Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society

Predicting the histological invasiveness of pulmonary adenocarcinoma manifesting as persistent pure ground-glass nodules by ultra-high-resolution CT target scanning in the lateral or oblique body position

Background

Ultra-high-resolution computed tomography (U-HRCT) has improved image quality for displaying the detailed characteristics of disease states and lung anatomy. The purpose of this study was to retrospectively examine whether U-HRCT target scanning in the lateral or oblique body position (protocol G scan) could predict histological invasiveness of pulmonary adenocarcinoma manifesting as pure ground-glass nodules (pGGNs).

Methods

From January 2015 to December 2016, 260 patients with 306 pathologically confirmed pGGNs who underwent preoperative protocol G scans were retrospectively reviewed and analyzed. The U-HRCT findings of preinvasive lesions [atypical adenomatous hyperplasias (AAH) and adenocarcinomas in situ (AIS)] and invasive pulmonary adenocarcinomas [minimally invasive adenocarcinomas (MIA) and invasive adenocarcinomas (IAC)] were manually compared and analyzed using orthogonal multiplanar reformation (MPR) images. The logistic regression model was established to determine variables that could predict the invasiveness of pGGNs. Receiver operating characteristic (ROC) curve analysis was performed to evaluate their diagnostic performance.

Results

There were 213 preinvasive lesions (59 AAHs and 154 AISs) and 93 invasive pulmonary adenocarcinomas (53 MIAs and 40 IACs). Compared with the preinvasive lesions, invasive adenocarcinomas exhibited a larger diameter (13.5 vs. 9.3 mm, P=0.000), higher mean attenuation (-571 vs. -613 HU, P=0.002), higher representative attenuation (-475 vs. -547 HU, P=0.000), lower relative attenuation (-339 vs. -292 HU, P=0.000) and greater frequencies of heterogeneity (P=0.001), air bronchogram (P=0.000), bubble lucency (P=0.000), and pleural indentation (P=0.000). Multiple logistic analysis revealed that larger diameter [odds ratio (OR), 1.328; 95% CI: 1.208-1.461; P=0.000] and higher representative attenuation (OR, 1.005; 95% CI: 1.003-1.007; P=0.000) were significant predictive factors of invasive pulmonary adenocarcinomas from preinvasive lesions. The optimal cut-off value of the maximum diameter for invasive pulmonary adenocarcinomas was larger than 10 mm (sensitivity, 66.7%; specificity, 72.8%).

Conclusions

The imaging features based on protocol G scanning can effectively help predict the histological invasiveness of pGGNs. The maximum diameter and representative attenuation are important parameters for predicting invasiveness.

Hybrid Clinical-Radiomics Model for Precisely Predicting the Invasiveness of Lung Adenocarcinoma Manifesting as Pure Ground-Glass Nodule

RATIONALE AND OBJECTIVES

To identify whether the radiomics features of computed tomography (CT) allowed for the preoperative discrimination of the invasiveness of lung adenocarcinomas manifesting as pure ground-glass nodules (pGGNs) and further to develop and compare different predictive models.

MATERIALS AND METHODS

We retrospectively included 187 lung adenocarcinomas presenting as pGGNs (66 preinvasive lesions and 121 invasive lesions), which were randomly divided into the training and test sets (8:2). Radiomics features were extracted from non-enhanced CT images. Clinical features, including patient's demographic characteristics, smoking status, and conventional CT features that reflect tumor's morphology and surrounding information were also collected. Intraclass correlation coefficient and ℓ_2.1-norm minimization were used to identify influential feature subset which was then used to build three predictive models (clinical, radiomics, and clinical-radiomics models) with the gradient boosting regression tree classifier. The performances of the predictive models were evaluated using the area under the curve (AUC).

RESULTS

Of the 1409 radiomics features and 27 clinical feature subtypes, 102 features were selected to construct the hybrid clinical-radiomics model, which achieved the best discriminative power (AUC = 0.934 and 0.929 in training and test set). The radiomics model showed comparable predictive performance (AUC = 0.911 and 0.901 in training and test set) compared to the clinical model (AUC = 0.911 and 0.894 in training and test set).

CONCLUSION

The radiomics model showed good predictive performance in discriminating invasive lesions from preinvasive lesions for lung adenocarcinomas presenting as pGGNs. Its performance can be further improved by adding clinical features.

Prediction of malignancy for solitary pulmonary nodules based on imaging, clinical characteristics and tumor marker levels

OBJECTIVE

To establish a prediction model of malignancy for solitary pulmonary nodules (SPNs) on the basis of imaging, clinical characteristics and tumor marker levels.

METHODS

Totally, 341 cases of SPNs were enrolled in this retrospective study, in which 70% were selected as the training group (n = 238) and the rest 30% as the verification group (n = 103). The imaging, clinical characteristics and tumor marker levels of patients with benign and malignant SPNs were compared. Influencing factors were identified using multivariate logistic regression analysis. The model was assessed by the area under the curve (AUC) of the receiver operating characteristic curve.

RESULTS

Differences were evident between patients with benign and malignant SPNs in age, gender, smoking history, carcinoembryonic antigen (CEA), neuron-specific enolase, nodule location, edge smoothing, spiculation, lobulation, vascular convergence sign, air bronchogram, ground-glass opacity, vacuole sign and calcification (all P < 0.05). Influencing factors for malignancy included age, gender, nodule location, spiculation, vacuole sign and CEA (all P < 0.05). The established model was as follows: Y = -5.368 + 0.055 × age + 1.012 × gender (female = 1, male = 0) + 1.302 × nodule location (right upper lobe = 1, others = 0) + 1.208 × spiculation (yes = 1, no = 0) + 2.164 × vacuole sign (yes = 1, no = 0) -0.054 × CEA. The AUC of the model with CEA was 0.818 (95% confidence interval, 0.763-0.865), with a sensitivity of 64.80% and a specificity of 84.96%, and the stability was better through internal verification.

CONCLUSIONS

The prediction model established in our study exhibits better accuracy and internal stability in predicting the probability of malignancy for SPNs.

A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning

Lung cancer has one of the highest mortalities of all cancers. According to the National Lung Screening Trial, patients who underwent low-dose computed tomography (CT) scanning once a year for 3 years showed a 20% decline in lung cancer mortality. To further improve the survival rate of lung cancer patients, computer-aided diagnosis (CAD) technology shows great potential. In this paper, we summarize existing CAD approaches applying deep learning to CT scan data for pre-processing, lung segmentation, false positive reduction, lung nodule detection, segmentation, classification and retrieval. Selected papers are drawn from academic journals and conferences up to November 2020. We discuss the development of deep learning, describe several important aspects of lung nodule CAD systems and assess the performance of the selected studies on various datasets, which include LIDC-IDRI, LUNA16, LIDC, DSB2017, NLST, TianChi, and ELCAP. Overall, in the detection studies reviewed, the sensitivity of these techniques is found to range from 61.61% to 98.10%, and the value of the FPs per scan is between 0.125 and 32. In the selected classification studies, the accuracy ranges from 75.01% to 97.58%. The precision of the selected retrieval studies is between 71.43% and 87.29%. Based on performance, deep learning based CAD technologies for detection and classification of pulmonary nodules achieve satisfactory results. However, there are still many challenges and limitations remaining including over-fitting, lack of interpretability and insufficient annotated data. This review helps researchers and radiologists to better understand CAD technology for pulmonary nodule detection, segmentation, classification and retrieval. We summarize the performance of current techniques, consider the challenges, and propose directions for future high-impact research.

DNA methylation patterns at and beyond the histological margin of early-stage invasive lung adenocarcinoma radiologically manifested as pure ground-glass opacity

Background

Early-stage lung cancers radiologically manifested as ground-glass opacities (GGOs) have been increasingly identified, among which pure GGO (pGGO) has a good prognosis after local resection. However, the optimal surgical margin is still under debate. Precancerous lesions exist in tumor-adjacent tissues beyond the histological margin. However, potential precancerous epigenetic variation patterns beyond the histological margin of pGGO are yet to be discovered and described.

