Texture Analysis of Torn Rotator Cuff on Preoperative Magnetic Resonance Arthrography as a Predictor of Postoperative Tendon Status.
10.3348/kjr.2017.18.4.691
- Author:
Yeonah KANG
1
;
Guen Young LEE
;
Joon Woo LEE
;
Eugene LEE
;
Bohyoung KIM
;
Su Jin KIM
;
Joong Mo AHN
;
Heung Sik KANG
Author Information
1. Department of Radiology, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul 07061, Korea.
- Publication Type:Original Article
- Keywords:
Rotator cuff;
Shoulder joint;
Magnetic resonance imaging;
Texture analysis;
Statistical data analyses
- MeSH:
Arthrography*;
Data Interpretation, Statistical;
Entropy;
Follow-Up Studies;
Humans;
Magnetic Resonance Imaging;
Retrospective Studies;
Rotator Cuff*;
Shoulder Joint;
Tears;
Tendons*
- From:Korean Journal of Radiology
2017;18(4):691-698
- CountryRepublic of Korea
- Language:English
-
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.
