• The factors causing problems in diffusion tensor imaging (DTI) tractography are specific to each tract and specific to each species, so transfer of results from other species to humans or from one tract to another cannot be relied upon.
• Conventional hodological techniques cannot be used in humans for ethical reasons, although they can validate tractography in other species.
• In human brains, comparison of blunt dissection of fixed human brains gives comparable results to DTI tractography where tracts are relatively uncomplicated, but both techniques run into similar difficulties where tracts intersect or run closely together.
• Electrical disruption of language produces a division of language pathways similar to DTI tractography and blunt dissection.
• Electromyography appears to identify a larger corticospinal tract than that with tractography, but this is almost certainly due to inadequate placement of the regions of interest used to generate the pathway and to the use of a high FA threshold.
• The somatotopic organization of corticostriatal hand, foot, and mouth pathways is different for functional MRI and DTI tractography; this is a difficult pathway fraught with problems caused by neighboring tracts.
• Pathways such as cerebellothalamic tracts, the occipitofrontal fasciculus, geniculate nuclei, and somatotopy in the internal capsule have been investigated, generally with positive results.
• In other species, Gd-DTPA contrast has been used to enhance the signal-to-noise ratio of DTI tractography in fixed primate brains; fiber reconstructions corresponded to known anatomy.
• Manganese-enhanced T1-weighted images have been used to compare the direction of a tract with the principle eigenvector of DTI tractography; the directions were largely parallel except where tracts crossed or terminated.
• Post-mortem tractography has been compared with in vivo injection of tracers and overlap functions of 0.58–0.98 were computed.
As we have already seen in this book, diffusion of water in white matter is rendered anisotropic by being hindered in directions perpendicular to fiber tracts (see Chapter 7 by Beaulieu for the biophysical underpinnings). The principal eigenvector of a tensor description of this anisotropy purports to identify axonal fiber tracts within the brain. The validity of this assumption can be tested directly in experimental animals using standard hodological techniques (hodology is the study of pathways).
A major problem in the validation of tractography in humans, however, is that there is no gold standard available. While gold standards are available in other animals, most of the invalidity of tractography derives from partial-volume and crossing-fiber issues (see Chapter 27 by Alexander and Seunarine and Chapter 28 by Tournier), which will be different for different tracts in the same species and different for the same tract in different species. Validation against a gold standard in one species, therefore, will have no implications for validation in another species, nor will validation of one tract carry any implications for validation of another tract. Furthermore, the human brain has developed some regions to a far greater extent than other species. This is particularly true for language pathways, for example, and for those areas that have expanded massively in the human brain, such as the prefrontal cortex and the temporal pole; in neither case will there be good animal models of the pathways involved.
Most hodological techniques used in neuroanatomy are concerned with determining which regions of the brain project to which other regions; they are much less concerned with the exact pathway taken. If principal eigenvectors are to be compared directly to histological specimens, however, further problems arise from the processes of fixation, dissection and sectioning, all of which cause a distortion of the tissue, tarnishing the “gold” of the standard. One solution to these dilemmas may be to use functional techniques to validate diffusion tensor imaging (DTI) tractography (Thiebaut de Schotten et al., 2005; Berman et al., 2007; Duffau, 2008). Electrical and magnetic stimulation, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) are examples of techniques that could be used as surrogate standards.
Studies in Humans: Direct Comparisons
Parker et al. (2001) used a fast marching tractography method to compare the optic radiation and corticopeduncular tracts with expectation in humans and macaques. Partial volume effects led to the inclusion of the anterior part of the occipitofrontal fasciculus and some spurious pathways with putative optic radiation in the macaque. This false-positive error was not evident in the human brain as a result of higher anatomical resolution in a bigger brain. Inspection of their Figure 6, however, reveals a substantial component of the putative optic radiation deviating to the dorsolateral surface instead of to the medial surface where it would be expected to end. This deviation suggests that the posterior part of the occipitofrontal fasciculus had been included after all. This underlies the need for validation: are these dorsolaterally terminating fibers a real component of the human optic radiation, or is this an error created by the close apposition of the occipitofrontal fasciculus?
Yoshiura et al. (2008) have used a three-dimensional directional diffusion function defined by a probability function of the local diffusion tensor to study the somatotopic organisation of the corticospinal tract within the posterior limb of the internal capsule. They refer to “cephalad to caudal” segments of the precentral gyrus, which appear to be dorsomedial and ventrolateral, respectively. These segments projected in a posterior-to-anterior distribution within the posterior limb of the internal capsule, but only in a proportion of patients. Although Yoshiura et al. claim that this corresponds to the known somatotopic organization of the corticospinal tract within the internal capsule, it is in reverse order to that given in standard neuroanatomical textbooks (Brodal, 1981; Nadeau et al., 2004). Given this discrepancy, the somatotopic organization found by them cannot be considered to validate their method. Oddly, the region in the precentral gyrus designated “caudal” contains the most cephalad part of the homunculus, whereas the region designated as “cephalad” contains the most caudal part of the homunculus present in the precentral gyrus. Perhaps their claim that their findings accord with the literature involves a misunderstanding along these lines.
