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Purpose The ACR developed the Lung CT Screening Reporting and Data System (Lung-RADS) to standardize the diagnostic follow-up of suspicious screening findings. A retrospective analysis showed that Lung-RADS would have reduced the false-positive rate in the National Lung Screening Trial, but the optimal timing of follow-up examinations has not been established. In this study, we assess the effectiveness of alternative diagnostic follow-up intervals on lung cancer screening. Methods We used the Lung Cancer Outcome Simulator to estimate population-level outcomes of alternative diagnostic follow-up intervals for Lung-RADS categories 3 and 4A. The Lung Cancer Outcome Simulator is a microsimulation model developed within the Cancer Intervention and Surveillance Modeling Network Consortium to evaluate outcomes of national screening guidelines. Here, among the evaluated outcomes are percentage of mortality reduction, screens performed, lung cancer deaths averted, screen-detected cases, and average number of screens and follow-ups per death averted. Results The recommended 3-month follow-up interval for Lung-RADS category 4A is optimal. However, for Lung-RADS category 3, a 5-month, instead of the recommended 6-month, follow-up interval yielded a higher mortality reduction (0.08% for men versus 0.05% for women), and a higher number of deaths averted (36 versus 27), a higher number of screen-detected cases (13 versus 7), and a lower number of combined low-dose CTs and diagnostic follow-ups per death avoided (8 versus 5), per one million general population. Sensitivity analysis of nodule progression threshold verifies a higher mortality reduction with a 1-month earlier follow-up for Lung-RADS 3. Conclusions One-month earlier diagnostic follow-ups for individuals with Lung-RADS category 3 nodules may result in a higher mortality reduction and warrants further investigation.

Introduction Brain metastasis (BM) is one of the most common metastases from primary lung cancer (PLC). Recently, the National Lung Screening Trial revealed the efficacy of low-dose computed tomography (LDCT) screening on LC mortality reduction. Nevertheless, it remains unknown if early detection of PLC through LDCT may be potentially beneficial in reducing the risk of subsequent metastases. Our study aimed to investigate the impact of LDCT screening for PLC on the risk of developing BM after PLC diagnosis. Methods We used the National Lung Screening Trial data to identify 1502 participants who were diagnosed with PLC in 2002 to 2009 and have follow-up data for BM. Cause-specific competing risk regression was applied to evaluate an association between BM risk and the mode of PLC detection—that is, LDCT screen-detected versus non-LDCT screen-detected. Subgroup analyses were conducted in patients with early stage PLC and those who underwent surgery for PLC. Results Of 1502 participants, 41.4% had PLC detected through LDCT screening versus 58.6% detected through other methods, for example, chest radiograph or incidental detection. Patients whose PLC was detected with LDCT screening had a significantly lower 3-year incidence of BM (6.5%) versus those without (11.9%), with a cause-specific hazard ratio (HR) of 0.53 (p = 0.001), adjusting for age at PLC diagnosis, PLC stage, PLC histology, and smoking status. This significant reduction in BM risk among PLCs detected through LDCT screening persisted in subgroups of participants with early stage PLC (HR = 0.47, p = 0.002) and those who underwent surgery (HR = 0.37, p = 0.001). Conclusions Early detection of PLC using LDCT screening is associated with lower risk of BM after PLC diagnosis on the basis of a large population-based study.

BACKGROUND Current lung cancer risk-based screening approaches use a single risk-threshold, disregard life-expectancy, and ignore past screening findings. We address these limitations with a comprehensive analytical framework, the individualized lung cancer screening decision (ENGAGE) tool that aims to optimize lung cancer screening for US ever-smokers under dynamic risk assessment by incorporating life expectancy and past screening findings over time. METHODS ENGAGE employs a partially observable Markov decision process framework that integrates published risk prediction and disease progression models, to dynamically assess the trade-off between the expected health benefits and harms associated with screening. ENGAGE evaluates lung cancer risk annually and provides real-time screening eligibility that maximizes the expected quality-adjusted life-years (QALYs) of ever-smokers. We compare ENGAGE against the 2013 U.S. Preventive Services Task Force (USPSTF) lung cancer screening guideline and single-threshold risk-based screening paradigms. RESULTS Compared with the 2013 USPSTF guidelines, ENGAGE expands screening coverage among ever-smokers (ENGAGE: 78%, USPSTF: 61%), while reducing the number of screening examinations per person (ENGAGE:10.43, USPSTF:12.07, P

Background To conserve personal protective equipment (PPE) and reduce exposure to potentially infected COVID‐19 patients, several Californian facilities independently implemented a method of acquiring portable chest radiographs through glass barriers that was originally developed by the University of Washington. Methods This work quantifies the transmission of radiation through a glass barrier using six radiographic systems at five facilities. Patient entrance air kerma (EAK) and effective dose were estimated both with and without the glass barrier. Beam penetrability and resulting exposure index (EI) and deviation index (DI) were measured and used to adjust the tube current‐time product (mAs) for glass barriers. Because of beam hardening, the contrast‐to‐noise ratio (CNR) was measured with image quality phantoms to ensure diagnostic integrity. Finally, scatter surveys were performed to assess staff radiation exposure both inside and outside the exam room. Results The glass barriers attenuated a mean of 61% of the normal X‐ray beams. When the mAs was increased to match EI values, there was no discernible degradation of image quality as determined by the CNR. This was corroborated with subjective assessments of image quality by chest radiologists. The glass‐hardened beams acted as a filter for low energy X‐rays, and some facilities observed slight changes in patient effective doses. There was scattering from both the phantoms and the glass barriers within the room. Conclusions Glass barriers require an approximate 2.5 times increase in beam intensity, with all other technique factors held constant. Further refinements are necessary for increased source‐to‐image distance and beam quality in order to adequately match EI values. This does not result in a significant increase in the radiation dose delivered to the patient. The use of lead aprons, mobile shields, and increased distance from scattering sources should be employed where practicable in order to keep staff radiation doses as low as reasonably achievable.

