Search

Abnormal airway dilatation, termed traction bronchiectasis, is a typical feature of idiopathic pulmonary fibrosis (IPF). Volumetric computed tomography (CT) imaging captures the loss of normal airway tapering in IPF. We postulated that automated quantification of airway abnormalities could provide estimates of IPF disease extent and severity. We propose AirQuant, an automated computational pipeline that takes an airway segmentation and CT image as input and systematically parcellates the airway tree into its lobes and generational branches, deriving airway structural measures from chest CT. Importantly, AirQuant prevents the occurrence of spurious airway branches by thick wave propagation and removes loops in the airway-tree by graph search, overcoming limitations of existing airway skeletonisation algorithms. Tapering between airway segments (intertapering) and airway tortuosity computed by AirQuant were compared between 14 healthy participants and 14 IPF patients. Airway intertapering was significantly reduced in IPF patients, and airway tortuosity was significantly increased when compared to healthy controls. Differences were most marked in the lower lobes, conforming to the typical distribution of IPF-related damage. AirQuant is an open-source pipeline that avoids limitations of existing airway quantification algorithms and has clinical interpretability. Automated airway measurements may have potential as novel imaging biomarkers of IPF severity and disease extent.

Rationale and Objectives: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease characterised by heterogeneously distributed fibrotic lesions. The inter- and intra-patient heterogeneity of the disease has meant that useful biomarkers of severity and progression have been elusive. Previous quantitative computed tomography (CT) based studies have focussed on characterising the pathological tissue. However, we hypothesised that the remaining lung tissue, which appears radiologically normal, may show important differences from controls in tissue characteristics., Materials and Methods: Quantitative metrics were derived from CT scans in IPF patients (N = 20) and healthy controls with a similar age (N = 59). An automated quantitative software (CALIPER, Computer-Aided Lung Informatics for Pathology Evaluation and Rating) was used to classify tissue as normal-appearing, fibrosis, or low attenuation area. Densitometry metrics were calculated for all lung tissue and for only the normal-appearing tissue. Heterogeneity of lung tissue density was quantified as coefficient of variation and by quadtree. Associations between measured lung function and quantitative metrics were assessed and compared between the two cohorts., Results: All metrics were significantly different between controls and IPF (p < 0.05), including when only the normal tissue was evaluated (p < 0.04). Density in the normal tissue was 14% higher in the IPF participants than controls (p < 0.001). The normal-appearing tissue in IPF had heterogeneity metrics that exhibited significant positive relationships with the percent predicted diffusion capacity for carbon monoxide., Conclusion: We provide quantitative assessment of IPF lung tissue characteristics compared to a healthy control group of similar age. Tissue that appears visually normal in IPF exhibits subtle but quantifiable differences that are associated with lung function and gas exchange., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Idiopathic pulmonary fibrosis (IPF) is characterised by progressive fibrosing interstitial pneumonia with an associated irreversible decline in lung function and quality of life. IPF prevalence increases with age, appearing most frequently in patients aged > 50 years. Pulmonary vessel-like volume (PVV) has been found to be an independent predictor of mortality in IPF and other interstitial lung diseases, however its estimation can be impacted by artefacts associated with image segmentation methods and can be confounded by adjacent fibrosis. This study compares PVV in IPF patients (N = 21) with PVV from a healthy cohort aged > 50 years (N = 59). The analysis includes a connected graph-based approach that aims to minimise artefacts contributing to calculation of PVV. We show that despite a relatively low extent of fibrosis in the IPF cohort (20% of the lung volume), PVV is 2-3 times higher than in controls. This suggests that a standardised method to calculate PVV that accounts for tree connectivity could provide a promising tool to provide early diagnostic or prognostic information in IPF patients and other interstitial lung disease., (© 2023. The Author(s).)

Purpose: Radiologists exhibit wide inter-reader variability in diagnostic performance. This work aimed to compare different feature sets to predict if a radiologist could detect a specific liver metastasis in contrast-enhanced computed tomography (CT) images and to evaluate possible improvements in individualizing models to specific radiologists. Approach: Abdominal CT images from 102 patients, including 124 liver metastases in 51 patients were reconstructed at five different kernels/doses using projection domain noise insertion to yield 510 image sets. Ten abdominal radiologists marked suspected metastases in all image sets. Potentially salient features predicting metastasis detection were identified in three ways: (i) logistic regression based on human annotations (semantic), (ii) random forests based on radiologic features (radiomic), and (iii) inductive derivation using convolutional neural networks (CNN). For all three approaches, generalized models were trained using metastases that were detected by at least two radiologists. Conversely, individualized models were trained using each radiologist's markings to predict reader-specific metastases detection. Results: In fivefold cross-validation, both individualized and generalized CNN models achieved higher area under the receiver operating characteristic curves (AUCs) than semantic and radiomic models in predicting reader-specific metastases detection ability ( p < 0.001 ). The individualized CNN with an AUC of mean (SD) 0.85(0.04) outperformed the generalized one [ AUC = 0.78 ( 0.06 ) , p = 0.004 ]. The individualized semantic [ AUC = 0.70 ( 0.05 ) ] and radiomic models [ AUC = 0.68 ( 0.06 ) ] outperformed the respective generalized versions [semantic AUC = 0.66 ( 0.03 ) , p = 0.009 ; radiomic AUC = 0.64 ( 0.06 ) , p = 0.03 ]. Conclusions: Individualized models slightly outperformed generalized models for all three feature sets. Inductive CNNs were better at predicting metastases detection than semantic or radiomic features. Generalized models have implementation advantages when individualized data are unavailable., (© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE).)

