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Three-dimensional dynamic analysis of knee joint during gait in medial knee osteoarthritis using loading axis of knee
Accepted Manuscript Title: Three-dimensional dynamic analysis of knee joint during gait in medial knee osteoarthritis using loading axis of knee Author: Katsutoshi Nishino Go Omori Yoshio Koga Koichi Kobayashi Makoto Sakamoto Yuji Tanabe Masaei Tanaka Masaaki Arakawa PII: DOI: Reference:
S0966-6362(15)00459-2 http://dx.doi.org/doi:10.1016/j.gaitpost.2015.04.018 GAIPOS 4478
To appear in:
Gait & Posture
Received date: Revised date: Accepted date:
17-7-2014 31-3-2015 30-4-2015
Please cite this article as: Nishino K, Omori G, Koga Y, Kobayashi K, Sakamoto M, Tanabe Y, Tanaka M, Arakawa M, Three-dimensional dynamic analysis of knee joint during gait in medial knee osteoarthritis using loading axis of knee, Gait and Posture (2015), http://dx.doi.org/10.1016/j.gaitpost.2015.04.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title: Three-dimensional dynamic analysis of knee joint during gait in medial knee osteoarthritis using loading axis of knee
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Authors: Katsutoshi Nishino, PhDa,*, Go Omori, MD,PhD b, Yoshio Koga, MD,PhDc, Koichi Kobayashi, PhDd, Makoto Sakamoto, PhDd, Yuji Tanabe, PhDe, Masaei Tanaka, PTa, Masaaki Arakawa, MD,PhDa
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Affiliations: a Niigata Institute for Health and Sports Medicine, 67-12 Seigorou, Chuoh-ku, Niigata, Japan b Department of Health and Sports, Faculty of Health Sciences, Niigata University of Health and Welfare, 1398 Shimami-cho, Kita-ku, Niigata, Japan c Department of Orthopaedic Surgery, Ninouji Spa Hospital, 452 Toramaru, Shibata-shi, Niigata, Japan d Department of Health Sciences, Niigata University School of Medicine, 2-746 Asahimachi-dori, Chuoh-ku, Niigata, Japan e Department of Mechanical Engineering, Faculty of Engineering Niigata University, 2-8050 Ikarashi, Nishi-ku, Niigata, Japan
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*Corresponding author: Katsutoshi Nishino, PhD Niigata Institute for Health and Sports Medicine 67-12 Seigorou, Chuoh-ku, Niigata, 950-0933, Japan Tel: +81-25-287-8806, Fax: +81-25-287-8807 E-mail address: [email protected] Article type: Original Paper (Full Paper)
Keywords: Knee osteoarthritis, gait, kinematics, kinetics, loading axis of knee. Word count Manuscript (Introduction to Discussion): 2,986 words Abstract: 249 words Figures/Tables in total: 3 figures, 2 tables 1 Page 1 of 25
Highlights: We have developed a method to analyze mechanism of knee osteoarthritis (KOA).
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Patient-specific information from standing X-ray and CT is applied to gait analysis.
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Medial movement of knee joint during gait is started from mild KOA.
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Local loading on tibial proximal surface during gait is occurred in severe KOA.
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Our method is helpful for recovery and conservation of activities of daily living.
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Abstract
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We recently developed a new method for three-dimensional evaluation of mechanical factors affecting knee joint in order to help identify factors that contribute to the progression of knee
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osteoarthritis (KOA). This study aimed to verify the clinical validity of our method by evaluating
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knee joint dynamics during gait. Subjects were 41 individuals (14 normal knees; 8 mild KOAs; 19
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severe KOAs). The positions of skin markers attached to the body were captured during gait, and
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bi-planar X-ray images of the lower extremities were obtained in standing position. The positional relationship between the markers and femorotibial bones was determined from the X-ray images. Combining this relationship with gait capture allowed for the estimation of relative movement between femorotibial bones. We also calculated the point of intersection of loading axis of knee on the tibial proximal surface (LAK point) to analyze knee joint dynamics. Knee flexion range in subjects with severe KOA during gait was significantly smaller than that in those with normal knees (p=.011), and knee adduction in those with severe KOA was significantly larger than in those with mild KOA (p<.000). LAK point was locally loaded on the medial compartment of the tibial surface as KOA progressed, with LAK point of subjects with severe KOA rapidly shifting medially during 2 Page 2 of 25
loading response. Local loading and medial shear force were applied to the tibial surface during stance phase as medial KOA progressed. Our findings suggest that our method is useful for the
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quantitative evaluation of mechanical factors that affect KOA progression.
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1. Introduction Knee osteoarthritis (KOA) in adult knee joints is associated with severe pain and loss of
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joint mobility, leading to impaired activities of daily living. In the United States, radiographic KOA was observed in 37% of adults aged >60 years [1]. In Japan, radiographic KOA was observed in
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42% of men and 62% of women aged >40 years [2]. Given its high prevalence, KOA will critically
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impact social activities in aging societies.
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KOA progression is accompanied by impairments in the mechanical functions of the knee joint during weight-bearing activities due to nonconformity of the knee-joint surface resulting from
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articular cartilage wear. Thus, identification of KOA risk factors would provide insight that might
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help prevent KOA. Factors associated with KOA progression have been previously reported, such
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as age, gender, lower extremity alignment (LEA), obesity, lifestyle, leg strength, knee injury history,
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ethnicity, osteoporosis, sex hormones, genetics, and micronutrients [3-5]. In most cases, KOA progresses to the medial compartment of the knee joint (medial KOA), resulting in an excess load being focused on its surface. In order to clarify the pathomechanism underlying the development of medial KOA, a detailed assessment of mechanical factors that directly influence the knee joint is important.
LEA analysis is typically used to statically evaluate mechanical factors affecting the knee joint. LEA is analyzed using frontal X-ray images of the entire lower extremity in the weight-bearing standing position, and typical parameters include the femorotibial angle and Mikulicz line [6]. Many LEA studies have been published [7, 8], although they involved 4 Page 4 of 25
two-dimensional (2D) evaluations of the knee frontal plane rather than a three-dimensional (3D) analysis.
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Knee adduction moment and varus thrust have typically been assessed to evaluate knee joint dynamics during gait. Knee adduction moment is derived by an inverse dynamics approach
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and has been used to analyze the relationship between gait characteristics and the dynamic
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mechanism of KOA progression [9-11]. Varus thrust is clinically abnormal with pathological
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kinematics in medial KOA and is defined as acute knee adduction during the early stance phase of gait. Effects of these parameters on medial KOA progression have already been reported [12-14];
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however, these reports only analyzed the frontal plane of the knee joint. Moreover, although some
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reports have analyzed the dynamics of the tibial proximal surface during gait, these studies involved
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only a few subjects because of the large device and/or complicated procedures involved [15].
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In order to evaluate 3D-LEA, we developed a bi-planar, radiographic-based 3D-LEA assessment system [16]. By combining this system with a motion capture system, mechanical factors affecting the knee joint during gait can be evaluated three-dimensionally. This study aimed to verify the clinical validity of our method by quantitatively evaluating knee joint dynamics during gait by medial KOA severity. 2. Materials and methods 2.1 Subjects A total of 41 healthy adults and medial KOA patients (17 males and 24 females) in Niigata City, Japan, participated in this study. Inclusion criteria were (1) age >20 years and (2) capable of 5 Page 5 of 25
self-standing walk. Exclusion criteria included (1) requirement of an aid stick and/or another orthosis and (2) previous high tibial osteotomy and/or total knee arthroplasty. The dominant knee
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was analyzed in all subjects. Two common questionnaire surveys were conducted to explore various knee parameters.
