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Invasive mucinous adenocarcinoma of the lung: clinicopathological features, 18F-FDG PET/CT findings, and survival outcomes

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Abstract

Objective

Invasive mucinous adenocarcinoma (IMA) is a rare subtype of lung adenocarcinoma. This study aimed to retrospectively evaluate the clinicopathological features, 18F-FDG PET/CT findings, and prognosis of IMA of the lung, as well as to investigate the associations among these variables, to improve the management of such patients.

Methods

Clinicopathological and 18F-FDG PET/CT characteristics of 72 patients with pathologically confirmed IMA of the lung were retrospectively collected and investigated, and their predictive efficacy on progression-free survival (PFS) was evaluated.

Results

The median age of the enrolled 72 patients was 61 years (range, 26–79 years), and the male-to-female ratio was 1:1.25. According to the radiological morphology of IMA, solidary nodule/mass type (n = 59, 81.9%) was the most common, followed by GGO type (n = 8, 11.1%) and pneumonia type (n = 5, 6.9%). Lobulated or spiculated margin and pleural traction were the most common radiological signs. The median SUVmax of IMA lesions was 3.0, ranging from 0.5 to 23.1. Higher SUVmax was observed in IMA with non-GGO type, clinical symptom, advanced stage, lobulated margin, pleural traction or spread through air spaces (STAS) (P < 0.05). Moreover, higher SUVmax was related to larger tumor size in non-pneumonia-type IMA (r = 0.708, P < 0.001). The median PFS was 21.3 months, and the 12-, 24- and 36-month PFS rates were 89.8%, 83.3% and 75.5%, respectively. A poorer PFS was significantly associated with SUVmax ≥ 3, advanced stage and STAS.

Conclusion

18F-FDG PET/CT combined with clinicopathological characteristics can aid the diagnosis and prognostic evaluation of lung IMA, which could provide guidance for the appropriate management of such patients.

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References

  1. Suzuki S, Aokage K, Hishida T, Yoshida J, Kuwata T, Yamauchi C, et al. Interstitial growth as an aggressive growth pattern in primary lung cancer. J Cancer Res Clin Oncol. 2016;142(7):1591–8.

    Article  PubMed  Google Scholar 

  2. Masai K, Sakurai H, Sukeda A, Suzuki S, Asakura K, Nakagawa K, et al. Prognostic Impact of Margin Distance and Tumor Spread Through Air Spaces in Limited Resection for Primary Lung Cancer. J Thorac Oncol. 2017;12(12):1788–97.

    Article  PubMed  Google Scholar 

  3. Travis WD, Brambilla E, Noguchi M, Nicholson AG, Geisinger KR, Yatabe Y, et al. International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol. 2011;6(2):244–85.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kish JK, Ro JY, Ayala AG, McMurtrey MJ. Primary mucinous adenocarcinoma of the lung with signet-ring cells: a histochemical comparison with signet-ring cell carcinomas of other sites. Hum Pathol. 1989;20(11):1097–102.

    Article  CAS  PubMed  Google Scholar 

  5. Travis WD, Brambilla E, Burke AP, Marx A, Nicholson AG. Introduction to The 2015 World Health Organization classification of tumors of the lung, pleura, thymus, and heart. J Thorac Oncol. 2015;10(9):1240–2.

    Article  PubMed  Google Scholar 

  6. Nie K, Nie W, Zhang YX, Yu H. Comparing clinicopathological features and prognosis of primary pulmonary invasive mucinous adenocarcinoma based on computed tomography findings. Cancer Imaging. 2019;19(1):47.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Watanabe H, Saito H, Yokose T, Sakuma Y, Murakami S, Kondo T, et al. Relation between thin-section computed tomography and clinical findings of mucinous adenocarcinoma. Ann Thorac Surg. 2015;99(3):975–81.

    Article  PubMed  Google Scholar 

  8. Beyer T, Townsend DW, Brun T, Kinahan PE, Charron M, Roddy R, et al. A combined PET/CT scanner for clinical oncology. J Nucl Med. 2000;41(8):1369–79.

    CAS  PubMed  Google Scholar 

  9. Wang T, Yang Y, Liu X, Deng J, Wu J, Hou L, et al. Primary invasive mucinous adenocarcinoma of the lung: prognostic value of CT imaging features combined with clinical factors. Korean J Radiol. 2021;22(4):652–62.

    Article  PubMed  Google Scholar 

  10. Han Y, Luo Y. Primary lung invasive adenocarcinoma misdiagnosed as infectious pneumonia in (18)F-FDG PET/CT: A case report. Radiol Case Rep. 2022;17(3):808–11.