A usual interstitial pneumonia (UIP) imaging pattern can be seen in both idiopathic pulmonary fibrosis (IPF) and connective tissue disease-related interstitial lung disease (CTD-ILD). The purpose of this multicenter study was to assess whether quantitative imaging data differ between IPF and CTD-ILD in the setting of UIP. Patients evaluated at two medical centers with CTD-ILD or IPF and a UIP pattern on CT or pathology served as derivation and validation cohorts. Chest CT data were quantitatively analyzed including total volumes of honeycombing, reticulation, ground-glass opacity, normal lung, and vessel related structures (VRS). VRS was compared with forced vital capacity percent predicted (FVC%) and percent predicted diffusing capacity of the lungs for carbon monoxide (DLCO%). There were 296 subjects in total, with 40 CTD-ILD and 85 IPF subjects in the derivation cohort, and 62 CTD-ILD and 109 IPF subjects in the validation cohort. VRS was greater in IPF across the cohorts on univariate ( p < 0.001) and multivariable ( p < 0.001-0.047) analyses. VRS was inversely correlated with DLCO% in both cohorts on univariate ( p < 0.001) and in the derivation cohort on multivariable analysis ( p = 0.003) but not FVC%. Total volume of normal lung was associated with DLCO% ( p < 0.001) and FVC% ( p < 0.001-0.009) on multivariable analysis in both cohorts. VRS appears to have promise in differentiating CTD-ILD from IPF. The underlying pathophysiological relationship between VRS and ILD is complex and is likely not explained solely by lung fibrosis.

Objectives: To test HRCT with either visual or quantitative analysis in both short-term and long-term follow-up of stable IPF against long-term (transplant-free) survival, beyond 2 years of disease stability., Methods: Fifty-eight IPF patients had FVC measurements and HRCTs at baseline (HRCT0), 10-14 months (HRCT1) and 22-26 months (HRCT2). Visual scoring, CALIPER quantitative analysis of HRCT measures, and their deltas were evaluated against combined all-cause mortality and lung transplantation by adjusted Cox proportional hazard models at each time interval., Results: At HRCT1, a ≥ 20% relative increase in CALIPER-total lung fibrosis yielded the highest radiological association with outcome (C-statistic 0.62). Moreover, the model combining FVC% drop ≥ 10% and ≥ 20% relative increase of CALIPER-total lung fibrosis improved the stratification of outcome (C-statistic 0.69, high-risk category HR 12.1; landmark analysis at HRCT1 C-statistic 0.66, HR 14.9 and at HRCT2 C-statistic 0.61, HR 21.8). Likewise, at HRCT2, the model combining FVC% decrease trend and ≥ 20% relative increase of CALIPER-pulmonary vessel-related volume (VRS) improved the stratification of outcome (C-statistic 0.65, HR 11.0; landmark analysis at HRCT1 C-statistic 0.62, HR 13.8 and at HRCT2 C-statistic 0.58, HR 12.6). A less robust stratification of outcome distinction was also demonstrated with the categorical visual scoring of disease change., Conclusions: Annual combined CALIPER -FVC changes showed the greatest stratification of long-term outcome in stable IPF patients, beyond 2 years., Key Points: • Longitudinal high-resolution computed tomography (HRCT) data is more helpful than baseline HRCT alone for stratification of long-term outcome in IPF. • HRCT changes by visual or quantitative analysis can be added with benefit to the current spirometric reference standard to improve stratification of long-term outcome in IPF. • HRCT follow-up at 12-14 months is more helpful than HRCT follow-up at 23-26 months in clinically stable subjects with IPF.

