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Statement of Problem: Soft liners are essential for denture wearers, which aids in the healing of soft tissue injuries caused by rough denture base surfaces. Silicone soft liners, while effective, can accumulate biofilm over time, necessitating enhancement., Purpose: This in vitro study aimed to assess the efficacy of silicone soft liners incorporating varying concentrations of cerium oxide nanoparticles., Materials and Methods: A stainless-steel die as per ISO standard 10139-2-2018 (35 × 6 mm), Using G*Power 3.0.10 software, 400 samples were prepared with 95 % confidence interval and 80 % power. Samples were divided into five groups: surface morphology (Group A), surface hardness (Group B), wettability (Group C), cytotoxicity (Group D), and antifungal property (Group E). Each group was subdivided based on cerium oxide nanoparticle concentrations. Samples were stored in artificial saliva until evaluation. Surface morphology was examined via scanning electron microscopy (SEM), surface hardness using Shore A Durometer, wettability by drop shape analysis, cytotoxicity via MTT assay, and antifungal properties using crystal violet staining.Data were assessed for normal distribution using Kolmogorov-Smirnov and Shapiro-Wilk tests., Results: SEM analysis showed optimal nanoparticle dispersion in Group A2(0.25 %) and A3 (0.5 %). Group B2 (0.25 %) exhibited the lowest mean surface hardness, decreasing from day 1 to day 30. Group C3 demonstrated the most hydrophobic surface across days. Group D2 exhibited the least cytotoxicity at all time intervals. Group E4 displayed the highest antifungal activity., Conclusion: Within study limitations, silicone soft liners modified with 0.25 % and 0.5 % cerium oxide nanoparticles exhibited superior properties in surface hardness and cytotoxicity. Optimal surface morphology and wettability were observed with 0.5 % concentration, while antifungal efficacy peaked at 1 %. These findings suggest clinical potential for treating damaged oral tissues., Clinical Implications: Soft liners modified with 0.25 % and 0.5 % cerium oxide nanoparticles may benefit patients with oral tissue abuse, offering enhanced therapeutic properties., Competing Interests: 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., (© 2024 The Authors.)

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.

Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification., Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes., Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival., Measurements and Main Results: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P < 0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases., Conclusions: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

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. [ABSTRACT FROM AUTHOR]

Background: In patients with pulmonary nodules undergoing computed tomography (CT)-guided localization procedures, a range of liquid-based materials have been employed to date in an effort to guide video-assisted thoracoscopic surgery (VATS) procedures to resect target nodules. However, the relative performance of these different liquid-based localization strategies has yet to be systematically evaluated. Accordingly, this study was developed with the aim of examining the relative safety and efficacy of CT-guided indocyanine green (IG) and blue-stained glue (BSG) PN localization. Methods: Consecutive patients with PNs undergoing CT-guided localization prior to VATS from November 2021 - April 2022 were enrolled in this study. Safety and efficacy outcomes were compared between patients in which different localization materials were used. Results: In total, localization procedures were performed with IG for 121 patients (140 PNs), while BSG was used for localization procedures for 113 patients (153 PNs). Both of these materials achieved 100% technical success rates for localization, with no significant differences between groups with respect to the duration of localization (P = 0.074) or visual analog scale scores (P = 0.787). Pneumothorax affected 8 (6.6%) and 8 (7.1%) patients in the respective IG and BSG groups (P = 0.887), while 12 (9.9%) and 10 (8.8%) patients of these patients experienced pulmonary hemorrhage. IG was less expensive than BSG ($17.2 vs. $165). VATS sublobar resection procedure technical success rates were also 100% in both groups, with no instances of conversion to thoracotomy. Conclusions: IG and BSG both offer similarly high levels of clinical safety and efficacy when applied for preoperative CT-guided PN localization, with IG being less expensive than BSG. [ABSTRACT FROM AUTHOR]

