An optimized test bolus for computed tomography pulmonary angiography and its application at 80 kV with 10 ml contrast agent

Computed tomography pulmonary angiography (CTPA) is usually used for pulmonary embolism (PE) detection. However, the determination of scan timing remains a challenge due to the short scan duration of CTPA. We aimed to develop an optimized test bolus to determine scan delay in CTPA. The time-enhancement curves were obtained by measuring the enhancement within a region of interest in the main pulmonary artery and vein. A total of 70 patients were randomly divided into two groups (n = 35 each): the control group underwent CTPA using the test bolus approach and the test group underwent CTPA using the biphasic time-enhancement curves approach. Tube voltages of 100 kVp and 80 kVp and 20 ml and 10 ml contrast agent were adopted in the control and test groups, respectively. The CT numbers, image quality, PE detection was evaluated. There was a point of intersection between the pulmonary artery and vein test bolus enhancement curves. The scan delay time (TDELAY) was obtained based on the time at intersection (TCROSS) and the scan duration (TSD): TDELAY = TCROSS - TSD. The mean CT numbers for pulmonary vein in the control were higher than those in the test group (all p < 0.001). The image quality for the pulmonary arteries in the test group was better than that in the control group (p < 0.01), with artifact reduction in the superior vena cava. Segmental PE could be detected using the optimized protocol. The radiation dose and iodine load in the test group were all lower than those in the control (p < 0.01). We established an approach to calculate the scan delay of CTPA, and this approach could be used for CTPA at 80 kVp with 10 ml contrast agent.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Scientific reports - 10(2020), 1 vom: 23. Juni, Seite 10208

Sprache:

Englisch

Beteiligte Personen:

Wu, Huiming [VerfasserIn]
Chen, Xiao [VerfasserIn]
Zhou, Hao [VerfasserIn]
Qin, Bin [VerfasserIn]
Cao, Jian [VerfasserIn]
Pan, Zhaochun [VerfasserIn]
Wang, Zhongqiu [VerfasserIn]

Links:

Volltext

Themen:

Contrast Media
Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 07.12.2020

Date Revised 23.06.2021

published: Electronic

Citation Status MEDLINE

doi:

10.1038/s41598-020-67145-9

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM311553656