The value of enhanced CT scanning for predicting lymph node metastasis along the right recurrent laryngeal nerve in esophageal squamous cell carcinoma

Value of Computed Tomography Scan for Detecting Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma

BACKGROUND

The necessity of computed tomography (CT) scan for detecting potential lymph node metastasis (LNM) in early esophageal squamous cell carcinoma (ESCC) before endoscopic and surgical treatments is under debate.

METHODS

Patients with histologically proven ESCC limited to the mucosa or submucosa were examined retrospectively. Diagnostic performance of CT for detecting LNM was analyzed by comparing original CT reports with pathology reports. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

RESULTS

A total of 625 patients from three tertiary referral hospitals were included. The rate of pathologically confirmed LNM was 12.5%. Based on original CT reports, the sensitivity, specificity, accuracy, PPV, and NPV of CT to determine LNM in T1 ESCC were 41.0%, 83.2%, 77.9%, 25.8%, and 90.8% respectively. For mucosal cancers (T1a), these parameters were 50.0%, 81.7%, 80.9%, 6.8%, and 98.4%, respectively. For submucosal cancers (T1b), they were 40.0%, 85.0%, 75.0%, 43.0%, and 83.3%, respectively. Additionally, the diagnostic performance of CT for LNM was relatively better for ESCC in the lower esophagus. Pathologically, 69.2% of patients with LNM did not exhibit lymphovascular invasion (LVI), and the sensitivity of CT for recognizing LNM in these patients (33.3%) was lower than those with LVI (58.3%).

CONCLUSIONS

Computed tomography can detect nearly half of the LNM cases in early ESCC with high specificity. The performance of CT further improved in LNM cases with LVI. Therefore, we conclude that routine preoperative CT for the assessment of potential LNM risk in patients with early ESCC is necessary.

Prediction of right recurrent laryngeal nerve lymph node metastasis in esophageal cancer based on computed tomography imaging histology

Purpose

This study aimed to identify risk factors for right recurrent laryngeal nerve lymph node (RRLNLN) metastasis using computed tomography (CT) imaging histology and clinical data from patients with esophageal squamous cell carcinoma (ESCC), ultimately developing a clinical prediction model.

Methods

Data were collected from 370 patients who underwent surgical resection at the Department of Thoracic Surgery, Zhongshan Hospital of Xiamen University, from December 2014 to December 2020. Subsequently, the venous-stage chest-enhanced CT images of the patients were imported into 3DSlicer 4.11 software, allowing for the extraction of imaging histological features. Additionally, by combining the clinical data of the patients, single- and multifactor analyses were conducted to screen the risk factors and build a predictive model in the form of a nomogram. The area under the curve (AUC) was used as a discriminant for model accuracy, while differentiation and calibration methods were applied to further evaluate the model's accuracy. Finally, the Bootstrap resampling method was employed to repeat sampling 2,000 times to draw calibration curves, while the K-fold crossvalidation method was used for the internal validation of the prediction model.

Results

The RRLNLN lymph node metastasis rate was 17.3%. Four significant factors-Maximum2DDiameterSlice, Mean, Imc1, and Dependence Entropy-were identified. Alignment diagrams were subsequently constructed, yielding an AUC of 0.938 and a C-index of 0.904 during internal validation.

Conclusion

The model demonstrates high predictive accuracy, making it a valuable tool for guiding the development of preoperative protocols.

Two-year outcomes of clinical N2-3 esophageal squamous cell carcinoma after neoadjuvant chemotherapy and immunotherapy from the phase 2 NICE study

OBJECTIVE

This study aims to report the 2-year outcomes of patients with clinical stage N2-3 esophageal squamous cell carcinoma who received neoadjuvant chemotherapy and immunotherapy followed by surgery from a phase 2 NICE trial.

METHODS

Eligible patients with clinical stage N2-3 esophageal squamous cell carcinoma were screened and enrolled, then treated with regimen of nab-paclitaxel (100 mg/m2, days 1, 8, 15), carboplatin (area under the curve = 5, day 1), camrelizumab (200 mg, day 1) of two 21-day cycles and esophagectomy 4 to 6 weeks after the last chemotherapy. Oncologic outcomes, recurrence patterns, overall survival (OS), and recurrence-free survival (RFS) were explored.

RESULTS

From November 20, 2019, to December 22, 2020, 60 patients were recruited. After a median follow-up of 27.4 months, disease recurrence was observed in 19 (37.3%) patients, with 5 (9.8%) locoregional recurrence, 9 (17.6%) distant metastasis, and 5 (9.8%) combined recurrence. Lung was the most commonly involved metastatic site. The median time to recurrence was 10.8 months (interquartile range, 7.5-12.7 months). The 2-year OS and RFS rates were 78.1% and 67.9%, respectively. Patients who achieved major pathologic response (MPR) had a significantly greater 2-year OS rate (91.4% vs 47.7%; P < .001) and RFS rate (77.1% vs 45.9%; P = .003). On multivariable analysis, MPR was indicated as an independent prognostic factor for disease recurrence (hazard ratio, 0.39; 95% confidence interval, 0.21-0.82; P = .029).

