Novel imaging techniques in staging oesophageal cancer

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.

Esophagectomy may have a role in stage IV esophageal adenocarcinoma

OBJECTIVE

We sought to determine whether aggressive local treatment provides a benefit in patients with stage IV esophageal adenocarcinoma and to determine factors associated with survival.

METHODS

Patients with clinical stage IV esophageal adenocarcinoma at diagnosis who underwent esophagectomy from 2010 to 2023 were identified from our prospectively maintained database. Clinicopathologic and demographic characteristics were compared among patients by stage. Overall survival was estimated using the Kaplan-Meier approach.

RESULTS

In total, 66 patients met the inclusion criteria. Of these, 30 (45%) had stage IVA disease, and 36 (55%) had stage IVB disease. Of the 36 patients with stage IVB disease, 26 had oligometastatic disease, and 10 had disseminated disease. All patients with stage IVA disease received standard neoadjuvant therapy followed by curative-intent surgery; 26 of these patients (87%) received chemoradiation. Patients with oligometastatic stage IVB disease underwent systemic therapy with the goal of surgical resection. Patients with disseminated stage IVB disease underwent palliative chemotherapy, which led to improvement in disease burden and performance of esophagectomy. Median time from the start of therapy to surgery was shorter for patients with stage IVA disease than patients with stage IVB disease (P < .001). Three-year progression-free survival was lower for patients with stage IVA disease (40% vs 56%), as was 3-year overall survival (57% vs 85%). Adjusted overall survival, from the start of therapy to most recent follow-up, was higher for patients with stage IVB disease.

CONCLUSIONS

Aggressive local treatment may provide a benefit for highly selected patients with advanced or metastatic esophageal adenocarcinoma.

Potential value of CT-based comprehensive nomogram in predicting occult lymph node metastasis of esophageal squamous cell paralaryngeal nerves: a two-center study

PURPOSE

The aim of this study is to construct a combined model that integrates radiomics, clinical risk factors and machine learning algorithms to predict para-laryngeal lymph node metastasis in esophageal squamous cell carcinoma.

METHODS

A retrospective study included 361 patients with esophageal squamous cell carcinoma from 2 centers. Radiomics features were extracted from the computed tomography scans. Logistic regression, k nearest neighbor, multilayer perceptron, light Gradient Boosting Machine, support vector machine, random forest algorithms were used to construct radiomics models. The receiver operating characteristic curve and The Hosmer-Lemeshow test were employed to select the better-performing model. Clinical risk factors were identified through univariate logistic regression analysis and multivariate logistic regression analysis and utilized to develop a clinical model. A combined model was then created by merging radiomics and clinical risk factors. The performance of the models was evaluated using ROC curve analysis, and the clinical value of the models was assessed using decision curve analysis.

RESULTS

A total of 1024 radiomics features were extracted. Among the radiomics models, the KNN model demonstrated the optimal diagnostic capabilities and accuracy, with an area under the curve (AUC) of 0.84 in the training cohort and 0.62 in the internal test cohort. Furthermore, the combined model exhibited an AUC of 0.97 in the training cohort and 0.86 in the internal test cohort.

CONCLUSION

A clinical-radiomics integrated nomogram can predict occult para-laryngeal lymph node metastasis in esophageal squamous cell carcinoma and provide guidance for personalized treatment.

Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer

BACKGROUND

Accurate preoperative prediction of lymph node metastasis (LNM) in esophageal cancer (EC) patients is of crucial clinical significance for treatment planning and prognosis.

AIM

To develop a clinical radiomics nomogram that can predict the preoperative lymph node (LN) status in EC patients.

METHODS

A total of 32 EC patients confirmed by clinical pathology (who underwent surgical treatment) were included. Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy, and its correlation with LNM was analyzed. Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python. Feature extraction, data dimensionality reduction, and feature selection were performed using XGBoost model and leave-one-out cross-validation. Multivariable logistic regression analysis was used to establish the prediction model, which included radiomics features, LN status from computed tomography (CT) reports, and B7-H3 mRNA expression, represented by a radiomics nomogram. Receiver operating characteristic area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate the predictive performance and clinical application value of the model.

RESULTS

The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis, and the difference was statistically significant (P < 0.05). The AUC value in the receiver operating characteristic (ROC) curve was 0.718 (95%CI: 0.528-0.907), with a sensitivity of 0.733 and specificity of 0.706, indicating good diagnostic performance. The individualized clinical prediction nomogram included radiomics features, LN status from CT reports, and B7-H3 mRNA expression. The ROC curve demonstrated good diagnostic value, with an AUC value of 0.765 (95%CI: 0.598-0.931), sensitivity of 0.800, and specificity of 0.706. DCA indicated the practical value of the radiomics nomogram in clinical practice.

