Department of Information Engineering, Università degli Studi di Firenze, 50139 Florence, Italy.
Consiglio Nazionale delle Ricerche of Italy, Istituto di Fisica Applicata "Nello Carrara", 50121 Florence, Italy.
Sensors (Basel). 2020 Feb 21;20(4):1183. doi: 10.3390/s20041183.
This study presents an improved strategy for the detection and localization of small size nodules (down to few mm) of agar in excised pork liver tissues via pulse-echo ultrasound measurements performed with a 16 MHz needle probe. This work contributes to the development of a new generation of medical instruments to support robotic surgery decision processes that need information about cancerous tissues in a short time (minutes). The developed ultrasonic probe is part of a scanning platform designed for the automation of surgery-associated histological analyses. It was coupled with a force sensor to control the indentation of tissue samples placed on a steel plate. For the detection of nodules, we took advantage of the property of nodules of altering not only the acoustical properties of tissues producing ultrasound attenuation, but also of developing patterns at their boundary that can modify the shape and the amplitude of the received echo signals from the steel plate supporting the tissues. Besides the Correlation Index Amplitude (CIA), which is linked to the overall amplitude changes of the ultrasonic signals, we introduced the Correlation Index Shape (CIS) linked to their shape changes. Furthermore, we applied AND-OR logical operators to these correlation indices. The results were found particularly helpful in the localization of the irregular masses of agar we inserted into some excised liver tissues, and in the individuation of the regions of major interest over which perform the vertical dissections of tissues in an automated analysis finalized to histopathology. We correctly identified up to 89% of inclusions, with an improvement of about 14% with respect to the result obtained (78%) from the analysis performed with the CIA parameter only.
本研究提出了一种改进的策略,通过使用 16MHz 针状探头进行的脉冲回波超声测量,来检测和定位切除的猪肝组织中微小(小至几毫米)的琼脂结节。这项工作有助于开发新一代医疗仪器,以支持机器人手术决策过程,这些过程需要在短时间(分钟)内获得有关癌组织的信息。所开发的超声探头是专为手术相关组织学分析自动化而设计的扫描平台的一部分。它与力传感器耦合,以控制放置在钢板上的组织样本的压痕。为了检测结节,我们利用结节不仅改变产生超声衰减的组织的声学特性,而且还在其边界处形成模式的特性,这些模式可以改变支撑组织的钢板的接收回波信号的形状和幅度。除了与超声信号整体幅度变化相关的相关指数幅度(CIA)之外,我们还引入了与形状变化相关的相关指数形状(CIS)。此外,我们将这些相关指数应用于 AND-OR 逻辑运算符。结果发现,这些相关指数在定位我们插入一些切除的肝组织中的不规则琼脂块,以及在个体化主要感兴趣区域方面特别有帮助,这些区域在自动化分析中执行组织的垂直切割,以进行组织病理学。我们正确识别了高达 89%的包含物,与仅使用 CIA 参数进行分析(78%)相比,提高了约 14%。