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Trimodality therapy for locally advanced esophageal squamous cell carcinoma: the role of volume-based PET/CT in patient management and prognostication

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Abstract

Purpose

To evaluate the role of positron emission tomography/computed tomography (PET/CT) in predicting pathologic complete response (pCR) and identify relevant prognostic factors from clinico-imaging-pathologic features of locally advanced esophageal squamous cell carcinoma (eSCC) patients undergoing trimodality therapy.

Methods

We evaluated 275 patients with eSCCs of T3-T4aN0M0 and T1-T4aN1-N3M0 who received trimodality therapy. We correlated volume-based PET/CT parameters before and after concurrent chemoradiation therapy with pCR after surgery, clinico-imaging-pathologic features, and patient survival.

Results

pCR occurred in 75 (27.3%) of 275 patients, of whom 61 (80.9%) showed 5-year survival. Pre-total lesion glycolysis (pre-TLG, OR = 0.318, 95% CI 0.169 to 0.600), post-metabolic tumor volume (post-MTV, OR = 0.572, 95% CI 0.327 to 0.999), and % decrease of average standardized uptake value (% SUVavg decrease, OR = 2.976, 95% CI = 1.608 to 5.507) were significant predictors for pCR. Among them, best predictor for pCR was pre-TLG with best cutoff value of 205.67 and with AUC value of 0.591.

Performance status (HR = 5.171, 95% CI 1.737 to 15.397), pathologic tumor size (HR = 1.645, 95% CI 1.351 to 2.002), pathologic N status (N1, HR = 1.572, 95% CI 1.010 to 2.446; N2, HR = 3.088, 95% CI 1.845 to 5.166), and post-metabolic tumor volume (HR = 1.506, 95% CI 1.033 to 2.195) were significant predictors of overall survival.

Conclusion

Pre-TLG, post-MTV, and % SUVavg decrease are predictive of pCR. Additionally, several clinico-imaging-pathologic factors are significant survival predictors in locally advanced eSCC patients undergoing trimodality therapy.

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Data availability

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Abbreviations

CCRT:

Concurrent chemoradiation therapy

CI :

Confidence interval

DFS :

Disease-free survival

EUS:

Endoscopic ultrasonography

MTV :

Metabolic tumor volume

eSCC :

Esophageal squamous cell carcinoma

LVI :

Lymphovascular invasion

OR :

Odds ratio

OS :

Overall survival

PNI :

Perineural invasion

pCR :

Pathologic complete response

RNL:

Recurrent laryngeal nerve

SD:

Standard deviation

SUV:

Standardized uptake value

SUVavg :

Average standardized uptake value

SUVmax:

Maximum standardized uptake value

TLG:

Total lesion glycolysis

References

  1. Jeong DY, Kim MY, Lee KS, et al. Surgically resected T1- and T2-stage esophageal squamous cell carcinoma: T and N staging performance of EUS and PET/CT. Cancer Med. 2018;7(8):3561–70. https://doi.org/10.1002/cam4.1617.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Jeong DY, Lee KS, Choi JY, et al. Surgically resected esophageal squamous cell carcinoma: patient survival and clinicopathological prognostic factors. Sci Rep. 2020;10(1):5077. https://doi.org/10.1038/s41598-020-62028-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Huang YC, Lu HI, Huang SC, et al. FDG PET using SUVmax for preoperative T-staging of esophageal squamous cell carcinoma with and without neoadjuvant chemoradiotherapy. BMC Med Imaging. 2017;17(1):1. https://doi.org/10.1186/s12880-016-0171-7.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Chuang HH, Macapinlac HA. The evolving role of PET-CT in the management of esophageal cancer. Q J Nucl Med Mol Imaging. 2009;53(2):201–9.

    CAS  PubMed  Google Scholar 

  5. Gebski V, Burmeister B, Smithers BM, et al. Survival benefits from neoadjuvant chemoradiotherapy or chemotherapy in oesophageal carcinoma: a meta-analysis. Lancet Oncol. 2007;8(3):226–34. https://doi.org/10.1016/S1470-2045(07)70039-6.

