Classification Of Esophageal Cancer Research Articles

Segmentation prompts classification: A nnUNet-based 3D transfer learning framework with ROI tokenization and cross-task attention for esophageal cancer T-stage diagnosis

The computer-aided diagnosis system for esophageal cancer (EC) holds vital significance in EC diagnosis and treatment making, with a primary focus on accurate segmentation of EC-related organs and classification of EC’s T-stage. Above two tasks are closely related and crucial in assisting surgeon segment and diagnose cancer early. Note that this paradigm is still at its infancy and limited by closely related open issues: (1) how to link the complementary relationship between these two tasks and improve the originally poor performance? and (2) how to determine whether the tumor has invaded the surrounding muscle layers from CT images? Aiming at these issues, this study develops nn-TransEC, a 3D transfer learning framework that builds upon nnU-Net and synergizes segmentation and classification. nn-TransEC focuses on prompting fine-grained classification of EC’s T-stage with the aid of prior segmentation, which is implemented in two parts: (1) A nnUNet-configured multi-task learning network (nn-MTNet) is designed for complementary segmentation of EC-related organs and classification of EC’s T-stages with cross-task attention gates and transfer learning. (2) A knowledge-embedded ROI tokenization method (KRT) is defined to mimic the diagnostic workflow of doctors for classifying EC’s T-stage. KRT is implemented by cropping the most concerned regions from entire CT volume based on prior segmentation. Experiments have been conducted on a private dataset collected from 169 patients with confirmed EC through pathological diagnosis. Our proposed nn-TransEC is compared against the state-of-the-art counterparts (e.g., nnU-Net and nnFormer), and results demonstrate that: nn-TransEC excels in all compared methods in multi-organ segmentation and classification of EC’s T-stages, with 3D Dice of EC and average AUC of T-stages reaching 0.844 and 0.941, respectively. In contrast, the state-of-the-art method nnFormer achieves 0.814 and 0.927, respectively. Meanwhile, nn-TransEC also outperforms state-of-the-art multi-task learning models in joint segmentation and classification, with Hausdorff Distance of EC and average precision of T-stages reaching 8.497 and 0.845, respectively. In contrast, the state-of-the-art method TransMT-Net achieves 12.206 and 0.730, respectively.

Japanese Classification of Esophageal Cancer, 12th Edition: Part I.

This is the first half of English edition of Japanese Classification of Esophageal Cancer, 12th Edition that was published by the Japan Esophageal Society in 2022.

Japanese Classification of Esophageal Cancer, 12th Edition: Part II

This is the second half of English edition of Japanese Classification of Esophageal Cancer, 12th Edition that was published by the Japan Esophageal Society in 2022.

Deep learning-based identification of esophageal cancer subtypes through analysis of high-resolution histopathology images.

Esophageal cancer (EC) remains a significant health challenge globally, with increasing incidence and high mortality rates. Despite advances in treatment, there remains a need for improved diagnostic methods and understanding of disease progression. This study addresses the significant challenges in the automatic classification of EC, particularly in distinguishing its primary subtypes: adenocarcinoma and squamous cell carcinoma, using histopathology images. Traditional histopathological diagnosis, while being the gold standard, is subject to subjectivity and human error and imposes a substantial burden on pathologists. This study proposes a binary class classification system for detecting EC subtypes in response to these challenges. The system leverages deep learning techniques and tissue-level labels for enhanced accuracy. We utilized 59 high-resolution histopathological images from The Cancer Genome Atlas (TCGA) Esophageal Carcinoma dataset (TCGA-ESCA). These images were preprocessed, segmented into patches, and analyzed using a pre-trained ResNet101 model for feature extraction. For classification, we employed five machine learning classifiers: Support Vector Classifier (SVC), Logistic Regression (LR), Decision Tree (DT), AdaBoost (AD), Random Forest (RF), and a Feed-Forward Neural Network (FFNN). The classifiers were evaluated based on their prediction accuracy on the test dataset, yielding results of 0.88 (SVC and LR), 0.64 (DT and AD), 0.82 (RF), and 0.94 (FFNN). Notably, the FFNN classifier achieved the highest Area Under the Curve (AUC) score of 0.92, indicating its superior performance, followed closely by SVC and LR, with a score of 0.87. This suggested approach holds promising potential as a decision-support tool for pathologists, particularly in regions with limited resources and expertise. The timely and precise detection of EC subtypes through this system can substantially enhance the likelihood of successful treatment, ultimately leading to reduced mortality rates in patients with this aggressive cancer.

