Inter-vendor harmonization of CT reconstruction kernels using unpaired image translation.

The reconstruction kernel in computed tomography (CT) generation determines the texture of the image. Consistency in reconstruction kernels is important as the underlying CT texture can impact measurements during quantitative image analysis. Harmonization (i.e., kernel conversion) minimizes differences in measurements due to inconsistent reconstruction kernels. Existing methods investigate harmonization of CT scans in single or multiple manufacturers. However, these methods require paired scans of hard and soft reconstruction kernels that are spatially and anatomically aligned. Additionally, a large number of models need to be trained across different kernel pairs within manufacturers. In this study, we adopt an unpaired image translation approach to investigate harmonization between and across reconstruction kernels from different manufacturers by constructing a multipath cycle generative adversarial network (GAN). We use hard and soft reconstruction kernels from the Siemens and GE vendors from the National Lung Screening Trial dataset. We use 50 scans from each reconstruction kernel and train a multipath cycle GAN. To evaluate the effect of harmonization on the reconstruction kernels, we harmonize 50 scans each from Siemens hard kernel, GE soft kernel and GE hard kernel to a reference Siemens soft kernel (B30f) and evaluate percent emphysema. We fit a linear model by considering the age, smoking status, sex and vendor and perform an analysis of variance (ANOVA) on the emphysema scores. Our approach minimizes differences in emphysema measurement and highlights the impact of age, sex, smoking status and vendor on emphysema quantification.

Potential for trans-pulmonary tumor markers in the early diagnosis of lung cancer: a case report.

BACKGROUND: Measurement of tumor markers from peripheral venous blood is an emerging tool to assist in the early diagnosis of lung cancer. Samples from the pulmonary artery and pulmonary artery wedge position (trans-pulmonary samples) are accessible via right-heart catheterization and, by virtue of their proximity to lung tumors, may increase diagnostic yield. CASE PRESENTATION: We report a case of a 64 year-old woman from whom trans-pulmonary samples were obtained and who was diagnosed 16 months later with recurrent metastatic small cell lung cancer. Carcinoembryonic antigen, cytokeratin fragment 21 - 1 (CYFRA), and human epididymis protein 4 (HE4) levels demonstrated increasing concentrations across the pulmonary circulation. These gradients exceeded the assays' coefficient of variation by several-fold. For CYFRA and HE4, pulmonary artery wedge concentrations exceeded peripheral venous levels by more than 10% and peripheral arterial levels were up to 8% higher than peripheral venous levels. CONCLUSIONS: Evaluating the feasibility and utility of trans-pulmonary tumor markers for lung cancer diagnosis in a larger cohort should be considered. The addition of a peripheral arterial sample to standard peripheral venous samples may be a more practical alternative.

Assessing the transportability of radiomic models for lung cancer diagnosis: commercial vs. open-source feature extractors.

