BACKGROUND AND PURPOSE: Whole-brain atrophy is of growing interest as an outcome measure in multiple sclerosis (MS) clinical trials. The authors compared the reproducibility and accuracy of 3 quantitative techniques of measurement in patients with MS. METHODS: Thirty-four patients with relapsing-remitting MS (median Expanded Disability Status Scale disability score = 1.5) were studied. Brain parenchymal fraction (BPF) was quantified on spin-echo 2-dimensional T1-weighted axial 5-mm slice thickness sequences by semiautomated (Buffalo, Trieste) or automated (SIENAX) algorithms. RESULTS: Mean +/- SD BPFs were 0.830 +/- 0.04 with Buffalo, 0.824 +/- 0.04 with Trieste, and 0.826 +/- 0.04 with SIENAX methods (P = nonsignificant [NS]). Mean BPF scan-rescan coefficient of variation (COV) was 0.41% for Buffalo, 0.44% for Trieste, and 0.32% for SIENAX (P =NS).The semiautomated methods showed higher accuracy than the automated method in brain extraction (masking; P = .001). The errors of skull stripping included scalp, skull bone marrow, inferior parts of temporal lobes anterior to the brain stem, face structures, sagittal sinuses, eyes, and optic nerves. Buffalo (r = -0.37, P = .034) and Trieste (r = -.36, P = .039) BPFs showed stronger cor relation with disability than SIENAX (r = -0.16, P = .219). These differences were statistically significant (P = .0031 for Buffalo and P = .0037 for Trieste BPF). CONCLUSIONS: This study showed a high reproducibility of both semiautomated and automated methods for brain atrophy measurement. The semiautomated methods showed higher accuracy than the automated SIENAX method did in the evaluation of brain extraction, especially in infratentorial and cortical regions, where operator interaction during the masking processes was essential.
BACKGROUND AND PURPOSE: Whole-brain atrophy is of growing interest as an outcome measure in multiple sclerosis (MS) clinical trials. The authors compared the reproducibility and accuracy of 3 quantitative techniques of measurement in patients with MS. METHODS: Thirty-four patients with relapsing-remitting MS (median Expanded Disability Status Scale disability score = 1.5) were studied. Brain parenchymal fraction (BPF) was quantified on spin-echo 2-dimensional T1-weighted axial 5-mm slice thickness sequences by semiautomated (Buffalo, Trieste) or automated (SIENAX) algorithms. RESULTS: Mean +/- SD BPFs were 0.830 +/- 0.04 with Buffalo, 0.824 +/- 0.04 with Trieste, and 0.826 +/- 0.04 with SIENAX methods (P = nonsignificant [NS]). Mean BPF scan-rescan coefficient of variation (COV) was 0.41% for Buffalo, 0.44% for Trieste, and 0.32% for SIENAX (P =NS).The semiautomated methods showed higher accuracy than the automated method in brain extraction (masking; P = .001). The errors of skull stripping included scalp, skull bone marrow, inferior parts of temporal lobes anterior to the brain stem, face structures, sagittal sinuses, eyes, and optic nerves. Buffalo (r = -0.37, P = .034) and Trieste (r = -.36, P = .039) BPFs showed stronger cor relation with disability than SIENAX (r = -0.16, P = .219). These differences were statistically significant (P = .0031 for Buffalo and P = .0037 for Trieste BPF). CONCLUSIONS: This study showed a high reproducibility of both semiautomated and automated methods for brain atrophy measurement. The semiautomated methods showed higher accuracy than the automated SIENAX method did in the evaluation of brain extraction, especially in infratentorial and cortical regions, where operator interaction during the masking processes was essential.
Authors: Kerstin Bendfeldt; Bernd Taschler; Laura Gaetano; Philip Madoerin; Pascal Kuster; Nicole Mueller-Lenke; Michael Amann; Hugo Vrenken; Viktor Wottschel; Frederik Barkhof; Stefan Borgwardt; Stefan Klöppel; Eva-Maria Wicklein; Ludwig Kappos; Gilles Edan; Mark S Freedman; Xavier Montalbán; Hans-Peter Hartung; Christoph Pohl; Rupert Sandbrink; Till Sprenger; Ernst-Wilhelm Radue; Jens Wuerfel; Thomas E Nichols Journal: Brain Imaging Behav Date: 2019-10 Impact factor: 3.978
Authors: M Vågberg; T Lindqvist; K Ambarki; J B M Warntjes; P Sundström; R Birgander; A Svenningsson Journal: AJNR Am J Neuroradiol Date: 2012-09-13 Impact factor: 3.825
Authors: C Tessa; M Giannelli; R Della Nave; C Lucetti; C Berti; A Ginestroni; U Bonuccelli; M Mascalchi Journal: AJNR Am J Neuroradiol Date: 2008-01-09 Impact factor: 3.825
Authors: C Wang; H N Beadnall; S N Hatton; G Bader; D Tomic; D G Silva; M H Barnett Journal: J Neurol Neurosurg Psychiatry Date: 2016-04-12 Impact factor: 10.154
Authors: Richard Erasto Sungura; John Martin Spitsbergen; Emmanuel Abraham Mpolya; Elingarami Sauli; John-Mary Vianney Journal: Pan Afr Med J Date: 2020-05-21