Mediastinal Lymph Node Stations Research Articles

Prognostic significance and risk factors of mediastinal lymph node metastasis in esophagogastric junction cancer: a single-center, retrospective study.

Although the optimal extent of lymph node dissection in esophagogastric junction cancer (EGJC) has been reported, the efficacy of mediastinal lymph node dissection remains unclear. We aimed to identify risk factors for mediastinal lymph node metastasis and its prognostic impact in patients with EGJC. A total of 100 consecutive patients who underwent curative surgery for EGJC were eligible. We examined the rates of metastasis, prognosis, and therapeutic value index at each mediastinal lymph node station. In addition, multivariate analyses were performed to identify risk factors for mediastinal lymph node metastasis. The rates of upper, middle, and lower mediastinal lymph node metastases were 12.0%, 20.7%, and 13.2%, respectively. The 5-year overall survival rate was lower in patients with mediastinal lymph node metastasis than in those without mediastinal lymph node metastasis (11.1% vs. 59.2%, p < 0.01). The therapeutic value index was 0 in patients with upper/middle mediastinal lymph node metastasis, and mediastinal lymph node metastasis was an independent prognostic factor (hazard ratio 6.59, 95% confidence interval [CI] 2.48-17.9, p < 0.01). Additionally, the length of esophageal invasion and the presence of hiatal hernia were independent predictors of mediastinal lymph node metastasis (odds ratio 8.21, 95%CI 1.44-46.8, p = 0.02 and odds ratio 7.13, 95%CI 1.22-41.8, p = 0.03). No survival benefit of mediastinal lymph node dissection was observed. Intensive multidisciplinary treatment could be considered in patients with predicted mediastinal lymph node metastasis, such as those with longer esophageal invasion and those with hiatal hernia.

Impact of imaging features on selecting limited lymph node resection for cT1N0M0 lung cancer.

Controversy still exists in the medical community regarding the performance of limited mediastinal lymphadenectomy (LML) in early-stage lung cancer. The objective of this study was to identify predictors of mediastinal lymph node (mLN) status and analyze its role in guiding surgical strategy. A retrospective cohort study was conducted on 2,834 surgical patients with peripheral cT1N0M0 non-small cell lung cancer between 2016 and 2018. Logistic regression was employed to identify predictors of N2 metastasis. Prognosis was compared between groups and independent prognostic factors were identified using Kaplan-Meier and multivariate Cox analysis. There were 2,126 patients with systematic mLN dissection and 708 with LML. The multivariate analysis showed that N2 metastasis were associated with tumor size and consolidation tumor ratio (CTR). Patients in group A, with CTR >0.5 and tumor size ≤1 cm or CTR ≤0.5, had a significantly lower rate of N2 metastasis compared to those in group B, with CTR >0.5 and tumor size >1 cm (14.2% vs. 0.2%, P<0.001). Additionally, LML demonstrated comparable recurrence-free survival (RFS) and overall survival (OS) in group A, but a worse prognosis in group B compared to systematic lymph node dissection (SND). Furthermore, multivariate Cox regression analysis indicated that SND (vs. LML) was a favorable prognostic predictor for patients in group B [RFS: hazard ratio (HR) =0.71, P=0.005; OS: HR =0.66, P=0.01]. But univariate analysis in group A showed no significant difference in prognosis between SND and LML (RFS: P=0.24; OS: P=0.10). The combination of CTR and tumor size can predict mLN metastasis and procedure-specific outcome (SND vs. LML). This information may assist surgeons in identifying suitable candidates for LML.

Application of tissue pneumoperitoneum technique around lymph nodes in thoracoscopic lung cancer resection.

