Peer reviewed publications as a co-author

Hager, B., Juras, V., Zaric, O., Szomolanyi, P., Trattnig, S., Deligianni, X. (2023). The Variable Echo Time (vTE) Sequence. In: Du, J., Bydder, G.M. (eds) MRI of Short and Ultrashort-T_2 Tissues. Springer, Cham. https://doi.org/10.1007/978-3-031-35197-6_9

Colelli G., Barzaghi L, …Deligianni X., Pichiecchio A., Radiomics and machine learning applied to STIR sequence for prediction of quantitative parameters in facioscapulohumeral disease, Frontiers in neurology, https://doi.org/10.3389/fneur.2023.1105276

Vegezzi E, Cortese A, …, Deligianni X, Santini F, …, Pichiecchio A., Muscle quantitative MRI as a novel biomarker in hereditary transthyretin amyloidosis with polyneuropathy: a cross-sectional study, J Neurol. 2022 Sep 6. doi: 10.1007/s00415-022-11336-z.

Hager, B., Schreiner, M.M., Walzer, S.M., Hirtler, L., Mlynarik, V., Berg, A., Deligianni, X., Bieri, O., Windhager, R., Trattnig, S. and Juras, V. (2022), Transverse Relaxation Anisotropy of the Achilles and Patellar Tendon Studied by MR Microscopy. J Magn Reson Imaging. https://doi.org/10.1002/jmri.28095

Paoletti M., Diamanti L, …, Deligianni X, …, Bergsland N, and Pichiecchio A, Longitudinal Quantitative MRI Evaluation of Muscle Involvement in Amyotrophic Lateral Sclerosis, Front. Neurol., (2021), https://doi.org/10.3389/fneur.2021.749736

Agosti A., Shaqiri E.,…, Deligianni X.,…et al., Deep learning for automatic segmentation of thigh and leg muscles, Magn Reson Mater Phy (2021). https://doi.org/10.1007

Putananickal N., …, Deligianni X., …et al., Treatment with L-Citrulline in patients with post-polio syndrome: A single center, randomized, double blind, placebo-controlled trial, Neuromuscular Disorders, (2021), https://doi.org/10.1016/j.nmd.2021.08.011

Weidensteiner C*, Madoerin P, Deligianni X, et al., Quantification and monitoring of the effect of botulinum toxin A on paretic calf muscles of children with cerebral palsy with MRI: a preliminary study, (2021), Front. Neurol. | doi: 0.3389/fneur.2021.630435

Savini G., Asteggiano C., …Deligianni X.,et al. , Pilot study on quantitative cervical cord and muscular MRI in spinal muscular atrophy: promising biomarkers of disease evolution and treatment?, (2021), Front. Neurol. | doi: 10.3389/fneur.2021.613834

Felisaz, P.F., Belatti, E., Deligianni, X. et al. Variable echo time imaging for detecting the short T2* components of the sciatic nerve: a validation study. Magn Reson Mater Phy 34, 411–419 (2021). https://doi.org/10.1007/s10334-020-00886-w

Akinci D’Antonoli T, Santini F, Deligianni X, et al. Combination of Quantitative MRI Fat Fraction and Texture Analysis to Evaluate Spastic Muscles of Children with Cerebral Palsy, (2021), Front. Neurol. | doi: 10.3389/fneur.2021.633808

Santini F*, Deligianni X, Paoletti M, et al., Fast Open-Source Toolkit for Water T2 Mapping in the Presence of Fat From Multi-Echo Spin-Echo Acquisitions for Muscle MRI, Front. Neurol., 26 February 2021 | https://doi.org/10.3389/fneur.2021.630387

Felisaz PF, Colelli G, … Deligianni X, et al., Texture analysis and machine learning to predict water T2 and fat fraction from non-quantitative MRI of thigh muscles in Facioscapulohumeral muscular dystrophy, European Journal of Radiology, 2020, 109460, ISSN 0720-48X, https://doi.org/10.1016/j.ejrad.2020.109460.

Zbýň, Š., Schreiner, M., …, Deligianni, X., et al., Assessment of Low-Grade Focal Cartilage Lesions in the Knee With Sodium MRI at 7 T Reproducibility and Short-Term, 6-Month Follow-up Data,Investigative Radiology: January 31, 2020,0 doi: 10.1097/RLI.0000000000000652.

Bachmann E., Rosskopf A. B., …, Deligianni X., et al., T1-and T2*-Mapping for Assessment of Tendon Tissue Biophysical Properties: A Phantom MRI Study, Investigative Radiology, (2019), Investigative radiology 54 (4), 212-220, doi:10.1097/RLI.0000000000000532

Hager B, Walzer S.M., Deligianni X., et al., Orientation dependence and decay characteristics of T2* relaxation in the human meniscus studied with 7 Tesla MR microscopy and compared to histology. Magn Reson Med. 81: 921– 933. (2019) doi.org/10.1002/mrm.27443

Schroeder J., Tobler P., …, Deligianni X., et al., Intra-rater and Inter-rater Reliability of Quantitative Thigh Muscle Magnetic Resonance Imaging, Imaging in Medicine (2019) Volume 11, Issue 2.

Strijkers G.J., Araujo E.CA, …., Deligianni X., et al., Exploration of New Contrasts, Targets, and MR Imaging and Spectroscopy Techniques for Neuromuscular Disease – A Workshop Report of Working Group 3 of the Biomedicine and Molecular Biosciences COST Action BM1304 MYO-MRI, Journal of Neuromuscular Diseases, vol. 6, no. 1, pp. 1-30, 2019.

Altermatt A., Santini F., Deligianni X., et al. , Design and construction of an innovative brain phantom prototype for MRI. Magn Reson Med. 2019; 81: 1165– 1171. doi.org/10.1002/mrm.27464.

A Altermatt, F Santini, X Deligianni, et al., Validation of brain atrophy measurements in multiple sclerosis: a physical phantom study, 2018, MULTIPLE SCLEROSIS JOURNAL 24, 222-223.

L Hornakova, V Juras, …, Deligianni X., et al., In vivo assessment of time dependent changes of T2* in medial meniscus under loading at 3T: A preliminary study, Journal of applied biomedicine 2018; 16 (2), 138-144. doi.org/10.1016/j.jab.2017.12.001

Robinson, S. D., Dymerska, B., …, Deligianni, X., et al. (2015), Combining phase images from array coils using a short echo time reference scan (COMPOSER). Magn. Reson. Med., 77: 318-327. doi: 10.1002/mrm.26093

Juras, V. , Apprich, S. , …,Deligianni, X. , et al. (2014), Quantitative MRI analysis of menisci using biexponential T2* fitting with a variable echo time sequence. Magn. Reson. Med., 71: 1015-1023. doi:10.1002/mrm.24760

Haneder, S., Juras, V., …, Deligianni X., et al.,   In vivo sodium (23Na) imaging of the human kidneys at 7 T: Preliminary results, European Radiology Volume 24, Issue 2 , pp 494-501l. Eur Radiol (2014) 24: 494. https://doi.org/10.1007/s00330-013-3032-6.

Riegler G., Deligianni X., Juras V., et al., Journal of Pharmacy and Pharmacology 2014; 2:59-69.

Anders J, SanGiorgio P, Deligianni X, et al., Integrated active tracking detector for MRI-guided interventions, (2012), Magnetic resonance in medicine 67 (1), 290-296, https:///doi.org/10.1002/mrm.23112