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Brain Fiber Tracking with Clinically Feasible Diffusion-Tensor MR Imaging: Initial Experience¹

¹ From the Departments of Radiology (K.Y., O.K., H.I., H.N., S.Y., T.K., O.T., W.A., T.N.) and Neurosurgery (H.S., K.M.), Kyoto Prefectural University of Medicine, Kajii-cyo, Kawaramachi Hirokoji Sagaru, Kamigyo-ku, Kyoto City, Kyoto 602-8566, Japan; and Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Md (S.M.). Received April 1, 2002; revision requested June 13; revision received June 20; accepted August 8. Address correspondence to K.Y. (e-mail: kyamada@koto.kpu-m.ac.jp).

	ABSTRACT

TOP ABSTRACT INTRODUCTION Materials and Methods Results Discussion REFERENCES

 
Two technical challenges must be overcome before brain fiber tracking with diffusion-tensor magnetic resonance (MR) imaging can be applied to clinical practice: Imaging time must be shortened, and image distortion must be minimized. Single-shot echo-planar MR imaging with parallel imaging technique enabled both objectives to be accomplished. Twenty-three consecutive patients with brain tumors underwent MR imaging with a 1.5-T whole-body MR system. Fiber tracts on the lesion side in the brain had varying degrees of displacement or disruption as a result of the tumor. Tract disruption resulted from direct tumor involvement, compression on the tract, and vasogenic edema surrounding the tumor. This diffusion-tensor MR imaging method with the parallel imaging technique allows clinically feasible brain fiber tracking.

© RSNA, 2003

Index terms: Brainstem, MR, 15.121416 • Brainstem, neoplasms, 15.30 • Diffusion tensor, 15.121416 • Magnetic resonance (MR), diffusion tensor, 15.121416

	INTRODUCTION

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Magnetic resonance (MR) imaging techniques have affected visualization of the anatomic contexts of disease processes. Advances in fast MR imaging with echo-planar techniques have enabled observation of the functional aspect of brain tissues (1,2). Diffusion-tensor MR imaging allows visualization of the anisotropy (directionality) of water movement caused by the presence of axons, axonal sheaths, glia cells, and vasculature (3).

The tensors can be reconstructed to track three-dimensional macroscopic fiber orientation in the brain. This method is known as fiber tracking or axonal tracking (4–7). This method is currently the only way to observe neuronal pathways in the living human brain. These pathways have been documented in experimental animals (8–11) and postmortem human brains, but with diffusion-tensor MR imaging, these pathways can be visualized in vivo. One drawback of this method is the duration of the examination (typically more than 30 minutes [7]), during which subjects have to refrain from moving even a few millimeters. Image acquisition is lengthy because the signal-to-noise ratio of the source diffusion-tensor MR image has to be high, and image distortion must be within the acceptable range. To obtain a sufficiently high signal-to-noise ratio, image averaging over 10 times has been used (6,7); to reduce image distortion, multishot echo-planar MR imaging with cardiac gating is used instead of single-shot echo-planar MR imaging (6).

The long examination time for diffusion-tensor MR imaging has been the largest obstacle to clinical application, and a method that reduces imaging time is desirable. We implemented single-shot echo-planar MR imaging with parallel imaging technique to overcome these technical difficulties. With the parallel imaging technique, the number of phase-encoding steps required to reconstruct the images is decreased (12–15), which reduces the readout length for data acquisition and substantially reduces image distortion. The purpose of our study was to evaluate the feasibility of diffusion-tensor MR imaging with a parallel imaging technique to detect sensorimotor pathways in patients with brain tumors.

	Materials and Methods

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Patient Population
From August 2001 to February 2002, diffusion-tensor MR images were obtained in 23 consecutive patients (15 male and eight female patients; age range, 5–92 years; mean age, 57.4 years) who were undergoing presurgical evaluation of brain tumors. Institutional review board approval was obtained for the study. All examinations were performed after written informed consent was obtained from the patients or their next of kin. Patient data are summarized in Table 1. Ten of the 23 patients underwent follow-up MR imaging that enabled pre- and postsurgical results with fiber tracking to be compared.

