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Prediction of Therapeutic Effect to Treatment in Patients with Colorectal Liver Metastases Using Functional Magnetic Resonance Imaging and RECIST Criteria: A Pilot Study in Comparison between Bevacizumab-Containing Chemotherapy and Standard Chemotherapy

  • Hepatobiliary Tumors
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Response Evaluation Criteria in Solid Tumors (RECIST) criteria are widely used for evaluating the therapeutic effect of colorectal liver metastases (CRLM) patients, but showed undesirable accuracy.

Objective

This study aimed to evaluate the value of functional MRI compared with RECIST criteria in predicting the therapeutic effect in CRLM patients receiving neoadjuvant chemotherapy with and without bevacizumab.

Methods

Overall, 137 patients with CRLM who received neoadjuvant chemotherapy followed by hepatic resection between January 2013 and November 2018 were included and were divided into the bevacizumab and non-bevacizumab groups. Apparent diffusion coefficient (ADC) values of pre- and post-treatment diffusion-weighted imaging (DWI) were generated on the whole-volume (ADCmean), periphery (ADCperi), and isocenter (ADCcentral) of the tumor at the maximum slice. Overall survival (OS) and relapse-free survival (RFS) were used as prognostic indicators.

Results

Post-treatment ADCmean was significantly associated with OS (p = 0.001) and RFS (p = 0.008) in the bevacizumab group, while RECIST-defined response was found to be only significantly associated with RFS in the non-bevacizumab group (p = 0.042). When categorizing the bevacizumab group by the post-treatment ADCmean cut-off value of 1.15 ×10-3 mm2/s, patients in the ADC response group showed significantly better OS than the non-response group (3-year OS: 91.5% vs. 64.5%, p = 0.001). However, no significant difference was found between RECIST-defined response and non-response in either OS (3-year OS: 60.2% vs. 44.0%, p = 0.104) or RFS (3-year RFS: 26.2% vs. 17.4%, p = 0.129) in the bevacizumab group.

Conclusions

DWI-related parameters such as post-treatment ADCmean could accurately reflect the therapeutic effectiveness and predicting survival in patients treated with bevacizumab, which is superior to the RECIST criteria.

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References

  1. Al-Asfoor A, Fedorowicz Z, Lodge M. Resection versus no intervention or other surgical interventions for colorectal cancer liver metastases. Cochrane Database Syst Rev. 2008;2:CD006039.

    Google Scholar 

  2. Van Cutsem E, Nordlinger B, Adam R, et al. Towards a pan-European consensus on the treatment of patients with colorectal liver metastases. Eur J Cancer. 2006;42(14):2212–21.

    Article  Google Scholar 

  3. Kopetz S, Chang GJ, Overman MJ, et al. Improved survival in metastatic colorectal cancer is associated with adoption of hepatic resection and improved chemotherapy. J Clin Oncol. 2009;27(22):3677–83.

    Article  Google Scholar 

  4. National Health Commission of the People’s Republic of China. National guidelines for diagnosis and treatment of colorectal cancer 2020 in China (English version). Chin J Cancer Res. 2020;32(4):415–45.

  5. Reissfelder C, Rahbari NN, Koch M, et al. Validation of prognostic scoring systems for patients undergoing resection of colorectal cancer liver metastases. Ann Surg Oncol. 2009;16(12):3279–88.

    Article  Google Scholar 

  6. Nordlinger B, Sorbye H, Glimelius B, et al. Perioperative FOLFOX4 chemotherapy and surgery versus surgery alone for resectable liver metastases from colorectal cancer (EORTC 40983): long-term results of a randomised, controlled, phase 3 trial. Lancet Oncol. 2013;14(12):1208–15.

    Article  CAS  Google Scholar 

  7. Hurwitz H, Fehrenbacher L, Novotny W, et al. Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. N Engl J Med. 2004;350(23):2335–42.

    Article  CAS  Google Scholar 

  8. Bennouna J, Sastre J, Arnold D, et al. Continuation of bevacizumab after first progression in metastatic colorectal cancer (ML18147): a randomised phase 3 trial. Lancet Oncol. 2013;14(1):29–37.

    Article  CAS  Google Scholar 

  9. Grothey A, Hedrick EE, Mass RD, et al. Response-independent survival benefit in metastatic colorectal cancer: a comparative analysis of N9741 and AVF2107. J Clin Oncol. 2008;26(2):183–9.

    Article  CAS  Google Scholar 

  10. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45(2):228–47.

    Article  CAS  Google Scholar 

  11. Chun YS, Vauthey JN, Boonsirikamchai P, et al. Association of computed tomography morphological criteria with pathologic response and survival in patients treated with bevacizumab for colorectal liver metastases. JAMA. 2009;302(21):2338–44.

