Radiologic implications of the 2011 classification of adenocarcinoma of the lung

Diseases Involving the Lung Peribronchovascular Region: A CT Imaging Pathologic Classification

TOPIC IMPORTANCE

Chest CT imaging holds a major role in the diagnosis of lung diseases, many of which affect the peribronchovascular region. Identification and categorization of peribronchovascular abnormalities on CT imaging can assist in formulating a differential diagnosis and directing further diagnostic evaluation.

REVIEW FINDINGS

The peribronchovascular region of the lung encompasses the pulmonary arteries, airways, and lung interstitium. Understanding disease processes associated with structures of the peribronchovascular region and their appearances on CT imaging aids in prompt diagnosis. This article reviews current knowledge in anatomic and pathologic features of the lung interstitium composed of intercommunicating prelymphatic spaces, lymphatics, collagen bundles, lymph nodes, and bronchial arteries; diffuse lung diseases that present in a peribronchovascular distribution; and an approach to classifying diseases according to patterns of imaging presentations. Lung peribronchovascular diseases can appear on CT imaging as diffuse thickening, fibrosis, masses or masslike consolidation, ground-glass or air space consolidation, and cysts, acknowledging that some diseases may have multiple presentations.

SUMMARY

A category approach to peribronchovascular diseases on CT imaging can be integrated with clinical features as part of a multidisciplinary approach for disease diagnosis.

Unusual presentation of ROS1 rearranged metastatic non-small cell lung cancer

The spectrum of clinical and radiographic presentations of lung adenocarcinoma is increasingly broad, including in the metastatic setting. Here, we report on a patient who initially presented with a mild chronic cough that remained stable over a decade, with serial CT scans showing gradual worsening of multifocal areas of consolidation and ground-glass opacities of the bilateral lungs. The patient was ultimately diagnosed with ROS1 rearranged lung adenocarcinoma and achieved a dramatic response with entrectinib. This case highlights the variable presentation of non-small cell lung cancer (NSCLC) and the importance of comprehensive molecular testing for newly diagnosed metastatic NSCLC.

Prognostic nomogram based on pre-treatment HALP score for patients with advanced non-small cell lung cancer

BACKGROUND

To explore the correlation of pre-treatment Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) score with the prognosis of patients with advanced Non-Small Cell Lung Cancer (NSCLC) undergoing first-line conventional platinum-based chemotherapy.

METHODS

In this retrospective cohort study, 203 patients with advanced NSCLC were recruited from January 2017 to December 2021. The cut-off value for the HALP score was determined by Receiver Operating Characteristic (ROC) curve analysis. The baseline characteristics and blood parameters were recorded, and the Log-rank test and Kaplan-Meier curves were applied for the survival analysis. In the univariate and multivariate analyses, the Cox regression analysis was carried out. The predictive accuracy and discriminative ability of the nomogram were determined by the Concordance index (C-index) and calibration curve and compared with a single HALP score by ROC curve analysis.

RESULTS

The optimal cut-off value for the HALP score was 28.02. The lower HALP score was closely associated with poorer Progression-Free Survival (PFS) and Overall Survival (OS). The male gender and other pathological types were associated with shorter OS. Disease progression and low HALP were correlated with shorter OS and PFS. In addition, nomograms were established based on HALP scores, gender, pathology type and efficacy rating, and used to predict OS. The C-index for OS prediction was 0.7036 (95% CI 0.643 to 0.7643), which was significantly higher than the C-index of HALP at 6-, 12-, and 24-months.

CONCLUSION

The HALP score is associated with the prognosis of advanced NSCLC patients receiving conventional platinum-based chemotherapy, and the nomogram established based on the HALP score has a better predictive capability for OS.

Limited resection is comparable to lobectomy for tumor size ≤ 2 cm pulmonary invasive mucinous adenocarcinoma

OBJECTIVES

Invasive mucinous adenocarcinoma (IMA) has a rare incidence with better prognosis than nonmucinous adenocarcinoma. We aimed to investigate the prognosis between limited resection and lobectomy for patients with clinical stage IA IMA ≤ 2 cm.

METHODS

Data were taken from two cohorts: In Shanghai Pulmonary Hospital (SPH) corhort, we identified 403 patients with clinical stage IA IMA who underwent surgery. In the SEER corhort, 480 patients with stage T1 IMA who after surgery were included. Recurrence-free survival (RFS) for SPH corhort, lung cancer-specific survival (LCSS) for the SEER corhort and overall survival (OS) for both corhort were compared between patients undergoing lobectomy and limited resection by Log-rank and Cox proportional hazard regression model.

RESULTS

In SPH corhort, patients who underwent limited resection had equivalent prognosis than those underwent lobectomy (5-year RFS: 79.3% versus. 82.6%, p = 0.116; 5-year OS: 86.2% versus. 88.3%, p = 0.235). However, patients with IMA > 2 to 3 cm had worse prognosis than those with IMA ≤ 2 cm (5-year RFS: 73.7% versus. 86.1%, p = 0.007). In the analysis of IMA > 2 to 3 cm subgroup, multivariate analysis showed that limited resection was an independent risk factor of RFS (hazard ratio, 2.417; 95% confidence interval, 1.157-5.049; p = 0.019), while OS (p = 0.122) was not significantly different between two groups. For IMA ≤ 2 cm, limited resection was not a risk factor of RFS (p = 0. 953) and OS (p = 0.552). In the SEER corhort, IMA ≤ 2 cm subgroup, limited resection was equivalent prognosis in LCSS (p = 0.703) and OS (p = 0.830).

CONCLUSIONS

Limited resection could be a potential surgical option which comparable to lobectomy in patients with clinical stage IA IMA ≤ 2 cm.

Uncommon Causes of Interlobular Septal Thickening on CT Images and Their Distinguishing Features

Interlobular septa thickening (ILST) is a common and easily recognized feature on computed tomography (CT) images in many lung disorders. ILST thickening can be smooth (most common), nodular, or irregular. Smooth ILST can be seen in pulmonary edema, pulmonary alveolar proteinosis, and lymphangitic spread of tumors. Nodular ILST can be seen in the lymphangitic spread of tumors, sarcoidosis, and silicosis. Irregular ILST is a finding suggestive of interstitial fibrosis, which is a common finding in fibrotic lung diseases, including sarcoidosis and usual interstitial pneumonia. Pulmonary edema and lymphangitic spread of tumors are the commonly encountered causes of ILST. It is important to narrow down the differential diagnosis as much as possible by assessing the appearance and distribution of ILST, as well as other pulmonary and extrapulmonary findings. This review will focus on the CT characterization of the secondary pulmonary lobule and ILST. Various uncommon causes of ILST will be discussed, including infections, interstitial pneumonia, depositional/infiltrative conditions, inhalational disorders, malignancies, congenital/inherited conditions, and iatrogenic causes. Awareness of the imaging appearance and various causes of ILST allows for a systematic approach, which is important for a timely diagnosis. This study highlights the importance of a structured approach to CT scan analysis that considers ILST characteristics, associated findings, and differential diagnostic considerations to facilitate accurate diagnoses.

Perspective on Management of Low-Dose Computed Tomography Findings on Low-Dose Computed Tomography Examinations for Lung Cancer Screening. From the International Association for the Study of Lung Cancer Early Detection and Screening Committee

Lung cancer screening using low-dose computed tomography (LDCT) carefully implemented has been found to reduce deaths from lung cancer. Optimal management starts with selection of eligibility criteria, counseling of screenees, smoking cessation, selection of the regimen of screening which specifies the imaging protocol, and workup of LDCT findings. Coordination of clinical, radiologic, and interventional teams and ultimately treatment of diagnosed lung cancers under screening determine the benefit of LDCT screening. Ethical considerations of who should be eligible for LDCT screening programs are important to provide the benefit to as many people at risk of lung cancer as possible. Unanticipated diseases identified on LDCT may offer important benefits through early detection of leading global causes of death, such as cardiovascular diseases and chronic obstructive pulmonary disease, as the latter may result from conditions such as emphysema and bronchiectasis, which can be identified early on LDCT. This report identifies the key components of the regimen of LDCT screening for lung cancer which include the need for a management system to provide data for continuous updating of the regimen and provides quality assurance assessment of actual screenings. Multidisciplinary clinical management is needed to maximize the benefit of early detection, diagnosis, and treatment of lung cancer. Different regimens have been evolving throughout the world as the resources and needs may be different, for countries with limited resources. Sharing of results, further knowledge, and incorporation of technologic advances will continue to accelerate worldwide improvements in the diagnostic and treatment approaches.

