Type:
Educational Exhibit
Keywords:
MR physics, Radiographers, MR, Education, Imaging sequences, Education and training
Authors:
P. A. Gutierrez, G. Dulcich, A. Soubielle, A. De Felippo, P. Puech, M. Pietrani
DOI:
10.26044/ecr2023/C-14718
Background
Despite recent Artificial Intelligence (AI) innovations that reduce acquisition time and improve image quality, there are many MRI artifacts that have to be detected and managed during acquisition.
Artifacts can be defined as any part of the image, which doesn't coincide with reality, generates noise, distorsion, or degrades image quality. They have a negative impact on the quality of interpretation and may have an impact on patient care.
They can be classified as a) Tissue, b) Movement, or c) Technical artifacts (table 1). They are numerous and multifactorial (magnet strength, objects in the room, faraday cage defect, body part, physiology and clinical state of the patient, etc...)
With the advent of teleradiology and increase of activity, radiologists tend to be less present besides technicians during acquisition. They need to identify these artifacts as quickly as possible, and give feedback to technicians who should not only prevent them, but detect, know the strategies to avoid or minimize them, and repeat corrected sequences if necessary.
Once an artifact is detected, internal or external factors must be identified to settle the most suitable strategy. In this work, we describe the most common types of artifacts, their appearance at MRI, their main causes, and potential actions available to reduce or avoid them. (fig 1)