[18F]FDG PET/CT-Derived Metabolic Characteristics and Tumour-Infiltrating Lymphocytes for Predicting Axillary Response to Neoadjuvant Chemo-(Immuno)Therapy in Clinically Node-Positive Breast Cancer
13 affiliations
- 1Department of Surgery, Maastricht University Medical Center+, 6229 HX Maastricht, The Netherlands
- 2GROW—Research Institute for Oncology and Reproduction, Maastricht University, 6229 HX Maastricht, The Netherlands
- 3Department of Pathology, Maastricht University Medical Center+, 6229 HX Maastricht, The Netherlands
- 4Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, 6229 HX Maastricht, The Netherlands
- 5Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center+, 6229 HX Maastricht, The Netherlands
- 6Department of Pathology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- 7Department of Nuclear Medicine, RWTH Aachen University Hospital, 52074 Aachen, Germany
- 8Center of Integrated Oncology Aachen Bonn Cologne Duesseldorf (CIO ABCD), 52074 Aachen, Germany
- 9College of Medicine and Health Sciences, UAE University, Al Ain P.O. Box 17666, United Arab Emirates
- 10Department of Surgical Oncology, Alrijne Hospital, 2353 GA Leiderdorp, The Netherlands
- 11Department of Surgical Oncology, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
- 12Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Centre Rotterdam, 3015 GD Rotterdam, The Netherlands
- 13Dutch Expert Center for Screening (LRCB), 6538 SW Nijmegen, The Netherlands
Abstract
Background: Accurate axillary response prediction is clinically relevant in clinically node-positive (cN+) breast cancer patients treated with neoadjuvant chemo-(immuno)therapy (NAC). This study evaluated the value of [18F]FDG PET/CT-derived metabolic characteristics and tumour-infiltrating lymphocytes (TILs) to predict axillary pathologic complete response (pCR). Second, the association between [18F]FDG PET/CT-derived metabolic characteristics and TILs was evaluated. Methods: This retrospective study included cN+ breast cancer patients treated with NAC and axillary surgery from the prospective multicentre RISAS trial (NCT02800317). Baseline [18F]FDG PET/CT-derived metabolic activity of the breast tumour, axillary lymph node metastases (ALNMs), and spleen was assessed, together with TILs measured in the breast tumour and ALNMs. TILs were classified as low (<10%) versus high (≥10%). Associations were evaluated using multivariable logistic regression and receiver operating characteristic analysis. Results: Of 135 patients, 46 (34.1%) achieved axillary pCR. Higher liver mean tumour-to-background ratio (2.7 vs. 1.9, p = 0.042), trends towards higher breast and ALNM maximum standardised uptake value (SUVmax), lower splenic SUVmax and high breast tumour TILs were associated with axillary pCR. Multivariable logistic regression combining tumour grade, subtype, maximum spleen-to-liver ratio, and breast tumour TILs yielded an apparent area under the curve of 0.80 [95%CI 0.73–0.88]. Higher ALNM SUVmax and SUVmean (10.5 vs. 6.3, p = 0.024; 6.4 vs. 3.7, p = 0.015) and lower splenic SUVmean (2.6 vs. 3.1, p = 0.035) were associated with high breast tumour TILs. Conclusions: A model combining clinicopathological, metabolic, and immune-related characteristics may be informative for predicting axillary response to NAC but did not perform better than clinicopathological characteristics alone. Future studies should evaluate whether accurate prediction models can support safe axillary treatment de-escalation.
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BibTeX
@article{lenaerts202618ffdg,
title = {{[18F]FDG PET/CT-Derived Metabolic Characteristics and Tumour-Infiltrating Lymphocytes for Predicting Axillary Response to Neoadjuvant Chemo-(Immuno)Therapy in Clinically Node-Positive Breast Cancer}},
author = {Melissa Lenaerts and Loes F. S. Kooreman and Chris C. P. Adang and Florien J. G. van Amstel and Sander M. J. van Kuijk and Paul J. van Diest and Felix M. Mottaghy and Cristina Mitea and Ernest J. T. Luiten and Carmen C. van der Pol and Linetta B. Koppert and Janine M. Simons and Marjolein L. Smidt and Thiemo J. A. van Nijnatten and on behalf of the REFINE Study Group},
journal = {Cancers},
year = {2026},
month = oct,
doi = {10.3390/cancers18203302},
url = {https://www.mdpi.com/2072-6694/18/20/3302},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - [18F]FDG PET/CT-Derived Metabolic Characteristics and Tumour-Infiltrating Lymphocytes for Predicting Axillary Response to Neoadjuvant Chemo-(Immuno)Therapy in Clinically Node-Positive Breast Cancer
AU - Melissa Lenaerts
AU - Loes F. S. Kooreman
AU - Chris C. P. Adang
AU - Florien J. G. van Amstel
AU - Sander M. J. van Kuijk
AU - Paul J. van Diest
AU - Felix M. Mottaghy
AU - Cristina Mitea
AU - Ernest J. T. Luiten
AU - Carmen C. van der Pol
AU - Linetta B. Koppert
AU - Janine M. Simons
AU - Marjolein L. Smidt
AU - Thiemo J. A. van Nijnatten
AU - on behalf of the REFINE Study Group
PY - 2026
DA - 2026/10/01
JO - Cancers
DO - 10.3390/cancers18203302
UR - https://www.mdpi.com/2072-6694/18/20/3302
AB - Background: Accurate axillary response prediction is clinically relevant in clinically node-positive (cN+) breast cancer patients treated with neoadjuvant chemo-(immuno)therapy (NAC). This study evaluated the value of [18F]FDG PET/CT-derived metabolic characteristics and tumour-infiltrating lymphocytes (TILs) to predict axillary pathologic complete response (pCR). Second, the association between [18F]FDG PET/CT-derived metabolic characteristics and TILs was evaluated. Methods: This retrospective study included cN+ breast cancer patients treated with NAC and axillary surgery from the prospective multicentre RISAS trial (NCT02800317). Baseline [18F]FDG PET/CT-derived metabolic activity of the breast tumour, axillary lymph node metastases (ALNMs), and spleen was assessed, together with TILs measured in the breast tumour and ALNMs. TILs were classified as low (<10%) versus high (≥10%). Associations were evaluated using multivariable logistic regression and receiver operating characteristic analysis. Results: Of 135 patients, 46 (34.1%) achieved axillary pCR. Higher liver mean tumour-to-background ratio (2.7 vs. 1.9, p = 0.042), trends towards higher breast and ALNM maximum standardised uptake value (SUVmax), lower splenic SUVmax and high breast tumour TILs were associated with axillary pCR. Multivariable logistic regression combining tumour grade, subtype, maximum spleen-to-liver ratio, and breast tumour TILs yielded an apparent area under the curve of 0.80 [95%CI 0.73–0.88]. Higher ALNM SUVmax and SUVmean (10.5 vs. 6.3, p = 0.024; 6.4 vs. 3.7, p = 0.015) and lower splenic SUVmean (2.6 vs. 3.1, p = 0.035) were associated with high breast tumour TILs. Conclusions: A model combining clinicopathological, metabolic, and immune-related characteristics may be informative for predicting axillary response to NAC but did not perform better than clinicopathological characteristics alone. Future studies should evaluate whether accurate prediction models can support safe axillary treatment de-escalation.
SN - 2072-6694
ER -