Chapter 196 Imaging for Peripheral Nerve Disorders
Diffusion neurography and the closely related diffusion tensor tractographic technique were the first methods reported.1–3 These methods have extremely high selectivity for nerves and should be very sensitive to a variety of types of more subtle pathology. However, the technical demands necessary to perform diffusion neurography have delayed its clinical application.4–6 In addition, diffusion images tend to degrade in detail at locations of more severe pathology.
Diffusion and Diffusion Tensor Neurography Techniques
When a strong diffusion gradient is applied in the appropriate direction along with fat suppression and heavy T2 weighting, it is possible to produce a relatively pure nerve image. This is a method that has been applied to produce whole-body neurography images.7,8
For both peripheral and central nervous system (CNS) neural tissue, Filler and colleagues9–12 pointed out that it was possible to measure each voxel (three-dimensional pixel) in an image volume using three or more gradients in order to calculate both the magnitude and the direction in three-dimensional space of the anisotropy. These two data components could then be used to depict actual curving neural tracts rather than to simply display two-dimensional contrast differences in cross section. When six or more gradient directions are used, the vector processing can be accomplished using a tensor model and the result becomes very robust across any curve or angle of progression. Vector models are used with as many as 256 directions of data acquisition. The end result is to determine the orientation of the primary characteristic vectors (eigenvector in tensor models) in a voxel. This can be done to determine more than one axonal direction in a voxel (crossing fibers) when large numbers of acquisition directions are used in vector methods.
When diffusion images are obtained in multiple different directions for a DTI study, the raw diffusion images can be helpful for identifying the nerve. This step can be done using the original images because they suppress signal from vessels and other structures that are bright on T2-weighted fat-suppressed images, leading to relatively pure nerve images depending on the orientation of the nerve and the image at a given location. Unlike fully processed DTI images, the raw diffusion component images remain embedded in the original DICOM (Digital Imaging and Communications in Medicine) format spatial grid and can be precisely correlated with T2 neurographic images obtained in the same imaging session (Fig. 196-1).
FIGURE 196-1 Use of diffusion tensor image (DTI) data for nerve identification. This series of images demonstrates the use of diffusion-weighted components of a DTI acquisition (a-ii) for nerve identification in the same patient as in Figure 196-4. The asterisks track the L5 spinal nerve as it progresses through to the sciatic nerve (f to ii). The arrows track the L3 spinal nerve (left arrow) and L4 spinal nerve (right arrow) as they progress into the femoral nerve (a to f) and then mark the femoral nerve (f to ii). The arrowheads (g to ii) show the progress of the obturator nerve as it forms from anterior L4 and L5 branches then descends through the obturator foramen. The lines track the S2 contribution to the pudendal nerve (l to dd). Appropriately selected DTI component images contain relatively pure nerve images with very significant suppression of vessels and other structures that are bright on T2-weighted images. Note that the matched B0 (non-diffusion) component of the DTI acquisition obtained a few seconds earlier in the same patient shows numerous bright structures at the inguinal ligament that make identification of the femoral nerve and obturator nerve impossible without reference to the diffusion image.
T2-Based Neurography
Once the diffusion method was understood, it was possible to show that structures with long decay times (imaged at a relatively long echo time) in fat-suppressed spin-echo images were, in fact, nerves. Previously, nerves had been misinterpreted as exhibiting short decay times on T2 imaging.13 This was because nerves are a mixture of different tissues including protein-laden axoplasmic water, myelin, fatty interfascicular epineurium, and connective tissues. Older methods allowed the image signal from these various component tissues to mix. In a variety of different imaging techniques, the result of the image signal mixing was a featureless gray image of the nerve that left nerves difficult to distinguish clearly in an image and caused confusion about the fundamental imaging characteristics of nerve.
In a number of settings, MR neurography has proved to be more efficacious than electrodiagnostic studies for identifying nerve compressions that will improve with surgical treatment. This is true both in diagnoses that are typically evaluated by electrodiagnostics, such as carpal tunnel syndrome,14,15 and in diagnoses in which electrodiagnostics have proved difficult to rely on, such as thoracic outlet syndrome, piriformis syndrome, and related sciatic nerve entrapments and pudendal nerve entrapment syndromes.11,16–18
Utility of MR neurography has now been established in evaluation of entrapment syndromes,16,19–22 nerve injury and evaluation of repair,23 and assessment of nerve tumors,24–26 as well as in the setting of neuritis and a variety of neuropathies.27 It has also proved effective for evaluating nerve disorders affecting young pediatric patients such as obstetric brachial plexus palsy.28
Classes of Image Findings
Image findings in MR neurography studies include regions of nerve hyperintensity or nerve swelling, which result from edema at the fascicular level (Fig. 196-2). Distortions of normal nerve course, abnormal contours, and alterations of nerve caliber are also readily seen, any of which can be classed by the degree or severity of the abnormality. These findings can indicate entrapment or adhesions as well as post-traumatic effects.
In trauma, assessments of nerve continuity and/or location of severed nerve endings are feasible. With the elapse of time after injury or repair, the development of traumatic neuromas may be readily appreciated (Fig. 196-3).