Predictive Factors for Differentiating Between Crohn's Disease and Intestinal Tuberculosis in Koreans

A novel multidisciplinary machine learning approach based on clinical, imaging, colonoscopy, and pathology features for distinguishing intestinal tuberculosis from Crohn's disease

OBJECTIVES

Differentiating intestinal tuberculosis (ITB) from Crohn's disease (CD) remains a diagnostic dilemma. Misdiagnosis carries potential grave implications. We aim to establish a multidisciplinary-based model using machine learning approach for distinguishing ITB from CD.

METHODS

Eighty-two patients including 25 patients with ITB and 57 patients with CD were retrospectively recruited (54 in training cohort and 28 in testing cohort). The region of interest (ROI) for the lesion was delineated on magnetic resonance enterography (MRE) and colonoscopy images. Radiomic features were extracted by least absolute shrinkage and selection operator regression. Pathological feature was extracted automatically by deep-learning method. Clinical features were filtered by logistic regression analysis. Diagnostic performance was evaluated by receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Delong's test was applied to compare the efficiency between the multidisciplinary-based model and the other four single-disciplinary-based models.

RESULTS

The radiomics model based on MRE features yielded an AUC of 0.87 (95% confidence interval [CI] 0.68-0.96) on the test data set, which was similar to the clinical model (AUC, 0.90 [95% CI 0.71-0.98]) and higher than the colonoscopy radiomics model (AUC, 0.68 [95% CI 0.48-0.84]) and pathology deep-learning model (AUC, 0.70 [95% CI 0.49-0.85]). Multidisciplinary model, integrating 3 clinical, 21 MRE radiomic, 5 colonoscopy radiomic, and 4 pathology deep-learning features, could significantly improve the diagnostic performance (AUC of 0.94, 95% CI 0.78-1.00) on the bases of single-disciplinary-based models. DCA confirmed the clinical utility.

CONCLUSIONS

Multidisciplinary-based model integrating clinical, MRE, colonoscopy, and pathology features was useful in distinguishing ITB from CD.

Artificial intelligence for discrimination of Crohn's disease and gastrointestinal tuberculosis: A systematic review

BACKGROUND AND AIM

Discrimination of gastrointestinal tuberculosis (GITB) and Crohn's disease (CD) is difficult. Use of artificial intelligence (AI)-based technologies may help in discriminating these two entities.

METHODS

We conducted a systematic review on the use of AI for discrimination of GITB and CD. Electronic databases (PubMed and Embase) were searched on June 6, 2022, to identify relevant studies. We included any study reporting the use of clinical, endoscopic, and radiological information (textual or images) to discriminate GITB and CD using any AI technique. Quality of studies was assessed with MI-CLAIM checklist.

RESULTS

Out of 27 identified results, a total of 9 studies were included. All studies used retrospective databases. There were five studies of only endoscopy-based AI, one of radiology-based AI, and three of multiparameter-based AI. The AI models performed fairly well with high accuracy ranging from 69.6-100%. Text-based convolutional neural network was used in three studies and Classification and regression tree analysis used in two studies. Interestingly, irrespective of the AI method used, the performance of discriminating GITB and CD did not match in discriminating from other diseases (in studies where a third disease was also considered).

CONCLUSION

The use of AI in differentiating GITB and CD seem to have acceptable accuracy but there were no direct comparisons with traditional multiparameter models. The use of multiple parameter-based AI models have the potential for further exploration in search of an ideal tool and improve on the accuracy of traditional models.

Few-shot learning for the classification of intestinal tuberculosis and Crohn's disease on endoscopic images: A novel learn-to-learn framework

Background and aim

Standard deep learning methods have been found inadequate in distinguishing between intestinal tuberculosis (ITB) and Crohn's disease (CD), a shortcoming largely attributed to the scarcity of available samples. In light of this limitation, our objective is to develop an innovative few-shot learning (FSL) system, specifically tailored for the efficient categorization and differential diagnosis of CD and ITB, using endoscopic image data with minimal sample requirements.

Methods

A total of 122 white-light endoscopic images (99 CD images and 23 ITB images) were collected (one ileum image from each patient). A 2-way, 3-shot FSL model that integrated dual transfer learning and metric learning strategies was devised. Xception architecture was selected as the foundation and then underwent a dual transfer process utilizing oesophagitis images sourced from HyperKvasir. Subsequently, the eigenvectors derived from the Xception for each query image were converted into predictive scores, which were calculated using the Euclidean distances to six reference images from the support sets.

Results

The FSL model, which leverages dual transfer learning, exhibited enhanced performance metrics (AUC 0.81) compared to a model relying on single transfer learning (AUC 0.56) across three evaluation rounds. Additionally, its performance surpassed that of a less experienced endoscopist (AUC 0.56) and even a more seasoned specialist (AUC 0.61).

Conclusions

The FSL model we have developed demonstrates efficacy in distinguishing between CD and ITB using a limited dataset of endoscopic imagery. FSL holds value for enhancing the diagnostic capabilities of rare conditions.

Deep learning model to differentiate Crohn's disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens

Crohn's disease (CD) and intestinal tuberculosis (ITB) share similar histopathological characteristics, and differential diagnosis can be a dilemma for pathologists. This study aimed to apply deep learning (DL) to analyze whole slide images (WSI) of surgical resection specimens to distinguish CD from ITB. Overall, 1973 WSI from 85 cases from 3 centers were obtained. The DL model was established in internal training and validated in external test cohort, evaluated by area under receiver operator characteristic curve (AUC). Diagnostic results of pathologists were compared with those of the DL model using DeLong's test. DL model had case level AUC of 0.886, 0.893 and slide level AUC of 0.954, 0.827 in training and test cohorts. Attention maps highlighted discriminative areas and top 10 features were extracted from CD and ITB. DL model's diagnostic efficiency (AUC = 0.886) was better than junior pathologists (*1 AUC = 0.701, P = 0.088; *2 AUC = 0.861, P = 0.788) and inferior to senior GI pathologists (*3 AUC = 0.910, P = 0.800; *4 AUC = 0.946, P = 0.507) in training cohort. In the test cohort, model (AUC = 0.893) outperformed senior non-GI pathologists (*5 AUC = 0.782, P = 0.327; *6 AUC = 0.821, P = 0.516). We developed a DL model for the classification of CD and ITB, improving pathological diagnosis accuracy effectively.

Intestinal tuberculosis with small bowel stricture and hemorrhage as the predominant manifestation: Three case reports

BACKGROUND

Intestinal tuberculosis is a chronic disease caused by Mycobacterium tuberculosis that mainly affects the ileum and cecum. Small bowel tuberculosis, characterized by predominant involvement of the small intestine, is an extremely rare condition with highly atypical clinical presentations, making diagnosis even more challenging.

CASE SUMMARY

We report three cases of small intestinal tuberculosis, two of the patients presented primarily with abdominal pain, and one presented with gastrointestinal bleeding. All patients underwent blood tests and imaging examinations. Small bowel endoscopy (SBE) revealed that the main lesions in these patients were intestinal stenosis or gastrointestinal bleeding caused by small intestinal ulcers. One patient ultimately underwent surgical treatment. Following a complex diagnostic process and comprehensive analysis, all patients were confirmed to have small intestinal tuberculosis and received standard antituberculosis treatment, leading to an improvement in their condition.