    Article  PubMed  Google Scholar 

  11. Zhu D, Zhang Q, Rui Z, Xu S. Pulmonary invasive mucinous adenocarcinoma mimicking pulmonary actinomycosis. BMC Pulm Med. 2022;22(1):181.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lee HY, Choi YL, Lee KS, Han J, Zo JI, Shim YM, et al. Pure ground-glass opacity neoplastic lung nodules: histopathology, imaging, and management. AJR Am J Roentgenol. 2014;202(3):W224–33.

    Article  PubMed  Google Scholar 

  13. Wislez M, Massiani MA, Milleron B, Souidi A, Carette MF, Antoine M, et al. Clinical characteristics of pneumonic-type adenocarcinoma of the lung. Chest. 2003;123(6):1868–77.

    Article  PubMed  Google Scholar 

  14. Duruisseaux M, Antoine M, Rabbe N, Poulot V, Fleury-Feith J, Vieira T, et al. The impact of intracytoplasmic mucin in lung adenocarcinoma with pneumonic radiological presentation. Lung Cancer. 2014;83(3):334–40.

    Article  PubMed  Google Scholar 

  15. Boland JM, Maleszewski JJ, Wampfler JA, Voss JS, Kipp BR, Yang P, et al. Pulmonary invasive mucinous adenocarcinoma and mixed invasive mucinous/nonmucinous adenocarcinoma-a clinicopathological and molecular genetic study with survival analysis. Hum Pathol. 2018;71:8–19.

    Article  CAS  PubMed  Google Scholar 

  16. Dirican N, Baysak A, Cok G, Goksel T, Aysan T. Clinical characteristics of patients with bronchioloalveolar carcinoma: a retrospective study of 44 cases. Asian Pac J Cancer Prev. 2013;14(7):4365–8.

    Article  PubMed  Google Scholar 

  17. Casali C, Rossi G, Marchioni A, Sartori G, Maselli F, Longo L, et al. A single institution-based retrospective study of surgically treated bronchioloalveolar adenocarcinoma of the lung: clinicopathologic analysis, molecular features, and possible pitfalls in routine practice. J Thorac Oncol. 2010;5(6):830–6.

    Article  PubMed  Google Scholar 

  18. Kandathil A, Sibley RC III, Subramaniam RM. Lung Cancer Recurrence: (18)F-FDG PET/CT in Clinical Practice. AJR Am J Roentgenol. 2019;213(5):1136–44.

    Article  PubMed  Google Scholar 

  19. Chang JM, Lee HJ, Goo JM, Lee HY, Lee JJ, Chung JK, et al. False positive and false negative FDG-PET scans in various thoracic diseases. Korean J Radiol. 2006;7(1):57–69.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Cha MJ, Lee KS, Kim TJ, Kim HS, Kim TS, Chung MJ, et al. Solitary nodular invasive mucinous adenocarcinoma of the lung: imaging diagnosis using the morphologic-metabolic dissociation sign. Korean J Radiol. 2019;20(3):513–21.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Lee H, Lee K, Han J, Kim B, Cho Y, Shim Y, et al. Mucinous versus nonmucinous solitary pulmonary nodular bronchioloalveolar carcinoma: CT and FDG PET findings and pathologic comparisons. Lung Cancer (Amsterdam, Netherlands). 2009;65(2):170–5.

    Article  PubMed  Google Scholar 

  22. Murakami S, Saito H, Karino F, Kondo T, Oshita F, Ito H, et al. 18F-fluorodeoxyglucose uptake on positron emission tomography in mucinous adenocarcinoma. Eur J Radiol. 2013;82(11):e721–5.

    Article  PubMed  Google Scholar 

  23. Lee HY, Cha MJ, Lee KS, Lee HY, Kwon OJ, Choi JY, et al. Prognosis in resected invasive mucinous adenocarcinomas of the lung: related factors and comparison with resected nonmucinous adenocarcinomas. J Thorac Oncol. 2016;11(7):1064–73.

    Article  PubMed  Google Scholar 

  24. Kadota K, Nitadori JI, Sima CS, Ujiie H, Rizk NP, Jones DR, et al. Tumor spread through air spaces is an important pattern of invasion and impacts the frequency and location of recurrences after limited resection for small Stage I lung adenocarcinomas. J Thorac Oncol. 2015;10(5):806–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Warth A, Muley T, Kossakowski CA, Goeppert B, Schirmacher P, Dienemann H, et al. Prognostic impact of intra-alveolar tumor spread in pulmonary adenocarcinoma. Am J Surg Pathol. 2015;39(6):793–801.

