Diagnosis of benign and malignant peripheral lung lesions based on a feature model constructed by the random forest algorithm for grayscale and contrast-enhanced ultrasound

Rationale and objectives

To construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value.

Materials and methods

We selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated.

Results

Age, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology.

Conclusion

The random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.

LDCT screening results among eligible and ineligible screening candidates in preventive health check-ups population: a real world study in West China

To compare the LDCT screening results between eligible and ineligible screening candidates in preventive health check-ups population. Using a real-world LDCT screening results among people who took yearly health check-up in health management center of West China Hospital between 2006 and 2017. Objects were classified according to the China National Lung Cancer Screening Guideline with Low-dose Computed Tomography (2018 version) eligibility criteria. Descriptive analysis were performed between eligible and ineligible screening candidates. The proportion of ineligible screening candidates was 64.13% (10,259), and among them there were 4005 (39.04%) subjects with positive screenings, 80 cases had a surgical lung biopsy. Pathology results from lung biopsy revealed 154 cancers (true-positive) and 26 benign results (false-positive), the surgical false-positive biopsy rate was 4.17%, and ineligible group (7.69%) was higher than eligible group (2.47%), P < 0.05. Further, in ineligible screening candidates, the proportion of current smokers was higher among males compared to females (53.85% vs. 4.88%, P < 0.05). Of the 69 lung cancer patients detected in ineligible screening candidates, lung adenocarcinoma accounts for a high proportion of lung cancers both in male (75.00%) and female (85.00%). The proportion of ineligible screening candidates and the surgical false-positive biopsy rate in ineligible candidates were both high in health check-ups population.

Robotic-assisted right upper lobectomy with systemic pulmonary vein anomaly: a case report

BACKGROUND

While the role of low-dose computed tomography (CT) in lung cancer screening is established, its limitations in detailing pulmonary vascular variations are less emphasized. Three-dimensional reconstruction technology allows surgeons to reconstruct a patient's bronchial and pulmonary vascular structures using CT scan results. However, low-dose CT may not provide the same level of clarity as enhanced CT in displaying pulmonary vascular details. This limitation can be unfavorable for preoperative detection of potential pulmonary vascular variations, especially in cases involving planned segmentectomy.

CASE PRESENTATION

We report a case of a 58-year-old female with lung cancer, initially planned for Da Vinci robot-assisted thoracoscopic segmentectomy. Unexpectedly, during surgery, a pulmonary vein variation in the right upper lobe was discovered, leading to a change in the surgical method to a lobectomy. The patient had four variant right upper lobe veins draining into the superior vena cava and one into the left atrium. The surgery was complicated by significant bleeding and postoperative pulmonary congestion. Postoperative pathology confirmed adenocarcinoma.

CONCLUSIONS

This case highlights the importance of meticulous intraoperative exploration, particularly in cases involving planned segmentectomy, as unexpected pulmonary vein variations can significantly affect surgical decision-making. While three-dimensional reconstruction based on preoperative CT data is a valuable tool, it may not capture the full complexity of the anatomical variations. We discuss potential preoperative imaging techniques, including contrast-enhanced CT and CT angiography, as methods to better identify these variations. The enhanced visualization provided by robot-assisted surgery plays a crucial role in identifying and adapting to these variations, underscoring the advantages of this surgical approach. Our report contributes to the existing literature by providing a detailed account of how these principles were applied in a real-world scenario, reinforcing the need for surgical adaptability and awareness of the limitations of low-dose CT in complex cases.

Rates of Downstream Procedures and Complications Associated With Lung Cancer Screening in Routine Clinical Practice : A Retrospective Cohort Study

BACKGROUND

Lung cancer screening (LCS) using low-dose computed tomography (LDCT) reduces lung cancer mortality but can lead to downstream procedures, complications, and other potential harms. Estimates of these events outside NLST (National Lung Screening Trial) have been variable and lacked evaluation by screening result, which allows more direct comparison with trials.

OBJECTIVE

To identify rates of downstream procedures and complications associated with LCS.

DESIGN

Retrospective cohort study.

SETTING

5 U.S. health care systems.

PATIENTS

Individuals who completed a baseline LDCT scan for LCS between 2014 and 2018.

MEASUREMENTS

Outcomes included downstream imaging, invasive diagnostic procedures, and procedural complications. For each, absolute rates were calculated overall and stratified by screening result and by lung cancer detection, and positive and negative predictive values were calculated.

RESULTS

Among the 9266 screened patients, 1472 (15.9%) had a baseline LDCT scan showing abnormalities, of whom 140 (9.5%) were diagnosed with lung cancer within 12 months (positive predictive value, 9.5% [95% CI, 8.0% to 11.0%]; negative predictive value, 99.8% [CI, 99.7% to 99.9%]; sensitivity, 92.7% [CI, 88.6% to 96.9%]; specificity, 84.4% [CI, 83.7% to 85.2%]). Absolute rates of downstream imaging and invasive procedures in screened patients were 31.9% and 2.8%, respectively. In patients undergoing invasive procedures after abnormal findings, complication rates were substantially higher than those in NLST (30.6% vs. 17.7% for any complication; 20.6% vs. 9.4% for major complications).

LIMITATION

Assessment of outcomes was retrospective and was based on procedural coding.

CONCLUSION

The results indicate substantially higher rates of downstream procedures and complications associated with LCS in practice than observed in NLST. Diagnostic management likely needs to be assessed and improved to ensure that screening benefits outweigh potential harms.

PRIMARY FUNDING SOURCE

National Cancer Institute and Gordon and Betty Moore Foundation.

Disparities in incidence and trends of colorectal, lung, female breast, and cervical cancers among non-Hispanic American Indian and Alaska Native people, 1999-2018

PURPOSE

This study is the first to comprehensively describe incidence rates and trends of screening-amenable cancers (colorectal, lung, female breast, and cervical) among non-Hispanic AI/AN (NH-AI/AN) people.

METHODS

Using the United States Cancer Statistics AI/AN Incidence Analytic Database, we, calculated incidence rates for colorectal, lung, female breast, and cervical cancers for NH-AI/AN and non-Hispanic White (NHW) people for the years 2014-2018 combined. We calculated age-adjusted incidence rates (per 100,000), total percent change in incidence rates between 1999 and 2018, and trends over this time-period using Joinpoint analysis. Screening prevalence by region was calculated using Behavioral Risk Factor Surveillance System data.

RESULTS

Rates of screening-amenable cancers among NH-AI/AN people varied by geographic region and age at diagnosis. Over half of all lung and colorectal cancers in NH-AI/AN people were diagnosed at later stages. Rates of lung and colorectal cancers decreased significantly between 1999-2018 among NH-AI/AN men, but no significant changes were observed in rates of screening-amenable cancers among NH-AI/AN women.

