Hepatobiliary&Pancreatic Diseases International

Copyright 2024,Hepatobiliary&Pancreatic Diseases International.All rights reserved.www.hbpdint.com.Aims and Scope.Hepatobiliary&Pancreatic Diseases International publishes peerreviewed original papers,reviews(meta-analysis,systematic review)and editorials concerned with clinical practice and research in the fields of hepatobiliary and pancreatic diseases.

Early diagnosis of pancreatic cancer: Shedding light on an unresolved challenge

Diagnosing early-stage pancreatic cancer(PC)remains a clinical challenge.Hence,studying novel imaging aspects that could enhance the diagnostic accuracy of malignant pancreatic precursor lesions is imperative.This article aims to un-derscore the promising role of emerging imaging aspects that may facilitate the earlier diagnosis of PC,thereby improving its management and prognosis.

Detachable string magnetically controlled capsule endoscopy for the noninvasive diagnosis of esophageal diseases:A prospective,blind clinical study

BACKGROUND Traditional esophagogastroduodenoscopy(EGD),an invasive examination method,can cause discomfort and pain in patients.In contrast,magnetically controlled capsule endoscopy(MCE),a noninvasive method,is being applied for the detection of stomach and small intestinal diseases,but its application in treating esophageal diseases is not widespread.AIM To evaluate the safety and efficacy of detachable string MCE(ds-MCE)for the diagnosis of esophageal diseases.METHODS Fifty patients who had been diagnosed with esophageal diseases were pros-pectively recruited for this clinical study and underwent ds-MCE and conven-tional EGD.The primary endpoints included the sensitivity,specificity,positive predictive value,negative predictive value,and diagnostic accuracy of ds-MCE for patients with esophageal diseases.The secondary endpoints consisted of visualizing the esophageal and dentate lines,as well as the subjects'tolerance of the procedure.RESULTS Using EGD as the gold standard,the sensitivity,specificity,positive predictive value,negative predictive value,and diagnostic accuracy of ds-MCE for esophageal disease detection were 85.71%,86.21%,81.82%,89.29%,and 86%,respectively.ds-MCE was more comfortable and convenient than EGD was,with 80%of patients feeling that ds-MCE examination was very comfortable or comfortable and 50%of patients believing that detachable string v examination was very convenient.CONCLUSION This study revealed that ds-MCE has the same diagnostic effects as traditional EGD for esophageal diseases and is more comfortable and convenient than EGD,providing a novel noninvasive method for treating esophageal diseases.

Association of age at diagnosis of diabetes with subsequent risk of age-related ocular diseases and vision acuity

BACKGROUND The importance of age on the development of ocular conditions has been reported by numerous studies.Diabetes may have different associations with different stages of ocular conditions,and the duration of diabetes may affect the development of diabetic eye disease.While there is a dose-response relationship between the age at diagnosis of diabetes and the risk of cardiovascular disease and mortality,whether the age at diagnosis of diabetes is associated with incident ocular conditions remains to be explored.It is unclear which types of diabetes are more predictive of ocular conditions.AIM To examine associations between the age of diabetes diagnosis and the incidence of cataract,glaucoma,age-related macular degeneration(AMD),and vision acuity.METHODS Our analysis was using the UK Biobank.The cohort included 8709 diabetic participants and 17418 controls for ocular condition analysis,and 6689 diabetic participants and 13378 controls for vision analysis.Ocular diseases were identified using inpatient records until January 2021.Vision acuity was assessed using a chart.RESULTS During a median follow-up of 11.0 years,3874,665,and 616 new cases of cataract,glaucoma,and AMD,respectively,were identified.A stronger association between diabetes and incident ocular conditions was observed where diabetes was diagnosed at a younger age.Individuals with type 2 diabetes(T2D)diagnosed at<45 years[HR(95%CI):2.71(1.49-4.93)],45-49 years[2.57(1.17-5.65)],50-54 years[1.85(1.13-3.04)],or 50-59 years of age[1.53(1.00-2.34)]had a higher risk of AMD independent of glycated haemoglobin.T2D diagnosed<45 years[HR(95%CI):2.18(1.71-2.79)],45-49 years[1.54(1.19-2.01)],50-54 years[1.60(1.31-1.96)],or 55-59 years of age[1.21(1.02-1.43)]was associated with an increased cataract risk.T2D diagnosed<45 years of age only was associated with an increased risk of glaucoma[HR(95%CI):1.76(1.00-3.12)].HRs(95%CIs)for AMD,cataract,and glaucoma associated with type 1 diabetes(T1D)were 4.12(1.99-8.53),2.95(2.17-4.02),and 2.40(1.09-5.31),respectively.In multivariable-adjusted analysis,individuals with T2D diagnosed<45 years of age[β95%CI:0.025(0.009,0.040)]had a larger increase in LogMAR.Theβ(95%CI)for LogMAR associated with T1D was 0.044(0.014,0.073).CONCLUSION The younger age at the diagnosis of diabetes is associated with a larger relative risk of incident ocular diseases and greater vision loss.

Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease

This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Clinical Cases.AI has enormous potentialfor various applications in the field of Kawasaki disease(KD).One is machinelearning(ML)to assist in the diagnosis of KD,and clinical prediction models havebeen constructed worldwide using ML;the second is using a gene signalcalculation toolbox to identify KD,which can be used to monitor key clinicalfeatures and laboratory parameters of disease severity;and the third is using deeplearning(DL)to assist in cardiac ultrasound detection.The performance of the DLalgorithm is similar to that of experienced cardiac experts in detecting coronaryartery lesions to promoting the diagnosis of KD.To effectively utilize AI in thediagnosis and treatment process of KD,it is crucial to improve the accuracy of AIdecision-making using more medical data,while addressing issues related topatient personal information protection and AI decision-making responsibility.AIprogress is expected to provide patients with accurate and effective medicalservices that will positively impact the diagnosis and treatment of KD in thefuture.

Delayed diagnosis in inflammatory bowel disease:Time to consider solutions

In this editorial,we discuss a recently published manuscript by Blüthner et al in the World Journal of Gastroenterology,with a specific focus on the delayed diagnosis of inflammatory bowel disease(IBD).IBD,which includes Crohn's disease and ulcerative colitis,is a chronic intestinal disorder.A time lag may exist between the onset of inflammation and the appearance of signs and symptoms,potentially leading to an incorrect or delayed diagnosis,a situation referred to as the delayed diagnosis of IBD.Early diagnosis is crucial for effective patient treatment and prognosis,yet delayed diagnosis remains common.The reasons for delayed diagnosis of IBD are numerous and not yet fully understood.One key factor is the nonspecific nature of IBD symptoms,which can easily be mistaken for other conditions.Additionally,the lack of specific diagnostic methods for IBD contributes to these delays.Delayed diagnosis of IBD can result in numerous adverse consequences,including increased intestinal damage,fibrosis,a higher risk of colorectal cancer,and a decrease in the quality of life of the patient.Therefore,it is essential to diagnose IBD promptly by raising physician awareness,enhancing patient education,and developing new diagnostic methods.

Physician-dependent diagnosis delay in Crohn's disease:A pseudoproposition or not?

The challenge of diagnosis delay in inflammatory bowel disease(IBD)has emerged as a significant concern for both patients and healthcare professionals.The widely accepted notion that there is an extended time frame from the onset of symptoms to the definitive diagnosis is often attributed to the heterogeneity of IBD and the non-specificity of clinical manifestations.Specific to patients with Crohn’s disease,the issue of delayed diagnosis appears to be more pronounced across different regions globally.The intricate interplay of real-world factors has led to debates regarding the primary contributors to these diagnostic delays.Drawing a comparison solely between patients and physicians and implicating the latter as the predominant influence factor may fall into a simplistic either-or logical trap that may obscure the truth.This letter,grounded in published evidence,explores areas for improvement in a forthcoming paper within the field,hoping to pinpoint the culprit behind the diagnosis delay issue for IBD patients rather than simply attributing it to so-called“physician-dependent factors”.Our objective is to motivate healthcare providers and policymakers in relevant fields to reflect on strategies for addressing this problem to reduce diagnostic delays and enhance patient outcomes.

Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

BACKGROUND Crohn’s disease(CD)is often misdiagnosed as intestinal tuberculosis(ITB).However,the treatment and prognosis of these two diseases are dramatically different.Therefore,it is important to develop a method to identify CD and ITB with high accuracy,specificity,and speed.AIM To develop a method to identify CD and ITB with high accuracy,specificity,and speed.METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB.Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm^(-1) and 1234 cm^(-1) bands,and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy,specificity,and sensitivity of 91.84%,92.59%,and 90.90%,respectively,for the differential diagnosis of CD and ITB.CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level,and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

Soluble ST2:A Novel Biomarker for Diagnosis and Prognosis of Cardiovascular Disease

The increasing incidence of cardiovascular disease(CVD)is a significant global health concern,affecting millions of individuals each year.Accurate diagnosis of acute CVD poses a formidable challenge,as misdiagnosis can significantly decrease patient survival rates.Traditional biomarkers have played a vital role in the diagnosis and prognosis of CVDs,but they can be influenced by various factors,such as age,sex,and renal function.Soluble ST2(sST2)is a novel biomarker that is closely associated with different CVDs.Its low reference change value makes it suitable for continuous measurement,unaffected by age,kidney function,and other confounding factors,facilitating risk stratification of CVDs.Furthermore,the combination of sST2 with other biomarkers can enhance diagnostic accuracy and prognostic value.This review aims to provide a comprehensive overview of sST2,focusing on its diagnostic and prognostic value as a myocardial marker for different types of CVDs and discussing the current limitations of sST2.