Prognostic factors for invasive mucinous adenocarcinoma of the lung: systematic review and meta-analysis

BACKGROUND

Invasive mucinous adenocarcinoma of the lung (IMA) is a unique and rare subtype of lung adenocarcinoma with poorly defined prognostic factors and highly controversial studies. Hence, this study aimed to comprehensively identify and summarize the prognostic factors associated with IMA.

METHODS

A comprehensive search of relevant literature was conducted in the PubMed, Embase, Cochrane, and Web of Science databases from their inception until June 2023. The pooled hazard ratio (HR) and corresponding 95% confidence intervals (CI) of overall survival (OS) and/or disease-free survival (DFS) were obtained to evaluate potential prognostic factors.

RESULTS

A total of 1062 patients from 11 studies were included. In univariate analysis, we found that gender, age, TNM stage, smoking history, lymph node metastasis, pleural metastasis, spread through air spaces (STAS), tumor size, pathological grade, computed tomography (CT) findings of consolidative-type morphology, pneumonia type, and well-defined heterogeneous ground-glass opacity (GGO) were risk factors for IMA, and spiculated margin sign was a protective factor. In multivariate analysis, smoking history, lymph node metastasis, pathological grade, STAS, tumor size, and pneumonia type sign were found to be risk factors. There was not enough evidence that epidermal growth factor receptor (EGFR) mutations, anaplastic lymphoma kinase (ALK) mutations, CT signs of lobulated margin, and air bronchogram were related to the prognosis for IMA.

CONCLUSION

In this study, we comprehensively analyzed prognostic factors for invasive mucinous adenocarcinoma of the lung in univariate and multivariate analyses of OS and/or DFS. Finally, 12 risk factors and 1 protective factor were identified. These findings may help guide the clinical management of patients with invasive mucinous adenocarcinoma of the lung.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma

BACKGROUND

Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment.

OBJECTIVE

This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers.

DESIGN

A retrospective case control, diagnostic accuracy study.

METHODS

This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines.

RESULTS

The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively.

CONCLUSION

This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

Ex-vivo 1.5T MR Imaging versus CT in Estimating the Size of the Pathologically Invasive Component of Lung Adenocarcinoma Spectrum Lesions

PURPOSE

The purpose of this study was to investigate whether ex-vivo MRI enables accurate estimation of the invasive component of lung adenocarcinoma.

METHODS

We retrospectively reviewed 32 patients with lung adenocarcinoma who underwent lung lobectomy. The specimens underwent MRI at 1.5T. The boundary between the lesion and the normal lung was evaluated on a 5-point scale in each three MRI sequences, and a one-way analysis of variance and post-hoc tests were performed. The invasive component size was measured histopathologically. The maximum diameter of each solid component measured on CT and MR T1-weighted (T1W) images and the maximum size obtained from histopathologic images were compared using the Wilcoxon signed-rank test. Inter-reader agreement was evaluated using intraclass correlation coefficients (ICC).

RESULTS

T1W images were determined to be optimal for the delineation of the lesions (P < 0.001). The histopathologic invasive area corresponded to the area where the T1W ex-vivo MR image showed a high signal intensity that was almost equal to the intravascular blood signal. The maximum diameter of the solid component on CT was overestimated compared with the maximum invasive size on histopathology (mean, 153%; P < 0.05), while that on MRI was evaluated mostly accurately without overestimation (mean, 108%; P = 0.48). The interobserver reliability of the measurements using CT and MRI was good (ICC = 0.71 on CT, 0.74 on MRI).

CONCLUSION

Ex-vivo MRI was more accurate than conventional CT in delineating the invasive component of lung adenocarcinoma.

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

Background

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

Methods

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

Results

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

Conclusion

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

Preoperative 18F-FDG PET/CT and CT radiomics for identifying aggressive histopathological subtypes in early stage lung adenocarcinoma

Lung adenocarcinoma (ADC) is the most common non-small cell lung cancer. Surgical resection is the primary treatment for early-stage lung ADC while lung-sparing surgery is an alternative for non-aggressive cases. Identifying histopathologic subtypes before surgery helps determine the optimal surgical approach. Predominantly solid or micropapillary (MIP) subtypes are aggressive and associated with a higher likelihood of recurrence and metastasis and lower survival rates. This study aims to non-invasively identify these aggressive subtypes using preoperative 18F-FDG PET/CT and diagnostic CT radiomics analysis. We retrospectively studied 119 patients with stage I lung ADC and tumors ≤ 2 cm, where 23 had aggressive subtypes (18 solid and 5 MIPs). Out of 214 radiomic features from the PET/CT and CT scans and 14 clinical parameters, 78 significant features (3 CT and 75 PET features) were identified through univariate analysis and hierarchical clustering with minimized feature collinearity. A combination of Support Vector Machine classifier and Least Absolute Shrinkage and Selection Operator built predictive models. Ten iterations of 10-fold cross-validation (10 ×10-fold CV) evaluated the model. A pair of texture feature (PET GLCM Correlation) and shape feature (CT Sphericity) emerged as the best predictor. The radiomics model significantly outperformed the conventional predictor SUVmax (accuracy: 83.5% vs. 74.7%, p = 9e-9) and identified aggressive subtypes by evaluating FDG uptake in the tumor and tumor shape. It also demonstrated a high negative predictive value of 95.6% compared to SUVmax (88.2%, p = 2e-10). The proposed radiomics approach could reduce unnecessary extensive surgeries for non-aggressive subtype patients, improving surgical decision-making for early-stage lung ADC patients.

Computed Tomography and 18F-Fluorodeoxyglucose-Positron Emission Tomography/Computed Tomography Imaging Biomarkers of Lung Invasive Non-mucinous Adenocarcinoma: Prediction of Grade 3 Tumour Based on World Health Organization Grading System

AIMS

To evaluate computed tomography (CT) and 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG-PET/CT) findings of invasive non-mucinous adenocarcinoma (INMA) of the lung as a predictor of histological tumour grade according to 2021 World Health Organization (WHO) classification.

MATERIALS AND METHODS

This retrospective study included consecutive patients with surgically resected INMA who underwent both preoperative CT and 18F-FDG-PET/CT. A three-tiered tumour grade was performed based on the fifth edition of the WHO classification of lung tumours. CT imaging features and the maximum standardised uptake value (SUVmax) were compared among the three tumour grades.

RESULTS

In total, 214 patients with INMA (median age 70 years; interquartile range 65-76 years; 123 men) were histologically categorised: 36 (17%) as grade 1, 102 (48%) as grade 2 and 76 (35%) as grade 3. Pure solid appearance was more frequent in grade 3 (83%) than in grades 1 (0%) and 2 (26%) (P < 0.001). The SUVmax of the entire tumour was higher in grade 3 than in grades 1 and 2 (P < 0.001). Multivariable analysis revealed that pure solid appearance (odds ratio = 94.0; P < 0.001), round/oval shape (odds ratio = 4.01; P = 0.001), spiculation (odds ratio = 2.13; P = 0.04), air bronchogram (odds ratio = 0.40; P = 0.03) and SUVmax (odds ratio = 1.45; P < 0.001) were significant predictors for grade 3 INMAs.

CONCLUSION

Pure solid appearance, round/oval shape, spiculation, absence of air bronchogram and high SUVmax were associated with grade 3 INMAs. CT and 18F-FDG-PET/CT were potentially useful non-invasive imaging methods to predict the histological grade of INMAs.

Suspicious lung lesions for malignancy: the lesion-to-spinal cord signal intensity ratio in T2WI and DWI–MRI versus PET/CT; a prospective pathologic correlated study with accuracy and ROC analyses

Background

The multi-detector computed tomography (MDCT) and tissue biopsy are the gold standards for the evaluation of lung malignancies. However, there is a wide range of pulmonary indeterminate lesions that could mimic lung cancer. Furthermore, the diagnosis of malignancy could be challenging if the lesion is small and early presenting by a part-solid or ground-glass nodule or if surrounded by parenchymal lung reaction with consolidation and atelectasis. The previous literature focused on the role of diffusion-weighted image–magnetic resonance imaging (DWI) and the apparent diffusion coefficient (ADC) mapping in the evaluation of lung malignancy. A novel quantitative T2 assessment is provided and tested in this study. Aim of the work: To evaluate the accuracy of specific non-invasive quantitative magnetic resonance imaging (MRI) parameters in the characterization of suspicious lung lesions and the discrimination between the malignant and benign nature. They included the lesion-to-spinal cord signal intensity ratio in T2-WI and DWI as well as the mean and minimum apparent diffusion coefficient (ADC) values. This is performed using a prospective pathologic correlated study with receiver-operating characteristics (ROC) analysis and comparison with positron emission tomography (PET-CT) accuracy results.