Purpose: To investigate the role of a quantitative analysis software (CALIPER) in identifying HRCT thresholds predicting IPF patients' survival and lung function decline and its role in detecting changes of HRCT abnormalities related to treatment and their correlation with Forced Vital Capacity (FVC)., Methods: This retrospective study included 105 patients with a multidisciplinary diagnosis of IPF for whom one HRCT at baseline and concomitant FVC were available. HRCTs were evaluated with CALIPER and the correlation between FVC and radiological features were assessed. Radiological thresholds for survival prediction and functional decline were calculated for all patients. Fifty-nine patients with at least 2 serial HRCTs were classified into two groups based on treatment. For patients for whom a FVC within 3 months of the HRCT was available (n = 44), the correlation of radiological and clinical progression was evaluated., Results: The correlation between FVC and CALIPER-derived features at baseline was significant and strong. A baseline CALIPER-derived interstitial lung disease (ILD%) extent higher than 20 % and pulmonary vascular related structures (PVRS%) score greater than 5 % defined a worse prognosis. A significant progression of CALIPER-derived features in all patients was found with a faster increase in untreated patients. ILD% and PVRS% changes during follow-up demonstrated strong correlations with FVC changes., Conclusions: CALIPER quantification of fibrosis and vascular involvement could distinguish disease progression in treated versus untreated patients and predict the survival. The changes in CALIPER-derived variables over time were significantly correlated to changes in FVC., Competing Interests: Declaration of Competing Interest Dr. Bartholmai declare personal fees from Promedior, LLC, and from Imbio, LLC, outside the submitted work. Mayo Clinic has received grants from NIH/NHLBI, fees from Imbio, LLC, and Boehringer Ingelheim outside the submitted work. In addition, Dr. Bartholmai has a patent for SYSTEMS AND METHODS FOR ANALYZING IN VIVO TISSUE VOLUMES USING MEDICAL IMAGING pending to Mayo Clinic. Dr. Karvoski declare personal fees from LLC, and from Imbio, LLC, outside the submitted work. The other authors of this manuscript declare no relationships with any company, whose products or services may be related to the subject matter of the article., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: Optimal strategies to detect early interstitial lung disease (ILD) are unknown. ILD is frequently subpleural in distribution and affects lung elasticity. Lung ultrasound surface wave elastography (LUSWE) is a noninvasive method of quantifying superficial lung tissue elastic properties. In LUWSE a handheld device applied at the intercostal space vibrates the chest at a set frequency, and the lung surface wave velocity is measured by an ultrasound probe 5 mm away in the same intercostal space. We explored LUWSE's ability to detect ILD and correlated LUSWE velocity with physiological, quantitative, and visual radiologic features of subjects with known ILD and of healthy controls., Materials and Methods: Seventy-seven subjects with ILD, mostly caused by connective tissue disease, and 19 healthy controls were recruited. LUSWE was performed on all subjects in 3 intercostal lung regions bilaterally. Comparison of LUSWE velocities pulmonary function testing, visual assessment, and quantitative analysis of recent computed tomographic imaging with Computer-Aided Lung Informatics for Pathology Evaluation and Rating (CALIPER) software., Results: Sonographic velocities were higher in all lung regions for cases, with the greatest difference in the lateral lower lung. Median velocity in m/s was 5.84 versus 4.11 and 5.96 versus 4.27 (P<0.00001) for cases versus controls, left and right lateral lower lung zones, respectively. LUSWE velocity correlated negatively with vital capacity and positively with radiologist and CALIPER-detected interstitial abnormalities., Conclusions: LUSWE is a safe and noninvasive technique that shows high sensitivity to detect ILD and correlated with clinical, physiological, radiologic, and quantitative assessments of ILD. Prospective study in detecting ILD is indicated.

The aim of this study was to compare radiology-based prediction models in rheumatoid arthritis-related interstitial lung disease (RAILD) to identify patients with a progressive fibrosis phenotype.RAILD patients had computed tomography (CT) scans scored visually and using CALIPER and forced vital capacity (FVC) measurements. Outcomes were evaluated using three techniques, as follows. 1) Scleroderma system evaluating visual interstitial lung disease extent and FVC values; 2) Fleischner Society idiopathic pulmonary fibrosis (IPF) diagnostic guidelines applied to RAILD; and 3) CALIPER scores of vessel-related structures (VRS). Outcomes were compared to IPF patients.On univariable Cox analysis, all three staging systems strongly predicted outcome (scleroderma system hazard ratio (HR) 3.78, p=9×10 -5 ; Fleischner system HR 1.98, p=2×10 -3 ; and 4.4% VRS threshold HR 3.10, p=4×10 -4 ). When the scleroderma and Fleischner systems were combined, termed the progressive fibrotic system (C-statistic 0.71), they identified a patient subset (n=36) with a progressive fibrotic phenotype and similar 4-year survival to IPF. On multivariable analysis, with adjustment for patient age, sex and smoking status, when analysed alongside the progressive fibrotic system, the VRS threshold of 4.4% independently predicted outcome (model C-statistic 0.77).The combination of two visual CT-based staging systems identified 23% of an RAILD cohort with an IPF-like progressive fibrotic phenotype. The addition of a computer-derived VRS threshold further improved outcome prediction and model fit, beyond that encompassed by RAILD measures of disease severity and extent., Competing Interests: Conflict of interest: J. Jacob reports advisory board fees from Boehringer Ingelheim, outside the submitted work. Conflict of interest: N. Hirani reports personal fees from Boehringer Ingelheim, Intermune, Roche, Galecto and UCB, outside the submitted work. Conflict of interest: C.H.M. van Moorsel has nothing to disclose. Conflict of interest: S. Rajagopalan reports grants (provided to Mayo Clinic for supporting the handling and processing of the CT datasets used in the study) from Royal Brompton Hospital, during the conduct of the study; and that Mayo Clinic has received royalties from Imbio, LCC towards licensing CALIPER, outside the submitted work; in addition, S. Rajagopalan has a patent Systems And Methods For Analysing In Vivo Tissue Volumes Using Medical Imaging Data licensed to Imbio, LLC. Conflict of interest: J.T. Murchison has nothing to disclose. Conflict of interest: H.W. van Es has nothing to disclose. Conflict of interest: B.J. Bartholmai reports grants (provided to Mayo Clinic for supporting the handling and processing of CT datasets used in the study) from Royal Brompton Hospital, during the conduct of the study; and that Mayo Clinic has received royalties from Imbio, LCC towards licensing CALIPER, outside the submitted work; in addition, B.J. Bartholmai has a patent Systems And Methods For Analysing In Vivo Tissue Volumes Using Medical Imaging Data licensed to Imbio, LLC. Conflict of interest: F.T. van Beek has nothing to disclose. Conflict of interest: M.H.L. Struik has nothing to disclose. Conflict of interest: G.A. Stewart has nothing to disclose. Conflict of interest: M. Kokosi has nothing to disclose. Conflict of interest: R. Egashira has nothing to disclose. Conflict of interest: A.L. Brun has nothing to disclose. Conflict of interest: G. Cross has nothing to disclose. Conflict of interest: J. Barnett has nothing to disclose. Conflict of interest: A. Devaraj reports personal fees from Roche and Boehringer Ingelheim, outside the submitted work. Conflict of interest: G. Margaritopoulos has nothing to disclose. Conflict of interest: R. Karwoski reports grants (provided to Mayo Clinic for supporting the handling and processing of CT datasets used in the study) from Royal Brompton Hospital, during the conduct of the study; and that Mayo Clinic has received royalties from Imbio, LCC towards licensing CALIPER, outside the submitted work; in addition, R. Karwoski has a patent Systems And Methods For Analysing In Vivo Tissue Volumes Using Medical Imaging Data licensed to Imbio, LLC. Conflict of interest: E. Renzoni reports lecture fees from Roche and Takeda, and lecture fees and advisory board fees from Boehringer, outside the submitted work. Conflict of interest: T.M. Maher has, via his institution, received industry-academic funding from GlaxoSmithKline R&D, UCB and Novartis and has received consultancy or speakers fees from Apellis, Astra Zeneca, Bayer, Biogen Idec, Boehringer Ingelheim, Cipla, GlaxoSmithKline R&D, Lanthio, InterMune, ProMetic, Roche, Sanofi-Aventis, Takeda and UCB. Conflict of interest: A.U. Wells reports advisory board and speaker fees from Intermune, Boehringer Ingelheim, Roche and Bayer, advisory board fees from Gilead and MSD, and speaker fees from Chiesi, outside the submitted work., (Copyright ©ERS 2019.)

