To investigate the correlation and agreement of placental vascular indices from sphere mode of threedimensional power Doppler ultrasonography (3D-PDU) with those from the entire placenta.
Methods:
3D-PDU examinations were performed in 154 singleton pregnancies at 11-14 weeks gestation. Sphere mode and manual trace mode of virtual organ computer aided analysis (VOCAL) program were used to
calculate the placental vascularization index (VI)
flow index (FI) and vascularization flow index (VFI) from stored images of each placenta by four spherical regions of interest and the whole placental. The mean values of each index from four spherical regions of interest were compared to those from the entire placenta to investigate the correlation and agreement.
Results:
All vascular indices from partial placental obtained by sphere mode [VI: 38.6014.31; FI: 29.496.17; VFI: 12.536.34)
]
were significantly correlated with those from the whole placental [VI: 38.9313.86; FI: 31.795.49; VFI: 12.906.50
]
[
r
=0.978 (
P
0.001)
0.677 (
P
0.001)
0.963(
P
0.001)
respectively
]
. The VI and VFI values obtained by the two modes were similar
and FI value was significantly different (
P
0.05).
Conclusion:
Sphere mode may be a valid alternative for evaluation of the placental vascularization when visualization of the entire placenta is not feasible. VI value appears to be more reliable than FI and VFI values in sphere mode.
Head-to-head comparative study of 18F-FDG and 18F-FMISO PET/CT in guiding carbon ion radiotherapy for patients with locally advanced non-small cell lung cancer
Standards and requirements for breast ultrasound examination—Shanghai expert consensus on ultrasound quality control (2025)
Value of a nomogram based on ultrasonic features in predicting cervical lymph node metastasis in Hashimoto’s thyroiditis complicated by papillary thyroid carcinoma
Comparison of diagnostic yields and analysis of influencing factors of core needle biopsy guided by conventional ultrasound or contrast‑enhanced ultrasound for retroperitoneal tumors
The value of automatic segmentation radiomics features in predicting pathological complete response after neoadjuvant therapy for breast cancer