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Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging
OBJECTIVES: Patellar maltracking has been traditionally difficult to assess due to its dynamic component. Unlike the assessment of malalignment, which relies on static radiographic measurements, maltracking is a dynamic phenomenon described subjectively with the J sign. The advent of dynamic, kinema...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4901560/ http://dx.doi.org/10.1177/2325967115S00014 |
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author | Tanaka, Miho Jean Williams, Ariel Elias, John J. Demehri, Shadpour Cosgarea, Andrew J. |
author_facet | Tanaka, Miho Jean Williams, Ariel Elias, John J. Demehri, Shadpour Cosgarea, Andrew J. |
author_sort | Tanaka, Miho Jean |
collection | PubMed |
description | OBJECTIVES: Patellar maltracking has been traditionally difficult to assess due to its dynamic component. Unlike the assessment of malalignment, which relies on static radiographic measurements, maltracking is a dynamic phenomenon described subjectively with the J sign. The advent of dynamic, kinematic computed tomographic imaging (DKCT) has allowed for the dynamic assessment of the patellofemoral joint. We used DKCT to visualize and quantify patterns of patellar maltracking and correlated these findings with the presence or absence of symptoms of patellar instability. METHODS: 76 knees in 38 subjects were analyzed using DKCT. Measurements of bisect offset at 10° intervals of knee flexion were performed for each knee during active flexion/extension cycles. Patterns in bisect offset were assessed and graded in terms of 1, 2 or 3 quadrants of lateral patellar motion, based on 75-100, 100-125, and >125% bisect offset. The presence or absence of symptomatic patellar instability were recorded for each knee, and ratios of patients with symptoms were calculated for J sign tracking patterns of grades 1, 2 and 3. Differences in ratios between Grades 1, 2 and 3 were calculated using chi squared analysis. RESULTS: 76 knees were available for analysis, of which 51 had symptomatic patellar instability. 9 knees demonstrated normal patterns of tracking. 58 knees demonstrated increased lateral translation in extension. 7 knees showed persistent lateralization of the patella throughout range of motion, and 2 knees showed increased translation in flexion. In the 58 knees that showed maximal lateral translation in extension (J sign), the J sign was graded as 1(N=24), 2 (N=20) and 3 (N=14). The sensitivities of J sign grades in predicting patellar instability were 45.8% (J1), 80% (J2), and 92.9% (J3) (p<0.01), with statistically significant differences between Grades 1 and 2/3 (0=0.018). CONCLUSION: On DKCT imaging, we noted additional patterns of patellar maltracking besides the standard J sign. Of those with maltracking in extension (J sign), Grade 2 and 3 J signs with > 2 quadrants of patellar lateralization in extension were predictive of symptomatic patellar instability. Further understanding of patellar maltracking patterns can provide the clinician with information regarding the pathoanatomy and pathophysiology of patellar instability, and allow us to better plan for surgical stabilization. |
format | Online Article Text |
id | pubmed-4901560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-49015602016-06-10 Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging Tanaka, Miho Jean Williams, Ariel Elias, John J. Demehri, Shadpour Cosgarea, Andrew J. Orthop J Sports Med Article OBJECTIVES: Patellar maltracking has been traditionally difficult to assess due to its dynamic component. Unlike the assessment of malalignment, which relies on static radiographic measurements, maltracking is a dynamic phenomenon described subjectively with the J sign. The advent of dynamic, kinematic computed tomographic imaging (DKCT) has allowed for the dynamic assessment of the patellofemoral joint. We used DKCT to visualize and quantify patterns of patellar maltracking and correlated these findings with the presence or absence of symptoms of patellar instability. METHODS: 76 knees in 38 subjects were analyzed using DKCT. Measurements of bisect offset at 10° intervals of knee flexion were performed for each knee during active flexion/extension cycles. Patterns in bisect offset were assessed and graded in terms of 1, 2 or 3 quadrants of lateral patellar motion, based on 75-100, 100-125, and >125% bisect offset. The presence or absence of symptomatic patellar instability were recorded for each knee, and ratios of patients with symptoms were calculated for J sign tracking patterns of grades 1, 2 and 3. Differences in ratios between Grades 1, 2 and 3 were calculated using chi squared analysis. RESULTS: 76 knees were available for analysis, of which 51 had symptomatic patellar instability. 9 knees demonstrated normal patterns of tracking. 58 knees demonstrated increased lateral translation in extension. 7 knees showed persistent lateralization of the patella throughout range of motion, and 2 knees showed increased translation in flexion. In the 58 knees that showed maximal lateral translation in extension (J sign), the J sign was graded as 1(N=24), 2 (N=20) and 3 (N=14). The sensitivities of J sign grades in predicting patellar instability were 45.8% (J1), 80% (J2), and 92.9% (J3) (p<0.01), with statistically significant differences between Grades 1 and 2/3 (0=0.018). CONCLUSION: On DKCT imaging, we noted additional patterns of patellar maltracking besides the standard J sign. Of those with maltracking in extension (J sign), Grade 2 and 3 J signs with > 2 quadrants of patellar lateralization in extension were predictive of symptomatic patellar instability. Further understanding of patellar maltracking patterns can provide the clinician with information regarding the pathoanatomy and pathophysiology of patellar instability, and allow us to better plan for surgical stabilization. SAGE Publications 2015-03-23 /pmc/articles/PMC4901560/ http://dx.doi.org/10.1177/2325967115S00014 Text en © The Author(s) 2015 http://creativecommons.org/licenses/by-nc-nd/3.0/ This open-access article is published and distributed under the Creative Commons Attribution - NonCommercial - No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/3.0/), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For reprints and permission queries, please visit SAGE’s Web site at http://www.sagepub.com/journalsPermissions.nav. |
spellingShingle | Article Tanaka, Miho Jean Williams, Ariel Elias, John J. Demehri, Shadpour Cosgarea, Andrew J. Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging |
title | Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging |
title_full | Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging |
title_fullStr | Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging |
title_full_unstemmed | Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging |
title_short | Characterizing Patterns In Patellar Maltracking On Dynamic Kinematic CT Imaging |
title_sort | characterizing patterns in patellar maltracking on dynamic kinematic ct imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4901560/ http://dx.doi.org/10.1177/2325967115S00014 |
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