Rationale: Quantitative computed tomographic (CT) measures of baseline disease severity might identify patients with idiopathic pulmonary fibrosis (IPF) with an increased mortality risk. We evaluated whether quantitative CT variables could act as a cohort enrichment tool in future IPF drug trials., Objectives: To determine whether computer-derived CT measures, specifically measures of pulmonary vessel-related structures (VRSs), can better predict functional decline and survival in IPF and reduce requisite sample sizes in drug trial populations., Methods: Patients with IPF undergoing volumetric noncontrast CT imaging at the Royal Brompton Hospital, London, and St. Antonius Hospital, Utrecht, were examined to identify pulmonary function measures (including FVC) and visual and computer-derived (CALIPER [Computer-Aided Lung Informatics for Pathology Evaluation and Rating] software) CT features predictive of mortality and FVC decline. The discovery cohort comprised 247 consecutive patients, with validation of results conducted in a separate cohort of 284 patients, all fulfilling drug trial entry criteria., Measurements and Main Results: In the discovery and validation cohorts, CALIPER-derived features, particularly VRS scores, were among the strongest predictors of survival and FVC decline. CALIPER results were accentuated in patients with less extensive disease, outperforming pulmonary function measures. When used as a cohort enrichment tool, a CALIPER VRS score greater than 4.4% of the lung was able to reduce the requisite sample size of an IPF drug trial by 26%., Conclusions: Our study has validated a new quantitative CT measure in patients with IPF fulfilling drug trial entry criteria-the VRS score-that outperformed current gold standard measures of outcome. When used for cohort enrichment in an IPF drug trial setting, VRS threshold scores can reduce a required IPF drug trial population size by 25%, thereby limiting prohibitive trial costs. Importantly, VRS scores identify patients in whom antifibrotic medication prolongs life and reduces FVC decline.