The 128 x 37 data points were recorded by using the parallel imaging technique (12–15). The reduction factor was 2 for this technique, which allows image reconstruction with half the encoding steps. Thus, the true resolution of the images is equivalent to 128 x 74 pixels. The data were zero filled to a final resolution of 256 x 256 pixels. Thirty-six sections were obtained with a thickness of 3 mm, without intersection gaps. The field of view was 230 x 230 mm; thus, the size of a voxel was 0.9 x 0.9 x 3.0 mm. Total time for diffusion-tensor MR imaging was 4 minutes 24 seconds. All of these diffusion-tensor MR images were acquired at the end of the routine examination for the evaluation of brain tumors, which included T1-, T2-, and T2*-weighted MR imaging; fluid-attenuated inversion-recovery, or FLAIR, MR imaging; and contrast material–enhanced (gadopentetate dimeglumine, Magnevist; Nihon Schering, Osaka, Japan) T1-weighted MR imaging in three orthogonal directions. Diffusion-tensor MR imaging was not performed as a separate examination.

All diffusion-tensor MR examinations were performed successfully, and no image distortions characteristic of single-shot echo-planar MR imaging were seen. Minor image distortion was noted near the mastoid air cells and sphenoid sinus, but it did not interfere with visualization of the brainstem on the fiber-tracking images. Slight signal intensity loss due to susceptibility effects was noted at the posterior fossa in patients 1 and 2, although this did not hamper the data processing. Slight head rotation occurred in patient 9 during MR imaging, which resulted in only subtle misregistration, and data processing was successful.

Data Processing
Diffusion-tensor MR imaging data were transferred to an off-line workstation (Precision 530; Dell, Round Rock, Texas) for analysis. Images were realigned by means of an automated image registration program (16) to correct any motion artifacts or image distortion. Diffusion-tensor elements and anisotropy at each voxel were then calculated. Diffusion-tensor elements were determined by means of multivariate least squares fitting weighted by signal-to-noise ratio (17–19). Anisotropy maps were obtained by means of orientation-independent fractional anisotropy (20). Color maps based on diffusion-tensor MR images were created from these data for the vector in the longest axis (v₁). Vector elements were assigned to red (x element, left to right), green (y element, anteroposterior), and blue (z element, superoinferior) (21,22). The intensities of the maps were scaled in proportion to the fractional anisotropy. Image postprocessing was performed by one author (K.Y.).

Fiber Tracking
Water-diffusion anisotropy is defined on the basis of the alignment of axons. Water diffusion is restricted in the direction perpendicular to the axons, and water diffuses preferentially in a direction parallel to them. This condition can be represented mathematically by the so-called diffusion ellipsoid, which is characterized by diffusion constants ₁, ₂, and ₃ along the three orthogonal directions and the (vector) direction of the longest axis (v₁). The tensors obtained from the diffusion-weighted MR images were diagonalized to obtain the eigenvalues ₁, ₂, and ₃. The eigenvector (v₁) associated with the largest eigenvalue (₁) was assumed to represent the local fiber direction. Translation of the vectors into neural trajectories is achieved by means of postprocessing of diffusion-tensor data by using a previously described method (4,5,23).

The procedure for mapping of neural connections was started by designating two arbitrary regions of interest (ROIs) in the three-dimensional space. The extent of the axonal projections was traced from these seed pixels within the ROIs in both the anterograde (forward) and retrograde (backward) directions. Tracking was terminated (stop criterion) when a pixel with low fractional anisotropy or a predetermined trajectory curvature between two contiguous vectors was reached. Fiber tracts that passed through both ROIs were determined to be the final tract of interest. The size of the ROIs ranged from 48 to 160 voxels.

