Robert L Harrigan1, Andrew J Plassard2, Frederick W Bryan1,3, Gabriela Caires4, Louise A Mawn5, Lindsey M Dethrage3, Siddharama Pawate6, Robert L Galloway7, Seth A Smith3,7,8, Bennett A Landman1,2,3,7,8. 1. Department of Electrical Engineering, Vanderbilt University, Nashville, Tennessee, USA. 2. Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA. 3. Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA. 4. Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, RN, Brazil. 5. Vanderbilt Eye Institute, Vanderbilt University, Nashville, Tennessee, USA. 6. Department of Neurology, Vanderbilt University, Nashville, Tennessee, USA. 7. Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA. 8. Department of Radiology, Vanderbilt University, Nashville, Tennessee, USA.
Abstract
PURPOSE: Our goal is to develop an accurate, automated tool to characterize the optic nerve (ON) and cerebrospinal fluid (CSF) to better understand ON changes in disease. METHODS: Multi-atlas segmentation is used to localize the ON and sheath on T2-weighted MRI (0.6 mm(3) resolution). A sum of Gaussian distributions is fit to coronal slice-wise intensities to extract six descriptive parameters, and a regression forest is used to map the model space to radii. The model is validated for consistency using tenfold cross-validation and for accuracy using a high resolution (0.4 mm(2) reconstructed to 0.15 mm(2)) in vivo sequence. We evaluated this model on 6 controls and 6 patients with multiple sclerosis (MS) and a history of optic neuritis. RESULTS: In simulation, the model was found to have an explanatory R-squared for both ON and sheath radii greater than 0.95. The accuracy of the method was within the measurement error on the highest possible in vivo resolution. Comparing healthy controls and patients with MS, significant structural differences were found near the ON head and the chiasm, and structural trends agreed with the literature. CONCLUSION: This is a first demonstration that the ON can be exclusively, quantitatively measured and separated from the surrounding CSF using MRI.
PURPOSE: Our goal is to develop an accurate, automated tool to characterize the optic nerve (ON) and cerebrospinal fluid (CSF) to better understand ON changes in disease. METHODS: Multi-atlas segmentation is used to localize the ON and sheath on T2-weighted MRI (0.6 mm(3) resolution). A sum of Gaussian distributions is fit to coronal slice-wise intensities to extract six descriptive parameters, and a regression forest is used to map the model space to radii. The model is validated for consistency using tenfold cross-validation and for accuracy using a high resolution (0.4 mm(2) reconstructed to 0.15 mm(2)) in vivo sequence. We evaluated this model on 6 controls and 6 patients with multiple sclerosis (MS) and a history of optic neuritis. RESULTS: In simulation, the model was found to have an explanatory R-squared for both ON and sheath radii greater than 0.95. The accuracy of the method was within the measurement error on the highest possible in vivo resolution. Comparing healthy controls and patients with MS, significant structural differences were found near the ON head and the chiasm, and structural trends agreed with the literature. CONCLUSION: This is a first demonstration that the ON can be exclusively, quantitatively measured and separated from the surrounding CSF using MRI.
Authors: L Weizman; L Ben Sira; L Joskowicz; S Constantini; R Precel; B Shofty; D Ben Bashat Journal: Med Image Anal Date: 2011-07-21 Impact factor: 8.545
Authors: Felipe A Medeiros; Linda M Zangwill; Christopher Bowd; Roberto M Vessani; Remo Susanna; Robert N Weinreb Journal: Am J Ophthalmol Date: 2005-01 Impact factor: 5.258
Authors: R Chrástek; M Wolf; K Donath; H Niemann; D Paulus; T Hothorn; B Lausen; R Lämmer; C Y Mardin; G Michelson Journal: Med Image Anal Date: 2005-04-08 Impact factor: 8.545
Authors: R W Beck; P A Cleary; M M Anderson; J L Keltner; W T Shults; D I Kaufman; E G Buckley; J J Corbett; M J Kupersmith; N R Miller Journal: N Engl J Med Date: 1992-02-27 Impact factor: 91.245
Authors: S J Hickman; C M H Brierley; P A Brex; D G MacManus; N J Scolding; D A S Compston; D H Miller Journal: Mult Scler Date: 2002-08 Impact factor: 6.312
Authors: S Anand Trip; Patricio G Schlottmann; Stephen J Jones; Daniel R Altmann; David F Garway-Heath; Alan J Thompson; Gordon T Plant; David H Miller Journal: Ann Neurol Date: 2005-09 Impact factor: 10.422
Authors: Robert L Harrigan; Andrew J Plassard; Louise A Mawn; Robert L Galloway; Seth A Smith; Bennett A Landman Journal: Proc SPIE Int Soc Opt Eng Date: 2015-03-20
Authors: Robert L Harrigan; Alex K Smith; Bailey Lyttle; Bailey Box; Bennett A Landman; Francesca Bagnato; Siddharama Pawate; Seth A Smith Journal: Mult Scler J Exp Transl Clin Date: 2017-09-13
Authors: Bao N Nguyen; Jon O Cleary; Rebecca Glarin; Scott C Kolbe; Bradford A Moffat; Roger J Ordidge; Bang V Bui; Allison M McKendrick Journal: Transl Vis Sci Technol Date: 2021-02-05 Impact factor: 3.283