ABSTRACT
Evaluation of treatment response in oncology is very important in terms of patient management and modification of treatment protocols. Imaging parameters obtained from anatomical and molecular imaging modalities have an important role in predicting and monitoring treatment response, and can effect clinical decision-making processes in oncology. As a hybrid imaging modality developed in recent years, positron emission tomography/magnetic resonance imaging (PET/MRI) enables the anatomical evaluation of treatment response due to the high soft tissue contrast of MRI. Furthermore, the combination of metabolic/molecular information obtained from PET images with various functional parameters that can be obtained from multiparametric MRI provides complementary information about different features of tumor biology such as metabolism, cellular density and perfusion, and makes it possible to evaluate treatment response earlier than anatomical imaging. Previous studies show that PET/MRI has a serious potential in a more holistic assessment of treatment response and in predicting patient prognosis. Further multicenter and comparative studies with larger patient populations are necessary for examining the role of imaging parameters obtained from PET/MRI with F-18 fluorodeoxyglucose (FDG) or new molecular radiopharmaceuticals in evaluating the efficacy of different treatment modalities in various types of malignancies. In this review, it is aimed to evaluate the contribution of PET/MRI in therapy response assessment in oncological patients.
References
1Harris LN, Ismaila N, McShane LM, et al. Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol 2016;34:1134-1150.
2Gillman JA, Pantel AR, Mankoff DA, Edmonds CE. Update on Quantitative Imaging for Predicting and Assessing Response in Oncology. Semin Nucl Med 2020;50:505-517.
3O’Connor JP, Aboagye EO, Adams JE, et al. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol 2017;14:169-186.
4Beyer T, Townsend DW, Brun T, et al. A combined PET/CT scanner for clinical oncology. J Nucl Med 2000;41:1369-1379.
5Mankoff DA, O’Sullivan F, Barlow WE, Krohn KA. Molecular imaging research in the outcomes era: measuring outcomes for individualized cancer therapy. Acad Radiol 2007;14:398-405.
6Ehman EC, Johnson GB, Villanueva-Meyer JE, et al. PET/MRI: Where might it replace PET/CT? J Magn Reson Imaging 2017;46:1247-1262.
7Schäfer JF, Gatidis S, Schmidt H, et al. Simultaneous whole-body PET/MR imaging in comparison to PET/CT in pediatric oncology: initial results. Radiology 2014;273:220-231.
8Hirsch FW, Sattler B, Sorge I, et al. PET/MR in children. Initial clinical experience in paediatric oncology using an integrated PET/MR scanner. Pediatr Radiol 2013;43:860-875.
9Kuhn FP, Hüllner M, Mader CE, et al. Contrast-enhanced PET/MR imaging versus contrast-enhanced PET/CT in head and neck cancer: how much MR information is needed? J Nucl Med 2014;55:551-558.
10Cheng Y, Bai L, Shang J, et al. Preliminary clinical results for PET/MR compared with PET/CT in patients with nasopharyngeal carcinoma. Oncol Rep 202;43:177-187.
11Queiroz MA, Hüllner M, Kuhn F, et al. PET/MRI and PET/CT in follow-up of head and neck cancer patients. Eur J Nucl Med Mol Imaging 2014;41:1066-1075.
12Nie J, Zhang J, Gao J, et al. Diagnostic role of 18F-FDG PET/MRI in patients with gynecological malignancies of the pelvis: A systematic review and meta-analysis. PLoS One 2017;12:e0175401.
13Fiaschetti V, Calabria F, Crusco S, et al. MR-PET fusion imaging in evaluating adnexal lesions: a preliminary study. Radiol Med 2011;116:1288-1302.
14Grueneisen J, Nagarajah J, Buchbender C, et al. Positron Emission Tomography/Magnetic Resonance Imaging for Local Tumor Staging in Patients With Primary Breast Cancer: A Comparison With Positron Emission Tomography/Computed Tomography and Magnetic Resonance Imaging. Invest Radiol 2015;50:505-513.
