Recent Trends in the Identification of Incidental Pulmonary Nodules

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.

Approach to Pulmonary Nodules in Connective Tissue Disease

The assessment of pulmonary nodules is a common and often challenging clinical scenario. This evaluation becomes even more complex in patients with connective tissue diseases (CTDs), as a range of disease-related factors must also be taken into account. These diseases are characterized by immune-mediated chronic inflammation, leading to tissue damage, collagen deposition, and subsequent organ dysfunction. A thorough examination of nodule features in these patients is required, incorporating anatomic and functional information, along with patient demographics, clinical factors, and disease-specific knowledge. This integrated approach is vital for effective risk stratification and precise diagnosis. This review article addresses specific CTD-related factors that should be taken into account when evaluating pulmonary nodules in this patient group.

Imaging modalities during navigational bronchoscopy

INTRODUCTION

Lung nodules are commonly encountered in clinical practice. Technological advances in navigational bronchoscopy and imaging modalities have led to paradigm shift from nodule screening or follow up to early lung cancer detection. This is due to improved nodule localization and biopsy confirmation with combined modalities of navigational platforms and imaging tools. To conduct this article, relevant literature was reviewed via PubMed from January 2014 until January 2024.

AREAS COVERED

This article highlights the literature on different imaging modalities combined with commonly used navigational platforms for diagnosis of peripheral lung nodules. Current limitations and future perspectives of imaging modalities will be discussed.

EXPERT OPINION

The development of navigational platforms improved localization of targets. However, published diagnostic yield remains lower compared to percutaneous-guided biopsy. The discordance between the actual location of lung nodule during the procedure and preprocedural CT chest is the main factor impacting accurate biopsies. The utilization of advanced imaging tools with navigation-based bronchoscopy has been shown to assist with localizing targets in real-time and improving biopsy success. However, it is important for interventional bronchoscopists to understand the strengths and limitations of these advanced imaging technologies.

Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis

BACKGROUND

There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (CADx) models, and assess their diagnostic performance for predicting the risk of malignancy in computed tomography (CT)-detected pulmonary nodules.

METHODS

An electronic search was performed in four databases (from inception to 10 August 2023). Studies were eligible if they were peer-reviewed experimental or observational articles comparing the diagnostic performance of externally validated DL-based CADx models with models widely used in clinical practice to predict the risk of malignancy. A bivariate random-effect approach for the meta-analysis on the included studies was used.

RESULTS

Seventeen studies were included, comprising 8553 participants and 9884 nodules. Pooled analyses showed DL-based CADx models were 11.6% more sensitive than physician judgement alone, and 14.5% more than clinical risk models alone. They had a similar pooled specificity to physician judgement alone [0.77 (95% CI 0.68-0.84) v 0.81 (95% CI 0.71-0.88)], and were 7.4% more specific than clinical risk models alone. They had superior pooled areas under the receiver operating curve (AUC), with relative pooled AUCs of 1.03 (95% CI 1.00-1.07) and 1.10 (95% CI 1.07-1.13) versus physician judgement and clinical risk models alone, respectively.

CONCLUSION

DL-based models are already used in clinical practice in certain settings for nodule management. Our results show their diagnostic performance potentially justifies wider, more routine deployment alongside experienced physician readers to help inform multidisciplinary team decision-making.

Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT

BACKGROUND

Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR).

METHODS

Individuals were selected from the "Lifelines" cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30-100 mm3 and 101-300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups.

RESULTS

Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57-0.77) in emphysema versus 0.71 (0.62-0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65-0.84) and 0.80 (0.72-0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30-100 mm3 nodules in non-emphysema (p = 0.009).

CONCLUSIONS

AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR.

RELEVANCE STATEMENT

In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs.

KEY POINTS

• The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI.

Multidisciplinary virtual management of pulmonary nodules

INTRODUCTION AND OBJECTIVES

Multidisciplinary nodule clinics provide high-quality care and favor adherence to guidelines. Virtual care has shown savings benefits along with patient satisfaction. Our aim is to describe the first year of operation of a multidisciplinary virtual lung nodule clinic, the population evaluated and issued decisions. Secondarily, among discharged patients, we aimed to analyze their follow-up prior to the existence of our consultation, evaluating its adherence to guidelines.

MATERIALS AND METHODS

Observational study including all patients evaluated at the Virtual Lung Nodule Clinic (VLNC) (March 2018- March 2019). Clinical and radiological data were recorded. Recommendations, based on 2017 Fleischner Society guidelines, were categorized into follow-up, discharge or referral to lung cancer consultation. Discharged patients were classified according to adherence to guidelines of their previous management, into adequate, prolonged and non-indicated follow-up.

RESULTS

A total of 365 patients (58.9% men; median age 64.0 years) were included. Sixty-four percent had smoking history and 23% had chronic obstructive pulmonary disease (COPD). Most nodules were solid (87.4%) and multiple (57.5%). The median diameter was 6.00 mm. 43.8% of patients were discharged following first VLNC evaluation. Among them, 27.5% had received appropriate follow-up, but 66.9% had received poor management. Patients with prolonged follow-up (33.1%) were older (67.0 vs 60.5 years) and had larger nodules (6.00 mm vs 5.00). Non-indicated follow-up patients (33.8%) were more non-smokers (77.8% vs 31.8%) and presented smaller nodules (4.00 vs 5.00 mm).

CONCLUSIONS

During its first year of operation, the VLNC has evaluated a population with a relevant risk profile for lung cancer development, management of which should be cautious and adhere to guidelines. After the first VLNC assessment, approximately one-half of this population was discharged. It was noticeable that previous follow-up of discharged patients was found poorly adherent to guidelines, with a marked tendency to overmanagement.

Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules

OBJECTIVES

The purpose of this study was to determine the influence of dose reduction on a commercially available lung cancer prediction convolutional neuronal network (LCP-CNN).

METHODS

CT scans from a cohort provided by the local lung cancer center (n = 218) with confirmed pulmonary malignancies and their corresponding reduced dose simulations (25% and 5% dose) were subjected to the LCP-CNN. The resulting LCP scores (scale 1-10, increasing malignancy risk) and the proportion of correctly classified nodules were compared. The cohort was divided into a low-, medium-, and high-risk group based on the respective LCP scores; shifts between the groups were studied to evaluate the potential impact on nodule management. Two different malignancy risk score thresholds were analyzed: a higher threshold of ≥ 9 ("rule-in" approach) and a lower threshold of > 4 ("rule-out" approach).

RESULTS

In total, 169 patients with 196 nodules could be included (mean age ± SD, 64.5 ± 9.2 year; 49% females). Mean LCP scores for original, 25% and 5% dose levels were 8.5 ± 1.7, 8.4 ± 1.7 (p > 0.05 vs. original dose) and 8.2 ± 1.9 (p < 0.05 vs. original dose), respectively. The proportion of correctly classified nodules with the "rule-in" approach decreased with simulated dose reduction from 58.2 to 56.1% (p = 0.34) and to 52.0% for the respective dose levels (p = 0.01). For the "rule-out" approach the respective values were 95.9%, 96.4%, and 94.4% (p = 0.12). When reducing the original dose to 25%/5%, eight/twenty-two nodules shifted to a lower, five/seven nodules to a higher malignancy risk group.

CONCLUSION

CT dose reduction may affect the analyzed LCP-CNN regarding the classification of pulmonary malignancies and potentially alter pulmonary nodule management.

CLINICAL RELEVANCE STATEMENT

Utilization of a "rule-out" approach with a lower malignancy risk threshold prevents underestimation of the nodule malignancy risk for the analyzed software, especially in high-risk cohorts.

KEY POINTS

• LCP-CNN may be affected by CT image parameters such as noise resulting from low-dose CT acquisitions. • CT dose reduction can alter pulmonary nodule management recommendations by affecting the outcome of the LCP-CNN. • Utilization of a lower malignancy risk threshold prevents underestimation of pulmonary malignancies in high-risk cohorts.

Transbronchial Microwave Ablation of Peripheral Lung Tumors: The NAVABLATE Study

BACKGROUND

Image-guided thermal ablation is a minimally invasive local therapy for lung malignancies. NAVABLATE characterized the safety and performance of transbronchial microwave ablation (MWA) in the lung.

METHODS

The prospective, single-arm, 2-center NAVABLATE study (NCT03569111) evaluated transbronchial MWA in patients with histologically confirmed lung malignancies ≤30 mm in maximum diameter who were not candidates for, or who declined, both surgery and stereotactic body radiation therapy. Ablation of 1 nodule was allowed per subject. The nodule was reached with electromagnetic navigation bronchoscopy. Cone-beam computed tomography was used to verify the ablation catheter position and to evaluate the ablation zone postprocedure. The primary end point was composite adverse events related to the transbronchial MWA device through 1-month follow-up. Secondary end points included technical success (nodule reached and ablated according to the study protocol) and technique efficacy (satisfactory ablation based on 1-month follow-up imaging).

