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Clinical Article
Nomogram based on clinical, pathological, and DWI quantitative parameters for predicting the programmed death-ligand 1 positive expression in cervical cancer: Comparison of different ROI options
LIU Kaihui  YANG Wei  TIAN Haiping  ZHANG Zhining  LI Yunxia  HE Jianli 

Cite this article as: LIU K H, YANG W, TIAN H P, et al. Nomogram based on clinical, pathological, and DWI quantitative parameters for predicting the programmed death-ligand 1 positive expression in cervical cancer: Comparison of different ROI options[J]. Chin J Magn Reson Imaging, 2023, 14(10): 98-104, 115. DOI:10.12015/issn.1674-8034.2023.10.017.


[Abstract] Objective To explore the value of the nomogram based on clinical, pathological, and diffusion weighted imaging (DWI) quantitative parameters for predicting programmed death-ligand 1 (PD-L1) positive expression in cervical cancer.Materials and Methods A total of 683 patients with pathologically confirmed cervical cancer between January 2018 to June 2020 were retrospectively enrolled as the training cohort. They underwent pelvic MRI scans and PD-L1 immunohistochemical staining. The solid component of tumors on DWI images was identified using T2WI and enhanced images. The region of interest (ROI) was manually drawn around the tumor borders, and apparent diffusion coefficient (ADC) values were obtained from corresponding ADC pseudo-color images. The mean ADC value (ADCmean) was calculated by averaging ADC values from selected slices. Additionally, the maximum solid component slice on DWI was chosen, and the ADC value for this slice was recorded as single section ADC (ADCss). For each slice containing solid tumor components, multiple circular or circular-like ROIs (30-50 mm²) were placed to extract minimum ADC (ADCmin) values. Differences in clinical, pathological, and imaging parameters including age at diagnosis, FIGO staging, pathological grade, parametrial invasion, lymph node status, and ADC values from different ROIs were compared between PD-L1 positive and negative groups. Univariable and multivariable logistic regression analyses were conducted to identify independent parameters related to PD-L1 positive expression. Clinical-pathological and combined clinical-pathological-imaging models were developed. Diagnostic effectiveness of different ADC values and models was assessed using area under the curve (AUC) of receiver operating characteristic (ROC) and DeLong test. The combined model's nomogram, calibration slope, and decision curve were evaluated. A validation cohort of 332 cervical cancer patients from July 2020 to December 2022 was enrolled to validate the nomogram.Results FIGO staging, pathological grade, parametrial invasion, lymph node status, ADCmean, ADCss, ADCmin were independently correlated with PD-L1 expression (all P<0.05). Among three ADC values, ADCmin demonstrated the highest diagnostic efficacy with an AUC of 0.882 (95% CI: 0.855-0.905). The combined nomogram, incorporating ADCmin, clinical, and pathological factors, performed well in both the training and validation cohorts, yielding AUC of 0.906 (95% CI: 0.882-0.927) and 0.903 (95% CI: 0.866-0.933) respectively. Calibration curves indicated good fit of the nomogram. Decision curve analysis showed the nomogram's higher net benefit compared to the clinicopathological model.Conclusions The nomogram, utilizing clinical, pathological, and ADCmin data, effectively predicted PD-L1 expression in cervical cancer.
[Keywords] uterine cervical neoplasms;magnetic resonance imaging;diffusion weighted imaging;immunotherapy;programmed death-ligand 1;ligand

LIU Kaihui1   YANG Wei2*   TIAN Haiping3   ZHANG Zhining4   LI Yunxia5   HE Jianli6  

1 College of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, China

2 Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China

3 Department of Pathology, General Hospital of Ningxia Medical University, Yinchuan 750004, China

4 Department of Gynecological Oncology, General Hospital of Ningxia Medical University, Yinchuan 750004, China

5 Department of Medical Oncology, General Hospital of Ningxia Medical University, Yinchuan 750004, China

6 Department of Radiotherapy, General Hospital of Ningxia Medical University, Yinchuan 750004, China

Corresponding author: YANG W, E-mail: yangwei_0521@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China Project (No. 81860302).
Received  2023-05-24
Accepted  2023-09-22
DOI: 10.12015/issn.1674-8034.2023.10.017
Cite this article as: LIU K H, YANG W, TIAN H P, et al. Nomogram based on clinical, pathological, and DWI quantitative parameters for predicting the programmed death-ligand 1 positive expression in cervical cancer: Comparison of different ROI options[J]. Chin J Magn Reson Imaging, 2023, 14(10): 98-104, 115. DOI:10.12015/issn.1674-8034.2023.10.017.

