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

BACKGROUND: Epidermal 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 METHODS: The 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. RESULTS: Finally, 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). CONCLUSIONS: In 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.

Lung adenocarcinoma manifesting as subsolid nodule potentially represents tumour in the equilibrium phase of immunoediting.

Lung adenocarcinomas manifesting as subsolid nodules (SSN-LUADs) possess distinct dormant behaviour. This study was designed to compare the immune landscapes of normal lungs (nLungs), SSN-LUADs and LUADs manifesting as solid nodules (SN-LUADs) so as to better understand the status of anti-tumour immunity in SSN-LUADs. Mass cytometry by time-of-flight analysis was performed on 299, 570 single cells from nLung, SSN-LUAD and SN-LUAD tissues. The immune cells were identified by phenotype, and the percentages of different immune cell subclusters were compared between SSN-LUADs, SN-LUADs and nLungs. Elevated percentage of CD8+ T cells were identified in SSN-LUADs compared with in nLungs and SN-LUADs. Elevated CD56bright NK cells and decreased CD56dim NK cells were identified in both SSN-LUADs and SN-LUADs compared with in nLungs. The immune landscape of SSN-LUAD fits the theory of equilibrium phase of immunoediting, thus functional adaptive anti-tumour immunity but impaired innate anti-tumour immunity potentially contributes to the maintaining of its dormant behaviour.

Diagnostic Yield of Shape-Sensing Robotic-Assisted Bronchoscopy for Ground-Glass Nodules and Subsolid Nodules with a Solid Component Less than 6 mm.

BACKGROUND: Ground-glass pulmonary nodules (GGNs) are most commonly sampled by percutaneous transthoracic biopsy. Diagnostic yield for ground-glass nodules using robotic-assisted bronchoscopy has been scarcely described, with a reported yield of 70.6%. OBJECTIVES: The aim of this study is to assess diagnostic yield for GGNs using shape-sensing robotic-assisted bronchoscopy (ssRAB). METHOD: A retrospective study of patients who underwent ssRAB for evaluation of GGNs, from September 2021 to April 2023. Primary outcome was diagnostic yield of ssRAB for GGNs, secondary outcomes were sensitivity for malignancy, and complications that required admission or intervention. RESULTS: A total of 23 nodules were biopsied from 22 patients. Median age was 71 years (IQR 66-81), 63.6% were female, and 40.9% had a previous history of cancer. Forty-three percent of nodules were in the right upper lobes, and the median lesion size was 1.8 × 1.21. Twelve were subsolid nodules (SSNs), and 11 were pure GGNs. Overall diagnostic yield was 87%, with a sensitivity for malignancy of 88.9%. Adenocarcinoma was the most common malignancy diagnosed (70%). No procedure-related complications were reported. CONCLUSION: The use of ssRAB shows a high diagnostic yield for diagnosing GGN and SSN with less than 6 mm solid component with a low risk for complications.

Software-based quantitative CT analysis to predict the growth trend of persistent nonsolid pulmonary nodules: a retrospective study.

PURPOSE: Persistent nonsolid nodules (NSNs) usually exhibit an indolent course and may remain stable for several years; however, some NSNs grow quickly and require surgical excision. Therefore, identifying quantitative features capable of early discrimination between growing and nongrowing NSNs is becoming a crucial aspect of radiological analysis. The main purpose of this study was to evaluate the performance of an open-source software (ImageJ) to predict the future growth of NSNs detected in a Caucasian (Italian) population. MATERIAL AND METHODS: We retrospectively selected 60 NSNs with an axial diameter of 6-30 mm scanned with the same acquisition-reconstruction parameters and the same computed tomography (CT) scanner. Software-based analysis was performed on thin-section CT images using ImageJ. For each NSNs, several quantitative features were extracted from the baseline CT images. The relationships of NSN growth with quantitative CT features and other categorical variables were analyzed using univariate and multivariable logistic regression analyses. RESULTS: In multivariable analysis, only the skewness and linear mass density (LMD) were significantly associated with NSN growth, and the skewness was the strongest predictor of growth. In receiver operating characteristic curve analyses, the optimal cutoff values of skewness and LMD were 0.90 and 19.16 mg/mm, respectively. The two predictive models that included the skewness, with or without LMD, exhibited an excellent power for predicting NSN growth. CONCLUSION: According to our results, NSNs with a skewness value > 0.90, specifically those with a LMD > 19.16 mg/mm, should require closer follow-up due to their higher growth potential, and higher risk of becoming an active cancer.

