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Objectives: The purpose of this study was to develop and validate a new feature fusion algorithm to improve the classification performance of benign and malignant ground-glass nodules (GGNs) based on deep learning. Methods: We retrospectively collected 385 cases of GGNs confirmed by surgical pathology from three hospitals. We utilized 239 GGNs from Hospital 1 as the training and internal validation set, and 115 and 31 GGNs from Hospital 2 and Hospital 3, respectively, as external test sets 1 and 2. Among these GGNs, 172 were benign and 203 were malignant. First, we evaluated clinical and morphological features of GGNs at baseline chest CT and simultaneously extracted whole-lung radiomics features. Then, deep convolutional neural networks (CNNs) and backpropagation neural networks (BPNNs) were applied to extract deep features from whole-lung CT images, clinical, morphological features, and whole-lung radiomics features separately. Finally, we integrated these four types of deep features using an attention mechanism. Multiple metrics were employed to evaluate the predictive performance of the model. Results: The deep learning model integrating clinical, morphological, radiomics and whole lung CT image features with attention mechanism (CMRI-AM) achieved the best performance, with area under the curve (AUC) values of 0.941 (95% CI: 0.898-0.972), 0.861 (95% CI: 0.823-0.882), and 0.906 (95% CI: 0.878-0.932) on the internal validation set, external test set 1, and external test set 2, respectively. The AUC differences between the CMRI-AM model and other feature combination models were statistically significant in all three groups (all p<0.05). Conclusion: Our experimental results demonstrated that (1) applying attention mechanism to fuse whole-lung CT images, radiomics features, clinical, and morphological features is feasible, (2) clinical, morphological, and radiomics features provide supplementary information for the classification of benign and malignant GGNs based on CT images, and (3) utilizing baseline whole-lung CT features to predict the benign and malignant of GGNs is an effective method. Therefore, optimizing the fusion of baseline whole-lung CT features can effectively improve the classification performance of GGNs. [ABSTRACT FROM AUTHOR]

Background and Objective Methods Results Conclusion Radiofrequency ablation (RFA) is an emerging treatment of lung cancer, yet it is accompanied by certain safety concerns and operational limitations. This first multi‐centre, large‐scale clinical trial aimed to investigate the technical performance, efficacy and safety of an innovative transbronchial RFA system for lung tumours.The study enrolled patients with malignant lung tumours who underwent transbronchial RFA using an automatic saline microperfusion system between January 2021 and December 2021 across 16 medical centres. The primary endpoint was the complete ablation rate. The performance and safety of the technique, along with the 1‐year survival rates, were evaluated.This study included 126 patients (age range: 23–85 years) with 130 lung tumours (mean size: 18.77 × 14.15 mm) who had undergone 153 transbronchial RFA sessions, with a technique success rate of 99.35% and an average ablation zone size of 32.47 mm. At the 12‐month follow‐up, the complete ablation rate and intrapulmonary progression‐free survival rates were 90.48% and 88.89%, respectively. The results of patients with ground‐glass nodules (GGNs) were superior to those of the patients with solid nodules (12‐month complete ablation rates: solid vs. pure GGN vs. mixed GGN: 82.14% vs. 100% vs. 96.08%, p = 0.007). No device defects were reported. Complications such as pneumothorax, haemoptysis, pleural effusion, pulmonary infection and pleural pain were observed in 3.97%, 6.35%, 8.73%, 11.11% and 10.32% of patients, respectively. Two subjects died during the follow‐up period.Transbronchial RFA utilizing an automatic saline microperfusion system is a viable, safe and efficacious approach for the treatment for lung tumours, particularly for patients with GGNs. [ABSTRACT FROM AUTHOR]

Objective: The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC. Methods: Thirty‐five patients with ground‐glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole‐exome sequencing (WES) and transcriptome sequencing (RNA‐Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA‐Seq were subsequently analyzed. Results: The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co‐mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD. Conclusions: Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recent advancements in computed tomography (CT) scanning have improved the detection rates of peripheral pulmonary nodules, including those with ground-glass opacities (GGOs). This study focuses on part-solid pure ground-glass nodules (GGNs) and aims to identify imaging predictors that can reliably differentiate primary lung cancer from nodules with other diagnoses among part-solid GGNs on highresolution CT (HRCT). A retrospective study was conducted on 609 patients who underwent surgical treatment or observation for lung nodules. Radiological findings from pre-operative HRCT scans were reviewed and several CT imaging features of part-solid GGNs were examined for their positive predictive value to identify primary lung cancer. The proportions of the nodules with a final diagnosis of primary lung cancer were significantly higher in part-solid GGNs (91.9%) compared with solid nodules (70.3%) or pure GGNs (66.7%). Among CT imaging features of part-solid GGNs that were evaluated, consolidation-totumor ratio (CTR) < 0.5 (98.1%), pleural indentation (96.4%), and clear tumor border (96.7%) had high positive predictive value to identify primary lung cancer. When two imaging features were combined, the combination of CTR < 0.5 and a clear tumor border was identified to have 100% positive predictive values with a sensitivity of 40.8%. Thus we conclude that part-solid GGNs with a CTR < 0.5 accompanied by a clear tumor border evaluated by HRCT are very likely to be primary lung cancers with an acceptable sensitivity. Preoperative diagnostic procedures to obtain a pathological diagnosis may potentially be omitted in patients harboring such part-solid GGNs. [ABSTRACT FROM AUTHOR]

Abstract Purpose Intraoperative frozen section pathology (FS) is widely used to guide surgical strategies while the accuracy is relatively low. Underestimating the pathological condition may result in inadequate surgical margins. This study aims to identify CT imaging features related to upgraded FS and develop a predictive model. Methods Collected data from 860 patients who underwent lung surgery from January to December 2019. We analyzed the consistency rate of FS and categorized the patients into three groups: Group 1 (n = 360) had both FS and Formalin-fixed Paraffin-embedded section (FP) as non-invasive adenocarcinoma (IAC); Group 2 (n = 128) had FS as non-IAC but FP as IAC; Group 3 (n = 372) had both FS and FP as IAC. Clinical baseline characteristics were compared and propensity score adjustment was used to mitigate the effects of these characteristics. Univariate analyses identified imaging features with inter-group differences. A multivariate analysis was conducted to screen independent risk factors for FS upgrade, after which a logistic regression prediction model was established and a receiver operating characteristic (ROC) curve was plotted. Results The consistency rate of FS with FP was 84.19%. 26.67% of the patients with non-IAC FS diagnosis were upgraded to IAC. The predictive model’s Area Under Curve (AUC) is 0.785. Consolidation tumor ratio (CTR) ≤ 0.5 and smaller nodule diameter are associated with the underestimation of IAC in FS. Conclusion CT imaging has the capacity to effectively detect patients at risk of upstaging during FS.

Abstract Multiple primary lung cancers (MPLCs) are becoming more and more common and these patients can benefit from minimally invasive surgery. Here, we report a case of a patient diagnosed with synchronous MPLCs who underwent bilateral thoracoscopic pulmonary resections in a two‐stage strategy, and achieved a good surgical outcome and high quality of life. A 66‐year‐old female was found to have one major ground‐glass nodule (GGN) in the right upper lobe and eight minor GGNs in the left upper and lower lobes. The patient underwent right upper lobe resection and systematic mediastinal lymph node dissection via single‐utility port thoracoscopic surgery in September 2018. Pathology was lepidic predominant adenocarcinoma pT1bN0M0, IA2. Regular high‐resolution computed tomography examination during 36 months after right upper lobectomy showed gradually increasing diameter and solid component of multiple GGNs in left lung. The patient underwent thoracoscopic multiple pulmonary resections using an intraoperative localization technique in a hybrid operating room in October 2021 and all eight nodules in the left lung were resected. Two segmentectomies and four wedge resections were performed, and the pathological results of the eight nodules included four adenocarcinomas, three adenocarcinomas in situ, and one alveolar epithelial hyperplasia. The two operations were successful with no intra‐ or postoperative 90‐day complications. During more than 20 months of follow‐up after the second operation, the patient had well recovered pulmonary function and physical status with a Karnofsky performance status score of 90 and no local recurrence or metastasis. A two‐stage surgical strategy for synchronous MPLCs is therefore feasible. The surgical strategy, timing of intervention, and extent of pulmonary resection should be individually designed according to the location and characteristics of each nodule. Intraoperative localization of small GGNs is very important to ensure that all nodules are completely and accurately resected during the operation.

