摘要
目的探讨结节性甲状腺肿的CT表现,提高认识。方法回顾性分析20例(共26侧甲状腺)结节性甲状腺肿的CT、手术及病理资料。重点分析的指标有病灶形态、边界、密度、钙化、淋巴结及是否侵犯周围组织。结果 20例患者术前CT检出病灶19例(25侧甲状腺病灶),病灶检出率为96.15%(25/26),1例峡部结节性甲状腺肿未检出,漏诊率为3.85%(1/26)。术前诊断结节性甲状腺肿9例(15侧甲状腺),诊断准确率为60.00%(15/25),术前诊断良性病灶17例(22侧甲状腺),诊断符合率88%(22/25)。结节性甲状腺肿CT主要征象为病灶常多发占90.00%(18/20),形态规则且边界清楚占88.46%(23/26),无淋巴结肿大及周围组织受侵(100.00%),肿瘤可合并钙化占23.08%(6/26),囊变/出血占46.15%(12/26),密度可均匀占61.54%(16/26)或不均匀占30.77%(8/26)。增强后病灶轻度至中度强化,瘤内坏死囊变区域无强化。结论 CT对结节性甲状腺肿的检出率高,掌握其主要CT征象有助于结节性甲状腺肿的诊断与鉴别诊断。
Objective To investigate the CT manifestations of nodular goiter. Methods CT findings of 20 patients （26 lesions） with nodular goiter proved by surgery and pathology were reviewed and compared with surgery and pathology findings. The shape, border, internal density, infiltration and metastasis of adjacent were emphatically observed. Results 25 lesions （19 patients） were detected by CT and the lesion detection rate was 96.15%（25/26） before operation and one lesion in the thyroid gorge was not detected and the omission diagnostic rate was 3.85 % （1/26）. 15 nodular goiter lesions （9 patients） were diagnosed and the CT accuracy rate with nodular goiter was 60.00%（15/25）. 22 （17 patients） benign lesions were diagnosed before operation and the diagnosis accordance rate of CT was 880% （22/25） in nodular goiter. The CT imaging of nodular goiter showed multiple lesions in 90.00% （18/20）, well-defined round or round-like and defined boundary in 88. 46% （23/26）, calification in 23.08% （6/26）, cystic-like and hemorrhagic area in 46. 15% （12/26）, uniform density in 61.54%（16/26） or not in 30. 77% （8/26）, infiltration and metastasis of adjacent could not be found in 100.00%. All cases had slightly and moderately enhancement on contrast-enhanced CT scans and enhancement could not be found in the central necrotic or cystic changed region. Conclusion The CT scan has a hign detection rate for the nodular goiter. Mastering the CT features of nodular goiter can improve the accuracy of differential diagnosis.
出处
《医学影像学杂志》
2013年第1期34-38,共5页
Journal of Medical Imaging
基金
湖北省教育厅科学技术研究项目(编号:D20112103)
