Introduction:MRI of extra-ocular muscles (EOM) in patients with myasthenia gravis (MG) could aid in diagnosis and provide insights in therapy-resistant ophthalmoplegia. We used quantitative MRI to... Show moreIntroduction:MRI of extra-ocular muscles (EOM) in patients with myasthenia gravis (MG) could aid in diagnosis and provide insights in therapy-resistant ophthalmoplegia. We used quantitative MRI to study the EOM in MG, healthy and disease controls, including Graves’ ophthalmopathy (GO), oculopharyngeal muscular dystrophy (OPMD) and chronic progressive external ophthalmoplegia (CPEO).Methods:Twenty recently diagnosed MG (59±19yrs), nineteen chronic MG (51±16yrs), fourteen seronegative MG (57±9yrs) and sixteen healthy controls (54±13yrs) were included. Six CPEO (49±14yrs), OPMD (62±10yrs) and GO patients (44±12yrs) served as disease controls. We quantified muscle fat fraction (FF), T2water and volume. Eye ductions and gaze deviations were assessed by synoptophore and Hess-charting.Results:Chronic, but not recent onset, MG patients showed volume increases (e.g. superior rectus and levator palpebrae [SR+LPS] 985±155 mm3 compared to 884±269 mm3 for healthy controls, p < 0.05). As expected, in CPEO volume was decreased (e.g. SR+LPS 602±193 mm3, p < 0.0001), and in GO volume was increased (e.g. SR+LPS 1419±457 mm3, p < 0.0001). FF was increased in chronic MG (e.g. medial rectus increased 0.017, p < 0.05). In CPEO and OPMD the FF was more severely increased. The severity of ophthalmoplegia did not correlate with EOM volume in MG, but did in CPEO and OPMD. No differences in T2water were found.Interpretation:We observed small increases in EOM volume and FF in chronic MG compared to healthy controls. Surprisingly, we found no atrophy in MG, even in patients with long-term ophthalmoplegia. This implies that even long-term ophthalmoplegia in MG does not lead to secondary structural myopathic changes precluding functional recovery. Show less
Purpose: To develop a method for MR Fingerprinting (MRF) sequence optimization that takes both the applied undersampling pattern and a realistic reference map into account. Methods: A predictive... Show morePurpose: To develop a method for MR Fingerprinting (MRF) sequence optimization that takes both the applied undersampling pattern and a realistic reference map into account. Methods: A predictive model for the undersampling error leveraging on perturbation theory was exploited to optimize the MRF flip angle sequence for improved robustness against undersampling artifacts. In this framework parameter maps from a previously acquired MRF scan were used as reference. Sequences were optimized for different sequence lengths, smoothness constraints and undersampling factors. Numerical simulations and in vivo measurements in eight healthy subjects were performed to assess the effect of the performed optimization. The optimized MRF sequences were compared to a conventionally shaped flip angle pattern and an optimized pattern based on the Cramer-Rao lower bound (CRB). Results: Numerical simulations and in vivo results demonstrate that the undersampling errors can be suppressed by flip angle optimization. Analysis of the in vivo results show that a sequence optimized for improved robustness against undersampling with a flip angle train of length 400 yielded significantly lower median absolute errors in T1: 5.6%+/- 2.9% and T2: 7.9%+/- 2.3% compared to the conventional (T1: 8.0%+/- 1.9%, T2: 14.5%+/- 2.6%) and CRB-based (T1: 21.6%+/- 4.1%, T2: 31.4%+/- 4.4%) sequences. Conclusion: The proposed method is able to optimize the MRF flip angle pattern such that significant mitigation of the artifacts from strong k-space undersampling in MRF is achieved. Show less
Nagtegaal, M.; Hartsema, E.; Koolstra, K.; Vos, F. 2022