Multiple primary lung cancers (MPLCs) are becoming more and more common and these patients can benefit from minimally invasive surgery. Here, we report a case of a patient diagnosed with synchronous MPLCs who underwent bilateral thoracoscopic pulmonary resections in a two‐stage strategy, and achieved a good surgical outcome and high quality of life. A 66‐year‐old female was found to have one major ground‐glass nodule (GGN) in the right upper lobe and eight minor GGNs in the left upper and lower lobes. The patient underwent right upper lobe resection and systematic mediastinal lymph node dissection via single‐utility port thoracoscopic surgery in September 2018. Pathology was lepidic predominant adenocarcinoma pT1bN0M0, IA2. Regular high‐resolution computed tomography examination during 36 months after right upper lobectomy showed gradually increasing diameter and solid component of multiple GGNs in left lung. The patient underwent thoracoscopic multiple pulmonary resections using an intraoperative localization technique in a hybrid operating room in October 2021 and all eight nodules in the left lung were resected. Two segmentectomies and four wedge resections were performed, and the pathological results of the eight nodules included four adenocarcinomas, three adenocarcinomas in situ, and one alveolar epithelial hyperplasia. The two operations were successful with no intra‐ or postoperative 90‐day complications. During more than 20 months of follow‐up after the second operation, the patient had well recovered pulmonary function and physical status with a Karnofsky performance status score of 90 and no local recurrence or metastasis. A two‐stage surgical strategy for synchronous MPLCs is therefore feasible. The surgical strategy, timing of intervention, and extent of pulmonary resection should be individually designed according to the location and characteristics of each nodule. Intraoperative localization of small GGNs is very important to ensure that all nodules are completely and accurately resected during the operation. [ABSTRACT FROM AUTHOR]

Abstract Objective The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC. Methods Thirty‐five patients with ground‐glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole‐exome sequencing (WES) and transcriptome sequencing (RNA‐Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA‐Seq were subsequently analyzed. Results The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co‐mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD. Conclusions Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC.

Ground-glass nodule (GGN) lung cancer often progresses slowly in clinical and there are few clinical studies on long-term follow-up of patients with operable GGN lung cancer treated with stereotactic body radiation therapy (SBRT). We present a successful case of GGN lung cancer treated with SBRT, but a new GGN was found in the lung adjacent to the SBRT target during follow-up. The nodule progressed rapidly and was confirmed as lung adenocarcinoma by surgical resection. No significant risk factors and related driving genes were found in molecular pathological findings and genetic tests. It deserves further study whether new GGN is related to the SBRT. This case suggests that the follow-up after SBRT should be vigilant against the occurrence of new rapidly progressive lung cancer in the target area and adjacent lung tissue.

Bin-Jie Fu,1,&ast; Xiao-Chuan Zhang,1,2,&ast; Fa-Jin Lv,1 Zhi-Gang Chu1 1Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Department of Radiology, Chonggang General Hospital, Chongqing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhi-Gang Chu, Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, 400016, People’s Republic of China, Tel +86 18723032809, Fax +86 23 68811487, Email chuzg0815@163.comPurpose: To determine the value of intrapulmonary concomitant lesions in differentiating non-neoplastic and neoplastic ground-glass nodules (GGNs).Patients and Methods: From January 2014 to March 2022, 395 and 583 patients with confirmed non-neoplastic and neoplastic GGNs were retrospectively enrolled. Their clinical and chest CT data were evaluated. The CT features of target GGNs and intrapulmonary concomitant lesions in these two groups were analyzed and compared, and the role of intrapulmonary concomitant lesions in improving differentiation was evaluated.Results: The intrapulmonary concomitant lesions were more common in patients with non-neoplastic GGNs than in those with neoplastic ones (87.88% vs 82.18%, P = 0.015). Specifically, patients with non-neoplastic GGNs had a higher incidence of multiple solid nodules (SNs), patchy ground-glass opacity/consolidation, and fibrosis/calcification in any lung fields (each P < 0.05). Logistic regression analysis indicated that patients < 44 years old, diameter < 7.35 mm, irregular shape, and coarse margin or ill-defined boundary for target GGN, pleural thickening, and concomitant SNs in the same lobe and fibrosis or calcification in any lung field were independent indicators for predicting non-neoplastic GGNs. The AUC of the model for predicting non-neoplastic GGNs increased from 0.894 to 0.926 (sensitivity, 83.10%; specificity, 87.10%) after including the concomitant lesions in the patients’ clinical characteristics and CT features of target GGNs (P < 0.0001).Conclusion: Besides the patients’ clinical characteristics and CT features of target GGNs, the concomitant multiple SNs in the same lobe and fibrosis/calcification in any lung field should be considered in further differentiating non-neoplastic and neoplastic GGNs.Keywords: ground-glass nodule, intrapulmonary concomitant lesion, differential diagnosis, tomography, X-rays

Abstract Background Early stage lung adenocarcinomas manifested as ground-glass nodules (GGNs) are increasingly being detected, but screening and diagnosis for GGN-featured lung adenocarcinomas in different risk populations reach no agreement. Objectives To analyze the clinical, pathological, imaging and genetic features of GGN-featured lung adenocarcinomas on high-resolution computed tomography (HRCT) in different risk groups. Methods Include patients with GGNs on HRCT surgically diagnosed as lung adenocarcinoma in the West China Hospital, Sichuan University from 2009 to 2021, and their clinical, pathological, imaging and gene sequencing data. Results According to Chinese Expert Consensus on Screening and Management of Lung Cancer, 1,800 patients with GGN-featured lung adenocarcinoma, 545 males (incl. 269 smokers) and 1,255 females (incl. 16 smokers), were divided into high-risk (509) and non-high-risk (1,291) groups. Among them, 1,095 were detected via physical examination. The mean age at diagnosis was 54.78 (23–84) and the mean time from detection to diagnosis was 9.59 months. There were more males than females in the high-risk group [288 (56.58%) vs 221 (43.42%)], just the opposite in the non-high-risk group [1,034 (80.09%) vs 257 (19.91%)] (both P 0.05). The frequency of invasive adenocarcinoma was higher in the high-risk group, while those of precursor lesions and minimally invasive adenocarcinoma were higher in the non-high-risk group (all P

Background and objective The three-dimensional (3D) can assist in planning lung segmentectomy. 3D reconstruction software based on artificial intelligence algorithm is gradually applied in clinic. The aim of this study was to evaluate the accuracy and safety of 3D reconstruction assisted planning of thoracoscopic segmentectomy. Methods A total of 90 patients admitted to Department of Thoracic Surgery of Lanzhou University Second Hospital were evaluated for thoracoscopic segmentectomy. Before operation, artificial intelligence 3D reconstruction software was used to make 3D lung images and conduct preoperative planning. Surgical videos were saved during the operation and perioperative data were recorded. Video recordings of 38 patients were selected to explore the effectiveness of artificial intelligence 3D reconstruction for surgical planning. The results of artificial intelligence 3D reconstruction and Mimics 21 software reconstruction were compared with the actual results in the operation, and the detection and classification ability of bronchus and blood vessels of the two reconstruction methods were compared. Results All the 90 patients underwent artificial intelligence 3D reconstruction planning, including 57 patients (63.3%) with single lung segmentectomy and 33 patients (36.7%) with combined sub-segmentectomy. The accuracy of artificial intelligence 3D reconstruction for lesion localization was 100.0%, and the accuracy of computed tomography (CT) was 94.4% (85/90). The detection accuracy of artificial intelligence 3D reconstruction and Mimics 21 software was 92.1% (35/38) and 89.5% (34/38), and the anatomic typing accuracy was 89.5% (34/38) and 84.2% (32/38), and the total accuracy was 76.3% (29/38) and 71.1% (27/38). In the comparative observation of 38 surgical videos and reconstructed images, the consistent rates of target segment planning, surgical approach, artery dissection, vein dissection and bronchial dissection for preoperative planning using artificial intelligence 3D reconstruction were 92.1% (35/38), 92.1% (35/38), 89.5% (34/38), 86.8% (33/38) and 94.7% (36/38). The overall planning operational consistency rate was 68.4% (26/38). Conclusion It is accurate and safe to use artificial intelligence 3D reconstruction to assist planning thoracoscopic segmentectomy.