    Article  CAS  PubMed  Google Scholar 

  6. Tepper J, Krasna MJ, Niedzwiecki D, et al. Phase III trial of trimodality therapy with cisplatin, fluorouracil, radiotherapy, and surgery compared with surgery alone for esophageal cancer: CALGB 9781. J Clin Oncol. 2008;26(7):1086–92. https://doi.org/10.1200/JCO.2007.12.9593.

    Article  CAS  PubMed  Google Scholar 

  7. Bollschweiler E, Metzger R, Drebber U, et al. Histological type of esophageal cancer might affect response to neo-adjuvant radiochemotherapy and subsequent prognosis. Ann Oncol. 2009;20(2):231–8. https://doi.org/10.1093/annonc/mdn622.

    Article  CAS  PubMed  Google Scholar 

  8. Connors RC, Reuben BC, Neumayer LA, Bull DA. Comparing outcomes after transthoracic and transhiatal esophagectomy: a 5-year prospective cohort of 17,395 patients. J Am Coll Surg. 2007;205(6):735–40. https://doi.org/10.1016/j.jamcollsurg.2007.07.001.

    Article  PubMed  Google Scholar 

  9. Chang AC, Ji H, Birkmeyer NJ, Orringer MB, Birkmeyer JD. Outcomes after transhiatal and transthoracic esophagectomy for cancer. Ann Thorac Surg. 2008;85(2):424–9. https://doi.org/10.1016/j.athoracsur.2007.10.007.

    Article  PubMed  Google Scholar 

  10. Depypere L, Thomas M, Moons J, et al. Analysis of patients scheduled for neoadjuvant therapy followed by surgery for esophageal cancer, who never made it to esophagectomy. World J Surg Oncol. 2019;17(1):89. https://doi.org/10.1186/s12957-019-1630-8.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Arnett ALH, Merrell KW, Macintosh EM, et al. Utility of (18)F-FDG PET for predicting histopathologic response in esophageal carcinoma following chemoradiation. J Thorac Oncol. 2017;12(1):121–8. https://doi.org/10.1016/j.jtho.2016.08.136.

    Article  PubMed  Google Scholar 

  12. Elimova E, Wang X, Etchebehere E, et al. 18-fluorodeoxy-glucose positron emission computed tomography as predictive of response after chemoradiation in oesophageal cancer patients. Eur J Cancer. 2015;51(17):2545–52. https://doi.org/10.1016/j.ejca.2015.07.044.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Song SY, Kim JH, Ryu JS, et al. FDG-PET in the prediction of pathologic response after neoadjuvant chemoradiotherapy in locally advanced, resectable esophageal cancer. Int J Radiat Oncol Biol Phys. 2005;63(4):1053–9. https://doi.org/10.1016/j.ijrobp.2005.03.033.

    Article  PubMed  Google Scholar 

  14. Li Y, Zschaeck S, Lin Q, Chen S, Chen L, Wu H. Metabolic parameters of sequential 18F-FDG PET/CT predict overall survival of esophageal cancer patients treated with (chemo-) radiation. Radiat Oncol. 2019;14(1):35. https://doi.org/10.1186/s13014-019-1236-x.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Hyun SH, Ahn HK, Ahn MJ, et al. Volume-based assessment with 18F-FDG PET/CT improves outcome prediction for patients with stage IIIA-N2 non-small cell lung cancer. AJR Am J Roentgenol. 2015;205(3):623–8. https://doi.org/10.2214/ajr.14.13847.

    Article  PubMed  Google Scholar 

  16. Hamai Y, Hihara J, Emi M, et al. Ability of fluorine-18 fluorodeoxyglucose positron emission tomography to predict outcomes of neoadjuvant chemoradiotherapy followed by surgical treatment for esophageal squamous cell carcinoma. Ann Thorac Surg. 2016;102(4):1132–9. https://doi.org/10.1016/j.athoracsur.2016.04.011.