Thoracoscopic surgery is a primary treatment for lung cancer, with lobectomy and mediastinal lymph node dissection being the predominant surgical approaches for invasive lung cancer. While many thoracic surgeons can proficiently perform lobectomy, thorough and standardized lymph node dissection remains challenging. This study aimed to explore a safer and more efficient surgical method for mediastinal lymph node dissection in lung cancer. A prospective randomized controlled study was conducted, involving 100 patients with right lung cancer who were admitted to our hospital from January 2021 to April 2024 and met the inclusion criteria. These patients were randomly divided into an observation group (tissue pneumoperitoneum technique around lymph nodes group) and a control group (conventional surgery group). Thoracoscopic lobectomy and mediastinal lymph node dissection were performed. Intraoperative and postoperative related indicators were observed to validate the effectiveness and safety of the tissue pneumoperitoneum technique around lymph nodes. The observation group showed a significantly shorter lymph node dissection surgery time compared to the control group, with a statistically significant difference (p < 0.05). The number of lymph nodes dissected in the observation group was significantly higher than that in the control group, with a statistically significant difference (p < 0.05). Although the observation group had slightly more mediastinal lymph node stations dissected than the control group, the difference was not statistically significant (p > 0.05). The total drainage volume within three days postoperatively was comparable between the two groups, with no statistically significant difference (p > 0.05). The observation group had shorter chest tube indwelling time and postoperative hospital stay than the control group, with statistically significant differences (p < 0.05). The incidence of surgical complications was similar between the two groups, and there were no perioperative deaths. The tissue pneumoperitoneum technique around lymph nodes is a more efficient method for mediastinal lymph node dissection in lung cancer, demonstrating safety and feasibility, and is worthy of promotion.

Impact of preoperative inflammatory indices and postoperative pneumonia on postoperative atrial fibrillation in patients with non-small cell lung cancer: a retrospective study

BackgroundThis study aimed to evaluate the impact of preoperative inflammatory indices and postoperative pneumonia (POP) on postoperative atrial fibrillation (POAF) in non–small cell lung cancer (NSCLC) patients.MethodsAll consecutive patients who underwent pulmonary resection at our hospital (January 2016-October 2019) were enrolled. Preoperative inflammatory indices, demographic data, surgical details, and postoperative conditions were analyzed. Univariate and multivariate analyses of risk factors associated with POAF were also conducted.ResultsAmong the 382 patients included in the study, 32 (8.38%) developed POAF. Compared to non-POAF patients, POAF patients had greater incidence of POP (P = 0.09). Approximately 31 patients (96.9%) developed atrial fibrillation within three days after surgery. The POAF group had a significantly greater mean age (68.94 years) than did the non-POAF group (63 years) (P = 0.002). Additionally, compared to non-POAF patients, POAF patients exhibited an increased number of resected mediastinal lymph nodes (P < 0.001) and mediastinal lymph node stations (P < 0.001).The POAF group also had a greater intraoperative blood volume (P = 0.006), longer surgical duration (P = 0.022), and greater drainage volume (P = 0.003). IA/B stage (P < 0.001) and IIIA/B stage(P < 0.001), and lobectomy resection (P = 0.008) and wedge resection (P = 0.023) were also associated with POAF. Compared to those in the non-POAF group, the POAF group had longer postoperative hospital stays (10.54 days vs. 9 days; P = 0.001) and longer drainage times (7 days vs. 5 days; P = 0.004). Multivariate analysis revealed age, POP, and stage IIIA/B as independent influencing factors of POAF in NSCLC patients.ConclusionPreoperative inflammatory indices were not significantly associated with POAF, but age, POP, and stage IIIA/B were identified as independent influencing factors. Advanced-stage NSCLC patients may have a greater susceptibility to POAF than early-stage patients, although further validation is needed. Additionally, POAF was linked to a longer postoperative hospital stay.

July 2024 Medical Image of the Month: Vocal Cord Paralysis on PET-CT

No abstract available. Article truncated after 150 words. A 60-year-old woman with a past medical history of hypertension, rheumatoid arthritis, and a significant smoking history (40+ pack-years) presented with a 3-month history of hoarseness of voice as well as a 10 lb weight loss over a 5-month period. Chest CT revealed a spiculated left upper lobe nodule (Figure 1A). Additionally, there was evidence of bulky mediastinal and left hilar lymphadenopathy (Figure 1B). A subsequent 17-FDG PET-CT (Figure 2) demonstrated marked metabolic activity in the left upper lobe nodule with an SUV maximum of 9.1. Metabolically active mediastinal and left hilar lymphadenopathy was also noted with an SUV maximum of 5.9. Interestingly, increased metabolic activity of the right vocal cord compared to the left was noted on the PET scan (Figure 2B). Direct laryngoscopy, performed during intubation for a diagnostic bronchoscopy and endobronchial ultrasound, confirmed left vocal cord paralysis. EBUS sampling of multiple mediastinal hilar lymph node stations, including …

Prediction of metastases in confusing mediastinal lymph nodes based on flourine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging using machine learning.

