Lung Adenocarcinoma: Screening and Surgical Treatment

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: closed (1 September 2023) | Viewed by 8741

Special Issue Editors


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Guest Editor
1. Division of Thoracic Surgery, IEO, European Institute of Oncology IRCCS, 20141 Milano, Italy
2. Department of Oncology and Hemato-Oncology, University of Milan, 201222 Milan, Italy
Interests: lung cancer surgery; lung cancer oncology; robotic surgery

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Guest Editor
Department of Thoracic Surgery, IEO, European Institute of Oncology IRCCS, Milan, Italy
Interests: lung cancer; lung cancer surgery; biostatistics
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Special Issue Information

Dear Colleagues,

While male incidence and fatality rates have decreased marginally in recent years, female rates continue to grow. Disseminated illness, including nodal and distant metastases, outnumbers localized disease by more than threefold. Due to the predictive significance of the tumor stage at diagnosis, a high prevalence of advanced tumor stages at diagnosis contributes to lung cancer’s high mortality.

Recent therapy advances, such as checkpoint inhibitors or immunotherapy, have the potential to increase survival. Despite this, they only cure a minority of patients, and long-term survivors of metastatic illness are uncommon. The stage of the tumor continues to have the most significant impact on overall and cancer-specific survival. To truly enhance survival, patients must be detected early in the course of the disease. The results of lung cancer screening trials are encouraging, indicating that individuals with lung cancer have an improved survival rate, owing primarily to a shift in tumor stages at the time of discovery. Increased lung nodules for histopathologic examination and early tumor stages result in increased patient volume and workload for thoracic surgical units.

This special edition of the Cancers journal will address lung adenocarcinoma screening and surgical treatment in the third millennium considering breakthrough technologies.

Prof. Dr. Lorenzo Spaggiari
Dr. Luca Bertolaccini
Guest Editors

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Keywords

  • lung cancer
  • screening
  • thoracic surgery
  • robotic surgery
  • minimally invasive surgery
  • cost-effectiveness

Published Papers (4 papers)

