Orientation entropy analysis of diffusion tensor in healthy and myelopathic spinal cord

MR diffusion tensor imaging applied to the spinal cord of patients with neuropathic pain secondary to herpes zoster infection

INTRODUCTION

Diffusion tensor imaging (DTI) has been increasingly utilized in the assessment of spinal cord pathologies for various clinical applications. DTI surpasses conventional MRI in delineating the microstructural integrity of the spinal cord, thereby serving as a potent, non-invasive modality sensitive to white matter pathologies. Postherpetic neuralgia (PHN) is acknowledged to be a consequence not only of peripheral nerve and root lesions but also of central nervous system abnormalities associated with such damage. Our premise posits that the manifestation of PHN may be linked to detectable spinal cord anomalies ascertained through DTI methodologies.

MATERIAL AND METHODS

To study the spinal cord of the patients with post herpetic neuralgia (PHN) using DTI techniques, looking at the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) to compare the parameters of the patients that developed PHN with the parameters of the patients that presented herpes zoster (HZ) but didn't present secondary neuralgia. Fifteen patients (two male and thirteen female) were studied. Ten patients presented PHN: nine female and one male; age from 54y to 83y (mean = 72,2). Five patients had HZ without chronic pain: four female and one male with age from 34y to 81y (mean = 60,8).

RESULTS

For ADC, we found higher values among the patients, significant differences in C5, T8, and T9 levels. For FA, we found lower values among the patients, significant differences in T7, T8, and T9 levels. On ROC curves, we identified that D8 was the single level with significant area under the curve (AUC) for discriminating patients with pain. For ADC, the AUC was 0.960 (95 %CI 0.865-1.000), p = 0.005. For FA, the AUC was 0.920 (95 %CI 0.764-1.000), p = 0.010. The cutoff value for pain on ADC was 2455.08, with a sensibility of 90 % and specificity of 100 %. For FA, the cutoff value for not having pain was 395.05, with sensibility of 100 %, and specificity of 90 %.

CONCLUSION

This investigation highlights the potential for DTI parameters, specifically FA and ADC, to provide insight into the microstructural changes associated with PHN in patients following herpes zoster infection. Future research should continue to explore the implications of these findings in larger cohorts to further elucidate the pathogenesis of neuropathic pain in this population.

Assessing biological self-organization patterns using statistical complexity characteristics: a tool for diffusion tensor imaging analysis

OBJECT

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are well-known and powerful imaging techniques for MRI. Although DTI evaluation has evolved continually in recent years, there are still struggles regarding quantitative measurements that can benefit brain areas that are consistently difficult to measure via diffusion-based methods, e.g., gray matter (GM). The present study proposes a new image processing technique based on diffusion distribution evaluation of López-Ruiz, Mancini and Calbet (LMC) complexity called diffusion complexity (DC).

MATERIALS AND METHODS

The OASIS-3 and TractoInferno open-science databases for healthy individuals were used, and all the codes are provided as open-source materials.

RESULTS

The DC map showed relevant signal characterization in brain tissues and structures, achieving contrast-to-noise ratio (CNR) gains of approximately 39% and 93%, respectively, compared to those of the FA and ADC maps.

DISCUSSION

In the special case of GM tissue, the DC map obtains its maximum signal level, showing the possibility of studying cortical and subcortical structures challenging for classical DTI quantitative formalism. The ability to apply the DC technique, which requires the same imaging acquisition for DTI and its potential to provide complementary information to study the brain's GM structures, can be a rich source of information for further neuroscience research and clinical practice.