15Melsaether AN, Raad RA, Pujara AC, et al. Comparison of Whole-Body (18)F FDG PET/MR Imaging and Whole-Body (18)F FDG PET/CT in Terms of Lesion Detection and Radiation Dose in Patients with Breast Cancer. Radiology 2016;281:193-202.
16Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009;45:228-247.
17Kimura M, Tominaga T. Outstanding problems with response evaluation criteria in solid tumors (RECIST) in breast cancer. Breast Cancer 2002;9:153-159.
18Sorace AG, Elkassem AA, Galgano SJ, et al. Imaging for Response Assessment in Cancer Clinical Trials. Semin Nucl Med 2020;50:488-504.
19Klenk C, Gawande R, Uslu L, et al. Ionising radiation-free whole-body MRI versus (18)F-fluorodeoxyglucose PET/CT scans for children and young adults with cancer: a prospective, non-randomised, single-centre study. Lancet Oncol 2014;15:275-285.
20Padhani AR, Liu G, Koh DM, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009;11:102-125.
21Dudeck O, Zeile M, Pink D, et al. Diffusion-weighted magnetic resonance imaging allows monitoring of anticancer treatment effects in patients with soft-tissue sarcomas. J Magn Reson Imaging 2008;27:1109-1113.
22Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986;161:401-407.
23Guo Y, Cai YQ, Cai ZL, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 2002;16:172-178.
24Razek AA, Gaballa G, Denewer A, Nada N. Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors. NMR Biomed 2010;23:619-623.
25Siegel MJ, Jokerst CE, Rajderkar D, et al. Diffusion-weighted MRI for staging and evaluation of response in diffuse large B-cell lymphoma: a pilot study. NMR Biomed 2014;27:681-691.
26Kyriazi S, Collins DJ, Messiou C, et al. Metastatic ovarian and primary peritoneal cancer: assessing chemotherapy response with diffusion-weighted MR imaging--value of histogram analysis of apparent diffusion coefficients. Radiology 2011;261:182-192.
27Chenevert TL, McKeever PE, Ross BD. Monitoring early response of experimental brain tumors to therapy using diffusion magnetic resonance imaging. Clin Cancer Res 1997;3:1457-1466.
28Galbán CJ, Hoff BA, Chenevert TL, Ross BD. Diffusion MRI in early cancer therapeutic response assessment. NMR Biomed 2017;30:10.1002/nbm.3458.
29Partridge SC, Zhang Z, Newitt DC, et al. Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial. Radiology 2018;289:618-627.
30Mayerhoefer ME, Karanikas G, Kletter K, et al. Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT-Controlled Prospective Study in 64 Patients. Clin Cancer Res 2015;21:2506-2513.
31Afaq A, Andreou A, Koh DM. Diffusion-weighted magnetic resonance imaging for tumour response assessment: why, when and how? Cancer Imaging 2010;10:S179-188.
32Oka K, Yakushiji T, Sato H, Hirai T, Yamashita Y, Mizuta H. The value of diffusion-weighted imaging for monitoring the chemotherapeutic response of osteosarcoma: a comparison between average apparent diffusion coefficient and minimum apparent diffusion coefficient. Skeletal Radiol 2010;39:141-146.
33Young H, Baum R, Cremerius U, et al. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. Eur J Cancer 1999;35:1773-1782.
34Wahl RL, Jacene H, Kasamon Y, Lodge MA. From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors. J Nucl Med 2009;50(Suppl 1):122S-150S.
35Michaelis LC, Ratain MJ. Measuring response in a post-RECIST world: from black and white to shades of grey. Nat Rev Cancer 2006;6:409-414.
36Lim R, Eaton A, Lee NY, et al. 18F-FDG PET/CT metabolic tumor volume and total lesion glycolysis predict outcome in oropharyngeal squamous cell carcinoma. J Nucl Med 2012;53:1506-1513.
37Chung HW, Lee KY, Kim HJ, Kim WS, So Y. FDG PET/CT metabolic tumor volume and total lesion glycolysis predict prognosis in patients with advanced lung adenocarcinoma. J Cancer Res Clin Oncol 2014;140:89-98.
