Differential detection of metastatic and inflammatory lymph nodes using inflow-based vascular-space-occupancy (iVASO) MR imaging

Liuji Guo, Xiaomin Liu, Jun Hua, Lin Dai, Ying Tao, Haimei Cao, Jie Qin, Xiaodan Li, Yuankui Wu

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To investigate the potential value of inflow-based vascular-space-occupancy (iVASO) MR imaging in differentiating metastatic from inflammatory lymph nodes (LNs). Methods: Ten female New Zealand rabbits with 2.5–3.0 kg body weight were studied. VX2 cells and egg yolk emulsion were inoculated into left and right thighs, respectively, to induce ten metastatic and ten inflammatory popliteal LNs. Conventional MRI and iVASO were performed 2 h prior to, and 10, 20 days after inoculation (D0, D10, D20). The short-axis diameter (S), short- to long-axis diameter ratio (SLR), and arteriolar blood volume (BVa) at each time point and their longitudinal changes of each model were recorded and compared. At D20, all rabbits were sacrificed to perform histological evaluation after the MR scan. Results: The mean values of S, SLR and BVa showed no significant difference between the two groups at D0 (P = 0.987, P = 0.778, P = 0.975). The BVa of the metastatic group was greater than that of the inflammatory at both D10 and D20 (P < 0.05; P < 0.001), whereas the S and SLR of the metastatic group were greater only at D20 (P < 0.001; P = 0.001). Longitudinal analyses showed that the BVa of the metastatic group increased at both D10 and D20 (P = 0.004; P = 0.001), while that of the inflammatory group only increased at D10 (P = 0.024). Conclusion: The BVa measured with iVASO has the potential to detect early metastatic LNs.

Original languageEnglish (US)
Pages (from-to)128-132
Number of pages5
JournalMagnetic Resonance Imaging
Volume85
DOIs
StatePublished - Jan 2022

Keywords

  • Animal
  • Lymph node
  • Model
  • Neoplasm
  • Perfusion magnetic resonance imaging

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering

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