Weight-bearing MRI of patellofemoral joint cartilage contact area

Purpose

To measure contact area of cartilage in the patellofemoral joint during weight bearing using an open MRI scanner.

Materials and Methods

We developed an MR‐compatible back support that allows three‐dimensional imaging of the patellofemoral cartilage under physiologic weight‐bearing conditions with negligible motion artifact in an open MRI scanner. To measure contact areas, we trained observers using a phantom of known area and tested intra‐ and interobserver variability. We measured in vivo contact areas between the patella and femoral cartilage with the knee in 30 degrees of flexion, loaded and unloaded, in six volunteers.

Results

We were able to measure the contact area of the patellofemoral cartilage with small interobserver (CV 7.0%) and intraobserver (CV 3.0%) variation. At 30 degrees of knee flexion, mean contact area increased from 400 mm² (unloaded) to 522 mm² (loaded to 0.45 times body weight per leg).

Conclusion

Using an open magnet and specially designed apparatus, it is possible to image the patellar cartilage during physiologic loading. Knowledge of patellar cartilage contact area is needed to assess patellofemoral stress, which may be increased in patients with patellofemoral pain syndrome. J. Magn. Reson. Imaging 2004;20:526–530. Published 2004 Wiley‐Liss, Inc.

     

Free‐breathing myocardial perfusion MRI using SW‐CG‐HYPR and motion correction

First‐pass perfusion MRI is a promising technique to detect ischemic heart disease. Sliding window (SW) conjugate‐gradient (CG) highly constrained back‐projection reconstruction (HYPR) (SW‐CG‐HYPR) has been proposed to increase spatial coverage, spatial resolution, and SNR. However, this method is sensitive to respiratory motion and thus requires breath‐hold. This work presents a non‐model‐based motion correction method combined with SW‐CG‐HYPR to perform free‐breathing myocardial MR imaging. Simulation studies were first performed to show the effectiveness of the proposed motion correction method and its independence from the pattern of the respiratory motion. After that, in vivo studies were performed in six healthy volunteers. From all of the volunteer studies, the image quality score of free breathing perfusion images with motion correction (3.11 ± 0.34) is improved compared with that of images without motion correction (2.27 ± 0.32), and is comparable with that of successful breath‐hold images (3.12 ± 0.38). This result was further validated by a quantitative sharpness analysis. The left ventricle and myocardium signal changes in motion corrected free‐breathing perfusion images were closely correlated to those observed in breath‐hold images. The correlation coefficient is 0.9764 for myocardial signals. Bland–Altman analysis confirmed the agreement between the free‐breathing SW‐CG‐HYPR method with motion correction and the breath‐hold SW‐CG‐HYPR. This technique may allow myocardial perfusion MRI during free breathing. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.     

Hybrid prospective and retrospective head motion correction to mitigate cross‐calibration errors

Utilization of external motion tracking devices is an emerging technology in head motion correction for MRI. However, cross‐calibration between the reference frames of the external tracking device and the MRI scanner can be tedious and remains a challenge in practical applications. In this study, we present two hybrid methods, both of which combine prospective, optical‐based motion correction with retrospective entropy‐based autofocusing to remove residual motion artifacts. Our results revealed that in the presence of cross‐calibration errors between the optical tracking device and the MR scanner, application of retrospective correction on prospectively corrected data significantly improves image quality. As a result of this hybrid prospective and retrospective motion correction approach, the requirement for a high‐quality calibration scan can be significantly relaxed, even to the extent that it is possible to perform external prospective motion tracking without any prior cross‐calibration step if a crude approximation of cross‐calibration matrix exists. Moreover, the motion tracking system, which is used to reduce the dimensionality of the autofocusing problem, benefits the retrospective approach at the same time. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.     