BACKGROUND Toxoplasmosis in hematopoietic stem-cell transplant (HSCT) recipients can be life threatening if not promptly diagnosed and treated. METHODS We performed a systematic review (PubMed last search March 29, 2020) of toxoplasmosis among HSCT recipients and calculated the toxoplasmosis prevalence across studies. We also created a compilation list of brain imaging, chest imaging, and autopsy findings of toxoplasmosis among HSCT recipients. RESULTS We identified 46 eligible studies (47 datasets) with 399 toxoplasmosis cases among 38 751 HSCT recipients. There was large heterogeneity in the reported toxoplasmosis prevalence across studies, thus formal meta-analysis was not attempted. The median toxoplasmosis prevalence among 38 751 HSCT recipients was 2.14% (range 0%-66.67%). Data on toxoplasmosis among at-risk R+HSCT recipients were more limited (25 studies; 2404 R+HSCT recipients [6.2% of all HSCT recipients]), although the median number of R+HSCT recipients was 56.79% across all HSCT recipients. The median toxoplasmosis prevalence across studies among 2404 R+HSCT was 7.51% (range 0%-80%) versus 0% (range 0%-1.23%) among 7438 R-HSCT. There were limited data to allow meaningful analyses of toxoplasmosis prevalence according to prophylaxis status of R+HSCT recipients. CONCLUSIONS Toxoplasmosis prevalence among HSCT recipients is underestimated. The majority of studies report toxoplasmosis prevalence among all HSCT recipients rather than only among the at-risk R+HSCT recipients. In fact, the median toxoplasmosis prevalence among all R+//R- HSCT recipients is 3.5-fold lower compared with the prevalence among only the at-risk R+HSCT recipients and the median prevalence among R+HSCT recipients is 7.51-fold higher than among R-HSCT recipients. The imaging findings of toxoplasmosis among HSCT recipients can be atypical. High index of suspicion is needed in R+HSCT recipients with fever, pneumonia, or encephalitis.

With more than 900,000 confirmed cases worldwide and nearly 50,000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.

Lung cancer is the most common fatal malignancy in adults worldwide, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography (CT) is routinely used in clinical practice to determine lung cancer treatment and assess prognosis. Here, we developed LungNet, a shallow convolutional neural network for predicting outcomes of NSCLC patients. We trained and evaluated LungNet on four independent cohorts of NSCLC patients from four medical centers: Stanford Hospital (n = 129), H. Lee Moffitt Cancer Center and Research Institute (n = 185), MAASTRO Clinic (n = 311) and Charite - Universitatsmedizin (n=84). We show that outcomes from LungNet are predictive of overall survival in all four independent survival cohorts as measured by concordance indices of 0.62, 0.62, 0.62 and 0.58 on cohorts 1, 2, 3, and 4, respectively. Further, the survival model can be used, via transfer learning, for classifying benign vs malignant nodules on the Lung Image Database Consortium (n = 1010), with improved performance (AUC=0.85) versus training from scratch (AUC=0.82). LungNet can be used as a noninvasive predictor for prognosis in NSCLC patients and can facilitate interpretation of CT images for lung cancer stratification and prognostication.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

Background The Lung Computed Tomography Screening Reporting and Data System (Lung-RADS) reduces the false-positive rate of lung cancer screening but introduces prolonged periods of uncertainty for indeterminate findings. We assess the cost-effectiveness of a screening program that assesses indeterminate findings earlier via a hypothetical diagnostic biomarker introduced in place of Lung-RADS 3 and 4A guidelines. Methods We evaluated the performance of the US Preventive Services Task Force (USPSTF) recommendations on lung cancer screening with and without a hypothetical noninvasive diagnostic biomarker using a validated microsimulation model. The diagnostic biomarker assesses the malignancy of indeterminate nodules, replacing Lung-RADS 3 and 4A guidelines, and is characterized by a varying sensitivity profile that depends on nodules' size, specificity, and cost. We tested the robustness of our findings through univariate sensitivity analyses. Results A lung cancer screening program per the USPSTF guidelines that incorporates a diagnostic biomarker with at least medium sensitivity profile and 90% specificity, that costs $250 or less, is cost-effective with an incremental cost-effectiveness ratio lower than $100 000 per quality-adjusted life year, and improves lung cancer-specific mortality reduction while requiring fewer screening exams than the USPSTF guidelines with Lung-RADS. A screening program with a biomarker costing $750 or more is not cost-effective. The health benefits accrued and costs associated with the screening program are sensitive to the disutility of indeterminate findings and specificity of the biomarker, respectively. Conclusions Lung cancer screening that incorporates a diagnostic biomarker, in place of Lung-RADS 3 and 4A guidelines, could improve the cost-effectiveness of the screening program and warrants further investigation.

We describe a 40-year-old man with severe COVID-19 requiring mechanical ventilation who developed aorto-bi-iliac arterial, right lower extremity arterial, intracardiac, pulmonary arterial and ilio-caval venous thromboses and required right lower extremity amputation for acute limb ischemia. This unique case illustrates COVID-19-associated thrombotic complications occurring at multiple, different sites in the cardiovascular system of a single infected patient., Highlights • COVID-19 related thrombosis may have various cardiovascular manifestations in the same patient. • Imaging has an important role in detection of COVID-19 related complications. • Knowledge of imaging and increased thromboembolism risk can lead to early detection and treatment.