RESULTS

Thirty subjects (30 nodules; 66.7% primary lung, 33.3% oligometastatic) were enrolled from February 2019 to September 2020. The pre-procedure median nodule size was 12.5 mm (range 5 to 27 mm). Procedure-day technical success was 100% (30/30), with a mean ablative margin of 9.9±2.7 mm. One-month imaging showed 100% (30/30) technique efficacy. The composite adverse event rate related to the transbronchial MWA device through 1-month follow-up was 3.3% (1 subject, mild hemoptysis). No deaths or pneumothoraces occurred. Four subjects (13.3%) experienced grade 3 complications; none had grade 4 or 5.

CONCLUSION

Transbronchial microwave ablation is an alternative treatment modality for malignant lung nodules ≤30 mm. There were no deaths or pneumothorax. In all, 13.3% of patients developed grade 3 or above complications.

Outcomes in Incidentally Versus Screening Detected Stage I Lung Cancer Surgery Patients

INTRODUCTION

Although the importance of lung cancer screening for early diagnosis is established, because of poor enrollment, incidental findings still play a role in diagnosis of patients who qualify. Nevertheless, analysis of this incidental cohort is lacking. We present a retrospective analysis comparing patients with thoracic surgery with incidental versus screening detected stage I lung cancer.

METHODS

Thoracic surgery cases at Mount Sinai Hospital from March, 1, 2012, to June, 30, 2022, were queried for patients eligible for lung cancer screening and a stage I diagnosis. The basis of lung nodule detection (incidental versus screening detected) was identified. We compared demographic variables, comorbidities, tumor staging, procedure details, and postoperative outcomes between the cohorts.

RESULTS

Of the patients eligible for screening with lung cancer resection and stage I diagnosis at Mount Sinai, 153 were identified incidentally and 67 through screening. The patients in the incidental cohort were older (p = 0.005), more likely to have quit smoking (p = 0.04), and had a greater number of comorbidities (p = 0.0002). There was no statistically significant difference between the groups with regard to pack-year smoking history, lung cancer histological type, location or size of tumor, and surgical approach, length of surgery or stay, number of postoperative outcomes, and survival.

CONCLUSIONS

In stage I lung cancers, no significant differences were identified between incidentally and screening detected lung nodules with regard to tumor characteristics, surgical approach, and postoperative outcomes. Imaging conducted for other reasons should be considered as a valid and important diagnostic tool, similar to traditional low-dose computed tomography, in patients who qualify for screening.

A Nasal Swab Classifier to Evaluate the Probability of Lung Cancer in Patients With Pulmonary Nodules

BACKGROUND

Accurate assessment of the probability of lung cancer (pCA) is critical in patients with pulmonary nodules (PNs) to help guide decision-making. We sought to validate a clinical-genomic classifier developed using whole-transcriptome sequencing of nasal epithelial cells from patients with a PN ≤ 30 mm who smoke or have previously smoked.

RESEARCH QUESTION

Can the pCA in individuals with a PN and a history of smoking be predicted by a classifier that uses clinical factors and genomic data from nasal epithelial cells obtained by cytologic brushing?

STUDY DESIGN AND METHODS

Machine learning was used to train a classifier using genomic and clinical features on 1,120 patients with PNs labeled as benign or malignant established by a final diagnosis or a minimum of 12 months of radiographic surveillance. The classifier was designed to yield low-, intermediate-, and high-risk categories. The classifier was validated in an independent set of 312 patients, including 63 patients with a prior history of cancer (other than lung cancer), comparing the classifier prediction with the known clinical outcome.

RESULTS

In the primary validation set, sensitivity and specificity for low-risk classification were 96% and 42%, whereas sensitivity and specificity for high-risk classification was 58% and 90%, respectively. Sensitivity was similar across stages of non-small cell lung cancer, independent of subtype. Performance compared favorably with clinical-only risk models. Analysis of 63 patients with prior cancer showed similar performance as did subanalyses of patients with light vs heavy smoking burden and those eligible for lung cancer screening vs those who were not.

INTERPRETATION

The nasal classifier provides an accurate assessment of pCA in individuals with a PN ≤ 30 mm who smoke or have previously smoked. Classifier-guided decision-making could lead to fewer diagnostic procedures in patients without cancer and more timely treatment in patients with lung cancer.

Comparative Study of Indocyanine Green Fluorescence Imaging in Lung Cancer with Near-Infrared-I/II Windows

BACKGROUND

We compare the application of intravenous indocyanine green (ICG) fluorescence imaging in lung cancer with near-infrared-I (NIR-I) and near-infrared-II (NIR-II) windows.

METHODS

From March to December 2022, we enrolled patients who received an intravenous injection of ICG (5 mg/kg) 1 day before the planned lung cancer surgery. The lung cancer nodules were imaged by NIR-I/II fluorescence imaging systems, and the tumor-to-normal-tissue ratio (TNR) was calculated. In addition, the fluorescence intensity and signal-to-background ratio (SBR) of capillary glass tubes containing ICG covered with different thicknesses of lung tissue were measured by NIR-I/II fluorescence imaging systems.

RESULTS

In this study, 102 patients were enrolled, and the mean age was 59.9 ± 9.2 years. A total of 96 (94.1%) and 98 (96.1%) lung nodules were successfully imaged with NIR-I and NIR-II fluorescence, and the TNR of NIR-II was significantly higher than that of NIR-I (3.9 ± 1.3 versus 2.4 ± 0.6, P < 0.001). In multiple linear regression, solid nodules (P < 0.001) and squamous cell carcinoma (P < 0.001) were independent predictors of a higher TNR of NIR-I/II. When capillary glass tubes were covered with lung tissue whose thickness was more than 2 mm, the fluorescence intensity and the SBR of NIR-II were significantly higher than those of NIR-I.

CONCLUSIONS

We verified the feasibility of NIR-II fluorescence imaging in intravenous ICG lung cancer imaging for the first time. NIR-II fluorescence can improve the TNR and penetration depth of lung cancer with promising clinical prospects.

Association of patient and health care organization factors with incidental nodule guidelines adherence: A multi-system observational study

BACKGROUND

Health care organizations are increasingly developing systems to ensure patients with pulmonary nodules receive guideline-adherent care. Our goal was to determine patient and organization factors that are associated with radiologist adherence as well as clinician and patient concordance to 2005 Fleischner Society guidelines for incidental pulmonary nodule follow-up.

MATERIALS

Trained researchers abstracted data from the electronic health record from two Veterans Affairs health care systems for patients with incidental pulmonary nodules as identified by interpreting radiologists from 2008 to 2016.

METHODS

We classified radiology reports and patient follow-up into two categories. Radiologist-Fleischner Adherence was the agreement between the radiologist's recommendation in the computed tomography report and the 2005 Fleischner Society guidelines. Clinician/Patient-Fleischner Concordance was agreement between patient follow-up and the guidelines. We calculated multivariable-adjusted predicted probabilities for factors associated with Radiologist-Fleischner Adherence and Clinician/Patient-Fleischner Concordance.

RESULTS

Among 3150 patients, 69% of radiologist recommendations were adherent to 2005 Fleischner guidelines, 4% were more aggressive, and 27% recommended less aggressive follow-up. Overall, only 48% of patients underwent follow-up concordant with 2005 Fleischner Society guidelines, 37% had less aggressive follow-up, and 15% had more aggressive follow-up. Radiologist-Fleischner Adherence was associated with Clinician/Patient-Fleischner Concordance with evidence for effect modification by health care system.

CONCLUSION

Clinicians and patients seem to follow radiologists' recommendations but often do not obtain concordant follow-up, likely due to downstream differential processes in each health care system. Health care organizations need to develop comprehensive and rigorous tools to ensure high levels of appropriate follow-up for patients with pulmonary nodules.

Development of the Korean Association for Lung Cancer Clinical Practice Guidelines: Recommendations on Radial Probe Endobronchial Ultrasound for Diagnosing Lung Cancer - An Updated Meta-Analysis

PURPOSE

Radial probe endobronchial ultrasound (RP-EBUS) accurately locates peripheral lung lesions (PLLs) during transbronchial biopsy (TBB). We performed an updated meta-analysis of the diagnostic yield of TBB for PLLs using RP-EBUS to generate recommendations for the development of the Korean Association of Lung Cancer guidelines.

MATERIALS AND METHODS

We systematically searched MEDLINE and EMBASE (from January 2013 to December 2022), and performed a meta-analysis using R software. The diagnostic yield was evaluated by dividing the number of successful diagnoses by the total lesion number. Subgroup analysis was performed to identify related factors.

