TY - JOUR
T1 - CatWalk XT gait parameters
T2 - a review of reported parameters in pre-clinical studies of multiple central nervous system and peripheral nervous system disease models
AU - Timotius, Ivanna K.
AU - Roelofs, Reinko F.
AU - Richmond-Hacham, Bar
AU - Noldus, Lucas P.J.J.
AU - von Hörsten, Stephan
AU - Bikovski, Lior
N1 - Publisher Copyright: Copyright © 2023 Timotius, Roelofs, Richmond-Hacham, Noldus, von Hörsten and Bikovski.
PY - 2023
Y1 - 2023
N2 - Automated gait assessment tests are used in studies of disorders characterized by gait impairment. CatWalk XT is one of the first commercially available automated systems for analyzing the gait of rodents and is currently the most used system in peer-reviewed publications. This automated gait analysis system can generate a large number of gait parameters. However, this creates a new challenge in selecting relevant parameters that describe the changes within a particular disease model. Here, for the first time, we performed a multi-disorder review on published CatWalk XT data. We identify commonly reported CatWalk XT gait parameters derived from 91 peer-reviewed experimental studies in mice, covering six disorders of the central nervous system (CNS) and peripheral nervous system (PNS). The disorders modeled in mice were traumatic brain injury (TBI), stroke, sciatic nerve injury (SNI), spinal cord injury (SCI), Parkinson’s disease (PD), and ataxia. Our review consisted of parameter selection, clustering, categorization, statistical evaluation, and data visualization. It suggests that certain gait parameters serve as potential indicators of gait dysfunction across multiple disease models, while others are specific to particular models. The findings also suggest that the more site-specific the injury is, the fewer parameters are reported to characterize its gait abnormalities. This study strives to present a clearly organized picture of gait parameters used in each one of the different mouse models, potentially helping novel CatWalk XT users to apply this information to similar or related mouse models they are working on.
AB - Automated gait assessment tests are used in studies of disorders characterized by gait impairment. CatWalk XT is one of the first commercially available automated systems for analyzing the gait of rodents and is currently the most used system in peer-reviewed publications. This automated gait analysis system can generate a large number of gait parameters. However, this creates a new challenge in selecting relevant parameters that describe the changes within a particular disease model. Here, for the first time, we performed a multi-disorder review on published CatWalk XT data. We identify commonly reported CatWalk XT gait parameters derived from 91 peer-reviewed experimental studies in mice, covering six disorders of the central nervous system (CNS) and peripheral nervous system (PNS). The disorders modeled in mice were traumatic brain injury (TBI), stroke, sciatic nerve injury (SNI), spinal cord injury (SCI), Parkinson’s disease (PD), and ataxia. Our review consisted of parameter selection, clustering, categorization, statistical evaluation, and data visualization. It suggests that certain gait parameters serve as potential indicators of gait dysfunction across multiple disease models, while others are specific to particular models. The findings also suggest that the more site-specific the injury is, the fewer parameters are reported to characterize its gait abnormalities. This study strives to present a clearly organized picture of gait parameters used in each one of the different mouse models, potentially helping novel CatWalk XT users to apply this information to similar or related mouse models they are working on.
KW - CNS
KW - CatWalk XT
KW - PNS
KW - gait
KW - locomotor deficits
KW - mouse
KW - rodents
UR - http://www.scopus.com/inward/record.url?scp=85163035202&partnerID=8YFLogxK
U2 - 10.3389/fnbeh.2023.1147784
DO - 10.3389/fnbeh.2023.1147784
M3 - مقالة مرجعية
SN - 1662-5153
VL - 17
JO - Frontiers in Behavioral Neuroscience
JF - Frontiers in Behavioral Neuroscience
M1 - 1147784
ER -