The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery.

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) tractography reconstruction of white matter pathways can help guide brain tumor resection. However, DTI tracts are complex mathematical objects and the validity of tractography-derived information in clinical settings has yet to be fully established. To address this issue, we initiated the DTI Challenge, an international working group of clinicians and scientists whose goal was to provide standardized evaluation of tractography methods for neurosurgery. The purpose of this empirical study was to evaluate different tractography techniques in the first DTI Challenge workshop. METHODS: Eight international teams from leading institutions reconstructed the pyramidal tract in four neurosurgical cases presenting with a glioma near the motor cortex. Tractography methods included deterministic, probabilistic, filtered, and global approaches. Standardized evaluation of the tracts consisted in the qualitative review of the pyramidal pathways by a panel of neurosurgeons and DTI experts and the quantitative evaluation of the degree of agreement among methods. RESULTS: The evaluation of tractography reconstructions showed a great interalgorithm variability. Although most methods found projections of the pyramidal tract from the medial portion of the motor strip, only a few algorithms could trace the lateral projections from the hand, face, and tongue area. In addition, the structure of disagreement among methods was similar across hemispheres despite the anatomical distortions caused by pathological tissues. CONCLUSIONS: The DTI Challenge provides a benchmark for the standardized evaluation of tractography methods on neurosurgical data. This study suggests that there are still limitations to the clinical use of tractography for neurosurgical decision making.

Lung Parenchymal Signal Intensity in MRI: A Technical Review with Educational Aspirations Regarding Reversible Versus Irreversible Transverse Relaxation Effects in Common Pulse Sequences.

Lung parenchyma is challenging to image with proton MRI. The large air space results in ~l/5th as many signal-generating protons compared to other organs. Air/tissue magnetic susceptibility differences lead to strong magnetic field gradients throughout the lungs and to broad frequency distributions, much broader than within other organs. Such distributions have been the subject of experimental and theoretical analyses which may reveal aspects of lung microarchitecture useful for diagnosis. Their most immediate relevance to current imaging practice is to cause rapid signal decays, commonly discussed in terms of short T2* values of 1 ms or lower at typical imaging field strengths. Herein we provide a brief review of previous studies describing and interpreting proton lung spectra. We then link these broad frequency distributions to rapid signal decays, though not necessarily the exponential decays generally used to define T2* values. We examine how these decays influence observed signal intensities and spatial mapping features associated with the most prominent torso imaging sequences, including spoiled gradient and spin echo sequences. Effects of imperfect refocusing pulses on the multiple echo signal decays in single shot fast spin echo (SSFSE) sequences and effects of broad frequency distributions on balanced steady state free precession (bSSFP) sequence signal intensities are also provided. The theoretical analyses are based on the concept of explicitly separating the effects of reversible and irreversible transverse relaxation processes, thus providing a somewhat novel and more general framework from which to estimate lung signal intensity behavior in modern imaging practice.

Clinical application of pharmacokinetic analysis as a biomarker of solitary pulmonary nodules: dynamic contrast-enhanced MR imaging.

The purpose of this study is to evaluate perfusion indices and pharmacokinetic parameters in solitary pulmonary nodules (SPNs). Thirty patients of 34 enrolled with SPNs (15-30 mm) were evaluated in this study. T1 and T2-weighted structural images and 2D turbo FLASH perfusion images were acquired with shallow free breathing. B-spline nonrigid image registration and optimization by χ² test against pharmacokinetic model curve were performed on dynamic contrast-enhanced MRI. This allowed voxel-by-voxel calculation of k(ep) , the rate constant for tracer transport to and from plasma and the extravascular extracellular space. Mean transit time, time-to-peak, initial slope, and maximum enhancement (E(max) ) were calculated from time-intensity curves fitted to a gamma variate function. After blinded data analysis, correlation with tissue histology from surgical resection or biopsy samples was performed. Histologic evaluation revealed 25 malignant and five benign SPNs. All benign SPNs had k(ep) < 1.0 min⁻¹. Nineteen of 25 (76%) malignant SPNs showed k(ep) > 1.0 min⁻¹. Sensitivity to diagnose malignant SPNs at a cutoff of k(ep) = 1.0 min⁻¹ was 76%, specificity was 100%, positive predictive value was 100%, negative predictive value was 45%, and accuracy was 80%. Of all indices studied, k(ep) was the most significant in differentiating malignant from benign SPNs.

Impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing pulmonary dynamic contrast-enhanced MR imaging.

PURPOSE: To investigates the impact of nonrigid motion correction on pixel-wise pharmacokinetic analysis of free-breathing DCE-MRI in patients with solitary pulmonary nodules (SPNs). Misalignment of focal lesions due to respiratory motion in free-breathing dynamic contrast-enhanced MRI (DCE-MRI) precludes obtaining reliable time-intensity curves, which are crucial for pharmacokinetic analysis for tissue characterization. MATERIALS AND METHODS: Single-slice 2D DCE-MRI was obtained in 15 patients. Misalignments of SPNs were corrected using nonrigid B-spline image registration. Pixel-wise pharmacokinetic parameters K(trans) , v(e) , and k(ep) were estimated from both original and motion-corrected DCE-MRI by fitting the two-compartment pharmacokinetic model to the time-intensity curve obtained in each pixel. The "goodness-of-fit" was tested with χ(2) -test in pixel-by-pixel basis to evaluate the reliability of the parameters. The percentages of reliable pixels within the SPNs were compared between the original and motion-corrected DCE-MRI. In addition, the parameters obtained from benign and malignant SPNs were compared. RESULTS: The percentage of reliable pixels in the motion-corrected DCE-MRI was significantly larger than the original DCE-MRI (P = 4 × 10(-7) ). Both K(trans) and k(ep) derived from the motion-corrected DCE-MRI showed significant differences between benign and malignant SPNs (P = 0.024, 0.015). CONCLUSION: The study demonstrated the impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing DCE-MRI in SPNs.

Diffusion-weighted MRI of malignant pleural mesothelioma: preliminary assessment of apparent diffusion coefficient in histologic subtypes.

OBJECTIVE: The purpose of this study was to prospectively assess, in the evaluation of patients with suspected malignant pleural mesothelioma (MPM), apparent diffusion coefficient (ADC) values derived from diffusion-weighted images obtained with a free-breathing single-shot spin-echo echo-planar imaging sequence and to correlate the ADC values with the three histologic subtypes of MPM. SUBJECTS AND METHODS: Sixty-two patients with a known pleural abnormality and clinical findings suggestive of MPM underwent diffusion-weighted 3-T MRI and ADC calculation. The pathologic diagnosis was confirmed by surgical procedure. ADC values were correlated with the histologic subtypes of MPM. Statistical analysis was performed with analysis of variance and the Student's t test. RESULTS: Fifty-seven patients had MPM. Forty of the tumors were epithelioid, 11 were biphasic, and six were sarcomatoid. The other five patients had pleural thickening (two patients), metastatic adenocarcinoma (one patient), chronic inflammation (one patient), and malignant lymphoma (one patient). Because of image distortion, the diffusion-weighted images and ADC maps were not satisfactory for assessment in seven cases. The ADC values of MPM were 1.31 +/- 0.15 x 10(-3) mm(2)/s for the epithelioid, 1.01 +/- 0.11 x 10(-3) mm(2)/s for the biphasic, and 0.99 +/- 0.07 x 10(-3) mm(2)/s for the sarcomatoid subtypes of MPM. The ADC of the epithelioid subtype was statistically significantly higher than that of the sarcomatoid subtype (p < 0.05). The ADC in the two cases of benign plaque was 0.85 +/- 0.17 x 10(-3) mm(2)/s. CONCLUSION: The ADC values of epithelioid mesothelioma are higher than those of sarcomatoid mesothelioma. There is no significant difference between the ACD values of biphasic and those of sarcomatoid MPM.