Remarkable response as a new indicator for endoscopic evaluation of local efficacy of non-surgical treatments for esophageal cancer.

In Japan, standard of care of the patients with resectable esophageal cancer is neoadjuvant chemotherapy (NAC) followed by esophagectomy. Patients unfitted for surgery or with unresectable locally advanced esophageal cancer are generally indicated with definitive chemoradiotherapy (CRT). Local disease control is undoubtful important for the management of patients with esophageal cancer, therefore endoscopic evaluation of local efficacy after non-surgical treatments must be essential. The significant shrink of primary site after NAC has been reported as a good indicator of pathological good response as well as favorable survival outcome after esophagectomy. And patients who could achieve remarkable shrink to T1 level after CRT had favorable outcomes with salvage surgery and could be good candidates for salvage endoscopic treatments. Based on these data, "Japanese Classification of Esophageal Cancer, 12th edition" defined the new endoscopic criteria "remarkable response (RR)", that means significant volume reduction after treatment, with the subjective endoscopic evaluation are proposed. In addition, the finding of local recurrence (LR) at primary site after achieving a CR was also proposed in the latest edition of Japanese Classification of Esophageal Cancer. The findings of LR are also important for detecting candidates for salvage endoscopic treatments at an early timing during surveillance after CRT. The endoscopic evaluation would encourage us to make concrete decisions for further treatment indications, therefore physicians treating patients with esophageal cancer should be well-acquainted with each finding.

Assessment of Narrow-Band Imaging Algorithm for Video Capsule Endoscopy Based on Decorrelated Color Space for Esophageal Cancer: Part II, Detection and Classification of Esophageal Cancer

Esophageal carcinoma (EC) is a prominent contributor to cancer-related mortality since it lacks discernible features in its first phases. Multiple studies have shown that narrow-band imaging (NBI) has superior accuracy, sensitivity, and specificity in detecting EC compared to white light imaging (WLI). Thus, this study innovatively employs a color space linked to décor to transform WLIs into NBIs, offering a novel approach to enhance the detection capabilities of EC in its early stages. In this study a total of 3415 WLI along with the corresponding 3415 simulated NBI images were used for analysis combined with the YOLOv5 algorithm to train the WLI images and the NBI images individually showcasing the adaptability of advanced object detection techniques in the context of medical image analysis. The evaluation of the model’s performance was based on the produced confusion matrix and five key metrics: precision, recall, specificity, accuracy, and F1-score of the trained model. The model underwent training to accurately identify three specific manifestations of EC, namely dysplasia, squamous cell carcinoma (SCC), and polyps demonstrates a nuanced and targeted analysis, addressing diverse aspects of EC pathology for a more comprehensive understanding. The NBI model effectively enhanced both its recall and accuracy rates in detecting dysplasia cancer, a pre-cancerous stage that might improve the overall five-year survival rate. Conversely, the SCC category decreased its accuracy and recall rate, although the NBI and WLI models performed similarly in recognizing the polyp. The NBI model demonstrated an accuracy of 0.60, 0.81, and 0.66 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it attained a recall rate of 0.40, 0.73, and 0.76 in the same categories. The WLI model demonstrated an accuracy of 0.56, 0.99, and 0.65 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it obtained a recall rate of 0.39, 0.86, and 0.78 in the same categories, respectively. The limited number of training photos is the reason for the suboptimal performance of the NBI model which can be improved by increasing the dataset.