Purpose: To develop a comprehensive multi-classification model that combines radiomics and clinic-radiological features to accurately predict the invasiveness and differentiation of pulmonary adenocarcinoma nodules. Methods: A retrospective analysis was conducted on a cohort comprising 500 patients diagnosed with lung adenocarcinoma between January 2020 and December 2022. The dataset included preoperative CT images and histological reports of adenocarcinoma in situ (AIS, n = 97), minimally invasive adenocarcinoma (MIA, n = 139), and invasive adenocarcinoma (IAC, n = 264) with well-differentiated (WIAC, n = 99), moderately differentiated (MIAC, n = 84), and poorly differentiated IAC (PIAC, n = 81). The patients were classified into two groups (IAC and non-IAC) for binary classification and further divided into three and five groups for multi-classification. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO) algorithm to identify the most informative radiomics and clinic-radiological features. Eight machine learning (ML) models were developed using these features, and their performance was evaluated using accuracy (ACC) and the area under the receiver-operating characteristic curve (AUC). Results: The combined model, utilizing the support vector machine (SVM) algorithm, demonstrated improved performance in the testing cohort, achieving an AUC of 0.942 and an ACC of 0.894 for the two-classification task. For the three- and five-classification tasks, the combined model employing the one versus one strategy of SVM (SVM-OVO) outperformed other models, with ACC values of 0.767 and 0.607, respectively. The AUC values for histological subtypes ranged from 0.787 to 0.929 in the testing cohort, while the Macro-AUC and Micro-AUC of the multi-classification models ranged from 0.858 to 0.896. Conclusions: A multi-classification radiomics model combined with clinic-radiological features, using the SVM-OVO algorithm, holds promise for accurately predicting the histological characteristics of pulmonary adenocarcinoma nodules, which contributes to personalized treatment strategies for patients with lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Background: Idiopathic pulmonary fibrosis (IPF) is a disease that primarily occurs in elderly individuals. However, it is difficult to diagnose and has a complex disease course. High-resolution computed tomography (HRCT) and lung function testing are crucial for its diagnosis and follow-up. However, the correlation of HRCT findings with lung function test results has not been extensively investigated. Methods: This study retrospectively analysed the medical records and images of patients with IPF. Patients with evident emphysema and lung cancer were excluded. The diagnosis of all the included cases was confirmed following a discussion among specialists from multiple disciplines. The correlation of HRCT findings, including fibrotic score, HRCT lung volume, pulmonary artery trunk (PA) diameter and pulmonary vascular volume (PVV), with lung function test parameters, such as forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO), was analysed. Results: A total of 32 patients were included. Higher fibrotic and PVV scores were significantly correlated with lower DLCO (r = − 0.59, p = 0.01; r = − 0.43, p = 0.03, respectively) but not with FVC. Higher PVV score significantly correlated with higher fibrotic score (r = 0.59, p < 0.01) and PA diameter (r = 0.47, p = 0.006). Conclusion: Our study demonstrated the structural and functional correlation of IPF. The extent of lung fibrosis (fibrotic score) and PVV score were associated with DLCO but not with FVC. The PA diameter, which reflects the pulmonary artery pressure, was found to be associated with the PVV score. [ABSTRACT FROM AUTHOR]

Differentiating the invasiveness of ground-glass nodules (GGN) is clinically important, and several institutions have attempted to develop their own solutions by using computed tomography images. The purpose of this study is to evaluate Computer-Aided Analysis of Risk Yield (CANARY), a validated virtual biopsy and risk-stratification machine-learning tool for lung adenocarcinomas, in a Korean patient population. To this end, a total of 380 GGNs from 360 patients who underwent pulmonary resection in a single institution were reviewed. Based on the Score Indicative of Lung Cancer Aggression (SILA), a quantitative indicator of CANARY analysis results, all of the GGNs were classified as "indolent" (atypical adenomatous hyperplasia, adenocarcinomas in situ, or minimally invasive adenocarcinoma) or "invasive" (invasive adenocarcinoma) and compared with the pathology reports. By considering the possibility of uneven class distribution, statistical analysis was performed on the 1) entire cohort and 2) randomly extracted six sets of class-balanced samples. For each trial, the optimal cutoff SILA was obtained from the receiver operating characteristic curve. The classification results were evaluated using several binary classification metrics. Of a total of 380 GGNs, the mean SILA for 65 (17.1%) indolent and 315 (82.9%) invasive lesions were 0.195±0.124 and 0.391±0.208 (p < 0.0001). The area under the curve (AUC) of each trial was 0.814 and 0.809, with an optimal threshold SILA of 0.229 for both. The macro F1-score and geometric mean were found to be 0.675 and 0.745 for the entire cohort, while both scored 0.741 in the class-equalized dataset. From these results, CANARY could be confirmed acceptable in classifying GGN for Korean patients after the cutoff SILA was calibrated. We found that adjusting the cutoff SILA is needed to use CANARY in other countries or races, and geometric mean could be more objective than F1-score or AUC in the binary classification of imbalanced data. [ABSTRACT FROM AUTHOR]