CONCLUSION

Patients with SBTs present with nonspecific symptoms such as abdominal pain, weight loss, and occasional gastrointestinal bleeding. Accurate diagnosis requires a thorough evaluation of clinical symptoms and various tests to avoid misdiagnosis and complications.

Differentiating gastrointestinal tuberculosis and Crohn's disease- a comprehensive review

Gastrointestinal Tuberculosis (GITB) and Crohn's disease (CD) are both chronic granulomatous diseases with a predilection to involve primarily the terminal ileum. GITB is often considered a disease of the developing world, while CD and inflammatory bowel disease are considered a disease of the developed world. But in recent times, the epidemiology of both diseases has changed. Differentiating GITB from CD is of immense clinical importance as the management of both diseases differs. While GITB needs anti-tubercular therapy (ATT), CD needs immunosuppressive therapy. Misdiagnosis or a delay in diagnosis can lead to catastrophic consequences. Most of the clinical features, endoscopic findings, and imaging features are not pathognomonic for either of these two conditions. The definitive diagnosis of GITB can be clinched only in a fraction of cases with microbiological positivity (acid-fast bacilli, mycobacterial culture, or PCR-based tests). In most cases, the diagnosis is often based on consistent clinical, endoscopic, imaging, and histological findings. Similarly, no single finding can conclusively diagnose CD. Multiparametric-based predictive models incorporating clinical, endoscopy findings, histology, radiology, and serology have been used to differentiate GITB from CD with varied results. However, it is limited by the lack of validation studies for most such models. Many patients, especially in TB endemic regions, are initiated on a trial of ATT to see for an objective response to therapy. Early mucosal response assessed at two months is an objective marker of response to ATT. Prolonged ATT in CD is recognized to have a fibrotic effect. Therefore, early discrimination may be vital in preventing the delay in the diagnosis of CD and avoiding a complicated course.

Computed tomography enterography-based multiregional radiomics model for differential diagnosis of Crohn's disease from intestinal tuberculosis

PURPOSE

To build computed tomography enterography (CTE)-based multiregional radiomics model for distinguishing Crohn's disease (CD) from intestinal tuberculosis (ITB).

MATERIALS AND METHODS

A total of 105 patients with CD and ITB who underwent CTE were retrospectively enrolled. Volume of interest segmentation were performed on CTE and radiomic features were obtained separately from the intestinal wall of lesion, the largest lymph node (LN), and region surrounding the lesion in the ileocecal region. The most valuable radiomic features was selected by the selection operator and least absolute shrinkage. We established nomogram combining clinical factors, endoscopy results, CTE features, and radiomic score through multivariate logistic regression analysis. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the prediction performance. DeLong test was applied to compare the performance of the models.

RESULTS

The clinical-radiomic combined model comprised of four variables including one radiomic signature from intestinal wall, one radiomic signature from LN, involved bowel segments on CTE, and longitudinal ulcer on endoscopy. The combined model showed good diagnostic performance with an area under the ROC curve (AUC) of 0.975 (95% CI 0.953-0.998) in the training cohort and 0.958 (95% CI 0.925-0.991) in the validation cohort. The combined model showed higher AUC than that of the clinical model in cross-validation set (0.958 vs. 0.878, P = 0.004). The DCA showed the highest benefit for the combined model.

CONCLUSION

Clinical-radiomic combined model constructed by combining CTE-based radiomics from the intestinal wall of lesion and LN, endoscopy results, and CTE features can accurately distinguish CD from ITB.

Frequency, outcomes, and need for intervention in stricturing gastrointestinal tuberculosis: a systematic review and meta-analysis

BACKGROUND

Gastrointestinal strictures impact clinical presentation in abdominal tuberculosis and are associated with significant morbidity.

AIM

To conduct a systematic review of the prevalence of stricturing disease in abdominal and gastrointestinal tuberculosis and response to antitubercular therapy (ATT).

METHODS

We searched Pubmed and Embase on 13th January 2022, for papers reporting on the frequency and outcomes of stricturing gastrointestinal tuberculosis. The data were extracted, and pooled prevalence of stricturing disease was estimated in abdominal tuberculosis and gastrointestinal (intestinal) tuberculosis. The pooled clinical response and stricture resolution (endoscopic or radiologic) rates were also estimated. Publication bias was assessed using the Funnel plot and Egger test. The risk of bias assessment was done using a modified Newcastle Ottawa Scale.

RESULTS

Thirty-three studies reporting about 1969 patients were included. The pooled prevalence of intestinal strictures in abdominal tuberculosis and gastrointestinal TB was 0.12 (95%CI 0.07-0.20, I² = 89%) and 0.27 (95% CI 0.21-0.33, I² = 85%), respectively. The pooled clinical response of stricturing gastrointestinal tuberculosis to antitubercular therapy was 0.77 (95%CI 0.65-0.86, I² = 74%). The pooled stricture response rate (endoscopic or radiological) was 0.66 (95%CI 0.40-0.85, I² = 91%). The pooled rate of need for surgical intervention was 0.21 (95%CI 0.13-0.32, I² = 70%), while endoscopic dilatation was 0.14 (95%CI 0.09-0.21, I² = 0%).

CONCLUSION

Stricturing gastrointestinal tuberculosis occurs in around a quarter of patients with gastrointestinal tuberculosis, and around two-thirds of patients have a clinical response with antitubercular therapy. A subset of patients may need endoscopic or surgical intervention. The estimates for the pooled prevalence of stricturing disease and response to ATT had significant heterogeneity.

Clinical characteristics and diagnosis of intestinal tuberculosis in clinical practice at Thailand's largest national tertiary referral center: An 11-year retrospective review

BACKGROUND

Diagnosing intestinal tuberculosis (ITB) is challenging due to the low diagnostic sensitivity of current methods. This study aimed to assess the clinical characteristics and diagnosis of ITB at our tertiary referral center, and to explore improved methods of ITB diagnosis.

METHODS

This retrospective study included 177 patients diagnosed with ITB at Siriraj Hospital (Bangkok, Thailand) during 2009-2020.

RESULTS

The mean age was 49 years, 55.4% were male, and 42.9% were immunocompromised. Most diagnoses (108/177) were made via colonoscopy; 12 patients required more than one colonoscopy. Among those, the sensitivity of tissue acid-fast bacilli (AFB), presence of caseous necrosis, polymerase chain reaction (PCR), and culture was 40.7%, 13.9%, 25.7%, and 53.4%, respectively. Among patients with negative tissue histopathology, 4 (3.7%) and 13 (12.0%) were ITB positive on tissue PCR and culture, respectively. The overall sensitivity when all diagnostic methods were used was 63%. Seventy-six patients had stool tests for mycobacteria. The overall sensitivity of stool tests was 75.0%. However, when analyzing the 31 patients who underwent both endoscopy and stool testing, the sensitivity of stool testing when using tissue biopsy as a reference was 45.8%. Combining stool testing and tissue biopsy did not significantly increase the sensitivity compared to tissue biopsy alone (83.9% vs. 77.4%, respectively).

CONCLUSION

Despite the availability of PCR and culture for TB, the overall diagnostic sensitivity was found to be low. The sensitivity increased when the tests were used in combination. Repeated colonoscopy may be beneficial. Adding stool mycobacteria tests did not significantly increase the diagnostic yield if endoscopy was performed, but it could be beneficial if endoscopy is unfeasible.

Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model

Background

China is a region with a high incidence of tuberculosis, and the incidence of IBD has also been rising rapidly in recent years. Differentiating Crohn’s disease(CD) from intestinal tuberculosis (ITB) has become a very challenging issue. We aimed to develop and assess a diagnostic nomogram to differentiate between CD and ITB to improve the accuracy and practicability of the model.

Methods

A total of 133 patients (CD 90 and ITB 43) were analyzed retrospectively. Univariate and multivariate logistic regression analysis was included to determine the independent predictive factors and establish the regression equation. On this basis, the nomogram prediction model was constructed. The discrimination, calibration and clinical efficiency of the nomogram were assessed using area under the curve(AUC), C-index, calibration curve, decision curve analysis (DCA) and clinical impact curve.

Results

T-SPOT positive, cobblestone appearance, comb sign and granuloma were significant predictors in differentiating CD from ITB. Base on the above independent predictors, a diagnostic nomogram was successfully established. The sensitivity, specificity, accuracy of the prediction model are 94.4%, 93.0%, 94.0% respectively. The AUC and the C-index of the prediction model are both 0.988, which suggest that the model had a good discrimination power. The calibration curve indicated a high calibration degree of the prediction model. The DCA and clinical impact curve indicated a good clinical efficiency of the prediction model which could bring clinical benefits.

Conclusion

A nomogram prediction model for distinguishing CD from ITB was developed and assessed, with high discrimination, calibration and clinical efficiency. It can be used as an accurate and convenient diagnostic tool to distinguish CD from ITB, facilitating clinical decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02519-z.

Comparative evaluation of interleukin-10, transforming growth factor-β, and interleukin-17 in gastrointestinal tuberculosis and crohn's disease

Background

Gastrointestinal tuberculosis (GITB) and Crohn's disease (CD) are close mimickers and difficult to discriminate. Recent work has focused on the immunological differences between GITB and CD based on cytokines related to T-regulatory cells and Th17 cells. In the present cross-sectional study, suspected cases of GITB or CD underwent extensive clinical, radiological, endoscopic, histological, and microbiological assessment. The diagnosis was based on standard criteria and response to antitubercular therapy endoscopically.

Methods

Interleukin (IL)-10, transforming growth factor-β (TGF-β), and IL-17 were measured and compared between GITB and CD along with other parameters. Fisher's exact test and Mann-Whitney U test were used as per the data type.

Results

Of the 27 patients, 11 had CD, 9 had GITB, and 7 had other conditions. Chronic diarrhea, involvement of left and long segments of the colon, and aphthous ulcers were significantly more frequent in CD; however, transverse ulcers were in GITB. IL-10 was reduced in both GITB (median-interquartile range [IQR] 9.54 [3.65-24.04]) and CD (median-IQR 13.28 [6.91-22.50]) compared to control (median-IQR 26.72 [10.34-35.43]). TGF-β showed little variation, but IL-17 was below the detection limit in most cases. None of these cytokines were significantly different between CD and GITB. The sensitivity and specificity of multiplex Mycobacterium tuberculosis-polymerase chain reaction were 44.44% and 100%, respectively.

Conclusion

Serum cytokine profiling (IL-10, IL-17, and TGF-β) could not significantly differentiate GITB and CD. Moreover, extensive molecular, transcriptomic, chemokines, and cytokine analyses may shed light on these aspects.

Applying logistic LASSO regression for the diagnosis of atypical Crohn's disease

In countries with a high incidence of tuberculosis, the typical clinical features of Crohn's disease (CD) may be covered up after tuberculosis infection, and the identification of atypical Crohn's disease and intestinal tuberculosis (ITB) is still a dilemma for clinicians. Least absolute shrinkage and selection operator (LASSO) regression has been applied to select variables in disease diagnosis. However, its value in discriminating ITB and atypical Crohn's disease remains unknown. A total of 400 patients were enrolled from January 2014 to January 2019 in second Xiangya hospital Central South University.Among them, 57 indicators including clinical manifestations, laboratory results, endoscopic findings, computed tomography enterography features were collected for further analysis. R software version 3.6.1 (glmnet package) was used to perform the LASSO logistic regression analysis. SPSS 20.0 was used to perform Pearson chi-square test and binary logistic regression analysis. In the variable selection step, LASSO regression and Pearson chi-square test were applied to select the most valuable variables as candidates for further logistic regression analysis. Secondly, variables identified from step 1 were applied to construct binary logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was performed on these models to assess the ability and the optimal cutoff value for diagnosis. The area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy rate, together with their 95% confidence and intervals (CIs) were calculated. MedCalc software (Version 16.8) was applied to analyze the ROC curves of models. 332 patients were eventually enrolled to build a binary logistic regression model to discriminate CD (including comprehensive CD and tuberculosis infected CD) and ITB. However, we did not get a satisfactory diagnostic value via applying the binary logistic regression model of comprehensive CD and ITB to predict tuberculosis infected CD and ITB (accuracy rate:79.2%VS 65.1%). Therefore, we further established a binary logistic regression model to discriminate atypical CD from ITB, based on Pearsonchi-square test (model1) and LASSO regression (model 2). Model 1 showed 89.9% specificity, 65.9% sensitivity, 88.5% PPV, 68.9% NPV, 76.9% diagnostic accuracy, and an AUC value of 0.811, and model 2 showed 80.6% specificity, 84.4% sensitivity, 82.3% PPV, 82.9% NPV, 82.6% diagnostic accuracy, and an AUC value of 0.887. The comparison of AUCs between model1 and model2 was statistically different (P < 0.05). Tuberculosis infection increases the difficulty of discriminating CD from ITB. LASSO regression showed a more efficient ability than Pearson chi-square test based logistic regression on differential diagnosing atypical CD and ITB.

Enterogenous Microbiotic Markers in the Differential Diagnosis of Crohn's Disease and Intestinal Tuberculosis

Crohn’s disease (CD) is a chronic intestinal disorder characterized by refractory gastrointestinal ulcerations. Intestinal tuberculosis (ITB) is one common intestinal disease in east Asia. The two diseases share similar clinical manifestations and endoscopic characteristics. Thus, it is difficult to establish a definite diagnosis of CD, CD concomitant with ITB (CD-ITB), and ITB in practice. Some enterogeneous microbiotic markers have been applied to differentiate CD and ITB, but it remains unknown how they work for the three groups of patients. The aim of our study was to explore the diagnostic values of these enterogeneous microbiotic markers (ASCA IgG, ASCA IgA, ACCA, Anti-I2 and AMCA) among CD, CD-ITB, and ITB patients. A total of 124 individuals were retrospectively enrolled in this study, namely, 103 CD patients, 10 CD-ITB patients, 9 ITB patients, and 68 healthy controls. The demographic and clinical characteristics of these patients were collected and analyzed. The values of these individual or combined enterogeneous microbiotic markers in diagnosis and classification were assessed in CD, CD-ITB, and ITB patients. ASCA IgG, ASCA IgA, and AMCA could accurately differentiate CD patients from healthy controls with an area under curve (AUC) of 0.688, 0.601, and 0.638, respectively. ASCA IgG was significantly higher in CD patients than in CD-ITB patients (P = 0.0003). The Anti-I2 antibody was appropriate for distinguishing CD-ITB from ITB patients (P = 0.039). In CD patients, ASCA IgG was higher in severe patients than in mild (P <0.0001) and inactive patients (P <0.0001), respectively. AMCA was significantly elevated in severe and moderate patients compared to inactive patients (P = 0.001, P = 0.003, respectively). AMCA was associated with a higher risk of CD-related surgery with a significant P-value of 0.0038. In our cohort, ASCAs and AMCA could accurately distinguish CD from healthy controls with an acceptable AUC. A combination of elevated ASCA IgG and AMCA antibodies established a higher sensitivity in differentiating CD from healthy controls. Elevated ASCA IgG demonstrated a differential diagnostic value between CD and CD-ITB. Anti-I2 could also distinguish CD-ITB from ITB. The level of AMCA was associated with both disease severity and CD-related surgery. Likewise, the level of ASCA IgG was also related to disease severity.