Collateral nerve fibers in human spinal cord: visualization with magnetic resonance diffusion tensor imaging.

Diffusion tensor magnetic resonance imaging provides structural information about nerve fiber tissue. The first eigenvector of the diffusion tensor is aligned with the nerve fibers, i.e., longitudinally in the spinal cord. The underlying hypothesis of this study is that the presence of collateral nerve fibers running orthogonal to the longitudinal fibers results in an orderly arrangement of the second eigenvectors. Magnetic resonance diffusion tensor scans were performed with line scan diffusion imaging on a clinical MR scanner. Axial sections were scanned in a human cervical spinal cord specimen at 625 microm resolution and the cervical spinal cord of four normal volunteers at 1250 microm resolution. The spinal cord specimen was fixed and stained for later light microscopy of the collateral fiber architecture at 0.53 microm resolution. Diffusion measured by MR was found to be anisotropic for both white and gray matter areas of the spinal cord specimen; the average fractional anisotropy (FA) was 0.63 +/- 0.09 (diffusion eigenvalues lambda1 0.38 +/- 0.05 micros/mm2, lambda2 0.14 +/- 0.03 micros/mm2, lambda3 0.10 +/- 0.03 micros/mm2) in white matter and 0.27 +/- 0.04 (lambda1 0.36 +/- 0.04 micros/mm2, lambda2 0.28 +/- 0.03 micros/mm2, lambda3 0.21 +/- 0.04 micros/mm2 in gray matter. The normal-volunteer FA values were similar, i.e., 0.66 +/- 0.04 (lambda1 1.66 +/- 0.14 micros/mm2, lambda2 0.55 +/- 0.02 micros/mm2, lambda3 0.40 +/- 0.01 micros/mm2) in white matter and 0.35 +/- 0.03 (lambda1 1.14 +/- 0.07 micros/mm2, lambda2 0.70 +/- 0.03 micros/mm2, lambda3 0.58 +/- 0.02 micros/mm2) in gray matter. The first eigenvector pointed, as expected, in the longitudinal direction. The second eigenvector directions exhibited a striking arrangement, consistent with the distribution of interconnecting collateral nerve fibers discerned on the histology section. This finding was confirmed for the specimen by quantitative pixel-wise comparison of second eigenvector directions and collateral fiber directions assessed on light microscopy image data. Diffusion tensor MRI can reveal non-invasively and in great detail the intricate fiber architecture of the human spinal cord.

Apparent diffusion coefficient and fractional anisotropy in spinal cord: age and cervical spondylosis-related changes.

PURPOSE: To present the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) change with age in the normal spinal cord and in cervical spondylosis. MATERIALS AND METHODS: A total of 11 normal volunteers and 79 cervical spondylosis patients entered this study. Line scan diffusion tensor images were obtained in a 1.5-Tesla whole-body scanner using a phased-array spine coil. The ADC and FA values were measured on a sagittal section. Spearman correlation of ADC/FA vs. age for normal spinal cord was calculated. RESULTS: The mean ADC of the normal spinal cord was 0.81 +/- 0.03 microm(2)/msec at the relatively wide C2-C3 level and 0.75 +/- 0.06 microm(2)/msec at the more narrow C4-C7 level. The FA at the corresponding level was 0.70 +/- 0.05 and 0.66 +/- 0.03, respectively. With age, ADC showed positive correlation (Spearman, r = 0.242) and FA exhibited negative correlation (Spearman, r = -0.244). A total of 54% of all spondylosis cases showed elevated ADC (P < 0.001) and decreased FA (P < 0.001) at the stenotic spinal canal level compared with the normal spinal cord. The average ADC and FA of high-signal lesions on T2-weighted images (seven patients) were 1.28 +/- 0.33 microm(2)/msec and 0.46 +/- 0.12, respectively. CONCLUSION: ADC increases and FA decreases with age in the normal spinal cord. Elevated ADC and reduced FA were measured in the spinal cord of spondylosis cases with clinical symptoms of myelopathy.

In vivo visualization of white matter fiber tracts of preterm- and term-infant brains with diffusion tensor magnetic resonance imaging.

