Purpose: The gradient system transfer function (GSTF) characterizes the frequency transfer behavior of a dynamic gradient system and can be used to correct non‐Cartesian k‐space trajectories. This study analyzes the impact of the gradient coil temperature of a 3T scanner on the GSTF. Methods: GSTF self‐ and B\(_0\)‐cross‐terms were acquired for a 3T Siemens scanner (Siemens Healthcare, Erlangen, Germany) using a phantom‐based measurement technique. The GSTF terms were measured for various temperature states up to 45°C. The gradient coil temperatures were measured continuously utilizing 12 temperature sensors which are integrated by the vendor. Different modeling approaches were applied and compared. Results: The self‐terms depend linearly on temperature, whereas the B0‐cross‐term does not. Effects induced by thermal variation are negligible for the phase response. The self‐terms are best represented by a linear model including the three gradient coil sensors that showed the maximum temperature dependence for the three axes. The use of time derivatives of the temperature did not lead to an improvement of the model. The B\(_0\)‐cross‐terms can be modeled by a convolution model which considers coil‐specific heat transportation. Conclusion: The temperature dependency of the GSTF was analyzed for a 3T Siemens scanner. The self‐ and B0‐cross‐terms can be modeled using a linear and convolution modeling approach based on the three main temperature sensor elements.

Background Skeletal muscle function dysfunction has been reported in patients with cystic fibrosis (CF). Studies so far showed inconclusive data whether reduced exercise capacity is related to intrinsic muscle dysfunction in CF. Methods Twenty patients with CF and 23 age-matched controls completed an incremental cardiopulmonary cycling test. Further, a Wingate anaerobic test to assess muscle power was performed. In addition, all participants completed an incremental knee-extension test with 31P magnetic resonance spectroscopy to assess muscle metabolism (inorganic phosphate (Pi) and phosphocreatinine (PCr) as well as intracellular pH). In the MRI, muscle cross-sectional area of the M. quadriceps (qCSA) was also measured. A subgroup of 15 participants (5 CF, 10 control) additionally completed a continuous high-intensity, high-frequency knee-extension exercise task during 31P magnetic resonance spectroscopy to assess muscle metabolism. Results Patients with CF showed a reduced exercise capacity in the incremental cardiopulmonary cycling test (VO2peak: CF 77.8 ± 16.2%predicted (36.5 ± 7.4 ml/qCSA/min), control 100.6 ± 18.8%predicted (49.1 ± 11.4 ml/qCSA/min); p < 0.001), and deficits in anaerobic capacity reflected by the Wingate test (peak power: CF 537 ± 180 W, control 727 ± 186 W; mean power: CF 378 ± 127 W, control 486 ± 126 W; power drop CF 12 ± 5 W, control 8 ± 4 W. all: p < 0.001). In the knee-extension task, patients with CF achieved a significantly lower workload (p < 0.05). However, in a linear model analysing maximal work load of the incremental knee-extension task and results of the Wingate test, respectively, only muscle size and height, but not disease status (CF or not) contributed to explaining variance. In line with this finding, no differences were found in muscle metabolism reflected by intracellular pH and the ratio of Pi/PCr at submaximal stages and peak exercise measured through MRI spectroscopy. Conclusions The lower absolute muscle power in patients with CF compared to controls is exclusively explained by the reduced muscle size in this study. No evidence was found for an intrinsic skeletal muscle dysfunction due to primary alterations of muscle metabolism.

Background: Fatty Degeneration (FD) of the rotator cuff muscles influences functional and anatomical outcome after rotator cuff repair. The MRI based estimation of fatty degeneration is the gold standard. There is some evidence that Ultrasound elastography (EUS) can detect local differences of tissue stiffness in muscles and tendons. Shear-wave elastography (SWE) was evaluated to determine the extent to which shear wave velocity was associated with measures of fatty degeneration. MRI-spectroscopic fat measurement was used as a reference to quantify the amount of fat in the muscle belly. Methods: Forty-two patients underwent SWE of the supraspinatus muscles at its thickest diameter. After ultrasound evaluation an MRI-spectroscopic fat measurement of the supraspinatus muscle was performed using the SPLASH-technique. A gel filled capsule was used to locate the measured area in the MRI. The values of shear wave velocity (SWV) measured with SWE and spectroscopic fat measurement were correlated statistically using Pearson’s correlation test. Results: Correlation of the fat amount measured with MRI-spectroscopy and the SWV measured with SWE was ρ =0.82. Spectroscopic measured fat ratio of the supraspinatus muscle ranged from 0% to 77.41% and SWV from 1.59 m/s to 5.32 m/s. In 4 patients no sufficient SWE could be performed, these individuals showed a larger diameter of the overlying soft tissue. SWV measured with SWE showed a good correlation with MRI spectroscopic fat amount of the supraspinatus muscle. Conclusion: These preliminary data suggest that SWE may be a sufficient tool in detecting and estimating the amount of fatty degeneration in the supraspinatus muscle in real time. Large overlying soft tissue may be a limitation in performing sufficient EUS.

