Screening for lung cancer with low-dose spiral computed tomography

Prediction of positive pulmonary nodules based on machine learning algorithm combined with central carbon metabolism data

BACKGROUND

Lung cancer causes a huge disease burden, and early detection of positive pulmonary nodules (PPNs) as an early sign of lung cancer is extremely important for effective intervention. It is necessary to develop PPNs risk recognizer based on machine learning algorithm combined with central carbon metabolomics.

METHODS

The study included 2248 participants at high risk for lung cancer from the Ma'anshan Community Lung Cancer Screening cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to screen 18 central carbon-related metabolites in plasma, recursive feature elimination (RFE) was used to select all 42 features, followed by five machine learning algorithms for model development. The performance of the model was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, precision, recall, and F1 scores. In addition, SHapley Additive exPlanations (SHAP) was performed to assess the interpretability of the final selected model and to gain insight into the impact of features on the predicted results.

RESULTS

Finally, the two prediction models based on the random forest (RF) algorithm performed best, with AUC values of 0.87 and 0.83, respectively, better than other models. We found that homogentisic acid, fumaric acid, maleic acid, hippuric acid, gluconic acid, and succinic acid played a significant role in both PPNs prediction model and NPNs vs PPNs model, while 2-oxadipic acid only played a role in the former model and phosphopyruvate only played a role in the NPNs vs PPNs model. This model demonstrates the potential of central carbon metabolism for PPNs risk prediction and identification.

CONCLUSION

We developed a series of predictive models for PPNs, which can help in the early detection of PPNs and thus reduce the risk of lung cancer.

A Retrospective Analysis of 2-Year Follow-Up of Patients with Incidental Findings of Sarcoidosis

INTRODUCTION

Sarcoidosis is a multi-system granulomatous disease most commonly involving the lungs. It may be incidentally diagnosed during imaging studies for other conditions or non-specific symptoms. The appropriate follow-up of incidentally diagnosed asymptomatic stage 1 disease has not been well defined.

OBJECTIVE

To define the clinical course of incidentally diagnosed asymptomatic stage 1 sarcoidosis and propose an algorithm for the follow-up of these patients.

METHODOLOGY

A retrospective case note analysis was performed of all EBUS-TBNA (endobronchial ultrasound-guided transbronchial needle aspiration)-confirmed cases of stage 1 sarcoidosis presenting incidentally to Bristol and Liverpool Interstitial Lung Disease services. Clinical history, serology results, imaging scans, and lung function parameters were examined at baseline, 12, and 24 months. A cost analysis was performed comparing the cost of the current 2-year follow-up guidance to a 1 year follow-up period.

RESULTS

Sixty-seven patients were identified as the final cohort. There was no significant change in the pulmonary function tests over the two-year follow-up period. Radiological disease stability was observed in the majority of patients (58%, n = 29), and disease regression was evidenced in 40% (n = 20) at 1 year. Where imaging was performed at 2 years, the majority (69.8%, n = 37) had radiological evidence of disease regression, and 30.2% (n = 16) showed radiological evidence of stability. All patients remained asymptomatic and did not require therapeutic intervention over the study period.

CONCLUSIONS

Our results show that asymptomatic patients with incidental findings of thoracic lymph nodal non-caseating granulomas do not progress over a 2-year period. Our results suggest that the prolonged secondary-care follow-up of such patients may not be necessary. We propose that these patients are followed up for 1 year with a further year of patient-initiated follow-up (PIFU) prior to discharge.

ERS/ESTS/ESTRO/ESR/ESTI/EFOMP statement on management of incidental findings from low dose CT screening for lung cancer

BACKGROUND

Screening for lung cancer with low radiation dose computed tomography has a strong evidence base, is being introduced in several European countries and is recommended as a new targeted cancer screening programme. The imperative now is to ensure that implementation follows an evidence-based process that will ensure clinical and cost effectiveness. This European Respiratory Society (ERS) task force was formed to provide an expert consensus for the management of incidental findings which can be adapted and followed during implementation.

METHODS

A multi-European society collaborative group was convened. 23 topics were identified, primarily from an ERS statement on lung cancer screening, and a systematic review of the literature was conducted according to ERS standards. Initial review of abstracts was completed and full text was provided to members of the group for each topic. Sections were edited and the final document approved by all members and the ERS Science Council.

RESULTS

Nine topics considered most important and frequent were reviewed as standalone topics (interstitial lung abnormalities, emphysema, bronchiectasis, consolidation, coronary calcification, aortic valve disease, mediastinal mass, mediastinal lymph nodes and thyroid abnormalities). Other topics considered of lower importance or infrequent were grouped into generic categories, suitable for general statements.

CONCLUSIONS

This European collaborative group has produced an incidental findings statement that can be followed during lung cancer screening. It will ensure that an evidence-based approach is used for reporting and managing incidental findings, which will mean that harms are minimised and any programme is as cost-effective as possible.

ERS/ESTS/ESTRO/ESR/ESTI/EFOMP statement on management of incidental findings from low dose CT screening for lung cancer

BACKGROUND

Screening for lung cancer with low radiation dose computed tomography has a strong evidence base, is being introduced in several European countries and is recommended as a new targeted cancer screening programme. The imperative now is to ensure that implementation follows an evidence-based process that will ensure clinical and cost effectiveness. This European Respiratory Society (ERS) task force was formed to provide an expert consensus for the management of incidental findings which can be adapted and followed during implementation.

METHODS

A multi-European society collaborative group was convened. 23 topics were identified, primarily from an ERS statement on lung cancer screening, and a systematic review of the literature was conducted according to ERS standards. Initial review of abstracts was completed and full text was provided to members of the group for each topic. Sections were edited and the final document approved by all members and the ERS Science Council.

RESULTS

Nine topics considered most important and frequent were reviewed as standalone topics (interstitial lung abnormalities, emphysema, bronchiectasis, consolidation, coronary calcification, aortic valve disease, mediastinal mass, mediastinal lymph nodes and thyroid abnormalities). Other topics considered of lower importance or infrequent were grouped into generic categories, suitable for general statements.

CONCLUSIONS

This European collaborative group has produced an incidental findings statement that can be followed during lung cancer screening. It will ensure that an evidence-based approach is used for reporting and managing incidental findings, which will mean that harms are minimised and any programme is as cost-effective as possible.

Significant Incidental Findings in the National Lung Screening Trial

Importance

Low-dose computed tomography (LDCT) lung screening has been shown to reduce lung cancer mortality. Significant incidental findings (SIFs) have been widely reported in patients undergoing LDCT lung screening. However, the exact nature of these SIF findings has not been described.

Objective

To describe SIFs reported in the LDCT arm of the National Lung Screening Trial and classify SIFs as reportable or not reportable to the referring clinician (RC) using the American College of Radiology's white papers on incidental findings.

Design, Setting, and Participants

This was a retrospective case series study of 26 455 participants in the National Lung Screening Trial who underwent at least 1 screening examination with LDCT. The trial was conducted from 2002 to 2009, and data were collected at 33 US academic medical centers.

Main Outcomes and Measures

Significant incident findings were defined as a final diagnosis of a negative screen result with significant abnormalities that were not suspicious for lung cancer or a positive screen result with emphysema, significant cardiovascular abnormality, or significant abnormality above or below the diaphragm.

