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. 2025 Jul;67(7):1935-1944.
doi: 10.1007/s00234-025-03635-9. Epub 2025 May 21.

PET/MR for predicting extranodal extension of head and neck cancer

Vanessa Sanchez  1 , Daniele A Pizzuto  1   2 , Alexander Maurer  1 , Urs J Muehlematter  1 , Bert-Ram Sah  1   3 , Lars Husmann  1 , Stephan Skawran  1   4 , Caecilia E Mader  1 , Gregoire B Morand  5 , Simon A Mueller  5 , Christian Meerwein  5 , Niels J Rupp  6 , Sandra Freiberger  6 , Martin Lanzer  7 , Michael Messerli  1 , Martin W Huellner  8
Affiliations

PET/MR for predicting extranodal extension of head and neck cancer

Vanessa Sanchez et al. Neuroradiology. 2025 Jul.

Abstract

Purpose: To analyze the diagnostic accuracy of multiparametric FDG-PET/MR in identifying pathologic extranodal extension (pENE) of lymph node metastases (LNM) in head and neck squamous cell carcinoma (HNSCC) patients.

Methods and materials: Retrospective analysis of 57 HNSCC patients who underwent preoperative FDG-PET/MR imaging. PET parameters of LNM SUVmax and MTV, lymph node size as well as MR parameters flare sign, shaggy margin sign and vanishing border sign were analyzed. Histopathological assessment of neck dissection specimens served as standard of reference.

Results: A logistic regression model consisting of lymph node size (p = 0.029), shaggy margin sign (p = 0.031) and MTV (p = 0.035) proved that all three parameters significantly contributed to the prediction of pENE (χ²(3) = 54.23, p < 0.001). A second model without the reader-dependent parameter shaggy margin sign yielded similar results (χ²(2) = 45.36, p < 0.001), with every increase in lymph node size (p = 0.006) by 1 mm increasing the likelihood of pENE by a factor of 1.41 (95%-CI[1.11, 1.81]), and every increase in MTV (p = 0.023) by 1 cm3 increasing the likelihood of pENE by a factor of 1.64 (95%-CI[1.07, 2.50]). This model yielded an accuracy of 94.7% (95%-CI [85.4, 98.9]) for predicting pENE, with a specificity of 97.3% (95%-CI [85.8, 99.9]) and a sensitivity of 90.0% (95%-CI [68.3, 98.8]). Internal validation using a test dataset confirmed high accuracy of this model.

Conclusion: PET/MR-based multivariate binomial logistic regression models consisting of MTV, lymph node size and/or shaggy lymph node margins predict pENE with high accuracy.

Keywords: 2- [18F]-fluorodeoxy-D-glucose; Extranodal extension; Head and neck cancer; Hybrid imaging; PET/MR.

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Conflict of interest statement

Declarations. Ethical approval: This retrospective study was performed in line with the principles of the Declaration of Helsinki. Approval for this study was obtained by the local ethics committee. Informed consent: All included patients provided written informed consent to the utilization of their medical data for research purposes. Competing interests: Dr. Stephan Skawran is supported by a grant from the Iten-Kohout Foundation, Switzerland and the Palatin-Foundation, Switzerland. Dr. Martin Huellner received grants and speaker honoraria from GE HealthCare, a fund by the Alfred and Annemarie von Sick legacy and a grant from the clinical research priority program (CRPP) Artificial Intelligence in Oncological Imaging Network of the University of Zurich.

Figures

Fig. 1
Fig. 1
FDG-PET/MR imaging features in patients with and without ENE. Panels A) - D) 54-year-old man with hypopharyngeal carcinoma and histopathologically confirmed extranodal extension of lymph node metastases. (A) Axial fused FDG-PET/MR shows a left-sided partially cystic / necrotic cervical lymph node metastasis with intense FDG uptake (SUVmax 17.7, MTV 7.2 cm3, white arrowheads). (B) Axial contrast-enhanced, fat-suppressed, T1-weighted MR image illustrates ENE of the lymph node metastasis, infiltrating adjacent structures (shaggy margin sign, white arrowheads). (C) On axial T1-weighted MR image, the lymph node metastasis cannot be reliably distinguished from adjacent structures (vanishing board sign, white arrowheads). (D) Axial fat-suppressed T2-weighted MR image reveals small hyperintense protrusions along the border of the lymph node metastasis (flare sign, white arrowheads). Panels (E - H) 57-year-old man with tonsillar carcinoma and absence of extranodal extension on histopathology. E) Axial fused FDG-PET/MR shows a right-sided cervical lymph node metastasis with faint FDG uptake (SUVmax, 2.2, MTV 3.9 cm3, white arrowheads). (F) Axial contrast-enhanced, fat-suppressed, T1-weighted MR image demonstrates a clear delineation of the border and the absence of extranodal extension of the lymph node metastasis (white arrowhead). (G) On axial T1-weighted MR image, the borders of the lymph node metastasis can be accurately distinguished from neighboring structures (white arrowhead). (H) Axial fat-suppressed, T2-weighted MR image illustrates the mainly cystic nature of the lymph node metastasis featuring a smooth border (white arrowhead)
Fig. 2
Fig. 2
Dot plot representing the lymph node metastases by size and MTV, categorized by presence of pENE
Fig. 3
Fig. 3
Logistic regression analysis-derived color-coded maps indicating the probability of pENE. (A) Heat map derived from the general model with shaggy margin sign, MTV, and lymph node size. (B) Heat map derived from the reader-independent model with MTV and lymph node size. MTV values greater than 40 cm³ and lymph node sizes greater than 60 mm are truncated for improved visualization
Fig. 4
Fig. 4
Logistic regression analysis-derived nomograms indicating the probability of pENE. (A) Nomogram derived from the general model with shaggy margin sign, MTV, and lymph node size. (B) Nomogram derived from the reader-independent model with MTV and lymph node size
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