Department of Radiology, Seoul National University Hospital, Seoul 03080, Korea.
Institute of Radiation Medicine, Seoul National University College of Medicine, Seoul 03080, Korea.
Korean J Radiol. 2018 Sep-Oct;19(5):930-937. doi: 10.3348/kjr.2018.19.5.930. Epub 2018 Aug 6.
The purpose of this study was to asses the CT findings and clinical features differentiating malignant from benign focal splenic lesions.
Among 673 patients with splenectomy, we included 114 patients with pathologically confirmed focal splenic lesions (malignant = 66, benign = 48). Two radiologists retrospectively assessed CT findings including: size, number, solid component, margin, wall, calcification, contrast-enhancement, lymph node (LN) enlargement and possible malignancy. We assessed clinical features including age, sex, underlying malignancy, fever, and leukocytosis. Multivariate logistic regression analysis was performed to identify significant predictors of malignant lesion. We used receiver operating curve analysis for determination of diagnostic performance.
Common findings of malignant lesions include enhanced, mainly solid, ill-defined margin, absence of splenomegaly, absence of the wall, absence of calcification, LN enlargement, and presence of underlying malignancy ( < 0.05). Among them, mainly solid features (odds ratio [OR], 39.098, = 0.007), LN enlargement (OR, 6.326, = 0.005), and presence of underlying malignancy (OR, 8.615, = 0.001) were significant predictors of malignancy. The mean size of benign splenic lesions (5.8 ± 3.3 cm) was larger than that of malignant splenic lesions (4.0 ± 3.4 cm). Diagnostic performance of CT findings by two reviewers using receiver operating characteristic curve analysis for differentiation of malignant lesions was 0.856 and 0.893, respectively.
Solid nature of the splenic mass on CT images, LN enlargement, and presence of underlying malignancy are significant predictors of malignant splenic lesion.
本研究旨在评估 CT 表现和临床特征对良恶性局灶性脾病变的鉴别诊断价值。
在 673 例行脾切除术的患者中，我们纳入了 114 例经病理证实的局灶性脾病变患者（恶性=66 例，良性=48 例）。两位放射科医生回顾性评估了 CT 表现，包括病变大小、数量、实性成分、边界、壁、钙化、增强方式、淋巴结（LN）肿大和可能的恶性肿瘤。评估了临床特征，包括年龄、性别、潜在恶性肿瘤、发热和白细胞增多。采用多变量逻辑回归分析确定恶性病变的显著预测因子。我们使用接收者操作特征曲线分析来确定诊断性能。
恶性病变的常见 CT 表现包括增强、主要为实性、边界不清、无脾肿大、无壁、无钙化、LN 肿大和潜在恶性肿瘤（<0.05）。其中，主要为实性（优势比[OR]，39.098，=0.007）、LN 肿大（OR，6.326，=0.005）和潜在恶性肿瘤（OR，8.615，=0.001）是恶性肿瘤的显著预测因子。良性脾病变的平均大小（5.8±3.3cm）大于恶性脾病变（4.0±3.4cm）。两位放射科医生使用接收者操作特征曲线分析对恶性病变进行鉴别诊断的 CT 表现的诊断性能分别为 0.856 和 0.893。
CT 图像上脾脏肿块的实性成分、LN 肿大和潜在恶性肿瘤是恶性脾病变的显著预测因子。