Background: Radiomics has shown promise in improving malignancy risk stratification of indeterminate pulmonary nodules (IPNs) with many platforms available, but with no head-to-head comparisons. This study aimed to evaluate transportability of radiomic models across platforms by comparing performances of a commercial radiomic feature extractor (HealthMyne) with an open-source extractor (PyRadiomics) on diagnosis of lung cancer in IPNs. Methods: A commercial radiomic feature extractor was used to segment IPNs from computed tomography (CT) scans, and a previously validated radiomic model based on commercial features was used as baseline (ComRad). Using same segmentation masks, PyRadiomics, an open-source feature extractor was used to build three open-source radiomic models (OpenRad) using different methods: de novo open-source model derived using least absolute shrinkage and selection operator (LASSO) for feature selection, selecting open-source features matched to ComRad features based upon Imaging Biomarker Standardization Initiative (IBSI) nomenclature, and selecting open-source features most highly correlated to ComRad features. Radiomic models were trained on an internal cohort (n=161) and externally validated on 3 cohorts (n=278). We added Mayo clinical risk score to OpenRad and ComRad models, creating integrated clinical radiomic (ClinRad) models. All models were compared using area under the curve (AUC) and evaluated for clinical improvement using bias-corrected clinical net reclassification indices (cNRIs). Results: ComRad AUC was 0.76 [95% confidence interval (CI): 0.71-0.82], and OpenRad AUC was 0.75 (95% CI: 0.69-0.81) for LASSO model, 0.74 (95% CI: 0.68-0.79) for Spearman's correlation, and 0.71 (95% CI: 0.65-0.77) for IBSI. Mayo scores were added to OpenRad LASSO model, which performed best, forming open-source ClinRad model with AUC of 0.80 (95% CI: 0.74-0.86), identical to commercial ClinRad's AUC. Both ClinRad models showed clinical improvement compared to Mayo alone, with commercial ClinRad achieving cNRI of 0.09 (95% CI: 0.02-0.15) for benign and 0.07 (95% CI: 0.00-0.13) for malignant, and open-source ClinRad achieving cNRI of 0.09 (95% CI: 0.02-0.15) for benign and 0.06 (95% CI: 0.00-0.12) for malignant. Conclusions: Transportability of radiomic models across platforms directly does not conserve performance, but radiomic platforms can provide equivalent results when building de novo models allowing for flexibility in feature selection to maximize prediction accuracy.

Economic Value of Bronchoscopy Technologies that Improves Sensitivity for Malignancy for Peripheral Pulmonary Lesions.

RATIONAL: While previous studies have assessed the clinical or economic value of specific technologies, the economic value of improving sensitivity for malignancy for lung cancer diagnoses broadly across technologies is unclear. OBJECTIVE: To identify the economic value of improving sensitivity of bronchoscopy biopsy for the diagnosis of lung cancer. METHODS: A decision analytic model was developed to quantify the economic value of increased sensitivity for malignancy for bronchoscopy biopsy of peripheral pulmonary lesions. Primary clinical outcomes included time-to-diagnosis and survival. Economic outcomes included (i) net monetary benefit (NMB), defined as the health benefits measured in quality-adjusted life year (QALY) times willingness to pay ($100,000/QALY) net of changes in medical costs, and (ii) incremental cost-effectiveness ratio (ICER). A decision tree modeling framework-with two Markov module branches-was developed. The two Markov modules corresponded to cancer patients who were (i) diagnosed and treated or (ii) undiagnosed and remained untreated. Outcomes were measured from a US payer perspective over 30 years. RESULTS: Improving sensitivity for malignancy by 10 percentage points decreased average time-to-diagnosis for lung cancer patients by 0.85 months (4 weeks) and increased survival by 0.36 years (19 weeks), due to faster treatment initiation. Overall health outcomes improved by 0.20 QALYs per patient. Cost increased by $6,727 per patient primarily through increased treatment costs among those diagnosed with cancer. Increasing sensitivity for malignancy by 10 percentage points improved NMB by $8,729 over 30 years (ICER of $34,052), driven largely by improved sensitivity to early-stage cancer (stage-specific NMB: I/II: $19,805; III: $2,101; IV: -$1,438). Forty-two percent of overall NMB ($3,668) accrued within 5 years of biopsy. The relationship between change in sensitivity and NMB was approximately linear (1% vs. 10% sensitivity improvement corresponded to NMB of $885 vs $8,729). The model was most sensitive to cancer treatment efficacy and follow-up time after a negative result. CONCLUSION: Increasing sensitivity of malignancy by 10 percentage points resulted in a $8,729 improvement in net economic value. Health systems can use this information when making decisions regarding the value of new bronchoscopy technologies. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Gravity- vs Wall Suction-Driven Large-Volume Thoracentesis: A Randomized Controlled Study.

