Background This retrospective study aims to evaluate the diagnostic value of volume measurement of central pulmonary arteries using computer tomography pulmonary angiography (CTPA) for predicting pulmonary arterial hypertension (PAH).
Methods A total of 59 patients in our hospital from November 2013 to February 2023 who underwent both right cardiac catheterization and CTPA examination were included. Systolic pulmonary artery pressure (SPAP), mean PAP (mPAP), and diastolic PAP (DPAP) were acquired. Patients were divided into two groups: non-PAH (18 cases) and PAH (41 cases). The diameters of the main pulmonary artery (DMPA), right pulmonary artery (DRPA), and left pulmonary artery (DLPA) were measured manually. A 3D model software was used for the segmentation of central pulmonary arteries. The cross-sectional areas (AMPA, ARPA, ALPA) and the volumes (VMPA, VRPA, VLPA) were calculated. A comparative analysis of the parameters of central pulmonary arteries between the two groups was performed. Through the ROC curves, the optimal cutpoints of the CTPA parameters for predicting PAH were identified. Additionally, we correlated the parameters from CTPA images with those from RHC. A multiple linear regression model with a forward-step approach was adopted to integrate all statistically significant CTPA parameters for PAH prediction.
Results All parameters (DMPA, DRPA, DLPA, AMPA, ARPA, ALPA, VMPA, VRPA, and VLPA) exhibited significantly elevated in the PAH group in contrast to the non-PAH group (P < 0.05). The one-dimensional measurements (DMPA, DRPA, DLPA), two-dimensional measurements (AMPA, ARPA, ALPA), and three-dimensional measurements (VMPA, VRPA, VLPA) of CTPA images all showed a positive correlation with the RHC results (mPAP, DPAP, SPAP), all with P < 0.05. Particularly, for the MPA and RPA, 3D CTPA parameters showed superior correlation coefficients compared to their one-dimensional and two-dimensional counterparts. The ROC analysis indicated that the volume measurements were more accurate and provided a greater area under the curve compared to the diameter and sectional area measurements. The predictive equations for mPAP, DPAP, and SPAP were formulated as [8.178 + 0.0006 * VMPA], [1.418 + 0.0005 * VMPA], and [-11.137 + 0.0006*VRPA + 1.259 * DMPA], respectively.
Conclusion The 3D volume measurement of the central pulmonary artery based on CTPA images outperforms the traditional diameter in predicting PAH.