Purpose Computed tomography (CT) findings of bronchiolitis obliterans syndrome (BOS) can be nonspecific and variable. This study aims to measure the incremental value of automated quantitative lung CT analysis to clinical CT interpretation. A head-to-head comparison of quantitative CT lung density analysis by parametric response mapping (PRM) with qualitative radiologist performance in BOS diagnosis was performed. Materials and methods Inspiratory and end-expiratory CTs of 65 patients referred to a post-bone marrow transplant lung graft-versus-host-disease clinic were reviewed by 3 thoracic radiologists for the presence of mosaic attenuation, centrilobular opacities, airways dilation, and bronchial wall thickening. Radiologists' majority consensus diagnosis of BOS was compared with automated PRM air trapping quantification and to the gold-standard diagnosis of BOS as per National Institutes of Health (NIH) consensus criteria. Results Using a previously established threshold of 28% air trapping on PRM, the diagnostic performance for BOS was as follows: sensitivity 56% and specificity 94% (area under the receiver operator curve [AUC]=0.75). Radiologist review of inspiratory CT images alone resulted in a sensitivity of 80% and a specificity of 69% (AUC=0.74). When radiologists assessed both inspiratory and end-expiratory CT images in combination, the sensitivity was 92% and the specificity was 59% (AUC=0.75). The highest performance was observed when the quantitative PRM report was reviewed alongside inspiratory and end-expiratory CT images, with a sensitivity of 92% and a specificity of 73% (AUC=0.83). Conclusions In the CT diagnosis of BOS, qualitative expert radiologist interpretation was noninferior to quantitative PRM. The highest level of diagnostic performance was achieved by the combination of quantitative PRM measurements with qualitative image feature assessments.

The ACR Incidental Findings Committee presents recommendations for managing incidentally detected lung findings on thoracic CT. The Chest Subcommittee is composed of thoracic radiologists who endorsed and developed the provided guidance. These recommendations represent a combination of current published evidence and expert opinion and were finalized by informal iterative consensus. The recommendations address commonly encountered incidental findings in the lungs and are not intended to be a comprehensive review of all pulmonary incidental findings. The goal is to improve the quality of care by providing guidance on management of incidentally detected thoracic findings.

Toxoplasmosis in hematopoietic stem-cell transplant (HSCT) recipients can be life threatening if not promptly diagnosed and treated.We performed a systematic review (PubMed last search March 29, 2020) of toxoplasmosis among HSCT recipients and calculated the toxoplasmosis prevalence across studies. We also created a compilation list of brain imaging, chest imaging, and autopsy findings of toxoplasmosis among HSCT recipients.We identified 46 eligible studies (47 datasets) with 399 toxoplasmosis cases among 38 751 HSCT recipients. There was large heterogeneity in the reported toxoplasmosis prevalence across studies, thus formal meta-analysis was not attempted. The median toxoplasmosis prevalence among 38 751 HSCT recipients was 2.14% (range 0%-66.67%). Data on toxoplasmosis among at-risk R+HSCT recipients were more limited (25 studies; 2404 R+HSCT recipients [6.2% of all HSCT recipients]), although the median number of R+HSCT recipients was 56.79% across all HSCT recipients. The median toxoplasmosis prevalence across studies among 2404 R+HSCT was 7.51% (range 0%-80%) versus 0% (range 0%-1.23%) among 7438 R-HSCT. There were limited data to allow meaningful analyses of toxoplasmosis prevalence according to prophylaxis status of R+HSCT recipients.Toxoplasmosis prevalence among HSCT recipients is underestimated. The majority of studies report toxoplasmosis prevalence among all HSCT recipients rather than only among the at-risk R+HSCT recipients. In fact, the median toxoplasmosis prevalence among all R+//R- HSCT recipients is 3.5-fold lower compared with the prevalence among only the at-risk R+HSCT recipients and the median prevalence among R+HSCT recipients is 7.51-fold higher than among R-HSCT recipients. The imaging findings of toxoplasmosis among HSCT recipients can be atypical. High index of suspicion is needed in R+HSCT recipients with fever, pneumonia, or encephalitis.

Background With advancing therapeutics, lung cancer (LC) survivors are rapidly increasing in number. Although mounting evidence suggests LC survivors have high risk of second primary lung cancer (SPLC), there is no validated prediction model available for clinical use to identify high-risk LC survivors for SPLC. Methods Using data from 6325 ever-smokers in the Multiethnic Cohort (MEC) study diagnosed with initial primary lung cancer (IPLC) in 1993-2017, we developed a prediction model for 10-year SPLC risk after IPLC diagnosis using cause-specific Cox regression. We evaluated the model’s clinical utility using decision curve analysis and externally validated it using 2 population-based data—Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST)—that included 2963 and 2844 IPLC (101 and 93 SPLC cases), respectively. Results Over 14 063 person-years, 145 (2.3%) ever-smoking IPLC patients developed SPLC in MEC. Our prediction model demonstrated a high predictive accuracy (Brier score = 2.9, 95% confidence interval [CI] = 2.4 to 3.3) and discrimination (area under the receiver operating characteristics [AUC] = 81.9%, 95% CI = 78.2% to 85.5%) based on bootstrap validation in MEC. Stratification by the estimated risk quartiles showed that the observed SPLC incidence was statistically significantly higher in the 4th vs 1st quartile (9.5% vs 0.2%; P Conclusions We developed and validated a SPLC prediction model based on large population-based cohorts. The proposed prediction model can help identify high-risk LC patients for SPLC and can be incorporated into clinical decision making for SPLC surveillance and screening.

Contains fulltext : 220721.pdf (Publisher’s version ) (Closed access) With more than 900 000 confirmed cases worldwide and nearly 50 000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.