Results

A genome-wide high-resolution DNA methylation analysis was performed on samples collected from 15 pGGO at tumor core (TC), tumor edge (TE), para-tumor tissues at the 5 mm, 10 mm, 15 mm, 20 mm beyond the tumor, and peripheral normal (PN) tissue. TC and TE were tested with the same genetic alterations, which were also observed in histologically normal tissue at 5 mm in two patients with lower mutation allele frequency. According to the difference of methylation profiles between PN samples, 2284 methylation haplotype blocks (MHBs), 1657 differentially methylated CpG sites (DMCs), and 713 differentially methylated regions (DMRs) were identified using reduced representation bisulfite sequencing (RRBS). Two different patterns of methylation markers were observed: Steep (S) markers sharply changed at 5 mm beyond the histological margin, and Gradual (G) markers changed gradually from TC to PN. S markers composed 86.2% of the tumor-related methylation markers, and G markers composed the other 13.8%. S-marker-associated genes enriched in GO terms that were related to the hallmarks of cancer, and G-markers-associated genes enriched in pathways of stem cell pluripotency and transcriptional misregulation in cancer. Significant difference in DNA methylation score was observed between peripheral normal tissue and tumor-adjacent tissues 5 mm further from the histological margin (p < 0.001 in MHB markers). DNA methylation score at and beyond 10 mm from histological margin is not significantly different from peripheral normal tissues (p > 0.05 in all markers).

Conclusions

According to the methylation pattern observed in our study, it was implied that methylation alterations were not significantly different between tissues at or beyond P10 and distal normal tissues. This finding explained for the excellent prognosis from radical resections with surgical margins of more than 15 mm. The inclusion of epigenetic characteristics into surgical margin analysis may yield a more sensitive and accurate assessment of remnant cancerous and precancerous cells in the surgical margins.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01140-3.

Predictors of Invasive Adenocarcinomas among Pure Ground-Glass Nodules Less Than 2 cm in Diameter

Simple Summary

Benign lesions, atypical adenomatous hyperplasia, and malignancies such as adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma may feature pure ground-glass nodules on chest CT images, and the prognosis of patients with invasive adenocarcinoma is worse than others. The early detection and adequate management of invasive adenocarcinoma is crucial, but the pathology diagnosis of small nodules is difficult to obtain without surgery. Our study aimed to analyze the CT characteristics of pure ground-glass nodules <2 cm for the identification of invasive adenocarcinomas. A total of 181 nodules in 171 patients were enrolled. The larger size, lobulation, and air cavity were significantly more common in invasive adenocarcinoma. The air cavity is the significant predictor in multivariate analysis. In conclusion, the possibility of invasive adenocarcinoma is higher in a pure ground-glass nodules when it is associated with a larger size, lobulation, and air cavity.

Abstract

Benign lesions, atypical adenomatous hyperplasia (AAH), and malignancies such as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA) may feature a pure ground-glass nodule (pGGN) on a thin-slide computed tomography (CT) image. According to the World Health Organization (WHO) classification for lung cancer, the prognosis of patients with IA is worse than those with AIS and MIA. It is relatively risky to perform a core needle biopsy of a pGGN less than 2 cm to obtain a reliable pathological diagnosis. The early and adequate management of patients with IA may provide a favorable prognosis. This study aimed to disclose suggestive signs of CT to accurately predict IA among the pGGNs. A total of 181 pGGNs of less than 2 cm, in 171 patients who had preoperative CT-guided localization for surgical excision of a lung nodule between December 2013 and August 2019, were enrolled. All had CT images of 0.625 mm slice thickness during CT-guided intervention to confirm that the nodules were purely ground glass. The clinical data, CT images, and pathological reports of those 171 patients were reviewed. The CT findings of pGGNs including the location, the maximal diameter in the long axis (size-L), the maximal short axis diameter perpendicular to the size-L (size-S), and the mean value of long and short axis diameters (size-M), internal content, shape, interface, margin, lobulation, spiculation, air cavity, vessel relationship, and pleural retraction were recorded and analyzed. The final pathological diagnoses of the 181 pGGNs comprised 29 benign nodules, 14 AAHs, 25 AISs, 55 MIAs, and 58 IAs. Statistical analysis showed that there were significant differences among the aforementioned five groups with respect to size-L, size-S, and size-M (p = 0.029, 0.043, 0.025, respectively). In the univariate analysis, there were significant differences between the invasive adenocarcinomas and the non-invasive adenocarcinomas with respect to the size-L, size-S, size-M, lobulation, and air cavity (p = 0.009, 0.016, 0.008, 0.031, 0.004, respectively) between the invasive adenocarcinomas and the non-invasive adenocarcinomas. The receiver operating characteristic (ROC) curve of size for discriminating invasive adenocarcinoma also revealed similar area under curve (AUC) values among size-L (0.620), size-S (0.614), and size-M (0.623). The cut-off value of 7 mm in size-M had a sensitivity of 50.0% and a specificity of 76.4% for detecting IAs. In the multivariate analysis, the presence of air cavity was a significant predictor of IA (p = 0.042). In conclusion, the possibility of IA is higher in a pGGN when it is associated with a larger size, lobulation, and air cavity. The air cavity is the significant predictor of IA.

Can Biologic Aggressiveness and Metastatic Potential of Primary Lung Cancer Be Predicted from Clinical Staging Alone?

The future biologic aggressiveness and metastatic potential of lung cancer, as in other cancers, cannot be predetermined from the current clinical information, imaging studies, and pathologic examination whose purpose is to provide diagnosis and mutation studies and molecular drivers only in making decision for treatment. There is a need for better understanding of the biologic characteristics and aggressiveness of lung cancer. The most that is achieved from clinical staging and pathologic staging is in the planning of treatment of lung cancer and predicting prognosis. Aggressive biologic behavior to come is not within the domain of clinical staging or pathologic staging.

Differentiation of adenocarcinoma in situ with alveolar collapse from minimally invasive adenocarcinoma or invasive adenocarcinoma appearing as part-solid ground-glass nodules (≤ 2 cm) using computed tomography

PURPOSE

To investigate the differentiating computed tomographic (CT) features between adenocarcinoma in situ (AIS) with alveolar collapse and minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) appearing as part-solid nodules.

METHODS

A total of 147 consecutive patients with 157 pathology-confirmed part-solid ground-glass nodules (GGNs) ≤ 20 mm without other pathological condition such as inflammation and fibrosis who underwent chest CT were included.

RESULTS

The 157 part-solid GGNs included 33 (21.02%) pathologically confirmed AISs with alveolar collapse. Multivariate analysis revealed that smaller lesion size (odds ratio [OR] 0.671), and well-defined border (OR 5.544), concentrated distribution (OR 7.994), and homogeneity of the solid portion (OR 4.365) were significant independent predictors for differentiating AIS with alveolar collapse from MIA (P < 0.05) with excellent accuracy (area under receiver operating characteristic [ROC] curve, 0.902). Multivariate analysis revealed that smaller lesion size (OR 0.782), and size (OR 0.821), well-defined border (OR 5.752), and homogeneity of solid portion (OR 6.182) were significant independent predictors differentiating AIS with alveolar collapse from IA (P < 0.05) with excellent accuracy (area under ROC curve 0.910).

CONCLUSION

Among part-solid GGNs, AIS with alveolar collapse can be accurately differentiated from MIA on the basis of smaller lesion size, well-defined border, concentrated distribution, and homogeneity of solid portion, and from IA according to smaller lesion size, and smaller size, well-defined border, and homogeneity of solid portion.

Contemporary issues in the implementation of lung cancer screening

Lung cancer screening with low-dose computed tomography can reduce death from lung cancer by 20-24% in high-risk smokers. National lung cancer screening programmes have been implemented in the USA and Korea and are being implemented in Europe, Canada and other countries. Lung cancer screening is a process, not a test. It requires an organised programmatic approach to replicate the lung cancer mortality reduction and safety of pivotal clinical trials. Cost-effectiveness of a screening programme is strongly influenced by screening sensitivity and specificity, age to stop screening, integration of smoking cessation intervention for current smokers, screening uptake, nodule management and treatment costs. Appropriate management of screen-detected lung nodules has significant implications for healthcare resource utilisation and minimising harm from radiation exposure related to imaging studies, invasive procedures and clinically significant distress. This review focuses on selected contemporary issues in the path to implement a cost-effective lung cancer screening at the population level. The future impact of emerging technologies such as deep learning and biomarkers are also discussed.

