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A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment

BACKGROUND: Ultrasound has advantages in prostate cancer (PCa) detection and biopsy guidance but lacks a comprehensive quantitative evaluation model with multiparametric features. We aimed to construct a biparametric ultrasound (BU) scoring system for PCa risk assessment and to provide an option for...

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Autores principales: Liu, Xiu, Zhou, Hang, Xu, Xinzhi, Li, Ying, Hong, Ruixia, Huang, Kaifeng, Shi, Hao, Li, Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240001/
https://www.ncbi.nlm.nih.gov/pubmed/37284097
http://dx.doi.org/10.21037/qims-22-1354
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author Liu, Xiu
Zhou, Hang
Xu, Xinzhi
Li, Ying
Hong, Ruixia
Huang, Kaifeng
Shi, Hao
Li, Fang
author_facet Liu, Xiu
Zhou, Hang
Xu, Xinzhi
Li, Ying
Hong, Ruixia
Huang, Kaifeng
Shi, Hao
Li, Fang
author_sort Liu, Xiu
collection PubMed
description BACKGROUND: Ultrasound has advantages in prostate cancer (PCa) detection and biopsy guidance but lacks a comprehensive quantitative evaluation model with multiparametric features. We aimed to construct a biparametric ultrasound (BU) scoring system for PCa risk assessment and to provide an option for clinically significant prostate cancer (csPCa) detection. METHODS: From January 2015 to December 2020, 392 consecutive patients at Chongqing University Cancer Hospital who underwent BU (grayscale, Doppler flow imaging, and contrast-enhanced ultrasound) and multiparametric magnetic resonance imaging (mpMRI) before biopsy were retrospectively enrolled in the training set to construct the scoring system. From January 2021 to May 2022, 166 consecutive patients at Chongqing University Cancer Hospital were retrospectively enrolled in the validation set. The ultrasound system was compared with mpMRI, and the gold standard was a biopsy. The primary outcome was the detection of csPCa in any area with a Gleason score (GS) ≥3+4, and the secondary outcome was defined as a GS ≥4+3 and/or maximum cancer core length (MCCL) ≥6 mm. RESULTS: Malignant association features in the nonenhanced biparametric ultrasound (NEBU) scoring system included echogenicity, capsule, and gland asymmetrical vascularity. In the biparametric ultrasound scoring system (BUS), the feature of contrast agent arrival time was added. In the training set, the area under the curves (AUCs) of the NEBU scoring system, BUS, and mpMRI were 0.86 [95% confidence interval (CI): 0.82–0.90], 0.86 (95% CI: 0.82–0.90), and 0.86 (95% CI: 0.83–0.90), respectively (P>0.05). Similar results were also observed in the validation set, in which the areas under the curves were 0.89 (95% CI: 0.84–0.94), 0.90 (95% CI: 0.85–0.95), and 0.88 (95% CI: 0.82–0.94), respectively (P>0.05). CONCLUSIONS: We constructed a BUS that showed efficacy and value for csPCa diagnosis as compared with mpMRI. However, in limited circumstances, the NEBU scoring system may also be an option.
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spelling pubmed-102400012023-06-06 A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment Liu, Xiu Zhou, Hang Xu, Xinzhi Li, Ying Hong, Ruixia Huang, Kaifeng Shi, Hao Li, Fang Quant Imaging Med Surg Original Article BACKGROUND: Ultrasound has advantages in prostate cancer (PCa) detection and biopsy guidance but lacks a comprehensive quantitative evaluation model with multiparametric features. We aimed to construct a biparametric ultrasound (BU) scoring system for PCa risk assessment and to provide an option for clinically significant prostate cancer (csPCa) detection. METHODS: From January 2015 to December 2020, 392 consecutive patients at Chongqing University Cancer Hospital who underwent BU (grayscale, Doppler flow imaging, and contrast-enhanced ultrasound) and multiparametric magnetic resonance imaging (mpMRI) before biopsy were retrospectively enrolled in the training set to construct the scoring system. From January 2021 to May 2022, 166 consecutive patients at Chongqing University Cancer Hospital were retrospectively enrolled in the validation set. The ultrasound system was compared with mpMRI, and the gold standard was a biopsy. The primary outcome was the detection of csPCa in any area with a Gleason score (GS) ≥3+4, and the secondary outcome was defined as a GS ≥4+3 and/or maximum cancer core length (MCCL) ≥6 mm. RESULTS: Malignant association features in the nonenhanced biparametric ultrasound (NEBU) scoring system included echogenicity, capsule, and gland asymmetrical vascularity. In the biparametric ultrasound scoring system (BUS), the feature of contrast agent arrival time was added. In the training set, the area under the curves (AUCs) of the NEBU scoring system, BUS, and mpMRI were 0.86 [95% confidence interval (CI): 0.82–0.90], 0.86 (95% CI: 0.82–0.90), and 0.86 (95% CI: 0.83–0.90), respectively (P>0.05). Similar results were also observed in the validation set, in which the areas under the curves were 0.89 (95% CI: 0.84–0.94), 0.90 (95% CI: 0.85–0.95), and 0.88 (95% CI: 0.82–0.94), respectively (P>0.05). CONCLUSIONS: We constructed a BUS that showed efficacy and value for csPCa diagnosis as compared with mpMRI. However, in limited circumstances, the NEBU scoring system may also be an option. AME Publishing Company 2023-04-11 2023-06-01 /pmc/articles/PMC10240001/ /pubmed/37284097 http://dx.doi.org/10.21037/qims-22-1354 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Liu, Xiu
Zhou, Hang
Xu, Xinzhi
Li, Ying
Hong, Ruixia
Huang, Kaifeng
Shi, Hao
Li, Fang
A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
title A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
title_full A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
title_fullStr A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
title_full_unstemmed A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
title_short A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
title_sort scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240001/
https://www.ncbi.nlm.nih.gov/pubmed/37284097
http://dx.doi.org/10.21037/qims-22-1354
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