Share this content in WeChat
Clinical Article
Clinical-radiomic analysis of multi-parametric magnetic resonance imaging predicts lymphovascular space invasion and outcomes in cervical cancer
CUI Yaqiong  HUANG Gang  WANG Lili  REN Jialiang  ZHAO Lianping  ZHOU Xing  MA Ying 

Cite this article as: CUI Y Q, HUANG G, WANG L L, et al. Clinical-radiomic analysis of multi-parametric magnetic resonance imaging predicts lymphovascular space invasion and outcomes in cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(2): 73-82. DOI:10.12015/issn.1674-8034.2023.02.013.

[Abstract] Objective The surgical outcomes for patients with cervical cancer (CC) are impaired by lymphovascular space invasion (LVSI). We analyzed the predictive efficacy of radiomic features extracted from pretreatment multi-parameter magnetic resonance imaging (mpMRI) to predict LVSI and clinical outcomes in CC patients due to the lack of a reliable indicator to predict LVSI before surgery.Materials and Methods A retrospective analysis of 125 individuals with CC was performed. We carried out a radiomic-based characterization on the pretreatment mpMRI to develop and validate a noninvasive imaging biomarker capable of distinguishing between LVSI + and LVSI-. The small field of view high-resolution T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), T2WI, and contrast-enhanced T1-weighted were included in the image modalities. The volume of interest of six different sequence images contained 107 extracted features in total. These features were then chosen using univariate analysis, LASSO, and stepwise logistic regression analysis. A Rad-score and 14 clinical factors were integrated into the combined (COMB) model, a stepwise logistic regression-based prediction model. Twenty times 3-fold cross-validation was repeated. The progression-free survival (PFS) survival curve was divided based on the follow-up results and the predicted LVSI status, and a difference in the model for the PFS grouping was observed.Results Radiomics related to intratumoral heterogeneity served as the primary indicator for LVSI prediction. The corresponding Rad-score varied considerably depending on the LVSI status (P<0.001). Multivariate logistics identified 3 LVSI risk variables. The Rad-score was more important than squamous cell carcinoma antigen and hemoglobin [odds ratio (OR): 2.626, 1.061, 0.982]. The radiomic model has an area under the curve (AUC) in the training cohort of 0.823. The COMB model predicted a substantial difference in PFS between the LVSI + and LVSI-groups (median PFS: 64.8 vs. 58.3 months).Conclusions The LVSI status and clinical outcome of CC patients could be predicted using radiomics features in combination with mpMRI radiomics and clinical variates. It may show utility for improving patient stratification strategies in neoadjuvant and surgical settings. The potential of radiomic features to predict tumor prognosis may be connected to their capacity to reflect the histology of LVSI.
[Keywords] uterine cervical neoplasms;lymphovascular space invasion;magnetic resonance imaging;radiomics;prognosis

CUI Yaqiong1   HUANG Gang1*   WANG Lili1   REN Jialiang2   ZHAO Lianping1   ZHOU Xing1   MA Ying1  

1 Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China

2 GE Healthcare China, Shanghai 200203, China

*Correspondence to: Huang G, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS The Project of Gansu Provincial Health Commission (No. GSWSKY2020-15); the Grant from the Gansu Provincial Hospital (No. 20GSSY1-18).
Received  2022-08-08
Accepted  2022-12-21
DOI: 10.12015/issn.1674-8034.2023.02.013
Cite this article as: CUI Y Q, HUANG G, WANG L L, et al. Clinical-radiomic analysis of multi-parametric magnetic resonance imaging predicts lymphovascular space invasion and outcomes in cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(2): 73-82. DOI:10.12015/issn.1674-8034.2023.02.013.

