Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension.

Rengier, Fabian; Wörz, Stefan; Melzig, Claudius; Ley, Sebastian; Fink, Christian; Benjamin, Nicola; Partovi, Sasan; von Tengg-Kobligk, Hendrik; Rohr, Karl; Kauczor, Hans-Ulrich; Grünig, Ekkehard (2016). Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension. PLoS ONE, 11(9), e0162516. Public Library of Science 10.1371/journal.pone.0162516

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PURPOSE

To demonstrate feasibility of automated 3D volumetry of central pulmonary arteries based on magnetic resonance angiography (MRA), to assess pulmonary artery volumes in patients with pulmonary hypertension compared to healthy controls, and to investigate the potential of the technique for predicting pulmonary hypertension.

METHODS

MRA of pulmonary arteries was acquired at 1.5T in 20 patients with pulmonary arterial hypertension and 21 healthy normotensive controls. 3D model-based image analysis software was used for automated segmentation of main, right and left pulmonary arteries (MPA, RPA and LPA). Volumes indexed to vessel length and mean, minimum and maximum diameters along the entire vessel course were assessed and corrected for body surface area (BSA). For comparison, diameters were also manually measured on axial reconstructions and double oblique multiplanar reformations. Analyses were performed by two cardiovascular radiologists, and by one radiologist again after 6 months.

RESULTS

Mean volumes of MPA, RPA and LPA for patients/controls were 5508 ± 1236/3438 ± 749, 3522 ± 934/1664 ± 468 and 3093 ± 692/1812 ± 474 μl/(cm length x m2 BSA) (all p<0.001). Mean, minimum and maximum diameters along the entire vessel course were also significantly increased in patients compared to controls (all p<0.001). Intra- and interobserver agreement were excellent for both volume and diameter measurements using 3D segmentation (intraclass correlation coefficients 0.971-0.999, p<0.001). Area under the curve for predicting pulmonary hypertension using volume was 0.998 (95% confidence interval 0.990-1.0, p<0.001), compared to 0.967 using manually measured MPA diameter (95% confidence interval 0.910-1.0, p<0.001).

CONCLUSIONS

Automated MRA-based 3D volumetry of central pulmonary arteries is feasible and demonstrated significantly increased volumes and diameters in patients with pulmonary arterial hypertension compared to healthy controls. Pulmonary artery volume may serve as a superior predictor for pulmonary hypertension compared to manual measurements on axial images but verification in a larger study population is warranted.

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