CONCLUSIONS

In patients receiving neoadjuvant chemotherapy and immunotherapy, distant metastasis remains the predominant recurrence pattern. MPR is associated with lower recurrence and better survival. Long-term results derived from randomized controlled trials are further required.

TRIAL REGISTRATION NUMBER

ChiCTR1900026240.

Machine learning to predict occult metastatic lymph nodes along the recurrent laryngeal nerves in thoracic esophageal squamous cell carcinoma

PURPOSE

Esophageal squamous cell carcinoma (ESCC) metastasizes in an unpredictable fashion to adjacent lymph nodes, including those along the recurrent laryngeal nerves (RLNs). This study is to apply machine learning (ML) for prediction of RLN node metastasis in ESCC.

METHODS

The dataset contained 3352 surgically treated ESCC patients whose RLN lymph nodes were removed and pathologically evaluated. Using their baseline and pathological features, ML models were established to predict RLN node metastasis on each side with or without the node status of the contralateral side. Models were trained to achieve at least 90% negative predictive value (NPV) in fivefold cross-validation. The importance of each feature was measured by the permutation score.

RESULTS

Tumor metastases were found in 17.0% RLN lymph nodes on the right and 10.8% on the left. In both tasks, the performance of each model was comparable, with a mean area under the curve ranging from 0.731 to 0.739 (without contralateral RLN node status) and from 0.744 to 0.748 (with contralateral status). All models showed approximately 90% NPV scores, suggesting proper generalizability. The pathology status of chest paraesophgeal nodes and tumor depth had the highest impacts on the risk of RLN node metastasis in both models.

CONCLUSION

This study demonstrated the feasibility of ML in predicting RLN node metastasis in ESCC. These models may potentially be used intraoperatively to spare RLN node dissection in low-risk patients, thereby minimizing adverse events associated with RLN injuries.

Implementation of the Esophagectomy Complication Consensus Group definitions: the benefits of speaking the same language

In 2015 the Esophagectomy Complication Consensus Group (ECCG) reported consensus definitions for complications after esophagectomy. This aimed to reduce variation in complication reporting, attributed to heterogeneous definitions. This systematic review aimed to describe the implementation of this definition set, including the effect on complication frequency and variation. A systematic literature review was performed, identifying all observational and randomized studies reporting complication frequencies after esophagectomy since the ECCG publication. Recruitment periods before and subsequent to the index ECCG publication date were included. Coefficients of variance were calculated to assess outcome heterogeneity. Of 144 studies which met inclusion criteria, 70 (48.6%) used ECCG definitions. The median number of separately reported complication types was five per study; only one study reported all ECCG complications. The coefficients of variance of the reported frequencies of eight of the 10 most common complications were reduced in studies which used the ECCG definitions compared with those that did not (P = 0.036). Among ECCG studies, the frequencies of postoperative pneumothorax, reintubation, and pulmonary emboli were significantly reduced in 2020-2021, compared with 2015-2019 (P = 0.006, 0.034, and 0.037 respectively). The ECCG definition set has reduced variation in esophagectomy morbidity reporting. This adds greater confidence to the observed gradual improvement in outcomes with time, and its ongoing use and wider dissemination should be encouraged. However, only a handful of outcomes are widely reported, and only rarely is it used in its entirety.

A novel web-based dynamic nomogram for recurrent laryngeal nerve lymph node metastasis in esophageal squamous cell carcinoma

Background

Patients with esophageal squamous cell carcinoma (ESCC) are liable to develop recurrent laryngeal nerve (RLN) lymph node metastasis (LNM). We aimed to assess the predictive value of the long diameter (LD) and short diameter (SD) of RLN lymph node (LN) and construct a web-based dynamic nomogram for RLN LNM prediction.

Methods

We reviewed 186 ESCC patients who underwent RLN LN dissection from January 2016 to December 2018 in the Affiliated Hospital of North Sichuan Medical College. Risk factors for left and right RLN LNM were determined by univariate and multivariate analyses. A web-based dynamic nomogram was constructed by using logistic regression. The performance was assessed by the area under the curve (AUC) and Brier score. Models were internally validated by performing five-fold cross-validation.

