Abstract
The Multimodal Imaging in Uveitis (MUV) project is a comprehensive initiative aimed at developing guidelines for the use of multimodal imaging (MMI) in diagnosing and managing non-infectious posterior uveitis (NIPU). This project seeks to develop standardized guidelines and a minimal imaging set leading to evidence and consensus-based imaging guidelines that are applicable across diverse clinical settings. This manuscript describes the overall goals and methodology of the project.
The MUV project was structured into seven phases: (1) a global survey to assess current practices and the need for standardized MMI criteria, (2) study design planning to define research questions and establish expert committees, (3) systematic review of the literature, (4) evidence and consensus-building on imaging guidelines through the Nominal Group Technique (NGT), (5) agreement with proposed guidelines by task force and development of consensus statements for use of MMI in the diagnosis and monitoring of NIPU, (6) standardizing the endpoints of inflammation on imaging in NIPU and (7) prospective validation of MMI criteria, using formal consensus techniques, to achieve supermajority agreement.
The initial survey revealed that nearly 90% of uveitis and retina specialists already incorporate MMI into their diagnostic process for NIPU, with strong support for standardized practices. The NGT phase formulated and achieved statements on clinical utility of MMI, findings that were further substantiated by the systematic review. The final guidelines, proposed by the NGT and approved by the task force, offer a standardized framework for utilizing MMI in NIPU. This was a key aspect of this patient-focused update.
The MUV project introduces a formalized set of guidelines for MMI use in NIPU, enhancing and extending the Standardization of Uveitis Nomenclature (SUN) classification framework. The comprehensive guidelines developed through this initiative will standardize the use of MMI in clinical practice, which should lead to optimal use of imaging for more accurate diagnoses, better monitoring of disease activity, and improved management of complications.