Results

Of 26 455 participants, 10 833 (41.0%) were women, the mean (SD) age was 61.4 (5.0) years, and there were 1179 (4.5%) Black, 470 (1.8%) Hispanic/Latino, and 24 123 (91.2%) White individuals. Participants were scheduled to undergo 3 screenings during the course of the trial; the present study included 75 126 LDCT screening examinations performed for 26 455 participants. A SIF was reported for 8954 (33.8%) of 26 455 participants who were screened with LDCT. Of screening tests with a SIF detected, 12 228 (89.1%) had a SIF considered reportable to the RC, with a higher proportion of reportable SIFs among those with a positive screen result for lung cancer (7632 [94.1%]) compared with those with a negative screen result (4596 [81.8%]). The most common SIFs reported included emphysema (8677 [43.0%] of 20 156 SIFs reported), coronary artery calcium (2432 [12.1%]), and masses or suspicious lesions (1493 [7.4%]). Masses included kidney (647 [3.2%]), liver (420 [2.1%]), adrenal (265 [1.3%]), and breast (161 [0.8%]) abnormalities. Classification was based on free-text comments; 2205 of 13 299 comments (16.6%) could not be classified. The hierarchical reporting of final diagnosis in NLST may have been associated with an overestimate of severe emphysema in participants with a positive screen result for lung cancer.

Conclusions and Relevance

This case series study found that SIFs were commonly reported in the LDCT arm of the National Lung Screening Trial, and most of these SIFs were considered reportable to the RC and likely to require follow-up. Future screening trials should standardize SIF reporting.

Accuracy of baseline low-dose computed tomography lung cancer screening: a systematic review and meta-analysis

BACKGROUND

Screening using low-dose computed tomography (LDCT) is a more effective approach and has the potential to detect lung cancer more accurately. We aimed to conduct a meta-analysis to estimate the accuracy of population-based screening studies primarily assessing baseline LDCT screening for lung cancer.

METHODS

MEDLINE, Excerpta Medica Database, and Web of Science were searched for articles published up to April 10, 2022. According to the inclusion and exclusion criteria, the data of true positives, false-positives, false negatives, and true negatives in the screening test were extracted. Quality Assessment of Diagnostic Accuracy Studies-2 was used to evaluate the quality of the literature. A bivariate random effects model was used to estimate pooled sensitivity and specificity. The area under the curve (AUC) was calculated by using hierarchical summary receiver-operating characteristics analysis. Heterogeneity between studies was measured using the Higgins I2 statistic, and publication bias was evaluated using a Deeks' funnel plot and linear regression test.

RESULTS

A total of 49 studies with 157,762 individuals were identified for the final qualitative synthesis; most of them were from Europe and America (38 studies), ten were from Asia, and one was from Oceania. The recruitment period was 1992 to 2018, and most of the subjects were 40 to 75 years old. The analysis showed that the AUC of lung cancer screening by LDCT was 0.98 (95% CI: 0.96-0.99), and the overall sensitivity and specificity were 0.97 (95% CI: 0.94-0.98) and 0.87 (95% CI: 0.82-0.91), respectively. The funnel plot and test results showed that there was no significant publication bias among the included studies.

CONCLUSIONS

Baseline LDCT has high sensitivity and specificity as a screening technique for lung cancer. However, long-term follow-up of the whole study population (including those with a negative baseline screening result) should be performed to enhance the accuracy of LDCT screening.

Diagnostic utility of trefoil factor families for the early detection of lung cancer and their correlation with tissue expression

Trefoil factors (TFFs) are upregulated in numerous types of cancer, including those of the breast, the colon, the lung and the pancreas, suggesting their potential utility as biomarkers for screening. In the present study, the clinical relevance of serum or urinary TFFs as biomarkers were comprehensively evaluated and the correlation with TFF expression levels in lung cancer tissue was examined. Serum and urine were collected from 199 patients with lung cancer and 198 healthy individuals. Concentrations of serum and urinary TFF1, TFF2 and TFF3 were measured using ELISA and the potential of TFF levels to discriminate between cancer and non-cancer samples was evaluated. In 100 of the cancer cases, expression of TFF1-3 was analyzed using immunohistochemical staining of paraffin sections. Furthermore, the relationship between TFF levels and clinicopathological factors among these cancer cases was analyzed using immunohistochemistry of tissue specimens, quantified and statistically analyzed. While serum levels of all TFFs measured using ELISA were significantly higher in patients with lung cancer compared with those in healthy individuals, urinary TFFs were lower. Areas under the curve (AUC) of the receiver operating characteristic curves for serum/urinary TFF1, TFF2 and TFF3 were 0.709/0.594, 0.722/0.501 and 0.663/0.665, respectively. Furthermore, the combination of serum TFF1, TFF2, TFF3 and urinary TFF1 and TFF3 demonstrated the highest AUC (0.826). In the clinicopathological analysis, serum TFF1 was higher in the early pathological T-stage (pTis/1/2) compared with the later stage (pT3/4) and TFF2 was higher in the pN0/1 than the pN2 group. With regards to the histological types, urinary TFF1 was higher in squamous cell carcinoma than adenocarcinoma (AC), but TFF2 tended to be higher in AC. Using immunohistochemical analysis, although TFF1 and TFF3 expression showed positive correlation with serum concentrations, TFF2 was inversely correlated. In conclusion, serum and urinary TFF levels are promising predictive biomarkers, and their measurements provide a useful in vivo and non-invasive diagnostic screening tool. In particular, TFF1 and TFF3 could be surrogate markers of clinicopathological profiles of human lung cancer.

A Comprehensive Survey on the Progress, Process, and Challenges of Lung Cancer Detection and Classification

Lung cancer is the primary reason of cancer deaths worldwide, and the percentage of death rate is increasing step by step. There are chances of recovering from lung cancer by detecting it early. In any case, because the number of radiologists is limited and they have been working overtime, the increase in image data makes it hard for them to evaluate the images accurately. As a result, many researchers have come up with automated ways to predict the growth of cancer cells using medical imaging methods in a quick and accurate way. Previously, a lot of work was done on computer-aided detection (CADe) and computer-aided diagnosis (CADx) in computed tomography (CT) scan, magnetic resonance imaging (MRI), and X-ray with the goal of effective detection and segmentation of pulmonary nodule, as well as classifying nodules as malignant or benign. But still, no complete comprehensive review that includes all aspects of lung cancer has been done. In this paper, every aspect of lung cancer is discussed in detail, including datasets, image preprocessing, segmentation methods, optimal feature extraction and selection methods, evaluation measurement matrices, and classifiers. Finally, the study looks into several lung cancer-related issues with possible solutions.

Single Camera-Based Dual-Channel Near-Infrared Fluorescence Imaging system

In this study, we propose a single camera-based dual-channel near-infrared (NIR) fluorescence imaging system that produces color and dual-channel NIR fluorescence images in real time. To simultaneously acquire color and dual-channel NIR fluorescence images of two fluorescent agents, three cameras and additional optical parts are generally used. As a result, the volume of the image acquisition unit increases, interfering with movements during surgical procedures and increasing production costs. In the system herein proposed, instead of using three cameras, we set a single camera equipped with two image sensors that can simultaneously acquire color and single-channel NIR fluorescence images, thus reducing the volume of the image acquisition unit. The single-channel NIR fluorescence images were time-divided into two channels by synchronizing the camera and two excitation lasers, and the noise caused by the crosstalk effect between the two fluorescent agents was removed through image processing. To evaluate the performance of the system, experiments were conducted for the two fluorescent agents to measure the sensitivity, crosstalk effect, and signal-to-background ratio. The compactness of the resulting image acquisition unit alleviates the inconvenient movement obstruction of previous devices during clinical and animal surgery and reduces the complexity and costs of the manufacturing process, which may facilitate the dissemination of this type of system.

Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality

BACKGROUND

Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT).  OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening.

SEARCH METHODS

We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021.  SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes.  DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity.  MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years.  None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence).  Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence).  False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour.  AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.

Screening programs for renal cell carcinoma: a systematic review by the EAU young academic urologists renal cancer working group

PURPOSE

To systematically review studies focused on screening programs for renal cell carcinoma (RCC) and provide an exhaustive overview on their clinical impact, potential benefits, and harms.

METHODS

A systematic review of the recent English-language literature was conducted according to the European Association of Urology guidelines and the PRISMA statement recommendations (PROSPERO ID: CRD42021283136) using the MEDLINE, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases. Risk-of-bias assessment was performed according to the QUality In Prognosis Studies (QUIPS) tool.