The majority of incidentally and screen-detected lung cancers are adenocarcinomas. Optimal management of these tumors is clinically challenging due to variability in tumor histopathology and behavior. Invasive adenocarcinoma (IA) is generally aggressive while adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) may be extremely indolent. Computer Aided Nodule Analysis and Risk Yield (CANARY) is a quantitative computed tomography (CT) analysis tool that allows non-invasive assessment of tumor characteristics. This analysis may obviate the need for tissue biopsy and facilitate the risk stratification of adenocarcinoma of the lung. CANARY was developed by unsupervised machine learning techniques using CT data of histopathologically-characterized adenocarcinomas of the lung. This technique identified 9 distinct exemplars that constitute the spectrum of CT features found in adenocarcinoma of the lung. The distributions of these features in a nodule correlate with histopathology. Further automated clustering of CANARY nodules defined three distinct groups that have distinctly different post-resection disease free survival (DFS). CANARY has been validated within the NLST cohort and multiple other cohorts. Using semi-automated segmentation as input to CANARY, there is excellent repeatability and interoperator correlation of results. Confirmation and longitudinal tracking of indolent adenocarcinoma with CANARY may ultimately add decision support in nuanced cases where surgery may not be in the best interest of the patient due to competing comorbidity. Currently under investigation is CANARY's role in detecting differing driver mutations and tumor response to targeted chemotherapeutics. Combining the results from CANARY analysis with clinical information and other quantitative techniques such as analysis of the tumor-free surrounding lung may aid in building more powerful predictive models. The next step in CANARY investigation will be its prospective application, both in selecting low-risk stage 1 adenocarcinoma for active surveillance and investigation in selecting high-risk early stage adenocarcinoma for adjuvant therapy., Competing Interests: Conflicts of Interest: CANARY software is currently licensed to Imbio LLC (annual royalties <$5,000). This COI applies to Mayo Clinic and B Bartholmai, F Maldonado, R Karwoski, T Peikert and S Rajagopalan. R Clay has no conflicts of interest to declare.

Background and Objective: This study evaluated whether patients with combined pulmonary fibrosis and emphysema (CPFE) have an increased likelihood of pulmonary hypertension (PHT) when compared with idiopathic pulmonary fibrosis (IPF) patients without emphysema., Methods: Two consecutive IPF populations having undergone transthoracic echocardiography were examined (n = 223 and n = 162). Emphysema and interstitial lung disease (ILD) extent were quantified visually; ILD extent was also quantified by a software tool, CALIPER. Echocardiographic criteria categorized PHT risk., Results: The prevalence of an increased PHT likelihood was 29% and 31% in each CPFE cohort. Survival at 12 months was 60% across both CPFE cohorts with no significantly worsened outcome identified when compared with IPF patients without emphysema. Using logistic regression models in both cohorts, total computed tomography (CT) disease extent (ILD and emphysema) predicted the likelihood of PHT. After adjustment for total disease extent, CPFE had no stronger association with PHT likelihood than IPF patients without emphysema., Conclusion: Our findings indicate that the reported association between CPFE and PHT is explained by the summed baseline CT extents of ILD and emphysema. Once baseline severity is taken into account, CPFE is not selectively associated with a malignant microvascular phenotype, when compared with IPF patients without emphysema., (© 2017 Asian Pacific Society of Respirology.)

Purpose: Fibrotic interstitial lung diseases presenting with nonspecific and overlapping radiologic findings may be difficult to diagnose without surgical biopsy. We hypothesized that baseline quantifiable radiologic features and their short-term interval change may be predictive of underlying histologic diagnosis as well as long-term survival in idiopathic pulmonary fibrosis (IPF) presenting without honeycombing versus nonspecific interstitial pneumonia (NSIP)., Materials and Methods: Forty biopsy-confirmed IPF and 20 biopsy-confirmed NSIP patients with available high-resolution chest computed tomography 4 to 24 months apart were studied. CALIPER software was used for the automated characterization and quantification of radiologic findings., Results: IPF subjects were older (66 vs. 48; P<0.0001) with lower diffusion capacity for carbon monoxide and higher volumes of baseline reticulation (193 vs. 83 mL; P<0.0001). Over the interval period, compared with NSIP, IPF patients experienced greater functional decline (forced vital capacity, -6.3% vs. -1.7%; P=0.02) and radiologic progression, as noted by greater increase in reticulation volume (24 vs. 1.74 mL; P=0.048), and decrease in normal (-220 vs. -37.7 mL; P=0.045) and total lung volumes (-198 vs. 58.1 mL; P=0.03). Older age, male gender, higher reticulation volumes at baseline, and greater interval decrease in normal lung volumes were predictive of IPF. Both baseline and short-term changes in quantitative radiologic findings were predictive of mortality., Conclusions: Baseline quantitative radiologic findings and assessment of short-term disease progression may help characterize underlying IPF versus NSIP in those with difficult to differentiate clinicoradiologic presentations. Our study supports the possible utility of assessing serial quantifiable high-resolution chest computed tomographic findings for disease differentiation in these 2 entities.

Objectives: To determine whether computer-based CT quantitation of change can improve on visual change quantification of parenchymal features in IPF., Methods: Sixty-six IPF patients with serial CT imaging (6-24 months apart) had CT features scored visually and with a computer software tool: ground glass opacity, reticulation and honeycombing (all three variables summed as interstitial lung disease extent [ILD]) and emphysema. Pulmonary vessel volume (PVV) was estimated by computer only. Relationships between changes in CT features and forced vital capacity (FVC) were examined using univariate and multivariate linear regression analyses., Results: On univariate analysis, changes in computer variables demonstrated stronger linkages to FVC change than changes in visual scores (CALIPER ILD:R 2 =0.53, p<0.0001; Visual ILD:R 2 =0.16, p=0.001). PVV increase correlated most strongly with relative FVC change (R 2 =0.57). When PVV constituents (vessel size and location) were examined, an increase in middle zone vessels linked most strongly to FVC decline (R 2 =0.57) and was independent of baseline disease severity (characterised by CT fibrosis extent, FVC, or DLco)., Conclusions: An increase in PVV, specifically an increase in middle zone lung vessels, was the strongest CT determinant of FVC decline in IPF and was independent of baseline disease severity., Key Points: • Computer analysis improves on visual CT scoring in evaluating deterioration on CT • Increasing pulmonary vessel volume is the strongest CT predictor of functional deterioration • Increasing pulmonary vessel volume predicts functional decline independent of baseline disease severity.