CONCLUSION

This study developed a radiomics nomogram that includes radiomics features, LN status from CT reports, and B7-H3 mRNA expression, enabling convenient preoperative individualized prediction of LNM in EC patients.

Radiomics-clinical nomogram for preoperative lymph node metastasis prediction in esophageal carcinoma

OBJECTIVES

This research aimed to develop a radiomics-clinical nomogram based on enhanced thin-section CT radiomics and clinical features for the purpose of predicting the presence or absence of metastasis in lymph nodes among patients with resectable esophageal squamous cell carcinoma (ESCC).

METHODS

This study examined the data of 256 patients with ESCC, including 140 cases with lymph node metastasis. Clinical information was gathered for each case, and radiomics features were derived from thin-section contrast-enhanced CT with the help of a 3D slicer. To validate risk factors that are independent of the clinical and radiomics models, least absolute shrinkage and selection operator logistic regression analysis was used. A nomogram pattern was constructed based on the radiomics features and clinical characteristics. The receiver operating characteristic curve and Brier Score were used to evaluate the model's discriminatory ability, the calibration plot to evaluate the model's calibration, and the decision curve analysis to evaluate the model's clinical utility. The confusion matrix was used to evaluate the applicability of the model. To evaluate the efficacy of the model, 1000 rounds of 5-fold cross-validation were conducted.

RESULTS

The clinical model identified esophageal wall thickness and clinical T (cT) stage as independent risk factors, whereas the radiomics pattern was built based on 4 radiomics features chosen at random. Area under the curve (AUC) values of 0.684 and 0.701 are observed for the radiomics approach and clinical model, respectively. The AUC of nomogram combining radiomics and clinical features was 0.711. The calibration plot showed good agreement between the incidence of lymph node metastasis predicted by the nomogram and the actual probability of occurrence. The nomogram model displayed acceptable levels of performance. After 1000 rounds of 5-fold cross-validation, the AUC and Brier score had median values of 0.702 (IQR: 0.65, 7.49) and 0.21 (IQR: 0.20, 0.23), respectively. High-risk patients (risk point >110) were found to have an increased risk of lymph node metastasis [odds ratio (OR) = 5.15, 95% CI, 2.95-8.99] based on the risk categorization.

CONCLUSION

A successful preoperative prediction performance for metastasis to the lymph nodes among patients with ESCC was demonstrated by the nomogram that incorporated CT radiomics, wall thickness, and cT stage.

ADVANCES IN KNOWLEDGE

This study demonstrates a novel radiomics-clinical nomogram for lymph node metastasis prediction in ESCC, which helps physicians determine lymph node status preoperatively.

Metabolic tumour and nodal response to neoadjuvant chemotherapy on FDG PET-CT as a predictor of pathological response and survival in patients with oesophageal adenocarcinoma

OBJECTIVES

2-deoxy-2[¹⁸F]Fluoro-D-glucose (FDG) PET-CT has an emerging role in assessing response to neoadjuvant therapy in oesophageal cancer. This study evaluated FDG PET-CT in predicting pathological tumour response (pTR), pathological nodal response (pNR) and survival.

METHODS

Cohort study of 75 patients with oesophageal or oesophago-gastric junction (GOJ) adenocarcinoma treated with neoadjuvant chemotherapy then surgery at Guy's and St Thomas' NHS Foundation Trust, London (2017-2020). Standardised uptake value (SUV) metrics on pre- and post-treatment FDG PET-CT in the primary tumour (mTR) and loco-regional lymph nodes (mNR) were derived. Optimum SUV_max thresholds for predicting pathological response were identified using receiver operating characteristic analysis. Predictive accuracy was compared to PERCIST (30% SUV_max reduction) and MUNICON (35%) criteria. Survival was assessed using Cox regression.

RESULTS

Optimum tumour SUV_max decrease for predicting pTR was 51.2%. A 50% cut-off predicted pTR with 73.5% sensitivity, 69.2% specificity and greater accuracy than PERCIST or MUNICON (area under the curve [AUC] 0.714, PERCIST 0.631, MUNICON 0.659). Using a 30% SUV_max threshold, mNR predicted pNR with high sensitivity but low specificity (AUC 0.749, sensitivity 92.6%, specificity 57.1%, p = 0.010). pTR, mTR, pNR and mNR were independent predictive factors for survival (pTR hazard ratio [HR] 0.10 95% confidence interval [CI] 0.03-0.34; mTR HR 0.17 95% CI 0.06-0.48; pNR HR 0.17 95% CI 0.06-0.54; mNR HR 0.13 95% CI 0.02-0.66).