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Knee pain was measured with a visual analog scale (VAS), and knee symptoms and disabilities in
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physical function were evaluated with the Japanese Knee Osteoarthritis Measure (JKOM) [19],
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which has been modified based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) [20]. The JKOM consists of 25 questions, with a higher score (maximum 100
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points) indicating worse pain and physical disability.
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KOA severity was diagnosed by an experienced orthopedic physician using the
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Kellgren-Lawrence grading scale from frontal X-ray images of the knee [21]. Grade-0 was observed
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in 9 knees, grade-I in 5 knees, grade-II in 8 knees, grade-III in 12 knees, and grade-IV in 7 knees. In this study, KOA severity was classified into three groups: normal knees (14 knees at grade-0 and grade-I), mild KOA (8 knees at grade-II), and severe KOA (19 knees at grade-III and grade-IV). This study was approved by the ethical review board of the Niigata Institute for Health and
Sports Medicine.
2.2 Static 3D-LEA assessment An X-ray stereophotogrammetric apparatus, which consisted of a 0-60 degree turn stage and a cassette holder in three vertically arranged X-ray imaging plates, was used to evaluate static 3D-LEA. The subject stood on the turn stage, and the entire lower extremity was roentgenized in 6 Page 6 of 25
the frontal and 60 degree oblique directions with computed radiography (FCR CAPSULA, Fujifilm Co., Japan). The 3D position of femorotibial bones could be estimated by superimposing the 3D
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skeletal models onto the bony outline of the entire lower extremity under the weight-bearing standing position on X-ray images (Fig. 1) [16]. The 3D skeletal model was obtained from CT
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scanning of the entire lower extremity. The femoral coordinate system ∑F and tibial coordinate
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system ∑T constructed in the 3D skeletal model were determined in the same manner described by
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Kai et al. [17]. The overlapping procedure used a 2D/3D image matching technique, with a matching error within a range of 0.6 degrees in rotation and 0.5 mm in translation [16].
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From the 3D relative position between femorotibial bones obtained by the superimposing
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procedure, the center of the femoral head and the center of the tibial distal surface were linked in a
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line, and this line was defined as the ‘loading axis of the knee’ (LAK) (Fig. 2a). LAK represents a
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loading line of the upper-body weight to the lower-extremity joints. The point of intersection of the LAK on the tibial proximal surface was defined as the ‘LAK point’ (Fig. 2b). The location of the LAK point in static standing was determined as follows: Lateral-medial direction = Lateral-medial distance / Medial compartment width of tibial
proximal surface (MCW);
Anterior-posterior direction = Anterior-posterior distance / Anterior-posterior width of tibial proximal surface (APW).
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2.3 Gait capture Thirty-four skin markers were attached to the whole body of subjects. With respect to the 7 Page 7 of 25
12 thigh markers and 10 shank markers, the original marker that included a steel ball was used so as to detect its 2D position on X-ray images. The thigh markers were attached at the following
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positions: great trochanter, medial and lateral femoral epicondyles, and around the femoral shaft. The shank markers were placed at the following positions: medial and lateral tibial condyles, medial
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and lateral malleoli, fibula head, tibial tuberosity, and around the tibial shaft. Markers were placed
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by an experienced investigator.
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The subjects walked along an 8 m lane at a self-selected speed. The center of the lane was set as a world coordinate system of a motion capture system, ∑W (VICON612, Vicon motion
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systems, UK), and gait was captured at a sampling rate of 120 Hz. The 3D positions of thigh and
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shank marker sets were defined as {qWT,i (t) | i=1,…,12} and {qWS,i (t) | i=1,…,8} with respect to
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∑W, respectively, where t denotes the sample number of the gait capture. The 3D marker position
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was smoothed with a fourth order zero-lag Butterworth filter (7Hz). Gait cycle was classified using the following four time points: initial contact, foot plant, heel rise, and toe off. First initial contact to toe off was defined as the stance phase. In the stance phase, first initial contact to foot plant was defined as the loading response, foot plant to heel rise as the mid-terminal stance, and heel rise to toe off as the pre-swing.
Bi-planar X-ray images of the lower extremity with the markers were obtained immediately following gait capture, and the 3D position was estimated from the 2D data of the markers on the X-ray image. The 3D positions of thigh and shank marker sets were represented as {pF,i | i=1,…,12} with respect to ∑F, and {pT,i | i=1,…,8} with respect to ∑T, respectively (Fig.1). 8 Page 8 of 25
2.3 Gait analysis Coordinate transformation from ∑F to ∑W at sample t was represented as TFW(t). TFW(t) was estimated using the least-squares technique so as to minimize the function J of TFW(t), as defined by J TFW t min wi p F ,i TFW t q WT ,i t , 12
2
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(2)
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where T shows a fourth-order homogeneous coordinate transformation matrix, and wi ( wi 1 |
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i 1
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i=1,…,12) expresses an individual weight coefficient set for each marker in order to reduce the estimation residual caused by non-rigid deformation of the marker set resulting from skin
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movement artifacts. Coordinate transformation TTG (t) from ∑T to ∑W also was estimated in the
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same manner as TFW (t). TFT (t) from ∑T to ∑F could be obtained by multiplying TFW (t) and TTW (t) as follows:
TFT t TTW t TFW t ,
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(3)
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where A B shows the composition of coordinate transformations A and B, and A-1 is the inverse
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matrix of A. The 3D relative position between the femorotibial bones at sample t was obtained by applying TFT (t) to the 3D skeletal models, and its continuous form was expressed as the 3D knee joint motion during gait. The kinematic parameters of 3D knee joint motion were calculated according to a previous study [18]: flexion-extension, abduction-adduction, external-internal rotation, lateral-medial shift, anterior-posterior shift, and proximal-distal shift. The LAK point, described in section 2.1, was calculated from the 3D relative position between femorotibial bones at sample t. LAK point tracking, its continuous form during the stance phase, was used to evaluate knee dynamics. Lateral-medial and anterior-posterior lengths were 9 Page 9 of 25
standardized by the MCW and APW of the tibial proximal surface, respectively (Fig. 2b). 2.4 Statistical analysis Differences in knee joint kinematic and dynamic parameters among KOA groups were
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evaluated using non-parametric statistical analysis (Kruskal-Wallis H-test, SPSS Statistics Ver.19,
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IBM Co.). The significance level was set at 0.05.
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3. Results
VAS and JKOM scores of subjects with severe KOA were significantly higher than those
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of the other groups. The LAK point of subjects with severe KOA in static standing was at a
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significantly more medial and posterior position on the tibial proximal surface compared to that of the other groups (p<.000 and p=.004) (Table 1).
