RadioGraphics Update: Functional MR Neurography in Evaluation of Peripheral Nerve Trauma and Postsurgical Assessment

An Updated Review of Magnetic Resonance Neurography for Plexus Imaging

Magnetic resonance neurography (MRN) is increasingly used to visualize peripheral nerves in vivo. However, the implementation and interpretation of MRN in the brachial and lumbosacral plexi are challenging because of the anatomical complexity and technical limitations. The purpose of this article was to review the clinical context of MRN, describe advanced magnetic resonance (MR) techniques for plexus imaging, and list the general categories of utility of MRN with pertinent imaging examples. The selection and optimization of MR sequences are centered on the homogeneous suppression of fat and blood vessels while enhancing the visibility of the plexus and its branches. Standard 2D fast spin-echo sequences are essential to assess morphology and signal intensity of nerves. Moreover, nerve-selective 3D isotropic images allow improved visualization of nerves and multiplanar reconstruction along their course. Diffusion-weighted and diffusion-tensor images offer microscopic and functional insights into peripheral nerves. The interpretation of MRN in the brachial and lumbosacral plexi should be based on a thorough understanding of their anatomy and pathophysiology. Anatomical landmarks assist in identifying brachial and lumbosacral plexus components of interest. Thus, understanding the varying patterns of nerve abnormalities facilitates the interpretation of aberrant findings.

Traumatic peripheral nerve injuries: a classification proposal

BACKGROUND

Peripheral nerve injuries (PNIs) include several conditions in which one or more peripheral nerves are damaged. Trauma is one of the most common causes of PNIs and young people are particularly affected. They have a significant impact on patients' quality of life and on the healthcare system, while timing and type of surgical treatment are of the utmost importance to guarantee the most favorable functional recovery. To date, several different classifications of PNIs have been proposed, most of them focusing on just one or few aspects of these complex conditions, such as type of injury, anatomic situation, or prognostic factors. Current classifications do not enable us to have a complete view of this pathology, which includes diagnosis, treatment choice, and possible outcomes. This fragmentation sometimes leads to an ambiguous definition of PNIs and the impossibility of exchanging crucial information between different physicians and healthcare structures, which can create confusion in the choice of therapeutic strategies and timing of surgery.

MATERIALS

The authors retrospectively analyzed a group of 24 patients treated in their center and applied a new classification for PNI injuries. They chose (a) five injury-related factors, namely nerve involved, lesion site, nerve type (whether motor, sensory or mixed), surrounding tissues (whether soft tissues were involved or not), and lesion type-whether partial/in continuity or complete. An alphanumeric code was applied to each of these classes, and (b) four prognostic codes, related to age, timing, techniques, and comorbidities.

RESULTS

An alphanumeric code was produced, similar to that used in the AO classification of fractures.

CONCLUSIONS

The authors propose this novel classification for PNIs, with the main advantage to allow physicians to easily understand the characteristics of nerve lesions, severity, possibility of spontaneous recovery, onset of early complications, need for surgical treatment, and the best surgical approach.

LEVEL OF EVIDENCE

according to the Oxford 2011 level of evidence, level 2.

A handbook for beginners in skeletal muscle diffusion tensor imaging: physical basis and technical adjustments

Magnetic resonance imaging (MRI) of skeletal muscle is routinely performed using morphological sequences to acquire anatomical information. Recently, there is an increasing interest in applying advanced MRI techniques that provide pathophysiologic information for skeletal muscle evaluation to complement standard morphologic information. Among these advanced techniques, diffusion tensor imaging (DTI) has emerged as a potential tool to explore muscle microstructure. DTI can noninvasively assess the movement of water molecules in well-organized tissues with anisotropic diffusion, such as skeletal muscle. The acquisition of DTI studies for skeletal muscle assessment requires specific technical adjustments. Besides, knowledge of DTI physical basis and skeletal muscle physiopathology facilitates the evaluation of this advanced sequence and both image and parameter interpretation. Parameters derived from DTI provide a quantitative assessment of muscle microstructure with potential to become imaging biomarkers of normal and pathological skeletal muscle. KEY POINTS: • Diffusion tensor imaging (DTI) allows to evaluate the three-dimensional movement of water molecules inside biological tissues. • The skeletal muscle structure makes it suitable for being evaluated with DTI. • Several technical adjustments have to be considered for obtaining robust and reproducible DTI studies for skeletal muscle assessment, minimizing potential artifacts.

Technical Update on MR Neurography

Imaging evaluation of peripheral nerves (PNs) is challenging. Magnetic resonance imaging (MRI) and ultrasonography are the modalities of choice in the imaging assessment of PNs. Both conventional MRI pulse sequences and advanced techniques have important roles. Routine MR sequences are the workhorse, with the main goal to provide superb anatomical definition and identify focal or diffuse nerve T2 signal abnormalities. Selective techniques, such as three-dimensional (3D) cranial nerve imaging (CRANI) or 3D NerveVIEW, allow for a more detailed evaluation of normal and pathologic states. These conventional pulse sequences have a limited role in the comprehensive assessment of pathophysiologic and ultrastructural abnormalities of PNs. Advanced functional MR neurography sequences, such as diffusion tensor imaging tractography or T2 mapping, provide useful and robust quantitative parameters that can be useful in the assessment of PNs on a microscopic level. This article offers an overview of various technical parameters, pulse sequences, and protocols available in the imaging of PNs and provides tips on avoiding potential pitfalls.

New insights into the evaluation of peripheral nerves lesions: a survival guide for beginners

PURPOSE

To perform a review of the physical basis of DTI and DCE-MRI applied to Peripheral Nerves (PNs) evaluation with the aim of providing readers the main concepts and tools to acquire these types of sequences for PNs assessment. The potential added value of these advanced techniques for pre-and post-surgical PN assessment is also reviewed in diverse clinical scenarios. Finally, a brief introduction to the promising applications of Artificial Intelligence (AI) for PNs evaluation is presented.

METHODS

We review the existing literature and analyze the latest evidence regarding DTI, DCE-MRI and AI for PNs assessment. This review is focused on a practical approach to these advanced sequences providing tips and tricks for implementing them into real clinical practice focused on imaging postprocessing and their current clinical applicability. A summary of the potential applications of AI algorithms for PNs assessment is also included.

RESULTS

DTI, successfully used in central nervous system, can also be applied for PNs assessment. DCE-MRI can help evaluate PN's vascularization and integrity of Blood Nerve Barrier beyond the conventional gadolinium-enhanced MRI sequences approach. Both approaches have been tested for PN assessment including pre- and post-surgical evaluation of PNs and tumoral conditions. AI algorithms may help radiologists for PN detection, segmentation and characterization with promising initial results.

CONCLUSION

DTI, DCE-MRI are feasible tools for the assessment of PN lesions. This manuscript emphasizes the technical adjustments necessary to acquire and post-process these images. AI algorithms can also be considered as an alternative and promising choice for PN evaluation with promising results.