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Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders
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Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Clinical Medicine, Cell, and Organism Physiology".

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 14802

Special Issue Editor

Dr. Chang Seok Bang

E-Mail Website
Guest Editor
Hallym Universtiy College of Medicine, Chuncheon, Korea
Interests: gastroenterology; Helicobacter pylori; gastric cancer; colon cancer; endoscopy; deep learning; machine learning; meta-analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Current clinical practice is moving towards precision medicine. Advances in understanding the pathophysiology of various gastrointestinal disorders have made it possible to identify the meaning of clinical features and develop accurate diagnostic methods or targeted therapies. The representative features of precision medicine are artificial intelligence technologies, including deep learning or machine learning. Artificial intelligence is rapidly being applied to medical practice in the context of the automatic identification, classification, and prediction of important features of gastrointestinal disorders, and it is expected to affect our clinical practice. Combining big data analysis with artificial intelligence has the potential to increase accuracy because analyzing large amounts of data can uncover unexpected associations or new trends. The purpose of this Special Issue is to highlight recent advances in the context of diagnosis or treatment for various gastrointestinal disorders.

Dr. Chang Seok Bang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • gastroenterology
  • diagnosis
  • treatment
  • precision medicine
  • deep learning
  • big data analysis

Published Papers (5 papers)

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Research

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12 pages, 1076 KiB  
Article
Semi-Supervised Segmentation Framework for Gastrointestinal Lesion Diagnosis in Endoscopic Images
by Zenebe Markos Lonseko, Wenju Du, Prince Ebenezer Adjei, Chengsi Luo, Dingcan Hu, Tao Gan, Linlin Zhu and Nini Rao
J. Pers. Med. 2023, 13(1), 118; https://doi.org/10.3390/jpm13010118 - 05 Jan 2023
Cited by 2 | Viewed by 1323
Abstract
Background: Accurate gastrointestinal (GI) lesion segmentation is crucial in diagnosing digestive tract diseases. An automatic lesion segmentation in endoscopic images is vital to relieving physicians’ burden and improving the survival rate of patients. However, pixel-wise annotations are highly intensive, especially in clinical settings, [...] Read more.
Background: Accurate gastrointestinal (GI) lesion segmentation is crucial in diagnosing digestive tract diseases. An automatic lesion segmentation in endoscopic images is vital to relieving physicians’ burden and improving the survival rate of patients. However, pixel-wise annotations are highly intensive, especially in clinical settings, while numerous unlabeled image datasets could be available, although the significant results of deep learning approaches in several tasks heavily depend on large labeled datasets. Limited labeled data also hinder trained models’ generalizability under fully supervised learning for computer-aided diagnosis (CAD) systems. Methods: This work proposes a generative adversarial learning-based semi-supervised segmentation framework for GI lesion diagnosis in endoscopic images to tackle the challenge of limited annotations. The proposed approach leverages limited annotated and large unlabeled datasets in the training networks. We extensively tested the proposed method on 4880 endoscopic images. Results: Compared with current related works, the proposed method validates better results (Dice similarity coefficient = 89.42 ± 3.92, Intersection over union = 80.04 ± 5.75, Precision = 91.72 ± 4.05, Recall = 90.11 ± 5.64, and Hausdorff distance = 23.28 ± 14.36) on the challenging multi-sited datasets, confirming the effectiveness of the proposed framework. Conclusion: We explore a semi-supervised lesion segmentation method to employ the full use of multiple unlabeled endoscopic images to improve lesion segmentation accuracy. Experimental results confirmed the potential of our method and outperformed promising results compared with the current related works. The proposed CAD system can minimize diagnostic errors. Full article
(This article belongs to the Special Issue Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders)
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8 pages, 4209 KiB  
Article
Efficacy of Twice a Day Bismuth Quadruple Therapy for Second-Line Treatment of Helicobacter pylori Infection
by Jeemyoung Kim, Eun Jeong Gong, Myeongsook Seo, Hyun Il Seo, Jong Kyu Park, Sang Jin Lee, Koon Hee Han, Woo Jin Jeong, Young Don Kim and Gab Jin Cheon
J. Pers. Med. 2022, 12(1), 56; https://doi.org/10.3390/jpm12010056 - 06 Jan 2022
Cited by 6 | Viewed by 1591
Abstract
Bismuth quadruple therapy (BQT) is an effective treatment for Helicobacter pylori infection. However, frequent dosing schedules of BQT regimen often compromise drug adherence and may affect treatment outcomes. This retrospective study aimed to investigate the efficacy of twice-daily BQT compared to that of [...] Read more.
Bismuth quadruple therapy (BQT) is an effective treatment for Helicobacter pylori infection. However, frequent dosing schedules of BQT regimen often compromise drug adherence and may affect treatment outcomes. This retrospective study aimed to investigate the efficacy of twice-daily BQT compared to that of four times a day therapy. From August 2018 to November 2020, adult patients who failed first-line standard triple therapy and underwent BQT were eligible. Patients were categorized into two groups according to dosing schedule: (i) the BQT group (n = 213) who received standard BQT administered four times a day; and (ii) the BQTb group (n = 141) who received proton pump inhibitor, bismuth 600 mg, metronidazole 500 mg, and tetracycline 1 g twice a day. The eradication rate did not differ between the BQT (92.5%) and the BQTb groups (90.1%) (p = 0.441). Adherence and adverse event rate were similar between the two groups. Multivariate analysis showed that current smoking was associated with eradication failure; however, dosing frequency was not associated with the efficacy of eradication therapy. This study suggested that twice a day BQT is as effective as four times a day therapy for second-line treatment of H. pylori infection. Full article
(This article belongs to the Special Issue Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders)
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Review

