A population-based cohort study to evaluate the effectiveness of lung cancer screening using low-dose CT in Hitachi city, Japan

Effects of low dose computed tomography (LDCT) on lung cancer screening on incidence and mortality in regions with high tuberculosis prevalence: A systematic review

BACKGROUND

Lung cancer screening (LCS) using low-dose computed tomography (LDCT) is a strategy for early-stage diagnosis. The implementation of LDCT screening in countries with a high prevalence/incidence of tuberculosis (TB) is controversial. This systematic review and meta-analysis aim to identify whether LCS using LDCT increases early-stage diagnosis and decreases mortality, as well as the false-positive rate, in regions with a high prevalence of TB.

METHODS/DESIGN

Studies were identified by searching BVS, PUBMED, EMBASE, and SCOPUS. RCT and cohort studies (CS) that show the effects of LDCT in LC screening on mortality and secondary outcomes were eligible. Two independent reviewers evaluated eligibility and a third judged disagreements. We used the Systematic Review Data Repository (SRDR+) to extract the metadata and record decisions. The analyses were stratified by study design and incidence of TB. We used the Cochrane "Risk of bias" assessment tool.

RESULTS

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) were used. Thirty-seven papers were included, referring to 22 studies (10 RCTs and 12 cohorts). Few studies were from regions with a high incidence of TB (One RCT and four cohorts). Nonetheless, the evidence is compatible with European and USA studies. RCTs and CS also had consistent results. There is an increase in early-stage (I-II) diagnoses and reduced LC mortality in the LCDT arm compared to the control. Although false-positive rates varied, they stayed within the 20 to 30% range.

DISCUSSION

This is the first meta-analysis of LDCT for LCS focused on its benefits in regions with an increased incidence/prevalence of TB. Although the specificity of Lung-RADS was higher in participants without TB sequelae than in those with TB sequelae, our findings point out that the difference does not invalidate implementing LDCT LCS in these regions.

TRIAL REGISTRATION

Systematic review registration Systematic review registration PROSPERO CRD42022309581.

Incidental diagnosis of lung cancer on chest CT scan performed for suspected or documented COVID-19 infection

CONTEXT

Recent studies have shown a benefit of chest computed tomography (CT scan) in lung cancer screening. The COVID-19 pandemic has led to many chest CT scan performed on a large population. The objective of this study was to describe the incidence and characteristics of lung cancer detected on chest CT scan, outside the framework of a clinical trial, for a suspected or documented COVID-19 infection.

METHODS

We conducted a multicenter study, carried out from the analysis of data from the prospective COVID-19 database of the Clinical Data Warehouse of the Greater Paris University Hospitals (AP-HP). We identified the patients who had been diagnosed with a lung cancer, due to a chest CT scan done for a suspected or confirmed COVID-19 infection. The study period was limited to the first two epidemic lockdowns: (03/01/20 - 05/31/20) and (10/10/20 - 11/30/20).

RESULTS

Over the study period, 24 390 patients had at least one chest CT scan. Among them, 72 lung cancer diagnoses were made (incidence 0.30 %; median age 67.4 years old, 50.0 % current smokers, 55.6 % adenocarcinoma). Half of the lung cancer patients (n = 36) did not meet the National Lung Screening Trial inclusion criteria. Twenty-six patients (36.1 %) were diagnosed at an early stage, 25 (34.7 %) of whom received radical curative treatment. Twenty-six patients died during the follow-up (36.1 %) but none in early stages. The median overall survival in lung cancer patients was 693 days [532 - NA].

CONCLUSIONS

A large-scale chest CT scan strategy for suspected or documented COVID-19 infection has allowed a significant proportion of early-stage lung cancer diagnosis, all of which have benefited from curative treatment.

Lung adenocarcinoma patients with ROS1-rearranged tumors by sex and smoking intensity

Background

ROS1 rearrangements (ROS1+) define a distinct molecular subset of lung adenocarcinomas. ROS1 + tumors are known to occur more in never-smokers, but the frequency and outcome of ROS1 positivity by sex and smoking intensity are not clearly documented.

Patients and methods

This patient cohort study included all never- (<100 cigarettes lifetime) and light- (100 cigarettes-20 pack-years) smokers, and a sample of heavy-smokers. ROS1 + rates by sex and smoking intensity were compared within and beyond our study. Survival outcomes were analyzed using Kaplan-Meier curves and Cox proportional hazards models.

Results

Of the 571 total patients, ROS1 + was detected in 24 (4.2%): 6.4% in men and 3.0% in women; 5.1% in never-, 5.7% in light-, and 1.8% in heavy-smokers (P=0.05). Among the 209 stage IIIB-IV patients, men had much higher ROS1 + rate (11.1%) not only than women (1.7%, P=0.004) in our study, but also than men (0.4%-1.8%) in 8 published studies (Ps = 0.0019-0.0001). ROS1+ rates were similar between never- (9.3%) and light-smokers (8.1%) and significantly lower in heavy-smokers (1.2%, P=0.017), a finding confirmed by 6 published studies (Ps = 0.041-0.0001). Overall survival of ROS1 + patients were significantly better than the ROS1- (P=0.023) mainly due to targeted therapy. Among patients who exhibited resistance to crizotinib, follow-up treatment of entrectinib and lorlatinib showed remarkable survival benefits.