Deep Learning-Based Auto-Segmentation of Spinal Cord Internal Structure of Diffusion Tensor Imaging in Cervical Spondylotic Myelopathy

Cervical spondylotic myelopathy (CSM) is a chronic disorder of the spinal cord. ROI-based features on diffusion tensor imaging (DTI) provide additional information about spinal cord status, which would benefit the diagnosis and prognosis of CSM. However, the manual extraction of the DTI-related features on multiple ROIs is time-consuming and laborious. In total, 1159 slices at cervical levels from 89 CSM patients were analyzed, and corresponding fractional anisotropy (FA) maps were calculated. Eight ROIs were drawn, covering both sides of lateral, dorsal, ventral, and gray matter. The UNet model was trained with the proposed heatmap distance loss for auto-segmentation. Mean Dice coefficients on the test dataset for dorsal, lateral, and ventral column and gray matter were 0.69, 0.67, 0.57, 0.54 on the left side and 0.68, 0.67, 0.59, 0.55 on the right side. The ROI-based mean FA value based on segmentation model strongly correlated with the value based on manual drawing. The percentages of the mean absolute error between the two values of multiple ROIs were 0.07, 0.07, 0.11, and 0.08 on the left side and 0.07, 0.1, 0.1, 0.11, and 0.07 on the right side. The proposed segmentation model has the potential to offer a more detailed spinal cord segmentation and would be beneficial for quantifying a more detailed status of the cervical spinal cord.

Specific microstructural changes of the cervical spinal cord in syringomyelia estimated by diffusion tensor imaging

The microstructure of the spinal cord in syringomyelia has not been well studied. The aim of this study was to evaluate the microstructure of the cervical cord in patients with syringomyelia using diffusion tensor imaging (DTI) and to investigate the association between DTI parameters and the size of the syrinx cavity. Thirty patients with syringomyelia and 11 age-matched controls were included in this study. DTI and T1/T2-weighted MRI were used to estimate spinal microstructure. The patients were divided into a clinical symptom group (group A) and a non-clinical symptom group (group B) according to ASIA assessments. The fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values (mm²/s) were measured and compared between patients and controls. Correlation between FA/ADC and the size of the syrinx cavity was examined with a bivariate analysis. FA values were lower (P < 0.000) and ADC values were higher (P < 0.000) compared to the controls at the level of all syrinxes examined in patients with syringomyelia; both FA values and ADC values reached normal values either above or below the syrinx levels (all P > 0.05). FA values and ADC values at all cervical levels were not significantly different either in controls or outside of the syrinx (all P > 0.05). FA values of group A was significantly lower than those of group B (P < 0.000). There was a negative association between FA values and the size of syrinx cavity, and a positive association between ADC values and the size of syrinx cavity (FA: P < 0.05, ADC: P < 0.05). The microstructure of the cervical spinal cord is different across all patients with syringomyelia. DTI is a promising tool for estimating quantitative pathological characteristics that are not visible with general MRI.

Effect of segmentation from different diffusive metric maps on diffusion tensor imaging analysis of the cervical spinal cord

Background

Segmentation is a crucial and necessary step in diffusion tensor imaging (DTI) analysis of the cervical spinal cord. In existing studies, different diffusive metric maps [B0, fractional anisotropy (FA) and axial diffusivity (AD) maps] have been involved in the segmentation of tissues of the cervical spinal cord. The selection of a diffusive metric map for segmentation may affect the accuracy of segmentation and then affect the validity and effectiveness of the extracted diffusive features. However, there are few discussions on this problem. Therefore, this study would like to examine the effect of segmentation based on different diffusive metric maps for DTI analysis of the cervical spinal cord.

Methods

Twenty-nine healthy subjects and thirty patients with cervical spondylotic myelopathy (CSM) were finally included in this study. All subjects accepted DTI scanning at cervical levels from C2 to C7/T1. For healthy subjects, all cervical levels were included for analysis; while, for each patient, only one compressed cervical level was included. After DTI scanning, DTI metrics including B0, FA, AD, radial diffusivity (RD) and mean diffusivity (MD) were calculated. The evaluation was performed to B0, FA and AD maps from two aspects. First, the accuracy of segmentation was evaluated via a comparison between segmentation based on each diffusive metric map and segmentation based on an average image, which was acquired by averaging B0, FA, AD, RD and MD maps. The segmentation was achieved by a semi-automatic segmentation process, and the similarity between two segmentation results was denoted by the intersection of the union (IOU). Second, the diversity of extracted diffusive features was equalized as their performance in the classification of image pixels of different regions of interest (ROIs) and then was evaluated by mutual information (MI) and area under the curve (AUC). One-way ANOVA and Bonferroni's post hoc tests were applied to compare the evaluation results.