RESULTS

Forty-one studies with a total of 13,133 PLLs were included. The pooled diagnostic yield of RP-EBUS was 0.72 (95% confidence interval [CI], 0.70 to 0.75). Significant heterogeneity was observed among studies (χ2=292.38, p < 0.01, I2=86.4%). In a subgroup analysis, there was a significant difference in diagnostic yield based on RP-EBUS findings (within, adjacent to, invisible), with a risk ratio of 1.45 (95% CI, 1.23 to 1.72) between within and adjacent to, 4.20 (95% CI, 1.89 to 9.32) between within and invisible, and 2.59 (95% CI, 1.32 to 5.01) between adjacent to and invisible. There was a significant difference in diagnostic yield based on lesion size, histologic diagnosis, computed tomography (CT) bronchus sign, lesion character, and location from the hilum. The overall complication rate of TBB with RP-EBUS was 6.8% (bleeding, 4.5%; pneumothorax, 1.4%).

CONCLUSION

Our study showed that TBB with RP-EBUS is an accurate diagnostic tool for PLLs with good safety profiles, especially for PLLs with within orientation on RP-EBUS or positive CT bronchus sign.

Does FDG-PET/CT for incidentally found pulmonary lesions lead to a cascade of more incidental findings?

OBJECTIVE

To determine the frequency, nature, and downstream healthcare costs of new incidental findings that are found on whole-body FDG-PET/CT in patients with a non-FDG-avid pulmonary lesion ≥10 mm that was incidentally found on previous imaging.

MATERIALS AND METHODS

This retrospective study included a consecutive series of patients who underwent whole-body FDG-PET/CT because of an incidentally found pulmonary lesion ≥10 mm.

RESULTS

Seventy patients were included, of whom 23 (32.9 %) had an incidentally found pulmonary lesion that proved to be non-FDG-avid. In 12 of these 23 cases (52.2 %) at least one new incidental finding was discovered on FDG-PET/CT. The total number of new incidental findings was 21, of which 7 turned out to be benign, 1 proved to be malignant (incurable metastasized cancer), and 13 whose nature remained unclear. One patient sustained permanent neurologic impairment of the left leg due to iatrogenic nerve damage during laparotomy for an incidental finding which turned out to be benign. The total costs of all additional investigations due to the detection of new incidental findings amounted to €9903.17, translating to an average of €141.47 per whole-body FDG-PET/CT scan performed for the evaluation of an incidentally found pulmonary lesion.

CONCLUSION

In many patients in whom whole-body FDG-PET/CT was performed to evaluate an incidentally found pulmonary lesion that turned out to be non-FDG-avid and therefore very likely benign, FDG-PET/CT detected new incidental findings in our preliminary study. Whether the detection of these new incidental findings is cost-effective or not, requires further research with larger sample sizes.

Unlocking the Value: Quantifying the Return on Investment of Hospital Artificial Intelligence

PURPOSE

A comprehensive return on investment (ROI) calculator was developed to evaluate the monetary and nonmonetary benefits of an artificial intelligence (AI)-powered radiology diagnostic imaging platform to inform decision makers interested in adopting AI.

METHODS

A calculator was constructed to calculate comparative costs, estimated revenues, and quantify the clinical value of using an AI platform compared with no use of AI in radiology workflows of a US hospital over a 5-year time horizon. Parameters were determined on the basis of expert interviews and a literature review. Scenario and deterministic sensitivity analyses were conducted to evaluate calculator drivers.

RESULTS

In the calculator, the introduction of an AI platform into the hospital radiology workflow resulted in labor time reductions and delivery of an ROI of 451% over a 5-year period. The ROI was increased to 791% when radiologist time savings were considered. Time savings for radiologists included more than 15 8-hour working days of waiting time, 78 days in triage time, 10 days in reading time, and 41 days in reporting time. Using the platform also provided revenue benefits for the hospital in bringing in patients for clinically beneficial follow-up scans, hospitalizations, and treatment procedures. Results were sensitive to the time horizon, health center setting, and number of scans performed. Among those, the most influential outcome was the number of additional necessary treatments performed because of AI identification of patients.

CONCLUSIONS

The authors demonstrate a substantial 5-year ROI of implementing an AI platform in a stroke management-accredited hospital. The ROI calculator may be useful for decision makers evaluating AI-powered radiology platforms.

Assessment of Advanced Diagnostic Bronchoscopy Outcomes for Peripheral Lung Lesions: A Delphi Consensus Definition of Diagnostic Yield and Recommendations for Patient-centered Study Designs. An Official American Thoracic Society/American College of Chest Physicians Research Statement

Background: Advanced diagnostic bronchoscopy targeting the lung periphery has developed at an accelerated pace over the last two decades, whereas evidence to support introduction of innovative technologies has been variable and deficient. A major gap relates to variable reporting of diagnostic yield, in addition to limited comparative studies. Objectives: To develop a research framework to standardize the evaluation of advanced diagnostic bronchoscopy techniques for peripheral lung lesions. Specifically, we aimed for consensus on a robust definition of diagnostic yield, and we propose potential study designs at various stages of technology development. Methods: Panel members were selected for their diverse expertise. Workgroup meetings were conducted in virtual or hybrid format. The cochairs subsequently developed summary statements, with voting proceeding according to a modified Delphi process. The statement was cosponsored by the American Thoracic Society and the American College of Chest Physicians. Results: Consensus was reached on 15 statements on the definition of diagnostic outcomes and study designs. A strict definition of diagnostic yield should be used, and studies should be reported according to the STARD (Standards for Reporting Diagnostic Accuracy Studies) guidelines. Clinical or radiographic follow-up may be incorporated into the reference standard definition but should not be used to calculate diagnostic yield from the procedural encounter. Methodologically robust comparative studies, with incorporation of patient-reported outcomes, are needed to adequately assess and validate minimally invasive diagnostic technologies targeting the lung periphery. Conclusions: This American Thoracic Society/American College of Chest Physicians statement aims to provide a research framework that allows greater standardization of device validation efforts through clearly defined diagnostic outcomes and robust study designs. High-quality studies, both industry and publicly funded, can support subsequent health economic analyses and guide implementation decisions in various healthcare settings.

Exploring the Diagnostic Dilemma of Indeterminate Pulmonary Nodules in Patients with Primary Sarcoma of Bone

Introduction

Bone sarcomas are known to have a predilection for pulmonary metastasis. Surveillance protocols are thus focused on periodic chest imaging, typically with CT scan. Pulmonary nodules can be easily identified with this modality, but smaller nodules are not readily biopsied and may not represent metastatic disease. These are called indeterminate. The natural history of indeterminate nodules in a bone sarcoma population and factors associated with progression to true metastatic disease are not clearly defined.

Methods

All bone sarcoma patients treated at a single institution from 2010 to 2020 were eligible for inclusion. We treated 327 patients over this period; 119 were excluded for age less than 16 years, 31 were excluded for evident metastatic disease at presentation, and 60 were excluded for incomplete clinical follow-up or CT chest imaging either at staging or in surveillance. We assessed chest CT images for presence of pulmonary nodules and selected variables both at the staging and on surveillance images. Nodules were considered metastatic if proven histologically with a biopsy or by clinical interpretation by the multidisciplinary sarcoma team. Clinical and imaging factors were assessed for the association of indeterminate nodule progression to true metastatic disease.

Results

Seventy three of the 117 patients had indeterminate nodules on their staging CT scan; 41.1% of those patients progressed to metastatic disease compared to 43.2% of the patients that did not have indeterminate nodules on staging CT. Fifty eight of the 117 patients developed indeterminate nodules on surveillance chest CT, and 55.2% of those patients progressed to metastatic disease. There were no clinical or imaging factors that predicted the development of metastatic disease in the group that had indeterminate nodules at presentation; however, the number and size of nodules did correlate with progression to metastasis in those that developed indeterminate nodules on surveillance.

Conclusion

Indeterminate pulmonary nodules are common on staging CT scans in patients with a bone sarcoma. The presence or absence of these indeterminate nodules was not predictive of progression to true metastatic disease in this cohort. However, the development of indeterminate nodules on surveillance imaging was associated with progression to metastatic disease with the size and number of nodules being important factors.

The Lung Cancer Prediction Model "Stress Test": Assessment of Models' Performance in a High-Risk Prospective Pulmonary Nodule Cohort

BACKGROUND

Pulmonary nodules represent a growing health care burden because of delayed diagnosis of malignant lesions and overtesting for benign processes. Clinical prediction models were developed to inform physician assessment of pretest probability of nodule malignancy but have not been validated in a high-risk cohort of nodules for which biopsy was ultimately performed.