RESULTS

Overall, nine studies and one clinical trials were included. Eight studies reported results from RCC screening programs involving a total of 159 136 patients and four studies reported screening cost-analysis. The prevalence of RCC ranged between 0.02 and 0.22% and it was associated with the socio-demographic characteristics of the subjects; selection of the target population decreased, overall, the screening cost per diagnosis.

CONCLUSIONS

Despite an increasing interest in RCC screening programs from patients and clinicians there is a relative lack of studies reporting the efficacy, cost-effectiveness, and the optimal modality for RCC screening. Targeting high-risk individuals and/or combining detection of RCC with other health checks represent pragmatic options to improve the cost-effectiveness and reduce the potential harms of RCC screening.

Incidental Findings on Low-Dose CT Scan Lung Cancer Screenings and Deaths From Respiratory Diseases

BACKGROUND

Incidental respiratory disease-related findings are frequently observed on low-dose CT (LDCT) lung cancer screenings. This study analyzed data from the National Lung Screening Trial (NLST) to assess the relationship between such findings and respiratory disease mortality (RDM), excluding lung cancer.

RESEARCH QUESTION

Are incidental respiratory findings on LDCT scanning associated with increased RDM?

STUDY DESIGN AND METHODS

Subjects in the NLST LDCT arm received three annual screens. Trial radiologists noted findings related to possible lung cancer, as well as respiratory-related incidental findings. Demographic characteristics, smoking history, and medical history were captured in a baseline questionnaire. Kaplan-Meier curves were used to assess cumulative RDM. Multivariate proportional hazards models were used to assess risk factors for RDM; in addition to incidental CT scan findings, variables included respiratory disease history (COPD/emphysema, and asthma), smoking history, and demographic factors (age, race, sex, and BMI).

RESULTS

Of 26,722 subjects in the NLST LDCT arm, 25,002 received the baseline screen and a subsequent LDCT screen. Overall, 59% were male, 26.5% were aged ≥ 65 years at baseline, and 10.6% reported a history of COPD/emphysema. Emphysema on LDCT scanning was reported in 30.7% of subjects at baseline and in 44.2% at any screen. Of those with emphysema on baseline LDCT scanning, 18% reported a history of COPD/emphysema. Median mortality follow-up was 10.3 years. There were 3,639 deaths, and 708 were from respiratory diseases. Among subjects with no history of COPD/emphysema, 10-year cumulative RDM ranged from 3.9% for subjects with emphysema and reticular opacities to 1.1% for those with neither condition; the corresponding range among subjects with a COPD/emphysema history was 17.3% (both) to 3.7% (neither). Emphysema on LDCT imaging was associated with a significantly elevated RDM hazard ratio (2.27; 95% CI, 1.92-2.7) in the multivariate model. Reticular opacities (including honeycombing/fibrosis/scar) also had a significantly elevated hazard ratio (1.39; 95% CI, 1.19-1.62).

INTERPRETATION

Incidental respiratory disease-related findings observed on NLST LDCT screens were frequent and associated with increased mortality from respiratory diseases.

Lung cancer risk prediction models based on pulmonary nodules: A systematic review

BACKGROUND

Screening with low-dose computed tomography (LDCT) is an efficient way to detect lung cancer at an earlier stage, but has a high false-positive rate. Several pulmonary nodules risk prediction models were developed to solve the problem. This systematic review aimed to compare the quality and accuracy of these models.

METHODS

The keywords "lung cancer," "lung neoplasms," "lung tumor," "risk," "lung carcinoma" "risk," "predict," "assessment," and "nodule" were used to identify relevant articles published before February 2021. All studies with multivariate risk models developed and validated on human LDCT data were included. Informal publications or studies with incomplete procedures were excluded. Information was extracted from each publication and assessed.

RESULTS

A total of 41 articles and 43 models were included. External validation was performed for 23.2% (10/43) models. Deep learning algorithms were applied in 62.8% (27/43) models; 60.0% (15/25) deep learning based researches compared their algorithms with traditional methods, and received better discrimination. Models based on Asian and Chinese populations were usually built on single-center or small sample retrospective studies, and the majority of the Asian models (12/15, 80.0%) were not validated using external datasets.

CONCLUSION

The existing models showed good discrimination for identifying high-risk pulmonary nodules, but lacked external validation. Deep learning algorithms are increasingly being used with good performance. More researches are required to improve the quality of deep learning models, particularly for the Asian population.

Screening for Lung Cancer: CHEST Guideline and Expert Panel Report

BACKGROUND

Low-dose chest CT screening for lung cancer has become a standard of care in the United States, in large part because of the results of the National Lung Screening Trial (NLST). Additional evidence supporting the net benefit of low-dose chest CT screening for lung cancer, and increased experience in minimizing the potential harms, has accumulated since the prior iteration of these guidelines. Here, we update the evidence base for the benefit, harms, and implementation of low-dose chest CT screening. We use the updated evidence base to provide recommendations where the evidence allows, and statements based on experience and expert consensus where it does not.

METHODS

Approved panelists reviewed previously developed key questions using the Population, Intervention, Comparator, Outcome format to address the benefit and harms of low-dose CT screening, and key areas of program implementation. A systematic literature review was conducted using MEDLINE via PubMed, Embase, and the Cochrane Library on a quarterly basis since the time of the previous guideline publication. Reference lists from relevant retrievals were searched, and additional papers were added. Retrieved references were reviewed for relevance by two panel members. The quality of the evidence was assessed for each critical or important outcome of interest using the Grading of Recommendations, Assessment, Development, and Evaluation approach. Meta-analyses were performed when enough evidence was available. Important clinical questions were addressed based on the evidence developed from the systematic literature review. Graded recommendations and ungraded statements were drafted, voted on, and revised until consensus was reached.

RESULTS

The systematic literature review identified 75 additional studies that informed the response to the 12 key questions that were developed. Additional clinical questions were addressed resulting in seven graded recommendations and nine ungraded consensus statements.

CONCLUSIONS

Evidence suggests that low-dose CT screening for lung cancer can result in a favorable balance of benefit and harms. The selection of screen-eligible individuals, the quality of imaging and image interpretation, the management of screen-detected findings, and the effectiveness of smoking cessation interventions can impact this balance.

Preliminary study of 3 T-MRI native T1-mapping radiomics in differential diagnosis of non-calcified solid pulmonary nodules/masses

Background

Cumulative CT radiation damage was positively correlated with increased tumor risks. Although it has recently been known that non-radiation MRI is alternative for pulmonary imaging. There is little known about the value of MRI T1-mapping in the diagnosis of pulmonary nodules. This article aimed to investigate the value of native T1-mapping-based radiomics features in differential diagnosis of pulmonary lesions.

Methods

73 patients underwent 3 T-MRI examination in this prospective study. The 99 pulmonary lesions on native T1-mapping images were segmented twice by one radiologist at indicated time points utilizing the in-house semi-automated software, followed by extraction of radiomics features. The inter-class correlation coefficient (ICC) was used for analyzing intra-observer’s agreement. Dimensionality reduction and feature selection were performed via univariate analysis, and least absolute shrinkage and selection operator (LASSO) analysis. Then, the binary logical regression (LR), support vector machine (SVM) and decision tree classifiers with the input of optimal features were selected for differentiating malignant from benign lesions. The receiver operative characteristics (ROC) curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated. Z-test was used to compare differences among AUCs.

Results

107 features were obtained, of them, 19.5% (n = 21) had relatively good reliability (ICC ≥ 0.6). The remained 5 features (3 GLCM, 1 GLSZM and 1 shape features) by dimensionality reduction were useful. The AUC of LR was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70%, 85% and 80%. The AUC of SVM was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70, 85 and 80%. The AUC of decision tree was 0.69(95%CI: 0.49–0.87), with sensitivity, specificity and accuracy of 50, 85 and 73.3%.

