We aimed to establish a new formula for estimating renal depth, based on anthropometric variables, and to compare the estimates with actual data from a group of living kidney donors undergoing computed tomography angiography (CTA).Renal depths in 167 living kidney donors were measured by CTA. Regression analysis was used to derive the formulae for estimation of renal depth of both kidneys based on patient age, sex, body height, body weight, and body mass index (BMI). The results of the renal depth estimation from the derived formulae were compared with those using existing formulae.Using regression analysis, we derived 2 new formulae as follows; for left kidney, renal depth (cm) = 0.083 × W − 0.058 × H + 11.541 (male) or 10.89 (female), for right kidney, renal depth (cm) = 13.498 × W/H + 2.141 (male) or 1.816 (female), in which W represents the weight (kg) and H represents the height (cm). The correlation coefficients between our left or right renal depth estimates and those obtained from other formulae in another 271 kidney donors were 0.864 (left) or 0.893 (right) by the Tønnesen, 0.937 (left) or 0.97 (right) by the Taylor, 0.937 (left) or 0.97 (right) by the Itoh, 0.927 (left) or 0.951 (right) by the Li-qian, and 0.937 (left) or 0.97 (right) by the Inoue formula.Our formula may be more precise than the Tønnesen formula in estimating the renal depth. Estimating formulae based on CT findings might be useful in clinical practice.
ObjectiveThe aim of this study was to further elucidate the mechanisms of dual-phase technetium-99m methoxyisobutylisonitrile (99mTc-MIBI) parathyroid imaging by exploring the association between early uptake results (EUR), delayed uptake results (DUR), and the retention index (RI) in dual-phase 99mTc-MIBI parathyroid imaging and P glycoprotein (P-gp), multidrug resistance-associated protein 1 (MRP1), and glutathione S-transferase-π (GST-π) expression in hyperparathyroidism (HPT).Patients and methodsPreoperative dual-phase (early and delayed) 99mTc-MIBI imaging was performed on 74 patients undergoing parathyroidectomy for HPT. EUR, DUR, and RI were calculated. P-gp, MRP1, and GST-π expressions were assessed using immunohistochemistry in resected tissue from HPT and control patients. The association between P-gp, MRP1, and GST-π expressions and EUR, DUR, and RI in HPT was evaluated.ResultsThe positive rate of dual-phase 99mT c-MIBI imaging was 91.89% (68/74) and the false-negative rate was 8.11% (6/74). P-gp and GST-π expressions were higher in tissues resected from control compared with HPT patients (47.37 and 81.5%, P<0.05); there was no difference in MRP1. EUR were associated with P-gp and GST-π expressions, and DUR were associated with MRP1 expression. There was a significant difference in MRP1 expression between RI greater than or equal to 0 and RI less than 0. There was no relationship between the sensitivity of dual-phase 99mTc-MIBI imaging and P-gp, MRP1, and GST-π expressions in resected parathyroid tissue. The six false-negative HPT cases consisted of three P-gp (−)/MRP1 (−) tissues, three P-gp (−)/GST-π (−) tissues, and four MRP1 (−)/GST-π (−) tissues.ConclusionAs P-gp and GST-π expressions were higher in tissues resected from control compared with HPT patients, 99mTc-MIBI may wash out faster from normal parathyroid tissue surrounding the lesion compared with the lesion itself, facilitating detection.
Highlights This is the first time to study and find out that sinomenine hydrochloride and iodine-131 synergic enhance the apoptosis and regulate DNA repair and cell cycle checkpoint on papillary thyroid carcinoma cells. This is the first time to study and find out that sinomenine hydrochloride increased the radiosensitivity of papillary thyroid carcinoma cells and normal thyroid cells. This is the first time to study and find out that sinomenine hydrochloride could be a potential therapeutic radiosensitizer in papillary thyroid carcinoma radiotherapy after total thyroidectomy .
