Identification of superficial invasive and indolent lymphomatous lymph nodes by multiple Ultrasonographic vascular imaging

Author:

Lu Wenjuan1,Li Lin1,Deng Hongyan2,Chen Wenqin1,Shu Hua2,Zhang Pingyang1,Ye Xinhua2

Affiliation:

1. Department of Cardiovascular Ultrasound, Nanjing First Hospital, Nanjing Medical University

2. Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University

Abstract

Abstract

Objective This study aimed to explore whether superficial invasive lymphomas and indolent lymphomas could be identified by Ultrasonographic vascular imaging. Method A retrospectively study enrolled 82 lymphoma patients. According to proliferation rates and clinical course, the lymph nodes were classified as invasive and indolent lymphomatous lymph nodes. All patients underwent ultrasound (US) with three effective techniques: color Doppler flow imaging (CDFI), angio plus ultrasound imaging (AngioPLUS), and contrast-enhanced ultrasound (CEUS). Qualitative and quantitative parameters from the two groups were compared. Finally, the area under the receiver-operating characteristic (ROC) and regression analysis were used to compare the differences between the two groups and determine the diagnostic efficiency of the three techniques for differentiating invasive lymphoma from indolent lymphoma. Result The types of blood flow distribution between invasive and indolent lymphomatous lymph nodes were statistically different in all three Ultrasound techniques. In CDFI, invasive or indolent lymphomatous lymph nodes were determined by resistance index (RI) (p < 0.001). In CEUS, the differences between the two groups in necrosis and arrival time (ATM) (p = 0.026, 0.043) were statistically significant. Finally, CDFI combined with CEUS had the highest diagnostic sensitivity of 98.1%. Interobserver agreements for qualitative parameters were all excellent. Conclusion Ultrasonographic Vascular imaging is an aid in identifying invasive and indolent lymphomatous lymph nodes, and CDFI combined with CEUS had the highest diagnostic sensitivity, which can guide clinicians to make more accurate diagnosis and better treatment for patients.

Publisher

Research Square Platform LLC

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