Abstract Objective This is a retrospective study of adverse events associated with preoperative computed tomography (CT)–guided hookwire or coil localisation. We analysed the experience and process flaws in resecting ground-glass nodules (GGNs) through video-assisted thoracoscopic surgery (VATS) and determined the remedial strategy. Methods Adverse events were evaluated in 40 patients with 45 GGNs who underwent CT-guided hookwire or coil localisation before VATS. For lesions not successfully marked or detected, palpation, resection of the highly suspected area, segmentectomy or lobectomy was performed. Results Among all adverse events, 15 were dislodgement of the marking materials, 5 were breakaway of the marking materials, 7 were > 2 cm distance between the lesions and the tips, 3 was marking material across the two adjacent lobes, 15 were pneumothorax and 2 were certain parts of marking materials stuck into the chest wall. All GGNs were resected successfully. 20 lesions were detected by palpation. 9 GGNs were discovered after the resection of highly suspected areas. Segmentectomies and lobectomies were performed directly on 7 and 9 GGNs, respectively. Conclusions When adverse events occur, a second intraoperative localisation, by resecting the highly suspected area either through non-anatomical resection (wedge resection) or anatomical resection (segmentectomy or lobectomy) using the VATS should be considered the alternatives for GGNs localization.

Abstract Background With the widespread use of low-dose computed tomography for lung cancer screening, the detection rate of pulmonary lesions manifesting as ground-glass opacities (GGOs) has been increasing dramatically. The volume doubling time (VDT) has been introduced in clinical practice to monitor the potential growth rate of GGOs during long-term follow-up periods. Case presentation A 72-year-old never-smoker female diagnosed with mixed GGO manifested abruptly accelerated growth with sudden decreased VDT from 400 to 36 days. A thoracoscopic left lower lobectomy with mediastinal lymph node dissection was performed, and the diagnosis was stage IB large-cell neuroendocrine carcinoma (LCNEC). Next-generation sequencing of the tumor highlights an EML4-ALK gene fusion. Conclusions The LCNEC may present as GGO with longer VDT in the early stage. VDT should calculate by the whole size either on the entire tumor diameter or on consolidation diameter. It is recommended that meticulous long-term follow-up with dynamic VDT monitoring may help select high-risk GGOs performing timely semi-elective surgical resection in clinical practice.

Purpose: To retrospectively examine the imaging characteristics of chest-computed tomography (CT) following percutaneous microwave ablation (MWA) of the ground-glass nodule (GGN)-like lung cancer and its dynamic evolution over time. Materials and Methods: From June 2020 to May 2021, 147 patients with 152 GGNs (51 pure GGNs and 101 mixed GGNs, mean size 15.0 ± 6.3 mm) were enrolled in this study. One hundred and forty-seven patients underwent MWA procedures. The imaging characteristics were evaluated at predetermined time intervals: immediately after the procedure, 24–48 h, 1, 3, 6, 12, and ≥18 months (47 GGNs). Results: This study population included 147 patients with 152 GGNs, as indicated by the results: 43.5% (66/152) adenocarcinoma in situ, 41.4% (63/152) minimally invasive adenocarcinoma, and 15.1% (23/152) invasive adenocarcinoma. Immediate post-procedure tumor-level analysis revealed that the most common CT features were ground-glass opacities (93.4%, 142/152), hyperdensity within the nodule (90.7%, 138/152), and fried egg sign or reversed halo sign (46.7%, 71/152). Subsequently, 24–48 h post-procedure, ground-glass attenuations, hyperdensity, and the fried egg sign remained the most frequent CT findings, with incidence rates of 75.0% (114/152), 71.0% (108/152), and 54.0% (82/152), respectively. Cavitation, pleural thickening, and consolidation were less frequent findings. At 1 month after the procedure, consolidation of the ablation region was the most common imaging feature. From 3 to 12 months after the procedure, the most common imaging characteristics were consolidation, involutional parenchymal bands and pleural thickening. At ≥18 months after the procedure, imaging features of the ablation zone revealed three changes: involuting fibrosis (80.8%, 38/47), consolidation nodules (12.8%, 6/47), and disappearance (6.4%, 3/47). Conclusions: This study outlined the anticipated CT imaging characteristics of GGN-like lung cancer following MWA. Diagnostic and interventional radiologists should be familiar with the expected imaging characteristics and dynamic evolution post-MWA in order to interpret imaging changes with a reference image. [ABSTRACT FROM AUTHOR]

Background: Early stage lung adenocarcinomas manifested as ground-glass nodules (GGNs) are increasingly being detected, but screening and diagnosis for GGN-featured lung adenocarcinomas in different risk populations reach no agreement. Objectives: To analyze the clinical, pathological, imaging and genetic features of GGN-featured lung adenocarcinomas on high-resolution computed tomography (HRCT) in different risk groups. Methods: Include patients with GGNs on HRCT surgically diagnosed as lung adenocarcinoma in the West China Hospital, Sichuan University from 2009 to 2021, and their clinical, pathological, imaging and gene sequencing data. Results: According to Chinese Expert Consensus on Screening and Management of Lung Cancer, 1,800 patients with GGN-featured lung adenocarcinoma, 545 males (incl. 269 smokers) and 1,255 females (incl. 16 smokers), were divided into high-risk (509) and non-high-risk (1,291) groups. Among them, 1,095 were detected via physical examination. The mean age at diagnosis was 54.78 (23–84) and the mean time from detection to diagnosis was 9.59 months. There were more males than females in the high-risk group [288 (56.58%) vs 221 (43.42%)], just the opposite in the non-high-risk group [1,034 (80.09%) vs 257 (19.91%)] (both P < 0.001). No statistical difference was found in GGN detection way (P > 0.05). The frequency of invasive adenocarcinoma was higher in the high-risk group, while those of precursor lesions and minimally invasive adenocarcinoma were higher in the non-high-risk group (all P < 0.001). The preoperative follow-up time in the non-high-risk group was shorter (P < 0.05). A total of 711 gene mutations were observed in 473 patients with a ratio of non-high-risk to high-risk of 494:217. The incidence of EGFR mutation was not statistically significant (P = 0.824), while those of TP53 and KRAS mutations were higher in the high-risk group (P < 0.05). Conclusions: GGN-featured lung adenocarcinoma is dominated by non-high-risk female patients. Shorter preoperative follow-up in the non-high-risk group and no statistical difference in GGN detection way suggests the existing screening criteria for high-risk population may not suit GGN-featured lung cancer. In addition, the incidences of KRAS and TP53 mutations are higher in the high-risk group. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: This is a retrospective study of adverse events associated with preoperative computed tomography (CT)–guided hookwire or coil localisation. We analysed the experience and process flaws in resecting ground-glass nodules (GGNs) through video-assisted thoracoscopic surgery (VATS) and determined the remedial strategy. Methods: Adverse events were evaluated in 40 patients with 45 GGNs who underwent CT-guided hookwire or coil localisation before VATS. For lesions not successfully marked or detected, palpation, resection of the highly suspected area, segmentectomy or lobectomy was performed. Results: Among all adverse events, 15 were dislodgement of the marking materials, 5 were breakaway of the marking materials, 7 were > 2 cm distance between the lesions and the tips, 3 was marking material across the two adjacent lobes, 15 were pneumothorax and 2 were certain parts of marking materials stuck into the chest wall. All GGNs were resected successfully. 20 lesions were detected by palpation. 9 GGNs were discovered after the resection of highly suspected areas. Segmentectomies and lobectomies were performed directly on 7 and 9 GGNs, respectively. Conclusions: When adverse events occur, a second intraoperative localisation, by resecting the highly suspected area either through non-anatomical resection (wedge resection) or anatomical resection (segmentectomy or lobectomy) using the VATS should be considered the alternatives for GGNs localization. [ABSTRACT FROM AUTHOR]