Conclusions

The LR and SVM models using native T1-mapping-based radiomics features can differentiate pulmonary malignant from benign lesions, especially for uncertain nodules requiring long-term follow-ups.

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.

Radiomics and functional imaging in lung cancer: the importance of radiological heterogeneity beyond FDG PET/CT and lung biopsy

PURPOSE

[¹⁸F]-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography (FDG PET/CT) has a central role in the lung nodules' characterization even if, with SUV < 2.5, percutaneous CT-guided Lung Biopsy (CTLB) is needed to assess nodule nature. In that scenario, CT Texture Analysis (CTTA) could be a non-invasive imaging biomarker. Our purpose is to test CTTA ability in differentiating malignant from benign nodules.

METHOD

Patients that underwent FDG PET/CT followed by CTLB between January 2013 and December 2018 were retrospectively enrolled. Were included patients with lung nodule SUV < 2.5 and histological diagnosis.

EXCLUSION CRITERIA

nodules SUV > 2.5, patients who refused CTLB or received oncological treatment before CTLB, indeterminate pathology report, CT motion artifacts. Two radiologists in consensus performed CTTA, drawing a volumetric Region of Interest of nodule with a dedicated first order TA software with and without spatial scaling filters, on preliminary CT performed for CTLB. Statistics included a comparison between malignant and benign neoplasms distribution (2-tailed T-test or Mann-Whitney test according to normal/non-normal data distribution), P-values < 0.05 were considered statistically significant. CTTA accuracy was tested with Receiver Operating Characteristics (ROC) curve.

RESULTS

Form an initial population of 1178, 46 patients encountered inclusion criteria. Pathologist reported 27/46 (59%) malignant and 19/46 (41%) benign nodules. In malignant lesions CTTA showed lower Kurtosis' and higher Skewness' values (all P ≤ 0.0013 and all filtered TA P < 0.024, respectively). ROC curve showed significant Area Under the Curve for Kurtosis and Skewness (0.654 and 0.642, P < 0.001) at medium filtration.

CONCLUSIONS

CTTA is a promising radiological tool to characterize benign and malignant lung nodules, even in those cases without an altered glucose metabolism.

Racial and socioeconomic disparities in lung cancer screening in the United States: A systematic review

Nonsmall cell lung cancer (NSCLC) is the leading cause of cancer deaths. Lung cancer screening (LCS) reduces NSCLC mortality; however, a lack of diversity in LCS studies may limit the generalizability of the results to marginalized groups who face higher risk for and worse outcomes from NSCLC. Identifying sources of inequity in the LCS pipeline is essential to reduce disparities in NSCLC outcomes. The authors searched 3 major databases for studies published from January 1, 2010 to February 27, 2020 that met the following criteria: 1) included screenees between ages 45 and 80 years who were current or former smokers, 2) written in English, 3) conducted in the United States, and 4) discussed socioeconomic and race-based LCS outcomes. Eligible studies were assessed for risk of bias. Of 3721 studies screened, 21 were eligible. Eligible studies were evaluated, and their findings were categorized into 3 themes related to LCS disparities faced by Black and socioeconomically disadvantaged individuals: 1) eligibility; 2) utilization, perception, and utility; and 3) postscreening behavior and care. Disparities in LCS exist along racial and socioeconomic lines. There are several steps along the LCS pipeline in which Black and socioeconomically disadvantaged individuals miss the potential benefits of LCS, resulting in increased mortality. This study identified potential sources of inequity that require further investigation. The authors recommend the implementation of prospective trials that evaluate eligibility criteria for underserved groups and the creation of interventions focused on improving utilization and follow-up care to decrease LCS disparities.

Determining cost-effectiveness of lung cancer screening in urban Chinese populations using a state-transition Markov model

OBJECTIVES

This study analyses the cost-effectiveness of annual low-dose CT (LDCT) screening of high-risk cancer populations in Chinese urban areas.

DESIGN

We used a Markov model to evaluate LDCT screening from a sociological perspective.

SETTING

The data from two large lung cancer screening programmes in China were used.

PARTICIPANTS

The sample consisted of 100 000 smokers who underwent annual LDCT screening until age 76.

INTERVENTION

The study comprises five screening strategies, with the initial screening ages in both the screening strategies and their corresponding non-screening strategies being 40, 45, 50, 55 and 60 years, respectively.

PRIMARY AND SECONDARY OUTCOME MEASURES

The incremental cost-effectiveness ratio (ICER) between screening and non-screening strategies at the same initial age was evaluated.

RESULTS

In the baseline scenario, compared with those who were not screened, the specific mortality from lung cancer decreased by 18.52%-23.13% among those who underwent screening. The ICER of LDCT screening ranges from US$13 056.82 to US$15 736.06 per quality-adjusted life year, which is greater than one but less than three times the gross domestic product per capita in China. An initial screening age of 55 years is the most cost-effective strategy.

CONCLUSIONS

Baseline analysis shows that annual LDCT screening of heavy smokers in Chinese urban areas is likely to be cost-effective. The sensitivity analysis reveals that sensitivity, specificity and the overdiagnosis rate influence the cost-effectiveness of LDCT screening. All scenarios tested demonstrate cost-effectiveness, except for the combination of worst values of sensitivity, specificity and overdiagnosis. Therefore, the cost-effectiveness of a screening strategy depends on the performance of LDCT screenings.

The impact of income and education on lung cancer screening utilization, eligibility, and outcomes: a narrative review of socioeconomic disparities in lung cancer screening

Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths in the US and worldwide. In particular, vulnerable populations such as those of low socioeconomic status (SES) are at the highest risk for and suffer the highest mortality from NSCLC. Although lung cancer screening (LCS) has been demonstrated to be a powerful tool to lower NSCLC mortality, it is underutilized by eligible smokers, and disparities in screening are likely to contribute to inequities in NSCLC outcomes. It is imperative that we collect and analyze LCS data focused on individuals of low socioeconomic position to identify and address barriers to LCS utilization and help close the gaps in NSCLC mortality along socioeconomic lines. Toward this end, this review aims to examine published studies that have evaluated the impact of income and education on LCS utilization, eligibility, and outcomes. We searched the PubMed, Ovid MEDLINE, and CINAHL Plus databases for all studies published from January 1, 2010, to October 21, 2020, that discussed socioeconomic-based LCS outcomes. The review reveals that income and education have impact on LCS utilization, eligibility, false positive rates and smoking cessation attempts; however, there is a lack of studies evaluating the impact of SES on LCS follow-up, stage at diagnosis, and treatment. We recommend the intentional inclusion of lower SES participants in LCS studies in order to clarify appropriate eligibility criteria, risk-based metrics and outcomes in this high-risk group. We also anticipate that low SES smokers and their providers will require increased support and education regarding smoking cessation and shared decision-making efforts.

Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

IMPORTANCE

Lung cancer is the leading cause of cancer-related death in the US.

OBJECTIVE

To review the evidence on screening for lung cancer with low-dose computed tomography (LDCT) to inform the US Preventive Services Task Force (USPSTF).

DATA SOURCES

MEDLINE, Cochrane Library, and trial registries through May 2019; references; experts; and literature surveillance through November 20, 2020.

STUDY SELECTION

English-language studies of screening with LDCT, accuracy of LDCT, risk prediction models, or treatment for early-stage lung cancer.

DATA EXTRACTION AND SYNTHESIS

Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings. Data were not pooled because of heterogeneity of populations and screening protocols.

MAIN OUTCOMES AND MEASURES

Lung cancer incidence, lung cancer mortality, all-cause mortality, test accuracy, and harms.