RESEARCH QUESTION

Do guideline-recommended prediction models sufficiently discriminate between benign and malignant nodules when applied to cases referred for biopsy by navigational bronchoscopy?

STUDY DESIGN AND METHODS

We assembled a prospective cohort of 322 indeterminate pulmonary nodules in 282 patients referred to a tertiary medical center for diagnostic navigational bronchoscopy between 2017 and 2019. We calculated the probability of malignancy for each nodule using the Brock model, Mayo Clinic model, and Veterans Affairs (VA) model. On a subset of 168 patients who also had PET-CT scans before biopsy, we also calculated the probability of malignancy using the Herder model. The performance of the models was evaluated by calculating the area under the receiver operating characteristic curves (AUCs) for each model.

RESULTS

The study cohort contained 185 malignant and 137 benign nodules (57% prevalence of malignancy). The malignant and benign cohorts were similar in terms of size, with a median longest diameter for benign and malignant nodules of 15 and 16 mm, respectively. The Brock model, Mayo Clinic model, and VA model showed similar performance in the entire cohort (Brock AUC, 0.70; 95% CI, 0.64-0.76; Mayo Clinic AUC, 0.70; 95% CI, 0.64-0.76; VA AUC, 0.67; 95% CI, 0.62-0.74). For 168 nodules with available PET-CT scans, the Herder model had an AUC of 0.77 (95% CI, 0.68-0.85).

INTERPRETATION

Currently available clinical models provide insufficient discrimination between benign and malignant nodules in the common clinical scenario in which a patient is being referred for biopsy, especially when PET-CT scan information is not available.

CT-guided microcoil localization of pulmonary nodules before VATS: clinical experience in 1059 patients

OBJECTIVE

To retrospectively evaluate the efficacy and safety of CT-guided microcoil localization of pulmonary nodules before video-assisted thoracoscopic surgery (VATS).

METHODS

A total of 1059 consecutive patients with 1331 pulmonary nodules treated between July 2018 and April 2021 were included in this study. Of the 1331 nodules, 1318 were localized using the tailed method and 13 were localized using the non-tailed method. The localization technical success rate and complications of the microcoil localization procedure were assessed. Univariate and multivariate logistic regression analyses were used to determine potential risk factors for technical failure, pneumothorax, and pulmonary hemorrhage.

RESULTS

The technical success rate of the localization procedure was 98.4% (1310/1331 nodules). Nodule location in the lower lobes (p = 0.015) and need for a longer needle path (p < 0.001) were independent predictors of technical failure. All localization procedure-related complications were minor (grade 1 or 2) adverse events, with the exception of one grade 3 complication. The most common complications were pneumothorax (302/1331 nodules [22.7%]) and pulmonary hemorrhage (328/1331 nodules [24.6%]). Male sex (p = 0.001), nodule location in the middle (p = 0.003) and lower lobes (p = 0.025), need for a longer needle path (p < 0.001), use of transfissural puncture (p = 0.042), and simultaneous multiple localizations (p < 0.001) were independent risk factors for pneumothorax. Female sex (p = 0.015), younger age (p = 0.023), nodules location in the upper lobes (p = 0.011), and longer needle path (p < 0.001) were independent risk factors for pulmonary hemorrhage.

CONCLUSIONS

CT-guided microcoil localization of pulmonary nodules before VATS using either the tailed or non-tailed method is effective and safe.

CLINICAL RELEVANCE STATEMENT

CT-guided microcoil localization of pulmonary nodules before VATS resection is effective and safe when using either the tailed or non-tailed method. Nodules requiring transfissural puncture and multiple nodules requiring simultaneous localizations can also be successfully localized with this method.

KEY POINTS

• Pre-VATS CT-guided microcoil localization of pulmonary nodules by tailed or non-tailed method was effective and safe. • When the feasible puncture path was beyond the scope of wedge resection, localization could be performed using the non-tailed method. • Although transfissural puncture and simultaneous multiple localization were independent risk factors for pneumothorax, they remained clinically feasible.

An International Survey of Practices in the Investigation and Endoscopic Treatment of Peripheral Pulmonary Lesions amongst Interventional Bronchoscopists

INTRODUCTION

The investigation of peripheral pulmonary lesions (PPLs) can be challenging. Several bronchoscopic modalities have been developed to reach and biopsy PPL but the level of adoption of these techniques by interventional pulmonologists (IPs) is unknown. This international survey was conducted to describe current practices in PPL investigation among IP.

METHODS

This survey was sent to all members of the World Association for Bronchology and Interventional Pulmonology, Canadian Thoracic Society Procedures Assembly, AABIP, and the Groupe d'Endoscopie Thoracique et Interventionnel Francophone. The survey was composed of 48 questions and three clinical cases to establish a portrait of modalities used to investigate and treat PPL by IP around the world.

RESULTS

Three hundred and twelve IP responded to the survey. Most of them practice in Europe (n = 122), North America (n = 97), and Asia (n = 49). Half of responders perform more than 100 endoscopic procedures for PPL annually. General anesthesia and conscious sedation are used in similar proportions (53% and 47%, respectively). Rapid on site evaluation (ROSE) is used when sampling PPL by 42%. Radial EBUS (69%), fluoroscopy (55%), and electromagnetic navigation (27%) are the most widely used techniques. Most IP combine techniques (89%). Robotic bronchoscopy (15%) and cone-beam CT (8%) are almost exclusively used in the USA where, respectively, 60% and 37% of respondents reported using these modalities. Ten percent of IP currently had access to endoscopic treatment modalities for PPL. However, half of the remaining IP plan to acquire an endoscopic treatment modality in the next 2 years.

CONCLUSION

Available techniques and practices worldwide vary significantly regarding PPL investigation and treatment.

Evaluation of Pulmonary Nodules by Radiologists vs. Radiomics in Stand-Alone and Complementary CT and MRI

Increased attention has been given to MRI in radiation-free screening for malignant nodules in recent years. Our objective was to compare the performance of human readers and radiomic feature analysis based on stand-alone and complementary CT and MRI imaging in classifying pulmonary nodules. This single-center study comprises patients with CT findings of pulmonary nodules who underwent additional lung MRI and whose nodules were classified as benign/malignant by resection. For radiomic features analysis, 2D segmentation was performed for each lung nodule on axial CT, T2-weighted (T2w), and diffusion (DWI) images. The 105 extracted features were reduced by iterative backward selection. The performance of radiomics and human readers was compared by calculating accuracy with Clopper-Pearson confidence intervals. Fifty patients (mean age 63 +/- 10 years) with 66 pulmonary nodules (40 malignant) were evaluated. ACC values for radiomic features analysis vs. radiologists based on CT alone (0.68; 95%CI: 0.56, 0.79 vs. 0.59; 95%CI: 0.46, 0.71), T2w alone (0.65; 95%CI: 0.52, 0.77 vs. 0.68; 95%CI: 0.54, 0.78), DWI alone (0.61; 95%CI:0.48, 0.72 vs. 0.73; 95%CI: 0.60, 0.83), combined T2w/DWI (0.73; 95%CI: 0.60, 0.83 vs. 0.70; 95%CI: 0.57, 0.80), and combined CT/T2w/DWI (0.83; 95%CI: 0.72, 0.91 vs. 0.64; 95%CI: 0.51, 0.75) were calculated. This study is the first to show that by combining quantitative image information from CT, T2w, and DWI datasets, pulmonary nodule assessment through radiomics analysis is superior to using one modality alone, even exceeding human readers' performance.

Incidental pulmonary nodules may lead to a high proportion of early-stage lung cancer: but it requires more than a high CT volume to achieve this

Background

The management of pulmonary nodules plays a critical role in early detection of lung cancer. Computed tomography (CT) has led to a stage-shift towards early-stage lung cancer, but regional differences in survival rates have been reported in Denmark. This study aimed to evaluate whether variations in nodule management among Danish health regions contributed to these differences.

Material and Methods

The Danish Health Data Authority and Danish Lung Cancer Registry provided data on CT usage and lung cancer stage distribution, respectively. Auditing of lung cancer stage IA patient referrals and nodule management of stage IV lung cancer patients was conducted in seven Danish lung cancer investigation centers, covering four of the five Danish health regions. CT scans were performed up to 2 years before the patients' diagnosis from 2019 to 2021.

Results

CT usage has increased steadily in Denmark over the past decade, with a simultaneous increase in the proportion of early-stage lung cancers, particularly stage IA. However, one Danish health region, Region Zealand, exhibited lower rates of early-stage lung cancer and overall survival despite a CT usage roughly similar to that of the other health regions. The audit did not find significant differences in pulmonary nodule management or a higher number of missed nodules by radiologists in this region compared to others.