Conclusions

The ROS1 + rates were higher in men than in women, and similar in never- and light-smokers, more pronounced in stage IIIB-IV patients. Newer-generation ALK/ROS1-targeted drugs showed efficacy in a cohort of crizotinib resistant ROS1 + patients. These results, when validated, could assist efficiently accruing ROS1 + patients.

Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array

INTRODUCTION

Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning.

METHODS

Patients who underwent lung cancer surgery at an academic medical center, Japan, between November 2018 and November 2019 were included. Exhaled breaths were collected just before surgery and about one month after surgery, and analyzed using an MSS array. The array had 12 channels with various receptor materials and provided 12 waveforms from a single exhaled breath sample. Boxplots of the perioperative changes in the expiratory waveforms of each channel were generated and Mann-Whitney U test were performed. An optimal lung cancer prediction model was created and validated using machine learning.

RESULTS

Sixty-six patients were enrolled of whom 57 were included in the analysis. Through the comprehensive analysis of the entire dataset, a prototype model for predicting lung cancer was created from the combination of array five channels. The optimal accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.809, 0.830, 0.807, 0.806, and 0.812, respectively.

CONCLUSION

Breath analysis with MSS and machine learning with careful control of both samples and measurement conditions provided a lung cancer prediction model, demonstrating its capacity for non-invasive screening of lung cancer.

Lung Cancer Screening in Asia: An Expert Consensus Report

INTRODUCTION

The incidence and mortality of lung cancer are highest in Asia compared with Europe and USA, with the incidence and mortality rates being 34.4 and 28.1 per 100,000 respectively in East Asia. Diagnosing lung cancer at early stages makes the disease amenable to curative treatment and reduces mortality. In some areas in Asia, limited availability of robust diagnostic tools and treatment modalities, along with variations in specific health care investment and policies, make it necessary to have a more specific approach for screening, early detection, diagnosis, and treatment of patients with lung cancer in Asia compared with the West.

METHOD

A group of 19 advisors across different specialties from 11 Asian countries, met on a virtual Steering Committee meeting, to discuss and recommend the most affordable and accessible lung cancer screening modalities and their implementation, for the Asian population.

RESULTS

Significant risk factors identified for lung cancer in smokers in Asia include age 50 to 75 years and smoking history of more than or equal to 20 pack-years. Family history is the most common risk factor for nonsmokers. Low-dose computed tomography screening is recommended once a year for patients with screening-detected abnormality and persistent exposure to risk factors. However, for high-risk heavy smokers and nonsmokers with risk factors, reassessment scans are recommended at an initial interval of 6 to 12 months with subsequent lengthening of reassessment intervals, and it should be stopped in patients more than 80 years of age or are unable or unwilling to undergo curative treatment.

CONCLUSIONS

Asian countries face several challenges in implementing low-dose computed tomography screening, such as economic limitations, lack of efforts for early detection, and lack of specific government programs. Various strategies are suggested to overcome these challenges in Asia.

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT

Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung function remains unclear. Purpose To develop a deep learning algorithm to predict pulmonary function with low-dose CT images in participants using health screening services. Materials and Methods In this retrospective study, participants underwent health screening with same-day low-dose CT and pulmonary function testing with spirometry at a university affiliated tertiary referral general hospital between January 2015 and December 2018. The data set was split into a development set (model training, validation, and internal test sets) and temporally independent test set according to first visit year. A convolutional neural network was trained to predict the forced expiratory volume in the first second of expiration (FEV₁) and forced vital capacity (FVC) from low-dose CT. The mean absolute error and concordance correlation coefficient (CCC) were used to evaluate agreement between spirometry as the reference standard and deep-learning prediction as the index test. FVC and FEV₁ percent predicted (hereafter, FVC% and FEV₁%) values less than 80% and percent of FVC exhaled in first second (hereafter, FEV₁/FVC) less than 70% were used to classify participants at high risk. Results A total of 16 148 participants were included (mean age, 55 years ± 10 [SD]; 10 981 men) and divided into a development set (n = 13 428) and temporally independent test set (n = 2720). In the temporally independent test set, the mean absolute error and CCC were 0.22 L and 0.94, respectively, for FVC and 0.22 L and 0.91 for FEV₁. For the prediction of the respiratory high-risk group, FVC%, FEV₁%, and FEV₁/FVC had respective accuracies of 89.6% (2436 of 2720 participants; 95% CI: 88.4, 90.7), 85.9% (2337 of 2720 participants; 95% CI: 84.6, 87.2), and 90.2% (2453 of 2720 participants; 95% CI: 89.1, 91.3) in the same testing data set. The sensitivities were 61.6% (242 of 393 participants; 95% CI: 59.7, 63.4), 46.9% (226 of 482 participants; 95% CI: 45.0, 48.8), and 36.1% (91 of 252 participants; 95% CI: 34.3, 37.9), respectively. Conclusion A deep learning model applied to volumetric chest CT predicted pulmonary function with relatively good performance. © RSNA, 2023 Supplemental material is available for this article.