Devlin et al. (2006) used probabilistic tractography to differentiate lateral from medial geniculate nuclei. They classified voxels from the diencephalic region based on a probability of connection exceeding 0.1%. A cross-correlation matrix of similarity between the connections of each voxel was then computed and voxels with high correlations forced to the diagonal. Clusters with high correlation were mapped back into anatomical space. The results identified both nuclei, which were displaced approximately one voxel from the locations given by high-resolution proton density weighted scanning optimized for subcortical gray–white contrast. Similar results were reported by Behrens et al. (2006) for differentiation of the supplementary motor area from pre-supplementary motor area. The DTI-based method was considerably faster in terms of acquisition times, a major issue if academic research is to be translated into clinical practice.
One approach to validation of tractography is to compare the results to dissection of formalin-fixed brains (Lawes et al., 2008). White matter can be teased apart with blunt dissection as sheets of axons have natural planes of cleavage parallel to the axons (see Chapter 3by Axer). Simple tracts in which axons remain parallel are easily dissected and correspond closely to the results of tractography. A dissection of the inferior occipitofrontal fasciculus corresponded closely to tractography obtained from the averaged DTI data from 15 male brains (Lawes et al., 2008) (see Fig. 26.1). Where the dissected tract curved, the tractography tract curved, and where the fibers changed direction, the direction-encoding color (DEC) assignment scheme of Pajevic and Pierpaoli (1999) showed a corresponding color.
Where the shape of the dissected tract changed, so too did the tractography-reconstructed tract (Fig. 26.1). As such, the similarities between the blunt dissection and the DTI reconstructions suggest that the fiber tractography accurately reconstructs the pathways of the inferior–occipital–frontal pathway. Appearances can be deceptive, however: where two tracts run closely together, both techniques run into similar difficulties (Fig. 26.1). The inferior occipitofrontal fasciculus runs alongside the lateral aspect of the optic radiation. In the dissection, some of the temporal fibers of the optic tract belonging to Meyer's loop came off with the occipitofrontal fasciculus. Interestingly, this same region of the optic tract shared voxels with the inferior occipitofrontal fasciculus and appeared in the DTI-reconstructed tract as well, in an identical location.
A novel tract between the temporal lobe and the occipital and parietal lobes, found only in the right hemisphere, was demonstrable in both the dissection and the tractography (Lawes et al., 2008). A fan-shaped tract between superior frontal gyrus and the pars triangularis of the inferior frontal gyrus also showed good correspondence between dissection and tractography, as far as the averaged DTI data set was concerned. An intersubject variability map was constructed, indicating differences and similarities between the individual brains. The intersubject variability map picked up a variable component that left the main tract on route to the pars triangularis and ascended to the middle frontal gyrus instead. Neither the dissection nor the tractography on the averaged DTI detected this variable component. Both dissection and tractography confirmed the posterior component of the arcuate fasciculus first described by Catani et al. (2005) and unpublished data confirmed the other components identified by the same authors as shown in Figure 26.2.
Lawes et al. (2008) showed that when using tractography to reconstruct lemniscal sensory pathways, one reconstructs a single ascending trajectory from the medulla, through the thalamus, all the way to the cortex. However, strictly speaking, the tracts should terminate in the thalamus, and then a second-order connection should continue from the thalamus to the cerebral cortex. Thus, while tractography has the advantage that the whole medulla–thalamus–cortex system is displayed, it has the disadvantage that the individual components are not differentiated. In many ways, tractography shares the same combination of advantages and disadvantages as hodological techniques that involve transneuronal transport of a tracer (see Chapter 3), i.e., such methods will also not exclusively reveal first-order connections, and will naturally reveal second-order connections. Hence, one has to think carefully about the characteristics of standard hodological techniques before using them as a tool to “validate” DTI tractography.
All these tracts demonstrate that where the anatomy is simple, with parallel axons and no shared voxels or crossing fibers, tractography gives a close representation of the anatomy. Where fiber tracts are at least comparable in size to the dimensions of voxels, tractography corresponds to fiber orientation (Lazar et al., 2003). This is typically the case with association fibers passing anteroposteriorly within one hemisphere, such as the occipitofrontal fasciculus.