A Novel Clinical Radiomics Nomogram to Identify Crohn's Disease from Intestinal Tuberculosis

Purpose

To establish a clinical radiomics nomogram to differentiate Crohn’s disease (CD) from intestinal tuberculosis (ITB).

Patients and Methods

Ninety-three patients with CD and 67 patients with ITB were recruited (111 in training cohort and 49 in test cohort). The region of interest (ROI) for the lesions in the ileocecal region was delineated on computed tomography enterography and radiomics features extracted. Radiomics features were filtered by the gradient boosting decision tree (GBDT), and a radiomics score was calculated by using the radiomics signature-based formula. We constructed a clinical radiomics model and nomogram combining clinical factors and radiomics score through multivariate logistic regression analysis, and the internal validation was undertaken by ten-fold cross validation. Analyses of receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the prediction performance. DeLong test was applied to evaluate the performance of the clinical, radiomics and combined model.

Results

The clinical radiomics nomogram, which was based on the 9 radiomics signature and two clinical factors, indicated that the clinical radiomics model had an area under the ROC curve (AUC) value of 0.96 (95% confidence interval [CI]: 0.93–0.99) in the training cohort and 0.93 (95% CI: 0.86–1.00) in validation cohort. The clinical radiomics model was superior to the clinical model and radiomics model, and the difference was significant (P = 0.006, 0.004) in the training cohort. DCA confirmed the clinical utility of clinical radiomics nomogram.

Conclusion

CTE-based radiomics model has a good performance in distinguishing CD from ITB. A nomogram constructed by combining radiomics and clinical factors can help clinicians accurately diagnose and select appropriate treatment strategies between CD and ITB.

Difficulties in the differential diagnosis of intestinal tuberculosis and Crohn‘s disease

The differential diagnosis of intestinal tuberculosis and Crohn’s disease is a difficult task for most specialists due to their high similarity in clinical manifestations, instrumental diagnosis and histological pattern.

The aim: to consider the clinical and diagnostic features of intestinal tuberculosis and Crohn’s disease, to show the role of various methods of their diagnosis (CT of the abdominal cavity, CT-enterography, colonoscopy with biopsy).

A clinical example shows a case illustrating the difficulties of diagnosing intestinal tuberculosis, initially diagnosed as Crohn’s disease. The features of the course, complex diagnosis and treatment of intestinal tuberculosis and its complications during immunosuppression are demonstrated. At the first stage of treatment, the patient’s data related to CT of the chest organs, colonoscopy and histological examination of biopsy samples were incorrectly interpreted. As a result, a wrong diagnosis of Crohn’s disease was made, and immunosuppressive therapy was prescribed that provoked a generalization of the existing tuberculosis process. Subsequently, repeated surgical interventions were performed for complications of intestinal tuberculosis – perforation of tuberculous ulcers, peritonitis. Based on the analysis of the literature data and our own observation, it is shown that granulomatous inflammation in the study of intestinal biopsies doesn’t always allow us to make a clear diagnosis, first of all, there are intestinal tuberculosis and Crohn’s disease in the differential diagnostic series. The use of histobacterioscopy according to Ziehl – Neelsen, the study of fecal matter by luminescent microscopy, as well as molecular genetic methods for detecting DNA MTB allow us to verify the diagnosis. If Crohn’s disease is misdiagnosed as intestinal tuberculosis, then the prescribed anti-tuberculosis therapy can cause harm and lead to a delay in the underlying disease treatment. The reverse misdiagnosis is potentially more dangerous: if tuberculosis is misdiagnosed as Crohn’s disease, then the appointment of immunosuppressive therapy can lead to the generalization of tuberculosis and the development of fatal complications. 

Deep-learning system for real-time differentiation between Crohn's disease, intestinal Behçet's disease, and intestinal tuberculosis

BACKGROUND AND AIM

Pattern analysis of big data can provide a superior direction for the clinical differentiation of diseases with similar endoscopic findings. This study aimed to develop a deep-learning algorithm that performs differential diagnosis between intestinal Behçet's disease (BD), Crohn's disease (CD), and intestinal tuberculosis (ITB) using colonoscopy images.

METHODS

The typical pattern for each disease was defined as a typical image. We implemented a convolutional neural network (CNN) using Pytorch and visualized a deep-learning model through Gradient-weighted Class Activation Mapping. The performance of the algorithm was evaluated using the area under the receiver operating characteristic curve (AUROC).

RESULTS

A total of 6617 colonoscopy images of 211 CD, 299 intestinal BD, and 217 ITB patients were used. The accuracy of the algorithm for discriminating the three diseases (all-images: 65.15% vs typical images: 72.01%, P = 0.024) and discriminating between intestinal BD and CD (all-images: 78.15% vs typical images: 85.62%, P = 0.010) was significantly different between all-images and typical images. The CNN clearly differentiated colonoscopy images of the diseases (AUROC from 0.7846 to 0.8586). Algorithmic prediction AUROC for typical images ranged from 0.8211 to 0.9360.

CONCLUSION

This study found that a deep-learning model can discriminate between colonoscopy images of intestinal BD, CD, and ITB. In particular, the algorithm demonstrated superior discrimination ability for typical images. This approach presents a beneficial method for the differential diagnosis of the diseases.

Development and validation of a new algorithm model for differential diagnosis between Crohn's disease and intestinal tuberculosis: a combination of laboratory, imaging and endoscopic characteristics

Background

Sometimes in clinical practice, it is a great challenge to distinguish Crohn's disease (CD) and intestinal tuberculosis (ITB), we conducted this study to identify simple and useful algorithm for distinguishing them.

Methods

We retrospectively reviewed the medical history of the patients who were diagnosed as ITB or CD. We firstly identified ITB patients, and then the patients diagnosed with CD were matched by age, sex, and admission time in a 1:1 ratio. Patients who admitted between May 1, 2013 and April 30, 2019 were regarded as training cohort, and patients admitted between May 1, 2019 and May 1, 2020 were regarded as validation cohort. We used multivariate analysis to identify the potential variables, and then we used R package rpart to build the classification and regression tree (CART), and validated the newly developed model.

Results

In total, the training cohort included 84 ITB and 84 CD patients, the validation cohort included 22 ITB and 22 CD patients. Multivariate analysis showed that, positive interferon-gamma release assays (IGRAs), ≥ 4 segments involved, longitudinal ulcer, circular ulcer, and aphthous ulcer were confirmed as independent discriminating factors. Using these parameters to build the CART model made an overall accuracy rate was 88.64%, with sensitivity, specificity, NPV, and PPV being 90.91%, 86.36%, 90.48% and 86.96%, respectively.