CONCLUSION

This study highlights disparities in screening-amenable cancers between NH-AI/AN and NHW people. Culturally informed, community-based interventions that increase access to preventive health services could reduce cancer disparities among AI/AN people.

Benign and malignant pulmonary parenchymal findings on chest CT among adult survivors of childhood and young adult cancer with a history of chest radiotherapy

PURPOSE

Childhood and young adult cancer survivors exposed to chest radiotherapy are at increased risk of lung cancer. In other high-risk populations, lung cancer screening has been recommended. Data is lacking on prevalence of benign and malignant pulmonary parenchymal abnormalities in this population.

METHODS

We conducted a retrospective review of pulmonary parenchymal abnormalities in chest CTs performed more than 5 years post-cancer diagnosis in survivors of childhood, adolescent, and young adult cancer. We included survivors exposed to radiotherapy involving the lung field and followed at a high-risk survivorship clinic between November 2005 and May 2016. Treatment exposures and clinical outcomes were abstracted from medical records. Risk factors for chest CT-detected pulmonary nodule were assessed.

RESULTS

Five hundred and ninety survivors were included in this analysis: median age at diagnosis, 17.1 years (range, 0.4-39.8); and median time since diagnosis, 22.3 years (range, 1-58.6). At least one chest CT more than 5 years post-diagnosis was performed in 338 survivors (57%). Among these, 193 (57.1%) survivors had at least one pulmonary nodule detected on a total of 1057 chest CTs, resulting in 305 CTs with 448 unique nodules. Follow-up was available for 435 of these nodules; 19 (4.3%) were malignant. Risk factors for first pulmonary nodule were older age at time of CT, CT performed more recently, and splenectomy.

CONCLUSIONS

Benign pulmonary nodules are very common among long-term survivors of childhood and young adult cancer.

IMPLICATIONS FOR CANCER SURVIVORS

High prevalence of benign pulmonary nodules in cancer survivors exposed to radiotherapy could inform future guidelines on lung cancer screening in this population.

Outcomes of Shared Decision-Making for Low-Dose Screening for Lung Cancer in an Academic Medical Center

Shared decision-making (SDM) helps patients weigh risks and benefits of screening approaches. Little is known about SDM visits between patients and healthcare providers in the context of lung cancer screening. This study explored the extent that patients were informed by their provider of the benefits and harms of lung cancer screening and expressed certainty about their screening choice. We conducted a survey with 75 patients from an academic medical center in the Southeastern U.S. Survey items included knowledge of benefits and harms of screening, patients' value elicitation during SDM visits, and decisional certainty. Patient and provider characteristics were collected through electronic medical records or self-report. Descriptive statistics, Kruskal-Wallis tests, and Pearson correlations between screening knowledge, value elicitation, and decisional conflict were calculated. The sample was predominately non-Hispanic White (73.3%) with no more than high school education (53.4%) and referred by their primary care provider for screening (78.7%). Patients reported that providers almost always discussed benefits of screening (81.3%), but infrequently discussed potential harms (44.0%). On average, patients had low knowledge about screening (score = 3.71 out of 8) and benefits/harms. Decisional conflict was low (score = - 3.12) and weakly related to knowledge (R= - 0.25) or value elicitation (R= - 0.27). Black patients experienced higher decisional conflict than White patients (score = - 2.21 vs - 3.44). Despite knowledge scores being generally low, study patients experienced low decisional conflict regarding their decision to undergo lung cancer screening. Additional work is needed to optimize the quality and consistency of information presented to patients considering screening.

A population-based study on social inequality and barriers to healthcare-seeking with lung cancer symptoms

Healthcare-seeking with lung cancer symptoms is a prerequisite for improving timely diagnosis of lung cancer. In this study we aimed to explore barriers towards contacting the general practitioner (GP) with lung cancer symptoms, and to analyse the impact of social inequality. The study is based on a nationwide survey with 69,060 individuals aged ≥40 years, randomly selected from the Danish population. The survey included information on lung cancer symptoms, GP contacts, barriers to healthcare-seeking and smoking status. Information about socioeconomics was obtained by linkage to Danish Registers. Descriptive statistics and multivariate logistic regression model were used to analyse the data. “Being too busy” and “Being worried about wasting the doctor’s time” were the most frequent barriers to healthcare-seeking with lung cancer symptoms. Individuals out of workforce and individuals who smoked more often reported “Being worried about what the doctor might find” and “Being too embarrassed” about the symptoms. The social inequality in barriers to healthcare-seeking with lung cancer symptoms is noticeable, which emphasises the necessity of focus on vulnerable groups at risk of postponing relevant healthcare-seeking.

Unsupervised contrastive learning based transformer for lung nodule detection

Objective.Early detection of lung nodules with computed tomography (CT) is critical for the longer survival of lung cancer patients and better quality of life. Computer-aided detection/diagnosis (CAD) is proven valuable as a second or concurrent reader in this context. However, accurate detection of lung nodules remains a challenge for such CAD systems and even radiologists due to not only the variability in size, location, and appearance of lung nodules but also the complexity of lung structures. This leads to a high false-positive rate with CAD, compromising its clinical efficacy.Approach.Motivated by recent computer vision techniques, here we present a self-supervised region-based 3D transformer model to identify lung nodules among a set of candidate regions. Specifically, a 3D vision transformer is developed that divides a CT volume into a sequence of non-overlap cubes, extracts embedding features from each cube with an embedding layer, and analyzes all embedding features with a self-attention mechanism for the prediction. To effectively train the transformer model on a relatively small dataset, the region-based contrastive learning method is used to boost the performance by pre-training the 3D transformer with public CT images.Results.Our experiments show that the proposed method can significantly improve the performance of lung nodule screening in comparison with the commonly used 3D convolutional neural networks.Significance.This study demonstrates a promising direction to improve the performance of current CAD systems for lung nodule detection.

Perinodular Parenchymal Features Improve Indeterminate Lung Nodule Classification

BACKGROUND

Radiomics, defined as quantitative features extracted from images, provide a non-invasive means of assessing malignant versus benign pulmonary nodules. In this study, we evaluate the consistency with which perinodular radiomics extracted from low-dose computed tomography images serve to identify malignant pulmonary nodules.

MATERIALS AND METHODS

Using the National Lung Screening Trial (NLST), we selected individuals with pulmonary nodules between 4mm to 20mm in diameter. Nodules were segmented to generate four distinct datasets; 1) a Tumor dataset containing tumor-specific features, 2) a 10 mm Band dataset containing parenchymal features between the segmented nodule boundary and 10mm out from the boundary, 3) a 15mm Band dataset, and 4) a Tumor Size dataset containing the maximum nodule diameter. Models to predict malignancy were constructed using support-vector machine (SVM), random forest (RF), and least absolute shrinkage and selection operator (LASSO) approaches. Ten-fold cross validation with 10 repetitions per fold was used to evaluate the performance of each approach applied to each dataset.

