Advanced diffusion-weighted MRI models for preoperative prediction of lymph node metastasis in resectable gastric cancer

被引:0
作者
Li, Jing [1 ,2 ]
Zhang, Hongkai [1 ,2 ]
Bei, Tianxia [1 ,2 ]
Wang, Yi [1 ,2 ]
Ma, Fei [1 ,2 ]
Wang, Shaoyu [3 ]
Li, Haocheng [4 ]
Qu, Jinrong [1 ,2 ]
机构
[1] Zhengzhou Univ, Affiliated Canc Hosp, Zhengzhou, Peoples R China
[2] Henan Canc Hosp, Zhengzhou, Peoples R China
[3] Siemens Hlthineers, MR Res Collaborat, Shanghai, Peoples R China
[4] Xinxiang Med Univ, Sanquan Coll, Xinxiang, Peoples R China
关键词
Diffusion-weighted magnetic resonance imaging; Stomach neoplasms; Lymph node metastasis; COEFFICIENT; DIFFERENTIATION; DIAGNOSIS; MOTION; TUMORS;
D O I
10.1007/s00261-024-04559-3
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectiveTo investigate the potential of six advanced diffusion-weighted imaging (DWI) models for preoperative prediction of lymph node metastasis (LNM) in resectable gastric cancer (GC).MethodsBetween Nov 2022 and Nov 2023, standard MRI scans were prospectively performed in consecutive patients with endoscopic pathology-confirmed gastric adenocarcinoma who were referred for direct radical gastrectomy. Six DWI models, including fractional order calculus (FROC), continuous-time random walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), the mono-exponential model (MEM) and the stretched exponential model (SEM) were computed. Surgical pathologic diagnosis of LNM was the reference standard, and patients were classified into LNM-positive or LNM-negative groups accordingly. The morphological features and quantitative parameters of the DWI models in different LNM categories were analyzed and compared. Multivariable logistic regression was used to screen significant predictors. Receiver-operating characteristic curves and the area under the curve (AUC) were plotted to evaluate the performances, the Delong test was performed to compare the AUCs.ResultsIn the LNM-positive group, tumor thickness and kurtosis (DKI_K) were significantly higher, while anomalous diffusion coefficient (CTRW_D), diffusivity (DKI_D), diffusion coefficient (FROC_D), pseudodiffusion coefficient (IVIM_D*), perfusion fraction (IVIM_f), and ADC were lower compared to the LNM-negative group. Clinical tumor staging (cT) and CTRW_D were independent predictors. Their combination demonstrated a superior AUC of 0.930, significantly higher than that of individual parameters.ConclusionsTumor thickness, DKI_K, CTRW_D, DKI_D, FROC_D, IVIM_D*, IVIM_f and ADC were associated with LNM status. The combination of independent predictors of cT and CTRW_D further enhanced the performance.
引用
收藏
页码:1057 / 1068
页数:12
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