Keywords: COLDICE; cryobiopsy; idiopathic pulmonary fibrosis; interstitial lung disease; telomeres EN COLDICE cryobiopsy idiopathic pulmonary fibrosis interstitial lung disease telomeres 756 763 8 06/22/20 20200701 NES 200701 Abbreviations CT computed tomography DL CO diffusion capacity of the lung for carbon monoxide FVC forced vital capacity ILA interstitial lung abnormality ILD interstitial lung disease IPF idiopathic pulmonary fibrosis MRCI Medication Regimen Complexity Index PrePF Preclinical pulmonary fibrosis SLB surgical lung biopsy TB tuberculosis TBLC transbronchial lung cryobiopsy Summary of key points Antifibrotic therapy has been proven to be effective in the treatment of progressive fibrosing lung diseases other than IPF. While the increased risk of sarcoidosis in patients with TB persisted throughout the 15-year follow-up period, the risk of developing TB in sarcoid patients was increased only in the first year after diagnosis. Silicosis, a severe occupational lung disease, is sometimes misdiagnosed as sarcoidosis due to imaging similarities, including centrilobular nodularity, bilateral airspace opacification (albeit unlike sarcoid often lower predominant) and calcified lymphadenopathy.[23] There remain no effective treatment options for this entirely avoidable lung disease, now a source of growing international concern.[24] IMPACT OF ILD ON QUALITY OF LIFE Key Points Patients continue to report deficiencies in the quality of their care with specific reference to provision of information, drug side effect management and access to specialist care. Polypharmacy is a common burden in patients with ILD, with the greatest increase seen in IPF patients following initiation of antifibrotic therapy. [Extracted from the article]

Background: Progression of the disease in idiopathic pulmonary fibrosis (IPF) is difficult to predict, due to its variable and heterogenous course. The relationship between radiographic progression and functional decline in IPF is unclear. We sought to confirm that a simple HRCT fibrosis visual score is a reliable predictor of mortality in IPF, when longitudinally followed; and to ascertain which pulmonary functional variables best reflect clinically significant radiographic progression.Methods: One-hundred-twenty-three consecutive patients with IPF from 2 centers were followed for an average of 3 years. Longitudinal changes of HRCT fibrosis scores, forced vital capacity (FVC), total lung capacity and diffusing lung capacity for carbon monoxide were considered. HRCTs were scored by 2 chest radiologists. The primary outcome was lung transplant (LTx)-free survival after the follow-up HRCT.Results: During the follow-up period, 43 deaths and 11 LTx occurred. On average, the HRCT fibrosis score increased significantly, and a longitudinal increase > 7% predicted LTx-free survival significantly, with good specificity, but limited sensitivity. The correlation between radiographic and functional progression was moderately significant. HRCT progression and FVC decline predicted LTx-free survival independently and significantly, with better sensitivity, but worse specificity for a ≥ 5% decline of FVC. However, the area under the curve towards LTx-survival were only 0.61 and 0.62, respectively.Conclusions: The HRCT fibrosis visual score is a reliable and responsive tool to detect clinically meaningful disease progression. Although no individual pulmonary function test closely reflects radiographic progression, a longitudinal FVC decline improves sensitivity in the detection of clinically significant disease progression. However, the accuracy of these methods remains limited, and better prognostication models need to be found. [ABSTRACT FROM AUTHOR]