Conclusion

This study suggests that a high CT scan volume alone is not sufficient for the early detection of lung cancer. Factors beyond hospital management practices, such as patient-related delays in socioeconomically disadvantaged areas, may contribute to regional differences in survival rates. This has implications for future strategies for reducing these differences.

Signs of Nothing: Negotiations Over Semiotic Indeterminacy in Danish Lung Cancer Diagnostics

In Denmark, injunctions of "early" cancer diagnosis increasingly imply surveillance of small tissue changes, which may or may not develop into cancer. Based on fieldwork at diagnostic lung cancer clinics and with people in CT surveillance for tissue changes, I explore how detected tissue changes are ascribed meaning as signs of "nothing" or "something." Inspired by Peircean semiotics, I suggest that the semiotic indeterminacy of tissue changes points to how diagnostic socialities both expand medical semiotics and enable this expansion. The article, thereby, contributes to understandings of signs as diagnostic infrastructures.

Radiomics and artificial intelligence for risk stratification of pulmonary nodules: Ready for primetime?

Pulmonary nodules are ubiquitously found on computed tomography (CT) imaging either incidentally or via lung cancer screening and require careful diagnostic evaluation and management to both diagnose malignancy when present and avoid unnecessary biopsy of benign lesions. To engage in this complex decision-making, clinicians must first risk stratify pulmonary nodules to determine what the best course of action should be. Recent developments in imaging technology, computer processing power, and artificial intelligence algorithms have yielded radiomics-based computer-aided diagnosis tools that use CT imaging data including features invisible to the naked human eye to predict pulmonary nodule malignancy risk and are designed to be used as a supplement to routine clinical risk assessment. These tools vary widely in their algorithm construction, internal and external validation populations, intended-use populations, and commercial availability. While several clinical validation studies have been published, robust clinical utility and clinical effectiveness data are not yet currently available. However, there is reason for optimism as ongoing and future studies aim to target this knowledge gap, in the hopes of improving the diagnostic process for patients with pulmonary nodules.

Interventional Pulmonology: Extending the Breadth of Thoracic Care

Interventional pulmonary medicine has developed as a subspecialty focused on the management of patients with complex thoracic disease. Leveraging minimally invasive techniques, interventional pulmonologists diagnose and treat pathologies that previously required more invasive options such as surgery. By mitigating procedural risk, interventional pulmonologists have extended the reach of care to a wider pool of vulnerable patients who require therapy. Endoscopic innovations, including endobronchial ultrasound and robotic and electromagnetic bronchoscopy, have enhanced the ability to perform diagnostic procedures on an ambulatory basis. Therapeutic procedures for patients with symptomatic airway disease, pleural disease, and severe emphysema have provided the ability to palliate symptoms. The combination of medical and procedural expertise has made interventional pulmonologists an integral part of comprehensive care teams for patients with oncologic, airway, and pleural needs. This review surveys key areas in which interventional pulmonologists have impacted the care of thoracic disease through bronchoscopic intervention.

Diagnosis and treatment of high-risk bilateral lung ground-glass opacity nodules

In recent years, there has been a significant increase in the detection rate of Ground Glass Opacity (GGO) nodules through high-resolution computed tomography (HRCT). GGO is an imaging finding that encompasses various pathological types, some of which exhibit indolent growth, while others may represent early lung cancer or remain relatively stable, not significantly impacting the surgical treatment outcome. In clinical practice, patients often experience psychological anxiety when multiple pulmonary GGO nodules are present, and they may request simultaneous resection. However, there is currently no standardized criterion for determining when multiple GGO nodules should be resected. As personalized medicine continues to advance, the treatment approach for multiple pulmonary GGO nodules needs to prioritize accuracy. High-risk factors associated with multiple pulmonary GGO nodules may necessitate surgical intervention along with mediastinal lymph node dissection or sampling. This article provides a review of the characteristics, treatment methods, and clinical experiences related to multiple pulmonary GGO nodules, offering practical insights and guidance for healthcare professionals.

Robotic versus Electromagnetic bronchoscopy for pulmonary LesIon AssessmeNT: the RELIANT pragmatic randomized trial

BACKGROUND

Robotic-assisted bronchoscopy has recently emerged as an alternative to electromagnetic navigational bronchoscopy for the evaluation of peripheral pulmonary lesions. While robotic-assisted bronchoscopy is proposed to have several advantages, such as an easier learning curve, it is unclear if it has comparable diagnostic utility as electromagnetic navigational bronchoscopy.

METHODS

Robotic versus Electromagnetic bronchoscopy for pulmonary LesIon AssessmeNT (RELIANT) is an investigator-initiated, single-center, open label, noninferiority, cluster randomized controlled trial conducted in two operating rooms at Vanderbilt University Medical Center. Each operating room (OR) is assigned to either robotic-assisted or electromagnetic navigational bronchoscopy each morning, with each OR day considered one cluster. All patients undergoing diagnostic bronchoscopy for evaluation of a peripheral pulmonary lesion in one of the two operating rooms are eligible. Schedulers, patients, and proceduralists are blinded to daily group allocations until randomization is revealed for each operating room each morning. The primary endpoint is the diagnostic yield defined as the proportion of cases yielding lesional tissue. Secondary and safety endpoints include procedure duration and procedural complications. Enrolment began on March 6, 2023, and will continue until 202 clusters have been accrued, with expected enrolment of approximately 400 patients by the time of completion in March of 2024.

DISCUSSION

RELIANT is a pragmatic randomized controlled trial that will compare the diagnostic yield of the two most commonly used bronchoscopic approaches for sampling peripheral pulmonary lesions. This will be the first known cluster randomized pragmatic trial in the interventional pulmonology field and the first randomized controlled trial of robotic-assisted bronchoscopy.

TRIAL REGISTRATION

ClinicalTrials.gov registration (NCT05705544) on January 30, 2023.

Segmentectomy versus lobectomy in the United States: Outcomes after resection for first primary lung cancer and treatment patterns for second primary lung cancers

OBJECTIVE

The study objective was to identify whether the results of JCOG0802 could be generalized to US clinical settings.

METHODS

Patients diagnosed with clinical stage IA (≤2 cm) non-small cell lung cancer who underwent segmentectomy versus lobectomy (2004-2017) in the National Cancer Database were identified. Overall survival of patients in the National Cancer Database was assessed using propensity score-matched analysis. A separate analysis of the Surveillance Epidemiology End Results database was conducted to evaluate treatment patterns of second primary lung cancers among patients who underwent segmentectomy versus lobectomy for a first primary lung cancer.

RESULTS

Of the 23,286 patients in the National Cancer Database meeting inclusion criteria, 1397 (6.0%) underwent segmentectomy and 21,889 (94.0%) underwent lobectomy. In a propensity score-matched analysis of all patients in the study cohort, there were no significant differences in overall survival between patients undergoing segmentectomy versus lobectomy (5-year overall survival: 79.9% [95% CI, 76.7%-82.0%] vs 81.8% [95% CI, 78.7%-84.4%], log-rank: P = .72). In subgroup analyses by tumor grade and histologic subtype, segmentectomy was associated with similar overall survival compared with lobectomy in all subgroups evaluated. In a propensity score-matched analysis of patients in the Surveillance Epidemiology End Results database, there were no significant differences in treatment patterns of second primary lung cancers between patients who underwent segmentectomy and patients who underwent lobectomy for their first primary lung cancer.

CONCLUSIONS

In this national analysis of US patients diagnosed with stage IA (≤2 cm) non-small cell lung cancer, there were no significant differences in overall survival between segmentectomy and lobectomy in the overall cohort or in subgroup analyses by tumor grade or histologic subtype.

Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer

Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting.

Robotic-assisted Navigation Bronchoscopy: A Meta-Analysis of Diagnostic Yield and Complications

BACKGROUND

Robotic-assisted navigation bronchoscopy (RANB) is a novel method to biopsy lung nodules, with initial reports demonstrating excellent accuracy. We aimed to evaluate pooled estimates of diagnostic yields and complication rates with RANB by performing a meta-analysis of the available literature.

METHODS

We searched 3 databases, including PubMed, EmBase, and Web of Science. The resulting abstracts were reviewed by 2 investigators. Analyses were performed using random effects models, and diagnostic yield and complication rates were estimated after the Freeman-Tukey transformation.

RESULTS

A total of 23 articles, comprising 1409 patients and 1541 nodules, were included in the final analysis. Mean ages ranged from 63.2 to 69.3 years. The average size of the nodules ranged between 5.9 and 25.0 mm. Most patients (54.0% to 92.0%) had a current or prior smoking history in studies that reported them (n=8). The pooled diagnostic yield was 81.9% (12 studies, 838 nodules, 95% CI: 83.4%-91.0%), and the pooled sensitivity for malignancy was 87.6% (8 studies, 699 nodules, 95% CI: 81.3%-89.5%). The pooled incidence of pneumothorax rates was 0.60% (95% CI: 0.11%-1.35%). The pooled incidence of major bleeding was <0.01%.

