Jessica L Nute1, Lucia Le Roux, Adam G Chandler, Veera Baladandayuthapani, Dawid Schellingerhout, Dianna D Cody. 1. From the Departments of *Imaging Physics, and †Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX; ‡GE Healthcare, Waukesha, WI; Departments of §Biostatistics, and ∥Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Abstract
OBJECTIVES: Calcific and hemorrhagic intracranial lesions with attenuation levels of less than 100 Hounsfield units (HUs) cannot currently be reliably differentiated by single-energy computed tomography (SECT). The proper differentiation of these lesion types would have a multitude of clinical applications. A phantom model was used to test the ability of dual-energy CT (DECT) to differentiate such lesions. MATERIALS AND METHODS: Agar gel-bound ferric oxide and hydroxyapatite were used to model hemorrhage and calcification, respectively. Gel models were scanned using SECT and DECT and organized into SECT attenuation-matched pairs at 16 attenuation levels between 0 and 100 HU. Dual-energy CT data were analyzed using 3-dimensional (3D) Gaussian mixture models (GMMs), as well as a simplified threshold plane metric derived from the 3D GMM, to assign voxels to hemorrhagic or calcific categories. Accuracy was calculated by comparing predicted voxel assignments with actual voxel identities. RESULTS: We measured 6032 voxels from each gel model, for a total of 193,024 data points (16 matched model pairs). Both the 3D GMM and its more clinically implementable threshold plane derivative yielded similar results, with higher than 90% accuracy at matched SECT attenuation levels of 50 HU and greater. CONCLUSIONS: Hemorrhagic and calcific lesions with attenuation levels between 50 and 100 HU were differentiable using DECT in a clinically relevant phantom system with higher than 90% accuracy. This method warrants further testing for potential clinical applications.
OBJECTIVES: Calcific and hemorrhagic intracranial lesions with attenuation levels of less than 100 Hounsfield units (HUs) cannot currently be reliably differentiated by single-energy computed tomography (SECT). The proper differentiation of these lesion types would have a multitude of clinical applications. A phantom model was used to test the ability of dual-energy CT (DECT) to differentiate such lesions. MATERIALS AND METHODS:Agar gel-bound ferric oxide and hydroxyapatite were used to model hemorrhage and calcification, respectively. Gel models were scanned using SECT and DECT and organized into SECT attenuation-matched pairs at 16 attenuation levels between 0 and 100 HU. Dual-energy CT data were analyzed using 3-dimensional (3D) Gaussian mixture models (GMMs), as well as a simplified threshold plane metric derived from the 3D GMM, to assign voxels to hemorrhagic or calcific categories. Accuracy was calculated by comparing predicted voxel assignments with actual voxel identities. RESULTS: We measured 6032 voxels from each gel model, for a total of 193,024 data points (16 matched model pairs). Both the 3D GMM and its more clinically implementable threshold plane derivative yielded similar results, with higher than 90% accuracy at matched SECT attenuation levels of 50 HU and greater. CONCLUSIONS:Hemorrhagic and calcific lesions with attenuation levels between 50 and 100 HU were differentiable using DECT in a clinically relevant phantom system with higher than 90% accuracy. This method warrants further testing for potential clinical applications.
Authors: John Mongan; Samira Rathnayake; Yanjun Fu; Runtang Wang; Ella F Jones; Dong-Wei Gao; Benjamin M Yeh Journal: Radiology Date: 2012-07-09 Impact factor: 11.105
Authors: Joel G Fletcher; Naoki Takahashi; Robert Hartman; Luis Guimaraes; James E Huprich; David M Hough; Lifeng Yu; Cynthia H McCollough Journal: Radiol Clin North Am Date: 2009-01 Impact factor: 2.303
Authors: M P M Tijssen; P A M Hofman; A A R Stadler; W van Zwam; R de Graaf; R J van Oostenbrugge; E Klotz; J E Wildberger; A A Postma Journal: Eur Radiol Date: 2013-11-21 Impact factor: 5.315
Authors: Lucas L Geyer; Michael Scherr; Markus Körner; Stefan Wirth; Paul Deak; Maximilian F Reiser; Ulrich Linsenmaier Journal: Eur J Radiol Date: 2011-03-21 Impact factor: 3.528
Authors: Anno Graser; Thorsten R C Johnson; Elizabeth M Hecht; Christoph R Becker; Christianne Leidecker; Michael Staehler; Christian G Stief; Henriette Hildebrandt; Myrna C B Godoy; Myra E Finn; Flora Stepansky; Maximilian F Reiser; Michael Macari Journal: Radiology Date: 2009-06-01 Impact factor: 11.105
Authors: Doris Leithner; Tatjana Gruber-Rouh; Martin Beeres; Julian L Wichmann; Scherwin Mahmoudi; Simon S Martin; Lukas Lenga; Moritz H Albrecht; Christian Booz; Thomas J Vogl; Jan-Erik Scholtz Journal: Br J Radiol Date: 2018-06-05 Impact factor: 3.039
Authors: Tommaso D'Angelo; Moritz H Albrecht; Danilo Caudo; Silvio Mazziotti; Thomas J Vogl; Julian L Wichmann; Simon Martin; Ibrahim Yel; Giorgio Ascenti; Vitali Koch; Giuseppe Cicero; Alfredo Blandino; Christian Booz Journal: Eur Radiol Exp Date: 2021-09-03