Jo Janggun, Siddiqui Javed, Zhu Yunhao, Ni Linyu, Kothapalli Sri-Rajasekhar, Tomlins Scott A, Wei John T, Keller Evan T, Udager Aaron M, Wang Xueding, Xu Guan
Opt Lett. 2020 Nov 1;45(21):6042-6045. doi: 10.1364/OL.409249.
The diagnosis of aggressive prostate cancer (PCa) has relied on microscopic architectures, namely Gleason patterns, of tissues extracted through core biopsies. Technology capable of assessing the tissue architecture without tissue extraction will reduce the invasiveness of PCa diagnosis and improve diagnostic accuracy by allowing for more sampling locations. Our recently developed photoacoustic spectral analysis (PASA) has achieved quantification of tissue architectural heterogeneity interstitially. Taking advantage of the unique optical absorption of cell nuclei at ultraviolet (UV) wavelengths, this study investigated PASA at 266 nm for quantifying the tissue architecture heterogeneity in prostates. The results have shown significant differences among the normal, early cancer, and late cancer stages in mouse prostates ex vivo and in vivo (=20, <0.05). The study with human samples ex vivo has shown a correlation of 0.80 (=11, <0.05) between PASA quantification and pathologic diagnosis.
侵袭性前列腺癌（PCa）的诊断一直依赖于通过穿刺活检提取的组织的微观结构，即 Gleason 模式。能够在不进行组织提取的情况下评估组织结构的技术，将降低 PCa 诊断的侵入性，并通过增加采样位置提高诊断准确性。我们最近开发的光声光谱分析（PASA）已实现对组织间结构异质性的量化。利用细胞核在紫外（UV）波长下独特的光吸收特性，本研究在 266 nm 波长下研究 PASA，以量化前列腺组织的结构异质性。结果显示，在体外和体内小鼠前列腺的正常、早期癌症和晚期癌症阶段之间存在显著差异（=20，<0.05）。体外人体样本研究显示，PASA 量化与病理诊断之间的相关性为 0.80（=11，<0.05）。
