Matthias Honal

Highly k-t-space-accelerated phase-contrast MRI

The purpose of this study was to combine a recently introduced spatiotemporal parallel imaging technique, PEAK‐GRAPPA (parallel MRI with extended and averaged generalized autocalibrating partially parallel acquisition), with two‐dimensional (2D) cine phase‐contrast velocity mapping. Phase‐contrast MRI was applied to measure the blood flow in the thoracic aorta and the myocardial motion of the left ventricle. To evaluate the performance of different reconstruction methods, fully acquired k‐space data sets were used to compare conventional parallel imaging using GRAPPA with reduction factors of R = 2–6 and PEAK‐GRAPPA as well as sliding window reconstruction with reduction factors R = 2–12 (net acceleration factors up to 5.2). PEAK‐GRAPPA reconstruction resulted in improved image quality with considerably reduced artifacts, which was also supported by error analysis. To analyze potential blurring or low‐pass filtering effects of spatiotemporal PEAK‐GRAPPA, the velocity time courses of aortic flow and myocardial tissue motion were evaluated and compared with conventional image reconstructions. Quantitative comparisons of blood flow velocities and pixel‐wise correlation analysis of velocities highlight the potential of PEAK‐GRAPPA for highly accelerated dynamic phase‐contrast velocity mapping. Magn Reson Med 60:1169–1177, 2008.

Parallel MRI with extended and averaged GRAPPA kernels (PEAK-GRAPPA): Optimized spatiotemporal dynamic imaging†

To evaluate an optimized k‐t‐space related reconstruction method for dynamic magnetic resonance imaging (MRI), a method called PEAK‐GRAPPA (Parallel MRI with Extended and Averaged GRAPPA Kernels) is presented which is based on an extended spatiotemporal GRAPPA kernel in combination with temporal averaging of coil weights.

Whole-body MRI-based fat quantification: a comparison to air displacement plethysmography.

To demonstrate the feasibility of an algorithm for MRI whole‐body quantification of internal and subcutaneous fat and quantitative comparison of total adipose tissue to air displacement plethysmography (ADP).

Artifact reduction in moving-table acquisitions using parallel imaging and multiple averages.

Two‐dimensional (2D) axial continuously‐moving‐table imaging has to deal with artifacts due to gradient nonlinearity and breathing motion, and has to provide the highest scan efficiency. Parallel imaging techniques (e.g., generalized autocalibrating partially parallel acquisition GRAPPA)) are used to reduce such artifacts and avoid ghosting artifacts. The latter occur in T2‐weighted multi‐spin‐echo (SE) acquisitions that omit an additional excitation prior to imaging scans for presaturation purposes. Multiple images are reconstructed from subdivisions of a fully sampled k‐space data set, each of which is acquired in a single SE train. These images are then averaged. GRAPPA coil weights are estimated without additional measurements. Compared to conventional image reconstruction, inconsistencies between different subsets of k‐space induce less artifacts when each k‐space part is reconstructed separately and the multiple images are averaged afterwards. These inconsistencies may lead to inaccurate GRAPPA coil weights using the proposed intrinsic GRAPPA calibration. It is shown that aliasing artifacts in single images are canceled out after averaging. Phantom and in vivo studies demonstrate the benefit of the proposed reconstruction scheme for free‐breathing axial continuously‐moving‐table imaging using fast multi‐SE sequences. Magn Reson Med 57:226–232, 2007.

The effect of reconstruction and acquisition parameters for GRAPPA-based parallel imaging on the image quality

Parallel imaging based on generalized autocalibrating partially parallel acquisitions is widely used in the clinical routine. To date, no detailed analysis has been presented describing the dependence of the image quality on the reconstruction and acquisition parameters such as the number of autocalibration signal (ACS) lines NACS, the reconstruction kernel size (bx × by), and the undersampling factor R. To evaluate their influence on the performance of generalized autocalibrating partially parallel acquisitions, two phantom data sets acquired with 12‐channel and 32‐channel receive coils and three in vivo measurements were analyzed. Reconstruction parameters were systematically varied between R = 2–4, NACS = 4–64, bx = 1–9, and by = 2–10 to characterize their influence on image quality and noise. A main aspect of the analysis was to optimize the parameter set with respect to the effectively achieved net image acceleration. Selecting the undersampling factor R as small as possible for a given net acceleration yielded the best result in a clear majority of cases. For all data sets and coil geometries, the optimal kernel sizes and number of ACS lines were similar for a chosen undersampling factor R. In summary, the number of ACS lines should not be chosen below NACS = 10–16. A robust choice for the kernel size was bx = 9 and by = 2–4. Magn Reson Med, 2011.

Increasing efficiency of parallel imaging for 2D multislice acquisitions.