DESIGN AND ANALYSIS OF IODINE STAINING AND NBI IN THE DIAGNOSTIC MODEL AND DIAGNOSIS OF EARLY ESOPHAGEAL CANCER AND ITS PRECANCEROUS LESIONS

Objective: This study aimed to compare the differences between narrowband imaging (NBI) and Lugo’s iodine staining endoscopy (LCE) for detecting and elucidating the site, clarity, and diagnostic accuracy of early esophageal cancer and precancerous lesions. Methods: We included patients with a high risk of developing esophageal cancer who visited the Zhongjiang County People’s Hospital between October 2020 and October 2022. Endoscopic examination was performed on each study participant. White-light endoscopy was used to observe and locate the diseased mucosa, after which NBI mode and LCE staining were used to observe the boundary between the diseased and normal mucosa. Abnormal lesions were found, and biopsies were performed on the identifiable diseased parts for pathological examination. Inflammation, LGIN, HGIN, and early esophageal cancer were diagnosed, and the differences between them were compared in terms of the two enhanced-image endoscopy techniques. A semantic segmentation model based on deep learning was adopted to assist in the diagnosis of early esophageal cancer and accurately locate cancerous areas. In order to improve its accurate diagnostic rate, we also built a semantic segmentation network model to assist in the computer-aided diagnosis of early esophageal cancer. Results: A total of 69 cases of early esophageal cancer were included in this study. The patients were aged 40–75 years, with an average age of [Formula: see text] years. Most early esophageal cancer lesions were located in the middle of the esophagus in 45/69 (65.2%) cases. LCE obtained higher clarity of lesion boundaries than NBI (59.4% versus 45.0% and 27.7% versus 15.9%, respectively), and the proportion of unclear lesions was lower (8.6% versus 21.7% and 4.3% versus 17.4%, respectively; [Formula: see text]). For early esophageal cancer and precancerous lesions, the missed-diagnosis rate of white-light endoscopy was 20%, that of NBI was 3.15%, and that of LCE was 0%, with statistical significance ([Formula: see text]). The rate of missed diagnosis of LGIN (three cases) by NBI was 3.15%, which was not significantly different from that of LCE ([Formula: see text]). We found that the lesion area could be more accurately determined using deep learning models to segment NBI images. By constructing a deep learning model for the diagnosis and classification of esophageal cancer, its diagnostic rate rose to 99.5%. Conclusion: The age range of patients with early esophageal cancer in Zhongjiang County, Sichuan Province, was 40–75 years, and tumors mostly occurred in the middle of the esophagus. The boundary clarity of early esophageal carcinomas was higher on LCE than that on NBI. The diagnostic accuracies of NBI and LCE are much higher than those of conventional white-light endoscopy. Therefore, both LCE and NBI are helpful for detecting early esophageal cancer and precancerous lesions. Moreover, the diagnostic rate of clinical esophageal cancer can be effectively improved using a dedicated deep learning network model.

Combined treatment with surgery and immune checkpoint inhibitor extended survival in a case of gastric intramural metastasis from esophageal cancer: a case report

BackgroundIntramural metastasis (IM) of esophageal cancer is classified as distant metastasis according to the Japanese Classification of Esophageal Cancer, and it is well-known to be associated with a poor prognosis. We herein report a case of perforated gastric IM of esophageal cancer that was successfully controlled with nonradical surgery and subsequent immune checkpoint inhibitor (ICI) treatment.Case presentationA 72-year-old woman was referred to our department for the treatment of esophageal cancer and perforated gastric ulcer. A histological examination of the main tumor and gastric ulcer lesion revealed squamous cell carcinoma. Since the gastric wall tumor had invaded the celiac artery, complete resection was considered impossible. Chemotherapy was administered but led to severe adverse events, so palliative resection was performed. Two months after surgery, computed tomography revealed enlargement of the residual tumor around the celiac artery. However, after nivolumab monotherapy was started, the tumor diminished remarkably, and the quality of life of the patient dramatically improved. Nine months after nonradical surgery, she is surviving without any disease concern.ConclusionsWith the increased availability of ICIs, multidisciplinary treatment with surgery and ICIs can potentially lead to long-term survival, even in cases expected to have a poor prognosis.

Mapping of Lymph Node Metastasis and Efficacy Index in Thoracic Esophageal Squamous Cell Carcinoma: A Large-Scale Retrospective Analysis.