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Research

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12 pages, 925 KiB  
Article
Incidence of Concomitant Neoplastic Diseases, Tumor Characteristics, and the Survival of Patients with Lung Adenocarcinoma or Squamous Cell Lung Carcinoma in Tobacco Smokers and Non-Smokers—10-Year Retrospective Single-Centre Cohort Study
by Błażej Ochman, Paweł Kiczmer, Paweł Ziora, Mateusz Rydel, Maciej Borowiecki, Damian Czyżewski and Bogna Drozdzowska
Cancers 2023, 15(6), 1896; https://doi.org/10.3390/cancers15061896 - 22 Mar 2023
Cited by 2 | Viewed by 1607
Abstract
Changes in smoking trends and changes in lifestyle, together with worldwide data regarding the incidence of lung cancer in the group of patients with no previous history of smoking, leads to consideration of the differences in the course of the disease, the time [...] Read more.
Changes in smoking trends and changes in lifestyle, together with worldwide data regarding the incidence of lung cancer in the group of patients with no previous history of smoking, leads to consideration of the differences in the course of the disease, the time of cancer diagnosis, the survival rate, and the occurrence of comorbidities in this group of patients. This study aimed to determine the occurrence of non-smokers among patients undergoing anatomical resection of the lung tissue due to lung carcinoma and to investigate the differences between the course of lung cancer, survival, and the comorbidities in the groups of patients with lung cancer depending on the history of tobacco smoking. The study included a cohort of 923 patients who underwent radical anatomical resection of the lung tissue with lung primary adenocarcinoma or squamous cell carcinoma. The Chi2 Pearson’s test, the t-test, the Mann–Whitney U test, the Kaplan–Meier method, the Log-rank test with Mantel correction, and the Cox proportional hazard model were used for data analysis. We observed a significantly higher mean age of smoking patients compared to the mean age of non-smoking patients. The coexistence of former neoplastic diseases was significantly more frequent in the group of non-smokers compared to the group of smoking patients. We did not observe differences depending on smoking status in the tumor stage, grade, vascular and pleural involvement status in the diagnostic reports. We did not observe differences in the survival between smokers vs. non-smokers, however, we revealed better survival in the non-smoker women group compared to the non-smoker men group. In conclusion, 22.11% of the patients undergoing radical anatomical resection of the lung tissue due to lung cancers were non-smokers. More research on survival depending on genetic differences and postoperative treatment between smokers and non-smokers is necessary. Full article
(This article belongs to the Special Issue Lung Adenocarcinoma: Screening and Surgical Treatment)
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18 pages, 3860 KiB  
Article
Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer Learning
by Bao Feng, Xiangmeng Chen, Yehang Chen, Tianyou Yu, Xiaobei Duan, Kunfeng Liu, Kunwei Li, Zaiyi Liu, Huan Lin, Sheng Li, Xiaodong Chen, Yuting Ke, Zhi Li, Enming Cui, Wansheng Long and Xueguo Liu
Cancers 2023, 15(3), 892; https://doi.org/10.3390/cancers15030892 - 31 Jan 2023
Cited by 7 | Viewed by 1431
Abstract
Purpose: This study aimed to find suitable source domain data in cross-domain transfer learning to extract robust image features. Then, a model was built to preoperatively distinguish lung granulomatous nodules (LGNs) from lung adenocarcinoma (LAC) in solitary pulmonary solid nodules (SPSNs). Methods: Data [...] Read more.
Purpose: This study aimed to find suitable source domain data in cross-domain transfer learning to extract robust image features. Then, a model was built to preoperatively distinguish lung granulomatous nodules (LGNs) from lung adenocarcinoma (LAC) in solitary pulmonary solid nodules (SPSNs). Methods: Data from 841 patients with SPSNs from five centres were collected retrospectively. First, adaptive cross-domain transfer learning was used to construct transfer learning signatures (TLS) under different source domain data and conduct a comparative analysis. The Wasserstein distance was used to assess the similarity between the source domain and target domain data in cross-domain transfer learning. Second, a cross-domain transfer learning radiomics model (TLRM) combining the best performing TLS, clinical factors and subjective CT findings was constructed. Finally, the performance of the model was validated through multicentre validation cohorts. Results: Relative to other source domain data, TLS based on lung whole slide images as source domain data (TLS-LW) had the best performance in all validation cohorts (AUC range: 0.8228–0.8984). Meanwhile, the Wasserstein distance of TLS-LW was 1.7108, which was minimal. Finally, TLS-LW, age, spiculated sign and lobulated shape were used to build the TLRM. In all validation cohorts, The AUC ranges were 0.9074–0.9442. Compared with other models, decision curve analysis and integrated discrimination improvement showed that TLRM had better performance. Conclusions: The TLRM could assist physicians in preoperatively differentiating LGN from LAC in SPSNs. Furthermore, compared with other images, cross-domain transfer learning can extract robust image features when using lung whole slide images as source domain data and has a better effect. Full article
(This article belongs to the Special Issue Lung Adenocarcinoma: Screening and Surgical Treatment)
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16 pages, 3267 KiB  
Article
Measurement Accuracy and Repeatability of RECIST-Defined Pulmonary Lesions and Lymph Nodes in Ultra-Low-Dose CT Based on Deep Learning Image Reconstruction
by Keke Zhao, Beibei Jiang, Shuai Zhang, Lu Zhang, Lin Zhang, Yan Feng, Jianying Li, Yaping Zhang and Xueqian Xie
Cancers 2022, 14(20), 5016; https://doi.org/10.3390/cancers14205016 - 13 Oct 2022
Cited by 3 | Viewed by 1805
Abstract
Background: Deep learning image reconstruction (DLIR) improves image quality. We aimed to compare the measured diameter of pulmonary lesions and lymph nodes between DLIR-based ultra-low-dose CT (ULDCT) and contrast-enhanced CT. Methods: The consecutive adult patients with noncontrast chest ULDCT (0.07–0.14 mSv) and contrast-enhanced [...] Read more.
Background: Deep learning image reconstruction (DLIR) improves image quality. We aimed to compare the measured diameter of pulmonary lesions and lymph nodes between DLIR-based ultra-low-dose CT (ULDCT) and contrast-enhanced CT. Methods: The consecutive adult patients with noncontrast chest ULDCT (0.07–0.14 mSv) and contrast-enhanced CT (2.38 mSv) were prospectively enrolled. Patients with poor image quality and body mass index ≥ 30 kg/m2 were excluded. The diameter of pulmonary target lesions and lymph nodes defined by Response Evaluation Criteria in Solid Tumors (RECIST) was measured. The measurement variability between ULDCT and enhanced CT was evaluated by Bland-Altman analysis. Results: The 141 enrolled patients (62 ± 12 years) had 89 RECIST-defined measurable pulmonary target lesions (including 30 malignant lesions, mainly adenocarcinomas) and 45 measurable mediastinal lymph nodes (12 malignant). The measurement variation of pulmonary lesions between high-strength DLIR (DLIR-H) images of ULDCT and contrast-enhanced CT was 2.2% (95% CI: 1.7% to 2.6%) and the variation of lymph nodes was 1.4% (1.0% to 1.9%). Conclusions: The measured diameters of pulmonary lesions and lymph nodes in DLIR-H images of ULDCT are highly close to those of contrast-enhanced CT. DLIR-based ULDCT may facilitate evaluating target lesions with greatly reduced radiation exposure in tumor evaluation and lung cancer screening. Full article
(This article belongs to the Special Issue Lung Adenocarcinoma: Screening and Surgical Treatment)
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Review

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12 pages, 1366 KiB  
Review
Lung Cancer Screening: New Perspective and Challenges in Europe
by Jan P. Van Meerbeeck, Emma O’Dowd, Brian Ward, Paul Van Schil and Annemiek Snoeckx
Cancers 2022, 14(9), 2343; https://doi.org/10.3390/cancers14092343 - 9 May 2022
Cited by 11 | Viewed by 3096
Abstract
Randomized-controlled trials have shown clear evidence that lung cancer screening with low-dose CT in a high-risk population of current or former smokers can significantly reduce lung-cancer-specific mortality by an inversion of stage distribution at diagnosis. This paper will review areas in which there [...] Read more.
Randomized-controlled trials have shown clear evidence that lung cancer screening with low-dose CT in a high-risk population of current or former smokers can significantly reduce lung-cancer-specific mortality by an inversion of stage distribution at diagnosis. This paper will review areas in which there is good or emerging evidence and areas which still require investment, research or represent implementation challenges. The implementation of population-based lung cancer screening in Europe is variable and fragmented. A number of European countries seem be on the verge of implementing lung cancer screening, mainly through the implementation of studies or trials. The cost and capacity of CT scanners and radiologists are considered to be the main hurdles for future implementation. Actions by the European Commission, related to its published Europe’s Beating Cancer Plan and the proposal to update recommendations on cancer screening, could be an incentive to help speed up its implementation. Full article
(This article belongs to the Special Issue Lung Adenocarcinoma: Screening and Surgical Treatment)
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