Incidence of solitary pulmonary nodules in Northeastern France: a population-based study in five regions

Incidental pulmonary nodules - current guidelines and management

BACKGROUND

 Due to the greater use of high-resolution cross-sectional imaging, the number of incidental pulmonary nodules detected each year is increasing. Although the vast majority of incidental pulmonary nodules are benign, many early lung carcinomas could be diagnosed with consistent follow-up. However, for a variety of reasons, the existing recommendations are often not implemented correctly. Therefore, potential for improvement with respect to competence, communication, structure, and process is described.

METHODS

 This article presents the recommendations for incidental pulmonary nodules from the current S3 guideline for lung cancer (July 2023). The internationally established recommendations (BTS guidelines and Fleischner criteria) are compared and further studies on optimized management were included after a systematic literature search in PubMed.

RESULTS AND CONCLUSION

 In particular, AI-based software solutions are promising, as they can be used in a support capacity on several levels at once and can lead to simpler and more automated management. However, to be applicable in routine clinical practice, software must fit well into the radiology workflow and be integrated. In addition, "Lung Nodule Management" programs or clinics that follow a high-quality procedure for patients with incidental lung nodules or nodules detected by screening have been established in the USA. Similar structures might also be implemented in Germany in a future screening program in which patients with incidental pulmonary nodules could be included.

KEY POINTS

  · Incidental pulmonary nodules are common but are often not adequately managed. · The updated S3 guideline for lung cancer now includes recommendations for incidental pulmonary nodules. · Competence, communication, structure, and process levels offer significant potential for improvement.

CITATION FORMAT

· Glandorf J, Vogel-Claussen J, . Incidental pulmonary nodules - current guidelines and management. Fortschr Röntgenstr 2024; 196: 582 - 590.

The effect of combining different sampling tools on the performance of electromagnetic navigational bronchoscopy for the evaluation of peripheral lung lesions and factors associated with its diagnostic yield

BACKGROUND

We assessed the performance of Electromagnetic navigational bronchoscopy (ENB) as a standalone diagnostic technique and the performance of different sampling tools used during the procedure.

METHODS

We recruited 160 consecutive patients who underwent ENB for peripheral lung lesions (PLL) at a tertiary care centre. The diagnostic performance of ENB and sampling tools was assessed using a logistic regression model and a ROC-curve in which the dependent variable was diagnostic success. A multivariate model was built to predict diagnostic success before performing ENB to select the best candidates for the procedure.

RESULTS

Most patients with PLLs in the study were male (65%), with a mean age of 67.9 years. The yield was 66% when the most common techniques were used together as suction catheter + transbronchial biopsy forceps (TBBx) + bronchoalveolar lavage + bronchial washing (p < 0.001) and increased to 69% when transbronchial needle aspiration (TBNA) and cytology brush were added (p < 0.001). Adding diagnostic techniques such as TBBx and TBNA resulted in an increase in diagnostic performance, with a statistically significant trend (p = 0.002). The logistic model area-under the ROC-curve for diagnostic success during ENB was 0.83 (95% CI:0.75-0.90; p < 0.001), and a logit value ≥ 0.12 was associated with ≥ 50% probability of diagnostic success.

CONCLUSIONS

ENB, as a stand-alone diagnostic tool for the evaluation of PLLs when performed by experienced operators using a multi-modality technique, has a good diagnostic yield. The probability of having a diagnostic ENB could be assessed using the proposed model.

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.

Benign and Malignant 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 imaging abnormalities in this population. Methods : We conducted a retrospective review of imaging 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, 21.1 years (range, 0.4-58.6). 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.

Incidental Pulmonary Nodules - What Do We Know in 2022

Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, and early LC diagnosis can significantly improve outcomes and survival rates in affected patients. Implementation of LC screening programs using low-dose computed tomography CT in high-risk subjects aims to detect LC as early as possible, but so far, adoption of screening programs into routine clinical care has been very slow. In recent years, the use of CT has significantly increased the rate of incidentally detected pulmonary nodules. Although most of those incidental pulmonary nodules (IPNs) are benign, some of them represent early-stage LC. Given the large number of IPNs detected in the range of several millions each year, this represents an additional, maybe even larger, opportunity to drive stage shift in LC diagnosis, next to LC screening programs. Comprehensive evaluation and targeted work-up of IPNs are mandatory to identify the malignant nodules from the crowd, and several guidelines provide radiologists and physicians' guidance on IPN assessment and management. However, IPNs still seem to be inadequately processed due to various reasons including insufficient reporting in the radiological report, missing communication between stakeholders, absence of patient tracking systems, and uncertainty regarding responsibilities for the IPN management. In recent years, several approaches such as lung nodule programs, patient tracking software, artificial intelligence, and communication software were introduced into clinical practice to address those shortcomings. This review evaluates the current situation of IPN management and highlights recent developments in process improvement to achieve first steps toward stage shift in LC diagnosis.