Differentiating focal interstitial fibrosis from adenocarcinoma in persistent pulmonary subsolid nodules (> 5 mm and < 20 mm): the role of coronal thin-section CT images.

OBJECTIVES: To investigate thin-section computed tomography (CT) features of pulmonary subsolid nodules (SSNs) with sizes between 5 and 20 mm to determine predictive factors for differentiating focal interstitial fibrosis (FIF) from adenocarcinoma. METHODS: From January 2017 to December 2018, 169 patients who had persistent SSNs 5-20 mm in size and underwent preoperative nodule localization were enrolled. Patient characteristics and thin-section CT features of the SSNs were reviewed and compared between the FIF and adenocarcinoma groups. Univariable and multivariable analyses were used to identify predictive factors of malignancy. Receiver operating characteristic (ROC) curve analysis was used to quantify the performance of these factors. RESULTS: Among the 169 enrolled SSNs, 103 nodules (60.9%) presented as pure ground-glass opacities (GGOs), and 40 (23.7%) were FIFs. Between the FIF and adenocarcinoma groups, there were significant differences (p< 0.05) in nodule border, shape, thickness, and coronal/axial (C/A) ratio. Multivariable analysis demonstrated that a well-defined border, a nodule thickness >4.2, and a C/A ratio >0.62 were significant independent predictors of malignancy. The performance of a model that incorporated these three predictors in discriminating FIF from adenocarcinoma achieved a high area under the ROC curve (AUC, 0.979) and specificity (97.5%). CONCLUSIONS: For evaluating persistent SSNs 5-20 mm in size, the combination of a well-defined border, a nodule thickness > 4.2, and a C/A ratio > 0.62 is strongly correlated with malignancy. High accuracy and specificity can be achieved by using this predictive model. KEY POINTS: • Thin-section coronal images play an important role in differentiating FIF from adenocarcinoma. • The combination of a well-defined border, nodule thickness>4.2 mm, and C/A ratio >0.62 is associated with malignancy. • This predictive model may be helpful for managing persistent SSNs between 5 and 20 mm in size.

Utility of FDG PET/CT for Preoperative Staging of Non-Small Cell Lung Cancers Manifesting as Subsolid Nodules With a Solid Portion of 3 cm or Smaller.

OBJECTIVE. The objective of our study was to investigate the utility of FDG PET/CT for the preoperative staging of subsolid non-small cell lung cancers (NSCLCs) with a solid portion size of 3 cm or smaller. MATERIALS AND METHODS. We retrospectively enrolled 855 patients with pathologically proven NSCLCs manifesting as subsolid nodules with a solid portion of 3 cm or smaller on CT. We then compared the diagnostic performances of FDG PET/CT and chest CT for detecting lymph node (LN), intrathoracic, or distant metastases in patients who underwent preoperative chest CT and FDG PET/CT. After propensity score matching, we compared the diagnostic performance of FDG PET/CT in the group who underwent both chest CT and FDG PET/CT with that of chest CT in patients who did not undergo FDG PET/CT. RESULTS. There were LN metastases in 25 of 765 patients (3.3%) who underwent surgical LN dissection or biopsy and intrathoracic or distant metastasis in two of 855 patients (0.2%). For LN staging, FDG PET/CT showed a sensitivity of 44.0%, specificity of 81.5%, positive predictive value of 9.6%, negative predictive value of 97.0%, and accuracy of 79.9%, which were lower than those of chest CT for accuracy (p < 0.0001). FDG PET/CT could not accurately detect any intrathoracic or distant metastasis. After propensity score matching, the diagnostic accuracy for LN staging of FDG PET/CT in the group who underwent both CT and FDG PET/CT was lower than that of chest CT in the group who did not undergo FDG PET/CT (p = 0.002), and the diagnostic accuracy for intrathoracic and distant metastases was not different (p > 0.999). CONCLUSION. FDG PET/CT has limited utility in preoperatively detecting LN or distant metastasis in patients with subsolid NSCLCs with a solid portion size of 3 cm or smaller.