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12 pages, 1441 KiB  
Review
When to Perform a Colonoscopy in Diverticular Disease and Why: A Personalized Approach
by Antonio Tursi, Valerio Papa, Loris Riccardo Lopetuso, Lorenzo Maria Vetrone, Antonio Gasbarrini and Alfredo Papa
J. Pers. Med. 2022, 12(10), 1713; https://doi.org/10.3390/jpm12101713 - 14 Oct 2022
Viewed by 6618
Abstract
Colonoscopy is a crucial diagnostic tool in managing diverticular disease (DD). Diverticulosis can often be an unexpected diagnosis when colonoscopy is performed in asymptomatic subjects, generally for colorectal cancer screening, or it could reveal an endoscopic picture compatible with DD, including acute diverticulitis, [...] Read more.
Colonoscopy is a crucial diagnostic tool in managing diverticular disease (DD). Diverticulosis can often be an unexpected diagnosis when colonoscopy is performed in asymptomatic subjects, generally for colorectal cancer screening, or it could reveal an endoscopic picture compatible with DD, including acute diverticulitis, in patients suffering from abdominal pain or rectal bleeding. However, alongside its role in the differential diagnosis of colonic diseases, particularly with colon cancer after an episode of acute diverticulitis or segmental colitis associated with diverticulosis, the most promising use of colonoscopy in patients with DD is represented by its prognostic role when the DICA (Diverticular Inflammation and Complication Assessment) classification is applied. Finally, colonoscopy plays a crucial role in managing diverticular bleeding, and it could sometimes be used to resolve other complications, particularly as a bridge to surgery. This article aims to summarize “when” to safely perform a colonoscopy in the different DD settings and “why”. Full article
(This article belongs to the Special Issue Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders)
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19 pages, 716 KiB  
Review
Pepsin and the Lung—Exploring the Relationship between Micro-Aspiration and Respiratory Manifestations of Gastroesophageal Reflux Disease
by Diana-Elena Iov, Oana-Bogdana Bărboi, Mariana Floria, Andrei Neamțu, Radu Iliescu and Vasile-Liviu Drug
J. Pers. Med. 2022, 12(8), 1296; https://doi.org/10.3390/jpm12081296 - 07 Aug 2022
Cited by 6 | Viewed by 2359
Abstract
Gastroesophageal reflux disease (GERD) is one of the most commonly encountered disorders in clinical practice nowadays, with an increasing burden on healthcare systems worldwide. GERD-related respiratory symptoms such as unexplained chronic cough, bronchial asthma or chronic obstructive pulmonary disease (COPD) with frequent exacerbations [...] Read more.
Gastroesophageal reflux disease (GERD) is one of the most commonly encountered disorders in clinical practice nowadays, with an increasing burden on healthcare systems worldwide. GERD-related respiratory symptoms such as unexplained chronic cough, bronchial asthma or chronic obstructive pulmonary disease (COPD) with frequent exacerbations often pose diagnostic and therapeutic challenges and may require a multidisciplinary approach. Moreover, a potential role of GERD as a risk factor has been proposed for chronic rejection in patients who underwent lung transplantation. Pepsin has gained considerable attention from the scientific community in the last