W Zhou1, J I Lane1, M L Carlson2, M R Bruesewitz1, R J Witte1, K K Koeller1, L J Eckel1, R E Carter3, C H McCollough1, S Leng4. 1. From the Departments of Radiology (W.Z., J.I.L., M.R.B., R.J.W., K.K.K., L.J.E., C.H.M., S.L.). 2. Otolaryngology-Head and Neck Surgery (M.L.C.). 3. Division of Biomedical Statistics and Informatics (R.E.C.), Mayo Clinic, Rochester, Minnesota. 4. From the Departments of Radiology (W.Z., J.I.L., M.R.B., R.J.W., K.K.K., L.J.E., C.H.M., S.L.) leng.shuai@mayo.edu.
Abstract
BACKGROUND AND PURPOSE: Evaluating abnormalities of the temporal bone requires high-spatial-resolution CT imaging. Our aim was to assess the performance of photon-counting-detector ultra-high-resolution acquisitions for temporal bone imaging and compare the results with those of energy-integrating-detector ultra-high-resolution acquisitions. MATERIALS AND METHODS: Phantom studies were conducted to quantify spatial resolution of the ultra-high-resolution mode on a prototype photon-counting-detector CT scanner and an energy-integrating-detector CT scanner that uses a comb filter. Ten cadaveric temporal bones were scanned on both systems with the radiation dose matched to that of the clinical examinations. Images were reconstructed using a sharp kernel, 0.6-mm (minimum) thickness for energy-integrating-detector CT, and 0.6- and 0.25-mm (minimum) thicknesses for photon-counting-detector CT. Image noise was measured and compared using adjusted 1-way ANOVA. Images were reviewed blindly by 3 neuroradiologists to assess the incudomallear joint, stapes footplate, modiolus, and overall image quality. The ranking results for each specimen and protocol were compared using the Friedman test. The Krippendorff α was used for interreader agreement. RESULTS: Photon-counting-detector CT showed an increase of in-plane resolution compared with energy-integrating-detector CT. At the same thickness (0.6 mm), images from photon-counting-detector CT had significantly lower (P < .001) image noise compared with energy-integrating-detector CT. Readers preferred the photon-counting-detector CT images to the energy-integrating-detector images for all 3 temporal bone structures. A moderate interreader agreement was observed with the Krippendorff α = 0.50. For overall image quality, photon-counting-detector CT image sets were ranked significantly higher than images from energy-integrating-detector CT (P < .001). CONCLUSIONS: This study demonstrated substantially better delineation of fine anatomy for the temporal bones scanned with the ultra-high-resolution mode of photon-counting-detector CT compared with the ultra-high-resolution mode of a commercial energy-integrating-detector CT scanner.
BACKGROUND AND PURPOSE: Evaluating abnormalities of the temporal bone requires high-spatial-resolution CT imaging. Our aim was to assess the performance of photon-counting-detector ultra-high-resolution acquisitions for temporal bone imaging and compare the results with those of energy-integrating-detector ultra-high-resolution acquisitions. MATERIALS AND METHODS: Phantom studies were conducted to quantify spatial resolution of the ultra-high-resolution mode on a prototype photon-counting-detector CT scanner and an energy-integrating-detector CT scanner that uses a comb filter. Ten cadaveric temporal bones were scanned on both systems with the radiation dose matched to that of the clinical examinations. Images were reconstructed using a sharp kernel, 0.6-mm (minimum) thickness for energy-integrating-detector CT, and 0.6- and 0.25-mm (minimum) thicknesses for photon-counting-detector CT. Image noise was measured and compared using adjusted 1-way ANOVA. Images were reviewed blindly by 3 neuroradiologists to assess the incudomallear joint, stapes footplate, modiolus, and overall image quality. The ranking results for each specimen and protocol were compared using the Friedman test. The Krippendorff α was used for interreader agreement. RESULTS: Photon-counting-detector CT showed an increase of in-plane resolution compared with energy-integrating-detector CT. At the same thickness (0.6 mm), images from photon-counting-detector CT had significantly lower (P < .001) image noise compared with energy-integrating-detector CT. Readers preferred the photon-counting-detector CT images to the energy-integrating-detector images for all 3 temporal bone structures. A moderate interreader agreement was observed with the Krippendorff α = 0.50. For overall image quality, photon-counting-detector CT image sets were ranked significantly higher than images from energy-integrating-detector CT (P < .001). CONCLUSIONS: This study demonstrated substantially better delineation of fine anatomy for the temporal bones scanned with the ultra-high-resolution mode of photon-counting-detector CT compared with the ultra-high-resolution mode of a commercial energy-integrating-detector CT scanner.
Authors: K S Caldemeyer; K Sandrasegaran; C N Shinaver; V P Mathews; R R Smith; K K Kopecky Journal: AJR Am J Roentgenol Date: 1999-06 Impact factor: 3.959
Authors: John I Lane; E Paul Lindell; Robert J Witte; David R DeLone; Colin L W Driscoll Journal: Radiographics Date: 2006 Jan-Feb Impact factor: 5.333
Authors: O Majdani; K Thews; S Bartling; M Leinung; C Dalchow; R Labadie; T Lenarz; G Heidrich Journal: AJNR Am J Neuroradiol Date: 2009-04-15 Impact factor: 3.825
Authors: J P Schlomka; E Roessl; R Dorscheid; S Dill; G Martens; T Istel; C Bäumer; C Herrmann; R Steadman; G Zeitler; A Livne; R Proksa Journal: Phys Med Biol Date: 2008-07-08 Impact factor: 3.609
Authors: Koen Nieman; Filippo Cademartiri; Pedro A Lemos; Rolf Raaijmakers; Peter M T Pattynama; Pim J de Feyter Journal: Circulation Date: 2002-10-15 Impact factor: 29.690
Authors: Christine M Glastonbury; H Christian Davidson; H Ric Harnsberger; John Butler; Thomas R Kertesz; Clough Shelton Journal: AJNR Am J Neuroradiol Date: 2002-04 Impact factor: 3.825
Authors: Amir Pourmorteza; Rolf Symons; Veit Sandfort; Marissa Mallek; Matthew K Fuld; Gregory Henderson; Elizabeth C Jones; Ashkan A Malayeri; Les R Folio; David A Bluemke Journal: Radiology Date: 2016-02-03 Impact factor: 11.105
Authors: Joakim da Silva; Fredrik Grönberg; Björn Cederström; Mats Persson; Martin Sjölin; Zlatan Alagic; Robert Bujila; Mats Danielsson Journal: J Med Imaging (Bellingham) Date: 2019-10-15
Authors: Nancy Pham; Osama Raslan; Edward B Strong; John Boone; Arthur Dublin; Shuai Chen; Lotfi Hacein-Bey Journal: J Neurol Surg B Skull Base Date: 2022-01-31
Authors: E Wehrse; L Klein; L T Rotkopf; W L Wagner; M Uhrig; C P Heußel; C H Ziener; S Delorme; S Heinze; M Kachelrieß; H-P Schlemmer; S Sawall Journal: Radiologe Date: 2021-02-17 Impact factor: 0.635
Authors: J C Benson; K Rajendran; J I Lane; F E Diehn; N M Weber; J E Thorne; N B Larson; J G Fletcher; C H McCollough; S Leng Journal: AJNR Am J Neuroradiol Date: 2022-03-24 Impact factor: 3.825