Natural History of Persistent Pulmonary Subsolid Nodules: Long-Term Observation of Different Interval Growth.

BACKGROUND: The long-term natural course and outcomes of subsolid nodules (SSNs) in terms of true growth, substantial growth, and stage shift need to be clarified. METHODS: Between 2002 and 2016, 128 subjects with persistent SSNs of 3cm or smaller were enrolled. The baseline and interval changes in the series computed tomography (CT) findings during the follow-up period were subsequently reviewed. RESULTS: The mean follow-up period was 3.57±2.93years. The cumulative percentage of growth nodules of the part-solid nodule (PSN) group was significantly higher than that of the ground-glass nodule (GGN) group by Kaplan-Meier estimation (all p<0.0001). For true SSN growth, GGNs usually take a median follow-up of 7 years to grow; PSNs usually take a median follow-up of 3 years to grow. For substantial SSN growth, GGNs usually take a median follow-up of 9 years to grow; PSNs usually take a median follow-up of 3 years to grow. For stage shift, GGNs usually take a median follow-up of 12 years to grow; PSNs usually take a median follow-up of 9 years to grow. CONCLUSIONS: The natural course in terms of true growth, substantial growth, and stage shift differed significantly according to their nodule type, which could contribute to the development of follow-up guidelines and management strategy of pulmonary SSNs.

Detection of lung carcinoma with predominant ground-glass opacity on CT using temporal subtraction method.

PURPOSE: To evaluate the usefulness of the CT temporal subtraction (TS) method for the detection of the lung cancer with predominant ground-glass opacity (LC-pGGO). MATERIALS AND METHODS: Twenty-five pairs of CT and their TS images in patients with LC-pGGO (31 lesions) and 25 pairs of those in patients without nodules were used for an observer performance study. Eight radiologists participated and the statistical significance of differences with and without the CT-TS was assessed by JAFROC analysis. RESULTS: The average figure-of-merit (FOM) values for all radiologists increased to a statistically significant degree, from 0.861 without CT-TS to 0.912 with CT-TS (p < .001). The average sensitivity for detecting the actionable lesions improved from 73.4 % to 85.9 % using CT-TS. The reading time with CT-TS was not significantly different from that without. CONCLUSION: The use of CT-TS improves the observer performance for the detection of LC-pGGO. KEY POINTS: • CT temporal subtraction can improve the detection accuracy of lung cancer. • Reading time with temporal subtraction is not different from that without. • CT temporal subtraction improves observer performance for ground-glass/subsolid nodule detection.

Comparison of the effects of model-based iterative reconstruction and filtered back projection algorithms on software measurements in pulmonary subsolid nodules.

OBJECTIVES: To evaluate the differences between filtered back projection (FBP) and model-based iterative reconstruction (MBIR) algorithms on semi-automatic measurements in subsolid nodules (SSNs). METHODS: Unenhanced CT scans of 73 SSNs obtained using the same protocol and reconstructed with both FBP and MBIR algorithms were evaluated by two radiologists. Diameter, mean attenuation, mass and volume of whole nodules and their solid components were measured. Intra- and interobserver variability and differences between FBP and MBIR were then evaluated using Bland-Altman method and Wilcoxon tests. RESULTS: Longest diameter, volume and mass of nodules and those of their solid components were significantly higher using MBIR (p < 0.05) with mean differences of 1.1% (limits of agreement, -6.4 to 8.5%), 3.2% (-20.9 to 27.3%) and 2.9% (-16.9 to 22.7%) and 3.2% (-20.5 to 27%), 6.3% (-51.9 to 64.6%), 6.6% (-50.1 to 63.3%), respectively. The limits of agreement between FBP and MBIR were within the range of intra- and interobserver variability for both algorithms with respect to the diameter, volume and mass of nodules and their solid components. There were no significant differences in intra- or interobserver variability between FBP and MBIR (p > 0.05). CONCLUSION: Semi-automatic measurements of SSNs significantly differed between FBP and MBIR; however, the differences were within the range of measurement variability. KEY POINTS: • Intra- and interobserver reproducibility of measurements did not differ between FBP and MBIR. • Differences in SSNs' semi-automatic measurement induced by reconstruction algorithms were not clinically significant. • Semi-automatic measurement may be conducted regardless of reconstruction algorithm. • SSNs' semi-automated classification agreement (pure vs. part-solid) did not significantly differ between algorithms.

