A histopathologic feature of the behavior of gastric signet‐ring cell carcinoma; an image analysis study with deep learning

2019 ◽  
Vol 69 (7) ◽  
pp. 437-439 ◽  
Author(s):  
Hideo Mori ◽  
Hideaki Miwa
Keyword(s):  
Image Analysis ◽  
Deep Learning ◽  
Cell Carcinoma ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Analysis Study ◽  
Signet Ring ◽  
Ring Cell ◽  
Histopathologic Feature

scholarly journals Quantifying the Cell Morphology and Predicting Biological Behavior of Signet Ring Cell Carcinoma using Deep Learning

2021 ◽  
Author(s):  
Qian Da ◽  
Shijie Deng ◽  
Jiahui Li ◽  
Hongmei Yi ◽  
Xiaodi Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cell Carcinoma ◽  
Histopathological Examination ◽  
Morphological Characteristics ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Biological Behavior ◽  
Signet Ring ◽  
Poorly Differentiated ◽  
Ring Cell

Abstract Signet ring cell carcinoma(SRCC) is a malignant tumor of the digestive system. This tumor has long been considered to be poorly differentiated and highly invasive because it has a higher rate of metastasis than well-differentiated adenocarcinoma. But some studies in recent years have shown that the prognosis of some SRCC is more favorable than other poorly differentiated adenocarcinomas, which suggests that SRCC has different degrees of biological behavior. Therefore, we need to find a histological stratification that can predict the biological behavior of SRCC. Some studies indicate that the morphological status of cells can be linked to the invasiveness potential of cells, however, the traditional histopathological examination can not objectively define and evaluate them. Recent improvements in biomedical image analysis using deep learning(DL) based neural networks could be exploited to identify and analyze SRCC. In this study, we used DL to identify each cancer cell of SRCC in whole slide images(WSIs) and quantify their morphological characteristics and atypia. Our results show that the biological behavior of SRCC can be predicted by quantifying the morphology of cancer cells by DL. This technique could be used to predict the biological behavior and may change the stratified treatment of SRCC.

scholarly journals Deep Learning Models for Gastric Signet Ring Cell Carcinoma Classification in Whole Slide Images

2021 ◽  
Vol 20 ◽  
pp. 153303382110279
Author(s):  
Fahdi Kanavati ◽  
Shin Ichihara ◽  
Michael Rambeau ◽  
Osamu Iizuka ◽  
Koji Arihiro ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cell Carcinoma ◽  
Supervised Learning ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Learning Models ◽  
Signet Ring ◽  
Ring Cell ◽  
Test Sets ◽  
Whole Slide Images

Signet ring cell carcinoma (SRCC) of the stomach is a rare type of cancer with a slowly rising incidence. It tends to be more difficult to detect by pathologists, mainly due to its cellular morphology and diffuse invasion manner, and it has poor prognosis when detected at an advanced stage. Computational pathology tools that can assist pathologists in detecting SRCC would be of a massive benefit. In this paper, we trained deep learning models using transfer learning, fully-supervised learning, and weakly-supervised learning to predict SRCC in Whole Slide Images (WSIs) using a training set of 1,765 WSIs. We evaluated the models on two different test sets (n = 999, n = 455). The best model achieved a ROC-AUC of at least 0.99 on all two test sets, setting a top baseline performance for SRCC WSI classification.

scholarly journals Quantifying the cell morphology and predicting biological behavior of signet ring cell carcinoma using deep learning

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Qian Da ◽  
Shijie Deng ◽  
Jiahui Li ◽  
Hongmei Yi ◽  
Xiaodi Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cell Carcinoma ◽  
Histopathological Examination ◽  
Morphological Characteristics ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Biological Behavior ◽  
Signet Ring ◽  
Poorly Differentiated ◽  
Ring Cell

AbstractSignet ring cell carcinoma (SRCC) is a malignant tumor of the digestive system. This tumor has long been considered to be poorly differentiated and highly invasive because it has a higher rate of metastasis than well-differentiated adenocarcinoma. But some studies in recent years have shown that the prognosis of some SRCC is more favorable than other poorly differentiated adenocarcinomas, which suggests that SRCC has different degrees of biological behavior. Therefore, we need to find a histological stratification that can predict the biological behavior of SRCC. Some studies indicate that the morphological status of cells can be linked to the invasiveness potential of cells, however, the traditional histopathological examination can not objectively define and evaluate them. Recent improvements in biomedical image analysis using deep learning (DL) based neural networks could be exploited to identify and analyze SRCC. In this study, we used DL to identify each cancer cell of SRCC in whole slide images (WSIs) and quantify their morphological characteristics and atypia. Our results show that the biological behavior of SRCC can be predicted by quantifying the morphology of cancer cells by DL. This technique could be used to predict the biological behavior and may change the stratified treatment of SRCC.

scholarly journals Primary signet‐ring cell carcinoma of the lung in an HIV‐positive patient

