Politecnico di Milano, Dipartimento di Fisica, Milan, Italy.
Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Milan, Italy.
J Biomed Opt. 2023 Jul;28(7):075002. doi: 10.1117/1.JBO.28.7.075002. Epub 2023 Jul 17.
Continuous wave near infrared spectroscopy (CW-NIRS) is widely exploited in clinics to estimate skeletal muscles and brain cortex oxygenation. Spatially resolved spectroscopy (SRS) is generally implemented in commercial devices. However, SRS suffers from two main limitations: the assumption on the spectral dependence of the reduced scattering coefficient [] and the modeling of tissue as homogeneous.
We studied the accuracy and robustness of SRS NIRS. We investigated the errors in retrieving hemodynamic parameters, in particular tissue oxygen saturation (), when was varied from expected values, and when layered tissue was considered.
We simulated hemodynamic variations mimicking real-life scenarios for skeletal muscles. Simulations were performed by exploiting the analytical solutions of the photon diffusion equation in different geometries: (1) semi-infinite homogeneous medium and constant ; (2) semi-infinite homogeneous medium and linear changes in ; (3) two-layered media with a superficial thickness , 7.5, 10 mm and constant . All simulated data were obtained at source-detector distances , 40, 45 mm, and analyzed with the SRS approach to derive hemodynamic parameters (concentration of oxygenated and deoxygenated hemoglobin, total hemoglobin concentration, and tissue oxygen saturation, ) and their relative error.
Variations in affect the estimated (up to ), especially if changes are different at the two wavelengths. However, the main limitation of the SRS method is the presence of a superficial layer: errors strongly larger than 20% were retrieved for the estimated when the superficial thickness exceeds 5 mm.
These results highlight the need for more sophisticated strategies (e.g., the use of multiple short and long distances) to reduce the influence of superficial tissues in retrieving hemodynamic parameters and warn the SRS users to be aware of the intrinsic limitation of this approach, particularly when exploited in the clinical environment.
连续波近红外光谱（CW-NIRS）广泛应用于临床，以估计骨骼肌和大脑皮层的氧合。空间分辨光谱（SRS）通常在商业设备中实现。然而，SRS 存在两个主要限制：对散射系数的光谱依赖性的假设[]和组织均匀性的建模。
我们研究了 SRS-NIRS 的准确性和稳健性。我们研究了当从预期值变化时，以及考虑分层组织时，在检索血液动力学参数（特别是组织氧饱和度 ()）时的误差。
我们通过在不同几何形状下利用光子扩散方程的解析解来模拟模拟骨骼肌的血液动力学变化：（1）半无限均匀介质和常数；（2）半无限均匀介质和线性变化；（3）两层介质，表面厚度 ，7.5 ，10 毫米和常数。所有模拟数据均在源-探测器距离 ，40 ，45 毫米处获得，并通过 SRS 方法进行分析，以得出血液动力学参数（氧合和去氧血红蛋白浓度、总血红蛋白浓度和组织氧饱和度 ()）及其相对误差。
变化会影响估计的 （高达 ），特别是如果两个波长的变化不同。然而，SRS 方法的主要限制是存在表面层：当表面厚度超过 5 毫米时，估计的 会出现误差，误差远大于 20%。
这些结果强调需要更复杂的策略（例如，使用多个短距离和长距离）来减少在检索血液动力学参数时对表面组织的影响，并警告 SRS 用户要意识到这种方法的内在局限性，特别是在临床环境中使用时。