Results

One-way ANOVA suggested that there were differences (P<0.001) in IOU, MI and AUC values among the three diffusive metric maps for both healthy subjects and patients. The post-hoc tests further indicated that FA performed the best (P<0.001), i.e., the most substantial accuracy of segmentation and the highest diversity in extracted diffusive features.

Conclusions

Different evaluation results had been observed for segmentation based on different diffusive metric maps, suggesting the necessity of selection of diffusive metric maps for segmentation in DTI analysis of the cervical spinal cord. Moreover, FA map is suggested for segmentation due to its best performance in the evaluation.

Classification of Diffusion Tensor Metrics for the Diagnosis of a Myelopathic Cord Using Machine Learning

In this study, we propose an automated framework that combines diffusion tensor imaging (DTI) metrics with machine learning algorithms to accurately classify control groups and groups with cervical spondylotic myelopathy (CSM) in the spinal cord. The comparison between selected voxel-based classification and mean value-based classification were performed. A support vector machine (SVM) classifier using a selected voxel-based dataset produced an accuracy of 95.73%, sensitivity of 93.41% and specificity of 98.64%. The efficacy of each index of diffusion for classification was also evaluated. Using the proposed approach, myelopathic areas in CSM are detected to provide an accurate reference to assist spine surgeons in surgical planning in complicated cases.

Diffusion tensor imaging predicts functional impairment in mild-to-moderate cervical spondylotic myelopathy

BACKGROUND CONTEXT

Magnetic resonance imaging (MRI) is the standard imaging modality for the assessment of cervical spinal cord; however, MRI assessment of the spinal cord in cervical spondylotic myelopathy patients has not demonstrated a consistent association with neurologic function or outcome after surgical or medical intervention. Thus, there is a need for sensitive imaging biomarkers that can predict functional impairment in patients with advanced cervical spondylosis.

PURPOSE

To implement diffusion tensor imaging (DTI) as an imaging biomarker for microstructural integrity and functional impairment in patients with cervical spondylosis.

STUDY DESIGN

Nonrandomized, single institution study.

PATIENT SAMPLE

Forty-eight cervical spondylosis patients with or without spinal cord signal change underwent DTI of the spinal cord along with functional assessment.

OUTCOME MEASURES

Functional measures of neurologic function via modified Japanese Orthopedic Association (mJOA) score.

METHODS

A zoomed-echoplanar imaging technique and two-dimensional spatially selective radiofrequency excitation pulse were used for DTI measurement. Fractional anisotropy (FA), mean diffusivity (MD), radial and axial diffusion (AD) coefficient, AD anisotropy, ψ, defined as AD-MD, and the standard deviation (SD) of primary eigenvector orientation were evaluated at the site of compression.

RESULTS

Results suggest average FA, transverse apparent diffusion coefficient, ψ, and SD of primary eigenvector orientation at the spinal level of highest compression were linearly correlated with mJOA score. Receiver-operator characteristic analysis suggested FA and ψ could identify stenosis patients with mild-to-moderate symptoms with a relatively high sensitivity and specificity.

CONCLUSIONS

The results of this study support the potential use of DTI as a biomarker for predicting functional impairment in patients with cervical spondylosis.

Does diffusion tensor data reflect pathological changes in the spinal cord with chronic injury

Magnetic resonance diffusion tensor imaging has been shown to quantitatively measure the early pathological changes in chronic cervical spondylotic myelopathy. In this study, a novel spongy polyurethane material was implanted in the rat C_3–5 epidural space to establish a rat model of chronic cervical spondylotic myelopathy. Diffusion tensor data were used to predict pathological changes. Results revealed that the fractional anisotropy value gradually decreased at 4, 24, and 72 hours and 1 week after injury in rat spinal cord, showing a time-dependent manner. Average diffusion coefficient increased at 72 hours and 1 week after implantation. Hematoxylin-eosin staining and Luxol-fast-blue staining exhibited that the number of neurons in the anterior horn of the spinal cord gray matter and the nerve fiber density of the white matter gradually reduced with prolonged compression time. Neuronal loss was most significant at 1 week after injury. Results verified that the fractional anisotropy value and average diffusion coefficient reflected the degree of pathological change in the site of compression in rat models at various time points after chronic spinal cord compression injury, which potentially has a reference value in the early diagnosis of chronic cervical spondylotic myelopathy.

