Grieser C, Heine G, Stelter L, Steffen I G, Rothe J H, Walter T C, Fischer C, Bahra M, Denecke T
Klinik für Radiologie, Campus Virchow-Klinikum, Charité - Universitätsmedizin Berlin.
Rofo. 2013 Mar;185(3):219-27. doi: 10.1055/s-0032-1325551. Epub 2012 Nov 29.
To evaluate morphologic characteristics and establish a standardized diagnostic algorithm to differentiate benign cystic pancreatic tumors (CPTs) in non-pancreatitis patients using multidetector computed tomography (CT) and magnetic resonance imaging (MRI).
Patients with histopathologically proven CPTs who had undergone MRI and/or CT and subsequent tumor resection in our institution were retrospectively identified. Images were analyzed for morphology and enhancement patterns by three independent blinded observers. Preoperative image findings were correlated with histopathological results. Based on the evaluated morphologic parameters, a standardized diagnostic algorithm was designed to help characterize the lesions.
A total of 62 consecutive patients with 64 CPTs were identified from the surgical database (21 intraductal papillary mucinous neoplasms; 10 mucinous cystic neoplasms; 12 serous microcystic adenomas; 3 serous oligocystic adenomas; 6 solid pseudopapillary tumors; 12 neuroendocrine neoplasms). The overall averaged accuracy for the 3 observers was 89.9 % for CT and 93.1 % for MRI with increasing overall accuracy in relation to the experience of the observer (88.2 %, 91.5 %, and 93.8 %, respectively). Overall, the generalized kappa value was 0.69 (CT, 0.64; MRI, 0.76); p < 0.001). The accuracy of the standardized diagnostic algorithm was 91.1 %.
It is possible to characterize benign CPTs with MRI and CT, while MRI appears to be superior to CT. Diagnostic accuracy depends on the observer's experience. The standardized algorithm can aid in the differential diagnosis but still needs to be tested in other patient populations.
利用多排螺旋计算机断层扫描(CT)和磁共振成像(MRI)评估非胰腺炎患者良性胰腺囊性肿瘤(CPT)的形态学特征,并建立标准化诊断算法以鉴别此类肿瘤。
回顾性纳入我院经组织病理学证实为CPT且接受过MRI和/或CT检查及后续肿瘤切除的患者。由三名独立的盲法观察者分析图像的形态和强化模式。将术前图像表现与组织病理学结果进行关联。基于评估的形态学参数,设计标准化诊断算法以帮助对病变进行特征性描述。
从手术数据库中识别出62例连续患者的64个CPT(21例导管内乳头状黏液性肿瘤;10例黏液性囊性肿瘤;12例浆液性微囊性腺瘤;3例浆液性少囊性腺瘤;6例实性假乳头状肿瘤;12例神经内分泌肿瘤)。3名观察者对CT的总体平均准确率为89.9%,对MRI为93.1%,且随着观察者经验增加总体准确率提高(分别为88.2%、91.5%和93.8%)。总体而言,广义kappa值为0.69(CT为0.64;MRI为0.76);p<0.001)。标准化诊断算法的准确率为91.1%。
利用MRI和CT可以对良性CPT进行特征性描述,而MRI似乎优于CT。诊断准确性取决于观察者的经验。标准化算法有助于鉴别诊断,但仍需在其他患者群体中进行验证。