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Table 2 shows the range of knee kinematics as the difference between maximum and
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minimum values during the stance phase of the gait cycle. Flexion range tended to decrease with
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increasing KOA severity, and flexion range in subjects with severe KOA was significantly smaller than in those with normal knees (p=.011). Adduction range of subjects with severe KOA was significantly larger than in those with mild KOA (p<.000). LAK point tracking length decreased with increasing KOA severity, and the length in subjects with severe KOA was significantly smaller than in those with normal knees (p=.017). The anterior-posterior length tended to decrease with increasing KOA severity (p=.027), while the lateral-medial length was significantly smaller in subjects with mild KOA than in those with severe KOA (p=.010). The lateral-medial length was more than 16.5% MCW (Mean, 31.3% MCW; SD, 14.8% MCW in mild KOA) (Table 2). 10 Page 10 of 25
LAK points in subjects with normal knees and mild KOA moved posteriorly during the loading response (Figs. 4a and 4b), but LAK point tracking in subjects with severe KOA shifted
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medially (Fig. 4c). From the mid-terminal stance to pre-swing, the LAK point initially shifted posteriorly, but subsequently moved anteriorly in all groups. The LAK point during the stance phase
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in subjects with normal knees was located at medial and posterior locations on the tibial proximal
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surface in subjects with normal knees, while it was located more anteriorly in those with mild KOA.
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The LAK point during the stance phase in those with severe KOA was located medially relative to the other groups.
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4. Discussion
3D knee joint kinematics during weight-bearing active motion has been evaluated with
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various methods, such as in vivo measurements using fluoroscopy [22] and in vitro estimations using a goniometer and motion capture system [15, 23, 24]. In vivo measurements are advantageous
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in that they enable a direct assessment of the relative motion between femorotibial bones, but are limited due to the small measurement space and radiation exposure. In vitro methods have been used in recent years for unrestricted analysis, although they suffer from skin movement artifacts. For instance, in one artifact, the absolute difference between actual knee motion and the estimated one from skin markers was 4.4 degrees in rotation and 13.0 mm in translation [25]. A point cluster technique has been developed to estimate knee joint kinematics with high accuracy by mathematically reducing skin movement artifacts [26]. Moreover, an in vitro method that combines X-ray stereophotogrammetry and goniometry has been used to evaluate 3D knee joint kinematics 11 Page 11 of 25
and kinetics during gait [23, 24]. More advanced methods have been used recently, such as one that combines a motion capture system with a 3D skeletal surface model obtained from CT [15] and
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MRI [27]. Our method has several advantages over other methods. First, mechanical effects on the
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knee joint can be evaluated by analyzing 3D-LEA in the weight-bearing standing position. Second,
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the femorotibial motion during gait is expressed based on anatomical coordinate system sets
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without depending on the position of the skin marker attached to the body. Thus, because inter- and intra-observer errors in skin marker position are negligible, it is possible to compare chronological
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changes in active knee motion of patients pre- and/or postoperatively with constant assessment
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independent of marker position. In other words, the method is capable of longitudinally studying
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gait as KOA progresses. Third, the level of radiation exposure from computed radiography is
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substantially smaller than that with CT. Kawakami et al. [15] used only CT scanning to estimate the relationship between skin marker position and femorotibial bones, and thus required CT scanning before and after each gait capture. In contrast, our method does not require multiple CT scanning sessions, but requires only computed radiography, which is the gold standard. For instance, when a subject’s gait is compared pre- and post-surgery, CT scanning is used only once in pre-surgery, and is not required post-surgery, which consequently results in effective reduction of radiation exposure. There are three potential errors associated with our method: (1) estimation error in the 3D relative position of femorotibial bones; (2) detection error of the 3D marker position using the motion capture system; and (3) skin movement artifacts. The error size of each has been assessed by 12 Page 12 of 25
various tests, but the total error of LAK point estimation is difficult to verify directly under conditions of weight-bearing active motion. Kawakami et al. [28] attempted to verify
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quasi-statically its accuracy using Open MRI, and reported an average error of LAK point estimation within 5.6%MCW. The lateral-medial length of LAK point tracking in the present study
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(16.5%MCW) was sufficiently larger than the error size reported by Kawakami et al. [28],
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suggesting that our method could be used to evaluate the dynamic characteristics of the knee joint
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based on KOA severity.
In conventional 2D analysis of static LEA, the LAK point was located more medially on
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the knee joint as medial KOA progressed [3]. In the present study, we found that the LAK point in
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subjects with severe KOA in static standing was located not only more medially, but also posteriorly
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on the tibial proximal surface. This result is consistent with tibial cartilage wear and bony defect
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locations observed in medial KOA [12]. However, the interquartile range of the LAK point location was considerably larger than that of other parameters. One reason for this may be that, when subjects stood on the stage for bi-planar roentgenography, we did not consider constant static conditions (e.g., leg stance and muscular contraction), and thus variability in standing may have caused variation in the LAK point location. The LAK-point tracking pattern of normal knees shifted in the anterior-posterior direction on the center line of the tibial proximal surface. With KOA progression, the LAK point shifted medially, and the anterior-posterior length of tracking decreased. In subjects with severe KOA, the LAK point shifted in the larger medial direction during the loading response. The decrease in 13 Page 13 of 25
anterior-posterior length of tracking with KOA progression represents knee flexion contracture, as reflected in a reduction in knee flexion range, and the medial shift can be attributed to effects of
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knee flexion contracture and increased knee adduction range. Further, the larger medial shift in subjects with severe KOA corresponded to the indication phase of the varus thrust, which may be
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expressed as rapid dynamic changes in the knee joint. These dynamic results may suggest that
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body-weight stress is locally loaded on the medial and posterior compartments of the tibial proximal
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surface with medial KOA progression and that an acute medial shear force is applied in severe KOA. Mild KOA is an early stage when knee symptoms and dysfunction initially appear. Although
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conventional gait analyses could not clarify the events of this stage mechanically, the new LAK
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point tracking method described herein allowed for a reduction in anterior-posterior length and
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medial movement to be observed. This result may offer valuable clinical insight into KOA
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prevention, and highlights the utility of LAK point tracking as a modality that allows for the quantitative and longitudinal assessment of the effects of KOA progression on knee joint mechanical parameters during gait. We expect that our method will help maintain activities of daily living and aid in physical exercises aimed at preventing KOA, as well as orthotic therapy, high tibial osteotomy, and total knee arthroplasty. This study has some limitations. First, knee joint dynamics as assessed by the LAK point do not assess the conditions of contact between femorotibial articular surfaces directly involved in KOA progression. Second, the pathomechanism underlying medial KOA, a multifactor disease, remains unclear given the relatively small sample size of each group in this study. Finally, this study 14 Page 14 of 25
did not perform assessments using knee functional tests such as range of motion, joint flexibility, and strength, and thus the relationship between knee function and knee joint dynamics could not be
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clarified. In the future, we hope to analyze contact conditions between femorotibial articular surfaces during gait by including the 3D articular cartilage model obtained from MRI in order to
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further clarify the relationship between LAK point tracking and KOA progression.
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Legends Fig.1.
Subject’s femorotibial bones which are projected onto frontal and 60 degrees oblique X-ray
images. {pF,i}and {pT,i} are three-dimensional position of reflective skin marker with respect to
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femoral coordinate system ∑F and tibial coordinate system ∑T, respectively.
(a) Loading axis of knee (LAK) and its intersectional point on tibial proximal surface
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Fig.2.
(LAK point). LAK is the line connecting femoral head center and center of tibial distal surface. (b)
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LAK-point tracking during stance phase of gait. Its lateral-medial and anterior-posterior lengths are normalized by medial compartment width (MCW) and anterior-posterior width (APW) of tibial
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proximal surface, respectively.
