ReviewEJNMMI research2026
Quantitative mid-treatment imaging biomarkers for response prediction after radiotherapy in head and neck cancer: a systematic review and meta-analysis.
Review in EJNMMI research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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6 authors.
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Abstract
backgroundTo systematically review and meta-analyse the prognostic value of quantitative mid-treatment imaging biomarkers for predicting locoregional tumour control in patients undergoing definitive radiotherapy for mucosal head and neck squamous cell carcinoma. MAIN BODY: A systematic literature search (2005-2023) was conducted in PubMed, EMBASE, Scopus, and Cochrane databases according to a pre-registered PROSPERO protocol. Studies evaluating quantitative imaging features derived from CT, MRI, or PET during radiotherapy were included. Imaging features were grouped as baseline, absolute mid-treatment, or relative mid-treatment (delta) parameters. A random-effects meta-analysis was performed on studies reporting receiver operating characteristic (ROC)-based area under the curve (AUC) values. Forty-one studies encompassing 1654 patients were included. Seventeen studies (n = 612 patients) reported sufficient data for meta-analysis. The pooled AUC for relative mid-treatment parameters was 0.796 (95% CI: 0.762-0.831), demonstrating higher predictive performance than absolute mid-treatment parameters (AUC 0.686; 95% CI: 0.628-0.745). Baseline parameters showed moderate predictive ability (AUC 0.736; 95% CI: 0.688-0.785), and while numerically lower than relative mid-treatment parameters, this difference did not reach statistical significance. Diffusion-weighted MRI (ΔADCmean) and FDG-PET (ΔMTV, ΔTLG) emerged as the most consistently predictive modalities. Relative measures offer practical advantages, including internal self-normalisation and improved reproducibility across imaging platforms.
conclusionsRelative mid-treatment imaging biomarkers demonstrate superior predictive performance compared to baseline and absolute measures, supporting their potential role in adaptive radiotherapy strategies. Further prospective multi-centre studies with standardised imaging protocols and external validation are essential for clinical translation.
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