Accuracy of MRI in Detection of Meniscal Injury when Compared with Knee Arthroscopy
DOI:
https://doi.org/10.51985/Keywords:
Arthroscopy; Diagnostic accuracy; Knee injuries; Magnetic resonance imaging; Meniscal injuryAbstract
Objective: The study aims to establish the level of diagnostic accuracy of magnetic resonance imaging in detecting meniscal injury with knee arthroscopy as the gold standard.
Study Design and Setting: cross-sectional descriptive study that was undertaken at Ghurki Trust Teaching Hospital, Lahore.
Methodology: 156 patients aged between 18 and 65 years old and of both sexes, who presented with clinical suspicion of having meniscal injury were selected through non-probability consecutive sampling. Patients who had undergone a knee surgery previously, knee tumor, those who were pregnant, immunocompromised or those who were not willing to participate were excluded. Every patient also received 1.5-Tesla magnetic-resonance-imaging (MRI) of the knee and knee-arthroscopy. The arthroscopic findings were compared with MRI findings. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy were computed with the help of a 2 × 2 contingency table.
Result: MRI showed injuries in 103 patients and arthroscopy showed injury in 98 patients. When compared to arthroscopy, MRI had 90 true-positives, 45 true-negatives, 13 false-positives and 8 false-negatives. The sensitivity, specificity, positive predictive value, negative predictive value, and the overall diagnostic accuracy of MRI were 91.84, 77.59, 87.38, 84.91 and 86.54 respectively.
Conclusion: MRI was both sensitive and has a good diagnostic accuracy in identifying meniscal injury. It is a convenient non-invasive diagnostic method but arthroscopy still is the gold standard when patients still have persistent symptoms or inconclusive results at imaging
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References
1. Kim SH, Lee HJ, Jang YH, Chun KJ, Park YB. Diagnostic
accuracy of magnetic resonance imaging in the detection of
type and location of meniscus tears: comparison with
arthroscopic findings. J Clin Med. 2021;10(4):606. doi:
10.3390/jcm10040606.
2. Koch JEJ, Ben-Elyahu R, Khateeb B, Ringart M, Nyska M,
Ohana N, et al. Accuracy measures of 1.5-tesla MRI for the
diagnosis of ACL, meniscus and articular knee cartilage
damage and characteristics of false negative lesions: a level
III prognostic study. BMC Musculoskelet Disord.
2021;22(1):124. doi: 10.1186/s12891-021-04011-3.
3. Li J, Qian K, Liu J, Huang Z, Zhang Y, Zhao G, et al.
Identification and diagnosis of meniscus tear by magnetic
resonance imaging using a deep learning model. J Orthop
Translat. 2022;34:91-101. doi: 10.1016/j.jot.2022.05.006.
4. Wang W, Li Z, Peng HM, Bian YY, Li Y, Qian WW, et al.
Accuracy of MRI diagnosis of meniscal tears of the knee: a
meta-analysis and systematic review. J Knee Surg.
2021;34(2):121-129. doi: 10.1055/s-0039-1694056.
5. El-Hagrasy AMA, Theckayil AJ, Khan MA, Khan HN, Butt
AJ. Magnetic resonance imaging is an effective first-line
noninvasive tool for meniscal tear detection: a retrospective
comparative analysis with knee arthroscopy. Arthrosc Sports
Med Rehabil. 2025;7(2):101065. doi: 10.1016/j.asmr.
2024.101065.
6. Zhao Y, Coppola A, Karamchandani U, Amiras D, Gupte CM.
Artificial intelligence applied to magnetic resonance imaging
reliably detects the presence, but not the location, of meniscus
tears: a systematic review and meta-analysis. Eur Radiol.
2024;34(9):5954-5964. doi: 10.1007/s00330-024-10625-7.
7. Vo TT, Nguyen DT, Dinh Le NA, Van Nguyen KH, Vuu HK,
Le TA, et al. Evaluation of meniscal injury on magnetic
resonance imaging and knee arthroscopy in patient with
anterior cruciate ligament tear. SICOT J. 2024;10:56. doi:
10.1051/sicotj/2024051.
8. Botnari A, Kadar M, Patrascu JM. A comprehensive evaluation
of deep learning models on knee MRIs for the diagnosis and
classification of meniscal tears: a systematic review and metaanalysis. Diagnostics (Basel). 2024;14(11):1090. doi:
10.3390/diagnostics14111090.
9. Shin H, Choi GS, Shon OJ, Kim GB, Chang MC. Development
of convolutional neural network model for diagnosing meniscus
tear using magnetic resonance image. BMC Musculoskelet
Disord. 2022;23(1):510. doi: 10.1186/s12891-022-05468-6.
