For decades, lung surgery in thoracic cancer has evolved in two ways: saving more parenchyma and being minimally invasive. Saving parenchyma is a fundamental principle of surgery. However, minimally invasive surgery (MIS) is a matter of approach, so it has to do with advances in surgical techniques and tools. For example, MIS has become possible with the introduction of VATS (video-assisted thoracic surgery), and the development of tools has extended the indication of MIS. Especially, RATS (robot-assisted thoracic surgery) improved the quality of life for patients and the ergonomics of doctors. However, the dichotomous idea that the MIS is new and right but the open thoracotomy is old and useless may be inappropriate. In fact, MIS is exactly the same as a classic thoracotomy in that it removes the mass/parenchyma containing cancer and mediastinal lymph nodes. Therefore, in this study, we compare randomized-controlled trials about open thoracotomy and MIS to find out which surgical method is more helpful.

Dohun Kim, M.D., Ph.D., Jung-Won Lee, Ph.D.. J Chest Surg 2022;55:1-9. https://doi.org/10.5090/jcs.21.105

The first step in treating lung cancer is to establish the stage of the disease, which in turn determines the treatment options and prognosis of the patient. Many factors are involved in lung cancer staging, but all involve anatomical information. However, new approaches, mainly those based on the molecular biology of cancer, have recently changed the paradigm for lung cancer treatment and have not yet been incorporated into staging. In a group of patients of the same stage who receive the same treatment, some may experience unexpected recurrence or metastasis, largely because current staging methods do not reflect the findings of molecular biological studies. In this review, we provide a brief summary of the latest research on lung cancer staging and the molecular events associated with carcinogenesis. We hope that this paper will serve as a bridge between clinicians and basic researchers and aid in our understanding of lung cancer.

Artificial intelligence (AI) techniques can be a solution for delayed or misdiagnosed pneumothorax. This study developed, a deep-learning-based AI model to estimate the pneumothorax amount on a chest radiograph and applied it to a treatment algorithm developed by experienced thoracic surgeons. U-net performed semantic segmentation and classification of pneumothorax and non-pneumothorax areas. The pneumothorax amount was measured using chest computed tomography (volume ratio, gold standard) and chest radiographs (area ratio, true label) and calculated using the AI model (area ratio, predicted label). Each value was compared and analyzed based on clinical outcomes. The study included 96 patients, of which 67 comprised the training set and the others the test set. The AI model showed an accuracy of 97.8%, sensitivity of 69.2%, a negative predictive value of 99.1%, and a dice similarity coefficient of 61.8%. In the test set, the average amount of pneumothorax was 15%, 16%, and 13% in the gold standard, predicted, and true labels, respectively. The predicted label was not significantly different from the gold standard (p = 0.11) but inferior to the true label (difference in MAE: 3.03%). The amount of pneumothorax in thoracostomy patients was 21.6% in predicted cases and 18.5% in true cases.

Dohun Kim, M.D., Ph.D.. Korean J Thorac Cardiovasc Surg 2020;53:233-41. https://doi.org/10.5090/kjtcs.2020.53.4.233

Background: Studies on the clinical implication of hospital selection for patients with lung cancer are few. Therefore, this study aimed to analyze 2005–2016 data from the Korean national database to assess annual trends of lung cancer surgery and clinical outcomes according to hospital selection.Methods: Data of 212 554 patients with lung cancer who underwent upfront surgery were screened. Trends according to sex, age, residence, and income were examined. Descriptive statistics were performed, and p_trend values were estimated. The association between survival and hospital selection was assessed using the log‐rank test. A multivariate Cox regression analysis was also performed.Results: A total of 49 021 patients were included in this study. Surgery was prevalent among men, patients aged 61–75 years, capital area residents, and high‐income patients. However, with the increasing rate of surgery among women, patients aged ≥76 years, city residents, and middle‐income patients, the current distribution of lung cancer surgery could change. The rate of lobectomy among these groups increased. All patients, except those in capital areas, preferred a hospital outside their area of residence (HOR); the number of patients with this tendency also increased. However, this trend was not observed among low‐income patients and those aged ≥76 years. There were significant differences in survival according to hospital selection.Conclusions: The trend of lung cancer surgery is changing. The current medical system is effective in providing lobectomy for patients including women, aged ≥76 years, city residents, and middle‐income. Increasing tendency to choose an HOR requires further study.