Data Validation
ROI placement for fiber tracking was performed at two levels of the brainstem (Fig 1). The fiber tracts that were traced included the corticospinal tract, corticopontine tract, and the sensory pathway. Two ROIs were placed at the brainstem for the fiber tracking, one at the level of the pons and the other at the level of the cerebral peduncle. When tracking failed with these ROI settings, the two ROIs were placed at the midbrain and internal capsule for motor tracts and the thalamus and internal capsule for sensory tracts. All the ROIs were placed by two authors (K.Y., O.K.), with consensus. Results were validated in the brain on both the normal side and the side with the lesion. The fiber-tracking results were validated by assessing the presence or absence of the fiber tracts at expected anatomic locations. The cause of disruption was assessed for tracts that appeared disrupted. These assessments were performed by the same authors, with consensus.

View larger version (74K): [in this window] [in a new window] [Download PPT slide]   Figure 1. ROIs for tracking the corticospinal tract (CST), corticopontine tract (CPT), and sensory tract. The first ROI (ROI-1) was placed at the superior level of the ventral pons. The second ROI (ROI-2) was placed at the level of the cerebral peduncle. The most medial and lateral ROIs correspond to corticopontine tracts. The medial corticopontine tract represents the frontopontine tract, and the lateral corticopontine tract represents the temporo-parieto-occipitopontine tract (TPOPT). The corticospinal tract is located between these tracts, and we arbitrarily divided it into two ROIs. The ROIs for the sensory tracts were chosen from the area that corresponded to the medial lemniscus and spinal lemniscus. All ROI placements were performed in transverse planes.

	Results

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View larger version (146K): [in this window] [in a new window] [Download PPT slide]   Figure 2. Patient 8. Bronchogenic large cell carcinoma in a 48-year-old man who presented with left arm weakness. Color-coded vector maps calculated from diffusion-tensor MR image (top left) and transverse conventional T2-weighted MR image (top right) reveal a mass in the right frontal lobe that is surrounded by vasogenic edema. Presurgical fiber-tracking results overlaid on the T2-weighted MR image depicted the locations of sensory (green), motor (red), and corticopontine (brown) tracts. Motor tracts on the right side were deviated slightly laterally compared with those on the contralateral side. Bottom left: Sagittal reconstruction image depicts termination of the tracts within the vasogenic edema. The patient underwent successful resection of the mass from a right frontal approach, with full recovery of motor function after surgery. Bottom right: Postoperative fiber-tracking image confirms the well-preserved fiber tracts. Motor tracts appear to have shifted back to a more medial position.

View larger version (44K): [in this window] [in a new window] [Download PPT slide]   Figure 3. Patient 15. Seizures in a 57-year-old woman. Left: Transverse diffusion-weighted MR image that was the source image for fiber tracking shows a left frontal lesion with substantial mass effect. Hypointensity of the central cystic component ruled out the possibility of brain abscess. Middle: Fiber-tracking results superimposed on transverse T2-weighted MR image show the motor tract (red) on the lesion side to be deviated toward the dorsal aspect. Left sensory tract was not depicted, which was assumed to be a result of remote mass effect. Sensory (green), motor (red), and corticopontine (brown) tracts on the contralateral side are depicted in normal locations. The patient underwent subtotal resection of this mass, which revealed glioblastoma multiforme. Right: Follow-up fiber-tracking MR image shows shift of the fiber tracts toward the rostral aspect. Left sensory tract (green) is clearly depicted posteromedially to the motor tract (red).