Parallel imaging algorithms require precise knowledge about the spatial sensitivity variation of the receiver coils to reconstruct images with full field of view (FOV) from undersampled Fourier encoded data. Sensitivity information must either be given a priori, or estimated from calibration data acquired along with the actual image data. In this study, two approaches are presented, which require very little or no additional data at all for calibration in two‐dimensional multislice acquisitions. Instead of additional data, information from spatially adjacent slices is used to estimate coil sensitivity information, thereby increasing the efficiency of parallel imaging. The proposed approaches rely on the assumption that over a small range of slices, coil sensitivities vary smoothly in slice direction. Both methods are implemented as variants of the GRAPPA algorithm. For a given effective acceleration, superior image quality is achieved compared to the conventional GRAPPA method. For the latter calibration lines for coil weight computation must be acquired in addition to the undersampled k‐spaces for coil weight computation, thus requiring higher k‐space undersampling, that is, a higher reduction factor to achieve the same effective acceleration. The proposed methods are particularly suitable to speed up parallel imaging for clinical applications where the reduction factor is limited to two or three. Magn Reson Med 2009

Detection of Pulmonary Nodules With Move-During-Scan Magnetic Resonance Imaging Using a Free-Breathing Turbo Inversion Recovery Magnitude Sequence

Purpose:Detection of pulmonary metastases is still a challenging task for magnetic resonance imaging (MRI). It was the aim of this study to evaluate the potential of a free-breathing move-during-scan turbo inversion recovery magnitude sequence for the detection of pulmonary nodules. Materials and Methods:The sensitivities and positive-predictive values of 2 radiologists to detect pulmonary nodules in 41 move-during-scan MRI examinations of 38 patients with different malignancies were calculated and subgroup analyses according to lesion size and localization were performed. Multidetector computed tomography served as the standard of reference. Additionally, 6 radiologists rated the confidence for the presence of nodular lesions in 212 regions-of-interest, which were randomly selected to represent lesions of various sizes as well as negative findings. Receiver-operator-characteristic was performed. Results:Three hundred twenty-one nodules were found in 30 patients by multidetector computed tomography. Sensitivity and specificity of MRI to detect pulmonary nodules larger than 3 mm on a per-patient basis were 81.8% and 94.7%, respectively. On a per-lesion basis, MRI revealed a sensitivity of 79.0% to 80.7% for lesions larger than 3 mm, if high conspicuity ratings were counted as positive, and 84.6%, if medium and high conspicuity ratings were counted as positive. Sensitivity increased uniformly with lesion size, and all lesions larger than 12 mm were detected. Receiver-operator-characteristic analysis revealed a mean accuracy of 0.90 and sensitivities over 90% for lesions larger than 3 mm with a specificity of 96.1%. For lesions larger than 6 mm the accuracy was 0.99. Conclusion:Detection of pulmonary nodules with a move-during-scan turbo inversion recovery magnitude sequence is feasible. Excellent detection of lesions larger than 6 mm is achievable with free-breathing moving-table MRI.

k-t-space accelerated myocardial perfusion

To investigate the performance of the recently introduced spatiotemporal parallel imaging technique called parallel MRI with extended and averaged generalized autocalibrating partially parallel acquisitions (GRAPPA) kernels (PEAK‐GRAPPA) for myocardial perfusion measurements.

In Vivo Analysis of Coracoclavicular Ligament Kinematics During Shoulder Abduction

Background: Anatomic reconstruction of the coracoclavicular ligaments for the treatment of acromioclavicular joint separations provides superior biomechanical stability compared with other procedures. Clavicular and coracoidal footprints of the conoid ligament (CL) and the trapezoid ligament (TL) are well described. So far, little is known about their kinematics and the changes of the coracoclavicular distance during shoulder abduction. Hypothesis: The coracoclavicular distance along the coracoclavicular ligaments changes significantly with shoulder abduction and weightbearing. Study Design: Descriptive laboratory study. Methods: With use of an open magnetic resonance imaging scanner, the shoulders of 13 healthy volunteers were examined in supine and sitting positions. Three-dimensional magnetic resonance images of the shoulders were obtained in 30° increments of abduction (0°-120°). A manual segmentation of the scapula, the clavicle, and the coracoclavicular ligaments was performed. The insertion points of the coracoclavicular ligaments were identified, and automated measures along the ligamentous course were carried out. Results: During transfer from the lying to sitting position, the coracoclavicular distance showed significant lengthening of 3 mm along the center of the CL, which significantly increased another 3 mm during shoulder abduction to a total lengthening of 6 mm. In the supine position, the coracoclavicular distance along the TL did not elongate significantly. In the sitting position, the distance along the medial portion of the TL shortened significantly, whereas the distance along the center portion did not elongate significantly during shoulder abduction. Conclusion: The distances between the coracoclavicular insertion points depend on both patient and shoulder positioning. To prevent overconstraining of the graft, the CL should be fixated during 90° to 120° of shoulder abduction in a sitting position. Isometric reconstruction of the TL can be achieved if precise fixation of the graft at the centers of the conoidal and clavicular footprints is performed.

Compensation of breathing motion artifacts for MRI with continuously moving table

Breathing motion is one of the main sources of artifacts in MRI acquisitions that can severely impair diagnosis. In MRI with continuously moving table, the application of common motion compensation approaches such as breath holding or the synchronization of the measurement with the breathing motion can be problematic. In this study, a technique for the reduction of breathing‐motion artifacts for MRI with continuously moving table is presented, which reconstructs motion‐consistent volumes from data acquired during free breathing. Axial images are acquired rapidly compared to the period of the breathing motion and consistently combined using a combination of rigid and nonrigid slice‐to‐volume registration. This new technique is compared to a previously reported artifact reduction method for MRI with continuously moving table that is based on the same acquisition scheme. While the latter method only suppresses ghosting artifacts, the new technique is shown to additionally reduce blurring, misregistrations, and signal cancellations in the reconstructed images. Magn Reson Med 63:701–712, 2010.