Strategies for Reducing False-Positive Screening Results for Intermediate-Size Nodules Evaluated Using Lung-RADS: A Secondary Analysis of National Lung Screening Trial Data

The Effect of X-ray Dose Photon-Counting Detector Computed Tomography on Nodule Properties in a Lung Cancer Screening Cohort: A Prospective Study

OBJECTIVES

The aim of the study was to evaluate the effect of photon-counting detector (PCD-)CT dose reduction to x-ray equivalent levels on nodule detection, diameter, volume, and density compared to a low-dose reference standard using semiautomated and manual methods.

MATERIALS AND METHODS

Between February and July 2023, 101 prospectively enrolled participants underwent noncontrast same-study low- and chest x-ray-dose CT scans using PCD-CT. Patients who were not referred for lung cancer screening or nodule follow-up, as well as those with nodules smaller than 5 mm in diameter, were excluded. Nodule detection and measurement of nodule diameters and volumes was semiautomatically performed for low- and x-ray-dose scans using computer-aided diagnosis software. Additionally, 2 blinded readers manually measured largest nodule diameters and examined nodule density. Nodules were classified using Lung-RADS v2022. Image quality was assessed with subjective and objective measures.

RESULTS

Mean CTDIvol for x-ray dose scans was 0.11 ± 0.03 mGy, compared to 0.65 ± 0.15 mGy for low-dose images (P < 0.001). One hundred seventy-two nodules larger than 5 mm were detected in 53 of the 101 participants (32 male, 61.6 ± 12.5 years; 21 female, 60.3 ± 12.5 years). The semiautomated method had high overall sensitivity for nodule detection (0.94) on x-ray dose scans, with a higher sensitivity for solid nodules (>0.95) and lower for subsolid nodules (>0.86). Nodules not detected on x-ray dose scans were significantly smaller. Semiautomated measurements underestimated nodule diameter for solid nodules on x-ray dose scans (P = 0.01), but no significant effect for nodule volume was found (P = 0.775). Readers rated nodule density less dense on x-ray dose scans (R1: P < 0.001, R2: P = 0.006). There was no significant difference in nodule diameter for both readers between scan doses (R1: P = 0.141; R2: P = 0.554). There were good to excellent correlations between semiautomated and reader nodule diameters. Agreement and accuracy between low-dose and x-ray dose Lung-RADS classifications across methods were good (Cohens' к = 0.73, 0.62, 0.76 for semiautomated method, R1 and R2; resp. Accuracy: 0.82, 0.78, 0.85). No Lung-RADS classification changes were observed with semiautomated volumetric measurements of nodules.

CONCLUSIONS

Semiautomated nodule detection is highly sensitive in PCD-CT x-ray dose scans. Semiautomated nodule volume measurement is more robust to image quality changes than nodule diameter. Accurate semiautomated and manual nodule measurements are feasible on x-ray dose scans, but nodule density was in tendency underestimated. Nodule classification using Lung-RADS was shown to be accurate on x-ray dose scans.

How I Do It: Management of Pleural-attached Pulmonary Nodules in Low-Dose CT Screening for Lung Cancer

Lung cancer is the leading cause of cancer deaths globally. In various trials, the ability of low-dose CT screening to diagnose early lung cancers leads to high cure rates. It is widely accepted that the potential benefits of low-dose CT screening for lung cancer outweigh the harms. The ability to reliably predict the benignity of nodules, especially at the baseline round, further reduces the potential for harm. Pleural-attached nodules are an important subgroup that represents nodules attached (distance from any pleural surface, 0 mm) to any pleural surfaces (fissural, costal, mediastinal, and diaphragmatic). Pleural-attached solid nodules less than 10 mm in average diameter with smooth margins and triangular, lentiform, oval, or semicircular shapes have a high likelihood of benignity. The 2019 Lung CT Screening Reporting and Data System (Lung-RADS) version 1.1 assigned pleural-attached nodules with these features to categories 3 (probably benign, recommend follow-up in 6 months) or 4 (suspicious for malignancy, recommend follow-up in 3 months or PET/CT). However, Lung-RADS version 2022 now recommends annual follow-up rather than short-term follow-up. These changes downgrade these nodules to category 2 (benign) and limits additional workup. This review article summarizes the terminology used to describe these nodules, characteristics for determining benignity, and the accuracy of the evidence used to make these recommendations.

