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<p>Lymphovascular space invasion (LVSI) is a key prognostic factor influencing treatment decisions in endometrial cancer (EC). Here, we evaluate whether diffusion-weighted imaging (DWI)-based habitat imaging can noninvasively identify LVSI in EC. We retrospectively analyzed 101 EC patients who underwent preoperative multi-b-value DWI examination between December 2020 and October 2024. EC lesions were decoded into four habitats determined by unsupervised K-means clustering using true diffusion coefficient (D), perfusion fraction (f), and mean kurtosis (MK) maps, and the volume fractions of each habitat were quantified. LVSI-positive EC ( <i>n</i> = 22 ) exhibited significantly higher volume fractions of Habitat 1 ( H1 ) and lower volume fractions of Habitat 2 ( H2 ) compared to LVSI-negative cases ( <i>p</i> &lt; 0.001 ). Logistic regression identified independent risk factors for LVSI, including H1, FIGO stage, and histologic grade. H1 demonstrated comparable diagnostic performance (AUC, 0.76 ; 95%CI: 0.67, 0.84 ) to pathological indicators, while achieving the highest sensitivity ( 81.82% ). Additionally, H1 correlated positively with tumor volume, while H2 correlated negatively with histologic grade. These findings suggest DWI-based habitat imaging could serve as a valuable preoperative tool for noninvasive LVSI assessment in EC.</p>

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Evaluate lymphovascular space invasion in endometrial cancer using diffusion-weighted imaging-based habitat imaging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月11日

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  • Wei Wang,
  • Junlan Lang,
  • Kaiming Xue,
  • Yunhai Mao,
  • Wenchao Wang,
  • Yao Meng,
  • Yueluan Jiang,
  • Yang Song,
  • Xuemei Wang,
  • Mengchao Zhang

摘要

Lymphovascular space invasion (LVSI) is a key prognostic factor influencing treatment decisions in endometrial cancer (EC). Here, we evaluate whether diffusion-weighted imaging (DWI)-based habitat imaging can noninvasively identify LVSI in EC. We retrospectively analyzed 101 EC patients who underwent preoperative multi-b-value DWI examination between December 2020 and October 2024. EC lesions were decoded into four habitats determined by unsupervised K-means clustering using true diffusion coefficient (D), perfusion fraction (f), and mean kurtosis (MK) maps, and the volume fractions of each habitat were quantified. LVSI-positive EC ( n = 22 ) exhibited significantly higher volume fractions of Habitat 1 ( H1 ) and lower volume fractions of Habitat 2 ( H2 ) compared to LVSI-negative cases ( p < 0.001 ). Logistic regression identified independent risk factors for LVSI, including H1, FIGO stage, and histologic grade. H1 demonstrated comparable diagnostic performance (AUC, 0.76 ; 95%CI: 0.67, 0.84 ) to pathological indicators, while achieving the highest sensitivity ( 81.82% ). Additionally, H1 correlated positively with tumor volume, while H2 correlated negatively with histologic grade. These findings suggest DWI-based habitat imaging could serve as a valuable preoperative tool for noninvasive LVSI assessment in EC.