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Diagnostic value of a radiomics model based on CT and MRI for prediction of lateral lymph node metastasis of rectal cancer

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Abstract

This study aimed to develop a radiomics model for predicting lateral lymph node (LLN) metastasis in rectal cancer patients using MR-T2WI and CT images, and assess its clinical value. This prospective study included rectal cancer patients with complete MR-T2WI and portal enhanced CT images who underwent LLN dissection at Tianjin Union Medical Center between June 2017 and November 2022. Primary lesions and LLN were segmented using 3D slicer. Radiomics features were extracted from the region of interest using pyradiomics in Python. Least absolute shrinkage and selection operator algorithm and backward stepwise regression were employed for feature selection. Three LLN metastasis radiomics prediction models were established via multivariable logistic regression analysis. The performance of the model was evaluated using receiver operating characteristic curve analysis, and the area under the curve (AUC), sensitivity, specificity were calculated for the training, validation, and test sets. A nomogram was constructed for visualization, and decision curve analysis (DCA) was performed to evaluate clinical value. We included 94 eligible patients in the analysis. For each patient, we extracted a total of 1344 radiomics features. The CT combined with MR-T2WI model had the highest AUC for all sets compared to CT and MR-T2WI models. AUC values for the CT combined with MR-T2WI model in the training, validation, and test sets were 0.957, 0.901, and 0.936, respectively. DCA revealed high prediction value for the combined MR-T2WI and CT model. A radiomics model based on CT and MR-T2WI data effectively predicted LLN metastasis in rectal cancer patients preoperatively.

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Data availability statement

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Abbreviations

LLN:

Lateral lymph node

LLND:

Lateral lymph node dissection

MLN:

Mesenteric lymph nodes

TME:

Total mesorectal excision

nCRT:

Neoadjuvant chemoradiotherapy

ROI:

Region of interest

MAX:

Maximum

MIN:

Minimum

STD:

Standard deviation

ROC:

Receiver operating characteristic

DCA:

Decision curve analysis

LASSO:

Least absolute shrinkage and selection operator

AUC:

Area under the curve

PPV:

Positive predictive value

NPV:

Negative predictive value

References

  1. Kim TG, Park W, Choi DH, Park HC, Kim SH, Cho YB et al (2014) Factors associated with lateral pelvic recurrence after curative resection following neoadjuvant chemoradiotherapy in rectal cancer patients. Int J Colorectal Dis 29(2):193–200. https://doi.org/10.1007/s00384-013-1797-3

    Article  PubMed  Google Scholar 

  2. Chen JN, Liu Z, Wang ZJ, Mei SW, Shen HY, Li J et al (2020) Selective lateral lymph node dissection after neoadjuvant chemoradiotherapy in rectal cancer. World J Gastroenterol 26(21):2877–2888. https://doi.org/10.3748/wjg.v26.i21.2877

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hazen SJA, Sluckin TC, Konishi T, Kusters M (2021) Lateral lymph node dissection in rectal cancer: state of the art review. Eur J Surg Oncol. https://doi.org/10.1016/j.ejso.2021.11.003

    Article  PubMed  Google Scholar 

  4. Yang X, Gu C, Hu T, Bi L, Wei M, Deng X et al (2019) Is laparoscopic selective lateral lymph node dissection for locally advanced rectal cancer after neoadjuvant chemoradiotherapy safe? ANZ J Surg 89(11):E492-e7. https://doi.org/10.1111/ans.15449

    Article  PubMed  Google Scholar 

  5. Sun Y, Lian L, Zhang H, Bai X, Xie Z, Ouyang J et al (2021) The feasibility and technical strategy of a fascia space priority approach in laparoscopic lateral lymph node dissection for advanced middle and low rectal cancer: a retrospective multicentre study. Wideochirurgia i inne techniki maloinwazyjne 16(2):312–320. https://doi.org/10.5114/wiitm.2021.105143

    Article  PubMed  PubMed Central  Google Scholar 

  6. Tang J, Li H, Liu T, Zhang J (2021) Thirty years’ changes of the strategy of lateral lymph node dissection in low rectal cancer: treatment experience and prognostic analysis of 289 cases in one single center. Chin J Gastrointest Surg 24(10):889–896