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Table 1 Median with interquartile range of subject’s profiles and intersectional point of loading axis of knee on tibial proximal surface (LAK point) in static standing among three KOA severity groups
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(n=41).
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Table 2 Median with interquartile range of knee-joint kinematic and dynamic parameters during stance phase of gait among three KOA severity groups (n=41).
Fig.3.
Typical tracking patterns of intersectional point of loading axis of knee on tibial proximal
surface (LAK point) during stance phase of gait: (a) normal knee; (b) mild KOA and (c) severe KOA.
20 Page 20 of 25
Table 1 Median with interquartile range of subject’s profiles and intersectional point of loading axis of knee on tibial proximal surface (LAK point) in static standing among three KOA severity groups (n=41).
Normal (N) Number (Male:Female)
p value
KOA severity Mild (M)
14(9:5)
Severe (S)
8(3:5)
19(5:14)
65(60,68)
73(65,77)
Profile
Height (cm)
31(23,64)
171.0(161.3,173.4) 159.3(153.9,165.8) 153.0(149.5,160.5)
NvsS
MvsS
.356
<.001
.322
.569
.001
.292
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Age (y.o.)
NvsM
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Parameter
68.3(54.6,73.7)
60.8(58.0,64.7)
63.0(56.5,69.7)
-
-
-
BMI
22.7(21.4,24.5)
23.0(21.6,25.5)
26.8(23.5,28.1)
.999
.037
.210
VAS (0 to 10)
0 (0,0.4)
0 (0,1.4)
4.3(1.8,6.5)
.229
.002
.048
JKOM score (max 100)
1 (0,5.5)
2 (0,9.3)
19 (12,35.5)
.999
<.001
.048
9.8(3.2,30.3)
17.2(8.9,22.3)
78.0(43.6,101.4)
.999
<.001
.002
46.9(15.2,67.9)
55.9(27.5,76.3)
86.3(75.9,120.9)
.999
.019
.142
lateral-medial
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LAK point in static standing
direction (%APW)
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direction (%MCW) Anterior-posterior
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Weight (kg)
BMI, body mass index; VAS, visual analogue scale; JKOM, Japanese knee osteoarthritis measure index; MCW, medial
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compartment width of tibial proximal surface; APW, anterior-posterior width of tibial proximal surface.
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Table 2 Median with interquartile range of knee-joint kinematic and dynamic parameters during stance phase of gait among three KOA severity groups (n=41).
p value
KOA severity
(Stance phase of gait)
Normal (N)
Mild (M)
Severe (S)
Range of knee-joint kinematics
.011
.610
.193
.079
<.001
-
-
-
11.3(7.3,17.3)
-
-
-
34.3(25.8,39.0)
-
-
-
9.6(8.8,13.1)
-
-
-
.017
.999
.112
.999
.010
241.4(223.8,261.0) 204.2(174.1,255.7) 199.1(184.7,230.8) .239
.027
.999
5.5(3.8,14.8)
5.7(4.9,7.5)
3.2(3.0,4.1)
7.8(6.1,9.5)
Internal rotation (deg)
12.5(9.2,17.1)
10.6(6.9,13.1)
9.2(7.6,14.1)
Lateral-medial shift (mm)
13.2(9.4,20.4)
12.9(10.1,18.2)
Anterior-posterior shift (mm)
40.0(34.0,47.5)
34.8(24.3,47.8)
Proximal-distal shift (mm)
10.6(9.2,15.8)
14.5(11.0,16.2)
Knee- joint dynamics: LAK-point tracking
178.6(158.8,227.9) 162.1(138.7,190.7) 132.4(118.6,172.7) .425
Lateral-medial length (%MCW) Anterior-posterior
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Length (mm)
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10.1(8.8,14.5)
Adduction (deg)
NvsS MvsS
.827
15.6(10.5,19.6)
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Flexion (deg)
NvsM
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Parameter
51.0(43.3,59.5)
53.7(46.5,67.6)
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length (%APW)
23.4(21.5,41.4)
LAK point, intersectional point of loading axis of knee on tibial proximal surface; MCW, medial compartment width of
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tibial proximal surface; APW, anterior-posterior width of tibial proximal surface.
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7. Fig 1
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Frontal image
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pF,i
ΣT
pT,i
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pt
ΣF
Skin markers into 1mm steel ball
Fig. 1. Subject’s femorotibial bones which are projected onto frontal and 60 degrees oblique X-ray images. {pF,i}and {pT,i} are threedimensional position of reflective skin marker with respect to femoral coordinate system ∑F and tibial coordinate system ∑T, respectively.
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7. Fig 2
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Femoral head center
Loading axis of knee (LAK)
ed
Femur LAK point Lateral
pt LAK
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Tibia
(a)
APW
MCW
Heel rise Posterior
Medial
Tibia
Center of tibial distal surface
Lateral
Medial
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Femur
Anterior
Anteriorposterior length
Initial contact Foot plant LAK-point tracking
Toe off Lateral-medial length (b)
Fig. 2. (a) Loading axis of knee (LAK) and its intersectional point on tibial proximal surface (LAK point). LAK is the line connecting femoral head center and center of tibial distal surface. (b) LAK-point tracking during stance phase of gait. The lateral-medial and anterior-posterior lengths are normalized by medial compartment width (MCW) and anterior-posterior width (APW) of tibial proximal surface, respectively.
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7. Fig 3
Anterior
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Initial contact Posterior Heel rise Initial contact
Foot plant
Heel rise Initial contact
ed
Foot plant
Foot plant
pt
Heel rise
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Lateral
Medial
Toe off
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Toe off
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LAK-point tracking
Toe off (a)
(b)
(c)
Fig. 3. Typical tracking patterns of intersectional point of loading axis of knee on tibial proximal surface (LAK point) during stance phase of gait: (a) normal knee; (b) mild KOA and (c) severe KOA.
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S0966-6362(15)00459-2 http://dx.doi.org/doi:10.1016/j.gaitpost.2015.04.018 GAIPOS 4478
To appear in:
Gait & Posture
Received date: Revised date: Accepted date:
17-7-2014 31-3-2015 30-4-2015
Please cite this article as: Nishino K, Omori G, Koga Y, Kobayashi K, Sakamoto M, Tanabe Y, Tanaka M, Arakawa M, Three-dimensional dynamic analysis of knee joint during gait in medial knee osteoarthritis using loading axis of knee, Gait and Posture (2015), http://dx.doi.org/10.1016/j.gaitpost.2015.04.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title: Three-dimensional dynamic analysis of knee joint during gait in medial knee osteoarthritis using loading axis of knee
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Authors: Katsutoshi Nishino, PhDa,*, Go Omori, MD,PhD b, Yoshio Koga, MD,PhDc, Koichi Kobayashi, PhDd, Makoto Sakamoto, PhDd, Yuji Tanabe, PhDe, Masaei Tanaka, PTa, Masaaki Arakawa, MD,PhDa
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Affiliations: a Niigata Institute for Health and Sports Medicine, 67-12 Seigorou, Chuoh-ku, Niigata, Japan b Department of Health and Sports, Faculty of Health Sciences, Niigata University of Health and Welfare, 1398 Shimami-cho, Kita-ku, Niigata, Japan c Department of Orthopaedic Surgery, Ninouji Spa Hospital, 452 Toramaru, Shibata-shi, Niigata, Japan d Department of Health Sciences, Niigata University School of Medicine, 2-746 Asahimachi-dori, Chuoh-ku, Niigata, Japan e Department of Mechanical Engineering, Faculty of Engineering Niigata University, 2-8050 Ikarashi, Nishi-ku, Niigata, Japan
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*Corresponding author: Katsutoshi Nishino, PhD Niigata Institute for Health and Sports Medicine 67-12 Seigorou, Chuoh-ku, Niigata, 950-0933, Japan Tel: +81-25-287-8806, Fax: +81-25-287-8807 E-mail address: [email protected] Article type: Original Paper (Full Paper)
Keywords: Knee osteoarthritis, gait, kinematics, kinetics, loading axis of knee. Word count Manuscript (Introduction to Discussion): 2,986 words Abstract: 249 words Figures/Tables in total: 3 figures, 2 tables 1 Page 1 of 25
Highlights: We have developed a method to analyze mechanism of knee osteoarthritis (KOA).
