Emerging Imaging Biomarkers in Crohn Disease

Body MRI in pediatrics: where we are and what the future holds

Body magnetic resonance imaging (MRI) is increasingly used for disease diagnosis, characterization, and monitoring in children of all ages. MRI has numerous advantages when compared to other imaging modalities, including a lack of ionizing radiation, superior soft tissue image contrast, and ability to provide objective, quantitative assessments. As MRI continues to evolve, pediatric body MRI examinations of the future will certainly be different than our current and past protocols. In this review article, we will discuss the present and likely future states of pediatric body MRI, including the increasing application of quantitative MRI methods, faster imaging techniques and implementation of abbreviated targeted protocols, and the growing use of artificial intelligence methods.

Biomarkers That Predict Crohn's Disease Outcomes

Crohn's disease (CD), a chronic inflammatory condition of the digestive tract, poses significant challenges in terms of disease prognosis and treatment selection. Biomarkers have the potential to predict CD outcomes and guide clinical decision-making. This review aims to summarize the current literature on promising biomarkers associated with CD outcomes and their potential clinical implications. The identification of reliable biomarkers for CD outcomes is of paramount importance in tailoring treatment strategies, monitoring disease activity, and predicting the risk of complications. Clinical prognostic factors traditionally used to assess disease severity, and the likelihood of complications have limitations in accuracy and predictive value. Thus, there is a need for more precise biomarkers, particularly in newly diagnosed and treatment-naive patients. Pharmacogenomic markers, such as TPMT and NUDT15 polymorphisms, have been utilized to identify patients at risk of adverse events with thiopurine therapy. Several biomarkers, including HLA haplotypes, oncostatin M expression, and transcriptomic profiles, have shown associations with response to anti-TNF therapy. Confocal laser endomicroscopy and single-cell analyses hold promise in predicting treatment response to specific therapies. The identification of biomarkers associated with post-operative recurrence in CD is crucial, as it could lead to changes in management algorithms. Several promising microbiome signatures and proteomic profiles have been identified. In conclusion, biomarkers have the potential to revolutionize the management of CD by providing valuable prognostic information and guiding treatment decisions. However, further research and validation are necessary to establish their clinical utility and integration into routine practice.

Radiomics could predict surgery at 10 years in Crohn's disease

BACKGROUND

Predicting clinical outcomes represents a major challenge in Crohn's disease (CD). Radiomics provides a method to extract quantitative features from medical images and may successfully predict clinical course.

AIMS

The aim of this pilot study is to evaluate the use of radiomics to predict 10-year surgery for CD patients.

METHODS

We selected a cohort of CD patients with CT scan enterographies and a 10-year follow up. The R library Moddicom was used to extract radiomic features from each lesion of CD, segmented in the CT scans. A logistic regression model based on selected radiomic features was developed to predict 10-year surgery. The model was evaluated by computing the area under the curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity, positive and negative predictive values (PPV, NPV).

RESULTS

We enroled 30 patients, with 44 CT scans and 93 lesions. We extracted 217 radiomic features from each lesion. The developed model was based on two radiomic features and presented an AUC (95% CI) of 0.83 (0.73-0.91) in predicting 10-year surgery. Sensitivity, specificity, PPV, NPV of the radiomic model were equal to 0.72, 0.90, 0.79, 0.86, respectively.

CONCLUSION

Radiomics could be a helpful tool to identify patients with high risk for surgery and needing a stricter monitoring.

Untargeted serum metabolomics reveals specific metabolite abnormalities in patients with Crohn's disease

Crohn's disease (CD) is a subtype of inflammatory bowel disease (IBD) characterized by skip intestinal lesions that can occur in any part of the gastrointestinal tract. Currently, the diagnosis of CD is based on clinical history, physical examination and complementary diagnostic tests. It is challenging for physicians to make a definitive diagnosis. This study aimed to analyze the variation in metabolites in CD serum and identify potential predictive biomarkers of CD diagnosis. We collected serum samples from 316 subjects, including patients with CD and healthy controls (HCs). Serum metabolomics was conducted using liquid chromatography coupled to mass spectrometry. Potential biomarkers were screened and evaluated by univariate and multivariate analyses. A panel of two metabolites (deoxycholic acid and palmitic amide) was identified as a specific biomarker of CD. Receiver operating characteristic analysis (ROC) showed that the panel had a sensitivity of 80.25% with a specificity of 95.54% in discriminating CD patients from healthy controls. The biomarkers identified are increased in CD compared with healthy controls. Our approach successfully identified serum biomarkers associated with CD patients. The potential biomarkers indicated that CD metabolic disturbance might be associated with bile acid biosynthesis, fatty acids and energy metabolism.