Interstitial lung disease (ILD) remains a major cause of morbidity and mortality in systemic sclerosis (SSc). Study aim is to characterize and quantify SSc-ILD by using Computer-Aided Lung Informatics for Pathology Evaluation and Rating (CALIPER). Secondly, our objective is to evaluate which radiological pattern is predictive of lung function decline at 12 months follow-up. In the prospective study (IRB 5435), 66 SSc patients underwent high-resolution computerized tomography (HRCT) at baseline. HRCT was performed according to standard protocol using a CT 64GE light speed VCT power scanner. CALIPER classified lung parenchyma on volume units. Every volume unit was classified into radiological parenchymal patterns (honeycombing, reticular and ground glass). Pulmonary function tests (PFTs) were performed at baseline and after 12 months of follow-up. Cigarette smoking and other lung diseases unrelated to SSc are exclusion criteria. CALIPER analysis showed normal lung parenchyma 87.4 ± 9.8%, ground glass 2.8 ± 5.3%, reticular 4 ± 5.7%, and honeycombing 1 ± 1%. In multiple regression analysis, FEV1 (p < 0.0001), FVC (p = 0.001), and DLCO (p < 0.0001) measurements at baseline showed a negative correlation with the reticular pattern percentage. At follow-up, DLCO reduction showed a positive correlation (p < 0.001) with the percentage of ground glass pattern (r = 0.33, beta coefficient = 0.51). In the ROC curve analysis, ground glass score is a good predictor (0.75, p = 0.009; 95% CI 0.59–0.91) of DLCO worsening, defined as a decrease of more than 10% of DLCO. Using a cutoff ≥ 4.5 for ground glass score, the RR for DLCO worsening is 6.8 (p < 0.01; 95% CI 1.6–29.2). The results of this study show that CALIPER is useful not only for quantifying lung damage but also for assessing worsening PFTs, but larger studies are needed to confirm these preliminary data. Key Points • At baseline reticular pattern showed negative correlation with PFTs • At follow-up ground glass pattern predicts worsening of DLCO • CALIPER is a useful to quantify lung damage [ABSTRACT FROM AUTHOR]

CALIPER is a computer-based quantitative algorithm to accurately characterize and quantify pulmonary fibrosis, and a revised version of composite physiologic index (CPI) has been developed against this new algorithm. The prognostic capabilities of the original and CALIPER-revised versions of CPI were compared in a cohort of 185 patients with IPF prospectively followed in 2 centers. CALIPER-revised CPI was a significant risk factor towards lung transplant (LTx)-free survival, with enhanced hazard ratio (5.68) compared to the original CPI (5.36). Accuracy of LTx-free survival was substantially improved with CALIPER-revised CPI (area under the curve [AUC] 0.75 vs. 0.66), with much better specificity (83% vs. 55%). Six-month changes of CALIPER-revised CPI predicted survival significantly (AUC 0.65). CALIPER-revised CPI is a better predictor of LTx-free survival in patients with IPF. Since CALIPER technology is not available to all centers, this simple and easy to obtain tool may be used to guide management decisions in IPF. [ABSTRACT FROM AUTHOR]

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Background and objective: This study aimed to investigate whether quantitative lung vessel morphology determined by a new fully automated algorithm is associated with functional indices in idiopathic pulmonary fibrosis (IPF). Methods: A total of 152 IPF patients had vessel volume, density, tortuosity and heterogeneity quantified from computed tomography (CT) images by a fully automated algorithm. Separate quantitation of vessel metrics in pulmonary arteries and veins was performed in 106 patients. Results were evaluated against readouts from lung function tests. Results: Normalized vessel volume expressed as a percentage of total lung volume was moderately correlated with functional indices on univariable linear regression analysis: forced vital capacity (R2 = 0.27, P < 1 × 10−6), diffusion capacity for carbon monoxide (DLCO; R2 = 0.12, P = 3 × 10−5), total lung capacity (TLC; R2 = 0.45, P < 1 × 10−6) and composite physiologic index (CPI; R2 = 0.28, P < 1 × 10−6). Normalized vessel volume was correlated with vessel density but not with vessel heterogeneity. Quantitatively derived vessel metrics (and artery and vein subdivision scores) were not significantly linked with the transfer factor for carbon monoxide (KCO), and only weakly with DLCO. On multivariable linear regression analysis, normalized vessel volume and vessel heterogeneity were independently linked with DLCO, TLC and CPI indicating that they capture different aspects of lung damage. Artery–vein separation provided no additional information beyond that captured in the whole vasculature. Conclusion: Our study confirms previous observations of links between vessel volume and functional measures of disease severity in IPF using a new vessel quantitation tool. Additionally, the new tool shows independent linkages of normalized vessel volume and vessel heterogeneity with functional indices. Quantitative vessel metrics do not appear to reflect vasculopathic damage in IPF. [ABSTRACT FROM AUTHOR]

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care. [ABSTRACT FROM AUTHOR]

