The subtype of lung cancer that presents as subsolid nodules on imaging exhibits unique biological behavior and favorable prognosis. Recently, the American Association for Thoracic Surgery (AATS) issued "The 2023 American Associationfor Thoracic Surgery (AATS) expert consensus document: Management of subsolid lung nodules". This consensus, based on the latest literature and current clinical experience, proposes updated strategies for managing subsolid nodules. It emphasizes the correlation between imaging findings and pathological classification, individualized follow-up and surgical management strategies for subsolid nodules, and multimodal treatment approaches for multiple subsolid pulmonary nodules.
Recent research data showed the concept that "surgery is still the main treatment for early non-small cell lung cancer (NSCLC)" now has new connotation: (1) Pure ground glass nodule (GGO) like lung adenocarcinoma should be regarded as a new clinical issue compared to solid tumors to avoid over-treatment. (2) The deep meaning of multidisciplinary pathological classification of lung adenocarcinoma should be fully understood to avoid over-diagnosis. (3) The T staging of lung adenocarcinoma mixed with GGO components should be correctly understood to avoid over-staging. (4) We should carefully understand the new data of relationship between lung resection extent and prognosis to avoid excessive resection. (5) Attention should be paid to the research progress of minimal residual disease (MRD) to avoid possible insufficient treatment.
With the development of multi-slice spiral computed tomography (CT) technology and the popularization of low-dose spiral CT screening, more and more adenocarcinomas presenting ground-glass nodule (GGN) are found. Pathological invasiveness is one of the important factors affecting the choice of treatment strategy and prognosis of patients with early lung adenocarcinoma. Imaging features have attracted wide attention due to their unique advantages in predicting the pathologic invasiveness of early lung adenocarcinoma. The imaging characteristics of GGN can be used to predict the pathologic invasiveness of lung adenocarcinoma and provide evidence for clinical decisions. However, the imaging parameters and numerical values for predicting pathologic invasiveness are still controversial, which will be reviewed in this paper.
ObjectiveTo compare the effectiveness and safety of preoperative lung localization by microcoil and anchor with scaled suture.MethodsA total of 286 patients underwent CT-guided puncture localization consecutively between October 2019 and December 2020 in our hospital. According to the different methods of localization, they were divided into a microcoil group (n=139, including 49 males and 90 females, aged 57.92±10.51 years) and an anchor group (n=147, including 53 males and 94 females, aged 56.68±11.31 years). The clinical data of the patients were compared.ResultsA total of 173 nodules were localized in the microcoil group, and 169 nodules in the anchor group. The localization success rate was similar in the two groups. However, the anchor group was significantly better than the microcoil group in the localization time (8.15±2.55 min vs. 9.53±3.08 min, P=0.001), the pathological receiving time (30.46±14.41 min vs. 34.96±19.75 min, P=0.029), and the hemoptysis rate (10.7% vs. 30.1%, P=0.001), but the pneumothorax rate was higher in the anchor group (21.3% vs. 11.0%, P=0.006).ConclusionPreoperative localization of small pulmonary nodules using anchor with suture is practical and safe. Due to its simplicity and convenience, it is worth of promotion in the clinic.
Whether anatomical segmentectomy can replace lobectomy in the treatment of early-stage lung cancer remains controversial. A large number of studies have been conducted for decades to explore whether pulmonary segmentectomy can treat early-stage lung cancer, which is actually to explore the indications of intentional segmentectomy. With the development of scientific researches, it is found that many characteristics affect the malignancy of lung cancer, and the different grades of each characteristic affect the prognosis of patients. It is worth exploring whether different surgical approaches can be used for early-stage lung cancer with different characteristics and different grades. This article reviews the literature and studies to discuss the advances in indications of segmentectomy for early-stage lung in terms of tumor size, consolidation-to-tumor ratio, pathological classification and tumor location, respectively. The objective of this review is to help thoracic surgeons to objectively and scientifically select the surgical method according to the clinical characteristics of early-stage lung cancer.