Type one autoimmune pancreatitis based on clinical diagnosis: A case report

BACKGROUND Autoimmune pancreatitis(AIP)is a rare form of autoimmune-mediated pancrea-titis,which is easily misdiagnosed as pancreatic cancer and thus treated surgi-cally.We studied the diagnosis and treatment of a patient with type 1 AIP recent-ly admitted to our hospital,and reviewed the literature to provide a reference for clinical diagnosis of AIP.CASE SUMMARY The chief complaint was yellowing of the body,eyes and urine for 21 d.The pa-tient's clinical presentation was obstructive jaundice and imaging suggested pan-creatic swelling.It was difficult to distinguish between inflammation and tumor.Serum immunoglobulin G4(IgG4)was markedly elevated.IgG4 is an important serological marker for type 1 AIP.The patient was diagnosed with AIP,IgG4-related cholangitis,acute cholecystitis and hepatic impairment.After applying hormonal therapy,the patient's symptoms improved significantly.At the same time,imaging suggested that pancreatic swelling subsided,and liver function and other biochemical indicators decreased.The treatment was effective.CONCLUSION In patients with pancreatic swelling,the possibility of AIP should be considered.

Mean nocturnal baseline impedance in gastro-esophageal reflux disease diagnosis:Should we strictly follow the Lyon 2 Consensus?

Clinical practice guidelines drive clinical practice and clinicians rely to them when trying to answer their most common questions.One of the most important position papers in the field of gastro-esophageal reflux disease(GERD)is the one produced by the Lyon Consensus.Recently an updated second version has been released.Mean nocturnal baseline impedance(MNBI)was proposed by the first Consensus to act as supportive evidence for GERD diagnosis.Originally a cut-off of 2292 Ohms was proposed,a value revised in the second edition.The updated Consensus recommended that an MNBI<1500 Ohms strongly suggests GERD while a value>2500 Ohms can be used to refute GERD.The proposed cut-offs move in the correct direction by diminishing the original cut-off,nevertheless they arise from a study of normal subjects where cut-offs were provided by measuring the mean value±2SD and not in symptomatic patients.However,data exist that even symptomatic patients with inconclusive disease or reflux hypersensitivity(RH)show lower MNBI values in comparison to normal subjects or patients with functional heartburn(FH).Moreover,according to the data,MNBI,even among symptomatic patients,is affected by age and body mass index.Also,various studies have proposed different cut-offs by using receiver operating characteristic curve analysis even lower than the one proposed.Finally,no information is given for patients submitted to on-proton pump inhibitors pH-impedance studies even if new and extremely important data now exist.Therefore,even if MNBI is an extremely important tool when trying to approach patients with reflux symptoms and could distinguish conclusive GERD from RH or FH,its values should be interpreted with caution.

Association of autoimmune thyroid disease with type 1 diabetes mellitus and its ultrasonic diagnosis and management

As a common hyperglycemic disease,type 1 diabetes mellitus(T1DM)is a complicated disorder that requires a lifelong insulin supply due to the immunemediated destruction of pancreaticβcells.Although it is an organ-specific autoimmune disorder,T1DM is often associated with multiple other autoimmune disorders.The most prevalent concomitant autoimmune disorder occurring in T1DM is autoimmune thyroid disease(AITD),which mainly exhibits two extremes of phenotypes:hyperthyroidism[Graves'disease(GD)]and hypothyroidism[Hashimoto's thyroiditis,(HT)].However,the presence of comorbid AITD may negatively affect metabolic management in T1DM patients and thereby may increase the risk for potential diabetes-related complications.Thus,routine screening of thyroid function has been recommended when T1DM is diagnosed.Here,first,we summarize current knowledge regarding the etiology and pathogenesis mechanisms of both diseases.Subsequently,an updated review of the association between T1DM and AITD is offered.Finally,we provide a relatively detailed review focusing on the application of thyroid ultrasonography in diagnosing and managing HT and GD,suggesting its critical role in the timely and accurate diagnosis of AITD in T1DM.

