Seeing the whole picture: Inflammatory bowel disease complications and extraintestinal manifestations on cross‐sectional imaging
Notice bibliographique
Résumé
Computed tomography (CT) and magnetic resonance (MR) enterography techniques are widely used for detection and monitoring of intestinal complications in inflammatory bowel disease (IBD). According to international recommendations, patients newly diagnosed with Crohn's disease (CD) and those with symptomatic small bowel disease should undergo small bowel assessment ideally using MR enterography, capsule endoscopy, or intestinal ultrasound (IUS).1 While the diagnostic yield of the three techniques is similar, cross-sectional tools such as CT imaging (involving ionizing radiation) should be reserved for those with a suspicion of more urgent pathology such as obstructive or fistulizing disease.2 Although commonly used for luminal indications in IBD, the use of cross-sectional imaging specifically for identifying extraintestinal manifestations (EIMs) has been less explored.3, 4 In a real-world retrospective study, Vuyyuru et al. analyzed the prevalence of transmural complications (stricture/fistula) and the incidental finding of EIMs in patients with IBD who underwent CT or MR enterography over 9 years at two Canadian centers.5 The study included over 550 IBD patients, 91% of whom had CD, with a median disease duration of 11 years. In this cohort, transmural imaging identified a B2 (stricturing) or B3 (fistulizing) phenotype in more than 40% of individuals. The overall prevalence of EIMs was 25%, with one-third in patients previously undiagnosed at the time of the enterography. Among those newly diagnosed with EIMs (n = 41), the most common were cholelithiasis (63%), followed by sacroiliitis (24%) and primary sclerosing cholangitis (5%). These results corroborate current international guidance, highlighting the importance of cross-sectional imaging to identify transmural complications. Additionally, this study emphasizes the need for vigilance and of the possibility to use cross-sectional imaging tools to help identify EIMs. It is important to note that for some patients the presence of EIMs may be earlier in development or asymptomatic. This may explain why there was a relatively large proportion of patients with newly diagnosed EIMs, despite a median disease duration of 11 years. In this regard, the authors demonstrate promise for cross-sectional imaging to detect even subclinical EIMs. More timely detection and diagnosis of EIMs may be crucial for some diseases such as primary sclerosing cholangitis due to its association with malignancy and need for surveillance. Moreover, earlier detection may also enable better understanding of the burden of EIMs and help guide treatment selection.6 For example, earlier introduction of biologic therapy might be considered in a patient with only mild luminal IBD but who has concomitant sacroiliitis. Although this study provides novel and important insights in a real-world setting, there remain some unanswered questions. First, selection of the most “appropriate or optimal” cross-sectional imaging modality remains a challenge. With increasing availability of IUS, it may be more difficult to justify use of CT or MR for first-line cross-sectional imaging. There are multiple potential benefits of IUS including being:less expensive, faster to perform, well tolerated for patients, with no ionizing radiation risk as well as more recently being validated to identify B2 and B3 phenotypes. However, this should be balanced with an awareness that MR in particular has been reported to have a higher specificity than IUS for small bowel disease extent, to detect deep-seated or pelvic fistulas, as well as abscesses.7, 8 Moreover, it is unknown whether IUS could also help identify EIMs with the same level as demonstrated by CT and MR imaging in this study. Second, the inter-observer agreement for identifying and grading EIMs remains unclear, with a possibility for more incidental or non-diagnostic findings if all cross-sectional imaging were to routinely report on presence or absence of EIMs. Third, it is not clear if the additional time and acquisition costs for specific sequences dedicated for EIMs should be routinely included for all patients with IBD or just those who have specific symptoms, signs, or investigation results to warrant additional assessment. Fourth and linked to the previous point, the prognostic impact of subclinical EIMs identified on cross-sectional imaging remains unknown. For example, while it is plausible that active joint inflammation would associate with IBD and later outcomes, the associations with other EIMs such as those of the biliary tract may not be so clear.9 It is important to note that prior studies have demonstrated high levels of complicated disease on cross-sectional imaging even at diagnosis.10 In line with these previous findings, use of cross-sectional imaging earlier in the disease course may provide crucial information on both IBD phenotype and the presence of EIMs. Performing such a detailed initial assessment could help better guide management decisions, potentially reducing future disability and improving quality of life for patients. Maria Manuela Estevinho wrote the initial manuscript draft. Nurulamin M. Noor provided critical input. Maria Manuela Estevinho and Nurulamin M. Noor approved the final version of the manuscript. NMN is supported by the NIHR Cambridge Biomedical Research Centre (NIHR203312). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. NMN has received personal fees from BMS, Galapagos, Janssen, Lilly, SBK Healthcare, Takeda outside the submitted work and grants from Celltrion, Dr Falk, Pfizer, Pharmacosmos, Tillotts Pharma outside the submitted work. NIHR Cambridge Biomedical Research Centre, Grant/Award Number: NIHR203312 Data sharing is not applicable to this article as no new data were created or analyzed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».