Managing Incidental Findings on Thoracic CT: Lung Findings. A White Paper of the ACR Incidental Findings Committee

The ACR Incidental Findings Committee presents recommendations for managing incidentally detected lung findings on thoracic CT. The Chest Subcommittee is composed of thoracic radiologists who endorsed and developed the provided guidance. These recommendations represent a combination of current published evidence and expert opinion and were finalized by informal iterative consensus. The recommendations address commonly encountered incidental findings in the lungs and are not intended to be a comprehensive review of all pulmonary incidental findings. The goal is to improve the quality of care by providing guidance on management of incidentally detected thoracic findings.

Tumor size in patients with severe pulmonary emphysema might be underestimated on preoperative CT

OBJECTIVES

To evaluate the effect of emphysema on tumor diameter measured on preoperative computed tomography (CT) images versus pathological specimens.

MATERIALS AND METHODS

We investigated patients who underwent primary lung cancer surgery: 55 patients (57 tumors) with severe emphysema and 57 patients (57 tumors) without emphysema. The tumor diameters measured in the postoperative pathological specimens were compared with those measured on the axial CT images and on multiplanar reconstruction (MPR) CT images by two independent radiologists; a subgroup analysis according to tumor size was also performed. A paired or unpaired t test was performed, depending on the tested subjects.

RESULTS

In the emphysema group, the mean axial CT diameter was significantly smaller than the mean pathological diameter (p = 0.025/0.001 for reader 1/2), whereas in the non-emphysema group, the mean axial CT diameter was not significantly different from the pathological one for both readers. The difference between CT axial diameter and pathological diameter (= CT diameter - pathological diameter) was significantly smaller (i.e., had a stronger tendency toward underestimation on radiological measurements) in the emphysema group compared with the non-emphysema group (p = 0.014/0.008 for reader 1/2), and the difference was significantly smaller in tumors sized > 30 mm than tumors sized ≤ 20 mm in both groups.

CONCLUSIONS

Tumor size is significantly smaller on preoperative CT in patients with severe emphysema compared to patients without emphysema, especially in the case of large tumors. MPR measurement using the widest of three dimensions should be used to select T-stage for patients with severe emphysema.

KEY POINTS

• The presence of emphysema affects the accuracy of tumor size measurements on CT. • Compared to patients without emphysema, the tumor size in severe emphysema patients tends to be measured smaller in preoperative CT than the pathological specimen. • This trend is more evident when large tumors are measured on axial CT images alone.

A clinicopathological study of lung adenocarcinomas with pure ground-glass opacity > 3 cm on high-resolution computed tomography

OBJECTIVES

This study aimed to discuss whether a diameter of 3 cm is a threshold for diagnosing lung adenocarcinomas presenting with radiological pure ground-glass mass (PGGM, pure ground-glass opacity > 3 cm) as adenocarcinomas in situ or minimally invasive adenocarcinomas (AIS-MIAs). Another aim was to identify CT features and patient prognosis that differentiate AIS-MIAs from invasive adenocarcinomas (IACs) in patients with PGGMs.

METHODS

From June 2007 to October 2015, 69 resected PGGMs with HRCT and followed up for ≥ 5 years were included in this study and divided into AIS-MIA (n = 13) and IAC (n = 56) groups. Firth's logistic regression model was performed to determine CT characteristics that helped distinguish IACs from AIS-MIAs. The discriminatory power of the significant predictors was tested with the area under the receiver operating characteristics curve (AUC). Disease recurrence was also evaluated.

RESULTS

Univariable and multivariable analyses identified that the mean CT attenuation (odds ratio: 1.054, p = 0.0087) was the sole significant predictor for preoperatively discriminating IACs from AIS-MIAs in patients with PGGMs. The CT attenuation had an excellent differentiating accuracy (AUC: 0.981), with the optimal cut-off value at -600 HU (sensitivity: 87.5%; specificity: 100%). Additionally, no recurrence was observed in patients manifesting with PGGMs > 3 cm, and the 5-year recurrence-free survival and overall survival rates were both 100%, even in cases of IAC.

CONCLUSIONS

This study demonstrated that PGGMs > 3 cm could still be AIS-MIAs. When PGGMs are encountered in clinical practice, the CT value may be the only valuable parameter to preoperatively distinguish IACs from AIS-MIAs.

KEY POINTS

• Patients with pure ground-glass opacity > 3 cm in diameter are rare but can be diagnosed as adenocarcinomas in situ or minimally invasive adenocarcinomas. • The mean CT attenuation is the sole significant CT parameter that differentiates invasive adenocarcinoma from adenocarcinoma in situ or minimally invasive adenocarcinoma in patients with pure ground-glass opacity > 3 cm. • Lung adenocarcinoma with pure ground-glass opacity > 3 cm has an excellent prognosis, even in cases of invasive adenocarcinoma.

Incidental Lung Nodules on Cross-sectional Imaging: Current Reporting and Management

Pulmonary nodules are the most common incidental finding in the chest, particularly on computed tomographs that include a portion or all of the chest, and may be encountered more frequently with increasing utilization of cross-sectional imaging. Established guidelines address the reporting and management of incidental pulmonary nodules, both solid and subsolid, synthesizing nodule and patient features to distinguish benign nodules from those of potential clinical consequence. Standard nodule assessment is essential for the accurate reporting of nodule size, attenuation, and morphology, all features with varying risk implications and thus management recommendations.

General Review on the Current Management of Incidental Findings on Cross-Sectional Imaging: What Guidelines to Use, How to Follow Them, and Management and Medical-Legal Considerations

"Incidentalomas" are a common part of daily practice for radiologists, and knowledge of appropriate management guidelines is important in ensuring that no potentially clinically relevant findings are missed or are lost to follow-up in asymptomatic patients. Incidental findings of the brain, spine, thyroid, lungs, breasts, liver, adrenals, spleen, pancreas, kidneys, bowel, and ovaries are discussed, including where to find guidelines for management recommendations, how to follow them, and medical-legal considerations.

Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports

BACKGROUND

There is an urgent need for population-based studies on managing patients with pulmonary nodules.

RESEARCH QUESTION

Is it possible to identify pulmonary nodules and associated characteristics using an automated method?

STUDY DESIGN AND METHODS

We revised and refined an existing natural language processing (NLP) algorithm to identify radiology transcripts with pulmonary nodules and greatly expanded its functionality to identify the characteristics of the largest nodule, when present, including size, lobe, laterality, attenuation, calcification, and edge. We compared NLP results with a reference standard of manual transcript review in a random test sample of 200 radiology transcripts. We applied the final automated method to a larger cohort of patients who underwent chest CT scan in an integrated health care system from 2006 to 2016, and described their demographic and clinical characteristics.

RESULTS

In the test sample, the NLP algorithm had very high sensitivity (98.6%; 95% CI, 95.0%-99.8%) and specificity (100%; 95% CI, 93.9%-100%) for identifying pulmonary nodules. For attenuation, edge, and calcification, the NLP algorithm achieved similar accuracies, and it correctly identified the diameter of the largest nodule in 135 of 141 cases (95.7%; 95% CI, 91.0%-98.4%). In the larger cohort, the NLP found 217,771 reports with nodules among 717,304 chest CT reports (30.4%). From 2006 to 2016, the number of reports with nodules increased by 150%, and the mean size of the largest nodule gradually decreased from 11 to 8.9 mm. Radiologists documented the laterality and lobe (90%-95%) more often than the attenuation, calcification, and edge characteristics (11%-14%).

INTERPRETATION

The NLP algorithm identified pulmonary nodules and associated characteristics with high accuracy. In our community practice settings, the documentation of nodule characteristics is incomplete. Our results call for better documentation of nodule findings. The NLP algorithm can be used in population-based studies to identify pulmonary nodules, avoiding labor-intensive chart review.

The Value of PETRA in Pulmonary Nodules of <3 cm Among Patients With Lung Cancer

Objective

This study aimed to evaluate the visibility of different subgroups of lung nodules of <3 cm using the pointwise encoding time reduction with radial acquisition (PETRA) sequence on 3T magnetic resonance imaging (MRI) in comparison with that obtained using low-dose computed tomography (LDCT).