Multivariate Analysis on Development of Lung Adenocarcinoma Lesion from Solitary Pulmonary Nodule

Objective

To analyze multiple factors developing lung adenocarcinoma lesion from solitary pulmonary nodule (SPN).

Methods

A total of 70 patients diagnosed with lung adenocarcinoma after finding SPN by chest CT and treated in our hospital (01, 2018–01, 2021) were selected as the malignant lesion group, and another 70 patients diagnosed with benign lesion after finding SPN by CT in the same period were included in the benign lesion group. All patients had complete medical records. With univariate analysis and multivariate logistic regression, the independent risk factors for developing lung adenocarcinoma lesions from SPN were analyzed.

Results

By conducting univariate analysis of patients' general information (age, course of disease, BMI, nodule diameter, and gender), smoking status (smoking history and number of cigarettes smoked per year), medical history (family history of lung cancer, history of extrapulmonary malignant tumor, and history of autoimmune diseases), basic complications (hypertension and diabetes), and laboratory examinations (CEA, NSE, CYFRA21-1, SCC-Ag, and CA125), it was concluded that age, course of disease, nodule diameter, CEA positive, CYFRA21-1 positive, and CA125 positive were significantly different between the two groups (P < 0.05); the logistic regression results showed that high age, increased nodule diameter, and CYFRA21-1 positive were the independent risk factors developing lung adenocarcinoma from SPN (P < 0.05).

Conclusion

In patients with SPN, higher age, longer course of disease, greater nodule diameter, and CYFRA21-1 positive imply increased risk for triggering lung adenocarcinoma lesion. Therefore, high attention should be paid in the clinic to such SPN patients for early diagnosis and treatment.

Association of computed tomography screening with lung cancer stage shift and survival in the United States: quasi-experimental study

OBJECTIVE

To determine the effect of the introduction of low dose computed tomography screening in 2013 on lung cancer stage shift, survival, and disparities in the stage of lung cancer diagnosed in the United States.

DESIGN

Quasi-experimental study using Joinpoint modeling, multivariable ordinal logistic regression, and multivariable Cox proportional hazards modeling.

SETTING

US National Cancer Database and Surveillance Epidemiology End Results program database.

PARTICIPANTS

Patients aged 45-80 years diagnosed as having non-small cell lung cancer (NSCLC) between 1 January 2010 and 31 December 2018.

MAIN OUTCOME MEASURES

Annual per cent change in percentage of stage I NSCLC diagnosed among patients aged 45-54 (ineligible for screening) and 55-80 (potentially eligible for screening), median all cause survival, and incidence of NSCLC; multivariable adjusted odds ratios for year-to-year changes in likelihood of having earlier stages of disease at diagnosis and multivariable adjusted hazard ratios for changes in hazard of death before versus after introduction of screening.

RESULTS

The percentage of stage I NSCLC diagnosed among patients aged 55-80 did not significantly increase from 2010 to 2013 (from 27.8% to 29.4%) and then increased at 3.9% (95% confidence interval 3.0% to 4.8%) per year from 2014 to 2018 (from 30.2% to 35.5%). In multivariable adjusted analysis, the increase in the odds per year of a patient having one lung cancer stage lower at diagnosis during the time period from 2014 to 2018 was 6.2% (multivariable adjusted odds ratio 1.062, 95% confidence interval 1.048 to 1.077; P<0.001) higher than the increase in the odds per year from 2010 to 2013. Similarly, the median all cause survival of patients aged 55-80 did not significantly increase from 2010 to 2013 (from 15.8 to 18.1 months), and then increased at 11.9% (8.9% to 15.0%) per year from 2014 to 2018 (from 19.7 to 28.2 months). In multivariable adjusted analysis, the hazard of death decreased significantly faster after 2014 compared with before 2014 (P<0.001). By 2018, stage I NSCLC was the predominant diagnosis among non-Hispanic white people and people living in the highest income or best educated regions. Non-white people and those living in lower income or less educated regions remained more likely to have stage IV disease at diagnosis. Increases in the detection of early stage disease in the US from 2014 to 2018 led to an estimated 10 100 averted deaths.