38Shankar LK, Hoffman JM, Bacharach S, et al. Consensus recommendations for the use of 18F-FDG PET as an indicator of therapeutic response in patients in National Cancer Institute Trials. J Nucl Med 2006;47:1059-1066.
39Yanagawa M, Tatsumi M, Miyata H, et al. Evaluation of response to neoadjuvant chemotherapy for esophageal cancer: PET response criteria in solid tumors versus response evaluation criteria in solid tumors. J Nucl Med 2012;53:872-880.
40Ding Q, Cheng X, Yang L, et al. PET/CT evaluation of response to chemotherapy in non-small cell lung cancer: PET response criteria in solid tumors (PERCIST) versus response evaluation criteria in solid tumors (RECIST). J Thorac Dis 2014;6:677-683.
41Baratto L, Davidzon GA, Moghbel M, Hatami N, Iagaru A, Mittra ES. Comparison Between Different PET and CT-Based Imaging Interpretation Criteria at Interim Imaging in Patients With Diffuse Large B-Cell Lymphoma. Clin Nucl Med 2018;43:1-8.
42Odawara S, Kitajima K, Katsuura T, Kurahashi Y, Shinohara H, Yamakado K. Tumor response to neoadjuvant chemotherapy in patients with esophageal cancer assessed with CT and FDG-PET/CT - RECIST 1.1 vs. PERCIST 1.0. Eur J Radiol 2018;101:65-71.
43Shang J, Ling X, Zhang L, Tang Y, et al. Comparison of RECIST, EORTC criteria and PERCIST for evaluation of early response to chemotherapy in patients with non-small-cell lung cancer. Eur J Nucl Med Mol Imaging 2016;43:1945-1953.
44Koshkin VS, Bolejack V, Schwartz LH, et al. Assessment of Imaging Modalities and Response Metrics in Ewing Sarcoma: Correlation With Survival. J Clin Oncol 2016;34:3680-3685.
45Peterson LM, O’Sullivan J, Wu QV, et al. Prospective Study of Serial 18F-FDG PET and 18F-Fluoride PET to Predict Time to Skeletal-Related Events, Time to Progression, and Survival in Patients with Bone-Dominant Metastatic Breast Cancer. J Nucl Med 2018;59:1823-1830.
46Riedl CC, Pinker K, Ulaner GA, et al. Comparison of FDG-PET/CT and contrast-enhanced CT for monitoring therapy response in patients with metastatic breast cancer. Eur J Nucl Med Mol Imaging 2017;44:1428-1437.
47Min SJ, Jang HJ, Kim JH. Comparison of the RECIST and PERCIST criteria in solid tumors: a pooled analysis and review. Oncotarget 2016;7:27848-27854.
48Boellaard R, Delgado-Bolton R, Oyen WJ, et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging 2015;42:328-354.
49Kurland BF, Peterson LM, Shields AT, et al. Test-Retest Reproducibility of 18F-FDG PET/CT Uptake in Cancer Patients Within a Qualified and Calibrated Local Network. J Nucl Med 2019;60:608-614.
50Turgeon GA, Iravani A, Akhurst T, et al. What 18F-FDG PET Response-Assessment Method Best Predicts Survival After Curative-Intent Chemoradiation in Non-Small Cell Lung Cancer: EORTC, PERCIST, Peter Mac Criteria, or Deauville Criteria? J Nucl Med 2019;60:328-334.
51Patz EF Jr, Connolly J, Herndon J. Prognostic value of thoracic FDG PET imaging after treatment for non-small cell lung cancer. AJR Am J Roentgenol 2000;174:769-774.
52Vera P, Mezzani-Saillard S, Edet-Sanson A, et al. FDG PET during radiochemotherapy is predictive of outcome at 1 year in non-small-cell lung cancer patients: a prospective multicentre study (RTEP2). Eur J Nucl Med Mol Imaging 2014;41:1057-1065.