RESULTS

This review included 223 publications. Seven randomized clinical trials (RCTs) (N = 86 486) evaluated lung cancer screening with LDCT; the National Lung Screening Trial (NLST, N = 53 454) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON, N = 15 792) were the largest RCTs. Participants were more likely to benefit than the US screening-eligible population (eg, based on life expectancy). The NLST found a reduction in lung cancer mortality (incidence rate ratio [IRR], 0.85 [95% CI, 0.75-0.96]; number needed to screen [NNS] to prevent 1 lung cancer death, 323 over 6.5 years of follow-up) with 3 rounds of annual LDCT screening compared with chest radiograph for high-risk current and former smokers aged 55 to 74 years. NELSON found a reduction in lung cancer mortality (IRR, 0.75 [95% CI, 0.61-0.90]; NNS to prevent 1 lung cancer death of 130 over 10 years of follow-up) with 4 rounds of LDCT screening with increasing intervals compared with no screening for high-risk current and former smokers aged 50 to 74 years. Harms of screening included radiation-induced cancer, false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, and increases in distress. For every 1000 persons screened in the NLST, false-positive results led to 17 invasive procedures (number needed to harm, 59) and fewer than 1 person having a major complication. Overdiagnosis estimates varied greatly (0%-67% chance that a lung cancer was overdiagnosed). Incidental findings were common, and estimates varied widely (4.4%-40.7% of persons screened).

CONCLUSIONS AND RELEVANCE

Screening high-risk persons with LDCT can reduce lung cancer mortality but also causes false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, increases in distress, and, rarely, radiation-induced cancers. Most studies reviewed did not use current nodule evaluation protocols, which might reduce false-positive results and invasive procedures for false-positive results.

Improvement in Follow-up Imaging With a Patient Tracking System and Computerized Registry for Lung Nodule Management

PURPOSE

Despite established guidelines, radiologists' recommendations and timely follow-up of incidental lung nodules remain variable. To improve follow-up of nodules, a system using standardized language (tracker phrases) recommending time-based follow-up in chest CT reports, coupled with a computerized registry, was created.

MATERIALS AND METHODS

Data were obtained from the electronic health record and a facility-built electronic lung nodule registry. We evaluated two randomly selected patient cohorts with incidental nodules on chest CT reports: before intervention (September 2008 to March 2011) and after intervention (August 2011 to December 2016). Multivariable logistic regression was used to compare the cohorts for the main outcome of timely follow-up, defined as a subsequent report within 13 months of the initial report.

RESULTS

In all, 410 patients were included in the pretracker cohort versus 626 in the tracker cohort. Before system inception, 30% of CT reports lacked an explicit time-based recommendation for nodule follow-up. The proportion of patients with timely follow-up increased from 46% to 55%, and the proportion of those with no documented follow-up or follow-up beyond 24 months decreased from 48% to 31%. The likelihood of timely follow-up increased 41%, adjusted for high risk for lung cancer and age 65 years or older. After system inception, reports missing a tracker phrase for nodule recommendation averaged 6%, without significant interyear variation.

CONCLUSIONS

Standardized language added to CT reports combined with a computerized registry designed to identify and track patients with incidental lung nodules was associated with improved likelihood of follow-up imaging.

Pulmonary nodule radiological diagnostic algorithm in lung cancer screening

Publications of the final results of the two largest randomized lung cancer screening (LCS) trials in the United States and Europe confirmed the reduction in the mortality rate associated with the use of screening with low-dose computed tomography (LDCT). Results of these trials led to widespread acceptance of LCS in properly defined high-risk populations, and its implementation in the clinical practice. Many countries started preparation for national LCS and refreshed still open debate about lung nodule management. Detection of lung cancer in the early stage with a reduction of lung cancer mortality requires dedicated programs with optimized protocols, including a specified pulmonary nodule diagnostic algorithm. The screening protocol should be clear with a precise nodule diameter or volume threshold, based on which a positive screen result is defined. The application of risk-prediction models and the introduction of the semiautomated assessment of detected nodules improves screening accuracy and should be applied in LCS protocols as verified tools to aid radiological diagnosis. In this review, we have summarized recent data about the radiological protocols from the most important LCS programs and pulmonary diagnostic algorithms. These protocols should be taken into consideration in the ongoing and planned LCS programs.

A computed tomography-based nomogram to predict pneumothorax caused by preoperative localization of ground glass nodules using hook wire

OBJECTIVE

To develop and validate a CT-based nomogram to predict the occurrence of loculated pneumothorax due to hook wire placement.

METHODS

Patients (n = 177) were divided into pneumothorax (n = 72) and non-pneumothorax (n = 105) groups. Multivariable logistic regression analysis was applied to build a clinical prediction model using significant predictors identified by univariate analysis of imaging features and clinical factors. Receiver operating characteristic (ROC) was applied to evaluate the discrimination of the nomogram, which was calibrated using calibration curve.

RESULTS

Based on the results of multivariable regression analysis, transfissure approach [odds ratio (OR): 757.94; 95% confidence interval CI (21.20-27099.30) p < 0.0001], transemphysema [OR: 116.73; 95% CI (12.34-1104.04) p < 0.0001], localization of multiple nodules [OR: 8.04; 95% CI (2.09-30.89) p = 0.002], and depth of nodule [OR: 0.77; 95% CI (0.71-0.85) p < 0.0001] were independent risk factors for pneumothorax and were included in the predictive model (p < 0.05). The area under the ROC curve value for the nomogram was 0.95 [95% CI (0.92-0.98)] and the calibration curve indicated good consistency between risk predicted using the model and actual risk.

CONCLUSION

A CT-based nomogram combining imaging features and clinical factors can predict the probability of pneumothorax before localization of ground-glass nodules. The nomogram is a decision-making tool to prevent pneumothorax and determine whether to proceed with further treatment.

ADVANCES IN KNOWLEDGE

A nomogram composed of transfissure, transemphysema, multiple nodule localization, and depth of nodule has been developed to predict the probability of pneumothorax before localization of GGNs.

Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives

In the past decade, the introduction of molecularly targeted agents and immune-checkpoint inhibitors has led to improved survival outcomes for patients with advanced-stage lung cancer; however, this disease remains the leading cause of cancer-related mortality worldwide. Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening in high-risk populations - the US National Lung Screening Trial (NLST) and NELSON - have provided evidence of a statistically significant mortality reduction in patients. LDCT-based screening programmes for individuals at a high risk of lung cancer have already been implemented in the USA. Furthermore, implementation programmes are currently underway in the UK following the success of the UK Lung Cancer Screening (UKLS) trial, which included the Liverpool Health Lung Project, Manchester Lung Health Check, the Lung Screen Uptake Trial, the West London Lung Cancer Screening pilot and the Yorkshire Lung Screening trial. In this Review, we focus on the current evidence on LDCT-based lung cancer screening and discuss the clinical developments in high-risk populations worldwide; additionally, we address aspects such as cost-effectiveness. We present a framework to define the scope of future implementation research on lung cancer screening programmes referred to as Screening Planning and Implementation RAtionale for Lung cancer (SPIRAL).

Performance of low-dose computed tomography on lung cancer screening in high-risk populations: The experience over five screening rounds in Sichuan, China

OBJECTIVE

To evaluate the performance of low-dose computed tomography (LDCT) on lung cancer screening in high-risk populations in Sichuan.

METHODS

From April 2014 to July 2018, LDCT was performed annually on 3185 subjects aged 50-74 years who had smoked ≥ 20 pack-years (or subjects having quit smoking within 5 years). Information about all deaths and lung cancer diagnoses were obtained by active investigation, or passive matching to disease surveillance system.

