Published online Sep 28, 2014. doi: 10.4329/wjr.v6.i9.716
Revised: July 13, 2014
Accepted: July 27, 2014
Published online: September 28, 2014
Recognition and characterization of central nervous system infections poses a formidable challenge to the neuro-radiologist. Imaging plays a vital role, the lesions typically being relatively inaccessible to tisue sampling. The results of an accurate diagnosis are endlessly rewarding, given the availability of excellent pharmacological regimen. The availability of numerous magnetic resonance (MR) sequences which provide functional and molecular information is a powerful tool in the hands of the radiologist. However, the plethora of sequences and the possibilities on each sequence is also intimidating, and often confusing as well as time consuming. While a large number of reviews have already described in detail the possible imaging findings in each infection, we intend to classify infections based on their imaging characteristics. In this review we describe an algorithm for first classifying the imaging findings into patterns based on basic MR sequences (T1, T2 and enhancement pattern with Gadolinium), and then sub-classify them based on more advanced molecular and functional sequences (Diffusion, Perfusion, Susceptibility imaging, MR Spectroscopy). This patterned approach is intended as a guide to radiologists in-training and in-practice for quickly narrowing their list of differentials when faced with a clinical challenge. The entire content of the article has also been summarised in the form of flow-charts for the purpose of quick reference.
Core tip: The plethora of magnetic resonance sequences available with the radiologist today provides a wealth of information about anatomical, pathological, physiological, functional and molecular aspects of the brain. While this provides an opportunity to transform patient management, the vast number of possibilities can be bewildering, particularly for the radiologist in-training. It is often easy to get lost in the details while forgetting the larger picture. In this article we first classify the infections into broad imaging patterns, and subsequently sub-classify them based on more advanced sequences (molecular and functional imaging). The flow-charts in the article are intended as a source of quick reference to the radiologist when faced with a clinical challenge.