[1]
LIN S J, GAO K, GU S M, et al. Worldwide trends in cervical cancer incidence and mortality, with predictions for the next 15 years[J]. Cancer, 2021, 127(21): 4030-4039. DOI: 10.1002/cncr.33795.
[2]
TOPALIAN S L, TAUBE J M, PARDOLL D M. Neoadjuvant checkpoint blockade for cancer immunotherapy[J/OL]. Science, 2020, 367(6477): eaax0182 [2023-05-24]. https://www.science.org/doi/10.1126/science.aax0182. DOI: 10.1126/science.aax0182.
[3]
PERUCHO J A U, WANG M D, VARDHANABHUTI V, et al. Association between IVIM parameters and treatment response in locally advanced squamous cell cervical cancer treated by chemoradiotherapy[J]. Eur Radiol, 2021, 31(10): 7845-7854. DOI: 10.1007/s00330-021-07817-w.
[4]
LIONTOS M, KYRIAZOGLOU A, DIMITRIADIS I, et al. Systemic therapy in cervical cancer: 30 years in review[J]. Crit Rev Oncol Hematol, 2019, 137: 9-17. DOI: 10.1016/j.critrevonc.2019.02.009.
[5]
FERRARA R, IMBIMBO M, MALOUF R, et al. Single or combined immune checkpoint inhibitors compared to first-line platinum-based chemotherapy with or without bevacizumab for people with advanced non-small cell lung cancer[J/OL]. Cochrane Database Syst Rev, 2020 [2023-05-24]. https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD013257.pub2. DOI: 10.1002/14651858.CD013257.pub2.
[6]
LIU K, ZHU Y W, ZHOU Y Y, et al. Cemiplimab as second-line therapy for patients with recurrent cervical cancer: a United States-based cost-effectiveness analysis[J]. Adv Ther, 2023, 40(4): 1838-1849. DOI: 10.1007/s12325-023-02472-7.
[7]
FRENEL J S, TOURNEAU C L, O'NEIL B, et al. Safety and efficacy of pembrolizumab in advanced, programmed death ligand 1-positive cervical cancer: results from the phase ib KEYNOTE-028 trial[J]. J Clin Oncol, 2017, 35(36): 4035-4041. DOI: 10.1200/JCO.2017.74.5471.
[8]
MA J T, QIN F Y, ZHAO M L, et al. The value of multimodal MRI combined with clinical indexes in predicting the short-term effect of neoadjuvant therapy for stage ⅠB1-ⅡA2 cervical cancer[J]. Chin J Magn Reson Imag, 2022, 13(1): 59-63, 102. DOI: 10.12015/issn.1674-8034.2022.01.012.
[9]
LIU J R, XU Y, GUO L M, et al. Multiparametric magnetic resonance imaging to characterize pathological grading and stage of cervical squamous cell carcinoma[J]. Chin J Magn Reson Imag, 2021, 12(12): 29-33. DOI: 10.12015/issn.1674-8034.2021.12.006.
[10]
MANGANARO L, LAKHMAN Y, BHARWANI N, et al. Staging, recurrence and follow-up of uterine cervical cancer using MRI: updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018[J]. Eur Radiol, 2021, 31(10): 7802-7816. DOI: 10.1007/s00330-020-07632-9.
[11]
ZHOU L W, LIU J W, CHEN M C, et al. Influence of HPV infection on expression of FOXP3, PD-1 and PD-L1 proteins in cervical cancer tissues[J]. Chin J Nosocomiology, 2021, 31(10): 1571-1575. DOI: 10.11816/cn.ni.2021-202582.
[12]
ZHANG Y, LI J, YANG F, et al. Relationship and prognostic significance of IL-33, PD-1/PD-L1, and tertiary lymphoid structures in cervical cancer[J]. J Leukoc Biol, 2022, 112(6): 1591-1603. DOI: 10.1002/JLB.5MA0322-746R.
[13]
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.
[14]
YANG W, QIANG J W, TIAN H P, et al. Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors[J]. Eur Radiol, 2018, 28(1): 437-445. DOI: 10.1007/s00330-017-4989-3.
[15]
ZHANG Y L, LI X C, ZHANG L, et al. Expression and clinical significance of FOXP3, PD-1 and PD-L1 protein in cervical cancer[J]. J Tianjin Norm Univ Nat Sci Ed, 2022, 42(6): 16-22. DOI: 10.19638/j.issn1671-1114.20220603.
[16]
BOSE C K. Balstilimab and other immunotherapy for recurrent and metastatic cervical cancer[J/OL]. Med Oncol, 2022, 39(4): 47 [2023-05-24]. https://link.springer.com/article/10.1007/s12032-022-01646-7. DOI: 10.1007/s12032-022-01646-7.
[17]
WANG R Z, ZHANG Y, SHAN F P. PD-L1: can it be a biomarker for the prognosis or a promising therapeutic target in cervical cancer?[J/OL]. Int Immunopharmacol, 2022, 103: 108484 [2023-05-24]. https://linkinghub.elsevier.com/retrieve/pii/S1567-5769(21)01120-6. DOI: 10.1016/j.intimp.2021.108484.
[18]
