Azevedo-Marques P M, Spagnoli H F, Frighetto-Pereira L, Menezes-Reis R, Metzner G A, Rangayyan R M, Nogueira-Barbosa M H
Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:723-6. doi: 10.1109/EMBC.2015.7318464.
Fractures with partial collapse of vertebral bodies are generically referred to as "vertebral compression fractures" or VCFs. VCFs can have different etiologies comprising trauma, bone failure related to osteoporosis, or metastatic cancer affecting bone. VCFs related to osteoporosis (benign fractures) and to cancer (malignant fractures) are commonly found in the elderly population. In the clinical setting, the differentiation between benign and malignant fractures is complex and difficult. This paper presents a study aimed at developing a system for computer-aided diagnosis to help in the differentiation between malignant and benign VCFs in magnetic resonance imaging (MRI). We used T1-weighted MRI of the lumbar spine in the sagittal plane. Images from 47 consecutive patients (31 women, 16 men, mean age 63 years) were studied, including 19 malignant fractures and 54 benign fractures. Spectral and fractal features were extracted from manually segmented images of 73 vertebral bodies with VCFs. The classification of malignant vs. benign VCFs was performed using the k-nearest neighbor classifier with the Euclidean distance. Results obtained show that combinations of features derived from Fourier and wavelet transforms, together with the fractal dimension, were able to obtain correct classification rate up to 94.7% with area under the receiver operating characteristic curve up to 0.95.
椎体部分塌陷的骨折通常被称为“椎体压缩性骨折”（VCF）。VCF可有不同病因，包括外伤、与骨质疏松相关的骨质破坏或影响骨骼的转移性癌症。与骨质疏松相关的VCF（良性骨折）和与癌症相关的VCF（恶性骨折）在老年人群中很常见。在临床环境中，良性和恶性骨折的鉴别复杂且困难。本文介绍了一项旨在开发一种计算机辅助诊断系统的研究，以帮助在磁共振成像（MRI）中鉴别恶性和良性VCF。我们使用了腰椎矢状面的T1加权MRI。研究了47例连续患者（31名女性，16名男性，平均年龄63岁）的图像，包括19例恶性骨折和54例良性骨折。从73个有VCF的椎体的手动分割图像中提取了光谱和分形特征。使用具有欧几里得距离的k近邻分类器对恶性与良性VCF进行分类。所得结果表明，来自傅里叶变换和小波变换的特征组合，以及分形维数，能够获得高达94.7%的正确分类率，受试者操作特征曲线下面积高达0.95。