Stage Shift Improves Lung Cancer Survival: Real-World Evidence

INTRODUCTION

Lung cancer is the global leading cause of cancer death. Taiwan initiated several health policies including smoking cessation, precision therapy, and low-dose computed tomography (LDCT) screening in 1997. We aimed to investigate the effect of public policies on lung cancer survival.

METHODS

We retrieved the nationwide cancer registry from the Ministry of Health and Welfare to evaluate the smoking prevalence and lung cancer incidence and mortality from 1994 to 2020. We also conducted a retrospective analysis of clinical characteristics and survival on 17,298 patients with lung cancer from 2006 to 2019 using the National Taiwan University Hospital database.

RESULTS

Taiwan initiated an anti-smoking campaign in 1997, reimbursed tyrosine kinase inhibitors since 2004, and conducted an LDCT screening trial in 2015. Lung cancer incidence keeps rising but the annual percent change in mortality rate gradually decreased from 0.41% to -2.41%. The National Taiwan University Hospital data revealed that the 5-year survival substantially improved from 22.1% in 2006 to 2011 to 54.9% in 2015 to 2020. Improvement was observed in all stages, especially late stages (stage III: from 17.2% to 35.2%; stage IV: from 7.9% to 16.5%). Furthermore, a remarkable shift in cancer stage was observed (stage 0, I, and IIincreased from 19.3% to 62.8%, and stage III and IV decreased from 70.9% to 33.8%). The prominent improvement in survival was primarily driven by the stage shift from advanced to localized, potentially curable disease.

CONCLUSIONS

This real-world evidence suggested an association between improved survival and LDCT screening and the diagnostic shift from late to early-stage of lung cancer, highlighting the importance of early detection for lung cancer control.

Opportunistic osteoporosis screening using chest CT with artificial intelligence

Osteoporosis has a high incidence and a low detection rate. If it is not detected in time, it will cause osteoporotic fracture and other serious consequences. This study showed that the attenuation values of vertebrae on chest CT could be used for opportunistic screening of osteoporosis. This will be beneficial to improve the detection rate of osteoporosis and reduce the incidence of adverse events caused by osteoporosis.

INTRODUCTION

To explore the value of the attenuation values of all thoracic vertebrae and the first lumbar vertebra measured by artificial intelligence on non-enhanced chest CT to do osteoporosis screening.

METHODS

On base of images of chest CT, using artificial intelligence (AI) to measure the attenuation values (HU) of all thoracic and the first vertebrae of patients who underwent CT examination for lung cancer screening and dual-energy X-ray absorptiometry (DXA) examination during the same period. The patients were divided into three groups: normal group, osteopenia group, and osteoporosis group according to the results of DXA. Clinical baseline data and attenuation values were compared among the three groups. The correlation between attenuation values and BMD values was analyzed, and the predictive ability and diagnostic efficacy of attenuation values of thoracic and first lumbar vertebrae on osteopenia or osteoporosis risk were further evaluated.

RESULTS

CT values of each thoracic vertebrae and the first lumbar vertebrae decreased with age, especially in menopausal women and presented high predictive ability and diagnostic efficacy for osteopenia or osteoporosis. After clinical data correction, with every 10 HU increase of CT values, the risk of osteopenia or osteoporosis decreased by 32 ~ 44% and 61 ~ 80%, respectively. And the combined diagnostic efficacy of all thoracic vertebrae was higher than that of a single vertebra. The AUC of recognizing osteopenia or osteoporosis from normal group was 0.831and 0.972, respectively.

CONCLUSIONS

The routine chest CT with AI is of great value in opportunistic screening for osteopenia or osteoporosis, which can quickly screen the population at high risk of osteoporosis without increasing radiation dose, thus reducing the incidence of osteoporotic fracture.

Advances in lung cancer screening and early detection

Lung cancer is associated with a heavy cancer-related burden in terms of patients' physical and mental health worldwide. Two randomized controlled trials, the US-National Lung Screening Trial (NLST) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON), indicated that low-dose CT (LDCT) screening results in a statistically significant decrease in mortality in patients with lung cancer, LDCT has become the standard approach for lung cancer screening. However, many issues in lung cancer screening remain unresolved, such as the screening criteria, high false-positive rate, and radiation exposure. This review first summarizes recent studies on lung cancer screening from the US, Europe, and Asia, and discusses risk-based selection for screening and the related issues. Second, an overview of novel techniques for the differential diagnosis of pulmonary nodules, including artificial intelligence and molecular biomarker-based screening, is presented. Third, current explorations of strategies for suspected malignancy are summarized. Overall, this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.

European lung cancer screening: valuable trial evidence for optimal practice implementation

Lung cancer screening (LCS) by low-dose computed tomography is a strategy for secondary prevention of lung cancer. In the last two decades, LCS trials showed several options to practice secondary prevention in association with primary prevention, however, the translation from trial to practice is everything but simple. In 2020, the European Society of Radiology and European Respiratory Society published their joint statement paper on LCS. This commentary aims to provide the readership with detailed description about hurdles and potential solutions that could be encountered in the practice of LCS.

