Strong Correlation Between Standing Long-Leg Radiographs and CT Scans in Measuring Coronal Knee Alignment.


Journal

The Journal of bone and joint surgery. American volume
ISSN: 1535-1386
Titre abrégé: J Bone Joint Surg Am
Pays: United States
ID NLM: 0014030

Informations de publication

Date de publication:
13 May 2024
Historique:
medline: 13 5 2024
pubmed: 13 5 2024
entrez: 13 5 2024
Statut: aheadofprint

Résumé

The objective of this study was to evaluate the correlation in measurements of the lower-limb coronal alignment between long-leg radiographs (LLRs) and computed tomography (CT) scanograms that were made during preoperative planning for robotic-arm-assisted knee arthroplasty. On the basis of published evidence demonstrating a good correlation between these imaging modalities in measuring the lower-limb mechanical axis, we hypothesized that there would be no significant differences between the 2 in the present study. This multicenter cohort study across 3 tertiary centers included 300 patients undergoing primary robotic-arm-assisted total knee arthroplasty (TKA) or unicompartmental knee arthroplasty (UKA) for whom LLRs and CT scanograms were available preoperatively. The study involved measuring the medial proximal tibial angle (MPTA), lateral distal femoral angle (LDFA), hip-knee-ankle angle (HKA), joint line obliquity (JLO), joint-line convergence angle (JLCA), and arithmetic HKA (aHKA). The aHKA represents a method for estimating constitutional alignment using angles that are unaffected by joint-space narrowing. Strong correlations (p < 0.001) between the imaging modalities were found for the HKA (correlation coefficient, 0.912), aHKA (0.883), MPTA (0.820), LDFA (0.871), and JLO (0.778). A weaker correlation was observed for the JLCA in valgus knees as compared with varus knees (Spearman coefficients, 0.412 and 0.518, respectively). Regression models demonstrated that the degree of agreement was associated with the preoperative intra-articular deformity and the positioning of the lower limb during the CT scan (i.e., the lower-limb rotational angle). An initial JLCA within ±5° was associated with higher agreement. We observed a strong correlation between LLRs and CT scanograms that were made during the preoperative planning stage of robotic-arm-assisted knee arthroplasty, implying that CT scanograms can reliably be utilized to estimate the coronal alignment of the knee, potentially replacing the need for LLRs. Nevertheless, to attain a higher degree of agreement, it is crucial to ensure appropriate radiographic positioning of the lower limb. Additionally, surgeons must remain vigilant regarding potential discrepancies in cases involving substantial deformities. Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Sections du résumé

BACKGROUND BACKGROUND
The objective of this study was to evaluate the correlation in measurements of the lower-limb coronal alignment between long-leg radiographs (LLRs) and computed tomography (CT) scanograms that were made during preoperative planning for robotic-arm-assisted knee arthroplasty. On the basis of published evidence demonstrating a good correlation between these imaging modalities in measuring the lower-limb mechanical axis, we hypothesized that there would be no significant differences between the 2 in the present study.
METHODS METHODS
This multicenter cohort study across 3 tertiary centers included 300 patients undergoing primary robotic-arm-assisted total knee arthroplasty (TKA) or unicompartmental knee arthroplasty (UKA) for whom LLRs and CT scanograms were available preoperatively. The study involved measuring the medial proximal tibial angle (MPTA), lateral distal femoral angle (LDFA), hip-knee-ankle angle (HKA), joint line obliquity (JLO), joint-line convergence angle (JLCA), and arithmetic HKA (aHKA). The aHKA represents a method for estimating constitutional alignment using angles that are unaffected by joint-space narrowing.
RESULTS RESULTS
Strong correlations (p < 0.001) between the imaging modalities were found for the HKA (correlation coefficient, 0.912), aHKA (0.883), MPTA (0.820), LDFA (0.871), and JLO (0.778). A weaker correlation was observed for the JLCA in valgus knees as compared with varus knees (Spearman coefficients, 0.412 and 0.518, respectively). Regression models demonstrated that the degree of agreement was associated with the preoperative intra-articular deformity and the positioning of the lower limb during the CT scan (i.e., the lower-limb rotational angle). An initial JLCA within ±5° was associated with higher agreement.
CONCLUSIONS CONCLUSIONS
We observed a strong correlation between LLRs and CT scanograms that were made during the preoperative planning stage of robotic-arm-assisted knee arthroplasty, implying that CT scanograms can reliably be utilized to estimate the coronal alignment of the knee, potentially replacing the need for LLRs. Nevertheless, to attain a higher degree of agreement, it is crucial to ensure appropriate radiographic positioning of the lower limb. Additionally, surgeons must remain vigilant regarding potential discrepancies in cases involving substantial deformities.
LEVEL OF EVIDENCE METHODS
Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Identifiants

pubmed: 38739702
doi: 10.2106/JBJS.23.01092
pii: 00004623-990000000-01098
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Authors. Published by The Journal of Bone and Joint Surgery, Incorporated. All rights reserved.

Déclaration de conflit d'intérêts

Disclosure: This work was supported by a scholarship from the Onassis Foundation (F ZR 065-1/2021-2022). The Article Processing Charge for open access publication was funded by University College London. The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article (http://links.lww.com/JBJS/I7).

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Auteurs

Andreas Fontalis (A)

Department of Trauma and Orthopaedic Surgery, University College Hospital, London, United Kingdom.
Division of Surgery and Interventional Science, University College London, London, United Kingdom.

Thomas Luyckx (T)

Department of Orthopaedic Surgery, AZ Delta Roeselare, Roeselare, Belgium.

Thomas Vanspauwen (T)

Hôpitaux Robert Schuman, Luxembourg City, Luxembourg.

Robin Moreels (R)

Department of Orthopaedic Surgery, AZ Delta Roeselare, Roeselare, Belgium.

Fabio Mancino (F)

Department of Trauma and Orthopaedic Surgery, University College Hospital, London, United Kingdom.

Rhody David Raj (RD)

Department of Trauma and Orthopaedic Surgery, University College Hospital, London, United Kingdom.

Philip Winnock de Grave (P)

Department of Orthopaedic Surgery, AZ Delta Roeselare, Roeselare, Belgium.

Ricci Plastow (R)

Department of Trauma and Orthopaedic Surgery, University College Hospital, London, United Kingdom.

Pierre Putzeys (P)

Hôpitaux Robert Schuman, Luxembourg City, Luxembourg.

Fares S Haddad (FS)

Department of Trauma and Orthopaedic Surgery, University College Hospital, London, United Kingdom.
Division of Surgery and Interventional Science, University College London, London, United Kingdom.

Classifications MeSH