CONCLUSION

Diagnostic yield for patients with pulmonary nodules undergoing RANB is high, though may be impacted by the prevalence of malignancy, participant selection, and publication bias. Complication rates, including pneumothoraces and bleeding rates, appear low across all studies. If RANB is available, clinicians should consider utilizing this platform to biopsy pulmonary nodules.

"Tool-in-lesion" Accuracy of Galaxy System-A Robotic Electromagnetic Navigation BroncHoscopy With Integrated Tool-in-lesion-Tomosynthesis Technology: The MATCH Study

BACKGROUND

The Galaxy System (Noah Medical) is a novel robotic endoluminal platform using electromagnetic navigation combined with integrated tomosynthesis technology and augmented fluoroscopy. It provides intraprocedural imaging to correct computerized tomography (CT) to body divergence and novel confirmation of tool-in-lesion (TIL). The primary aim of this study was to assess the TIL accuracy of the robotic bronchoscope with integrated digital tomosynthesis and augmented fluoroscopy.

METHODS

Four operators conducted the experiment using 4 pigs. Each physician performed between 4 and 6 nodule biopsies for 20 simulated lung nodules with purple dye and a radio pacifier. Using Galaxy's "Tool-in-Lesion Tomography (TOMO+)" with augmented fluoroscopy, the physician navigated to the lung nodules, and a tool (needle) was placed into the lesion. TIL was defined by the needle in the lesion determined by cone-beam CT.

RESULTS

The lung nodule's average size was 16.3 ± 0.97 mm and was predominantly in the lower lobes (65%). All 4 operators successfully navigated to all (100%) of the lesions in an average of 3 minutes and 39 seconds. The median number of tomosynthesis sweeps was 3 and augmented fluoroscopy was utilized in most cases (17/20 or 85%). TIL after the final TOMO sweep was 95% (19/20) and tool-touch-lesion was 5% (1/20). Biopsy yielding purple pigmentation was also 100% (20/20).

CONCLUSION

The Galaxy System demonstrated successful digital TOMO confirmed TIL success in 95% (19/20) of lesions and tool-touch-lesion in 5% (1/20) as confirmed by cone-beam CT. Successful diagnostic yield was achieved in 100% (20/20) of lesions as confirmed by intralesional pigment acquisition.

Advances in navigating to the nodule and targeting

PURPOSE OF REVIEW

The multitude of available platforms and imaging modalities for navigational bronchoscopy, in combination with the various sampling tools that can be used intra-procedurally, is complex. This review seeks to describe the recent developments in peripheral bronchoscopy in regards to navigation, imaging, and sampling target lesions in the pulmonary parenchyma.

RECENT FINDINGS

Robotic assisted bronchoscopy has improved navigation to the peripheral airways for sampling of peripheral parenchymal lesions. These navigational platforms use innovative technology utilizing electromagnetic navigation and shape-sensing technology for guidance. The greatest improvement has been the stabilization of the robotic scope in the periphery to allow for accurate sampling. Despite improvements in these platforms, limitations of CT to body divergence continue to impact navigation to the lesion and therefore diagnostic yield of the procedure. Advanced intraprocedural imaging with cone beam CT or augmented fluoroscopy has been a recent focus to improve this area. Further, the adoption of newer sampling tools, such as cryobiopsy, offers the possibility of increased diagnostic yield.

SUMMARY

The developments in advanced bronchoscopy will impact the role of biopsy in the diagnosis of peripheral pulmonary parenchymal lesions.

Diagnostic Yield vs Diagnostic Accuracy for Peripheral Lung Biopsy Evaluation: Evidence Supporting a Future Pragmatic End Point

BACKGROUND

Diagnostic yield and accuracy endpoints have been used inconsistently in the evaluation of advanced diagnostic bronchoscopy devices and techniques, limiting between-study comparisons. In addition, diagnostic accuracy can be adjudicated only after prolonged clinical follow-up, which delays reporting on the performance of novel devices.

RESEARCH QUESTION

Will a conservative diagnostic yield definition result in few false-negative initial results to closely approximate diagnostic accuracy and represent a useful outcome for future studies of diagnostic utility?

METHODS

Commonly used definitions of diagnostic yield were applied to a prospective data set of consecutive peripheral pulmonary lesions sampled by navigational bronchoscopy from 2017 to 2019. All consider malignancy to be diagnostic but differ in their classification of nonmalignant biopsy findings, which were subcategorized as specific benign, nonspecific benign, or normal lung. Diagnostic yield calculations were also compared with diagnostic accuracy, defined as the proportion of biopsy specimens deemed diagnostic by each definition that were confirmed accurate through 2 years of follow-up.

RESULTS

A total of 450 biopsy specimens of lesions were analyzed. The prevalence of malignancy was 60.9% (274 of 450). On initial bronchoscopy pathology, there were 227 malignant diagnoses (50.4%), with a single false positive (0.4%). Among 104 biopsy specimens with specific benign findings, only two were false negative for malignancy (1.9%). There were 119 nonspecific benign biopsy specimens, with 46 false negatives for malignancy (38.7%). The discrepancy between diagnostic yield and accuracy was 0.7% for the conservative definition, which only considered malignant or specific benign findings as diagnostic.

INTERPRETATION

A conservative diagnostic yield definition excluding nonspecific benign diagnoses closely approximated diagnostic accuracy through 2 years' follow-up, with a less than 1% discrepancy. Using this conservative yield definition may allow for dissemination of reliable diagnostic utility data without protracted delays needed for follow-up data in this era of rapid technological change in advanced diagnostic bronchoscopy.

Developing a multi-institutional nomogram for assessing lung cancer risk in patients with 5-30 mm pulmonary nodules: a retrospective analysis

Background

The diagnosis of benign and malignant solitary pulmonary nodules based on personal experience has several limitations. Therefore, this study aims to establish a nomogram for the diagnosis of benign and malignant solitary pulmonary nodules using clinical information and computed tomography (CT) results.

Methods

Retrospectively, we collected clinical and CT characteristics of 1,160 patients with pulmonary nodules in Guang'an People's Hospital and the hospital affiliated with North Sichuan Medical College between 2019 and 2021. Among these patients, data from 773 patients with pulmonary nodules were used as the training set. We used the least absolute shrinkage and selection operator (LASSO) to optimize clinical and imaging features and performed a multivariate logistic regression to identify features with independent predictive ability to develop the nomogram model. The area under the receiver operating characteristic curve (AUC), C-index, decision curve analysis, and calibration plot were used to evaluate the performance of the nomogram model in terms of predictive ability, discrimination, calibration, and clinical utility. Finally, data from 387 patients with pulmonary nodules were utilized for validation.

Results

In the training set, the predictors for the nomogram were gender, density of the nodule, nodule diameter, lobulation, calcification, vacuole, vascular convergence, bronchiole, and pleural traction, selected through LASSO and logistic regression analysis. The resulting model had a C-index of 0.842 (95% CI [0.812-0.872]) and AUCs of 0.842 (95% CI [0.812-0.872]). In the validation set, the C-index was 0.856 (95% CI [0.811-0.901]), and the AUCs were 0.844 (95% CI [0.797-0.891]). Results from the calibration curve and clinical decision curve analyses indicate that the nomogram has a high fit and clinical benefit in both the training and validation sets.

Conclusion

The establishment of a nomogram for predicting the benign or malignant diagnosis of solitary pulmonary nodules by this study has shown good efficacy. Such a nomogram may help to guide the diagnosis, follow-up, and treatment of patients.

Outcome of Incidental Pulmonary Nodules in a Real-World Setting

OBJECTIVES

Early diagnosis of lung cancer is imperative to improve survival. Incidental pulmonary nodules (IPN) may represent early stages of lung cancer and appropriate follow-up and management of these nodules is important, but also very resource demanding. We aim to describe the results of the CT-based follow-up on a cohort of patients with IPN in terms of detected malignancies, the proportion undergoing invasive procedures, and the subsequent outcome.

MATERIALS AND METHODS

Retrospective cohort study of patients in a CT IPN follow-up program who underwent a needle biopsy of the lung from 2018 to 2021 at Aarhus University Hospital.

RESULTS

A total of 4181 patients with IPN were followed with CT control scans. Out of these 249 (6%) were diagnosed with lung cancer of which 224 (90%) were diagnosed as a result of the IPN follow-up. Seventy-five percent of the patients were diagnosed in stages I to II and curable treatment was possible in 77.9% of the patients. In the CT IPN follow-up program 449 patients underwent a CT guided needle biopsy. Out of these 190 patients underwent biopsy without the detection of malignancy, corresponding to 4.5% of the entire IPN population.

