Translational Therapeutics

Does multiparametric imaging with 18F-FDG-PET/MRI capture spatial variation in immunohistochemical cancer biomarkers in head and neck squamous cell carcinoma?



The purpose of this study is to test if functional multiparametric imaging with 18F-FDG-PET/MRI correlates spatially with immunohistochemical biomarker status within a lesion of head and neck squamous cell carcinoma (HNSCC), and also whether a biopsy with the highest FDG uptake was more likely to have the highest PD-L1 expression or the highest percentage of vital tumour cells (VTC) compared with a random biopsy.


Thirty-one patients with HNSCC were scanned on an integrated PET/MRI scanner with FDG prior to surgery in this prospective study. Imaging was quantified with SUV, ADC and Ktrans. A 3D-morphometric MRI scan of the specimen was used to co-register the patient and the specimen scans. All specimens were sectioned in consecutive slices, and slices from six different locations were selected randomly from each tumour. Core biopsies were performed to construct TMA blocks for IHC staining with the ten predefined biomarkers. The spatial correlation was assessed with a partial correlation analysis.


Twenty-eight patients with a total of 33 lesions were eligible for further analysis. There were significant correlations between the three imaging biomarkers and some of the IHC biomarkers. Moreover, a biopsy taken from the most FDG-avid part of the tumour did not have a statistically significantly higher probability of higher PD-L1 expression or VTC, compared with a random biopsy.


We found statistically significant correlations between functional imaging parameters and key molecular cancer markers.

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Fig. 1: Illustration of the steps in the study from a patient with a tumour in the oral cavity and a lymph-node metastasis in level I.
Fig. 2: Example of multiparametric imaging with FDG uptake, diffusion and perfusion of a patient with a T2N0M0 tumour in the right maxilla involving both the maxillary sinus and the oral cavity.
Fig. 3: Boxplot illustrating the heterogeneity of vital tumour cells (VTC) and the IHC biomarkers in each of the 194 cores from all 33 lesions.
Fig. 4: Example of the functional imaging and pathology from a patient with a lymph node metastasis.


  1. 1.

    Network TCGA. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517, 576–582 (2015).

    Article  Google Scholar 

  2. 2.

    Mroz, E. A., Tward, A. D., Tward, A. M., Hammon, R. J., Ren, Y. & Rocco, J. W. Intra-tumor genetic heterogeneity and mortality in head and neck cancer: analysis of data from the Cancer Genome Atlas. PLoS Med. 12, e1001786 (2015).

    Article  Google Scholar 

  3. 3.

    Leemans, C. R., Braakhuis, B. J. M. & Brakenhoff, R. H. The molecular biology of head and neck cancer. Nat. Rev. Cancer 11, 9–22 (2011).

    CAS  Article  Google Scholar 

  4. 4.

    Rasmussen, J. H., Håkansson, K., Rasmussen, G. B., Vogelius, I. R., Friborg, J., Fischer, B. M. et al. A clinical prognostic model compared to the newly adopted UICC staging in an independent validation cohort of P16 negative/positive head and neck cancer patients. Oral. Oncol. 81, 52–60 (2018).

    Article  Google Scholar 

  5. 5.

    Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

    CAS  Article  Google Scholar 

  6. 6.

    Baschnagel, A. M., Wobb, J. L., Dilworth, J. T., Williams, L., Eskandari, M., Wu, D. et al. The association of 18 F-FDG PET and glucose metabolism biomarkers GLUT1 and HK2 in p16 positive and negative head and neck squamous cell carcinomas. Radiother. Oncol. 117, 118–124 (2015).

  7. 7.

    Oliveira, L. R. & Ribeiro-Silva, A. Prognostic significance of immunohistochemical biomarkers in oral squamous cell carcinoma. Int. J. Oral. Maxillofac. Surg. 40, 298–307 (2010).

    Article  Google Scholar 

  8. 8.

    Ferris, R. L. Immunology and immunotherapy of head and neck cancer. J. Clin. Oncol. 33, 3293–3304 (2015).