Radiomics in Early Lung Cancer Diagnosis: From Diagnosis to Clinical Decision Support and Education

Lung cancer is the most frequent cause of cancer-related death around the world. With the recent introduction of low-dose lung computed tomography for lung cancer screening, there has been an increasing number of smoking- and non-smoking-related lung cancer cases worldwide that are manifesting with subsolid nodules, especially in Asian populations. However, the pros and cons of lung cancer screening also follow the implementation of lung cancer screening programs. Here, we review the literature related to radiomics for early lung cancer diagnosis. There are four main radiomics applications: the classification of lung nodules as being malignant/benign; determining the degree of invasiveness of the lung adenocarcinoma; histopathologic subtyping; and prognostication in lung cancer prediction models. In conclusion, radiomics offers great potential to improve diagnosis and personalized risk stratification in early lung cancer diagnosis through patient–doctor cooperation and shared decision making.

Earlier diagnosis of lung cancer

The purpose of this article is to review options for more rapid diagnosis of lung cancer at an earlier stage, thereby improving survival. These options include screening, allowing general practitioners to refer patients directly to low-dose computed tomography scan instead of a chest X-ray and the abolition of the "visitation filter", i.e. hospital doctors' ability to reject referrals from general practitioners without prior discussion with the referring doctor.

Association of Computed Tomographic Screening Promotion With Lung Cancer Overdiagnosis Among Asian Women

IMPORTANCE

As smoking continues to decline in many developed countries, the proportion of lung cancers in nonsmokers will rise. This shift may create substantial pressure to further expand lung cancer screening to lower-risk groups.

OBJECTIVE

To determine the association of lung cancer incidence with the promotion of screening in a largely nonsmoking population.

DESIGN, SETTING, AND PARTICIPANTS

This population-based ecological cohort study of stage-specific lung cancer incidence used the Taiwan Cancer Registry to identify women diagnosed with lung cancer from January 1, 2004, to December 31, 2018. Smoking prevalence among Taiwanese women has been less than 5% since 1980. Data were analyzed from February 13, 2020, to November 10, 2021.

EXPOSURES

Low-dose computed tomography (LDCT) screening for lung cancer, initiated during the early 2000s.

MAIN OUTCOMES AND MEASURES

Change in stage-specific lung cancer incidence. An effective cancer screening program will not only increase the incidence of early-stage cancer but also decrease the incidence of cancer presenting at a late stage.

RESULTS

A total of 57 898 women were diagnosed with lung cancer in a population of approximately 12 million Taiwanese women. After the introduction of LDCT screening, the incidence of early-stage (stages 0-I) lung cancer in women increased more than 6-fold, from 2.3 to 14.4 per 100 000 population (absolute difference, 12.1 [95% CI, 11.3-12.8]) from 2004 to 2018. There was no change, however, in the incidence of late-stage (stages II-IV) lung cancer, from 18.7 to 19.3 per 100 000 (absolute difference, 0.6 [95% CI, -0.5 to 1.7]). Because the additional 12.1 per 100 000 early-stage cancers were not accompanied by a concomitant decline in late-stage cancers, virtually all the additional cancers detected represent overdiagnosis. Despite stable mortality, 5-year survival more than doubled from 2004 to 2013, from 18% to 40%, which is arguably the highest lung cancer survival rate in the world.

CONCLUSIONS AND RELEVANCE

This population-based ecological cohort study found that low-dose computed tomographic screening of mostly nonsmoking Asian women was associated with considerable lung cancer overdiagnosis. Five-year survival is biased by the increased LDCT detection of indolent early-stage lung cancers. Unless randomized trials can demonstrate some value to low-risk groups, LDCT screening should remain targeted only to heavy smokers.

Descriptive study of chest x-ray examination in mandatory annual health examinations at the workplace in Japan

The utility of chest x-ray examination (CXR) in mandatory annual health examinations for occupational health is debatable in Japan. This study aimed to provide basic data to consider future policies for mandatory annual health examinations in the workplace. A nationwide descriptive survey was performed to determine the rate of detection of tuberculosis, lung cancer, and other diseases through CXR in organizations associated with National Federation of Industrial Health Association. The rate of finding on CXR conducted during annual health examinations in FY2016 was evaluated. Data regarding diagnosis based on follow-up examination findings were obtained and compared with the national statistics. In addition, CXR findings were compared with the results of low-dose lung computed tomography performed at the Hitachi Health Care Center. From 121 surveyed institutions, 88 institutions with 8,669,403 workers were included. For all ages, 1.0% of examinees required follow-up examination. Among 4,764,985 workers with diagnosis data, the tuberculosis detection rate was 1.8–5.3 per 100,000 persons. For Lung cancer, 3,688,396 workers were surveyed, and 334 positive cases were detected. The lung cancer detection rate using CXR was 9.1–24.4 per 100,000 persons. From 164 cases with information regarding the clinical stage, 72 (43.9%) had Stage I lung cancer. From 40,045 workers who underwent low-dose computed tomography multiple times, 31 lung cancer cases, all with Stage I disease, were detected (detection rate: 77.4 per 100,000 persons). Our findings suggest that CXR plays a little role in the detection of active tuberculosis. With regard to LC screening, the detection rate of LC by CXR was lower, approximately 50%, than the expected rate (41.0 per 100,000 persons) of LC morbidity based on the age–sex distribution of this study population. However, the role of CXR for LC screening cannot be mentioned based on this result, because assessment of mortality reduction is essential to evaluate the role.