Predictive CT Features of Visceral Pleural Invasion by T1-Sized Peripheral Pulmonary Adenocarcinomas Manifesting as Subsolid Nodules.

OBJECTIVE: The objective of our study was to determine whether visceral pleural invasion (VPI) of T1-sized peripheral pulmonary adenocarcinomas manifesting as subsolid nodules (SSNs) abutting the pleural surface or associated with pleural tags can be predicted. MATERIALS AND METHODS: Our study population consisted of 188 T1-sized peripheral pulmonary adenocarcinomas that appeared as SSNs (24 pure ground-glass nodules [GGNs] and 164 part-solid nodules) and underwent surgical resection between January 2007 and December 2013. Logistic regression analysis was performed to identify significant factors in predicting VPI. RESULTS: VPI occurred in 36 of 188 adenocarcinomas (19.1%). There were no cases of VPI in patients with pure GGNs. In part-solid nodules, there were significant differences regarding the presence of pleural contact, presence of pleural thickening, presence of solid portion abutting the pleura, nodule size, solid portion size, solid proportion, interface length, and length of the solid portion contacting the pleura (p < 0.05). Multivariate analysis revealed pleural contact (p < 0.001), pleural thickening (p = 0.003), solid proportion greater than 50% (p = 0.002), and nodule size greater than 20 mm (p = 0.015) as significant independent predictive features for VPI with adjusted odds ratios of 8.300, 3.966, 4.636, and 2.993, respectively. CONCLUSION: In part-solid nodules, the CT features of pleural contact, pleural thickening, solid proportion greater than 50%, and nodule size greater than 20 mm were shown to be significant indicators of VPI by T1-sized peripheral adenocarcinomas.

Software performance in segmenting ground-glass and solid components of subsolid nodules in pulmonary adenocarcinomas.

OBJECTIVE: To evaluate the performance of software in segmenting ground-glass and solid components of subsolid nodules in pulmonary adenocarcinomas. METHOD: Seventy-three pulmonary adenocarcinomas manifesting as subsolid nodules were included. Two radiologists measured the maximal axial diameter of the ground-glass components on lung windows and that of the solid components on lung and mediastinal windows. Nodules were segmented using software by applying five (-850 HU to -650 HU) and nine (-130 HU to -500 HU) attenuation thresholds. We compared the manual and software measurements of ground-glass and solid components with pathology measurements of tumour and invasive components. RESULTS: Segmentation of ground-glass components at a threshold of -750 HU yielded mean differences of +0.06 mm (p = 0.83, 95 % limits of agreement, 4.51 to 4.67) and -2.32 mm (p < 0.001, -8.27 to 3.63) when compared with pathology and manual measurements, respectively. For solid components, mean differences between the software (at -350 HU) and pathology measurements and between the manual (lung and mediastinal windows) and pathology measurements were -0.12 mm (p = 0.74, -5.73 to 5.55]), 0.15 mm (p = 0.73, -6.92 to 7.22), and -1.14 mm (p < 0.001, -7.93 to 5.64), respectively. CONCLUSION: Software segmentation of ground-glass and solid components in subsolid nodules showed no significant difference with pathology. KEY POINTS: • Software can effectively segment ground-glass and solid components in subsolid nodules. • Software measurements show no significant difference with pathology measurements. • Manual measurements are more accurate on lung windows than on mediastinal windows.

Transient subsolid nodules in patients with extrapulmonary malignancies: their frequency and differential features.