Background: With the widespread use of low-dose computed tomography for lung cancer screening, the detection rate of pulmonary lesions manifesting as ground-glass opacities (GGOs) has been increasing dramatically. The volume doubling time (VDT) has been introduced in clinical practice to monitor the potential growth rate of GGOs during long-term follow-up periods. Case presentation: A 72-year-old never-smoker female diagnosed with mixed GGO manifested abruptly accelerated growth with sudden decreased VDT from 400 to 36 days. A thoracoscopic left lower lobectomy with mediastinal lymph node dissection was performed, and the diagnosis was stage IB large-cell neuroendocrine carcinoma (LCNEC). Next-generation sequencing of the tumor highlights an EML4-ALK gene fusion. Conclusions: The LCNEC may present as GGO with longer VDT in the early stage. VDT should calculate by the whole size either on the entire tumor diameter or on consolidation diameter. It is recommended that meticulous long-term follow-up with dynamic VDT monitoring may help select high-risk GGOs performing timely semi-elective surgical resection in clinical practice. [ABSTRACT FROM AUTHOR]

Visceral pleural invasion (VPI) is one of the negative prognostic factors of non-small cell lung cancer (NSCLC). With the popularization of computed tomography (CT) screening for lung cancer, more and more ground-glass nodule (GGN) have been found. However, it remains unclear whether the relationship between the pleural deformation of lung cancer manifesting as ground-glass opacity (GGO) and VPI affects the effect of sub-lobectomy, which is reviewed in this paper.

Objective: To discuss the accuracy of the automatic measurement of the volume of pure ground glass nodules (pGGN) by the artificial intelligence pulmonary nodule detection software and the influencing factors of the measurement error. Methods: 170 pGGNs from 90 patients who underwent routine chest CT scan from January 1 to 31, 2021 in our hospital were selected in this retrospective study. The original CT scan data (including 1 mm thin-slice images) was sent to the AI server of Inference Technology to automatically measure the volume of lung nodules and record the measurement data. Two senior chest imaging diagnosticians manually carried out pGGNs layer-by-layer measurement and added the volume value, then took the average of three measurements as the "gold standard" data to compare with the AI measurement results, and then analyzed the influence of pGGN location, size, proximity and other factors on the AI measurement error. SPSS 26.0 was used for statistical analysis. Results: Among the total 170 pGGNs in the 90 patients in this study, 49 (28.82%) were in the right upper lobe, 21 (12.35%) were in the right middle lobe, 27 (15.88%) were in the right lower lobe, and left upper lobe 49 patients (28.82%) were involved, and 24 patients were in the lower lobe of the left lung (14.12%). Among the adjacent relationships of pGGN, 82 (48.24%) were completely located in the lung parenchyma without adjacency, 29 (17.06%) were close to the blood vessel, and 59 (34.70%) were close to the pleura. (1) There was no statistically significant difference in the volume values of pGGNs between two observers and the same observer at different time points. (2) For the measurement of the same pGGN, there was no statistically significant difference between the results of automatic measurement by AI and manual measurement and the correlation between the two was quite high (r=0.981), and the agreement was also very high (ICC value is 0.987). (3) The size, location, and adjacent relationship of pGGN lesions were not statistically significant for the error of AI volume measurement. Conclusions: The InferRead lung nodule measurement software shows high accuracy in the measurement of lung pGGN three-dimensional volume, which can be applied in clinical lung nodule diagnosis and related research. (2) For the measurement of the same pGGN volume, there was no difference between the results of automatic measurement by AI and manual measurement, and the correlation between them was quite high (r = 0.981), and the consistency was high (ICC value is 0.987). (3) The volume size, occurrence position and adjacent relationship of pGGN have no statistical significance on the error of AI volume measurement. Conclusion: The InferRead lung nodule detection software shows high accuracy in measuring the three-dimensional volume of lung pGGN, and can be applied to clinical diagnosis and related research of lung nodules.

Objective: Synchronous multiple ground-glass nodules (SM-GGNs) are a distinct entity of lung cancer which has been emerging increasingly in recent years in China. The oncogenesis molecular mechanisms of SM-GGNs remain elusive. Methods: We investigated single nucleotide variations (SNV), insertions and deletions (INDEL), somatic copy number variations (CNV), and germline mutations of 69 SM-GGN samples collected from 31 patients, using target sequencing (TRS) and whole exome sequencing (WES). Results: In the entire cohort, many known driver mutations were found, including EGFR (21.7%), BRAF (14.5%), and KRAS (6%). However, only one out of the 31 patients had the same somatic missense or truncated events within SM-GGNs, indicating the independent origins for almost all of these SM-GGNs. Many germline mutations with a low frequency in the Chinese population, and genes harboring both germline and somatic variations, were discovered in these pre-stage GGNs. These GGNs also bore large segments of copy number gains and/or losses. The CNV segment number tended to be positively correlated with the germline mutations (r = 0.57). The CNV sizes were correlated with the somatic mutations (r = 0.55). A moderate correlation (r = 0.54) was also shown between the somatic and germline mutations. Conclusion: Our data suggests that the precancerous unstable CNVs with potentially predisposing genetic backgrounds may foster the onset of driver mutations and the development of independent SM-GGNs during the local stimulation of mutagens.

Abstract Objectives To investigate feasibility and safety of autologous blood in preoperative computed tomography (CT)-guided localization of pulmonary ground-glass nodules (GGNs) by comparing to mico-coil prior to video-assisted thoracoscopic surgery. Methods Clinical data of patients with GGNs who underwent video-assisted thoracoscopic surgery followed by preoperative CT-guided autologous blood or micro-coil localization was retrospectively reviewed in our department between September 2019 and November 2021. The localization duration, localization success rate, localization-related complication, localization cost, operation time, and conversion rate were compared between the 2 localization groups. Results Totally 65 patients with 65 GGNs were included in our study, with 34 patients in autologous blood group (group B) and 31 patients in micro-coil group (group M). There is no conversion to thoracotomy. The age, sex, nodule location, diameter of nodule and distance from the pleura between the 2 groups were statistically comparable. Compared with group M, group B had similar localization success rate (94.1% vs 83.9%, P = 0.183) but shorter localization time (14.50 ± 2.61 min vs 16.35 ± 2.30 min, P = 0.004), lower cost ($92.4 ± 3.2 vs $475.6 ± 8.5, P = 0.001), and lower incidence of puncture complications (3.0% vs 19.3%, P = 0.042). Conclusions The autologous blood localization is an effective and more economical method for preoperative GGNs localization, and is associated with fewer complications compared to micro-coil localization.