Impact of Smoking Status on Lung Cancer Characteristics and Mortality Rates between Screened and Non-Screened Lung Cancer Cohorts: Real-World Knowledge Translation and Education

This was a retrospective hospital-based cohort study of participants diagnosed with lung cancer in the lung cancer register database, and our goal was to evaluate the impact of smoking and screening status on lung cancer characteristics and clinical outcomes. According to the hospital-based lung cancer register database, a total of 2883 lung cancers were diagnosed in 2883 patients between January 2007 and September 2017, which were divided into four groups according to smoking and screening status. A comparison was performed in terms of clinical characteristics and outcomes of lung cancer between the four groups. For non-smokers, age, gender, screened status, tumor size, targeted therapy, and curative surgery were independent prognostic factors of overall survival for lung cancer subjects. However, screened status and gender were not significant prognostic factors for lung cancer survival in smokers with lung cancer. For the non-smoker group, about 4.9% of lung cancer subjects (N = 81) were detected by screening. However, only 0.97% of lung cancer subjects (N = 12) were detected by screening in smokers. This could be attributed to smokers' negative attitudes and low socioeconomic status preventing LDCT lung cancer screening. In summary, our real-world data suggest that effectively encouraging smokers to be more willing to participate in lung cancer screening programs with screening allowance and educational training in the future is an important issue.

Results of 10-year mobile low-dose computed tomography screenings for lung cancer in Shimane, Japan

BACKGROUND

Some randomized controlled trials have evaluated the effects of low-dose computed tomography (CT) screening on lung cancer mortality in heavy smokers. Based on the results of those trials, our CT screening program recommended screening for people aged ≥40 years with a history of smoking. This retrospective study aimed to verify the validity of our CT screening program and elucidate the current state of CT screening program.

METHODS

We retrospectively examined lung cancer detection in 25,189 participants who underwent chest CT screening by a mobile low-dose CT screening unit in the 10-year period from April 2009 to March 2019. Participants were recruited at Japan Agricultural Cooperatives (JA) Shimane Kouseiren. Participants requested CT screening for lung cancer. CT images were read by two pulmonologists.

RESULTS

Lung cancer was identified in 82 of the 25,189 participants over 10 years, an overall lung cancer detection rate (percentage of lung cancers detected among all participants) of 0.33%. Lung cancer among never smokers accounted for 54.9% of the detected cases. The lung cancer detection rate was similar for smokers versus never smokers. The stage IA detection rate (percentage of stage IA lung cancers among all lung cancers detected) was 62%, while the stage Ⅳ detection rate was 10%.

CONCLUSIONS

Chest CT detected lung cancer in never smokers as well as current or former smokers. Our CT screening program was not effective for never smokers; thus, further study of the effectiveness of CT screening in never smokers is needed.

Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement

Purpose To compare the inter- and intraobserver agreement and reading times achieved when assigning Lung Imaging Reporting and Data System (Lung-RADS) categories to baseline and follow-up lung cancer screening studies by using a dedicated CT lung screening viewer with integrated nodule detection and volumetric support with those achieved by using a standard picture archiving and communication system (PACS)-like viewer. Materials and Methods Data were obtained from the National Lung Screening Trial (NLST). By using data recorded by NLST radiologists, scans were assigned to Lung-RADS categories. For each Lung-RADS category (1 or 2, 3, 4A, and 4B), 40 CT scans (20 baseline scans and 20 follow-up scans) were randomly selected for 160 participants (median age, 61 years; interquartile range, 58-66 years; 61 women) in total. Seven blinded observers independently read all CT scans twice in a randomized order with a 2-week washout period: once by using the standard PACS-like viewer and once by using the dedicated viewer. Observers were asked to assign a Lung-RADS category to each scan and indicate the risk-dominant nodule. Inter- and intraobserver agreement was analyzed by using Fleiss κ values and Cohen weighted κ values, respectively. Reading times were compared by using a Wilcoxon signed rank test. Results The interobserver agreement was moderate for the standard viewer and substantial for the dedicated viewer, with Fleiss κ values of 0.58 (95% CI: 0.55, 0.60) and 0.66 (95% CI: 0.64, 0.68), respectively. The intraobserver agreement was substantial, with a mean Cohen weighted κ value of 0.67. The median reading time was significantly reduced from 160 seconds with the standard viewer to 86 seconds with the dedicated viewer (P < .001). Conclusion Lung-RADS interobserver agreement increased from moderate to substantial when using the dedicated CT lung screening viewer. The median reading time was substantially reduced when scans were read by using the dedicated CT lung screening viewer. Keywords: CT, Thorax, Lung, Computer Applications-Detection/Diagnosis, Observer Performance, Technology Assessment Supplemental material is available for this article. © RSNA, 2021.