Conclusion

We developed a simple and novel algorithm model covering laboratory, imaging, and endoscopy parameters with CART to differentiate ITB and CD with good accuracy. Positive IGRAs and circular ulcer were suggestive of ITB, while ≥ 4 segments involved, longitudinal ulcer, and aphthous ulcer were suggestive of CD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-01838-x.

Gastrointestinal tuberculosis: A systematic review of epidemiology, presentation, diagnosis and treatment

Tuberculosis (TB) once considered a disease of the developing world is infrequent in the developing world too. Its worldwide prevalence with a huge impact on the healthcare system both in economic and health terms has prompted the World Health Organization to make it a top priority infectious disease. Tuberculous infection of the pulmonary system is the most common form of this disease, however, extrapulmonary TB is being increasingly recognized and more often seen in immunocompromised situations. Gastrointestinal TB is a leading extrapulmonary TB manifestation that can defy diagnosis. Overlap of symptoms with other gastrointestinal diseases and limited accuracy of diagnostic tests demands more awareness of this disease. Untreated gastrointestinal TB can cause significant morbidity leading to prolonged hospitalization and surgery. Prompt diagnosis with early initiation of therapy can avoid this. This timely review discusses the epidemiology, risk factors, pathogenesis, clinical presentation, current diagnostic tools and therapy.

Application value of tissue tuberculosis antigen combined with Xpert MTB/RIF detection in differential diagnoses of intestinal tuberculosis and Crohn's disease

Background

The purpose of this study was to examine the value of Xpert MTB/RIF assay and detection of additional Mycobacterium tuberculosis complex (MTBC) species antigens from intestinal tissue samples in differentiating intestinal tuberculosis (ITB) from Crohn’s disease (CD).

Methods

Several clinical specimens of intestinal tissue obtained by either endoscopic biopsy or surgical excision were used for mycobacteriologic solid cultures,Xpert MTB/RIF assays, immunohistochemistry, and histological examinations. Four antigens (38KDa, ESAT-6, MPT64, and Ag85 complex) of MTBC in the intestinal tissue were detected by immunohistochemical analysis.

Results

The study included 42 patients with ITB and 46 with CD. Perianal lesions and longitudinal ulcers were more common in patients with CD, while caseating granuloma and annular ulcers were more common in patients with ITB. The positive rate of MTBC detected by Xpert MTB/RIF in intestinal tissues of patients with ITB was 33.33%, which was significantly higher than that in patients with CD and that detected using acid-fast staining smears. It was also higher than that detected by tissue MTBC culture, but the difference was not statistically significant. The positive MPT64 expression rate in patients with ITB was 40.48%, which was significantly higher than that observed in patients with CD. The sensitivity of parallelly combined detection of tuberculosis protein MPT64 and Xpert MTB/RIF in diagnosing ITB was 50.0%.

Conclusions

The detection of Xpert MTB/RIF in intestinal tissue is a rapid and useful method for establishing an early diagnosis of ITB. The detection of MTBC using Xpert MTB/RIF and MPT64 antigen in intestinal tissues has a definitive value in the differential diagnosis ofITB and CD. The combination of these two methods can improve the detection sensitivity.

Performance of Diagnostic Model for Differentiating Between COVID-19 and Influenza: A 2-Center Retrospective Study

Background

COVID-19 and influenza share many similarities, such as mode of transmission and clinical symptoms. Failure to distinguish the 2 diseases may increase the risk of transmission. A fast and convenient differential diagnosis between COVID-19 and influenza has significant clinical value, especially for low- and middle-income countries with a shortage of nucleic acid detection kits. We aimed to establish a diagnostic model to differentiate COVID-19 and influenza based on clinical data.

Material/Methods

A total of 493 patients were enrolled in the study, including 282 with COVID-19 and 211 with influenza. All data were collected and reviewed retrospectively. The clinical and laboratory characteristics of all patients were analyzed and compared. We then randomly divided all patients into development sets and validation sets to establish a diagnostic model using multivariate logistic regression analysis. Finally, we validated the diagnostic model using the validation set.

Results

We preliminarily established a diagnostic model for differentiating COVID-19 from influenza that consisted of 5 variables: age, dry cough, fever, white cell count, and D-dimer. The model showed good performance for differential diagnosis.

Conclusions

This initial model including clinical features and laboratory indices effectively differentiated COVID-19 from influenza. Patients with a high score were at a high risk of having COVID-19, while patients with a low score were at a high risk of having influenza. This model could help clinicians quickly identify and isolate cases in the absence of nucleic acid tests, especially during the cocirculation of COVID-19 and influenza. Owing to the study’s retrospective nature, further prospective study is needed to validate the accuracy of the model.

Validation of models using basic parameters to differentiate intestinal tuberculosis from Crohn's disease: A multicenter study from Asia

BACKGROUND

Data on external validation of models developed to distinguish Crohn's disease (CD) from intestinal tuberculosis (ITB) are limited. This study aimed to validate and compare models using clinical, endoscopic, and/or pathology findings to differentiate CD from ITB.

METHODS

Data from newly diagnosed ITB and CD patients were retrospectively collected from 5 centers located in Thailand or Hong Kong. The data was applied to Lee, et al., Makharia, et al., Jung, et al., and Limsrivilai, et al. model.

RESULTS

Five hundred and thirty patients (383 CD, 147 ITB) with clinical and endoscopic data were included. The area under the receiver operating characteristic curve (AUROC) of Limsrivilai's clinical-endoscopy (CE) model was 0.853, which was comparable to the value of 0.862 in Jung's model (p = 0.52). Both models performed significantly better than Lee's endoscopy model (AUROC: 0.713, p<0.01). Pathology was available for review in 199 patients (116 CD, 83 ITB). When 3 modalities were combined, Limsrivilai's clinical-endoscopy-pathology (CEP) model performed significantly better (AUROC: 0.887) than Limsrivilai's CE model (AUROC: 0.824, p = 0.01), Jung's model (AUROC: 0.798, p = 0.005) and Makharia's model (AUROC: 0.637, p<0.01). In 83 ITB patients, the rate of misdiagnosis with CD when used the proposed cutoff values in each original study was 9.6% for Limsrivilai's CEP, 15.7% for Jung's, and 66.3% for Makharia's model.

CONCLUSIONS

Scoring systems with more parameters and diagnostic modalities performed better; however, application to clinical practice is still limited owing to high rate of misdiagnosis of ITB as CD. Models integrating more modalities such as imaging and serological tests are needed.

Prospective validation of CD4+CD25+FOXP3+ T-regulatory cells as an immunological marker to differentiate intestinal tuberculosis from Crohn's disease

Background/Aims

Crohn’s disease (CD) and intestinal tuberculosis (ITB) remain “difficult-to-differentiate” diseases. We have previously documented peripheral blood frequency of CD4⁺ CD25⁺ FOXP3⁺ T-regulatory cells (Treg) as a biomarker to differentiate CD and ITB. We tried to validate these results in a larger cohort of CD and ITB patients.

Methods

Seventy treatment naïve patients of CD (n = 23) and ITB (n = 47) (diagnosed by standard criteria) were recruited prospectively from October 2016 to May 2017. Patients with history of antitubercular therapy in the past were excluded. The frequency of Treg cells in peripheral blood was determined by flow cytometry, and compared between CD and ITB patients.