RESULTS

With respect to the RF, the Tumor, 10mm Band, and 15mm Band datasets achieved areas under the receiver-operator curve (AUC) of 84.44%, 84.09%, and 81.57%, respectively. Significant differences in performance were observed between the Tumor and 15mm Band datasets (adj. p-value <0.001). However, when combining tumor-specific features with perinodular features, the 10mm Band + Tumor and 15mm Band + Tumor datasets (AUC 87.87% and 86.75%, respectively) performed significantly better than the Tumor Size dataset (66.76%) or the Tumor dataset. Similarly, the AUCs from the SVM and LASSO were 84.71% and 88.91%, respectively, for the 10mm Band + Tumor.

CONCLUSIONS

The combined 10mm Band + Tumor dataset improved the differentiation between benign and malignant lung nodules compared to the Tumor datasets across all methodologies. This demonstrates that parenchymal features capture novel diagnostic information beyond that present in the nodule itself. (data agreement: NLST-163).

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.

Controversies and challenges in lung cancer screening

Two large randomized controlled trials have shown mortality benefit from lung cancer screening (LCS) in high-risk groups. Updated guidelines by the United State Preventative Service Task Force in 2020 will allow for inclusion of more patients who are at high risk of developing lung cancer and benefit from screening. As medical clinics and lung cancer screening programs around the country continue to work on perfecting the LCS workflow, it is important to understand some controversial issues surrounding LCS that should be addressed. In this article, we identify some of these issues, including false positive rates of low-dose CT, over-diagnosis, cost expenditure, LCS disparities in minorities, and utility of biomarkers. We hope to provide clarity, potential solutions, and future directions on how to address these controversies.

Personalised Lung Cancer Screening (PLuS) study to assess the importance of coexisting chronic conditions to clinical practice and policy: protocol for a multicentre observational study

INTRODUCTION

Lung cancer is the leading cause of cancer death in the USA and worldwide, and lung cancer screening (LCS) with low-dose CT (LDCT) has the potential to improve lung cancer outcomes. A critical question is whether the ratio of potential benefits to harms found in prior LCS trials applies to an older and potentially sicker population. The Personalised Lung Cancer Screening (PLuS) study will help close this knowledge gap by leveraging real-world data to fully characterise LCS recipients. The principal goal of the PLuS study is to characterise the comorbidity burden of individuals undergoing LCS and quantify the benefits and harms of LCS to enable informed decision-making.

METHODS AND ANALYSIS

PLuS is a multicentre observational study designed to assemble an LCS cohort from the electronic health records of ~40 000 individuals undergoing annual LCS with LDCT from 2016 to 2022. Data will be integrated into a unified repository to (1) examine the burden of multimorbidity by race/ethnicity, socioeconomic status and age; (2) quantify potential benefits and harms; and (3) use the observational data with validated simulation models in the Cancer Intervention and Surveillance Modeling Network (CISNET) to provide LCS outcomes in the real-world US population. We will fit a multivariable logistic regression model to estimate the adjusted ORs of comorbidity, functional limitations and impaired pulmonary function adjusted for relevant covariates. We will also estimate the cumulative risk of LCS outcomes using discrete-time survival models. To our knowledge, this is the first study to combine observational data and simulation models to estimate the long-term impact of LCS with LDCT.

ETHICS AND DISSEMINATION

The study was approved by the Kaiser Permanente Southern California Institutional Review Board and VA Portland Health Care System. The results will be disseminated through publications and presentations at national and international conferences. Safety considerations include protection of patient confidentiality.

Combining plasma extracellular vesicle Let-7b-5p, miR-184 and circulating miR-22-3p levels for NSCLC diagnosis and drug resistance prediction

Low-dose computed tomography (LDCT) Non-Small Cell Lung (NSCLC) screening is associated with high false-positive rates, leading to unnecessary expensive and invasive follow ups. There is a need for minimally invasive approaches to improve the accuracy of NSCLC diagnosis. In addition, NSCLC patients harboring sensitizing mutations in epidermal growth factor receptor EGFR (T790M, L578R) are treated with Osimertinib, a potent tyrosine kinase inhibitor (TKI). However, nearly all patients develop TKI resistance. The underlying mechanisms are not fully understood. Plasma extracellular vesicle (EV) and circulating microRNA (miRNA) have been proposed as biomarkers for cancer screening and to inform treatment decisions. However, the identification of highly sensitive and broadly predictive core miRNA signatures remains a challenge. Also, how these systemic and diverse miRNAs impact cancer drug response is not well understood. Using an integrative approach, we examined plasma EV and circulating miRNA isolated from NSCLC patients versus screening controls with a similar risk profile. We found that combining EV (Hsa-miR-184, Let-7b-5p) and circulating (Hsa-miR-22-3p) miRNAs abundance robustly discriminates between NSCLC patients and high-risk cancer-free controls. Further, we found that Hsa-miR-22-3p, Hsa-miR-184, and Let-7b-5p functionally converge on WNT/βcatenin and mTOR/AKT signaling axes, known cancer therapy resistance signals. Targeting Hsa-miR-22-3p and Hsa-miR-184 desensitized EGFR-mutated (T790M, L578R) NSCLC cells to Osimertinib. These findings suggest that the expression levels of circulating hsa-miR-22-3p combined with EV hsa-miR-184 and Let-7b-5p levels potentially define a core biomarker signature for improving the accuracy of NSCLC diagnosis. Importantly, these biomarkers have the potential to enable prospective identification of patients who are at risk of responding poorly to Osimertinib alone but likely to benefit from Osimertinib/AKT blockade combination treatments.

Clinical Applications of Circulating Tumour Cells and Circulating Tumour DNA in Non-Small Cell Lung Cancer-An Update

Despite efforts to improve earlier diagnosis of non-small cell lung cancer (NSCLC), most patients present with advanced stage disease, which is often associated with poor survival outcomes with only 15% surviving for 5 years from their diagnosis. Tumour tissue biopsy is the current mainstream for cancer diagnosis and prognosis in many parts of the world. However, due to tumour heterogeneity and accessibility issues, liquid biopsy is emerging as a game changer for both cancer diagnosis and prognosis. Liquid biopsy is the analysis of tumour-derived biomarkers in body fluids, which has remarkable advantages over the use of traditional tumour biopsy. Circulating tumour cells (CTCs) and circulating tumour DNA (ctDNA) are two main derivatives of liquid biopsy. CTC enumeration and molecular analysis enable monitoring of cancer progression, recurrence, and treatment response earlier than traditional biopsy through a minimally invasive liquid biopsy approach. CTC-derived ex-vivo cultures are essential to understanding CTC biology and their role in metastasis, provide a means for personalized drug testing, and guide treatment selection. Just like CTCs, ctDNA provides opportunity for screening, monitoring, treatment evaluation, and disease surveillance. We present an updated review highlighting the prognostic and therapeutic significance of CTCs and ctDNA in NSCLC.

