Browsing by Author "Nopoulos, Peggy"

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    Fully Automated 3D Segmentation of MR-Imaged Calf Muscle Compartments: Neighborhood Relationship Enhanced Fully Convolutional Network
    (Elsevier, 2021) Guo, Zhihui; Zhang, Honghai; Chen, Zhi; van der Plas, Ellen; Gutmann, Laurie; Thedens, Daniel; Nopoulos, Peggy; Sonka, Milan; Neurology, School of Medicine
    Automated segmentation of individual calf muscle compartments from 3D magnetic resonance (MR) images is essential for developing quantitative biomarkers for muscular disease progression and its prediction. Achieving clinically acceptable results is a challenging task due to large variations in muscle shape and MR appearance. In this paper, we present a novel fully convolutional network (FCN) that utilizes contextual information in a large neighborhood and embeds edge-aware constraints for individual calf muscle compartment segmentations. An encoder-decoder architecture is used to systematically enlarge convolution receptive field and preserve information at all resolutions. Edge positions derived from the FCN output muscle probability maps are explicitly regularized using kernel-based edge detection in an end-to-end optimization framework. Our method was evaluated on 40 T1-weighted MR images of 10 healthy and 30 diseased subjects by fourfold cross-validation. Mean DICE coefficients of 88.00-91.29% and mean absolute surface positioning errors of 1.04-1.66 mm were achieved for the five 3D muscle compartments.
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    Quantitative muscle MRI as a sensitive marker of early muscle pathology in myotonic dystrophy type 1
    (Wiley, 2021) van der Plas, Ellen; Gutmann, Laurie; Thedens, Dan; Shields, Richard K.; Langbehn, Kathleen; Guo, Zhihui; Sonka, Milan; Nopoulos, Peggy; Neurology, School of Medicine
    Background: Quantitative muscle MRI as a sensitive marker of early muscle pathology and disease progression in adult-onset myotonic dystrophy type 1. The utility of muscle MRI as a marker of muscle pathology and disease progression in adult-onset myotonic dystrophy type 1 (DM1) was evaluated. Methods: This prospective, longitudinal study included 67 observations from 36 DM1 patients (50% female), and 92 observations from 49 healthy adults (49% female). Lower-leg 3T magnetic resonance imaging (MRI) scans were acquired. Volume and fat fraction (FF) were estimated using a three-point Dixon method, and T2-relaxometry was determined using a multi-echo spin-echo sequence. Muscles were segmented automatically. Mixed linear models were conducted to determine group differences across muscles and image modality, accounting for age, sex, and repeated observations. Differences in rate of change in volume, T2-relaxometry, and FF were also determined with mixed linear regression that included a group by elapsed time interaction. Results: Compared with healthy adults, DM1 patients exhibited reduced volume of the tibialis anterior, soleus, and gastrocnemius (GAS) (all, P < .05). T2-relaxometry and FF were increased across all calf muscles in DM1 compared to controls. (all, P < .01). Signs of muscle pathology, including reduced volume, and increased T2-relaxometry and FF were already noted in DM1 patients who did not exhibit clinical motor symptoms of DM1. As a group, DM1 patients exhibited a more rapid change than did controls in tibialis posterior volume (P = .05) and GAS T2-relaxometry (P = .03) and FF (P = .06). Conclusions: Muscle MRI renders sensitive, early markers of muscle pathology and disease progression in DM1. T2 relaxometry may be particularly sensitive to early muscle changes related to DM1.