Difficulties arise, however, where the anatomy is not simple. As we have described above, if tracts run closely together but in different directions, both tractography and blunt dissection are prone to errors easily detected with sufficient a priori knowledge. This was the case with Meyer's loop and the occipitofrontal fasciculus (Lawes et al., 2008). Electrophysiology and hodological techniques give good evidence that the hand and face regions of sensorimotor cortex have strong descending connections with the brainstem and spinal cord. There appears to be a lack of evidence in the literature for these connections to be displayed by blunt dissection, although motor pathway architecture has been demonstrated using quantitative cytoarchitectonic and myeloarchitectonic image analysis (Rademacher et al., 2001). Streamline tractography, based on a single tensor model, however, consistently fails to reveal these connections. One assumption is that other pathways running anteroposteriorly conceal the pathways. Where fibers with different orientations occupy the same voxel, directional information is corrupted (Wiegell et al., 2000; Alexander et al., 2001; see also Chapters 27 and 28 in this book). In regions where sheets of axons running in different directions are interleaved, streamline tractography on DTI data fails to give an accurate representation of the anatomy. Thus almost all connections to the brainstem are confounded by shared voxel and crossing-fiber problems (see Chapters 27 and 28). Although Lawes et al. (2008) were able to demonstrate parts of the conventional corticopontocerebellar pathways using simple streamline tractography, there were as many artifactual connections that did not decussate in the pons. Strong but erroneous ipsilateral corticocerebellar “tracts” were visible in the tractography. The corticopontine tracts merged with pontocerebellar tracts running ipsilaterally instead of contralaterally. Another decussating pathway, the dentatothalamic tract through the superior cerebellar peduncle, could not be displayed by streamline tractography using a single-tensor model (Lawes et al., 2008).
Studies in Humans: Indirect Comparisons
DTI tractography has been compared to known anatomical pathways without necessarily revisiting the anatomical data. In tractography, cumulative errors due to noise cause deviations from the actual pathway. This divergence depends on the shape of the tract, step size, voxel size, method of interpolation, and degree of anisotropy (Basser and Pajevic, 2000; see also Chapter 22 by Alexander). Chen et al. (2006) developed a multipass approach to fiber tracking to minimize the cumulative effect of noise. Fiber tracking is initiated from a region of interest (ROI) and followed until a region of ambiguity is reached. Semi-random directions of tracking are generated until the fiber tract meets stopping criteria or a second designated ROI. This is done in both directions. Fiber tracts are merged, the center line is computed, and fiber tracking is then guided by this center line. Cerebellothalamic tracts were successfully reconstructed using this approach, despite the crossing of axons in the midbrain. Chen et al. warned that this method can generate false tracts, so a priori knowledge of the existence of valid tracts is required. Despite the deficiencies of the single-tensor model of streamline tractography, other methods are capable of producing results consistent with known anatomy.
Another example of comparison to known anatomical pathways without necessarily revisiting the anatomical data concerns the anterior parts of the fornix and the medial parts of the anterior commissure; the anatomy of this region can be obtained from routine dissections. This region provides a clear example of where tractography failed to display known anatomy. Postcommissural fibers between the hippocampus and the mamillary bodies are visible in Figure 26.3 from Lawes et al. (2008), but an artifactual component ran on into the amygdala. This was almost certainly a part of the anterior commissure that blended into the fornix. No precomissural fibers could be detected. More strikingly, the anterior commissure could be traced from periamygdaloid regions toward the midline but did not cross it, disappearing at precisely the location of the missing precomissural fornix. This may depend on exactly where the image plane intersects the anterior commissure, as Catani et al. (2002) obtained a more complete image. Clearly, these two tracts shared the same voxels and thereby corrupted the tractography.
Where a tract branches or merges with another, or where two tracts approach each other then diverge, the direction of the principle eigenvector no longer represents the direction of the tracts (see Chapters 27 and 28). If a tract shares a voxel with cerebrospinal fluid (CSF) or gray matter, the FA may drop below the threshold required to continue tracking. Areas where tracts take a highly curved course will also cause problems, particularly if an angle threshold has been artificially imposed. Intersubject agreement is often mistaken for validation. Intersubject agreement may indicate consistency in production of an artifactual tract and cannot be taken as evidence of validity of the putative tract.