Esophageal squamous cell carcinoma has a high mortality rate in China. The metastatic pattern in the lymph nodes and the value of their dissection on the overall survival of these patients remain controversial. The primary aim of this study was to provide a basis for accurate staging of esophageal cancer and to identify the relationship between esophageal cancer surgery, lymph node dissection, and overall survival rates. We utilized our hospital database to retrospectively review the data of 1727 patients with esophageal cancer who underwent R0 esophagectomy from January 2010 to December 2017. The lymph nodes were defined according to Japanese Classification of Esophageal Cancer, 11th Edition. The Efficacy Index (EI) was calculated by multiplying the frequency (%) of metastases to a zone and the 5-year survival rate (%) of patients with metastases to that zone, and then dividing by 100. The EI was high in the supraclavicular and mediastinal zones in patients with upper esophageal tumors, and the EI of 101R was 17.39, which was the highest among the lymph node stations. In patients with middle esophageal tumors, the EI was highest in the mediastinal zone, followed by the celiac and supraclavicular zones. Furthermore, the EI was highest in the celiac zone, followed by the mediastinal zones in patients with lower esophageal tumors. The EI of resected lymph nodes was found to vary between stations and was related to the primary location of the tumor.

The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy.

Esophageal cancer (EC) is one of the fatal malignant neoplasms worldwide. Neoadjuvant therapy (NAT) combined with surgery has become the standard treatment for locally advanced EC. However, the treatment efficacy for patients with EC who received NAT varies from patient to patient. Currently, the evaluation of efficacy after NAT for EC lacks accurate and uniform criteria. Radiomics is a multi-parameter quantitative approach for developing medical imaging in the era of precision medicine and has provided a novel view of medical images. As a non-invasive image analysis method, radiomics is an inevitable trend in NAT efficacy prediction and prognosis classification of EC by analyzing the high-throughput imaging features of lesions extracted from medical images. In this literature review, we discuss the definition and workflow of radiomics, the advances in efficacy prediction after NAT, and the current application of radiomics for predicting efficacy after NAT.

Short-term safety of adjuvant nivolumab therapy after neoadjuvant docetaxel plus cisplatin and 5-FU therapy for locally advanced esophageal squamous cell carcinoma.

312 Background: CheckMate 577 trial demonstrated efficacy of adjuvant nivolumab (Ad-Nivo) therapy in locally advanced esophageal cancer patients (pts) who underwent surgery after neoadjuvant chemoradiotherapy and did not achieve pathologic complete response. In Japan, neoadjuvant docetaxel plus cisplatin, 5-FU (NeoDCF) therapy is the standard care for locally advanced resectable esophageal squamous cell carcinoma (ESCC) based on the results of the JCOG1109 study. The efficacy and safety of Ad-Nivo therapy after NeoDCF therapy were unknown, so guidelines recommendations have not been determined. Methods: The subjects of this retrospective study were pts with histologically confirmed resectable locally advanced ESCC who received Ad-Nivo (480mg/body, every 4 weeks for 12 times) after NeoDCF in our hospital from Jan 2022 to Sep 2022. We evaluated safety as adverse events during treatments and clinical outcomes. Results: Twenty pts were selected in this study. Characteristics were median age (range) 65 (51–75) years, male/female 70/30%, PS 0/1 85/15%, Ce/Ut/Mt/Lt 5/15/50/30%, clinical stage II/III/IVA/IVB (supraclavicular lymph node) 10/70/0/20%, pathological stage IIB/IIIA/IIIB/IVA/IVB 30/5/40/10/15%. The pathological response according to Japanese Classification of Esophageal Cancer was Grade 0/1a/1b/2/3 5/20/20/40/15%. Median time (range) from surgery to Ad-Nivo was 9 weeks (4-20 weeks). The adverse events included fatigue (30%), increase AST (30%), increase ALT (15%), pruritus (15%), hyperthyroidism (15%), diarrhea (10%), decreased appetite (10%), and pneumonitis (10%). Grade >3 adverse events were not observed. Recurrence was observed in three pts (15%), which site was regional lymph node (2 pts of pathological stage III and IVB) and anastomosis (1pt of pathological stage IVA). Three pts with recurrence received definitive chemoradiotherapy, and still continue the treatment. Conclusions: The short-term toxicity of Ad-Nivo after NeoDCF was well-tolerated and acceptable.

