Ground-glass Nodules Research Articles

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma.

To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. A total of 542 patients with clinical stage 0-I peripheral LUAD and with preoperative CT data of 1-mm slice thickness were included. Maximal solid size on axial image (MSSA) was evaluated by two chest radiologists. MSSA, volume of solid component (SV), and mass of solid component (SM) were evaluated by DL. Consolidation-to-tumor ratios (CTRs) were calculated. For ground glass nodules (GGNs), solid parts were extracted with different density level thresholds. The prognosis prediction efficacy of DL was compared with that of manual measurements. Multivariate Cox proportional hazards model was used to find independent risk factors. The prognosis prediction efficacy of T-staging (TS) measured by radiologists was inferior to that of DL. For GGNs, MSSA-based CTR measured by radiologists (RMSSA%) could not stratify RFS and OS risk, whereas measured by DL using 0HU (2D-AIMSSA0HU%) could by using different cutoffs. SM and SV measured by DL using 0 HU (AISM0HU% and AISV0HU%) could effectively stratify the survival risk regardless of different cutoffs and were superior to 2D-AIMSSA0HU%. AISM0HU% and AISV0HU% were independent risk factors. DL algorithm can replace human for more accurate T-staging of LUAD. For GGNs, 2D-AIMSSA0HU% could predict prognosis rather than RMSSA%. The prediction efficacy of AISM0HU% and AISV0HU% was more accurate than of 2D-AIMSSA0HU% and both were independent risk factors. Deep learning algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma. • Deep learning (DL) algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma (LUAD). • For GGNs, maximal solid size on axial image (MSSA)-based consolidation-to-tumor ratio (CTR) measured by DL using 0 HU could stratify survival risk than that measured by radiologists. • The prediction efficacy of mass- and volume-based CTRs measured by DL using 0 HU was more accurate than of MSSA-based CTR and both were independent risk factors.

Radiomics-based Machine Learning Methods for Volume Doubling Time Prediction of Pulmonary Ground-glass Nodules With Baseline Chest Computed Tomography.

Reliable prediction of volume doubling time (VDT) is essential for the personalized management of pulmonary ground-glass nodules (GGNs). We aimed to determine the optimal VDT prediction method by comparing different machine learning methods only based on the baseline chest computed tomography (CT) images. Seven classical machine learning methods were evaluated in terms of their stability and performance for VDT prediction. The VDT, calculated by the preoperative and baseline CT, was divided into 2 groups with a cutoff value of 400 days. A total of 90 GGNs from 3 hospitals constituted the training set, and 86 GGNs from the fourth hospital served as the external validation set. The training set was used for feature selection and model training, and the validation set was used to evaluate the predictive performance of the model independently. The eXtreme Gradient Boosting showed the highest predictive performance (accuracy: 0.890±0.128 and area under the ROC curve (AUC): 0.896±0.134), followed by the neural network (NNet) (accuracy: 0.865±0.103 and AUC: 0.886±0.097). While regarding stability, the NNet showed the highest robustness against data perturbation (relative SDs [%] of mean AUC: 10.9%). Therefore, the NNet was chosen as the final model, achieving high accuracy of 0.756 in the external validation set. The NNet is a promising machine learning method to predict the VDT of GGNs, which would assist in the personalized follow-up and treatment strategies for GGNs reducing unnecessary follow-up and radiation dose.

Different nodal upstaging rates and prognoses for patients with clinical T1N0M0 lung adenocarcinoma classified according to the presence of solid components in the lung and mediastinal windows.

Little is known about the correlation between nodal upstaging and pulmonary nodules classified according to the presence of solid components in the lung and mediastinal windows. This study thus aimed to analyze the risk factors of nodal upstaging and prognosis based on different imaging features, clinical characteristics, and pathological results from patients with clinical stage T1N0M0 lung adenocarcinoma. A total of 340 patients between January 2016 and June 2017 were selected from the Affiliated Hospital of Qingdao University database. Imaging features, clinical characteristics, and pathological results were collected for survival and analysis of nodal upstaging risk factors. We used logistic regression models to identify important metastatic risk factors for nodal upstaging. Survival rates were calculated using Kaplan-Meier (KM) survival curves and compared with the log-rank test. Significant prognostic risk factors were identified using the Cox proportional hazards model. A total of 340 patients, with an average age of 64.89 (±8.775) years, were enrolled. Among them, nonnodal upstaging occurred both in 77 (22.6%) patients with pure ground-glass nodules (pGGNs) and in 30 (8.8%) patients with heterogenous ground-glass nodules (hGGNs). Compared to the 92 (27.1%) patients with real part-solid nodules (rPSNs), the 141 (41.5%) patients with solid nodules were significantly different in terms of in nodal upstaging (P<0.001). Moreover, preoperative carcinoembryonic antigen (CEA) level >3.4 µg/L [odds ratio (OR): 2.931; 95% confidence interval (CI): 1.511-5.688; P=0.001], imaging tumor size >18.3 mm (OR, 3.482; 95% CI: 1.609-7.535; P=0.002), and consolidation tumor ratio (CTR) >0.788 (OR 8.791; 95% CI: 3.570-21.651; P<0.001) were independent risk factors for nodal upstaging. The KM survival curve results showed that patients with pGGNs and those with hGGNs had a much better 5-year disease-free survival (DFS) and 5-year overall survival (OS) than did those with rPSNs and those with solid nodules (DFS: 98.7% vs. 100% vs. 81.4% vs. 73.7%, P<0.001; OS: 97.4% vs. 100% vs. 90.2% vs. 83.7%, P=0.003). In the multivariate Cox regression analysis of patients with rPSNs and solid nodules, tumor location and pathological lymph node grade were found to be independent risk factors for DFS and OS. Patients with pGGNs and those with hGGNs were more likely to be free of nodal upstaging and had better prognosis than did those with clinical stage IA rPSNs and solid nodules. The patients with pGGNs or hGGNs with preoperative CEA level <3.4 µg/L, imaging tumor size <18.3 mm, and CTR <0.788 can choose systematic lymph node sampling (SLNS) or decline lymph node dissection to avoid postoperative complications.