Methods

The appropriate detection rate was calculated for each of the different subgroups of lung nodules of <3 cm. The mean diameter of each detected nodule was determined. The detection rates and diameters of the lung nodules detected by MRI with the PETRA sequence were compared with those detected by computed tomography (CT). The sensitivity of detection for the different subgroups of pulmonary nodules was determined based on the location, size, type of nodules and morphologic characteristics. Agreement of nodule characteristics between CT and MRI were assessed by intraclass correlation coefficient (ICC) and Kappa test.

Results

The CT scans detected 256 lung nodules, comprising 99 solid nodules (SNs) and 157 subsolid nodules with a mean nodule diameter of 8.3 mm. For the SNs, the MRI detected 30/47 nodules of <6 mm in diameter and 52/52 nodules of ≥6 mm in diameter. For the subsolid nodules, the MRI detected 30/51 nodules of <6 mm in diameter and 102/106 nodules of ≥6 mm in diameter. The PETRA sequence returned a high detection rate (84%). The detection rates of SN, ground glass nodules, and PSN were 82%, 72%, and 94%, respectively. For nodules with a diameter of >6 mm, the sensitivity of the PETRA sequence reached 97%, with a higher rate for nodules located in the upper lung fields than those in the middle and lower lung fields. Strong agreement was found between the CT and PETRA results (correlation coefficients = 0.97).

Conclusion

The PETRA technique had high sensitivity for different type of nodule detection and enabled accurate assessment of their diameter and morphologic characteristics. It may be an effective alternative to CT as a tool for screening and follow up pulmonary nodules.

ENB-guided microwave ablation combined with uniportal VATS for multiple ground glass opacities

BACKGROUND

An increasing number of patients are being diagnosed with multiple ground glass opacities (GGOs), but a consensus on the treatment of these patients is still lacking. The aim of this study was to investigate the safety and feasibility of a novel technique, electromagnetic navigation bronchoscopy (ENB)-guided microwave ablation combined with uniportal video-assisted thoracoscopic surgery (Uni-VATS), in patients with multiple GGOs.

METHODS

The clinical, radiographic, surgical, and pathological data of patients with multiple GGOs who underwent ENB-guided microwave ablation combined with Uni-VATS from October 2018 to December 2019 were reviewed.

RESULTS

Eleven patients with multiple GGOs underwent ENB-guided microwave ablation combined with Uni-VATS, including 6 males and 5 females with a mean age of 61.3±5.1 (53-68) years. Thirty-seven lesions were observed in the 11 patients, 21 of which were microwave ablated and 16 of which were surgically resected. Only one patient developed postoperative pneumothorax and subcutaneous emphysema and was successfully discharged from the hospital after symptomatic treatment. The success rate and efficiency of microwave ablation under ENB guidance were 100%, with no other serious complications or procedure-related deaths occurring. No local metastasis or recurrence occurred in any patients during the follow-up period.

CONCLUSIONS

ENB-guided microwave ablation combined with Uni-VATS is safe and feasible in patients with multiple GGOs suspected of having multiple primary lung cancers, and may represent an alternative approach for more patients, particularly patients who cannot tolerate the simultaneous resection of multiple tumors.

Semi-Quantitative Analysis for Determining the Optimal Threshold Value on CT to Measure the Solid Portion of Pulmonary Subsolid Nodules

PURPOSE

This study aimed to investigate the optimal threshold value in Hounsfield units (HU) on CT to detect the solid components of pulmonary subsolid nodules using pathologic invasive foci as reference.

MATERIALS AND METHODS

Thin-section non-enhanced chest CT scans of 25 patients with pathologically confirmed minimally invasive adenocarcinoma were retrospectively reviewed. On CT images, the solid portion was defined as the area with higher attenuation than various HU thresholds ranging from -600 to -100 HU in 50-HU intervals. The solid portion was measured as the largest diameter on axial images and as the maximum diameter on multiplanar reconstruction images. A linear mixed model was used to evaluate bias in each threshold by using the pathological size of invasive foci as reference.

RESULTS

At a threshold of -400 HU, the biases were lowest between the largest/maximum diameter of the solid portion of subsolid nodule and the size of invasive foci of the pathological specimen, with 0.388 and -0.0176, respectively. They showed insignificant difference (p = 0.2682, p = 0.963, respectively) at a threshold of -400 HU.

CONCLUSION

For quantitative analysis, -400 HU may be the optimal threshold to define the solid portion of subsolid nodules as a surrogate marker of invasive foci.

Preoperative computer tomography-guided indocyanine green injection is associated with successful localization of small pulmonary nodules

Background

Localization of small pulmonary nodules (SPNs) is challenging in minimally invasive pulmonary resection, and it is unknown whether computer tomography (CT) guided by indocyanine green (ICG) can provide accurate localization with minimal complications.

Methods

We performed a retrospective study of patients who underwent thoracoscopic resection of pulmonary nodules after CT-guided preoperative localization with ICG from May 2019 to May 2020. Demographics, procedural data, postoperative complications, and pathologic information, were collected, and an analysis of the accuracy and complications after surgery was conducted.

Results

In 471 patients, there was a total of 512 peripheral pulmonary nodules that were ≤2 cm in size. The average time for CT-guided percutaneous ICG injection for localization was 18 minutes, and 98.4% (504/512) of the nodules were successfully localized. The average size of the nodules was 9.1 mm, and the average depth from the pleural surface was 8.9 mm. Overall, 5.9% (28/471) of the patients had asymptomatic pneumothorax after localization, but none needed a tube thoracostomy. All the nodules were resected using video-assisted thoracoscopy technique.

Conclusions

Preoperative CT-guided transthoracic ICG injection is safe and feasible for localization of small lung nodules for minimally invasive pulmonary resection. This technique should be considered for preoperative CT-guided localization of small lung nodules.

Management of pulmonary ground-glass opacities: a position paper from a panel of experts of the Italian Society of Thoracic Surgery (SICT)

OBJECTIVES

A significant gap in our knowledge of how to manage pulmonary ground-glass opacities (GGOs) still exists. Accordingly, there is a lack of consensus among clinicians on this topic. The Italian Society of Thoracic Surgery (Società Italiana di Chirurgia Toracica, SICT) promoted a national expert meeting to provide insightful guidance for clinical practice. Our goal was to publish herein the final consensus document from this conference.

METHODS

The working panel of the PNR group (Pulmonary Nodules Recommendation Group, a branch of the SICT) together with 5 scientific supervisors (nominated by the SICT) identified a jury of expert thoracic surgeons who organized a multidisciplinary meeting to propose specific statements (n = 29); 73 participants discussed and voted on statements using a modified Delphi process (repeated iterations of anonymous voting over 2 rounds with electronic support) requiring 70% agreement to reach consensus on a statement.

RESULTS

Consensus was reached on several critical points in GGO management, in particular on the definition of GGO, radiological and radiometabolic evaluation, indications for a non-surgical biopsy, GGO management based on radiological characteristics, surgical strategies (extension of pulmonary resection and lymphadenectomy) and radiological surveillance. A list of 29 statements was finally approved.

CONCLUSIONS

The participants at this national expert meeting analysed this challenging topic and provided a list of suggestions for health institutions and physicians with practical indications for GGO management.

Global evolution of research on pulmonary nodules: a bibliometric analysis

Aim: To provide a historical and global picture of research concerning lung nodules, compare the contributions of major countries and explore research trends over the past 10 years. Methods: A bibliometric analysis of publications from Scopus (1970-2020) and Web of Science (2011-2020). Results: Publications about pulmonary nodules showed an enormous growth trend from 1970 to 2020. There is a high level of collaboration among the 20 most productive countries and regions, with the USA located at the center of the collaboration network. The keywords 'deep learning', 'artificial intelligence' and 'machine learning' are current hotspots. Conclusions: Abundant research has focused on pulmonary nodules. Deep learning is emerging as a promising tool for lung cancer diagnosis and management.

Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks

OBJECTIVES

The interpretability of convolutional neural networks (CNNs) for classifying subsolid nodules (SSNs) is insufficient for clinicians. Our purpose was to develop CNN models to classify SSNs on CT images and to investigate image features associated with the CNN classification.