Change in knee cartilage T2 in response to mechanical loading

PURPOSE: To assess the clinical feasibility of magnetic resonance (MR) imaging with a mechanical loading system for evaluation of load-bearing function in knee joints using cartilage T2 as a surrogate of cartilage matrix changes. MATERIALS AND METHODS: Sagittal T2 maps of the medial and lateral femorotibial joints of 22 healthy volunteers were obtained using 3.0T MR imaging. After preloading for 6-9 minutes, MR images under static loading conditions were obtained by applying axial compression force of 50% of body weight during imaging. T2 values of the femoral and tibial cartilage at the weight-bearing area were compared between unloading and loading conditions. RESULTS: Under loading conditions, mean cartilage T2 decreased, depending on location of the knee cartilage. For the femoral side a significant decrease in T2 with loading was observed only at the region in direct contact with the opposing tibial cartilage, in the medial femoral cartilage (5.4%, P < 0.0005). For the tibial side a significant decrease in T2 with loading was widely observed in the medial and lateral joint, at regions both covered and not covered by the meniscus (4.3%-7.6%, P < 0.005). CONCLUSION: MR imaging with mechanical loading is feasible to detect site-specific changes in cartilage T2 during static loading.     

Diffusion imaging with prospective motion correction and reacquisition

A major source of artifacts in diffusion‐weighted imaging is subject motion. Slow bulk subject motion causes misalignment of data when more than one average or diffusion gradient direction is acquired. Fast bulk subject motion can cause signal dropout artifacts in diffusion‐weighted images and results in erroneous derived maps, e.g., fractional anisotropy maps. To address both types of artifacts, a fully automatic method is presented that combines prospective motion correction with a reacquisition scheme. Motion correction is based on the prospective acquisition correction method modified to work with diffusion‐weighted data. The images to reacquire are determined automatically during the acquisition from the imaging data, i.e., no extra reference scan, navigators, or external devices are necessary. The number of reacquired images, i.e., the additional scan duration can be adjusted freely. Diffusion‐weighted prospective acquisition correction corrects slow bulk motion well and reduces misalignment artifacts like image blurring. Mean absolute residual values for translation and rotation were <0.6 mm and 0.5°. Reacquisition of images affected by signal dropout artifacts results in diffusion maps and fiber tracking free of artifacts. The presented method allows the reduction of two types of common motion related artifacts at the cost of slightly increased acquisition time. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

Advantages and limitations of prospective head motion compensation for MRI using an optical motion tracking device

RATIONALE AND OBJECTIVES: Subject motion appears to be a limiting factor in numerous magnetic resonance (MR) imaging (MRI) applications. In particular, head tremor, which often accompanies stroke, may render certain high-resolution two- (2D) and three-dimensional (3D) techniques inapplicable. The reason for that is head movement during acquisition. The study objective is to achieve a method able to compensate for complete motion during data acquisition. The method should be usable for every sequence and easily implemented on different MR scanners. MATERIALS AND METHODS: The possibility of interfacing the MR scanner with an external optical motion-tracking system capable of determining the object's position with submillimeter accuracy and an update rate of 60 Hz is shown. Movement information on the object position (head) is used to compensate for motion in real time by updating the field of view (FOV) by recalculating the gradients and radiofrequency parameter of the MR scanner during acquisition of k-space data, based on tracking data. RESULTS: Results of rotation phantom, in vivo experiments, and implementation of three different MRI sequences, 2D spin echo, 3D gradient echo, and echo planar imaging, are presented. Finally, the proposed method is compared with the prospective motion correction software available on the scanner software. CONCLUSION: A prospective motion correction method that works in real time only by updating the FOV of the MR scanner is presented. Results show the feasibility of using an external optical motion-tracking system to compensate for strong and fast subject motion during acquisition.     

Real‐time correction by optical tracking with integrated geometric distortion correction for reducing motion artifacts in functional MRI

Head motion artifacts are a major problem in functional MRI that limit its use in neuroscience research and clinical settings. Real‐time scan‐plane correction by optical tracking has been shown to correct slice misalignment and nonlinear spin‐history artifacts; however, residual artifacts due to dynamic magnetic field nonuniformity may remain in the data. A recently developed correction technique, Phase Labeling for Additional Coordinate Encoding, can correct for absolute geometric distortion using only the complex image data from two echo planar images with slightly shifted k‐space trajectories. An approach is presented that integrates Phase Labeling for Additional Coordinate Encoding into a real‐time scan‐plane update system by optical tracking, applied to a tissue‐equivalent phantom undergoing complex motion and an functional MRI finger tapping experiment with overt head motion to induce dynamic field nonuniformity. Experiments suggest that such integrated volume‐by‐volume corrections are very effective at artifact suppression, with potential to expand functional MRI applications. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.     