Combining pulmonary and cardiac computed tomography biomarkers for disease-specific risk modelling in lung cancer screening

OBJECTIVES

Combined assessment of cardiovascular disease (CVD), COPD and lung cancer may improve the effectiveness of lung cancer screening in smokers. The aims were to derive and assess risk models for predicting lung cancer incidence, CVD mortality and COPD mortality by combining quantitative computed tomography (CT) measures from each disease, and to quantify the added predictive benefit of self-reported patient characteristics given the availability of a CT scan.

METHODS

A survey model (patient characteristics only), CT model (CT information only) and final model (all variables) were derived for each outcome using parsimonious Cox regression on a sample from the National Lung Screening Trial (n=15 000). Validation was performed using Multicentric Italian Lung Detection data (n=2287). Time-dependent measures of model discrimination and calibration are reported.

RESULTS

Age, mean lung density, emphysema score, bronchial wall thickness and aorta calcium volume are variables that contributed to all final models. Nodule features were crucial for lung cancer incidence predictions but did not contribute to CVD and COPD mortality prediction. In the derivation cohort, the lung cancer incidence CT model had a 5-year area under the receiver operating characteristic curve of 82.5% (95% CI 80.9-84.0%), significantly inferior to that of the final model (84.0%, 82.6-85.5%). However, the addition of patient characteristics did not improve the lung cancer incidence model performance in the validation cohort (CT model 80.1%, 74.2-86.0%; final model 79.9%, 73.9-85.8%). Similarly, the final CVD mortality model outperformed the other two models in the derivation cohort (survey model 74.9%, 72.7-77.1%; CT model 76.3%, 74.1-78.5%; final model 79.1%, 77.0-81.2%), but not the validation cohort (survey model 74.8%, 62.2-87.5%; CT model 72.1%, 61.1-83.2%; final model 72.2%, 60.4-84.0%). Combining patient characteristics and CT measures provided the largest increase in accuracy for the COPD mortality final model (92.3%, 90.1-94.5%) compared to either other model individually (survey model 87.5%, 84.3-90.6%; CT model 87.9%, 84.8-91.0%), but no external validation was performed due to a very low event frequency.

CONCLUSIONS

CT measures of CVD and COPD provides small but reproducible improvements to nodule-based lung cancer risk prediction accuracy from 3 years onwards. Self-reported patient characteristics may not be of added predictive value when CT information is available.

Impact of low-dose computed tomography for lung cancer screening on lung cancer surgical volume: The urgent need in health workforce education and training

This study aimed to investigate the time trend variation in the surgical volume and prognostic outcome of patients with lung cancer after the gradual prolonged implementation of a low-dose computed tomography (LDCT) lung cancer screening program.Using the hospital-based cancer registry data on number of patients with lung cancer and deaths from 2008 to 2017, we conducted a retrospective study using a hospital-based cohort to investigate the relationship between changes in lung cancer surgical volume, the proportion of lung-sparing surgery, and prolonged prognostic outcomes after the gradual implementation of the LDCT lung cancer screening program in recent years.From 2008 to 2017, 3251 patients were diagnosed with lung cancer according to the hospital-based cancer registry. The 5-year mortality rate decreased gradually from 83.54% to 69.44% between 2008 and 2017. The volume of total lung cancer surgical procedures and proportion of lung-sparing surgery performed gradually increased significantly from 2008 to 2017, especially from 2014 to 2017 after implementation of a large volume of LDCT lung cancer screening examinations. In conclusion, our real-world data suggest that there will be an increase in cases of operable early-stage lung cancers, which in turn will increase the surgical volume and proportion of lung-sparing surgery, after the gradual implementation of the LDCT lung cancer screening program in recent years. These findings suggest the importance of a successful national policy regarding LDCT screening programs, regulation of shortage of thoracic surgeons, thoracic radiologist workforce training positions, and education programs.

A Novel Model-Based Questionnaire Based on Low-Dose CT Screening Data for Chronic Obstructive Pulmonary Disease Diagnosis in Shimane, Japan

Purpose

Although there have been many reports on the use of respiratory function tests and questionnaires for creating chronic obstructive pulmonary disease (COPD) questionnaires, there have been no reports on the effectiveness of questionnaires using computed tomography (CT) screening data. We aimed to validate the International Primary Care Airways Group (IPAG) questionnaire and to propose a novel COPD screening questionnaire based on the CT screening data of Japanese participants.

Patients and Methods

Low-dose CT screening was performed for early detection of lung cancer and COPD since 2009 in Shimane, Japan, and clinical information was collected using an original questionnaire that included all the IPAG questionnaire items and eight additional items (for eg, on dyspnea) during CT screening. Participants with emphysema, smoking history, and respiratory symptoms were instructed to undergo a respiratory function test. The participants with the forced expiratory volume in one second (FEV₁)/forced vital capacity (FVC) <0.7 on the respiratory function test were diagnosed with COPD, and 11,458 participants underwent CT screening from 2013 to 2016 and were enrolled and filtered using <22.5 pack-years. Data from 3252 participants were selected for the final analysis. The receiver operating characteristic curve determined the best cutoff points for discriminating patients with COPD. The efficacy of the questionnaire items was determined using logistic regression analysis.