Results

This study was prospectively performed during the period between June/2021 and June/2022. It was conducted on 43 suspicious lung lesions detected by MDCT. MRI and PET/CT examinations were performed for all patients, and the results were compared to the final diagnosis obtained after biopsy and pathological assessment, using the statistical tests of significance and P-value. Cutoff values were automatically calculated, and then, accuracy tests and ROC analyses were performed. Five expert radiologists and a single consulting pulmonologist participated in this study. The inter-rater reliability ranges between good and excellent with the intra-class correlation coefficient (ICC) ranging between 0.85 and 0.94. In T2-WI: The lesion-to-spinal cord signal intensity ratio was higher in the malignant group (1.35 ± 0.29) than in the benign group (0.88 ± 0.40), (P < 0.001). At the estimated cutoff value (> 1), the sensitivity was 96.43%, the specificity was 80.00%, and AUC = 0.86. In b500-DWI: The lesion-to-spinal cord signal intensity ratio was higher in the malignant group (0.70–1.35) than in the benign group (0.20–0.70) (P < 0.001). At the estimated cutoff value (> 0.7), the sensitivity was 71.43%, the specificity was 86.67%, and AUC = 0.86. The mean and minimum ADC values were lower in the malignant group (0.6–1.3 and 0.3–1.1 × 10–3 mm2/s) than the benign group (1–1.6 and 0.7–1.4 × 10–3 mm2/s), (P < 0.01 and < 0.001, respectively). At their estimated cutoff values (≤ 1.2 and ≤ 0.9 × 10–3 mm2/s, respectively), the sensitivity was (71.4 and 85.7%), specificity was (83.3 and 66.7%), respectively, and AUC = 0.77 for both. PET/CT had 96.4% sensitivity, 92.3% specificity, and AUC = 0.94.

Conclusions

PET-CT remains the most specific and sensitive tool for the differentiation between benign and malignant lesions. The lesion-to-cord signal intensity ratios in T2WI and DWI-MRI and to a minor extent the mean and minimum ADC values are also considered good parameters for this differentiation based on their accurate statistical results, particularly if PET/CT was not available or feasible. The study added to the previous literature a novel quantitative T2WI assessment which proved a high sensitivity equal to PET/CT with a lower but a good specificity. The availability, expertise, time factor, and patients' tolerance remain challenging factors for MRI.

Natural progression of persistent pure ground-glass nodules 10 mm or smaller: long-term observation and risk factor assessment

PURPOSE

Semi-automatic segmentation was used to investigate the natural progression of pure ground-glass nodules (pGGNs) of 5-10 mm in long-term follow-up and to analyze independent risk factors for subsequent growth.

MATERIALS AND METHODS

A total of 154 pGGNs of 5-10 mm from 132 patients with 698 follow-up CT scans were retrospectively identified. Subsequently, enrolled pGGNs were semiautomatically segmented on initial and follow-up CT to obtain diameter, density and volume, thus calculating mass, volume doubling time (VDT), and mass doubling time (MDT). Kaplan‒Meier analysis and multivariate Cox proportional risk regression were performed to explore independent predictors of pGGN growth. We analyzed growth differences among different pathological results of pGGNs confirmed by surgery. The prognosis was analyzed using the total diameter or solid size of the nodules on the last preoperative CT.

RESULTS

Among the 85 (55.2%) pGGNs with growth, 5.9%, 51.8%, and 80.0% showed growth within 1, 3, and 5 years, respectively. The median VDT and MDT were 1206.4 (range 349.8-5134.4) days and 1161.3 (range 339.4-6630.4) days, respectively. The multivariate Cox risk regression analysis showed that mean CT attenuation (m-CTA) [hazard ratio (HR) = 2.098, p = 0.010] and roundness index (HR = 1.892, p = 0.021) were independent risk factors for pGGN growth. In total, 67.6% of surgically resected and growing pGGNs were invasive non-mucinous adenocarcinoma (IA), including 2 cases of endpoint events, showing a PSN with solid components of 5.6 mm and a solid nodule with a diameter of 19.9 mm.

CONCLUSIONS

pGGNs of 5-10 mm showed an indolent clinical course. Follow-up CT imaging of pGGNs in the latter half of the first two years should be a rational management strategy. Small pGGNs with a larger overall m-CTA and roundness index on baseline CT are more likely to grow.

Value of preoperative 18F-FDG PET/CT and HRCT in predicting the differentiation degree of lung adenocarcinoma dominated by solid density

Purpose

To evaluate the value of positron emission tomography/computed tomography (PET/CT) combined with high-resolution CT (HRCT) in determining the degree of differentiation of lung adenocarcinoma.

Methods

From January 2018 to January 2022, 88 patients with solid density nodules that are lung adenocarcinoma were surgically treated. All patients were examined using HRCT and PET/CT before surgery. During HRCT, two independent observers assessed the presence of lobulation, spiculation, pleural indentation, vascular convergence, and air bronchial signs (bronchial distortion and bronchial disruption). The diameter and CT value of the nodules were measured simultaneously. During PET/CT, the maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the nodules were measured. The risk factors of pathological classification were predicted by logistic regression analysis.

Results

All 88 patients (mean age 60 ± 8 years; 44 males and 44 females) were evaluated. The average nodule size was 2.6 ± 1.1 cm. The univariate analysis showed that carcinoembryonic antigen (CEA), pleural indentation, vascular convergence, bronchial distortion, and higher SUVmax were more common in poor differentiated lung adenocarcinoma, and in the multivariate analysis, pleural indentation, vascular convergence, and SUVmax were predictive factors. The combined diagnosis using these three factors showed that the area under the curve (AUC) was 0.735.

Conclusion

SUVmax >6.99 combined with HRCT (pleural indentation sign and vascular convergence sign) is helpful to predict the differentiation degree of lung adenocarcinoma dominated by solid density.

Prognostic Factors for Survival in Multiple Primary Lung Adenocarcinomas: A Retrospective Analysis of 283 Patients

Purpose: In recent years, a rising number of multiple primary lung cancers have been detected with the advancement of imaging technology. No detailed study has assessed the prognosis of multiple primary lung adenocarcinomas based on computed tomography characteristics. The present study aimed to analyze outcomes and determine valuable factors for predicting the prognosis of multiple primary lung adenocarcinoma. Methods: This single-center retrospective study was performed from January 2013 to October 2021. All patients were divided into 3 groups based on tumor density as follows: multi-pure ground-glass nodules, at least one part-solid nodule without solid nodules, and at least one solid nodule. Clinicopathologic features, computed tomography signs, and survival outcomes were compared between these groups. The Kaplan-Meier method was used for survival analysis. The multivariable Cox proportional hazards regression model was used to identify independent predictors for recurrence-free survival and overall survival. Results: The sample included 283 patients with 623 lesions who met the inclusion criteria for multiple primary lung adenocarcinoma. Of these patients, 71 (25.1%) presented with multi-pure ground-glass nodules, 100 (35.3%) with at least one part-solid nodule without solid nodule, and 112 (39.6%) with at least one solid nodule. The 3 groups had distinguished clinicopathologic and radiological features of age, adjuvant therapy, types of tumor resection, TNM stage, pathological subtypes, pleural indentation, spicule, and vacuole (all P < .001). Multivariate analysis found that lesion number was an independent predictor for both recurrence-free survival (hazard ratio 2.41; 95% confidence interval 1.12-5.19; P = .025) and overall survival (hazard ratio 4.78; 95% confidence interval 1.88-12.18; P = .001), and the at least one solid nodule was an independent predictor for overall survival (hazard ratio 5.307; 95% confidence interval 1.16-24.31; P = .032). Stage III (hazard ratio 5.71; 95% confidence interval 1.94-16.81; P = .002) and adjuvant therapy (hazard ratio 2.52; 95% confidence interval 1.24-5.13; P = .011) influenced the recurrence-free survival. Conclusions: Survival of multiple primary lung adenocarcinoma patients is strongly correlated with the lesion number and the at least one solid nodule tumors in radiological. This information may be useful for predicting survival and making clinical decisions in future studies.