53Groheux D, Hindié E, Giacchetti S, et al. Early assessment with 18F-fluorodeoxyglucose positron emission tomography/computed tomography can help predict the outcome of neoadjuvant chemotherapy in triple negative breast cancer. Eur J Cancer 2014;50:1864-1871.
54Humbert O, Cochet A, Riedinger JM, et al. HER2-positive breast cancer: 18F-FDG PET for early prediction of response to trastuzumab plus taxane-based neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging 2014;41:1525-1533.
55Kinahan PE, Perlman ES, Sunderland JJ, et al. The QIBA Profile for FDG PET/CT as an Imaging Biomarker Measuring Response to Cancer Therapy. Radiology 2020;294:647-657.
56Cheson BD, Fisher RI, Barrington SF, et al. Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification. J Clin Oncol 2014;32:3059-3068.
57Barrington SF, Mikhaeel NG, Kostakoglu L, et al. Role of imaging in the staging and response assessment of lymphoma: consensus of the International Conference on Malignant Lymphomas Imaging Working Group. J Clin Oncol 2014;32:3048-3058.
58Gallamini A, Hutchings M, Rigacci L, et al. Early interim 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography is prognostically superior to international prognostic score in advanced-stage Hodgkin’s lymphoma: a report from a joint Italian-Danish study. J Clin Oncol 2007;25:3746-3752.
59André MPE, Girinsky T, Federico M, et al. Early Positron Emission Tomography Response-Adapted Treatment in Stage I and II Hodgkin Lymphoma: Final Results of the Randomized EORTC/LYSA/FIL H10 Trial. J Clin Oncol 2017;35:1786-1794.
60Johnson P, Federico M, Kirkwood A, et al. Adapted Treatment Guided by Interim PET-CT Scan in Advanced Hodgkin’s Lymphoma. N Engl J Med 2016;374:2419-2429.
61Casasnovas RO, Meignan M, Berriolo-Riedinger A, et al. SUVmax reduction improves early prognosis value of interim positron emission tomography scans in diffuse large B-cell lymphoma. Blood 2011;118:37-43.
62Itti E, Meignan M, Berriolo-Riedinger A, et al. An international confirmatory study of the prognostic value of early PET/CT in diffuse large B-cell lymphoma: comparison between Deauville criteria and ΔSUVmax. Eur J Nucl Med Mol Imaging 2013;40:1312-1320.
63Schöder H, Polley MC, Knopp MV, et al. Prognostic value of interim FDG-PET in diffuse large cell lymphoma: results from the CALGB 50303 Clinical Trial. Blood 2020;135:2224-2234.
64Lheureux S, Denoyelle C, Ohashi PS, De Bono JS, Mottaghy FM. Molecularly targeted therapies in cancer: a guide for the nuclear medicine physician. Eur J Nucl Med Mol Imaging 2017;44(Suppl 1):41-54.
65Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 2012;12:252-264.
66Aide 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;46:238-250.
67Cho SY, Lipson EJ, Im HJ, et al. Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma. J Nucl Med 2017;58:1421-1428.
68Anwar 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;45:376-383.
69Iravani A, Hicks RJ. Imaging the Cancer Immune Environment and Its Response to Pharmacologic Intervention, Part 1: The Role of 18F-FDG PET/CT. J Nucl Med 2020;61:943-950.
70Rakheja R, Chandarana H, DeMello L, et al. Correlation between standardized uptake value and apparent diffusion coefficient of neoplastic lesions evaluated with whole-body simultaneous hybrid PET/MRI. AJR Am J Roentgenol 2013;201:1115-1119.
71Kitajima K, Miyoshi Y, Yamano T, Odawara S, Higuchi T, Yamakado K. Assessment of tumor response to neoadjuvant chemotherapy in patients with breast cancer using MRI and FDG-PET/CT-RECIST 1.1 vs. PERCIST 1.0. Nagoya J Med Sci 2018;80:183-197.
72Grueneisen J, Schaarschmidt B, Demircioglu A, et al. 18F-FDG PET/MRI for Therapy Response Assessment of Isolated Limb Perfusion in Patients with Soft-Tissue Sarcomas. J Nucl Med 2019;60:1537-1542.