BACKGROUND: Prior studies have found no differences in procedural chest discomfort for patients undergoing manual syringe aspiration or drainage with gravity after thoracentesis. However, whether gravity drainage could protect against chest pain due to the larger negative-pressure gradient generated by wall suction has not been investigated. RESEARCH QUESTION: Does wall suction drainage result in more chest discomfort compared with gravity drainage in patients undergoing large-volume thoracentesis? STUDY DESIGN AND METHODS: In this multicenter, single-blinded, randomized controlled trial, patients with large free-flowing effusions of ≥ 500 mL were assigned at a 1:1 ratio to wall suction or gravity drainage. Wall suction was performed with a suction system attached to the suction tubing and with vacuum pressure adjusted to full vacuum. Gravity drainage was performed with a drainage bag placed 100 cm below the catheter insertion site and connected via straight tubing. Patients rated chest discomfort on a 100-mm visual analog scale before, during, and after drainage. The primary outcome was postprocedural chest discomfort at 5 min. Secondary outcomes included measures of postprocedure chest discomfort, breathlessness, procedure time, volume of fluid drained, and complication rates. RESULTS: Of the 228 patients initially randomized, 221 were included in the final analysis. The primary outcome of procedural chest discomfort did not differ significantly between the groups (P = .08), nor did the secondary outcomes of postprocedural discomfort and dyspnea. Similar volumes were drained in both groups, but the procedure duration was longer in the gravity arm by approximately 3 min. No differences in rate of pneumothorax or reexpansion pulmonary edema were noted between the two groups. INTERPRETATION: Thoracentesis via wall suction and gravity drainage results in similar levels of procedural discomfort and dyspnea improvement. CLINICAL TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT05131945; URL: www. CLINICALTRIALS: gov.

Clinical validation of a cell-free DNA fragmentome assay for augmentation of lung cancer early detection.

Lung cancer screening via annual low-dose computed tomography (LDCT) has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by an LDCT. Changes in genome-wide cell-free DNA (cfDNA) fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples, and then validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer, and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a five-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.

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.

Non-Small Cell Lung Cancer, Version 4.2024, NCCN Clinical Practice Guidelines in Oncology

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non-Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of patients with NSCLC, including diagnosis, primary disease management, surveillance for relapse, and subsequent treatment. The panel has updated the list of recommended targeted therapies based on recent FDA approvals and clinical data. This selection from the NCCN Guidelines for NSCLC focuses on treatment recommendations for advanced or metastatic NSCLC with actionable molecular biomarkers.

Elucidating the role of EPPK1 in lung adenocarcinoma development.

BACKGROUND: We recently found that epiplakin 1 (EPPK1) alterations were present in 12% of lung adenocarcinoma (LUAD) cases and were associated with a poor prognosis in early-stage LUAD when combined with other molecular alterations. This study aimed to identify a probable crucial role for EPPK1 in cancer development. METHODS: EPPK1 mRNA and protein expression was analyzed with clinical variables. Normal bronchial epithelial cell lines were exposed to cigarette smoke for 16 weeks to determine whether EPPK1 protein expression was altered after exposure. Further, we used CRISPR-Cas9 to knock out (KO) EPPK1 in LUAD cell lines and observed how the cancer cells were altered functionally and genetically. RESULTS: EPPK1 protein expression was associated with smoking and poor prognosis in early-stage LUAD. Moreover, a consequential mesenchymal-to-epithelial transition was observed, subsequently resulting in diminished cell proliferation and invasion after EPPK1 KO. RNA sequencing revealed that EPPK1 KO induced downregulation of 11 oncogenes, 75 anti-apoptosis, and 22 angiogenesis genes while upregulating 8 tumor suppressors and 12 anti-cell growth genes. We also observed the downregulation of MYC and upregulation of p53 expression at both protein and RNA levels following EPPK1 KO. Gene ontology enrichment analysis of molecular functions highlighted the correlation of EPPK1 with the regulation of mesenchymal cell proliferation, mesenchymal differentiation, angiogenesis, and cell growth after EPPK1 KO. CONCLUSIONS: Our data suggest that EPPK1 is linked to smoking, epithelial to mesenchymal transition, and the regulation of cancer progression, indicating its potential as a therapeutic target for LUAD.