Results

Similar to our previous study, frequency of Treg cells in peripheral blood was significantly increased in ITB as compared to CD patients (40.9 [interquartile range, 33–50] vs. 24.9 [interquartile range, 14.4–29.6], P<0.001). Further, the receiver operating characteristics curve also showed good diagnostic accuracy with an area under the curve (AUC) of 0.77 (95% confidence interval, 0.65–0.89) and a FOXP3⁺ cutoff value of > 31.3% had a sensitivity and specificity of 83% and 82.6% respectively, to differentiate ITB from CD. Even for the indeterminate cases (n = 33), Treg cell frequency had similar diagnostic accuracy with an AUC of 0.85 (95% confidence interval, 0.68–0.95) and a cutoff of 32.37% had sensitivity and specificity of 87% and 95% respectively, to differentiate ITB from CD.

Conclusions

The current findings validate that the increased frequency of CD4⁺ CD25⁺ FOXP3⁺ Treg in the peripheral blood can be used as a biomarker with high diagnostic accuracy to differentiate ITB from CD.

Intestinal tuberculosis or Crohn's disease: a review of the diagnostic models designed to differentiate between these two gastrointestinal diseases

Differentiating Crohn’s disease (CD) from intestinal tuberculosis (ITB) is a diagnostic dilemma, particularly in regions where ITB is prevalent and CD incidence is increasing, because both diseases can present quite similarly, and diagnostic tests to identify Mycobacterium tuberculosis in tissue samples have rather poor sensitivity. Studies that were conducted to determine the factors that differentiate CD from ITB identified some significant characteristics, but none of those characteristics are exclusive to either ITB or CD. Many diagnostic models or scoring systems that use one to several diagnostic parameters have been proposed to help distinguish these two intestinal diseases. Early models consisted of parameters common to routine clinical practice, such as clinical features, and endoscopic and pathologic findings. The later models also include more advanced diagnostic parameters like high-resolution imaging and serological testing. However, the number and types of parameters differ among diagnostic models, and the systems used to calculate scoring also vary from model to model. Enhanced awareness and understanding of the currently available diagnostic models will help physicians determine which model(s) is/are most suitable for differentiating CD from ITB in their clinical practice.

Effect of Age on the Initiation of Biologic Agent Therapy in Patients With Inflammatory Bowel Disease: Korean Common Data Model Cohort Study

BACKGROUND

The Observational Health Data Sciences and Informatics (OHDSI) network is an international collaboration established to apply open-source data analytics to a large network of health databases, including the Korean common data model (K-CDM) network.

OBJECTIVE

The aim of this study is to analyze the effect that age at diagnosis has on the prognosis of inflammatory bowel disease (IBD) in Korea using a CDM network database.

METHODS

We retrospectively analyzed the K-CDM network database from 2005 to 2015. We transformed the electronic medical record into the CDM version 5.0 used in OHDSI. A worsened IBD prognosis was defined as the initiation of therapy with biologic agents, including infliximab and adalimumab. To evaluate the effect that age at diagnosis had on the prognosis of IBD, we divided the patients into an early-onset (EO) IBD group (age at diagnosis <40 years) and a late-onset (LO) IBD group (age at diagnosis ≥40 years) with the cutoff value of age at diagnosis as 40 years, which was calculated using the Youden index method. We then used the logrank test and Cox proportional hazards model to analyze the effect that age at diagnosis (EO group vs LO group) had on the prognosis in patients with IBD.

RESULTS

A total of 3480 patients were enrolled. There was 2017 patients with ulcerative colitis (UC) and 1463 with Crohn's disease (CD). The median follow up period was 109.5 weeks. The EO UC group was statistically significant and showed less event-free survival (ie, experiences of biologic agents) than the LO UC group (P<.001). In CD, the EO CD group showed less event-free survival (ie, experiences of biologic agents) than the LO CD group. In the Cox proportional hazard analysis, the odds ratio (OR) of the EO UC group on experiences of biologic agents compared with the LO UC group was 2.3 (95% CI 1.3-3.8, P=.002). The OR of the EO CD group on experiences of biologic agents compared with the LO CD group was 5.4 (95% CI 1.9-14.9, P=.001).

CONCLUSIONS

The EO IBD group showed a worse prognosis than the LO IBD group in Korean patients with IBD. In addition, this study successfully verified the CDM model in gastrointestinal research.

Gastrointestinal Tuberculosis Mimicking Crohn's Disease

We present the case of a 24-year-old woman with complaints of abdominal pain, bloody diarrhea, and weight loss for 3 months. An outpatient colonoscopy revealed scattered ulcers, suggestive of Crohn's disease (CD). Histopathology also favored the diagnosis of CD. However, after admission to our hospital for further investigation, a chest radiograph revealed pulmonary cavitations. A computed tomography scan suggested the diagnosis of active pulmonary tuberculosis (TB). Therefore, a bronchofibroscopy, a total colonoscopy with ileoscopy, and an upper endoscopy were performed. Not only were acid-fast bacilli present in both bronchoalveolar lavage fluid and gastric juice, but also in colonic biopsies. A complete resolution of gastrointestinal symptoms was achieved 2 weeks after starting anti-TB drugs.

Intestinal tuberculosis and Crohn's disease: the importance and difficulty of a differential diagnosis

Tuberculosis (TB) is the most prevalent infection worldwide and affects one third of the population, predominantly in developing countries. Intestinal TB (ITB) is the sixth most frequent extra-pulmonary TB infection. Crohn's disease (CD) is a chronic inflammatory bowel disease that arises from the interaction of immunological, environmental and genetic factors. Due to changes in the epidemiology of both diseases, distinguishing CD from ITB is a challenge, particularly in immunocompromised patients and those from areas where TB is endemic. Furthermore, both TB and CD have a predilection for the ileocecal area. In addition, they share very similar clinical, radiological and endoscopic findings. An incorrect diagnosis and treatment may increase morbidity and mortality. Thus, a great degree of caution is required as well as a familiarity with certain characteristics of the diseases, which will aid the differentiation between the two diseases.

Comparison of outcomes of continuation/discontinuation of 5-aminosalicylic acid after initiation of anti-tumor necrosis factor-alpha therapy in patients with inflammatory bowel disease

BACKGROUND

Few maintenance therapeutic options are available for inflammatory bowel disease (IBD). Data on the effects of continuing 5-aminosalicylic acid (5-ASA) treatment in patients who commence on biologics as maintenance treatment remain scarce. We evaluated IBD patient outcomes after continuation/discontinuation of 5-ASA when biologics were administered as maintenance treatment.

METHODS

We retrospectively reviewed the clinical, laboratory, and imaging data of patients diagnosed with IBD (ulcerative colitis (UC), 763; Crohn's disease (CD), 537) in the Gil Medical Center (GMC) from February 2005 to June 2018. We divided patients administered with biologics as maintenance treatment into those who did and did not continue on 5-ASA and compared the efficacies of the two treatment options using the log-rank test and Cox proportional hazards models.

RESULTS

Of 1300 total IBD patients, 128 (UC, 63; CD, 65) were prescribed biologics as induction and maintenance treatments. The median follow-up period was 109.5 weeks. All cases were divided into those who did or did not combine 5-ASA with biologics as maintenance treatments. Kaplan-Meier analysis showed that the event-free survival (exacerbation of disease activity) of UC patients treated with biologics and 5-ASA (n = 42) was not significantly lower than that of those taking biologics alone (n = 21) (log rank test, P = 0.68). The same was true of CD patients (n = 42, biologics and 5-ASA; n = 23, biologics only) (log rank test, P = 0.87).