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Patient-specific information from standing X-ray and CT is applied to gait analysis.
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Medial movement of knee joint during gait is started from mild KOA.
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Local loading on tibial proximal surface during gait is occurred in severe KOA.
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Our method is helpful for recovery and conservation of activities of daily living.
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Abstract
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We recently developed a new method for three-dimensional evaluation of mechanical factors affecting knee joint in order to help identify factors that contribute to the progression of knee
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osteoarthritis (KOA). This study aimed to verify the clinical validity of our method by evaluating
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knee joint dynamics during gait. Subjects were 41 individuals (14 normal knees; 8 mild KOAs; 19
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severe KOAs). The positions of skin markers attached to the body were captured during gait, and
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bi-planar X-ray images of the lower extremities were obtained in standing position. The positional relationship between the markers and femorotibial bones was determined from the X-ray images. Combining this relationship with gait capture allowed for the estimation of relative movement between femorotibial bones. We also calculated the point of intersection of loading axis of knee on the tibial proximal surface (LAK point) to analyze knee joint dynamics. Knee flexion range in subjects with severe KOA during gait was significantly smaller than that in those with normal knees (p=.011), and knee adduction in those with severe KOA was significantly larger than in those with mild KOA (p<.000). LAK point was locally loaded on the medial compartment of the tibial surface as KOA progressed, with LAK point of subjects with severe KOA rapidly shifting medially during 2 Page 2 of 25
loading response. Local loading and medial shear force were applied to the tibial surface during stance phase as medial KOA progressed. Our findings suggest that our method is useful for the
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quantitative evaluation of mechanical factors that affect KOA progression.
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1. Introduction Knee osteoarthritis (KOA) in adult knee joints is associated with severe pain and loss of
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joint mobility, leading to impaired activities of daily living. In the United States, radiographic KOA was observed in 37% of adults aged >60 years [1]. In Japan, radiographic KOA was observed in
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42% of men and 62% of women aged >40 years [2]. Given its high prevalence, KOA will critically
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impact social activities in aging societies.
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KOA progression is accompanied by impairments in the mechanical functions of the knee joint during weight-bearing activities due to nonconformity of the knee-joint surface resulting from
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articular cartilage wear. Thus, identification of KOA risk factors would provide insight that might
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help prevent KOA. Factors associated with KOA progression have been previously reported, such
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as age, gender, lower extremity alignment (LEA), obesity, lifestyle, leg strength, knee injury history,
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ethnicity, osteoporosis, sex hormones, genetics, and micronutrients [3-5]. In most cases, KOA progresses to the medial compartment of the knee joint (medial KOA), resulting in an excess load being focused on its surface. In order to clarify the pathomechanism underlying the development of medial KOA, a detailed assessment of mechanical factors that directly influence the knee joint is important.
LEA analysis is typically used to statically evaluate mechanical factors affecting the knee joint. LEA is analyzed using frontal X-ray images of the entire lower extremity in the weight-bearing standing position, and typical parameters include the femorotibial angle and Mikulicz line [6]. Many LEA studies have been published [7, 8], although they involved 4 Page 4 of 25
two-dimensional (2D) evaluations of the knee frontal plane rather than a three-dimensional (3D) analysis.
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Knee adduction moment and varus thrust have typically been assessed to evaluate knee joint dynamics during gait. Knee adduction moment is derived by an inverse dynamics approach
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and has been used to analyze the relationship between gait characteristics and the dynamic
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mechanism of KOA progression [9-11]. Varus thrust is clinically abnormal with pathological
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kinematics in medial KOA and is defined as acute knee adduction during the early stance phase of gait. Effects of these parameters on medial KOA progression have already been reported [12-14];
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however, these reports only analyzed the frontal plane of the knee joint. Moreover, although some
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reports have analyzed the dynamics of the tibial proximal surface during gait, these studies involved
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only a few subjects because of the large device and/or complicated procedures involved [15].
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In order to evaluate 3D-LEA, we developed a bi-planar, radiographic-based 3D-LEA assessment system [16]. By combining this system with a motion capture system, mechanical factors affecting the knee joint during gait can be evaluated three-dimensionally. This study aimed to verify the clinical validity of our method by quantitatively evaluating knee joint dynamics during gait by medial KOA severity. 2. Materials and methods 2.1 Subjects A total of 41 healthy adults and medial KOA patients (17 males and 24 females) in Niigata City, Japan, participated in this study. Inclusion criteria were (1) age >20 years and (2) capable of 5 Page 5 of 25
self-standing walk. Exclusion criteria included (1) requirement of an aid stick and/or another orthosis and (2) previous high tibial osteotomy and/or total knee arthroplasty. The dominant knee
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was analyzed in all subjects. Two common questionnaire surveys were conducted to explore various knee parameters.
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Knee pain was measured with a visual analog scale (VAS), and knee symptoms and disabilities in
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physical function were evaluated with the Japanese Knee Osteoarthritis Measure (JKOM) [19],
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which has been modified based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) [20]. The JKOM consists of 25 questions, with a higher score (maximum 100
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points) indicating worse pain and physical disability.
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KOA severity was diagnosed by an experienced orthopedic physician using the
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Kellgren-Lawrence grading scale from frontal X-ray images of the knee [21]. Grade-0 was observed
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in 9 knees, grade-I in 5 knees, grade-II in 8 knees, grade-III in 12 knees, and grade-IV in 7 knees. In this study, KOA severity was classified into three groups: normal knees (14 knees at grade-0 and grade-I), mild KOA (8 knees at grade-II), and severe KOA (19 knees at grade-III and grade-IV). This study was approved by the ethical review board of the Niigata Institute for Health and
Sports Medicine.
2.2 Static 3D-LEA assessment An X-ray stereophotogrammetric apparatus, which consisted of a 0-60 degree turn stage and a cassette holder in three vertically arranged X-ray imaging plates, was used to evaluate static 3D-LEA. The subject stood on the turn stage, and the entire lower extremity was roentgenized in 6 Page 6 of 25
the frontal and 60 degree oblique directions with computed radiography (FCR CAPSULA, Fujifilm Co., Japan). The 3D position of femorotibial bones could be estimated by superimposing the 3D
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skeletal models onto the bony outline of the entire lower extremity under the weight-bearing standing position on X-ray images (Fig. 1) [16]. The 3D skeletal model was obtained from CT
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scanning of the entire lower extremity. The femoral coordinate system ∑F and tibial coordinate
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system ∑T constructed in the 3D skeletal model were determined in the same manner described by
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Kai et al. [17]. The overlapping procedure used a 2D/3D image matching technique, with a matching error within a range of 0.6 degrees in rotation and 0.5 mm in translation [16].