For patient management and prognosis, accurate assessment of mediastinal lymph node (LN) status is essential. This study aimed to use machine learning approaches to assess the status of confusing LNs in the mediastinum using positron emission tomography/computed tomography (PET/CT) images; the results were then compared with the diagnostic conclusions of nuclear medicine physicians. A total of 509 confusing mediastinal LNs that had undergone pathological assessment or follow-up from 320 patients from three centres were retrospectively included in the study. LNs from centres I and II were randomised into a training cohort (N=324) and an internal validation cohort (N=81), while those from centre III patients formed an external validation cohort (N=104). Various parameters measured from PET and CT images and extracted radiomics and deep learning features were used to construct PET/CT-parameter, radiomics, and deep learning models, respectively. Model performance was compared with the diagnostic results of nuclear medicine physicians using the area under the curve (AUC), sensitivity, specificity, and decision curve analysis (DCA). The coupled model of gradient boosting decision tree-logistic regression (GBDT-LR) incorporating radiomic features showed AUCs of 92.2% [95% confidence interval (CI), 0.890-0.953], 84.6% (95% CI, 0.761-0.930) and 84.6% (95% CI, 0.770-0.922) across the three cohorts. It significantly outperformed the deep learning model, the parametric PET/CT model and the physician's diagnosis. DCA demonstrated the clinical usefulness of the GBDT-LR model. The presented GBDT-LR model performed well in evaluating confusing mediastinal LNs in both internal and external validation sets. It not only crossed radiometric features but also avoided overfitting.

Combining machine and deep transfer learning for mediastinal lymph node evaluation in patients with lung cancer

BackgroundThe prognosis and survival of patients with lung cancer are likely to deteriorate with metastasis. Using deep-learning in the detection of lymph node metastasis can facilitate the noninvasive calculation of the likelihood of such metastasis, thereby providing clinicians with crucial information to enhance diagnostic precision and ultimately improve patient survival and prognosis MethodsIn total, 623 eligible patients were recruited from two medical institutions. Seven deep learning models, namely Alex, GoogLeNet, Resnet18, Resnet101, Vgg16, Vgg19, and MobileNetv3 (small), were utilized to extract deep image histological features. The dimensionality of the extracted features was then reduced using the Spearman correlation coefficient (r ≥ 0.9) and Least Absolute Shrinkage and Selection Operator. Eleven machine learning methods, namely Support Vector Machine, K-nearest neighbor, Random Forest, Extra Trees, XGBoost, LightGBM, Naive Bayes, AdaBoost, Gradient Boosting Decision Tree, Linear Regression, and Multilayer Perceptron, were employed to construct classification prediction models for the filtered final features. The diagnostic performances of the models were assessed using various metrics, including accuracy, area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, and negative predictive value. Calibration and decision-curve analyses were also performed. ResultsThe present study demonstrated that using deep radiomic features extracted from Vgg16, in conjunction with a prediction model constructed via a linear regression algorithm, effectively distinguished the status of mediastinal lymph nodes in patients with lung cancer. The performance of the model was evaluated based on various metrics, including accuracy, area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, and negative predictive value, which yielded values of 0.808, 0.834, 0.851, 0.745, 0.829, and 0.776, respectively. The validation set of the model was assessed using clinical decision curves, calibration curves, and confusion matrices, which collectively demonstrated the model's stability and accuracy ConclusionIn this study, information on the deep radiomics of Vgg16 was obtained from computed tomography images, and the linear regression method was able to accurately diagnose mediastinal lymph node metastases in patients with lung cancer.

Minimally Invasive with Maximal Yield: A Narrative Review of Current Practices in Mediastinal Lymph Node Staging in Non-Small Cell Lung Cancer.

