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CC BY-NC-ND 4.0 · Indian J Med Paediatr Oncol 2022; 43(01): 052-059
DOI: 10.1055/s-0042-1742609
Review Article

A Radiologist's Perspective on Treatment-Related Pseudoprogression: Clues and Hues

Nivedita Chakrabarty
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
,
Abhishek Mahajan
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
,
Akshay D. Baheti 
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
,
Amit Choudhari
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
,
Vasundhara Patil
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
,
Palak Popat
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
,
Himangi Unde
1   Department of Radiodiagnosis, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India
› Author Affiliations Funding None.
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Abstract

Pseudoprogression refers to the initial apparent increase in tumor burden observed on imaging after cancer therapy, with subsequent delayed response to the same treatment, thus giving a false initial appearance of disease progression. It is essential to differentiate pseudoprogression from true progression to prevent the patients from getting deprived of the benefits of their ongoing cancer therapy owing to their early withdrawal. It also affects their recruitment for clinical trials. Pseudoprogression, albeit uncommon, has been observed after various types of cancer therapy; however, this phenomenon has gained momentum of late due to the emergence of immunotherapy for the treatment of various malignancies. Besides immunotherapy, pseudoprogression has predominantly been of concern in a few patients after radiation therapy for brain tumors and metastasis, after molecular targeted therapy for a variety of tumors, and after chemotherapy in metastatic bone lesions. This article reviews the available data on imaging of pseudoprogression from various types of cancer therapies, highlighting ways to suspect or identify it on imaging.

Keywords

pseudoprogression - immunotherapy - radiation therapy - targeted therapy

Contributions of Each Author

N.C. contributed to the concept, design, definition of intellectual content, literature search, and manuscript preparation. A.M. contributed to manuscript editing and manuscript review. A.D.B. contributed to manuscript review. A.C. contributed to manuscript review. V.P. contributed to manuscript review. P.P. contributed to manuscript review. H.U. contributed to manuscript review.


The manuscript has been read and approved by all the authors and the requirements for authorship have been met, and each author believes that the manuscript represents honest work.




Publication History

Article published online:
14 February 2022

© 2022. Indian Society of Medical and Paediatric Oncology. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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  • References