Results

Patients who underwent left and right RLN LN dissection were categorized as left cohort (n = 132) and right cohort (n = 159), with RLN LNM rates of 15.9% (21/132) and 21.4% (34/159), respectively. The AUCs of the LD (SD) of RLN LN were 0.663 (0.688) in the left cohort and 0.696 (0.705) in the right cohort. The multivariate analysis showed that age, the SD of RLN LN, and clinical T stage were significant risk factors for left RLN LNM (all P < 0.05), while tumor location, the SD of RLN LN, and clinical T stage were significant risk factors for right RLN LNM (all P < 0.05). The dynamic nomograms showed reliable performance after five-fold cross-validation [(left (right), mean AUC: 0.814, range: 0.614–0.891 (0.775, range: 0.084–0.126); mean Brier score: 0.103, range: 0.084–0.126 (0.145, range: 0.105–0.206)], available at https://mpthtw.shinyapps.io/leftnomo/ and https://mpthtw.shinyapps.io/rightnomo/.

Conclusion

The LD and SD of RLN LN are inadequate to predict RLN LNM accurately, but online dynamic nomograms by combined risk factors show better prediction performance and convenient clinical application.

Multicenter, single-arm, phase II trial of camrelizumab and chemotherapy as neoadjuvant treatment for locally advanced esophageal squamous cell carcinoma

Background

Camrelizumab and chemotherapy demonstrated durable antitumor activity with a manageable safety profile as first-line treatment in patients with advanced esophageal squamous cell carcinoma (ESCC). This study aimed to evaluate the safety and efficacy of camrelizumab plus neoadjuvant chemotherapy, using pathologically complete response (pCR) as primary endpoint, in the treatment for locally advanced ESCC.

Methods

Patients with locally advanced but resectable thoracic ESCC, staged as T1b-4a, N2-3 (≥3 stations), and M0 or M1 lymph node metastasis (confined to the supraclavicular lymph nodes) were enrolled. Eligible patients received intravenous camrelizumab (200 mg, day 1) plus nab-paclitaxel (100 mg/m², day 1, 8, 15) and carboplatin (area under curve of 5 mg/mL/min, day 1) of each 21-days cycle, for two cycles before surgery. The primary endpoint is pCR rate in the per-protocol population. Safety was assessed in the modified intention-to-treat population that was treated with at least one dose of camrelizumab.

Results

From November 20, 2019 to December 22, 2020, 60 patients were enrolled. 55 (91.7%) patients completed the full two-cycle treatment successfully. 51 patients underwent surgery and R0 resection was achieved in 50 (98.0%) patients. pCR (ypT0N0) was identified in 20 (39.2%) patients and 5 (9.8%) patients had complete response of the primary tumor but residual disease in lymph nodes alone (ypT0N+). 58 patients (96.7%) had any-grade treatment-related adverse events (TRAEs), with the most common being leukocytopenia (86.7%). 34 patients (56.7%) had adverse events of grade 3 or worse, and one patient (1.7%) occurred a grade 5 adverse event. There was no in-hospital and postoperative 30-day as well as 90-day mortality.

Conclusions

The robust antitumor activity of camrelizumab and chemotherapy was confirmed and demonstrated without unexpected safety signals. Our findings established camrelizumab and chemotherapy as a promising neoadjuvant treatment for locally advanced ESCC.

Trial registration number

ChiCTR1900026240.

Optimal criteria for predicting lymph node metastasis in esophageal squamous cell carcinoma by anatomical location using preoperative computed tomography: a retrospective cohort study

PURPOSE

Predicting lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) is critical for selecting appropriate treatments despite the low accuracy of computed tomography (CT) for detecting LNM. Variation in potential nodal sizes among locations or patients' clinicopathological background factors may impact the diagnostic quality. This study explored the optimal criteria and diagnostic ability of CT by location.

METHODS

We retrospectively reviewed preoperative CT scans of 229 patients undergoing curative esophagectomy. We classified nodal stations into six groups: Cervical (C), Right-upper mediastinal (U_R), Left-upper mediastinal (U_L), Middle mediastinal (M), Lower mediastinal (L), and Abdominal (A). We then measured the short-axial diameter (SAD) of the largest lymph node in each area. We used receiver operating characteristics analyses to evaluate the CT diagnostic ability and determined the cut-off values for the SAD in all groups.

RESULTS

Optimal cut-offs were 6.5 mm (M), 6 mm (C, L, and A), and 5 mm (U_R and U_L). Diagnostic abilities differed among locations, and U_R had the highest sensitivity. A multivariate analysis showed poor differentiation to be an independent risk factor for a false-negative diagnosis (p = 0.044).

CONCLUSIONS

Optimal criteria and diagnostic abilities for predicting LNM in ESCC varied among locations, and poor differentiation might contribute to failure to detect LNM.

Imaging features of sentinel lymph node mapped by multidetector-row computed tomography lymphography in predicting axillary lymph node metastasis

INTRODUCTION

Accurately assessing axillary lymph node (ALN) status in breast cancer is vital for clinical decision making and prognosis. The purpose of this study was to evaluate the predictive value of sentinel lymph node (SLN) mapped by multidetector-row computed tomography lymphography (MDCT-LG) for ALN metastasis in breast cancer patients.