few years as a possible surrogate biomarker for GERD. The aim of this narrative review was to provide an overview of the potential utility of pepsin detection as a marker of micro-aspiration in various biological fluids retrieved from patients with suspected GERD-induced respiratory manifestations and in lung transplant patients with allograft dysfunction. Data on the subject remains highly contradictory, and while certain studies support its applicability in investigating atypical GERD manifestations, at the moment, it would be realistic to accept a modest utility at best. A major lack of consensus persists regarding topics such as the optimal timeframe for fluid collection and cut-off values. Further research is warranted in order to address these issues. Full article
(This article belongs to the Special Issue Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders)
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16 pages, 2804 KiB  
Review
Computer-Aided Diagnosis of Gastrointestinal Protruded Lesions Using Wireless Capsule Endoscopy: A Systematic Review and Diagnostic Test Accuracy Meta-Analysis
by Hye Jin Kim, Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee, Ki Tae Suk and Gwang Ho Baik
J. Pers. Med. 2022, 12(4), 644; https://doi.org/10.3390/jpm12040644 - 17 Apr 2022
Cited by 8 | Viewed by 2131
Abstract
Background: Wireless capsule endoscopy allows the identification of small intestinal protruded lesions, such as polyps, tumors, or venous structures. However, reading wireless capsule endoscopy images or movies is time-consuming, and minute lesions are easy to miss. Computer-aided diagnosis (CAD) has been applied to [...] Read more.
Background: Wireless capsule endoscopy allows the identification of small intestinal protruded lesions, such as polyps, tumors, or venous structures. However, reading wireless capsule endoscopy images or movies is time-consuming, and minute lesions are easy to miss. Computer-aided diagnosis (CAD) has been applied to improve the efficacy of the reading process of wireless capsule endoscopy images or movies. However, there are no studies that systematically determine the performance of CAD models in diagnosing gastrointestinal protruded lesions. Objective: The aim of this study was to evaluate the diagnostic performance of CAD models for gastrointestinal protruded lesions using wireless capsule endoscopic images. Methods: Core databases were searched for studies based on CAD models for the diagnosis of gastrointestinal protruded lesions using wireless capsule endoscopy, and data on diagnostic performance were presented. A systematic review and diagnostic test accuracy meta-analysis were performed. Results: Twelve studies were included. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of protruded lesions were 0.95 (95% confidence interval, 0.93–0.97), 0.89 (0.84–0.92), 0.91 (0.86–0.94), and 74 (43–126), respectively. Subgroup analyses showed robust results. Meta-regression found no source of heterogeneity. Publication bias was not detected. Conclusion: CAD models showed high performance for the optical diagnosis of gastrointestinal protruded lesions based on wireless capsule endoscopy. Full article
(This article belongs to the Special Issue Recent Advancement in the Diagnosis and Management of Gastrointestinal Disorders)
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