Subsolid Nodules Research Articles

Application of 18 F-fluorodeoxyglucose PET/computed tomography in the diagnosis of infiltrative subsolid nodules in lung adenocarcinoma.

To investigate the diagnostic value of 18 F-fluorodeoxyglucose(FDG) PET/computed tomography (CT) for infiltrative subsolid nodules at different stages of lung adenocarcinoma and to explore predictive factors for invasive adenocarcinoma, providing compelling evidence for timely intervention. A retrospective analysis was conducted on PET/CT imaging data of 170 subsolid nodules lesions confirmed postoperatively as lung adenocarcinoma or precursor glandular lesions. Lesions were categorized into preinvasive lesions including atypical adenomatous hyperplasia and adenocarcinoma in situ, microinvasive adenocarcinoma, and invasive adenocarcinoma. Compared the differences in imaging features and metabolic parameters among different groups and used a multifactor logistic regression model and receiver operating characteristic curve analysis to identify predictive factors for invasive adenocarcinoma. From preinvasive lesions through microinvasive adenocarcinoma to invasive adenocarcinoma, there was a gradual increase in nodule diameter, nodule area, and proportion of part-solid nodule. Statistical significance ( P < 0.05) was observed in the rates of spiculation and pleural indentation between preinvasive lesions versus microinvasive adenocarcinoma and invasive adenocarcinoma groups. The maximum standardized uptake value and maximum standardized uptake ratio show statistically significant differences ( P < 0.05) between the invasive adenocarcinoma group and the other groups. Logistic regression analysis indicated that nodule composition, nodule diameter, and maximum standardized uptake ratio were predictive factors for invasive adenocarcinoma ( P < 0.05). For part-solid nodules, the longest diameter of the solid component has a high diagnostic value. The imaging features of 18 F-FDG PET/CT contribute to the diagnosis of infiltrative subsolid nodules at different stages of lung adenocarcinoma, providing robust evidence for timely intervention.

Unlocking the Potential of Computed Tomography-Guided Tracers in Pinpointing Lung Lesions during Surgery: A Collaborative Multi-Institutional Journey.

Background: Multiple techniques exist for the preoperative localization of small, deeply located solid or subsolid pulmonary nodules to guide limited thoracoscopic resection. This study aims to conduct a multi-institutional comparison of three different tomography-guided tracers' methods. Methods: A retrospective multicenter cross-sectional study was conducted. All patients suitable for CT-guided tracers with microcoil (GROUP1, n = 58), hook wire (GROUP2, n = 86), or bioabsorbable hydrogel plug (GROUP3, n = 33) were scheduled for video-assisted thoracoscopic wedge resection. Outcome variables: successful nodule localization, safety, and the feasibility of the tracers' placement. A χ2 test or Fisher's test for expected numbers less than five and a Kruskal-Wallis test were used to analyze the categorical and continuous variables, respectively. For the power calculations, we used G*Power version 3.1.9.6. Results: One hundred seventy-seven patients underwent the localization and resection of 177 nodules detected with three different CT-guided tracers. A significant difference was recorded for cancer history (p = 0.030), respiratory function, Charlson comorbidity index (p = 0.018), lesion type (p < 0.0001), distance from pleura surface (p < 0.0001), and time between preoperative CT-guided tracers and surgical procedures (p < 0.0001). Four post-procedural complications were recorded and in GROUP2, four cases of tracer dislocations occurred. Finally, hook wire group was associated with the shortest surgical time (93 min, p = 0.001). Conclusions: All methods were feasible and efficient, resulting in a 100% success rate for the microcoils and the bioabsorbable hydrogel plugs and a 94.2% success rate for the hook wires. Our results highlight the need to choose a technique that is less stressful for the patient and helps the surgeon by extending the approach to deep nodules and resecting over the course of several days from deployment.

Intraoperative marking of pulmonary nodules in a hybrid operating room: electromagnetic navigation bronchoscopy versus percutaneous marking.

Intraoperative identification of subsolid or small pulmonary nodules during minimally invasive procedures is challenging. Recent localization techniques show varying success and complications. Hybrid operating rooms (HORs), equipped with radiological tools, facilitate intraoperative imaging. This study compares the accuracy and safety of marking pulmonary nodules using electromagnetic navigation bronchoscopy (ENB) combined with Cone Beam Computed Tomography (CBCT) vs. CBCT-guided percutaneous marking (PM). This retrospective cohort study included patients with pulmonary nodules scheduled for minimally invasive resection in a HOR. Marking techniques included ENB assisted by CBCT and PM guided by CBCT. The study compared the success rate, procedure time, intraoperative complications and radiation dose of both techniques. A total of 104 patients with 114 nodules were included (October 2021-July 2024). Thirty nodules were marked using ENB, and 84 with PM. One case used both techniques due to ENB failure. No differences among groups were found in nodule characteristics. Success rates were similar (93.3% in ENB group vs. 91.7% in PM group, p = 1). Marking took significantly longer time in the ENB group (median 40 min) compared to PM group (25 min, p = 0.007). Five (6%) patients in the PM group experienced intraoperative complications compared to none in the ENB (p = 0.323). Radiation dose was significantly higher in the ENB group (p = 0.002). ENB assisted by CBCT is a safe and effective technique, with success rates comparable to CBCT-guided PM, though it may result in longer procedural times and higher radiation doses.