CONCLUSIONS

Metabolic tumour and nodal response predicted pTR and pNR, respectively, in patients with oesophageal or GOJ adenocarcinoma. However, currently utilised response criteria may not be optimal. pTR, mTR, pNR and mNR were independent predictors of survival.

KEY POINTS

• FDG PET-CT has an emerging role in evaluating response to neoadjuvant therapy in patients with oesophageal cancer. • Prospective cohort study demonstrated that metabolic response in the primary tumour and lymph nodes was predictive of pathological response in a cohort of patients with adenocarcinoma of the oesophagus or oesophago-gastric junction treated with neoadjuvant chemotherapy followed by surgical resection. • Patients who demonstrated a response to neoadjuvant chemotherapy in the primary tumour or lymph nodes on FDG PET-CT demonstrated better survival and reduced rates of tumour recurrence.

Prognostic value of baseline 18F-FDG PET/CT in patients with esophageal squamous cell carcinoma treated with definitive (chemo)radiotherapy

PURPOSE

To investigate the prognostic value of baseline ¹⁸F-FDG PET/CT in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive (chemo)radiotherapy.

METHODS

A total of 98 ESCC patients with cTNM stage T1-4, N1-3, M0 who received definitive (chemo)radiotherapy after ¹⁸F-FDG PET/CT examination from December 2013 to December 2020 were retrospectively analyzed. Clinical factors included age, sex, histologic differentiation grade, tumor location, clinical stage, and treatment strategies. Parameters obtained by ¹⁸F-FDG PET/CT included SUV_max of primary tumor (SUV_Tumor), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV_max of lymph node (SUV_LN), PET positive lymph nodes (PLNS) number, the shortest distance between the farthest PET positive lymph node and the primary tumor in three-dimensional space after the standardization of the patient BSA (SD_max(LN-T)). Univariate and multivariate analysis was conducted by Cox proportional hazard model to explore the significant factors affecting overall survival (OS) and progression-free survival (PFS) in ESCC patients.

RESULTS

Univariate analysis showed that tumor location, SUV_Tumor, MTV, TLG, PLNS number, SD_{max (LN-T)} were significant predictors of OS and tumor location, and clinical T stage, SUV_Tumor, MTV, TLG, SD_{max (LN-T)} were significant predictors of PFS (all p < 0.1). Multivariate analysis showed that MTV and SD_{max (LN-T)} were independent prognostic factors for OS (HR = 1.018, 95% CI 1.006-1.031; p = 0.005; HR = 6.988, 95% CI 2.119-23.042; p = 0.001) and PFS (HR = 1.019, 95% CI 1.005-1.034; p = 0.009; HR = 5.819, 95% CI 1.921-17.628; p = 0.002). Combined with independent prognostic factors MTV and SD_{max (LN-T)}, we can further stratify patient risk.

CONCLUSIONS

Before treatment, ¹⁸F-FDG PET/CT has important prognostic value for patients with ESCC treated with definitive (chemo)radiotherapy. The lower the value of MTV and SD_{max (LN-T)}, the better the prognosis of patients.

Radiomics models based on CT at different phases predicting lymph node metastasis of esophageal squamous cell carcinoma (GASTO-1089)

PURPOSE

To investigate the value of radiomics models based on CT at different phases (non-contrast-enhanced and contrast-enhanced images) in predicting lymph node (LN) metastasis in esophageal squamous cell carcinoma (ESCC).

METHODS AND MATERIALS

Two hundred and seventy-four eligible patients with ESCC were divided into a training set (n =193) and a validation set (n =81). The least absolute shrinkage and selection operator algorithm (LASSO) was used to select radiomics features. The predictive models were constructed with radiomics features and clinical factors through multivariate logistic regression analysis. The predictive performance and clinical application value of the models were evaluated by area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). The Delong Test was used to evaluate the differences in AUC among models.

RESULTS

Sixteen and eighteen features were respectively selected from non-contrast-enhanced CT (NECT) and contrast-enhanced CT (CECT) images. The model established using only clinical factors (Model 1) has an AUC value of 0.655 (95%CI 0.552-0.759) with a sensitivity of 0.585, a specificity of 0.725 and an accuracy of 0.654. The models contained clinical factors with radiomics features of NECT or/and CECT (Model 2,3,4) have significantly improved prediction performance. The values of AUC of Model 2,3,4 were 0.766, 0.811 and 0.809, respectively. It also achieved a great AUC of 0.800 in the model built with only radiomics features derived from NECT and CECT (Model 5). DCA suggested the potential clinical benefit of model prediction of LN metastasis of ESCC. A comparison of the receiver operating characteristic (ROC) curves using the Delong test indicated that Models 2, 3, 4, and 5 were superior to Model 1(P< 0.05), and no difference was found among Model 2, 3, 4 and Model 5(P > 0.05).

