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Clinical Article
Preoperative prediction of vascular invasion in rectal cancer patients without lymph node metastasis based on multimodal MRI imaging features combined with clinical risk factors
YANG Yan  WEI Huanhuan  FU Fangfang  WEI Wei  WU Yaping  JI Xiang  WANG Meiyun 

Cite this article as: YANG Y, WEI H H, FU F F, et al. Preoperative prediction of vascular invasion in rectal cancer patients without lymph node metastasis based on multimodal MRI imaging features combined with clinical risk factors[J]. Chin J Magn Reson Imaging, 2023, 14(1): 94-99, 110. DOI:10.12015/issn.1674-8034.2023.01.017.

[Abstract] Objective To explore the application value of the clinical-radiomics model based on axial fat suppression T2-weighted imaging (FS-T2WI) and T1-weighted contrast-enhanced (T1CE) sequences combined with clinical predictors in the prediction of preoperative lymphovascular invasion (LVI) in patients with rectal cancer without lymph node metastasis.Materials and Methods The cases and imaging data of 221 patients with rectal cancer who underwent MRI scan and were confirmed by postoperative pathology in Henan Provincial People's Hospital from December 2016 to December 2021 were retrospectively included. Univariate and multivariate logistic regression were used to analyze the clinical data of the LVI positive group and the LVI negative group to determine the independent predictors of LVI. The full-layer region of interest (ROI) of tumor was manually delineated by ITK-SNAP software , and the open source software PyRadiomics was used to extract the radiomics features. Patients were divide into the training set (177 cases) and the test set (44 cases) according to the ratio of 8∶2 by SPSS random number table method, and the radiomics signature was constructed after feature dimension reduction. Four prediction models were constructed based on whether clinical predictors were included in the image omics model. The diagnostic efficacy of different prediction models was evaluated according to the area under curve (AUC) of receiver operating characteristic (ROC), sensitivity and specificity.Results Maximum tumor diameter was independent predictors of LVI in patients with rectal cancer (P<0.05). The AUC of FS-T2WI, T1CE and their combination (FS-T2WI+T1CE) was 0.757, 0.802 and 0.869, respectively. The FS-T2WI+T1CE combined with clinical predictors clinical-radiomics model had the best diagnostic performance, with an AUC of 0.898 (95% CI: 0.769, 0.968) in the test set.Conclusions The clinical-radiomics model constructed in this study has a high diagnostic efficiency, which can assist the clinical prediction of preoperative individualized LVI in rectal cancer patients without lymph node metastasis and improve the treatment plan.
[Keywords] rectal cancer;lymphovascular invasion;radiomics;magnetic resonance imaging;logistic regression

YANG Yan1   WEI Huanhuan1   FU Fangfang1, 2   WEI Wei1, 2   WU Yaping1, 2   JI Xiang3   WANG Meiyun1, 2*  

1 Department of Medical Imaging, the People's Hospital of Zhengzhou University, Zhengzhou 450003, China

2 Henan Provincial People's Hospital, Henan Key Laboratory of Neurological Imaging, Zhengzhou 450003, China

3 School of Computers and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, China

Corresponding author: Wang MY, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Henan Provincial Science and Technology Research Project (No. 212102310689); Joint Construction Project of Henan Medical Science and Technology Research Project (No. LHGJ20210001, LHGJ20210005).
Received  2022-08-29
Accepted  2022-12-05
DOI: 10.12015/issn.1674-8034.2023.01.017
Cite this article as: YANG Y, WEI H H, FU F F, et al. Preoperative prediction of vascular invasion in rectal cancer patients without lymph node metastasis based on multimodal MRI imaging features combined with clinical risk factors[J]. Chin J Magn Reson Imaging, 2023, 14(1): 94-99, 110. DOI:10.12015/issn.1674-8034.2023.01.017.

