Tanaka Miho J, Elias John J, Williams Ariel A, Demehri Shadpour, Cosgarea Andrew J
Department of Orthopaedic Surgery, The Johns Hopkins University, 601 N. Caroline St. JHOC 5, Baltimore, MD, 21287, USA.
Department of Research, Cleveland Clinic Akron General, Akron, OH, USA.
Knee Surg Sports Traumatol Arthrosc. 2016 Nov;24(11):3634-3641. doi: 10.1007/s00167-016-4216-9. Epub 2016 Jun 29.
Little has been reported on the relationship between patellar maltracking and instability. Patellar maltracking has been subjectively described with the "J sign" but is difficult to assess objectively using traditional imaging. Dynamic kinematic computed tomography (DKCT) allows dynamic assessment of the patellofemoral joint. DKCT was used to visualize and quantify patellar maltracking patterns, and severity of maltracking was correlated with the presence or absence of patellar instability symptoms.
Seventy-six knees in 38 patients were analysed using DKCT. Maltracking was defined as deviation of the patella from the trajectory of the trochlear groove and was characterized by patellar bisect offset, which was measured at 10° intervals of knee flexion during active flexion and extension. Bisect offset measurements were grouped by number of quadrants of maximum lateral patellar motion, with one, two, and three quadrants corresponding to 75-99, 100-125, and >125 %, respectively. Patellar instability symptoms were correlated with maltracking severity.
Two knees were excluded because of poor imaging quality. Fifty of 74 knees had patellar instability, and 13 patients had bilateral symptoms. Of these, four (8 %) had normal tracking patterns; 41 (82 %) had increased lateral translation in extension, which we termed the J-sign pattern; 4 (8 %) had persistent lateralization of the patella throughout range of motion; and 1 had increased lateral translation in flexion. In knees with the J-sign pattern, degree of maltracking was graded by severity: J1 (n = 24), J2 (n = 19), and J3 (n = 15). The sensitivities of J-sign grades in predicting patellar instability symptoms were 50 % (J1), 80 % (J2), and 93 % (J3) (p < 0.01). There were significant differences in sensitivity between knees with no J sign or J1 versus J2 or J3 (p = 0.02).
DKCT showed several patellar maltracking patterns in patients with patellar instability. A J-sign pattern with more than two quadrants of lateral translation correlated with the presence of patellar instability symptoms. Incorporation of this approach of objectively quantifying maltracking patterns is recommended in the evaluation of patellofemoral instability.
IV.
关于髌骨轨迹不良与不稳定之间的关系,此前报道较少。髌骨轨迹不良一直通过“J征”进行主观描述,但使用传统成像技术很难进行客观评估。动态运动计算机断层扫描(DKCT)可对髌股关节进行动态评估。本研究使用DKCT来可视化和量化髌骨轨迹不良模式,并将轨迹不良的严重程度与髌骨不稳定症状的有无进行关联分析。
对38例患者的76个膝关节进行DKCT分析。轨迹不良定义为髌骨偏离滑车沟轨迹,其特征为髌骨二分偏移,在主动屈伸过程中,以膝关节屈曲10°的间隔进行测量。二分偏移测量结果按髌骨最大外侧运动象限数分组,一个、两个和三个象限分别对应75 - 99%、100 - 125%和>125%。将髌骨不稳定症状与轨迹不良严重程度进行关联分析。
由于成像质量差,排除2个膝关节。74个膝关节中,50个存在髌骨不稳定,13例患者有双侧症状。其中,4个(8%)轨迹模式正常;41个(82%)在伸展时出现外侧平移增加,我们称之为J征模式;4个(8%)在整个运动范围内髌骨持续向外侧移位;1个在屈曲时出现外侧平移增加。在具有J征模式的膝关节中,根据严重程度对轨迹不良程度进行分级:J1(n = 24)、J2(n = 19)和J3(n = 15)。J征分级在预测髌骨不稳定症状方面的敏感性分别为50%(J1)、80%(J2)和93%(J3)(p < 0.01)。无J征或J1的膝关节与J2或J3的膝关节在敏感性上存在显著差异(p = 0.02)。
DKCT显示髌骨不稳定患者存在多种髌骨轨迹不良模式。外侧平移超过两个象限的J征模式与髌骨不稳定症状的存在相关。在髌股关节不稳定的评估中,建议采用这种客观量化轨迹不良模式的方法。
IV级。