Comparison of Lung-RADS Version 2022 and British Thoracic Society Guidelines in Classifying Solid Pulmonary Nodules Detected at Lung Cancer Screening CT

BACKGROUND AND OBJECTIVES

Lung cancer screening is critical for early detection and management, particularly through the use of computed tomography (CT). This study aims to compare the Lung Imaging Reporting and Data System (Lung-RADS) Version 2022 with the British Thoracic Society (BTS) guidelines in classifying solid pulmonary nodules detected at lung cancer screening CT examinations.

MATERIALS AND METHODS

This retrospective study included 224 patients who underwent lung cancer screening CT between 2016 and 2022 and had a reported solid pulmonary nodule. A fellowship-trained thoracic radiologist reviewed the CT images, characterizing nodules by size, location, margins, attenuation, calcification, growth at follow-up, and final pathologic diagnosis if malignant. The sensitivity and specificity of Lung-RADS Version 2022 in detecting malignant nodules were compared with those of the BTS guidelines using the McNemar test.

RESULTS

Of the 224 patients, 198 (88%) had nodules deemed benign, while 26 (12%) had malignant nodules. The Lung-RADS Version 2022 resulted in higher specificity than the BTS guidelines (85% vs. 65%, p < 0.001), without sacrificing sensitivity (92% for both). Nodules larger than 8 mm, spiculated margins, upper lobe location, and interval growth were associated with higher malignancy risk (p < 0.01).

CONCLUSIONS

Compared with the BTS guidelines, Lung-RADS Version 2022 reduces the number of false-positive screening CT examinations while maintaining high sensitivity for detecting malignant solid pulmonary nodules.

Blood microRNA testing in participants with suspicious low-dose CT findings: follow-up of the BioMILD lung cancer screening trial

Background

The proper management of suspicious radiologic findings is crucial to optimize the effectiveness of low-dose computed tomography (LDCT) lung cancer screening trials. In the BioMILD study, we evaluated the utility of combining a plasma 24-microRNA signature classifier (MSC) and LDCT to define the individual risk and personalize screening strategies. Here we aim to assess the utility of repeated MSC testing during annual screening rounds in 1024 participants with suspicious LDCT findings.

Methods

The primary outcome was two-year lung cancer incidence in relation to MSC test results, reported as relative risk (RR) with 95% confidence interval (CI). Lung cancer incidence and mortality were estimated using extended Cox models for time-dependent covariates, yielding the respective hazard ratios (HR). Clinicaltrials.gov ID: NCT02247453.

Findings

With a median follow-up of 8.5 years, the full study set included 1403 indeterminate LDCT (CTind) and 584 positive LDCT (CT+) results. A lung cancer RR increase in MSC+ compared to MSC- participants was observed in both the CTind (RR: 2.5; 95% CI: 1.4-4.32) and CT+ (RR: 2.6; 95% CI: 1.81-3.74) groups and was maintained when considering stage I or resectable tumors only. A 98% negative predictive value in CTind/MSC- and a 30% positive predictive value in CT+/MSC+ lesions were recorded. At seven years' follow-up, MSC+ participants had a cumulative HR of 4.4 (95% CI: 3.0-6.4) for lung cancer incidence and of 8.1 (95% CI: 2.7-24.5) for lung cancer mortality.

Interpretation

Our study shows that MSC can be reliably performed during LDCT screening rounds to increase the accuracy of lung cancer risk and mortality prediction and supports its clinical utility in the management of LDCT findings of uncertain malignancy.

Funding

Italian Association for Cancer Research; Italian Ministry of Health; Horizon2020; National Cancer Institute (NCI); Gensignia LifeScience.

Volumetric Analysis: Effect on Diagnosis and Management of Indeterminate Solid Pulmonary Nodules in Routine Clinical Practice

OBJECTIVE

To evaluate the effect of volumetric analysis on the diagnosis and management of indeterminate solid pulmonary nodules in routine clinical practice.

METHODS

This was a retrospective study with 107 computed tomography (CT) cases of solid pulmonary nodules (range, 6-15 mm), 57 pathology-proven malignancies (lung cancer, n = 34; metastasis, n = 23), and 50 benign nodules. Nodules were evaluated on a total of 309 CT scans (average number of CTs/nodule, 2.9 [range, 2-7]). CT scans were from multiple institutions with variable technique. Nine radiologists (attendings, n = 3; fellows, n = 3; residents, n = 3) were asked their level of suspicion for malignancy (low/moderate or high) and management recommendation (no follow-up, CT follow-up, or care escalation) for baseline and follow-up studies first without and then with volumetric analysis data. Effect of volumetry on diagnosis and management was assessed by generalized linear and logistic regression models.

