Reproducibility assessment of different descriptions of the Kellgren and Lawrence classification for osteoarthritis of the knee

Gonçalves, Felipe Borges; Rocha, Felipe Almeida; Albuquerque, Rodrigo Pires e; Mozella, Alan de Paula; Crespo, Bernardo; Cobra, Hugo Alexandre de Araújo Barros

doi:10.1016/j.rboe.2016.10.009

Cited by 7 publications

(7 citation statements)

References 20 publications

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“…Comparable to other studies on ROA, we included them in our analysis to avoid inflation of incidence and progression rates 20 . Despite these limitations, our results are comparable to the estimates from other well-known cohort studies, which gives us confidence that, in most cases, our results are reliable 5,27,28 .…”

Section: J O U R N a L P R E -P R O O Fsupporting

confidence: 87%

The prevalence, incidence, and progression of radiographic thumb base osteoarthritis in a population-based cohort: the Rotterdam Study

Teunissen

Wouters

Bierma-Zeintra

et al. 2022

Osteoarthritis and Cartilage

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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.

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Section: J O U R N a L P R E -P R O O Fsupporting

confidence: 87%

The prevalence, incidence, and progression of radiographic thumb base osteoarthritis in a population-based cohort: the Rotterdam Study

Teunissen

Wouters

Bierma-Zeintra

et al. 2022

Osteoarthritis and Cartilage

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“…Although widely used by orthopedists and radiologists, the subjective component of KL classification has been mentioned in previous literature. 6 Therefore, it is essential to develop a KL classification model with good interobserver agreement compared with physicians. We merged the KL 0 and 1 classes based on the finding that both represent no radiographic evidence of OA change.…”

Section: Discussionmentioning

confidence: 99%

Successful real‐world application of an osteoarthritis classification deep‐learning model using 9210 knees—An orthopedic surgeon's view

Wang

Huang

Thogiti

et al. 2022

Journal Orthopaedic Research

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This study aimed to evaluate the performance of a deep‐learning model to evaluate knee osteoarthritis using Kellgren–Lawrence grading in real‐life knee radiographs. A deep convolutional neural network model was trained using 8964 knee radiographs from the osteoarthritis initiative (OAI), including 962 testing set images. Another 246 knee radiographs from the Far Eastern Memorial Hospital were used for external validation. The OAI testing set and external validation images were evaluated by experienced specialists, two orthopedic surgeons, and a musculoskeletal radiologist. The accuracy, interobserver agreement, F1 score, precision, recall, specificity, and ability to identify surgical candidates were used to compare the performances of the model and specialists. Attention maps illustrated the interpretability of the model classification. The model had a 78% accuracy and consistent interobserver agreement for the OAI (model‐surgeon 1 К = 0.80, model‐surgeon 2 К = 0.84, model‐radiologist К = 0.86) and external validation (model‐surgeon 1 К = 0.81, model‐surgeon 2 К = 0.82, model‐radiologist К = 0.83) images. A lower interobserver agreement was found in the images misclassified by the model (model‐surgeon 1 К = 0.57, model‐surgeon 2 К = 0.47, model‐radiologist К = 0.65). The model performed better than specialists in identifying surgical candidates (Kellgren–Lawrence Stages 3 and 4) with an F1 score of 0.923. Our model not only had comparable results with specialists with respect to the ability to identify surgical candidates but also performed consistently with open database and real‐life radiographs. We believe the controversy of the misclassified knee osteoarthritis images was based on a significantly lower interobserver agreement.

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“…In a recent study, Gonçalves et al. while reporting on reliability testing for grading of OA using the KL method showed conflicting results [3]. The study reported that the level of agreement in the inter observer analysis was superficial.…”

Section: Introductionmentioning

confidence: 99%

“…Although Kellgren and Lawrence (KL) method is the most commonly used grading system for knee OA, however, it has poor objectivity [2]. In a recent study, Gonçalves et al while reporting on reliability testing for grading of OA using the KL method showed conflicting results [3]. The study reported that the level of agreement in the inter observer analysis was superficial.…”

Section: Introductionmentioning

confidence: 99%

Non‐invasive assessment of knee osteoarthritis patients using thermal imaging

Lohchab

Rathod

Mahapatra

et al. 2021

IET Science Measure & Tech

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Radiography is a widely used method for grading and tracking the anatomical changes in knee osteoarthritis (OA) patients. The ease of thermography in mapping functional information via the skin temperature (Tsk) helps in the diagnosis of various musculoskeletal diseases. There is a significant involvement of soft tissues in knee OA due to the complex osteoligamentous degeneration, which may affect the knee Tsk. A total of 62 patients with knee OA were analysed using thermography. The mean Tsk was computed by extracting the region of interest from the acquired thermal images using an automatic segmentation technique for frontal, lateral, and medial views. The mean Tsk for grade 1, 2, 3 and 4 were 30.96 ± 0.59, 31.56 ± 0.79, 31.40 ± 1.22, 32.20 ± 0.70˚C respectively. A significant temperature difference was found between grade 2 and 4 (p = 0.02, p = 0.018), grade 3 and 4 (p = 0.03, p = 0.02) for frontal and lateral views; whereas no significant difference was found between grade 2 and 3. Further, 2-way ANOVA test showed that risk factors (like age, BMI and duration of disease) do affect the mean Tsk significantly with a p-value of 0.0003, 0.02, and 0.008. INTRODUCTIONAccording to the world health organization, 9.6% of men and 18% of women over the age of 60 years are affected by Osteoarthritis (OA) [1]. OA is a degenerative disease, where the cartilage of the joints, such as the knee, hip, toe, and fingers deteriorate with time. Although Kellgren and Lawrence (KL) method is the most commonly used grading system for knee OA, however, it has poor objectivity [2]. In a recent study, Gonçalves et al. while reporting on reliability testing for grading of OA using the KL method showed conflicting results [3]. The study reported that the level of agreement in the inter observer analysis was superficial. In contrast to radiography, the thermography captures the infrared (IR) radiations emanated from the body surface and provides the map of skin temperature (Tsk).It is a non-radiative, non-invasive, and non-contact imaging modality. A bone is a highly vascular structure that can lead to high blood flow due to bone remodelling in osteoarthritis [4][5][6].Unlike radiology which only captures structural changes, ther-This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Reproducibility assessment of different descriptions of the Kellgren and Lawrence classification for osteoarthritis of the knee

Cited by 7 publications

References 20 publications

The prevalence, incidence, and progression of radiographic thumb base osteoarthritis in a population-based cohort: the Rotterdam Study

The prevalence, incidence, and progression of radiographic thumb base osteoarthritis in a population-based cohort: the Rotterdam Study

Successful real‐world application of an osteoarthritis classification deep‐learning model using 9210 knees—An orthopedic surgeon's view

Non‐invasive assessment of knee osteoarthritis patients using thermal imaging

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