ضياء بكرى فؤاد محمد عبدالرحمن الديب
أستاذ مساعد
MRI-Based Classification for Tibial Spine Fracture: Detection Efficacy, Classification Accuracy, and Reliability
Academic Radiology • 2024
معلومات البحث
المؤلفون
Rania Mostafa Almolla, Diaa Bakry Eldib, at al
الكلمات المفتاحية
Not Available
المجلة العلمية
Academic Radiology
الناشر
Elsevier
المجلد
31
العدد
4
الصفحات
1480-1490
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
Rationale and Objectives
Recently, a new MRI-based classification for evaluating tibial spine fractures (TSFs) was developed to aid in treating these injuries. Our objective was to assess the detection efficacy, classification accuracy, and reliability of this classification in detecting and grading TSFs, as well as its impact on treatment strategy, compared to the Meyers and McKeever (MM) classification.
Materials and Methods
A retrospective study included 68 patients with arthroscopically confirmed TSFs. All patients had plain radiography and conventional MRI of the affected knee before arthroscopy. Three experienced radiologists independently reviewed all plain radiographs and MRI data and graded each patient according to MM and MRI-based classifications. The detection efficacy, classification accuracy, and inter-rater agreement of both classifications were evaluated and compared, using arthroscopic findings as the gold standard.
Results
The final analysis included 68 affected knees. Compared to the MM classification, the MRI-based classification produced 22.0% upgrade of TSFs and 11.8% downgrade of TSFs. According to the reviewers, the fracture classification accuracy of the MRI-based classification (91.2–95.6%) was significantly higher than that of the MM classification (73.5–76.5%, p = 0.002–0.01). The fracture detection rate of MRI-based classification (94.1–98.5%) was non-significantly higher than that of the MM classification (83.8–89.7%, p = 0.07–0.4). The soft tissue injury detection accuracy for MRI-based classification was 91.2–94.1%. The inter-rater reliability for grading TSFs was substantial for both the MM classification (κ = 0.69) and MRI-based classification (κ = 0.79).
Conclusion
MRI-based classification demonstrates greater accuracy and reliability compared to MM classification for detecting and grading TSFs and associated soft tissue injuries.
Recently, a new MRI-based classification for evaluating tibial spine fractures (TSFs) was developed to aid in treating these injuries. Our objective was to assess the detection efficacy, classification accuracy, and reliability of this classification in detecting and grading TSFs, as well as its impact on treatment strategy, compared to the Meyers and McKeever (MM) classification.
Materials and Methods
A retrospective study included 68 patients with arthroscopically confirmed TSFs. All patients had plain radiography and conventional MRI of the affected knee before arthroscopy. Three experienced radiologists independently reviewed all plain radiographs and MRI data and graded each patient according to MM and MRI-based classifications. The detection efficacy, classification accuracy, and inter-rater agreement of both classifications were evaluated and compared, using arthroscopic findings as the gold standard.
Results
The final analysis included 68 affected knees. Compared to the MM classification, the MRI-based classification produced 22.0% upgrade of TSFs and 11.8% downgrade of TSFs. According to the reviewers, the fracture classification accuracy of the MRI-based classification (91.2–95.6%) was significantly higher than that of the MM classification (73.5–76.5%, p = 0.002–0.01). The fracture detection rate of MRI-based classification (94.1–98.5%) was non-significantly higher than that of the MM classification (83.8–89.7%, p = 0.07–0.4). The soft tissue injury detection accuracy for MRI-based classification was 91.2–94.1%. The inter-rater reliability for grading TSFs was substantial for both the MM classification (κ = 0.69) and MRI-based classification (κ = 0.79).
Conclusion
MRI-based classification demonstrates greater accuracy and reliability compared to MM classification for detecting and grading TSFs and associated soft tissue injuries.