CONCLUSIONS

Continuation of 5-ASA after initiation of anti-tumor necrosis factor-alpha agents did not improve prognosis in Korean IBD patients compared with that of those who discontinued 5-ASA during maintenance treatment, particularly in patients who experienced more than two disease aggravations.

Imaging in discriminating intestinal tuberculosis and Crohn's disease: past, present and the future

Introduction: Intestinal tuberculosis (ITB) and Crohn's disease (CD) have similar clinical presentation, but require different treatment approaches. Despite advances in various endoscopic, imaging, microbiological, and histological techniques, the differentiation of these two entities is often difficult. Newer radiological and image acquisition modalities have now become indispensable tools for evaluation of these two diseases.Areas covered: This review summarizes the currently available literature on various radiological investigations to differentiate ITB from CD. This review also enumerates the newer modalities in image acquisition techniques and their potential role for differentiating these two diseases. At present abdominal computed tomography (CT) scan is used as a first line investigation for differentiating ITB from CD. Magnetic resonance imaging (MRI) is preferred in pediatric patients and for follow-up studies.Expert opinion: Role of newer modalities like contrast enhanced abdominal ultrasound, perfusion CT, advanced MRI and positron emission tomography (PET) is evolving and requires further exploration. Till further robust studies are available, differentiation between ITB and CD requires use of a combination of clinical, endoscopic, serological, histological, and radiological parameters rather than relying on a single test.

Analysis of Phenotypic Variables and Differentiation Between Untypical Crohn's Disease and Untypical Intestinal Tuberculosis

BACKGROUND

The differentiation between untypical intestinal tuberculosis (UITB) and untypical Crohn's disease (UCD) is a challenge.

AIMS

To analyze phenotypic variables and propose a novel prediction model for differential diagnosis of two conditions.

METHODS

A total of 192 patients were prospectively enrolled. The clinical, laboratory, endoscopic, and radiological features were investigated and subjected to univariable and multivariable analyses. The final prediction model for differentiation between UCD and UITB was developed by logistic regression analysis and Fisher discriminant analysis on the training set. The same discriminant function was tested on the validation set.

RESULTS

Twenty-five candidates were selected from 52 phenotypic variables of typical Crohn's disease (TCD), UCD, and UITB patients. UCD's variables overlapped with both TCD and UITB. The percentages of tuberculosis history, positive PPD, and positive T-SPOT result in UCD were all significantly higher than that in TCD (11.6% vs. 0.0%, 27.9% vs. 0.0%, 25.6% vs. 4.5%, respectively, P < 0.05). The regression equations and Fisher discriminant function for discrimination between UCD and UITB were developed. In the training data, the area under the receiver operating characteristic of equations was 0.834, 0.69, and 0.648 in the clinical-laboratory, endoscopic, and radiological model, respectively. The accuracy of Fisher discriminant function for discrimination was 86% in UCD and 73% in UITB in the validation data.

CONCLUSIONS

Phenotypes of UCD patients in TB-endemic countries may be associated with TB infection history. Fisher discriminant analysis is a good choice to differentiate UCD from UITB, which is worthy of verification in clinical practice.

Development and Validation of a Novel Diagnostic Nomogram to Differentiate Between Intestinal Tuberculosis and Crohn's Disease: A 6-year Prospective Multicenter Study

OBJECTIVES

Differentiating Crohn's disease (CD) from intestinal tuberculosis (ITB) remains a diagnostic challenge. Misdiagnosis carries potential grave implications. We aimed to develop and validate a novel diagnostic nomogram for differentiating them.

METHODS

In total, 310 eligible patients were recruited from 6 tertiary inflammatory bowel disease centers. Among them, 212 consecutive patients (143 CD and 69 ITB) were used in the derivation cohort for the establishment of diagnostic equation and nomogram; 7 investigative modalities including clinical manifestations, laboratory results, endoscopic findings, computed tomography enterography features, and histology results were used to derive the diagnostic model and nomogram. Ninety-eight consecutive patients (76 CD and 22 ITB) were included for validation of the diagnostic model.

RESULTS

Eight out of total 79 parameters were identified as valuable parameters used for establishing diagnostic equations. Two regression models were built based on 7 differential variables: age, transverse ulcer, rectum involvement, skipped involvement of the small bowel, target sign, comb sign, and interferon-gamma release assays (for model 1) or purified protein derivative (for model 2), respectively. Accordingly, 2 nomograms of the above 2 models were developed for clinical practical use, respectively. Further validation test verified the efficacy of the nomogram 1 with 90.9% specificity, 86.8% sensitivity, 97.1% PPV, 66.7% negative predictive value (NPV), and 87.8% accuracy for identifying CD, and the efficacy of the nomogram 2 with 100% specificity, 84.2% sensitivity, 100% positive predictive value, 64.7% NPV, and 87.8% accuracy for diagnosing CD.

CONCLUSIONS

The derivation and validation cohorts identified and validated 2 highly accurate and practical diagnostic nomograms for differentiating CD from ITB. These diagnostic nomograms can be conveniently used to identify some difficult CD or ITB cases, allowing for decision-making in a clinical setting.

Differentiating Crohn’s disease from intestinal tuberculosis

Differentiating Crohn’s disease (CD) and intestinal tuberculosis (ITB) has remained a dilemma for most of the clinicians in the developing world, which are endemic for ITB, and where the disease burden of inflammatory bowel disease is on the rise. Although, there are certain clinical (diarrhea/hematochezia/perianal disease common in CD; fever/night sweats common in ITB), endoscopic (longitudinal/aphthous ulcers common in CD; transverse ulcers/patulous ileocaecal valve common in ITB), histologic (caseating/confluent/large granuloma common in ITB; microgranuloma common in CD), microbiologic (positive stain/culture for acid fast-bacillus in ITB), radiologic (long segment involvement/comb sign/skip lesions common in CD; necrotic lymph node/contiguous ileocaecal involvement common in ITB), and serologic differences between CD and ITB, the only exclusive features are caseation necrosis on biopsy, positive smear for acid-fast bacillus (AFB) and/or AFB culture, and necrotic lymph node on cross-sectional imaging in ITB. However, these exclusive features are limited by poor sensitivity, and this has led to the development of multiple multi-parametric predictive models. These models are also limited by complex formulae, small sample size and lack of validation across other populations. Several new parameters have come up including the latest Bayesian meta-analysis, enumeration of peripheral blood T-regulatory cells, and updated computed tomography based predictive score. However, therapeutic anti-tubercular therapy (ATT) trial, and subsequent clinical and endoscopic response to ATT is still required in a significant proportion of patients to establish the diagnosis. Therapeutic ATT trial is associated with a delay in the diagnosis of CD, and there is a need for better modalities for improved differentiation and reduction in the need for ATT trial.

Diagnostic Performance of a 5-Marker Predictive Model for Differential Diagnosis Between Intestinal Tuberculosis and Crohn's Disease

BACKGROUND

The differentiation between intestinal tuberculosis (ITB) and Crohn's disease (CD) is a challenge. The aim of this study was to investigate a predictive model for differential diagnosis between ITB and CD.

