PURPOSE: Fat fraction measurement in muscular dystrophy has an important role to play in future therapy trials. Undersampled data acquisition reconstructed by combined compressed sensing and parallel imaging (CS-PI) can potentially reduce trial cost and improve compliance. These benefits are only gained from prospectively undersampled acquisitions. METHODS: Eight patients with Becker muscular dystrophy were recruited and prospectively undersampled data at ratios of 3.65×, 4.94×, and 6.42× were acquired in addition to fully sampled data: equivalent coherent undersamplings were acquired for reconstruction with parallel imaging alone (PI). Fat fraction maps and maps of total signal were created using a combined compressed sensing/parallel imaging (CS-PI) reconstruction. RESULTS: The CS-PI reconstructions are of sufficient quality to allow muscle delineation at 3.65× and 4.94× undersampling but some muscles were obscured at 6.42×. When plotted against the fat fractions derived from fully sampled data, non-significant bias and 95% limits of agreement of 1.58%, 2.17% and 2.41% were found for the three CS-PI reconstructions, while a 3.36× PI reconstruction yields 2.78%, 1.8 times worse than the equivalent CS-PI reconstruction. CONCLUSION: Prospective undersampling and CS-PI reconstruction of muscle fat fraction mapping can be used to accelerate muscle fat fraction measurement in muscular dystrophy.
PURPOSE: Fat fraction measurement in muscular dystrophy has an important role to play in future therapy trials. Undersampled data acquisition reconstructed by combined compressed sensing and parallel imaging (CS-PI) can potentially reduce trial cost and improve compliance. These benefits are only gained from prospectively undersampled acquisitions. METHODS: Eight patients with Becker muscular dystrophy were recruited and prospectively undersampled data at ratios of 3.65×, 4.94×, and 6.42× were acquired in addition to fully sampled data: equivalent coherent undersamplings were acquired for reconstruction with parallel imaging alone (PI). Fat fraction maps and maps of total signal were created using a combined compressed sensing/parallel imaging (CS-PI) reconstruction. RESULTS: The CS-PI reconstructions are of sufficient quality to allow muscle delineation at 3.65× and 4.94× undersampling but some muscles were obscured at 6.42×. When plotted against the fat fractions derived from fully sampled data, non-significant bias and 95% limits of agreement of 1.58%, 2.17% and 2.41% were found for the three CS-PI reconstructions, while a 3.36× PI reconstruction yields 2.78%, 1.8 times worse than the equivalent CS-PI reconstruction. CONCLUSION: Prospective undersampling and CS-PI reconstruction of muscle fat fraction mapping can be used to accelerate muscle fat fraction measurement in muscular dystrophy.
Authors: Felix Lugauer; Dominik Nickel; Jens Wetzl; Berthold Kiefer; Joachim Hornegger; Andreas Maier Journal: MAGMA Date: 2016-11-07 Impact factor: 2.310
Authors: Pierre G Carlier; Benjamin Marty; Olivier Scheidegger; Paulo Loureiro de Sousa; Pierre-Yves Baudin; Eduard Snezhko; Dmitry Vlodavets Journal: J Neuromuscul Dis Date: 2016-03-03
Authors: Alison M Barnard; Donovan J Lott; Abhinandan Batra; William T Triplett; Sean C Forbes; Samuel L Riehl; Rebecca J Willcocks; Barbara K Smith; Krista Vandenborne; Glenn A Walter Journal: J Neurol Date: 2019-07-26 Impact factor: 4.849
Authors: Thom T J Veeger; Erik W van Zwet; Diaa Al Mohamad; Karin J Naarding; Nienke M van de Velde; Melissa T Hooijmans; Andrew G Webb; Erik H Niks; Jurriaan H de Groot; Hermien E Kan Journal: Muscle Nerve Date: 2021-08-25 Impact factor: 3.852
Authors: Valeria Ricotti; Matthew R B Evans; Christopher D J Sinclair; Jordan W Butler; Deborah A Ridout; Jean-Yves Hogrel; Ahmed Emira; Jasper M Morrow; Mary M Reilly; Michael G Hanna; Robert L Janiczek; Paul M Matthews; Tarek A Yousry; Francesco Muntoni; John S Thornton Journal: PLoS One Date: 2016-09-20 Impact factor: 3.240
Authors: Gustav J Strijkers; Ericky C A Araujo; Noura Azzabou; David Bendahan; Andrew Blamire; Jedrek Burakiewicz; Pierre G Carlier; Bruce Damon; Xeni Deligianni; Martijn Froeling; Arend Heerschap; Kieren G Hollingsworth; Melissa T Hooijmans; Dimitrios C Karampinos; George Loudos; Guillaume Madelin; Benjamin Marty; Armin M Nagel; Aart J Nederveen; Jules L Nelissen; Francesco Santini; Olivier Scheidegger; Fritz Schick; Christopher Sinclair; Ralph Sinkus; Paulo L de Sousa; Volker Straub; Glenn Walter; Hermien E Kan Journal: J Neuromuscul Dis Date: 2019