OBJECTIVE: The goal of this study was to test the feasibility of visualizing a 3-dimensional structure of cerebral white matter fiber tracts in preterm infants, postconceptional age (PCA) 28 weeks to term, by using volumetric diffusion tensor magnetic resonance imaging (DTI) data. MATERIALS AND METHOD: We combined tractography algorithms and visualization methods, currently available for adult DTI data, to trace the pixelated principal direction of a diffusion tensor originating from regions-of-interest with high fractional anisotropy. Consequently, white matter fiber bundles from the genu and the splenium of corpus callosum, the corticospinal tracts, the inferior fronto-occipital fasciculi, and optic radiations were visualized. RESULTS: Our results suggest that major white matter tracts of preterm infant brains, with PCAs ranging from 28 weeks to term (40 weeks old), can be successfully visualized despite the small brain volume and low anisotropy. CONCLUSION: The feasibility of fiber tractography in preterm neonates with DTI may add a new dimension in detection and characterization of white matter injuries of preterm infants.

Diffusion tensor imaging of the spinal cord.

The spinal cord is an important part of the nervous system and provides the connection of the brain with the periphery. It consists not only of a large number of longitudinal fibers, but also contains collateral fibers and a central gray matter structure, which are part of autonomous circuits. Magnetic resonance diffusion tensor imaging can reveal this complex fiber architecture in great detail. This report summarizes the normal findings for ADC, diffusion anisotropy, and diffusion eigenvector directions in the spinal cord. Sagittal and axial diffusion-weighted images of the spinal cord were obtained with line scan diffusion imaging (LSDI) in adults, children, infants, and a spinal cord specimen.

Characterization of central nervous system structures by magnetic resonance diffusion anisotropy.

Diffusion-weighted magnetic resonance imaging (MRI) provides information about tissue water diffusion. Diffusion anisotropy, which can be measured with diffusion tensor MRI, is a quantitative measure of the directional dependence of the diffusion restriction that is introduced by biological structures such as nerve fibers. Diffusion tensor MRI data was obtained in the brain, brain stem, and cervical spinal cord. For each region, scans were performed in four normal volunteers. Fractional anisotropy (FA), an index of diffusion anisotropy, was measured within regions of interest located in the corpus callosum, capsula interna, thalamus, caudate nucleus, putamen, brain cortex, pyramidal tract of the medulla, accessory olivary nucleus, dorsal olivary nucleus, inferior olivary nucleus, spinal white and gray matter. The highest FA value was measured in the corpus callosum (81 +/- 3%). The values of the other areas decreased in the following order: pyramidal tract in the medulla (72 +/- 1%), spinal white matter (65 +/- 4%), capsula interna (62 +/- 3%), accessory olivary nucleus (36 +/- 2%), spinal gray matter (35 +/- 5%), dorsal olivary nucleus in the medulla (29 +/- 2%), thalamus (28 +/- 2%), inferior olivary nucleus (15 +/- 2%), putamen (13 +/- 2%), caudate nucleus (13 +/- 2%), and brain cortex (9 +/- 1%). Our results indicate that the underlying fiber architecture, fiber density, and uniformity of nerve fiber direction affect anisotropy values of the various structures. Characterization of various central nervous system structures with diffusion anisotropy is possible and may be useful to monitor degenerative diseases in the central nervous system.

Biexponential diffusion tensor analysis of human brain diffusion data.

Several studies have shown that in tissues over an extended range of b-factors, the signal decay deviates significantly from the basic monoexponential model. The true nature of this departure has to date not been identified. For the current study, line scan diffusion images of brain suitable for biexponential diffusion tensor analysis were acquired in normal subjects on a clinical MR system. For each of six noncollinear directions, 32 images with b-factors ranging from 5 to 5000 s/mm2 were collected. Biexponential fits yielded parameter maps for a fast and a slow diffusion component. A subset of the diffusion data, consisting of the images obtained at the conventional range of b-factors between 5 and 972 s/mm2, was used for monoexponential diffusion tensor analysis. Fractional anisotropy (FA) of the fast-diffusion component and the monoexponential fit exhibited no significant difference. FA of the slow-diffusion biexponential component was significantly higher, particularly in areas of lower fiber density. The principal diffusion directions for the two biexponential components and the monoexponential solution were largely the same and in agreement with known fiber tracts. The second and third diffusion eigenvector directions also appeared to be aligned, but they exhibited significant deviations in localized areas.

