Xiaopeng Wu, Ruijun Wang

The Affliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, People’s Republic of China

Correspondence: Ruijun Wang, Email 602507851@qq.com

Abstract: Brucella spondylitis (BS) is one of the most common and serious complications of brucellosis, with insidious clinical manifestations and lack of specificity, which often delay the disease and cause a series of adverse consequences such as multi-organ involvement and dysfunction in severe cases. Due to the lag of laboratory-related laboratory tests and pathological examinations and the many factors that interfere with the confirmed results, the diagnosis and treatment of BS are affected. Magnetic resonance imaging (MRI) is particularly important in the diagnosis of BS and in the assessment of disease progression, treatment efficacy, and prognosis through a refined response to the structure and function of diseased tissues due to its multiparametric imaging and good tissue resolution. Radiomics, as an emerging means to quantitatively analyze image information and provide disease diagnosis and treatment assistance, is gradually showing its important value, by screening the omics features of the imaging affected vertebral bodies, constructing a diagnostic model based on machine learning, and conducting research on the diagnosis and differential diagnosis of BS.

Keywords: brucella spondylitis, conventional magnetic resonance, functional magnetic resonance, radiomics, machine learning, disease staging