Inter-observer consistency on subsolid nodule follow-up recommendation based on National Comprehensive Cancer Network (NCCN) guidelines in low-dose computed tomography (LDCT) lung cancer screening.

Follow-up management of pulmonary nodules is a crucial component of lung cancer screening. Consistency in follow-up recommendations is essential for effective lung cancer screening. This study aimed to assess inter-observer agreement on National Comprehensive Cancer Network (NCCN) guideline-based follow-up recommendation for subsolid nodules from low-dose computed tomography (LDCT) screening. A retrospective collection of LDCT reports from 2014 to 2017 for lung cancer screening was conducted using the Radiology Information System and keyword searches, focusing on subsolid nodules. A total of 110 LDCT cases containing subsolid nodules were identified. Two senior radiologists provided standardized follow-up recommendation. Follow-up recommendation was categorized into four groups (0-, 3-, 6-, and 12-month). To ensure overall balance and representativeness of the follow-up categories, 60 scans from 60 participants were included (distribution ratio 1:1:2:2). Cases were categorised into follow-up recommendation groups by five observers following NCCN guidelines. Fleiss' kappa statistic was used to evaluate inter-observer agreement. Overall accuracy rate for follow-up recommendation among five observers was 72.3%. Chest radiologists' overall agreement was significantly higher than radiology residents (P<0.01). The overall agreement among the five observers was moderate, with a Fleiss' kappa of 0.437. For all paired readers, the mean Cohen's kappa value was 0.603, with 95% confidence interval (CI) from 0.489 to 0.716. Chest radiologists demonstrated substantial agreement, evidenced by a Cohen's kappa of 0.655 (95% CI: 0.503-0.807). In contrast, the mean Cohen's kappa among radiology residents was 0.533 (95% CI: 0.501-0.565). The majority of cases with discrepancies, accounting for 73.5%, were associated with the same risk-dominant nodules. A higher proportion of part-solid nodule was a risk factor for discrepancies. Of the 600 paired readings, major discrepancies and substantial discrepancies were observed in 27.5% and 4.8% (29/600) of the cases. In subsolid nodules, category evaluation of observer follow-up recommendation based on NCCN guidelines achieved moderate consistency. Disagreements were mainly caused by measurement and type disagreements of identical risk-dominant nodules. Part-solid nodule was a contributor for discrepancies in follow-up recommendation. Major and substantial management discrepancies were 27.5% and 4.8% in the paired evaluations.

Impact on Image Quality and Diagnostic Performance of Dual-Layer Detector Spectral CT for Pulmonary Subsolid Nodules: Comparison With Hybrid and Model-Based Iterative Reconstruction.

To evaluate the image quality and diagnostic performance of pulmonary subsolid nodules on conventional iterative algorithms, virtual monoenergetic images (VMIs), and electron density mapping (EDM) using a dual-layer detector spectral CT (DLSCT). This retrospective study recruited 270 patients who underwent DLSCT scan for lung nodule screening or follow-up. All CT examinations with subsolid nodules (pure ground-glass nodules [GGNs] or part-solid nodules) were reconstructed with hybrid and model-based iterative reconstruction, VMI at 40, 70, 100, and 130 keV levels, and EDM. The CT number, objective image noise, signal-to-noise ratio, contrast-to-noise ratio, diameter, and volume of subsolid nodules were measured for quantitative analysis. The overall image quality, image noise, visualization of nodules, artifact, and sharpness were subjectively rated by 2 thoracic radiologists on a 5-point scale (1 = unacceptable, 5 = excellent) in consensus. The objective image quality measurements, diameter, and volume were compared among the 7 groups with a repeated 1-way analysis of variance. The subjective scores were compared with Kruskal-Wallis test. A total of 198 subsolid nodules, including 179 pure GGNs, and 19 part-solid nodules were identified. Based on the objective analysis, EDM had the highest signal-to-noise ratio (164.71 ± 133.60; P < 0.001) and contrast-to-noise ratio (227.97 ± 161.96; P < 0.001) among all image sets. Furthermore, EDM had a superior mean subjective rating score (4.80 ± 0.42) for visualization of GGNs compared to other reconstructed images (all P < 0.001), although the model-based iterative reconstruction had superior subjective scores of overall image quality. For pure GGNs, the measured diameter and volume did not significantly differ among different reconstructions (both P > 0.05). EDM derived from DLSCT enabled improved image quality and lesion conspicuity for the evaluation of lung subsolid nodules compared to conventional iterative reconstruction algorithms and VMIs.

