Discrimination between Malignant and Benign Vertebral Fractures Using Magnetic Resonance Imaging.
10.4184/asj.2017.11.3.478
- Author:
Tomoyuki TAKIGAWA
1
;
Masato TANAKA
;
Yoshihisa SUGIMOTO
;
Tomoko TETSUNAGA
;
Keiichiro NISHIDA
;
Toshifumi OZAKI
Author Information
1. Department of Orthopaedic Surgery, Okayama University Hospital, Okayama, Japan. takigawa2004@yahoo.co.jp
- Publication Type:Original Article
- Keywords:
Spine;
Spinal fracture;
Osteoporosis;
Metastasis;
Logistic model
- MeSH:
Diagnosis;
Discrimination (Psychology)*;
Humans;
Logistic Models;
Magnetic Resonance Imaging*;
Multiple Myeloma;
Neoplasm Metastasis;
Osteoporosis;
Retrospective Studies;
Spinal Fractures;
Spine
- From:Asian Spine Journal
2017;11(3):478-483
- CountryRepublic of Korea
- Language:English
-
Abstract:
STUDY DESIGN: Retrospective analysis using magnetic resonance imaging (MRI). PURPOSE: To identify MRI features that could discriminate benign from malignant vertebral fractures. OVERVIEW OF LITERATURE: Discrimination between benign and malignant vertebral fractures remains challenging, particularly in patients with osteoporosis and cancer. Presently, the most sensitive means of detecting and assessing fracture etiology is MRI. However, published reports have focused on only one or a few discriminators. METHODS: Totally, 106 patients were assessed by MRI within six weeks of sustaining 114 thoracic and/or lumbar vertebral fractures (benign, n=65; malignant, n=49). The fractures were pathologically confirmed if malignant or clinically diagnosed if benign and were followed up for a minimum of six months. Seventeen features were analyzed in all fractures' magnetic resonance images. Single parameters were analyzed using the chi-square test; a logit model was established using multivariate logistic regression analysis. RESULTS: The chi-square test revealed 11 malignant and 4 benign parameters. Multivariate logistic regression analysis selected (i) posterior wall diffuse protrusion (odds ratio [OR], 48; 95% confidence interval [CI], 4.2–548; p=0.002), (ii) pedicle involvement (OR, 21; 95% CI, 2.0–229; p=0.01), (iii) posterior involvement (OR, 21; 95% CI, 1.5–21; p=0.02), and (iv) band pattern (OR, 0.047; 95% CI, 0.0005–4.7; p=0.19). The logit model was expressed as P=1/[1+exp (x)], x=−3.88×(i)−3.05×(ii)−3.02×(iii)+3.05×(iv)+5.00, where P is the probability of malignancy. The total predictive value was 97.3%. The only exception was multiple myeloma with features of a benign fracture. CONCLUSIONS: Although each MRI feature had a different meaning with a variable differentiation power, combining them led to an accurate diagnosis. This study identified the most relevant MRI features that would be helpful in discriminating benign from malignant vertebral fractures.
