Advances in the Diagnosis and Treatment of Hepatogastroenterology

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 5601

Special Issue Editor


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Guest Editor
1. Endoscopic Center, Changhua Christian Hospital, 3 Lane 138 Tai-An 2nd Street, Changhua City 500, Taiwan
2. Yuan Lin Branch, Department of Hospitality Management, MingDao University, Changhua City 523, Taiwan
Interests: gastrointestinal diseases; hepatobiliary and pancreatic diseases; small intestinal diseases

Special Issue Information

Dear Colleagues,

Advances in the diagnosis and treatment of hepato-gastrointestinal diseases have been remarkable in recent years. Imaging has advanced significantly regarding the diagnosis of gastrointestinal diseases, including chromoendoscopy, upper and lower gastrointestinal endoscopy, employing artificial intelligence (AI) applications, capsule endoscopy, deep enteroscopy, and endoscopic ultrasound. Imaging in the diagnosis of hepatology has also crucially developed, particularly in terms of producing color ultrasound with contrast, abdominal multidetector-computed tomography, and advanced magnetic resonance imaging.

Surgery remains a major aspect of treating hepato-gastrointestinal diseases, especially with regard to malignancy. The introductions of multimodal therapy, including target therapy and immuno-oncological (I-O) therapy, have dramatically enhanced the chance of surviving advanced malignancy.

I wish to express my sincere gratitude to all the authors wishing to submit contributions to this Special Issue.

The forthcoming Special Issue focuses on the diagnosis and treatment of hepato-gastrointestinal diseases. Welcome topics include, but are not limited to, the following:

Novel diagnostic imaging and therapeutic techniques for application in hepatic diseases;

Novel diagnostic imaging and therapeutic techniques for application in gastroenterology diseases.

Dr. Yang-Yuan Chen
Guest Editor

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Keywords

  • primary hepatic angiosarcoma
  • deep enteroscopy
  • pneumatosis intestinalis and portal vein air
  • acute abdomen
  • refractory gastrointestinal bleeding
  • medical diagnosis

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Published Papers (3 papers)