262. A STUDY OF METASTATIC LOCATION AND PROGNOSIS FOR ESOPHAGEAL CANCER WITH ONE OR TWO METASTATIC LYMPH NODES

Abstract Esophageal cancer has high frequency of lymph node (LN) metastasis and poor prognosis, and often relapse early even after radical esophagectomy. Extensive LN dissection has made it possible to grasp the detailed metastatic status and the relationship between LN metastasis and prognosis. It is necessary to study more about metastatic style and prognostic factors for minimalization of surgical invasion and individualization of treatment. We analyzed about metastatic location, prognosis and recurrence for esophageal cancer cases with a few LN metastasis. We study 168 stageII, III esophageal cancer cases that underwent radical esophageal resection with regional LN dissection (D2 or more) from January 2015 to December 2017. Those cases included 37 or 29 cases with one or two LN metastasis. The number of cases on each tumor location (Ce/Ut/Mt/Lt/Ae) were 4/19/80/55/10 cases. On LN dissection, D2 were 68 cases and D3 were 100 cases. In a comparison of survival rate, age (<65/≧65), lymphatic invasion, the number of metastatic lymph node have significant difference. The 5-years overall survival rate of esophageal cancer with one or two metastatic LNs was each 82.9% or 65%. Most of a few LN metastasis cases have first group LN metastasis (11th Japanese Classification of Esophageal Cancer), for example No.106rec or abdominal LNs, but we didn’t sometimes detect them prior to surgery. Esophageal cancer with a few metastatic lymph nodes had relatively good prognosis, and metastasis was likely to stay nearby the primary lesion. However, it is difficult to detect metastasis precisely prior to surgery, so developing the further technique of diagnosis and individualized treatment are expected in the future.

544. NON-EPSTEIN-BARR VIRUS ASSOCIATED LYMPHOEPITHELIOMA-LIKE CARCINOMA OF THE ESOPHAGUS WITH SURGICAL TREATMENT: A REPORT OF TWO CASES

Abstract Lymphoepithelioma-like carcinoma (LELC) can occur in many organs such as lung, stomach, skin, breast, bile ducts, esophagus, and other many organs. Esopahageal lymphoepithelioma-like carcinoma is an extremely rare disease. LELC has been reported to be associated with Epstein-Barr virus (EBV) in some organs, although there are many controversies. Here, we report a surgically treated two cases of non-Epstein-Barr virus associated LELC of the esophagus. Case 1was a 46-year-old woman who was presented epigastralgia while eating. Upper gastrointestinal endoscopy showed a submucosal tumor in the lower esophagus. Biopsies were taken, and they identified atypical cells proliferating follicular manner and heavy infiltration of lymphocytes. Case 2 was a 71-year-old man who was pointed out to have a tumor in the esophagus by barium examination and was referred to our hospital. Upper gastrointestinal endoscopy showed submucosal tumor was found 23-26 cm from the cut tooth. Endoscopic Ultrasound-guided Fine Needle Aspiration (EUS-FNA) was performed and diagnosed with LELC. These patients underwent subtotal esophagectomy with lymphadenectomy and reconstruction with gastric tube. Case1 was pathologically diagnosed with LELC, SM3, INFa, ly0, V0, pIM0, pPM0 (100mm), pDM0 (120mm), pRM0, pN0, cM0, pStageI, and case2 was diagnosed with LELC, ly1, V1, pIM0, pPM0, pDM0, pRM0, pN0, cM0, pStageI, according to the 10th edition of Japanese classification of Esophageal cancer. Immunohistochemical staining of the specimen from case 1 was positive for AE1/AE3, P40, p63, and negative for CD56 and chromogranin A. Immunohistochemical staining of the specimen from case 2 was positive for CK, EMA, P40, and negative forαSMA and desmin. EBV was not detected by EBER in situ hybridization in the specimen from both patients. LELC is relatively common in salivary glands, thymus, lungs, stomach, skin, and cervix, and EBV that directly infects epithelial cells or infects lymphocytes infects epithelial cells and infects them. EBV infects epithelial cells and is thought to be associated with carcinogenesis of these organs. However, esophageal LELC is rare and it has been argued that EBV may not be involved. In these two cases, EBV was not detected in situ hybridization.