RESULTS

The screening population had a median age of 60 years. 62.4 % of which were current smokers and had smoked 30 pack-years. After participating in the baseline screening, the compliance rates of subjects consecutively completing one round, two rounds, three rounds, and four rounds of annual screening were 67.22 %, 52.84 %, 43.24 %, and 40.04 %, respectively. The positive rates in baseline and annual screening were 6.53 % and 5.79 %, respectively. During the 5 rounds, a total of 9522 person-times were screened by LDCT with a screening sensitivity of 89.13 % (95 % CI: 76.96-95.27), specificity of 94.36 % (95 % CI: 93.88-94.81), positive predictive value of 7.13 % (95 % CI: 5.30-9.53), and negative predictive value of 99.94 % (95 % CI: 99.87-99.98). There were no statistically significant performance differences between baseline and annual screening. The difference in the proportion of screen-detected stage I lung cancer between baseline screening and annual screening was not statistically significant, neither.

CONCLUSION

The application of LDCT on lung cancer screening in high-risk populations shows favorable compliance and a high screening performance in the project area of Sichuan,China.

Rethinking prostate cancer screening: could MRI be an alternative screening test?

In the past decade rigorous debate has taken place about population-based screening for prostate cancer. Although screening by serum PSA levels can reduce prostate cancer-specific mortality, it is unclear whether the benefits outweigh the risks of false-positive results and overdiagnosis of insignificant prostate cancer, and it is not recommended for population-based screening. MRI screening for prostate cancer has the potential to be analogous to mammography for breast cancer or low-dose CT for lung cancer. A number of potential barriers and technical challenges need to be overcome in order to implement such a programme. We discuss different approaches to MRI screening that could address these challenges, including abbreviated MRI protocols, targeted MRI screening, longer rescreening intervals and a multi-modal screening pathway. These approaches need further investigation, and we propose a phased stepwise research framework to ensure proper evaluation of the use of a fast MRI examination as a screening test for prostate cancer.

Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study

Lung cancer remains the overwhelmingly greatest cause of cancer death in the United States, accounting for more annual deaths than breast, prostate, and colon cancer combined. Accumulated evidence since the mid to late 1990s, however, indicates that low-dose CT screening of high-risk patients enables detection of lung cancer at an early stage and can reduce the risk of dying from lung cancer. CT screening is now a recommended clinical service in the United States, subject to guidelines and reimbursement requirements intended to standardize practice and optimize the balance of benefits and risks. In this review, the evidence on the effectiveness of CT screening will be summarized and the current guidelines and standards will be described in the context of knowledge gained from lung cancer screening studies. In addition, an overview of the potential advances that may improve CT screening will be presented, and the need to better understand the performance in clinical practice outside of the research trial setting will be discussed. © RSNA, 2020.

Surgical resection is sufficient for incidentally discovered solitary pulmonary nodule caused by nontuberculous mycobacteria in asymptomatic patients

Incidentally discovered solitary pulmonary nodules (SPN) caused by nontuberculous mycobacteria (NTM) is uncommon, and its optimal treatment strategy remains uncertain. This cohort study determined the clinical characteristics and outcome of asymptomatic patients with NTM-SPN after surgical resection. Resected SPNs with culture-positive for NTM in six hospitals in Taiwan during January, 2010 to January, 2017 were identified. Asymptomatic patients without a history of NTM-pulmonary disease (PD) or same NTM species isolated from the respiratory samples were selected. All were followed until May 1, 2019. A total of 43 patients with NTM-SPN were enrolled. Mycobacterium avium complex (60%) and M. kansasii (19%) were the most common species. The mean age was 61.7 ± 13.4. Of them, 60% were female and 4% had history of pulmonary tuberculosis. The NTM-SPN was removed by wedge resection in 38 (88%), lobectomy in 3 (7%) and segmentectomy in 2 (5%). Caseating granuloma was the most common histologic feature (58%), while chronic inflammation accounts for 23%. Mean duration of the follow-up was 5.2 ± 2.8 years (median: 4.2 years [2.5–7.0]), there were no mycobacteriology recurrence or NTM-PD development. In conclusion, surgical resection is likely to curative for incidentally discovered NTM-SPN in asymptomatic patients without culture evidence of the same NTM species from respiratory specimens, and routine mycobacterium culture for resected SPN might be necessary for differentiating pulmonary tuberculosis and NTM because further treatment differs.

Consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography

Background

To study the consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography (LDCT), and to analyze factors that affect the consistency.

Methods

A total of 750 LDCT cases were collected randomly from three medical centers. Three experienced chest radiologists independently evaluated and detected the pulmonary nodules on 625 cases of LDCT images. The detected nodules were classified into 3 groups: group I (detected by all radiologists); group II (detected by two radiologists); group III (detected by only one radiologist). The consistency with respect to the image features of individual nodules was assessed.

Results

A total of 1,206 nodules were identified by the three radiologists. There were 234 (19.4%) nodules in group I, 377 (31.3%) nodules in group II, and 595 (49.3%) nodules in group III. Logistic regression showed that the size, density, and location of the nodules correlated with the detection of nodules. Nodules sized great than or equal to 4 mm were more consistently identified than nodules sized less than 4 mm. Solid and calcified nodules were more consistently identified than sub-solid nodules. Nodules located in the outer zone were more consistently identified than hilar nodules.

Conclusions

There was considerable inter-reader variability with respect to identification of pulmonary nodules in LDCT. Larger nodules, solid or calcified nodules, and nodules located in the outer zone were more consistently identified.

A retrospective study analyzing missed diagnosis of lung metastases at their early stages on computed tomography

Background

Lungs are one of the target organs of metastases of primary lung, breast, liver, colorectal, and esophageal cancer. While computed tomography (CT) is the most widely used modality for detecting lung metastases, it is still very challenging to detect them at the earlier stages. If lung metastases could be found on CT scans at the earliest time points, patients would benefit by beginning treatment earlier. The objective of this study was to demonstrate that CT can reveal lung metastases in many cases at even earlier stages than current radiological practice may find.

Methods

One hundred patients with lung metastases were randomly selected and their surveillance CT scans were analyzed retrospectively. The patients had primary cancer in the breasts, lungs, esophagus, colorectum, and liver. All patients had multiple CT examinations of the lungs and their metastases, if any, were confirmed by subsequent CT scans. The earliest CT scans were examined to determine whether lung metastases at the same locations had been diagnosed or missed. Missed lung metastases, categorized by type of the primary cancer and adjacency to nearby blood vessels, were statistically analyzed.

Results

There were 36/100 (36%) cases of missed lung metastases, including 15 cases of single metastasis and 21 cases of multiple metastases. There were a total of 174 missed loci of lung metastases. Where metastases were missed, there was a statistically significant difference (P<0.001) in their distribution within the sub-regions of the lungs. Adjacency to blood vessels appeared to be a significant factor in metastases being missed during diagnosis (P<0.001).

Conclusions

There was a considerable percentage of early lung metastases that were missed by radiologists but actually appeared on CT scans. The capability of CT to reveal such early metastases opens up an opportunity to move up the time points of detecting lung metastases through clinical and training improvement and technology development such as computer-aided detection.

A Novel Computer-Aided Diagnosis Scheme on Small Annotated Set: G2C-CAD

Purpose

Computer-aided diagnosis (CAD) can aid in improving diagnostic level; however, the main problem currently faced by CAD is that it cannot obtain sufficient labeled samples. To solve this problem, in this study, we adopt a generative adversarial network (GAN) approach and design a semisupervised learning algorithm, named G2C-CAD.

Methods

From the National Cancer Institute (NCI) Lung Image Database Consortium (LIDC) dataset, we extracted four types of pulmonary nodule sign images closely related to lung cancer: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, obtaining a total of 3,196 samples. In addition, we randomly selected 2,000 non-lesion image blocks as negative samples. We split the data 90% for training and 10% for testing. We designed a DCGAN generative adversarial framework and trained it on the small sample set. We also trained our designed CNN-based fuzzy Co-forest on the labeled small sample set and obtained a preliminary classifier. Then, coupled with the simulated unlabeled samples generated by the trained DCGAN, we conducted iterative semisupervised learning, which continually improved the classification performance of the fuzzy Co-forest until the termination condition was reached. Finally, we tested the fuzzy Co-forest and compared its performance with that of a C4.5 random decision forest and the G2C-CAD system without the fuzzy scheme, using ROC and confusion matrix for evaluation.