73Varoquaux A, Rager O, Dulguerov P, Burkhardt K, Ailianou A, Becker M. Diffusion-weighted and PET/MR Imaging after Radiation Therapy for Malignant Head and Neck Tumors. Radiographics 2015;35:1502-1527.
74Hojjati M, Badve C, Garg V, et al. Role of FDG-PET/MRI, FDG-PET/CT, and Dynamic Susceptibility Contrast Perfusion MRI in Differentiating Radiation Necrosis from Tumor Recurrence in Glioblastomas. J Neuroimaging 2018;28:118-125.
75Jena A, Taneja S, Jha A, et al. Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous 18F-FDG-PET/MRI: A Single-Institution Retrospective Study. AJNR Am J Neuroradiol 2017;38:899-907.
76Sarabhai T, Tschischka A, Stebner V, et al. Simultaneous multiparametric PET/MRI for the assessment of therapeutic response to chemotherapy or concurrent chemoradiotherapy of cervical cancer patients: Preliminary results. Clin Imaging 2018;49:163-168.
77Nakamura K, Joja I, Kodama J, Hongo A, Hiramatsu Y. Measurement of SUVmax plus ADCmin of the primary tumour is a predictor of prognosis in patients with cervical cancer. Eur J Nucl Med Mol Imaging 2012;39:283-290.
78Freihat O, Tóth Z, Pintér T, et al. Pre-treatment PET/MRI based FDG and DWI imaging parameters for predicting HPV status and tumor response to chemoradiotherapy in primary oropharyngeal squamous cell carcinoma (OPSCC). Oral Oncol 2021;116:105239.
79Kim YI, Cheon GJ, Kang SY, et al. Prognostic value of simultaneous 18F-FDG PET/MRI using a combination of metabolo-volumetric parameters and apparent diffusion coefficient in treated head and neck cancer. EJNMMI Res 2018;8:2.
80Theruvath AJ, Siedek F, Muehe AM, et al. Therapy Response Assessment of Pediatric Tumors with Whole-Body Diffusion-weighted MRI and FDG PET/MRI. Radiology 2020;296:143-151.
81Su H, Bodenstein C, Dumont RA, et al. Monitoring tumor glucose utilization by positron emission tomography for the prediction of treatment response to epidermal growth factor receptor kinase inhibitors. Clin Cancer Res 2006;12:5659-5667.
82Cullinane C, Dorow DS, Kansara M, et al. An in vivo tumor model exploiting metabolic response as a biomarker for targeted drug development. Cancer Res 2005;65:9633-9636.
83Uslu-Beşli L, Mermut Ö, Yardimci AH, Gündoğan C, Gürsu RU, Çermik TF. Comparison of 18F-FDG PET/CT and DW-MRI in assessment of neoadjuvant radiochemotherapy response in locally advanced rectal cancer patients. Rev Esp Med Nucl Imagen Mol (Engl Ed) 2021;40:19-29.
84Borggreve AS, Goense L, van Rossum PSN, et al. Preoperative Prediction of Pathologic Response to Neoadjuvant Chemoradiotherapy in Patients With Esophageal Cancer Using 18F-FDG PET/CT and DW-MRI: A Prospective Multicenter Study. Int J Radiat Oncol Biol Phys 2020;106:998-1009.
85Wang ZJ, Behr S, Consunji MV, et al. Early Response Assessment in Pancreatic Ductal Adenocarcinoma Through Integrated PET/MRI. AJR Am J Roentgenol 2018;211:1010-1019.
86Tokuda Y, Yanagawa M, Fujita Y, et al. Prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer: comparison of diagnostic performances of dedicated breast PET, whole-body PET, and dynamic contrast-enhanced MRI. Breast Cancer Res Treat 2021;188:107-115.
87Cho N, Im SA, Cheon GJ, et al. Integrated 18F-FDG PET/MRI in breast cancer: early prediction of response to neoadjuvant chemotherapy. Eur J Nucl Med Mol Imaging 2018;45:328-339.
