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Added value of DCER-features to clinicopathologic model for predicting metachronous metastases in rectal cancer patients

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Abdominal Radiology Aims and scope Submit manuscript

Abstract

Rationale and objectives

The study aimed to investigate whether dynamic contrast-enhanced MRI parameters and preoperative radiological features (DCER-Features) add value to the clinicopathologic model for predicting metachronous metastases in rectal cancer patients.

Materials and methods

From January 2014 to December 2020, 859 patients in the PACS system were retrospectively screened. Of the initial 722 patients with surgically confirmed rectal cancer and no synchronous metastases, 579 patients were excluded for various reasons such as lack of clinicopathological or radiological information. 143 patients were finally included in this study. And 73 Patients of them developed metachronous metastasis within five years. After stepwise multiple regression analyses, we constructed three distinct models. Model 1 was developed solely based on clinicopathological factors, and model 2 incorporated clinicopathological characteristics along with DCE-MRI parameters. Finally, model 3 was built on all available factors, including clinicopathological characteristics, DCE-MRI parameters, and radiological features based on rectal magnetic resonance imaging. The radiological features assessed in this study encompass tumor imaging staging, location, and circumferential resection margin (CRM) for primary tumors, as well as the number of visible lymph nodes and suspected metastatic lymph nodes. Receiver operating characteristic (ROC) and decision curve analysis (DCA) were conducted to evaluate whether the diagnostic efficiency was improved.

Results

The performance of model 3 (including clinicopathologic characteristics and DCER-Features) was the best (AUC: 0.856, 95% CI 0.778–0.886), whereas it was 0.796 (95% CI 0.720–0.828) for model 2 and 0.709 (95% CI 0.612–0.778) for model 1 (DeLong test: model 1 vs model 2, p = 0.004; model 2 vs model 3, p = 0.037; model 1 vs model 3, p < 0.001). The decision curves indicated that the net benefit of model 3 was higher than the other two models at each referral threshold. The calibration plot of the three models revealed an excellent predictive accuracy.

Conclusion

This study suggests that DCER-Features have added value for the clinicopathological model to predict metachronous metastasis in patients with rectal cancers.

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References

  1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022; 72(1):7-33.

    Article  PubMed  Google Scholar 

  2. Keller DS, Berho M, Perez RO, Wexner SD, Chand M. The multidisciplinary management of rectal cancer. Nat Rev Gastroenterol Hepatol. 2020; 17(7):414-29.

    Article  PubMed  Google Scholar 

  3. Boca Petresc B, Caraiani C, Popa L, et al. The Utility of ADC First-Order Histogram Features for the Prediction of Metachronous Metastases in Rectal Cancer: A Preliminary Study. Biology (Basel). 2022; 11(3).

  4. Frambach P, Pucciarelli S, Perin A, et al. Metastatic pattern and new primary tumours after neoadjuvant therapy and surgery in rectal cancer. Colorectal Dis. 2018; 20(12):O326-O34.

    Article  CAS  PubMed  Google Scholar 

  5. Liang M, Cai Z, Zhang H, et al. Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis. Acad Radiol. 2019; 26(11):1495-504.

    Article  PubMed  Google Scholar 

  6. Ikoma N, You YN, Bednarski BK, et al. Impact of Recurrence and Salvage Surgery on Survival After Multidisciplinary Treatment of Rectal Cancer. J Clin Oncol. 2017; 35(23):2631-8.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bartolini I, Ringressi MN, Melli F, et al. Analysis of Prognostic Factors for Resected Synchronous and Metachronous Liver Metastases from Colorectal Cancer. Gastroenterol Res Pract. 2018; 2018:5353727.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Yang X, Liu Y, Chen Y, et al. Evaluation of Mesorectal Microcirculation With Quantitative Dynamic Contrast-Enhanced MRI. AJR Am J Roentgenol. 2020; 215(6):1370-6.

    Article  PubMed  Google Scholar 

  9. Jayaprakasam VS, Paroder V, Gibbs P, et al. MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer. Eur Radiol. 2022; 32(2):971-80.

    Article  CAS  PubMed  Google Scholar 

  10. Yeo DM, Oh SN, Jung CK, et al. Correlation of dynamic contrast-enhanced MRI perfusion parameters with angiogenesis and biologic aggressiveness of rectal cancer: Preliminary results. J Magn Reson Imaging. 2015; 41(2):474-80.

    Article  PubMed  Google Scholar 

  11. Akasu T, Iinuma G, Takawa M, Yamamoto S, Muramatsu Y, Moriyama N. Accuracy of high-resolution magnetic resonance imaging in preoperative staging of rectal cancer. Ann Surg Oncol. 2009; 16(10):2787-94.