METHODS

A total of 268 patients who were suspected of having ITB or CD were prospectively recruited between January 2013 and September 2016. The clinical, laboratory, radiological, endoscopic, and histological features were investigated and subjected to univariate and multivariate analyses. The final predictive model was developed based on the regression coefficients of multivariate logistic regression. To validate the model, the same regression equation was tested on the other group.

RESULTS

A total of 239 patients had a final diagnosis, including 86 ITB and 153 CD. Five variables (perianal disease, pulmonary involvement, longitudinal ulcer, left colon, and ratio of tuberculosis-specific antigen to phytohaemagglutinin) were selected for the predictive model to discriminate between ITB and CD. In the predictive model of the training data set, the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy, with a cutoff level of 0.29, were 0.975 (95% confidence interval [CI], 0.939-0.993), 96.7%, 90.7%, and 92.8%, respectively. Application of the predictive model to the validation data set showed similar performance in distinguishing ITB from CD. The area under the ROC curve, sensitivity, specificity, and accuracy were 0.950 (95% CI, 0.871-0.987), 88.5%, 93.5%, and 91.7%, respectively.

CONCLUSIONS

This 5-marker predictive model could be conveniently used by clinicians to draw a reliable differential diagnosis between ITB and CD in clinical practice. 10.1093/ibd/izy154_video1izy154.video15790725497001.

Combination of increased visceral fat and long segment involvement: Development and validation of an updated imaging marker for differentiating Crohn's disease from intestinal tuberculosis

BACKGROUND AND AIM

Computed tomographic (CT) features (long segment, ileocaecal area involvement, and lymph nodes > 1 cm) have demonstrated good specificity but poor sensitivity, while visceral to subcutaneous fat ratio on CT (VF/SC > 0.63) has moderate sensitivity and specificity in differentiating Crohn's disease (CD) and intestinal tuberculosis (ITB). This study aims to develop and validate an updated model incorporating CT features and VF/SC to improve the diagnostic accuracy of imaging in differentiating CD/ITB.

METHODS

Computed tomographic features and VF/SC were documented in two cohorts (development [n = 59, follow-up: January 2012 to November 2014] and validation [n = 69, follow-up: December 2014 to December 2015]) of CD/ITB patients diagnosed by standard criteria. Patients with normal CT were excluded. Features significantly different between CD/ITB were incorporated into a model.

RESULTS

In both the cohorts, necrotic lymph nodes were exclusive for ITB (23.1% vs 0% and 43.3% vs 0%), while long segment involvement (57.6% vs 7.7%, P < 0.001, and 52.6% vs 16.1%, P < 0.001) and VF/SC ratio > 0.63 (72.7% vs 19.2%, P < 0.001, and 81.6% vs 25.8%, P < 0.001) were significantly more common in CD. A risk score of 2, based upon long segment involvement and VF/SC ratio > 0.63, had an excellent specificity of 100% and 100% and sensitivity of 54% and 50% for CD in development and validation cohorts, respectively. Based upon these features, in 43% patients with the diagnostic dilemma of CD/ITB, a definite diagnosis based only on imaging could be made.

CONCLUSION

Necrotic lymph nodes are exclusive for ITB, and the combination of long segment involvement and VF/SC ratio > 0.63 is exclusive for CD, and these features can make a definite diagnosis in 43% patients with a CD/ITB dilemma.

Temporal trends in the misdiagnosis rates between Crohn's disease and intestinal tuberculosis

AIM

To investigate the temporal trends in the misdiagnosis rate between Crohn's disease (CD) and intestinal tuberculosis (ITB) in South Korea.

METHODS

We retrospectively reviewed the medical records of patients managed for CD or ITB at Asan Medical Center, a tertiary referral hospital, Seoul, Korea between 1996 and 2014. The temporal trends in the misdiagnosis rates between the two diseases were analyzed. The demographic and clinical characteristics were compared between CD patients who were initially misdiagnosed as ITB (final CD group) and vice versa (final ITB group). Final diagnostic criteria for ITB and medication for CD before definite diagnosis of TB were also analyzed in final ITB group.

RESULTS

In total, 2760 patients were managed for CD and 772 patients for ITB between 1996 and 2014. As well, 494 of the 2760 CD patients (17.9%) were initially misdiagnosed as ITB and 83 of the 772 ITB patients (10.8%) as CD. The temporal trend in misdiagnosing CD as ITB showed a decrease (OR = 0.89, 95%CI: 0.87-0.91, P < 0.001), whereas the temporal trend in misdiagnosing ITB as CD showed an increase (OR = 1.06, 95%CI: 1.01-1.11, P = 0.013). Age at diagnosis, presenting symptoms, and proportion of patients with active/past perianal fistula and active/inactive pulmonary tuberculosis (TB) were significantly different between final CD group and final ITB group. Forty patients (48.2%) in final ITB group were diagnosed by favorable response to empirical anti-TB treatment. Seventeen patients (20.5%) in final ITB group had inappropriately received corticosteroids and/or thiopurines due to misdiagnosis as CD. However, there were no mortalities in both groups.

CONCLUSION

Cases of CD misdiagnosed as ITB have been decreasing, whereas cases of ITB misdiagnosed as CD have been increasing over the past two decades.

Meta-Analytic Bayesian Model For Differentiating Intestinal Tuberculosis from Crohn's Disease

OBJECTIVES

Distinguishing intestinal tuberculosis (ITB) from Crohn's disease (CD) is difficult, although studies have reported clinical, endoscopic, imaging, and laboratory findings that help to differentiate these two diseases. We aimed to produce estimates of the predictive power of these findings and construct a comprehensive model to predict the probability of ITB vs. CD.

METHODS

A systematic literature search for studies differentiating ITB from CD was conducted in MEDLINE, PUBMED, and EMBASE from inception until September 2015. Fifty-five distinct meta-analyses were performed to estimate the odds ratio of each predictive finding. Estimates with a significant difference between CD and ITB and low to moderate heterogeneity (I²<50%) were incorporated into a Bayesian prediction model incorporating the local pretest probability.

RESULTS

Thirty-eight studies comprising 2,117 CD and 1,589 ITB patients were included in the analyses. Findings in the model that significantly favored CD included male gender, hematochezia, perianal disease, intestinal obstruction, and extraintestinal manifestations; endoscopic findings of longitudinal ulcers, cobblestone appearance, luminal stricture, mucosal bridge, and rectal involvement; pathological findings of focally enhanced colitis; and computed tomographic enterography (CTE) findings of asymmetrical wall thickening, intestinal wall stratification, comb sign, and fibrofatty proliferation. Findings that significantly favored ITB included fever, night sweats, lung involvement, and ascites; endoscopic findings of transverse ulcers, patulous ileocecal valve, and cecal involvement; pathological findings of confluent or submucosal granulomas, lymphocyte cuffing, and ulcers lined by histiocytes; a CTE finding of short segmental involvement; and a positive interferon-γ release assay. The model was validated by gender, clinical manifestations, endoscopic, and pathological findings in 49 patients (27 CD, 22 ITB). The sensitivity, specificity, and accuracy for diagnosis of ITB were 90.9%, 92.6%, and 91.8%, respectively.

CONCLUSIONS

A Bayesian model based on the meta-analytic results is presented to estimate the probability of ITB and CD calibrated to local prevalence. This model can be applied to patients using a publicly available web application.