RESULTS

Volumetric analysis improved sensitivity ( P = 0.009) and allowed earlier recognition ( P < 0.05) of malignant nodules. Attending radiologists showed higher sensitivity in recognition of malignant nodules ( P = 0.03) and recommendation of care escalation ( P < 0.001) compared with trainees. Volumetric analysis altered management of high suspicion nodules only in the fellow group ( P = 0.008). κ Statistics for suspicion for malignancy and recommended management were fair to substantial (0.38-0.66) and fair to moderate (0.33-0.50). Volumetric analysis improved interobserver variability for identification of nodule malignancy from 0.52 to 0.66 ( P = 0.004) only on the second follow-up study.

CONCLUSIONS

Volumetric analysis of indeterminate solid pulmonary nodules in routine clinical practice can result in improved sensitivity and earlier identification of malignant nodules. The effect of volumetric analysis on management recommendations is variable and influenced by reader experience.

Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial

Screening with low-dose CT (LDCT) in a high-risk population, as defined by age and smoking behavior, reduces lung cancer-related mortality. However, LDCT screening presents a major challenge. Numerous, mostly benign, nodules are seen in the lungs during screening. The question is how to distinguish the malignant from the benign nodules. Various studies use different protocols for nodule management. The Dutch-Belgian NELSON (Nederlands-Leuvens Longkanker Screenings Onderzoek) trial, the largest European lung cancer screening trial, used distinctions based on nodule volumetric assessment and growth rate. This review discusses key findings from the NELSON study regarding the characteristics of screening-detected nodules, including nodule size and its volumetric assessment, growth rate, subtype, and their associated malignancy risk. These results are compared with findings from other screening studies and current recommendations for lung nodule management. By examining differences in nodule management strategies and providing a comprehensive overview of outcomes specific to lung cancer screening, this review aims to contribute to the broader discussion on optimizing lung nodule management in screening programs.

Lung-Reporting and Data System 2.0: Impact of the Updated Approach to Juxtapleural Nodules During Lung Cancer Screening Using the National Lung Cancer Screening Trial Data Set

PURPOSE

To determine the frequency of malignancy of nonperifissural juxtapleural nodules (JPNs) measuring 6 to < 10 mm in a subset of low-dose chest computed tomographies from the National Lung Cancer Screening Trial and the rate of down-classification of such nodules in Lung-Reporting and Data System (RADS) 2.0 compared with Lung-RADS 1.1.

MATERIALS AND METHODS

A secondary analysis of a subset of the National Lung Screening Trial was performed. An exemption was granted by the Institutional Review Board. The dominant noncalcified nodule measuring 6 to <10 mm was identified on all available prevalence computed tomographies. Nodules were categorized as pleural or nonpleural. Benign or malignant morphology was recorded. Initial and updated categories based on Lung-RADS 1.1 and Lung-RADS 2.0 were assigned, respectively. The impact of the down-classification of JPN was assessed. Both classification schemes were compared using the McNemar test ( P < 0.01).

RESULTS

A total of 2813 patients (62 ± 5 y, 1717 men) with 4408 noncalcified nodules were studied. One thousand seventy-three dominant nodules measuring 6 to <10 mm were identified. Three hundred forty-eight (32.4%) were JPN. The updated scheme allowed down-classification of 310 JPN from categories 3 (n = 198) and 4A (n = 112) to category 2. We, therefore, estimate a 4.8% rate of down-classification to category 2 in the entire National Lung Screening Trial screening group. Two/348 (0.57%) JPN were malignant, both nonbenign in morphology. The false-positive rate decreased in the updated classification ( P < 0.01).

CONCLUSION

This study demonstrates the low malignant potential of benign morphology JPN measuring 6 mm to <10 mm. The Lung-RADS 2.0 approach to JPN is estimated to reduce short-term follow-ups and false-positive results.

Impact of annual trend volume of low-dose computed tomography for lung cancer screening on overdiagnosis, overmanagement, and gender disparities

BACKGROUND

With the increasing prevalence of nonsmoking-related lung cancer in Asia, Asian countries have increasingly adopted low-dose computed tomography (LDCT) for lung cancer screening, particularly in private screening programs. This study examined how annual LDCT volume affects lung cancer stage distribution, overdiagnosis, and gender disparities using a hospital-based lung cancer database.