Proposal of Modified Lung-RADS in Assessing Pulmonary Nodules of Patients with Previous Malignancies: A Primary Study

Background: In addition to the diameters of pulmonary nodules, the number and morphology of blood vessels in pure ground-glass nodules (pGGNs) were closely related to the occurrence of lung cancer. Moreover, the benign and malignant signs of nodules were also valuable for the identification of nodules. Based on these two points, we tried to revise Lung-RADS 2022 and proposed our Modified Lung-RADS. The aim of the study was to verify the diagnostic performance of Modified Lung-RADS for pulmonary solid nodules (SNs) and pure ground-glass nodules (pGGNs) in patients with previous malignancies. Methods: The chest CT and clinical data of patients with prior cancer who underwent pulmonary nodulectomies from 1 January 2018 to 30 November 2021 were enrolled according to inclusion and exclusion criteria. A total of 240 patients with 293 pulmonary nodules were included in this study. In contrast with the original version, the risk classification of pGGNs based on the GGN–vascular relationships (GVRs), and the SNs without burrs and with benign signs, could be downgraded to category 2. The sensitivity, specificity, and agreement rate of the original Lung-RADS 2022 and Modified Lung-RADS for pGGNs and SNs were calculated and compared. Results: Compared with the original version, the sensitivity and agreement rate of the Modified version for pGGNs increased from 0 and 23.33% to 97.10% and 92.22%, respectively, while the specificity decreased from 100% to 76.19%. As regards SNs, the specificity and agreement rate of the Modified version increased from 44.44% to 75.00% (p &lt; 0.05) and 88.67% to 94.09% (p = 0.052), respectively, while the sensitivity was unchanged (98.20%). Conclusions: In general, the diagnostic efficiency of Modified Lung-RADS was superior to that of the original version, and Modified Lung-RADS could be a preliminary attempt to improve Lung-RADS 2022.

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

ObjectiveTo evaluate whether wedge resection (WR) was appropriate for the patients with peripheral T1 N0 solitary subsolid invasive lung adenocarcinoma. MethodsPatients 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. ResultsTwo 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<CTR≤0.5, 5-year recurrence-free survival and lung cancer-specific overall survival were 97.87% and 100% following WR versus 97.73% and 92.86% following segmentectomy (recurrence-free survival: P = .987; lung cancer-specific overall survival: P = .199), respectively. For patients with GGN between 2 and 3 cm and CTR ≤0.5, 5-year recurrence-free survival following WR was significantly lower than that following SEG (90.61% vs 100%; P = .043). Multi-variable Cox regression analysis showed that spread through airspace, visceral pleural invasion, and nerve invasion remained independent risk factors for recurrence of patients with GGN between 2 and 3 cm and CTR ≤0.5 following WR. ConclusionsWR might be appropriate for patients with invasive lung adenocarcinoma appearing as peripheral GGN ≤2 cm and CTR ≤0.5, but inappropriate for those with invasive lung adenocarcinoma appearing as peripheral GGN between 2 and 3 cm and CTR ≤0.5.

Deep convolutional neural network based on CT images of pulmonary nodules in the lungs of adolescent and young adult patients with osteosarcoma.