MENG N, FU F F, SUN J, et al. Sensitivity and specificity of amide proton transfer-weighted imaging for assessing programmed death-ligand 1 status in non-small cell lung cancer: a comparative study with intravoxel incoherent motion and 18F-FDG PET[J]. Quant Imaging Med Surg, 2022, 12(9): 4474-4487. DOI: 10.21037/qims-22-189.
[19]
COOK D, BIANCALANA M, LIADIS N, et al. Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer[J/OL]. Front Artif Intell, 2023, 6: 1153083 [2023-05-24]. https://www.frontiersin.org/articles/10.3389/frai.2023.1153083. DOI: 10.3389/frai.2023.1153083.
[20]
SUN L, MU L W, ZHOU J, et al. Imaging features of gadoxetic acid-enhanced MR imaging for evaluation of tumor-infiltrating CD8 cells and PD-L1 expression in hepatocellular carcinoma[J]. Cancer Immunol Immunother, 2022, 71(1): 25-38. DOI: 10.1007/s00262-021-02957-w.
[21]
GONG X Q, LIU N, TAO Y Y, et al. Radiomics models based on multisequence MRI for predicting PD-1/PD-L1 expression in hepatocellular carcinoma[J/OL]. Sci Rep, 2023, 13(1): 7710 [2023-05-24]. https://www.nature.com/articles/s41598-023-34763-y. DOI: 10.1038/s41598-023-34763-y.
[22]
ZHENG Y M, ZHAN J F, YUAN M G, et al. A CT-based radiomics signature for preoperative discrimination between high and low expression of programmed death ligand 1 in head and neck squamous cell carcinoma[J/OL]. Eur J Radiol, 2022, 146: 110093 [2023-05-24]. https://www.ejradiology.com/article/S0720-048X(21)00574-X. DOI: 10.1016/j.ejrad.2021.110093.
[23]
HOTTAT N A, BADR D A, LECOMTE S, et al. Value of diffusion-weighted MRI in predicting early response to neoadjuvant chemotherapy of breast cancer: comparison between ROI-ADC and whole-lesion-ADC measurements[J]. Eur Radiol, 2022, 32(6): 4067-4078. DOI: 10.1007/s00330-021-08462-z.
[24]
RASMUSSEN J H, OLIN A, LELKAITIS G, et al. Does multiparametric imaging with 18F-FDG-PET/MRI capture spatial variation in immunohistochemical cancer biomarkers in head and neck squamous cell carcinoma?[J]. Br J Cancer, 2020, 123(1): 46-53. DOI: 10.1038/s41416-020-0876-9.
[25]
MEYER H J, HÖHN A K, SUROV A. Relationships between apparent diffusion coefficient (ADC) histogram analysis parameters and PD-L 1-expression in head and neck squamous cell carcinomas: a preliminary study[J]. Radiol Oncol, 2021, 55(2): 150-157. DOI: 10.2478/raon-2021-0005.
[26]
TAVAKOLI A A, HIELSCHER T, BADURA P, et al. Contribution of dynamic contrast-enhanced and diffusion MRI to PI-RADS for detecting clinically significant prostate cancer[J]. Radiology, 2023, 306(1): 186-199. DOI: 10.1148/radiol.212692.
[27]
ABDEL WAHAB C, JANNOT A S, BONAFFINI P A, et al. Diagnostic algorithm to differentiate benign atypical leiomyomas from malignant uterine sarcomas with diffusion-weighted MRI[J]. Radiology, 2020, 297(2): 361-371. DOI: 10.1148/radiol.2020191658.
[28]
BICKEL H, PINKER K, POLANEC S, et al. Diffusion-weighted imaging of breast lesions: region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values[J]. Eur Radiol, 2017, 27(5): 1883-1892. DOI: 10.1007/s00330-016-4564-3.
[29]
OMENAI S A, AJANI M A, OKOLO C A. Programme death ligand 1 expressions as a surrogate for determining immunotherapy in cervical carcinoma patients[J/OL]. PLoS One, 2022, 17(2): e0263615 [2023-05-24]. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263615.
[30]
HAN L P, LIU L Y, SUN X H, et al. Expression and correlation analysis of FOXP3, PD-1 and PD-L1 in the cervical cancer[J]. J Zhengzhou Univ Med Sci, 2017, 52(1): 83-88. DOI: 10.13705/j.issn.1671-6825.2017.01.022.
[31]
HUANG W J, LIU J W, XU K, et al. PD-1/PD-L1 inhibitors for advanced or metastatic cervical cancer: from bench to bed[J/OL]. Front Oncol, 2022, 12: 849352 [2023-05-24]. https://www.frontiersin.org/articles/10.3389/fonc.2022.849352. DOI: 10.3389/fonc.2022.849352.
[32]
MAREI H E, HASAN A, POZZOLI G, et al. Cancer immunotherapy with immune checkpoint inhibitors (ICIs): potential, mechanisms of resistance, and strategies for reinvigorating T cell responsiveness when resistance is acquired[J/OL]. Cancer Cell Int, 2023, 23(1): 64 [2023-05-24]. https://cancerci.biomedcentral.com/articles/10.1186/s12935-023-02902-0. DOI: 10.1186/s12935-023-02902-0.

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