Department of Biomedical Engineering, Pennsylvania State University, University Park, State College, PA 16802, USA.
Research & Business Development Division, CYBERDYNE INC, Cambridge Innovation Center, 3013 AK Rotterdam, The Netherlands.
Sensors (Basel). 2021 Jan 9;21(2):424. doi: 10.3390/s21020424.
Vascular diseases are becoming an epidemic with an increasing aging population and increases in obesity and type II diabetes. Point-of-care (POC) diagnosis and monitoring of vascular diseases is an unmet medical need. Photoacoustic imaging (PAI) provides label-free multiparametric information of deep vasculature based on strong absorption of light photons by hemoglobin molecules. However, conventional PAI systems use bulky nanosecond lasers which hinders POC applications. Recently, light-emitting diodes (LEDs) have emerged as cost-effective and portable optical sources for the PAI of living subjects. However, state-of-art LED arrays carry significantly lower optical energy (<0.5 mJ/pulse) and high pulse repetition frequencies (PRFs) (4 KHz) compared to the high-power laser sources (100 mJ/pulse) with low PRFs of 10 Hz. Given these tradeoffs between portability, cost, optical energy and frame rate, this work systematically studies the deep tissue PAI performance of LED and laser illuminations to help select a suitable source for a given biomedical application. To draw a fair comparison, we developed a fiberoptic array that delivers laser illumination similar to the LED array and uses the same ultrasound transducer and data acquisition platform for PAI with these two illuminations. Several controlled studies on tissue phantoms demonstrated that portable LED arrays with high frame averaging show higher signal-to-noise ratios (SNRs) of up to 30 mm depth, and the high-energy laser source was found to be more effective for imaging depths greater than 30 mm at similar frame rates. Label-free in vivo imaging of human hand vasculature studies further confirmed that the vascular contrast from LED-PAI is similar to laser-PAI for up to 2 cm depths. Therefore, LED-PAI systems have strong potential to be a mobile health care technology for diagnosing vascular diseases such as peripheral arterial disease and stroke in POC and resource poor settings.
血管疾病随着人口老龄化、肥胖症和 2 型糖尿病的增加而成为一种流行疾病。即时诊断和监测血管疾病是未满足的医疗需求。光声成像是一种基于血红蛋白分子对光光子强吸收的无标记多参数深层血管成像技术。然而,传统的光声成像系统使用体积庞大的纳秒激光器,这阻碍了即时诊断的应用。最近,发光二极管(LED)已成为活体光声成像的经济实惠且便携的光学光源。然而,与高功率激光源(100 mJ/pulse)相比,最先进的 LED 阵列携带的光能量(<0.5 mJ/pulse)和高重复频率(PRF)(4 KHz)要低得多,而激光源的 PRF 则低至 10 Hz。鉴于便携性、成本、光能量和帧率之间的这些权衡,本工作系统地研究了 LED 和激光照明的深层组织光声成像性能,以帮助为给定的生物医学应用选择合适的光源。为了进行公平的比较,我们开发了一种光纤阵列,该阵列提供类似于 LED 阵列的激光照明,并使用相同的超声换能器和数据采集平台用于这两种照明的光声成像。在组织体模的几项对照研究中,我们证明了具有高帧平均的便携式 LED 阵列可实现高达 30 mm 深度的更高信噪比(SNR),并且在类似帧率下,高能激光源对于大于 30 mm 的成像深度更为有效。对人体手部血管的无标记活体成像研究进一步证实,对于高达 2 cm 的深度,LED-PAI 的血管对比度与激光-PAI 相似。因此,LED-PAI 系统具有成为即时诊断血管疾病(如外周动脉疾病和中风)的移动医疗技术的强大潜力,可用于在即时诊断和资源匮乏的环境中使用。