Andrea Ferrero1, Ralf Gutjahr2, Ahmed F Halaweish3, Shuai Leng1, Cynthia H McCollough4. 1. Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905. 2. Institut für Informatik, Technische Universität München, Garching bei München, Germany. 3. Siemens Healthcare, Malvern, Pennsylvania. 4. Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905. Electronic address: mccollough.cynthia@mayo.edu.
Abstract
RATIONAL AND OBJECTIVES: This study aims to investigate the performance of a whole-body, photon-counting detector (PCD) computed tomography (CT) system in differentiating urinary stone composition. MATERIALS AND METHODS: Eighty-seven human urinary stones with pure mineral composition were placed in four anthropomorphic water phantoms (35-50 cm lateral dimension) and scanned on a PCD-CT system at 100, 120, and 140 kV. For each phantom size, tube current was selected to match CTDIvol (volume CT dose index) to our clinical practice. Energy thresholds at [25, 65], [25, 70], and [25, 75] keV for 100, 120, and 140 kV, respectively, were used to generate dual-energy images. Each stone was automatically segmented using in-house software; CT number ratios were calculated and used to differentiate stone types in a receiver operating characteristic (ROC) analysis. A comparison with second- and third-generation dual-source, dual-energy CT scanners with conventional energy integrating detectors (EIDs) was performed under matching conditions. RESULTS: For all investigated settings and smaller phantoms, perfect separation between uric acid and non-uric acid stones was achieved (area under the ROC curve [AUC] = 1). For smaller phantoms, performance in differentiation of calcium oxalate and apatite stones was also similar between the three scanners: for the 35-cm phantom size, AUC values of 0.76, 0.79, and 0.80 were recorded for the second- and third-generation EID-CT and for the PCD-CT, respectively. For larger phantoms, PCD-CT and the third-generation EID-CT outperformed the second-generation EID-CT for both differentiation tasks: for a 50-cm phantom size and a uric acid/non-uric acid differentiating task, AUC values of 0.63, 0.95, and 0.99 were recorded for the second- and third-generation EID-CT and for the PCD-CT, respectively. CONCLUSION: PCD-CT provides comparable performance to state-of-the-art EID-CT in differentiating urinary stone composition.
RATIONAL AND OBJECTIVES: This study aims to investigate the performance of a whole-body, photon-counting detector (PCD) computed tomography (CT) system in differentiating urinary stone composition. MATERIALS AND METHODS: Eighty-seven human urinary stones with pure mineral composition were placed in four anthropomorphic water phantoms (35-50 cm lateral dimension) and scanned on a PCD-CT system at 100, 120, and 140 kV. For each phantom size, tube current was selected to match CTDIvol (volume CT dose index) to our clinical practice. Energy thresholds at [25, 65], [25, 70], and [25, 75] keV for 100, 120, and 140 kV, respectively, were used to generate dual-energy images. Each stone was automatically segmented using in-house software; CT number ratios were calculated and used to differentiate stone types in a receiver operating characteristic (ROC) analysis. A comparison with second- and third-generation dual-source, dual-energy CT scanners with conventional energy integrating detectors (EIDs) was performed under matching conditions. RESULTS: For all investigated settings and smaller phantoms, perfect separation between uric acid and non-uric acid stones was achieved (area under the ROC curve [AUC] = 1). For smaller phantoms, performance in differentiation of calcium oxalate and apatite stones was also similar between the three scanners: for the 35-cm phantom size, AUC values of 0.76, 0.79, and 0.80 were recorded for the second- and third-generation EID-CT and for the PCD-CT, respectively. For larger phantoms, PCD-CT and the third-generation EID-CT outperformed the second-generation EID-CT for both differentiation tasks: for a 50-cm phantom size and a uric acid/non-uric acid differentiating task, AUC values of 0.63, 0.95, and 0.99 were recorded for the second- and third-generation EID-CT and for the PCD-CT, respectively. CONCLUSION:PCD-CT provides comparable performance to state-of-the-art EID-CT in differentiating urinary stone composition.
Authors: Ralf Gutjahr; Ahmed F Halaweish; Zhicong Yu; Shuai Leng; Lifeng Yu; Zhoubo Li; Steven M Jorgensen; Erik L Ritman; Steffen Kappler; Cynthia H McCollough Journal: Invest Radiol Date: 2016-07 Impact factor: 6.016
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: Zhicong Yu; Shuai Leng; Steven M Jorgensen; Zhoubo Li; Ralf Gutjahr; Baiyu Chen; Ahmed F Halaweish; Steffen Kappler; Lifeng Yu; Erik L Ritman; Cynthia H McCollough Journal: Phys Med Biol Date: 2016-02-02 Impact factor: 3.609
Authors: Xinhui Duan; Zhoubo Li; Lifeng Yu; Shuai Leng; Ahmed F Halaweish; Joel G Fletcher; Cynthia H McCollough Journal: AJR Am J Roentgenol Date: 2015-12 Impact factor: 3.959
Authors: Chad A Zarse; James A McAteer; Andre J Sommer; Samuel C Kim; Erin K Hatt; James E Lingeman; Andrew P Evan; James C Williams Journal: BMC Urol Date: 2004-12-13 Impact factor: 2.264
Authors: Roy P Marcus; Joel G Fletcher; Andrea Ferrero; Shuai Leng; Ahmed F Halaweish; Ralf Gutjahr; Terri J Vrtiska; Mike L Wells; Felicity T Enders; Cynthia H McCollough Journal: Radiology Date: 2018-08-07 Impact factor: 11.105
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