Results

The best cutoff point for the Japanese IPAG questionnaire was 23. The logistic regression analysis revealed significant differences in the question items of "age", "pack-year", "cough", "phlegm", and "feeling of dyspnea". COPD-CT questionnaire was developed based on the CT screening data. The COPD predicted value was determined using the regression model obtained in this study.

Conclusion

The IPAG questionnaire had low specificity for discriminating COPD in Japanese patients. A novel questionnaire (COPD-CT) and the COPD predicted value based on the CT screening data was developed.

The International Association for the Study of Lung Cancer Early Lung Imaging Confederation

PURPOSE

To improve outcomes for lung cancer through low-dose computed tomography (LDCT) early lung cancer detection. The International Association for the Study of Lung Cancer is developing the Early Lung Imaging Confederation (ELIC) to serve as an open-source, international, universally accessible environment to analyze large collections of quality-controlled LDCT images and associated biomedical data for research and routine screening care.

METHODS

ELIC is an international confederation that allows access to efficiently analyze large numbers of high-quality computed tomography (CT) images with associated de-identified clinical information without moving primary imaging/clinical or imaging data from its local or regional site of origin. Rather, ELIC uses a cloud-based infrastructure to distribute analysis tools to the local site of the stored imaging and clinical data, thereby allowing for research and quality studies to proceed in a vendor-neutral, collaborative environment. ELIC’s hub-and-spoke architecture will be deployed to permit analysis of CT images and associated data in a secure environment, without any requirement to reveal the data itself (ie, privacy protecting). Identifiable data remain under local control, so the resulting environment complies with national regulations and mitigates against privacy or data disclosure risk.

RESULTS

The goal of pilot experiments is to connect image collections of LDCT scans that can be accurately analyzed in a fashion to support a global network using methodologies that can be readily scaled to accrued databases of sufficient size to develop and validate robust quantitative imaging tools.

CONCLUSION

This initiative can rapidly accelerate improvements to the multidisciplinary management of early, curable lung cancer and other major thoracic diseases (eg, coronary artery disease and chronic obstructive pulmonary disease) visualized on a screening LDCT scan. The addition of a facile, quantitative CT scanner image quality conformance process is a unique step toward improving the reliability of clinical decision support with CT screening worldwide.

Use of routine computed tomography scans for detecting osteoporosis in thoracolumbar vertebral bodies

OBJECTIVE

This study observed the distribution of CT attenuation values for T10-L3 vertebral bodies and derived the Hounsfield unit (HU) thresholds using the quantitative computed tomography (QCT) as a reference to predict osteoporosis and normal bone density.

METHODS

We included 482 subjects who were scheduled to undergo CT lung cancer screening and pulmonary nodule follow-up from May 2015 to February 2019. The subjects were scanned with the calibration phantom beneath the back while performing a chest CT scan. The volumetric bone mineral density (vBMD) and CT attenuation values of T10-L3 vertebral bodies were measured, and the correlation between the two measurements was analyzed. Receiver operator characteristic (ROC) curves were generated to determine diagnostic optimal thresholds.

RESULTS

A total of 2716 vertebral bodies of 457 participants were measured after exclusion screening. CT attenuation value of each plane's vertebral body showed a strong correlation with vBMD. The optimal threshold of > 141 HU was 93.5% sensitive and 86.1% specific for the recognition of normal BMD. The optimal threshold of < 102.4 HU was 96.9% specific and 82.1% sensitive for distinguishing osteoporosis from osteopenia and normal BMD. The average CT attenuation values of vertebral bodies with compressed and normal morphology were 108.9 ± 20.6 and 136.8 ± 32.2 HU, respectively.

CONCLUSION

Sagittal reconstruction of the thoracic vertebrae using routine thoracic CT image combined with CT attenuation value measurements of the spine is valuable for predicting bone mineral density in high-risk populations. The mean CT attenuation values of the vertebral bodies with vertebral compression appearance were lower than that of normal vertebral shape.

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).

Progress in cancer mortality, incidence, and survival: a global overview

Cancer mortality has declined over the last three decades in most high-income countries reflecting improvements in cancer prevention, diagnosis, and management. However, there are persisting and substantial differences in mortality, incidence, and survival worldwide. In order to provide an up-to-date overview of trends in mortality, incidence, and survival, we retrieved data from high-quality, population-based cancer registries for all cancers and 10 selected cancer sites in six high-income countries and the European Union. We computed age-standardized (world standard population) mortality and incidence rates, and applied joinpoint regression models. Mortality from all cancers and most common cancer sites has declined over the last 25 years, except for the pancreas and lung (in women). The patterns for incidence are less consistent between countries, except for a steady decrease in stomach cancer in both sexes and lung cancer in men. Survival for all cancers and the selected cancer sites increased in all countries, even if there is still a substantial variability. Although overall cancer death rates continue to decline, incidence rates have been levelling off among men and have been moderately increasing among women. These trends reflect changes in cancer risk factors, screening test use, diagnostic practices, and treatment advances. Many cancers can be prevented or treated effectively if they are diagnosed early. Population-based cancer incidence and mortality data can be used to focus efforts to decrease the cancer burden and regularly monitor progress towards cancer control goals.

