Diagnostics

Research

11 pages, 1543 KiB

Open AccessArticle

Eosinophilic Esophagitis: Cytokines Expression and Fibrotic Markers in Comparison to Celiac Disease

by Annamaria Pronio, Francesco Covotta, Lucia Pallotta, Rossella Palma, Danilo Badiali, Maria Carlotta Sacchi, Antonietta Lamazza and Carola Severi

Diagnostics 2022, 12(9), 2092; https://doi.org/10.3390/diagnostics12092092 - 29 Aug 2022

Cited by 3 | Viewed by 1347

Abstract

Introduction: Eosinophilic esophagitis (EoE) is now recognized as the main inflammatory condition that leads to fibrosis, unlike other chronic inflammatory gastrointestinal diseases, such as celiac disease. The aim of our study is to characterize the collagen deposition and cytokine expression involved in the [...] Read more.

Introduction: Eosinophilic esophagitis (EoE) is now recognized as the main inflammatory condition that leads to fibrosis, unlike other chronic inflammatory gastrointestinal diseases, such as celiac disease. The aim of our study is to characterize the collagen deposition and cytokine expression involved in the fibrogenic response in patients affected by EoE in comparison to celiac disease. Materials and Methods: Consecutive patients with a clinical suspicion of untreated EoE or active celiac disease were enrolled. In the control group, patients with negative upper endoscopy were included. Total RNA was isolated from biopsy specimens using a commercial kit (SV Total RNA Isolation System, Promega Italia Srl). Quantitative real-time PCR (qRT-PCR) was performed in triplicate using a StepOne™ Real-Time PCR instrument (Thermo Fisher Scientific, Monza, Italy). mRNA encoding for inflammatory molecules: interleukin 4 (IL-4), interleukin 5 (IL-5), interleukin 13 (IL-13), and fibrotic markers: transforming growth factor beta 1 (TGF-β), mitogen-activated protein kinase kinase kinase 7 (MAP3K7), serpin family E member 1 (SERPINE1), were quantified using TaqMan Gene Expression Assays (Applied Biosystems). RESULTS. In EoE, the qPCR analysis showed an increase in all the inflammatory cytokines. Both IL-5 and Il-3 mRNA expression resulted in a statistically significant increase in oesophageal mucosa with respect to the celiac duodenum, while no differences were present in IL-4 expression. TGF-β expression was similar to the controls in the mid esophagus but reduced in the distal EoE esophagus (RQ: 0.46 ± 0.1). MAP3K7 expression was reduced in the mid esophagus (RQ: 0.59 ± 0.3) and increased in the distal esophagus (RQ: 1.75 ± 0.6). In turn, the expression of SERPINE1 was increased in both segments and was higher in the mid than in the distal esophagus (RQ: 5.25 ± 3.9, 1.92 ± 0.9, respectively). Collagen deposition was greater in the distal esophagus compared to the mid esophagus [18.1% ± 8 vs. 1.3% ± 1; p = 0.008]. Conclusions: The present study confirms the esophageal fibrotic involution involving the distal esophagus and shows that the inflammatory pathway in EoE is peculiar to this disease and different from other chronic inflammatory gastrointestinal disorders such as celiac disease. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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11 pages, 2721 KiB

Open AccessArticle

Development of a Deep Learning Model for Malignant Small Bowel Tumors Survival: A SEER-Based Study

by Minyue Yin, Jiaxi Lin, Lu Liu, Jingwen Gao, Wei Xu, Chenyan Yu, Shuting Qu, Xiaolin Liu, Lijuan Qian, Chunfang Xu and Jinzhou Zhu

Diagnostics 2022, 12(5), 1247; https://doi.org/10.3390/diagnostics12051247 - 17 May 2022

Cited by 7 | Viewed by 1998

Abstract

Background This study aims to explore a deep learning (DL) algorithm for developing a prognostic model and perform survival analyses in SBT patients. Methods The demographic and clinical features of patients with SBTs were extracted from the Surveillance, Epidemiology and End Results (SEER) [...] Read more.