Purpose To develop an efficient algorithm for multicomponent MR fingerprinting (MC-MRF) reconstructions directly from highly undersampled data without making prior assumptions about tissue... Show morePurpose To develop an efficient algorithm for multicomponent MR fingerprinting (MC-MRF) reconstructions directly from highly undersampled data without making prior assumptions about tissue relaxation times and expected number of tissues. Methods The proposed method reconstructs MC-MRF maps from highly undersampled data by iteratively applying a joint-sparsity constraint to the estimated tissue components. Intermediate component maps are obtained by a low-rank multicomponent alternating direction method of multipliers (MC-ADMM) including the non-negativity of tissue weights as an extra regularization term. Over iterations, the used dictionary compression is adjusted. The proposed method (k-SPIJN) is compared with a two-step approach in which image reconstruction and multicomponent estimations are performed sequentially and tested in numerical simulations and in vivo by applying different undersampling factors in eight healthy volunteers. In the latter case, fully sampled data serves as the reference. Results The proposed method shows improved precision and accuracy in simulations compared with a state-of-art sequential approach. Obtained in vivo magnetization fraction maps for different tissue types show reduced systematic errors and reduced noise-like effects. Root mean square errors in estimated magnetization fraction maps significantly reduce from 13.0%+/-$$ \pm $$ 5.8% with the conventional, two-step approach to 9.6%+/-$$ \pm $$ 3.9% and 9.6%+/-$$ \pm $$ 3.2% with the proposed MC-ADMM and k-SPIJN methods, respectively. Mean standard deviation in homogeneous white matter regions reduced significantly from 8.6% to 2.9% (two step vs. k-SPIJN). Conclusion The proposed MC-ADMM and k-SPIJN reconstruction methods estimate MC-MRF maps from highly undersampled data resulting in improved image quality compared with the existing method. Show less
Kooreman, E.S.; Tanaka, M.; Beek, L.C. ter; Peters, F.P.; Marijnen, C.A.M.; Heide, U.A. van der; Houdt, P.J. van 2022
Quantitative MRI has the potential to produce imaging biomarkers for the prediction of early response to radiotherapy treatment. In this pilot study, a potential imaging biomarker, the T-1 rho... Show moreQuantitative MRI has the potential to produce imaging biomarkers for the prediction of early response to radiotherapy treatment. In this pilot study, a potential imaging biomarker, the T-1 rho relaxation time, is assessed for this purpose. A T-1 rho sequence was implemented on a 1.5 T MR-linac system, a system that combines an MRI with a linear accelerator for radiation treatment. An agar phantom with concentrations of 1-4% w/w was constructed for technical validation of the sequence. Phantom images were assessed in terms of short-term repeatability and signal-to-noise ratio. Twelve rectal cancer patients, who were treated with 5 x 5 Gy, were imaged on each treatment fraction. Individual changes in the T-1 rho values of the gross tumor volume (GTV) showed an increase for most patients, although a paired t-test comparing values in the GTV from the first to the last treatment fraction showed no statistically significant difference. The phantom measurements showed excellent short-term repeatability (0.5-1.5 ms), and phantom T-1 rho values corresponded to the literature values. T-1 rho imaging was implemented successfully on the MR-linac, with a repeatability comparable to diagnostic systems, although clinical benefit in terms of treatment response monitoring remains to be demonstrated. Show less
Keene, K.R.; Vught, L. van; Velde, N.M. van de; Ciggaar, I.A.; Notting, I.C.; Genders, S.W.; ... ; Beenakker, J.W.M. 2020
Although quantitative MRI can be instrumental in the diagnosis and assessment of disease progression in orbital diseases involving the extra-ocular muscles (EOM), acquisition can be challenging as... Show moreAlthough quantitative MRI can be instrumental in the diagnosis and assessment of disease progression in orbital diseases involving the extra-ocular muscles (EOM), acquisition can be challenging as EOM are small and prone to eye-motion artefacts. We explored the feasibility of assessing fat fractions (FF), muscle volumes and water T2 (T2(water)) of EOM in healthy controls (HC), myasthenia gravis (MG) and Graves' orbitopathy (GO) patients. FF, EOM volumes and T2(water)values were determined in 12 HC (aged 22-65 years), 11 MG (aged 28-71 years) and six GO (aged 28-64 years) patients at 7 T using Dixon and multi-echo spin-echo sequences. The EOM were semi-automatically 3D-segmented by two independent observers. MANOVA and