Comparison of single-shot echo-planar and line scan protocols for diffusion tensor imaging.

RATIONALE AND OBJECTIVES: Both single-shot diffusion-weighted echo-planar imaging (EPI) and line scan diffusion imaging (LSDI) can be used to obtain magnetic resonance diffusion tensor data and to calculate directionally invariant diffusion anisotropy indices, ie, indirect measures of the organization and coherence of white matter fibers in the brain. To date, there has been no comparison of EPI and LSDI. Because EPI is the most commonly used technique for acquiring diffusion tensor data, it is important to understand the limitations and advantages of LSDI relative to EPI. MATERIALS AND METHODS: Five healthy volunteers underwent EPI and LSDI diffusion on a 1.5 Tesla magnet (General Electric Medical Systems, Milwaukee, WI). Four-mm thick coronal sections, covering the entire brain, were obtained. In addition, one subject was tested with both sequences over four sessions. For each image voxel, eigenvectors and eigenvalues of the diffusion tensor were calculated, and fractional anisotropy (FA) was derived. Several regions of interest were delineated, and for each, mean FA and estimated mean standard deviation were calculated and compared. RESULTS: Results showed no significant differences between EPI and LSDI for mean FA for the five subjects. When intersession reproducibility for one subject was evaluated, there was a significant difference between EPI and LSDI in FA for the corpus callosum and the right uncinate fasciculus. Moreover, errors associated with each FA measure were larger for EPI than for LSDI. CONCLUSION: Results indicate that both EPI- and LSDI-derived FA measures are sufficiently robust. However, when higher accuracy is needed, LSDI provides smaller error and smaller inter-subject and inter-session variability than EPI.

Characterization of normal brain and brain tumor pathology by chisquares parameter maps of diffusion-weighted image data.

OBJECTIVE: To characterize normal and pathologic brain tissue by quantifying the deviation of diffusion-related signal from a simple monoexponential decay, when measured over a wider than usual range of b-factors. METHODS AND MATERIALS: Line scan diffusion imaging (LSDI), with diffusion weighting at multiple b-factors between 100 and 5000 s/mm(2), was performed on 1.5 T clinical scanners. Diffusion data of single slice sections were acquired in five healthy subjects and 19 brain tumor patients. In-patients, conventional T2-weighted and contrast-enhanced T1-weighted images were obtained for reference purposes. The chisquare (chi(2)) error parameter associated with the monoexponential fits of the measured tissue water signals was then used to quantify the departure from a simple monoexponential signal decay on a pixel-by-pixel basis. RESULTS: Diffusion-weighted images over a wider b-factor range than typically used were successfully obtained in all healthy subjects and patients. Normal and pathologic tissues demonstrated signal decays, which clearly deviate from a simple monoexponential behavior. The chi(2) of cortical and deep grey matter was considerably lower than in white matter. In peritumoral edema, however, chi(2) was 68% higher than in normal white matter. In highly malignant brain tumors, such as glioblastoma multiforme (GBM) or anaplastic astrocytoma, chi(2) values were on average almost 400% higher than in normal white matter, while for one low grade astrocytoma and two cases of metastasis, chi(2) was not profoundly different from the chi(2) value of white matter. Maps of the chi(2) values provide good visualization of spatial details. However, the tumor tissue contrast generated appeared in many cases to be different from the enhancement produced by paramagnetic contrast agents. For example, in cases where the contrast agent only highlighted the rim of the tumor, chi(2) enhancement was present within the solid part of the tumor. CONCLUSION: The deviation from a purely monoexponential diffusion signal decay becomes evident as diffusion encoding is extended well beyond the normal range. The chi(2) error parameter as a measure of this deviation seems to provide sufficient lesion contrast to permit differentiation of malignant brain tumors from normal brain tissue.