Background: Lung cancer remains the leading cause of cancer deaths in the United States despite declining incidence and improved outcomes because of advancements in early detection and development of novel therapies. Accurate mediastinal lymph node staging is crucial for determining prognosis and guiding treatment decisions, particularly for non-small cell lung cancer (NSCLC). Materials and Methods: A systematic search of PubMed was conducted to identify English language articles published between January 2010 and January 2024 focusing on preoperative lymph node staging in adults with NSCLC. Case series, observational studies, randomized trials, guidelines, narrative reviews, systematic reviews, and meta-analyses were included. Results: Various imaging modalities, surgical and nonsurgical procedures for mediastinal lymph node staging were reviewed, including positron emission tomography with computed tomography, cervical mediastinoscopy, video-assisted cervical mediastinoscopy, anterior mediastinotomy, video-assisted thoracoscopy, endobronchial ultrasound-guided fine needle aspiration (EBUS-FNA), transesophageal endoscopic ultrasound-guided fine needle aspiration (EUS-FNA), and computed tomography-guided percutaneous lymph node biopsy. EBUS-FNA emerged as the preferred initial staging procedure because of its high sensitivity and low complication rate. Combining it with other procedures or confirmatory testing may be helpful in determining appropriate treatment. Conclusions: Although cervical mediastinoscopy remains a valuable confirmatory procedure in select cases, its role as a first-line staging modality is diminishing with the widespread adoption of EBUS-FNA and EUS-FNA. The combination of EBUS-FNA and EUS-FNA allows access to nearly all mediastinal lymph node stations with high diagnostic accuracy. Future research may further refine the selection criteria for invasive mediastinal staging procedures, ultimately optimizing patient outcomes in the management of NSCLC.

The International Association for the Study of Lung Cancer Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groups in the Forthcoming (Ninth) Edition of the TNM Classification for Lung Cancer

IntroductionThe TNM classification of lung cancer is periodically revised. The International Association for the Study of Lung Cancer collected and analyzed a new database to inform the forthcoming ninth edition of the TNM classification. The results are herewith presented. MethodsAfter exclusions, 76,518 patients from a total of 124,581 registered patients were available for analyses: 58,193 with clinical stage, 39,192 with pathologic stage, and 62,611 with best stage NSCLC. The proposed new N2 subcategories (N2a, involvement of single ipsilateral mediastinal or subcarinal nodal station, and N2b, involvement of multiple ipsilateral mediastinal nodal stations with or without involvement of the subcarinal nodal station) and the new M1c subcategories (M1c1, multiple extrathoracic metastases in one organ system, and M1c2, multiple extrathoracic metastases in multiple organ systems) were considered in the survival analyses. Several potential stage groupings were evaluated, using multiple analyses, including recursive partitioning, assessment of homogeneity within and discrimination between potential groups, clinical and statistical significance of survival differences, multivariable regression, and broad assessment of generalizability. ResultsT1N1, T1N2a, and T3N2a subgroups are assigned to IIA, IIB, and IIIA stage groups, respectively. T2aN2b and T2bN2b subgroups are assigned to IIIB. M1c1 and M1c2 remain in stage group IVB. Analyses reveal consistent ordering, discrimination of prognosis, and broad generalizability of the proposed ninth edition stage classification of lung cancer. ConclusionsThe proposed stages for the ninth edition TNM improve the granularity of nomenclature about anatomic extent that has benefits as treatment approaches become increasingly differentiated and complex.

Preoperative mediastinal staging in early-stage lung cancer: Targeted nodal sampling is not inferior to systematic nodal sampling