Objective: The relationship between inflammation, obesity, and adverse metabolic conditions is associated with adipose tissue macrophages (ATM). This study compared the measurements of human ATM using flow cytometry, immunohistochemistry (IHC), and real-time polymerase chain reaction (RT-PCR) of ATM markers., Methods: A new software program (AMCounter) was evaluated to help measure ATM using IHC, and this was compared to flow cytometry and RT-PCR., Results: IHC had good intraindividual reproducibility for total (CD68), proinflammatory (CD14), and anti-inflammatory (CD206) ATM. The AMCounter improved interreader agreement and was more time efficient. Flow cytometry had acceptable intraindividual reproducibility for the percentage of CD68 + cells that were CD14 + or CD206 + , but not for ATMs per gram of tissue. ATMs per gram of tissue was much greater using IHC than flow cytometry. The flow cytometry and IHC measures of ATM from the same biopsies were not correlated. There were statistically significant correlations between RT-PCR CD68 and IHC CD68, CD14, and CD206 ATMs per 100 adipocytes. Also of interest were statistically significant correlations between RT-PCR CD68 and IHC CD68, CD14, and adipose flow cytometry measures of CD68 + , CD68 + /CD14 + , and CD68 + /CD206 + ATMs per gram of tissue., Conclusions: The AMCounter software helps provide reproducible and efficient measures of IHC ATMs. Flow cytometry, IHC, and RT-PCR measures of adipose inflammation provide somewhat different information., (© 2017 The Obesity Society.)

Background and Objective: To determine whether computer-based quantification (CALIPER software) is superior to visual computed tomography (CT) scoring in the identification of CT patterns indicative of restrictive and obstructive functional indices in hypersensitivity pneumonitis (HP)., Methods: A total of 135 consecutive HP patients had CT parenchymal patterns evaluated quantitatively by both visual scoring and CALIPER. Results were evaluated against: forced vital capacity (FVC), total lung capacity (TLC), diffusing capacity for carbon monoxide (DL CO ) and a composite physiological index (CPI) to identify which CT scoring method better correlated with functional indices., Results: CALIPER-derived scores of total interstitial lung disease extent correlated more strongly than visual scores: FVC (CALIPER R = 0.73, visual R = 0.51); DL CO (CALIPER R = 0.61, visual R = 0.48); and CPI (CALIPER R = 0·70, visual R = 0·55). The CT variable that correlated most strongly with restrictive functional indices was CALIPER pulmonary vessel volume (PVV): FVC R = 0.75, DL CO R = 0.68 and CPI R = 0.76. Ground-glass opacity quantified by CALIPER alone demonstrated strong associations with restrictive functional indices: CALIPER FVC R = 0.65; DL CO R = 0.59; CPI R = 0.64; and visual = not significant. Decreased attenuation lung quantified by CALIPER was a better morphological measure of obstructive lung disease than equivalent visual scores as judged by relationships with TLC (CALIPER R = 0.63 and visual R = 0.12). All results were maintained on multivariate analysis., Conclusion: CALIPER improved on visual scoring in HP as judged by restrictive and obstructive functional correlations. Decreased attenuation regions of the lung quantified by CALIPER demonstrated better linkages to obstructive lung physiology than visually quantified CT scores. A novel CALIPER variable, the PVV, demonstrated the strongest linkages with restrictive functional indices and could represent a new automated index of disease severity in HP., (© 2017 Asian Pacific Society of Respirology.)

Background: Unclassifiable-interstitial lung disease (uILD) represents a heterogeneous collection of pathologies encompassing those fibrosing lung diseases which do not fulfill current diagnostic criteria. We evaluated baseline and longitudinal functional and CT (visual and quantitative computer [CALIPER] analysis) variables to identify outcome predictors in uILD., Methods: Consecutive patients with uILD on multidisciplinary review (n = 95) had baseline functional (FVC, DLco, CPI [composite physiologic index]) and CT features (visual evaluation: CT pattern, fibrosis extent, honeycombing presence, traction bronchiectasis severity, pulmonary artery (PA) diameter; CALIPER evaluation: fibrosis extent, pulmonary vessel volume (PVV)) examined in univariate and multivariate Cox regression models. Change in functional and CT variables were examined in a patient subset (n = 37), to identify indicators of outcome., Results: On univariate analysis, CPI was the most powerful functional predictor of mortality (p < 0.0001). Visual traction bronchiectasis (p < 0.0001), PA diameter (p < 0.0001) and honeycombing presence (p = 0.0001) and CALIPER PVV (p = 0.0003) were the strongest CT outcome predictors. On multivariate analysis of baseline indices, traction bronchiectasis (p = 0.003), PA diameter (p = 0.003) and CPI (p = 0.0001) independently predicted mortality. Colinearity with functional indices precluded the evaluation of CALIPER PVV in multivariate models. On evaluation of longitudinal variables, increasing CALIPER fibrosis extent was the strongest outcome predictor, and remained so following adjustment for baseline disease severity, and when FVC declines were marginal., Conclusions: In uILD patients, CPI, traction bronchiectasis severity and PA diameter independently predicted outcome at baseline. Increasing fibrosis extent measured by CALIPER was the most powerful index of outcome regardless of baseline disease severity and strongly predicted outcome in patients with marginal FVC declines., (Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.)

