J Maranzano1, D A Rudko1, D L Arnold1, S Narayanan2. 1. From the Department of Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, McGill University, Montreal, Quebec, Canada. 2. From the Department of Neurology and Neurosurgery, Montreal Neurological Hospital and Institute, McGill University, Montreal, Quebec, Canada. sridar.narayanan@mcgill.ca.
Abstract
BACKGROUND AND PURPOSE: Double inversion recovery has been suggested as the MR imaging contrast of choice for segmenting cortical lesions in patients with multiple sclerosis. In this study, we sought to determine the utility of double inversion recovery for cortical lesion identification by comparing 3 MR imaging reading protocols that combine different MR imaging contrasts. MATERIALS AND METHODS: Twenty-five patients with relapsing-remitting MS and 3 with secondary-progressive MS were imaged with 3T MR imaging by using double inversion recovery, dual fast spin-echo proton-density/T2-weighted, 3D FLAIR, and 3D T1-weighted imaging sequences. Lesions affecting the cortex were manually segmented by using the following 3 MR imaging reading protocols: Protocol 1 (P1) used all available MR imaging contrasts; protocol 2 (P2) used all the available contrasts except for double inversion recovery; and protocol 3(P3) used only double inversion recovery. RESULTS: Six hundred forty-three cortical lesions were identified with P1 (mean = 22.96); 633, with P2 (mean = 22.6); and 280, with P3 (mean = 10). The counts obtained by using P1 and P2 were not significantly different (P = .93). The counts obtained by using P3 were significantly smaller than those obtained by using either P1 (P < .001) or P2 (P < .001). The intraclass correlation coefficients were P1 versus P2 = 0.989, P1 versus P3 = 0.615, and P2 versus P3 = 0.588. CONCLUSIONS: MR imaging cortical lesion segmentation can be performed by using 3D T1-weighted and 3D FLAIR images acquired with a 1-mm isotropic voxel size, supported by conventional T2-weighted and proton-density images with 3-mm-thick sections. Inclusion of double inversion recovery in this multimodal reading protocol did not significantly improve the cortical lesion identification rate. A multimodal approach is superior to using double inversion recovery alone.
BACKGROUND AND PURPOSE: Double inversion recovery has been suggested as the MR imaging contrast of choice for segmenting cortical lesions in patients with multiple sclerosis. In this study, we sought to determine the utility of double inversion recovery for cortical lesion identification by comparing 3 MR imaging reading protocols that combine different MR imaging contrasts. MATERIALS AND METHODS: Twenty-five patients with relapsing-remitting MS and 3 with secondary-progressive MS were imaged with 3T MR imaging by using double inversion recovery, dual fast spin-echo proton-density/T2-weighted, 3D FLAIR, and 3D T1-weighted imaging sequences. Lesions affecting the cortex were manually segmented by using the following 3 MR imaging reading protocols: Protocol 1 (P1) used all available MR imaging contrasts; protocol 2 (P2) used all the available contrasts except for double inversion recovery; and protocol 3(P3) used only double inversion recovery. RESULTS: Six hundred forty-three cortical lesions were identified with P1 (mean = 22.96); 633, with P2 (mean = 22.6); and 280, with P3 (mean = 10). The counts obtained by using P1 and P2 were not significantly different (P = .93). The counts obtained by using P3 were significantly smaller than those obtained by using either P1 (P < .001) or P2 (P < .001). The intraclass correlation coefficients were P1 versus P2 = 0.989, P1 versus P3 = 0.615, and P2 versus P3 = 0.588. CONCLUSIONS: MR imaging cortical lesion segmentation can be performed by using 3D T1-weighted and 3D FLAIR images acquired with a 1-mm isotropic voxel size, supported by conventional T2-weighted and proton-density images with 3-mm-thick sections. Inclusion of double inversion recovery in this multimodal reading protocol did not significantly improve the cortical lesion identification rate. A multimodal approach is superior to using double inversion recovery alone.
Authors: A Scott Nielsen; R Philip Kinkel; Emanuele Tinelli; Thomas Benner; Julien Cohen-Adad; Caterina Mainero Journal: J Magn Reson Imaging Date: 2011-11-01 Impact factor: 4.813
Authors: Emma C Tallantyre; Paul S Morgan; Jennifer E Dixon; Ali Al-Radaideh; Matthew J Brookes; Peter G Morris; Nikos Evangelou Journal: J Magn Reson Imaging Date: 2010-10 Impact factor: 4.813
Authors: Jeroen J G Geurts; Petra J W Pouwels; Bernard M J Uitdehaag; Chris H Polman; Frederik Barkhof; Jonas A Castelijns Journal: Radiology Date: 2005-07 Impact factor: 11.105
Authors: I D Kilsdonk; W L de Graaf; A Lopez Soriano; J J Zwanenburg; F Visser; J P A Kuijer; J J G Geurts; P J W Pouwels; C H Polman; J A Castelijns; P R Luijten; F Barkhof; M P Wattjes Journal: AJNR Am J Neuroradiol Date: 2012-10-04 Impact factor: 3.825
Authors: J Maranzano; M Dadar; D A Rudko; D De Nigris; C Elliott; J S Gati; S A Morrow; R S Menon; D L Collins; D L Arnold; S Narayanan Journal: AJNR Am J Neuroradiol Date: 2019-06-20 Impact factor: 3.825
Authors: Mahsa Dadar; Josefina Maranzano; Simon Ducharme; Owen T Carmichael; Charles Decarli; D Louis Collins Journal: Hum Brain Mapp Date: 2017-11-27 Impact factor: 5.038
Authors: Michael Osadebey; Marius Pedersen; Douglas Arnold; Katrina Wendel-Mitoraj Journal: IEEE J Transl Eng Health Med Date: 2018-08-23 Impact factor: 3.316
Authors: Josefina Maranzano; David A Rudko; Kunio Nakamura; Stuart Cook; Diego Cadavid; Leo Wolansky; Douglas L Arnold; Sridar Narayanan Journal: Neurology Date: 2017-07-19 Impact factor: 9.910