View larger version (55K): [in this window] [in a new window] [Download PPT slide]   Figure 4. Patient 16. Bronchogenic carcinoma in a 64-year-old man who presented with progressive motor aphasia and weakness in the right upper and lower extremities. Transverse contrast-enhanced T1-weighted (left) and T2-weighted (middle) MR images reveal a large mass in the left frontal lobe, with cystic degeneration and wall enhancement. Incidental meningioma is noted medial to this mass. Middle: Fiber-tracking MR image depicts the sensorimotor pathways, which deviated posteromedially to the mass. Since these tracts were in proximity to the mass, we suggested use of a careful approach to the posteromedial wall of the mass. Sensory (green), motor (red), and corticopontine (brown) tracts on the contralateral side are depicted in normal locations. Right: Follow-up fiber-tracking MR image obtained after subtotal resection of the tumor clearly depicts the well-preserved sensorimotor pathway dorsal to the surgical cavity. The patient experienced dramatic improvement in motor symptoms soon after surgery.

	Discussion

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With our MR imaging method, a reasonable estimation of location the major fiber tracts can be obtained with an imaging time of less than 5 minutes, which we believe is a clinically feasible time frame. Acquisition of high-quality diffusion-weighted MR images is essential for this method because the images must have a sufficient signal-to-noise ratio and a minimal degree of geometric distortion. We increased the number of images averaged to six to achieve a sufficiently high signal-to-noise ratio.

Reduction of image distortion is a greater challenge. Image distortion in diffusion-weighted MR images arises from magnetic field heterogeneity and large motion-probing gradients. Image distortion at the skull base and posterior fossa can be especially troublesome in a conventional echo-planar MR imaging sequence. These artifacts may affect images of the brainstem, a critical location for placement of the seed points.

Multishot echo-planar MR imaging can be used to reduce image distortion. This method, however, must be performed with cardiac gating to avoid echo artifacts on images obtained during the systolic phase, which may contain substantial phase error. Cardiac gating limits the number of echoes acquired but remarkably prolongs the imaging time. Therefore, instead of performing multishot echo-planar MR imaging, we chose to apply the parallel imaging technique to avoid geometric distortion.

There are two major classes of parallel acquisition techniques: simultaneous acquisition of spatial harmonics and sensitivity encoding. Simultaneous acquisition of spatial harmonics is accomplished with parallel acquisition of the data in k space (24), whereas sensitivity encoding is a method that involves unfolding of the Fourier-transformed MR images. The coils are arranged in a linear fashion, and the method is commonly used for cardiac imaging by placing an array of coils at the anterior chest wall. Sensitivity encoding is independent of coil orientation, a benefit for neuroimaging, in which it is ideal to have the coils arranged in a circular fashion around the brain.

Sensitivity encoding permits the unfolding of MR images with reduced field of view into MR images with full field of view. The reduction in the number of phase-encoding steps is compensated for with spatial encoding based on the location of a signal. For sequences other than that for echo-planar MR imaging, this technique has been used either to multiply the speed of existing imaging sequences or to increase the spatial resolution without increasing the imaging time (12). For the echo-planar MR imaging sequence, however, the reduction in the number of phase-encoding steps will not lead to a reduction in imaging acquisition time because data are obtained with one signal acquired. Instead, the reduction of phase-encoding steps will lead to a reduction in the readout length for data acquisition, which will result in a major reduction in image distortion.

Although sensitivity encoding is a powerful tool for reducing the image distortion of echo-planar MR imaging sequences, a few drawbacks should be mentioned. First, sensitivity-encoding echo-planar MR imaging will result in a reduction in the signal-to-noise ratio (12). The loss of signal-to-noise ratio is at least equivalent to the square root of the reduction in acquisition time. The signal-to-noise ratio in the reconstructed images is the following: SNR_SENSE = SNR_full/gR, where SENSE is sensitivity encoding; g is the geometry factor, which describes the constructive interaction of noise coming from the elements of the phased-array coil; and R is the reduction factor for the field of view. In an ideal condition, g is nearly equal to 1. Another limitation of the sensitivity-encoding technique is related to the incomplete penetrability of the surface coils, which may result in poor imaging quality at the deep structures of the brain, although this effect was not apparent in our study.