Purpose To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non-small cell lung cancer (NSCLC). Materials and Methods A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics. Next, total RNA was extracted from the tissue and analyzed with RNA sequencing technology. Ten highly coexpressed gene clusters, termed metagenes, were identified, validated in publicly available gene-expression cohorts, and correlated with prognosis. Next, a radiogenomics map was built that linked semantic image features to metagenes by using the t statistic and the Spearman correlation metric with multiple testing correction. Results RNA sequencing analysis resulted in 10 metagenes that capture a variety of molecular pathways, including the epidermal growth factor (EGF) pathway. A radiogenomic map was created with 32 statistically significant correlations between semantic image features and metagenes. For example, nodule attenuation and margins are associated with the late cell-cycle genes, and a metagene that represents the EGF pathway was significantly correlated with the presence of ground-glass opacity and irregular nodules or nodules with poorly defined margins. Conclusion Radiogenomic analysis of NSCLC showed multiple associations between semantic image features and metagenes that represented canonical molecular pathways, and it can result in noninvasive identification of molecular properties of NSCLC. Online supplemental material is available for this article.

Background While lepidic-predominant lung adenocarcinomas are known to have better outcomes than similarly sized solid tumors, the impact of smaller noninvasive foci within predominantly solid tumors is less clearly characterized. We tested the hypothesis that lung adenocarcinomas with even a small ground-glass opacity (GGO) component have a better prognosis than otherwise similar pure solid (PS) adenocarcinomas. Patients and Methods The maximum total and solid-component diameters were determined by preoperative computed tomography in patients who underwent lobar or sublobar resection of clinical N0 adenocarcinomas without induction therapy between May 2003 and August 2013. Survival between patients with PS tumors (0% GGO) or tumors with a minor ground-glass (MGG) component (1%-25% GGO) was compared by Kaplan-Meier and Cox analyses. Results A total of 123 patients met the inclusion criteria, comprising 54 PS (44%) and 69 MGG (56%) whose mean ground-glass component was 18 ± 7%. The solid component tumor diameter was not significantly different between the groups (2.3 ± 1.2 cm vs. 2.5 ± 1.3 cm, P = .2). Upstaging to pN1-2 was more common for the PS group (13% [7/54] vs. 3% [2/69], P = .04), but the distribution of pathologic stage was not significantly different between the groups (PS 76% stage I [41/54] vs. MGG 80% stage I [55/69], P = .1). Having a MGG component was associated with markedly better survival in both univariate analysis (MGG 5-year overall survival 86.7% vs. PS 64.5%, P = .001) and multivariable survival analysis (hazard ratio, 0.30, P = .01). Conclusion Patients with resected cN0 lung adenocarcinoma who have even a small GGO component have markedly better survival than patients with PS tumors, which may have implications for both treatment and surveillance strategies.

Low dose CT (LDCT) for lung cancer screening is an evidence-based, guideline recommended, and Medicare approved test but uptake requires further study. We therefore conducted patient and provider surveys to elucidate factors associated with utilization. Patients referred for LDCT at an academic medical center were questioned about their attitudes, knowledge, and beliefs on lung cancer screening. Adherent patients were defined as those who met screening eligibility criteria and completed a LDCT. Referring primary care providers within this same medical system were surveyed in parallel about their practice patterns, attitudes, knowledge and beliefs about screening. Eighty patients responded (36%), 48 of whom were adherent. Among responders, non-Hispanic patients (p = 0.04) were more adherent. Adherent respondents believed that CT technology is accurate and early detection is useful, and they trusted their providers. A majority of non-adherent patients (79%) self-reported an intention to obtain a LDCT in the future. Of 36 of 87 (41%) responding providers, only 31% knew the correct lung cancer screening eligibility criteria, which led to a 37% inappropriate referral rate from 2013 to 2015. Yet, 75% had initiated lung cancer screening discussions, 64% thought screening was at least moderately effective, and 82% were interested in learning more of the 33 providers responding to these questions. Overall, patients were motivated and providers engaged to screen for lung cancer by LDCT. Non-adherent patient “procrastinators” were motivated to undergo screening in the future. Additional follow through on non-adherence may enhance screening uptake, and raising awareness for screening eligibility through provider education may reduce inappropriate referrals., Highlights • Lung cancer screening was viewed favorably by patients at our medical center. • Non-Hispanic patients were more likely to adhere to a prescribed screening test. • Eligible, non-adherent, patients were still interested in screening. • Providers were motivated to screen but under-informed on patient eligibility. • Providers were open to additional education on lung cancer screening.

// Ryogo Minamimoto 1 , Mehran Jamali 1 , Olivier Gevaert 1 , Sebastian Echegaray 1 , Amanda Khuong 2 , Chuong D. Hoang 2 , Joseph B. Shrager 2 , Sylvia K. Plevritis 1 , Daniel L. Rubin 1 , Ann N. Leung 1 , Sandy Napel 1 and Andrew Quon 1 1 Department of Radiology, Stanford University, Stanford, CA, USA 2 Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA Correspondence to: Andrew Quon, email: aquon@stanford.edu Keywords: 18 FDG-PET/CT, heterogeneity, KRAS gene mutation, EGFR gene mutation, NSCLC Received: September 16, 2016 Accepted: March 20, 2017 Published: May 10, 2017 ABSTRACT This study investigated the relationship between epidermal growth factor receptor ( EGFR ) and Kirsten rat sarcoma viral oncogene homolog ( KRAS ) mutations in non-small-cell lung cancer (NSCLC) and quantitative FDG-PET/CT parameters including tumor heterogeneity. 131 patients with NSCLC underwent staging FDG-PET/CT followed by tumor resection and histopathological analysis that included testing for the EGFR and KRAS gene mutations. Patient and lesion characteristics, including smoking habits and FDG uptake parameters, were correlated to each gene mutation. Never-smoker ( P < 0.001) or low pack-year smoking history ( p = 0.002) and female gender ( p = 0.047) were predictive factors for the presence of the EGFR mutations. Being a current or former smoker was a predictive factor for the KRAS mutations ( p = 0.018). The maximum standardized uptake value (SUV max ) of FDG uptake in lung lesions was a predictive factor of the EGFR mutations ( p = 0.029), while metabolic tumor volume and total lesion glycolysis were not predictive. Amongst several tumor heterogeneity metrics included in our analysis, inverse coefficient of variation (1/COV) was a predictive factor ( p < 0.02) of EGFR mutations status, independent of metabolic tumor diameter. Multivariate analysis showed that being a never-smoker was the most significant factor ( p < 0.001) for the EGFR mutations in lung cancer overall. The tumor heterogeneity metric 1/COV and SUV max were both predictive for the EGFR mutations in NSCLC in a univariate analysis. Overall, smoking status was the most significant factor for the presence of the EGFR and KRAS mutations in lung cancer.