Background and objective: Combined pulmonary fibrosis and emphysema (CPFE) is characterized by preserved lung volume and slower lung function decline. However, it is unclear at what extent emphysema begins to impact respiratory physiology and prognostic characteristics in idiopathic pulmonary fibrosis (IPF). We estimated the extent of emphysema that could be used to define CPFE in IPF. Methods: The extent of emphysema was observed on high‐resolution computed tomography scans and measured by a texture‐based automated quantification system in 209 IPF patients. We analysed the impact of differences in the extent of emphysema on the annual decline rate and prognostic significance of lung function parameters. Results: The extent of emphysema was ≥5% in 53 patients (25%), ≥10% in 23 patients (11%) and ≥15% in 12 patients (6%). Patients with emphysema to an extent of ≥5% were more frequently men and ever‐smokers; they had more preserved lung volume and lower forced vital capacity (FVC) decline rates than those with no or trivial emphysema. The FVC decline rate was a significant predictor of mortality in patients with no or trivial emphysema (hazard ratio (HR): 0.933, P < 0.001) and in patients with an extent of emphysema ≥5% (HR: 0.906, P < 0.001). However, diffusing capacity of the lung for carbon monoxide (DLCO) was the most significant prognostic factor in those patients with an extent of emphysema ≥10% (HR: 0.972, P = 0.040) and ≥15% (HR: 0.942, P = 0.023). A 10% cut‐off value for the extent of emphysema created the most significant difference in the annual FVC decline rate in IPF patients. Conclusion: In IPF, emphysema to an extent of ≥10% affects both the annual decline rate and the prognostic significance of FVC. This extent could be used to define CPFE. Patients with idiopathic pulmonary fibrosis (IPF) and emphysema exceeding 10% had more preserved lung volume and lower rates of decline in forced vital capacity (FVC) than those with no or trivial emphysema. Diffusing capacity of the lung for carbon monoxide (DLCO) was the most significant prognostic factor in these patients. See relatedEditorial [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (ADC), the most common lung cancer type, is recognized increasingly as a disease spectrum. To guide individualized patient care, a non-invasive means of distinguishing indolent from aggressive ADC subtypes is needed urgently. Computer-Aided Nodule Assessment and Risk Yield (CANARY) is a novel computed tomography (CT) tool that characterizes early ADCs by detecting nine distinct CT voxel classes, representing a spectrum of lepidic to invasive growth, within an ADC. CANARY characterization has been shown to correlate with ADC histology and patient outcomes. This study evaluated the inter-observer variability of CANARY analysis. Three novice observers segmented and analyzed independently 95 biopsy-confirmed lung ADCs from Vanderbilt University Medical Center/Nashville Veterans Administration Tennessee Valley Healthcare system (VUMC/TVHS) and the Mayo Clinic (Mayo). Inter-observer variability was measured using intra-class correlation coefficient (ICC). The average ICC for all CANARY classes was 0.828 (95% CI 0.76, 0.895) for the VUMC/TVHS cohort, and 0.852 (95% CI 0.804, 0.901) for the Mayo cohort. The most invasive voxel classes had the highest ICC values. To determine whether nodule size influenced inter-observer variability, an additional cohort of 49 sub-centimeter nodules from Mayo were also segmented by three observers, with similar ICC results. Our study demonstrates that CANARY ADC classification between novice CANARY users has an acceptably low degree of variability, and supports the further development of CANARY for clinical application. [ABSTRACT FROM AUTHOR]

Purpose: Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Material and methods: Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Results: Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P<0.01. The optimism-corrected AUC for these 8 features is 0.939. Conclusions: Our novel radiomic LDCT-based approach for indeterminate screen-detected nodule characterization appears extremely promising however independent external validation is needed. [ABSTRACT FROM AUTHOR]