The Prevalence of Benign Pathology Following Major Pulmonary Resection for Suspected Malignancy

BACKGROUND

In the era of lung cancer screening with low-dose computed tomography, there is concern that high false-positive rates may lead to an increase in nontherapeutic lung resection. The aim of this study is to determine the current rate of major pulmonary resection for ultimately benign pathology.

MATERIALS AND METHODS

A single-institution, retrospective analysis of all patients > 18 y who underwent major pulmonary resection between 2013 and 2018 for suspected malignancy and had benign final pathology was performed.

RESULTS

Of 394 major pulmonary resections performed for known or presumed malignancy, 10 (2.5%) were benign. Of these 10, the mean age was 61.1 y (SD 14.6). Most were current or former smokers (60%). Ninety percent underwent a fluorodeoxyglucose positron emission tomography scan. Median nodule size was 27 mm (IQR 21-35) and most were in the right middle lobe (50%). Preoperative biopsy was performed in four (40%) but were nondiagnostic. Video-assisted thoracoscopic lobectomy (70%) was the most common surgical approach. Final pathology revealed three (30%) infectious, three (30%) inflammatory, two (20%) fibrotic, and two (20%) benign neoplastic nodules. Two (20%) patients had perioperative complications, both of which were prolonged air leaks, one (10%) patient was readmitted within 30 d, and there was no mortality.

CONCLUSIONS

A small percentage of patients (2.5% in our series) may undergo major pulmonary resection for unexpectedly benign pathology. Knowledge of this rate is useful to inform shared decision-making models between surgeons and patients and evaluation of thoracic surgery program performance.

Computer tomography guided thoracoscopic resection of small pulmonary nodules in the hybrid theatre

Purpose

Thoracic surgeons are currently asked to resect smaller and deeper lesions which are difficult to detect thoracoscopically. The growing number of those lesions arises both from lung cancer screening programs and from follow-up of extrathoracic malignancies. This study analyzed the routine use of a CT-aided thoracoscopic approach to small pulmonary nodules in the hybrid theatre and the resulting changes in the treatment pathway.

Methods

50 patients were retrospectively included. The clinical indication for histological diagnosis was suspected metastasis in 46 patients. Technically, the radiological distance between the periphery of the lesion and the visceral pleura had to exceed the maximum diameter of the lesion for the patient to be included. A spiral wire was placed using intraoperative CT-based laser navigation to guide the thoracoscopic resection.

Results

The mean diameter of the lesions was 8.4 mm (SD 4.27 mm). 29.4 minutes (SD 28.5) were required on average for the wire placement and 42.3 minutes (SD 20.1) for the resection of the lesion. Histopathology confirmed the expected diagnosis in 30 of 52 lesions. In the remaining 22 lesions, 9 cases of primary lung cancer were detected while 12 patients showed a benign disease.

Conclusion

Computer tomography assisted thoracoscopic surgery (CATS) enabled successful resection in all cases with minimal morbidity. The histological diagnosis led to a treatment change in 42% of the patients. The hybrid-CATS technique provides good access to deeply located small pulmonary nodules and could be particularly valuable in the emerging setting of lung cancer screening.

[Lung cancer screening with low dose computed tomography : a systematic review]

INTRODUCTION

Bronchial cancer, often diagnosed at a late stage, is the leading cause of cancer death. As early detection could potentially lead to curative treatment, several studies have evaluated low-dose chest CT (LDCT) as a screening method. The main objective of this work is to determine the impact of LDCT screening on overall mortality of a smoking population.

METHODS

Systematic review of randomised controlled screening trials comparing LDCT with no screening or chest x-ray.

RESULTS

Thirteen randomised controlled trials were identified, seven of which reported mortality results. NSLT showed a significant reduction of 6.7% in overall mortality and 20% in lung cancer mortality after 6.5 years of follow-up. NELSON showed a significant reduction in lung cancer mortality of 24% at 10 years among men. LUSI and MILD showed a reduction in lung cancer mortality of 69% at 8 years among women and 39% at 10 years, respectively.

CONCLUSION

Screening for bronchial cancer is a complex issue. Clarification is needed regarding the selection of individuals, the definition of a positive result and the attitude towards a suspicious nodule.

Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges

Randomised clinical trials have shown the efficacy of computed tomography lung cancer screening, initiating discussions on whether and how to implement population‐based screening programs. Due to smoking behaviour being the primary risk‐factor for lung cancer and part of the criteria for determining screening eligibility, lung cancer screening is inherently risk‐based. In fact, the selection of high‐risk individuals has been shown to be essential in implementing lung cancer screening in a cost‐effective manner. Furthermore, studies have shown that further risk‐stratification may improve screening efficiency, allow personalisation of the screening interval and reduce health disparities. However, implementing risk‐based lung cancer screening programs also requires overcoming a number of challenges. There are indications that risk‐based approaches can negatively influence the trade‐off between individual benefits and harms if not applied thoughtfully. Large‐scale implementation of targeted, risk‐based screening programs has been limited thus far. Consequently, questions remain on how to efficiently identify and invite high‐risk individuals from the general population. Finally, while risk‐based approaches may increase screening program efficiency, efficiency should be balanced with the overall impact of the screening program. In this review, we will address the opportunities and challenges in applying risk‐stratification in different aspects of lung cancer screening programs, as well as the balance between screening program efficiency and impact.

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.

Evaluation of a novel deep learning-based classifier for perifissural nodules

Objectives

To evaluate the performance of a novel convolutional neural network (CNN) for the classification of typical perifissural nodules (PFN).

Methods

Chest CT data from two centers in the UK and The Netherlands (1668 unique nodules, 1260 individuals) were collected. Pulmonary nodules were classified into subtypes, including “typical PFNs” on-site, and were reviewed by a central clinician. The dataset was divided into a training/cross-validation set of 1557 nodules (1103 individuals) and a test set of 196 nodules (158 individuals). For the test set, three radiologically trained readers classified the nodules into three nodule categories: typical PFN, atypical PFN, and non-PFN. The consensus of the three readers was used as reference to evaluate the performance of the PFN-CNN. Typical PFNs were considered as positive results, and atypical PFNs and non-PFNs were grouped as negative results. PFN-CNN performance was evaluated using the ROC curve, confusion matrix, and Cohen’s kappa.