Light-Activated Virtual Sensor Array with Machine Learning for Non-Invasive Diagnosis of Coronary Heart Disease

Early non-invasive diagnosis of coronary heart disease(CHD)is critical.However,it is challenging to achieve accurate CHD diagnosis via detecting breath.In this work,heterostructured complexes of black phosphorus(BP)and two-dimensional carbide and nitride(MXene)with high gas sensitivity and photo responsiveness were formulated using a self-assembly strategy.A light-activated virtual sensor array(LAVSA)based on BP/Ti_(3)C_(2)Tx was prepared under photomodulation and further assembled into an instant gas sensing platform(IGSP).In addition,a machine learning(ML)algorithm was introduced to help the IGSP detect and recognize the signals of breath samples to diagnose CHD.Due to the synergistic effect of BP and Ti_(3)C_(2)Tx as well as photo excitation,the synthesized heterostructured complexes exhibited higher performance than pristine Ti_(3)C_(2)Tx,with a response value 26%higher than that of pristine Ti_(3)C_(2)Tx.In addition,with the help of a pattern recognition algorithm,LAVSA successfully detected and identified 15 odor molecules affiliated with alcohols,ketones,aldehydes,esters,and acids.Meanwhile,with the assistance of ML,the IGSP achieved 69.2%accuracy in detecting the breath odor of 45 volunteers from healthy people and CHD patients.In conclusion,an immediate,low-cost,and accurate prototype was designed and fabricated for the noninvasive diagnosis of CHD,which provided a generalized solution for diagnosing other diseases and other more complex application scenarios.

Intestinal Behçet's disease: A review of clinical diagnosis and treatment

Behçet's disease(BD)is a chronic inflammatory disorder prone to frequent re-currences,with a high predilection for intestinal involvement.However,the ef-ficacy and long-term effects of surgical treatment for intestinal BD are unknown.In the current issue of World J Gastrointest Surg,Park et al conducted a retrospec-tive analysis of 31 patients with intestinal BD who received surgical treatment.They found that elevated C-reactive protein levels and emergency surgery were poor prognostic factors for postoperative recurrence,emphasizing the adverse impact of severe inflammation on the prognosis of patients with intestinal BD.This work has clinical significance for evaluating the postoperative condition of intestinal BD.The editorial attempts to summarize the clinical diagnosis and treatment of intestinal BD,focusing on the impact of adverse factors on surgical outcomes.We hope this review will facilitate more precise postoperative management of patients with intestinal BD by clinicians.

Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis

Pancreatic cancer(PC)has a low incidence rate but a high mortality,with patients often in the advanced stage of the disease at the time of the first diagnosis.If detected,early neoplastic lesions are ideal for surgery,offering the best prognosis.Preneoplastic lesions of the pancreas include pancreatic intraepithelial neoplasia and mucinous cystic neoplasms,with intraductal papillary mucinous neoplasms being the most commonly diagnosed.Our study focused on predicting PC by identifying early signs using noninvasive techniques and artificial intelligence(AI).A systematic English literature search was conducted on the PubMed electronic database and other sources.We obtained a total of 97 studies on the subject of pancreatic neoplasms.The final number of articles included in our study was 44,34 of which focused on the use of AI algorithms in the early diagnosis and prediction of pancreatic lesions.AI algorithms can facilitate diagnosis by analyzing massive amounts of data in a short period of time.Correlations can be made through AI algorithms by expanding image and electronic medical records databases,which can later be used as part of a screening program for the general population.AI-based screening models should involve a combination of biomarkers and medical and imaging data from different sources.This requires large numbers of resources,collaboration between medical practitioners,and investment in medical infrastructures.

Vibrational spectroscopy-are we close to finding a solution for early pancreatic cancer diagnosis?

Pancreatic cancer(PC)is an aggressive and lethal neoplasm,ranking seventh in the world for cancer deaths,with an overall 5-year survival rate of below 10%.The knowledge about PC pathogenesis is rapidly expanding.New aspects of tumor biology,including its molecular and morphological heterogeneity,have been reported to explain the complicated“cross-talk”that occurs between the cancer cells and the tumor stroma or the nature of pancreatic ductal adenocarcinoma-associated neural remodeling.Nevertheless,currently,there are no specific and sensitive diagnosis options for PC.Vibrational spectroscopy(VS)shows a promising role in the development of early diagnosis technology.In this review,we summarize recent reports about improvements in spectroscopic methodologies,briefly explain and highlight the drawbacks of each of them,and discuss available solutions.The important aspects of spectroscopic data evaluation with multivariate analysis and a convolutional neural network methodology are depicted.We conclude by presenting a study design for systemic verification of the VS-based methods in the diagnosis of PC.