    Article  PubMed  Google Scholar 

  17. Blum Murphy M, Xiao L, Patel VR, et al. Pathological complete response in patients with esophageal cancer after the trimodality approach: the association with baseline variables and survival-The University of Texas MD Anderson Cancer Center experience. Cancer. 2017;123(21):4106–13. https://doi.org/10.1002/cncr.30953.

    Article  PubMed  Google Scholar 

  18. Kurokawa T, Hamai Y, Emi M, et al. Risk factors for recurrence in esophageal squamous cell carcinoma without pathological complete response after trimodal therapy. Anticancer Res. 2020;40(8):4387–94. https://doi.org/10.21873/anticanres.14442.

    Article  CAS  PubMed  Google Scholar 

  19. Khan M, Urooj N, Syed AA, et al. Prognostic factors for recurrence in esophageal cancer patients treated with neoadjuvant therapy and surgery: a single-institution analysis. Cureus. 2020;12(5): e8108. https://doi.org/10.7759/cureus.8108.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Tu CC, Hsu PK, Chien LI, et al. Prognostic histological factors in patients with esophageal squamous cell carcinoma after preoperative chemoradiation followed by surgery. BMC Cancer. 2017;17(1):62. https://doi.org/10.1186/s12885-017-3063-5.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Stahl M, Lehmann N, Walz MK, Stuschke M, Wilke H. Prediction of prognosis after trimodal therapy in patients with locally advanced squamous cell carcinoma of the oesophagus. Eur J Cancer. 2012;48(16):2977–82. https://doi.org/10.1016/j.ejca.2012.03.010.

    Article  PubMed  Google Scholar 

  22. Hamai Y, Hihara J, Emi M, et al. Evaluation of prognostic factors for esophageal squamous cell carcinoma treated with neoadjuvant chemoradiotherapy followed by surgery. World J Surg. 2018;42(5):1496–505. https://doi.org/10.1007/s00268-017-4283-1.

    Article  PubMed  Google Scholar 

  23. Lee HY, Hyun SH, Lee KS, et al. Volume-based parameter of 18)F-FDG PET/CT in malignant pleural mesothelioma: prediction of therapeutic response and prognostic implications. Ann Surg Oncol. 2010;17(10):2787–94. https://doi.org/10.1245/s10434-010-1107-z.

    Article  PubMed  Google Scholar 

  24. Shim SS, Lee KS, Kim BT, et al. Non-small cell lung cancer: prospective comparison of integrated FDG PET/CT and CT alone for preoperative staging. Radiology. 2005;236(3):1011–9. https://doi.org/10.1148/radiol.2363041310.

    Article  PubMed  Google Scholar 

  25. Lee JY, Kim YH, Park YJ, et al. Improved detection of metastatic lymph nodes in oesophageal squamous cell carcinoma by combined interpretation of fluorine-18-fluorodeoxyglucose positron-emission tomography/computed tomography. Cancer Imaging. 2019;19(1):40. https://doi.org/10.1186/s40644-019-0225-5.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Korst RJ, Rusch VW, Venkatraman E, et al. Proposed revision of the staging classification for esophageal cancer. J Thorac Cardiovasc Surg. 1998;115(3):660–669; discussion 669–670. https://doi.org/10.1016/s0022-5223(98)70332-0

  27. Rice TW, Blackstone EH, Rusch VW. 7th edition of the AJCC Cancer Staging Manual: esophagus and esophagogastric junction. Ann Surg Oncol. 2010;17(7):1721–4. https://doi.org/10.1245/s10434-010-1024-1.

    Article  PubMed  Google Scholar 

  28. Mandard AM, Dalibard F, Mandard JC, et al. Pathologic assessment of tumor regression after preoperative chemoradiotherapy of esophageal carcinoma. Clinicopathologic correlations. Cancer. 1994;73(11):2680–6. https://doi.org/10.1002/1097-0142(19940601)73:11%3c2680::aid-cncr2820731105%3e3.0.co;2-c.

    Article  CAS  PubMed  Google Scholar 

  29. Kaplan ELMP. Nonparametric-estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457–81. https://doi.org/10.1080/01621459.1958.10501452.

    Article  Google Scholar 

  30. Kock NLGS. Lateral collinearity and misleading results in variance-based SEM: an illustration and recommendations. J Assoc Inf Syst. 2012;13(7):546–80.

    Google Scholar 

  31. Schoenfeld DA. Partial residuals for the proportional hazards regression model. Biometrika. 1982;69:239–41.

    Article  Google Scholar 

  32. Lin DY, Wei LJ, Ying Z. Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika. 1993;80:557–72.

    Article  Google Scholar 

  33. Miller RaS D. Maximally selected chi square statistics. Biometrics. 1982;38:1011–6.

    Article  Google Scholar 

  34. Contal C, O’Quigley J. An application of changepoint methods in studying the effect of age on survival in breast cancer. Comput Stat Data Anal. 1999;30:253–70.

    Article  Google Scholar 

  35. Shapiro J, van Lanschot JJB, Hulshof M, et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial. Lancet Oncol. 2015;16(9):1090–8. https://doi.org/10.1016/s1470-2045(15)00040-6.

    Article  PubMed  Google Scholar 

  36. Sjoquist KM, Burmeister BH, Smithers BM, et al. Survival after neoadjuvant chemotherapy or chemoradiotherapy for resectable oesophageal carcinoma: an updated meta-analysis. Lancet Oncol. 2011;12(7):681–92. https://doi.org/10.1016/s1470-2045(11)70142-5.

    Article  PubMed  Google Scholar 

  37. van Hagen P, Hulshof MC, van Lanschot JJ, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med. 2012;366(22):2074–84. https://doi.org/10.1056/NEJMoa1112088.

    Article  PubMed  Google Scholar 

  38. Bedenne L, Michel P, Bouché O, et al. Chemoradiation followed by surgery compared with chemoradiation alone in squamous cancer of the esophagus: FFCD 9102. J Clin Oncol. 2007;25(10):1160–8. https://doi.org/10.1200/jco.2005.04.7118.

    Article  CAS  PubMed  Google Scholar 

  39. Stahl M, Stuschke M, Lehmann N, et al. Chemoradiation with and without surgery in patients with locally advanced squamous cell carcinoma of the esophagus. J Clin Oncol. 2005;23(10):2310–7. https://doi.org/10.1200/jco.2005.00.034.

    Article  PubMed  Google Scholar 

  40. Valkema MJ, Noordman BJ, Wijnhoven BPL, et al. Accuracy of (18)F-FDG PET/CT in predicting residual disease after neoadjuvant chemoradiotherapy for esophageal cancer. J Nucl Med. 2019;60(11):1553–9. https://doi.org/10.2967/jnumed.118.224196.

    Article  CAS  PubMed  Google Scholar 

  41. Hamai Y, Emi M, Ibuki Y, et al. Predictions of pathological features and recurrence based on FDG-PET Findings of esophageal squamous cell carcinoma after trimodal therapy. Ann Surg Oncol. 2020. https://doi.org/10.1245/s10434-020-08609-0.

    Article  PubMed  Google Scholar 

  42. Borggreve AS, Goense L, van Rossum PSN, et al. Preoperative prediction of pathologic response to neoadjuvant chemoradiotherapy in patients with esophageal cancer using (18)F-FDG PET/CT and DW-MRI: a prospective multicenter study. Int J Radiat Oncol Biol Phys. 2020;106(5):998–1009. https://doi.org/10.1016/j.ijrobp.2019.12.038.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Alnaji RM, Du W, Gabriel E, et al. Pathologic complete response is an independent predictor of improved survival following neoadjuvant chemoradiation for esophageal adenocarcinoma. J Gastrointest Surg. 2016;20(9):1541–6. https://doi.org/10.1007/s11605-016-3177-0.

    Article  PubMed  Google Scholar 

  44. Berger AC, Farma J, Scott WJ, et al. Complete response to neoadjuvant chemoradiotherapy in esophageal carcinoma is associated with significantly improved survival. J Clin Oncol. 2005;23(19):4330–7. https://doi.org/10.1200/jco.2005.05.017.

    Article  PubMed  Google Scholar 

  45. de Gouw D, Klarenbeek BR, Driessen M, et al. Detecting pathological complete response in esophageal cancer after neoadjuvant therapy based on imaging techniques: a diagnostic systematic review and meta-analysis. J Thorac Oncol. 2019;14(7):1156–71. https://doi.org/10.1016/j.jtho.2019.04.004.

    Article  CAS  PubMed  Google Scholar 

  46. Bedenne L. MC. Comparison of systematic surgery versus surveillance and rescue surgery in operable oesophageal cancer with a complete clinical response to radiochemotherapy (esostrate).https://clinicaltrials.gov/ct2/show/NCT02551458.

  47. Noordman BJ, Wijnhoven BPL, Lagarde SM, et al. Neoadjuvant chemoradiotherapy plus surgery versus active surveillance for oesophageal cancer: a stepped-wedge cluster randomised trial. BMC Cancer. 2018;18(1):142. https://doi.org/10.1186/s12885-018-4034-1.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Guo JC, Huang TC, Lin CC, et al. Postchemoradiotherapy pathologic stage classified by the American Joint Committee on the Cancer Staging System predicts prognosis of patients with locally advanced esophageal squamous cell carcinoma. J Thorac Oncol. 2015;10(10):1481–9. https://doi.org/10.1097/jto.0000000000000651.

    Article  PubMed  Google Scholar 

  49. O JH, Jacene H, Luber B, et al. Quantitation of cancer treatment response by (18)F-FDG PET/CT: multicenter assessment of measurement variability. J Nucl Med. 2017;58(9):1429–1434. https://doi.org/10.2967/jnumed.117.189605

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Acknowledgements

We are grateful for the librarians Myung-Ah Shim and Jaero Park for their dedicated support of manuscript formatting. Both librarians are working at the Samsung Medical Information & Media Services of Samsung Medical Center located in Seoul, South Korea.

Funding

This work was supported by the National R&D Program for Cancer Control, Ministry of Health & Welfare of Korea [1720180].

Author information

Author notes

  1. Kyung Soo Lee

    Present address: Department of Radiology, Samsung ChangWon Hospital, Sungkyunkwan University School of Medicine (SKKU-SOM), ChangWon, 51353, Gyeongsangnam-Do, Korea

Authors and Affiliations

  1. Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea

    Yeonu Choi & Kyung Soo Lee

  2. Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea

    Joon Young Choi

  3. Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea

    Tae Hee Hong, Young Mog Shim, Jae Ill Zo & Hong Kwan Kim

  4. Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea

    Yoon-La Choi

  5. Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea

    Dongryul Oh

  6. Biostatistics Unit, Samsung Biomedical Research Institute, Samsung Medical Center, Seoul, Korea

    Sook Young Woo

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  1. Yeonu Choi
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Contributions

Study conception and design: Yeonu Choi, Joon Young Choi, Hong Kwan Kim, Kyung Soo Lee. Data acquisition and analysis: Yeonu Choi, Joon Young Choi, Tae Hee Hong, Yoon-La Choi, Sook Young Woo, Kyung Soo Lee. Data interpretation and manuscript writing: Yeonu Choi, Joon Young Choi, Tae Hee Hong, Yoon-La Choi, Sook Young Woo, Kyung Soo Lee. Revision of manuscript and contribution of intellectual content: All authors.

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Correspondence to Kyung Soo Lee.

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Yeonu Choi and Joon Young Choi contributed equally to this manuscript.

This article is part of the Topical Collection on Oncology - Digestive tract

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Choi, Y., Choi, J.Y., Hong, T.H. et al. Trimodality therapy for locally advanced esophageal squamous cell carcinoma: the role of volume-based PET/CT in patient management and prognostication. Eur J Nucl Med Mol Imaging 49, 751–762 (2022). https://doi.org/10.1007/s00259-021-05487-w

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