ObjectiveTo understand the characteristics of genetic mutation in multiple primary lung cancer so as to guide clinical decisions in targeted therapy.MethodsWe analyzed a total of 265 tumors from 111 patients who underwent surgery for multiple lung cancers. Individual tumors were subjected to histological evaluation and gene mutation analysis using ABI 7500 Fluorescence quantitative PCR.ResultsIn this study, we analyzed demographic and clinical parameters such as age, gender, smoking, alcohol consumption, pathological type, number of nodules, and other details of 111 patients with early multiple primary lung cancer. We also compared the clinicopathologic characteristics of different populations based on the gene mutation status of pulmonary nodules. Subsequently, we performed a clinicopathological analysis of all 265 pulmonary nodules from these patients. Results showed significant differences in clinicopathological features of pulmonary nodules in different genetic mutations.ConclusionThis study revealed the gene mutation characteristics and clinicopathological features in early multiple primary lung cancer. We found that the gene mutation status between different nodules in patients with early multiple primary lung cancer was inconsistent in most cases. Therefore, the use of targeted therapy based on the genetic sequencing of only one nodule, is unreliable. We hope this study can be helpful in guiding clinical treatment decisions.

Objectives: Few studies have explored the use of spectral dual-layer detector-based computed tomography (SDCT) parameters, thymidine kinase-1 (TK1), and tumor abnormal protein (TAP) for the detection of ground-glass nodules (GGNs). Therefore, we aimed to evaluate the quantitative and qualitative parameters generated from SDCT for predicting the pathological subtypes of GGN-featured lung adenocarcinoma combined with TK1 and TAP. Material and Methods: Between July 2021 and September 2022, 238 patients with GGNs were retrospectively enrolled in this study. SDCT and tests for TK1 and TAP were performed preoperatively, and the lesions were divided into glandular precursor lesions (PGL), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC), according to the pathological results. A receiver operating characteristic (ROC) curve was used to compare the diagnostic performance of these parameters. Multivariate logistic regression analysis was performed to construct a joint diagnostic model and create a nomogram. Results: This study included 238 GGNs, including 41 atypical adenomatous hyperplasias (AAH), 62 adenocarcinomas in situ (AIS), 49 MIA, and 86 IAC, with a high proportion of women, non-smokers, and pure ground-glass nodule (pGGN). CT100 keV (a/v), electronic density (EDW) (a/v), Daverage, Dsolid, TK1, and TAP of MIA and IAC were higher than those of PGL. The effective atomic number (Zeff (a/v)) was lower in MIA and IAC than in PGL (all p < 0.05). Logistic regression analysis showed that Zeff (a), EDW (a), TK1, Daverage, and internal bronchial morphology were crucial factors in predicting the aggressiveness of GGN. Zeff (a) had the highest diagnostic performance with an area under the ROC curve (AUC) = 0.896, followed by EDW (a) (AUC = 0.838) and CT100 keVa (AUC = 0.819). The diagnostic model and nomogram constructed using these five parameters (Zeff (a) + EDW (a) + CT100 keVa + Daverage + TK1) had an AUC = 0.933, which was higher than the individual parameters (p < 0.05). Conclusions: Multiple quantitative and functional parameters can be selected based on SDCT, especially Zeff (a) and EDW (a), which have high sensitivity and specificity for predicting GGNs' invasiveness. Additionally, the combination of TK1 can further improve diagnostic performance, and using a nomogram is helpful for individualized predictions. [ABSTRACT FROM AUTHOR]

Simple Summary: To forecast the invasiveness of the increasingly detected pure ground glass nodules, 338 cases were included in this study. Among them, 22.8% (77/338) of patients with pGGN were diagnosed with invasive adenocarcinoma. There were no nodal metastases or recurrence during a mean 78-month follow-up. A radiomic prediction model was constructed to predict the tumor's invasiveness. The radiomic prediction model achieved good performance with an AUC of 0.7676. The prediction model can be used clinically in the treatment selection process. It remains a challenge to preoperatively forecast whether lung pure ground-glass nodules (pGGNs) have invasive components. We aimed to construct a radiomic model using tumor characteristics to predict the histologic subtype associated with pGGNs. We retrospectively reviewed clinicopathologic features of pGGNs resected in 338 patients with lung adenocarcinoma between 2011–2016 at a single institution. A radiomic prediction model based on forward sequential selection and logistic regression was constructed to differentiate adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma. The study cohort included 133 (39.4%), 128 (37.9%), and 77 (22.8%) patients with AIS, MIA, and invasive adenocarcinoma (acinar 55.8%, lepidic 33.8%, papillary 10.4%), respectively. The majority (83.7%) underwent sublobar resection. There were no nodal metastases or tumor recurrence during a mean follow-up period of 78 months. Three radiomic features—cluster shade, homogeneity, and run-length variance—were identified as predictors of histologic subtype and were selected to construct a prediction model to classify the AIS/MIA and invasive adenocarcinoma groups. The model achieved accuracy, sensitivity, specificity, and AUC of 70.6%, 75.0%, 70.0%, and 0.7676, respectively. Applying the developed radiomic feature model to predict the histologic subtypes of pGGNs observed on CT scans can help clinically in the treatment selection process. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Lung Cancer is the property of Chinese Journal of Lung Cancer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: To develop a novel multimodal data fusion model by incorporating computed tomography (CT) images and clinical variables based on deep learning for predicting the invasiveness risk of stage I lung adenocarcinoma that manifests as ground‐glass nodules (GGNs) and compare the diagnostic performance of it with that of radiologists. Methods: A total of 1946 patients with solitary and histopathologically confirmed GGNs with maximum diameter less than 3 cm were retrospectively enrolled. The training dataset containing 1704 GGNs was augmented by resampling, scaling, random cropping, and so forth, to generate new training data. A multimodal data fusion model based on residual learning architecture and two multilayer perceptron with attention mechanism combining CT images with patient general data and serum tumor markers was built. The distance‐based confidence scores (DCS) were calculated and compared among multimodal data models with different combinations. An observer study was conducted and the prediction performance of the fusion algorithms was compared with that of the two radiologists by an independent testing dataset with 242 GGNs. Results: Among the whole GGNs, 606 GGNs are confirmed as invasive adenocarcinoma (IA) and 1340 are non‐IA. The proposed novel multimodal data fusion model combining CT images, patient general data, and serum tumor markers achieved the highest accuracy (88.5%), area under a ROC curve (0.957), F1 (81.5%), F1weighted (81.9%), and Matthews correlation coefficient (73.2%) for classifying between IA and non‐IA GGNs, which was even better than the senior radiologist's performance (accuracy, 86.1%). In addition, the DCSs for multimodal data suggested that CT image had a stronger influence (0.9540) quantitatively than general data (0.6726) or tumor marker (0.6971). Conclusion: This study demonstrated that the feasibility of integrating different types of data including CT images and clinical variables, and the multimodal data fusion model yielded higher performance for distinguishing IA from non‐IA GGNs. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Spread through air spaces (STAS) is significantly associated with decreased overall survival (OS) and reduced recurrence-free survival. However, there are no reliable methods to confirm the presence of STAS before surgery. The sensitivity and specificity of the intraoperative frozen section diagnosis of STAS are not satisfactory. This study sought to determine the clinical, pathological, and computed tomography (CT) features of lung cancer with STAS before surgery to guide treatment decisions., Methods: The data of 121 patients who were positive for STAS and 121 who were negative for STAS as confirmed by surgery and pathology were collected at Jiangsu Cancer Hospital from January 2020 to December 2022. The differences between the two groups in terms of the clinical, pathological, and CT characteristics were compared., Results: STAS occurred not only in lung adenocarcinoma (LUAD) (106 of 121, 87.6%), but also in other pathological types of lung cancer (15 of 121, 12.4%). STAS was significantly correlated with pathological invasiveness [pathological differentiation, tumor, node, metastasis (TNM) staging, vascular invasion, and pleural invasion; all P<0.05]. STAS was most common in solid tumors (95 of 121, 78.51%). The receiver operating characteristic (ROC) curve showed that the optimal cut-off value for diagnosing STAS based on diameter is 1.55 cm with a sensitivity of 73.3% and a specificity of 47.9%. The percentage of solid components (PSC) is an independent influencing factor of lung cancer with STAS [odds ratio (OR) =111.27; P<0.05] with an optimal cut-off value of 63%, a sensitivity of 92.5%, and a specificity of 72.7%. In the part-solid nodules, the occurrence rate of STAS increased as the PSC increased. STAS was only observed in part-solid nodules with a PSC greater than 25%. Among the CT morphological features, lobulation was an independent influencing factor of lung cancer with STAS (OR =3.513; P<0.05), and persistent indistinct margin ground-glass opacity around the primary lesion of lung cancer (21 of 121, 17.36%) and satellite foci (9 of 121, 7.44%) strongly indicated the existence of STAS., Conclusions: The clinical, pathological and CT features of STAS may guide clinicians to develop appropriate strategies and improve the survival rate of patients., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-715/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Background: Different pathological stages of lung adenocarcinoma require different surgical strategies and have varying prognoses. Predicting their invasiveness is clinically important. This study aims to develop a nomogram to predict the invasiveness of lung adenocarcinoma manifesting as ground-glass nodules (GGNs) based on follow-up computed tomography (CT) imaging., Methods: We retrospectively collected data of 623 GGNs from 601 patients who underwent two follow-up chest CT scans and were confirmed as lung adenocarcinoma by postoperative pathology between June 2017 and August 2023. These patients were randomly divided into training and testing sets in a 7:3 ratio. Eighty-seven GGNs from 86 patients who underwent surgery between September 2023 and April 2024 were prospectively collected as a validation set. The volume, mean density, solid component volume (SV), percentage of solid component (PSC), and mass of GGNs were evaluated using the InferRead CT Lung software. Patients were classified into Group A (atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma) and Group B (invasive adenocarcinoma). Three predictive models were established: model 1 utilized clinical characteristics and morphological features on pre-surgical CT, model 2 incorporated clinical characteristics, morphological features and quantitative parameters on pre-surgical CT, and model 3 utilized all selected features on baseline and pre-surgical CT., Results: Model 3 achieved a satisfying area under the curves values of 0.911, 0.893, and 0.932 in the training, testing, and validation sets, respectively, demonstrating superior predictive performance than model1 (0.855, 0.858, and 0.816) and model2 (0.895, 0.891, and 0.903). A nomogram was constructed based on model 3. Calibration curves showed a good fit, and decision curve analysis showed that the nomogram was clinically useful., Conclusions: The nomogram based on morphological features and quantitative parameters from follow-up CT images showed good discrimination and calibration abilities in predicting the invasiveness of lung adenocarcinoma manifesting as GGNs., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-492/coif). C.D. is an employee of Bayer Healthcare. The other authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Objectives: The purpose of this study was to develop and validate a new feature fusion algorithm to improve the classification performance of benign and malignant ground-glass nodules (GGNs) based on deep learning., Methods: We retrospectively collected 385 cases of GGNs confirmed by surgical pathology from three hospitals. We utilized 239 GGNs from Hospital 1 as the training and internal validation set, and 115 and 31 GGNs from Hospital 2 and Hospital 3, respectively, as external test sets 1 and 2. Among these GGNs, 172 were benign and 203 were malignant. First, we evaluated clinical and morphological features of GGNs at baseline chest CT and simultaneously extracted whole-lung radiomics features. Then, deep convolutional neural networks (CNNs) and backpropagation neural networks (BPNNs) were applied to extract deep features from whole-lung CT images, clinical, morphological features, and whole-lung radiomics features separately. Finally, we integrated these four types of deep features using an attention mechanism. Multiple metrics were employed to evaluate the predictive performance of the model., Results: The deep learning model integrating clinical, morphological, radiomics and whole lung CT image features with attention mechanism (CMRI-AM) achieved the best performance, with area under the curve (AUC) values of 0.941 (95% CI: 0.898-0.972), 0.861 (95% CI: 0.823-0.882), and 0.906 (95% CI: 0.878-0.932) on the internal validation set, external test set 1, and external test set 2, respectively. The AUC differences between the CMRI-AM model and other feature combination models were statistically significant in all three groups (all p<0.05)., Conclusion: Our experimental results demonstrated that (1) applying attention mechanism to fuse whole-lung CT images, radiomics features, clinical, and morphological features is feasible, (2) clinical, morphological, and radiomics features provide supplementary information for the classification of benign and malignant GGNs based on CT images, and (3) utilizing baseline whole-lung CT features to predict the benign and malignant of GGNs is an effective method. Therefore, optimizing the fusion of baseline whole-lung CT features can effectively improve the classification performance of GGNs., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Deng, Huang, Zhou, Zhou, Fan and Liu.)