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From the 3D relative position between femorotibial bones obtained by the superimposing
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procedure, the center of the femoral head and the center of the tibial distal surface were linked in a
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line, and this line was defined as the ‘loading axis of the knee’ (LAK) (Fig. 2a). LAK represents a
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loading line of the upper-body weight to the lower-extremity joints. The point of intersection of the LAK on the tibial proximal surface was defined as the ‘LAK point’ (Fig. 2b). The location of the LAK point in static standing was determined as follows: Lateral-medial direction = Lateral-medial distance / Medial compartment width of tibial
proximal surface (MCW);
Anterior-posterior direction = Anterior-posterior distance / Anterior-posterior width of tibial proximal surface (APW).
(1)
2.3 Gait capture Thirty-four skin markers were attached to the whole body of subjects. With respect to the 7 Page 7 of 25
12 thigh markers and 10 shank markers, the original marker that included a steel ball was used so as to detect its 2D position on X-ray images. The thigh markers were attached at the following
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positions: great trochanter, medial and lateral femoral epicondyles, and around the femoral shaft. The shank markers were placed at the following positions: medial and lateral tibial condyles, medial
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and lateral malleoli, fibula head, tibial tuberosity, and around the tibial shaft. Markers were placed
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by an experienced investigator.
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The subjects walked along an 8 m lane at a self-selected speed. The center of the lane was set as a world coordinate system of a motion capture system, ∑W (VICON612, Vicon motion
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systems, UK), and gait was captured at a sampling rate of 120 Hz. The 3D positions of thigh and
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shank marker sets were defined as {qWT,i (t) | i=1,…,12} and {qWS,i (t) | i=1,…,8} with respect to
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∑W, respectively, where t denotes the sample number of the gait capture. The 3D marker position
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was smoothed with a fourth order zero-lag Butterworth filter (7Hz). Gait cycle was classified using the following four time points: initial contact, foot plant, heel rise, and toe off. First initial contact to toe off was defined as the stance phase. In the stance phase, first initial contact to foot plant was defined as the loading response, foot plant to heel rise as the mid-terminal stance, and heel rise to toe off as the pre-swing.
Bi-planar X-ray images of the lower extremity with the markers were obtained immediately following gait capture, and the 3D position was estimated from the 2D data of the markers on the X-ray image. The 3D positions of thigh and shank marker sets were represented as {pF,i | i=1,…,12} with respect to ∑F, and {pT,i | i=1,…,8} with respect to ∑T, respectively (Fig.1). 8 Page 8 of 25
2.3 Gait analysis Coordinate transformation from ∑F to ∑W at sample t was represented as TFW(t). TFW(t) was estimated using the least-squares technique so as to minimize the function J of TFW(t), as defined by J TFW t min wi p F ,i TFW t q WT ,i t , 12
2
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(2)
i 1
where T shows a fourth-order homogeneous coordinate transformation matrix, and wi ( wi 1 |
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i 1
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i=1,…,12) expresses an individual weight coefficient set for each marker in order to reduce the estimation residual caused by non-rigid deformation of the marker set resulting from skin
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movement artifacts. Coordinate transformation TTG (t) from ∑T to ∑W also was estimated in the
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same manner as TFW (t). TFT (t) from ∑T to ∑F could be obtained by multiplying TFW (t) and TTW (t) as follows:
TFT t TTW t TFW t ,
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1
(3)
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where A B shows the composition of coordinate transformations A and B, and A-1 is the inverse
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matrix of A. The 3D relative position between the femorotibial bones at sample t was obtained by applying TFT (t) to the 3D skeletal models, and its continuous form was expressed as the 3D knee joint motion during gait. The kinematic parameters of 3D knee joint motion were calculated according to a previous study [18]: flexion-extension, abduction-adduction, external-internal rotation, lateral-medial shift, anterior-posterior shift, and proximal-distal shift. The LAK point, described in section 2.1, was calculated from the 3D relative position between femorotibial bones at sample t. LAK point tracking, its continuous form during the stance phase, was used to evaluate knee dynamics. Lateral-medial and anterior-posterior lengths were 9 Page 9 of 25
standardized by the MCW and APW of the tibial proximal surface, respectively (Fig. 2b). 2.4 Statistical analysis Differences in knee joint kinematic and dynamic parameters among KOA groups were
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evaluated using non-parametric statistical analysis (Kruskal-Wallis H-test, SPSS Statistics Ver.19,
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IBM Co.). The significance level was set at 0.05.
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3. Results
VAS and JKOM scores of subjects with severe KOA were significantly higher than those
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of the other groups. The LAK point of subjects with severe KOA in static standing was at a
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significantly more medial and posterior position on the tibial proximal surface compared to that of the other groups (p<.000 and p=.004) (Table 1).
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Table 2 shows the range of knee kinematics as the difference between maximum and
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minimum values during the stance phase of the gait cycle. Flexion range tended to decrease with
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increasing KOA severity, and flexion range in subjects with severe KOA was significantly smaller than in those with normal knees (p=.011). Adduction range of subjects with severe KOA was significantly larger than in those with mild KOA (p<.000). LAK point tracking length decreased with increasing KOA severity, and the length in subjects with severe KOA was significantly smaller than in those with normal knees (p=.017). The anterior-posterior length tended to decrease with increasing KOA severity (p=.027), while the lateral-medial length was significantly smaller in subjects with mild KOA than in those with severe KOA (p=.010). The lateral-medial length was more than 16.5% MCW (Mean, 31.3% MCW; SD, 14.8% MCW in mild KOA) (Table 2). 10 Page 10 of 25
LAK points in subjects with normal knees and mild KOA moved posteriorly during the loading response (Figs. 4a and 4b), but LAK point tracking in subjects with severe KOA shifted
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medially (Fig. 4c). From the mid-terminal stance to pre-swing, the LAK point initially shifted posteriorly, but subsequently moved anteriorly in all groups. The LAK point during the stance phase
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in subjects with normal knees was located at medial and posterior locations on the tibial proximal
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surface in subjects with normal knees, while it was located more anteriorly in those with mild KOA.
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The LAK point during the stance phase in those with severe KOA was located medially relative to the other groups.