METHODS

112 patients with breast cancer who underwent preoperative MDCT-LG examination were included in the study. Long-axis diameter, short-axis diameter, ratio of long-/short-axis and cortical thickness were measured. Logistic regression analysis was performed to evaluate independent predictors associated with ALN metastasis. The prediction of ALN metastasis was determined with related variables of SLN using receiver operating characteristic (ROC) curve analysis.

RESULTS

Among the 112 cases, 35 (30.8%) cases had ALN metastasis. The cortical thickness in metastatic ALN group was significantly thicker than that in non-metastatic ALN group (4.0 ± 1.2 mm vs. 2.4 ± 0.7 mm, P < 0.001). Multi-logistic regression analysis indicated that cortical thickness of > 3.3 mm (OR 24.53, 95% CI 6.58-91.48, P < 0.001) had higher risk for ALN metastasis. The best sensitivity, specificity, negative predictive value(NPV) and AUC of MDCT-LG for ALN metastasis prediction based on the single variable of cortical thickness were 76.2%, 88.5%, 90.2% and 0.872 (95% CI 0.773-0.939, P < 0.001), respectively.

CONCLUSION

ALN status can be predicted using the imaging features of SLN which was mapped on MDCT-LG in breast cancer patients. Besides, it may be helpful to select true negative lymph nodes in patients with early breast cancer, and SLN biopsy can be avoided in clinically and radiographically negative axilla.

Plasma cell-free circRNAs panel act as fingerprint predicts the occurrence of laryngeal squamous cell carcinoma

Background: Circular RNAs (circRNAs) have recently emerged as a new class of RNAs, highly enriched in the human tissues and very stable within cells, exosomes and body fluids. In this study, we aimed to screen the plasma cell-free derived circRNAs in laryngeal squamous cell carcinoma (LSCC) and investigate whether these circRNAs could predicted LSCC as potential biomarkers.

Methods: The circRNA microarray was employed with three samples in each group to screen the dysregulated circRNAs isolated from plasma samples. The top 20 circRNAs were first selected as candidates with the upregulated level in the plasma of LSCC.

Results: Further validation found that only circ_0019201, circ_0011773 and circ_0122790 was consistent with training set. The ROC curve also revealed a high diagnostic ability an area under ROC curve value (AUC) for single circRNA and combined. The AUC for circ_0019201, circ_0011773 and circ_0122790 and the combined was 0.933, 0.908, 0.965 and 0.990 in training set. For the validation set, the AUC was 0.766, 0.864, 0.908 and 0.951. The three circRNAs were further investigated with stable expression in human plasma samples.

Conclusions: The plasma derived circ_0019201, circ_0011773 and circ_0122790 might be the potential biomarker for predicting the LSCC.

Development of a prediction model for the risk of recurrent laryngeal nerve lymph node metastasis in thoracolaparoscopic esophagectomy with cervical anastomosis

Background

There are no effective preoperative diagnostic measures to predict the probability of left and right recurrent laryngeal nerve (RLN) lymph node (LN) metastasis using preoperative clinical data in patients undergoing thoracolaparoscopic esophagectomy with cervical anastomosis.

Methods

We retrospectively reviewed the clinical data of 1,660 consecutive patients with thoracic esophageal cancer who underwent esophagectomy with cervical anastomosis at the Department of Thoracic Surgery at the First Affiliated Hospital of Zhengzhou University between January 2015 and December 2020.

Results

A total of 299 and 343 patients who underwent left (Cohort 1) and right (Cohort 2) RLN LN dissection were included in the final analyses. The analyses were conducted within each cohort. Among the 299 patients in Cohort 1, left RLN LN involvement was found in 41 patients (13.7%). A multivariable analysis showed that age, tumor location, and short axis were significantly associated with RLN LN metastasis (all P<0.05). Among the 343 patients in Cohort 2, right RLN LN involvement was found in 65 patients (19.0%). A multivariable analysis showed that computed tomography (CT) appearance, tumor location, long axis, and short axis were significantly associated with RLN LN metastasis (all P<0.05). Based on the results of the multivariable analyses, we constructed nomograms that could estimate the probability of RLN LN metastasis. Finally, we stratified the 2 cohorts into risk subgroups using a recursive partitioning analysis (RPA). The risk of left and right RLN LN metastasis was found to be 9.3% and 7.5%, 27.3% and 21.4%, and 52.4% and 47.3% for the low-risk, intermediate-risk, and high-risk groups, respectively.

Conclusions

Our nomograms and RPAs appear to be suitable for the risk stratification of left and right RLN LN metastasis in patients undergoing thoracolaparoscopic esophagectomy with cervical anastomosis. This tool could be used to help clinicians to select more effective locoregional treatments, such as surgical protocols and radiation area selection.