INTRODUCTION: Accurate quantification of hemodynamic parameters using dynamic contrast enhanced (DCE) MRI requires a measurement of tissue T 1 prior to contrast injection (T 1). We evaluate (i) T 1 estimation using the variable flip angle (VFA) and the saturation recovery (SR) techniques and (ii) investigate if accurate estimation of DCE parameters outperform a time-saving approach with a predefined T 1 value when differentiating high- from low-grade gliomas. METHODS: The accuracy and precision of T 1 measurements, acquired by VFA and SR, were investigated by computer simulations and in glioma patients using an equivalence test (p > 0.05 showing significant difference). The permeability measure, K trans, cerebral blood flow (CBF), and - volume, V p, were calculated in 42 glioma patients, using fixed T 1 of 1500 ms or an individual T 1 measurement, using SR. The areas under the receiver operating characteristic curves (AUCs) were used as measures for accuracy to differentiate tumor grade. RESULTS: The T 1 values obtained by VFA showed larger variation compared to those obtained using SR both in the digital phantom and the human data (p > 0.05). Although a fixed T 1 introduced a bias into the DCE calculation, this had only minor impact on the accuracy differentiating high-grade from low-grade gliomas, (AUCfix = 0.906 and AUCind = 0.884 for K trans; AUCfix = 0.863 and AUCind = 0.856 for V p; p for AUC comparison > 0.05). CONCLUSION: T 1 measurements by VFA were less precise, and the SR method is preferable, when accurate parameter estimation is required. Semiquantitative DCE values, based on predefined T 1 values, were sufficient to perform tumor grading in our study.
INTRODUCTION: Accurate quantification of hemodynamic parameters using dynamic contrast enhanced (DCE) MRI requires a measurement of tissue T 1 prior to contrast injection (T 1). We evaluate (i) T 1 estimation using the variable flip angle (VFA) and the saturation recovery (SR) techniques and (ii) investigate if accurate estimation of DCE parameters outperform a time-saving approach with a predefined T 1 value when differentiating high- from low-grade gliomas. METHODS: The accuracy and precision of T 1 measurements, acquired by VFA and SR, were investigated by computer simulations and in gliomapatients using an equivalence test (p > 0.05 showing significant difference). The permeability measure, K trans, cerebral blood flow (CBF), and - volume, V p, were calculated in 42 gliomapatients, using fixed T 1 of 1500 ms or an individual T 1 measurement, using SR. The areas under the receiver operating characteristic curves (AUCs) were used as measures for accuracy to differentiate tumor grade. RESULTS: The T 1 values obtained by VFA showed larger variation compared to those obtained using SR both in the digital phantom and the human data (p > 0.05). Although a fixed T 1 introduced a bias into the DCE calculation, this had only minor impact on the accuracy differentiating high-grade from low-grade gliomas, (AUCfix = 0.906 and AUCind = 0.884 for K trans; AUCfix = 0.863 and AUCind = 0.856 for V p; p for AUC comparison > 0.05). CONCLUSION: T 1 measurements by VFA were less precise, and the SR method is preferable, when accurate parameter estimation is required. Semiquantitative DCE values, based on predefined T 1 values, were sufficient to perform tumor grading in our study.
Authors: Brian M Dale; John A Jesberger; Jonathan S Lewin; Claudia M Hillenbrand; Jeffrey L Duerk Journal: J Magn Reson Imaging Date: 2003-11 Impact factor: 4.813
Authors: Tobias Heye; Matthew S Davenport; Jeffrey J Horvath; Sebastian Feuerlein; Steven R Breault; Mustafa R Bashir; Elmar M Merkle; Daniel T Boll Journal: Radiology Date: 2012-12-06 Impact factor: 11.105
Authors: G M Conte; L Altabella; A Castellano; V Cuccarini; A Bizzi; M Grimaldi; A Costa; M Caulo; A Falini; N Anzalone Journal: Eur Radiol Date: 2019-04-10 Impact factor: 5.315
Authors: Hyun Jung Yoon; Kook Jin Ahn; Song Lee; Jin Hee Jang; Hyun Seok Choi; So Lyung Jung; Bum Soo Kim; Shin Soo Jeun; Yong Kil Hong Journal: Neuroradiology Date: 2017-05-26 Impact factor: 2.804
Authors: J G Nam; K M Kang; S H Choi; W H Lim; R-E Yoo; J-H Kim; T J Yun; C-H Sohn Journal: AJNR Am J Neuroradiol Date: 2017-10-26 Impact factor: 3.825
Authors: Sun Won Park; Seung Hong Choi; Yeonah Kang; Eun Kyoung Hong; Jung Hyo Rhim; Roh Eul Yoo; Koung Mi Kang; Tae Jin Yun; Ji Hoon Kim; Chul Ho Sohn Journal: Korean J Radiol Date: 2020-06 Impact factor: 3.500
Authors: Anna Tietze; Anne Nielsen; Irene Klærke Mikkelsen; Mikkel Bo Hansen; Annette Obel; Leif Østergaard; Kim Mouridsen Journal: PLoS One Date: 2018-09-26 Impact factor: 3.240
Authors: Seyed Ali Nabavizadeh; Jeffrey B Ware; Samantha Guiry; MacLean P Nasrallah; Jazmine J Mays; Jacob E Till; Jasmin Hussain; Aseel Abdalla; Stephanie S Yee; Zev A Binder; Donald M O'Rourke; Steven Brem; Arati S Desai; Ronald Wolf; Erica L Carpenter; Stephen J Bagley Journal: Neurooncol Adv Date: 2020-02-27