The aim of the present study was to explore the diagnostic value of a deep convolutional neural network (DCNN) model for the diagnosis of pulmonary nodules in adolescent and young adult patients with osteosarcoma. For the present study, 675 chest CT images were retrospectively collected from 109 patients with clinically confirmed osteosarcoma who underwent chest CT examination at Hangzhou Third People's Hospital (Hangzhou, China) from March 2011 to February 2022. CT images were then evaluated using the DCNN and manual models. Subsequently, pulmonary nodules of osteosarcoma were divided into calcified nodules, solid nodules, partially solid nodules and ground glass nodules using the DCNN model. Those patients with osteosarcoma who were diagnosed and treated were followed up to observe dynamic changes in the pulmonary nodules. A total of 3,087 nodules were detected, while 278 nodules were missed compared with those determined using the reference standard given by the consensus of three Experienced radiologists., which was analyzed by two diagnostic radiologists. In the manual model group, 2,442 nodules were detected, while 657 nodules were missed. The DCNN model showed significantly higher sensitivity and specificity compared with the manual model (sensitivity, 0.923 vs. 0.908; specificity, 0.552 vs. 0.351; P<0.05). In addition, the DCNN model yielded an area under the curve (AUC) value of 0.795 [95% confidence interval (CI), 0.743-0.846], outperforming that of the manual model (AUC, 0.687; 95% CI, 0.629-0.732; P<0.05). The film reading time of the DCNN model was also significantly shorter compared with that of the manual model [mean ± standard deviation (SD); 173.25±24.10 vs. 328.32±22.72 sec; P<0.05)]. The AUC of calcified nodules, solid nodules, partially solid nodules and ground glass nodules was calculated to be 0.766, 0.771, 0.761 and 0.796, respectively, using the DCNN model. Using this model, the majority of the pulmonary nodules were detected in patients with osteosarcoma at the initial diagnosis (69/109, 62.3%), and the majority of these were found with multiple pulmonary nodules instead of a single nodule (71/109, 65.1% vs. 38/109, 34.9%). These data suggest that, compared with the manual model, the DCNN model proved to be beneficial for the detection of pulmonary nodules in adolescent and young adult patients with osteosarcoma, which may reduce the time of artificial radiograph reading. In conclusion, the proposed DCNN model, developed using data from 675 chest CT images retrospectively collected from 109 patients with clinically confirmed osteosarcoma, may be used as an effective tool to evaluate pulmonary nodules in patients with osteosarcoma.

The Prognostic Impact of Epidermal Growth Factor Receptor Mutation in Clinical Stage I Lung Adenocarcinoma

This study investigated the prognostic impact of epidermal growth factor receptor (EGFR) mutation in clinical stage I lung adenocarcinoma patients. Data for 952 patients who received surgical resection and underwent detection of oncogenic driver mutations were retrospectively collected. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared using the log-rank test. The adjusted hazard ratio (aHR) with 95% CI of the prognosticator was calculated by Cox proportional hazards model, and cumulative incidence function was measured by competing risk regression model. EGFR mutation was detected in 581 patients (61.0%) and was more frequent in women (63.9%), nonsmokers (85.5%), and those with ground-glass nodules (GGNs; 56.6%). EGFR mutation was not associated with recurrence and death in the entire cohort or GGN cohort. However, for patients with radiologic pure-solid appearance, EGFR mutation was an independent risk factor for RFS (aHR, 1.623; 95% CI, 1.192-2.210) and distant recurrence (aHR, 1.863; 95% CI, 1.311-2.650), but not OS. Subsequently, subgroup analysis based on EGFR mutation subtypes, including exon 19 deletions (19-Del), exon 21 L858R substitution (L858R), and rare mutations in patients with radiologic pure-solid appearance, revealed that all 3 subtypes have poorer RFS (19-Del: aHR, 1.424; 95% CI, 0.991-2.047; L858R: aHR, 1.708; 95% CI, 1.172-2.490; rare mutations: aHR, 2.500; 95% CI, 1.400-4.465) and higher prevalent distant recurrence (19-Del: aHR, 1.595; 95% CI, 1.061-2.400; L858R: aHR, 2.073; 95% CI, 1.371-3.140; rare mutations: aHR, 2.657; 95% CI, 1.397-5.050) compared with wild-type. In clinical stage I lung adenocarcinoma, EGFR mutation was associated with worse RFS and higher prevalent distant recurrence in patients with radiologic pure-solid appearance but not in patients with GGN.

Differentiation Between Heterogeneous GGN and Part-Solid Nodule Using 2 D Grayscale Histogram Analysis of Thin-Section CT Image

Introduction/BackgroundTo evaluate cases of surgically resected pulmonary adenocarcinoma (Ad) with heterogenous ground-glass nodules (HGGNs) or part-solid nodules (PSNs) and to clarify the differences between them, and between invasive adenocarcinoma (IVA) and minimally invasive adenocarcinoma (MIA) + adenocarcinoma in situ (AIS) using grayscale histogram analysis of thin-section computed tomography (TSCT). Materials and Methods241 patients with pulmonary Ad were retrospectively classified into HGGNs and PSNs on TSCT by three thoracic radiologists. Sixty HGGNs were classified into 17 IVAs, 26 MIAs, and 17 AISs. 181 PSNs were classified into 114 IVAs, 55 MIAs, and 12 AISs. ResultsWe found significant differences in area (P = 0.0024), relative size of solid component (P <0.0001), circumference (P <0.0001), mean CT value (P <0.0001), standard deviation of the CT value (P <0.0001), maximum CT value (P <0.0001), skewness (P <0.0001), kurtosis (P <0.0001), and entropy (P <0.0001) between HGGNs and PSNs. In HGGNs, we found significant differences in relative size of solid component (P <0.0001), mean CT value (P = 0.0005), standard deviation of CT value (P = 0.0071), maximum CT value (P = 0.0237), and skewness (P = 0.0027) between IVAs and MIA+AIS lesions. In PSNs, we found significant differences in area (P = 0.0029), relative size of solid component (P = 0.0003), circumference (P = 0.0004), mean CT value (P = 0.0011), skewness (P = 0.0009), and entropy (P = 0.0002) between IVAs and the MIA+AIS lesions. ConclusionQuantitative evaluations using grayscale histogram analysis can clearly distinguish between HGGNs and PSNs, and may be useful for estimating the pathology of such lesions.