A Combination of Radiomic Features, Imaging Characteristics, and Serum Tumor Biomarkers to Predict the Possibility of the High-Grade Subtypes of Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Lung adenocarcinomas (LADC) containing high-grade subtypes have a poorer prognosis. And some studies have shown that high-grade subtypes have been identified as an independent predictor of local recurrence in patients treated with limited resection. The aim of this study was to construct a combined model based on radiomic features, imaging characteristics and serum tumor biomarkers to predict the possibility of preoperative high-grade subtypes.

MATERIALS AND METHODS

156 patients with LADC were retrospectively recruited in this study. These patients were randomly divided into training and validation cohorts. Radiomics features and imaging characteristics were extracted from plain CT images. A nomogram was developed in a training cohort by univariate and multivariate logistic analysis, and its performance was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) in the training and validation cohorts.

RESULTS

A total of 1316 radiomic features were extracted from the lesions in plain chest CT images. After applying the mRMR algorithm and the LASSO regression, 4 features were retained. Based on these radiomic features, Radiomic score (Radscore) was calculated for each patient. Spiculation, air bronchogram sign, CYFRA 21-1 and Radscore had been used in the construction of the combined model. The AUC of the combined model was respectively 0.88 (95% CI, 0.82-0.95) and 0.94 (95% CI, 0.86-1.00) in the training and validation cohorts.

CONCLUSION

The combined model based on CT images and serum tumor biomarkers, can predict the high-grade subtypes of LADC in a non-invasive manner, which may influence individual treatment planning, such as the choice of surgical approach and postoperative adjuvant therapy.

Risk of adenocarcinoma in patients with a suspicious ground-glass opacity: a retrospective review

BACKGROUND

Both primary lung adenocarcinoma and benign processes can have a ground-glass opacity (GGO) appearance on imaging. This study evaluated the incidence of and risk factors for malignancy in a diverse cohort of patients who underwent resection of a GGO suspicious for lung cancer.

METHODS

All patients who underwent resection of a pulmonary nodule with a GGO component and suspected to be primary lung cancer at a single institution from 2001-2017 were retrospectively reviewed. Risk factors for malignancy were evaluated using multivariable logistic regression analysis that included nodule size, age, sex, and race as potential predictors.

RESULTS

The incidence of pulmonary adenocarcinoma in the 243 patients who met inclusion criteria was 86% (n=208). The most common pathologic findings in 35 patients with a benign pathology was granulomatous inflammation (n=14, 40%). Risk factors for adenocarcinoma in multivariable logistic regression were age [odds ratio (OR) 1.06, P=0.003], GGO size (OR 2.76, P<0.001), female sex (OR 4.47, P=0.002), and Asian race (OR 8.35, P=0.002). In this cohort, adenocarcinoma was found in 100% (44/44) of Asian females, 86% (25/29) of Asian males, 84% (98/117) of non-Asian females, and 77% (41/53) of non-Asian males.

CONCLUSIONS

The likelihood of adenocarcinoma in lung nodules with a ground-glass component is influenced by sex and race. Asian females with a GGO have a much higher likelihood of having adenocarcinoma than men and non-Asians. This data can be used when deciding whether to pursue nodule resection or surveillance in a patient with a GGO.

Solitary Pulmonary Capillary Hemangioma: CT and PET-CT Features with Clinicopathologic Correlation

The aim of this study was to evaluate the CT and PET-CT features of solitary pulmonary capillary hemangioma (SPCH) with clinicopathologic correlations. This retrospective study included 17 patients with histologically proven SPCH from four tertiary institutions. The clinical, pathological and imaging findings of SPCH were reviewed. The CT features assessed included lesion location, size, density, contour, margin, enhancement, presence of air bronchogram, perivascular lucency and pleural retraction, and 18F-fluorodeoxyglucose uptake on PET-CT. Changes in the size during the follow-up period were also evaluated. Imaging features were correlated with the clinicopathologic findings. The mean age of the patients was 47 years (range 30–60 years). All SPCHs were incidentally detected during screening CT examinations (n = 13, 76%) or during cancer work-up (n = 4, 24%). Most SPCHs appeared as part-solid nodules (n = 15, 88%), the remaining appeared as a pure ground-glass nodule or a pure solid nodule, respectively. Most had smooth contours (n = 16, 94%), while one had a lobulated contour. Nine SPCHs (53%) showed ill-defined margins. Air bronchogram was present in ten (59%) SPCHs, and perivascular lucency in two (12%). All SPCHs exhibited hypoattenuation on contrast-enhanced CT and hypometabolism on PET-CT. During the follow-up period (mean 14.8 ± 17.7 months), the lesions showed no change in size or density in ten SPCHs (59%), decreased or fluctuation in size and density in three (18%). SPCH is often incidentally detected in young and middle-aged adults, commonly as an ill-defined part-solid nodule that may accompany air bronchogram, perivascular lucency, and fluctuation in size or density on CT and hypometabolism on PET-CT.

Combined Radiomic and Visual Assessment for Improved Detection of Lung Adenocarcinoma Invasiveness on Computed Tomography Scans: A Multi-Institutional Study

Objective

The timing and nature of surgical intervention for semisolid abnormalities are dependent upon distinguishing between adenocarcinoma-in-situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (INV). We sought to develop and evaluate a quantitative imaging method to determine invasiveness of small, ground-glass lesions on computed tomography (CT) chest scans.

Methods

The study comprised 268 patients from 4 institutions with resected (<=3 cm) semisolid lesions with confirmed histopathological diagnosis of MIA/AIS or INV. A total of 248 radiomic texture features from within the tumor nodule (intratumoral) and adjacent to the nodule (peritumoral) were extracted from manually annotated lung nodules of chest CT scans. The datasets were randomly divided, with 40% of patients used for training and 60% used for testing the machine classifier (Training D_Train, N=106; Testing, D_Test, N=162).

Results

The top five radiomic stable features included four intratumoral (Laws and Haralick feature families) and one peritumoral feature within 3 to 6 mm of the nodule (CoLlAGe feature family), which successfully differentiated INV from MIA/AIS nodules with an AUC of 0.917 [0.867-0.967] on D_Train and 0.863 [0.79-0.931] on D_Test. The radiomics model successfully differentiated INV from MIA cases (<1 cm AUC: 0.76 [0.53-0.98], 1-2 cm AUC: 0.92 [0.85-0.98], 2-3 cm AUC: 0.95 [0.88-1]). The final integrated model combining the classifier with the radiologists’ score gave the best AUC on D_Test (AUC=0.909, p<0.001).

Conclusions

Addition of advanced image analysis via radiomics to the routine visual assessment of CT scans help better differentiate adenocarcinoma subtypes and can aid in clinical decision making. Further prospective validation in this direction is warranted.

Recurrence dynamics after curative surgery in patients with invasive mucinous adenocarcinoma of the lung

Background

We investigated the patterns and timing of recurrence and death as well as prognostic factors based on clinicopathological and radiological factors in patients who underwent surgical treatment for invasive mucinous adenocarcinoma (IMA).

Methods

We reviewed clinicopathological findings including spread through air spaces (STAS) and CT findings of IMA such as morphology, solidity, margin, well-defined heterogeneous ground-glass opacity, CT angiogram, and air bronchogram signs from 121 consecutive patients who underwent surgical resection. Prognostic factors for disease-free survival (DFS) and overall survival (OS) were identified. Hazard rate analyses were performed for the survival dynamics.

Results

T stage (hazard ratio [HR] = 4.102, p = 0.03), N stage (N2 vs. N0, HR = 7.653, p < 0.001), and consolidative CT morphology (HR = 3.556, p = 0.008) remained independent predictors for DFS. Age (HR = 1.110, p = 0.002), smoking (HR = 12.893, p < 0.001), T stage (HR = 13.005, p = 0.006), N stage (N2 vs. N0, HR = 7.653, p = 0.004), STAS (HR = 7.463, p = 0.008), and consolidative CT morphology (HR = 6.779, p = 0.007) remained independent predictors for OS. Consolidative morphology, higher T and N stage, and presence of STAS revealed initial sharp peaks after steep decline of the hazard rate curves for recurrence or death in follow-up period.

Conclusions

Consolidative morphology, higher T and N stage, smoking, and STAS were indicators of significantly greater risk of early recurrence or death in patients with IMA. Thus, these findings could be incorporated into future surveillance strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01208-5.

