BACKGROUND: Fat-suppressed (FS) proton density (PD)-weighted magnetic resonance imaging (MRI) and FS three-dimensional (3D) gradient-echo imaging such as spoiled gradient-recalled (SPGR) sequence have been established as accurate methods for detecting articular cartilage defects. PURPOSE: To retrospectively compare the diagnostic efficacy between FS PD-weighted and FS 3D gradient-echo MRI for differentiating between grade 3 and grade 4 cartilage defects of the knee with arthroscopy as the standard of reference. MATERIAL AND METHODS: Twenty-one patients who had grade 3 or 4 cartilage defects in medial femoral condyle at arthroscopy and knee MRI were included in this study: grade 3, >50% cartilage defects; grade 4, full thickness cartilage defects exposed to the bone. Sagittal FS PD-weighted MR images and FS 3D gradient-echo images with 1.5 T MR images were independently graded for the cartilage abnormalities of medial femoral condyle by two musculoskeletal radiologists. Statistical analysis was performed by Fisher's exact test. Inter-observer agreement in grading of cartilage was assessed using kappa coefficients. RESULTS: Arthroscopy revealed grade 3 defects in 17 patients and grade 4 defects in 4 patients in medial femoral condyles. For FS 3D gradient-echo images grade 3 defects were graded as grade 3 (n=15) and grade 4 (n=2), and all grade 4 defects (n=4) were correctly graded. However, for FS PD-weighted MR images all grade 3 defects were misinterpreted as grade 1 (n=1) and grade 4 (n=16), whereas all grade 4 defects (n=4) were correctly graded. FS 3D gradient-echo MRI could differentiate grade 3 from grade 4 defects (P=0.003), whereas FS PD-weighted imaging could not (P=1.0). Inter-observer agreement was substantial (kappa=0.70) for grading of cartilage using FS PD-weighted imaging, whereas it was moderate (kappa=0.46) using FS 3D gradient-echo imaging. CONCLUSION: FS 3D gradient-echo MRI is more helpful for differentiating between grade 3 and grade 4 cartilage defects than is FS PD-weighted imaging.
BACKGROUND: Fat-suppressed (FS) proton density (PD)-weighted magnetic resonance imaging (MRI) and FS three-dimensional (3D) gradient-echo imaging such as spoiled gradient-recalled (SPGR) sequence have been established as accurate methods for detecting articular cartilage defects. PURPOSE: To retrospectively compare the diagnostic efficacy between FS PD-weighted and FS 3D gradient-echo MRI for differentiating between grade 3 and grade 4 cartilage defects of the knee with arthroscopy as the standard of reference. MATERIAL AND METHODS: Twenty-one patients who had grade 3 or 4 cartilage defects in medial femoral condyle at arthroscopy and knee MRI were included in this study: grade 3, >50% cartilage defects; grade 4, full thickness cartilage defects exposed to the bone. Sagittal FS PD-weighted MR images and FS 3D gradient-echo images with 1.5 T MR images were independently graded for the cartilage abnormalities of medial femoral condyle by two musculoskeletal radiologists. Statistical analysis was performed by Fisher's exact test. Inter-observer agreement in grading of cartilage was assessed using kappa coefficients. RESULTS: Arthroscopy revealed grade 3 defects in 17 patients and grade 4 defects in 4 patients in medial femoral condyles. For FS 3D gradient-echo images grade 3 defects were graded as grade 3 (n=15) and grade 4 (n=2), and all grade 4 defects (n=4) were correctly graded. However, for FS PD-weighted MR images all grade 3 defects were misinterpreted as grade 1 (n=1) and grade 4 (n=16), whereas all grade 4 defects (n=4) were correctly graded. FS 3D gradient-echo MRI could differentiate grade 3 from grade 4 defects (P=0.003), whereas FS PD-weighted imaging could not (P=1.0). Inter-observer agreement was substantial (kappa=0.70) for grading of cartilage using FS PD-weighted imaging, whereas it was moderate (kappa=0.46) using FS 3D gradient-echo imaging. CONCLUSION: FS 3D gradient-echo MRI is more helpful for differentiating between grade 3 and grade 4 cartilage defects than is FS PD-weighted imaging.
Authors: Bashir Zikria; Nima Hafezi-Nejad; Ian Patten; Alex Johnson; Arya Haj-Mirzaian; John H Wilckens; James R Ficke; Shadpour Demehri Journal: JB JS Open Access Date: 2019-05-29