Video-Assisted Thoracic Surgery Without Intraoperative Fluoroscopy After Microcoil Localization

BackgroundSmall nodules and ground-glass opacities can present a challenge when surgeons rely on direct visualization or digital palpation. Preoperative localization improves nodule detection. We aimed to determine the efficacy and safety of video-assisted thoracoscopic surgery (VATS) nodulectomy without intraoperative fluoroscopy after computed tomography (CT)–guided microcoil localization of peripheral pulmonary nodules. MethodsThe cases of 147 consecutive patients (152 nodules) who underwent CT-guided microcoil localization (157 coils) followed by same-day VATS resection between 2016 and 2021 were retrospectively reviewed, and descriptive statistics were reported. ResultsAll 152 nodules (mean size, 13.5 ± 6.1 mm; mean distance to pleura, 4.2 ± 5.5 mm; 82 [54%] ground-glass nodules, 34 [22%] part-solid nodules) in study patients (mean age, 64.6 ± 11.8 years) were successfully resected. The technical success rate of percutaneous nodule localization with pleural tagging was 96% (150/157); the surgical efficacy of VATS nodulectomy without intraoperative fluoroscopy was 98% (149/152). Twelve patients (8%) required chest tubes after localization. Pathologic examination identified 24 benign and 123 malignant nodules, including 85 primary lung cancers. ConclusionsCT-guided microcoil localization with pleural tagging is safe and effective and obviates the need for intraoperative fluoroscopy.

Preliminary results from the Female Asian Nonsmoker Screening Study (FANSS).

8510 Background: Lung cancer (LC) is the leading cause of cancer death in Asian Americans and unfortunately the majority are diagnosed at advanced or late stages. In Asia, approximately 60-80% of female LC patients are never smokers. Current screening in the U.S. with low-dose CT (LDCT) Chest scans is offered only to current or former smokers based on the National Lung Screening Trial (NLST). The LC detection rate in NLST was 1.1%. The TALENT study, a LC screening study for high-risk nonsmokers in Taiwan reported a LC detection rate of 2.6% which included invasive adenocarcinoma (adeno), adeno in situ, minimally invasive adeno and adenosquamous carcinoma. Invasive adeno detection rate was 1.52%. We are conducting the ongoing FANSS in the U.S. to screen female Asian nonsmokers with LDCT Chest scans to evaluate the feasibility of a LC screening program in this population. We report preliminary results here. Methods: This is an IRB-approved, prospective, multicenter study (NYU, MGH, UCI). Inclusion criteria are women, age between 40-74 years old (yo), never smoked or smoked &lt;100 cigarettes in one's lifetime and identify as from Asian descent (report ancestry or race from the continent of Asia). Participants (pts) with history of LC or treatment of any cancer &lt;5 years ago are excluded. Following informed consent, eligible pts undergo a shared-decision making discussion prior to obtaining a baseline LDCT Chest scan, read according to Lung-RADS 1.1 with plan for annual LDCT for two additional years. A plasma-based assay to analyze cell-free DNA (cfDNA) fragments for early detection of cancer by Delfi Diagnostics (Baltimore, MD) is sent at the time of each scan. A questionnaire regarding ethnicity, family history and environmental exposures is collected at baseline. Results: From 3/1/21 to 1/15/23, 222 pts signed consent and 201 had a baseline LDCT at NYU. Age range was 40-74 yo and median age of 56.8 yo. 83 (41%) reported a family history of LC. Of 201 pts who completed a baseline LDCT, 87 (43%) were Lung-RADS 1, 101 (50%) were Lung-RADS 2, 6 (3%) were Lung-RADS 3 and 7 (3.5%) were Lung-RADS 4. 5 pts with Lung-RADS 3 and 3 pts with Lung-RADS 4 have solid, subsolid or groundglass nodules &gt;6mm that remain in close follow-up. 3 pts were diagnosed with invasive lung adeno for a LC detection rate of 1.5%; 2 are stage IIB and 1 is stage IIIC. All pts were surgically resected, EGFR mutation positive and are receiving adjuvant osimertinib. Analysis of the cfDNA fragmentation profiles is ongoing. Conclusions: Our data shows that LC screening in Asian female nonsmokers is feasible. Preliminary results demonstrate an invasive adeno detection rate comparable with TALENT and higher than in NLST. Early detection brings new meaning with the recent FDA approval for adjuvant targeted therapy in early stage LC. The expansion of LC screening guidelines to other high-risk populations warrants further attention. FANSS is continuing to accrue at additional U.S. sites this year. Clinical trial information: NCT05164757 .

