|
KMID : 0880420170180040691
|
|
Korean Journal of Radiology
2017 Volume.18 No. 4 p.691 ~ p.698
|
|
|
Texture Analysis of Torn Rotator Cuff on Preoperative Magnetic Resonance Arthrography as a Predictor of Postoperative Tendon Status
|
|
Kang Yeon-Ah
Lee Guen-Young
Lee Joon-Woo
Lee Eu-Gene
Kim Bo-Hyoung
Kim Su-Jin
Ahn Joong-Mo
Kang Heung-Sik
|
|
|
Abstract
|
|
|
Objective: To evaluate texture data of the torn supraspinatus tendon (SST) on preoperative T2-weighted magnetic resonance arthrography (MRA) using the gray-level co-occurrence matrix (GLCM) for prediction of post-operative tendon state.
Materials and Methods: Fifty patients who underwent arthroscopic rotator cuff repair for full-thickness tears of the SST were included in this retrospective study. Based on 1-year follow-up, magnetic resonance imaging showed that 30 patients had intact SSTs, and 20 had rotator cuff retears. Using GLCM, two radiologists measured independantly the highest signal intensity area of the distal end of the torn SST on preoperative T2-weighted MRA, which were compared between two groups.The relationships with other well-known prognostic factors, including age, tear size (anteroposterior dimension), retraction size (mediolateral tear length), grade of fatty degeneration of the SST and infraspinatus tendon, and arthroscopic fixation technique (single or double row), also were evaluated.
Results: Of all the GLCM features, the retear group showed significantly higher entropy (p < 0.001 and p = 0.001), variance (p = 0.030 and 0.011), and contrast (p = 0.033 and 0.012), but lower angular second moment (p < 0.001 and p = 0.002) and inverse difference moment (p = 0.027 and 0.027), as well as larger tear size (p = 0.001) and retraction size (p = 0.002) than the intact group. Retraction size (odds ratio [OR] = 3.053) and entropy (OR = 17.095) were significant predictors.
Conclusion: Texture analysis of torn SSTs on preoperative T2-weighted MRA using the GLCM may be helpful to predict postoperative tendon state after rotator cuff repair.
|
|
|
KEYWORD
|
|
|
Rotator cuff, Shoulder joint, Magnetic resonance imaging, Texture analysis, Statistical data analyses
|
|
|
FullTexts / Linksout information
|
|
 
|
|
|
Listed journal information
|
|
    
|
|