Prognosis for Pneumonic-Type Invasive Mucinous Adenocarcinoma in a Single Lobe on CT: Is It Reasonable to Designate It as Clinical T3?

Objective

To compare pneumonic-type invasive mucinous adenocarcinoma (pIMA) confined to a single lobe with clinical T2, T3, and T4 stage lung cancer without pathological node metastasis regarding survival after curative surgery and to identify prognostic factors for pIMA.

Materials and Methods

From January 2010 to December 2017, 41 patients (15 male; mean age ± standard deviation, 66.0 ± 9.9 years) who had pIMA confined to a single lobe on computed tomography (CT) and underwent curative surgery were identified in two tertiary hospitals. Three hundred and thirteen patients (222 male; 66.3 ± 9.4 years) who had non-small cell lung cancer (NSCLC) without pathological node metastasis and underwent curative surgery in one participating institution formed a reference group. Relapse-free survival (RFS) and overall survival (OS) were calculated using the Kaplan–Meier method. Cox proportional hazard regression analysis was performed to identify factors associated with the survival of patients with pIMA.

Results

The 5-year RFS and OS rates in patients with pIMA were 33.1% and 56.0%, respectively, compared with 74.3% and 91%, 64.3% and 71.8%, and 46.9% and 49.5% for patients with clinical stage T2, T3, and T4 NSCLC in the reference group, respectively. The RFS of patients with pIMA was comparable to that of patients with clinical stage T4 NSCLC and significantly worse than that of patients with clinical stage T3 NSCLC (p = 0.012). The differences in OS between patients with pIMA and those with clinical stage T3 or T4 NSCLC were not significant (p = 0.11 and p = 0.37, respectively). In patients with pIMA, the presence of separate nodules was a significant factor associated with poor RFS and OS {unadjusted hazard ratio (HR), 4.66 (95% confidence interval [CI], 1.95–11.11), p < 0.001 for RFS; adjusted HR, 4.53 (95% CI, 1.59–12.89), p = 0.005 for OS}.

Conclusion

The RFS of patients with pIMA was comparable to that of patients with clinical stage T4 lung cancer. Separate nodules on CT were associated with poor RFS and OS in patients with pIMA.

COVID-19 Pneumonia and Lung Cancer: A Challenge for the Radiological Review of the Main Radiological Features, Differential Diagnosis and Overlapping Pathologies

The COVID-19 pneumonia pandemic represents the most severe health emergency of the 21st century and has been monopolizing health systems’ economic and human resources world-wide. Cancer patients have been suffering from the health systems’ COVID-19 priority management with evidence of late diagnosis leading to patients’ poor prognosis and late medical treatment. The radiologist plays a pivotal role as CT represents a non-invasive radiological technique which may help to identify possible overlap and differential diagnosis between COVID-19 pneumonia and lung cancer, which represents the most frequent cancer histology in COVID-19 patients. Our aims are: to present the main CT features of COVID-19 pneumonia; to provide the main differential diagnosis with lung cancer, chemotherapy-, immunotherapy-, and radiotherapy-induced lung disease; and to suggest practical tips and key radiological elements to identify possible overlap between COVID-19 pneumonia and lung cancer. Despite similarities or overlapping findings, the combination of clinics and some specific radiological findings, which are also identified by comparison with previous and follow-up CT scans, may guide differential diagnosis. It is crucial to search for typical COVID-19 pneumonia phase progression and typical radiological features on HRTC. The evidence of atypical findings such as lymphadenopathies and mediastinal and vessel invasion, as well as the absence of response to therapy, should arouse the suspicion of lung cancer and require contrast administration. Ground-glass areas and/or consolidations bound to radiotherapy fields or pneumonitis arising during and after oncological therapy should always arouse the suspicion of radiation-induced lung disease and chemo/immunotherapy-induced lung disease. The radiological elements we suggest for COVID-19 and lung cancer differential diagnosis may be used to develop AI protocols to guarantee an early and proper diagnosis and treatment to improve patients’ quality of life and life expectancy.

A case of haemoptysis and bilateral areas of lung consolidation sparing the right lower lobe

Multiple primary lung cancers (MPLC) are often neglected. Obtaining pre-operative specimens through bronchoscopy could play a role. It is important to distinguish aerogenous metastasis from MPLC in the adenocarcinoma spectrum due to the different prognosis.https://bit.ly/3zbdVrw

Updates in grading and invasion assessment in lung adenocarcinoma

The pathologic evaluation of lung adenocarcinoma, because of greater understanding of disease progression and prognosis, has become more complex. It is clear that histologic growth patterns reflect indolent and aggressive disease, resulting in clearer morphologic groups that can be the underpinning of a grading system. In addition, the progression of adenocarcinoma from a tumor that preserves alveolar architecture to one that remodels and effaces lung structure has led to criteria that reflect invasive rather than in-situ growth. While some of these are based on tumor cell growth pattern, aspects of this remodeling from desmoplasia to artifacts of lung collapse and sectioning, can lead to difficult to interpret patterns with lower reproducibility between observers. Such scenarios are examined to provide updates on new histologic concepts and to highlight ongoing problem areas.

Absence of clinical benefit of FDG PET-CT in staging T1 part-solid lung adenocarcinoma

AIM

To assess the rates of nodal and metastatic disease and change in management when staging part-solid T1 lung adenocarcinomas using integrated 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)-computed tomography (CT) in a UK population.

MATERIALS AND METHODS

This was a retrospective review of PET-CT examinations performed to stage radiologically suspected T1 part-solid lung adenocarcinoma (n=58) from two different centres. Rates of detection of nodal and metastatic disease, change in management, and final patient outcome were recorded.

RESULTS

PET-CT changed the stage in one patient from N0 to N1. It did not change final management in any patient.

CONCLUSIONS

In this UK population, PET-CT had minimal additional diagnostic benefit in staging patients with T1 part-solid lung adenocarcinoma. Especially given its cost, the inclusion of PET-CT for this indication in guidelines should be reviewed.

Is the combination of bilateral pulmonary nodules and mosaic attenuation on chest CT specific for DIPNECH?

Background

Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH) is characterized by multifocal proliferation of pulmonary neuroendocrine cells. On chest CT, DIPNECH exhibits bilateral pulmonary nodules and mosaic attenuation in most patients. We sought to: (1) assess the specificity of this pattern (i.e., bilateral pulmonary nodules together with mosaic attenuation) for DIPNECH; (2) describe its differential diagnosis; and (3) identify the clinico-radiologic features that may help prioritize DIPNECH over other diagnostic considerations.

Methods

We searched the Mayo Clinic records from 2015 to 2019 for patients with bilateral pulmonary nodules and mosaic attenuation on CT who had a diagnostic lung biopsy. A thoracic radiologist reviewed all CT scans. Chi-square test was used for categorical variables, and odds ratios were utilized to measure the association between certain variables and DIPNECH.

Results

Fifty-one patients met our inclusion criteria; 40 (78%) were females and 34 (67%) were never-smokers. Median age was 65 (interquartile range 55–73) years. Lung biopsy was surgical in 21 patients (41%), transbronchial in 17 (33%), and transthoracic in 12 (24%); explanted lungs were examined in 1 (2%). Metastatic/multifocal cancer was the most common diagnosis, and was found in 17 (33%) cases. Bronchiolitis was diagnosed in 12 patients (24%), interstitial lung disease in 10 (20%), and DIPNECH in 5 (10%). Previous diagnosis of an obstructive lung disease (odds ratio 15.8; P = 0.002), and peribronchial nodular distribution on CT (odds ratio 14.4; P = 0.006) were significantly correlated with DIPNECH. Although statistical significance was not reached, DIPNECH nodules were more likely to display solid attenuations (80% vs. 67%, P = 0.45), and were more numerous; > 10 nodules were seen in 80% of DIPNECH cases vs. 52% in others (P = 0.23). Because DIPNECH primarily affects women, we analyzed the women-only cohort and found similar results.

Conclusions

Various disorders can manifest the CT pattern of bilateral pulmonary nodules together with mosaic attenuation, and this combination is nonspecific for DIPNECH, which was found in only 10% of our cohort. Previous diagnosis of an obstructive lung disease, and peribronchial distribution of the nodules on CT increased the likelihood of DIPNECH vs. other diagnoses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-02103-w.

Cystic Primary Lung Cancer: Evolution of Computed Tomography Imaging Morphology Over Time

PURPOSE

Primary lung cancers associated with cystic airspaces are increasingly being recognized; however, there is a paucity of data on their natural history. We aimed to evaluate the prevalence, pathologic, and imaging characteristics of cystic lung cancer in a regional thoracic surgery center with a focus on the evolution of computed tomography morphology over time.