    CAS  Google Scholar 

  7. Rogers W, Thulasi Seetha S, Refaee TAG, Lieverse RIY, Granzier RWY, Ibrahim A et al (2020) Radiomics: from qualitative to quantitative imaging. Br J Radiol 93(1108):20190948. https://doi.org/10.1259/bjr.20190948

    Article  PubMed  PubMed Central  Google Scholar 

  8. Guiot J, Vaidyanathan A, Deprez L, Zerka F, Danthine D, Frix AN et al (2022) A review in radiomics: making personalized medicine a reality via routine imaging. Med Res Rev 42(1):426–440. https://doi.org/10.1002/med.21846

    Article  PubMed  Google Scholar 

  9. Chen LD, Liang JY, Wu H, Wang Z, Li SR, Li W et al (2018) Multiparametric radiomics improve prediction of lymph node metastasis of rectal cancer compared with conventional radiomics. Life Sci 208:55–63. https://doi.org/10.1016/j.lfs.2018.07.007

    Article  CAS  PubMed  Google Scholar 

  10. Meng X, Xia W, Xie P, Zhang R, Li W, Wang M et al (2019) Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer. Eur Radiol 29(6):3200–3209. https://doi.org/10.1007/s00330-018-5763-x

    Article  PubMed  Google Scholar 

  11. Hui C, Baclay R, Liu K, Sandhu N, Loo P, von Eyben R et al (2022) Rectosigmoid cancer-rectal cancer or sigmoid cancer? Am J Clin Oncol 45(8):333–337. https://doi.org/10.1097/coc.0000000000000931

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. van Griethuysen JJM, Fedorov A, Parmar C, Hosny A, Aucoin N, Narayan V et al (2017) Computational radiomics system to decode the radiographic phenotype. Cancer Res 77(21):e104–e107. https://doi.org/10.1158/0008-5472.Can-17-0339

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zhu H, Zhang X, Li X, Shi Y, Zhu H, Sun Y (2019) Prediction of pathological nodal stage of locally advanced rectal cancer by collective features of multiple lymph nodes in magnetic resonance images before and after neoadjuvant chemoradiotherapy. Chin J Cancer Res 31(6):984–992. https://doi.org/10.21147/j.issn.1000-9604.2019.06.14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Han EC, Kwon YH, Park KJ, Jeong SY, Kang SB, Oh JH et al (2018) Significance of lymph node metastasis in the survival of stage IV colorectal cancer by hematogenous metastasis. Ann Surg Treat Res 95(4):201–212. https://doi.org/10.4174/astr.2018.95.4.201

    Article  PubMed  PubMed Central  Google Scholar 

  15. Li XT, Sun YS, Tang L, Cao K, Zhang XY (2015) Evaluating local lymph node metastasis with magnetic resonance imaging, endoluminal ultrasound and computed tomography in rectal cancer: a meta-analysis. Colorectal Dis 17(6):129–135. https://doi.org/10.1111/codi.12909

    Article  Google Scholar 

  16. Tsunoda Y, Ito M, Fujii H, Kuwano H, Saito N (2008) Preoperative diagnosis of lymph node metastases of colorectal cancer by FDG-PET/CT. Jpn J Clin Oncol 38(5):347–353. https://doi.org/10.1093/jjco/hyn032

    Article  PubMed  Google Scholar 

  17. Bae SU, Won KS, Song BI, Jeong WK, Baek SK, Kim HW (2018) Accuracy of F-18 FDG PET/CT with optimal cut-offs of maximum standardized uptake value according to size for diagnosis of regional lymph node metastasis in patients with rectal cancer. Cancer Imaging 18(1):32. https://doi.org/10.1186/s40644-018-0165-5

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ogawa S, Itabashi M, Hirosawa T, Hashimoto T, Bamba Y, Kameoka S (2015) A logistic model including risk factors for lymph node metastasis can improve the accuracy of magnetic resonance imaging diagnosis of rectal cancer. Asian Pac J Cancer Prev 16(2):707–712. https://doi.org/10.7314/apjcp.2015.16.2.707