Background: Hypersensitivity pneumonitis (HP) has a variable clinical course. Modelling of quantitative CALIPER-derived CT data can identify distinct disease phenotypes. Mortality prediction using CALIPER analysis was compared to the interstitial lung disease gender, age, physiology (ILD-GAP) outcome model., Methods: CALIPER CT analysis of parenchymal patterns in 98 consecutive HP patients was compared to visual CT scoring by two radiologists. Functional indices including forced vital capacity (FVC) and diffusion capacity for carbon monoxide (DLco) in univariate and multivariate Cox mortality models. Automated stratification of CALIPER scores was evaluated against outcome models., Results: Univariate predictors of mortality included visual and CALIPER CT fibrotic patterns, and all functional indices. Multivariate analyses identified only two independent predictors of mortality: CALIPER reticular pattern (p = 0.001) and DLco (p < 0.0001). Automated stratification distinguished three distinct HP groups (log-rank test p < 0.0001). Substitution of automated stratified groups for FVC and DLco in the ILD-GAP model demonstrated no loss of model strength (C-Index = 0.73 for both models). Model strength improved when automated stratified groups were combined with the ILD-GAP model (C-Index = 0.77)., Conclusions: CALIPER-derived variables are the strongest CT predictors of mortality in HP. Automated CT stratification is equivalent to functional indices in the ILD-GAP model for predicting outcome in HP., Key Points: • Computer CT analysis better predicts mortality than visual CT analysis in HP. • Quantitative CT analysis is equivalent to functional indices for prognostication in HP. • Prognostication using the ILD-GAP model improves when combined with quantitative CT analysis.

This study aimed to investigate whether the combination of fibrosis and emphysema has a greater effect than the sum of its parts on functional indices and outcome in idiopathic pulmonary fibrosis (IPF), using visual and computer-based (CALIPER) computed tomography (CT) analysis.Consecutive patients (n=272) with a multidisciplinary IPF diagnosis had the extent of interstitial lung disease (ILD) scored visually and by CALIPER. Visually scored emphysema was subcategorised as isolated or mixed with fibrotic lung. The CT scores were evaluated against functional indices forced vital capacity (FVC), diffusing capacity of the lungs for carbon monoxide ( D LCO ), transfer coefficient of the lung for carbon monoxide ( K CO ), composite physiologic index (CPI)) and mortality.The presence and extent of emphysema had no impact on survival. Results were maintained following correction for age, gender, smoking status and baseline severity using D LCO , and combined visual emphysema and ILD extent. Visual emphysema quantitation indicated that relative preservation of lung volumes (FVC) resulted from tractionally dilated airways within fibrotic lung, ventilating areas of admixed emphysema (p<0.0001), with no independent effect on FVC from isolated emphysema. Conversely, only isolated emphysema (p<0.0001) reduced gas transfer ( D LCO ).There is no prognostic impact of emphysema in IPF, beyond that explained by the additive extents of both fibrosis and emphysema. With respect to the location of pulmonary fibrosis, emphysema distribution determines the functional effects of emphysema., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2017.)

Background: Chronic hypersensitivity pneumonitis (CHP) has a variable disease course. Computer analysis of CT features was used to identify a subset of CHP patients with an outcome similar to patients with idiopathic pulmonary fibrosis (IPF)., Methods: Consecutive patients with a multi-disciplinary team diagnosis of CHP (n = 116) had pulmonary function tests (FEV1, FVC, DLco, Kco, and a composite physiologic index [CPI]) and CT variables predictive of mortality evaluated by analysing visual and computer-based (CALIPER) parenchymal features: total interstitial lung disease (ILD) extent, honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume (PVV), emphysema, and traction bronchiectasis. Mean survival was compared between both CHP and IPF patients (n = 185)., Results: In CHP, visual/CALIPER measures of reticular pattern, honeycombing, visual traction bronchiectasis, and CALIPER ILD extent were predictive of mortality (p < 0 · 05) on univariate analysis. PVV was strongly predictive of mortality on univariate (p < 0 · 0001) and multivariate analysis independent of age, gender and disease severity (represented by the CPI [p < 0 · 01]). CHP patients with a PVV threshold >6 · 5% of the lung had a mean survival (35 · 3 ± 6 · 1 months; n = 20/116 [17%]) and rate of disease progression that closely matched IPF patients (38 · 4 ± 2 · 2 months; n = 185)., Conclusions: Pulmonary vessel volume can identify CHP patients at risk of aggressive disease and a poor IPF-like prognosis.