Atom Search Optimization with the Deep Transfer Learning-Driven Esophageal Cancer Classification Model.

Esophageal cancer (EC) is a commonly occurring malignant tumor that significantly affects human health. Earlier recognition and classification of EC or premalignant lesions can result in highly effective targeted intervention. Accurate detection and classification of distinct stages of EC provide effective precision therapy planning and improve the 5-year survival rate. Automated recognition of EC can aid physicians in improving diagnostic performance and accuracy. However, the classification of EC is challenging due to identical endoscopic features, like mucosal erosion, hyperemia, and roughness. The recent developments of deep learning (DL) and computer-aided diagnosis (CAD) models have been useful for designing accurate EC classification models. In this aspect, this study develops an atom search optimization with a deep transfer learning-driven EC classification (ASODTL-ECC) model. The presented ASODTL-ECC model mainly examines the medical images for the existence of EC in a timely and accurate manner. To do so, the presented ASODTL-ECC model employs Gaussian filtering (GF) as a preprocessing stage to enhance image quality. In addition, the deep convolution neural network- (DCNN-) based residual network (ResNet) model is applied as a feature extraction approach. Besides, ASO with an extreme learning machine (ELM) model is utilized for identifying the presence of EC, showing the novelty of the work. The performance of the ASODTL-ECC model is assessed and compared with existing models under several medical images. The experimental results pointed out the improved performance of the ASODTL-ECC model over recent approaches.

Efficacy and safety of definitive chemoradiotherapy in patients with unresectable locally advanced esophageal squamous cell carcinoma.

252 Background: The standard treatment for patients with unresectable locally advanced esophageal squamous cell carcinoma (ESCC) is platinum-based definitive chemoradiotherapy (dCRT). Previous clinical trials have indicated a clinical complete response (cCR) rate of 11%-25% and median overall survival (OS) of 9-10 months. The cCR rate is strongly correlated with good prognosis, however the predictive factors have not been elucidated. Methods: In this multi-institutional retrospective study, we evaluated the efficacy and safety of dCRT in patients with unresectable locally advanced ESCC. “Unresectable” was defined as the primary lesion (T4b) invading adjacent structures such as the aorta, vertebral body, and trachea, or the regional and/or supraclavicular lymph nodes (LNT4b) invading unresectable adjacent structures. cCR was determined by both computed tomography and endoscopy based on the Response Evaluation Criteria in Solid Tumors (version 1.1) with modifications and Japanese Classification of Esophageal Cancer (11th edition), respectively. Results: A total of 175 patients who started dCRT between January 2013 to March 2020, were included in this study. The overall median age was 68 (31-86). A total of 95 (54%) patients had a performance status of 0. Of these, 124 (71%) patients had T4b and 81 (46%) had LNT4b. The clinically involved site were as follows: thoracic aorta (22%), tracheobronchial tree (73%), and others (14%). The median tumor length was 6 (2-22) cm. 56 (32%) patients were tube-fed owing to obstructive tumors. 165 (96%) patients completed at least one cycle of chemotherapy with 60 Gy of radiation. Further, 84 (48%) patients received consolidation chemotherapy following dCRT. The confirmed cCR rate was 24% (42/175). At a median follow-up interval of 20 months, the 2-year OS and progression-free survival (PFS) rates of cCR cases vs. non-cCR cases were 90% vs. 31% (log-rank p < 0.001) and 59% vs. 2% (log-rank p < 0.001), respectively. Multivariate analysis of the clinicopathological factors contributing to cCR revealed that a tumor length of≥6 cm (OR, 0.4; 95% CI, 0.2–0.9 p = 0.03) was the only a significant predictive factor. The primary adverse events of grade 3 or above were esophagitis (32%), pneumonitis (13%), fistula formation (10%), febrile neutropenia (9%), and dyspnea (6%). Among 22 patients who originally presented with fistula formation, fistula disappeared in 14 (64%), including 3 cCR cases. Two (1%) sudden deaths secondary to severe hemorrhage and suspected aortic fistula were observed during the treatment period. Conclusions: dCRT is feasible for patients with unresectable locally advanced ESCC. The cCR rate of dCRT is consistent with that reported in previous clinical trials, and favorable OS and PFS rates were observed in patients with cCR. Tumor length was observed to be a significant predictive factor of cCR. Research Sponsor: None.