Echo‐planar imaging with prospective slice‐by‐slice motion correction using active markers

Head motion is a fundamental problem in functional magnetic resonance imaging and is often a limiting factor in its clinical implementation. This work presents a rigid‐body motion correction strategy for echo‐planar imaging sequences that uses micro radiofrequency coil “active markers” for real‐time, slice‐by‐slice prospective correction. Before the acquisition of each echo‐planar imaging‐slice, a short tracking pulse‐sequence measures the positions of three active markers integrated into a headband worn by the subject; the rigid‐body transformation that realigns these markers to their initial positions is then fed back to dynamically update the scan‐plane, maintaining it at a fixed orientation relative to the head. Using this method, prospectively‐corrected echo‐planar imaging time series are acquired on volunteers performing in‐plane and through‐plane head motions, with results demonstrating increased image stability over conventional retrospective image‐realignment. The benefit of this improved image stability is assessed in a blood oxygenation level dependent functional magnetic resonance imaging application. Finally, a non‐rigid‐body distortion‐correction algorithm is introduced to reduce the remaining signal variation. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

Combined prospective and retrospective correction to reduce motion‐induced image misalignment and geometric distortions in EPI

Despite rigid‐body realignment to compensate for head motion during an echo‐planar imaging time‐series scan, nonrigid image deformations remain due to changes in the effective shim within the brain as the head moves through the B₀ field. The current work presents a combined prospective/retrospective solution to reduce both rigid and nonrigid components of this motion‐related image misalignment. Prospective rigid‐body correction, where the scan‐plane orientation is dynamically updated to track with the subject's head, is performed using an active marker setup. Retrospective distortion correction is then applied to unwarp the remaining nonrigid image deformations caused by motion‐induced field changes. Distortion correction relative to a reference time‐frame does not require any additional field mapping scans or models, but rather uses the phase information from the echo‐planar imaging time‐series itself. This combined method is applied to compensate echo‐planar imaging scans of volunteers performing in‐plane and through‐plane head motions, resulting in increased image stability beyond what either prospective or retrospective rigid‐body correction alone can achieve. The combined method is also assessed in a blood oxygen level dependent functional MRI task, resulting in improved Z‐score statistics. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.     

MRI与关节镜测量膝关节软骨缺损面积的对比

目的：探讨磁共振成像(MRI)与关节镜测量膝关节软骨缺损面积的一致性。方法选取36例(36膝)因膝关节软骨缺损的入院患者,对照分析其关节镜及术前 MRI 资料。比较 MRI 与关节镜术中测量软骨缺损区面积的一致性。结果MRI 与关节镜均发现膝关节软骨缺损92处,平均每例2.6处。经 MRI 测量,平均每膝的软骨缺损面积为(1.9±1.5)cm2;经关节镜测量,平均每膝的软骨缺损面积为(2.9±2.6)cm2;MRI 与关节镜测量结果之间差异有统计学意义(P <0.001)。MRI 的评估结果低于关节镜测量结果,平均差值为(1.7±1.1)cm2。MRI 测量的面积为关节镜测量结果的70.1%。结论MRI 诊断关节软骨缺损病灶数目上与关节镜具有良好的一致性;可直接或间接反映膝关节软骨缺损面积,定位、定性诊断较为准确。     

Elliptical subject‐specific model of respiratory motion for cardiac MRI

Respiratory motion is a major problem in cardiac MRI. In this work, the displacement of the heart relative to the diaphragm was investigated. A subject‐specific nonlinear elliptical affine model has been developed to incorporate the effect of hysteresis in motion correction. Nine healthy volunteers participated in a study in which the diaphragm position and an image of the heart were acquired during each cardiac cycle, while breathing freely. The elliptical model was compared to a linear affine model, and the results show that the elliptical model performed significantly (P < 0.05) better than the linear model. Further, it has been established that the model can be constructed from 25 s of prescan data, which makes it feasible to perform a short prescan to construct the model, so that subject‐specific prospective motion correction of the heart can be integrated into structural cardiac MRI sequences. Magn Reson Med 70:722–731, 2013. © 2012 Wiley Periodicals, Inc.