Diagnostic performance and safety of percutaneous fine-needle aspiration immediately before microwave ablation for pulmonary ground-glass nodules.

This study sought to evaluate the safety and diagnostic performance of computed tomography (CT)-guided fine-needle aspiration (FNA) immediately before microwave ablation (MWA) for pulmonary ground-glass nodules (GGNs). This retrospective study analyzed the synchronous CT-guided biopsy and MWA data of 92 GGNs (male to female ratio 37:55; age 60.4±12.5 years; size 1.4±0.6 cm). FNA was performed in all patients, and sequential core-needle biopsy (CNB) was performed in 62 patients. The positive diagnosis rate was determined. The diagnostic yield was compared on the basis of the biopsy methods (FNA, CNB, or both), the nodule diameter (<1.5 and ≥1.5 cm), and the lesion component (pure GGN or part-solid GGN). The procedure-related complications were recorded. The technical success rate was 100%. The positive rates of FNA and CNB were 70.7% and 72.6% respectively, but did not differ significantly (P=0.8). Sequential FNA and CNB showed better diagnostic performance (88.7%) than did either alone (P=0.008 and P=0.023, respectively). The diagnostic yield of CNB for pure GGNs was significantly lower than that for part-solid GGNs (P=0.016). The diagnostic yield was lower for smaller nodules (78.3% vs. 87.5%; P=0.28), but the differences were not significant. Grade 1 pulmonary hemorrhages were observed in 10 (10.9%) sessions after FNA, including 8 cases of hemorrhage along the needle track and 2 cases of perilesional hemorrhage, but these hemorrhages did not hamper the accuracy of the antenna placement. FNA immediately before MWA is a reliable technique for the diagnosis of GGNs that does not alter the accuracy of the antenna placement. Sequential FNA and CNB improves the diagnostic ability of GGNs compared to either method used alone.

Growth assessment of pure ground-glass nodules on CT: comparison of density and size measurement methods.

To investigate the differences of size and density measurements in assessing pure ground-glass nodules (pGGNs) growth, and compare the growth rates and growth proportions of the two methods during follow-up period. Ninety patients with at least 3 consecutive thin-section chest CTs and confirmed 103 pGGNs on baseline CT were enrolled retrospectively. Using the two definitions of size and density to evaluate pGGNs growth with semi-automated segmentation. Then, the two methods were compared to assess differences in pGGNs growth. For the size and density methods to assess nodule growth, 50.5% and 26.2% showed interval growth at the last CT (p < 0.001). Among the 19 nodules that grew in both size and density, the volume doubling time (VDT) of solid component (mean, 317.1; standard deviation, 224.8days) was shorter than total VDT (median, 942.8; range, 400.1-2315.9days) (p < 0.001). Of the 27 growth pGGNs assessed by the density method, the growth rates at years 1 and 2 were 25.9% and 63.0%, while the growth rates of 52 growing nodules assessed by size method were 11.5% and 48.1%, respectively. Twenty of 103 (19.4%) nodules were classified into category 4A lesions, and 7 (6.8%) were 4B lesions. Compared to size measurements, observed density increases have a higher proportion of early growth and faster growth rates in growing nodules. Clinicians need to pay close attention to the nodules of new solid components and make timely decision management.

European guidelines for the surgical management of pure ground-glass opacities and part-solid nodules: Task Force of the European Association of Cardio-Thoracic Surgery and the European Society of Thoracic Surgeons.

Pulmonary nodules are often encountered by respiratory physicians, radiologists, and thoracic surgeons alike. The European Society of Thoracic Surgery (ESTS) and European Association of Cardiothoracic Surgery (EACTS) established a multidisciplinary collaboration of clinicians with expertise in managing pulmonary nodules with the aim of producing the first joint comprehensive review of the scientific literature, with a specific focus on the management of pure ground glass opacities and part-solid nodules. The scope of the document has been defined by the EACTS and ESTS governing bodies and focuses on six areas of main interest agreed upon by the Task Force. These include: management of solitary and multiple pure ground glass nodules, solitary part-solid nodules, identifying the non-palpable lesion, the role of minimally invasive surgery and the decision making behind sub-lobar versus lobar resection. The literature revealed that with the increasing use of incidental CT scans and CT lung cancer screening programs, the detection of early-stage lung cancer is going to rise with a higher number of potential cancers presenting on the ground glass and part-solid nodule spectrum. Given that the gold standard for improved survival is surgical resection, there is an urgent need for comprehensive characterisation of these nodules and guidelines that are directed towards their surgical management. It is recommended that standard decision-making tools are used to determine the risk of malignancy and thus guide referral for surgical management and decisions for surgical resection are made in a multidisciplinary setting with equitable consideration given to radiological characteristics, the evolution of the lesion, presence of solid component, patient fitness and co-morbidities. Given the recent surge in robust level I data comparing sublobar and lobar resection with the release of JCOG0802 and CALGB140503 data, a global overview of an individual case must be adopted into clinical practice. This set of recommendations are based on the available literature; however, close collaboration in the design and conduct of randomized controlled trials is still of utmost importance to answer further questions in this rapidly evolving field.