The use of a reduction factor (sensitivity-encoding factor) of 2 in the present study sufficiently suppressed geometric distortion. To further reduce the distortion, a higher sensitivity-encoding factor can be applied. As indicated previously, however, there is a trade-off with signal-to-noise ratio; thus, a higher averaging of images becomes necessary, which leads to a longer imaging time. The same rule applies when one attempts to increase the spatial resolution with diffusion-tensor MR imaging: A higher reduction factor is needed to achieve more data line collection per signal acquired; thus, there is a limitation to how high the reduction factor can be set.

The way to interpret the fiber-tracking results needs to be elucidated in future studies. The true effectiveness of this technique should be based on results of a well-designed clinical study with data from patients who have undergone surgery. The number of postoperative patients in our series was limited, which makes it difficult to draw firm conclusions. However, the preliminary results of the present study deserve some comments. First, a disrupted tract did not necessarily represent direct damage to the tract but was more commonly noted to be a result of vasogenic edema and tract compression by the mass. With our program, tracking is terminated when either one of the following stop criteria are encountered: Fractional anisotropy decreases below a predetermined level or two contiguous vectors exceed predetermined trajectory curvature. The former may apply for vasogenic edema, and the latter can occur as a result of compression on the tract. Second, the sensitivity of the method is limited. It became apparent as the study progressed that this method is capable of depicting only a portion of the major fiber tracts. For example, our method was somewhat limited in its ability to depict the frontopontine tract. Poor sensitivity may be a result of the limited signal-to-noise ratio and spatial resolution of our MR imaging technique.

The effect of intravenous contrast material should also be considered because all the diffusion-tensor MR images were obtained at the end of routine tumor work-up. We found one study in which the effect of a contrast agent on the apparent diffusion coefficient of normal brain was evaluated (25). The authors of that study predicted that the susceptibility effect from the intravascular contrast agent would decrease the apparent diffusion coefficient by suppressing the effect from perfusion. They showed that the reduction in the apparent diffusion coefficient at a customary dose is only a few percent; thus, the reduction will be below the level of clinical importance (25). On the basis of their results, we believe it is reasonable to assume that there would be minimum effect of a contrast agent on the fractional anisotropy, although further studies are needed to clarify this issue.

Despite the technical difficulties related to image acquisition and interpretation, we believe that our fiber-tracking method is a promising technique. One advantage is the fact that the source images are simple diffusion-weighted MR images with full brain coverage obtained with a high signal-to-noise ratio and a low degree of distortion. These MR images are useful not only for generation of fiber-tracking images but also for diagnosis of various pathologic conditions in the brain, including infarcts and hemorrhages. The examination is short enough to be included in routine clinical work-up. In fact, all diffusion-tensor MR imaging examinations were performed at the end of the routine MR imaging protocol. Finally, to our knowledge, information regarding white matter tracts is not available with other modern imaging techniques. We believe that diffusion-tensor MR imaging is currently the only method that can depict the location of the major fiber tracts.

In conclusion, the time frame of our diffusion-tensor MR imaging protocol is short enough to make it applicable for routine clinical practice. We have shown that it is a promising technique for depicting major fiber tracts and evaluating tract distortion due to intracerebral masses.

	ACKNOWLEDGMENTS

 
We are grateful for the valuable training provided for K.Y. in the Young Investigators Seminar hosted by RSNA 2000. We express our special thanks to the invaluable technical support MR imaging performed by Nobuhiro Kakoi, RT, and Toru Osawa, RT.

	FOOTNOTES

 
Abbreviation: ROI = region of interest

Author contributions: Guarantors of integrity of entire study, K.Y., T.N.; study concepts, K.Y., O.K., S.M.; study design, K.Y., O.K.; literature research, H.N., W.A.; clinical studies, H.I., S.Y.; data acquisition, S.I., S.Y., T.K., O.T.; data analysis/interpretation, H.S., K.M.; manuscript preparation, K.Y., O.K.; manuscript definition of intellectual content and editing, T.N., S.M.; manuscript revision/review and final version approval, K.Y., O.K., T.N.

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