☆ 4.1 Review

Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry

JOURNAL OF GASTRIC CANCER (2023)

Related references

Note: Only part of the references are listed.

Article Oncology

Korean Practice Guidelines for Gastric Cancer 2022: An Evidence-based, Multidisciplinary Approach

Tae-Han Kim et al.

Summary: This is the fourth gastric cancer guideline published in Korea, revised in 2018 based on evidence-based approach. It is a collaborative work of an interdisciplinary working group and includes 33 updated or proposed key questions, with 40 statements developed based on systematic review. The evidence level and recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation proposition. The guideline covers screening, diagnosis, staging and follow-up.

JOURNAL OF GASTRIC CANCER (2023)

Add to Collection

Article Multidisciplinary Sciences

Development and validation of a CT radiomics and clinical feature model to predict omental metastases for locally advanced gastric cancer

Ahao Wu et al.

Summary: This study developed and validated a preoperative prediction model using radiomics and clinical features to estimate omental metastases status in patients with locally advanced gastric cancer (LAGC). The model combined radiomics scores and selected clinical features to construct a prediction model and nomogram. The model showed good predictive ability and clinical net benefit, as well as good performance in predicting omental metastases status in LAGC, which could contribute to clinical decision-making.

SCIENTIFIC REPORTS (2023)

Add to Collection

Article Geriatrics & Gerontology

Prognostic artificial intelligence model to predict 5 year survival at 1 year after gastric cancer surgery based on nutrition and body morphometry

Heewon Chung et al.

Summary: This study developed a personalized prognostic artificial intelligence (AI) model to predict 5 year survival at 1 year after gastric cancer surgery based on a large dataset. The AI model showed good performance in both internal and external validation, and the nutritional and fat/muscle indices contributed to the prediction performance.

JOURNAL OF CACHEXIA SARCOPENIA AND MUSCLE (2023)

Add to Collection

Article Oncology

Deep learning model for diagnosing early gastric cancer using preoperative computed tomography images

Qingwen Zeng et al.

Summary: This research aims to construct an AI model for discriminating early gastric cancer (EGC). The results showed that the deep learning model based on ResNet101 neural network can effectively discriminate EGC and differentiate between different tumor locations. This suggests that deep learning classifiers have the potential to be used as a screening tool for EGC, which is crucial in the individualized treatment of EGC patients.

FRONTIERS IN ONCOLOGY (2022)

Add to Collection

Article Surgery

Accuracy of preoperative clinical staging for locally advanced gastric cancer in KLASS-02 randomized clinical trial

Dong Jin Kim et al.

Summary: This study demonstrated the accuracy of preoperative staging for locally advanced gastric cancer through a large-scale randomized clinical trial, and identified risk factors for staging underestimation. It provides important insights for treatment selection and clinical trial design in gastric cancer.

FRONTIERS IN SURGERY (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics signature for predicting postoperative disease-free survival of patients with gastric cancer: development and validation of a predictive nomogram

Shuguang Shi et al.

Summary: Radiomics features combined with clinical factors can effectively predict disease-free survival after gastric cancer surgery. The Rad-score, along with positive lymph nodes and cancer antigen-125, were independently associated with DFS and used to construct a nomogram for clinical prediction. The nomogram showed superior predictive performance compared to the single Rad-score, as validated in training and validation groups.

DIAGNOSTIC AND INTERVENTIONAL RADIOLOGY (2022)

Add to Collection

Article Oncology

Larger Remaining Stomach Volume Is Associated With Better Nutrition and Muscle Preservation in Patients With Gastric Cancer Receiving Distal Gastrectomy With Gastroduodenostomy

Amy Kim et al.

Summary: A larger residual stomach volume is associated with improved nutritional status and better preservation of muscle and fat in patients treated with distal gastrectomy.

JOURNAL OF GASTRIC CANCER (2022)

Add to Collection

Review Oncology

A Comprehensive and Comparative Review of Global Gastric Cancer Treatment Guidelines

Sang Soo Eom et al.

Summary: Countries have diverse treatment guidelines for gastric cancer based on their expertise and research results. This review compared treatment guidelines from five countries and found differences in endoscopic treatment, surgery, perioperative period, and systemic treatment.

JOURNAL OF GASTRIC CANCER (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Utility of the gastric window in computed tomography for differentiation of early gastric cancer (T1 stage) from muscularis involvement (T2 stage)

Zhi-Long Wang et al.

Summary: The use of the gastric window in computed tomography showed higher accuracy in staging T1 and T2 stages of gastric cancer compared to the conventional abdominal window.

ABDOMINAL RADIOLOGY (2021)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

A Heterogeneity Radiomic Nomogram for Preoperative Differentiation of Primary Gastric Lymphoma From Borrmann Type IV Gastric Cancer

Bao Feng et al.

Summary: A nomogram based on heterogeneity radiomic parameters was developed to differentiate primary gastric lymphoma from Borrmann type IV gastric cancer preoperatively. Subjective findings and heterogeneity signature were significant predictors for distinguishing the two groups, with high-enhanced serosa sign identified as an independent predictor. The nomogram demonstrated high diagnostic performance and clinical utility.

JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY (2021)

Add to Collection

Article Oncology

Preoperative nutritional risk index and postoperative one-year skeletal muscle loss can predict the prognosis of patients with gastric adenocarcinoma: a registry-based study

Kyung Won Kim et al.

Summary: Patients with gastric cancer face increased nutritional risk and significant skeletal muscle loss post-surgery. Preoperative nutritional status and muscle loss during the first year after surgery are significant predictors of prognosis in gastric cancer patients. Factors such as skeletal muscle index and nutritional risk index can enhance the accuracy of predicting prognosis, even in cases of tumor recurrence.