Mutation of TP53 Confers Ferroptosis Resistance in Lung Cancer Through the FOXM1/MEF2C Axis

Ferroptosis is a highly regulated tumor suppressor process. Loss or mutation of TP53 can cause changes in sensitivity to ferroptosis. Mutations in TP53 may be associated with the malignant or indolent progression of ground glass nodules in early lung cancer, but whether ferroptosis may also be involved in determining this biological process has not yet been determined. Using invivo and invitro gain- and loss-of-function approaches, this study used clinical tissue for mutation analysis and pathological research to show that wild-type TP53 inhibited the expression of forkhead box M1 (FOXM1) by binding to peroxisome proliferator-activated receptor-γ coactivator 1α, maintaining the mitochondrial function and thus affecting the sensitivity to ferroptosis. This function was absent in mutant cells, resulting in overexpression of FOXM1 and ferroptosis resistance. Mechanistically, FOXM1 activated the transcription level of myocyte-specific enhancer factor 2C in the mitogen-activated protein kinase signaling pathway, leading to stress protection when exposed to ferroptosis inducers. This study provides new insights into the mechanism of association between TP53 mutation and ferroptosis tolerance, which can aid a deeper understanding of the role of TP53 in the malignant progression of lung cancer.

Establishment and Verification of Benign and Malignant Prediction Model of Subcentimeter Pulmonary Ground Glass Nodules Based on HRCT

Pre-operative accuracy of subcentimeter ground glass nodules (SGGNs) is a difficult problem in clinical practice, but there are few clinical studies on the benign and malignant prediction model of SGGNs. The aim of this study was to help identify benign and malignant lesions of SGGNs based on the imaging features of high resolution computed tomography (HRCT) and the general clinical data of patients, and to build a risk prediction model. This study retrospectively analyzed the clinical data of 483 patients with SGGNs who underwent surgical resection and were confirmed by histology from the First Affiliated Hospital of University of Science and Technology of China from August 2020 to December 2021. The patients were divided into the training set (n=338) and the validation set (n=145) according to 7:3 random assignment. According to the postoperative histology, they were divided into adenocarcinoma group and benign lesion group. The independent risk factors and models were analyzed by univariate analysis and multivariate Logistic regression. The receiver operator characteristic (ROC) curve was constructed to evaluate the model differentiation, and the calibration curve was used to evaluate the model consistency. The clinical application value of the decision curve analysis (DCA) evaluation model was drawn, and the validation set data was substituted for external verification. Multivariate Logistic analysis screened out patients' age, vascular sign, lobular sign, nodule volume and mean-CT value as independent risk factors for SGGNs. Based on the results of multivariate analysis, Nomogram prediction model was constructed, and the area under ROC curve was 0.836 (95%CI: 0.794-0.879). The critical value corresponding to the maximum approximate entry index was 0.483. The sensitivity was 76.6%, and the specificity was 80.1%. The positive predictive value was 86.5%, and the negative predictive value was 68.7%. The benign and malignant risk of SGGNs predicted by the calibration curve was highly consistent with the actual occurrence risk after sampling 1,000 times using Bootstrap method. DCA showed that patients showed a positive net benefit when the predictive probability of the predicted model probability was 0.2 to 0.9. Based on preoperative medical history and preoperative HRCT examination indicators, the benign and malignant risk prediction model of SGGNs was established to have good predictive efficacy and clinical application value. The visualization of Nomogram can help to screen out high-risk groups of SGGNs, providing support for clinical decision-making.

Watershed analysis in wedge resection of pulmonary pure ground-glass nodules hardly localized by CT-guided puncture

BackgroundTo investigate the feasibility and safety of watershed analysis after target pulmonary vascular occlusion for the wedge resection in patients with non-palpable and non-localizable pure ground-glass nodules during uniport thoracoscopic surgery.MethodsA total of 30 patients with pure ground-glass nodules < 1 cm in diameter, localized in the lateral third of the lung parenchyma, were enrolled. Three-dimensional reconstruction of thin-section computed tomography (CT) data was performed using Mimics software before surgery to observe and identify the target pulmonary vessels supplying the lung tissue in the area where the pulmonary nodules were localized and to temporarily block the target pulmonary vessels during surgery. Next, the extent of the watershed was determined with the expansion-collapse method, and finally, wedge resection was performed. After wedge resection of the target lung tissue, the blocked pulmonary vessel was released, thus allowing operators to complete the procedure without damaging pulmonary vessels.ResultsNone of the patients experienced postoperative complications. The chest CT of all patients was reviewed six months after the operation, revealing no tumor recurrence.ConclusionsOur results suggest that watershed analysis following target pulmonary vascular occlusion for wedge resection in pulmonary pure ground-glass nodules is a safe and feasible approach.