Estimation of pathological subtypes in subsolid lung nodules using artificial intelligence

ObjectiveThis study aimed to investigate the value of artificial intelligence (AI) for distinguishing pathological subtypes of invasive pulmonary adenocarcinomas in patients with subsolid nodules (SSNs). Materials and methodsThis retrospective study included 110 consecutive patients with 120 SSNs. The qualitative and quantitative imaging characteristics of SSNs were extracted automatically using an artificially intelligent assessment system. Then, radiologists had to verify these characteristics again. We split all cases into two groups: non-IA including 11 Atypical adenomatous hyperplasia (AAH) and 25 adenocarcinoma in situ (AIS) or IA including 7 minimally invasive adenocarcinoma (MIA) and 77 invasive adenocarcinoma (IAC). Variables that exhibited statistically significant differences between the non-IA and IA in the univariate analysis were included in the multivariate logistic regression analysis. Receiver operating characteristic (ROC) analyses were conducted to determine the cut-off values and their diagnostic performances. ResultsMultivariate logistic regression analysis showed that the major diameter (odds ratio [OR] = 1.38; 95 % confidence interval [CI], 1.02–1.87; P = 0.036) and entropy of three-dimensional(3D) CT value (OR = 3.73, 95 % CI, 1.13–2.33, P = 0.031) were independent risk factors for adenocarcinomas. The cut-off values of the major diameter and the entropy of 3D CT value for the diagnosis of invasive adenocarcinoma were 15.5 mm and 5.17, respectively. To improve the classification performance, we fused the major diameter and the entropy of 3D CT value as a combined model, and the (AUC） of the model was 0.868 (sensitivity = 0.845, specificity = 0.806). ConclusionThe major diameter and entropy of 3D CT value can distinguish non-IA from IA. AI can improve performance in distinguishing pathological subtypes of invasive pulmonary adenocarcinomas in patients with SSNs.

Comparative analysis of three-dimensional and two-dimensional models for predicting the malignancy probability of subsolid nodules

To construct three-dimensional (3D) and two-dimensional (2D) models to predict the malignancy probability of subsolid nodules (SSNs) and compare their effectiveness. A total of 371 SSNs from 332 patients, collected between January 2020 and January 2024, were included in the study. The SSNs were divided into a training set for constructing the models and a test set for validating the models. Models were developed using binary logistic backward regression, based on factors that showed significant differences in univariate analyses. The performance of the models was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). The AUCs of different models were compared using the DeLong test. The AUCs for the two 3D models, one 2D model, and the Brock model were 0.785 (0.733-0.836), 0.776 (0.723-0.829), 0.764 (0.710-0.818), and 0.738 (0.679-0.798) in the training set. In the test set, these AUCs were 0.817 (0.706-0.928), 0.796 (0.679-0.913), 0.771 (0.647-0.895), and 0.790 (0.678-0.903). The two 3D models demonstrated statistically significant differences from the Brock model in the training set (P=0.024 and P=0.046). None of the four models showed significant differences in the test set (all P>0.05). The 3D models outperform both the 2D model and the Brock model in predicting the malignancy probability of SSNs, and the 3D model incorporating volume, mean CT attenuation value, and lobulation as factors performed the best.

Clinical Outcomes of Resected Pure Ground-Glass, Heterogeneous Ground-Glass, and Part-Solid Pulmonary Nodules.