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4. Discussion
3D knee joint kinematics during weight-bearing active motion has been evaluated with
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various methods, such as in vivo measurements using fluoroscopy [22] and in vitro estimations using a goniometer and motion capture system [15, 23, 24]. In vivo measurements are advantageous
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in that they enable a direct assessment of the relative motion between femorotibial bones, but are limited due to the small measurement space and radiation exposure. In vitro methods have been used in recent years for unrestricted analysis, although they suffer from skin movement artifacts. For instance, in one artifact, the absolute difference between actual knee motion and the estimated one from skin markers was 4.4 degrees in rotation and 13.0 mm in translation [25]. A point cluster technique has been developed to estimate knee joint kinematics with high accuracy by mathematically reducing skin movement artifacts [26]. Moreover, an in vitro method that combines X-ray stereophotogrammetry and goniometry has been used to evaluate 3D knee joint kinematics 11 Page 11 of 25
and kinetics during gait [23, 24]. More advanced methods have been used recently, such as one that combines a motion capture system with a 3D skeletal surface model obtained from CT [15] and
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MRI [27]. Our method has several advantages over other methods. First, mechanical effects on the
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knee joint can be evaluated by analyzing 3D-LEA in the weight-bearing standing position. Second,
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the femorotibial motion during gait is expressed based on anatomical coordinate system sets
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without depending on the position of the skin marker attached to the body. Thus, because inter- and intra-observer errors in skin marker position are negligible, it is possible to compare chronological
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changes in active knee motion of patients pre- and/or postoperatively with constant assessment
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independent of marker position. In other words, the method is capable of longitudinally studying
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gait as KOA progresses. Third, the level of radiation exposure from computed radiography is
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substantially smaller than that with CT. Kawakami et al. [15] used only CT scanning to estimate the relationship between skin marker position and femorotibial bones, and thus required CT scanning before and after each gait capture. In contrast, our method does not require multiple CT scanning sessions, but requires only computed radiography, which is the gold standard. For instance, when a subject’s gait is compared pre- and post-surgery, CT scanning is used only once in pre-surgery, and is not required post-surgery, which consequently results in effective reduction of radiation exposure. There are three potential errors associated with our method: (1) estimation error in the 3D relative position of femorotibial bones; (2) detection error of the 3D marker position using the motion capture system; and (3) skin movement artifacts. The error size of each has been assessed by 12 Page 12 of 25
various tests, but the total error of LAK point estimation is difficult to verify directly under conditions of weight-bearing active motion. Kawakami et al. [28] attempted to verify
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quasi-statically its accuracy using Open MRI, and reported an average error of LAK point estimation within 5.6%MCW. The lateral-medial length of LAK point tracking in the present study
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(16.5%MCW) was sufficiently larger than the error size reported by Kawakami et al. [28],
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suggesting that our method could be used to evaluate the dynamic characteristics of the knee joint
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based on KOA severity.
In conventional 2D analysis of static LEA, the LAK point was located more medially on
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the knee joint as medial KOA progressed [3]. In the present study, we found that the LAK point in
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subjects with severe KOA in static standing was located not only more medially, but also posteriorly
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on the tibial proximal surface. This result is consistent with tibial cartilage wear and bony defect
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locations observed in medial KOA [12]. However, the interquartile range of the LAK point location was considerably larger than that of other parameters. One reason for this may be that, when subjects stood on the stage for bi-planar roentgenography, we did not consider constant static conditions (e.g., leg stance and muscular contraction), and thus variability in standing may have caused variation in the LAK point location. The LAK-point tracking pattern of normal knees shifted in the anterior-posterior direction on the center line of the tibial proximal surface. With KOA progression, the LAK point shifted medially, and the anterior-posterior length of tracking decreased. In subjects with severe KOA, the LAK point shifted in the larger medial direction during the loading response. The decrease in 13 Page 13 of 25
anterior-posterior length of tracking with KOA progression represents knee flexion contracture, as reflected in a reduction in knee flexion range, and the medial shift can be attributed to effects of
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knee flexion contracture and increased knee adduction range. Further, the larger medial shift in subjects with severe KOA corresponded to the indication phase of the varus thrust, which may be
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expressed as rapid dynamic changes in the knee joint. These dynamic results may suggest that
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body-weight stress is locally loaded on the medial and posterior compartments of the tibial proximal
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surface with medial KOA progression and that an acute medial shear force is applied in severe KOA. Mild KOA is an early stage when knee symptoms and dysfunction initially appear. Although
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conventional gait analyses could not clarify the events of this stage mechanically, the new LAK
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point tracking method described herein allowed for a reduction in anterior-posterior length and
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medial movement to be observed. This result may offer valuable clinical insight into KOA
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prevention, and highlights the utility of LAK point tracking as a modality that allows for the quantitative and longitudinal assessment of the effects of KOA progression on knee joint mechanical parameters during gait. We expect that our method will help maintain activities of daily living and aid in physical exercises aimed at preventing KOA, as well as orthotic therapy, high tibial osteotomy, and total knee arthroplasty. This study has some limitations. First, knee joint dynamics as assessed by the LAK point do not assess the conditions of contact between femorotibial articular surfaces directly involved in KOA progression. Second, the pathomechanism underlying medial KOA, a multifactor disease, remains unclear given the relatively small sample size of each group in this study. Finally, this study 14 Page 14 of 25
did not perform assessments using knee functional tests such as range of motion, joint flexibility, and strength, and thus the relationship between knee function and knee joint dynamics could not be
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clarified. In the future, we hope to analyze contact conditions between femorotibial articular surfaces during gait by including the 3D articular cartilage model obtained from MRI in order to
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further clarify the relationship between LAK point tracking and KOA progression.
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Mündermann A, Dyrby CO, Andriacchi TP. A comparison of measuring mechanical axis alignment using three-dimensional position capture with skin markers and radiographic measurements in patients with bilateral medial compartment knee osteoarthritis. Knee 2008; 15: 480-5. 16 Page 16 of 25
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[13] Chang A, Hochberg M, Song J, Dunlop D, Chmiel JS, Nevitt M, Hayes K, Eaton C, Bathon J,
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Jackson R, Kwoh CK, Sharma L. Frequency of varus and valgus thrust and factors associated with thrust presence in persons with or at higher risk of developing knee osteoarthritis.
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Quantification and effects of different gait-related interventions using a single case study. Arthritis Care Res 2011; 63: 293-7. [15] Kawakami H, Sugano N, Yonenobu K, Yoshikawa H, Ochi T, Nakata K, Toritsuka Y, Hattori A, Suzuki N. Change in the locus of dynamic loading axis on the knee joint after high tibial osteotomy. Gait Posture 2005; 21: 271-8. [16] Kobayashi K, Sakamoto M, Tanabe Y, Ariumi A, Sato T, Omori G, Koga Y. Automated image registration for assessing three-dimensional alignment of entire lower extremity and implant position using bi-plane radiography. J Biomech 2009; 42: 2818-22. [17] Kai S, Sato T, Koga Y, Omori G, Kobayashi K, Sakamoto M, Tanabe Y. Automatic construction of an anatomical coordinate system for three-dimensional bone models of the lower extremities – Pelvis, femur, and tibia. J Biomech 2014; 47: 1229-33. 17 Page 17 of 25
[18] Grood ES, Suntay WJ. A joint coordinate system for the clinical description of three-dimensional motions: application to the knee. J Biomech Eng 1983; 105; 136-44. [19] Akai M, Doi T, Fujino K, Iwaya T, Kurosawa H, Nasu T. An outcome measure for Japanese people with knee osteoarthritis. J Rheumatol 2005; 32: 1524-32.
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[21] Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis 1957;
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technique for the measurement of dynamic knee joint motion. J Biomech 2008; 41; 1616-22. [23] Li J, Wyss UP, Costigan PA, Deluzio KJ. An integrated procedure to assess knee-joint
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kinematics and kinetics during gait using an optoelectric system and standardized X-rays. J
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[24] Takemae T, Omori G, Nishino K, Terajima K, Koga Y, Endo N. Three-dimensional knee motion before and after high tibial osteotomy for medial knee osteoarthritis. J Orthop Sci 2006; 11: 601-6.