ObjectiveTo determine whether targeted sampling (TS), which omits biopsy of triple- normal lymph nodes (LNs) on positron emission tomography, computed tomography, and endobronchial ultrasound (EBUS), is noninferior to systematic sampling (SS) of mediastinal LNs during EBUS for staging of patients with early-stage non–small cell lung cancer (NSCLC). MethodsPatients who are clinical nodal (cN)0-N1 with suspected NSCLC eligible for EBUS based on positron emission tomography/computed tomography were enrolled in this prospective, multicenter trial. During EBUS, all patients underwent TS and then crossed over to SS, whereby at least 3 mediastinal LN stations (4R, 4L, 7) were routinely sampled. Gold standard of comparison was pathologic results. Based on the previous feasibility trial, a noninferiority margin of 6% was established for difference in missed nodal metastasis (MNM) incidence between TS and SS. The McNemar test on paired proportions was used to determine MNM incidence for each sampling method. Analysis was per-protocol using a level of significance of P < .05. ResultsBetween November 2020 and April 2022, 91 patients were enrolled at 6 high-volume Canadian tertiary care centers. A total of 256 LNs underwent TS and SS. Incidence of MNM was 0.78% in SS and 2.34% in TS, with an absolute difference of 1.56% (95% confidence interval, −0.003% to 4.1%; P = .13). This falls within the noninferiority margin. A total of 6/256 LNs from 4 patients who were not sampled by TS were found to be malignant when sampled by SS. ConclusionsIn high-volume thoracic endosonography centers, TS is not inferior to SS in nodal staging of early-stage NSCLC. This results in change of clinical management for a minority of patients.

Deep Learning for Automatic Prediction of Lymph Node Station Metastasis in Esophageal Cancer Patients from Contrast-Enhanced CT

The diagnosis of lymph node (LN) metastasis in computed tomography (CT) is an essential yet challenging task in esophageal cancer staging and treatment planning. Although criteria (e.g., RECIST, morphological/texture features) are proposed to predict LN metastasis, the diagnostic accuracy remains low with sensitivity <50% and specificity <75%, as reported in previous studies. Deep learning (DL) has the potential to address this issue by learning from large-scale labeled data. However, due to the practical surgery procedure in lymph node dissection, it is difficult to pair the metastasis of individual LN reported in the pathology report to the LN instance found in the CT image. Hence, in this study, we first use pathology reports to determine the LNS metastasis, then develop a multiple instance deep learning (MIDL) model to predict lymph node station (LNS) metastasis. We collected 1200 esophageal cancer patients with preoperative contrast-enhanced CT before surgery. A recently developed automatic mediastinal LNS segmentation model was first applied to segment LNS of 1 to 8 based on the IASLC protocol. For each LNS, the local CT region of interest (ROI) was cropped to generate a station-wise CT patch, where the LNS was labeled as metastatic if at least one metastatic LN was indicated in the pathology report. Using the station-wise CT patch and LNS label, we train a 3D MIDL model, MobileNetV3, to predict LNS metastasis. To better provide the LN position priors in MIDL, LN instances (with a short axis >4mm) were also segmented using an automatic LN detection algorithm and were added to the MIDL model as an auxiliary input. Five-fold cross-validation was conducted to evaluate the MIDL performance. The MIDL model's performance is summarized in Table 1. The MIDL model incorporating an additional LN instance mask demonstrated a superior overall AUC of 0.7539, surpassing the model without the LN mask input by 2.93%. The specificity was evaluated at a threshold resulting in a recall of 0.7, and the best model outperformed the CT input model in terms of specificity by 2.11%. This highlights the value of including the LN position prior to the MIDL model. Notably, when a threshold was set to result in a specificity of 75%, the best MIDL model demonstrated a significantly higher recall compared to the previously reported clinical diagnostic recall (39.7% vs. 63.21%). We developed a MIDL classification model to predict LNS metastasis using CT scans of 1200 patients. Our findings suggest that the MIDL model can substantially improve LNS metastasis prediction and has the potential to play an essential role in cancer staging, treatment planning, and prognostic analysis.

Prognostic Significance of the Proposed Residual Tumor Classification in Patients With NSCLC After Sleeve Lobectomy