NCCN Guidelines® Insights: Mesothelioma: Pleural, Version 1.2024.

Mesothelioma is a rare cancer that originates from the mesothelial surfaces of the pleura and other sites, and is estimated to occur in approximately 3,500 people in the United States annually. Pleural mesothelioma is the most common type and represents approximately 85% of these cases. The NCCN Guidelines for Mesothelioma: Pleural provide recommendations for the diagnosis, evaluation, treatment, and follow-up for patients with pleural mesothelioma. These NCCN Guidelines Insights highlight significant updates to the NCCN Guidelines for Mesothelioma: Pleural, including revised guidance on disease classification and systemic therapy options.

Curating retrospective multimodal and longitudinal data for community cohorts at risk for lung cancer.

BACKGROUND: Large community cohorts are useful for lung cancer research, allowing for the analysis of risk factors and development of predictive models. OBJECTIVE: A robust methodology for (1) identifying lung cancer and pulmonary nodules diagnoses as well as (2) associating multimodal longitudinal data with these events from electronic health record (EHRs) is needed to optimally curate cohorts at scale. METHODS: In this study, we leveraged (1) SNOMED concepts to develop ICD-based decision rules for building a cohort that captured lung cancer and pulmonary nodules and (2) clinical knowledge to define time windows for collecting longitudinal imaging and clinical concepts. We curated three cohorts with clinical data and repeated imaging for subjects with pulmonary nodules from our Vanderbilt University Medical Center. RESULTS: Our approach achieved an estimated sensitivity 0.930 (95% CI: [0.879, 0.969]), specificity of 0.996 (95% CI: [0.989, 1.00]), positive predictive value of 0.979 (95% CI: [0.959, 1.000]), and negative predictive value of 0.987 (95% CI: [0.976, 0.994]) for distinguishing lung cancer from subjects with SPNs. CONCLUSION: This work represents a general strategy for high-throughput curation of multi-modal longitudinal cohorts at risk for lung cancer from routinely collected EHRs.

Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

BACKGROUND: The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to substantial shifts in measurements unrelated to underlying anatomical structures. PURPOSE: In this study, we investigate kernel harmonization in a multi-vendor low-dose CT lung cancer screening cohort and evaluate our approach's validity in quantitative CT-based assessments. METHODS: Using the National Lung Screening Trial, we identified CT scan pairs of the same sessions with one reconstructed from a soft tissue kernel and one from a hard kernel. In total, 1000 pairs of five different paired kernel types (200 each) were identified. We adopt the pix2pix architecture to train models for kernel conversion. Each model was trained on 100 pairs and evaluated on 100 withheld pairs. A total of 10 models were implemented. We evaluated the efficacy of kernel conversion based on image similarity metrics including root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM) as well as the capability of the models to reduce measurement shifts in quantitative emphysema and body composition measurements. Additionally, we study the reproducibility of standard radiomic features for all kernel pairs before and after harmonization. RESULTS: Our approach effectively converts CT images from one kernel to another in all paired kernel types, as indicated by the reduction in RMSE (p < 0.05) and an increase in the PSNR (p < 0.05) and SSIM (p < 0.05) for both directions of conversion for all pair types. In addition, there is an increase in the agreement for percent emphysema, skeletal muscle area, and subcutaneous adipose tissue (SAT) area for both directions of conversion. Furthermore, radiomic features were reproducible when compared with the ground truth features. CONCLUSIONS: Kernel conversion using deep learning reduces measurement variation in percent emphysema, muscle area, and SAT area.

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.

Utility of bronchoalveolar lavage for COVID-19: a perspective from the Dragon consortium.