A semiautomated radiomics model based on multimodal dual-layer spectral CT for preoperative discrimination of the invasiveness of pulmonary ground-glass nodules.

In recent years, spectral computed tomography (CT) has shown excellent performance in the diagnosis of ground-glass nodules (GGNs) invasiveness; however, no research has combined spectral multimodal data and radiomics analysis for comprehensive analysis and exploration. Therefore, this study goes a step further on the basis of the previous research: to investigate the value of dual-layer spectral CT-based multimodal radiomics in accessing the invasiveness of lung adenocarcinoma manifesting as GGNs. In this study, 125 GGNs with pathologically confirmed preinvasive adenocarcinoma (PIA) and lung adenocarcinoma were divided into a training set (n=87) and a test set (n=38). Each lesion was automatically detected and segmented by the pre-trained neural networks, and 63 multimodal radiomic features were extracted. The least absolute shrinkage and selection operator (LASSO) was used to select target features, and a rad-score was constructed in the training set. Logistic regression analysis was conducted to establish a joint model which combined age, gender, and the rad-score. The diagnostic performance of the two models was compared by the receiver operating characteristic (ROC) curve and precision-recall curve. The difference between the two models was compared by the ROC analysis. The test set was used to evaluate the predictive performance and calibrate the model. Five radiomic features were selected. In the training and test sets, the area under the curve (AUC) of the radiomics model was 0.896 (95% CI: 0.830-0.962) and 0.881 (95% CI: 0.777-0.985) respectively, and the AUC of the joint model was 0.932 (95% CI: 0.882-0.982) and 0.887 (95% CI: 0.786-0.988) respectively. There was no significant difference in AUC between the radiomics model and joint model in the training and test sets (0.896 vs. 0.932, P=0.088; 0.881 vs. 0.887, P=0.480). Multimodal radiomics based on dual-layer spectral CT showed good predictive performance in differentiating the invasiveness of GGNs, which could assist in the decision of clinical treatment strategies.

The influence of different previous cancer histories on the diagnostic efficacy of Lung Imaging Reporting and Data System.

For lung cancer screening in patients with previous malignant tumors, Lung Imaging Reporting and Data System (Lung-RADS) and other lung cancer screening tools are controversial in terms of requirements for the previous cancer history. This study investigated the effect of the length and type of malignancy history on the diagnostic efficacy of Lung Imaging Reporting and Data System (Lung-RADS) 2022 in pulmonary nodules (PNs). Chest computed tomography and clinical data of PNs in patients with a history of cancer who underwent surgical resection in The First Affiliated Hospital of Chongqing Medical University from January 1, 2018, to November 30, 2021, were retrospectively collected and evaluated based on Lung-RADS. All PNs were divided into 2 groups: the prior lung cancer (PLC) and the prior extrapulmonary cancer (PEPC) groups. Each group was divided into the ≥5 years and <5 years groups based on the duration of cancer history. The diagnostic agreement of Lung-RADS was evaluated based on the pathological diagnosis of nodules after operation. The diagnostic agreement rate (AR) of Lung-RADS and the composition ratios of different types between different groups were calculated and compared. A total of 451 patients with 565 PNs were included in this study. These patients were divided into the PLC group (<5 years: 135 cases, 175 PNs; ≥5 years: 9 cases, 12 PNs) and the PEPC group (<5 years: 219 cases, 278 PNs; ≥5 years: 88 cases, 100 PNs). The diagnostic AR of partial solid nodules (93.0%; 95% CI: 88.7-97.2%) and solid nodules (88.1%; 95% CI: 84.1-92.1%) was close (P=0.13), while both were higher than that of the pure ground-glass nodules (24.0%; 95% CI: 17.5-30.4%; all P values <0.001). Within 5 years, the composition ratio of PNs and the diagnostic AR (PLC: 58.9%, 95% CI: 51.5-66.2%; PEPC: 76.6%, 95% CI: 71.6-81.6%) between the PLC and PEPC groups were all different (all P values <0.001), and the others [composition ratio of PNs & the diagnostic AR: PLC (≥5 years) vs. PEPC (≥5 years); PLC (<5 years) vs. PLC (≥5 years); PEPC (<5 years) vs. PEPC (≥5 years)] were similar (all P values >0.05; range: 0.10-0.93). The length of prior cancer history may affect the diagnostic agreement of Lung-RADS, especially for patients with prior lung cancer within 5 years.

