. Notably, the root-mean-squared difference (RMSD) of Q, a measure of distance from the mean value of the healthy group, clearly distinguished the IPF subjects (RMSD of Q > 1.59) from the healthy group (RMSD of Q < 0.67).ConclusionThis study shows that lung volume and flow distribution change heterogeneously across the lung lobes of IPF subjects, with reduced capacity in the lower lobes. These volumetric changes may improve our understanding of the pathophysiology in IPF lungs.

Project description:Purpose To develop handcrafted radiomics (HCR) and deep learning (DL) based automated diagnostic tools that can differentiate between idiopathic pulmonary fibrosis (IPF) and non-IPF interstitial lung diseases (ILDs) in patients using high-resolution computed tomography (HRCT) scans. Material and Methods In this retrospective study, 474 HRCT scans were included (mean age, 64.10 years ± 9.57 [SD]). Five-fold cross-validation was performed on 365 HRCT scans. Furthermore, an external dataset comprising 109 patients was used as a test set. An HCR model, a DL model, and an ensemble of HCR and DL model were developed. A virtual in-silico trial was conducted with two radiologists and one pulmonologist on the same external test set for performance comparison. The performance was compared using DeLong method and McNemar test. Shapley Additive exPlanations (SHAP) plots and Grad-CAM heatmaps were used for the post-hoc interpretability of HCR and DL models, respectively. Results In five-fold cross-validation, the HCR model, DL model, and the ensemble of HCR and DL models achieved accuracies of 76.2 ± 6.8, 77.9 ± 4.6, and 85.2 ± 2.7%, respectively. For the diagnosis of IPF and non-IPF ILDs on the external test set, the HCR, DL, and the ensemble of HCR and DL models achieved accuracies of 76.1, 77.9, and 85.3%, respectively. The ensemble model outperformed the diagnostic performance of clinicians who achieved a mean accuracy of 66.3 ± 6.7% (p < 0.05) during the in-silico trial. The area under the receiver operating characteristic curve (AUC) for the ensemble model on the test set was 0.917 which was significantly higher than the HCR model (0.817, p = 0.02) and the DL model (0.823, p = 0.005). The agreement between HCR and DL models was 61.4%, and the accuracy and specificity for the predictions when both the models agree were 93 and 97%, respectively. SHAP analysis showed the texture features as the most important features for IPF diagnosis and Grad-CAM showed that the model focused on the clinically relevant part of the image. Conclusion Deep learning and HCR models can complement each other and serve as useful clinical aids for the diagnosis of IPF and non-IPF ILDs.

Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) and pleuroparenchymal fibroelastosis (PPFE) are known to have poor outcomes but detailed examinations of prognostic significance of an association between these morphologic processes are lacking.MethodsRetrospective observational study of independent derivation and validation cohorts of IPF populations. Upper-lobe PPFE extent was scored visually (vPPFE) as categories of absent, moderate, marked. Computerised upper-zone PPFE extent (cPPFE) was examined continuously and using a threshold of 2·5% pleural surface area. vPPFE and cPPFE were evaluated against 1-year FVC decline (estimated using mixed-effects models) and mortality. Multivariable models were adjusted for age, gender, smoking history, antifibrotic treatment and diffusion capacity for carbon monoxide.FindingsPPFE prevalence was 49% (derivation cohort, n = 142) and 72% (validation cohort, n = 145). vPPFE marginally contributed 3-14% to variance in interstitial lung disease (ILD) severity across both cohorts.In multivariable models, marked vPPFE was independently associated with 1-year FVC decline (derivation: regression coefficient 18·3, 95 CI 8·47-28·2%; validation: 7·51, 1·85-13·2%) and mortality (derivation: hazard ratio [HR] 7·70, 95% CI 3·50-16·9; validation: HR 3·01, 1·33-6·81). Similarly, continuous and dichotomised cPPFE were associated with 1-year FVC decline and mortality (cPPFE ≥ 2·5% derivation: HR 5·26, 3·00-9·22; validation: HR 2·06, 1·28-3·31). Individuals with cPPFE ≥ 2·5% or marked vPPFE had the lowest median survival, the cPPFE threshold demonstrated greater discrimination of poor outcomes at two and three years than marked vPPFE.InterpretationPPFE quantification supports distinction of IPF patients with a worse outcome independent of established ILD severity measures. This has the potential to improve prognostic management and elucidate separate pathways of disease progression.FundingThis research was funded in whole or in part by the Wellcome Trust [209,553/Z/17/Z] and the NIHR UCLH Biomedical Research Centre, UK.

Project description:OBJECTIVE:To characterize the high-resolution computed tomography (HRCT) pulmonary abnormalities in patients with synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome. METHODS:Pulmonary HRCT images were reconstructed from whole-spine computed tomography (CT) images of 67 patients with SAPHO syndrome. HRCT images of 58 healthy controls were also obtained and reviewed. Patients with pneumonia and tuberculosis were excluded. Demographic and clinical data such as gender, age, onset age, disease duration, erythrocyte sedimentation rate (ESR), highly sensitive C-reactive protein (hs-CRP) and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) were collected from the SAPHO syndrome patients. Demographic characteristics, ESR and hs-CRP data from the healthy controls were also recorded. Student's t test, Mann-Whitney U test, chi-squared test and logistic regression were employed to compare the HRCT findings of the two groups of patients. RESULTS:The median age of the SAPHO syndrome patients was 47.0 years, interquartile range [38.0-53.0]; that of the healthy controls was 37.0[30.8-53.8]. From the detailed HRCT evaluations, abnormalities were identified in 45 patients. We found irregular linear opacities in 29 (43.3%) patients, opacities in 22 (32.8%), ground-glass opacity in 11 (16.4%), pleural thickening in 9 (13.4%), solitary nodules in 6 (9%), bronchiectasis in 3 (4.5%), pulmonary bulla in 2 (3%), multiple nodules in 1 (1.5%), and reticular patterns in 1 (1.5%). Compared to the healthy controls, the SAPHO syndrome patients had a significantly higher rate of opacities but a significantly lower percentage of nodules (especially multiple nodules), although the overall rates of abnormal HRCT findings were similar in the two groups. According to the multivariate logistic regression analysis, increased age and BASDAI < 4 were significant predictors of abnormal HRCT findings. CONCLUSION:Our study is the first to address HRCT pulmonary abnormalities in SAPHO syndrome patients. SAPHO syndrome patients have a significantly higher percentage of opacities and a significantly lower rate of pulmonary nodules than healthy controls. BASDAI and age are possible good predictors of abnormal HRCT pulmonary findings.

Dataset Information

Clinical Course and Changes in High-Resolution Computed Tomography Findings in Patients with Idiopathic Pulmonary Fibrosis without Honeycombing.

Publications

Clinical Course and Changes in High-Resolution Computed Tomography Findings in Patients with Idiopathic Pulmonary Fibrosis without Honeycombing.

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