IntroductionTo validate the residual tumor (R) classification proposed by the International Association for the Study of Lung Cancer (IASLC) in NSCLC after sleeve lobectomy. MethodsA total of 682 patients were analyzed. The R status, on the basis of the Union for International Cancer Control (UICC) criteria, was recategorized according to the IASLC descriptors. Recurrence-free survival (RFS) and overall survival (OS) among different R classifications were assessed for the entire cohort and pathologic node (pN) subgroups. ResultsAll in all, 631 (92.5%), 48 (7.1%), and three patients (0.4%) were classified as R0, R1, and R2, respectively, by the UICC criteria, whereas 489 (71.7%), 110 (16.1%), and 83 patients (12.2%), received R0, uncertain resection (R[un]), and R1/2 resection, respectively, according to the IASLC criteria. There were 96 patients (15.2%) with UICC R0 who were reclassified as R(un), mainly because of the positive highest mediastinal node station (82 of 96, 85.4%). A total of 46 patients (7.3%) were reassigned from UICC R0 to IASLC R1/2 owing to extracapsular extension. For the entire cohort, patients with R(un) and R1/2 exhibited worse RFS (R[un], adjusted p = 0.023; R1/2, adjusted p = 0.001) and OS (R[un], adjusted p = 0.040; R1/2, adjusted p = 0.051) compared with R0. No significant differences were observed between R(un) and R1/2 (RFS, adjusted p = 0.586; OS, adjusted p = 0.781). Furthermore, subgroup analysis revealed a distinct prognostic impact of the IASLC R status—with prognostic significances in the pN1 and pN2 subgroups, but not in the pN0 subgroup. ConclusionsThe IASLC R descriptors helped to stratify the prognosis of NSCLC after sleeve lobectomy, with its prognostic impact varied among pN stages.

Comparison of deep learning-based recurrence-free survival with random survival forest and Cox proportional hazard models in Stage-I NSCLC patients.

The curative treatment for Stage I non-small cell lung cancer (NSCLC) is surgical resection. Even for Stage I patients, the probability of recurrence after curative treatment is around 20%. In this retrospective study, we included 268 operated Stage I NSCLC patients between January 2008 and June 2018 to analyze the prognostic factors (pathological stage, histological type, number of sampled mediastinal lymph node stations, type of resection, SUVmax of the lesion) that may affect relapse with three different methods, Cox proportional hazard (CoxPH), random survival forest (RSF), DeepSurv, and to compare the performance of these methods with Harrell's C-index. The dataset was randomly split into two sets, training and test sets. In the training set, DeepSurv showed the best performance among the three models, the C-index of the training set was 0.832, followed by RSF (0.675) and CoxPH (0.672). In the test set, RSF showed the best performance among the three models, followed by DeepSurv with 0.677 and CoxPH methods with 0.625. In conclusion, machine-learning techniques can be useful in predicting recurrence for lung cancer and guide clinicians both in choosing the adjuvant treatment options and best follow-up programs.

Identification of Factors Related to the Quality of Lymphadenectomy for Lung Cancer: Secondary Analysis of Prospective Randomized Trial Data.

The outcomes of non-small cell lung cancer surgery are influenced by the quality of lymphadenectomy. This study aimed to evaluate the impact of different energy devices on lymphadenectomy quality and identify additional influencing factors. This secondary analysis of the prospective randomized trial data (clinicaltrials.gov: NCT03125798) compared patients who underwent thoracoscopic lobectomy with the LigaSure device (study group, n = 96) and monopolar device (control group, n = 94). The primary endpoint was the lobe-specific mediastinal lymphadenectomy. Lobe-specific mediastinal lymphadenectomy criteria were met in 60.4% and 38.3% of patients in the study and control groups, respectively (p = 0.002). In addition, in the study group, the median number of mediastinal lymph node stations removed was higher (4 vs. 3, p = 0.017), and complete resection was more often achieved (91.7% vs. 80.9%, p = 0.030). Logistic regression analysis indicated that lymphadenectomy quality was positively associated with the use of the LigaSure device (OR, 2.729; 95% CI, 1.446 to 5.152; p = 0.002) and female sex (OR, 2.012; 95% CI, 1.058 to 3.829; p = 0.033), but negatively associated with a higher Charlson Comorbidity Index (OR, 0.781; 95% CI, 0.620 to 0.986; p = 0.037), left lower lobectomy (OR, 0.263; 95% CI, 0.096 to 0.726; p = 0.010) and middle lobectomy (OR, 0.136; 95% CI, 0.031 to 0.606, p = 0.009). This study found that using the LigaSure device can improve the quality of lymphadenectomy in lung cancer patients and also identified other factors that affect the quality of lymphadenectomy. These findings contribute to improving lung cancer surgical treatment outcomes and provide valuable insights for clinical practice.