54 CLINICOPATHOLOGICAL FEATURES AND TREATMENT OUTCOMES OF ESOPHAGOGASTRIC JUNCTIONAL CARCINOMA TREATED WITH CURATIVE SURGERY

Abstract Compared to Western countries, Japanese esophagogastric junctional carcinoma (JC) demonstrates different epidemiologic backgrounds; squamous cell carcinoma is dominant over Barrett adenocarcinoma, and there is no consensus on surgical approach or dissection range of lymph node. JC is defined as the cancer, that is the center of the tumor is within 2 cm from the esophagogastric junction to the esophagus and stomach respectively by the Japanese Classification of Esophageal Cancer, 11th edition. Methods According to the definition, we examined the clinicopathological features and treatment outcomes of patients who underwent curative resection and pathologically defined as JC. From 2012 to 2019, 23 consecutive patients with JC who received with curative surgery in Shiga University of Medical Science Hospital were included. Clinicopathological classification was based on Japanese Classification of Esophageal Cancer, 11th edition. The patients consisted of 18 males and 5 females, median age was 68 (43–91) years old. Results Pathological diagnoses were 19 adenocarcinoma, 1 squamous cell carcinoma, 2 mixed adenoneuroendocrine carcinoma (MANEC) and 1 malignant melanoma. Patients with Barrett’s esophagus were 7 cases (30.4%). Surgical procedure was esophagectomy via right thoracotomy 9 cases, esophagectomy via left thoracotomy 2 case and laparotomy 12 cases. Tumor invasion was pT1:6 (26.1%), pT2:3 (13.0%), pT3:5 (21.7%) and pT4:9 (39.1%). Lymph node metastases were observed in 16 cases (69.6%) and #1,2,3:15 cases (93.8%), #4,5: 3 cases (18.8%), #7,8a,9: 6 cases (37.5%), #19,20: 3 cases (18.8%) and #105–110: 5 cases (31.3%). Among 7 recurrence patients, peritonitis carcinomatosa was 4 cases. Conclusion In most positive lymph node metastasis cases, metastasis was observed in #1, 2 and 3 lymph nodes, but metastasis to the cervical lymph node was not observed. In the G, GE cases, right thoracotomy was not performed because there were no metastases to the upper mediastinal lymph nodes. These results suggested that surgical operation could be reduced to proximal gastrectomy for early G, GE cases. Future studies are necessary to further evaluate this result.

Prognostic Significance of the Number and Extent of Metastatic Lymph Nodes in Patients with Esophageal Cancer: Comparison of the Union for International Cancer Control 8th Edition and Japan Esophageal Society Japanese Classification of Esophageal Cancer 11th Edition Classifications for Esophageal Cancer.

The tumor, node, metastasis staging system of the Union for International Cancer Control (UICC) has been used worldwide for esophageal cancer, and, in Japan, the Japan Esophageal Society Japanese Classification of Esophageal Cancer (JES) has also been used; however, there is a big difference between the two classifications with regard to node staging. We hypothesized that these two node staging systems may lead to different outcome predictions in terms of tumor location. This study enrolled 409 patients who underwent esophagectomy at Keio University Hospital, Tokyo, Japan, between January 2005 and December 2017. We included those who underwent R0 or R1 resection or esophagectomy with additional organ excision, and excluded those who underwent salvage surgery. Thereafter, we investigated how the number or spread of metastatic lymph nodes affected the prognosis. For all 409 patients, the 5-year overall survival rate was 64.1% and the 5-year recurrence-free survival rate was 58.4%. The concordance indices were 0.756 for UICC 8th edition pathological node staging and 0.732 for JES 11th edition pathological node staging (p = 0.06). Based on tumor location, the difference in the concordance indices between these two classifications was greatest for lower thoracic esophageal tumors (p = 0.02). For all patients, the UICC 8th edition node staging system tended to reflect survival more precisely than that of the JES 11th edition. For lower thoracic esophageal tumors in particular, the former node staging system could be more useful.

