脊柱多发郎格汉斯细胞组织细胞增多症的CT、MRI征象分析

CT and MR findings of Langerhans cell histiocytosis with multiple spinal involvement

目的探讨脊柱多发郎格汉斯细胞组织细胞增多症(LCH)的CT、MRI征象。方法回顾性分析13例经病理证实的脊柱多发LCH患者的影像学检查资料,13例均接受CT检查(1例增强扫描),其中12例接受MR检查(6例增强扫描)。结果 13例中,单中心病变8例,多中心病变5例。共34个病变脊椎,其中核心病变脊椎19个,邻近侵犯脊椎15个。18个(18/19,94.74%)核心病变脊椎存在不同形态、程度的压缩骨折。13例患者共34个病变脊椎CT均表现为溶骨性骨质破坏;19个核心病变脊椎中,18个(18/19,94.74%)骨皮质不完整、可见椎旁软组织肿块。MRI显示12例患者共33个病变脊椎,包括核心病变脊椎18个,邻近侵犯脊椎15个,T1WI均呈等、稍低或低信号,T2WI呈稍高或高信号,脂肪抑制序列呈高信号;17个(17/18,94.44%)核心病变脊椎有椎旁软组织肿块。结论脊柱多发LCH的CT、MRI表现具有一定特征性,加深对本病影像表现的认识可提高诊断和鉴别水平,但确诊需依靠病理检查。

Objective To investigate the CT and MRI features of Langerhans cell histiocytosis（LCH）with multiple spinal involvement.Methods The CT and MRI data of 13 patients with multiple LCH lesions in spine confirmed by pathology were retrospectively analyzed.All of 13 cases underwent CT examination（1 case underwent enhanced scanning）and 12 cases underwent MR examination（6 cases underwent enhanced scanning）.Results In 13 cases,there were 8 cases of single central lesions invading the adjacent vertebrae and 5 cases of multiple central lesions.There were 19 core spinal lesions and 15 adjacent invading lesions in a total of 34 vertebrae lesions.Eighteen core lesions（18/19,94.74%）had different degrees and shape of vertebral compression.A total of 34 abnormal vertebrae were found in 13 cases by CT,which were manifested as osteolytic bone destruction.Eighteen cortical bones of 19 core vertebrae were incomplete,and a paravertebral soft-tissue masses were observed.There were 33 vertebrae lesions in 12 patients who underwent MR examination,including 18 core spinal lesions and 15 adjacent invading lesions.The lesions displayed equal,slightly lower or low signal on T1WI,slightly higher or high signal on T2WI and high signals on fat suppression sequences.A paravertebral soft-tissue masses were observed in 17 core spinal lesions（17/18,94.44%）.Conclusion CT and MRI manifestations of spinal multiple LCH have certain characteristics.The level of diagnosis and differential diagnosis should be improved by deepen understanding of the disease image performance,but the diagnosis still depends on the pathology.