Results

Four different types of lung cancer-related signs were used in the classification experiment: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, along with negative image samples. For these five classes, the G2C-CAD system obtained AUCs of 0.946, 0.912, 0.908, 0.887, and 0.939, respectively. The average accuracy of G2C-CAD exceeded that of the C4.5 random decision tree by 14%. G2C-CAD also obtained promising test results on the LISS signs dataset; its AUCs for GGO, lobulation, spiculation, pleural indentation, and negative image samples were 0.972, 0.964, 0.941, 0.967, and 0.953, respectively.

Conclusion

The experimental results show that G2C-CAD is an appropriate method for addressing the problem of insufficient labeled samples in the medical image analysis field. Moreover, our system can be used to establish a training sample library for CAD classification diagnosis, which is important for future medical image analysis.

Development of Protocol for Korean Lung Cancer Screening Project (K-LUCAS) to Evaluate Effectiveness and Feasibility to Implement National Cancer Screening Program

Purpose

To reduce lung cancer mortality, lung cancer screening was recommended using low-dose computed tomography (LDCT) to high-risk population. A protocol for multicenter lung cancer screening pilot project was developed to evaluate the effectiveness and feasibility of lung cancer screening to implement National Cancer Screening Program in Korea.

Materials and Methods

Multidisciplinary expert committee was comprised to develop a standardized protocol for Korean Lung Cancer Screening Project (K-LUCAS). K-LUCAS is a population-based single arm trial that targets high-risk population aged 55-74 years with at least 30 pack-year smoking history. LDCT results are reported by Lung-RADS suggested by American Radiology Society. Network-based system using computer-aided detection program is prepared to assist reducing diagnostic errors. Smoking cessation counselling is provided to all currently smoking participants. A small pilot test was conducted to check the feasibility and compliance of the protocols for K-LUCAS.

Results

In pilot test, 256 were participated. The average age of participants was 63.2 years and only three participants (1.2%) were female. The participants had a smoking history of 40.5 pack-year on average and 53.9% were current smokers. Among them, 86.3% had willing to participate in lung cancer screening again. The average willingness to quit smoking among current smokers was 12.7% higher than before screening. In Lung-RADS reports, 10 (3.9%) were grade 3 and nine (3.5%) were grade 4. One participant was diagnosed as lung cancer.

Conclusion

The protocol developed by this study is assessed to be feasible to perform K-LUCAS in multicenter nationwide scale.

Vancouver Risk Calculator Compared with ACR Lung-RADS in Predicting Malignancy: Analysis of the National Lung Screening Trial

Purpose To compare the Vancouver risk calculator (VRC) with American College of Radiology (ACR) Lung Imaging Reporting and Data System (Lung-RADS) in predicting the risk of malignancy in the National Lung Screening Trial (NLST). Materials and Methods A total of 2813 patients with 4408 nodules (4078 solid, 330 subsolid) were available from the NLST for evaluation. Nodules were scored by using VRC with nine parameters (output was the percentage likelihood of malignancy; VRC threshold for malignancy likelihood set as greater than 5%) and Lung-RADS (output was category 2-4B; malignancy defined as category 4A or 4B; malignancy likelihood greater than 5%). Lung-RADS and VRC were compared for sensitivity, specificity, and accuracy for malignancy on a per-nodule and per-patient basis. Results Of 4408 total nodules, 100 of 4078 (2.5%) solid nodules were malignant and 10 of 330 (3%) subsolid nodules were malignant. On an overall per-nodule basis, the sensitivity, specificity, and accuracy for VRC and Lung-RADS were 93%, 90%, and 90% for VRC and 87%, 83%, and 83% for Lung-RADS, respectively (P = .077, P < .001, and P < .001, respectively). On a per-patient basis, the sensitivity, specificity, and accuracy for VRC and Lung-RADS were 93%, 85%, and 85% for VRC and 87%, 76%, and 76% for Lung-RADS, respectively (P = .077, P < .001, and P < .001, respectively). Conclusion The Vancouver risk calculator had superior overall accuracy than the Lung Imaging Reporting and Data System in predicting malignancy in the National Lung Screening Trial for total nodules, as well as on a per-patient basis. © RSNA, 2019 See also the editorial by Black in this issue.

Medical Care Costs Were Similar Across the Low-dose Computed Tomography and Chest X-Ray Arms of the National Lung Screening Trial Despite Different Rates of Significant Incidental Findings

BACKGROUND

The National Lung Screening Trial (NLST) reported lung cancer and all-cause mortality reductions for low-dose computed tomography (LDCT) versus chest x-ray (CXR) screening. Although LDCT lung screening has received a grade B from the United States Preventive Services Task Force and is a covered service under most health plans, concerns remain on the costs engendered by screening, and the impact of the high rate of significant incidental finding (SIF) detection on those costs.

METHODS

We linked American College of Radiology Imaging Network NLST and Medicare fee-for-service claims data for participants from 23 sites for 2002-2009. We performed participant-level analyses using generalized linear regression models to estimate the adjusted annual mean of the 3-year total medical costs per person in each study arm and within screen outcome categories (ever positive with abnormalities suspicious for lung cancer, always negative for abnormalities suspicious for lung cancer, but with SIFs, and always negative without SIFs).

RESULTS

The adjusted annual mean total per person costs were not significantly different between screening arms [LDCT, $11,029 (95% confidence interval, $10,107-$11,951); CXR, $10,905 (95% confidence interval, $10,059-$11,751)], despite higher proportions of individuals with SIFs in the LDCT versus the CXR arm (18% vs. 4%; P<0.0001).

CONCLUSIONS

We found little difference in total annual per person costs between LDCT-screened and CXR-screened Medicare participants, despite the higher number of SIFs in the LDCT arm of the study.

Persisting new nodules in incidence rounds of the NELSON CT lung cancer screening study

BACKGROUND

The US guidelines recommend low-dose CT (LDCT) lung cancer screening for high-risk individuals. New solid nodules after baseline screening are common and have a high lung cancer probability. Currently, no evidence exists concerning the risk stratification of non-resolving new solid nodules at first LDCT screening after initial detection.

METHODS

In the Dutch-Belgian Randomized Lung Cancer Screening (NELSON) trial, 7295 participants underwent the second and 6922 participants the third screening round. We included participants with solid nodules that were registered as new or <15 mm³ (study detection limit) at previous screens and received additional screening after initial detection, thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500 mm³).

RESULTS

Overall, 680 participants with 1020 low-risk and intermediate-risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a non-resolving new solid nodule, of whom 25 (7%) were diagnosed with lung cancer. At first screening after initial detection, volume doubling time (VDT), volume, and VDT combined with a predefined ≥200 mm³ volume cut-off had high discrimination for lung cancer (VDT, area under the curve (AUC): 0.913; volume, AUC: 0.875; VDT and ≥200 mm³ combination, AUC: 0.939). Classifying a new solid nodule with either ≤590 days VDT or ≥200 mm³ volume positive provided 100% sensitivity, 84% specificity and 27% positive predictive value for lung cancer.

CONCLUSIONS

More than half of new low-risk and intermediate-risk solid nodules in LDCT lung cancer screening resolve. At follow-up, growth assessment potentially combined with a volume limit can be used for risk stratification.

TRIAL REGISTRATION NUMBER

ISRCTN63545820; pre-results.

Evaluating the performance of a deep learning-based computer-aided diagnosis (DL-CAD) system for detecting and characterizing lung nodules: Comparison with the performance of double reading by radiologists

Background

The study was conducted to evaluate the performance of a state‐of‐the‐art commercial deep learning‐based computer‐aided diagnosis (DL‐CAD) system for detecting and characterizing pulmonary nodules.