Thoracic surgeons need to be aware of several important points regarding intraoperative lymph node dissection during surgery for non-small cell lung cancer with ground-glass opacities. The first point relates to the need for lymph node dissection during sublobar resection. Since even patients undergoing sublobar resection may benefit from lymph node dissection, it should be selectively performed according to adequate indications, which require further study. Second, there seems to be no difference in postoperative morbidity between systematic sampling and systematic dissection, but the survival benefit from systematic dissection remains unclear. The results of randomized controlled trials on this topic are conflicting, and their evidence is jeopardized by a high risk of bias in terms of the study design. Therefore, further randomized controlled trials with a sound design should investigate this issue. Third, more favorable survival outcomes tend to be positively associated with the number of examined lymph nodes. Minimum requirements for the number of examined lymph nodes in non-small cell lung cancer should be defined in the future. Finally, lobe-specific lymph node dissection does not have a negative prognostic impact. It should not be routinely performed, but it can be recommended in selected patients with smaller, less invasive tumors. Results from an ongoing randomized controlled trial on this topic should be awaited.

Introduction: Lung cancer presenting as ground-glass nodules (GGNs) with little consolidation is often diagnosed as noninvasive carcinoma. Increasing evidence suggests that sublobar lung resection, such as wedge resection, provides satisfactory long-term outcomes equivalent to those of lobectomy. Spread through alveolar spaces (STAS) is a reported risk factor for recurrence, especially when sublobar lung resection is applied. We herein report a rare case of a pure GGN that was histologically confirmed to be adenocarcinoma in situ (AIS) and associated STAS after limited resection. Case presentation: A 67-year-old woman presented with an 8-mm pure GGN in S2 of the right upper lobe and a part-solid GGN in S8 of the right lower lobe. The clinical stages of these GGNs were TisN0M0 stage 0 and T1aN0M0 stage IA1, respectively. The patient underwent video-assisted thoracoscopic segmentectomies of S2 and S8. Histopathological examination of the resected specimens revealed minimally invasive adenocarcinoma in S8 and AIS in S2. Stromal invasion was not observed in the tumor located in S2, but a tumor cell cluster was found in the air space located away from the AIS lesion. Thus, the lesion was positive for STAS. Conclusion: We have reported a rare case of a pure GGN that was histologically STAS-positive, otherwise diagnosed as AIS after limited resection.

PurposeTo retrospectively evaluate the cost and effectiveness in consecutive patients with ground-glass nodules (GGNs) treated with video-assisted thoracoscopic surgery (VATS; i.e., wedge resection or segmentectomy) or microwave ablation (MWA).Materials and methodsFrom May 2017 to April 2019, 204 patients who met our study inclusion criteria were treated with VATS (n = 103) and MWA (n = 101). We calculated the rate of 3-year overall survival (OS), local progression-free survival (LPFS), and cancer−specific survival (CSS), as well as the cost during hospitalization and the length of hospital stay.ResultsThe rates of 3-year OS, LPFS, and CSS were 100%, 98.9%, and 100%, respectively, in the VATS group and 100%, 100% (p = 0.423), and 100%, respectively, in the MWA group. The median cost of VATS vs. MWA was RMB 54,314.36 vs. RMB 21,464.98 (p < 0.001). The length of hospital stay in the VATS vs. MWA group was 10.0 vs. 6.0 d (p < 0.001).ConclusionsMWA had similar rates of 3-year OS, LPFS, and CSS for patients with GGNs and a dramatically lower cost and shorter hospital stay compared with VATS. Based on efficacy and cost, MWA provides an alternative treatment option for patients with GGNs.