    Article  CAS  Google Scholar 

  12. Shindoh J, Loyer EM, Kopetz S, et al. Optimal morphologic response to preoperative chemotherapy: an alternate outcome end point before resection of hepatic colorectal metastases. J Clin Oncol. 2012;30(36):4566–72.

    Article  CAS  Google Scholar 

  13. Dohan A, Gallix B, Guiu B, et al. Early evaluation using a radiomic signature of unresectable hepatic metastases to predict outcome in patients with colorectal cancer treated with FOLFIRI and bevacizumab. Gut. 2020;69(3):531–9.

    Article  CAS  Google Scholar 

  14. Krajewski KM, Nishino M, Franchetti Y, et al. Intraobserver and interobserver variability in computed tomography size and attenuation measurements in patients with renal cell carcinoma receiving antiangiogenic therapy: implications for alternative response criteria. Cancer. 2014;120(5):711–21.

    Article  Google Scholar 

  15. Yabuuchi H, Kawanami S, Iwama E, et al. Prediction of therapeutic effect of chemotherapy for NSCLC using dual-input perfusion CT analysis: comparison among bevacizumab treatment, two-agent platinum-based therapy without bevacizumab, and other non-bevacizumab treatment groups. Radiology. 2018;286(2):685–95.

    Article  Google Scholar 

  16. Choi H, Charnsangavej C, Faria SC, et al. Correlation of computed tomography and positron emission tomography in patients with metastatic gastrointestinal stromal tumor treated at a single institution with imatinib mesylate: proposal of new computed tomography response criteria. J Clin Oncol. 2007;25(13):1753–9.

    Article  Google Scholar 

  17. He H, Cai C, Charnsangavej C, et al. Contrast-enhanced computed tomography evaluation of hepatic metastases in breast cancer patients before and after cytotoxic chemotherapy or targeted therapy. Can Assoc Radiol J. 2015;66(4):356–62.

    Article  Google Scholar 

  18. Escudier B, Eisen T, Stadler WM, et al. Sorafenib in advanced clear-cell renal-cell carcinoma. N Engl J Med. 2007;356(2):125–34.

    Article  CAS  Google Scholar 

  19. Diederich S. Imaging beyond RECIST: CT and MRI in molecular therapies. Cancer Imaging. 2012;12(2):347–50.

    Article  Google Scholar 

  20. Tang L, Zhang XP, Sun YS, et al. Gastrointestinal stromal tumors treated with imatinib mesylate: apparent diffusion coefficient in the evaluation of therapy response in patients. Radiology. 2011;258(3):729–38.

    Article  Google Scholar 

  21. Lahrsow M, Albrecht MH, Bickford MW, et al. Predicting treatment response of colorectal cancer liver metastases to conventional lipiodol-based transarterial chemoembolization using diffusion-weighted MR imaging: value of pretreatment apparent diffusion coefficients (ADC) and ADC changes under therapy. Cardiovasc Intervent Radiol. 2017;40(6):852–9.

    Article  Google Scholar 

  22. Liu LH, Zhou GF, Lv H, et al. Identifying response in colorectal liver metastases treated with bevacizumab: development of RECIST by combining contrast-enhanced and diffusion-weighted MRI. Eur Radiol. 2021;31(8):5640–9.

    Article  CAS  Google Scholar 

  23. Rubbia-Brandt L, Giostra E, Brezault C, et al. Importance of histological tumor response assessment in predicting the outcome in patients with colorectal liver metastases treated with neo-adjuvant chemotherapy followed by liver surgery. Ann Oncol. 2007;18:299–304.

    Article  CAS  Google Scholar 

  24. Chung WS, Park MS, Shin SJ, et al. Response evaluation in patients with colorectal liver metastases: RECIST version 1.1 versus modified CT criteria. AJR Am J Roentgenol. 2012;199(4):809–15.

    Article  Google Scholar 

  25. Yang Z, Tang LH, Klimstra DS. Effect of tumor heterogeneity on the assessment of Ki67 labeling index in well-differentiated neuroendocrine tumors metastatic to the liver: implications for prognostic stratification. Am J Surg Pathol. 2011;35(6):853–60.

    Article  Google Scholar 

  26. Behrenbruch C, Prabhakaran S, Udayasiri DD, et al. Association between imaging response and survival following neoadjuvant chemotherapy in patients with resectable colorectal liver metastases: a cohort study. J Surg Oncol. 2021;123(5):1263–73.

    Article  CAS  Google Scholar 

  27. Ricotta R, Vanzulli A, Moroni M, et al. Magnetic resonance imaging as an early indicator of clinical outcome in patients with metastatic colorectal carcinoma treated with cetuximab or panitumumab. Clin Colorectal Cancer. 2013;12(1):45–53.

