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Clinical Article
Study on the value of MRI multiple b-value DWI quantitative parameters in predicting lymphovascular invasion of gastric cancer
YU Wenwei  LI Qiong  WEI Xiaoxue  SANG Zitong  HOU Yajun  LIU Xisheng 

DOI:10.12015/issn.1674-8034.2025.08.013.


[Abstract] Objective To investigate the efficacy of MRI multiple b-value diffusion weighted imaging (DWI) quantitative parameters in predicting lymphovascular invasion of gastric cancer.Materials and Methods Two hundred and thirty gastric cancer patients who underwent radical gastrectomy and gastric MRI examination before the operation. The patients were divided into positive group and negative group according to postoperative pathological results for lymphorascular invasion. The preoperative image T-staging and image N-staging were evaluated, and the lesion thickness, lesion volume and quantitative parameters of mono-exponential mode (MEM), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and stretched exponential model (SEM) of the patients were measured. Logistic regression analysis was used to screen out independent risk factors with positive lymphovascular invasion, receiver operating characteristic (ROC) curve was used to evaluate the efficacy of each parameter in identifying lymphovascular invasion status, and DeLong test was used to compare the efficacy of each parameter.Results There were statistical differences in image T-staging, image N-staging, lesion thickness, lesion volume, apparent diffusion coefficient (ADC) of MEM, mean kurtosis (MK) of DKI, diffusion coefficient (D) and pseudodiffusion coefficient (D*) of IVIM and α of SEM between two groups (all P < 0.05). The area under the curve (AUC) values of DKI_MK, image N-staging and combined models were 0.809 [95% confidence interval (CI): 0.752 to 0.866], 0.666 (0.596 to 0.736) and 0.828 (0.776 to 0.879), respectively. There was no significant difference between DKI_MK and combined model (P > 0.05).Conclusions MRI multiple b-value DWI quantitative parameters can predict lymphovascular invasion in gastric cancer effectively before operation.
[Keywords] gastric cancer;magnetic resonance imaging;diffusion weighted imaging;lymphovascular invasion;preoperative evaluation;prediction

YU Wenwei   LI Qiong   WEI Xiaoxue   SANG Zitong   HOU Yajun   LIU Xisheng*  

Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China

Corresponding author: LIU X S, E-mail: njmu_lxs@163.com

Conflicts of interest   None.

Received  2025-03-22
Accepted  2025-07-07
DOI: 10.12015/issn.1674-8034.2025.08.013
DOI:10.12015/issn.1674-8034.2025.08.013.