BACKGROUND: For pulmonary subsolid nodules (SSNs) in patients with extrapulmonary malignancies, it is still unclear what proportion of SSNs is transient and how we can more accurately diagnose these transient SSNs. PURPOSE: To investigate the frequency of transient SSNs and their differentiating clinical and thin-section computed tomography (CT) features in patients with extrapulmonary malignancies. MATERIAL AND METHODS: From January 2005 to February 2012, 78 SSNs in 63 individuals (30 men and 33 women; mean age, 55.1 years ± 15.5) with extrapulmonary malignancies were identified. Their clinical and thin-section CT characteristics were reviewed and compared between transient and persistent SSNs. Differentiating factors and their performance were also measured. RESULTS: Thirty-six of the 78 SSNs (46.2%) were transient. Between transient and persistent SSNs, there were significant differences in patients' age, sex, detection mode, and the presence of eosinophilia, lesion multiplicity, lesion margin, and pleural retraction (P < 0.05). Multivariate analysis revealed that follow-up detected SSNs (adjusted odds ratio [OR], 38.88), multiple lesions (OR, 7.64), and an ill-defined nodular margin (OR, 11.93) were significant discriminators of transient SSNs (P < 0.05). Discrimination of transient SSNs was significantly better upon incorporating both clinical and thin-section CT features than using clinical features alone (P < 0.05). CONCLUSION: Approximately half of the SSNs detected in patients with extrapulmonary malignancies were transient. Transient SSNs in these patients can be very accurately differentiated using their thin-section CT and clinical features.

Extent of surgical resection for radiologically subsolid T1N0 invasive lung adenocarcinoma: When is a wedge resection acceptable?

OBJECTIVE: To evaluate whether wedge resection (WR) was appropriate for the patients with peripheral T1 N0 solitary subsolid invasive lung adenocarcinoma. METHODS: Patients with peripheral T1N0 solitary subsolid invasive lung adenocarcinoma who received sublobar resection were retrospectively reviewed. Clinicopathologic characteristics, 5-year recurrence-free survival, and 5-year lung cancer-specific overall survival were analyzed. Cox regression model was used to elucidate risk factors for recurrence. RESULTS: Two hundred fifty-eight patients receiving WR and 1245 patients receiving segmentectomy were included. The mean follow-up time was 36.87 ± 16.21 months. Five-year recurrence-free survival following WR was 96.89% for patients with ground-glass nodule (GGN) ≤2 cm and 0.25< consolidation-to-tumor ratio (CTR) ≤0.5, not statistically different from 100% for those with GGN≤2 cm and CTR ≤0.25 (P = .231). The 5-year recurrence-free survival was 90.12% for patients with GGN between 2 and 3 cm and CTR ≤0.5, significantly lower than that of patients with GGN ≤2 cm and CTR ≤0.25 (P = .046). For patients with GGN≤2 cm and 0.25

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.

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

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

RATIONALE AND OBJECTIVES: 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. MATERIALS AND METHODS: 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. RESULTS: 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). CONCLUSION: 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.

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.

Prediction of Interval Growth of Lung Adenocarcinomas Manifesting as Persistent Subsolid Nodules ≤3 cm Based on Radiomic Features.

RATIONALES AND OBJECTIVES: To investigate the prognostic value of the radiomic-based prediction model in predicting the interval growth rate of persistent subsolid nodules (SSNs) with an initial size of ≤ 3 cm manifesting as lung adenocarcinomas. MATERIALS AND METHODS: A total of 133 patients (mean age, 59.02 years; male, 37.6%) with 133 SSNs who underwent a series of CT examinations at our hospital between 2012 and 2022 were included in this study. Forty-one radiomic features were extracted from each volumetric region of interest. Radiomic features combined with conventional clinical and semantic parameters were then selected for radiomic-based model building. To investigate the model performance in terms of substantial SSN growth and stage shift growth, the model performance was compared by the area under the curve (AUC) obtained by receiver operating characteristic analysis. RESULTS: The mean follow-up period was 3.62 years. For substantial SSN growth, a radiomic-based model (Model 2) based on clinical characteristics, CT semantic features, and radiomic features yielded an AUCs of 0.869 (95% CI: 0.799-0.922). In comparison with Model 1 (clinical characteristics and CT semantic features), Model 2 performed better than Model 1 for substantial SSN growth (AUC model 1:0.793 versus AUC model 2:0.869, p = 0.028). A radiomic-based nomogram combining sex, follow-up period, and three radiomic features was built for substantial SSN growth prediction. For the stage shift growth, a radiomic-based model (Model 4) based on clinical characteristics, CT semantic features, and radiomic features yielded an AUCs of 0.883 (95% CI: 0.815-0.933). Compared with Model 3 (clinical characteristics and CT semantic features), Model 4 performed better than the model 3 for stage shift growth (AUC model 1: 0.769 versus AUC model 2: 0.883, p = 0.006). A radiomic-based nomogram combining the initial nodule size, SSN classification, follow-up period, and three radiomic features was built to predict the stage shift growth. CONCLUSION: Radiomic-based models have superior utility in estimating the prognostic interval growth of patients with early lung adenocarcinomas (≤ 3 cm) than conventional clinical-semantic models in terms of substantial interval growth and stage shift growth, potentially guiding clinical decision-making with follow-up strategies of SSNs in personalized precision medicine.