MATERIALS AND METHODS

Consecutive patients referred for potential surgical management of primary lung cancer between January 2016 and December 2018 were included. Clinical, imaging, and pathologic data were collected at the time of diagnosis and at the time of the oldest computed tomography showing the target lesion. Descriptive analysis was carried out.

RESULTS

A total of 441 cancers in 431 patients (185 males, 246 females), median age 69.6 years (interquartile range: 62.6 to 75.3 y), were assessed. Overall, 41/441 (9.3%) primary lung cancers were cystic at the time of diagnosis. The remaining showed solid (67%), part-solid (22%), and ground-glass (2%) morphologies. Histopathology of the cystic lung cancers at diagnosis included 31/41 (76%) adenocarcinomas, 8/41 (20%) squamous cell carcinomas, 1/41 (2%) adenosquamous carcinoma, and 1/41 (2%) unspecified non-small cell lung carcinoma. Overall, 8/34 (24%) cystic cancers at the time of diagnosis developed from different morphologic subtype precursor lesions, while 8/34 (24%) cystic precursor lesions also transitioned into part-solid or solid cancers at the time of diagnosis.

CONCLUSIONS

This study demonstrates that cystic airspaces within lung cancers are not uncommon, and may be seen transiently as cancers evolve. Increased awareness of the spectrum of cystic lung cancer morphology is important to improve diagnostic accuracy and lung cancer management.

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.

Radiomics is feasible for prediction of spread through air spaces in patients with nonsmall cell lung cancer

Tumor spread through air spaces (STAS) in non-small-cell lung cancer (NSCLC) is known to influence a poor patient outcome, even in patients presenting with early-stage disease. However, the pre-operative diagnosis of STAS remains challenging. With the progress of radiomics-based analyses several attempts have been made to predict STAS based on radiological findings. In the present study, patients with NSCLC which is located peripherally and tumors ≤ 2 cm in size on computed tomography (CT) that were potential candidates for sublobar resection were enrolled in this study. The radiologic features of the targeted tumors on thin-section CT were extracted using the PyRadiomics v3.0 software package, and a predictive model for STAS was built using the t-test and XGBoost. Thirty-five out of 226 patients had a STAS histology. The predictive model of STAS indicated an area under the receiver-operator characteristic curve (AUC) of 0.77. There was no significant difference in the overall survival (OS) for lobectomy between the predicted-STAS (+) and (−) groups (p = 0.19), but an unfavorable OS for sublobar resection was indicated in the predicted-STAS (+) group (p < 0.01). These results suggest that radiomics with machine-learning helped to develop a favorable model of STAS (+) NSCLC, which might be useful for the proper selection of candidates who should undergo sublobar resection.

Deep learning classification of lung cancer histology using CT images

Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical image analysis allude to the utility of radiologic data in further describing disease characteristics and for risk stratification. In this study, we propose a radiomics approach to predicting non-small cell lung cancer (NSCLC) tumor histology from non-invasive standard-of-care computed tomography (CT) data. We trained and validated convolutional neural networks (CNNs) on a dataset comprising 311 early-stage NSCLC patients receiving surgical treatment at Massachusetts General Hospital (MGH), with a focus on the two most common histological types: adenocarcinoma (ADC) and Squamous Cell Carcinoma (SCC). The CNNs were able to predict tumor histology with an AUC of 0.71(p = 0.018). We also found that using machine learning classifiers such as k-nearest neighbors (kNN) and support vector machine (SVM) on CNN-derived quantitative radiomics features yielded comparable discriminative performance, with AUC of up to 0.71 (p = 0.017). Our best performing CNN functioned as a robust probabilistic classifier in heterogeneous test sets, with qualitatively interpretable visual explanations to its predictions. Deep learning based radiomics can identify histological phenotypes in lung cancer. It has the potential to augment existing approaches and serve as a corrective aid for diagnosticians.

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.

Tumor cell proliferation (Ki-67) expression and its prognostic significance in histological subtypes of lung adenocarcinoma

OBJECTIVES

Ki-67 is a key molecular marker to indicate the proliferative activity of tumor cells in lung cancer. However, Ki-67 expression and its prognostic significance in histological subtypes of lung adenocarcinoma (LUAD) remain unclear.

MATERIALS AND METHODS

We retrospectively analyzed 1028 invasive LUAD patients who underwent surgery treatment between January 2012 and April 2020 in our department. Associations between Ki-67 expression and histological subtypes of LUAD, as well as other clinicopathological characteristics, were evaluated. The prognostic role of Ki-67 in LUAD subtypes was further assessed using log-rank test and univariate/multivariate Cox proportional hazards regression analyses.

RESULTS

Ki-67 expression differed across LUAD histological subtypes. The solid-predominant adenocarcinoma (SPA, 46.31 ± 24.72) had the highest expression level of Ki-67, followed by micropapillary (MPA, 31.71 ± 18.14), papillary (PPA, 22.09 ± 19.61), acinar (APA, 19.73 ± 18.71) and lepidic-predominant adenocarcinoma (LPA, 9.86 ± 8.10, P <  0.001). Tumors with solid or micropapillary components also had a higher Ki-67 expression than those without solid or micropapillary components. Besides, males, smokers, larger tumor size, lymph node metastasis and EGFR wild type were correlated with elevated Ki-67 expression. Univariate analysis indicated that increased Ki-67 expression and MPA/SPA subtypes were significantly associated with a poorer prognosis. Notably, the survival differences between LUAD subtypes vanished after adjusting for tumor size and Ki-67 expression in multivariate analysis, while Ki-67 was an independent prognostic factor of LUAD. Patients with MPA/SPA had non-inferior overall and disease-free survival than LPA/APA/PPA patients with a Ki-67 expression comparable to MPA/SPA subjects.

CONCLUSION

Ki-67 expression varied considerably according to the predominant histological subtypes of LUAD. Ki-67 expression level and tumor size contributed to the survival differences between LUAD histological subtypes.

A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules

This study aims to predict the histological invasiveness of pulmonary adenocarcinoma spectrum manifesting with subsolid nodules ≦ 3 cm using the preoperative CT-based radiomic approach. A total of 186 patients with 203 SSNs confirmed with surgically pathologic proof were retrospectively reviewed from February 2016 to March 2020 for training cohort modeling. The validation cohort included 50 subjects with 57 SSNs confirmed with surgically pathologic proof from April 2020 to August 2020. CT-based radiomic features were extracted using an open-source software with 3D nodular volume segmentation manually. The association between CT-based conventional features/selected radiomic features and histological invasiveness of pulmonary adenocarcinoma status were analyzed. Diagnostic models were built using conventional CT features, selected radiomic CT features and experienced radiologists. In addition, we compared diagnostic performance between radiomic CT feature, conventional CT features and experienced radiologists. In the training cohort of 203 SSNs, there were 106 invasive lesions and 97 pre-invasive lesions. Logistic analysis identified that a selected radiomic feature named GLCM_Entropy_log10 was the predictor for histological invasiveness of pulmonary adenocarcinoma spectrum (OR: 38.081, 95% CI 2.735–530.309, p = 0.007). The sensitivity and specificity for predicting histological invasiveness of pulmonary adenocarcinoma spectrum using the cutoff value of CT-based radiomic parameter (GLCM_Entropy_log10) were 84.8% and 79.2% respectively (area under curve, 0.878). The diagnostic model of CT-based radiomic feature was compared to those of conventional CT feature (morphologic and quantitative) and three experienced radiologists. The diagnostic performance of radiomic feature was similar to those of the quantitative CT feature (nodular size and solid component, both lung and mediastinal window) in prediction invasive pulmonary adenocarcinoma (IPA). The AUC value of CT radiomic feature was higher than those of conventional CT morphologic feature and three experienced radiologists. The c-statistic of the training cohort model was 0.878 (95% CI 0.831–0.925) and 0.923 (0.854–0.991) in the validation cohort. Calibration was good in both cohorts. The diagnostic performance of CT-based radiomic feature is not inferior to solid component (lung and mediastinal window) and nodular size for predicting invasiveness. CT-based radiomic feature and nomogram could help to differentiate IPA lesions from preinvasive lesions in the both independent training and validation cohorts. The nomogram may help clinicians with decision making in the management of subsolid nodules.