t-tests were used to assess differences in FF, T2(water)and volume of EOM between groups (P< .05). Bland-Altman limits of agreement (LoA) were used to assess the reproducibility of segmentations and Dixon scans. The scans were well tolerated by all subjects. The bias in FF between the repeated Dixon scans was -0.7% (LoA: +/- 2.1%) for the different observers; the bias in FF was -0.3% (LoA: +/- 2.8%) and 0.03 cm(3)(LoA: +/- 0.36 cm(3)) for volume. Mean FF of EOM in MG (14.1% +/- 1.6%) was higher than in HC (10.4% +/- 2.5%). Mean muscle volume was higher in both GO (1.2 +/- 0.4 cm(3)) and MG (0.8 +/- 0.2 cm(3)) compared with HC (0.6 +/- 0.2 cm(3)). The average T2(water)for all EOM was 24.6 +/- 4.0 ms for HC, 24.0 +/- 4.7 ms for MG patients and 27.4 +/- 4.2 ms for the GO patient. Quantitative MRI at 7 T is feasible for measuring FF and muscle volumes of EOM in HC, MG and GO patients. The measured T2(water)was on average comparable with skeletal muscle, although with higher variation between subjects. The increased FF in the EOM in MG patients suggests that EOM involvement in MG is accompanied by fat replacement. The unexpected EOM volume increase in MG may provide novel insights into underlying pathophysiological processes. Show less
Quantitative MRI and MRS of muscle are increasingly being used to measure individual pathophysiological processes in Becker muscular dystrophy (BMD). In particular, muscle fat fraction was shown to... Show moreQuantitative MRI and MRS of muscle are increasingly being used to measure individual pathophysiological processes in Becker muscular dystrophy (BMD). In particular, muscle fat fraction was shown to be highly associated with functional tests in BMD. However, the muscle strength per unit of contractile cross-sectional area is lower in patients with BMD compared with healthy controls. This suggests that the quality of the non-fat-replaced (NFR) muscle tissue is lower than in healthy controls. Consequently, a measure that reflects changes in muscle tissue itself is needed. Here, we explore the potential of waterT(2)relaxation times, diffusion parameters and phosphorus metabolic indices as early disease markers in patients with BMD. For this purpose, we examined these measures in fat-replaced (FR) and NFR lower leg muscles in patients with BMD and compared these values with those in healthy controls. Quantitative proton MRI (three-point Dixon, multi-spin-echo and diffusion-weighted spin-echo echo planar imaging) and 2D chemical shift imaging(31)P MRS data were acquired in 24 patients with BMD (age 18.8-66.2 years) and 13 healthy controls (age 21.3-63.6 years). Muscle fat fractions, phosphorus metabolic indices, and averages and standard deviations (SDs) of the waterT(2)relaxation times and diffusion tensor imaging (DTI) parameters were assessed in six individual leg muscles. Phosphodiester levels were increased in the NFR and FR tibialis anterior, FR peroneus and FR gastrocnemius lateralis muscles. No clear pattern was visible for the other metabolic indices. IncreasedT(2)SD was found in the majority of FR muscles compared with NFR and healthy control muscles. No differences in average waterT(2)relaxation times or DTI indices were found between groups. Overall, our results indicate that primarily muscles that are further along in the disease process showed increases inT(2)heterogeneity and changes in some metabolic indices. No clear differences were found for the DTI indices between groups. Show less
Tao, Q.; Lelieveldt, B.P.F.; Geest, R.J. van der 2020
OBJECTIVE. The recent advancement of deep learning techniques has profoundly impacted research on quantitative cardiac MRI analysis. The purpose of this article is to introduce the concept of deep... Show moreOBJECTIVE. The recent advancement of deep learning techniques has profoundly impacted research on quantitative cardiac MRI analysis. The purpose of this article is to introduce the concept of deep learning, review its current applications on quantitative cardiac MRI, and discuss its limitations and challenges.CONCLUSION. Deep learning has shown state-of-the-art performance on quantitative analysis of multiple cardiac MRI sequences and holds great promise for future use in clinical practice and scientific research. Show less