METHODS

CT images containing SSNs with a diameter of ≤ 3 cm were retrospectively collected. We trained and validated CNNs by a 5-fold cross-validation method for classifying SSNs into three categories (benign and preinvasive lesions [PL], minimally invasive adenocarcinoma [MIA], and invasive adenocarcinoma [IA]) that were histologically confirmed or followed up for 6.4 years. The mechanism of CNNs on human-recognizable CT image features was investigated and visualized by gradient-weighted class activation map (Grad-CAM), separated activation channels and areas, and DeepDream algorithm.

RESULTS

The accuracy was 93% for classifying 586 SSNs from 569 patients into three categories (346 benign and PL, 144 MIA, and 96 IA in 5-fold cross-validation). The Grad-CAM successfully located the entire region of image features that determined the final classification. Activated areas in the benign and PL group were primarily smooth margins (p < 0.001) and ground-glass components (p = 0.033), whereas in the IA group, the activated areas were mainly part-solid (p < 0.001) and solid components (p < 0.001), lobulated shapes (p < 0.001), and air bronchograms (p < 0.001). However, the activated areas for MIA were variable. The DeepDream algorithm showed the image features in a human-recognizable pattern that the CNN learned from a training dataset.

CONCLUSION

This study provides medical evidence to interpret the mechanism of CNNs that helps support the clinical application of artificial intelligence.

KEY POINTS

• CNN achieved high accuracy (93%) in classifying subsolid nodules on CT images into three categories: benign and preinvasive lesions, MIA, and IA. • The gradient-weighted class activation map (Grad-CAM) located the entire region of image features that determined the final classification, and the visualization of the separated activated areas was consistent with radiologists' expertise for diagnosing subsolid nodules. • DeepDream showed the image features that CNN learned from a training dataset in a human-recognizable pattern.

Racial disparities in provider-patient communication of incidental medical findings

Health disparities research often focuses on the social patterning of health outcomes. Increasingly, there has been an emphasis on understanding the mechanisms perpetuating disparities, even after issues of patient access to health services are addressed. The following study utilizes a novel dataset of electronic medical records (EMR), radiology records, and U.S. Census data to investigate the racial/ethnic patterning of provider-patient communication among patients diagnosed with incidental medical findings requiring follow-up. My results indicate that racial/ethnic disparities in follow-up adherence stem from initial disparities in provider-patient communication. These communication disparities persist even after accounting for multiple socioeconomic, health, and provider characteristics, indicating a bias in medicine, whereby providers are less likely to communicate information about incidental medical findings to patients of color relative to White patients. This paper has important clinical implications, as it sheds new light on why we might see low adherence to medical advice among patients of color. Findings also have social, political, and policy relevance, as they suggest an important mechanism through which health inequalities persist. To finally eliminate racial/ethnic health inequalities in the United States, racial bias and discrimination within medical and public health infrastructures must be eliminated.

Watershed analysis of the target pulmonary artery for real-time localization of non-palpable pulmonary nodules

Background

Some pulmonary nodules are not suitable for computed tomography-guided percutaneous localization. This study aimed to investigate the feasibility and safety of real-time localization for these non-palpable pulmonary nodules using watershed analysis of the target pulmonary artery during thoracoscopic wedge resection.

Methods

Watershed analysis is a novel technique that can be used to create a specific area on the lung surface for nodule localization. This analysis is performed by temporarily blocking the target pulmonary artery and using indocyanine green fluorescence during surgery. In our study, the surgery was simulated and evaluated preoperatively using a high-precision three-dimensional reconstruction model obtained by multidetector spiral computed tomography. The lung was observed using an infrared thoracoscopy system after an intravenous injection of indocyanine green (2.5 mg/mL), and the white-to-blue transitional zone was marked using electrocautery, after which a wedge resection was performed.

Results

A total of 25 out of 26 patients underwent successful wedge resection. The mean tumor size and depth based on computed tomography scans were 13.2±6.4 and 12.2±7.8 mm, respectively. The mean operation duration was 142.6±52.8 min. The mean bleeding volume during surgery was 12.9±9.7 mL. The mean drainage tube indwelling time was 35.6±20.0 h, and the median length of postoperative stay was 3 days (range, 2-6 days).

Conclusions

Our experience showed that the watershed analysis of the target pulmonary artery for nodule localization was safe and feasible. It may become an effective and attractive alternative method for localizing non-palpable pulmonary nodules in selected patients undergoing thoracoscopic wedge resection.

Association Between 18F-FDG PET/CT-Based SUV Index and Malignant Status of Persistent Ground-Glass Nodules

To explore the association between ¹⁸F-FDG PET/CT-based SUV index and malignant risk of persistent ground-glass nodules (GGNs). We retrospectively analyzed a total of 166 patients with GGN who underwent PET/CT examination from January 2012 to October 2019. There were 113 women and 53 men, with an average age of 60.8 ± 9.1 years old. A total of 192 GGNs were resected and confirmed by pathology, including 22 in benign group and 170 in adenocarcinoma group. They were divided into three groups according to SUV index tertiles: Tertile 1 (0.14–0.54), Tertile 2 (0.55–1.17), and Tertile 3 (1.19–6.78), with 64 GGNs in each group. The clinical and imaging data of all patients were collected and analyzed. After adjusting for the potential confounding factors, we found that the malignancy risk of GGN significantly decreased as the SUV index increased (OR, 0.245; 95%CI, 0.119–0.504; P <0.001), the average probability of malignant GGN was 89.1% (95% CI, 53.1–98.3%), 80.5% (95% CI, 36.7–96.7%), and 34.3% (95%CI, 9.5–72.2%) for Tertile 1 to Tertile 3. And the increasing trend of SUV index was significantly correlated with the reduction of malignant risk (OR, 0.099; 95%CI, 0.025–0.394; P = 0.001), especially between Tertile 3 versus Tertile 1 (OR, 0.064; 95%CI, 0.012–0.356; P = 0.002). Curve fitting showed that the SUV index was linearly and negatively correlated with the malignant risk of GGN. SUV index is an independent correlation factor for malignancy risk of GGN, the higher the SUV index, the lower the probability of GGN malignancy.

Protocol and Rationale for the International Lung Screening Trial

Rationale: The NLST (National Lung Screening Trial) reported a 20% reduction in lung cancer mortality with low-dose computed tomography screening; however, important questions on how to optimize screening remain, including which selection criteria are most accurate at detecting lung cancers and what nodule management protocol is most efficient. The PLCO_m2012 (Prostate, Lung, Colorectal and Ovarian) Cancer Screening Trial 6-year and PanCan (Pan-Canadian Early Detection of Lung Cancer) nodule malignancy risk models are two of the better validated risk prediction models for screenee selection and nodule management, respectively. Combined use of these models for participant selection and nodule management could significantly improve screening efficiency.

Objectives: The ILST (International Lung Screening Trial) is a prospective cohort study with two primary aims: 1) Compare the accuracy of the PLCO_m2012 model against U.S. Preventive Services Task Force (USPSTF) criteria for detecting lung cancers and 2) evaluate nodule management efficiency using the PanCan nodule probability calculator-based protocol versus Lung-RADS.

Methods: ILST will recruit 4,500 participants who meet USPSTF and/or PLCO_m2012 risk ≥1.51%/6-year selection criteria. Participants will undergo baseline and 2-year low-dose computed tomography screening. Baseline nodules are managed according to PanCan probability score. Participants will be followed up for a minimum of 5 years. Primary outcomes for aim 1 are the proportion of individuals selected for screening, proportion of lung cancers detected, and positive predictive values of either selection criteria, and outcomes for aim 2 include comparing distributions of individuals and the proportion of lung cancers in each of three management groups: next surveillance scan, early recall scan, or diagnostic evaluation recommended. Statistical powers to detect differences in the four components of primary study aims were ≥82%.

Conclusions: ILST will prospectively evaluate the comparative accuracy and effectiveness of two promising multivariable risk models for screenee selection and nodule management in lung cancer screening.

Clinical trial registered with www.clinicaltrials.gov (NCT02871856).

ERS International Congress 2020: highlights from the Thoracic Surgery and Transplantation Assembly

The Thoracic Surgery and Lung Transplantation Assembly of the European Respiratory Society is delighted to present the highlights from the 2020 Virtual International Congress. We have selected four sessions that discussed recent advances in a wide range of topics. From the use of robotic surgery in thoracic surgery and extracorporeal life support as a bridge to lung transplantation, to lung transplantation in the era of new drugs. The sessions are summarised by early career members in close collaboration with the assembly leadership. We aim to give the reader an update on the highlights of the conference in the fields of thoracic surgery and lung transplantation.