BACKGROUND. Increased (but not definitively solid) attenuation within pure ground-glass nodules (pGGNs) may indicate invasive adenocarcinoma and the need for resection rather than surveillance. OBJECTIVE. The purpose of this study was to compare the clinical outcomes among resected pGGNs, heterogeneous ground-glass nodules (GGNs), and part-solid nodules (PSNs). METHODS. This retrospective study included 469 patients (335 female patients and 134 male patients; median age, 68 years [IQR, 62.5-73.5 years]) who, between January 2012 and December 2020, underwent resection of lung adenocarcinoma that appeared as a subsolid nodule on CT. Two radiologists, using lung windows, independently classified each nodule as a pGGN, a heterogeneous GGN, or a PSN, resolving discrepancies through discussion. A heterogeneous GGN was defined as a GGN with internal increased attenuation not quite as dense as that of pulmonary vessels, and a PSN was defined as having an internal solid component with the same attenuation as that of the pulmonary vessels. Outcomes included pathologic diagnosis of invasive adenocarcinoma, 5-year recurrence rates (locoregional or distant), and recurrence-free survival (RFS) and overall survival (OS) over 7 years, as analyzed by Kaplan-Meier and Cox proportional hazards regression analyses, with censoring of patients with incomplete follow-up. RESULTS. Interobserver agreement for nodule type, expressed as a kappa coefficient, was 0.69. Using consensus assessments, 59 nodules were pGGNs, 109 were heterogeneous GGNs, and 301 were PSNs. The frequency of invasive adenocarcinoma was 39.0% in pGGNs, 67.9% in heterogeneous GGNs, and 75.7% in PSNs (for pGGNs vs heterogeneous GGNs, p < .001; for pGGNs vs PSNs, p < .001; and for heterogeneous GGNs vs PSNs, p = .28). The 5-year recurrence rate was 0.0% in patients with pGGNs, 6.3% in those with heterogeneous GGNs, and 10.8% in those with PSNs (for pGGNs vs heterogeneous GGNs, p = .06; for pGGNs vs PSNs, p = .02; and for heterogeneous GGNs vs PSNs, p = .18). At 7 years, RFS was 97.7% in patients with pGGNs, 82.0% in those with heterogeneous GGNs, and 79.4% in those with PSNs (for pGGNs vs heterogeneous GGNs, p = .02; for pGGNs vs PSNs, p = .006; and for heterogeneous GGNs vs PSNs, p = .40); OS was 98.0% in patients with pGGNs, 84.6% in those with heterogeneous GGNs, and 82.9% in those with PSNs (for pGGNs vs heterogeneous GGNs, p = .04; for pGGNs vs PSNs, p = .01; and for heterogeneous GGNs vs PSNs, p = .50). CONCLUSION. Resected pGGNs had excellent clinical outcomes. Heterogeneous GGNs had relatively worse outcomes, more closely resembling outcomes for PSNs. CLINICAL IMPACT. The findings support surveillance for truly homogeneous pGGNs versus resection for GGNs showing internal increased attenuation even if not having a true solid component.

Value of peripheral blood rare cell EGFR gene amplification detection in the evaluation of benign and malignant pulmonary nodules

Objective: To explore the value of detection of epidermal growth factor receptor (EGFR) gene amplification in peripheral blood rare cells in the assessment of benign and malignant pulmonary nodules. Methods: A total of 262 patients with pulmonary nodules were selected as the retrospectively study subjects from the Second Affiliated Hospital of Army Military Medical University and Peking Union Medical College Hospital from July 2022 to August 2023. There were 98 males and 164 females, with the age range from 16 to 79 (52.1±12.1) years. The EGFR gene amplification testing was performed on the rare cells enriched from patients' peripheral blood, and the clinical manifestations, CT imaging features, histopathological and/or pathological cytological confirmed results of patients were collected. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value of the method of detection of EGFR gene amplification in peripheral blood rare cells, and its diagnostic efficacy was evaluated. Results: Among the 262 patients, 143 were malignant pulmonary nodules and 119 were benign pulmonary nodules. The differences between malignant pulmonary nodules and benign pulmonary nodules in nodule diameter and nodule density were statistically significant (both P<0.001), while the differences in age, gender and nodule number were not statistically significant (all P>0.05). The number [M (Q1, Q3)] of EGFR gene amplification positive rare cells in patients with malignant pulmonary nodule was 8 (6, 11), which was higher than that in patients with benign pulmonary nodule [2 (1, 4), P<0.001]. The ROC curve results showed that when the optimal cut-off value was 5 (that was, the number of EGFR gene amplification positive rare cells was>5), the area under the curve (AUC) of the detection of EGFR gene amplification in peripheral blood rare cells for discrimination of benign and malignant pulmonary lesions was 0.816 (95%CI: 0.761-0.870), with a sensitivity of 83.2%, a specificity of 80.7%, and an accuracy of 82.1%. Based on the analysis of the diameter of the nodules, the AUC for distinguishing between benign and malignant pulmonary nodules with diameter 5-9 mm and 10-30 mm was 0.797 (95%CI: 0.707-0.887) and 0.809 (95%CI: 0.669-0.949), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule density, the AUC for distinguishing between benign and malignant solid nodule and subsolid nodule was 0.845 (95%CI: 0.751-0.939) and 0.790 (95%CI: 0.701-0.880), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule number, the AUC for distinguishing between benign and malignant solitary pulmonary nodule and multiple pulmonary nodule was 0.830 (95%CI: 0.696-0.965) and 0.817 (95%CI: 0.758-0.877), respectively, with sensitivity, specificity and accuracy reached 80% or above. Conclusion: The detection of EGFR gene amplification in peripheral blood rare cells contributes to the evaluation of benign and malignant pulmonary nodules, and can be used in the auxiliary diagnosis of benign and malignant pulmonary nodules.