lent fluidity at room temperature, electrical and thermal conductivity, deformability in response to various stimuli, etc. Thus it has been intensively investigated in the field of thermal management, [1,2] flexible electronics and devices, [3][4][5][6][7] additive manufacture, [8,9] medical therapies, [10][11][12] soft robotics, [13,14] etc. Among the applications, the solid-liquid phase transition of gallium can enable diverse and specific functions beyond the single liquid-state metal behaviors. For instance, the phase transition of gallium-based polymer can achieve reversible transitional insulator and conductor, which can be applied as temperature-controlled electrical switches and circuits. [15] Taking advantage of the mechanical strength of solid gallium, the mechanically transformative electronics, sensors, and implantable devices can be also realized by solid-phase phase transition. [10,16] Moreover, phase transition of the liquid gallium or its alloy composite can generate reversible and strong adhesion to different surfaces, which can be used as transformable grippers for various objects. [14,13,17] During the solid-liquid phase transition, the melting process is relatively quick as temperature rises above the melting point. However, the solidification of gallium usually requires a much lower temperature than the melting point as well much longer time due to the significant supercooling effect (the With excellent electrical conductivity, fluidity, rheological property, and biocompatibility, gallium has been intensively studied in the fields of flexible electronics and devices, thermal management, and soft robotics. However, the large degree of supercooling of gallium presents a large limitation for phase transition-related applications such as the very low temperature required for solidification, the impurities, and side effects brought in by nucleating agents. In this study, solidification process of liquid gallium by using solid gallium as a nucleating agent is discovered to be fast and facile at room temperature compared with other agent materials including copper, iron, and nickel. Quantificationally, solidified gallium as a nucleating agent, can effectively reduce the supercooling degree from about 66.3 to 14.8 °C. The freezing velocity can reach to 200 mm 3 min −1 . The possible mechanism is reducing the energy barrier via adding nucleation site, allowing rapid solidification at room temperature accompanying heat dissipation. Moreover, micromechanical properties are compared between raw solid Ga and the solidified Ga induced by Ga agent, which suggests a slight decrease in mechanical strength at room temperature with the nucleating agent. It will be beneficial to understand the phase change and also provide guidance for the application of gallium regarding its mechanical properties.
Objective To compare image quality and diagnostic accuracy of arterial stenosis in low-dose lower-extremity CT angiography (CTA) between adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) algorithms. Methods Forty-six patients undergoing low-dose lower-extremity CTA were enrolled. Images were reconstructed using ASIR-V (blending factor of 50% (AV-50) and 100% (AV-100)) and DLIR (medium (DL-M), and high (DL-H)). CT values and standard deviation (SD) of the aorta, psoas, popliteal artery, popliteal and ankle muscles were measured. The edge-rise-distance (ERD) and edge-rise-slope (ERS) were calculated. The degrees of granularity and edge blurring were assessed using a 5-point scale. The stenosis degrees were measured on the four reconstructions, and their mean-square-errors (MSE) against that of digital subtraction angiography (DSA) were calculated and compared. Results For both ASIR-V and DLIR, higher reconstruction intensity generated lower noise and higher SNR and CNR values. The SD values in AV-100 images were significantly lower than other reconstructions. The two DLIR image groups had higher ERS and lower ERD (DL-M:1.79 ± 0.37 mm and DL-H:1.82 ± 0.38 mm vs AV-50:1.96 ± 0.39 mm and AV-100:2.01 ± 0.36 mm, p = 0.014) than ASIR-V images. The overall image quality of DLIR was rated higher than ASIR-V (DL-M:0.83 ± 0.61, DL-H:0.41 ± 0.62, AV-50:1.85 ± 0.60 and AV-100:2.37 ± 0.77, p < 0.001), with DL-H having the highest overall image quality score. For stenosis measurement, DL-H had the lowest MSE compared to DSA among all reconstruction groups. Conclusion DLIR images had higher image quality ratings with lower image noise and sharper vessel walls in low-dose lower-extremity CTA, and DL-H provides the best overall image quality and highest accuracy in diagnosing artery stenoses.
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