A Nomogram Incorporating Tumor-Related Vessels for Differentiating Adenocarcinoma In Situ from Minimally Invasive and Invasive Adenocarcinoma Appearing as Subsolid Nodules.

OBJECTIVES: To develop a nomogram incorporating the quantity of tumor-related vessels (TRVs) and conventional CT features (CCTFs) for the preoperative differentiation of adenocarcinoma in situ (AIS) from minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) appearing as subsolid nodules. METHODS: High-resolution CT target scans of 274 subsolid nodules from 268 patients were included in this study and randomly assigned to the training and validation groups at a ratio of 7:3. A nomogram incorporating CCTFs with the category of TRVs (CTRVs, using TRVs as categorical variables) and a final nomogram combining the number of TRVs (QTRVs) and CCTFs were constructed using multivariable logistic regression analysis. The performance levels of the two nomograms were evaluated and validated on the training and validation datasets and then compared. RESULTS: The CCTF-QTRV nomogram incorporating abnormal air bronchogram, density, number of dilated and distorted vessels and number of adherent vessels showed more favorable predictive efficacy than the CCTF-CTRV nomogram (training cohort: area under the curve (AUC) = 0.893 vs. 0.844, validation cohort: AUC = 0.871 vs. 0.807). The net reclassification index (training cohort: 0.188, validation cohort: 0.326) and the integrated discrimination improvement values (training cohort: 0.091, validation cohort: 0.125) indicated that the CCTF-QTRV nomogram performed significantly better discriminative ability than the CCTF-CTRV nomogram (all p-value < 0.05). CONCLUSIONS: The nomogram incorporating the QTRVs and CCTFs showed favorable predictive efficacy for differentiating AIS from MIA-IAC appearing as subsolid nodules and may serve as a potential tool to provide individual care for these patients.

A narrative review of the clinical approach to subsolid pulmonary nodules.

Background and Objective: The widespread use of chest computed tomography (CT) for lung cancer screening has led to increased detection of subsolid pulmonary nodules. The management of subsolid nodules (SSNs) is challenging since they are likely to grow slowly and a long-term follow-up is needed. In this review, we discuss the characteristics, natural history, genetic features, surveillance, and management of SSNs. Methods: PubMed and Google Scholar were searched to identify relevant articles published in English between January 1998 and December 2022 using the following keywords: "subsolid nodule", "ground-glass nodule (GGN)", and "part-solid nodule (PSN)". Key Content and Findings: The differential diagnosis of SSNs includes transient inflammatory lesions, focal fibrosis, and premalignant or malignant lesions. Long-term CT surveillance follow-up is needed to manage SSNs that persist for >3 months. Although most SSNs have an indolent clinical course, PSNs may have a more aggressive clinical course than pure GGNs. The proportion of growth and the time to grow is higher and shorter in PSN than pure GGN. In lung adenocarcinoma manifesting as SSNs, EGFR mutations were the major driver mutations. Guidelines are available for the management of incidentally detected and screening-detected SSNs. The size, solidity, location, and number of SSNs are important factors in determining the need for surveillance and surgical resection, as well as the interval of follow-up. Positron emission tomography/CT and brain magnetic resonance imaging (MRI) are not recommended for the diagnosis of SSNs, especially for pure GGNs. Periodic CT surveillance and lung-sparing surgery are the main strategies for the management of persistent SSNs. Nonsurgical treatment options for persistent SSNs include stereotactic body radiotherapy (SBRT) and radiofrequency ablation (RFA). For multifocal SSNs, the timing of repeated CT scans and the need for surgical treatment are decided based on the most dominant SSN(s). Conclusions: The SSN is a heterogeneous disease and a personalized medicine approach is required in the future. Future studies of SSNs should focus on their natural history, optimal follow-up duration, genetic features, and surgical and nonsurgical treatments to improve the corresponding clinical management. All these efforts will lead to the personalized medicine approach for the SSNs.