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called “digital biopsy,” that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non–small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of 0.7, comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs &gt, 0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required.

BACKGROUND: Primary tumor maximum standardized uptake value is a prognostic marker for non–small cell lung cancer. In the setting of malignancy, bone marrow activity from fluorine 18–fluorodeoxyglucose (FDG) PET may be informative for clinical risk stratification. PURPOSE: To determine whether integrating FDG PET radiomic features of the primary tumor, tumor penumbra, and bone marrow identifies lung cancer disease-free survival more accurately than clinical features alone. MATERIALS AND METHODS: Patients were retrospectively analyzed from two distinct cohorts collected between 2008 and 2016. Each tumor, its surrounding penumbra, and bone marrow from the L3–L5 vertebral bodies was contoured on pretreatment FDG PET/CT images. There were 156 bone marrow and 512 tumor and penumbra radiomic features computed from the PET series. Randomized sparse Cox regression by least absolute shrinkage and selection operator identified features that predicted disease-free survival in the training cohort. Cox proportional hazards models were built and locked in the training cohort, then evaluated in an independent cohort for temporal validation. RESULTS: There were 227 patients analyzed; 136 for training (mean age, 69 years ± 9 [standard deviation]; 101 men) and 91 for temporal validation (mean age, 72 years ± 10; 91 men). The top clinical model included stage; adding tumor region features alone improved outcome prediction (log likelihood, −158 vs −152; P = .007). Adding bone marrow features continued to improve performance (log likelihood, −158 vs −145; P = .001). The top model integrated stage, two bone marrow texture features, one tumor with penumbra texture feature, and two penumbra texture features (concordance, 0.78; 95% confidence interval: 0.70, 0.85; P < .001). This fully integrated model was a predictor of poor outcome in the independent cohort (concordance, 0.72; 95% confidence interval: 0.64, 0.80; P < .001) and a binary score stratified patients into high and low risk of poor outcome (P < .001). CONCLUSION: A model that includes pretreatment fluorine 18–fluorodeoxyglucose PET texture features from the primary tumor, tumor penumbra, and bone marrow predicts disease-free survival of patients with non–small cell lung cancer more accurately than clinical features alone. © RSNA, 2019 Online supplemental material is available for this article.

Background Numerous health policy organizations recommend lung cancer screening, but no consensus exists on the optimal policy. Moreover, the impact of the Lung CT screening reporting and data system guidelines to manage small pulmonary nodules of unknown significance (a.k.a. indeterminate nodules) on the cost-effectiveness of lung cancer screening is not well established. Methods We assess the cost-effectiveness of 199 screening strategies that vary in terms of age and smoking eligibility criteria, using a microsimulation model. We simulate lung cancer-related events throughout the lifetime of US-representative current and former smokers. We conduct sensitivity analyses to test key model inputs and assumptions. Results The cost-effectiveness efficiency frontier consists of both annual and biennial screening strategies. Current guidelines are not on the frontier. Assuming 4% disutility associated with indeterminate findings, biennial screening for smokers aged 50–70 years with at least 40 pack-years and less than 10 years since smoking cessation is the cost-effective strategy using $100 000 willingness-to-pay threshold yielding the highest health benefit. Among all health utilities, the cost-effectiveness of screening is most sensitive to changes in the disutility of indeterminate findings. As the disutility of indeterminate findings decreases, screening eligibility criteria become less stringent and eventually annual screening for smokers aged 50–70 years with at least 30 pack-years and less than 10 years since smoking cessation is the cost-effective strategy yielding the highest health benefit. Conclusions The disutility associated with indeterminate findings impacts the cost-effectiveness of lung cancer screening. Efforts to quantify and better understand the impact of indeterminate findings on the effectiveness and cost-effectiveness of lung cancer screening are warranted.

Career situation of first and presenting author Post-doctoral fellow. Introduction The advent of anti-IL-1/IL-6 therapies transformed the management of systemic juvenile idiopathic arthritis (sJIA), a debilitating childhood inflammatory condition. However, concurrent with practice change, pediatric rheumatologists noted an increase in sporadic cases of types of lung disease in sJIA, that were rarely seen in previous decades. Objectives The study aims to provide an up-to-date characterization of lung disease and identify novel risk factors. Methods We organized a multi-center retrospective study and obtained information on 61 cases of lung disease in children with sJIA or sJIA-like disease. Results Clinical data from our cohort showed that lung disease in the setting of sJIA is associated with distinctive features, including acute clubbing (in 61%), atypical rash (in 56%) and an unusually high frequency of serious adverse reactions to tocilizumab (40%, OR=79 compared to the control). This lung disease has unique radiological findings and lung pathology similar to pulmonary alveolar proteinosis and/or endogenous lipoid pneumonia (PAP/ELP, 64%) often with associated pulmonary vascular changes. Whole-exome sequencing on 18 patients ruled out a novel monogenic disorder or known causes of congenital PAP. Thus, the etiology of the disease is not clear, while its mortality is high (5 years survival: 42%, 25%–68%). When compared to a control cohort of children entered as sJIA in a patient registry, the lung disease cohort has similar overall anti-IL-1/IL-6 exposure level. However, in the anti-IL-1/IL-6 exposed subset, but not in the non-exposed, young sJIA onset age potently increased the risk of lung disease (age Conclusions Lung disease associated with anti-IL-1/anti-IL-6 therapies often presents as an alveolar and pulmonary vascular complication with high mortality in children with sJIA/sJIA-like disease. Risk is significantly increased in children with young age at sJIA onset or concurrent T21. In sJIA patients (including those with initial treatment response), emergence of atypical clinical features, rising ferritin and dropping absolute lymphocyte count should raise suspicion of this complication. Disclosure of Interest G. Chen: None declared, V. Saper: None declared, G. Deutsch: None declared, R. P. Guillerman: None declared, K. Jagadeesh: None declared, G. Schulert: None declared, S. Canna: None declared, Y. Lu: None declared, J. Birgmeier: None declared, A. Leung: None declared, A. Grom: None declared, G. Bejerano : None declared, M. Davis: None declared, P. Khatri: None declared, E. Mellins Grant/research support from: Novartis, GlaxoSmithKline, Codexis, Inc.

