Björn Lampinen1, Filip Szczepankiewicz2,3, Johan Mårtensson4, Danielle van Westen2, Oskar Hansson5, Carl-Fredrik Westin3, Markus Nilsson2. 1. Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden. 2. Clinical Sciences Lund, Radiology, Lund University, Lund, Sweden. 3. Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States. 4. Clinical Sciences Lund, Department of Logopedics, Phoniatrics and Audiology, Lund University, Lund, Sweden. 5. Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Lund, Sweden.
Abstract
PURPOSE: To optimize diffusion-relaxation MRI with tensor-valued diffusion encoding for precise estimation of compartment-specific fractions, diffusivities, and T2 values within a two-compartment model of white matter, and to explore the approach in vivo. METHODS: Sampling protocols featuring different b-values (b), b-tensor shapes (bΔ ), and echo times (TE) were optimized using Cramér-Rao lower bounds (CRLB). Whole-brain data were acquired in children, adults, and elderly with white matter lesions. Compartment fractions, diffusivities, and T2 values were estimated in a model featuring two microstructural compartments represented by a "stick" and a "zeppelin." RESULTS: Precise parameter estimates were enabled by sampling protocols featuring seven or more "shells" with unique b/bΔ /TE-combinations. Acquisition times were approximately 15 minutes. In white matter of adults, the "stick" compartment had a fraction of approximately 0.5 and, compared with the "zeppelin" compartment, featured lower isotropic diffusivities (0.6 vs. 1.3 μm2 /ms) but higher T2 values (85 vs. 65 ms). Children featured lower "stick" fractions (0.4). White matter lesions exhibited high "zeppelin" isotropic diffusivities (1.7 μm2 /ms) and T2 values (150 ms). CONCLUSIONS: Diffusion-relaxation MRI with tensor-valued diffusion encoding expands the set of microstructure parameters that can be precisely estimated and therefore increases their specificity to biological quantities.
PURPOSE: To optimize diffusion-relaxation MRI with tensor-valued diffusion encoding for precise estimation of compartment-specific fractions, diffusivities, and T2 values within a two-compartment model of white matter, and to explore the approach in vivo. METHODS: Sampling protocols featuring different b-values (b), b-tensor shapes (bΔ ), and echo times (TE) were optimized using Cramér-Rao lower bounds (CRLB). Whole-brain data were acquired in children, adults, and elderly with white matter lesions. Compartment fractions, diffusivities, and T2 values were estimated in a model featuring two microstructural compartments represented by a "stick" and a "zeppelin." RESULTS: Precise parameter estimates were enabled by sampling protocols featuring seven or more "shells" with unique b/bΔ /TE-combinations. Acquisition times were approximately 15 minutes. In white matter of adults, the "stick" compartment had a fraction of approximately 0.5 and, compared with the "zeppelin" compartment, featured lower isotropic diffusivities (0.6 vs. 1.3 μm2 /ms) but higher T2 values (85 vs. 65 ms). Children featured lower "stick" fractions (0.4). White matter lesions exhibited high "zeppelin" isotropic diffusivities (1.7 μm2 /ms) and T2 values (150 ms). CONCLUSIONS: Diffusion-relaxation MRI with tensor-valued diffusion encoding expands the set of microstructure parameters that can be precisely estimated and therefore increases their specificity to biological quantities.
Authors: Sune N Jespersen; Christopher D Kroenke; Leif Østergaard; Joseph J H Ackerman; Dmitriy A Yablonskiy Journal: Neuroimage Date: 2006-12-22 Impact factor: 6.556
Authors: D J Werring; D Brassat; A G Droogan; C A Clark; M R Symms; G J Barker; D G MacManus; A J Thompson; D H Miller Journal: Brain Date: 2000-08 Impact factor: 13.501
Authors: Björn Lampinen; Filip Szczepankiewicz; Danielle van Westen; Elisabet Englund; Pia C Sundgren; Jimmy Lätt; Freddy Ståhlberg; Markus Nilsson Journal: Magn Reson Med Date: 2016-03-10 Impact factor: 4.668
Authors: Santiago Coelho; Steven H Baete; Gregory Lemberskiy; Benjamin Ades-Aron; Genevieve Barrol; Jelle Veraart; Dmitry S Novikov; Els Fieremans Journal: Neuroimage Date: 2022-05-08 Impact factor: 7.400
Authors: Qiuyun Fan; Cornelius Eichner; Maryam Afzali; Lars Mueller; Chantal M W Tax; Mathias Davids; Mirsad Mahmutovic; Boris Keil; Berkin Bilgic; Kawin Setsompop; Hong-Hsi Lee; Qiyuan Tian; Chiara Maffei; Gabriel Ramos-Llordén; Aapo Nummenmaa; Thomas Witzel; Anastasia Yendiki; Yi-Qiao Song; Chu-Chung Huang; Ching-Po Lin; Nikolaus Weiskopf; Alfred Anwander; Derek K Jones; Bruce R Rosen; Lawrence L Wald; Susie Y Huang Journal: Neuroimage Date: 2022-02-23 Impact factor: 7.400
Authors: E V R DiBella; A Sharma; L Richards; V Prabhakaran; J J Majersik; S K HashemizadehKolowri Journal: AJNR Am J Neuroradiol Date: 2022-03-10 Impact factor: 3.825
Authors: Markus Nilsson; Greta Eklund; Filip Szczepankiewicz; Mikael Skorpil; Karin Bryskhe; Carl-Fredrik Westin; Claes Lindh; Lennart Blomqvist; Fredrik Jäderling Journal: Magn Reson Med Date: 2021-05-31 Impact factor: 3.737
Authors: Remika Mito; Thijs Dhollander; Ying Xia; David Raffelt; Olivier Salvado; Leonid Churilov; Christopher C Rowe; Amy Brodtmann; Victor L Villemagne; Alan Connelly Journal: Neuroimage Clin Date: 2020-10-26 Impact factor: 4.881
Authors: Daniel Johnson; Antonio Ricciardi; Wallace Brownlee; Baris Kanber; Ferran Prados; Sara Collorone; Enrico Kaden; Ahmed Toosy; Daniel C Alexander; Claudia A M Gandini Wheeler-Kingshott; Olga Ciccarelli; Francesco Grussu Journal: Front Neurol Date: 2021-06-14 Impact factor: 4.003
Authors: Björn J Langbein; Filip Szczepankiewicz; Carl-Fredrik Westin; Camden Bay; Stephan E Maier; Adam S Kibel; Clare M Tempany; Fiona M Fennessy Journal: Invest Radiol Date: 2021-12-01 Impact factor: 6.016