Studies in Humans: Comparison with Functional Techniques
Staempfli et al. (2008) used fMRI to verify DTI-based tractography of connections between motor cortex and putamen. Subjects were asked to flex and extend fingers and toes, and elevate the corner of the mouth. An advanced fast marching algorithm was used to generate tracts and a likelihood index was derived to estimate the probability of a connection. The fMRI results depicted an anteroinferior-to-posterosuperior somatotopic organization, with the face anteroinferiorly, the foot posterosuperiorly, and the hand in between. Tractography, however, showed a different pattern: the face and hand preserved the same relative, though displaced, location as in the fMRI data, but the foot area clearly moved inferiorly and foot-related voxels were present both anteriorly and posteriorly. Only 14.3% of hand voxels and 6.3% of face voxels shared fMRI and DTI somatotopy. As the authors deliberately chose a pathway that has several other pathways passing close by, the discrepancies are not surprising. The approach is clearly promising, despite the difficulties encountered.
Kinoshita et al. (2005) compared the size of “pyramidal” tracts in two subjects with the area from which electrical excitation of tracts evoked electromyographic responses during operations to remove tumors. After removal of tumor in one subject, including areas from which motor evoked responses could be elicited by electrical stimulation but which were outside the tracts displayed by DTI, the patient's left hemiparesis was worse. Inspection of their Figures 3 and 4, however, suggests that the “pyramidal” tracts identified by their DTI procedure were unusually narrow.
There are no specific data on where they placed their ROIs, apart from the comment that they were in motor cortex. As only a small proportion of the “pyramidal” tract originates in motor cortex, it is not surprising that DTI based on an ROI in motor cortex underestimated the extent of the tract. Typical estimates of the origin of the corticospinal tract (a.k.a. the “pyramidal” tract) are 22%–31% from BA4 (motor cortex), 29% from BA6 (premotor cortex), and 40%–79% from BA3, 1, 2, 5, 7 (sensory cortex and superior parietal lobule). A significant part of the corticospinal tract originates on the medial surface of the cerebral hemispheres, from paracentral lobule, premotor cortex, and supplementary motor cortex, so it would be a mistake to restrict an ROI to the precentral gyrus. It would appear that the problem may not be so much the failure of DTI to delineate the full extent of the tract as the placement of ROIs based on a limited view of the anatomy of the corticospinal system. A more realistic representation of the extent of the corticospinal system delineated by DTI is shown in Figure 10iii in Lawes et al. (2008). A valid comment made by Kinoshita et al. is that the contribution to the “pyramidal” tract made by fibers passing through the centrum semiovale from more lateral cortical regions is usually not visible in DTI tractography. The decision to terminate tracking when the FA dropped below 0.3 may also have excluded a significant proportion of the tracts.
Duffau (2008) reviewed comparisons of intraoperative electrostimulation of subcortical language pathways to DTI tractography. Electrostimulation of the inferior occipitofrontal fasciculus delineated by Catani et al. (2002) induced errors concerning the meaning of words, or semantic paraphasias. Electrostimulation of the arcuate fasciculus, delineated in tractography by Catani et al. (2005), induced errors in the phonological form of words, or phonemic paraphasias. Combined electrostimulation of the anterior perisylvian language area and an electrocorticogram of the posterior language area confirmed that this connection is bidirectional (Matsumoto et al., 2004). The posterior limb of the indirect component of the arcuate fasciculus (Catani et al., 2005) connecting temporal cortex with the inferior parietal lobule was implicated in syllable discrimination and identification (Parker et al., 2005). Electrostimulation of the anterior component of this pathway connecting the inferior parietal lobule with Broca's area produced articulatory disorders, including complete anarthria. In short, a partitioning of the arcuate fasciculus into direct and anterior and posterior indirect components on the basis of DTI tractography corresponds closely to a functional subdivision based on intraoperative electrostimulation. This is perhaps the strongest validation currently available in human brains.
Duffau (2008) also reviewed the corticostriatal control stream of the subcallosal fasciculus. The subcallosal fasciculus was delineated with DTI tractography by Catani at el. (2002) and intraoperative electrostimulation of it induced a motor aphasia of spontaneous speech, leaving repetition intact (Duffau et al., 2002). Electrostimulation of the head of the caudate induced perseveration of the previous test item instead of the current item. Electrostimulation and DTI tractography concurred in tracing pathways from the lower motor area medially, bifurcating before a sharp turn into the “pyramidal” tract (presumably corticobulbar tract) and cerebral peduncle (Henry et al., 2004).
Studies in Other Species
A major problem with diffusion tensor imaging is the time necessary to acquire high-resolution images. With fixed brains, time is no longer a problem, so if tractography can be applied to fixed brains, many of the problems associated with large voxels can be circumvented.
