Assessment of interobserver concordance in radiomic tools for lung nodule classification, with a focus on BRODERS and SILA.

While CT lung cancer screening reduces lung cancer-specific mortality, there are remaining challenges. Radiomic tools promiss to address these challenges, however, they are subject to interobserver variability if semi-automated segmentation techniques are used. Herein we report interobserver variability for two validated radiomic tools, BRODERS (Benign versus aggRessive nODule Evaluation using Radiomic Stratification) and CANARY (Computer-Aided Nodule Assessment and Risk Yield). We retrospectively analyzed the CT images of 95 malignant lung nodules of the adenocarcinoma spectrum using BRODERS and CANARY. Cases were identified at Mayo Clinic (n = 45) and Vanderbilt University Medical Center and Nashville/Veteran Administration Tennessee Valley Health Care System (n = 50). Three observers with different training levels (medical student, internal medicine resident and thoracic radiology fellow) each performed lung nodule segmentation. All methods were carried out in accordance with relevant guidelines and regulations. Interclass correlation coefficients (ICC) of 0.77, 0.98 and 0.97 for the average nodule volume, BRODERS cancer probability and Score Indicative of Lesion Aggression (SILA) which summarizes the distribution of the CANARY exemplars indicated good to excellent reliability, respectively. The dice similarity coefficient was 0.79 and 0.81 for the data sets from the two institutions. BRODERS and CANARY are robust radiomics tools with excellent interobserver variability. These tools are simple and reliable regardless the observer/operator's level of training.

Spirometric assessment of emphysema presence and severity as measured by quantitative CT and CT-based radiomics in COPD.

BACKGROUND: The mechanisms underlying airflow obstruction in COPD cannot be distinguished by standard spirometry. We ascertain whether mathematical modeling of airway biomechanical properties, as assessed from spirometry, could provide estimates of emphysema presence and severity, as quantified by computed tomography (CT) metrics and CT-based radiomics. METHODS: We quantified presence and severity of emphysema by standard CT metrics (VIDA) and co-registration analysis (ImbioLDA) of inspiratory-expiratory CT in 194 COPD patients who underwent pulmonary function testing. According to percentages of low attenuation area below - 950 Hounsfield Units (%LAA-950insp) patients were classified as having no emphysema (NE) with %LAA-950insp < 6, moderate emphysema (ME) with %LAA-950insp ≥ 6 and < 14, and severe emphysema (SE) with %LAA-950insp ≥ 14. We also obtained stratified clusters of emphysema CT features by an automated unsupervised radiomics approach (CALIPER). An emphysema severity index (ESI), derived from mathematical modeling of the maximum expiratory flow-volume curve descending limb, was compared with pulmonary function data and the three CT classifications of emphysema presence and severity as derived from CT metrics and radiomics. RESULTS: ESI mean values and pulmonary function data differed significantly in the subgroups with different emphysema degree classified by VIDA, ImbioLDA and CALIPER (p < 0.001 by ANOVA). ESI differentiated NE from ME/SE CT-classified patients (sensitivity 0.80, specificity 0.85, AUC 0.86) and SE from ME CT-classified patients (sensitivity 0.82, specificity 0.87, AUC 0.88). CONCLUSIONS: Presence and severity of emphysema in patients with COPD, as quantified by CT metrics and radiomics can be estimated by mathematical modeling of airway function as derived from standard spirometry.

Assessment of Interstitial Lung Disease Using Lung Ultrasound Surface Wave Elastography: A Novel Technique With Clinicoradiologic Correlates.

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.

Assessing the inter-observer variability of Computer-Aided Nodule Assessment and Risk Yield (CANARY) to characterize lung adenocarcinomas.

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.

Computer-Aided Nodule Assessment and Risk Yield (CANARY) may facilitate non-invasive prediction of EGFR mutation status in lung adenocarcinomas.

