武居 昌宏

Heparin concentration c in a blood extracorporeal circulation has been real-timely predicted based on the relaxation strength Δεm at relaxation frequency fm extracted by relaxation time distribution (RTD). The simulated extracorporeal circulation was conducted to optimize the number of Δεm for the prediction of c using the porcine whole blood (WB) and low-leukocyte and −platelet blood (LLPB) under the condition of the gradual increment of c from 0 to 8 U/mL with constant flow rate and blood temperature. The experimental results show that among the three relaxation strengths Δε1, Δε2 and Δε3 (in ascending order of frequency), Δε2 at f2 = 5.2 ∼ 6.2 MHz and Δε3 at f3 = 42 ∼ 50 MHz were correlated to c. The Δε3 was decreasing with increasing c in both cases, which was influenced by the plasma macromolecular concentrations, while the Δε2 was increased with increasing c in WB case but was hardly changed in LLPB case because the Δε2 is influenced by the blood cell concentrations and the shape changes of blood cell membranes. Heparin concentration c is estimated by the linear regression formula cPRE=a1(Δε2-Δε2c=0)+a2(Δε3-Δε3c=0) (a1 = -0.991, a2 = -0.123) within the mean absolute percentage error (MAPE) of 0.291.

Albumin andγ-globulin concentrations in subcutaneous adipose tissues (SAT) have been quantified by multivariate regression based on admittance relaxation time distribution (mrARTD) under the fluctuated background of sodium electrolyte concentration. ThemrARTD formulatesP=Ac+Ξ(P: peak matrix of distribution function magnitudeγˆand relaxation timesτˆ,c: concentration matrix of albumincAlb,γ-globulinGloc, and sodium electrolyteNac,A: coefficient matrix of a multivariate regression model, andΞ: error matrix). ThemrARTD is implemented by two processes which are: (1) the training process ofAthrough the maximum likelihood estimation ofPand (2) the quantification process ofcAlb,Gloc, andNacthrough the model prediction. In the training process, a positive correlation is present betweencAlb,Gloc, andNactoγˆ1atτˆ1= 0.1 as well asγˆ2atτˆ2= 1.40 μs as under a fixed concentration of proteins solution into a porcine SAT (cAlb= 0.800-2.400 g/dL,Gloc= 0.400-1.200 g dl-1andNac= 0.700-0.750 g dl-1). ThemrARTD method quantifiescAlb,Gloc, andNacin SAT with an absolute error of 33.79%, 44.60%, and 2.18%, respectively.

Breast cancer detection and differentiation of breast tissues are critical for accurate diagnosis and treatment planning. This study addresses the challenge of distinguishing between invasive ductal carcinoma (IDC), normal glandular breast tissues (nGBT), and adipose tissue using electrical impedance spectroscopy combined with Gaussian relaxation-time distribution (EIS-GRTD). The primary objective is to investigate the relaxation-time characteristics of these tissues and their potential to differentiate between normal and abnormal breast tissues. We applied a single-point EIS-GRTD measurement to ten mastectomy specimens across a frequency rangef= 4 Hz to 5 MHz. The method calculates the differential ratio of the relaxation-time distribution functionΔγbetween IDC and nGBT, which is denoted byΔγIDC-nGBT,andΔγbetween IDC and adipose tissues, which is denoted byΔγIDC-adipose.As a result, the differential ratio ofΔγbetween IDC and nGBTΔγIDC-nGBTis 0.36, and between IDC and adiposeΔγIDC-adiposeis 0.27, which included in theα-dispersion atτpeak1=0.033±0.001s.In all specimens, the relaxation-time distribution functionγof IDCγIDCis higher, and there is no intersection withγof nGBTγnGBTand adiposeγadipose.The difference inγsuggests potential variations in relaxation properties at the molecular or structural level within each breast tissue that contribute to the overall relaxation response. The average mean percentage errorδfor IDC, nGBT, and adipose tissues are 5.90%, 6.33%, and 8.07%, respectively, demonstrating the model's accuracy and reliability. This study provides novel insights into the use of relaxation-time characteristic for differentiating breast tissue types, offering potential advancements in diagnosis methods. Future research will focus on correlating EIS-GRTD finding with pathological results from the same test sites to further validate the method's efficacy.