[1]
SMYTH E C, NILSSON M, GRABSCH H I, et al. Gastric cancer[J]. Lancet, 2020, 396(10251): 635-648. DOI: 10.1016/S0140-6736(20)31288-5.
[2]
ZHANG Y J, YU J C. The role of MRI in the diagnosis and treatment of gastric cancer[J]. Diagn Interv Radiol, 2020, 26(3): 176-182. DOI: 10.5152/dir.2019.19375.
[3]
ILIC M, ILIC I. Epidemiology of stomach cancer[J]. World J Gastroenterol, 2022, 28(12): 1187-1203. DOI: 10.3748/wjg.v28.i12.1187.
[4]
CHOI S, SONG J H, LEE S J, et al. Lymphovascular invasion: traditional but vital and sensible prognostic factor in early gastric cancer[J]. Ann Surg Oncol, 2021, 28(13): 8928-8935. DOI: 10.1245/s10434-021-10224-6.
[5]
YANG J X, LU Z Y, LI L T, et al. Relationship of lymphovascular invasion with lymph node metastasis and prognosis in superficial esophageal carcinoma: systematic review and meta-analysis[J/OL]. BMC Cancer, 2020, 20(1): 176 [2025-07-01]. https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-6656-3. DOI: 10.1186/s12885-020-6656-3.
[6]
LI X W, LIU A L, CHEN A L, et al. Preliminary study on the value of T2 mapping in predicting lymphovascular invasion of rectal cancer[J]. Chin J Magn Reson Imag, 2022, 13(6): 23-27. DOI: 10.12015/issn.1674-8034.2022.06.005.
[7]
MIN B H, BYEON S J, LEE J H, et al. Lymphovascular invasion and lymph node metastasis rates in papillary adenocarcinoma of the stomach: implications for endoscopic resection[J]. Gastric Cancer, 2018, 21(4): 680-688. DOI: 10.1007/s10120-017-0785-7.
[8]
LI Q, FENG Q X, QI L, et al. Prognostic aspects of lymphovascular invasion in localized gastric cancer: new insights into the radiomics and deep transfer learning from contrast-enhanced CT imaging[J]. Abdom Radiol (NY), 2022, 47(2): 496-507. DOI: 10.1007/s00261-021-03309-z.
[9]
FUJIKAWA H, KOUMORI K, WATANABE H, et al. The clinical significance of lymphovascular invasion in gastric cancer[J]. In Vivo, 2020, 34(3): 1533-1539. DOI: 10.21873/invivo.11942.
[10]
ZHANG C D, NING F L, ZENG X T, et al. Lymphovascular invasion as a predictor for lymph node metastasis and a prognostic factor in gastric cancer patients under 70 years of age: a retrospective analysis[J]. Int J Surg, 2018, 53: 214-220. DOI: 10.1016/j.ijsu.2018.03.073.
[11]
RENZULLI M, CLEMENTE A, SPINELLI D, et al. Gastric cancer staging: is it time for magnetic resonance imaging [J/OL]. Cancers (Basel), 2020, 12(6): 1402 [2025-07-01]. https://www.mdpi.com/2072-6694/12/6/1402. DOI: 10.3390/cancers12061402.
[12]
LI Q, XU W Y, SUN N N, et al. MRI versus dual-energy CT in local-regional staging of gastric cancer[J/OL]. Radiology, 2024, 312(1): e232387 [2025-07-01]. http://pubs.rsna.org/doi/10.1148/radiol.232387. DOI: 10.1148/radiol.232387.
[13]
LI Q, XU W Y, SUN N N, et al. Deep learning-accelerated T2WI: image quality, efficiency, and staging performance against BLADE T2WI for gastric cancer[J]. Abdom Radiol (NY), 2024, 49(8): 2574-2584. DOI: 10.1007/s00261-024-04323-7.
[14]
ZHU Y J, ZHOU Y T, ZHANG W, et al. Value of quantitative dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging in predicting extramural venous invasion in locally advanced gastric cancer and prognostic significance[J]. Quant Imaging Med Surg, 2021, 11(1): 328-340. DOI: 10.21037/qims-20-246.
[15]
SU X H, JIN G Q. Research advances of DWI in response prediction of nasopharyngeal carcinoma[J]. Chin J Magn Reson Imag, 2023, 14(7): 155-159. DOI: 10.12015/issn.1674-8034.2023.07.028.
[16]
KISELEV V G. Microstructure with diffusion MRI: what scale we are sensitive to [J/OL]. J Neurosci Meth, 2021, 347: 108910 [2025-07-01]. https://linkinghub.elsevier.com/retrieve/pii/S0165027020303332. DOI: 10.1016/j.jneumeth.2020.108910.
[17]
TONG P, SUN D, CHEN G, et al. Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer[J/OL]. BMC Cancer, 2023, 23(1): 61 [2025-07-01]. https://bmccancer.biomedcentral.com/articles/10.1186/s12885-023-10534-w. DOI: 10.1186/s12885-023-10534-w.
[18]
JIANG W Y, MENG R Q, CHENG Y, et al. Intra- and peritumoral based radiomics for assessment of lymphovascular invasion in invasive breast cancer[J]. J Magn Reson Imaging, 2024, 59(2): 613-625. DOI: 10.1002/jmri.28776.