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Research

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12 pages, 516 KiB  
Article
Non-Invasive Serum Biomarkers for the Diagnosis of Cirrhosis in Patients with Autoimmune Hepatitis (AIH) and AIH-Primary Biliary Cholangitis Overlap Syndrome (AIH-PBC): Red Cell Distribution Width to Platelet Ratio (RPR) Yielded the Most Promising Result
by Siwanon Nawalerspanya, Jarukit Tantipisit, Suraphon Assawasuwannakit, Apichat Kaewdech, Naichaya Chamroonkul and Pimsiri Sripongpun
Diagnostics 2024, 14(3), 265; https://doi.org/10.3390/diagnostics14030265 - 25 Jan 2024
Cited by 1 | Viewed by 2177
Abstract
Several serum biomarkers for fibrosis assessment have been proposed in various liver diseases, but in autoimmune hepatitis (AIH) or overlap with primary biliary cholangitis (PBC; AIH-PBC) patients, the data are scarce. This retrospective cross-sectional study was conducted to validate six non-invasive biomarkers in [...] Read more.
Several serum biomarkers for fibrosis assessment have been proposed in various liver diseases, but in autoimmune hepatitis (AIH) or overlap with primary biliary cholangitis (PBC; AIH-PBC) patients, the data are scarce. This retrospective cross-sectional study was conducted to validate six non-invasive biomarkers in the diagnosis of cirrhosis (F4 fibrosis) in such patients. We included adult patients diagnosed with AIH or AIH-PBC overlap syndrome who underwent a liver biopsy between 2011 and 2021. Laboratory data were collected to calculate the following scores: red cell distribution width to platelet ratio (RPR), aspartate aminotransferase/platelet ratio index (APRI), Fibrosis-4 index (FIB-4), aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio (AAR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-platelet ratio (LPR). A total of 139 patients were eligible (111 AIH and 28 AIH-PBC). The prevalence of cirrhosis was 35.3% (36% in AIH and 32.1% in AIH-PBC). The AUROCs of the RPR, FIB-4, APRI, AAR, LPR, and NLR in all patients were 0.742, 0.724, 0.650, 0.640, 0.609, and 0.585, respectively. RPR was significantly superior to APRI, NLR, and LPR. Moreover, RPR showed the highest AUROC (0.915) in the overlap AIH-PBC subgroup. In conclusion, RPR yielded the highest diagnostic accuracy to predict cirrhosis in AIH and AIH-PBC overlap syndrome patients, while FIB-4 was considerably optimal. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Treatment of Hepatogastroenterology)
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11 pages, 1639 KiB  
Article
Predictive Factors Correlated with Successful Early Endoscopic Removal of Pancreaticolithiasis in Chronic Pancreatitis after Extracorporeal Shock Wave Lithotripsy
by Thanawin Wong, Tanawat Pattarapuntakul, Nisa Netinatsunton, Bancha Ovartlarnporn, Jaksin Sottisuporn, Thanapon Yaowmaneerat, Siriboon Attasaranya, Kamonwon Cattapan and Pimsiri Sripongpun
Diagnostics 2024, 14(2), 172; https://doi.org/10.3390/diagnostics14020172 - 12 Jan 2024
Cited by 1 | Viewed by 1227
Abstract
Background: The treatment of chronic pancreatitis (CP) and symptomatic pancreatic duct (PD) calculi often involves techniques like endoscopic retrograde cholangiopancreatography (ERCP), extracorporeal shock wave lithotripsy (ESWL), or a combination of both. However, identifying predictive factors for the successful removal of these calculi remains [...] Read more.
Background: The treatment of chronic pancreatitis (CP) and symptomatic pancreatic duct (PD) calculi often involves techniques like endoscopic retrograde cholangiopancreatography (ERCP), extracorporeal shock wave lithotripsy (ESWL), or a combination of both. However, identifying predictive factors for the successful removal of these calculi remains variable. This study aimed to determine the factors predicting successful ESWL and endoscopic removal in CP and PD calculi patients. Methods: We examined data from CP patients who underwent complete PD calculi removal via ESWL combined with ERCP between July 2012 and 2022, and assessed baseline characteristics, imaging findings, and treatment details. Patients were categorized into early- and late-endoscopic complete removal groups (EER and LER groups, respectively). Results: Of the 27 patients analyzed, 74.1% were male with an average age of 44 ± 9.6 years. EER was achieved in 74% of the patients. Patients in the EER group exhibited smaller PD calculi diameter (8.5 vs. 19 mm, p = 0.012) and lower calculus density (964.6 vs. 1313.3 HU, p = 0.041) compared to the LER group. Notably, PD stricture and the rate of PD stent insertion were not different between the groups. A calculus density threshold of 1300 HU on non-contrast CT demonstrated 71% sensitivity and 80% specificity in predicting EER. Conclusions: Smaller and low-density PD calculi may serve as predictors for successful EER, potentially aiding in the management of CP patients with PD calculi. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Treatment of Hepatogastroenterology)
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Review

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12 pages, 1259 KiB  
Review
The Advent of Domain Adaptation into Artificial Intelligence for Gastrointestinal Endoscopy and Medical Imaging
by Min Ji Kim, Sang Hoon Kim, Suk Min Kim, Ji Hyung Nam, Young Bae Hwang and Yun Jeong Lim
Diagnostics 2023, 13(19), 3023; https://doi.org/10.3390/diagnostics13193023 - 22 Sep 2023
Cited by 4 | Viewed by 1862
Abstract
Artificial intelligence (AI) is a subfield of computer science that aims to implement computer systems that perform tasks that generally require human learning, reasoning, and perceptual abilities. AI is widely used in the medical field. The interpretation of medical images requires considerable effort, [...] Read more.
Artificial intelligence (AI) is a subfield of computer science that aims to implement computer systems that perform tasks that generally require human learning, reasoning, and perceptual abilities. AI is widely used in the medical field. The interpretation of medical images requires considerable effort, time, and skill. AI-aided interpretations, such as automated abnormal lesion detection and image classification, are promising areas of AI. However, when images with different characteristics are extracted, depending on the manufacturer and imaging environment, a so-called domain shift problem occurs in which the developed AI has a poor versatility. Domain adaptation is used to address this problem. Domain adaptation is a tool that generates a newly converted image which is suitable for other domains. It has also shown promise in reducing the differences in appearance among the images collected from different devices. Domain adaptation is expected to improve the reading accuracy of AI for heterogeneous image distributions in gastrointestinal (GI) endoscopy and medical image analyses. In this paper, we review the history and basic characteristics of domain shift and domain adaptation. We also address their use in gastrointestinal endoscopy and the medical field more generally through published examples, perspectives, and future directions. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Treatment of Hepatogastroenterology)
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