Computer-Aided Nodule Assessment and Risk Yield (CANARY) is quantitative imaging analysis software that predicts the histopathological classification and post-treatment disease-free survival of patients with adenocarcinoma of the lung. CANARY characterizes nodules by the distribution of nine color-coded texture-based exemplars. We hypothesize that quantitative computed tomography (CT) analysis of the tumor and tumor-free surrounding lung facilitates non-invasive identification of clinically-relevant mutations in lung adenocarcinoma. Comprehensive analysis of targetable mutations (50-gene-panel) and CANARY analysis of the preoperative (≤3 months) high resolution CT (HRCT) was performed for 118 pulmonary nodules of the adenocarcinoma spectrum surgically resected between 2006-2010. Logistic regression with stepwise variable selection was used to determine predictors of mutations. We identified 140 mutations in 106 of 118 nodules. TP53 (n = 48), KRAS (n = 47) and EGFR (n = 15) were the most prevalent. The combination of Y (Yellow) and G (Green) exemplars, fibrosis within the surrounding lung and smoking status were the best discriminators for an EGFR mutation (AUC 0.77 and 0.87, respectively). None of the EGFR mutants expressing TP53 (n = 5) had a good prognosis based on CANARY features. No quantitative features were significantly associated with KRAS mutations. Our exploratory analysis indicates that quantitative CT analysis of a nodule and surrounding lung may noninvasively predict the presence of EGFR mutations in pulmonary nodules of the adenocarcinoma spectrum.

Novel Assessment of Interstitial Lung Disease Using the "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) Software System in Idiopathic Inflammatory Myopathies.

PURPOSE: To evaluate the correlation between measurements from quantitative thoracic high-resolution CT (HRCT) analysis with "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) software and measurements from pulmonary function tests (PFTs) in patients with idiopathic inflammatory myopathies (IIM)-associated interstitial lung disease (ILD). METHODS: A cohort of patients with IIM-associated ILD seen at Mayo Clinic was identified from medical record review. Retrospective analysis of HRCT data and PFTs at baseline and 1 year was performed. The abnormalities in HRCT were quantified using CALIPER software. RESULTS: A total of 110 patients were identified. At baseline, total interstitial abnormalities as measured by CALIPER, both by absolute volume and by percentage of total lung volume, had a significant negative correlation with diffusing capacity for carbon monoxide (DLCO), total lung capacity (TLC), and oxygen saturation. Analysis by subtype of interstitial abnormality revealed significant negative correlations between ground glass opacities (GGO) and reticular density (RD) with DLCO and TLC. At one year, changes of total interstitial abnormalities compared with baseline had a significant negative correlation with changes of TLC and oxygen saturation. A negative correlation between changes of total interstitial abnormalities and DLCO was also observed, but it was not statistically significant. Analysis by subtype of interstitial abnormality revealed negative correlations between changes of GGO and RD and changes of DLCO, TLC, and oxygen saturation, but most of the correlations did not achieve statistical significance. CONCLUSION: CALIPER measurements correlate well with functional measurements in patients with IIM-associated ILD.

Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma: The Future of Imaging?

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.

Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield (CANARY)--a pilot study.

INTRODUCTION: Pulmonary nodules of the adenocarcinoma spectrum are characterized by distinctive morphological and radiologic features and variable prognosis. Noninvasive high-resolution computed tomography-based risk stratification tools are needed to individualize their management. METHODS: Radiologic measurements of histopathologic tissue invasion were developed in a training set of 54 pulmonary nodules of the adenocarcinoma spectrum and validated in 86 consecutively resected nodules. Nodules were isolated and characterized by computer-aided analysis, and data were analyzed by Spearman correlation, sensitivity, and specificity and the positive and negative predictive values. RESULTS: Computer-aided nodule assessment and risk yield (CANARY) can noninvasively characterize pulmonary nodules of the adenocarcinoma spectrum. Unsupervised clustering analysis of high-resolution computed tomography data identified nine unique exemplars representing the basic radiologic building blocks of these lesions. The exemplar distribution within each nodule correlated well with the proportion of histologic tissue invasion, Spearman R = 0.87, p < 0.0001 and 0.89 and p < 0.0001 for the training and the validation set, respectively. Clustering of the exemplars in three-dimensional space corresponding to tissue invasion and lepidic growth was used to develop a CANARY decision algorithm that successfully categorized these pulmonary nodules as "aggressive" (invasive adenocarcinoma) or "indolent" (adenocarcinoma in situ and minimally invasive adenocarcinoma). Sensitivity, specificity, positive predictive value, and negative predictive value of this approach for the detection of aggressive lesions were 95.4, 96.8, 95.4, and 96.8%, respectively, in the training set and 98.7, 63.6, 94.9, and 87.5%, respectively, in the validation set. CONCLUSION: CANARY represents a promising tool to noninvasively risk stratify pulmonary nodules of the adenocarcinoma spectrum.

Inverse probability weighting to control for censoring in a post hoc analysis of quality-adjusted survival data from a clinical trial of temsirolimus for renal cell carcinoma.