A National Survey of Surgeons Evaluating the Accuracy of Mediastinal Lymph Node Identification

The Commission on Cancer implemented Standard 5.8 in 2021, which requires removal of 3 mediastinal nodes and 1 hilar node with lung cancer resection. We conducted a national survey to assess whether surgeons who treat lung cancer in different clinical settings correctly identify mediastinal lymph node stations. Cardiac or thoracic surgeons expressing interest in lung cancer surgery on the Cardiothoracic Surgery Network were asked to complete a 7-question survey assessing their knowledge of lymph node anatomy. General surgeons whose practice includes thoracic surgery were invited through American College of Surgeon's Cancer Research Program. Results were analyzed using Pearson's chi-square test. Multivariable linear regression was used to identify predictors of a higher score on the survey. Of the 280 surgeons that responded, 86.8% were male and 13.2% were female; the median age was 50 years. Of these surgeons, 211 (75.4%) were thoracic, 59 (21.1%) were cardiac, and 10 (3.6%) were general surgeons. Surgeons were most likely to correctly identify lymph node stations 8R and 9R and least likely to correctly identify the midline pretracheal node just superior to the carina (4R). Surgeons whose practice involved a greater percentage of thoracic surgery patients and surgeons who performed a greater number of lobectomies scored higher on the lymph node assessment. Knowledge of mediastinal node anatomy among surgeons who perform thoracic surgery is generally high, but varies by clinical setting. Efforts are under way to better educate lung cancer surgeons on nodal anatomy, and to increase adoption of Standard 5.8.

Real world practice of postoperative radiotherapy for patients with completely resected pIIIA-N2 non-small cell lung cancer: a national survey of radiation oncologists in China

BackgroundResults from Lung ART and PORT-C trials suggest that postoperative radiotherapy (PORT) cannot routinely be recommended as standard treatment in completely resected pIIIA-N2 NSCLC patients, but their effects on the real-world practice of PORT in China remain unclear.MethodsA national cross-section survey was conducted by using an online survey service. Participants were voluntarily recruited using a river sampling strategy. A link to the survey was posted on websites of radiation oncologist associations and tweets from public WeChat accounts. The survey collected the real names of participants to ensure that they were board-certified radiation oncologists.ResultsA total of 484 radiation oncologists were included with a median age of 40 years (IQR, 35–47). A total of 377 (77.9%) participants were male, and 282 (58.1%) had more than 10 years of clinical experience practicing thoracic radiotherapy. Before Lung ART and PORT-C trials were published, 313 (64.7%) respondents recommended PORT, 11 (2.3%) did not recommend it, and 160 (33.1%) reported that they made decisions based on risk factors. After the presentation of two trials, only 42 (8.7%) did not recommend PORT, while 108 (22.3%) recommended it, and 334 (69.0%) made decisions based on risk factors. The five most commonly considered risk factors among these 334 respondents were as follows: nodal extracapsular extension, the highest lymph node (LN) station involved, the number of dissected mediastinal LN stations, the number of positive mediastinal LN stations, and surgical approaches. In addition, the majority of all 484 respondents recommended a total dose of 50 Gy, lung stump + ipsilateral hilus + regions containing positive LNs as the targeted region, lung V20 < 25%, and heart V30 < 40% as dose constraints for PORT.ConclusionMost Chinese radiation oncologists recommended PORT for completely resected IIIA-N2 NSCLC patients based on risk factors, especially status of LN station.

Visualization of patterns of lymph node metastases in non–small cell lung cancer using network analysis

ObjectiveWe aimed to visualize complicated patterns of lymph node metastases in surgically resected non–small cell lung cancer by applying a data mining technique. MethodsIn this retrospective study, 783 patients underwent lobectomy or pneumonectomy with systematic mediastinal lymph node dissection for non–small cell lung cancer between January 2010 and December 2018. Surgically resected lymph nodes were classified according to the International Association for the Study of Lung Cancer lymph node map. Network analysis generated patterns of lymph node metastases from stations 1 to 14, and the degree of connection between 2 lymph node stations was assessed. ResultsThe median number of lymph nodes examined per patient was 20, and the pathological N category was pN0 in 428 cases, pN1 in 132, pN2 in 221, and pN3 in 2. N1 lymph node stations had strong associations with superior mediastinal lymph node stations for patients with primary tumors in the upper lobes and with station 7 for the lower lobes. There was also a connection from the N1 lymph node stations to superior mediastinal lymph node stations in the lower lobes. In the right middle lobe, an even distribution from station 12m toward stations 2R, 4R, and 7 was noted. We released an interactive web application to visualize these data: http://www.canexapp.com. ConclusionsLymph node metastasis patterns differed according to the lobe bearing the tumor. Our results support the need for clinical trials to further investigate selective mediastinal lymph node dissection.