Computer-based computed tomography (CT) analysis can provide objective quantitation of disease in idiopathic pulmonary fibrosis (IPF). A computer algorithm, CALIPER, was compared with conventional CT and pulmonary function measures of disease severity for mortality prediction.CT and pulmonary function variables (forced expiratory volume in 1 s, forced vital capacity, diffusion capacity of the lung for carbon monoxide, transfer coefficient of the lung for carbon monoxide and composite physiologic index (CPI)) of 283 consecutive patients with a multidisciplinary diagnosis of IPF were evaluated against mortality. Visual and CALIPER CT features included total extent of interstitial lung disease, honeycombing, reticular pattern, ground glass opacities and emphysema. In addition, CALIPER scored pulmonary vessel volume (PVV) while traction bronchiectasis and consolidation were only scored visually. A combination of mortality predictors was compared with the Gender, Age, Physiology model.On univariate analyses, all visual and CALIPER-derived interstitial features and functional indices were predictive of mortality to a 0.01 level of significance. On multivariate analysis, visual CT parameters were discarded. Independent predictors of mortality were CPI (hazard ratio (95% CI) 1.05 (1.02-1.07), p<0.001) and two CALIPER parameters: PVV (1.23 (1.08-1.40), p=0.001) and honeycombing (1.18 (1.06-1.32), p=0.002). A three-group staging system derived from this model was powerfully predictive of mortality (2.23 (1.85-2.69), p<0.0001).CALIPER-derived parameters, in particular PVV, are more accurate prognostically than traditional visual CT scores. Quantitative tools such as CALIPER have the potential to improve staging systems in IPF., (Copyright ©ERS 2017.)

Background: To evaluate computer-based computer tomography (CT) analysis (CALIPER) against visual CT scoring and pulmonary function tests (PFTs) when predicting mortality in patients with connective tissue disease-related interstitial lung disease (CTD-ILD). To identify outcome differences between distinct CTD-ILD groups derived following automated stratification of CALIPER variables., Methods: A total of 203 consecutive patients with assorted CTD-ILDs had CT parenchymal patterns evaluated by CALIPER and visual CT scoring: honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume, emphysema, and traction bronchiectasis. CT scores were evaluated against pulmonary function tests: forced vital capacity, diffusing capacity for carbon monoxide, carbon monoxide transfer coefficient, and composite physiologic index for mortality analysis. Automated stratification of CALIPER-CT variables was evaluated in place of and alongside forced vital capacity and diffusing capacity for carbon monoxide in the ILD gender, age physiology (ILD-GAP) model using receiver operating characteristic curve analysis., Results: Cox regression analyses identified four independent predictors of mortality: patient age (P < 0.0001), smoking history (P = 0.0003), carbon monoxide transfer coefficient (P = 0.003), and pulmonary vessel volume (P < 0.0001). Automated stratification of CALIPER variables identified three morphologically distinct groups which were stronger predictors of mortality than all CT and functional indices. The Stratified-CT model substituted automated stratified groups for functional indices in the ILD-GAP model and maintained model strength (area under curve (AUC) = 0.74, P < 0.0001), ILD-GAP (AUC = 0.72, P < 0.0001). Combining automated stratified groups with the ILD-GAP model (stratified CT-GAP model) strengthened predictions of 1- and 2-year mortality: ILD-GAP (AUC = 0.87 and 0.86, respectively); stratified CT-GAP (AUC = 0.89 and 0.88, respectively)., Conclusions: CALIPER-derived pulmonary vessel volume is an independent predictor of mortality across all CTD-ILD patients. Furthermore, automated stratification of CALIPER CT variables represents a novel method of prognostication at least as robust as PFTs in CTD-ILD patients.

Purpose: The aim of the study was to determine whether a novel computed tomography (CT) postprocessing software technique (CALIPER) is superior to visual CT scoring as judged by functional correlations in idiopathic pulmonary fibrosis (IPF)., Materials and Methods: A total of 283 consecutive patients with IPF had CT parenchymal patterns evaluated quantitatively with CALIPER and by visual scoring. These 2 techniques were evaluated against: forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), diffusing capacity for carbon monoxide (DLco), carbon monoxide transfer coefficient (Kco), and a composite physiological index (CPI), with regard to extent of interstitial lung disease (ILD), extent of emphysema, and pulmonary vascular abnormalities., Results: CALIPER-derived estimates of ILD extent demonstrated stronger univariate correlations than visual scores for most pulmonary function tests (PFTs): (FEV1: CALIPER R=0.29, visual R=0.18; FVC: CALIPER R=0.41, visual R=0.27; DLco: CALIPER R=0.31, visual R=0.35; CPI: CALIPER R=0.48, visual R=0.44). Correlations between CT measures of emphysema extent and PFTs were weak and did not differ significantly between CALIPER and visual scoring. Intriguingly, the pulmonary vessel volume provided similar correlations to total ILD extent scored by CALIPER for FVC, DLco, and CPI (FVC: R=0.45; DLco: R=0.34; CPI: R=0.53)., Conclusions: CALIPER was superior to visual scoring as validated by functional correlations with PFTs. The pulmonary vessel volume, a novel CALIPER CT parameter with no visual scoring equivalent, has the potential to be a CT feature in the assessment of patients with IPF and requires further exploration.