CONCLUSION

Radiomics models based on CT at different phases could accurately predict the lymph node metastasis in patients with ESCC, and their predictive efficiency was better than the clinical model based on tumor size criteria. NECT-based radiomics model could be a reasonable option for ESCC patients due to its lower price and availability for renal failure or allergic patients.

Selection of dilution material for non-iodinated iodine as an oral contrast agent for esophageal cancer: a preliminary clinical trial

PURPOSE

To investigate the filling state of the esophagus using different oral contrast agents for the diagnosis of esophageal cancer by computed tomography (CT).

MATERIALS AND METHODS

This preliminary clinical trial enrolled patients with suspected esophageal carcinoma and admitted from January 2015 to January 2018. The patients were randomized into the yogurt (mixed with ioversol), lotus root powder (mixed with ioversol), gas-producing powder, and control (pure iodine water) groups. Chest CT examinations were performed. The degree of esophageal filling and the detection of esophageal lesions were compared.

RESULTS

Finally, 136 participants were enrolled (n = 34/group). There were no significant differences in esophageal filling degree among the yogurt, lotus root powder, and gas-producing powder groups (P = 0.093). There were 30/3/1 and 30/3/1 confirmed/false-negative/false-positive diagnoses in the yogurt and lotus powder groups, respectively, compared with 28/5/1 and 25/8/1 in the gas-producing powder and control groups, respectively. The concordance rates were the highest for the yogurt (88.2%, with 91.7% specificity and 86.4% sensitivity) and lotus root powder groups (88.2%, with 92.3% specificity and 85.7% sensitivity) and the lowest for the control group (73.5%, with 90.0% specificity and 66.7% sensitivity).

CONCLUSION

Yogurt mixed with ioversol could fill and expand the esophagus with minimal preparation, displaying the structure of the esophageal lumen and wall thickness. This mixture might be used as a positive contrast agent for esophageal CT. Similar results were observed for the lotus root powder mixed with ioversol, but its preparation was more arduous.

A Novel Model Combining Tumor Length, Tumor Thickness, TNM_Stage, Nutritional Index, and Inflammatory Index Might Be Superior to the 8th TNM Staging Criteria in Predicting the Prognosis of Esophageal Squamous Cell Carcinoma Patients Treated With Definitive Chemoradiotherapy

Background

We aimed to determine whether the tumor length and tumor thickness should be used as prognostic factors for esophageal squamous cell carcinoma (ESCC) patients treated with definitive chemoradiotherapy (dCRT).

Methods

A retrospective analysis consists of 902 non-operative ESCC patients received dCRT. The nomogram was used to predict the survival. Besides, Restricted Cubic Splines (RCS) was used to examine the relationship between prognostic factors and survival outcomes. Finally, the prognostic index (PI) scores were constructed according to the tumor length and tumor thickness, and the patients were divided into the low-, medium-, and high-risk groups.

Results

The median follow-up of overall survival (OS) and progression-free survival (PFS) were 23.0 months and 17.5 months. Multivariate Cox regression analysis showed that tumor length and tumor thickness were independent prognostic factors associated with survival. Our novel nomograms for OS and PFS were superior to the TNM classification (p < 0.001). Besides, RCS analysis demonstrated that the death hazard of tumor length and tumor thickness sharply increased at 7.7 cm and 1.6 cm (p < 0.001). Finally, there were significant differences for ESCC patients with clinical TNM stage group of the OS and PFS in different risk groups. The higher risk group was significantly associated with shorter OS and PFS in ESCC patients (both p < 0.001 for all).

Conclusion

The study results suggest that the novel models integrating tumor length and tumor thickness may provide a simple and widely available method for evaluating the prognosis of non-operative ESCC patients. The tumor length and tumor thickness should be considered as prognostic factors for ESCC.

Value of 18F-FDG PET/MRI in the Preoperative Assessment of Resectable Esophageal Squamous Cell Carcinoma: A Comparison With 18F-FDG PET/CT, MRI, and Contrast-Enhanced CT

Objectives

To investigate the value of ¹⁸F-FDG PET/MRI in the preoperative assessment of esophageal squamous cell carcinoma (ESCC) and compare it with ¹⁸F-FDG PET/CT, MRI, and CECT.