CONCLUSIONS

A recent stage shift toward stage I NSCLC coincides with improved survival and the introduction of lung cancer screening. Non-white patients and those living in areas of greater deprivation had lower rates of stage I disease identified, highlighting the need for efforts to increase access to screening in the US.

Use of a Dual Artificial Intelligence Platform to Detect Unreported Lung Nodules

OBJECTIVE

To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, comprising computer-vision (CV) algorithm to detect pulmonary nodules, with positive results filtered by natural language processing (NLP) analysis of the dictated report.

METHODS

Retrospective analysis of 5047 chest CT scans and corresponding reports. Cases which were both CV algorithm positive (nodule ≥ 6 mm) and NLP negative (nodule not reported), were outputted for review by 2 chest radiologists.

RESULTS

The CV algorithm detected nodules that are 6 mm or greater in 1830 (36.3%) of 5047 cases. Three hundred fifty-five (19.4%) were unreported by the radiologist, as per NLP algorithm. Expert review determined that 139 (39.2%) of 355 cases were true positives (2.8% of all cases). One hundred thirty (36.7%) of 355 cases were unnecessary alerts-vague language in the report confounded the NLP algorithm. Eighty-six (24.2%) of 355 cases were false positives.

CONCLUSIONS

Dual-AI platform detected actionable unreported nodules in 2.8% of chest CT scans, yet minimized intrusion to radiologist's workflow by avoiding alerts for most already-reported nodules.

Development and clinical application of deep learning model for lung nodules screening on CT images

Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who evaluate a large LDCT screening images face enormous challenges, including mechanical repetition and boring work, the easy omission of small nodules, lack of consistent criteria, etc. It requires an efficient method for helping radiologists improve nodule detection accuracy with efficiency and cost-effectiveness. Many novel deep neural network-based systems have demonstrated the potential for use in the proposed technique to detect lung nodules. However, the effectiveness of clinical practice has not been fully recognized or proven. Therefore, the aim of this study to develop and assess a deep learning (DL) algorithm in identifying pulmonary nodules (PNs) on LDCT and investigate the prevalence of the PNs in China. Radiologists and algorithm performance were assessed using the FROC score, ROC-AUC, and average time consumption. Agreement between the reference standard and the DL algorithm in detecting positive nodules was assessed per-study by Bland-Altman analysis. The Lung Nodule Analysis (LUNA) public database was used as the external test. The prevalence of NCPNs was investigated as well as other detailed information regarding the number of pulmonary nodules, their location, and characteristics, as interpreted by two radiologists.

PET/CT Radiomics in Lung Cancer: An Overview

Quantitative extraction of imaging features from medical scans (‘radiomics’) has attracted a lot of research attention in the last few years. The literature has consistently emphasized the potential use of radiomics for computer-assisted diagnosis, as well as for predicting survival and response to treatment. Radiomics is appealing in that it enables full-field analysis of the lesion, provides nearly real-time results, and is non-invasive. Still, a lot of studies suffer from a series of drawbacks such as lack of standardization and repeatability. Such limitations, along with the unmet demand for large enough image datasets for training the algorithms, are major hurdles that still limit the application of radiomics on a large scale. In this paper, we review the current developments, potential applications, limitations, and perspectives of PET/CT radiomics with specific focus on the management of patients with lung cancer.

Lung nodules: A comprehensive review on current approach and management

In daily clinical practice, radiologists and pulmonologists are faced with incidental radiographic findings of pulmonary nodules. Deciding how to manage these findings is very important as many of them may be benign and require no further action, but others may represent early disease and importantly early-stage lung cancer and require prompt diagnosis and definitive treatment. As the diagnosis of pulmonary nodules includes invasive procedures which can be relatively minimal, such as bronchoscopy or transthoracic aspiration or biopsy, but also more invasive procedures such as thoracic surgical biopsies, and as these procedures are linked to anxiety and to cost, it is important to have clearly defined algorithms for the description, management, and follow-up of these nodules. Clear algorithms for the imaging protocols and the management of positive findings should also exist in lung cancer screening programs, which are already established in the USA and which will hopefully be established worldwide. This article reviews current knowledge on nodule definition, diagnostic evaluation, and management based on literature data and mainly recent guidelines.