@article{Xiong2026, 
author = {Ziman Xiong and Yufan Wang and Shuxin Luo and Zhen Li and Yaqi Shen},
title = {Precision Imaging for Optimized Crohn's Disease Management: Navigating the Evolution of Objective Healing Goals},
year = {2026},
journal = {iRADIOLOGY},
volume = {4},
number = {2},
pages = {113-126},
keywords = {artificial intelligence, Crohn's disease, disease management, multimodal imaging, transmural healing},
url = {https://www.sciopen.com/article/10.1002/ird3.70062},
doi = {10.1002/ird3.70062},
abstract = {As the management of Crohn's disease (CD) shifts from symptom control toward objective healing targets, the limitations of conventional assessments underscore the need for imaging to transcend detection and guide personalized therapy. Although endoscopy remains central for the evaluation of CD, its limitations in the assessment of submucosal lesions and penetrating complications necessitate advanced imaging solutions. Noninvasive multimodal imaging techniques, including computed tomography enterography, magnetic resonance enterography, and intestinal ultrasound, have emerged as indispensable tools in the management of CD. These modalities enable a comprehensive evaluation of transmural inflammation and extramural complications while also providing prognostic information to guide therapeutic decisions. This review focuses on the transformative role of multimodal imaging in the modern management landscape for CD. We discuss how imaging facilitates baseline risk stratification, quantification of transmural healing as a deep therapeutic endpoint, and differentiation of inflammatory from fibrotic strictures to guide medical versus surgical decision‐making. Furthermore, we examine the integration of artificial intelligence and body composition analysis, providing tools enabling personalized prognostication. By aligning imaging innovations with evolving clinical goals, we propose a clinically oriented framework for integrating imaging‐defined transmural healing into precision‐based CD management.}
}