The Pre-Surgical Planning of Brain Neoplasms: From Diffusion Tensor Imaging to More Advanced Approaches

Abstract

The pre-surgical planning of brain neoplasms is strongly contributing to change the
prognosis of neoplastic patients. Indeed, it supplies more and more detailed and reliable functional
and morphological information before as well as during surgery. Both invasive and noninvasive
approaches are available to achieve this goal. A powerful technique for the pre-surgical
planning of brain neoplasms is Diffusion Weighted Imaging (DWI) based tractography.
Differently from other approaches, tractography is able to provide, non-invasively, morphological
information regarding brain pathways relationship with the neoplasm, by analyzing
water diffusion within white matter. This is important especially for eloquent bundles, such as
Cortico-Spinal Tract (CST) and Arcuate Fasciculus (AF), whose damages have a bad impact on
the patient’s Quality of Life (QoL). Tractography can be performed through several diffusion
signal modeling techniques, among which Diffusion Tensor Imaging (DTI) is the most known.
DTI has been widely used for neurosurgery both in pre-operative and intra-operative contexts,
also in combination with other functional approaches such as functional MRI (fMRI) and cortical
stimulation.1-8 This useful technique was able to reduce post-surgical deficits as well as to
improve the survival of neoplastic patients, through a better delineation of maximal safe resection.
9 Moreover, its use provided great benefits in patients with high-grade gliomas in terms
of risk of death.9 Several studies have demonstrated that DTI suffers from many limitations
regarding its reliability to correctly model diffusion signal in different conditions.10,11 Furthermore,
tensorial models are not able to resolve different fibers geometries (i.e. crossing fibers)
within the same voxel; these complex configurations have been demonstrated to characterize
more than 90% of white matter voxels,12 thus making DTI an unreliable diffusion modeling
technique. In order to overcome these limitations, several other approaches were developed; in
particular, High Angular Resolution Diffusion-weighted Imaging (HARDI),13 Q-Ball Imaging
(QBI)14 and Diffusion Spectrum Imaging (DSI)15 were found to be promising techniques for
resolving voxels with multiple fibers orientations. Nevertheless, tractography was further improved
by an HARDI modified approach called Constrained Spherical Deconvolution (CSD);
this technique does not require very long acquisition time with respect to DSI16 and it is able to
improve angular resolution if compared to QBI.17 CSD-based tractography was widely used in
physiological contexts as well as in pathological ones, showing high sensitivity for the detection
of white matter pathways.18-22 Although tensorial approaches were proved to be inadequate
for reliably reconstructing brain pathways23 and histological validation of CSD-based tractography
has been recently provided,24 more advanced diffusion techniques are still considered
not usable in clinical settings due to their too high technical requirements.25 For these reasons,
DTI remains, to date, the most used technique for investigating white matter bundles, also for
the pre-surgical planning of brain neoplasms.26-28 In reality, as recently highlighted by Mormina
and colleagues,29 CSD-based tractography is feasible in clinical settings and it is able to provide
very useful information during the pre-surgical evaluation of eloquent bundles in patients
with high-grade gliomas. It was shown that DTI-based reconstructions can be affected also by
neoplasm’s effects on white matter bundles. Indeed, brain pathways might result dislocated,
disrupted and/or infiltrated by neoplasm,30 with simultaneous Fractional Anisotropy (FA) decrements; tensorial models are not able to distinguish among these different conditions, thus causing partial reconstructions or null
detection of bundles involved. Moreover, peritumoral edema surrounding high-grade gliomas is able to reduce FA values,31 causing,
also in this case, misleading fiber tracking. Mormina, et al.29 showed how CSD-based tractography is able to clearly define fiber
bundles involved by high-grade gliomas. Comparative qualitative analysis between CSD-based tractography and DTI-based one in
patients with high-grade gliomas is shown in Figures 1 and 2.