    CAS  Article  Google Scholar 

  9. 9.

    Zandberg, D. P. & Strome, S. E. The role of the PD-L1:PD-1 pathway in squamous cell carcinoma of the head and neck. Oral. Oncol. 50, 627–632 (2014).

    CAS  Article  Google Scholar 

  10. 10.

    Balyasnikova, S., Löfgren, J., de Nijs, R., Zamogilnaya, Y., Højgaard, L. & Fischer, B. M. PET/MR in oncology: an introduction with focus on MR and future perspectives for hybrid imaging. Am. J. Nucl. Med. Mol. Imaging 2, 458–474 (2012).

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Becker, M. & Zaidi, H. Imaging in head and neck squamous cell carcinoma: the potential role of PET/MRI. Br. J. Radiol. 87, 20130677 (2014).

    Article  Google Scholar 

  12. 12.

    Buchbender, C., Heusner, T. A., Lauenstein, T. C., Bockisch, A. & Antoch, G. Oncologic PET/MRI, part 1: tumors of the brain, head and neck, chest, abdomen, and pelvis. J. Nucl. Med. 53, 928–938 (2012).

    Article  Google Scholar 

  13. 13.

    Pauwels, E. K., Sturm, E. J., Bombardieri, E., Cleton, F. J. & Stokkel, M. P. Positron-emission tomography with [18F]fluorodeoxyglucose. Part I. Biochemical uptake mechanism and its implication for clinical studies. J. Cancer Res. Clin. Oncol. 126, 549–59 (2000).

    CAS  Article  Google Scholar 

  14. 14.

    Koh, D.-M. & Collins, D. J. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am. J. Roentgenol. 188, 1622–1635 (2007).

    Article  Google Scholar 

  15. 15.

    Bernstein, J. M., Homer, J. J. & West, C. M. Dynamic contrast-enhanced magnetic resonance imaging biomarkers in head and neck cancer: potential to guide treatment? A systematic review. Oral. Oncol. 50, 963–970 (2014).

    Article  Google Scholar 

  16. 16.

    Tofts, P. S., Brix, G., Buckley, D. L., Evelhoch, J. L., Henderson, E., Knopp, M. V. et al. Estimating kinetic parameters from dynamic contrast-enhanced t1-weighted MRI of a diffusable tracer: Standardized quantities and symbols. J. Magn. Reson. Imaging 10, 223–232 (1999).

    CAS  Article  Google Scholar 

  17. 17.

    Padhani, A. R. & Miles, K. A. Multiparametric imaging of tumor response to therapy. Radiology 256, 348–64. (2010).

    Article  Google Scholar 

  18. 18.

    Hanahan, D. & Weinberg, R. A. The hallmarks of cancer. Cell 100, 57–70 (2000).

    CAS  Article  Google Scholar 

  19. 19.

    Rasmussen, G. B., Vogelius, I. R., Rasmussen, J. H., Schumaker, L., Ioffe, O., Cullen, K. et al. Immunohistochemical biomarkers and FDG uptake on PET/CT in head and neck squamous cell carcinoma. Acta Oncol. 54, 1408–1415 (2015).

    CAS  Article  Google Scholar 

  20. 20.

    Surov, A., Meyer, H. J. & Wienke, A. Can imaging parameters provide information regarding histopathology in head and neck squamous cell carcinoma? A meta-analysis. Transl. Oncol. 11, 498 (2018).

    Article  Google Scholar 

  21. 21.

    Covello, M., Cavaliere, C., Aiello, M., Cianelli, M., Mesolella, M., Iorio, B. et al. Simultaneous PET/MR head–neck cancer imaging: Preliminary clinical experience and multiparametric evaluation. Eur. J. Radiol. 84, 1269–1276 (2015).

    CAS  Article  Google Scholar 

  22. 22.

    Even, A. J. G., De Ruysscher, D. & Van Elmpt, W. The promise of multiparametric imaging in oncology: how do we move forward? Eur. J. Nucl. Med. Mol. Imaging 43, 1195–1198 (2016).

  23. 23.

    Rasmussen, J. H., Nørgaard, M., Hansen, A. E., Vogelius, I. R., Aznar, M. C., Johannesen, H. H. et al. Feasibility of multiparametric imaging with PET/MR in head and neck Squamous cell carcinoma. J. Nucl. Med. 58, 69–74 (2017).

  24. 24.

    Porter, D. A. & Heidemann, R. M. High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition. Magn. Reson. Med. 62, 468–475 (2009).

    Article  Google Scholar 

  25. 25.

    Tofts, P. S., Brix, G., Buckley, D. L., Evelhoch, J. L., Henderson, E., Knopp, M. V. et al. Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols. J. Magn. Reson. Imaging 10, 223–232 (1999).

    CAS  Article  Google Scholar 

  26. 26.

    Boellaard, R., Delgado-Bolton, R., Oyen, W. J. G., Giammarile, F., Tatsch, K., Eschner, W. et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur. J. Nucl. Med. Mol. Imaging 42, 328–354 (2014).

    Article  Google Scholar 

  27. 27.

    Agrawal, N., Frederick, M. J., Pickering, C. R., Bettegowda, C., Chang, K., Li, R. J. et al. Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1. Science 333, 1154–1157 (2011).

    CAS  Article  Google Scholar 

  28. 28.

    Bankhead, P., Loughrey, M. B., Fernández, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878 (2017).

    Article  Google Scholar 

  29. 29.

    Kim, S. ppcor: an R package for a fast calculation to semi-partial correlation coefficients. Commun. Stat. Appl. Methods 22, 665–674 (2015).

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    Rasmussen, J. H., Lelkaitis, G., Håkansson, K., Vogelius, I. R., Johannesen, H. H., Fischer, B. M. et al. Intratumor heterogeneity of PD-L1 expression in head and neck squamous cell carcinoma. Br. J. Cancer 120, 1003 (2019).

    Article  Google Scholar 

  31. 31.

    Nicolay, N. H., Wiedenmann, N., Mix, M., Weber, W. A., Werner, M., Grosu, A. L. et al. Correlative analyses between tissue-based hypoxia biomarkers and hypoxia PET imaging in head and neck cancer patients during radiochemotherapy—results from a prospective trial. Eur. J. Nucl. Med. Mol. Imaging. (2019).

  32. 32.

    Dierckx, R. A. & Van De Wiele, C. FDG uptake, a surrogate of tumour hypoxia? Eur. J. Nucl. Med. Mol. Imaging 35, 1544–1549 (2008).

    CAS  Article  Google Scholar 

  33. 33.

    Bos, R., van Der Hoeven, J. J. M., van Der Wall, E., van Der Groep, P., van Diest, P. J., Comans, E. F. I. et al. Biologic correlates of (18)fluorodeoxyglucose uptake in human breast cancer measured by positron emission tomography. J. Clin. Oncol. 20, 379–387 (2002).

    CAS  Article  Google Scholar 

  34. 34.

    Eryilmaz, A., Cengiz, A., Basal, Y., Meteoglu, I., Omurlu, I. & Yurekli, Y. The correlation of prognostic biomarkers (Ki-67, Bcl-2, HIF-1α, cyclin D1) with metabolic tumor volume measured by F-FDG PET/CT inlaryngeal cancer. J. Cancer Res Ther. 14, 994–998 (2018).

    CAS  Article  Google Scholar 

  35. 35.

    Han, M. W., Lee, H. J., Cho, K.-J., Kim, J. S., Roh, J.-L., Choi, S.-H. et al. Role of FDG-PET as a biological marker for predicting the hypoxic status of tongue cancer. Head Neck 34, 1395–1402 (2012).

    Article  Google Scholar 

  36. 36.

    Zhao, K., Yang, S.-Y., Zhou, S.-H., Dong, M. J., Bao, Y.-Y. & Yao, H.-T. Fluorodeoxyglucose uptake in laryngeal carcinoma is associated with the expression of glucose transporter-1 and hypoxia-inducible-factor-1α and the phosphoinositide 3-kinase/protein kinase B pathway. Oncol. Lett. 7, 984–990 (2014).

