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Purpose@#The purpose of this study was to compare the sensitivity of MicroFlow Imaging (MFI) with that of color and power Doppler imaging (CDI and PDI, respectively) in detecting the vascularity of hepatocellular carcinomas (HCCs). @*Methods@#This prospective study enrolled 51 patients diagnosed with HCC between August 2018 and December 2018. CDI, PDI, MFI, and contrast-enhanced ultrasound (CEUS) were performed. Two radiologists evaluated the presence and pattern of tumoral vascularity on CDI, PDI, and MFI. Vascular presence was graded on a 5-point scale (0, absent; 4, >50% of the tumor). The vascular pattern was chosen from following categories: basket, vessels in tumor, spot, detouring, mixed, or others. Two additional radiologists assessed CEUS images for the presence and pattern of tumoral vascularity, which served as the reference standard. If the tumoral vascular pattern on each examination matched that of the CEUS images, the Wilcoxon test and McNemar test, respectively, were used to compare the sensitivity for detecting tumoral vascularity between MFI and CDI, and between MFI and PDI. Logistic regression analysis was performed to identify factors associated with MFI detectability of tumoral vascularity. @*Results@#CEUS demonstrated tumoral vascularity in 98.0% (50 of 51) of patients. MFI (58.0%, 29 of 50) demonstrated a higher sensitivity than CDI (14.0%, 7 of 50) or PDI (14.0%, 7 of 50) (P<0.001 for both) in detecting tumoral vascularity, provided that the vascular pattern was correctly depicted. Only tumor depth was associated with the MFI detectability of tumoral vascularity. @*Conclusion@#The sensitivity of MFI was higher than that of CDI or PDI in detecting the vascularity of HCCs when the vascular pattern was considered. MFI better detected the vascularity of shallow tumors.
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OBJECTIVE: The purpose of this study was to asses the CT findings and clinical features differentiating malignant from benign focal splenic lesions. MATERIALS AND METHODS: 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. RESULTS: 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 (p < 0.05). Among them, mainly solid features (odds ratio [OR], 39.098, p = 0.007), LN enlargement (OR, 6.326, p = 0.005), and presence of underlying malignancy (OR, 8.615, p = 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. CONCLUSION: Solid nature of the splenic mass on CT images, LN enlargement, and presence of underlying malignancy are significant predictors of malignant splenic lesion.