We identified computational imaging features on 18F-fluorodeoxyglucose positron emission tomography (PET) that predict recurrence/progression in non–small cell lung cancer (NSCLC). We retrospectively identified 291 patients with NSCLC from 2 prospectively acquired cohorts (training, n = 145, validation, n = 146). We contoured the metabolic tumor volume (MTV) on all pretreatment PET images and added a 3-dimensional penumbra region that extended outward 1 cm from the tumor surface. We generated 512 radiomics features, selected 435 features based on robustness to contour variations, and then applied randomized sparse regression (LASSO) to identify features that predicted time to recurrence in the training cohort. We built Cox proportional hazards models in the training cohort and independently evaluated the models in the validation cohort. Two features including stage and a MTV plus penumbra texture feature were selected by LASSO. Both features were significant univariate predictors, with stage being the best predictor (hazard ratio [HR] = 2.15 [95% confidence interval (CI): 1.56–2.95], p &lt, 0.001). However, adding the MTV plus penumbra texture feature to stage significantly improved prediction (p = 0.006). This multivariate model was a significant predictor of time to recurrence in the training cohort (concordance = 0.74 [95% CI: 0.66–0.81], p &lt, 0.001) that was validated in a separate validation cohort (concordance = 0.74 [95% CI: 0.67–0.81], p &lt, 0.001). A combined radiomics and clinical model improved NSCLC recurrence prediction. FDG PET radiomic features may be useful biomarkers for lung cancer prognosis and add clinical utility for risk stratification.

ObjectiveTo investigate the characteristics and risk factors of a novel parenchymal lung disease (LD), increasingly detected in systemic juvenile idiopathic arthritis (sJIA).MethodsIn a multicentre retrospective study, 61 cases were investigated using physician-reported clinical information and centralised analyses of radiological, pathological and genetic data.ResultsLD was associated with distinctive features, including acute erythematous clubbing and a high frequency of anaphylactic reactions to the interleukin (IL)-6 inhibitor, tocilizumab. Serum ferritin elevation and/or significant lymphopaenia preceded LD detection. The most prevalent chest CT pattern was septal thickening, involving the periphery of multiple lobes ± ground-glass opacities. The predominant pathology (23 of 36) was pulmonary alveolar proteinosis and/or endogenous lipoid pneumonia (PAP/ELP), with atypical features including regional involvement and concomitant vascular changes. Apparent severe delayed drug hypersensitivity occurred in some cases. The 5-year survival was 42%. Whole exome sequencing (20 of 61) did not identify a novel monogenic defect or likely causal PAP-related or macrophage activation syndrome (MAS)-related mutations. Trisomy 21 and young sJIA onset increased LD risk. Exposure to IL-1 and IL-6 inhibitors (46 of 61) was associated with multiple LD features. By several indicators, severity of sJIA was comparable in drug-exposed subjects and published sJIA cohorts. MAS at sJIA onset was increased in the drug-exposed, but was not associated with LD features.ConclusionsA rare, life-threatening lung disease in sJIA is defined by a constellation of unusual clinical characteristics. The pathology, a PAP/ELP variant, suggests macrophage dysfunction. Inhibitor exposure may promote LD, independent of sJIA severity, in a small subset of treated patients. Treatment/prevention strategies are needed.

Purpose To assess inter-observer variability in identifying traction bronchiectasis on computed tomography (CT) using additional criteria for chronic fibrosing interstitial pneumonia. Methods Seven experts categorized CT image set representing 39 patients into three groups on the basis of the presence of traction bronchiectasis, using a three-point scale: 3-definitely/probably yes; 2-possibly yes; and 1-definitely/probably no. This scale served as a reference standard. The image set included cases of chronic fibrosing interstitial pneumonia, non-interstitial lung disease, and difficult-to-determine cases. Forty-eight observers similarly assessed the same image set, first according to the Fleischner Society definition, and second with additional criteria, in which traction bronchiectasis was observed exclusively in chronic fibrosing interstitial pneumonia. The agreement level between the reference standard and each observer's evaluation in each session was calculated using weighted kappa values which were compared between the two sessions using a paired t test. Results The mean weighted kappa value for all observers was significantly higher in the second reading session (mean 0.75) than in the first reading session (mean 0.62) (p < 0.001). Conclusion Inter-observer agreement in identifying traction bronchiectasis improves when using the additional criteria which specify chronic fibrosing interstitial pneumonia as the underlying disease.

Pulmonary hypertension (PH) is defined by a mean pulmonary artery pressure greater than 20 mm Hg and classified into five different groups sharing similar pathophysiologic mechanisms, hemodynamic characteristics, and therapeutic management. Radiologists play a key role in the multidisciplinary assessment and management of PH. A working group was formed from within the Fleischner Society based on expertise in the imaging and/or management of patients with PH, as well as experience with methodologies of systematic reviews. The working group identified key questions focusing on the utility of CT, MRI, and nuclear medicine in the evaluation of PH: (a) Is noninvasive imaging capable of identifying PH? (b) What is the role of imaging in establishing the cause of PH? (c) How does imaging determine the severity and complications of PH? (d) How should imaging be used to assess chronic thromboembolic PH before treatment? (e) Should imaging be performed after treatment of PH? This systematic review and position paper highlights the key role of imaging in the recognition, work-up, treatment planning, and follow-up of PH. This article is a simultaneous joint publication in Radiology and European Respiratory Journal. The articles are identical except for stylistic changes in keeping with each journal's style. Either version may be used in citing this article. © 2021 RSNA and the European Respiratory Society. Online supplemental material is available for this article.