Methods

Thirty-five patients with resectable ESCC were prospectively enrolled and underwent PET/MRI, PET/CT, and CECT before surgery. The primary tumor and regional lymph nodes were assessed by PET/MRI, PET/CT, MRI, and CECT, respectively, and the diagnostic efficiencies were determined with postoperative pathology as a reference standard. The predictive role of imaging and clinical parameters on pathological staging was analyzed.

Results

For primary tumor staging, the accuracy of PET/MRI, MRI, and CECT was 85.7%, 77.1%, and 51.4%, respectively. For lymph node assessment, the accuracy of PET/MRI, PET/CT, MRI, and CECT was 96.2%, 92.0%, 86.8%, and 86.3%, respectively, and the AUCs were 0.883, 0.745, 0.697, and 0.580, respectively. PET/MRI diagnosed 13, 7, and 6 more stations of lymph node metastases than CECT, MRI, and PET/CT, respectively. There was a significant difference in SUV_max, TLG, and tumor wall thickness between T1-2 and T3 tumors (p = 0.004, 0.024, and < 0.001, respectively). Multivariate analysis showed that thicker tumor wall thickness was a predictor of a higher T stage (p = 0.040, OR = 1.6).

Conclusions

¹⁸F-FDG PET/MRI has advantages over ¹⁸F-FDG PET/CT, MRI, and CECT in the preoperative assessment of primary tumors and regional lymph nodes of ESCC. ¹⁸F-FDG PET/MRI may be a potential supplement or alternative imaging method for preoperative staging of ESCC.

Detecting lymph node metastasis of esophageal cancer on dual-energy computed tomography

Background

Using conventional computed tomography (CT), the accurate diagnosis of lymph node (LN) metastasis of esophageal cancer is difficult.

Purpose

To examine dual-energy CT parameters to predict LN metastasis preoperatively in patients with esophageal cancer.

Material and Methods

Twenty-six consecutive patients who underwent dual-energy CT before an esophageal cancer surgery (19 patients with LN metastases) were analyzed. The included LNs had a short-axis diameter of ≥4 mm and were confirmed to be resected on postoperative CT. Their short-axis diameter, CT value, iodine concentration (IC), and fat fraction were measured on early- and late-phase contrast-enhanced dual-energy CT images and compared between pathologically confirmed metastatic and non-metastatic LNs.

Results

In total, 51 LNs (34 metastatic and 17 non-metastatic) were included. In the early phase, IC and fat fraction were significantly lower in the metastatic than in the non-metastatic LNs (IC = 1.6 mg/mL vs. 2.2 mg/mL; fat fraction = 20.3% vs. 32.5%; both P < 0.05). Furthermore, in the late phase, IC and fat fraction were significantly lower in the metastatic than in the non-metastatic LNs (IC = 2.0 mg/mL vs. 3.0 mg/mL; fat fraction = 20.4% vs. 33.0%; both P < 0.05). Fat fraction exhibited accuracies of 82.4% and 78.4% on early- and late-phase images, respectively. Conversely, short-axis diameter and CT value on both early- and late-phase images were not significantly different between the metastatic and non-metastatic LNs (P > 0.05).

Conclusion

Using dual-energy CT images, IC and fat fraction are useful for diagnosing LN metastasis in patients with esophageal cancer.

Early Esophageal Cancer detection using Deep learning Techniques. (Review Article)

Esophageal cancer is one of the deadliest diseases for humans, since it is discovered in very advanced stages. As result, pathologists are increasingly relying in image recognition and artificial intelligence tools to aid in the early identification and evaluation of this lesion. We examined a number of papers that dealt with this issue during the time span in order to shed light on the studies that were performed in this area (2017 and 2020). We have looked at experiments that used Convolutional Neural Network (CNN) technologies in the study of endoscopic images to help with early detection or diagnosis of esophageal cancer and its various forms. More research on esophageal malignant growth is required, as well as improving the disease’s indicative existence and employing more proven techniques for feature selection/extraction of endoscopic images. The aim of this review is to highlight the research conducted on endoscopic images of the esophagus using deep learning algorithms, including CNN, Support Vector Machine (SVM), Random Forests (RF) and other techniques that were used to design the Computer-Aided Detection (CAD) system. In this review we covered some but not all articles that was of great contact with our master’s thesis research in this regard.

Trends in Esophageal Cancer Mortality and Stage at Diagnosis by Race and Ethnicity in the United States

Introduction

Esophageal cancer (EC) is an aggressive malignancy with poor prognosis. Mortality and disease stage at diagnosis are important indicators of improvements in cancer prevention and control. We examined United States trends in esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) mortality and stage at diagnosis by race and ethnicity.