Quantitative assessment of column-specific degeneration in cervical spondylotic myelopathy based on diffusion tensor tractography

PURPOSE

Cervical spondylotic myelopathy (CSM) is a common spinal cord disorder in the elderly. Diffusion tensor imaging (DTI) has been shown to be of great value for evaluating the microstructure of nerve tracts in the spinal cord. Currently, the quantitative assessment of the degeneration on the specific tracts in CSM is still rare. The aim of the present study was to use tractography-based quantification to investigate the column-specific degeneration in CSM.

METHODS

A total of 43 volunteers were recruited with written informed consent, including 20 healthy subjects and 23 CSM patients. Diffusion MRI was taken by 3T MRI scanner. Fiber tractography was performed using TrackVis to reconstruct the white matter tracts of the anterior, lateral and posterior column on the bilateral sides. The DTI metrics acquired from tractography, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD), were compared between healthy subjects and CSM patients.

RESULTS

Compared to healthy subjects, FA was found significantly lower in the lateral (Healthy 0.64 ± 0.07 vs. CSM 0.53 ± 0.08) and posterior column (Healthy 0.67 ± 0.08 vs. CSM 0.47 ± 0.08) (p < 0.001), while MD, AD and RD were significantly higher in the anterior, lateral and posterior column in CSM (p < 0.05).

CONCLUSION

Loss of microstructural integrity was detected in the lateral and posterior column in CSM. Tractography-based quantification was capable of evaluating the subtle pathological insult within white matter on a column-specific basis, which exhibited potential clinical value for in vivo evaluation of the severity of CSM.

Variation in anisotropy and diffusivity along the medulla oblongata and the whole spinal cord in adolescent idiopathic scoliosis: a pilot study using diffusion tensor imaging

BACKGROUND AND PURPOSE

Disturbed somatosensory evoked potentials have been demonstrated in patients with adolescent idiopathic scoliosis (but this functional delay was found to originate above the C5-6 level, while the lower cord level was unaffected). Together with MR imaging observation of tonsillar ectopia and a relatively tethered cord, we hypothesized that there is disturbed mean diffusivity integrity along the spinal cord. In this study, advanced DTI was used to evaluate whether there was underlying decreased WM integrity within the brain stem and spinal cord in adolescent idiopathic scoliosis and any relationship to cerebellar tonsillar ectopia. Clinical impact on balance testing was also correlated.

MATERIALS AND METHODS

Thirteen girls with adolescent idiopathic scoliosis with right thoracic curves were compared with 13 age-matched healthy girls. DTI of the brain and whole spinal cord was performed. ROIs were manually defined for the medulla oblongata and along each intervertebral segment of the cord. Mean values of fractional anisotropy and mean diffusivity were computed at the defined regions. Between-group comparisons were performed by 1-way ANOVA.

RESULTS

Significantly decreased fractional anisotropy values and increased mean diffusivity values were found at the medulla oblongata and C1-2, C2-3, C3-4, and C4-5 segments in patients with adolescent idiopathic scoliosis compared with healthy subjects. No significant difference was found in the lower cord levels. Significant correlation was found between the tonsillar level and fractional anisotropy value at the C4-5 level in patients with adolescent idiopathic scoliosis only.

CONCLUSIONS

The findings from this study are in agreement with previous findings showing abnormal somatosensory evoked potential readings occurring only above the C5-6 level in patients with adolescent idiopathic scoliosis; these findings might partially explain the pathophysiology of the neural pathway involved.

Potential use of diffusion tensor imaging in level diagnosis of multilevel cervical spondylotic myelopathy

STUDY DESIGN

A prospective study on a series of consecutive patients.