    Article  PubMed  Google Scholar 

  12. Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010; 17(6):1471–4.

  13. Mekenkamp LJ, Koopman M, Teerenstra S, et al. Clinicopathological features and outcome in advanced colorectal cancer patients with synchronous vs metachronous metastases. Br J Cancer. 2010; 103(2):159-64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Baird DLH, Kontovounisios C, Simillis C, Pellino G, Rasheed S, Tekkis PP. Factors associated with metachronous metastases and survival in locally advanced and recurrent rectal cancer. BJS Open. 2020; 4(6):1172–9.

  15. Valentini V, van Stiphout RG, Lammering G, et al. Nomograms for predicting local recurrence, distant metastases, and overall survival for patients with locally advanced rectal cancer on the basis of European randomized clinical trials. J Clin Oncol. 2011; 29(23):3163-72.

    Article  PubMed  Google Scholar 

  16. Bouquot M, Creavin B, Goasguen N, et al. Prognostic value and characteristics of N1c colorectal cancer. Colorectal Dis. 2018; 20(9):O248-O55.

    Article  CAS  PubMed  Google Scholar 

  17. Lord AC, D'Souza N, Shaw A, et al. MRI-Diagnosed Tumor Deposits and EMVI Status Have Superior Prognostic Accuracy to Current Clinical TNM Staging in Rectal Cancer. Ann Surg. 2022; 276(2):334-44.

    Article  PubMed  Google Scholar 

  18. Lord AC, Knijn N, Brown G, Nagtegaal ID. Pathways of spread in rectal cancer: a reappraisal of the true routes to distant metastatic disease. Eur J Cancer. 2020; 128:1-6.

    Article  PubMed  Google Scholar 

  19. Li R, Zhang C, Du K, et al. Analysis of Prognostic Factors of Rectal Cancer and Construction of a Prognostic Prediction Model Based on Bayesian Network. Front Public Health. 2022; 10:842970.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lino-Silva LS, Loaeza-Belmont R, Gomez Alvarez MA, et al. Mesorectal Invasion Depth in Rectal Carcinoma Is Associated With Low Survival. Clin Colorectal Cancer. 2017; 16(1):73-7.

    Article  PubMed  Google Scholar 

  21. Chen CH, Hsieh MC, Hsiao PK, Lin EK, Lu YJ, Wu SY. Tumor location is an independent predictive factor for distant metastasis and metastatic sites of rectal adenocarcinoma in patients receiving total mesorectal excision. J Cancer. 2018; 9(6):950-8.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Yang H, Yao Z, Cui M, et al. Influence of tumor location on short- and long-term outcomes after laparoscopic surgery for rectal cancer: a propensity score matched cohort study. BMC Cancer. 2020; 20(1):761.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yang H, Chen L, Wu X, et al. Patterns and predictors of recurrence after laparoscopic resection of rectal cancer. Front Oncol. 2022; 12:1034838.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Chiang JM, Hsieh PS, Chen JS, Tang R, You JF, Yeh CY. Rectal cancer level significantly affects rates and patterns of distant metastases among rectal cancer patients post curative-intent surgery without neoadjuvant therapy. World J Surg Oncol. 2014; 12:197.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Yu J, Xu Q, Huang DY, et al. Prognostic aspects of dynamic contrast-enhanced magnetic resonance imaging in synchronous distant metastatic rectal cancer. Eur Radiol. 2017; 27(5):1840-7.

    Article  PubMed  Google Scholar 

  26. Li M, Zhu YZ, Zhang YC, Yue YF, Yu HP, Song B. Radiomics of rectal cancer for predicting distant metastasis and overall survival. World J Gastroenterol. 2020; 26(33):5008-21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liu Z, Meng X, Zhang H, et al. Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer. Nat Commun. 2020; 11(1):4308.

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

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Funding

This work was supported by National Natural Science Foundation of China [Grant No.: 81801662].

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Author notes

  1. Jie Dai and Ke-xin Wang are the co-first authors.

Authors and Affiliations

  1. Department of Radiology, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Nanjing, 210029, China

    Jie Dai, Ke-xin Wang, Ling-yu Wu, Xiao-han Bai, Hong-yuan Shi, Qing Xu & Jing Yu

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  1. Jie Dai
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  2. Ke-xin Wang
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  7. Jing Yu
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Correspondence to Jing Yu.

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Dai, J., Wang, Kx., Wu, Ly. et al. Added value of DCER-features to clinicopathologic model for predicting metachronous metastases in rectal cancer patients. Abdom Radiol (2024). https://doi.org/10.1007/s00261-023-04153-z

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  • DOI: https://doi.org/10.1007/s00261-023-04153-z

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