Radiomics technology for identifying early-stage lung adenocarcinomas suitable for sublobar resection

OBJECTIVE

Early-stage lung adenocarcinomas that are suitable for limited resection to preserve lung function are difficult to identify. Using a radiomics approach, we investigated the efficiency of voxel-based histogram analysis of 3-dimensional computed tomography images for detecting less-invasive lesions suitable for sublobar resection.

METHODS

We retrospectively reviewed the medical records of 197 patients with pathological stage 0 or IA adenocarcinomas who underwent lung resection for primary lung cancer at our institution between January 2014 and June 2018. The lesions were categorized as either less invasive or invasive. We evaluated tumor volumes, solid volume percentages, mean computed tomography values, and variance, kurtosis, skewness, and entropy levels. We analyzed the relationships between these variables and pathologically less-invasive lesions and designed an optimal model for detecting less-invasive adenocarcinomas.

RESULTS

Univariate analysis revealed seven variables that differed significantly between less invasive (n = 71) and invasive (n = 141) lesions. A multivariate analysis revealed odds ratios for tumor volumes (0.64; 95% confidence interval (CI), 0.46-0.89; P = .008), solid volume percentages (0.96; 95% CI, 0.93-0.99; P = .024), skewness (3.45; 95% CI, 1.38-8.65; P = .008), and entropy levels (0.21; 95% CI, 0.07-0.58; P = .003). The area under the receiver operating characteristic curve was 0.90 (95% CI, 0.85-0.94) for the optimal model containing these 4 variables, with 85% sensitivity and 79% specificity.

CONCLUSIONS

Voxel-based histogram analysis of 3-dimensional computed tomography images accurately detected early-stage lung adenocarcinomas suitable for sublobar resection.

Differences in lung cancer characteristics and mortality rate between screened and non-screened cohorts

Screening programs for lung cancer aim to allow diagnosis at the early stage, and therefore the decline in mortality rates. Thus, the aim of this retrospective cohort study was to the comparison of screened and non-screened lung cancer in terms of lung cancer characteristics, overdiagnosis and survival rate. A retrospective study in which 2883 patients with 2883 lung cancer diagnosed according to the hospital-based lung cancer register database between 2007 and 2017. A comparison was performed in term of clinical characteristics and outcomes of lung cancer between the screened and non-screening patient groups. 2883 subjects were identified (93 screened and 2790 non-screened). Screened group patients were younger (59.91 ± 8.14 versus 67.58 ± 12.95; p < 0.0001), and were more likely to be female than non-screened group (61.3% versus 36.8%; p < 0.0001). The screened group showed significantly better outcomes in overall mortality than the non-screened group (10.75% versus 79.06%; <0.0001). In a Cox proportional hazard model, lung cancer in the screened group proved to be an independent prognostic factor in lung cancer subjects. Our findings point to the improved survival outcome in the screened group and might underline the benefit of low-dose computed tomography (LDCT) screening program in Asian populations with the high prevalence of non-smoking-related lung cancer. Further study aimed at the LDCT mass screening program targeting at light smokers and non-smoker outside of existing screening criteria is warranted.

A simulation study of the effect of lung cancer screening in China, Japan, Singapore, and South Korea

More than 50% of the world's lung cancer cases occur in Asia and more than 20% of cancer deaths in Asia are attributable to lung cancer. The U.S. National Lung Screening Trial has shown that lung cancer screening with computed tomography (CT) can reduce lung cancer deaths. Using the Lung Cancer Policy Model-Asia (LCPM-Asia), we estimated the potential mortality reduction achievable through the implementation of CT-based lung cancer screening in China, Japan, Singapore, and South Korea. The LCPM-Asia was calibrated to the smoking prevalence of each of the aforementioned countries based on published national surveys and to lung cancer mortality rates from the World Health Organization. The calibrated LCPM-Asia was then used to simulate lung cancer deaths under screening and no-screening scenarios for the four countries. Using screening eligibility criteria recommended by the U.S. Centers for Medicare & Medicaid Services (CMS), which are based on age and smoking history, we estimated the lung cancer mortality reduction from screening through year 2040. By 2040, lung cancer screening would result in 91,362 life-years gained and 4.74% mortality reduction in South Korea; 290,325 life-years gained and 4.33% mortality reduction in Japan; 3,014,215 life-years gained and 4.22% mortality reduction in China; and 8,118 life-years gained and 3.76% mortality reduction in Singapore. As for mortality reduction by smoker type, current smokers would have the greatest mortality reduction in each country, ranging from 5.56% in Japan to 6.86% in Singapore. Among the four countries, lung cancer screening under CMS eligibility criteria was most effective in South Korea and least effective in Singapore. Singapore's low smoking prevalence and South Korea's aging population and higher smoking prevalence may partially explain the discrepancy in effectiveness. CT screening was shown to be promising as a means of reducing lung cancer mortality in the four countries.