Methods

We used Surveillance, Epidemiology, and End Results (SEER) data to identify individuals with histologically confirmed EAC and ESCC between 1 January 1992 and 31 December 2016. For both EAC and ESCC, we calculated age-adjusted mortality and the proportion presenting at each stage by race/ethnicity, sex, and year. We then calculated the annual percent change (APC) in each indicator by race/ethnicity and examined changes over time.

Results

The study included 19,257 EAC cases and 15,162 ESCC cases. EAC mortality increased significantly overall and in non-Hispanic Whites from 1993 to 2012 and from 1993 to 2010, respectively. EAC mortality continued to rise among non-Hispanic Blacks (NHB) (APC = 1.60, p = 0.01). NHB experienced the fastest decline in ESCC mortality (APC = − 4.53, p < 0.001) yet maintained the highest mortality at the end of the study period. Proportions of late stage disease increased overall by 18.5 and 24.5 percentage points for EAC and ESCC respectively; trends varied by race/ethnicity.

Conclusion

We found notable differences in trends in EAC and ESCC mortality and stage at diagnosis by race/ethnicity. Stage migration resulting from improvements in diagnosis and treatment may partially explain recent trends in disease stage at diagnosis. Future efforts should identify factors driving current esophageal cancer disparities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10552-021-01443-z.

Diagnostic Performance of MRI for Esophageal Carcinoma: A Systematic Review and Meta-Analysis

Background Although CT, endoscopic US, and PET are critical in determining the appropriate management of esophageal carcinoma (squamous cell carcinoma and adenocarcinoma), previous reports show that staging accuracy remains low, particularly for nodal involvement sensitivity. Purpose To perform a systematic review and meta-analysis to determine the diagnostic performance of MRI for multiple staging thresholds in patients with biopsy-proven esophageal carcinoma (differentiation of stage T0 disease from stage T1 or higher disease, differentiation of stage T2 or lower disease from stage T3 or higher disease, and differentiation of stage N0 disease from stage N1 or higher disease [where T refers to tumor stage and N refers to nodal stage]). Materials and Methods Studies of the diagnostic performance of MRI in determining the stage of esophageal carcinoma in patients before esophagectomy and pathologic staging between 2000 and 2019 were searched in PubMed, Scopus, Web of Science, and Cochrane Library by a librarian and radiation oncologist. Pooled diagnostic performance of MRI was calculated with a bivariate random effects model. Bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (version 2) tool. Results Twenty studies with a total of 984 patients were included in the analysis. Pooled accuracy for stage T0 versus stage T1 or higher had a sensitivity of 92% (95% CI: 82, 96) and a specificity of 67% (95% CI: 51, 81). Pooled accuracy for stage T2 or lower versus stage T3 or higher had a sensitivity of 86% (95% CI: 76, 92) and a specificity of 86% (95% CI: 75, 93). Pooled accuracy for stage N0 versus stage N1 or higher had a sensitivity of 71% (95% CI: 60, 80) and a specificity of 72% (95% CI: 64, 79). The concern for applicability was low for the patient selection, index test, and reference test domains, except for 10% of studies (two of 20) that had unclear concern for patient selection applicability. Conclusion MRI has high sensitivity but low specificity for the detection of esophageal carcinoma, which shows promise for determining neoadjuvant therapy response and for detecting locally advanced disease for potential trimodality therapy. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Leeflang in this issue.

Hospital clinical staging accuracy for upper gastrointestinal malignancy

BACKGROUND

Decisions about multimodality treatment for upper gastrointestinal malignancies are largely predicted on clinical staging information. However, hospital-level accuracy of clinical staging is currently unknown.

METHODS

A national cohort study of patients with adenocarcinoma of the esophagus, stomach, or pancreas in the NCDB (2006-2015) who were treated with upfront resection. Hospital-level staging accuracy (ascertained by comparing clinical stage to pathologic stage) was calculated. Within hospital correlation of staging accuracy across disease sites was evaluated using risk and reliability adjustment.

RESULTS

Overall, 1246 hospitals were evaluated. Median hospital T-staging accuracy was 77.5%, 73.7%, and 60.8% for esophageal, gastric, and pancreatic cancer, respectively. Median hospital N-staging accuracy was 80.2%, 72.9%, and 61.8%, respectively. For T-stage, over-staging was most frequently observed in esophageal patients (11.2%) while under-staging was most frequent in pancreatic patients (36.1%). For N-stage, over-staging was infrequent for all three, while under-staging was most common in pancreatic patients (37.4%). Correlation across disease sites was weak for both T- (best observed, r = .34) and N-stages (r = .30). When high volume hospitals were evaluated, correlation improved but accuracy rates were similar.