Background This study aims to explore a deep learning (DL) algorithm for developing a prognostic model and perform survival analyses in SBT patients. Methods The demographic and clinical features of patients with SBTs were extracted from the Surveillance, Epidemiology and End Results (SEER) database. We randomly split the samples into the training set and the validation set at 7:3. Cox proportional hazards (Cox-PH) analysis and the DeepSurv algorithm were used to develop models. The performance of the Cox-PH and DeepSurv models was evaluated using receiver operating characteristic curves, calibration curves, C-statistics and decision-curve analysis (DCA). A Kaplan–Meier (K–M) survival analysis was performed for further explanation on prognostic effect of the Cox-PH model. Results The multivariate analysis demonstrated that seven variables were associated with cancer-specific survival (CSS) (all p < 0.05). The DeepSurv model showed better performance than the Cox-PH model (C-index: 0.871 vs. 0.866). The calibration curves and DCA revealed that the two models had good discrimination and calibration. Moreover, patients with ileac malignancy and N2 stage disease were not responding to surgery according to the K–M analysis. Conclusions This study reported a DeepSurv model that performed well in CSS in SBT patients. It might offer insights into future research to explore more DL algorithms in cohort studies. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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18 pages, 3184 KiB

Open AccessArticle

Resource Management through Artificial Intelligence in Screening Programs—Key for the Successful Elimination of Hepatitis C

by Anca Elena Butaru, Mădălin Mămuleanu, Costin Teodor Streba, Irina Paula Doica, Mihai Mircea Diculescu, Dan Ionuț Gheonea and Carmen Nicoleta Oancea

Diagnostics 2022, 12(2), 346; https://doi.org/10.3390/diagnostics12020346 - 29 Jan 2022

Cited by 5 | Viewed by 2120

Abstract

Background: The elimination of the Hepatitis C virus (HCV) will only be possible if rapid and efficient actions are taken. Artificial neural networks (ANNs) are computing systems based on the topology of the biological brain, containing connected artificial neurons that can be tasked [...] Read more.

Background: The elimination of the Hepatitis C virus (HCV) will only be possible if rapid and efficient actions are taken. Artificial neural networks (ANNs) are computing systems based on the topology of the biological brain, containing connected artificial neurons that can be tasked with solving medical problems. Aim: We expanded the previously presented HCV micro-elimination project started in September 2020 that aimed to identify HCV infection through coordinated screening in asymptomatic populations and developed two ANN models able to identify at-risk subjects selected through a targeted questionnaire. Material and method: Our study included 14,042 screened participants from a southwestern region of Oltenia, Romania. Each participant completed a 12-item questionnaire along with anti-HCV antibody rapid testing. Hepatitis-C-positive subjects were linked to care and ultimately could receive antiviral treatment if they had detectable viremia. We built two ANNs, trained and tested on the dataset derived from the questionnaires and then used to identify patients in a similar, already existing dataset. Results: We found 114 HCV-positive patients (81 females), resulting in an overall prevalence of 0.81%. We identified sharing personal hygiene items, receiving blood transfusions, having dental work or surgery and re-using hypodermic needles as significant risk factors. When used on an existing dataset of 15,140 persons (119 HCV cases), the first ANN models correctly identified 97 (81.51%) HCV-positive subjects through 13,401 tests, while the second ANN model identified 81 (68.06%) patients through only 5192 tests. Conclusions: The use of ANNs in selecting screening candidates may improve resource allocation and prioritize cases more prone to severe disease. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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18 pages, 22605 KiB

Open AccessArticle

Role of Contrast-Enhanced Ultrasonography in Hepatocellular Carcinoma by Using LI-RADS and Ancillary Features: A Single Tertiary Centre Experience

by Adriana Ciocalteu, Sevastita Iordache, Sergiu Marian Cazacu, Cristiana Marinela Urhut, Sarmis Marian Sandulescu, Ana-Maria Ciurea, Adrian Saftoiu and Larisa Daniela Sandulescu

Diagnostics 2021, 11(12), 2232; https://doi.org/10.3390/diagnostics11122232 - 29 Nov 2021

Cited by 6 | Viewed by 2278

Abstract

Clinical utility of ancillary features (AFs) in contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS^®) is yet to be established. In this study, we assessed the diagnostic yield of CEUS LI-RADS and AFs in hepatocellular carcinoma (HCC). We retrospectively [...] Read more.