Surveillance of subsolid nodules avoids unnecessary resections in lung cancer screening: long-term results of the prospective BioMILD trial.

The management of subsolid nodules (SSNs) in lung cancer screening (LCS) is still a topic of debate, with no current uniform strategy to deal with these lesions at risk of overdiagnosis and overtreatment. The BioMILD LCS trial has implemented a prospective conservative approach for SSNs, managing with annual low-dose computed tomography nonsolid nodules (NSNs) and part-solid nodules (PSNs) with a solid component <5 mm, regardless of the size of the nonsolid component. The present study aims to determine the lung cancer (LC) detection and survival in BioMILD volunteers with SSNs. Eligible participants were 758 out of 4071 (18.6%) BioMILD volunteers without baseline LC and at least one SSN detected at the baseline or further low-dose computed tomography rounds. The outcomes of the study were LC detection and long-term survival. A total of 844 NSNs and 241 PSNs were included. LC detection was 3.7% (31 out of 844) in NSNs and 7.1% (17 out of 241) in PSNs, being significantly greater in prevalent than incident nodules (8.4% versus 1.3% in NSNs; 14.1% versus 2.1% in PSNs; p-value for both nodule types p<0.01). Most LCs from SSNs were stage I (42/48, 87.5%), resectable (47/48, 97.9%), and caused no deaths. The 8-year cumulative survival of volunteers with LC derived from SSNs and not derived from SSNs was 93.8% and 74.9%, respectively. Conservative management of SSNs in LCS enables timely diagnosis and treatment of LCs arising from SSNs while ensuring the resection of more aggressive LCs detected away from SSNs.

The impact of PET/CT and brain MRI for metastasis detection among patients with clinical T1-category lung cancer: Findings from a large-scale cohort study

Purpose[18F]-FDG PET/CT and brain MRI are common approaches to detect metastasis in patients of lung cancer. Current guidelines for the use of PET/CT and MRI in clinical T1-category lung cancer lack risk-based stratification and require optimization. This study stratified patients based on metastatic risk in terms of the lesions' size and morphological characteristics.MethodsThe detection rate of metastasis was measured in different sizes and morphological characteristics (solid and sub-solid) of tumors. To confirm the cut-off value for discriminating metastasis and overall survival (OS) prediction, the receiver operating characteristic (ROC) analysis was performed based on PET/CT metabolic parameters (SUVmax/SUVmean/SULpeak/MTV/TLG), followed by Kaplan–Meier analysis for survival in post-operation patients with and without PET/CT plus MRI.Results2,298 patients were included. No metastasis was observed in patients with solid nodules < 8.0 mm and sub-solid nodules < 10.0 mm. The cut-off of PET/CT metabolic parameters on discriminating metastasis were 1.09 (SUVmax), 0.26 (SUVmean), 0.31 (SULpeak), 0.55 (MTV), and 0.81 (TLG), respectively. Patients undergoing PET/CT plus MRI exhibited longer OS compared to those who did not receive it in solid nodules ≥ 8.0 mm & sub-solid nodules ≥ 10.0 mm (HR, 0.44; p < 0.001); in solid nodules ≥ 8.0 mm (HR, 0.12; p<0.001) and in sub-solid nodules ≥ 10.0 mm (HR; 0.61; p=0.075), respectively. Compared to patients with metabolic parameters lower than cut-off values, patients with higher metabolic parameters displayed shorter OS: SUVmax (HR, 12.94; p < 0.001), SUVmean (HR, 11.33; p <0.001), SULpeak (HR, 9.65; p < 0.001), MTV (HR, 9.16; p = 0.031), and TLG (HR, 12.06; p < 0.001).ConclusionThe necessity of PET/CT and MRI should be cautiously evaluated in patients with solid nodules < 8.0 mm and sub-solid nodules < 10.0 mm, however, these examinations remained essential and beneficial for patients with solid nodules ≥ 8.0 mm and sub-solid nodules ≥ 10.0 mm.

Diagnostic Accuracy of a Computed Tomography-Guided Transthoracic Needle Biopsy for Ground-Glass Opacities and Subsolid Pulmonary Nodules.

