Ziyafer Gizem Portakal1,2, Sophie Shermer3, Christopher Jenkins3, Emiliano Spezi2,4, Teresa Perrett2, Nina Tuncel5, Jonathan Phillips6. 1. Department of Physics, Science and Arts Faculty, Cukurova University, 01330, Adana, Turkey. 2. Department of Medical Physics, Velindre Cancer Centre, CF14 2TL, Cardiff, UK. 3. Department of Physics, College of Science, Swansea University, SA2 8PP, Swansea, UK. 4. School of Engineering, Cardiff University, CF24 3AA, Cardiff, UK. 5. Department of Physics, Science Faculty, Akdeniz University, 07058, Antalya, Turkey. 6. Institute of Life Science, Medical School, Swansea University, Swansea, SA2 8PP, UK.
Abstract
PURPOSE: The aim of this work was to create tissue-mimicking gel phantoms appropriate for diffusion kurtosis imaging (DKI) for quality assurance, protocol optimization, and sequence development. METHODS: A range of agar, agarose, and polyvinyl alcohol phantoms with concentrations ranging from 1.0% to 3.5%, 0.5% to 3.0%, and 10% to 20%, respectively, and up to 3 g of glass microspheres per 100 ml were created. Diffusion coefficients, excess kurtosis values, and relaxation rates were experimentally determined. RESULTS: The kurtosis values for the plain gels ranged from 0.05 with 95% confidence interval (CI) of (0.029,0.071) to 0.216(0.185,0.246), well below the kurtosis values reported in the literature for various tissues. The addition of glass microspheres increased the kurtosis of the gels with values up to 0.523(0.465,0.581) observed for gels with the highest concentration of microspheres. Repeat scans of some of the gels after more than 6 months of storage at room temperature indicate changes in the diffusion parameters of less than 10%. The addition of the glass microspheres reduces the apparent diffusion coefficients (ADCs) and increases the longitudinal and transverse relaxation rates, but the values remain comparable to those for plain gels and tissue, with ADCs observed ranging from 818(585,1053) × 10-6 mm2 /s to 2257(2118,2296) × 10-6 mm2 /s, R1 values ranging from 0.34(0.32,0.35) 1/s to 0.51(0.50,0.52) 1/s, and R2 values ranging from 9.69(9.34,10.04) 1/s to 33.07(27.10, 39.04) 1/s. CONCLUSIONS: Glass microspheres can be used to effectively modify diffusion properties of gel phantoms and achieve a range of kurtosis values comparable to those reported for a variety of tissues.
PURPOSE: The aim of this work was to create tissue-mimicking gel phantoms appropriate for diffusion kurtosis imaging (DKI) for quality assurance, protocol optimization, and sequence development. METHODS: A range of agar, agarose, and polyvinyl alcohol phantoms with concentrations ranging from 1.0% to 3.5%, 0.5% to 3.0%, and 10% to 20%, respectively, and up to 3 g of glass microspheres per 100 ml were created. Diffusion coefficients, excess kurtosis values, and relaxation rates were experimentally determined. RESULTS: The kurtosis values for the plain gels ranged from 0.05 with 95% confidence interval (CI) of (0.029,0.071) to 0.216(0.185,0.246), well below the kurtosis values reported in the literature for various tissues. The addition of glass microspheres increased the kurtosis of the gels with values up to 0.523(0.465,0.581) observed for gels with the highest concentration of microspheres. Repeat scans of some of the gels after more than 6 months of storage at room temperature indicate changes in the diffusion parameters of less than 10%. The addition of the glass microspheres reduces the apparent diffusion coefficients (ADCs) and increases the longitudinal and transverse relaxation rates, but the values remain comparable to those for plain gels and tissue, with ADCs observed ranging from 818(585,1053) × 10-6 mm2 /s to 2257(2118,2296) × 10-6 mm2 /s, R1 values ranging from 0.34(0.32,0.35) 1/s to 0.51(0.50,0.52) 1/s, and R2 values ranging from 9.69(9.34,10.04) 1/s to 33.07(27.10, 39.04) 1/s. CONCLUSIONS: Glass microspheres can be used to effectively modify diffusion properties of gel phantoms and achieve a range of kurtosis values comparable to those reported for a variety of tissues.
Authors: Dariya I Malyarenko; Scott D Swanson; Amaresha S Konar; Eve LoCastro; Ramesh Paudyal; Michael Z Liu; Sachin R Jambawalikar; Lawrence H Schwartz; Amita Shukla-Dave; Thomas L Chenevert Journal: Tomography Date: 2019-03
Authors: Xiaoman Mao; Pilar Calero-Pérez; David Montpeyó; Jordi Bruna; Victor J Yuste; Ana Paula Candiota; Julia Lorenzo; Fernando Novio; Daniel Ruiz-Molina Journal: Nanomaterials (Basel) Date: 2022-04-05 Impact factor: 5.076
Authors: M Martin Jensen; Zachary B Barber; Nitish Khurana; Kyle J Isaacson; Douglas Steinhauff; Bryant Green; Joseph Cappello; Abigail Pulsipher; Hamidreza Ghandehari; Jeremiah A Alt Journal: Theranostics Date: 2020-03-15 Impact factor: 11.556