CONCLUSIONS

Despite the importance of clinical staging in multimodality treatment planning, hospitals inaccurately stage 20-40% of patients, with low correlation across disease sites.

Role of precision imaging in esophageal cancer

Esophageal cancer is a major cause of morbidity and mortality worldwide. Recent advancements in the management of esophageal cancer have allowed for earlier detection, improved ability to monitor progression, and superior treatment options. These innovations allow treatment teams to formulate more customized management plans and have led to an increase in patient survival rates. For example, in order for the most effective management plan to be constructed, accurate staging must be performed to determine tumor resectability. This article reviews the multimodality imaging approach involved in making a diagnosis, staging, evaluating treatment response and detecting recurrence in esophageal cancer.

Heterogeneity of T3 stage esophageal squamous cell carcinoma in different parts based on enhanced CT radiomics

Esophageal cancer is a common malignant tumor of the digestive system with a high incidence and a poor prognosis. At the present, CT-based radiomics is providing more and more valuable information. However, the heterogeneity of the study and the poor repeatability of the texture feature parameters have limited its wider clinical application. In the present study, we focused on comparing the differences in the texture features of T3 stage esophageal squamous cell carcinoma at different locations and normal esophageal wall, aiming to provide some pieces of useful information for future research on esophageal squamous cell carcinoma.Fifty seven cases with throat CT imaging, including esophageal cancer contrast enhanced CT and conventional CT of healthy control group. The texture characteristics in control group and tumor group among different parts were compared. Using Univariable analysis, we compared the difference and conducted receiver-operator curve analysis to evaluate the performance of tumor grade diagnosis model.53 radiomic features were significantly different in control group and so as 93 features for tumor group. The upper section was the mostly different from the other 2 sections. Run-length matrix (RLM) features in tumor group accounted for the highest proportion, only Surface Volume Ratio was different.There are differences in the texture features of the tube wall in different parts of the esophagus of healthy adults, and this difference is more obvious in pT3 stage esophageal squamous cell carcinoma. In the future radiomics study of esophageal squamous cell carcinoma, we need to pay attention to this to avoid affecting the accuracy of the results.

Comparison of gross target volumes based on four-dimensional CT, positron emission tomography-computed tomography, and magnetic resonance imaging in thoracic esophageal cancer

PURPOSE

The application value of ¹⁸ F-FDG PET-CT combined with MRI in the radiotherapy of esophageal carcinoma was discussed by comparing the differences in position, volume, and the length of GTVs delineated on the end-expiration (EE) phase of 4DCT, ¹⁸ F-FDG PET-CT, and T₂ W-MRI.

METHODS

A total of 26 patients with thoracic esophageal cancer sequentially performed 3DCT, 4DCT, ¹⁸ F-FDG PET-CT, and MRI simulation for thoracic localization. All images were fused with the 3DCT images by deformable registration. GTV_CT and GTV_50% were delineated on 3DCT and the EE phase of 4DCT images, respectively. The GTV based on PET-CT images was determined by thresholds of SUV ≥ 2.5 and designated as GTV_PET2.5 . The images of T₂ -weighted sequence and diffusion-weighted sequence were referred as GTV_MRI and GTV_DWI , respectively. The length of the abnormality seen on the 4DCT, PET-CT, and DWI was compared.

RESULTS

GTV_PET2.5 was significantly larger than GTV_50% and GTV_MRI (P = .000 and 0.008, respectively), and the volume of GTV_MRI was similar to that of GTV_50% (P = .439). Significant differences were observed between the CI of GTV_MRI to GTV_50% and GTV_PET2.5 to GTV_50% (P = .004). The CI of GTV_MRI to GTV_CT and GTV_PET2.5 to GTV_CT were statistically significant (P = .039). The CI of GTV_MRI to GTV_PET2.5 was significantly lower than that of GTV_MRI to GTV_50% , GTV_MRI to GTV_CT , GTV_PET2.5 to GTV_50% , and GTV_PET2.5 to GTV_CT (P = .000-0.021). Tumor length measurements by endoscopy were similar to the tumor length as measured by PET and DWI scan (P > .05), and there was no significant difference between the longitudinal length of GTV_PET2.5 and GTV_DWI (P = .072).

CONCLUSION

The volumes of GTV_MRI and GTV_50% were similar. However, GTV_MRI has different volumes and poor spatial matching compared with GTV_PET2.5 .The MRI imaging could not include entire respiration. It may be a good choice to guide target delineation and construction of esophageal carcinoma by combining 4DCT with MRI imaging. Utilization of DWI in treatment planning for esophageal cancer may provide further information to assist with target delineation. Further studies are needed to determine if this technology will translate into meaningful differences in clinical outcome.