Diffusion tensor imaging and its application to neuropsychiatric disorders.

Magnetic resonance diffusion tensor imaging (DTI) is a new technique that can be used to visualize and measure the diffusion of water in brain tissue; it is particularly useful for evaluating white matter abnormalities. In this paper, we review research studies that have applied DTI for the purpose of understanding neuropsychiatric disorders. We begin with a discussion of the principles involved in DTI, followed by a historical overview of magnetic resonance diffusion-weighted imaging and DTI and a brief description of several different methods of image acquisition and quantitative analysis. We then review the application of this technique to clinical populations. We include all studies published in English from January 1996 through March 2002 on this topic, located by searching PubMed and Medline on the key words "diffusion tensor imaging" and "MRI." Finally, we consider potential future uses of DTI, including fiber tracking and surgical planning and follow-up.

High-resolution line scan diffusion tensor MR imaging of white matter fiber tract anatomy.

BACKGROUND AND PURPOSE: MR diffusion tensor imaging permits detailed visualization of white matter fiber tracts. This technique, unlike T2-weighted imaging, also provides information about fiber direction. We present findings of normal white matter fiber tract anatomy at high resolution obtained by using line scan diffusion tensor imaging. METHODS: Diffusion tensor images in axial, coronal, and sagittal sections covering the entire brain volume were obtained with line scan diffusion imaging in six healthy volunteers. Images were acquired for b factors 5 and 1000 s/mm(2) at an imaging resolution of 1.7 x 1.7 x 4 mm. For selected regions, images were obtained at a reduced field of view with a spatial resolution of 0.9 x 0.9 x 3 mm. For each pixel, the direction of maximum diffusivity was computed and used to display the course of white matter fibers. RESULTS: Fiber directions derived from diffusion tensor imaging were consistent with known white matter fiber anatomy. The principal fiber tracts were well observed in all cases. The tracts that were visualized included the following: the arcuate fasciculus; superior and inferior longitudinal fasciculus; uncinate fasciculus; cingulum; external and extreme capsule; internal capsule; corona radiata; auditory and optic radiation; anterior commissure; corpus callosum; pyramidal tract; gracile and cuneatus fasciculus; medial longitudinal fasciculus; rubrospinal, tectospinal, central tegmental, and dorsal trigeminothalamic tract; superior, inferior, and middle cerebellar peduncle; pallidonigral and strionigral fibers; and root fibers of the oculomotor and trigeminal nerve. CONCLUSION: We obtained a complete set of detailed white matter fiber anatomy maps of the normal brain by means of line scan diffusion tensor imaging at high resolution. Near large bone structures, line scan produces images with minimal susceptibility artifacts.

Intraoperative magnetic resonance imaging and magnetic resonance imaging-guided therapy for brain tumors.

Since their introduction into surgical practice in the mid 1990s, intraoperative MRI systems have evolved into essential, routinely used tools for the surgical treatment of brain tumors in many centers. Clear delineation of the lesion, "under-the-surface" vision, and the possibility of obtaining real-time feedback on the extent of resection and the position of residual tumor tissue (which may change during surgery due to "brain-shift") are the main strengths of this method. High-performance computing has further extended the capabilities of intraoperative MRI systems, opening the way for using multimodal information and 3D anatomical reconstructions, which can be updated in "near real time." MRI sensitivity to thermal changes has also opened the way for innovative, minimally invasive (LASER ablations) as well as noninvasive therapeutic approaches for brain tumors (focused ultrasound). Although we have not used intraoperative MRI in clinical applications sufficiently long to assess long-term outcomes, this method clearly enhances the ability of the neurosurgeon to navigate the surgical field with greater accuracy, to avoid critical anatomic structures with greater efficacy, and to reduce the overall invasiveness of the surgery itself.