D’Arceuil et al. (2007) investigated conditions affecting the use of Gd-DTPA contrast to optimize the signal-to-noise ratio of diffusion tensor imaging scans of formalin-fixed primate brains. They found that diffusion anisotropy was preserved after tissue fixation. Fractional anisotropy was slightly elevated in white matter but the apparent diffusion coefficient values were greatly decreased, an effect partly attributed to tissue death and reduced temperature. They confirmed that there was significant diffusion anisotropy in cortical gray matter (see Chapter 39 by D’Arceuil and De Crespigny for more details). Fiber reconstructions seeded from the forceps major, forceps minor, and posterior limb of the internal capsule of one hemisphere were compared with high-resolution FLASH scans and were apparently consistent with known anatomy (Fig. 26.4). One slightly puzzling comment indicated that tracts from the posterior limb of the internal capsule coursed through the thalamus and medullary pyramids. There is no known tract that does this, so perhaps they were referring to two separate tracts, one passing through the thalamus and a separate one passing through the medullary pyramids.
Lin et al., (2001) used manganese-enhanced T1-weighted images as a gold standard for estimating of DTI tractography. Manganese chloride was injected into the vitreous humor of the eye and the rats were scanned 10 hours later. The deviation between principal diffusion eigenvectors and tangents to the manganese-enhanced images was calculated. Figure 26.5 shows the methods used to determine the tract orientation from the manganese-enhanced MRI. Comparison of the manganese-enhanced MRI and eigenvector map derived from DTI data is shown Figure 26.6. Except at the optic chiasma and the lateral geniculate nucleus, the directions were largely parallel. The rms deviation was 13.27°, 5.11° attributed to the manganese-enhanced T1-weighted images and 12.25° to DTI tractography. Lin et al. chose a pathway where technical considerations were optimal, in contrast to Staempfli et al. (2008), for example, who investigated the more challenging pathway between motor cortex and putamen. Thus Lin et al. were concerned with whether the principal eigenvector accurately predicted the direction of a tract or not, rather than with the validity of tractography in situations where crossing fibers, partial volumes, and kissing and other factors had a potentially negative impact. Lin et al. give several reasons why the technique would not be applicable to longer pathways requiring greater transport times, one being that the manganese enhancement fades after 48 hours.
Dyrby et al. (2007) compared postmortem multifiber probabilistic tractography to in vivo injection of tracers in the gyrencephalic minipig brain. Biotinylated dextran amine and manganese chloride were injected into three pig brains. They were scanned 2 days before and after injection (see Fig. 26.7) then sacrificed 2 weeks later. After perfusion with paraformaldehyde, the brains were postfixed in paraformaldehyde then scanned again and processed histochemically. An overlap function compared termination sites obtained by tractography with those obtained with manganese chloride–enhanced MRI. Connections between somatosensory cortex and cortical, thalamic, and nigral sites produced overlap functions ranging from 0.63 to 0.93. Connections between prefrontal cortex and cortical, thalamic, and nigral sites produced overlap functions ranging from 0.58 to 0.98, although one brain lacked any thalamic connection demonstrated by tractography. Connections between motor cortex and cortical and nigral sites produced overlap functions ranging from 0.59 to 0.89, although a different brain lacked any thalamic connection demonstrated by tractography. The biotinylated dextran amine results were discrete, in line with standard hodological techniques. The tracts obtained with manganese chloride, by contrast, appeared to show evidence of considerable diffusion out of recognized axonal pathways into the surrounding extracellular fluid. It is unclear, therefore, whether the lower overlap functions represent an issue with tractography or one with manganese chloride–enhanced MRI. Nevertheless, the two techniques gave broadly comparable results.
In conclusion, many attempts have been made to validate diffusion tensor imaging and tractography. Comparison of tractography with conventional hodological methods in experimental animals will ultimately become the gold standard, but only for the specific tracts investigated in the particular species studied. The precise anatomical relationships between any tract and its confounding factors will differ from tract to tract and from species to species, rendering a universal gold standard an unattainable goal. Conventional hodological techniques are, of course, inapplicable to humans.
Use of functional techniques in humans offers a more realistic approach. Functional MRI has its own limitations, but offers one potential avenue. Intraoperative electrostimulation is also a powerful strategy but relies on the pathway being sufficiently eloquent to be tested in an operative setting. The study of language is particularly relevant in this context, as no other species has the same capacity.
Ultimately, higher-quality imaging data in terms of both resolution and signal-to-noise ratio together with improved descriptions of complex fiber architecture including crossing and kissing fibers will render much of the current difficulties and their prohibitively expensive solutions obsolete. Despite this requirement, significant progress has been made in the quest to validate DTI and tractography. These techniques now represent the primary modality for investigation of connectivity in the living human brain.
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