METHODS

This study analyzed the annual utilized LDCT volume, clinical characteristics of lung cancer, stage shift distribution, and potential overdiagnosis. At the individual level, this study also investigated the relationship between stage 0 lung cancer (potential strict definition regarding overdiagnosis) and the clinical characteristics of lung cancer.

RESULTS

This study reviewed the annual trend of 4971 confirmed lung cancer cases from 2008 to 2021 and conducted a link analysis with an LDCT imaging examination database over these years. As the volume of lung cancer screenings has increased over the years, the number and proportion of stage 0 lung cancers have increased proportionally. Our study revealed that the incidence of stage 0 lung cancer increased with increasing LDCT scan volume, particularly during the peak growth period from 2017 to 2020. Conversely, stage 4 lung cancer cases remained consistent across different time intervals. Furthermore, the increase in the lung cancer screening volume had a more pronounced effect on the increase in stage 0 lung cancer cases among females than it had among males. The estimated potential for overdiagnosis brought about by the screening process, compared to non-participating individuals, ranged from an odds ratio of 7.617 to one of 17.114. Both strict and lenient definitions of overdiagnosis (evaluating cases of stage 0 lung cancer and stages 0 to 1 lung cancer) were employed.

CONCLUSIONS

These results provide population-level evidence of potential lung cancer overdiagnosis in the Taiwanese population due to the growing use of LDCT screening, particularly concerning the strict definition of stage 0 lung cancer. The impact was greater in the female population than in the male population, especially among females younger than 40 years. To improve lung cancer screening in Asian populations, creating risk-based prediction models for smokers and nonsmokers, along with gender-specific strategies, is vital for ensuring survival benefits and minimizing overdiagnosis.

Interpreting Lung Cancer Screening CTs: Practical Approach to Lung Cancer Screening and Application of Lung-RADS

Lung cancer screening via low-dose computed tomography (CT) reduces mortality from lung cancer, and eligibility criteria have recently been expanded to include patients aged 50 to 80 with at least 20 pack-years of smoking history. Lung cancer screening CTs should be interepreted with use of Lung Imaging Reporting and Data System (Lung-RADS), a reporting guideline system that accounts for nodule size, density, and growth. The revised version of Lung-RADS includes several important changes, such as expansion of the definition of juxtapleural nodules, discussion of atypical pulmonary cysts, and stepped management for suspicious nodules. By using Lung-RADS, radiologists and clinicians can adopt a uniform approach to nodules detected during CT lung cancer screening and reduce false positives.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

The ACR created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

Radiologic Features of Nodules Attached to the Mediastinal or Diaphragmatic Pleura at Low-Dose CT for Lung Cancer Screening

Background Pulmonary noncalcified nodules (NCNs) attached to the fissural or costal pleura with smooth margins and triangular or lentiform, oval, or semicircular (LOS) shapes at low-dose CT are recommended for annual follow-up instead of immediate workup. Purpose To determine whether management of mediastinal or diaphragmatic pleura-attached NCNs (M/DP-NCNs) with the same features as fissural or costal pleura-attached NCNs at low-dose CT can follow the same recommendations. Materials and Methods This retrospective study reviewed chest CT examinations in participants from two databases. Group A included 1451 participants who had lung cancer that was first present as a solid nodule with an average diameter of 3.0-30.0 mm. Group B included 345 consecutive participants from a lung cancer screening program who had at least one solid nodule with a diameter of 3.0-30.0 mm at baseline CT and underwent at least three follow-up CT examinations. Radiologists reviewed CT images to identify solid M/DP-NCNs, defined as nodules 0 mm in distance from the mediastinal or diaphragmatic pleura, and recorded average diameter, margin, and shape. General descriptive statistics were used. Results Among the 1451 participants with lung cancer in group A, 163 participants (median age, 68 years [IQR, 61.5-75.0 years]; 92 male participants) had 164 malignant M/DP-NCNs 3.0-30.0 mm in average diameter. None of the 164 malignant M/DP-NCNs had smooth margins and triangular or LOS shapes (upper limit of 95% CI of proportion, 0.02). Among the 345 consecutive screening participants in group B, 146 participants (median age, 65 years [IQR, 59-71 years]; 81 female participants) had 240 M/DP-NCNs with average diameter 3.0-30.0 mm. None of the M/DP-NCNs with smooth margins and triangular or LOS shapes were malignant after a median follow-up of 57.8 months (IQR, 46.3-68.1 months). Conclusion For solid M/DP-NCNs with smooth margins and triangular or LOS shapes at low-dose CT, the risk of lung cancer is extremely low, which supports the recommendation of Lung Imaging Reporting and Data System version 2022 for annual follow-up instead of immediate workup. © RSNA, 2024 See also the editorial by Goodman and Baruah in this issue.