10. Giammanco PA, Collins CE, Trivedi SM, Sarsour RO,
Kricfalusi M, Elsissy JG. Diagnostic accuracy of artificial
intelligence for detection of meniscus pathology on magnetic
resonance imaging: a systematic review. Cureus. 2025;17(9).
doi: 10.7759/cureus.91832.
11. Khalid D, Iqbal J, Mustafa K, Altaf R, Fatima R. Diagnostic
accuracy of magnetic resonance imaging in the detection of
meniscal injury in patients with knee trauma: keeping
arthroscopy as a gold standard. Cureus. 2024;16(10). doi:
10.7759/cureus.72343.
12. Noorelahi Y. Comparative diagnostic accuracy of MRI and
ultrasound in meniscal tear detection: evaluating reliability
and limitations against arthroscopic outcomes. Radiol Res
Pract. 2025;2025:6270476. doi: 10.1155/rrp/6270476.
13. Bottomley J, Al-Dadah O. Diagnostic accuracy of magnetic
resonance imaging in meniscal tears. Cureus. 2025;17(9).
doi: 10.7759/cureus.92155.
14. Nonaka S, Hashimoto Y, Nishino K, Yoshida K, Takahashi
S, Nakamura H, et al. Diagnostic accuracy of magnetic
resonance imaging in the 120° flexed-knee position for
detecting and classifying meniscal ramp lesion. Am J Sports
Med. 2024;52(14):3602-3610. doi: 10.1177/ 03635465
241290516.
15. Escoda Menéndez S, García González P, Meana Morís AR,
Del Valle Soto M, Maestro Fernández A. Evaluation of the
reliability and accuracy of MRI for the diagnosis of meniscal
ramp lesions. Acta Radiol. 2024;65(11):1391-1399. doi:
10.1177/02841851241286765.
16. Moteshakereh SM, Zarei H, Nosratpour M, Zaker Moshfegh
M, Shirvani P, Mirahmadi A, et al. Evaluating the diagnostic
performance of MRI for identification of meniscal ramp
lesions in ACL-deficient knees: a systematic review and metaanalysis. J Bone Joint Surg Am. 2024;106(12):1117-1127.
doi: 10.2106/JBJS.23.00501.
17. Zappia M, Sconfienza LM, Guarino S, Mariani PP. Meniscal
ramp lesions: diagnostic performance of MRI with arthroscopy
as reference standard. Radiol Med. 2021;126(8):1106-1116.
doi: 10.1007/s11547-021-01375-3.
18. D’Ambrosi R, Di Maria F, Ursino C, Ursino N, Di Feo F,
Formica M, et al. Magnetic resonance imaging shows low
sensitivity but good specificity in detecting ramp lesions in
children and adolescents with ACL injury: a systematic review.
J ISAKOS. 2024;9(3):371-377. doi: 10.1016/j.jisako.
2023.12.005.
19. Garcia JR, Ayala SG, Allende F, Mameri E, Haynes M,
Familiari F, et al. Diagnosis and treatment strategies of
meniscus root tears: a scoping review. Orthop J Sports Med.
2024;12(11):23259671241283962. doi: 10.1177/
23259671241283962.
20. Van Dyck P, Vandenrijt J, Vande Vyvere T, Snoeckx A,
Heusdens CHW. Analysis of discordant findings between 3T
magnetic resonance imaging and arthroscopic evaluation of
the knee meniscus. J Clin Med. 2023;12(17):5667. doi:
10.3390/ jcm12175667.
21. Walter SS, Vosshenrich J, Cantarelli Rodrigues T, Dalili D,
Fritz B, Kijowski R, et al. Deep learning superresolution for
simultaneous multislice parallel imaging-accelerated knee
MRI using arthroscopy validation. Radiology. 2025;314(1).
doi: 10.1148/radiol.241249.
22. Escoda Menéndez S, García González P, Meana Morís AR,
Del Valle Soto M, Maestro Fernández A. Reproducibility of
MRI in the diagnosis of meniscal ramp lesions: an interobserver study. Acta Radiol. 2023;64(3):1078-1085. doi:
10.1177/02841851221101878.
23. Vosshenrich J, Breit HC, Donners R, Obmann MM, Harder
D, Ahlawat S, et al. Arthroscopy-validated diagnostic
performance of sub-5-min deep learning super-resolution 3T
knee MRI in children and adolescents. Skeletal Radiol.
2025;54(12):2705-2716. doi: 10.1007/s00256-025-04969-4.
24. Yasuma S, Kobayashi S, Nozaki M, Ueda Y, Sugita T, Kondo
E. Diagnosis of medial meniscal ramp lesion is difficult by
pre-operative magnetic resonance imaging evaluation and
needs a methodical arthroscopic exploration. J Orthop Sci.
2022;27(6):1323-1328. doi: 10.1016/j.jos.2021.07.018
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