SUNG H, FERLAY J, SIEGEL R L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
LEWICKI P J, BASOURAKOS S P, QIU Y Q, et al. Effect of a randomized, controlled trial on surgery for cervical cancer[J]. N Engl J Med, 2021, 384(17): 1669-1671. DOI: 10.1056/NEJMc2035819.
COHEN P A, JHINGRAN A, OAKNIN A, et al. Cervical cancer[J]. Lancet, 2019, 393(10167): 169-182. DOI: 10.1016/s0140-6736(18)32470-x.
MORICE P, PIOVESAN P, REY A, et al. Prognostic value of lymphovascular space invasion determined with hematoxylin-eosin staining in early stage cervical carcinoma: results of a multivariate analysis[J]. Ann Oncol, 2003, 14(10): 1511-1517. DOI: 10.1093/annonc/mdg412.
LAMBIN P, LEIJENAAR R T H, DEIST T M, et al. Radiomics: the bridge between medical imaging and personalized medicine[J]. Nat Rev Clin Oncol, 2017, 14(12): 749-762. DOI: 10.1038/nrclinonc.2017.141.
CHEN X L, CHEN G W, XU G H, et al. Tumor size at magnetic resonance imaging association with lymph node metastasis and lymphovascular space invasion in resectable cervical cancer: a multicenter evaluation of surgical specimens[J]. Int J Gynecol Cancer, 2018, 28(8): 1545-1552. DOI: 10.1097/IGC.0000000000001327.
LI S J, LIU J, ZHANG F F, et al. Novel T2 mapping for evaluating cervical cancer features by providing quantitative T2 maps and synthetic morphologic images: a preliminary study[J]. J Magn Reson Imaging, 2020, 52(6): 1859-1869. DOI: 10.1002/jmri.27297.
YANG W, QIANG J W, TIAN H P, et al. Minimum apparent diffusion coefficient for predicting lymphovascular invasion in invasive cervical cancer[J]. J Magn Reson Imaging, 2017, 45(6): 1771-1779. DOI: 10.1002/jmri.25542.
XU C, YU Y, LI X R, et al. Value of integrated PET-IVIM MRI in predicting lymphovascular space invasion in cervical cancer without lymphatic metastasis[J]. Eur J Nucl Med Mol Imaging, 2021, 48(9): 2990-3000. DOI: 10.1007/s00259-021-05208-3.
XU X, ZHANG H L, LIU Q P, et al. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma[J]. J Hepatol, 2019, 70(6): 1133-1144. DOI: 10.1016/j.jhep.2019.02.023.
Cui YQ, Wang LL, Zhao LP, et al. Application progress of radiomics in cervical cancer. Chin J Magn Reson Imaging, 2020, 11(6):477-480. DOI: 10.12015/issn.1674-8034.2020.06.020.
DU W, WANG Y, LI D, et al. Preoperative Prediction of Lymphovascular Space Invasion in Cervical Cancer With Radiomics-Based Nomogram[J/OL]. Front Oncol, 2021, 11: 637794 [2022-11-01]. DOI: 10.3389/fonc.2021.637794.
Li Z, Li H, Wang S, et al. MR-Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph-Vascular Space Invasion preoperatively[J]. J Magn Reson Imaging, 2019, May;49(5):1420-1426. DOI: 10.1002/jmri.26531.
HAN M R, RIM N J, LEE J S, et al. Feasibility of high-resolution MR imaging for the diagnosis of intracranial vertebrobasilar artery dissection[J]. Eur Radiol, 2014, 24(12): 3017-3024. DOI: 10.1007/s00330-014-3296-5.
DOWNEY K, RICHES S F, MORGAN V A, et al. Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images[J]. AJR Am J Roentgenol, 2013, 200(2): 314-320. DOI: 10.2214/AJR.12.9545.
PEEKEN J C, SPRAKER M B, KNEBEL C, et al. Tumor grading of soft tissue sarcomas using MRI-based radiomics[J]. EBioMedicine, 2019, 48: 332-340. DOI: 10.1016/j.ebiom.2019.08.059.
WANG S, CHEN X, LIU Z Y, et al. Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancer[C]//SPIE Medical Imaging. Proc SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, California, USA.2019, 10950: 1011-1016. DOI: 10.1117/12.2513129.
WU Q X, SHI D P, DOU S W, et al. Radiomics analysis of multiparametric MRI evaluates the pathological features of cervical squamous cell carcinoma[J]. J Magn Reson Imaging, 2019, 49(4): 1141-1148. DOI: 10.1002/jmri.26301.
HUA W, XIAO T, JIANG X, et al. Lymph-vascular space invasion prediction in cervical cancer: Exploring radiomics and deep learning multilevel features of tumor and peritumor tissue on multiparametric MRI[J/OL]. Biomedical Signal Processing and Control, 2020, 58: 101869 [2022-11-01]. DOI: 10.1016/j.bspc.2020.101869.