    CAS  Article  Google Scholar 

  37. 37.

    Bentzen, S. M. Theragnostic imaging for radiation oncology: dose-painting by numbers. Lancet Oncol. 6, 112–117 (2005).

    Article  Google Scholar 

  38. 38.

    Lazovic, J., Guo, L., Nakashima, J., Mirsadraei, L., Yong, W., Kim, H. J. et al. Nitroxoline induces apoptosis and slows glioma growth in vivo. Neuro Oncol. 17, 53–62 (2015).

    CAS  Article  Google Scholar 

  39. 39.

    Swartz, J. E., Driessen, J. P., Van Kempen, P. M. W., De Bree, R., Janssen, L. M., Pameijer, F. A. et al. Influence of tumor and microenvironment characteristics on diffusion-weighted imaging in oropharyngeal carcinoma: a pilot study. Oral. Oncol. 77, 9–15 (2018).

    Article  Google Scholar 

  40. 40.

    Surov, A., Meyer, H. J., Winter, K., Richter, C., Hoehn, A.-K., Surov, A. et al. Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma. Oncotarget 9, 23599–23607 (2018).

    Article  Google Scholar 

  41. 41.

    Shen, L., Zhou, G., Tong, T., Tang, F., Lin, Y., Zhou, J. et al. ADC at 3.0 T as a noninvasive biomarker for preoperative prediction of Ki67 expression in invasive ductal carcinoma of breast. Clin. Imaging 52, 16–22 (2018).

    Article  Google Scholar 

  42. 42.

    Surov, A., Gottschling, S., Mawrin, C., Prell, J., Spielmann, R. P., Wienke, A. et al. Diffusion-weighted imaging in meningioma: prediction of tumor grade and association with histopathological parameters. Transl. Oncol. 8, 517–523 (2015).

    Article  Google Scholar 

  43. 43.

    Surov, A., Meyer, H. J. & Wienke, A. Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis. Oncotarget 8, 59492–59499 (2017).

    Article  Google Scholar 

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The authors thank Katrin E. Håkansson, PhD, for her guidance in using the statistical software R.

Author information




J.H.R., I.V.R., S.M.B., I.W., C.v.B., L.S.P. and B.M.F. contributed substantially to the conception and the design of the study. J.H.R., A.O., G.L., A.E.H., F.L.A., H.H.J. and A.K. contributed substantially to the acquisition and analysis. J.H.R., I.V.R., S.M.B. and B.M.F contributed substantially to the analysis and all authors contributed to the interpretation as well as writing the paper. All authors have approved the paper.

Corresponding author

Correspondence to Jacob H. Rasmussen.

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Ethics approval and consent to participate

The study was approved by Regional Committee on Health Research Ethics (The Capital Region of Denmark), approval number H-16049387. All patients provided informed consent to participate in the study, and the study was conducted accordance with the Declaration of Helsinki.

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Not applicable.

Data availability

The data set used and analysed during the current study is available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.

Funding information

This project received funding from the Research Foundation of Rigshospitalet, the Danish Cancer Society (grant nos. R167-A10858 and R134-A8543-B79), the Aase and Ejnar foundation, National Cancer Institute (NCI grant no. P30 CA 134274-04) the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 670261), the Lundbeck Foundation, the Novo Nordisk Foundation, the Innovation Fund Denmark, Svend Andersen Foundation, the Neye Foundation. SMB acknowledges support from the Maryland Department of Health’s Cigarette Restitution Fund Program and the NCI University of Maryland Cancer Center Support Grant (P30CA134274).

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Rasmussen, J.H., Olin, A., Lelkaitis, G. et al. Does multiparametric imaging with 18F-FDG-PET/MRI capture spatial variation in immunohistochemical cancer biomarkers in head and neck squamous cell carcinoma?. Br J Cancer 123, 46–53 (2020).

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