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PLGA-Au-PFH-NPs-based Ultrasound Imaging in Detecting Fetal Spinal Deformities

Cell Mol Biol (Noisy-le-grand). 2022 Mar 31;68(3):15-23. doi: 10.14715/cmb/2022.68.3.3.

ABSTRACT

The study focused on the performance of ultrasound imaging in detecting fetal spinal deformities. First, the double emulsification method and the carbodiimide method were used to prepare the target Au-loaded nanorod phase-change nano-level contrast agent-PLGA-Au-PFH-NPs. After being characterized for physical and chemical properties, it was used in ultrasound imaging diagnosis. The results showed that the prepared PLGA-Au-PFH-NPs solution was a milky white suspension, the particle size detected by the laser particle sizer was (376.17±20.74) nm, and the Zeta potential was (-4.82±2.88) mV. Under the light microscope, it showed a spherical shape, uniform size distribution, and a very smooth surface. The encapsulation rate measured by the UV spectrophotometer was (80.63±4.82) %, and there was no significant difference in cell survival rate between different concentrations (P>0.05). Prenatal ultrasound in the observation group accurately diagnosed 10 cases with spinal deformities, and the diagnostic accuracy rate was 50%, including 5 cases of meningocele, 3 cases of invisible spina bifida, 1 case of myelomeningocele, and 1 case of hemivertebrae. In the control group, 7 cases were diagnosed correctly by conventional ultrasound, and the diagnosis accuracy rate was 35%, including 3 cases of meningocele, 3 cases of invisible spina bifida, and 1 case of hemivertebra. The diagnostic accuracy of the observation group was higher than that of the control group, and the difference was statistically significant (P<0.05). In conclusion, the prepared PLGA-Au-PFH-NPs had good physical and chemical properties. Ultrasound imaging based on the PLGA-Au-PFH-NPs had high accuracy in diagnosing fetal spinal deformities. To a certain extent, it provides a basis for clinical diagnosis of fetal spinal abnormality and some new ideas for ultrasound imaging diagnosis.

PMID:35988201 | DOI:10.14715/cmb/2022.68.3.3

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