OBJECTIVE: This post hoc analysis evaluated treatment-associated quality-adjusted survival (QAS) in patients randomly assigned to temsirolimus or interferon alfa (IFN-alfa), corrected for censoring using inverse probability weighting (IPW), in the Advanced Renal Cell Carcinoma (ARCC) trial. METHODS: Follow-up was divided into 11 time intervals; Kaplan-Meier estimates for not being censored were estimated for each interval. The QAS for each interval was weighted by the inverse probability of not being censored in that interval. Overall treatment-associated QAS was calculated as the sum of the weighted QAS across all follow-up intervals. Differences in mean QAS between temsirolimus and IFN-alfa were evaluated with t-statistics at a two-sided α = 0.05. RESULTS: In total, 416 patients were randomly assigned to temsirolimus (n = 209) or IFN-alfa (n = 207); 400 patients were included in this analysis. Overall weighted mean (standard deviation) QAS during progression-free survival was 111.9 (5.3) days with temsirolimus (n = 204) and 75.7 (6.3) days with IFN-alfa (n = 196). The mean weighted QAS difference of 36.2 days in favor of temsirolimus was significant (p < 0.05). LIMITATIONS: One potential limitation is that the weights developed by the Kaplan-Meier estimates did not allow for covariates to be adjusted among treatment arms. Another possible limitation is that the ARCC trial included patients with advanced renal cell carcinoma, and thus it cannot be conclusively determined how our findings would apply to patients with less advanced disease. CONCLUSIONS: Patients with poor-prognosis advanced renal cell carcinoma treated with temsirolimus had an incremental gain of 48% (36.2 days) in QAS compared with patients treated with IFN-alfa.

Comparative survival and cost of antifungal therapy: posaconazole versus standard antifungals in the treatment of refractory invasive aspergillosis.

BACKGROUND: Refractory invasive aspergillosis (IA) is a life-threatening condition. Cost of treatment, although secondary, is important if newer drugs are to be widely accepted. Posaconazole has been shown to have activity against aspergillosis. METHODS: Analyses were conducted to compare the effectiveness and cost of posaconazole 800 mg/day with those of standard antifungal therapy, using Walsh et al. 2007 data. All-cause mortality and total drug costs were analyzed for three patient groups: All Refractory, Refractory Non-neutropenic, and Refractory Neutropenic IA Patients. Comparative survival analysis using Kaplan-Meier estimates after censoring data at 28, 42, 84, 182, and 365 days and Cox proportional hazard method was used to estimate hazard rates after controlling for difference in baseline neutropenia. For cost analysis, only antifungal drug acquisition cost was used. RESULTS: Significantly more of the 94 patients treated with posaconazole remained alive at every time point compared with the 68 external control patients within the All Refractory group (p = 0.0001). Similar results were obtained for the other two groups. For the posaconazole-treated patients mean total drug costs were $11846 (±$12406), $12642 (±$11811), and $8903 (±$14345), and for the external controls total drug costs were $35537 (±$73059), $48097 (±$88702), and $13556 (±$16324) for the All Refractory, Refractory Non-neutropenic, and Neutropenic IA groups, respectively. Key limitations of the study included noninclusion of hospitalization or other drug costs, low patient numbers beyond 84 days, and the fact that the Walsh et al. 2007 study was completed before other newer antifungal agents (such as voriconazole and caspofungin) were available. CONCLUSIONS: Posaconazole appears to confer a survival benefit and reduced total drug cost compared with standard antifungal therapy, such as amphotericin B (lipid and nonlipid formulations), itraconazole, or both, to treat patients with probable or proven refractory IA.

Enhancing profitability of dry mill ethanol plants: process modeling and economics of conversion of degermed defibered corn to ethanol.

An Aspen Plus modeling platform was developed to evaluate the performance of the conversion process of degermed defibered corn (DDC) to ethanol in 15- and 40-million gallons per year (MGPY) dry mill ethanol plants. Upstream corn milling equipment in conventional dry mill ethanol plants was replaced with germ and fiber separation equipment. DDC with higher starch content was fed to the existing saccharification and fermentation units, resulting in higher ethanol productivity than with regular corn. The results of the DDC models were compared with those of conventional dry mill ethanol process models. A simple financial analysis that included capital and operating costs, revenues, earnings, and return on investment was created to evaluate each model comparatively. Case studies were performed on 15- and 40-MGPY base case models with two DDC process designs and DDC with a mechanical oil extraction process.