    Article  PubMed  Google Scholar 

  19. Liu Y, Wang R, Ding Y, Tu S, Liu Y, Qian Y et al (2016) A predictive nomogram improved diagnostic accuracy and interobserver agreement of perirectal lymph nodes metastases in rectal cancer. Oncotarget 7(12):14755–14764. https://doi.org/10.18632/oncotarget.7548

    Article  PubMed  PubMed Central  Google Scholar 

  20. Kumar V, Gu Y, Basu S, Berglund A, Eschrich SA, Schabath MB et al (2012) Radiomics: the process and the challenges. Magn Reson Imaging 30(9):1234–1248. https://doi.org/10.1016/j.mri.2012.06.010

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bedrikovetski S, Dudi-Venkata NN, Kroon HM, Seow W, Vather R, Carneiro G et al (2021) Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis. BMC Cancer 21(1):1058. https://doi.org/10.1186/s12885-021-08773-w

    Article  PubMed  PubMed Central  Google Scholar 

  22. Yang YS, Feng F, Qiu YJ, Zheng GH, Ge YQ, Wang YT (2021) High-resolution MRI-based radiomics analysis to predict lymph node metastasis and tumor deposits respectively in rectal cancer. Abdom Radiol (NY) 46(3):873–884. https://doi.org/10.1007/s00261-020-02733-x

    Article  PubMed  Google Scholar 

  23. Xian MF, Zheng X, Xu JB, Li X, Chen LD, Wang W (2021) Prediction of lymph node metastasis in rectal cancer: comparison between shear-wave elastography based ultrasomics and MRI. Diagn Interv Radiol 27(3):424–431. https://doi.org/10.5152/dir.2021.20031

    Article  PubMed  PubMed Central  Google Scholar 

  24. He J, Wang Q, Zhang Y, Wu H, Zhou Y, Zhao S (2021) Preoperative prediction of regional lymph node metastasis of colorectal cancer based on 18F-FDG PET/CT and machine learning. Ann Nucl Med 35(5):617–627. https://doi.org/10.1007/s12149-021-01605-8

    Article  CAS  PubMed  Google Scholar 

  25. Nakanishi R, Akiyoshi T, Toda S, Murakami Y, Taguchi S, Oba K et al (2020) Radiomics approach outperforms diameter criteria for predicting pathological lateral lymph node metastasis after neoadjuvant (chemo)radiotherapy in advanced low rectal cancer. Ann Surg Oncol 27(11):4273–4283. https://doi.org/10.1245/s10434-020-08974-w

    Article  PubMed  Google Scholar 

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Funding

This study has received funding by Science and Technology Project of Tianjin municipal health and Health Committee (ZC20081); Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-044A); Project supported by the hospital level scientific research fund of Tianjin Union Medical Center (2022GCXK001).

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Author notes

  1. Yi Sun and Siwei Zhu have contributed equally to this work and share last authorship.

Authors and Affiliations

  1. Nankai University, Tianjin, 300071, China

    Hongjie Yang, Peishi Jiang, Yi Sun & Siwei Zhu

  2. Department of Oncology, Tianjin Union Medical Center, Tianjin, 300121, China

    Siwei Zhu

  3. The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, 300121, China

    Hongjie Yang, Peng Li, Yi Sun & Siwei Zhu

  4. Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China

    Hongjie Yang, Peng Li & Yi Sun

  5. Department of Radiology, Tianjin Union Medical Center, Tianjin, 300121, China

    Longchun Dong

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  1. Hongjie Yang
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Correspondence to Yi Sun or Siwei Zhu.

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The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Research involving human participants and/or animals and Informed consent

This study is retrospective, using anonymized existing data. Therefore, it did not involve new research with human participants or animals, and specific informed consent was not required.

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Yang, H., Jiang, P., Dong, L. et al. Diagnostic value of a radiomics model based on CT and MRI for prediction of lateral lymph node metastasis of rectal cancer. Updates Surg 75, 2225–2234 (2023). https://doi.org/10.1007/s13304-023-01618-0

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  • DOI: https://doi.org/10.1007/s13304-023-01618-0

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