2021 ◽  
Vol 12 (7) ◽  
pp. 1122-1125
Author(s):  
Alberto Testori ◽  
Gianluca Perroni ◽  
Camilla De Carlo ◽  
Alessandro Crepaldi ◽  
Marco Alloisio ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Positive Patient ◽  
Hiv Positive ◽  
Signet Ring ◽  
Ring Cell

scholarly journals Primary Signet Ring Cell/Histiocytoid Carcinoma of the Eyelid: Somatic Mutations in CDH1 and Other Clinically Actionable Mutations Imply Early Use of Targeted Agents

2021 ◽  
Vol 28 (1) ◽  
pp. 918-927
Author(s):  
Lei-Chi Wang ◽  
Tai-Chi Lin ◽  
Yi-Chen Yeh ◽  
Hsiang-Ling Ho ◽  
Chieh-Chih Tsai ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Cell Carcinoma ◽  
Tumor Tissue ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Next Generation ◽  
Signet Ring ◽  
Ring Cell ◽  
Generation Sequencing ◽  
E Cadherin

Primary signet ring cell/histiocytoid carcinoma of the eyelid is a rare ocular malignancy and its diagnosis is often delayed. This neoplasm presents as an insidious, diffusely infiltrative mass in the periocular area that later infiltrates the orbit. An exenteration is usually indicated; however, nearly one-third of patients develop local recurrence or metastasis. Morphologically, it resembles signet ring cell carcinoma of the stomach and breast, raising the possibility of mutations in CDH1, the gene encoding E-cadherin. To determine whether primary signet ring cell/histiocytoid carcinoma harbors the CDH1 mutation or other actionable mutations, we analyzed the tumor tissue via next-generation sequencing. We identified only one case of primary signet ring cell carcinoma of the eyelid with adequate DNA quality for sequencing from the pathological archive during the period 2000 to 2020. A comprehensive evaluation including histopathology, immunohistochemistry, and next-generation sequencing assay was performed on tumor tissue. Immunohistochemically, the tumor exhibited E-cadherin membranous staining with the aberrant cytoplasmic staining of β-catenin. Using next-generation sequencing, we demonstrated the mutation in the CDH1 gene. In addition, other clinically actionable mutations including ERBB2 and PIK3CA were also detected. The alterations in other actionable genes indicate a need for larger studies to evaluate the pathogenesis and potential therapies for primary signet ring cell/histiocytoid carcinoma of the eyelid.

Fundic Gland Polyp With Parietal Cell Vacuolation Mimicking Signet Ring Cell Carcinoma

2021 ◽  
pp. 106689692199418
Author(s):  
John D. Coyne ◽  
S. Thampy
Keyword(s):  
Proton Pump Inhibitor ◽  
Cell Carcinoma ◽  
Parietal Cell ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Fundic Gland ◽  
Fundic Gland Polyp ◽  
Signet Ring ◽  
Ring Cell

Pseudo-signet ring parietal cell vacuolation has been described as a mimic of invasive signet ring cell carcinoma. Moreover, signet ring cell carcinoma has been described in a fundic gland polyp. This case demonstrates parietal cell vacuolation in a fundic gland polyp in a patient on a long-term proton pump inhibitor.

scholarly journals A Signet Ring Cell Carcinoma Presented as Refractory Acquired Thrombotic Thrombocytopenic Purpura

2020 ◽  
Vol 13 (3) ◽  
pp. 1368-1372
Author(s):  
Umit Yavuz Malkan ◽  
Murat Albayrak ◽  
Hacer Berna Ozturk ◽  
Merih Reis Aras ◽  
Bugra Saglam ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Plasma Exchange ◽  
Thrombotic Thrombocytopenic Purpura ◽  
Unknown Origin ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Thrombocytopenic Purpura ◽  
Signet Ring ◽  
Gastric Endoscopy ◽  
Ring Cell

Microangiopathic hemolytic anemia (MAHA) can be observed as a paraneoplastic syndrome (PS) in certain tumors. MAHA-related signet ring cell carcinoma (SRCC) of an unknown origin is very infrequent. Herein we present a SRCC case presented with refractory acquired thrombotic thrombocytopenic purpura (TTP). A 35-year-old man applied to the emergency service with fatigue and headache. His laboratory tests resulted as white blood cell 9,020/µL, hemoglobin 3.5 g/dL, platelet 18,000/µL. Schistocytes, micro-spherocytes, and thrombocytopenia were observed in his blood smear. MAHA was present and he was considered as having TTP. Plasma exchange treatment was initiated; however, he was refractory to this treatment. Thorax and abdomen computerized tomography revealed thickening of minor curvature in stomach corpus with hepatogastric and paraceliac lymphadenopathy. Bone marrow (BM) investigation by our clinic resulted as the metastasis of adenocarcinoma. Ulceration and necrosis were observed by gastric endoscopy procedure. Biopsy was taken during endoscopic intervention, which resulted as SRCC. MAHA may be seen as a PS in some tumors, especially gastric cancers. Tumor-related MAHA is generally accompanied by BM metastases. As a result, BM investigation may be used as the main diagnostic method to find the underlying cancer. The clinical course of cases with tumor-related MAHA is usually poor, and these cases are usually refractory to plasma exchange treatment. In conclusion, physicians should suspect a malignancy and BM involvement when faced with a case of refractory TTP.

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