Mapping the longitudinal relaxation time \(T_1\) has widespread applications in clinical MRI as it promises a quantitative comparison of tissue properties across subjects and scanners. Due to the long scan times of conventional methods, however, the use of quantitative MRI in clinical routine is still very limited. In this work, an acceleration of Inversion-Recovery Look-Locker (IR-LL) \(T_1\) mapping is presented. A model-based algorithm is used to iteratively enforce an exponential relaxation model to a highly undersampled radially acquired IR-LL dataset obtained after the application of a single global inversion pulse. Using the proposed technique, a \(T_1\) map of a single slice with 1.6mm in-plane resolution and 4mm slice thickness can be reconstructed from data acquired in only 6s. A time-consuming segmented IR experiment was used as gold standard for \(T_1\) mapping in this work. In the subsequent validation study, the model-based reconstruction of a single-inversion IR-LL dataset exhibited a \(T_1\) difference of less than 2.6% compared to the segmented IR-LL reference in a phantom consisting of vials with \(T_1\) values between 200ms and 3000ms. In vivo, the \(T_1\) difference was smaller than 5.5% in WM and GM of seven healthy volunteers. Additionally, the \(T_1\) values are comparable to standard literature values. Despite the high acceleration, all model-based reconstructions were of a visual quality comparable to fully sampled references. Finally, the reproducibility of the \(T_1\) mapping method was demonstrated in repeated acquisitions. In conclusion, the presented approach represents a promising way for fast and accurate \(T_1\) mapping using radial IR-LL acquisitions without the need of any segmentation.

Background: MRI has become the mainstay of diagnostic imaging in paediatric rheumatology for lesion detection, differential diagnosis and therapy surveillance. MR imaging of synovitis, in particular, is indispensable for early diagnosis and follow-up in arthritis patients. We used diffusion-weighted MRI (DWI) as a new imaging modality in comparison to standard MRI sequences to study bone marrow oedema, soft-tissue oedema and synovitis in paediatric patients. Methods: A total of 52 patients (mean age 11 ± 5 years) with bone marrow oedema (n = 31), soft-tissue oedema (n = 20) and synovitis (n = 15) were examined with transversal diffusion-weighted single-shot echoplanar imaging in addition to standard MR sequences (T2W TIRM, T1W pre- and post-contrast). Diffusion-weighted images were used for lesion detection and apparent diffusion coefficient (ADC, unit × 10-3 mm2/s) values were measured with ROI technique on ADC maps. Results: In 50 of 52 patients, DWI delineated the lesion of interest corresponding to pathological signal increase on standard sequences. Mean ADC was 1.60 ± 0.14 (range 1.38 - 1.99) in osseous lesions, 1.72 ± 0.31 (range 1.43 - 2.56) in soft tissue oedema and 2.82 ± 0.24 (range 2.47 - 3.18) for joint effusion (ANOVA p<0.001). No significant difference in mean ADC was seen for inflammatory vs. non-inflammatory lesions. Relative signal intensity of oedema was similar for DWI and T2W TIRM. DWI visualised synovial restricted diffusion with a mean ADC of 2.12 ± 0.45 in 12 of 15 patients with synovitis. Conclusions: Diffusion-weighted MRI reliably visualises osseous and soft tissue oedema, as compared to standard sequences. DWI of synovitis is feasible in large joints and presents a novel approach to contrast-free imaging of synovitis. Whole-body DWI for chronic non-bacterial osteomyelitis should be evaluated in future studies.