Objectives: To assess the performance of the "Computer-Aided Nodule Assessment and Risk Yield" (CANARY) software in the differentiation and risk assessment of histological subtypes of lung adenocarcinomas manifesting as pure ground glass nodules on computed tomography (CT).Methods: 64 surgically resected and histologically proven adenocarcinomas manifesting as pure ground-glass nodules on CT were assessed using CANARY software, which classifies voxel-densities into three risk components (low, intermediate, and high risk). Differences in risk components between histological adenocarcinoma subtypes were analysed. To determine the optimal threshold reflecting the presence of an invasive focus, sensitivity, specificity, negative predictive value, and positive predictive value were calculated.Results: 28/64 (44%) were adenocarcinomas in situ (AIS); 26/64 (41%) were minimally invasive adenocarcinomas (MIA); and 10/64 (16%) were invasive ACs (IAC). The software showed significant differences in risk components between histological subtypes (P<0.001-0.003). A relative volume of 45% or less of low-risk components was associated with histological invasiveness (specificity 100%, positive predictive value 100%).Conclusions: CANARY-based risk assessment of ACs manifesting as pure ground glass nodules on CT allows the differentiation of their histological subtypes. A threshold of 45% of low-risk components reflects invasiveness in these groups.Key Points: • CANARY-based risk assessment allows the differentiation of their histological subtypes. • 45% or less of low-risk component reflects histological invasiveness. • CANARY has potential role in suspected adenocarcinomas manifesting as pure ground-glass nodules. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the potential effects of methyl donor supplementation of pregnant animals in the presence or absence of a concomitant lactation on the methylome of the offspring. Twenty Holstein cows, 10 nulliparous (non-lactating while pregnant) and 10 multiparous (lactating while pregnant) were blocked by parity and randomly assigned to an i.m. weekly injections of a placebo (CTRL) or a solution containing methyl donors (MET). After calving, 5 calves randomly selected from each treatment (two born to non-lactating and three to lactating dams) were blood-sampled to determine their full methylome. There were more than 2,000 CpG differentially methylated between calves born to CTRL and those born to MET, and also between calves born to lactating and non-lactating dams. Most of the differences affected genes involved in immune function, cell growth regulation and differentiation, kinase activity, and ion channeling. We conclude that the coexistence of pregnancy and lactation affects the methylome of the offspring, and that supplementation of methyl donors early in gestation has also consequences on the methylome. [ABSTRACT FROM AUTHOR]

The noninvasive diagnosis of lung cancer remains a formidable challenge. Although tissue diagnosis will remain the gold standard for the foreseeable future, questions pertaining to the risks and costs associated with invasive diagnostic procedures are of prime relevance. This review addresses new modalities for improving the noninvasive evaluation of suspicious lung nodules. Ultimately, the goal is to translate early diagnosis into early treatment. We discuss how biomarkers could assist in distinguishing benign from malignant nodules and aggressive from indolent tumors. The field of biomarkers is rapidly expanding and progressing, and efforts are well underway to apply molecular diagnostics to address the shortcomings of current lung cancer diagnostic tools. [ABSTRACT FROM AUTHOR]

Thoracic computed tomography (CT) is considered the gold standard for detection lung pathology, yet its efficacy as a screening tool in regards to cost and radiation dose continues to evolve. Chest radiography (CXR) remains a useful and ubiquitous tool for detection and characterization of pulmonary pathology, but reduced sensitivity and specificity compared to CT. This prospective, blinded study compares the sensitivity of digital tomosynthesis (DTS), to that of CT and CXR for the identification and characterization of lung nodules. Ninety-five outpatients received a posteroanterior (PA) and lateral CXR, DTS, and chest CT at one care episode. The CXR and DTS studies were independently interpreted by three thoracic radiologists. The CT studies were used as the gold standard and read by a fourth thoracic radiologist. Nodules were characterized by presence, location, size, and composition. The agreement between observers and the effective radiation dose for each modality was objectively calculated. One hundred forty-five nodules of greatest diameter larger than 4 mm and 215 nodules less than 4 mm were identified by CT. DTS identified significantly more >4 mm nodules than CXR (DTS 32 % vs. CXR 17 %). CXR and DTS showed no significant difference in the ability to identify the smaller nodules or central nodules within 3 cm of the hilum. DTS outperformed CXR in identifying pleural nodules and those nodules located greater than 3 cm from the hilum. Average radiation dose for CXR, DTS, and CT were 0.10, 0.21, and 6.8 mSv, respectively. Thoracic digital tomosynthesis requires significantly less radiation dose than CT and nearly doubles the sensitivity of that of CXR for the identification of lung nodules greater than 4 mm. However, sensitivity and specificity for detection and characterization of lung nodules remains substantially less than CT. The apparent benefits over CXR, low cost, rapid acquisition, and minimal radiation dose of thoracic DTS suggest that it may be a useful procedure. Work-up of a newly diagnosed nodule will likely require CT, given its superior cross-sectional characterization. Further investigation of DTS as a diagnostic, screening, and surveillance tool is warranted. [ABSTRACT FROM AUTHOR]

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