Reflux Disease and Adenocarcinoma of the Esophagus and Cardia: Global Management and Surgical Treatment

Introduction: Adenocarcinoma of the esophagus and cardia is a rare cancer, associated with chronic reflux disease. Its associated mortality is still very high, reflecting both aggressive biology and lack of adequate treatments. The aim of this article was to describe up to date management of these complex tumors. Materials and Methods: A systematic review of the literature was performed, using PubMed Central database. Articles published after the year 2000 were included, with no language exclusion. Results: Reflux disease and Barrett esophagus are strongly associated with esophageal adenocarcinoma. A strict surveillance should be initiated at diagnosis. Both proton pump inhibitors and antireflux surgery failed to influence the incidence of cancer. Surgery and multimodal therapies are keystones for curative treatment, but no clear consensus exists for the best option. A clear trend in standardization of the surgical approach is observed since last ten years. However, the optimal approach for the tumors of the cardia is still not completely set. Complication rate is still high, but real progresses are made, through the implementation of less invasive techniques. Conclusion: Progress has been made in the management of esophageal cancer. However, the multiplicity of choices failed to lead to standardization. The development of international consensus regarding multimodal treatment and surgical approaches is needed.

A Nomogram to Predict Distant Metastasis for Patients with Esophageal Cancer

BACKGROUND

Distant metastasis of esophageal cancer (EC) is prone to be neglected, so it is necessary to screen out the high-risk population for more sensitive and rigorous pretreatment imaging evaluations.

OBJECTIVE

The aim of this study was to evaluate the risk factors for distant metastasis in patients with EC and to construct a clinical nomogram.

METHODS

Eligible patients diagnosed from 2010 to 2015 were selected from the Surveillance, Epidemiology and End Results (SEER) database. Multivariable logistic regression analysis was applied to establish a prediction nomogram. Discrimination, calibration, clinical usefulness, and reproducibility were assessed by C-index, receiver-operating characteristic curve/the area under the curve (AUC), calibration plot, decision curve analysis (DCA), and bootstrapping validation. DCA was also used to compare the novel model with the conventional predictive methods.

RESULTS

A total of 9,026 patients were included for analysis. The nomogram incorporated the predictors: age, sex, race, grade, T stage, N stage, histology, tumor location, and pathological grading. The prediction model presented good discrimination with an AUC of 0.738 and a concordance index of 0.747 (95% confidence interval: 0.734-0.760), which was confirmed to be 0.745 through bootstrapping validation. Calibration plot and DCA showed satisfactory calibration and good net benefit, respectively. Comparing with the conventional prediction methods, the nomogram yielded superior net benefit.

CONCLUSIONS

We constructed and validated a novel nomogram to help clinicians access the risk of distant metastasis in patients with EC.

Prognostic value of tumor length and diameter for esophageal squamous cell cancer patients treated with definitive (chemo)radiotherapy: Potential indicators for nonsurgical T staging

PURPOSE

The aim of this work was to evaluate the prognostic value of tumor length and diameter for patients with esophageal squamous cell cancer (ESCC) treated with definitive (chemo)radiotherapy to identify potential indicators for separate nonsurgical T staging, which are needed in clinical practice.

MATERIALS AND METHODS

A total of 682 patients with ESCC who underwent definitive (chemo)radiotherapy between 2009 and 2015 were reviewed. Esophageal tumor length and diameter were determined by barium esophagography and computed tomography before treatment. Univariate and multivariate analyses were used to assess the impact of tumor length and diameter on long-term overall survival (OS) and progression-free survival (PFS). Propensity score matching (PSM) analysis was also used to control intergroup heterogeneity.

RESULTS

The median OS and PFS were 22.2 months and 15.4 months, respectively, in the tumor length ≤ 6 cm group, which were significantly longer than those in the tumor length > 6 cm group (13.4 and 8.5 months, respectively). The median OS and PFS were 23.3 months and 15.9 months, respectively, in the tumor diameter ≤ 3.5 cm group, which were also significantly longer than those in the tumor diameter > 3.5 cm group (13.3 and 8.8 months, respectively). Similar results were found after PSM. Univariate and multivariate analyses showed that tumor length and diameter were both independent predictors of long-term survival.

CONCLUSION

Tumor length and diameter are both independent prognostic factors for ESCC patients treated with definitive (chemo)radiotherapy. These two imaging parameters have the potential for development and use in nonsurgical T staging.