Purpose The increasing use of computed tomography (CT) imaging has led to the detection of more ground-glass nodules (GGNs) and subsolid nodules (SSNs), which may be malignant and require a biopsy for proper diagnosis. Approximately 75% of persistent GGNs can be attributed to adenocarcinoma in situ or minimally invasive adenocarcinoma. A CT-guided biopsy has been proven to be a reliable procedure with high diagnostic performance. However, the diagnostic accuracy and safety of a CT-guided biopsy for GGNs and SSNs with solid components ≤6 mm are still uncertain.The aim of this study is to assess the diagnostic accuracy of a CT-guided core needle biopsy (CNB) for GGN and SSNs with solid components ≤6 mm. Methods This is a retrospective study of patients who underwent CT-guided CNB for the evaluation of GGNs and SSNs with solid components ≤6 mm between February 2020 and January 2023. Biopsy findings were compared to the final diagnosis determined by definite histopathologic examination and clinical course. Results A total of 22 patients were enrolled, with a median age of 74 years (IQR: 68-81). A total of 22 nodules were assessed, comprising 15 (68.2%) SSNs with a solid component measuring ≤6 mm and seven (31.8%) pure GGNs. The histopathological examination revealed that 12 (54.5%) were diagnosed as malignant, nine (40.9%) as benign, and one (4.5%) as non-diagnostic. The overall diagnostic accuracy and sensitivity for malignancy were 86.36% and 85.7%, respectively. Conclusion A CT-guided CNB for GGNs and SSNs with solid components measuring ≤6 mm appears to have a high diagnostic accuracy.

The radiological characteristics, tertiary lymphoid structures, and survival status associated with EGFR mutation in patients with subsolid nodules like stage I-II LUAD.

BackgroundEpidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) recommended for the patients with subsolid nodule in early lung cancer stage is not routinely. The clinical value and impact in patients with EGFR mutation on survival outcomes is further needed to be elucidated to decide whether the application of EGFR-TKIs was appropriate in early lung adenocarcinoma (LUAD) stage appearing as subsolid nodules.Materials and methodsThe inclusion of patients exhibiting clinical staging of IA-IIB subsolid nodules. Clinical information, computed tomography (CT) features before surgical resection and pathological characteristics including tertiary lymphoid structures of the tumors were recorded for further exploration of correlation with EGFR mutation and prognosis.ResultsFinally, 325 patients were enrolled into this study, with an average age of 56.8 ± 9.8 years. There are 173 patients (53.2%) harboring EGFR mutation. Logistic regression model analysis showed that female (OR = 1.944, p = 0.015), mix ground glass nodule (OR = 2.071, p = 0.003, bubble-like lucency (OR = 1.991, p = 0.003) were significant risk factors of EGFR mutations. Additionally, EGFR mutations were negatively correlated with TLS presence and density. Prognosis analysis showed that the presence of TLS was associated with better recurrence-free survival (RFS)(p = 0.03) while EGFR mutations were associated with worse RFS(p = 0.01). The RFS in patients with TLS was considerably excel those without TLS within EGFR wild type group(p = 0.018). Multivariate analyses confirmed that EGFR mutation was an independent prognostic predictor for RFS (HR = 3.205, p = 0.037).ConclusionsIn early-phase LUADs, subsolid nodules with EGFR mutation had specific clinical and radiological signatures. EGFR mutation was associated with worse survival outcomes and negatively correlated with TLS, which might weaken the positive impact of TLS on prognosis. Highly attention should be paid to the use of EGFR-TKI for further treatment as agents in early LUAD patients who carrying EGFR mutation.

Shape-Sensing Robotic-Assisted Bronchoscopy versus Computed Tomography-Guided Transthoracic Biopsy for the Evaluation of Subsolid Pulmonary Nodules

Introduction: Lung cancer remains the leading cause of cancer death worldwide. Subsolid nodules (SSN), including ground-glass nodules (GGNs) and part-solid nodules (PSNs), are slow-growing but have a higher risk for malignancy. Therefore, timely diagnosis is imperative. Shape-sensing robotic-assisted bronchoscopy (ssRAB) has emerged as reliable diagnostic procedure, but data on SSN and how ssRAB compares to other diagnostic interventions such as CT-guided transthoracic biopsy (CTTB) are scarce. In this study, we compared diagnostic yield of ssRAB versus CTTB for evaluating SSN. Methods: A retrospective study of consecutive patients who underwent either ssRAB or CTTB for evaluating GGN and PSN with a solid component less than 6 mm from February 2020 to April 2023 at Mayo Clinic Florida and Rochester. Clinicodemographic information, nodule characteristics, diagnostic yield, and complications were compared between ssRAB and CTTB. Results: A total of 66 nodules from 65 patients were evaluated: 37 PSN and 29 GGN. Median size of PSN solid component was 5 mm (IQR: 4.5, 6). Patients were divided into two groups: 27 in the ssRAB group and 38 in the CTTB group. Diagnostic yield was 85.7% for ssRAB and 89.5% for CTTB (p = 0.646). Sensitivity for malignancy was similar between ssRAB and CTTB (86.4% vs. 88.5%; p = 0.828), with no statistical difference. Complications were more frequent in CTTB with no significant difference (8 vs. 2; p = 0.135). Conclusion: Diagnostic yield for SSN was similarly high for ssRAB and CTTB, with ssRAB presenting less complications and allowing mediastinal staging within the same procedure.