Medical image biomarkers of cancer promise improvements in patient care through advances in precision medicine. Compared to genomic biomarkers, image biomarkers provide the advantages of being non-invasive, and characterizing a heterogeneous tumor in its entirety, as opposed to limited tissue available via biopsy. We developed a unique radiogenomic dataset from a Non-Small Cell Lung Cancer (NSCLC) cohort of 211 subjects. The dataset comprises Computed Tomography (CT), Positron Emission Tomography (PET)/CT images, semantic annotations of the tumors as observed on the medical images using a controlled vocabulary, and segmentation maps of tumors in the CT scans. Imaging data are also paired with results of gene mutation analyses, gene expression microarrays and RNA sequencing data from samples of surgically excised tumor tissue, and clinical data, including survival outcomes. This dataset was created to facilitate the discovery of the underlying relationship between tumor molecular and medical image features, as well as the development and evaluation of prognostic medical image biomarkers.

Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. Early detection of lung cancer is an important opportunity for decreasing mortality. Data support using low-dose computed tomography (LDCT) of the chest to screen select patients who are at high risk for lung cancer. Lung screening is covered under the Affordable Care Act for individuals with high-risk factors. The Centers for Medicare & Medicaid Services (CMS) covers annual screening LDCT for appropriate Medicare beneficiaries at high risk for lung cancer if they also receive counseling and participate in shared decision-making before screening. The complete version of the NCCN Guidelines for Lung Cancer Screening provides recommendations for initial and subsequent LDCT screening and provides more detail about LDCT screening. This manuscript focuses on identifying patients at high risk for lung cancer who are candidates for LDCT of the chest and on evaluating initial screening findings.

PURPOSE: The 8(th) edition of the TNM classification of malignant tumors for the first time includes an official staging system for thymic epithelial tumors (TETs) recognized by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). Staging is critical for the management of TETs, and determining stage accurately from imaging has the potential to improve clinical outcomes. We examine preoperative computed tomography (CT) characteristics of TETs associated with AJCC/UICC pathologic TNM stage. MATERIALS AND METHODS: In this retrospective study, patients were included if they met all the following criteria: 1) diagnosis of TET, 2) had primary curative-intent surgery performed at our institution, and 3) had available preoperative CT imaging for review. Tumor pathology was staged according to the 8(th) edition TNM classification. Fifteen CT scan features were examined from each patient case according to the International Thymic Malignancy Interest Group (ITMIG) standard report terms in a blinded fashion. A Lasso regularized multivariate model was used to produce a weighted scoring system predictive of pathologic TNM stage. RESULTS: Examining the 54 patients included, the following CT characteristics were associated with higher pathologic TNM stage when using the following scoring system: elevated hemidiaphragm (score of 6), vascular endoluminal invasion (score of 6), pleural nodule (score of 2), lobulated contour (score of 2), and heterogeneous internal density (score of 1). Area under the ROC curve was 0.76. CONCLUSIONS: TETs with clearly invasive or metastatic features seen on CT are associated with having higher AJCC/UICC pathologic TNM stage, as expected. However, features of lobulated contour and heterogeneous internal density are also associated with higher stage disease. These findings need to be validated in an independent cohort.

ObjectivesWe propose a novel computational approach for the automated classification of classic versus atypical usual interstitial pneumonia (UIP).Materials and MethodsThirty-three patients with UIP were enrolled in this study. They were classified as classic versus atypical UIP by a consensus of 2

Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, the proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10−5). Conclusions: This study constitutes a novel perspective on how to interpret imaging information from CT examinations by suggesting that most of the information related to adenocarcinoma aggressiveness is related to the intensity and morphological properties of solid components of the tumor. The prediction of adenocarcinoma relapse was found to have low specificity but very high sensitivity. Our results could be useful in clinical practice to identify patients for which no recurrence is expected with a very high confidence using a presurgical CT scan only. It also provided an accurate estimation of the risk of recurrence after a given duration t from surgical resection (i.e., C-index = 0.81 ± 0.02).

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Lung Cancer Screening provide recommendations for selecting individuals for lung cancer screening, and for evaluation and follow-up of nodules found during screening, and are intended to assist with clinical and shared decision-making. These NCCN Guidelines Insights focus on the major updates to the 2015 NCCN Guidelines for Lung Cancer Screening, which include a revision to the recommendation from category 2B to 2A for one of the high-risk groups eligible for lung cancer screening. For low-dose CT of the lung, the recommended slice width was revised in the table on "Low-Dose Computed Tomography Acquisition, Storage, Interpretation, and Nodule Reporting."

Item does not contain fulltext The Fleischner Society Guidelines for management of solid nodules were published in 2005, and separate guidelines for subsolid nodules were issued in 2013. Since then, new information has become available; therefore, the guidelines have been revised to reflect current thinking on nodule management. The revised guidelines incorporate several substantive changes that reflect current thinking on the management of small nodules. The minimum threshold size for routine follow-up has been increased, and recommended follow-up intervals are now given as a range rather than as a precise time period to give radiologists, clinicians, and patients greater discretion to accommodate individual risk factors and preferences. The guidelines for solid and subsolid nodules have been combined in one simplified table, and specific recommendations have been included for multiple nodules. These guidelines represent the consensus of the Fleischner Society, and as such, they incorporate the opinions of a multidisciplinary international group of thoracic radiologists, pulmonologists, surgeons, pathologists, and other specialists. Changes from the previous guidelines issued by the Fleischner Society are based on new data and accumulated experience. (c) RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on March 13, 2017.