Thin-slice computed tomography enables to classify pulmonary subsolid nodules into pre-invasive lesion/minimally invasive adenocarcinoma and invasive adenocarcinoma: a retrospective study

The aim was to investigate the ability of thin-slice computed tomography (TSCT) to differentiate invasive pulmonary adenocarcinomas (IACs) from pre-invasive/minimally invasive adenocarcinoma (AAH-MIAs), manifesting as subsolid nodules (SSNs) of diameter less than 30 mm. The CT findings of 810 patients with single subsolid nodules diagnosed by pathology of resection specimens were analyzed (atypical adenomatous hyperplasia, n = 13; adenocarcinoma in situ, n = 175; minimally invasive adenocarcinoma, n = 285; and invasive adenocarcinoma, n = 337). According to the classification of lung adenocarcinoma published by WHO classification of thoracic tumors in 2015, TSCT features of 368 pure ground-glass nodules (pGGN) and 442 part-solid nodules (PSNs) were compared AAH-MIAs with IACs. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed. In pGGNs, multivariate analysis of factors found to be significant by univariate analysis revealed that higher mean-CT values (p = 0.006, OR 1.006, 95% CI 1.002–1.010), larger tumor size (p < 0.001, OR 1.483, 95% CI 1.304–1.688) with air bronchogram and non-smooth margins were significantly associated with IACs. The optimal cut-off tumor diameter for AAH-MIAs lesions was less than 10.75 mm (sensitivity, 82.8%; specificity, 80.6%) and optimal cut-off mean-CT value − 629HU (sensitivity, 78.1%; specificity, 50.7%). In PSNs, multivariate analysis of factors found to be significant by univariate analysis revealed that smaller tumor diameter (p < 0.001, OR 0.647, 95% CI 0.481–0.871), smaller size of solid component (p = 0.001, OR 83.175, 95% CI 16.748–413.079),and lower mean-CT value of solid component (p < 0.001, OR 1.009, 95% CI 1.004–1.014) were significantly associated with AAH-MIAs (p < 0.05). The optimal cut-off tumor diameter, size of solid component, and mean-CT value of solid component for AAH-MIAs lesions were less than 14.595 mm (sensitivity, 71.1%; specificity, 83.4%), 4.995 mm (sensitivity, 97.8%; specificity, 92.3%) and − 227HU (sensitivity, 65.6%; specificity, 76.3%), respectively. In subsolid nodules, whether pGGN or PSNs, the characteristics of TSCT can help in distinguishing IACs from AAH-MIAs.

Growth Regularity of Pulmonary Ground Glass Nodules Based on 3D Reconstruction Technology

Since the popularization of computed tomography (CT) technology, the detection rate of pulmonary ground glass nodules (GGNs) with imaging follow-up as the main management method has increased significantly. The purpose of this study is to quantitatively analyze the changes of pulmonary GGNs during the follow-up process with three-dimensional reconstruction technology, explore the natural progression of pulmonary GGNs, and provide effective basis for clinical guidance for patients to conduct reasonable management of nodules. A total of 115 cases of pulmonary GGNs with regular follow-up in the Combined Outpatient Department of Zhoushan Hospital from March 2015 to November 2022 were enrolled. Quantitative imaging features of nodules were extracted by semi-automatic segmentation of 3D Slicer software to evaluate the growth of nodules and clinical intervention during follow-up. The average baseline age of the patients was (56.9±10.1) yr. The mean follow-up time was (48.8±18.9) months. The two-dimensional diameter of baseline CT scan was (7.9±2.9) mm, and the maximum three-dimensional diameter was (10.1±3.4) mm. The two-dimensional diameter of the last CT scan was (9.9±4.7) mm, and the maximum three-dimensional diameter was (11.4±5.1) mm. A total of 27 cases (23.5%) showed an increase during follow-up, with a median volume doubling time of 822 days and a median mass doubling time of 1,007 days. 32 cases were surgically resected, including 6 cases of invasive adenocarcinoma (IAC), 16 cases of minimally invasive adenocarcinoma (MIA), 8 cases of adenocarcinoma in situ (AIS) and 2 cases of atypical adenomatous hyperplasia (AAH). Five nodules underwent surgical intervention due to the progression of two-dimensional diameter, which was pathologically confirmed as pre-invasive lesions, but their three-dimensional maximum diameter showed no significant change. Nodular morphology, lobulated sign, spiculated sign and vacuole signs all promoted the growth of nodules in univariate analysis. There were significant differences in age, baseline diameter, mean CT value, median CT value, 10% and 90% percentile CT number between the growth group and the stable group (P<0.05). Multivariate Logistic regression analysis showed that age and average CT value were risk factors for nodule growth (P<0.05). Receiver-operating characteristic (ROC) curve analysis results indicated that the age ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU were more likely to accelerate the growth of GGNs. The maximum three-dimensional diameter ≥14.4 mm and the average CT value ≥-495.7 HU may be a higher malignant probability. GGNs show an inert growth process, and the use of three-dimensional measurements during follow-up is of greater significance. For persistent glass grinding nodules ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU are more likely to increase. However, most nodules still have good prognosis after progression, and long-term follow-up is safe.