[19]
LI J, YAN L L, ZHANG H K, et al. Application of intravoxel incoherent motion diffusion-weighted imaging for preoperative knowledge of lymphovascular invasion in gastric cancer: A prospective study[J]. Abdom Radiol (NY), 2023, 48(7): 2207-2218. DOI: 10.1007/s00261-023-03920-2.
[20]
ALANGARI A I, KIM S, LEE H H, et al. Prognostic impact of lymphovascular invasion in node-negative gastric cancer: A retrospective cohort study[J/OL]. World J Surg Oncol, 2024, 22(1): 340 [2025-07-01]. https://wjso.biomedcentral.com/articles/10.1186/s12957-024-03629-6. DOI: 10.1186/s12957-024-03629-6.
[21]
SUMIYOSHI S, OHASHI T, KUBOTA T, et al. Lymphovascular invasion is associated with poor long-term outcomes in patients with pT1N0-3 or PT2-3N0 remnant gastric cancer: a retrospective cohort study[J/OL]. World J Surg Oncol, 2024, 22(1): 86 [2025-07-01]. https://wjso.biomedcentral.com/articles/10.1186/s12957-024-03371-z. DOI: 10.1186/s12957-024-03371-z.
[22]
LI P, HE H Q, ZHU C M, et al. The prognostic significance of lymphovascular invasion in patients with resectable gastric cancer: a large retrospective study from Southern China[J/OL]. BMC Cancer, 2015, 15: 370 [2025-07-01]. http://bmccancer.biomedcentral.com/articles/10.1186/s12885-015-1370-2. DOI: 10.1186/s12885-015-1370-2.
[23]
QIAO Y H, LI J P, CHEN L, et al. Risk factors of vascular invasion in patients with resectable gastric cancer[J]. Cancer Res Prev Treat, 2022, 49(2): 123-127. DOI: 10.3971/j.issn.1000-8578.2022.21.0565.
[24]
LEONG S P, NAXEROVA K, KELLER L, et al. Molecular mechanisms of cancer metastasis via the lymphatic versus the blood vessels[J]. Clin Exp Metastasis, 2022, 39(1): 159-179. DOI: 10.1007/s10585-021-10120-z.
[25]
SHEYBANI A, MENIAS C O, LUNA A, et al. MRI of the stomach: a pictorial review with a focus on oncological applications and gastric motility[J]. Abdom Imaging, 2015, 40(4): 907-930. DOI: 10.1007/s00261-014-0251-5.
[26]
XU W Y, LI Q, HOU Y J, et al. Application value of ZOOMit DWI in preoperative T staging evaluation of gastric cancer, a comparison with conventional DWI[J]. J Clin Radiol, 2024, 43(8): 1365-1370. DOI: 10.13437/j.cnki.jcr.2024.08.023.
[27]
HOU Y J, SANG Z T, LI Q, et al. Advanced multiparametric MRI strategies for tumor restaging after neoadjuvant therapy in locally advanced gastric cancer[J]. Ann Surg Oncol, 2025, 32(5): 3382-3391. DOI: 10.1245/s10434-025-16972-z.
[28]
SANG Z T, HOU Y J, LI Q, et al. The application value of DCE-MRI based on XD-VIBE in predicting histopathological features of locally advanced gastric cancer[J]. J Clin Radiol, 2024, 43(10): 1744-1749. DOI: 10.13437/j.cnki.jcr.2024.10.005.
[29]
LU J, DAI Y, XIE J W, et al. Combination of lymphovascular invasion and the AJCC TNM staging system improves prediction of prognosis in N0 stage gastric cancer: results from a high-volume institution[J/OL]. BMC Cancer, 2019, 19(1): 216 [2025-07-01]. https://bmccancer.biomedcentral.com/articles/10.1186/s12885-019-5416-8. DOI: 10.1186/s12885-019-5416-8.
[30]
ZENG Q, HONG Y L, CHENG J, et al. Quantitative study of preoperative staging of gastric cancer using intravoxel incoherent motion diffusion-weighted imaging as a potential clinical index[J/OL]. Eur J Radiol, 2021, 141: 109627 [2025-07-01]. https://linkinghub.elsevier.com/retrieve/pii/S0720048X21001078. DOI: 10.1016/j.ejrad.2021.109627.
[31]
YANG H Y, QU J R, WANG Y, et al. Predictive value of intravoxel incoherent motion imaging for lymphovascular invasion in resectable gastric adenocarcinomas[J]. Radiol Pract, 2024, 39(4): 503-508. DOI: 10.13609/j.cnki.1000-0313.2024.04.012.
[32]
YUAN L T, LIN X T, ZHAO P, et al. Correlations between DKI and DWI with ki-67 in gastric adenocarcinoma[J]. Acta Radiol, 2023, 64(5): 1792-1798. DOI: 10.1177/02841851231153035.
[33]
LIU L, LIU W, ZHOU B N, et al. Effect of initial b values on stretched-exponential model diffusion-weighted imaging parameters of prostate cancer[J]. Oncoradiology, 2022, 31(3): 323-329. DOI: 10.19732/j.cnki.2096-6210.2022.03.017.

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