Imaging examinations are often performed in patients with Legionnaires' disease. The literature to date has documented that the imaging findings in this disorder are relatively nonspecific, and it is therefore difficult to prospectively differentiate legionella pneumonia from other forms of pneumonia, and from other noninfectious thoracic processes. Through a review of clinical cases and the literature, our objective is for the reader to gain a better understanding of the spectrum of radiographic manifestations of Legionnaires' disease.

Molecular analysis of the mutation status for EGFR and KRAS are now routine in the management of non-small cell lung cancer. Radiogenomics, the linking of medical images with the genomic properties of human tumors, provides exciting opportunities for non-invasive diagnostics and prognostics. We investigated whether EGFR and KRAS mutation status can be predicted using imaging data. To accomplish this, we studied 186 cases of NSCLC with preoperative thin-slice CT scans. A thoracic radiologist annotated 89 semantic image features of each patient’s tumor. Next, we built a decision tree to predict the presence of EGFR and KRAS mutations. We found a statistically significant model for predicting EGFR but not for KRAS mutations. The test set area under the ROC curve for predicting EGFR mutation status was 0.89. The final decision tree used four variables: emphysema, airway abnormality, the percentage of ground glass component and the type of tumor margin. The presence of either of the first two features predicts a wild type status for EGFR while the presence of any ground glass component indicates EGFR mutations. These results show the potential of quantitative imaging to predict molecular properties in a non-invasive manner, as CT imaging is more readily available than biopsies.

Rationale and Objectives To compare quality of ultra-low-dose thin-section computed tomography (CT) images of the lung reconstructed using model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASIR) to filtered back projection (FBP) and to determine the minimum tube current–time product on MBIR images by comparing to standard-dose FBP images. Materials and Methods Ten cadaveric lungs were scanned using 120 kVp and four different tube current–time products (8, 16, 32, and 80 mAs). Thin-section images were reconstructed using MBIR, three ASIR blends (30%, 60%, and 90%), and FBP. Using the 8-mAs data, side-to-side comparison of the four iterative reconstruction image sets to FBP was performed by two independent observers who evaluated normal and abnormal findings, subjective image noise, streak artifact, and overall image quality. Image noise was also measured quantitatively. Subsequently, 8-, 16-, and 32-mAs MBIR images were compared to standard-dose FBP images. Comparisons of image sets were analyzed using the Wilcoxon signed rank test with Bonferroni correction. Results At 8 mAs, MBIR images were significantly better ( P P Conclusions MBIR imaging shows higher overall quality with lower noise and streak artifacts than ASIR or FBP imaging, resulting in nearly 80% dose reduction without any degradations of overall image quality.

Left heart disease is associated with left atrial enlargement and is a common cause of pulmonary hypertension (PH). We investigated the relationship between left atrium maximal axial cross-sectional area (LA-MACSA), as measured on chest computed tomography (CT), and PH due to left heart disease (World Health Organization group 2) in patients with right heart catheterization-proven PH.A total of 165 patients with PH who had undergone right heart catheterization with pulmonary artery pressure and pulmonary capillary wedge pressure (PCWP) measurements and nongated chest CTs were included. LA-MACSA, LA anterior-posterior, and LA transverse measurements were independently obtained using the hand-drawn region-of-interest and distance measurement tools on standard PACS by 2 blinded cardiothoracic radiologists. Nonparametric statistical analyses and receiver operating characteristic curve were performed.Forty-three patients had group 2 PH (PCWP15 mm Hg), and 122 had nongroup 2 PH (PCWP≤15 mm Hg). Median LA-MACSA was significantly different between the group 2 PH and nongroup 2 PH patients (2312 vs. 1762 mm, P0.001). Interobserver concordance correlation for LA-MACSA was high at 0.91 (P0.001). At a threshold of 2400 mm, LA-MACSA demonstrated 93% specificity for classifying group 2 PH (area under the curve, 0.73; P0.001).LA-MACSA is a readily obtainable and reproducible measurement of left atrial enlargement on CT and can distinguish between group 2 and nongroup 2 PH with high specificity.

With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.

To assess the effect of radiation dose reduction on the appearance and visual quantification of specific CT patterns of fungal infection in immuno-compromised patients.Raw data of thoracic CT scans (64 × 0.75 mm, 120 kVp, 300 reference mAs) from 41 consecutive patients with clinical suspicion of pulmonary fungal infection were collected. In 32 patients fungal infection could be proven (median age of 55.5 years, range 35-83). A total of 267 cuboids showing CT patterns of fungal infection and 27 cubes having no disease were reconstructed at the original and 6 simulated tube currents of 100, 40, 30, 20, 10, and 5 reference mAs. Eight specific fungal CT patterns were analyzed by three radiologists: 76 ground glass opacities, 42 ground glass nodules, 51 mixed, part solid, part ground glass nodules, 36 solid nodules, 5 lobulated nodules, 6 spiculated nodules, 14 cavitary nodules, and 37 foci of air-space disease. The standard of reference was a consensus subjective interpretation by experts whom were not readers in the study.The mean sensitivity and standard deviation for detecting pathological cuboids/disease using standard dose CT was 0.91 ± 0.07. Decreasing dose did not affect sensitivity significantly until the lowest dose level of 5 mAs (0.87 ± 0.10, p=0.012). Nodular pattern discrimination was impaired below the dose level of 30 reference mAs: specificity for fungal 'mixed nodules' decreased significantly at 20, 10 and 5 reference mAs (p0.05). At lower dose levels, classification drifted from 'solid' to 'mixed nodule', although no lesion was missed.Our simulation data suggest that tube current levels can be reduced from 300 to 30 reference mAs without impairing the diagnostic information of specific CT patterns of pulmonary fungal infections.