    Article  PubMed  Google Scholar 

  26. Nishimori M, Iwasa H, Miyatake K, Nitta N, Nakaji K, Matsumoto T, et al. 18F FDG-PET/CT analysis of spread through air spaces (STAS) in clinical stage I lung adenocarcinoma. Ann Nucl Med. 2022;36(10):897–903.

    Article  CAS  PubMed  Google Scholar 

  27. Yoshizawa A, Motoi N, Riely GJ, Sima CS, Gerald WL, Kris MG, et al. Impact of proposed IASLC/ATS/ERS classification of lung adenocarcinoma: prognostic subgroups and implications for further revision of staging based on analysis of 514 stage I cases. Mod Pathol. 2011;24(5):653–64.

    Article  CAS  PubMed  Google Scholar 

  28. Russell PA, Wainer Z, Wright GM, Daniels M, Conron M, Williams RA. Does lung adenocarcinoma subtype predict patient survival?: A clinicopathologic study based on the new International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary lung adenocarcinoma classification. J Thorac Oncol. 2011;6(9):1496–504.

    Article  PubMed  Google Scholar 

  29. Warth A, Muley T, Meister M, Stenzinger A, Thomas M, Schirmacher P, et al. The novel histologic International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification system of lung adenocarcinoma is a stage-independent predictor of survival. J Clin Oncol. 2012;30(13):1438–46.

    Article  PubMed  Google Scholar 

  30. Yoshizawa A, Sumiyoshi S, Sonobe M, Kobayashi M, Fujimoto M, Kawakami F, et al. Validation of the IASLC/ATS/ERS lung adenocarcinoma classification for prognosis and association with EGFR and KRAS gene mutations: analysis of 440 Japanese patients. J Thorac Oncol. 2013;8(1):52–61.

    Article  CAS  PubMed  Google Scholar 

  31. Groheux D, Quere G, Blanc E, Lemarignier C, Vercellino L, de Margerie-Mellon C, et al. FDG PET-CT for solitary pulmonary nodule and lung cancer: Literature review. Diagn Interv Imaging. 2016;97(10):1003–17.

    Article  CAS  PubMed  Google Scholar 

  32. Tosi D, Pieropan S, Cattoni M, Bonitta G, Franzi S, Mendogni P, et al. Prognostic value of 18F-FDG PET/CT metabolic parameters in surgically treated stage I lung adenocarcinoma patients. Clin Nucl Med. 2021;46(8):621–6.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Khiewvan B, Ziai P, Houshmand S, Salavati A, Ziai P, Alavi A. The role of PET/CT as a prognosticator and outcome predictor in lung cancer. Expert Rev Respir Med. 2016;10(3):317–30.

    Article  CAS  PubMed  Google Scholar 

  34. Shimizu K, Okita R, Saisho S, Maeda A, Nojima Y, Nakata M. Clinicopathological and immunohistochemical features of lung invasive mucinous adenocarcinoma based on computed tomography findings. Onco Targets Ther. 2017;10:153–63.

    Article  CAS  PubMed  Google Scholar 

  35. Uruga H, Fujii T, Fujimori S, Kohno T, Kishi K. Semiquantitative assessment of tumor spread through air spaces (STAS) in early-stage lung adenocarcinomas. J Thorac Oncol. 2017;12(7):1046–51.

    Article  PubMed  Google Scholar 

  36. Lu S, Tan KS, Kadota K, Eguchi T, Bains S, Rekhtman N, et al. Spread through air spaces (STAS) is an independent predictor of recurrence and lung cancer-specific death in squamous cell carcinoma. J Thorac Oncol. 2017;12(2):223–34.

    Article  PubMed  Google Scholar 

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Funding

This work was supported by the fund from the National Natural Science Foundation of China (81971645), Guangdong Provincial People's Hospital (KY0120211130) and Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (2022B1212010011).

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Author notes

  1. Xiaolin Sun and Baozhen Zeng contributed equally to this work.

Authors and Affiliations

  1. PET Center, Department of Nuclear Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, China

    Xiaolin Sun, Xiaoyue Tan, Zhijian Chen, Xiaoqiang Pan & Lei Jiang

  2. Department of Pathology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China

    Baozhen Zeng

  3. Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China

    Lei Jiang

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  1. Xiaolin Sun
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Sun, X., Zeng, B., Tan, X. et al. Invasive mucinous adenocarcinoma of the lung: clinicopathological features, 18F-FDG PET/CT findings, and survival outcomes. Ann Nucl Med 37, 198–207 (2023). https://doi.org/10.1007/s12149-022-01816-7

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  • DOI: https://doi.org/10.1007/s12149-022-01816-7

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