The first “virtual” #ERSCongress was a great success, with very diverse and important sessions on innovation and the state of the art in thoracic surgery and lung transplantation, summarised in this articlehttps://bit.ly/392uwUA

Deep sequencing reveals the genomic characteristics of lung adenocarcinoma presenting as ground-glass nodules (GGNs)

Background

The concept of multi-step progression from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (ADC) has been proposed, and ground-glass nodules (GGNs) may play a critical role during the early lung tumorigenesis. We present the first comprehensive description of the genomic architecture of GGNs to unravel the genetic basis of GGN.

Methods

We investigated 30 GGN-like lungs ADC by performing >1,000× whole-exome sequencing (WES) and characterized the genomic variations and evaluate the relationship between the clinicopathologic and molecular characteristics in this disease.

Results

Despite the low somatic mutation burden, GGNs exhibited high intratumor heterogeneity (ITH) characterized by the proportion of subclonal mutations. Different mutagenesis shaped the genomes of GGN during cancer evolution and were mostly featured by molecular clock-like signatures that occur in clonal mutations and defective DNA mismatch signatures that occur in subclonal mutations. Moreover, 10.7–67.1% clonal mutations occurred after whole-genome doubling (WGD), indicating that WGD could be a frequent truncal event in GGNs. Samples with WGD showed higher genomic instability but lower ITH. These GGNs were characterized by recurrent focal copy-number changes that are highly associated with tumorigenesis, with only two genes (EGFR and RBM10) that were recurrently mutated. Additionally, GGNs with different pathological subtypes or computed tomography (CT) features exhibited distinct genetic characteristics. Lepidic predominant or pure GGNs in CT images carried a lower mutation burden and had a relatively stable genome than nonlepidic or mixed GGNs. GGNs with RBM10 mutations tended to accompany a pathologically lepidic pattern, indicating RBM10 may drive the distinct subtype of lung cancer with better prognosis.

Conclusions

These findings facilitated interpreting the genomic characteristics of GGNs, provided insight into the early stages of lung cancer evolution, and possessed potential clinical significance.

Intergroupe francophone de cancérologie thoracique, Société de pneumologie de langue française, and Société d'imagerie thoracique statement paper on lung cancer screening

Following the American National Lung Screening Trial results in 2011 a consortium of French experts met to edit a statement. Recent results of other randomized trials gave the opportunity for our group to meet again in order to edit updated guidelines. After literature review, we provide here a new update on lung cancer screening in France. Notably, in accordance with all international guidelines, the experts renew their recommendation in favor of individual screening for lung cancer in France as per the conditions laid out in this document. In addition, the experts recommend the very rapid organization and funding of prospective studies, which, if conclusive, will enable the deployment of lung cancer screening organized at the national level.

Pulmonary Benign Ground-Glass Nodules: CT Features and Pathological Findings

Background

Some pulmonary ground-glass nodules (GGNs) are benign and frequently misdiagnosed due to lack of understanding of their CT characteristics. This study aimed to reveal the CT features and corresponding pathological findings of pulmonary benign GGNs to help improve diagnostic accuracy.

Patients and Methods

From March 2016 to October 2019, patients with benign GGNs confirmed by operation or follow-up were enrolled retrospectively. According to overall CT manifestations, GGNs were classified into three types: I, GGO with internal high-attenuation zone; II, nodules lying on adjacent blood vessels; and other type, lesions without obvious common characteristics. CT features and pathological findings of each nodule type were evaluated.

Results

Among the 40 type I, 25 type II, and 14 other type GGNs, 24 (60.0%), 19 (76.0%), and 10 (71.4%) nodules were resected, respectively. Type I GGNs were usually irregular (25 of 40, 62.5%) with only one high-attenuation zone (38 of 40, 95.0%) (main pathological components: thickened alveolar walls with inflammatory cells, fibrous tissue, and exudation), which was usually centric (24 of 40, 60.0%), having blurred margin (38 of 40, 95.0%), and connecting to blood vessels (32 of 40, 80.0%). The peripheral GGO (main pathological component: a small amount of inflammatory cell infiltration with fibrous tissue proliferation) was usually ill-defined (28 of 40, 70.0%). Type II GGNs (main pathological components: focal interstitial fibrosis with or without inflammatory cell infiltration) lying on adjacent vessel branches were usually irregular (19 of 25, 76.0%) and well defined (16 of 25, 64.0%) but showed coarse margins (15 of 16, 93.8%). Other type GGNs had various CT manifestations but their pathological findings were similar to that of type II.

Conclusion

For subsolid nodules with CT features manifested in type I or II GGNs, follow-up should be firstly considered in further management.

Improvement in Follow-up Imaging With a Patient Tracking System and Computerized Registry for Lung Nodule Management

PURPOSE

Despite established guidelines, radiologists' recommendations and timely follow-up of incidental lung nodules remain variable. To improve follow-up of nodules, a system using standardized language (tracker phrases) recommending time-based follow-up in chest CT reports, coupled with a computerized registry, was created.

MATERIALS AND METHODS

Data were obtained from the electronic health record and a facility-built electronic lung nodule registry. We evaluated two randomly selected patient cohorts with incidental nodules on chest CT reports: before intervention (September 2008 to March 2011) and after intervention (August 2011 to December 2016). Multivariable logistic regression was used to compare the cohorts for the main outcome of timely follow-up, defined as a subsequent report within 13 months of the initial report.

RESULTS

In all, 410 patients were included in the pretracker cohort versus 626 in the tracker cohort. Before system inception, 30% of CT reports lacked an explicit time-based recommendation for nodule follow-up. The proportion of patients with timely follow-up increased from 46% to 55%, and the proportion of those with no documented follow-up or follow-up beyond 24 months decreased from 48% to 31%. The likelihood of timely follow-up increased 41%, adjusted for high risk for lung cancer and age 65 years or older. After system inception, reports missing a tracker phrase for nodule recommendation averaged 6%, without significant interyear variation.

CONCLUSIONS

Standardized language added to CT reports combined with a computerized registry designed to identify and track patients with incidental lung nodules was associated with improved likelihood of follow-up imaging.

Predictive factors of recurrence after resection of subsolid clinical stage IA lung adenocarcinoma

BACKGROUND

Ongoing studies are currently investigating the extent of surgical resection required for subsolid cancers. This study aimed to investigate the predictive factors related to recurrence in patients with clinical stage IA subsolid cancer who underwent either lobectomy or sublobar resection.

METHODS

This was a prospective multicenter observational study conducted in eight qualifying university teaching hospitals between April 2014 and December 2016. A total of 173 patients with subsolid nodules pathologically confirmed to have primary lung adenocarcinoma and stage IA disease were included in the final analysis. All patients underwent lobectomy, segmentectomy, or wedge resection performed by experienced thoracoscopic surgeons at each site. The surgical procedure was chosen based on the decision of the surgeons involved. The primary endpoint was time to recurrence (TTR).

RESULTS

The study population was 43.9% (76 of 173) male with a mean age of 60.7 years. During the median follow-up period of 5.01 years, nine patients (5%) experienced disease recurrence. In the multivariable analysis, tumor size (size ≥2 cm) (hazard ratio: 73.717, 95% confidence interval [CI]: 3.635-895.036; p < 0.001) and stage IA3 (hazard ratio: 62.010, 95% CI: 2.837-855.185; p < 0.001) were independent predictors of tumor recurrence. When analyzing the recurrence outcome in patients according to surgical procedure, no significant difference was found in TTR among the three groups (i.e., lobectomy, segmentectomy, and wedge resection; p = 0.99).

CONCLUSIONS

Patients with radiologically subsolid lung adenocarcinoma measuring <3 cm could be candidates for sublobar resection instead of lobectomy.

[Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes]

背景与目的

肺实性小结节的术前诊断及鉴别诊断十分困难。计算机断层扫描（computed tomography, CT）作为肺癌筛查的常用手段，被广泛应用于临床。本研究旨在对 < 1 cm的肺实性结节临床诊疗中肺恶性结节与肺内淋巴结患者的临床资料进行分析，为两者的鉴别提供参考。

方法

回顾性分析2017年6月-2020年6月行手术治疗的肺实性结节患者。共收集了145个结节（肺腺癌60个，肺类癌2个，恶性间皮瘤1个，肉瘤样癌1个，淋巴结81个）的患者临床资料，最终分为肺腺癌和肺内淋巴结两组，并对其临床资料进行了统计分析。根据单因素分析（χ²检验、t检验）结果筛选有统计学差异的变量，纳入Logistic回归多因素分析，确定预测变量并绘制受试者工作曲线（receiver operating characteristic, ROC）曲线，得到曲线下面积（area under the curve, AUC）值。

结果

Logistic回归分析显示结节最长径、Max CT值、分叶征和毛刺征是肺腺癌与肺内淋巴结鉴别的重要指标，风险比分别为106.645（95%CI: 3.828-2, 971.220, P < 0.01）、0.980（95%CI: 0.969-0.991, P < 0.01）、3.550（95%CI: 1.299-9.701, P=0.01）、3.618（95%CI: 1.288-10.163, P=0.02）。根据Logistic回归分析结果确定预测模型，绘制ROC曲线，计算曲线下面积AUC值=0.877（95%CI: 0.821-0.933, P < 0.01）。

结论

对于 < 1 cm的肺实性结节，在众多因素中，肺结节最长径、Max CT值、分叶征和毛刺征对鉴别肺恶性结节和肺内淋巴结更为重要。

Localization of Small Pulmonary Nodules Using Augmented Fluoroscopic Bronchoscopy: Experience from 100 Consecutive Cases

BACKGROUND

We developed augmented fluoroscopic bronchoscopy (AFB) for the localization of small pulmonary nodules. Here, we review the results of 100 consecutive cases of AFB localization performed in our institute in order to evaluate its efficacy, safety, and procedural details.

METHODS

This study was a retrospective analysis of prospectively collected data. Between July 2018 and September 2019, a total of 100 patients with 124 small lung nodules underwent AFB localization with dye marking and/or microcoil placement. All localizations were performed in a cone-beam computed tomography examination room followed by thoracoscopic resection within 3 days.

RESULTS

The mean nodule size was 9.7 mm, and the mean distance from the pleural space was 18.6 mm. Sixty-three patients received dye marking only, and 37 patients received microcoil placement with/without additional dye marking. The mean bronchoscopy duration was 10.4 min, and the mean fluoroscopy duration was 3.4 min. The mean radiation exposure (expressed as the dose-area product) was 3140.8 μGy × m². The AFB procedures were successful in 94 patients [augmented fluoroscopy discrepancy (n = 2), incomplete C-arm confirmation (n = 3), microcoil unlooping (n = 1)]; of those, 91 received successful marker-guided resection [invisible dye (n = 2), failed nodule resection with first wedge (n = 1)]. The mean length of postoperative stay and chest drainage was 4.2 and 2.9 days, respectively.

CONCLUSIONS

The AFB technique is a safe and reproducible alternative for localizing small pulmonary nodules, and various localization strategies can be implemented for different nodule locations and resection plans.

Radiomics nomogram: A noninvasive tool for preoperative evaluation of the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules

In this study, we aimed to establish a radiomics nomogram that noninvasively evaluates the invasiveness of pulmonary adenocarcinomas manifesting as ground-glass nodules (GGNs). Computed tomography (CT) images of 509 patients manifesting as GGNs were collected: 70% of cases were included in the training cohort and 30% in the validation cohort. The Max-Relevance and Min-Redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to select the radiomics features and construct a radiomics signature. Univariate and multivariate logistic regression were used to select the invasiveness-related clinical and CT morphological predictors. Age, smoking history, long diameter, and average CT value were retained as independent predictors of GGN invasiveness. A radiomics nomogram was established by integrating clinical and CT morphological features with the radiomics signature. The radiomics nomogram showed good predictive ability in the training set (area under the curve [AUC], 0.940; 95% confidence interval [CI], 0.916-0.964) and validation set (AUC, 0.946; 95% CI, 0.907-0.986). This radiomics nomogram may serve as a noninvasive and accurate predictive tool to determine the invasiveness of GGNs prior to surgery and assist clinicians in creating personalized treatment strategies.

Decoding the multicellular ecosystem of lung adenocarcinoma manifested as pulmonary subsolid nodules by single-cell RNA sequencing

Lung adenocarcinomas (LUAD) that radiologically display as subsolid nodules (SSNs) exhibit more indolent biological behavior than solid LUAD. The transcriptomic features and tumor microenvironment (TME) of SSN remain poorly understood. Here, we performed single-cell RNA sequencing analyses of 16 SSN samples, 6 adjacent normal lung tissues (nLung), and 9 primary LUAD with lymph node metastasis (mLUAD). Approximately 0.6 billion unique transcripts were obtained from 118,293 cells. We found that cytotoxic natural killer/T cells were dominant in the TME of SSN, and malignant cells in SSN undergo a strong metabolic reprogram and immune stress. In SSN, the subtype composition of endothelial cells was similar to that in mLUAD, while the subtype distribution of fibroblasts was more like that in nLung. Our study provides single-cell transcriptomic profiling of SSN and their TME. This resource provides deeper insight into the indolent nature of SSN and will be helpful in advancing lung cancer immunotherapy.

Dependence of radiomic features on pixel size affects the diagnostic performance of radiomic signature for the invasiveness of pulmonary ground-glass nodule

OBJECTIVE

To investigate the effect of reducing pixel size on the consistency of radiomic features and the diagnostic performance of the downstream radiomic signatures for the invasiveness for pulmonary ground-glass nodules (GGNs) on CTs.

METHODS

We retrospectively collected the clinical data of 182 patients with GGNs on high resolution CT (HRCT). The CT images of different pixel sizes (0.8mm, 0.4mm, 0.18 mm) were obtained by reconstructing the single HRCT scan using three combinations of field of view and matrix size. For each pixel size setting, radiomic features were extracted for all GGNs and radiomic signatures for the invasiveness of GGNs were built through two modeling pipelines for comparison.

RESULTS

The study finally extracted 788 radiomic features. 87% radiomic features demonstrated inter pixel size variation. By either modeling pipeline, the radiomic signature under small pixel size performed significantly better than those under middle or large pixel sizes in predicting the invasiveness of GGNs (p's value <0.05 by Delong test). With the independent modeling pipeline, the three pixel size bounded radiomic signatures shared almost no common features.

CONCLUSIONS

Reducing pixel size could cause inconsistency in most radiomic features and improve the diagnostic performance of the downstream radiomic signatures. Particularly, super HRCTs with small pixel size resulted in more accurate radiomic signatures for the invasiveness of GGNs.

ADVANCES IN KNOWLEDGE

The dependence of radiomic features on pixel size will affect the performance of the downstream radiomic signatures. The future radiomic studies should consider this effect of pixel size.

Digital tomosynthesis and ground glass nodules: Optimization of acquisition protocol. A phantom study

INTRODUCTION

Ground-glass nodules may be the expression of benign conditions, pre-invasive lesions or malignancies. The aim of our study was to evaluate the capability of chest digital tomosynthesis (DTS) in detecting pulmonary ground-glass opacities (GGOs).

METHODS

An anthropomorphic chest phantom and synthetic nodules were used to simulate pulmonary ground-glass nodules. The nodules were positioned in 3 different regions (apex, hilum and basal); then the phantom was scanned by multi-detector CT (MDCT) and DTS. For each set (nodule-free phantom, nodule in apical zone, nodule in hilar zone, nodule in basal zone) seven different scans (n = 28) were performed varying the following technical parameters: Cu-filter (0.1-0.3 mm), dose rateo (10-25) and X-ray tube voltage (105-125 kVp). Two radiologists in consensus evaluated the DTS images and provided in agreement a visual score: 1 for unidentifiable nodules, 2 for poorly identifiable nodules, 3 for nodules identifiable with fair certainty, 4 for nodules identifiable with absolute certainty.

RESULTS

Increasing the dose rateo from 10 to 15, GGOs located in the apex and in the basal zone were better identified (from a score = 2 to a score = 3). GGOs located in the hilar zone were not visible even with a higher dose rate. Intermediate density GGOs had a good visibility score (score = 3) and it did not improve by varying technical parameters. A progressive increase of voltage (from 105 kVp to 125 kVp) did not provide a better nodule visibility.