Diagnosing COVID-19 and treating its complications remains a challenge. This review reflects the perspective of some of the Dragon (IMI 2-call 21, #101005122) research consortium collaborators on the utility of bronchoalveolar lavage (BAL) in COVID-19. BAL has been proposed as a potentially useful diagnostic tool to increase COVID-19 diagnosis sensitivity. In both critically ill and non-critically ill COVID-19 patients, BAL has a relevant role in detecting other infections or supporting alternative diagnoses and can change management decisions in up to two-thirds of patients. BAL is used to guide steroid and immunosuppressive treatment and to narrow or discontinue antibiotic treatment, reducing the use of unnecessary broad antibiotics. Moreover, cellular analysis and novel multi-omics techniques on BAL are of critical importance for understanding the microenvironment and interaction between epithelial cells and immunity, revealing novel potential prognostic and therapeutic targets. The BAL technique has been described as safe for both patients and healthcare workers in more than a thousand procedures reported to date in the literature. Based on these preliminary studies, we recognize that BAL is a feasible procedure in COVID-19 known or suspected cases, useful to properly guide patient management, and has great potential for research.

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.

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.

Spray Cryotherapy for Benign Large Airway Stenosis: A Multicenter Retrospective Cohort Study of Safety and Practice Patterns.

BACKGROUND: Benign airway stenosis (BAS) represents a significant burden on patients, providers, and healthcare systems. Spray cryotherapy (SCT) has been proposed as an adjunctive treatment to reduce BAS recurrence. We sought to examine safety and practice variations of the latest SCT system when used for BAS. METHODS: We conducted a retrospective multicenter cohort study in seven academic institutions within the Interventional Pulmonary Outcomes Group. All patients who underwent at least one SCT session with a diagnosis of BAS at the time of procedure at these institutions were included. Demographics, procedure characteristics, and adverse events were captured through each center's procedural database and electronic health record. RESULTS: A total of 102 patients underwent 165 procedures involving SCT from 2013 to 2022. The most frequent etiology of BAS was iatrogenic (n = 36, 35%). In most cases, SCT was used prior to other standard BAS interventions (n = 125; 75%). The most frequent SCT actuation time per cycle was five seconds. Pneumothorax complicated four procedures, requiring tube thoracostomy in two. Significant post-SCT hypoxemia was noted in one case, with recovery by case conclusion and no long-term effects. There were no instances of air embolism, hemodynamic compromise, or procedural or in-hospital mortality. CONCLUSION: SCT as an adjunctive treatment for BAS was associated with a low rate of complications in this retrospective multicenter cohort study. SCT-related procedural aspects varied widely in examined cases, including actuation duration, number of actuations, and timing of actuations relative to other interventions.

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.

Assessing the clinical utility of biomarkers using the intervention probability curve (IPC).

BACKGROUND: Assessing the clinical utility of biomarkers is a critical step before clinical implementation. The reclassification of patients across clinically relevant subgroups is considered one of the best methods to estimate clinical utility. However, there are important limitations with this methodology. We recently proposed the intervention probability curve (IPC) which models the likelihood that a provider will choose an intervention as a continuous function of the probability, or risk, of disease. OBJECTIVE: To assess the potential impact of a new biomarker for lung cancer using the IPC. METHODS: The IPC derived from the National Lung Screening Trial was used to assess the potential clinical utility of a biomarker for suspected lung cancer. The summary statistics of the change in likelihood of intervention over the population can be interpreted as the expected clinical impact of the added biomarker. RESULTS: The IPC analysis of the novel biomarker estimated that 8% of the benign nodules could avoid an invasive procedure while the cancer nodules would largely remain unchanged (0.1%). We showed the benefits of this approach compared to traditional reclassification methods based on thresholds. CONCLUSIONS: The IPC methodology can be a valuable tool for assessing biomarkers prior to clinical implementation.