Results

Internal validation yielded a mean AUC of 91.9% (95% CI 90.6–92.9) with 78.7% sensitivity and 90.4% specificity. For the test set, the reader consensus rated 45/196 (23%) of nodules as typical PFN. The classifier-reader agreement (k = 0.62–0.75) was similar to the inter-reader agreement (k = 0.64–0.79). Area under the ROC curve was 95.8% (95% CI 93.3–98.4), with a sensitivity of 95.6% (95% CI 84.9–99.5), and specificity of 88.1% (95% CI 81.8–92.8).

Conclusion

The PFN-CNN showed excellent performance in classifying typical PFNs. Its agreement with radiologically trained readers is within the range of inter-reader agreement. Thus, the CNN-based system has potential in clinical and screening settings to rule out perifissural nodules and increase reader efficiency.

Key Points

• Agreement between the PFN-CNN and radiologically trained readers is within the range of inter-reader agreement.

• The CNN model for the classification of typical PFNs achieved an AUC of 95.8% (95% CI 93.3–98.4) with 95.6% (95% CI 84.9–99.5) sensitivity and 88.1% (95% CI 81.8–92.8) specificity compared to the consensus of three readers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-020-07509-x.

Multi-Window CT Based Radiological Traits for Improving Early Detection in Lung Cancer Screening

Rationale and Objectives

Evaluate ability of radiological semantic traits assessed on multi-window computed tomography (CT) to predict lung cancer risk.

Materials and Methods

A total of 199 participants were investigated, including 60 incident lung cancers and 139 benign positive controls. Twenty lung window features and 2 mediastinal window features were extracted and scored on a point scale in three screening rounds. Multivariate logistic regression analysis was used to explore the association of these radiological traits with the risk of developing lung cancer. The areas under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and positive predictive value (PPV) were computed to evaluate the best predictive model.

Results

Combining mediastinal window-specific features with the lung window features-based model significantly improves performance compared to individual window features. Model performance is consistent both at baseline and the first follow-up scan, with an AUROC increased from 0.822 to 0.871 (p = 0.009) and from 0.877 to 0.917 (p = 0.008), respectively, for single to multi-window feature models. We also find that the multi-window CT based model showed better specificity and PPV, with PPV at the second follow-up scan improved to 0.953.

Conclusion

We find combining window semantic features improves model performance in identifying cancerous nodules. We also find that lung window features are more informative compared to mediastinal features in predicting malignancy.

Lung Cancer Screening by Low-Dose Computed Tomography - Part 1: Expected Benefits, Possible Harms, and Criteria for Eligibility and Population Targeting

BACKGROUND

 Trials in the USA and Europe have convincingly demonstrated the efficacy of screening by low-dose computed tomography (LDCT) as a means to lower lung cancer mortality, but also document potential harms related to radiation, psychosocial stress, and invasive examinations triggered by false-positive screening tests and overdiagnosis. To ensure that benefits (lung cancer deaths averted; life years gained) outweigh the risk of harm, lung cancer screening should be targeted exclusively to individuals who have an elevated risk of lung cancer, plus sufficient residual life expectancy.

METHODS AND CONCLUSIONS

 Overall, randomized screening trials show an approximate 20 % reduction in lung cancer mortality by LDCT screening. In view of declining residual life expectancy, especially among continuing long-term smokers, risk of being over-diagnosed is likely to increase rapidly above the age of 75. In contrast, before age 50, the incidence of LC may be generally too low for screening to provide a positive balance of benefits to harms and financial costs. Concise criteria as used in the NLST or NELSON trials may provide a basic guideline for screening eligibility. An alternative would be the use of risk prediction models based on smoking history, sex, and age as a continuous risk factor. Compared to concise criteria, such models have been found to identify a 10 % to 20 % larger number of LC patients for an equivalent number of individuals to be screened, and additionally may help provide security that screening participants will all have a high-enough LC risk to balance out harm potentially caused by radiation or false-positive screening tests.

KEY POINTS

  · LDCT screening can significantly reduce lung cancer mortality. · Screening until the age of 80 was shown to be efficient in terms of cancer deaths averted; in terms of LYG relative to overdiagnosis, stopping at a younger age (e. g. 75) may have greater efficiency. · Risk models may improve the overall net benefit of lung cancer screening.

CITATION FORMAT

· Kaaks R, Delorme S. Lung Cancer Screening by Low-Dose Computed Tomography - Part 1: Expected Benefits, Possible Harms, and Criteria for Eligibility and Population Targeting. Fortschr Röntgenstr 2021; 193: 527 - 536.

Time Difference of Arrival on Contrast-Enhanced Ultrasound in Distinguishing Benign Inflammation From Malignant Peripheral Pulmonary Lesions

Introduction

Worldwide, the incidence and mortality of lung cancer are at the highest levels, and the most lesions are located in the lung periphery. Despite extensive screening and diagnosis, the pathologic types of peripheral pulmonary lesions (PPLs) are difficult to diagnose by noninvasive examination. This study aimed to identify a novel index—time difference of arrival (TDOA)—to discriminate between benign inflammation and malignant PPLs.

Methods

Using contrast-enhanced ultrasound (CEUS), we retrospectively analyzed 96 patients with PPLs who had undergone biopsy to confirm the pathologic types. All data were collected from Dazhou Central Hospital between December 2012 and July 2019. The parameters of CEUS were analyzed by two assistant chief physicians of ultrasound diagnosis. Area under the receiver operating characteristic curve analysis, sensitivity, specificity, positive predictive value, and negative predictive value were calculated to assess the diagnostic ability of different indices.

Results

We found that the TDOA significantly distinguished benign inflammation from malignant lesions. The TDOA was markedly increased in patients with malignant lesions than benign inflammation lesions (P < 0.001). Compared with conventional time-intensity curve (TIC) indices, TDOA showed high diagnostic accuracy (area under the curve = 0.894). Moreover, conventional diagnostic indices did not affect the diagnostic performance of TDOA by adjusting the receiver operating characteristic curve.

Conclusion

TDOA is feasible for the diagnosis of benign inflammation and malignant PPLs.

Lung Cancer Screening with Low-Dose CT: a Meta-Analysis

BACKGROUND

Randomized controlled trials have evaluated the efficacy of low-dose CT (LDCT) lung cancer screening on lung cancer (LC) outcomes.

OBJECTIVE

Meta-analyze LDCT lung cancer screening trials.

METHODS

We identified studies by searching PubMed, Google Scholar, the Cochrane Registry, ClinicalTrials.gov , and reference lists from retrieved publications. We abstracted data on study design features, stage I LC diagnoses, LC and overall mortality, false positive results, harm from invasive diagnostic procedures, overdiagnosis, and significant incidental findings. We assessed study quality using the Cochrane risk-of-bias tool. We used random-effects models to calculate relative risks and assessed effect modulators with subgroup analyses and meta-regression.