BITTENCOURT L K, ATTENBERGER U I, LIMA D, et al. Feasibility study of computed vs measured high b-value (1400 s/mm²) diffusion-weighted MR images of the prostate[J]. World J Radiol, 2014, 6(6): 374-380. DOI: 10.4329/wjr.v6.i6.374.
THOENY H C, DE KEYZER F, KING A D. Diffusion-weighted MR imaging in the head and neck[J]. Radiology, 2012, 263(1): 19-32. DOI: 10.1148/radiol.11101821.
MI H L, SUO S T, CHENG J J, et al. The invasion status of lymphovascular space and lymph nodes in cervical cancer assessed by mono-exponential and bi-exponential DWI-related parameters[J]. Clin Radiol, 2020, 75(10): 763-771. DOI: 10.1016/j.crad.2020.05.024.
LIU Y, YE Z X, SUN H R, et al. Clinical application of diffusion-weighted magnetic resonance imaging in uterine cervical cancer[J]. Int J Gynecol Cancer, 2015, 25(6): 1073-1078. DOI: 10.1097/IGC.0000000000000472.
GUIOT J, VAIDYANATHAN A, DEPREZ L, et al. A review in radiomics: making personalized medicine a reality via routine imaging[J]. Med Res Rev, 2022, 42(1): 426-440. DOI: 10.1002/med.21846.
YANG L F, YANG J B, ZHOU X B, et al. Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients[J]. Eur Radiol, 2019, 29(5): 2196-2206. DOI: 10.1007/s00330-018-5770-y.
YAP F Y, VARGHESE B A, CEN S Y, et al. Shape and texture-based radiomics signature on CT effectively discriminates benign from malignant renal masses[J]. Eur Radiol, 2021, 31(2): 1011-1021. DOI: 10.1007/s00330-020-07158-0.
CRANDALL J P, FRAUM T J, LEE M, et al. Repeatability of 18F-FDG PET radiomic features in cervical cancer[J]. J Nucl Med, 2021, 62(5): 707-715. DOI: 10.2967/jnumed.120.247999.
TRAVERSO A, WEE L, DEKKER A, et al. Repeatability and reproducibility of radiomic features: a systematic review[J]. Int J Radiat Oncol Biol Phys, 2018, 102(4): 1143-1158. DOI: 10.1016/j.ijrobp.2018.05.053.
COHEN P A, JHINGRAN A, OAKNIN A, et al. Cervical cancer[J]. Lancet, 2019, 393(10167): 169-182. DOI: 10.1016/s0140-6736(18)32470-x.
ZHANG R, SONG Y, GAO W J, et al. Expression of P53, COX2 and CD44V6 in early-stage squamous carcinoma of cervix with lymph vascular space invasion positive and negative and its relationship with prognosis[J]. Natl Med J China, 2009, 89(47): 3341-3345. DOI: 10.3760/cma.j.issn.0376-2491.2009.47.010.
BALAYA V, GUANI B, MAGAUD L, et al. Validation of the 2018 FIGO Classification for Cervical Cancer: Lymphovascular Space Invasion Should Be Considered in IB1 Stage[J/OL]. Cancers (Basel), 2020, 12(12): 3554 [2022-11-01]. DOI: 10.3390/cancers12123554.
DONSKOV F. Immunomonitoring and prognostic relevance of neutrophils in clinical trials[J]. Semin Cancer Biol, 2013, 23(3): 200-207. DOI: 10.1016/j.semcancer.2013.02.001.
GIANNI C, PALLESCHI M, SCHEPISI G, et al. Circulating inflammatory cells in patients with metastatic breast cancer: Implications for treatment[J/OL]. Front Oncol, 2022, 12: 882896 [2022-11-01]. DOI: 10.3389/fonc.2022.882896.
TEMUR I, KUCUKGOZ GULEC U, PAYDAS S, et al. Prognostic value of pre-operative neutrophil/lymphocyte ratio, monocyte count, mean platelet volume, and platelet/lymphocyte ratio in endometrial cancer[J]. Eur J Obstet Gynecol Reprod Biol, 2018, 226: 25-29. DOI: 10.1016/j.ejogrb.2018.05.028.
MA JY, KE LC, LIU Q. The pretreatment platelet-to-lymphocyte ratio predicts clinical outcomes in patients with cervical cancer: A meta-analysis[J/OL]. Medicine, 2018, 97(43): e12897 [2022-11-01]. DOI: 10.1097/MD.0000000000012897.
SCHERNBERG A, REUZE S, ORLHAC F, et al. A score combining baseline neutrophilia and primary tumor SUVpeak measured from FDG PET is associated with outcome in locally advanced cervical cancer[J]. Eur J Nucl Med Mol Imaging, 2018, 45(2): 187-195. DOI: 10.1007/s00259-017-3824-z.
FOLLEN M, LEVENBACK C F, IYER R B, et al. Imaging in cervical cancer[J]. Cancer, 2003, 98(9Suppl): 2028-2038. DOI: 10.1002/cncr.11679.

PREV The application of magnetic resonance diffusion kurtosis imaging in efficacy evaluation of early radiotherapy of cervical carcinoma
NEXT The value of ADC texture analysis in differential diagnosis of ovarian epithelial tumors

Tel & Fax: +8610-67113815    E-mail: