Simulation of tagged MR images with linear tetrahedral solid elements

Computer simulation of tagged magnetic resonance (MR) images is presented using signals derived from connected solid triangular or tetrahedral elements. Simulation provides precisely-known deformations for validating tag quantification algorithms. MR imaging signal is derived by Fourier-transforming over a standard element, then mapping to actual elements via transformations. Linear intensity variations over the element are interpolated from vertex intensities determined by tag calculations.     

Noise-adaptive nonlinear diffusion filtering of MR images with spatially varying noise levels.

Anisotropic diffusion filtering is widely used for MR image enhancement. However, the anisotropic filter is nonoptimal for MR images with spatially varying noise levels, such as images reconstructed from sensitivity-encoded data and intensity inhomogeneity-corrected images. In this work, a new method for filtering MR images with spatially varying noise levels is presented. In the new method, a priori information regarding the image noise level spatial distribution is utilized for the local adjustment of the anisotropic diffusion filter. Our new method was validated and compared with the standard filter on simulated and real MRI data. The noise-adaptive method was demonstrated to outperform the standard anisotropic diffusion filter in both image error reduction and image signal-to-noise ratio (SNR) improvement. The method was also applied to inhomogeneity-corrected and sensitivity encoding (SENSE) images. The new filter was shown to improve segmentation of MR brain images with spatially varying noise levels.     

Three-dimensional method for comparing in vivo interventional MR images of thermally ablated tissue with tissue response

PURPOSE: To investigate the ability of magnetic resonance (MR) to monitor radio-frequency (RF) ablation treatments by comparing MR images of thermal lesions to histologically assayed cellular damage. We developed a new methodology using three-dimensional registration for making spatial correlations. MATERIALS AND METHODS: A low-field, open MRI system was used to guide an ablation probe into rabbit thigh muscle and acquire MR volumes after ablation. After fixation, we sliced and photographed the tissue at 3-mm intervals, using a specially designed apparatus, to obtain a volume of tissue images. Histologic samples were digitized using a video microscopy system. For our three-dimensional registration method, we used the tissue images as the reference, and registered histology and MR images to them using two different computer alignment steps. First, the MR volume was aligned to the volume of tissue images by registering needle fiducials placed near the tissue of interest. Second, we registered the histology images with the tissue images using a two-dimensional warping technique that aligned internal features and the outside boundary of histology and tissue images. RESULTS: The MR and histology images were very well aligned, and registration accuracy, determined from displacement of needle fiducials, was 1.32 +/- 0.39 mm (mean +/- SD), which compared favorably to the MR voxel dimensions (0.70 mm in-plane and 3.0 mm thick). A preliminary comparison of MR and tissue response showed that the region inside the elliptical hyperintense rim in MR closely corresponds to the region of necrosis as established by histology, with a mean absolute distance between MR and histology boundaries of 1.17 mm, slightly smaller than the mean registration error. The MR region slightly overestimated the region of necrosis, with a mean signed distance between boundaries of 0.85 mm. CONCLUSION: Our results suggest that our methodology can be used to achieve three-dimensional registration of histology and in vivo MR images. In MR lesion images, the inner border of the hyperintense region corresponds to the border of irreversible cell damage. This is good evidence that during RF ablation treatments, iMRI lesion images can be used for real-time feedback.     

Elastic matching of dynamic MR mammographic images

Dynamic magnetic resonance imaging (MRI) carried out with paramagnetic contrast media has been proven to increase sensitivity and specificity in the detection of breast cancer. Due to movements of the patients and changes in the shape of the breasts during the measurement period, a coregistration (matching) of the acquired data volumes is necessary to obtain higher accuracy for the localization of lesions. In this study, an algorithm for the elastic matching of dynamic MRI volume data is presented. The approach includes automatic feature extraction along with the analysis of corresponding features between the data sets. The matching is actually slice‐oriented, even though information on displacement vectors in adjacent slices is taken into account. An extension of the procedure to fully three‐dimensionally (3D) matching is straight forward. Up until now, the approach has been applied to 20 dynamic MRI studies. The matching time for two image data sets with 256 × 256 × 15 voxels each was about 4 min using a PC (Pentium Pro, 200MHz). Magn Reson Med 43:9–16, 2000. © 2000 Wiley‐Liss, Inc.     

Multiparametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images

RATIONALE AND OBJECTIVES: Treatment of brain neoplasms can greatly benefit from better delineation of bulk neoplasm boundary and the extent and degree of more subtle neoplastic infiltration. Magnetic resonance imaging (MRI) is the primary imaging modality for evaluation before and after therapy, typically combining conventional sequences with more advanced techniques such as perfusion-weighted imaging and diffusion tensor imaging (DTI). The purpose of this study is to quantify the multiparametric imaging profile of neoplasms by integrating structural MRI and DTI via statistical image analysis methods to potentially capture complex and subtle tissue characteristics that are not obvious from any individual image or parameter. MATERIALS AND METHODS: Five structural MRI sequences, namely, B0, diffusion-weighted images, fluid-attenuated inversion recovery, T1-weighted, and gadolinium-enhanced T1-weighted, and two scalar maps computed from DTI (ie, fractional anisotropy and apparent diffusion coefficient) are used to create an intensity-based tissue profile. This is incorporated into a nonlinear pattern classification technique to create a multiparametric probabilistic tissue characterization, which is applied to data from 14 patients with newly diagnosed primary high-grade neoplasms who have not received any therapy before imaging. RESULTS: Preliminary results demonstrate that this multiparametric tissue characterization helps to better differentiate among neoplasm, edema, and healthy tissue, and to identify tissue that is likely to progress to neoplasm in the future. This has been validated on expert assessed tissue. CONCLUSION: This approach has potential applications in treatment, aiding computer-assisted surgery by determining the spatial distributions of healthy and neoplastic tissue, as well as in identifying tissue that is relatively more prone to tumor recurrence.     

Classification of trabecular structure in magnetic resonance images based on morphological granulometries

A new method of detecting structured changes in trabecular bone, such as those associated with osteoporosis, was evaluated on magnetic resonance images of the wrist. The method was based on gray-scale morphological granulometries which classify image texture by iteratively filtering an image and measuring the rate of change of structural diminution in a filtered-image sequence. A classification scheme capable of distinguishing structural changes in trabecular bone starting from normal trabeculae through sclerotic, cystic, and grossly porotic bone is presented. Results of the application of this technique to the evaluation of high resolution magnetic resonance images of the wrist are presented.     

Characterization and prediction of gradient acoustic noise in MR imagers

Gradient acoustic noise has been measured and characterized for an epoxy-potted, shielded gradient assembly in a 1.5 T MRI system. Noise levels vary by 10 dB or more as a function of longitudinal position in the scanner and reflect the pattern of forces applied to the gradient assembly. The noise level increases slightly (1–3 dB) with a patient in the scanner. The spectrum of the noise is similar (but not identical) to the spectrum of the input signal. A gradient-pulse-to-acoustic-noise transfer function was obtained by using a white noise voltage input to the gradient system. The transfer function enabled us to accurately predict acoustic noise output for a pulse sequence consisting of a series of trapezoidal pulses on a single axis and for a clinical fast spin echo sequence with gradients present on all three axes.     

Implementation of a fast gradient-echo SVD encoding technique for dynamic imaging

In the paper, the results of a fast gradient-echo implementation of the singular value decomposition (SVD) encoding technique for dynamic imaging are presented. The method used is an adaptation with several critical modifications of a keyhole-type approach previously proposed but not implemented. The method was tested by imaging the events following injection of a contrast agent into a phantom, producing a series of dynamic image updates. It is demonstrated that, for this type of application, the SVD encoding technique adequately follows dynamic changes with even a small number of encodes. The result is comared qualitatively to that obtained by standard Fourier-based keyhole imaging and is shown to provide improved spatial resolution of dynamic events when updating with the same number of encodes.     

A knowledge-guided active model method of cortical structure segmentation on pediatric MR images

PURPOSE: To develop an automated method for quantification of cortical structures on pediatric MR images. MATERIALS AND METHODS: A knowledge-guided active model (KAM) approach was proposed with a novel object function similar to the Gibbs free energy function. Triangular mesh models were transformed to images of a given subject by maximizing entropy, and then actively slithered to boundaries of structures by minimizing enthalpy. Volumetric results and image similarities of 10 different cortical structures segmented by KAM were compared with those traced manually. Furthermore, the segmentation performances of KAM and SPM2, (statistical parametric mapping, a MATLAB software package) were compared. RESULTS: The averaged volumetric agreements between KAM- and manually-defined structures (both 0.95 for structures in healthy children and children with medulloblastoma) were higher than the volumetric agreement for SPM2 (0.90 and 0.80, respectively). The similarity measurements (kappa) between KAM- and manually-defined structures (0.95 and 0.93, respectively) were higher than those for SPM2 (both 0.86). CONCLUSION: We have developed a novel automatic algorithm, KAM, for segmentation of cortical structures on MR images of pediatric patients. Our preliminary results indicated that when segmenting cortical structures, KAM was in better agreement with manually-delineated structures than SPM2. KAM can potentially be used to segment cortical structures for conformal radiation therapy planning and for quantitative evaluation of changes in disease or abnormality.     

Three-Dimensional MR image registration of the human brain

An automatic three-dimensional technique for registration of MR images of human brain is described. The algorithm was tested, using MR images of human brain, and was found to estimate angular offsets to within 0.5° and translational offsets to within about 1 pixel. The quality of final registration was evaluated by histogram analysis. The algorithm was found to be computationally efficient and robust.     

Dynamic coronary MR angiography and first-pass perfusion with intracoronary administration of contrast agent

PURPOSE: To evaluate whether dynamic imaging of the coronary arteries can be performed with intracoronary infusion of low-dose gadolinium (Gd)-based contrast agent and assess the effect of long duration and multiple infusions on the image signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). MATERIALS AND METHODS: Dynamic coronary magnetic resonance (MR) imaging (130 msec/image) and contrast agent first pass myocardial perfusion studies were performed with intracoronary infusions of low-dose Gd-based MR contrast agent on dogs (N = 4) using a fast multislice gradient recalled echo (GRE) sequence. RESULTS: Contrast-enhanced coronary arteries were clearly imaged during infusion periods as long as 2.3 minutes. The SNR and CNR of the contrast-enhanced coronary arteries remained essentially unchanged over multiple consecutive angiographic sessions. In addition, we demonstrated that first pass studies performed with intracoronary injection of MR contrast agent can be used as a means of assessing regional myocardial perfusion. CONCLUSION: These studies demonstrated that, using intracoronary infusion of Gd, coronary magnetic resonance angiography (MRA) can be performed with high temporal resolution, and multiple low-dose slow infusions of Gd-based MR contrast agent can be performed without compromise of the vessel SNR and CNR.     

Analysis of ischemic stroke MR images by means of brain atlases of anatomy and blood supply territories

RATIONALE AND OBJECTIVES: A method for atlas-assisted analysis of stroke magnetic resonance images that is a part of a stroke computer-assisted diagnosis system supporting rapid and quantitative checking of thrombolysis conditions is presented. MATERIALS AND METHODS: Two brain atlases are used for analysis: atlas of anatomy (AA) and atlas of blood supply territories (BSTs). To map these atlases onto scans, two methods are used at present: (1) fast Talairach transformation and (2) midsagittal plane and brain's bounding box matching. After atlas-to-scan mapping, both atlases are superimposed onto the studied images and can be used to get their underlying anatomy and BSTs. To speed up the process of analysis, the system automatically analyzes entire regions occupied by the infarct and penumbra. RESULTS: By using both atlases, the system calculates the following values for each infarct and penumbra region: (1) names of all anatomic structures and BSTs within the region, (2) volumes of occupancy for each structure and territory, and (3) percentages of occupancy for each structure and territory. In addition, the system calculates the infarct-middle cerebral artery (MCA) territory ratio for diffusion-weighted images and the penumbra-MCA territory ratio for perfusion images. Atlas-assisted analysis is fast, and calculations take less than 10 seconds. CONCLUSION: This method potentially facilitates and speeds up stroke data analysis, as well as supports decision making.     

Hemodynamic segmentation of MR brain perfusion images using independent component analysis, thresholding, and Bayesian estimation.

Dynamic-susceptibility-contrast MR perfusion imaging is a widely used imaging tool for in vivo study of cerebral blood perfusion. However, visualization of different hemodynamic compartments is less investigated. In this work, independent component analysis, thresholding, and Bayesian estimation were used to concurrently segment different tissues, i.e., artery, gray matter, white matter, vein and sinus, choroid plexus, and cerebral spinal fluid, with corresponding signal-time curves on perfusion images of five normal volunteers. Based on the spatiotemporal hemodynamics, sequential passages and microcirculation of contrast-agent particles in these tissues were decomposed and analyzed. Late and multiphasic perfusion, indicating the presence of contrast agents, was observed in the choroid plexus and the cerebral spinal fluid. An arterial input function was modeled using the concentration-time curve of the arterial area on the same slice, rather than remote slices, for the deconvolution calculation of relative cerebral blood flow.     

Glenoid bone lesions: comparison between 3D VIBE images in MR arthrography and nonarthrographic MSCT

Purpose:

To evaluate the feasibility of using a fat‐suppressed 3D volumetric interpolated breath‐hold examination (VIBE) sequence in magnetic resonance (MR) arthrography as a substitute for nonarthrographic multislice computed tomography (MSCT) in detecting glenoid bone lesions.

Materials and Methods:

Fat‐suppressed 3D VIBE MR arthrography and MSCT were performed in 56 patients (46 male, 10 female; age range, 14–51 years; mean age, 26 years). Based on the results of MSCT, the sensitivity and specificity of fat‐suppressed 3D VIBE images for detection of bony Bankart lesion and glenoid bone loss were determined. Statistical significance of the percentages of glenoid bone loss between these two methods was calculated.

Results:

Bony Bankart lesions were noted in 23 (41.1%) of 56 glenohumeral joints, and glenoid bone loss was found in 40 (71.4%) of 56 patients at nonarthrographic MSCT. Compared with MSCT, the sensitivity and specificity of fat‐suppressed 3D VIBE images in detecting bony Bankart lesions were 95.7%–100% and 93.9%–97.0%, respectively (kappa value = 0.926), and those in predicting glenoid bone loss were 95.0% and 93.8%, respectively. For quantification of glenoid bone loss, there was a high correlation between fat‐suppressed 3D VIBE and MSCT (r = 0.921, P < 0.001).

Conclusion:

Fat‐suppressed 3D VIBE MR arthrography is a promising substitute for MSCT as a reliable method for evaluating bony Bankart lesion and glenoid bone loss. J. Magn. Reson. Imaging 2012;36:231–236. © 2012 Wiley Periodicals Inc.     

A knowledge-guided active contour method of segmentation of cerebella on MR images of pediatric patients with medulloblastoma

PURPOSE: To develop an automated method for identification of the cerebella on magnetic resonance (MR) images of patients with medulloblastoma. MATERIALS AND METHODS: The method used a template constructed from 10 patients' aligned MR head images, and the contour of this template was superimposed on the aligned data set of a given patient as the starting contour. The starting contour was then actively adjusted to locate the boundary of the cerebellum of the given patient. Morphologic operations were applied to the outlined volume to generate cerebellum images. The method was then applied to data sets of 20 other patients to generate cerebellum images and volumetric results. RESULTS: Comparison of the automatically generated cerebellum images with two sets of manually traced images showed a strong correlation between the automatically and manually generated volumetric results (correlation coefficient, 0.97). The average Jaccard similarities were 0.89 and 0.88 in comparison to each of two manually traced images, respectively. The same comparisons yielded average kappa indexes of 0.94 and 0.93, respectively. CONCLUSION: The method was robust and accurate for cerebellum segmentation on MR images of patients with medulloblastoma. The method may be applied to investigations that require segmentation and quantitative measurement of MR images of the cerebellum.     

磁共振全身弥散加权成像的基本原理及临床应用价值

磁共振全身弥散加权成像(WB-DWI)是近几年来在磁共振常规序列基础上发展起来的一项新技术,其作为一种磁共振功能成像技术,是目前仅有的能够反映人体活体组织中水质子扩散运动的非创伤性技术.它是将MR-DWI与回波平面成像(EPI)及短时反转恢复(STIR)脂肪抑制技术相结合,明显缩短了扫描时间,能够在短时间内完成全身大范围扫描(从颅脑到膝关节),且全身背景信号被充分抑制,突出了病变组织尤其是恶性肿瘤及其转移灶的显示.由于WB-DWI具有检查时间短,覆盖范围大,检查费用低,较高的敏感性及无辐射、无创伤等优点,在临床上有广泛的应用前景.现就WB-DWI的技术原理及临床应用进行阐述.     

敏感性编码技术在肝脏磁敏感成像中应用的参数优选探讨

目的探讨敏感性编码(SENSE)技术应用于肝脏磁敏感成像(SWI)中的最佳扫描参数。资料与方法对20名成年健康自愿者行肝脏SWI,比较不同SENSE因子及激励次数(NEX)对图像质量的影响。SENSE因子分别取1.0、1.5、2.5、3.5,NEX分别取1、2、3。结果在不同参数的比较中,SENSE因子为1.5的图像质量较好,NEX为1的图像质量较好。结论应用SENSE技术能显著缩短扫描时间,SENSE为1.5、NEX为1是肝脏SWI较好的扫描参数。