Evaluation of Prognosis in Patients with Lung Adenocarcinoma with Atypical Solid Nodules on Thin-Section CT Images.

Purpose To evaluate the clinicopathologic characteristics and prognosis of patients with clinical stage IA lung adenocarcinoma with atypical solid nodules (ASNs) on thin-section CT images. Materials and Methods Data from patients with clinical stage IA lung adenocarcinoma who underwent resection between January 2005 and December 2012 were retrospectively reviewed. According to their manifestations on thin-section CT images, nodules were classified as ASNs, subsolid nodules (SSNs), and typical solid nodules (TSNs). The clinicopathologic characteristics of the ASNs were investigated, and the differences across the three groups were analyzed. The Kaplan-Meier method and multivariable Cox analysis were used to evaluate survival differences among patients with ASNs, SSNs, and TSNs. Results Of the 254 patients (median age, 58 years [IQR, 53-66]; 152 women) evaluated, 49 had ASNs, 123 had SSNs, and 82 had TSNs. Compared with patients with SSNs, those with ASNs were more likely to have nonsmall adenocarcinoma (P < .001), advanced-stage adenocarcinoma (P = .004), nonlepidic growth adenocarcinoma (P < .001), and middle- or low-grade differentiation tumors (P < .001). Compared with patients with TSNs, those with ASNs were more likely to have no lymph node involvement (P = .009) and epidermal growth factor receptor mutation positivity (P = .018). Average disease-free survival in patients with ASNs was significantly longer than that in patients with TSNs (P < .001) but was not distinguishable from that in patients with SSNs (P = .051). Conclusion ASNs were associated with better clinical outcomes than TSNs in patients with clinical stage IA lung adenocarcinoma. Keywords: Adenocarcinoma, Atypical Solid Nodules, CT, Disease-free Survival, Lung, Prognosis, Pulmonary Supplemental material is available for this article. Published under a CC BY 4.0 license.

Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches

BackgroundLow-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate...

Clinical and non-contrast computed tomography characteristics and disease development in patients with benign pulmonary subsolid nodules with a solid component ≤ 5 mm

ObjectivesTo evaluate the clinical and non-contrast computed tomography (CT) features of patients with benign pulmonary subsolid nodules (SSNs) with a solid component ≤ 5 mm and their development trends via follow-up CT.MethodsWe retrospectively collected 436 data from patients who had SSNs with a solid component ≤ 5 mm, including 69 with absorbable benign SSNs (AB-SSNs), 70 with nonabsorbable benign SSNs (NB-SSNs), and 297 with malignant SSNs (M-SSNs). Models 1, 2, and 3 for distinguishing the different types of SSNs were then developed and validated.ResultsPatients with AB-SSNs were younger and exhibited respiratory symptoms more frequently than those with M-SSNs. The frequency of nodules detected during follow-up CT was in the following order: AB-SSNs > NB-SSNs > M-SSNs. NB-SSNs were smaller than M-SSNs, and ill-defined margins were more frequent in AB-SSNs than in NB-SSNs and M-SSNs. Benign SSNs exhibited irregular shape, target sign, and lower CT values more frequently compared to M-SSNs, whereas the latter demonstrated bubble lucency more commonly compared to the former. Furthermore, AB-SSNs showed more thickened interlobular septa and satellite lesions than M-SSNs and M-SSNs had more pleural retraction than AB-SSNs (all p < 0.017). The three models had AUCs ranging 0.748–0.920 and 0.790–0.912 in the training and external validation cohorts, respectively. A follow-up CT showed nodule progression in four benign SSNs.ConclusionsThe three SSN types have different clinical and imaging characteristics, with some benign SSNs progressing to resemble malignancy.Critical relevance statementA good understanding of the imaging features and development trends of benign SSNs may help reduce unnecessary follow-up or interventions. This retrospective study explores the CT characteristics of benign SSNs with a solid component ≤ 5 mm by comparing AB-SSNs, NB-SSNs, and M-SSNs and delineates their development trends via follow-up CT.Key points1. Different subsolid nodule types exhibit distinct clinical and imaging features.2. A miniscule number of benign subsolid nodules can progress to resemble malignancy.3. Knowing the clinical and imaging features and development trends of benign subsolid nodules can improve management.Graphical

Growth and Clinical Impact of Subsolid Lung Nodules ≥6 mm During Long-Term Follow-Up After Five Years of Stability.