A proposal for uniformity in classification of lymph node stations in esophageal cancer.

SummaryThe 11th edition of the “Japanese Classification of Esophageal Cancer” by the Japan Esophageal Society (JES) and the 8th edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) “Cancer Staging Manual” are two separate classification systems both widely used for the clinical and pathological staging of esophageal cancer. Furthermore, the lymph node stations from these classification systems are combined for research purposes in the multinational TIGER study, which investigates the distribution pattern of lymph node metastases. The existing classification systems greatly differ with regard to number, location and anatomical boundaries of locoregional lymph node stations. The differences in these classifications cause significant heterogeneity in studies on lymph node metastases in esophageal cancer. This makes data interpretation difficult and comparison of studies challenging. In this article, we propose a match for these two commonly used classification systems and additionally for the TIGER study classification, in order to be able to compare results of studies and exchange knowledge and to make steps towards one global uniform classification system for all patients with esophageal cancer.

Evaluation and treatment results of trimodality therapy for advanced esophageal squamous cell carcinoma.

The prognosis for highly advanced esophageal squamous cell carcinoma (ESCC) remains poor, and there is currently no standard treatment. The purpose of this study was to examine the benefits of trimodality therapy [chemoradiation plus surgery, (CRT + S)] by evaluating the surgical outcomes of patients with ESCC in Keiyukai Sapporo Hospital, Japan. We assessed the preoperative and postoperative adverse events, treatment effects of preoperative CRT, metastatic diagnosis of the dissected lymph nodes, and survival. Between 2012 and 2018, 148 patients with highly advanced ESCC who underwent preoperative CRT + S were analyzed for diagnosis and staging, preoperative complications, clinical and histopathological effects of CRT in the resected specimens, survival rates, and recurrences. The grade 3 and higher complications of preoperative CRT were neutropenia in 3 cases and thrombocytopenia in 1 case. Among the postoperative complications, there were 2 cases (1.4%) of direct surgical death, only tracheobronchial bleeding and liver failure. Using the 11th edition of the classification of esophageal cancer by the Japanese Esophageal Society, 60 patients (40.5%) were classified as grade 3 (negative for cancer cells, pathological complete response). However, 20 of them (33.3%) had metastatic tumor cells in the lymph nodes. The overall 5-year survival rate was 58.5%. Including references to the pathological findings and recurrence patterns, there is no effective diagnostic method for selecting the subsequent approach based on the effectiveness of CRT. Planned surgery following CRT was the only solution for achieving better treatment results. CRT + S is a promising treatment with low direct surgical mortality.

Ways and tradition of Japan in esophageal surgery for cancer.

This report presents the essence in practice of Japanese methods and tradition in surgery for esophageal cancer. The etiology of esophageal cancer and the concepts of lymphadenectomy in esophagectomy, in neoadjuvant treatments, and in stage classifications are compared between Western countries and Japan. With respect to the type and relative incidence of esophageal cancer, in Western countries, adenocarcinoma in the lower thoracic esophagus and in the cardia is common, and among esophageal surgeons, there remains some controversy over the extent of lymphadenectomy. On the other hand, in Japan, squamous cell carcinoma in the middle thoracic esophagus is common, and concerning lymphadenectomy, Japanese esophageal surgeons consider that three-field lymphadenectomy is superior to other types of lymphadenectomy. In Japan, surgeons believe that most patients with esophageal cancer even those having lymph node metastasis can be best treated using esophagectomy and lymphadenectomy. In Japan, the tradition in esophageal surgery places great significance on lymphadenectomy. The ways and procedures for esophageal cancer surgery, the neoadjuvant and adjuvant treatments, the Japanese Classification of Esophageal Cancer, the Esophageal Cancer Practice Guidelines, and other scientific reports are all based on a close combination of esophagectomy with lymphadenectomy.