MRI-Based Classification for Tibial Spine Fracture: Detection Efficacy, Classification Accuracy, and Reliability

Rania Mostafa Almolla; Yassir Edrees Almalki; Mohammad Abd Alkhalik Basha; Mohamed Abd El-Aziz Mohamed Farag; Maha Ibrahim Metwally; Mohamad Gamal Nada; Yasmin Ibrahim Libda; Mohamed M A Zaitoun; Ahmed A El-Hamid M Abdalla; Hala Y Yousef; Marwa E Abd Elhamed; Amgad M Elsheikh; Sharifa Khalid Alduraibi; Diaa Bakry Eldib; Hamada M Khater; Hossam Fathi Mahmoud; Engy S Elkayal; Shaker Hassan S Alshehri; Asim S Aldhilan; Ahmed M A Basha; Hanan A Hassan

doi:10.1016/j.acra.2023.10.007

MRI-Based Classification for Tibial Spine Fracture: Detection Efficacy, Classification Accuracy, and Reliability

Acad Radiol. 2024 Apr;31(4):1480-1490. doi: 10.1016/j.acra.2023.10.007. Epub 2023 Oct 31.

Authors

Rania Mostafa Almolla¹, Yassir Edrees Almalki², Mohammad Abd Alkhalik Basha³, Mohamed Abd El-Aziz Mohamed Farag⁴, Maha Ibrahim Metwally¹, Mohamad Gamal Nada¹, Yasmin Ibrahim Libda¹, Mohamed M A Zaitoun¹, Ahmed A El-Hamid M Abdalla¹, Hala Y Yousef¹, Marwa E Abd Elhamed¹, Amgad M Elsheikh¹, Sharifa Khalid Alduraibi⁵, Diaa Bakry Eldib⁶, Hamada M Khater⁶, Hossam Fathi Mahmoud⁷, Engy S Elkayal⁸, Shaker Hassan S Alshehri⁹, Asim S Aldhilan⁵, Ahmed M A Basha¹⁰, Hanan A Hassan¹

Affiliations

¹ Department of Radio-diagnosis, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt (R.M.A., M.A.A.B., M.I.M., M.G.N., Y.I.L., M.M.A.Z., A.A.E-H.M.A., H.Y.Y., M.E.A.E., A.M.E., H.A.H.).
² Division of Radiology, Department of Internal Medicine, Medical College, Najran University, Najran, Kingdom of Saudi Arabia (Y.E.A.).
³ Department of Radio-diagnosis, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt (R.M.A., M.A.A.B., M.I.M., M.G.N., Y.I.L., M.M.A.Z., A.A.E-H.M.A., H.Y.Y., M.E.A.E., A.M.E., H.A.H.). Electronic address: Mohammad_basha76@yahoo.com.
⁴ Department of Radio-diagnosis, Faculty of Human Medicine, Al Azhar University, Cairo, Egypt (M.A.E-A.M.F.).
⁵ Department of Radiology, College of Medicine, Qassim University, Buraidah, Kingdom of Saudi Arabia (S.K.A., A.S.A.).
⁶ Department of Radio-diagnosis, Faculty of Human Medicine, Benha University, Benha, Egypt (D.B.E., H.M.K.).
⁷ Department of Orthopedic Surgery and Traumatology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt (H.F.M.).
⁸ Department of Radio-diagnosis, Faculty of Human Medicine, Fayoum University, Fayoum, Egypt (E.S.E.).
⁹ Department of Orthopedic Surgery, College of Medicine, King Khalid University, Abha, Kingdom of Saudi Arabia (S.H.S.A.).
¹⁰ Faculty of General Medicine, Tyumen State Medical University, Tyumen, Russian Federation (A.M.A.B.).

PMID: 37914624
DOI: 10.1016/j.acra.2023.10.007

Abstract

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.

Keywords: Knee; MRI; Mayer and McKeever classification; Tibial spine fractures.

MeSH terms

Humans
Knee Fractures*
Magnetic Resonance Imaging
Reproducibility of Results
Retrospective Studies
Tibial Fractures* / diagnostic imaging
Tibial Fractures* / surgery