TY - JOUR
T1 - Combination of defined catwalk gait parameters for predictive locomotion recovery in experimental spinal cord injury rat models
AU - Timotius, Ivanna K.
AU - Bieler, Lara
AU - Couillard-Despres, Sebastien
AU - Sandner, Beatrice
AU - Garcia-Ovejero, Daniel
AU - Labombarda, Florencia
AU - Estrada, Veronica
AU - Müller, Hans W.
AU - Winkler, Jürgen
AU - Klucken, Jochen
AU - Eskofier, Bjoern
AU - Weidner, Norbert
AU - Puttagunta, Radhika
N1 - Funding Information:
I.K.T. was supported by the DAAD Research Grant 57129429. B.E. was supported by the German Research Foundation (DFG), the Heisenberg Professorship Program Grant ES 434/8-1. Work in Study 1 was supported by the Olympia Morata Program at Heidelberg University Medical Faculty for B.S. and R.P. as well as the Interdisciplinary Neurobehavioral Core Grant AZ42-04HV.MED(15)/6/1 in Heidelberg. L.B. and S.C.-D. were supported by the Austrian Agency for International Cooperation in Education and Research (OeAD-GmbH) Grant HR02/2018 and Paracelsus Medical University Research Fund Grants PMU-FFF R-13/05/054-GRA, E-15/22/113-COS, and R-19/04/ 124-BIG.
Publisher Copyright:
© 2021 Timotius et al.
PY - 2021/2/18
Y1 - 2021/2/18
N2 - In many preclinical spinal cord injury (SCI) studies, assessment of locomotion recovery is key to understanding the effectiveness of the experimental intervention. In such rat SCI studies, the most basic locomotor recovery scoring system is a subjective observation of animals freely roaming in an open field, the Basso Beattie Bresnahan (BBB) score. In comparison, CatWalk is an automated gait analysis system, providing further parameter specifications. Although together the CatWalk parameters encompass gait, studies consistently report single parameters, which differ in significance from other behavioral assessments. Therefore, we believe no single parameter produced by the CatWalk can represent the fully-coordinated motion of gait. Typically, other locomotor assessments, such as the BBB score, combine several locomotor characteristics into a representative score. For this reason, we ranked the most distinctive CatWalk parameters between uninjured and SC injured rats. Subsequently, we combined nine of the topmost parameters into an SCI gait index score based on linear discriminant analysis (LDA). The resulting combination was applied to assess gait recovery in SCI experiments comprising of three thoracic contusions, a thoracic dorsal hemisection, and a cervical dorsal column lesion model. For thoracic lesions, our unbiased machine learning model revealed gait differences in lesion type and severity. In some instances, our LDA was found to be more sensitive in differentiating recovery than the BBB score alone. We believe the newly developed gait parameter combination presented here should be used in CatWalk gait recovery work with preclinical thoracic rat SCI models.
AB - In many preclinical spinal cord injury (SCI) studies, assessment of locomotion recovery is key to understanding the effectiveness of the experimental intervention. In such rat SCI studies, the most basic locomotor recovery scoring system is a subjective observation of animals freely roaming in an open field, the Basso Beattie Bresnahan (BBB) score. In comparison, CatWalk is an automated gait analysis system, providing further parameter specifications. Although together the CatWalk parameters encompass gait, studies consistently report single parameters, which differ in significance from other behavioral assessments. Therefore, we believe no single parameter produced by the CatWalk can represent the fully-coordinated motion of gait. Typically, other locomotor assessments, such as the BBB score, combine several locomotor characteristics into a representative score. For this reason, we ranked the most distinctive CatWalk parameters between uninjured and SC injured rats. Subsequently, we combined nine of the topmost parameters into an SCI gait index score based on linear discriminant analysis (LDA). The resulting combination was applied to assess gait recovery in SCI experiments comprising of three thoracic contusions, a thoracic dorsal hemisection, and a cervical dorsal column lesion model. For thoracic lesions, our unbiased machine learning model revealed gait differences in lesion type and severity. In some instances, our LDA was found to be more sensitive in differentiating recovery than the BBB score alone. We believe the newly developed gait parameter combination presented here should be used in CatWalk gait recovery work with preclinical thoracic rat SCI models.
KW - CatWalk
KW - Gait parameter
KW - Linear discriminant analysis
KW - Locomotion recovery
KW - Preclinical development
KW - Spinal cord injury
UR - http://www.scopus.com/inward/record.url?scp=85102119003&partnerID=8YFLogxK
U2 - 10.1523/ENEURO.0497-20.2021
DO - 10.1523/ENEURO.0497-20.2021
M3 - Article
C2 - 33593735
AN - SCOPUS:85102119003
SN - 2373-2822
VL - 8
SP - 1
EP - 14
JO - eNeuro
JF - eNeuro
IS - 2
M1 - ENEURO.0497-20.2021
ER -