CONCLUSION

DTS with optimized technical parameters can identify GGOs, in particular those with a diameter greater than 10 mm.

IMPLICATIONS FOR PRACTICE

DTS could have a role in the follow-up of patients with known GGOs identified in lung apex or base region.

Primary pulmonary diffuse large B-cell lymphoma with multiple ground-glass nodules as the primary manifestation: A case report

INTRODUCTION

Primary pulmonary lymphoma (PPL) is a rare extranodal lymphoma. Only 5% to 20% of patients suffering from PPL have diffuse large β-cell lymphoma (DLBCL), and their chest computed tomography (CT) findings show single- or double-lung patchy or flocculated shadows, isolated or multifocal nodules, or masses. In this research paper, we report an older woman having multiple ground-glass nodules, who was eventually diagnosed with primary pulmonary diffuse large β-cell lymphoma (PPDLBCL).

PATIENT CONCERNS

A 69-year-old woman suffering from cough was admitted to the Second Hospital of Jilin University.

DIAGNOSES

A chest CT scan showed multiple ground-glass nodules. She had received 2 weeks of antibiotic treatment, but the multiple ground-glass nodules were still present. Lung biopsy was performed by tracheoscopy, which showed non-Hodgkin diffuse large β-cell lymphoma.

INTERVENTIONS

The patient received R-CHOP-21 chemotherapy.

OUTCOMES

The multiple ground-glass nodules were absorbed.

CONCLUSION

The current study shows that spotting multiple ground-glass nodules in the lungs is a clear indication of the presence of PPDLBCL. It is important to spread awareness of PPDLBCL, which needs timely diagnosis and management.

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

Rationale and Objectives

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

Materials and Methods

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

Results

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

Conclusion

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

A radiomics study to predict invasive pulmonary adenocarcinoma appearing as pure ground-glass nodules

AIM

To establish a machine-learning model to differentiate adenocarcinoma in situ (AIS) or minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma (IAC) appearing as pure ground-glass nodules (pGGNs).

MATERIALS AND METHODS

This retrospective study enrolled 136 patients with histopathologically diagnosed with AIS, MIA, and IAC. All pGGNs were divided randomly into a training and a testing dataset at a ratio of 7 : 3. Radiomics features were extracted based on the unenhanced computed tomography (CT) images derived from the last preoperative CT examination of each patient. The F-test and least absolute shrinkage and selection operator (LASSO) logistic regression were applied to select the most valuable features to establish a support vector machine (SVM) model. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUROC), and the accuracy, sensitivity, and specificity were calculated to compare the diagnostic performance of radiologists and the SVM model.

RESULTS

Six significant radiomics features were selected to develop the SVM model and showed excellent ability to differentiate AIS/MIA from IAC in both the training dataset (AUROC=0.950, 95% confidence interval [CI]: 0.886-0.984) and the testing dataset (AUROC=0.945, 95% CI: 0.826-0.992). Compared with two radiologists, the proposed model possessed significant advantages with higher accuracy (90.24% versus 75.61% and 80.49%), sensitivity (91.67% versus 50% and 75%), and specificity (89.66% versus 86.21% and 82.76%).

CONCLUSION

A machine-learning model based on radiomics features exhibits superior diagnostic performance in differentiating AIS/MIA from IAC appearing as pGGNs.

Lung Cancer Staging

Anatomic staging is a critical step in evaluation of patients with lung cancer. Accurate identification of stage based on features of primary tumor (T), regional nodes (N), and metastatic disease (M) is fundamental to determining appropriate care. In this article, the TNM components of the anatomic staging system and a framework for description of lung cancer with multiple pulmonary sites of involvement are discussed. TNM combinations are grouped according to prognosis, with patient-level, tumor-level, and environment-level factors also influencing survival outcomes. Although the staging system does not include molecular and immunologic information, anatomic staging remains the common language for communicating extent of disease.

The value of percentile base on computed tomography histogram in differentiating the invasiveness of adenocarcinoma appearing as pure ground-glass nodules

To investigate the value of percentile base on computed tomography (CT) histogram analysis for distinguishing invasive adenocarcinoma (IA) from adenocarcinoma in situ (AIS) or micro invasive adenocarcinoma (MIA) appearing as pure ground-glass nodules.A total of 42 cases of pure ground-glass nodules that were surgically resected and pathologically confirmed as lung adenocarcinoma between January 2015 and May 2019 were included. Cases were divided into IA and AIS/MIA in the study. The percentile on CT histogram was compared between the 2 groups. Univariate and multivariate logistic regression were used to determine which factors demonstrated a significant effect on invasiveness. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to evaluate the predictive ability of individual characteristics and the combined model.The 4 histogram parameters (25th percentile, 55th percentile, 95th percentile, 97.5th percentile) and the combined model all showed a certain diagnostic value. The combined model demonstrated the best diagnostic performance. The AUC values were as follows: 25th percentile = 0.693, 55th percentile = 0.706, 95th percentile = 0.713, 97.5th percentile = 0.710, and combined model = 0.837 (all P < .05).The percentile of histogram parameters help to improve the ability to radiologically determine the invasiveness of lung adenocarcinoma appearing as pure ground-glass nodules.

Retrospective Review of Preoperative Wire Localization for Peripheral Ground Glass Opacities

Video-assisted thoracoscopy (VATS) is performed for diagnosis and treatment of peripheral lung nodules. Localization of peripherally located ground-glass opacities (GGOs) can be challenging. We report the results and usefulness of preoperative computed tomography (CT)-guided wire localization. Records for patients who underwent CT-guided wire localization prior to VATS resection for peripherally located GGOs were analyzed. Our technique for targeting the GGOs, complications, and histopathology of GGOs is reviewed. Forty patients (mean age 68 years) underwent pulmonary resections following CT-guided wire localization. The mean diameter of the GGO was 11.0 mm. The mean distance from the pleural surface to the peripheral margin of the GGO was 18.6 mm. Complications from the wire localization included pneumothorax in 5 patients (12.5%), none of whom required insertion of a chest tube; parenchymal hemorrhage in 3 patients (7.5%); and pleural effusion requiring chest tube drainage (unrelated to the wire) in 1 patient (2.5%). The mean operative time was 74 (range: 21-186 ) minutes. Pathological examination revealed lung malignancy in 36 patients (90%). The diagnostic yield was 100%. Preoperative CT-guided wire localization for solitary or multiple peripherally located GGOs allows for determination of histopathologic diagnosis and high diagnostic yield.

Approach to the Subsolid Nodule

Most focal persistent ground glass nodules (GGNs) do not progress over 10 years. Research suggests that GGNs that do not progress, those that do, and solid lung cancers are fundamentally different diseases, although histologically they seem similar. Surveillance of GGNs to identify those that gradually progress is safe and does not risk losing a window. GGNs with 5 mm solid component or less than 10 mm consolidation (mediastinal and lung windows, respectively, on thin slice CT) are highly curable with resection. The optimal type of resection is unclear; sublobar resection is reasonable but an adequate margin is critically important.

Application of large-scale targeted sequencing to distinguish multiple lung primary tumors from intrapulmonary metastases

The effective differentiation between multiple primary lung tumors (MPs) and intrapulmonary metastases (IMs) in patients is imperative to discover the exact disease stage and to select the most appropriate treatment. In this study, the authors was to evaluate the efficacy and validity of large-scale targeted sequencing (LSTS) as a supplement to estimate whether multifocal lung cancers (MLCs) are primary or metastatic. Targeted sequencing of 520 cancer-related oncogenes was performed on 36 distinct tumors from 16 patients with MPs. Pairing analysis was performed to evaluate the somatic mutation pattern of MLCs in each patient. A total of 25 tumor pairs from 16 patients were sequenced, 88% (n = 22) of which were classified as MPs by LSTS, consistent with clinical diagnosis. One tumor pair from a patient with lymph node metastases had highly consistent somatic mutation profiles, thus predicted as a primary-metastatic pair. In addition, some matched mutations were observed in the remaining two paired ground-glass nodules (GGNs) and classified as high-probability IMs by LSTS. Our study revealed that LSTS can potentially facilitate the distinction of MPs from IMs. In addition, our results provide new genomic evidence of the presence of cancer invasion in GGNs, even pure GGNs.