Methods

Pulmonary nodules in 346 healthy subjects (male: female = 221:125, mean age 51 years) from a lung cancer screening program conducted from March to November 2017 were screened using a DL‐CAD system and double reading independently, and their performance in nodule detection and characterization were evaluated. An expert panel combined the results of the DL‐CAD system and double reading as the reference standard.

Results

The DL‐CAD system showed a higher detection rate than double reading, regardless of nodule size (86.2% vs. 79.2%; P < 0.001): nodules ≥ 5 mm (96.5% vs. 88.0%; P = 0.008); nodules < 5 mm (84.3% vs. 77.5%; P < 0.001). However, the false positive rate (per computed tomography scan) of the DL‐CAD system (1.53, 529/346) was considerably higher than that of double reading (0.13, 44/346; P < 0.001). Regarding nodule characterization, the sensitivity and specificity of the DL‐CAD system for distinguishing solid nodules > 5 mm (90.3% and 100.0%, respectively) and ground‐glass nodules (100.0% and 96.1%, respectively) were close to that of double reading, but dropped to 55.5% and 93%, respectively, when discriminating part solid nodules.

Conclusion

Our DL‐CAD system detected significantly more nodules than double reading. In the future, false positive findings should be further reduced and characterization accuracy improved.

Virtual bronchoscopic navigation as an aid to CT-guided transbronchial biopsy improves the diagnostic yield for small peripheral pulmonary lesions

BACKGROUND AND OBJECTIVE

Virtual bronchoscopic navigation (VBN) entails the provision of a virtual display of the bronchial routes that lead to small peripheral pulmonary lesions (PPL). It has been predicted that a combination of computed tomography (CT)-guided transbronchial biopsy (CT-TBB) with VBN might improve the diagnostic yield for small PPL. This study sought to investigate that prediction.

METHODS

A total of 100 patients with small PPL (<20 mm) were enrolled for CT-TBB and randomly allocated to either a VBN+ or VBN- group (50 subjects per group). Group results were then compared in terms of diagnostic yield, whole procedure time, times at which the first CT scan and biopsy were taken and the number of lung biopsy specimens retrieved.

RESULTS

The diagnostic yield for small PPL was significantly higher in the VBN+ group versus VBN- group (84% vs 58%, respectively (P = 0.013)), with no significant difference in (whole) examination time between groups (VBN+: 32:53 (32 min and 53 s) ± 12:01 vs VBN-: 33:06 ± 10:08 (P = NS)). However, the time periods between commencing the examination and either the first CT scan or first biopsy were significantly shorter for the VBN+ group, while the net biopsy time tended to be longer for this group with a significantly higher number of specimens collected (VBN+: 3.54 ± 1.07 specimens vs VBN-: 2.98 ± 1.06 specimens (P = 0.01)).

CONCLUSION

Combining VBN with CT-TBB significantly improved the diagnostic yield for small PPL.

Serum microRNAs improving the diagnostic accuracy in lung cancer presenting with pulmonary nodules

Background

MicroRNA (miRNA) is an approach for early diagnosing of cancer. We validated a panel of miRNAs (hsa-miR-199a-3p, hsa-miR-148a-3p, hsa-miR-210-3p, hsa-miR-378d and hsa-miR-138-5p) to aid early diagnosis of lung adenocarcinoma by blood test in lung cancer presenting with pulmonary nodules.

Methods

A total of 369 individuals who were detected pulmonary nodules by computed tomography (CT) scan were enrolled into this study. These patients included 274 pulmonary malignant or borderline lung diseases and 122 lung benign pulmonary nodules. When the lung nodules were detected by combining with CT scan, we got patient blood samples in 2 days. Patients' serum was collected within 2 days prior to miRNAs analyses. We performed miRNAs panel by reverse transcription-polymerase chain reaction (RT-PCR).

Results

The sensitivity of miRNAs panel was 34.0% and the specificity of miRNAs panel was 90.2%. In invasive adenocarcinoma, the sensitivity of miRNAs panel was 44.7%. The overall false positive rate of CT imaging for nodules and glass ground nodules (GGNs) was 33.1%. When miRNAs panel test positive patients combined with the nodule size, the false positive rate was decreased to 3.2%.

Conclusions

The greatest impact of using the miRNAs panel CT scan was decreasing the false positive. miRNAs panel can improve the diagnosis of lung cancer presenting with nodules combined with CT.

Low-dose computed tomography (LDCT) versus other cancer screenings in early diagnosis of lung cancer: A meta-analysis

BACKGROUND

Lung cancer is the leading cause of cancer mortality worldwide. It is often diagnosed at an advanced stage when treatment is no longer possible. Early population-based screening may provide an opportunity for early diagnosis and reduce mortality rates.

METHODS

Study characteristics were collected and outcome data (lung cancer diagnosis and mortality) were extracted and used for meta-analysis. Statistical analyses were performed using OpenMetaAnalyst-0.1503 software. The odds ratio (OR) and 95% confidence interval (CI) were used to assess LDCT compared to other screening methods under the random-effects model. The I2 statistic was used to assess heterogeneity.

RESULTS

Pooling data from 4 studies (64,129 patients) showed a higher incidence of diagnosed lung cancer with LDCT screening (OR = 1.86, 95% CI: 1.02-3.37), compared to other screening tools. However, no significant difference (OR = 1.13, 95% CI: 0.78-1.64) was found in lung cancer mortality between both groups.

CONCLUSIONS

Although no significant difference was found between LDCT and other control groups in terms of lung cancer mortality, this meta-analysis suggests an increased diagnosis of lung cancer with LDCT as compared with other screening modalities. This meta-analysis displays the potential but also the limitations of LDCT for early lung cancer detection.

The role of plasma miRNAs in the diagnosis of pulmonary nodules

Background

In this study, we aimed to assess the clinical utility of detection of plasma microRNAs (miRNAs) in the diagnosis of pulmonary nodules.

Methods

Fifty-seven patients with pulmonary nodules who had undergone surgery were enrolled in our study from July 2016 to July 2017 at Sun Yat-sen University Cancer Center. We measured the expression levels of 12 miRNAs (miRNA-17, -146a, -200b, -182, -155, -221, -205, -126, -7, -21, -145, and miRNA-210) in plasma samples of 57 patients, including 15 benign pulmonary nodules patients and 42 malignant pulmonary nodules patients. The levels of these miRNAs were detected by Real-time quantitative polymerase chain reaction (RT-PCR). The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of plasma miRNAs for non-small cell lung cancer (NSCLC).

Results

The expression levels of plasma miRNA-17, -146a, -200b, -182, -155, -221, -205, -126, -7, -21, -145, and miRNA-210 are not associated with gender, age, pTNM stage, differentiation grade. The levels of miRNA-17, -146a, -200b, -182, -221, -205, -7, -21, -145, and miRNA-210 in NSCLC patients are significantly higher than those in benign pulmonary nodules patients (P<0.05). However, there are no significant differences for the expression levels of miRNA-155 and miRNA-126. For diagnosing NSCLC, the sensitivity and specificity was 66.7% and 80.0% for miRNA-17, 54.8% and 86.7% for miRNA-146a, 64.3% and 86.7% for miRNA-200b, 83.3% and 73.3% for miRNA-182, 54.8% and 80.0% for miRNA-221, 73.8% and 80.0% for miRNA-205, 78.6% and 73.3% for miRNA-7, 78.6% and 60.0% for miRNA-21, 78.6% and 73.3% for miRNA-145, 76.2% and 73.3% for miRNA-210.

Conclusions

Plasma miRNAs (miRNA-17, -146a, -200b, -182, -221, -205, -7, -21, -145, and miRNA-210) have relatively high sensitivity and specificity for the diagnosis of NSCLC. These plasma miRNAs may be the potential biomarkers for early diagnosis of lung cancer.

Lung cancer screening: nodule identification and characterization

The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.