OBJECTIVE

To investigate the use of diffusion tensor imaging (DTI) and orientation entropy in level localization in patients diagnosed with multilevel cervical spondylotic myelopathy (CSM).

SUMMARY OF BACKGROUND DATA

Multilevel CSM presents complex neurological signs that make level localization difficult. DTI is recently found to be able to assess the microstructural changes of the white matter caused by cord compression.

METHODS

Sixteen patients with CSM with multilevel compression were recruited. The level(s) responsible for the clinical symptoms were determined by detailed neurological examination, T2-weighted (T2W) magnetic resonance imaging (MRI), and DTI. On T2W MRI, anterior-posterior compression ratio and increased signal intensities were used to determine the affected level(s). The level diagnosis results from T2W MRI, increased signal intensities, DTI, and combination method were correlated to that of neurological examination on a level-to-level basis, respectively. The accuracy, sensitivity, and specificity were calculated.

RESULTS

When correlated with the clinical level determination, the weighted orientation entropy-based DTI analysis was found to have higher accuracy (82.76% vs. 75.86%) and sensitivity (84.62% vs. 76.92%) than those of the anterior-posterior compression ratio. The increased signal intensities have the highest specificity (100.00%) but the lowest accuracy (58.62%) and sensitivity (53.85%). When combined with the level diagnosis result of wOE with that of anterior-posterior compression ratio, it demonstrated the highest accuracy and sensitivity that were 93.10% and 96.15%, respectively, and equal specificity (66.67%) with using them individually.

CONCLUSION

DTI can be a useful tool to determine the pathological spinal cord levels in multilevel CSM. This information from orientation entropy-based DTI analysis, in addition to conventional MRI and clinical neurological assessment, should help spine surgeons in deciding the optimal surgical strategy.

Advances in MR imaging for cervical spondylotic myelopathy

PURPOSE

To outline the pathogenesis of cervical spondylotic myelopathy (CSM), the correlative abnormalities observed on standard magnetic resonance imaging (MRI), the biological implications and current status of diffusion tensor imaging (DTI), and MR spectroscopy (MRS) as clinical tools, and future directions of MR technology in the management of CSM patients.

METHODS

A systematic review of the pathogenesis and current state-of-the-art in MR imaging technology for CSM was performed.

RESULTS

CSM is caused by progressive, degenerative, vertebral column abnormalities that result in spinal cord damage related to both primary mechanical and secondary biological injuries. The T2 signal change on conventional MRI is most commonly associated with neurological deficits, but tends not to be a sensitive predictor of recovery of function. DTI and MRS show altered microstructure and biochemistry that reflect patient-specific pathogenesis.

CONCLUSION

Advanced imaging techniques, including DTI and MRS, show higher sensitivity to microstructural and biochemical changes within the cord, and may aid in management of CSM patients.

The current state-of-the-art of spinal cord imaging: applications

A first-ever spinal cord imaging meeting was sponsored by the International Spinal Research Trust and the Wings for Life Foundation with the aim of identifying the current state-of-the-art of spinal cord imaging, the current greatest challenges, and greatest needs for future development. This meeting was attended by a small group of invited experts spanning all aspects of spinal cord imaging from basic research to clinical practice. The greatest current challenges for spinal cord imaging were identified as arising from the imaging environment itself; difficult imaging environment created by the bone surrounding the spinal canal, physiological motion of the cord and adjacent tissues, and small crosssectional dimensions of the spinal cord, exacerbated by metallic implants often present in injured patients. Challenges were also identified as a result of a lack of "critical mass" of researchers taking on the development of spinal cord imaging, affecting both the rate of progress in the field, and the demand for equipment and software to manufacturers to produce the necessary tools. Here we define the current state-of-the-art of spinal cord imaging, discuss the underlying theory and challenges, and present the evidence for the current and potential power of these methods. In two review papers (part I and part II), we propose that the challenges can be overcome with advances in methods, improving availability and effectiveness of methods, and linking existing researchers to create the necessary scientific and clinical network to advance the rate of progress and impact of the research.