ObjectiveTo establish a machine learning model based on computed tomography (CT) radiomics for preoperatively predicting invasive degree of lung ground-glass nodules (GGNs). MethodsWe retrospectively analyzed the clinical data of GGNs patients whose solid component less than 3 cm in the Department of Thoracic Surgery of Shanghai Pulmonary Hospital from March 2021 to July 2021 and the First Hospital of Lanzhou University from January 2019 to May 2022. The lesions were divided into pre-invasiveness and invasiveness according to postoperative pathological results, and the patients were randomly divided into a training set and a test set in a ratio of 7∶3. Radiomic features (1 317) were extracted from CT images of each patient, the max-relevance and min-redundancy (mRMR) was used to screen the top 100 features with the most relevant categories, least absolute shrinkage and selection operator (LASSO) was used to select radiomic features, and the support vector machine (SVM) classifier was used to establish the prediction model. We calculated the area under the curve (AUC), sensitivity, specificity, accuracy, negative predictive value, positive predictive value to evaluate the performance of the model, drawing calibration and decision curves of the prediction model to evaluate the accuracy and clinical benefit of the model, analyzed the performance in the training set and subgroups with different nodule diameters, and compared the prediction performance of this model with Mayo and Brock models. Two primary thoracic surgeons were required to evaluate the invasiveness of GGNs to investigate the clinical utility of the model. ResultsA total of 400 patients were divided into the training set (n=280) and the test set (n=120) according to the admission criteria. There were 267 females and 133 males with an average age of 52.4±12.7 years. Finally, 8 radiomic features were screened out from the training set data to build SVM model. The AUC, sensitivity and specificity of the model in the training and test sets were 0.91, 0.89, 0.75 and 0.86, 0.92, 0.60, respectively. The model showed good prediction performance in the training set 0-10 mm, 10-20 mm and the test set 0-10 mm, 10-20 mm subgroups, with AUC values of 0.82, 0.88, 0.84, 0.72, respectively. The AUC of SVM model was significantly better than that of Mayo model (0.73) and Brock model (0.73). With the help of this model, the AUC value, sensitivity, specificity and accuracy of thoracic surgeons A and B in distinguishing invasive or non-invasive adenocarcinoma were significantly improved. ConclusionThe SVM model based on radiomics is helpful to distinguish non-invasive lesions from invasive lesions, and has stable predictive performance for GGNs of different sizes and has better prediction performance than Mayo and Brock models. It can help clinicians to more accurately judge the invasiveness of GGNs, to make more appropriate diagnosis and treatment decisions, and achieve accurate treatment.
With the development and improved availability of low-dose computed tomography (LDCT), an increasing number of patients are clinically diagnosed with lung cancer manifesting as ground-glass nodules. Although radical surgery is currently the mainstay of treatment for patients with early-stage lung cancer, traditional anatomic lobectomy and mediastinal lymph node dissection (MLND) are not ideal for every patient. Clinically, it is critical to adopt an appropriate approach to pulmonary lobectomy, determine whether it is necessary to perform MLND, establish standard criteria to define the scope of lymph node dissection, and optimize the decision-making process. Thereby avoiding over- and under-treatment of lung cancer with surgical intervention and achieving optimal results from clinical diagnosis and treatment are important issues before us.
ObjectiveTo explore the feasibility and clinical value of free-of-puncture positioning in three-dimension-guided anatomical segmentectomy for ground-glass nodule (GGN) compared with percutaneous positioning.MethodsClinical data of 268 enrolled patients undergoing anatomical pulmonary segmentectomy from October 2018 to June 2019 were retrospectively collected, including 75 males and 193 females with an average age of 56.55±12.10 years. The patients were divided into two groups, including a percutaneous positioning group (n=89) and a free-of-puncture positioning group (n=179). Perioperative data of the two groups were compared.ResultsThe average CT scan times of the percutaneous positioning group was 3.01±0.98 times, and the numerical rating scale (NRS) score of puncture pain was 3.98±1.61 points. Pulmonary compression pneumothorax (≥30%) occurred in 7 (7.87%) patients and intercostal vascular hemorrhage occurred in 8 (8.99%) patients after puncture. Lung nodules were successfully found and removed in both groups. There was no statistically significant difference between the two groups in the location of nodules (P=0.466), operation time (151.83±39.23 min vs. 154.35±33.19 min, P=0.585), margin width (2.07±0.35 cm vs. 1.98±0.28 cm, P=0.750), or the number of excised subsegments (2.83±1.13 vs. 2.73±1.16, P=0.530).ConclusionAnatomical segmentectomy with three-dimensional navigation avoids the adverse consequences of puncture, which has the same clinical efficacy and meets the requirements of oncology compared with percutaneous positioning. The free-of-puncture positioning method can be used for GGN located in the central region of pulmonary segment/subsegment or adjacent to intersegment veins instead of percutaneous positioning.
With the development of technology, the detection rate of ground-glass opacity (GGO) is rapidly increasing. GGO comprises of pure GGO and mixed GGO. Many researches have studied the characteristics of GGO, and they found that different malignant probability of GGO was associated with different image characteristics. It is obvious that there is a close relationship between the image characteristics of GGO and its prognosis. However, due to the various image characteristics of GGO, it is essential to assess the prognosis of lung adenocarcinoma patients in a more comprehensive way. In this review, we summarize the correlation between the main GGO image features (solid proportion, size, mean CT value, shape characteristics) and the prognosis of lung adenocarcinoma patients, to provide clinical reference for prognosis prediction and decision-making for patients with lung adenocarcinoma.