To investigate the incidence and timing of late growth of subsolid nodules (SSNs) ≥6 mm after initial 5-year stability, its clinical implications, and the appropriate follow-up strategy. This retrospective study included SSNs ≥6 mm that remained stable for the initial five years after detection. The incidence and timing of subsequent growth after five years of stability were analyzed using the Kaplan-Meier method. Descriptive analyses were conducted to evaluate the clinical stage shift in the SSNs, showing growth and the presence of metastasis during the follow-up period. Finally, an effective follow-up CT scan strategy for managing SSNs after a 5-year period of stability was investigated. Two hundred thirty-five eligible SSNs (211 pure ground-glass and 24 part-solid nodules) in 235 patients (median age, 63 years; 132 female) were followed for additional <1 to 181 months (median, 87.0 months; interquartile range [IQR], 47.0-119.0 months) after 5-year stability. Fourteen SSNs (6.0%) showed growth at two to 145 months (median, 96 months; IQR: 43.0-122.25 months) from the CT scan confirming 5-year stability, with the estimated cumulative incidence of growth of 0.4%, 2.1%, and 6.5% at 1, 5, and 10 years, respectively. Nine SSNs (3.8%) exhibited clinical stage shifts. No lung cancer metastases were observed. Hypothetical follow-up CT scans performed at 5, 10, and 15 years after 5-years of stability, would have detected 5 (36%), 11 (79%), and 14 (100%) of the 14 growing SSNs, along with 4 (44%), 8 (89%), and 9 (100%) of the nine stage shifts, respectively. During a long-term follow-up of pulmonary SSNs ≥6 mm after 5-years of stability, a low incidence of growth without occurrence of metastasis was noted. CT scans every five years after the initial 5-year stability period may be reasonable.

Application of computer-aided detection for NCCN-based follow-up recommendation in subsolid nodules: Effect on inter-observer agreement.

Computer-aided detection (CAD) of pulmonary nodules reduces the impact of observer variability, improving the reliability and reproducibility of nodule assessments in clinical practice. Therefore, this study aimed to assess the impact of CAD on inter-observer agreement in the follow-up management of subsolid nodules. A dataset comprising 60 subsolid nodule cases was constructed based on the National Cancer Center lung cancer screening data. Five observers independently assessed all low-dose computed tomography scans and assigned follow-up management strategies to each case according to the National Comprehensive Cancer Network (NCCN) guidelines, using both manual measurements and CAD assistance. The linearly weighted Cohen's kappa test was used to measure agreement between paired observers. Agreement among multiple observers was evaluated using the Fleiss kappa statistic. The agreement of the five observers for NCCN follow-up management categorization was moderate when measured manually, with a Fleiss kappa score of 0.437. Utilizing CAD led to a notable enhancement in agreement, achieving a substantial consensus with a Fleiss kappa value of 0.623. After using CAD, the proportion of major and substantial management discrepancies decreased from 27.5% to 15.8% and 4.8% to 1.5%, respectively (p < 0.01). In 23 lung cancer cases presenting as part-solid nodules, CAD significantly elevates the average sensitivity in detecting lung cancer cases presenting as part-solid nodules (overall sensitivity, 82.6% vs. 92.2%; p < 0.05). The application of CAD significantly improves inter-observer agreement in the follow-up management strategy for subsolid nodules. It also demonstrates the potential to reduce substantial management discrepancies and increase detection sensitivity in lung cancer cases presenting as part-solid nodules.

An artificial intelligence-assisted diagnostic system for the prediction of benignity and malignancy of pulmonary nodules and its practical value for patients with different clinical characteristics.

This study aimed to explore the value of an artificial intelligence (AI)-assisted diagnostic system in the prediction of pulmonary nodules. The AI system was able to make predictions of benign or malignant nodules. 260 cases of solitary pulmonary nodules (SPNs) were divided into 173 malignant cases and 87 benign cases based on the surgical pathological diagnosis. A stratified data analysis was applied to compare the diagnostic effectiveness of the AI system to distinguish between the subgroups with different clinical characteristics. The accuracy of AI system in judging benignity and malignancy of the nodules was 75.77% (p < 0.05). We created an ROC curve by calculating the true positive rate (TPR) and the false positive rate (FPR) at different threshold values, and the AUC was 0.755. Results of the stratified analysis were as follows. (1) By nodule position: the AUC was 0.677, 0.758, 0.744, 0.982, and 0.725, respectively, for the nodules in the left upper lobe, left lower lobe, right upper lobe, right middle lobe, and right lower lobe. (2) By nodule size: the AUC was 0.778, 0.771, and 0.686, respectively, for the nodules measuring 5-10, 10-20, and 20-30 mm in diameter. (3) The predictive accuracy was higher for the subsolid pulmonary nodules than for the solid ones (80.54 vs. 66.67%). The AI system can be applied to assist in the prediction of benign and malignant pulmonary nodules. It can provide a valuable reference, especially for the diagnosis of subsolid nodules and small nodules measuring 5-10 mm in diameter.