BMC CANCER (2021)

Add to Collection

Article Multidisciplinary Sciences

Development of a fully automatic deep learning system for L3 selection and body composition assessment on computed tomography

Jiyeon Ha et al.

Summary: A deep learning model, named L3SEG-net, was developed to select the L3 slice and segment abdominal muscle and fat cross-sectional areas. In internal and external validation datasets, high accuracy of automatic L3 slice selection was achieved, but decreased in accuracy in subgroup analysis of anatomic variations.

SCIENTIFIC REPORTS (2021)

Add to Collection

Review Cell Biology

Updated systematic review and meta-analysis on diagnostic issues and the prognostic impact of myosteatosis: A new paradigm beyond sarcopenia

Hyemin Ahn et al.

Summary: Myosteatosis, excessive fat infiltration in skeletal muscle, is considered a distinct disease from sarcopenia. However, the diagnosis and clinical impact of myosteatosis have not been well established. Providing a systematic review of current issues can elucidate future directions for developing standardized diagnosis and management.

AGEING RESEARCH REVIEWS (2021)

Add to Collection

Review Oncology

Intraoperative Tumor Localization of Early Gastric Cancers

Sang-Ho Jeong et al.

Summary: Recent advances in endoscopic screening systems have enabled the early diagnosis of gastric cancer. Different tumor localization methods for laparoscopic resection of early gastric cancer have been reviewed, with intraoperative gastrofibroscopy showing high accuracy in real-time feedback. The use of endoscopic magnetic marking clips and other detection systems is expected to provide real-time accurate feedback in the near future.

JOURNAL OF GASTRIC CANCER (2021)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics analysis using contrast-enhanced CT for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer

Shunli Liu et al.

EUROPEAN RADIOLOGY (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

Jing Li et al.

EUROPEAN RADIOLOGY (2020)

Add to Collection

Article Surgery

Prediction of Postoperative Mortality in Patients with Organ Failure After Gastric Cancer Surgery

Ji-Ho Park et al.

WORLD JOURNAL OF SURGERY (2020)

Add to Collection

Article Oncology

Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study

D. Dong et al.

ANNALS OF ONCOLOGY (2020)

Add to Collection

Article Oncology

Development and validation of a CT-based radiomic nomogram for preoperative prediction of early recurrence in advanced gastric cancer

Wenjuan Zhang et al.

RADIOTHERAPY AND ONCOLOGY (2020)

Add to Collection

Article Oncology

Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study

Ziyu Li et al.

CANCER MEDICINE (2020)

Add to Collection

Review Oncology

Artificial intelligence in gastric cancer: a systematic review

Peng Jin et al.

JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY (2020)

Add to Collection

Review Gastroenterology & Hepatology

Artificial intelligence in gastric cancer: Application and future perspectives

Peng-Hui Niu et al.

WORLD JOURNAL OF GASTROENTEROLOGY (2020)

Add to Collection

Article Medical Informatics

Assessment of Myosteatosis on Computed Tomography by Automatic Generation of a Muscle Quality Map Using a Web-Based Toolkit: Feasibility Study

Dong Wook Kim et al.

JMIR MEDICAL INFORMATICS (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

CT-based deep learning radiomics analysis for evaluation of serosa invasion in advanced gastric cancer

Rui-Jia Sun et al.

EUROPEAN JOURNAL OF RADIOLOGY (2020)

Add to Collection

Article Oncology

Deep Convolutional Neural Network Based on Computed Tomography Images for the Preoperative Diagnosis of Occult Peritoneal Metastasis in Advanced Gastric Cancer

Zixing Huang et al.

FRONTIERS IN ONCOLOGY (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography

Hyo Jung Park et al.

KOREAN JOURNAL OF RADIOLOGY (2020)

Add to Collection

Article Geriatrics & Gerontology

Sarcopenia: revised European consensus on definition and diagnosis

Alfonso J. Cruz-Jentoft et al.

AGE AND AGEING (2019)

Add to Collection

Article Oncology

Radiomics Signature on Computed Tomography Imaging: Association With Lymph Node Metastasis in Patients With Gastric Cancer

Yuming Jiang et al.

FRONTIERS IN ONCOLOGY (2019)

Add to Collection

Article Oncology

Impact of remnant stomach volume and anastomosis on nutrition and body composition in gastric cancer patients

Koeun Lee et al.

SURGICAL ONCOLOGY-OXFORD (2019)

Add to Collection

Review Radiology, Nuclear Medicine & Medical Imaging

Recent Issues on Body Composition Imaging for Sarcopenia Evaluation

Koeun Lee et al.

KOREAN JOURNAL OF RADIOLOGY (2019)

Add to Collection

Article Medicine, General & Internal

Deep neural network-assisted computed tomography diagnosis of metastatic lymph nodes from gastric cancer

Yuan Gao et al.

CHINESE MEDICAL JOURNAL (2019)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

CT gastrography for volumetric measurement of remnant stomach after distal gastrectomy: a feasibility study

Jimi Huh et al.

ABDOMINAL RADIOLOGY (2016)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

The Role of Three-Dimensional Multidetector CT Gastrography in the Preoperative Imaging of Stomach Cancer: Emphasis on Detection and Localization of the Tumor

Jin Woong Kim et al.

KOREAN JOURNAL OF RADIOLOGY (2015)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Texture-based classification of different gastric tumors at contrast-enhanced CT

Ahmed Ba-Ssalamah et al.

EUROPEAN JOURNAL OF RADIOLOGY (2013)

Add to Collection

Article Oncology

Preoperative N Staging of Gastric Cancer by Stomach Protocol Computed Tomography

Se Hoon Kim et al.

JOURNAL OF GASTRIC CANCER (2013)

Add to Collection

© Peeref 2019-2024. All rights reserved.