Objectives: To investigate feasibility and safety of autologous blood in preoperative computed tomography (CT)-guided localization of pulmonary ground-glass nodules (GGNs) by comparing to mico-coil prior to video-assisted thoracoscopic surgery.Methods: Clinical data of patients with GGNs who underwent video-assisted thoracoscopic surgery followed by preoperative CT-guided autologous blood or micro-coil localization was retrospectively reviewed in our department between September 2019 and November 2021. The localization duration, localization success rate, localization-related complication, localization cost, operation time, and conversion rate were compared between the 2 localization groups.Results: Totally 65 patients with 65 GGNs were included in our study, with 34 patients in autologous blood group (group B) and 31 patients in micro-coil group (group M). There is no conversion to thoracotomy. The age, sex, nodule location, diameter of nodule and distance from the pleura between the 2 groups were statistically comparable. Compared with group M, group B had similar localization success rate (94.1% vs 83.9%, P = 0.183) but shorter localization time (14.50 ± 2.61 min vs 16.35 ± 2.30 min, P = 0.004), lower cost ($92.4 ± 3.2 vs $475.6 ± 8.5, P = 0.001), and lower incidence of puncture complications (3.0% vs 19.3%, P = 0.042).Conclusions: The autologous blood localization is an effective and more economical method for preoperative GGNs localization, and is associated with fewer complications compared to micro-coil localization. [ABSTRACT FROM AUTHOR]

Purpose The role of epidermal growth factor receptor–tyrosine kinase inhibitors (EGFR-TKIs) in the management of persistent subsolid nodules (SSNs) is unclear. This study aimed to investigate the impact of EGFR-TKIs on concurrent SSNs in patients with stage IV non–small cell lung cancer (NSCLC). Materials and Methods Patients who received an EGFR-TKI for at least 1 month for stage IV NSCLC and had concurrent SSN(s) that had existed for at least 3 months on chest computed tomography were included in this retrospective study. Size change of each nodule before and after EGFR-TKI therapies were evaluated using a cutoff value of 2 mm; increase (≥ 2 mm), decrease (≤ –2 mm), and no change (–2 mm < size change < +2 mm). Results A total of 77 SSNs, 51 pure ground-glass (66.2%) and 26 part-solid nodules (33.8%), were identified in 59 patients who received gefitinib (n=45) and erlotinib (n=14). Among 58 EGFR mutation analysis performed for primary lung cancer, 45 (77.6%) were EGFR mutant. The proportions of decrease group were 19.5% (15/77) on per-nodule basis and 25.4% (15/59) on per-patient basis. Four SSNs (5.2%) disappeared completely. On per-patient based multivariable analysis, EGFR exon 19 deletion positivity for primary lung cancer was associated with a decrease after initial EGFR-TKI therapy (adjusted odds ratio, 4.29; 95% confidence interval, 1.21 to 15.29; p=0.025). Conclusion Approximately 20% of the concurrent SSNs decreased after the initial EGFR-TKI therapy. EGFR exon 19 deletion positivity for primary lung cancer was significantly associated with the size change of concurrent SSNs. [ABSTRACT FROM AUTHOR]

“The Expert Group on Tumor Ablation Therapy of Chinese Medical Doctor Association, The Tumor Ablation Committee of Chinese College of Interventionalists, The Society of Tumor Ablation Therapy of Chinese Anti-Cancer Association and The Ablation Expert Committee of the Chinese Society of Clinical Oncology” have organized multidisciplinary experts to formulate the consensus for thermal ablation of pulmonary subsolid nodules or ground-glass nodule (GGN). The expert consensus reviews current literatures and provides clinical practices for thermal ablation of GGN. The main contents include: (1) clinical evaluation of GGN, (2) procedures, indications, contraindications, outcomes evaluation and related complications of thermal ablation for GGN and (3) future development directions.

Objective: This study aimed to develop effective artificial intelligence (AI) diagnostic models based on CT images of pulmonary nodules only, on descriptional and quantitative clinical or image features, or on a combination of both to differentiate benign and malignant ground-glass nodules (GGNs) to assist in the determination of surgical intervention. Methods: Our study included a total of 867 nodules (benign nodules: 112; malignant nodules: 755) with postoperative pathological diagnoses from two centers. For the diagnostic models to discriminate between benign and malignant GGNs, we adopted three different artificial intelligence (AI) approaches: a) an image-based deep learning approach to build a deep neural network (DNN); b) a clinical feature-based machine learning approach based on the clinical and image features of nodules; c) a fusion diagnostic model integrating the original images and the clinical and image features. The performance of the models was evaluated on an internal test dataset (the "Changzheng Dataset") and an independent test dataset collected from an external institute (the "Longyan Dataset"). In addition, the performance of automatic diagnostic models was compared with that of manual evaluations by two radiologists on the 'Longyan dataset'. Results: The image-based deep learning model achieved an appealing diagnostic performance, yielding AUC values of 0.75 (95% confidence interval [CI]: 0.62, 0.89) and 0.76 (95% CI: 0.61, 0.90), respectively, on both the Changzheng and Longyan datasets. The clinical feature-based machine learning model performed well on the Changzheng dataset (AUC, 0.80 [95% CI: 0.64, 0.96]), whereas it performed poorly on the Longyan dataset (AUC, 0.62 [95% CI: 0.42, 0.83]). The fusion diagnostic model achieved the best performance on both the Changzheng dataset (AUC, 0.82 [95% CI: 0.71-0.93]) and the Longyan dataset (AUC, 0.83 [95% CI: 0.70-0.96]), and it achieved a better specificity (0.69) than the radiologists (0.33-0.44) on the Longyan dataset. Conclusion: The deep learning models, including both the image-based deep learning model and the fusion model, have the ability to assist radiologists in differentiating between benign and malignant nodules for the precise management of patients with GGNs. [ABSTRACT FROM AUTHOR]

We investigated the role of [18F]FDG positron emission tomography/computed tomography (PET/CT) in evaluating ground-glass nodules (GGNs) by visual analysis and tissue fraction correction. A total of 40 pathologically confirmed ≥1 cm GGNs were evaluated visually and semiquantitatively. [18F]FDG uptake of GGN distinct from background lung activity was considered positive in visual analysis. In semiquantitative analysis, we performed tissue fraction correction for the maximum standardized uptake value (SUVmax) of GGN. Of the 40 GGNs, 25 (63%) were adenocarcinomas, 9 (23%) were minimally invasive adenocarcinomas (MIAs), and 6 (15%) were adenocarcinomas in situ (AIS). On visual analysis, adenocarcinoma showed the highest positivity rate among the three pathological groups (88%, 44%, and 17%, respectively). Both SUVmax and tissue-fraction–corrected SUVmax (SUVmaxTF) were in the order of adenocarcinoma > MIA > AIS (p = 0.033 and 0.018, respectively). SUVmaxTF was significantly higher than SUVmax before correction (2.4 [1.9–3.0] vs. 1.3 [0.8–1.8], p < 0.001). When using a cutoff value of 2.5, the positivity rate of GGNs was significantly higher in SUVmaxTF than in SUVmax (50% vs. 5%, p < 0.001). The diagnostic sensitivity of [18F]FDG PET/CT in predicting the malignancy of lung GGN was improved by tissue fraction correction and visual analysis. [ABSTRACT FROM AUTHOR]