AN ALTERNATE APPROACH: TRANSESOPHAGEAL BRONCHOSCOPIC ULTRASOUND-GUIDED FINE NEEDLE ASPIRATION (EUS-B-FNA) TO ASSESS PLEURAL MESOTHELIOMA

AN ALTERNATE APPROACH: TRANSESOPHAGEAL BRONCHOSCOPIC ULTRASOUND-GUIDED FINE NEEDLE ASPIRATION (EUS-B-FNA) TO ASSESS PLEURAL MESOTHELIOMA

Transesophageal Endoscopic Ultrasound Fine Needle Biopsy for the Diagnosis of Mediastinal Masses: A Retrospective Real-World Analysis.

Background: Endoscopic ultrasound (EUS) plays an important role in the diagnosis and staging of thoracic disease. Our report studies the diagnostic performance and clinical impact of EUS fine needle aspiration (FNA) in a homogenous cohort of patients according to the distribution of the enlarged MLNs or pulmonary masses. Methods: We retrospectively reviewed the diagnostic performance of 211 EUS-FNA in 200 consecutive patients with enlarged or PET-positive MLNs and para-mediastinal masses who were referred to our oncological center between January 2019 and May 2020. Results: The overall sensitivity of EUS-FNA was 85% with a corresponding negative predictive value (NPV) of 56% and an accuracy of 87.5%. The sensitivity and accuracy in patients with abnormal MLNs were 81.1% and 84.4%, respectively. In those with para-mediastinal masses, sensitivity and accuracy were 96.4% and 96.8%. The accuracy for both masses and lymph nodes was 100%, and in the LAG (left adrenal gland), it was 66.6%. Conclusions: Our results show that, in patients with suspected mediastinal masses, EUS-FNA is an accurate technique to evaluate all reachable mediastinal nodal stations, including station 5.

When a segmentectomy is not a segmentectomy: Quality assurance audit and evaluation of required elements for an anatomic segmentectomy

ObjectiveThe advent of lung cancer screening and detection of smaller nodules amplifies the need to clarify the oncological quality of sublobar resections. Furthermore, studies comparing sublobar resections to lobectomies offer conflicting conclusions. We hypothesize that this is driven, in part, by inconsistency in reporting; that is, variable interpretation of what constitutes an operative segment. Without an established standard, 2 very different operations may be reported as segmental resections, leaving the data on sublobar approaches subject to interpretative variability. MethodsA retrospective audit was performed on all segmental resections from May 2016 to December 2019 at Brigham and Women's Hospital. Pathology and operative reports were reviewed, with particular attention to the dissection of the component artery, vein, and bronchus. Resections with dissection and division of at least 1 major vascular structure (the segmental artery or vein), as well as the segmental bronchus, met operative criteria for anatomic segmentectomy. Surgical quality metrics were compared between the 2 groups. ResultsThere were 271 segmental resections: 219 (80.8%) were anatomic segmentectomies and 52 (19.2%) were nonanatomic segmentectomies. For the entire cohort, nonanatomic segmentectomies had smaller margins (1.0 vs 1.5 cm; P = .02), fewer lymph nodes (2.0 vs 6.0; P < .001), and fewer mediastinal lymph node stations sampled (1.0 vs 2.0; P < .001). Similarly, there were smaller margins (1.5 vs 1.8 cm; P = .03), fewer lymph nodes (2.0 vs 6.0; P < .001), and fewer mediastinal lymph node stations sampled (1.0 vs 2.0; P < .001) in nonanatomic segmentectomies for non–small cell lung cancer. ConclusionsNearly 20% of reported segmentectomies may not meet criteria for true segmental resection. Therefore, prior studies may need further scrutiny to clarify outcomes and results. Establishing a professional standard may help mitigate ambiguity in published data on this subject.