RESULTS

We identified 9 studies that enrolled 96,559 subjects. The risk of bias across studies was judged to be low. Overall, LDCT screening significantly increased the detection of stage I LC, RR = 2.93 (95% CI, 2.16-3.98), I² = 19%, and reduced LC mortality, RR = 0.84 (95% CI, 0.75-0.93), I² = 0%. The number needed to screen to prevent an LC death was 265. Women had a lower risk of LC death (RR = 0.69, 95% CI, 0.40-1.21) than men (RR = 0.86, 95% CI, 0.66-1.13), p value for interaction = 0.11. LDCT screening did not reduce overall mortality, RR = 0.96 (95% CI, 0.91-1.01), I² = 0%. The pooled false positive rate was 8% (95% CI, 4-18); subjects with false positive results had < 1 in 1000 risk of major complications following invasive diagnostic procedures. The most valid estimates for overdiagnosis and significant incidental findings were 8.9% and 7.5%, respectively.

DISCUSSION

LDCT screening significantly reduced LC mortality, though not overall mortality, with women appearing to benefit more than men. The estimated risks for false positive results, screening complications, overdiagnosis, and incidental findings were low. Long-term survival data were available only for North American and European studies limiting generalizability.

Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19

Artificial intelligence (AI) is transforming healthcare delivery. The digital revolution in medicine and healthcare information is prompting a staggering growth of data intertwined with elements from many digital sources such as genomics, medical imaging and electronic health records. Such massive growth has sparked the development of an increasing number of AI-based applications that can be deployed in clinical practice. Pulmonary specialists who are familiar with the principles of AI and its applications will be empowered and prepared to seize future practice and research opportunities. The goal of this review is to provide pulmonary specialists and other readers with information pertinent to the use of AI in pulmonary medicine. First, we describe the concept of AI and some of the requisites of machine learning and deep learning. Next, we review some of the literature relevant to the use of computer vision in medical imaging, predictive modelling with machine learning, and the use of AI for battling the novel severe acute respiratory syndrome-coronavirus-2 pandemic. We close our review with a discussion of limitations and challenges pertaining to the further incorporation of AI into clinical pulmonary practice.

Artificial intelligence (AI) is changing the landscape in medicine. AI-based applications will empower pulmonary specialists to seize modern practice and research opportunities. Data-driven precision medicine is already here.https://bit.ly/324tl2m

[Research Progress on Lung Cancer Screening]

肺癌是世界上最常见的恶性肿瘤，其5年生存率仅为19.7%，严重威胁人类健康。肺癌筛查是降低肺癌死亡率的有效措施，已有的研究证明用低剂量螺旋计算机断层扫描（low-dose computed tomography, LDCT）进行筛查可降低20%的肺癌死亡，目前国际和国内均建议进行肺癌筛查。研究肺癌筛查的发展现状有助于我们明确肺癌的高危人群，探索合理的筛查方案，提高筛查的成本效益，减轻经济负担。因此本文就肺癌筛查现状、肺癌筛查的成本效益以及存在的问题综述如下。

Practice, clinician, and patient factors associated with the adoption of lung cancer screening

OBJECTIVES

Lung cancer remains the leading cause of cancer-related deaths in the United States. In 2013, the US Preventive Services Task Force recommended annual screening for lung cancer with low-dose computed tomography in adults meeting certain criteria. This study seeks to assess lung cancer screening uptake in three health systems.

SETTING

This study was part of a randomized controlled trial to engage underserved populations in preventive care and includes 45 primary care practices in eight states.

METHODS

Practice and clinician characteristics were manually collected. Lung cancer was measured from electronic health record data. A generalized linear mixed model was used to assess characteristics associated with screening.

RESULTS

Patient records between 2012 and 2016 were examined. Lung cancer screening uptake overall increased only slightly after the guideline change (2.8-5.6%, p < 0.01). One health system did not show an increase in uptake (0.2-0.1%, p = 0.32), another had a clinically insignificant increase (1.5-2.9%, p < 0.01), and the third nearly doubled its higher baseline screening rate (10.4-19.1%, p < 0.01). Within the third health system, patients more likely to be screened were older, male, had more comorbid conditions, visited the office more frequently, were seen in practices closer to the screening clinic, or were uninsured or covered by Medicare or Medicaid.

CONCLUSIONS

Certain patients appeared more likely to be screened. The only health system with increased lung cancer screening explicitly promoted screening rather than relying on clinicians to implement the new guideline. Systems approaches may help increase the low uptake of lung cancer screening.

Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data

As randomized trials in the USA and Europe have convincingly demonstrated efficacy of lung cancer screening by computed tomography (CT), European countries are discussing the introduction of screening programs. To maintain acceptable cost-benefit and clinical benefit-to-harm ratios, screening should be offered to individuals at sufficiently elevated risk of having lung cancer. Using federal-wide survey and lung cancer incidence data (2008–2013), we examined the performance of four well-established risk models from the USA (PLCO_M2012, LCRAT, Bach) and the UK (LLP₂₀₀₈) in the German population, comparing with standard eligibility criteria based on age limits, minimal pack years of smoking (or combination of total duration with average intensity) and maximum years since smoking cessation. The eligibility criterion recommended by the United States Preventive Services Taskforce (USPSTF) would select about 3.2 million individuals, a group equal in size to the upper fifth of ever smokers age 50–79 at highest risk, and to 11% of all adults aged 50–79. According to PLCO_M2012, the model showing best concordance between numbers of lung cancer cases predicted and reported in registries, persons with 5-year risk ≥ 1.7% included about half of all lung cancer incidence in the full German population. Compared to eligibility criteria (e.g. USPSTF), risk models elected individuals in higher age groups, including ex-smokers with longer average quitting times. Further studies should address how in Germany these shifts may affect expected benefits of CT screening in terms of life-years gained versus the potential harm of age-specific increasing risk of over-diagnosis.

Attitudes of Clinicians about Screening Head and Neck Cancer Survivors for Lung Cancer Using Low-Dose Computed Tomography

OBJECTIVE

National guidelines recommend lung cancer screening (LCS) using low-dose computed tomography (LDCT) for high-risk patients, including survivors of other tobacco-related cancers like head and neck cancer (HNC). This qualitative study investigated clinicians' practices and attitudes toward LCS with LDCT with patients who have survived HNC, in the context of mandated requirements for shared decision making (SDM) using decision aids.

METHODS

Thematic analysis of transcribed semi-structured clinician interviews and focus group.