Quantitative analysis of fiber tractography in cervical spondylotic myelopathy

BACKGROUND CONTEXT

Diffusion tensor fiber tractography is an emerging tool for the visualization of spinal cord microstructure. However, there are few quantitative analyses of the damage in the nerve fiber tracts of the myelopathic spinal cord.

PURPOSE

The aim of this study was to develop a quantitative approach for fiber tractography analysis in cervical spondylotic myelopathy (CSM).

STUDY DESIGN/SETTING

Prospective study on a series of patients.

MATERIALS AND METHODS

A total of 22 volunteers were recruited with informed consent, including 15 healthy subjects and 7 CSM patients. The clinical severity of CSM was evaluated using modified Japanese Orthopedic Association (JOA) score. The microstructure of myelopathic cervical cord was analyzed using diffusion tensor imaging. Diffusion tensor imaging was performed with a 3.0-T magnetic resonance imaging scanner using pulsed gradient, spin-echo, echo-planar imaging sequence. Fiber tractography was generated via TrackVis with fractional anisotropy threshold set at 0.2 and angle threshold at 40°. Region of interest (ROI) was defined to cover C4 level only or the whole-length cervical spinal cord from C1 to C7 for analysis. The length and density of tracked nerve bundles were measured for comparison between healthy subjects and CSM patients.

RESULTS

The length of tracked nerve bundles significantly shortened in CSM patients compared with healthy subjects (healthy: 6.85-77.90 mm, CSM: 0.68-62.53 mm). The density of the tracked nerve bundles was also lower in CSM patients (healthy: 086±0.03, CSM: 0.80±0.06, p<.05). Although the definition of ROI covering C4 only or whole cervical cord appeared not to affect the trend of the disparity between healthy and myelopathic cervical cords, the density of the tracked nerve bundle through whole myelopathic cords was in an association with the modified JOA score in CSM cases (r=0.949, p=.015), yet not found with ROI at C4 only (r=0.316, p=.684).

CONCLUSIONS

The quantitative analysis of fiber tractography is a reliable approach to detect cervical spondylotic myelopathic lesions compared with healthy spinal cords. It could be employed to delineate the severity of CSM.

Diffusion imaging quality control via entropy of principal direction distribution

Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, "venetian blind" artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies.

Fully automatic stitching of diffusion tensor images in spinal cord

Diffusion tensor imaging (DTI) has become an important tool for studying the spinal cord pathologies. To enable high resolution imaging for modern studies, the DTI technique utilizes a small field of view (FOV) to capture partial human spinal cords. However, normal aging and many other diseases which affect the entire spinal cord increase the desire of acquiring the continuous full-view of the spinal cord. To overcome this problem, this paper presents a novel pipeline for automatic stitching of three-dimensional (3D) DTI of different portions of the spinal cord. The proposed technique consists of two operations, e.g. feature-based registration and adaptive composition to stitch every source image together to create a panoramic image. In the feature-based registration process, feature points are detected from the apparent diffusion coefficient map, and then a novel feature descriptor is designed to characterize feature points directly from a tensor neighborhood. 3D affine transforms are achieved by determining the correspondence matching. In the adaptive composition process, an effective feathering approach is presented to compute the tensors in the overlap region by the Log-Euclidean metrics. We evaluate the algorithm on real datasets from one healthy subject and one adolescent idiopathic scoliosis (AIS) patient. The colored FA maps and fiber tracking results show the effectiveness and accuracy of the proposed stitching framework.

ENTROPY BASED DTI QUALITY CONTROL VIA REGIONAL ORIENTATION DISTRIBUTION

Diffusion Tensor Imaging (DTI) has received increasing attention in the neuroimaging community. However, the complex Diffusion Weighted Images (DWI) acquisition protocol are prone to artifacts induced by motion and low signal-to-noise rations(SNRs). A rigorous quality control (QC) and error correction procedure is absolutely necessary for DTI data analysis. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts. We propose a new regional, alignment-independent DTI-QC measure that is based in the DTI domain employing the entropy of the regional distribution of the principal directions. This new QC measurement is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Experiments show that our automatic method can reliably detect and potentially correct such residual artifacts. The results indicate its usefulness for general quality assessment in DTI studies.