Clinical utility of ancillary features (AFs) in contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS^®) is yet to be established. In this study, we assessed the diagnostic yield of CEUS LI-RADS and AFs in hepatocellular carcinoma (HCC). We retrospectively included patients with risk factors for HCC and newly diagnosed focal liver lesions (FLL). All lesions have been categorized according to the CEUS LI-RADS v2017 by an experienced sonographer blinded to clinical data and to the final diagnosis. From a total of 143 patients with 191 FLL, AFs favoring HCC were observed in 19.8% cases as hypoechoic rim and in 16.7% cases as nodule-in nodule architecture. From the total of 141 HCC cases, 83.6% were correctly classified: 57.4%- LR-5 and 26.2%- LR-4. In 9.21% cases, CEUS indicated LR-M; 2.12% cases- LR-3. The LR-5 category was 96.2% predictive (PPV) of HCC. LR-5 had 60.4% sensitivity and 93.6% specificity. PPV for primitive malignancy (LR-4 + LR-5) was 95.7%, with 88% sensitivity, 89.3% specificity and 88.4% accuracy for HCC. LR-4 category had 94.8% PPV and 26.2% sensitivity. CEUS LR4 + LR5 had 81,8% sensitivity for HCCs over 2 cm and 78.57% sensitivity for smaller HCCs. CEUS LR-5 remains an excellent diagnostic tool for HCC, despite the size of the lesion. The use of AFs might improve the overarching goal of LR-5 + LR-4 diagnosis of high specificity for HCC and exclusion of non-HCC malignancy. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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Review

Jump to: Research, Other

11 pages, 898 KiB

Open AccessReview

Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going?

by Radu-Alexandru Vulpoi, Mihaela Luca, Adrian Ciobanu, Andrei Olteanu, Oana-Bogdana Barboi and Vasile Liviu Drug

Diagnostics 2022, 12(4), 927; https://doi.org/10.3390/diagnostics12040927 - 08 Apr 2022

Cited by 15 | Viewed by 3281

Abstract

Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive [...] Read more.

Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive endoscopy included. The detection rate of preneoplastic lesions (i.e., polyps) during colonoscopy may be increased with artificial intelligence assistance. It has also proven useful in detecting signs of ulcerative colitis activity. In upper digestive endoscopy, deep learning models may prove to be useful in the diagnosis and management of upper digestive tract diseases, such as gastroesophageal reflux disease, Barrett’s esophagus, and gastric cancer. As is the case with all new medical devices, there are challenges in the implementation in daily medical practice. The regulatory, economic, organizational culture, and language barriers between humans and machines are a few of them. Even so, many devices have been approved for use by their respective regulators. Future studies are currently striving to develop deep learning models that can replicate a growing amount of human brain activity. In conclusion, artificial intelligence may become an indispensable tool in digestive endoscopy. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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15 pages, 2167 KiB

Open AccessReview

Diagnostic Value of Artificial Intelligence-Assisted Endoscopic Ultrasound for Pancreatic Cancer: A Systematic Review and Meta-Analysis

by Elena Adriana Dumitrescu, Bogdan Silviu Ungureanu, Irina M. Cazacu, Lucian Mihai Florescu, Liliana Streba, Vlad M. Croitoru, Daniel Sur, Adina Croitoru, Adina Turcu-Stiolica and Cristian Virgil Lungulescu

Diagnostics 2022, 12(2), 309; https://doi.org/10.3390/diagnostics12020309 - 25 Jan 2022

Cited by 21 | Viewed by 3642

Abstract

We performed a meta-analysis of published data to investigate the diagnostic value of artificial intelligence for pancreatic cancer. Systematic research was conducted in the following databases: PubMed, Embase, and Web of Science to identify relevant studies up to October 2021. We extracted or [...] Read more.

We performed a meta-analysis of published data to investigate the diagnostic value of artificial intelligence for pancreatic cancer. Systematic research was conducted in the following databases: PubMed, Embase, and Web of Science to identify relevant studies up to October 2021. We extracted or calculated the number of true positives, false positives true negatives, and false negatives from the selected publications. In total, 10 studies, featuring 1871 patients, met our inclusion criteria. The risk of bias in the included studies was assessed using the QUADAS-2 tool. R and RevMan 5.4.1 software were used for calculations and statistical analysis. The studies included in the meta-analysis did not show an overall heterogeneity (I² = 0%), and no significant differences were found from the subgroup analysis. The pooled diagnostic sensitivity and specificity were 0.92 (95% CI, 0.89–0.95) and 0.9 (95% CI, 0.83–0.94), respectively. The area under the summary receiver operating characteristics curve was 0.95, and the diagnostic odds ratio was 128.9 (95% CI, 71.2–233.8), indicating very good diagnostic accuracy for the detection of pancreatic cancer. Based on these promising preliminary results and further testing on a larger dataset, artificial intelligence-assisted endoscopic ultrasound could become an important tool for the computer-aided diagnosis of pancreatic cancer. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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Other

