{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T11:03:56Z","timestamp":1772017436631,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T00:00:00Z","timestamp":1771977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guerbe"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: While deep learning-based AI algorithms have been shown to perform well for OPSCC tumor segmentation, the relative value of contrast-enhanced versus T2-weighted sequences for automated segmentation has not been systematically evaluated. In this study, we compared the sequence-specific deep learning performance on contrast-enhanced T1-weighted fat-suppressed and T2-weighted fat-suppressed MRI in HPV-positive OPSCC. Methods: Pretreatment MRI from 39 patients with paired sequences from a single center were retrospectively analyzed. OPSCC primary tumors were manually segmented using both sequences, which served as the ground truth. Three sequence-specific configurations were evaluated: contrast-enhanced (CE), T2-only, and combined CE + T2. Quantitative evaluation was carried out on aggregated out-of-fold predictions using Dice score (primary), Surface-Dice@2mm (secondary), and other boundary and volumetric metrics, and paired comparisons (combined vs. T2-only; CE-only vs. T2-only) were performed using an exact Wilcoxon signed-rank test. Qualitative evaluation was performed on 4-point ordinal acceptability ratings recorded using a blind reader study, and the ratings were compared using the exact Wilcoxon signed-rank test (pairwise) and dichotomized acceptability using the McNemar test. Results: Median Dice was comparable across configurations (0.63 for CE + T2, 0.60 for T2-only, and 0.55 for CE-only). Median Surface-Dice@2mm was highest for the combined configuration (0.62), followed by CE-only (0.6) and T2-only (0.57). Median ASSD were 2.71, 2.98, and 2.98 mm, and median HD95 were 11.39, 15.0, and 11.3 mm for combined, CE, and T2, respectively. The median GTV differences (\u22121.31, \u22121.29, and \u22121.49 mL for combined, T2, and CE, respectively) showed a slight bias toward under-segmentation across all configurations. No significant differences in Dice scores were observed for combined vs. T2 (p = 0.11) or contrast-enhanced vs. T2-only (p = 0.98). Similarly, qualitative analysis also showed no evidence of performance difference for ratings and acceptability rates across sequence configurations (paired Wilcoxon, p \u2265 0.35; McNemar, p = 1.00). Conclusions: In this single-center study, the segmentation performance using non-contrast sequences was comparable to that using both contrast-enhanced and non-contrast sequences. The drop in performance when the contrast-enhanced sequences were excluded from the combination was not significant. These findings justify multi-center validation to support the feasibility of contrast-sparing automated primary OPSCC segmentation when use of contrast agents is contraindicated.<\/jats:p>","DOI":"10.3390\/diagnostics16050658","type":"journal-article","created":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T09:42:22Z","timestamp":1772012542000},"page":"658","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning (nnU-Net)-Based Segmentation of Primary HPV-Positive OPSCC: Contrast-Enhanced T1-Weighted Fat-Suppressed Versus Non-Contrast-Enhanced T2-Weighted Fat-Suppressed MRI (Paired Single-Center Study)"],"prefix":"10.3390","volume":"16","author":[{"given":"Viktoriia","family":"Zarovniaeva","sequence":"first","affiliation":[{"name":"Department of Radiology, University of Chicago, Chicago, IL 60637, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1545-8929","authenticated-orcid":false,"given":"Ramkumar Rajabathar","family":"Babu Jai Shanker","sequence":"additional","affiliation":[{"name":"Department of Radiology, University of Chicago, Chicago, IL 60637, USA"},{"name":"Rad-Lab.ai, Dover, DE 19904, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8065-6444","authenticated-orcid":false,"given":"Amogh","family":"Shetty","sequence":"additional","affiliation":[{"name":"Department of Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3301-4364","authenticated-orcid":false,"given":"Daniel T.","family":"Ginat","sequence":"additional","affiliation":[{"name":"Rad-Lab.ai, Dover, DE 19904, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,25]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2023, April 06). 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