CONCLUSION

The cumulated incidence of lung cancer in our population in the IPN follow-up program was 6%. The probability of malignancy when undergoing an invasive procedure on an IPN was 55.7% of which lung cancer was vastly predominant. The majority of lung cancers were diagnosed in an early and potentially curable stage.

CT-Based Screening for Pulmonary Metastases in Head and Neck Squamous Cell Cancers: Diagnostic Accuracy and Cost Comparison with PET-CECT

This study's objective was to compare detection rates of radiograph, computed tomography (CT), and positron emission tomography-contrast-enhanced computed tomography (PET-CECT) for pulmonary metastasis/synchronous primary lung tumors in head and neck squamous cell cancer (HNSCC) and its association with clinico-radio-pathological factors. Our retrospective study included 837 HNSCC patients from January 2012 to December 2017. Lung nodules were characterized on CT as benign, indeterminate, and metastatic. The true detection rate and statistical significance of associated risk factors were calculated. Risk factors for metastasis were determined using univariate and multivariate logistic regression models. Seventy-five (8.9%) patients had pulmonary metastasis and 3 (0.3%) had second lung primary. Detection rate of pulmonary metastasis by CT was higher (sensitivity-97.3%, specificity-97.2%) as compared to radiograph (sensitivity 49% and specificity 89%). Correlation was found between pulmonary and extra-pulmonary metastasis and N classification (P = 0.01, P = 0.02) and positive low jugular node (P = 0.001, P = 0.001). Using PET-CECT in place of CT costed an extra outlay of 7,033,805 INR (95,551.85 USD) while detecting distant metastasis in only 4 (0.47%) extra cases. Chest CT is a useful pulmonary metastases screening tool in advanced HNSCC patients with reasonable imaging cost as compared to PET-CT.

Evaluation of Socioeconomic Disparities in Follow-Up Completion for Incidental Pulmonary Nodules

PURPOSE

The aim of this study was to evaluate the association between census tract-level measures of social vulnerability and residential segregation and incidental pulmonary nodule (IPN) follow-up.

METHODS

This retrospective cohort study included patients with IPNs ≥6 mm in size or multiple subsolid or ground-glass IPNs <6 mm (with nonoptional follow-up recommendations) diagnosed between January 1, 2018, and December 30, 2019, at a large urban tertiary center and followed for ≥2 years. Geographic sociodemographic context was characterized by the 2018 Centers for Disease Control and Prevention Social Vulnerability Index (SVI) and the index of concentration at the extremes (ICE), categorized in quartiles. Multivariable binomial regression models were used, with a primary outcome of inappropriate IPN follow-up (late or no follow-up). Models were also stratified by nodule risk.

RESULTS

The study consisted of 2,492 patients (mean age, 65.6 ± 12.6 years; 1,361 women). Top-quartile SVI patients were more likely to have inappropriate follow-up (risk ratio [RR], 1.24; 95% confidence interval [CI], 1.12-1.36) compared with the bottom quartile; risk was also elevated in top-quartile SVI subcategories of socioeconomic status (RR, 1.23; 95% CI, 1.13-1.34), Minority status and language (RR, 1.24; 95% CI, 1.03-1.48), housing and transportation (RR, 1.13; 95% CI, 1.02-1.26), and ICE (RR, 1.20; 95% CI, 1.11-1.30). Furthermore, top-quartile ICE was associated with greater risk for inappropriate follow-up among high-risk versus lower risk IPNs (RR, 1.33 [95% CI, 1.18-1.50] versus 1.13 [95% CI, 1.02-1.25]), respectively; P for interaction = .017).

CONCLUSIONS

Local social vulnerability and residential segregation are associated with inappropriate IPN follow-up and may inform policy or interventions tailored for neighborhoods.

Diagnostic Performance and Safety Profile of Robotic-assisted Bronchoscopy: A Systematic Review and Meta-Analysis

Rationale: Conventional electromagnetic navigation bronchoscopy and other guided bronchoscopic modalities have a very desirable safety profile, but their diagnostic yield is only 60-70% for pulmonary lesions. Recently, robotic-assisted bronchoscopy (RAB) platforms have been introduced to improve the diagnostic performance of bronchoscopic modalities. Objectives: To determine the diagnostic performance and safety profile of RAB (using shape-sensing and electromagnetic navigation-based platforms) by performing a systematic review and meta-analysis. Methods: The PubMed, Embase, and Google Scholar databases were searched to find studies that reported on the diagnostic performance and/or the safety profile of one of the RAB systems. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Meta-analysis was performed using MedCalc version 20.118. Pooled diagnostic yield was calculated using a Freeman-Tukey transformation. We planned to use a random-effects model if the I2 index was >40%. Results: Twenty-five studies were included: 20 including diagnostic and safety analyses and 5 including only safety analyses. The pooled diagnostic yield of RAB (20 studies, 1,779 lesions) was 84.3% (95% confidence interval, 81.1-87.2%). The I2 index was 65.6%. On the basis of our subgroup analyses, the heterogeneity was likely driven by differences in study designs (prospective vs. retrospective) and procedural protocols (such as different RAB systems). Lesion size > 2 cm, the presence of a computed tomography bronchus sign, and concentric radial endobronchial ultrasound view were associated with a statistically significant increase in the odds of diagnosis with RAB. The overall rates of pneumothorax, need for tube thoracostomy, and significant hemorrhage were 2.3%, 1.2%, and 0.5%, respectively. Conclusions: RAB systems have significantly increased the diagnostic yield of navigational bronchoscopy compared with conventional systems such as electromagnetic navigation bronchoscopy, but well-designed prospective studies are needed to better understand the impact of various factors, such as the use of three-dimensional imaging modalities, cryobiopsy, and specific ventilatory protocols, on the diagnostic yield of RAB.

The diagnosis performance of convolutional neural network in the detection of pulmonary nodules: a systematic review and meta-analysis

BACKGROUND

Pulmonary nodules are an early imaging indication of lung cancer, and early detection of pulmonary nodules can improve the prognosis of lung cancer. As one of the applications of machine learning, the convolutional neural network (CNN) applied to computed tomography (CT) imaging data improves the accuracy of diagnosis, but the results could be more consistent.

PURPOSE

To evaluate the diagnostic performance of CNN in assisting in detecting pulmonary nodules in CT images.

MATERIAL AND METHODS

PubMed, Cochrane Library, Web of Science, Elsevier, CNKI and Wanfang databases were systematically retrieved before 30 April 2023. Two reviewers searched and checked the full text of articles that might meet the criteria. The reference criteria are joint diagnoses by experienced physicians. The pooled sensitivity, specificity and the area under the summary receiver operating characteristic curve (AUC) were calculated by a random-effects model. Meta-regression analysis was performed to explore potential sources of heterogeneity.

RESULTS

Twenty-six studies were included in this meta-analysis, involving 2,391,702 regions of interest, comprising segmented images with a few wide pixels. The combined sensitivity and specificity values of the CNN model in detecting pulmonary nodules were 0.93 and 0.95, respectively. The pooled diagnostic odds ratio was 291. The AUC was 0.98. There was heterogeneity in sensitivity and specificity among the studies. The results suggested that data sources, pretreatment methods, reconstruction slice thickness, population source and locality might contribute to the heterogeneity of these eligible studies.

CONCLUSION

The CNN model can be a valuable diagnostic tool with high accuracy in detecting pulmonary nodules.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis

BACKGROUND

Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis.

METHODS

Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools.

RESULTS

In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers.

CONCLUSIONS

SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

Robotic navigational bronchoscopy in a thoracic surgery practice: Leveraging technology in the management of pulmonary nodules

Objectives

Robotic navigational bronchoscopy is increasingly used to improve diagnostic yield for pulmonary nodules compared with the 50% to 60% obtained by standard bronchoscopy; however, safety and efficacy data are limited to small series. The aim of this study was to evaluate diagnostic yield and clinical outcomes in a large multisurgeon single-center cohort.

Methods

All patients who underwent robotic navigational bronchoscopy and biopsy from September 2020 to October 2022 were identified from a prospective institutional registry. The primary outcome was diagnostic yield. The secondary outcome was diagnostic yield for molecular testing.

Results

A total of 503 nodules were biopsied during the study period. Median nodule size was 2.1 cm. Overall diagnostic yield was 87.9%. Factors associated with increased diagnostic yield were decreased time from date of planning computed tomography to procedure date (odds ratio, 0.98; 95% CI, 0.96-0.99; P = .04) and greater nodule size (odds ratio, 1.03; 95% CI, 1.01-1.07; P = .02) per 0.1-cm increment. Molecular analysis was sent in 101 patients and was sufficient in 90% of cases. Complications occurred in 22 (5%) patients, including 13 (3.1%) with pneumothoraxes (7 patients requiring a chest drain), and 5 (1.2%) patients had bleeding requiring intraprocedural bronchial intervention. A total of 41 patients were consented for biopsy and resection during a single anesthetic event. Four of these cases were stopped at robotic navigational bronchoscopy due to an alternative diagnosis. Mean length of stay was 3.4 ± 1.1 days. There were no major complications.