Analysis of the correlation between clinical and imaging features of malignant lung nodules and pathological types

Introduction

To explore the correlation between clinical and imaging features of malignant lung nodules and pathology types.

Methods

Patients with lung nodules admitted to the Affiliated Hospital of Jiangsu University from January 1, 2020 to December 31, 2020 were collected as study subjects, and all of them underwent surgical treatment and were clearly diagnosed by pathology. The correlation between clinical and imaging features and pathological types of lung cancer patients was analyzed.

Results

Among them, The pathological types of malignant pulmonary nodules are correlated with age, gender, smoking history, ground glass sign, nodule size, solid to solid ratio, lobulation sign, pleural indentation sign, hair prick sign, CEA, SCCA. The imaging features of ground glass sign and nodule size are most significantly correlated with the pathological type.

Conclusion

It was found that, the clinical and imaging characteristics of patients with malignant lung nodules have a certain correlation with the pathological type, and gender, age, smoking history, nodule size, nodule nature, burr sign, pleural depression sign, and tumor markers are of great value for pathological typing.

RadioGraphics Update: Lung-RADS 2022

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Volume Doubling Times of Benign and Malignant Nodules in Lung Cancer Screening

The purpose of this study was to measure the fractions of benign and malignant nodules in lung cancer screening that grow on follow-up, and to measure the volume doubling time (VDT) of those that grow. In this retrospective study, we included nodules from CT lung cancer screening in our healthcare network, for which a follow-up CT performed at least 2 months later showed the nodule to be persistent. The nodules were measured using semiautomated volumetric segmentation software at both timepoints. Growth was defined as an increase in volume by 25%. VDTs were calculated, and the fraction <400 days was recorded. Categorical variables were compared with Fisher's exact test, and continuous variables by the Wilcoxon test. The study included 153 nodules, of which 44 were malignant and 109 benign. Thirty (68%) of malignant nodules and 36 (33%) of benign nodules grew (P < 0.001). For growing nodules, VDT was 318 days for malignant nodules and 389 for benign nodules (P = 0.21). For growing solid nodules, VDT was 204 days for malignant nodules and 386 days for benign nodules (P = 0.01); of these, VDT was <400 days for 12/13 (92%) of malignant nodules and 15/26 (58%) of benign nodules. In conclusion, malignant nodules were more likely to grow, and solid malignant nodules grew faster, than benign nodules. However, there was substantial overlap between benign and malignant nodules. This limits the utility of volume doubling time in determining malignant nodules.

Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules

Objectives

This study aimed to investigate the ability of quantitative parameters of dual-energy computed tomography (DECT) and nodule size for differentiation between lung cancers and benign lesions in solid pulmonary nodules.

Materials and Methods

A total of 151 pathologically confirmed solid pulmonary nodules including 78 lung cancers and 73 benign lesions from 147 patients were consecutively and retrospectively enrolled who underwent dual-phase contrast-enhanced DECT. The following features were analyzed: diameter, volume, Lung CT Screening Reporting and Data System (Lung-RADS) categorization, and DECT-derived quantitative parameters including effective atomic number (Zeff), iodine concentration (IC), and normalized iodine concentration (NIC) in arterial and venous phases. Multivariable logistic regression analysis was used to build a combined model. The diagnostic performance was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity.

Results

The independent factors for differentiating lung cancers from benign solid pulmonary nodules included diameter, Lung-RADS categorization of diameter, volume, Zeff in arterial phase (Zeff_A), IC in arterial phase (IC_A), NIC in arterial phase (NIC_A), Zeff in venous phase (Zeff_V), IC in venous phase (IC_V), and NIC in venous phase (NIC_V) (all P < 0.05). The IC_V, NIC_V, and combined model consisting of diameter and NIC_V showed good diagnostic performance with AUCs of 0.891, 0.888, and 0.893, which were superior to the diameter, Lung-RADS categorization of diameter, volume, Zeff_A, and Zeff_V (all P < 0.001). The sensitivities of IC_V, NIC_V, and combined model were higher than those of IC_A and NIC_A (all P < 0.001). The combined model did not increase the AUCs compared with IC_V (P = 0.869) or NIC_V (P = 0.633).

Conclusion

The DECT-derived IC_V and NIC_V may be useful in differentiating lung cancers from benign lesions in solid pulmonary nodules.