IEEE Trans Biomed Eng. 2018 Sep;65(9):2011-2022. doi: 10.1109/TBME.2017.2714666. Epub 2017 Jun 12.
Many commercially available arterial blood pressure measurement devices suffer from a range of weaknesses. For example, common weaknesses include being inaccurate, invasive, and ad hoc; many also require explicit user calibration or cut off blood flow to a limb. A novel algorithmic approach is presented to accurately estimate systolic and diastolic blood pressure in a way that does not require any explicit user calibration, is noninvasive, and does not cut off blood flow.
The approach uses ultrasound images of the arterial wall and corresponding contact force data to obtain blood pressure estimates. To acquire data, an ultrasound probe was placed on the patient's carotid artery and the contact force was increased from 1.5 to 12 N. The artery was then algorithmically segmented from the recorded DICOM B-Mode data. The segmentation data and the contact force were used as input into the Levenberg-Marquardt optimization method to solve for the parameters, including blood pressure, of a simple finite element model of the carotid artery.
The algorithm was validated on 24 healthy volunteers. Algorithm arterial blood pressure predictions were compared to oscillometric blood pressure cuff readings. Regression and Bland-Altman analyses were performed on the data.
Both systolic pressure and diastolic pressure can be estimated using this novel noninvasive ultrasound-based method (systolic accuracy/precision: $-$ 2.36 mmHg/10.21 mmHg; diastolic accuracy/precision: $-$ 0.32/8.23 mmHg).
The method occupies a clinical middle ground between the arterial catheter and cuff-based techniques. It has the potential to give accurate results for patients with hypertension and atherosclerosis.
许多市售的动脉血压测量设备存在一系列弱点。例如,常见的弱点包括不准确、侵入性和特定用途;许多还需要明确的用户校准或阻断肢体的血流。本文提出了一种新的算法方法,能够以无需任何明确用户校准、非侵入性且不阻断血流的方式准确估计收缩压和舒张压。
该方法使用动脉壁的超声图像和相应的接触力数据来获得血压估计值。为了获取数据,将超声探头放置在患者的颈动脉上,并将接触力从 1.5 增加到 12 N。然后,通过记录的 DICOM B 模式数据自动对动脉进行分割。将分割数据和接触力作为输入输入到 Levenberg-Marquardt 优化方法中,以求解包括血压在内的颈动脉简单有限元模型的参数。
该算法在 24 名健康志愿者中进行了验证。将算法动脉血压预测与示波血压袖带读数进行了比较。对数据进行了回归和 Bland-Altman 分析。
可以使用这种新的非侵入性基于超声的方法来估计收缩压和舒张压(收缩压准确性/精度:$-2.36$mmHg/10.21mmHg;舒张压准确性/精度:$-0.32/8.23$mmHg)。
该方法在动脉导管和基于袖带的技术之间占据了临床中间地位。它有可能为高血压和动脉粥样硬化患者提供准确的结果。