Conclusions

This study suggests robotic navigational bronchoscopy has a high diagnostic yield and obtains adequate tissue for molecular analysis critical for selection of targeted therapies. With careful patient selection robotic navigational bronchoscopy can be combined with surgery to treat lung cancer as a single procedure with low complication rates.

Navigational Bronchoscopy versus Computed Tomography-guided Transthoracic Needle Biopsy for the Diagnosis of Indeterminate Lung Nodules: protocol and rationale for the VERITAS multicenter randomized trial

Background

Lung nodule incidence is increasing. Many nodules require biopsy to discriminate between benign and malignant etiologies. The gold-standard for minimally invasive biopsy, computed tomography-guided transthoracic needle biopsy (CT-TTNB), has never been directly compared to navigational bronchoscopy, a modality which has recently seen rapid technological innovation and is associated with improving diagnostic yield and lower complication rate. Current estimates of the diagnostic utility of both modalities are based largely on non-comparative data with significant risk for selection, referral, and publication biases.

Methods

The VERITAS trial (na V igation E ndoscopy to R each Indeterminate lung nodules versus T ransthoracic needle A spiration, a randomized controlled S tudy) is a multicenter, 1:1 randomized, parallel-group trial designed to ascertain whether electromagnetic navigational bronchoscopy with integrated digital tomosynthesis is noninferior to CT-TTNB for the diagnosis of peripheral lung nodules 10-30 mm in diameter with pre-test probability of malignancy of at least 10%. The primary endpoint is diagnostic accuracy through 12 months follow-up. Secondary endpoints include diagnostic yield, complication rate, procedure duration, need for additional invasive diagnostic procedures, and radiation exposure.

Discussion

The results of this rigorously designed trial will provide high-quality data regarding the management of lung nodules, a common clinical entity which often represents the earliest and most treatable stage of lung cancer. Several design challenges are described. Notably, all nodules are centrally reviewed by an independent interventional pulmonology and radiology adjudication panel relying on pre-specified exclusions to ensure enrolled nodules are amenable to sampling by both modalities while simultaneously protecting against selection bias favoring either modality. Conservative diagnostic yield and accuracy definitions with pre-specified criteria for what non-malignant findings may be considered diagnostic were chosen to avoid inflation of estimates of diagnostic utility.

Trial registration

ClinicalTrials.gov NCT04250194.

Incidence of Clinically Relevant Solitary Pulmonary Nodules Utilizing a Universal Health Care System

INTRODUCTION

Solitary pulmonary nodules (SPNs) are common, but the clinical relevance of these nodules is unknown. Utilizing current screening guidelines, we sought to better characterize the national incidence of clinically important SPNs within the largest universal health care system in the nation.

MATERIALS AND METHODS

TRICARE data were queried to identify SPNs for ages 18-64 years. SPNs that had been diagnosed within a year with no prior oncologic history were included to ensure true incidence. A proprietary algorithm was applied to determine clinically significant nodules. Further analysis characterized incidence by age grouping, gender, region, military branch, and beneficiary status.

RESULTS

A total of 229,552 SPNs were identified with a 60% reduction seen after application of the clinical significance algorithm (N = 88,628). The incidence increased in each decade of life (all P < 0.01). Adjusted incident rate ratios were significantly higher for SPNs detected in the Midwest and Western regions. The incident rate ratio was also higher in females (1.05, confidence interval [CI] 1.018, P = 0.001) as well as non-active duty members (dependents = 1.4 and retired = 1.6, respectively, CIs 1.383-1.492 and 1.591-1.638, P < 0.01). The incidence calculated per 1,000 patients overall was 3.1/1,000. Ages 44-54 years had an incidence of 5.5/1,000 patients, which is higher than the previously reported incidence of < 5.0 nationally for the same age group.

CONCLUSIONS

This analysis represents the largest evaluation of SPNs to date combined with clinical relevance adjustment. These data suggest a higher incidence of clinically significant SPNs starting at an age of 44 years in nonmilitary or retired women localized to the Midwest and Western regions of the United States.

Trends in the incidence of pulmonary nodules in chest computed tomography: 10-year results from two Dutch hospitals

OBJECTIVE

To study trends in the incidence of reported pulmonary nodules and stage I lung cancer in chest CT.

METHODS

We analyzed the trends in the incidence of detected pulmonary nodules and stage I lung cancer in chest CT scans in the period between 2008 and 2019. Imaging metadata and radiology reports from all chest CT studies were collected from two large Dutch hospitals. A natural language processing algorithm was developed to identify studies with any reported pulmonary nodule.

RESULTS

Between 2008 and 2019, a total of 74,803 patients underwent 166,688 chest CT examinations at both hospitals combined. During this period, the annual number of chest CT scans increased from 9955 scans in 6845 patients in 2008 to 20,476 scans in 13,286 patients in 2019. The proportion of patients in whom nodules (old or new) were reported increased from 38% (2595/6845) in 2008 to 50% (6654/13,286) in 2019. The proportion of patients in whom significant new nodules (≥ 5 mm) were reported increased from 9% (608/6954) in 2010 to 17% (1660/9883) in 2017. The number of patients with new nodules and corresponding stage I lung cancer diagnosis tripled and their proportion doubled, from 0.4% (26/6954) in 2010 to 0.8% (78/9883) in 2017.

CONCLUSION

The identification of incidental pulmonary nodules in chest CT has steadily increased over the past decade and has been accompanied by more stage I lung cancer diagnoses.

CLINICAL RELEVANCE STATEMENT

These findings stress the importance of identifying and efficiently managing incidental pulmonary nodules in routine clinical practice.

KEY POINTS

• The number of patients who underwent chest CT examinations substantially increased over the past decade, as did the number of patients in whom pulmonary nodules were identified. • The increased use of chest CT and more frequently identified pulmonary nodules were associated with more stage I lung cancer diagnoses.

ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule

Incidental pulmonary nodules are common. Although the majority are benign, most are indeterminate for malignancy when first encountered making their management challenging. CT remains the primary imaging modality to first characterize and follow-up incidental lung nodules. This document reviews available literature on various imaging modalities and summarizes management of indeterminate pulmonary nodules detected incidentally. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

The Thoracic Research Evaluation and Treatment 2.0 Model: A Lung Cancer Prediction Model for Indeterminate Nodules Referred for Specialist Evaluation

BACKGROUND

Appropriate risk stratification of indeterminate pulmonary nodules (IPNs) is necessary to direct diagnostic evaluation. Currently available models were developed in populations with lower cancer prevalence than that seen in thoracic surgery and pulmonology clinics and usually do not allow for missing data. We updated and expanded the Thoracic Research Evaluation and Treatment (TREAT) model into a more generalized, robust approach for lung cancer prediction in patients referred for specialty evaluation.

RESEARCH QUESTION

Can clinic-level differences in nodule evaluation be incorporated to improve lung cancer prediction accuracy in patients seeking immediate specialty evaluation compared with currently available models?

STUDY DESIGN AND METHODS

Clinical and radiographic data on patients with IPNs from six sites (N = 1,401) were collected retrospectively and divided into groups by clinical setting: pulmonary nodule clinic (n = 374; cancer prevalence, 42%), outpatient thoracic surgery clinic (n = 553; cancer prevalence, 73%), or inpatient surgical resection (n = 474; cancer prevalence, 90%). A new prediction model was developed using a missing data-driven pattern submodel approach. Discrimination and calibration were estimated with cross-validation and were compared with the original TREAT, Mayo Clinic, Herder, and Brock models. Reclassification was assessed with bias-corrected clinical net reclassification index and reclassification plots.

RESULTS

Two-thirds of patients had missing data; nodule growth and fluorodeoxyglucose-PET scan avidity were missing most frequently. The TREAT version 2.0 mean area under the receiver operating characteristic curve across missingness patterns was 0.85 compared with that of the original TREAT (0.80), Herder (0.73), Mayo Clinic (0.72), and Brock (0.68) models with improved calibration. The bias-corrected clinical net reclassification index was 0.23.

INTERPRETATION

The TREAT 2.0 model is more accurate and better calibrated for predicting lung cancer in high-risk IPNs than the Mayo, Herder, or Brock models. Nodule calculators such as TREAT 2.0 that account for varied lung cancer prevalence and that consider missing data may provide more accurate risk stratification for patients seeking evaluation at specialty nodule evaluation clinics.