ORIGINAL RESEARCH article
Front. Oncol.
Sec. Genitourinary Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1644411
This article is part of the Research TopicEmerging Fast Medical Imaging Techniques in RadiologyView all 5 articles
Time-Intensity Curve (TIC) Parametric Imaging as a Novel Quantitative Biomarker: Enhancing Diagnostic Accuracy and Inter-Rater Reliability in Prostate Cancer Ultrasound
Provisionally accepted- 1Department of Ultrasound Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China
- 2Information Center, Peking Union Medical College Hospital, Beijing, China
- 3Statistics Office, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, China
- 4Department of Ultrasound, Peking Union Medical College Hospital, Beijing, China
- 5Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Objective: To investigate the diagnostic utility of a novel TIC parametric imaging technique for improving the accuracy of prostate cancer detection. This study aimed to quantitatively assess the technology's impact on the diagnostic performance of ultrasound physicians with disparate levels of clinical experience and to evaluate its potential to standardize diagnostic interpretation.Methods: We conducted a retrospective analysis of 62 patients who underwent transrectal CEUS at Zhangzhou Affiliated Hospital of Fujian Medical University between December 2024 and March 2025. All diagnoses were confirmed by systematic 12-core prostate biopsy. A proprietary TIC parametric imaging software was used to perform a pixel-wise analysis of CEUS cineloops, generating quantitative maps of the perfusion parameter "mean gradient to peak." These maps were then qualitatively classified based on the spatial heterogeneity of perfusion into a four-tier discreteness system. Four junior physicians and four senior physicians independently evaluated patient cases, first using conventional grayscale and CEUS images, and then again after a washout period with the addition of the TIC parametric maps. A paired chi-square test compared diagnostic outcomes. Inter-rater and intra-rater reliability were assessed using ICC. Diagnostic performance was evaluated using ROC curve analysis, with Area Under the Curve as the primary metric.Results: A paired chi-square test demonstrated a statistically significant improvement in diagnostic accuracy when TIC parametric imaging was used as an adjunct to conventional ultrasound. The introduction of TIC maps markedly improved intra-group diagnostic consistency; the ICC for junior physicians increased from a good 0.83 to an excellent 0.91, and for senior physicians, it rose from an excellent 0.87 to a near-perfect 0.94. Most notably, the diagnostic performance gap between experience levels was effectively eliminated. The AUC for junior physicians surged from 0.43 to 0.85. For senior physicians, the AUC improved from 0.53 to an outstanding 0.95. With TIC assistance, the diagnostic efficacy of both junior and senior physicians converged at a high level of performance.Conclusion: TIC parametric imaging demonstrates profound clinical value by substantially mitigating the influence of operator experience, thereby shortening the learning curve for novice physicians and standardizing diagnostic quality across all levels of expertise.
Keywords: prostate cancer, Contrast-enhanced ultrasound (CEUS), Time-intensity curve (TIC), parametric imaging, Quantitative ultrasound, Diagnostic accuracy, Angiogenesis
Received: 10 Jun 2025; Accepted: 19 Sep 2025.
Copyright: © 2025 Zhou, LIU, Zhou, Lin, Lan, Xu, Yang and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiao Yang, yangxiao1@pumch.cn
Ming Chen, fjcm@fjmu.edu.cn
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