Since the 1990s, low-dose computed tomography technology has been used in lung cancer screening. With the increase of computed tomography screening, the detection rate of ground-glass nodules (GGN) has increased dramatically. At present, the main treatment strategy for GGN is surgical resection. However, for patients with poor cardiopulmonary functions, a history of lung resection, multiple pulmonary nodules, or the age of >75 years, surgical resection is very difficult and not medically encouraged. This article reviews the applications and outcomes evaluation of nonsurgical treatments, such as chemotherapy, radiotherapy, moleculartargeted drug therapy, immunity therapy, and image-guided thermal ablation in patients with GGN. [ABSTRACT FROM AUTHOR]

Open in new tab Download slide Open in new tab Download slide OBJECTIVES Indications of limited resection, such as segmentectomy, have recently been reported for patients with solid-predominant lung cancers ≤2 cm. This study aims to identify unfavourable prognostic factors using three-dimensional imaging analysis with artificial intelligence (AI) technology. METHODS A total of 157 patients who had clinical N0 non-small cell lung cancer with a radiological size ≤2 cm, and a consolidation tumour ratio > 0.5, who underwent anatomical lung resection between 2011 and 2017 were enrolled. To evaluate the three-dimensional structure, the ground-glass nodule/Solid Automatic Identification AI software Beta Version (AI software; Fujifilm Corporation, Japan) was used. RESULTS Maximum standardized uptake value (SUVmax) and solid-part volume measured by AI software (AI-SV) showed significant differences between the 139 patients with adenocarcinoma and the 18 patients with non-adenocarcinoma. Among the adenocarcinoma patients, 42 patients (30.2%) were found to be pathological upstaging. Multivariable analysis demonstrated that high SUVmax, high carcinoembryonic antigen level and high AI-SV were significant prognostic factors for recurrence-free survival (RFS; P  <   0.05). The 5-year RFS was compared between patients with tumours showing high SUVmax and those showing low SUVmax (67.7% vs 95.4%, respectively, P  <   0.001). The 5-year RFS was 91.0% in patients with small AI-SV and 68.1% in those with high AI-SV (P  =   0.001). CONCLUSIONS High AI-SV, high SUVmax and abnormal carcinoembryonic antigen level were unfavourable prognostic factors of patients with solid-predominant lung adenocarcinoma with a radiological size ≤2 cm. Our results suggest that lobectomy should be preferred to segmentectomy for patients with these prognostic factors. [ABSTRACT FROM AUTHOR]

Wang-Jia Li,1,* Fa-Jin Lv,1,* Yi-Wen Tan,2 Bin-Jie Fu,1 Zhi-Gang Chu1 1Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Department of Pathology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhi-Gang ChuDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, 400016, People’s Republic of ChinaTel +86 18723032809Fax +86 23 68811487Email chuzg0815@163.comBackground: Some pulmonary ground-glass nodules (GGNs) are benign and frequently misdiagnosed due to lack of understanding of their CT characteristics. This study aimed to reveal the CT features and corresponding pathological findings of pulmonary benign GGNs to help improve diagnostic accuracy.Patients and Methods: From March 2016 to October 2019, patients with benign GGNs confirmed by operation or follow-up were enrolled retrospectively. According to overall CT manifestations, GGNs were classified into three types: I, GGO with internal high-attenuation zone; II, nodules lying on adjacent blood vessels; and other type, lesions without obvious common characteristics. CT features and pathological findings of each nodule type were evaluated.Results: Among the 40 type I, 25 type II, and 14 other type GGNs, 24 (60.0%), 19 (76.0%), and 10 (71.4%) nodules were resected, respectively. Type I GGNs were usually irregular (25 of 40, 62.5%) with only one high-attenuation zone (38 of 40, 95.0%) (main pathological components: thickened alveolar walls with inflammatory cells, fibrous tissue, and exudation), which was usually centric (24 of 40, 60.0%), having blurred margin (38 of 40, 95.0%), and connecting to blood vessels (32 of 40, 80.0%). The peripheral GGO (main pathological component: a small amount of inflammatory cell infiltration with fibrous tissue proliferation) was usually ill-defined (28 of 40, 70.0%). Type II GGNs (main pathological components: focal interstitial fibrosis with or without inflammatory cell infiltration) lying on adjacent vessel branches were usually irregular (19 of 25, 76.0%) and well defined (16 of 25, 64.0%) but showed coarse margins (15 of 16, 93.8%). Other type GGNs had various CT manifestations but their pathological findings were similar to that of type II.Conclusion: For subsolid nodules with CT features manifested in type I or II GGNs, follow-up should be firstly considered in further management.Keywords: ground-glass nodule, benignity, CT, pathology, lung

ObjectiveThis study aimed to develop effective artificial intelligence (AI) diagnostic models based on CT images of pulmonary nodules only, on descriptional and quantitative clinical or image features, or on a combination of both to differentiate benign and malignant ground-glass nodules (GGNs) to assist in the determination of surgical intervention.MethodsOur study included a total of 867 nodules (benign nodules: 112; malignant nodules: 755) with postoperative pathological diagnoses from two centers. For the diagnostic models to discriminate between benign and malignant GGNs, we adopted three different artificial intelligence (AI) approaches: a) an image-based deep learning approach to build a deep neural network (DNN); b) a clinical feature-based machine learning approach based on the clinical and image features of nodules; c) a fusion diagnostic model integrating the original images and the clinical and image features. The performance of the models was evaluated on an internal test dataset (the “Changzheng Dataset”) and an independent test dataset collected from an external institute (the “Longyan Dataset”). In addition, the performance of automatic diagnostic models was compared with that of manual evaluations by two radiologists on the ‘Longyan dataset’.ResultsThe image-based deep learning model achieved an appealing diagnostic performance, yielding AUC values of 0.75 (95% confidence interval [CI]: 0.62, 0.89) and 0.76 (95% CI: 0.61, 0.90), respectively, on both the Changzheng and Longyan datasets. The clinical feature-based machine learning model performed well on the Changzheng dataset (AUC, 0.80 [95% CI: 0.64, 0.96]), whereas it performed poorly on the Longyan dataset (AUC, 0.62 [95% CI: 0.42, 0.83]). The fusion diagnostic model achieved the best performance on both the Changzheng dataset (AUC, 0.82 [95% CI: 0.71-0.93]) and the Longyan dataset (AUC, 0.83 [95% CI: 0.70-0.96]), and it achieved a better specificity (0.69) than the radiologists (0.33-0.44) on the Longyan dataset.ConclusionThe deep learning models, including both the image-based deep learning model and the fusion model, have the ability to assist radiologists in differentiating between benign and malignant nodules for the precise management of patients with GGNs.

Background and objective How to locate pulmonary ground-glass nodules in thoracoscopic surgery is an important clinical topic in minimally invasive thoracic surgery. There is no unified localization method at present. This study intends to investigate the accuracy and security of body surface theodolitic puncture localization method in video-assisted thoracoscopic surgery for pulmonary ground-glass nodules. Methods The clinical data of 41 patients from August 2018 to December 2019 were analyzed retrospectively, including 28 males and 13 females. After anesthesia, the patient was located by body surface theodolitic puncture, and then partial lobectomy was performed under video-assisted thoracoscopy. The distance from the nodule to the marked suture and the distance from the nodule to the incisal margin were measured, and the accuracy of localization, the rate of complication and the success rate of surgical resection were calculated. Results A total of 51 nodules in 41 patients were located by body surface theodolitic puncture localization method. The accuracy rate was 96.1%, and the average location time was 8.3 min. Puncture bleeding occurred in 5 cases (12.2%), all of which were successfully stopped by video-assisted thoracoscopy, and there were no other complications. All patients underwent thoracoscopic partial lobectomy, including 33 cases of anatomical segmentectomy and 8 cases of wedge lobectomy. All the patients in operation process smoothly. The distance between nodule and incisal margin was measured, and all specimens were more than 2 cm, reaching a safe distance. The success rate of surgical resection was 100.0%. Conclusion In video-assisted thoracoscopic surgery for ground glass nodules of lung, the body surface theodolitic puncture localization method can be accurate, safe and simple.