Jump to: Research, Review

11 pages, 1629 KiB

Open AccessProject Report

IBD Monitor: Romanian National Mobile Application for Inflammatory Bowel Disease Personalized Treatment and Monitoring

by Carmen-Nicoleta Oancea, Răzvan-Cristian Statie, Dan-Ionuț Gheonea, Tudorel Ciurea, Mircea-Sebastian Șerbănescu and Costin-Teodor Streba

Diagnostics 2022, 12(6), 1345; https://doi.org/10.3390/diagnostics12061345 - 28 May 2022

Viewed by 1819

Abstract

Background: In the last 30 years, we have seen an increase in the incidence of inflammatory bowel disease (IBD). Most cases are diagnosed in the 2nd and 3rd decades of life, a population group that is most familiar with the latest innovations in [...] Read more.

Background: In the last 30 years, we have seen an increase in the incidence of inflammatory bowel disease (IBD). Most cases are diagnosed in the 2nd and 3rd decades of life, a population group that is most familiar with the latest innovations in technology. Patients want to obtain more information about their disease and have complete control over the pathology, while reducing physical meetings with their doctor. Starting from these ideas, the present study aimed to develop a mobile application (app) to support IBD patients on symptoms/events reporting and on treatment administration monitoring. Methods: A multidisciplinary team was created to document and develop the app requirements and design its functionality. The app was beta-tested by several IBD patients. Their feedback was used to further refine the app. Results: We developed connected apps for both smartphones and smartwatches, with dedicated sections for event reporting and medication administration reminders/reporting. Conclusions: The development of apps dedicated to IBD patients is still in early progress. By creating this app, we aim to improve the evolution and compliance of IBD patients and to obtain new information that will have a beneficial impact on the management of these patients and open the door for personalized medicine. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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5 pages, 1396 KiB

Open AccessCase Report

Chronic Appendicitis—From Ambiguous Clinical Image to Inconclusive Imaging Studies

by Agnieszka Brodzisz, Maryla Kuczyńska, Monika Zbroja, Weronika Cyranka, Czesław Cielecki and Magdalena Maria Woźniak

Diagnostics 2022, 12(4), 818; https://doi.org/10.3390/diagnostics12040818 - 26 Mar 2022

Cited by 1 | Viewed by 2182

Abstract

A six-year-old boy visits a general practitioner due to diarrhea and abdominal pain with a moderate fever of up to 39 °C for 2 days. Treatment is initiated; however, the recurrence of abdominal pain is observed. Physical examination of the child at the [...] Read more.

A six-year-old boy visits a general practitioner due to diarrhea and abdominal pain with a moderate fever of up to 39 °C for 2 days. Treatment is initiated; however, the recurrence of abdominal pain is observed. Physical examination of the child at the emergency department reveals abdominal guarding and visible, palpable, painful intestinal loops in the left iliac and hypogastric regions—this is referred to as an ‘acute abdomen’. An X-ray shows single levels of air and fluid indicative of bowel obstruction. Ultrasound reveals distended, fluid-filled intestinal loops with diminished motility. The intestinal wall is swollen. Laboratory tests indicate increased inflammatory indices. Contrast-enhanced computed tomography examination of the abdominal cavity and lesser pelvis shows intestinal dilation. The loops were filled with liquid content and numerous collections of gas. The patient is qualified for a laparotomy. An intraoperative diagnosis of perforated gangrenous appendicitis with autoamputation was made. In addition, numerous interloop and pelvic abscesses, excessive adhesions, signs of small intestine micro-perforation, and diffuse peritonitis are found. The patient’s condition and laboratory parameters significantly improve during the following days of hospitalization. Despite the implementation of multidirectional, specialized diagnostics in the case of acute abdomen, in everyday practice we still encounter situations where the final diagnosis is made intraoperatively only. Full article

(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology)

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