Latest global cancer data: cancer burden rises to 19.3 million new cases and 10.0 million cancer deaths in 2020[EB/OL]. IARC, [2020-12-15].
BRAY F, FERLAY J, SOERJOMATARAM I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68(6): 394-424. DOI: 10.3322/caac.21492.
COMPTON C C, FIELDING L P, BURGART L J, et al. Prognostic factors in colorectal cancer. college of American pathologists consensus statement 1999[J]. Arch Pathol Lab Med, 2000, 124(7): 979-994. DOI: 10.5858/2000-124-0979-PFICC.
KNIJN N, VAN EXSEL U E M, DE NOO M E, et al. The value of intramural vascular invasion in colorectal cancer-a systematic review and meta-analysis[J]. Histopathology, 2018, 72(5): 721-728. DOI: 10.1111/his.13404.
SOHN B, LIM J S, KIM H, et al. MRI-detected extramural vascular invasion is an independent prognostic factor for synchronous metastasis in patients with rectal cancer[J]. Eur Radiol, 2015, 25(5): 1347-1355. DOI: 10.1007/s00330-014-3527-9.
ALE ALI H, KIRSCH R, RAZAZ S, et al. Extramural venous invasion in rectal cancer: overview of imaging, histopathology, and clinical implications[J]. Abdom Radiol (NY), 2019, 44(1): 1-10. DOI: 10.1007/s00261-018-1673-2.
AMIN M B, GREENE F L, EDGE S, et al. AJCC Cancer Staging Manual-8th Edition[M]. New York: Springer, 2017.
ROSÉN R, NILSSON E, RAHMAN M, et al. Accuracy of MRI in early rectal cancer: national cohort study[J]. Br J Surg, 2022, 109(7): 570-572. DOI: 10.1093/bjs/znac059.
GRÖNE J, LOCH F N, TAUPITZ M, et al. Accuracy of various lymph node staging criteria in rectal cancer with magnetic resonance imaging[J]. J Gastrointest Surg, 2018, 22(1): 146-153. DOI: 10.1007/s11605-017-3568-x.
YANG Y S, FENG F, QIU Y J, et al. High-resolution MRI-based radiomics analysis to predict lymph node metastasis and tumor deposits respectively in rectal cancer[J]. Abdom Radiol (NY), 2021, 46(3): 873-884. DOI: 10.1007/s00261-020-02733-x.
CHEN J H, LI R, LIU H, et al. The value of radiomics in preoperative prediction of lymphovascular invasion in colorectal cancer[J]. J Clin Radiol, 2022, 41(3): 495-499. DOI: 10.19401/j.cnki.1007-3639.2020.01.006.
XIE Y H, QIAN Y F, LIU X, et al. Value of the diffusion weighted imaging and dynamic contrast enhanced MRI for diagnosis of neurovascular invasion of rectal cancer[J]. Radiol Pract, 2021, 36(5): 637-641. DOI: 10.13609/j.cnki.1000-0313.2021.05.013.
LI M, JIN Y M, RUI J, et al. Computed tomography-based radiomics for predicting lymphovascular invasion in rectal cancer[J/OL]. Eur J Radiol, 2022, 146: 110065 [2022-08-28]. DOI: 10.1016/j.ejrad.2021.110065.
ZHENG X Y, CAO D R, YOU R X, et al. Comparison of 3.0 tesla magnetic resonance imaging sequences for the diagnostic efficacy of T staging rectal cancer[J]. J Clin Radiol, 2015, 34(12): 1925-1928. DOI: 10.3969/j.issn.1005-5185.2010.05.008
SONG L R, YIN J D. Application of texture analysis based on sagittal fat-suppression and oblique axial T2-weighted magnetic resonance imaging to identify lymph node invasion status of rectal cancer[J/OL]. Front Oncol, 2020, 10: 1364 [2022-08-28]. DOI: 10.3389/fonc.2020.01364.
WEI C X, GU J, ZHAO Z Y, et al. Value of pharmacokinetic DCE-MRI combined with IVIM-DWI in early diagnosis of ductal carcinoma in situ revoke[J]. Radiol Pract, 2020, 35(7): 878-882. DOI: 10.13609/j.cnki.1000-0313.2020.07.009.
DU C Z, XUE W C, CAI Y, et al. Lymphovascular invasion in rectal cancer following neoadjuvant radiotherapy: a retrospective cohort study[J]. World J Gastroenterol, 2009, 15(30): 3793-3798. DOI: 10.3748/wjg.15.3793.
TSUBAMOTO H, YAMAMOTO S, KANAZAWA R, et al. Prognostic factors for locally advanced cervical cancer treated with neoadjuvant intravenous and transuterine arterial chemotherapy followed by radical hysterectomy[J]. Int J Gynecol Cancer, 2013, 23(8): 1470-1475. DOI: 10.1097/IGC.0b013e3182a3402f.