Adenocarcinoma of the lung with concurrent Mycobacterium avium complex infection

Nontuberculous mycobacterial infection, particularly Mycobacterium avium complex (MAC), which is also known as Lady Windermere syndrome usually presents with chronic cough, typically seen in elderly caucasian women who chronically suppress the normal cough reflex. Computerized tomography of the chest in patients with MAC infection can present as a tree in bud nodules, pulmonary nodules, cavity, or consolidation. However, other coexisting diseases such as lung cancer should be kept in mind while investigating these radiographic changes in patients with suspected MAC infection, more so if they have underlying risk factors for malignancy. We present a patient with suspected MAC infection who had co-existing lung adenocarcinoma.

The Effect of Lung Volume on the Size and Volume of Pulmonary Subsolid Nodules on CT: Intraindividual Comparison between Total Lung Capacity and Tidal Volume

Purpose

Materials and Methods

Results

Conclusion

2020 Clinical Practice Guideline for Percutaneous Transthoracic Needle Biopsy of Pulmonary Lesions: A Consensus Statement and Recommendations of the Korean Society of Thoracic Radiology

Percutaneous transthoracic needle biopsy (PTNB) is one of the essential diagnostic procedures for pulmonary lesions. Its role is increasing in the era of CT screening for lung cancer and precision medicine. The Korean Society of Thoracic Radiology developed the first evidence-based clinical guideline for PTNB in Korea by adapting pre-existing guidelines. The guideline provides 39 recommendations for the following four main domains of 12 key questions: the indications for PTNB, pre-procedural evaluation, procedural technique of PTNB and its accuracy, and management of post-biopsy complications. We hope that these recommendations can improve the diagnostic accuracy and safety of PTNB in clinical practice and promote standardization of the procedure nationwide.

Primary Invasive Mucinous Adenocarcinoma of the Lung: Prognostic Value of CT Imaging Features Combined with Clinical Factors

Objective

To investigate the association between CT imaging features and survival outcomes in patients with primary invasive mucinous adenocarcinoma (IMA).

Materials and Methods

Preoperative CT image findings were consecutively evaluated in 317 patients with resected IMA from January 2011 to December 2015. The association between CT features and long-term survival were assessed by univariate analysis. The independent prognostic factors were identified by the multivariate Cox regression analyses. The survival comparison of IMA patients was investigated using the Kaplan-Meier method and propensity scores. Furthermore, the prognostic impact of CT features was assessed based on different imaging subtypes, and the results were adjusted using the Bonferroni method.

Results

The median follow-up time was 52.8 months; the 5-year disease-free survival (DFS) and overall survival rates of resected IMAs were 68.5% and 77.6%, respectively. The univariate analyses of all IMA patients demonstrated that 15 CT imaging features, in addition to the clinicopathologic characteristics, significantly correlated with the recurrence or death of IMA patients. The multivariable analysis revealed that five of them, including imaging subtype (p = 0.002), spiculation (p < 0.001), tumor density (p = 0.008), air bronchogram (p < 0.001), emphysema (p < 0.001), and location (p = 0.029) were independent prognostic factors. The subgroup analysis demonstrated that pneumonic-type IMA had a significantly worse prognosis than solitary-type IMA. Moreover, for solitary-type IMAs, the most independent CT imaging biomarkers were air bronchogram and emphysema with an adjusted p value less than 0.05; for pneumonic-type IMA, the tumors with mixed consolidation and ground-glass opacity were associated with a longer DFS (adjusted p = 0.012).

Conclusion

CT imaging features characteristic of IMA may provide prognostic information and individual risk assessment in addition to the recognized clinical predictors.

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.

[Progress in Survival Prognosis of Segmentectomy for Early-stage Non-small Cell Lung Cancer]

Surgery is currently the most appropriate treatment for early-stage non-small cell lung cancer (NSCLC). Increasing unilateral or bilateral multiple primary lung cancer being found, segmentectomy has attracted wide attention for its unique advantages in the treatment for such tumors. Ground glass opacity dominant early-stage NSCLC is associated with a good prognosis and can be cured by segmentectomy, however, the treatment of solid-dominant NSCLC remains controversial owing to the invasive nature. With the in-depth study on the lymph node metastasis pathway, radiological characteristics and molecular biology of NSCLC, a large part of solid nodules with certain characteristics can also be cured by segmentectomy. This paper reviews the research status and progress about the indication of segmentectomy.
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An Unusual Presentation of Aggressive Primary Invasive Adenocarcinoma of Lung

Bilateral diffuse infiltrates on chest imaging can present a diagnostic challenge due to a broader differential diagnosis which includes pulmonary and non-pulmonary causes. Malignancy is generally not considered under differential diagnosis at the time of initial presentation. Here we present a case of primary adenocarcinoma of lung manifesting as diffuse bilateral infiltrates on imaging. Our case is unique in regards to its acute presentation, rapid progression to respiratory failure, ultimately leading to the demise of the patient. This indicates the aggressive nature of this malignancy and its variable presentation, like male gender and young age, thus emphasizing the importance of entertaining malignancy in such presentations, especially if there is no response to conventional antibiotic therapy.

Role of CT in differentiation between subtypes of lung cancer; is it possible?

Background

Context and purpose: lung cancer is the second in the incidence rate and the first in death rate in the United States of America in 2017. Its treatment depends upon the tumor staging as well as the histological subtype of lung cancer. CT has been the modality of choice for screening as well as diagnosis of lung cancer; however, few studies tried to correlate different CT features of lung cancer to certain pathological subtypes. Our study aims to assess the CT characteristics of the subtypes of bronchogenic carcinoma.

Results

SQCC shows a higher incidence of central location compared with the rest of the lung cancers (significance level of 50%, p value of 0.5), internal cavitations (significance level of 94.9%, p value of less than 0.05) as well as more frequency of higher stage within the study population, ADC shows significant predilection to peripheral location compared with the rest of the lung cancers (significance level of 94.9%, p value of less than 0.05).

Conclusion

There is an evident correlation between the MDCT diagnosis of bronchogenic carcinoma and that of histopathology/cytology. The most common types are SQCC and ADC subtypes. The SQCC type of bronchial carcinoma tends to be central with the internal cavitations are common while ADC tends to be peripheral and solid.

Advanced pneumonic type of lung adenocarcinoma: survival predictors and treatment efficacy of the tumor

PURPOSE

To retrospectively explore the survival predictors and treatment efficacy of advanced pneumonic-type lung adenocarcinoma (P-ADC).

METHODS

Retrospective analysis of clinical data and survival follow-up was undertaken on 41 patients with advanced P-ADC from January 1, 2009, to April 30, 2019. Analysis on tumor biomarkers such as carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and the cytokeratin-19-fragment (Cyfra21-1) were undertaken. The patients in this study were divided into three groups based on usage of tyrosine kinase inhibitor (TKI): TKI therapy group (including combination with chemotherapy), non-TKI therapy group (chemotherapy alone), and palliative care group.

RESULTS

More than half of the patients had higher levels of tumor biomarkers and the incidence of NSE was highest (81.8%), followed by CEA (74.4%) and Cyfra21-1 (74.1%). All patients had abnormal findings on chest computed tomography and with adenocarcinoma pathology. The overall survival (OS) time was 10.4 months in TKI group, 8.8 months in the non-TKI group, and 2.1 months in the palliative care group. Patients with higher level of serum Cyfra21-1 had insignificantly shorter survival time compared to those with normal Cyfra21-1 (p = 0.067). TKI therapy and non-TKI therapy provided a better prognosis prediction compared to palliative care. TKI therapy improved prognosis compared to non-TKI therapy. The comprehensive based TKI therapy provided improved OS vs the non-TKI therapy.

CONCLUSION

TKI-based therapy could improve the prognosis and OS for advanced P-ADC. This study recommends the analysis of EGFR mutations for all patients with advanced P-ADC.

Identification of benign and malignant pulmonary nodules on chest CT using improved 3D U-Net deep learning framework

PURPOSE

To accurately distinguish benign from malignant pulmonary nodules with CT based on partial structures of 3D U-Net integrated with Capsule Networks (CapNets) and provide a reference for the early diagnosis of lung cancer.