Pancreatic cancer,autoimmune or chronic pancreatitis,beyond tissue diagnosis:Collateral imaging and clinical characteristics may differentiate them

Pancreatic ductal adenocarcinoma(PDAC)is one of the most lethal malignancies and is developing into the 2nd leading cause of cancer-related death.Often,the clinical and radiological presentation of PDAC may be mirrored by other inflammatory pancreatic masses,such as autoimmune pancreatitis(AIP)and massforming chronic pancreatitis(MFCP),making its diagnosis challenging.Differentiating AIP and MFCP from PDAC is vital due to significant therapeutic and prognostic implications.Current diagnostic criteria and tools allow the precise differentiation of benign from malignant masses;however,the diagnostic accuracy is imperfect.Major pancreatic resections have been performed in AIP cases under initial suspicion of PDAC after a diagnostic approach failed to provide an accurate diagnosis.It is not unusual that after a thorough diagnostic evaluation,the clinician is confronted with a pancreatic mass with uncertain diagnosis.In those cases,a re-evaluation must be entertained,preferably by an experienced multispecialty team including radiologists,pathologists,gastroenterologists,and surgeons,looking for disease-specific clinical,imaging,and histological hallmarks or collateral evidence that could favor a specific diagnosis.Our aim is to describe current diagnostic limitations that hinder our ability to reach an accurate diagnosis among AIP,PDAC,and MFCP and to highlight those disease-specific clinical,radiological,serological,and histological characteristics that could support the presence of any of these three disorders when facing a pancreatic mass with uncertain diagnosis after an initial diagnostic approach has been unsuccessful.

Hybrid Deep Learning Method for Diagnosis of Cucurbita Leaf Diseases

In agricultural engineering,the main challenge is on methodologies used for disease detection.The manual methods depend on the experience of the personal.Due to large variation in environmental condition,disease diagnosis and classification becomes a challenging task.Apart from the disease,the leaves are affected by climate changes which is hard for the image processing method to discriminate the disease from the other background.In Cucurbita gourd family,the disease severity examination of leaf samples through computer vision,and deep learning methodologies have gained popularity in recent years.In this paper,a hybrid method based on Convolutional Neural Network(CNN)is proposed for automatic pumpkin leaf image classification.The Proposed Denoising and deep Convolutional Neural Network(CNN)method enhances the Pumpkin Leaf Pre-processing and diagnosis.Real time data base was used for training and testing of the proposed work.Investigation on existing pre-trained network Alexnet and googlenet was investigated is done to evaluate the performance of the pro-posed method.The system and computer simulations were performed using Matlab tool.

Role of artificial intelligence in the characterization of indeterminate pancreatic head mass and its usefulness in preoperative diagnosis

Artificial intelligence(AI)has been used in various fields of day-to-day life and its role in medicine is immense.Understanding of oncology has been improved with the introduction of AI which helps in diagnosis,treatment planning,management,prognosis,and follow-up.It also helps to identify high-risk groups who can be subjected to timely screening for early detection of malignant conditions.It is more important in pancreatic cancer as it is one of the major causes of cancer-related deaths worldwide and there are no specific early features(clinical and radiological)for diagnosis.With improvement in imaging modalities(computed tomography,magnetic resonance imaging,endoscopic ultrasound),most often clinicians were being challenged with lesions that were difficult to diagnose with human competence.AI has been used in various other branches of medicine to differentiate such indeterminate lesions including the thyroid gland,breast,lungs,liver,adrenal gland,kidney,etc.In the case of pancreatic cancer,the role of AI has been explored and is still ongoing.This review article will focus on how AI can be used to diagnose pancreatic cancer early or differentiate it from benign pancreatic lesions,therefore,management can be planned at an earlier stage.

Diagnosis and management of pancreatic neuroendocrine tumor in von Hippel-Lindau disease

The pancreatic manifestations seen in patients with von Hippel-Lindau(VHL) disease are subdivided into 2 categories:pancreatic neuroendocrine tumors(NET),and cystic lesions,including simple cyst and serous cystadenoma.The VHL-associated cystic lesions are generally asymptomatic and do not require any treatment,unless they are indistinguishable from other cystic tumor types with malignant potential.Because pancreatic NET in VHL disease are non-functioning and have malignant potential,it is of clinical importance to find and diagnose these as early as possible.It will be recommended that comprehensive surveillance using dynamic computed tomography for abdominal manifestations,including pancreatic NET,should start from the age of 15 years in VHL patients.Unlike sporadic non-functioning NET without VHL disease,in which surgical resection is generally recommended,VHL patients at lower metastatic risk of pancreatic NET should be spared the risks of operative resection.