RESULTS

Clinicians recognized LCS' utility for some HNC survivors with smoking histories. However, they identified many challenges to SDM in diverse clinic settings, including time, workflow, uncertainty about guidelines and reimbursement, decision aids, competing patient priorities, unclear evidence, potentially heightened patient receptivity and stress, and the complexity of discussions. They also identified challenges to LCS implementation.

CONCLUSIONS

While clinicians feel that LDCT LCS may benefit some HNC survivors, there are barriers both to implementing LCS SDM for these patients in primary care as currently recommended and to integrating it into cancer clinics. Challenges for SDM across settings include a lack of decision aids tailored to patients with cancer histories. Given recommendations to broaden LCS eligibility criteria, more research may be required before refinement of current guidelines.

Circulating ensembles of tumor-associated cells: A redoubtable new systemic hallmark of cancer

Circulating ensembles of tumor‐associated cells (C‐ETACs) which comprise tumor emboli, immune cells and fibroblasts pose well‐recognized risks of thrombosis and aggressive metastasis. However, the detection, prevalence and characterization of C‐ETACs have been impaired due to methodological difficulties. Our findings show extensive pan‐cancer prevalence of C‐ETACs on a hitherto unreported scale in cancer patients and virtual undetectability in asymptomatic individuals. Peripheral blood mononuclear cells (PBMCs) were isolated from blood samples of 16,134 subjects including 5,509 patients with epithelial malignancies in various organs and 10,625 asymptomatic individuals with age related higher cancer risk. PBMCs were treated with stabilizing reagents to protect and harvest apoptosis‐resistant C‐ETACs, which are defined as cell clusters comprising at least three EpCAM⁺ and CK⁺ cells irrespective of leucocyte common antigen (CD45) status. All asymptomatic individuals underwent screening investigations for malignancy including PAP smear, mammography, low‐dose computed tomography, evaluation of cancer antigen 125, cancer antigen 19‐9, alpha fetoprotein, carcinoembryonic antigen, prostate specific antigen (PSA) levels and clinical examination to identify healthy individuals with no indication of cancer. C‐ETACs were detected in 4,944 (89.8%, 95% CI: 89.0–90.7%) out of 5,509 cases of cancer. C‐ETACs were detected in 255 (3%, 95% CI: 2.7–3.4%) of the 8,493 individuals with no abnormal findings in screening. C‐ETACs were detected in 137 (6.4%, 95% CI: 5.4–7.4%) of the 2,132 asymptomatic individuals with abnormal results in one or more screening tests. Our study shows that heterotypic C‐ETACs are ubiquitous in epithelial cancers irrespective of radiological, metastatic or therapy status. C‐ETACs thus qualify to be a systemic hallmark of cancer.

What's new?

Circulating Ensembles of Tumor Associated Cells (C‐ETACs) comprised of tumor emboli, immune cells, and fibroblasts pose well‐recognized risks of thrombosis and aggressive metastasis. However, the detection and characterization of C‐ETACs have been impaired by methodological difficulties. Here, the authors have developed a label‐free non‐mechanical process that permits enrichment of viable apoptosis‐resistant C‐ETACs from peripheral blood. They show that heterotypic C‐ETACs are not merely incidental findings in cancer but rather a systemic manifestation of malignancy. C‐ETACs are present in a significant proportion of all solid organ malignancies and are rare in asymptomatic individuals. Monitoring of C‐ETACs could help inform cancer management.

Long-term cancer risk associated with lung nodules observed on low-dose screening CT scans

OBJECTIVE

Non-calcified nodules (NCNs) associated with false positive low-dose CT (LDCT) lung cancer screens have been attributed to various causes. Some, however, may represent lung cancer precursors. An association of NCNs with long-term lung cancer risk would provide indirect evidence of some NCNs being cancer precursors.

METHODS

LDCT arm participants in the National Lung Screening Trial (NLST) received LDCT screens at baseline and years 1-2. The relationship between NCNs found on LDCT screens and subsequent lung cancer diagnosis over different time periods was examined at the person and lobe level. For the latter, a lobe had a cancer outcome only if the cancer was located in the lobe. Separate analyses were performed on baseline and post-baseline LDCT findings; for the latter, those with baseline NCNs were excluded and only new (non-pre-existing) NCNs examined. Raw and adjusted rate-ratios (RRs) were computed for presence of NCNs and subsequent lung cancer risk; adjusted RRs controlled for demographic and smoking factors.

RESULTS

26,309 participants received the baseline LDCT screen. Over median 11.3 years follow-up, 1675 lung cancers were diagnosed. Adjusted RRs for time periods 0-4, 4-8 and 8-12 years following the baseline screen were 5.1 (95 % CI:4.4-5.9), 1.5 (95 % CI:1.3-1.9) and 1.5 (95 % CI:1.2-1.8) at the person-level and 14.7 (95 % CI:12.6-17.2), 2.6 (95 % CI: 2.0-3.4) and 2.2 (95 % CI:1.6-2.9) at the lobe-level. 18,585 participants were included in the post-baseline analysis. Adjusted RRs for periods 0-4, 4-8 and 8-11 years were 5.6 (95 % CI: 4.5-7.0), 1.9 (95 % CI: 1.3-2.7) and 1.6 (95 % CI: 0.9-2.9) at the person-level and 19.6 (95 % CI:14.9-25.3), 2.5 (95 % CI:1.3-4.7) and 3.3 (95 % CI:1.4-7.6) at the lobe-level. Raw RRs were similar.

CONCLUSION

NCNs are associated with excess long-term lung cancer risk, suggesting that some may be lung cancer precursors.

Primary care providers' views on a future lung cancer screening program

BACKGROUND

The National Lung Screening Trial demonstrated that screening with low-dose computed tomography significantly reduces mortality from lung cancer in high-risk individuals.

OBJECTIVE

To describe the role preferences and information needs of primary care providers (PCPs) in a future organized lung cancer screening program.

METHODS

We purposively sampled PCPs from diverse health regions of Ontario and from different practice models including family health teams and community health centres. We also recruited family physicians with a leadership role in cancer screening. We used focus groups and a nominal group process to identify informational priorities. Two analysts systematically applied a coding scheme to interview transcripts.

RESULTS

Four groups were held with 34 providers and administrative staff [28 (82%) female, 21 (62%) physicians, 7 (20%) other health professionals and 6 (18%) administrative staff]. PCPs and staff were generally positive about a potential lung cancer screening program but had variable views on their involvement. Informational needs included evidence of potential benefits and harms of screening. Most providers preferred that a new program be modelled on positive features of an existing breast cancer screening program. Lung cancer screening was viewed as a new opportunity to counsel patients about smoking cessation.

CONCLUSIONS

The development of a future lung cancer screening program should consider the wide variability in the roles that PCPs preferred. An explicit link to existing smoking cessation programs was seen as essential. As providers had significant information needs, learning materials and opportunities should be developed with them.