  • 1 Ma Y, Wang Q, Dong Q, Zhan L, Zhang J. How to differentiate pseudoprogression from true progression in cancer patients treated with immunotherapy. Am J Cancer Res 2019; 9 (08) 1546-1553
    PubMedGoogle Scholar
  • 2 Hygino da Cruz Jr LC, Rodriguez I, Domingues RC, Gasparetto EL, Sorensen AG. Pseudoprogression and pseudoresponse: imaging challenges in the assessment of posttreatment glioma. AJNR Am J Neuroradiol 2011; 32 (11) 1978-1985
    CrossrefPubMedGoogle Scholar
  • 3 Nishino M, Hatabu H, Hodi FS. Imaging of cancer immunotherapy: current approaches and future directions. Radiology 2019; 290 (01) 9-22
    CrossrefPubMedGoogle Scholar
  • 4 Tirumani SH, Fairchild A, Krajewski KM. et al. Anti-VEGF molecular targeted therapies in common solid malignancies: comprehensive update for radiologists. Radiographics 2015; 35 (02) 455-474
    CrossrefPubMedGoogle Scholar
  • 5 Parvez K, Parvez A, Zadeh G. The diagnosis and treatment of pseudoprogression, radiation necrosis and brain tumor recurrence. Int J Mol Sci 2014; 15 (07) 11832-11846
    CrossrefPubMedGoogle Scholar
  • 6 Borcoman E, Nandikolla A, Long G, Goel S, Le Tourneau C. Patterns of response and progression to immunotherapy. Am Soc Clin Oncol Educ Book 2018; 38 (38) 169-178
    CrossrefPubMedGoogle Scholar
  • 7 Persigehl T, Lennartz S, Schwartz LH. iRECIST: how to do it. Cancer Imaging 2020; 20 (01) 2
    CrossrefPubMedGoogle Scholar
  • 8 Tirkes T, Hollar MA, Tann M, Kohli MD, Akisik F, Sandrasegaran K. Response criteria in oncologic imaging: review of traditional and new criteria. Radiographics 2013; 33 (05) 1323-1341
    CrossrefPubMedGoogle Scholar
  • 9 Chalian H, Töre HG, Horowitz JM, Salem R, Miller FH, Yaghmai V. Radiologic assessment of response to therapy: comparison of RECIST Versions 1.1 and 1.0. Radiographics 2011; 31 (07) 2093-2105
    CrossrefPubMedGoogle Scholar
  • 10 Vancini C, De Falco Alfano D, Abousiam RN. et al. Comparison of radiological criteria (RECIST-MASS-SACT-Choi) in antiangiogenic therapy of renal cell carcinoma. Univers J Public Health 2016; 4 (05) 239-243
    CrossrefGoogle Scholar
  • 11 Aide N, Hicks RJ, Le Tourneau C, Lheureux S, Fanti S, Lopci E. FDG PET/CT for assessing tumour response to immunotherapy: report on the EANM symposium on immune modulation and recent review of the literature. Eur J Nucl Med Mol Imaging 2019; 46 (01) 238-250
    CrossrefPubMedGoogle Scholar
  • 12 Dhingra VK, Mahajan A, Basu S. Emerging clinical applications of PET based molecular imaging in oncology: the promising future potential for evolving personalized cancer care. Indian J Radiol Imaging 2015; 25 (04) 332-341
    Article in Thieme ConnectPubMedGoogle Scholar
  • 13 Thian Y, Gutzeit A, Koh D-M. et al. Revised Choi imaging criteria correlate with clinical outcomes in patients with metastatic renal cell carcinoma treated with sunitinib. Radiology 2014; 273 (02) 452-461
    CrossrefPubMedGoogle Scholar
  • 14 Smith AD, Lieber ML, Shah SN. Assessing tumor response and detecting recurrence in metastatic renal cell carcinoma on targeted therapy: importance of size and attenuation on contrast-enhanced CT. AJR Am J Roentgenol 2010; 194 (01) 157-165
    CrossrefPubMedGoogle Scholar
  • 15 Smith AD, Shah SN, Rini BI, Lieber ML, Remer EM. Morphology, attenuation, size, and structure (MASS) criteria: assessing response and predicting clinical outcome in metastatic renal cell carcinoma on antiangiogenic targeted therapy. AJR Am J Roentgenol 2010; 194 (06) 1470-1478
    CrossrefPubMedGoogle Scholar
  • 16 Leao DJ, Craig PG, Godoy LF, Leite CC, Policeni B. Response assessment in neuro-oncology criteria for gliomas: practical approach using conventional and advanced techniques. AJNR Am J Neuroradiol 2020; 41 (01) 10-20
    CrossrefPubMedGoogle Scholar
  • 17 Chukwueke UN, Wen PY. Use of the response assessment in neuro-oncology (RANO) criteria in clinical trials and clinical practice. CNS Oncol 2019; 8 (01) CNS28
    CrossrefPubMedGoogle Scholar
  • 18 Costelloe CM, Chuang HH, Madewell JE, Ueno NT. Cancer response criteria and bone metastases: RECIST 1.1, MDA and PERCIST. J Cancer 2010; 1: 80-92
    CrossrefPubMedGoogle Scholar
  • 19 Borcoman E, Kanjanapan Y, Champiat S. et al. Novel patterns of response under immunotherapy. Ann Oncol 2019; 30 (03) 385-396
    CrossrefPubMedGoogle Scholar
  • 20 Gong J, Chehrazi-Raffle A, Reddi S, Salgia R. Development of PD-1 and PD-L1 inhibitors as a form of cancer immunotherapy: a comprehensive review of registration trials and future considerations. J Immunother Cancer 2018; 6 (01) 8
    CrossrefPubMedGoogle Scholar
  • 21 Onesti CE, Frères P, Jerusalem G. Atypical patterns of response to immune checkpoint inhibitors: interpreting pseudoprogression and hyperprogression in decision making for patients' treatment. J Thorac Dis 2019; 11 (01) 35-38
    CrossrefPubMedGoogle Scholar
  • 22 Dromain C, Beigelman C, Pozzessere C, Duran R, Digklia A. Imaging of tumour response to immunotherapy. Eur Radiol Exp 2020; 4 (01) 2
    CrossrefPubMedGoogle Scholar
  • 23 Anwar H, Sachpekidis C, Winkler J. et al. Absolute number of new lesions on 18F-FDG PET/CT is more predictive of clinical response than SUV changes in metastatic melanoma patients receiving ipilimumab. Eur J Nucl Med Mol Imaging 2018; 45 (03) 376-383
    CrossrefPubMedGoogle Scholar
  • 24 Fatterpekar GM, Galheigo D, Narayana A, Johnson G, Knopp E. Treatment-related change versus tumor recurrence in high-grade gliomas: a diagnostic conundrum—use of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI. AJR Am J Roentgenol 2012; 198 (01) 19-26
    CrossrefPubMedGoogle Scholar
  • 25 Brandsma D, Stalpers L, Taal W, Sminia P, van den Bent MJ. Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas. Lancet Oncol 2008; 9 (05) 453-461
    CrossrefPubMedGoogle Scholar
  • 26 Brandes AA, Franceschi E, Tosoni A. et al. MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients. J Clin Oncol 2008; 26 (13) 2192-2197
    CrossrefPubMedGoogle Scholar
  • 27 Seow P, Wong JHD, Ahmad-Annuar A, Mahajan A, Abdullah NA, Ramli N. Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review. Br J Radiol 2018; 91 (1092): 20170930
    CrossrefPubMedGoogle Scholar
  • 28 Mahajan A, Deshpande SS, Thakur MH. Diffusion magnetic resonance imaging: a molecular imaging tool caught between hope, hype and the real world of “personalized oncology”. World J Radiol 2017; 9 (06) 253-268
    CrossrefPubMedGoogle Scholar
  • 29 Mahajan A, Azad GK, Cook GJ. PET imaging of skeletal metastases and its role in personalizing further management. PET Clin 2016; 11 (03) 305-318
    CrossrefPubMedGoogle Scholar