METHOD

The dataset consisted of 1177 samples (benign/malignant: 414/763) from 997 patients provided by collaborating hospital. All nodules were biopsy or surgery proven, and pathologic results were regarded as the "golden standard". This study utilized partial U-Net to capture the low-level (edge, corner, etc.) information and CapNets to preserve high-level (semantic information) information of nodules. For CapNets, each capsule had a 4 × 4 matrix representing the pose and an activation probability representing the presence of an object. Furthermore, we chose accuracy (ACC), area under the curve (AUC), sensitivity (SE) and specificity (SP) to evaluate the generalization of the proposed architecture and compared its identification performance with 3D U-Net and experienced radiologists.

RESULTS

The AUC of our architecture (0.84) was superior to that (0.81) of the original 3D U-Net (p = 0.04, DeLong's test). Moreover, ACC (84.5 %) and SE (92.9 %) of our model were clearly higher than radiologists' ACC (81.0 %) and SE (84.3 %) at the optimal operating point. However, SP (70 %) of our model was slightly lower than radiologists' SP (75 %), which might be the result of class imbalance with limited benign samples involved for algorithm training.

CONCLUSIONS

Our architecture showed a high performance for identifying benign and malignant pulmonary nodules, indicating the improved model has a promising application in clinic.

The growth feature and its diagnostic value for benign and malignant pulmonary nodules met in routine clinical practice

Background

Growth rate is an independent risk factor for lung cancer in screened pulmonary nodules. This study aimed to clarify growth characteristics of pulmonary nodules in routine clinical practice and examine whether volume doubling time (VDT) can predict the malignancy of these nodules.

Methods

We retrospectively enrolled patients with 5-30-mm-sized pulmonary nodules that had been surgically resected after a follow-up of at least 3 months. Two follow-up computed tomography (CT) images with similar thickness and long interval were obtained. Then, three-dimensional (3D) manual segmentation for all nodules was performed on two follow-up CT scans. Subsequently, VDT was calculated for nodules with a change in volume of at least 25%.

Results

Overall, 305 pulmonary nodules in 305 patients (men, 36.7%; median age, 57) were included. The mean increased diameter, mass, and volume of benign (n=86) and malignant (n=219) nodules were 0.09 vs. 2.37 mm, 0.10 vs. 0.66 g, and 32.74 vs. 1,871.28 mm3, respectively (P<0.05). In total, 24 of 86 benign nodules (28%, 18 grew and 6 shrank) and 121 of 219 malignant nodules (55%, 114 grew and 7 shrank) changed over time. The median VDTs of growing benign and malignant nodules were 389 and 526 days, respectively, (P=0.18), and the area under the receiver operating characteristic (ROC) curve was 0.67 (0.55-0.78), with a sensitivity and specificity of 69% and 58%, respectively. The median VDT for growing nodules was 339 days for inflammatory pseudotumors, 226 days for granulomas, 640 days for benign tumors, 1,541 days for enlarged lymph nodes, 762 days for adenocarcinoma in situ, 954 days for microinvasive adenocarcinoma, 534 days for invasive adenocarcinoma, and 118 days for squamous cell carcinoma.

Conclusions

In routine clinical practice, many malignant nodules could grow slowly or even remain stable over time. Regarding growing nodules, the diagnostic value of VDT was limited.

Two nomograms based on CT features to predict tumor invasiveness of pulmonary adenocarcinoma and growth in pure GGN: a retrospective analysis

PURPOSE

The aim of the study is to construct two nomograms for predicting the invasive extent of pulmonary adenocarcinoma and nodule growth in patients with pulmonary pure ground-glass nodules (pGGN).

METHOD

Consecutive patients with pGGNs (n = 172) were retrospectively studied at one institution, formed the development cohort in predicting IPAs' nomogram. A separate cohort of patients with pGGNs (n = 116) from another institution was used for validation. For the predicting growth nomogram, the primary cohort of patients with pGGNs (n = 80) was from the former institution. We developed the nomogram for predicting IPA using binary logistic regression model, and a Cox multivariable model for the growth nomogram. We assessed nomogram model performance by calibration and discrimination (C-index).

RESULTS

The variables selected in binary logistic regression model (lesion size and shape) had a significant effect on identifying IPA from preinvasive lesion. The C-index of the development and validation cohort were 0.819 (95% CI 0.753-0.874) and 0.811 (95% CI 0.728-0.878), respectively. The risk variables (lesion size, blood vessel types) were selected in the multivariable Cox model. The C-index was 0.880 in the development cohort.

CONCLUSION

Our nomograms are reliable prognostic methods that can predict the invasiveness of pulmonary adenocarcinomas and the growth of pure GGN in preoperative.

Chronic airspace disease: Review of the causes and key computed tomography findings

Chronic airspace diseases are commonly encountered by chest, body or general radiologists in everyday practice. Even though there is significant overlap in the imaging findings of different causes of chronic airspace disease, some key clinical, laboratory and imaging findings can be used to guide the radiologist to the correct diagnosis. The goal of this article is to review and compare these features.

Prognostic impact of solid-part tumour volume doubling time in patients with radiological part-solid or solid lung cancer

OBJECTIVES

The measurement of part-solid and whole tumour sizes in patients with non-small-cell lung cancer (NSCLC) using computed tomography (CT) has been widely accepted for assessing clinical outcomes. Although the volume doubling time (VDT) of a tumour is useful for distinguishing high-risk nodules from low-risk ones, it remains to be clarified whether separate calculation of whole-tumour VDT and solid-part tumour VDT (SVDT) greatly affects the survival rate of patients with radiologically node-negative part-solid or solid NSCLC.

METHODS

The study included 258 patients with NSCLC who had radiologically node-negative, part-solid or solid tumours and who had at least 2 preoperative CT scans taken more than 30 days apart followed by radical lobectomy and systemic lymph node dissection between January 2012 and December 2015. Univariable and multivariable analyses of recurrence-free survival were performed using the Cox proportional hazards regression model.

RESULTS

The mean whole-tumour VDT and SVDT were 375 and 458 days, respectively. Multivariable analyses demonstrated that whole-tumour VDT (P = 0.003), SVDT (P < 0.001), solid-part tumour size, whole-tumour size and comorbidities significantly affected the recurrence-free survival. Using the receiver operating characteristic curve, the cut-off value of the SVDT for recurrence was 215 days, and the 5-year recurrence-free survival rates for patients with SVDT >215 days and those with SVDT <215 days were 85.7% and 43.0%, respectively (P < 0.001).

CONCLUSION

The calculation of SVDT in patients with node-negative, part-solid or solid NSCLC is highly useful for predicting postoperative survival outcomes.

Value of TSCT Features for Differentiating Preinvasive and Minimally Invasive Adenocarcinoma From Invasive Adenocarcinoma Presenting as Subsolid Nodules Smaller Than 3 cm

BACKGROUND

To distinguish preinvasive (adenocarcinoma in situ/atypical adenomatous hyperplasia) and minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma (IA) appearing as solitary subsolid nodules (SSNs) less than 3 cm based on thin-section computed tomography (TSCT) features to guide therapeutic approaches.

METHODS

A total of 154 lesions that were histopathologically confirmed to have pre/minimally invasive adenocarcinoma (hereafter pre/MIA) and IA presenting as part-solid nodules (PSNs) or pure ground-glass nodules (pGGNs) were retrospectively reviewed. The TSCT features, including diameter, area, CT value, shape, air bronchogram, margins, and location, were compared and assessed. Receiver operating characteristic analyses were conducted to determine the cut-off values for the qualitative variables and their diagnostic performances.

RESULTS

Of 154 nodules, 89 IA, 53 MIA, eight adenocarcinoma in situ, and four atypical adenomatous hyperplasia lesions were found. Univariate and multivariate logistic regression of the pre/MIA and IA lesions were compared and analyzed among PSNs and pGGNs. Among pGGNs, a significant difference was found in the area (p = 0.004, odds ratio [OR] = 0.124, 95% confidence interval [CI] = 0.300-0.515) between the pre/MIA and IA groups. In PSNs, significant differences were found in the diameter (p = 0.001, OR = 0.171, 95% CI = 0.063-0.467) and CT value (p = 0.001, OR = 0.996, 95% CI = 0.993-0.998) between the pre/MIA and IA groups. According to the corresponding receiver operating characteristic curves, the optimal cut-off tumor area in pGGNs to differentiate pre/MIA from IA was 0.595 cm². A higher CT value of the lesion (≥ -298.500 HU) and a larger diameter (≥1.450 cm) in PSNs were significantly associated with IA.

CONCLUSION

Imaging features from TSCT contribute to distinguishing pre/MIA from IA in solitary subsolid nodules and may contribute to guide the clinical management of these lesions.