[Lung cancer screening among the smoker population]

CONTEXT

Lung cancer is the most common cancer in men and the leading cause of cancer death worldwide. This cancer, often diagnosed at an advanced stage, mainly affects smokers and survival could increase with early detection. Screening by chest x-ray has not shown its effectiveness, then several randomized trials have been carried out about screening by thoracic low-dose computed tomography in smokers.

METHODS

A systematic review of these trials was conducted according to the PRISMA criteria as well as a point of the difficulties of setting up screening following these trials.

RESULTS

Among five trials that published mortality results, only the US one, the National Lung Screening Trial (NLST) was showed a 20% decrease in lung cancer mortality in smokers screened by low-dose computed tomography compared to chest x-ray. However, besides the lack of power of the other trials, a great heterogeneity of the methods makes the synthesis of the results difficult. While many expert groups are in favor of testing, only the United States has implemented a screening program, whose adherence remains low.

CONCLUSION

Many persistent questions about the eligible population, the organization, the side effects, and finally the cost-benefit, need additional research around these issues.

The Reach and Feasibility of an Interactive Lung Cancer Screening Decision Aid Delivered by Patient Portal

OBJECTIVE

Health systems could adopt population-level approaches to screening by identifying potential screening candidates from the electronic health record and reaching out to them via the patient portal. However, whether patients would read or act on sent information is unknown. We examined the feasibility of this digital health outreach strategy.

METHODS

We conducted a single-arm pragmatic trial in a large academic health system. An electronic health record algorithm identified primary care patients who were potentially eligible for lung cancer screening (LCS). Identified patients were sent a patient portal invitation to visit a LCS interactive Web site which assessed screening eligibility and included a decision aid. The primary outcome was screening completion. Secondary outcomes included the proportion of patients who read the invitation, visited the interactive Web site, and completed the interactive Web site.

RESULTS

We sent portal invitations to 1,000 patients. Almost all patients (86%, 862/1,000) read the invitation, 404 (40%) patients visited the interactive Web site, and 349 patients (35%) completed it. Of the 99 patients who were confirmed screening eligible by the Web site, 81 made a screening decision (30% wanted screening, 44% unsure, 26% declined screening), and 22 patients had a chest computed tomography completed.

CONCLUSION

The digital outreach strategy reached the majority of patient portal users. While the study focused on LCS, this digital outreach approach could be generalized to other health needs. Given the broad reach and potential low cost of this digital strategy, future research should investigate best practices for implementing the system.

Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method

BACKGROUND

Accurately detecting and examining lung nodules early is key in diagnosing lung cancers and thus one of the best ways to prevent lung cancer deaths. Radiologists spend countless hours detecting small spherical-shaped nodules in computed tomography (CT) images. In addition, even after detecting nodule candidates, a considerable amount of effort and time is required for them to determine whether they are real nodules. The aim of this paper is to introduce a high performance nodule classification method that uses three dimensional deep convolutional neural networks (DCNNs) and an ensemble method to distinguish nodules between non-nodules.

METHODS

In this paper, we use a three dimensional deep convolutional neural network (3D DCNN) with shortcut connections and a 3D DCNN with dense connections for lung nodule classification. The shortcut connections and dense connections successfully alleviate the gradient vanishing problem by allowing the gradient to pass quickly and directly. Connections help deep structured networks to obtain general as well as distinctive features of lung nodules. Moreover, we increased the dimension of DCNNs from two to three to capture 3D features. Compared with shallow 3D CNNs used in previous studies, deep 3D CNNs more effectively capture the features of spherical-shaped nodules. In addition, we use an alternative ensemble method called the checkpoint ensemble method to boost performance.

RESULTS

The performance of our nodule classification method is compared with that of the state-of-the-art methods which were used in the LUng Nodule Analysis 2016 Challenge. Our method achieves higher competition performance metric (CPM) scores than the state-of-the-art methods using deep learning. In the experimental setup ESB-ALL, the 3D DCNN with shortcut connections and the 3D DCNN with dense connections using the checkpoint ensemble method achieved the highest CPM score of 0.910.

CONCLUSION

The result demonstrates that our method of using a 3D DCNN with shortcut connections, a 3D DCNN with dense connections, and the checkpoint ensemble method is effective for capturing 3D features of nodules and distinguishing nodules between non-nodules.

Screening BRCA1 and BRCA2 Mutation Carriers for Breast Cancer

Women with BRCA mutations, who choose to decline or defer risk-reducing mastectomy, require a highly sensitive breast screening regimen they can begin by age 25 or 30. Meta-analysis of multiple observational studies, in which both mammography and magnetic resonance imaging (MRI) were performed annually, demonstrated a combined sensitivity of 94% for MRI plus mammography compared to 39% for mammography alone. There was negligible benefit from adding screening ultrasound or clinical breast examination to the other two modalities. The great majority of cancers detected were non-invasive or stage I. While the addition of MRI to mammography lowered the specificity from 95% to 77%, the specificity improved significantly after the first round of screening. The median follow-up of women with screen-detected breast cancer in the above observational studies now exceeds 10 years, and the long-term breast cancer-free survival in most of these studies is 90% to 95%. However, ongoing follow-up of these study patients, as well of women screened and treated more recently, is necessary. Advances in imaging technology will make highly sensitive screening accessible to a greater number of high-risk women.

Multilevel Opportunities to Address Lung Cancer Stigma across the Cancer Control Continuum

The public health imperative to reduce the burden of lung cancer has seen unprecedented progress in recent years. Fully realizing the advances in lung cancer treatment and control requires attention to potential barriers in their momentum and implementation. In this analysis, we present and evaluate the argument that stigma is a highly significant barrier to fulfilling the clinical promise of advanced care and reduced lung cancer burden. This evaluation of the stigma of lung cancer is based on a multilevel perspective that incorporates the individual, persons in the individual's immediate environment, the health care system, and the larger societal structure that shapes perceptions and decisions. We also consider current interventions and interventional needs within and across aspects of the lung cancer continuum, including prevention, screening, diagnosis, treatment, and survivorship. Current evidence suggests that stigma detrimentally affects psychosocial, communication, and behavioral outcomes over the entire lung cancer control continuum and across multiple levels. Interventional efforts to alleviate stigma in the context of lung cancer show promise, yet more work is needed to evaluate their impact. Understanding and addressing the multilevel role of stigma is a crucial area for future study to realize the full benefits offered by lung cancer prevention, control, and treatment. Coordinated, interdisciplinary, and well-conceptualized efforts have the potential to reduce the barrier of stigma in the context of lung cancer and facilitate demonstrable improvements in clinical care and quality of life.