[25] Benoit DL, Ramsey DK, Lamontagne M, Xu L, Wretenberg P, Renström P. Effect of skin movement artifact on knee kinematics during gait and cutting motions measured in vivo. Gait Posture 2006; 24: 152-64.
[26] Andriacchi TP, Alexander EJ, Toney MK, Dyrby C, Sum J. A point cluster method for in vivo motion analysis: Applied to study of knee kinematics. J Biomech Eng 1998; 120: 743-9. [27] Scheys L, Desloovere K, Spaepen A, Suetens P, Jonkers I. Calculating gait kinematics using MR-based kinematic models. Gait Posture 2011; 33: 158-64. [28] Kawakami H, Sugano N, Yonenobu K, Yoshikawa H, Ochi T, Hattori A, Suzuki N. Gait 18 Page 18 of 25
analysis system for assessment of dynamic loading axis of the knee. Gait Posture 2005; 21:
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125-30.
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Legends Fig.1.
Subject’s femorotibial bones which are projected onto frontal and 60 degrees oblique X-ray
images. {pF,i}and {pT,i} are three-dimensional position of reflective skin marker with respect to
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femoral coordinate system ∑F and tibial coordinate system ∑T, respectively.
(a) Loading axis of knee (LAK) and its intersectional point on tibial proximal surface
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Fig.2.
(LAK point). LAK is the line connecting femoral head center and center of tibial distal surface. (b)
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LAK-point tracking during stance phase of gait. Its lateral-medial and anterior-posterior lengths are normalized by medial compartment width (MCW) and anterior-posterior width (APW) of tibial
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proximal surface, respectively.
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Table 1 Median with interquartile range of subject’s profiles and intersectional point of loading axis of knee on tibial proximal surface (LAK point) in static standing among three KOA severity groups
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(n=41).
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Table 2 Median with interquartile range of knee-joint kinematic and dynamic parameters during stance phase of gait among three KOA severity groups (n=41).
Fig.3.
Typical tracking patterns of intersectional point of loading axis of knee on tibial proximal
surface (LAK point) during stance phase of gait: (a) normal knee; (b) mild KOA and (c) severe KOA.
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Table 1 Median with interquartile range of subject’s profiles and intersectional point of loading axis of knee on tibial proximal surface (LAK point) in static standing among three KOA severity groups (n=41).
Normal (N) Number (Male:Female)
p value
KOA severity Mild (M)
14(9:5)
Severe (S)
8(3:5)
19(5:14)
65(60,68)
73(65,77)
Profile
Height (cm)
31(23,64)
171.0(161.3,173.4) 159.3(153.9,165.8) 153.0(149.5,160.5)
NvsS
MvsS
.356
<.001
.322
.569
.001
.292
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Age (y.o.)
NvsM
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Parameter
68.3(54.6,73.7)
60.8(58.0,64.7)
63.0(56.5,69.7)
-
-
-
BMI
22.7(21.4,24.5)
23.0(21.6,25.5)
26.8(23.5,28.1)
.999
.037
.210
VAS (0 to 10)
0 (0,0.4)
0 (0,1.4)
4.3(1.8,6.5)
.229
.002
.048
JKOM score (max 100)
1 (0,5.5)
2 (0,9.3)
19 (12,35.5)
.999
<.001
.048
9.8(3.2,30.3)
17.2(8.9,22.3)
78.0(43.6,101.4)
.999
<.001
.002
46.9(15.2,67.9)
55.9(27.5,76.3)
86.3(75.9,120.9)
.999
.019
.142
lateral-medial
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LAK point in static standing
direction (%APW)
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direction (%MCW) Anterior-posterior
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Weight (kg)
BMI, body mass index; VAS, visual analogue scale; JKOM, Japanese knee osteoarthritis measure index; MCW, medial
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compartment width of tibial proximal surface; APW, anterior-posterior width of tibial proximal surface.
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Table 2 Median with interquartile range of knee-joint kinematic and dynamic parameters during stance phase of gait among three KOA severity groups (n=41).
p value
KOA severity
(Stance phase of gait)
Normal (N)
Mild (M)
Severe (S)
Range of knee-joint kinematics
.011
.610
.193
.079
<.001
-
-
-
11.3(7.3,17.3)
-
-
-
34.3(25.8,39.0)
-
-
-
9.6(8.8,13.1)
-
-
-
.017
.999
.112
.999
.010
241.4(223.8,261.0) 204.2(174.1,255.7) 199.1(184.7,230.8) .239
.027
.999
5.5(3.8,14.8)
5.7(4.9,7.5)
3.2(3.0,4.1)
7.8(6.1,9.5)
Internal rotation (deg)
12.5(9.2,17.1)
10.6(6.9,13.1)
9.2(7.6,14.1)
Lateral-medial shift (mm)
13.2(9.4,20.4)
12.9(10.1,18.2)
Anterior-posterior shift (mm)
40.0(34.0,47.5)
34.8(24.3,47.8)
Proximal-distal shift (mm)
10.6(9.2,15.8)
14.5(11.0,16.2)
Knee- joint dynamics: LAK-point tracking
178.6(158.8,227.9) 162.1(138.7,190.7) 132.4(118.6,172.7) .425
Lateral-medial length (%MCW) Anterior-posterior
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Length (mm)
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10.1(8.8,14.5)
Adduction (deg)
NvsS MvsS
.827
15.6(10.5,19.6)
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Flexion (deg)
NvsM
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Parameter
51.0(43.3,59.5)
53.7(46.5,67.6)
M
length (%APW)
23.4(21.5,41.4)
LAK point, intersectional point of loading axis of knee on tibial proximal surface; MCW, medial compartment width of
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tibial proximal surface; APW, anterior-posterior width of tibial proximal surface.
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7. Fig 1
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Frontal image
ed
pF,i
ΣT
pT,i
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pt
ΣF
Skin markers into 1mm steel ball
Fig. 1. Subject’s femorotibial bones which are projected onto frontal and 60 degrees oblique X-ray images. {pF,i}and {pT,i} are threedimensional position of reflective skin marker with respect to femoral coordinate system ∑F and tibial coordinate system ∑T, respectively.
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7. Fig 2
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Femoral head center
Loading axis of knee (LAK)
ed
Femur LAK point Lateral
pt LAK
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Tibia
(a)
APW
MCW
Heel rise Posterior
Medial
Tibia
Center of tibial distal surface
Lateral
Medial
M
Femur
Anterior
Anteriorposterior length
Initial contact Foot plant LAK-point tracking
Toe off Lateral-medial length (b)
Fig. 2. (a) Loading axis of knee (LAK) and its intersectional point on tibial proximal surface (LAK point). LAK is the line connecting femoral head center and center of tibial distal surface. (b) LAK-point tracking during stance phase of gait. The lateral-medial and anterior-posterior lengths are normalized by medial compartment width (MCW) and anterior-posterior width (APW) of tibial proximal surface, respectively.
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7. Fig 3
Anterior
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Initial contact Posterior Heel rise Initial contact
Foot plant
Heel rise Initial contact
ed
Foot plant
Foot plant
pt
Heel rise
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Lateral
Medial
Toe off
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Toe off
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LAK-point tracking
Toe off (a)
(b)
(c)
Fig. 3. Typical tracking patterns of intersectional point of loading axis of knee on tibial proximal surface (LAK point) during stance phase of gait: (a) normal knee; (b) mild KOA and (c) severe KOA.
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