Advancements in mri-based radiomics and artificial intelligence for prostate cancer: A comprehensive review and future prospects

A Chaddad, G Tan, X Liang, L Hassan, S Rathore… - Cancers, 2023 - mdpi.com
Simple Summary The integration of artificial intelligence (AI) into radiomic models has
become increasingly popular due to advances in computer-aided diagnosis tools. These …

Landmarks in the evolution of prostate biopsy

MJ Connor, MA Gorin, D Eldred-Evans, EJ Bass… - Nature Reviews …, 2023 - nature.com
Approaches and techniques used for diagnostic prostate biopsy have undergone
considerable evolution over the past few decades: from the original finger-guided …

Self-activated arsenic manganite nanohybrids for visible and synergistic thermo/immuno-arsenotherapy

Y Zhai, M Liu, T Yang, J Luo, C Wei, J Shen… - Journal of Controlled …, 2022 - Elsevier
Arsenotherapy has been clinically exploited to treat a few types of solid tumors despite of
acute promyelocytic leukemia using arsenic trioxide (ATO), however, its efficacy is …

Multiparametric ultrasound of prostate: role in prostate cancer diagnosis

M Kaneko, MSL Lenon… - Therapeutic …, 2022 - journals.sagepub.com
Recent advances in ultrasonography (US) technology established modalities, such as
Doppler-US, HistoScanning, contrast-enhanced ultrasonography (CEUS), elastography, and …

2022 年度前列腺癌基础研究及临床诊疗新进展

潘剑, 朱耀, 戴波, 叶定伟 - 中国癌症杂志, 2023 - china-oncology.com
中国初诊的前列腺癌患者中40%~ 70% 已处于转移性疾病阶段, 而前列腺癌发生,
发展的时空异质性及独特的转移模式使得基于活检组织取材分析免疫标志物的方式困难重重 …

Multi-reader evaluation of different image quality scoring systems in prostate MRI

AM Hötker, S Njoh, LJ Hofer, U Held, NJ Rupp… - European Journal of …, 2023 - Elsevier
Objectives To evaluate different image quality scoring systems in the assessment of factors
limiting diagnostic accuracy of prostate MRI. Methods This retrospective IRB-approved study …

[HTML][HTML] Ultrasound-responsive microparticles from droplet microfluidics

D Huang, J Wang, J Che, B Wen, W Kong - Biomedical Technology, 2023 - Elsevier
Ultrasound (US)-responsive microparticles show broad potential in controlled drug delivery
systems. Compare with the traditional micron-scale material fabrication methods, capillary …

Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional …

YK Sun, BY Zhou, Y Miao, YL Shi, SH Xu, DM Wu… - …, 2023 - thelancet.com
Background Identifying patients with clinically significant prostate cancer (csPCa) before
biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic …

Development and validation of a clinic machine-learning nomogram for the prediction of risk stratifications of prostate cancer based on functional subsets of peripheral …

C Yang, Z Liu, Y Fang, X Cao, G Xu, Z Wang… - Journal of translational …, 2023 - Springer
Background Non-invasive risk stratification contributes to the precise treatment of prostate
cancer (PCa). In previous studies, lymphocyte subsets were used to differentiate between …

Beyond multiparametric MRI and towards radiomics to detect prostate cancer: a machine learning model to predict clinically significant lesions

C Gaudiano, M Mottola, L Bianchi, B Corcioni… - Cancers, 2022 - mdpi.com
Simple Summary Early diagnosing clinically significant prostate cancer (csPCa) through
Magnetic Resonance Imaging (MRI) is very challenging and, nowadays, csPCa confirmation …