    Article  CAS  Google Scholar 

  28. Barabasch A, Heinzel A, Bruners P, et al. Diffusion-weighted MRI is superior to PET/CT in predicting survival of patients undergoing 90 Y radioembolization of hepatic metastases. Radiology. 2018;288(3):764–73.

    Article  Google Scholar 

  29. Yuan SJ, Qiao TK, Qiang JW. Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer. J Transl Med. 2018;16(1):340.

    Article  CAS  Google Scholar 

  30. Matsushima S, Sato T, Nishiofuku H, et al. Equivalent cross-relaxation rate imaging and diffusion weighted imaging for early prediction of response to bevacizumab-containing treatment in colorectal liver metastases-preliminary study. Clin Imaging Jan-Feb. 2017;41:1–6.

    Article  Google Scholar 

  31. Dunet V, Halkic N, Prior JO, et al. Detection and viability of colorectal liver metastases after neoadjuvant chemotherapy: a multiparametric PET/CT-MRI study. Clin Nucl Med. 2017;42(4):258–63.

    Article  Google Scholar 

  32. Boraschi P, Donati F, Cervelli R, et al. Colorectal liver metastases: ADC as an imaging biomarker of tumor behavior and therapeutic response. Eur J Radiol. 2021;137:109609.

    Article  Google Scholar 

  33. Amodeo S, Rosman A, Desiato V, et al. MRI-based apparent diffusion coefficient for predicting pathologic response of rectal cancer after neoadjuvant therapy: systematic review and meta-analysis. AJR Am J Roentgenol. 2018;211(5):W205–16.

    Article  Google Scholar 

  34. Alis D, Durmaz ESM, Gulsen F, et al. Prognostic value of ADC measurements in predicting overall survival in patients undergoing 90 Y radioembolization for colorectal cancer liver metastases. Clin Imaging. 2019;57:124–30.

    Article  Google Scholar 

  35. Fouladi DF, Zarghampour M, Pandey P, et al. Baseline 3D-ADC outperforms 2D-ADC in predicting response to treatment in patients with colorectal liver metastases. Eur Radiol. 2020;30(1):291–300.

    Article  Google Scholar 

  36. Sun Y, Xiao Q, Hu F, et al. Diffusion kurtosis imaging in the characterisation of rectal cancer: utilizing the most repeatable region-of-interest strategy for diffusion parameters on a 3T scanner. Eur Radiol. 2018;28(12):5211–20.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Key R&D Program of China (2019YFC0117705), the National Natural Science Foundation of China (91959116, 81971584), Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (No. ZYLX201803), Beijing Hospitals Authority Ascent Plan (Code: 20191103), Capital’s Funds for Health Improvement and Research (2020-1-2151), Beijing Natural Science Foundation (Z200015), and the third round of public welfare development and reform pilot projects of Beijing Municipal Medical Research Institutes (Beijing Medical Research Institute, 2019-1). The authors thank Dr. Li Sun for her contribution to the pathological evaluation.

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Author notes

  1. Hai-bin Zhu and Da Xu have contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiology, Peking University Cancer Hospital and Institute, Hai Dian District, Beijing, 100142, China

    Hai-bin Zhu MD, Xiao-Yan Zhang MD, Xiao-Ting Li MM & Ying-Shi Sun MD

  2. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Hepatopancreatobiliary Surgery Department I, Peking University Cancer Hospital and Institute, Hai Dian District, Beijing, 100142, China

    Da Xu MD & Bao-Cai Xing MD

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  1. Hai-bin Zhu MD
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Contributions

Conception and design: H.B.Z., D.X., Y.S.S., B.C.X.; Collection and assembly of data: H.B.Z., D.X., X.Y.Z.; Development of methodology: H.B.Z., D.X., X.Y.Z., X.T.L., Y.S.S., B.C.X.; Data analysis and interpretation: H.B.Z., D.X., X.Y.Z., X.T.L., Y.S.S., B.C.X.; Manuscript writing: All authors. Final approval of the manuscript: All authors.

Corresponding authors

Correspondence to Bao-Cai Xing MD or Ying-Shi Sun MD.

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Disclosures

Hai-bin Zhu, Da Xu, Xiao-Yan Zhang, Xiao-Ting Li, Bao-Cai Xing, and Ying-Shi Sun report no conflicts of interest.

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Zhu, Hb., Xu, D., Zhang, XY. et al. Prediction of Therapeutic Effect to Treatment in Patients with Colorectal Liver Metastases Using Functional Magnetic Resonance Imaging and RECIST Criteria: A Pilot Study in Comparison between Bevacizumab-Containing Chemotherapy and Standard Chemotherapy. Ann Surg Oncol 29, 3938–3949 (2022). https://doi.org/10.1245/s10434-021-11101-y

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  • DOI: https://doi.org/10.1245/s10434-021-11101-y

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