O'BRIEN S, MUTABDZIC D, HANDORF E, et al. Stage Ⅱ and Ⅲ rectal adenocarcinoma outcomes related to lymphovascular invasion[J/OL]. J Clin Oncol, 2019, 37(4_suppl): 698 [2022-08-28]. DOI: 10.1200/JCO.2019.37.4_suppl.698.
YANG Y C, HUANG X Z, SUN J X, et al. Prognostic value of perineural invasion in colorectal cancer: a meta-analysis[J]. J Gastrointest Surg, 2015, 19(6): 1113-1122. DOI: 10.1007/s11605-015-2761-z.
LEE H, LEE H H, KIM I, et al. Long-term outcomes of rectal neuroendocrine tumors according to the risk after endoscopic resection: a multicenter study[J/OL]. J Clin Oncol, 2022, 40(4_suppl): 505 [2022-08-28]. DOI: 10.1200/JCO.2022.40.4_suppl.505.
NG F, KOZARSKI R, GANESHAN B, et al. Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis?[J]. Eur J Radiol, 2013, 82(2): 342-348. DOI: 10.1016/j.ejrad.2012.10.023.
ZHANG Y F, LI Y Y, YANG Y S, et al. High resolution T2WI-based radiomics nomogram for prediction of lymphovascular invasion in rectal cancer[J]. J China Clin Med Imaging, 2021, 32(7): 500-505. DOI: 10.12117/jccmi.2021.07.010.
ZHANG Y Y, HE K, GUO Y, et al. A novel multimodal radiomics model for preoperative prediction of lymphovascular invasion in rectal cancer[J/OL]. Front Oncol, 2020, 10: 457 [2022-08-28]. DOI: 10.3389/fonc.2020.00457.
LIANG C S, HUANG Y Q, HE L, et al. Preoperative prediction of lymphovascular invasion of colorectal cancer based on radiomics approach[J]. Chin J Med Imaging, 2018, 26(3): 191-196, 201. DOI: 10.3969/j.issn.1005-5185.2018.03.008.
GE Y X, XU W B, WANG Z, et al. Prognostic value of CT radiomics in evaluating lymphovascular invasion in rectal cancer: diagnostic performance based on different volumes of interest[J]. J Xray Sci Technol, 2021, 29(4): 663-674. DOI: 10.3233/XST-210877.
ZHANG J, JIN H J, ZHANG F, et al. Correlation of DWI and T2WI volume analysis with extramural vascular invasion and lymph node metastasis in rectal cancer[J]. Radiol Pract, 2020, 35(9): 1151-1156. DOI: 10.13609/j.cnki.1000-0313.2020.09.015.
CHEN X L, CHEN G W, PU H, et al. DWI and T2-weighted MRI volumetry in resectable rectal cancer: correlation with lymphovascular invasion and lymph node metastases[J]. AJR Am J Roentgenol, 2019: 1-8. DOI: 10.2214/AJR.18.20564.
LEE J H, LEE J L, PARK I J, et al. Identification of recurrence-predictive indicators in stage I colorectal cancer[J]. World J Surg, 2017, 41(4): 1126-1133. DOI: 10.1007/s00268-016-3833-2.
LI X Z, XIONG Z Z, XIE M H, et al. Prognostic value of the ratio of carcinoembryonic antigen concentration to maximum tumor diameter in patients with stage Ⅱ colorectal cancer[J]. J Gastrointest Oncol, 2021, 12(4): 1470-1481. DOI: 10.21037/jgo-21-61.
XU H S, ZHAO W Y, GUO W B, et al. Prediction model combining clinical and MR data for diagnosis of lymph node metastasis in patients with rectal cancer[J]. J Magn Reson Imaging, 2021, 53(3): 874-883. DOI: 10.1002/jmri.27369.
HAO C J, SUI Y B, LI J, et al. The clinical value of the combined detection of enhanced CT, MRI, CEA, and CA199 in the diagnosis of rectal cancer[J/OL]. J Oncol, 2021, 2021: 8585371 [2022-08-28]. DOI: 10.1155/2021/8585371.
ZHAO J Y, ZHAO H M, JIA T T, et al. Combination of changes in CEA and CA199 concentration after neoadjuvant chemoradiotherapy could predict the prognosis of stage Ⅱ/Ⅲ rectal cancer patients receiving neoadjuvant chemoradiotherapy followed by total mesorectal excision[J]. Cancer Manag Res, 2022, 14: 2933-2944. DOI: 10.2147/CMAR.S377784.
AKTEKIN A, ÖZKARA S, GÜRLEYIK G, et al. The factors effecting lymphovascular invasion in adenocarcinoma of the colon and rectum[J]. Indian J Surg, 2015, 77(Suppl 2): 314-318. DOI: 10.1007/s12262-013-0816-5.

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