Evidence map›Paper›PMID 30788246›Full record

ArticleQuantitative imaging in medicine and surgery2019

Optimization of computed tomography pulmonary angiography protocols using 3D printed model with simulation of pulmonary embolism.

Sultan Aldosari, Shirley Jansen, Zhonghua Sun

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 37 citations in OpenAlex.

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  15. Personalized 3D printed coronary models in coronary stenting.Quantitative imaging in medicine and surgery · 2019
    Article
  16. Insights into 3D printing in medical applications.Quantitative imaging in medicine and surgery · 2019
    Article
  17. Article
  18. Patient-specific 3D printed model of biliary ducts with congenital cyst.Quantitative imaging in medicine and surgery · 2019
    Article
  19. 3D printing in medicine: current applications and future directions.Quantitative imaging in medicine and surgery · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Sultan AldosariDiscipline of Medical Radiation Sciences, School of Molecular and Life Sciences, Curtin University, Perth, Western Australia, Australia.
Shirley JansenDepartment of Vascular and Endovascular Surgery, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.
Zhonghua SunDiscipline of Medical Radiation Sciences, School of Molecular and Life Sciences, Curtin University, Perth, Western Australia, Australia.
Curtin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThree-dimensional (3D) printing has been shown to accurately replicate anatomical structures and pathologies in complex cardiovascular disease. Application of 3D printed models to simulate pulmonary arteries and pulmonary embolism (PE) could assist development of computed tomography pulmonary angiography (CTPA) protocols with low radiation dose, however, this has not been studied in the literature. The aim of this study was to investigate optimal CTPA protocols for detection of PE based on a 3D printed pulmonary model.

methodsA patient-specific 3D printed pulmonary artery model was generated with thrombus placed in both main pulmonary arteries to represent PE. The model was scanned with 128-slice dual-source CT with slice thickness of 1 and 0.5 mm reconstruction interval. The tube voltage was selected to range from 70, 80, 100 to 120 kVp, and pitch value from 0.9 to 2.2 and 3.2. Quantitative assessment of image quality in terms of signal-to-noise ratio (SNR) was measured in the main pulmonary arteries and within the thrombus regions to determine the relationship between image quality and scanning protocols. Both two-dimensional (2D) and 3D virtual intravascular endoscopy (VIE) images were generated to demonstrate pulmonary artery and thrombus appearances.

resultsPE was successfully simulated in the 3D printed pulmonary artery model. There were no significant differences in SNR measured in the main pulmonary arteries with 100 and 120 kVp CTPA protocols (P>0.05), regardless of pitch value used. SNR was significantly lower in the high-pitch 3.2 protocols when compared to other protocols using 70 and 80 kVp (P<0.05). There were no significant differences in SNR measured within the thrombus among the 100 and 120 kVp protocols (P>0.05). For low dose 70 and 80 kVp protocols, SNR was significantly lower in the high-pitch of 3.2 protocols than that in other protocols with different pitch values (P<0.01). 2D images showed the pulmonary arteries and thrombus clearly, while 3D VIE demonstrated intraluminal appearances of pulmonary wall and thrombus in all protocols, except for the 70 kVp and pitch 3.2 protocol, with visualization of thrombus and pulmonary artery wall affected by artifact associated with high image noise. Radiation dose was reduced by up to 80% when lowering kVp from 120 to 100 and 80 kVp with use of 3.2 high-pitch protocol, without significantly affecting image quality.

conclusionsLow-dose CT pulmonary angiography can be achieved with use of low kVp (80 and 100) and high-pitch protocol with significant reduction in radiation dose while maintaining diagnostic images of PE. Use of high pitch, 3.2 in 70 kVp protocol should be avoided due to high image noise and poorer quality.

Indexed as

Computed tomography pulmonary angiography (CTPA)diagnosisdoseimage qualitymodelthree-dimensional printing

Identifiers

PMID30788246
PMCPMC6351811
OpenAlexW2896652380

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.