Evidence map›Paper›PMID 42010396›Full record

ArticleBMC medical imaging2026

Quantitative assessment of intrapulmonary vessel volume by CTPA in vasculitis patients with pulmonary vascular involvement.

Ying Ming, Sirong Piao, Ruijie Zhao, Jiaru Wang, Zicheng Liao, Lan Song, Ran Xiao, Rui Zhao, Zhuangfei Ma, Bing Li and 2 more

Abstract read
In one paragraph

Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Ying MingDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Sirong PiaoDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Ruijie ZhaoDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Jiaru WangDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Zicheng LiaoDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Lan SongDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Ran XiaoDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Rui ZhaoDepartment of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Zhuangfei MaCanon Medical Systems (China), No.3, Xinyuan South Road, Chaoyang District, Beijing, 100027, China.
Bing LiCanon Medical Systems (China), No.3, Xinyuan South Road, Chaoyang District, Beijing, 100027, China.
Fuling Zheng *Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. lele7870@163.com.
Wei Song *Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. cjr.songwei@vip.163.com.

Funding

China Postdoctoral Science Foundation 2025M772188National High Level Hospital Clinical Research Funding 2022-PUMCH-B-069National Natural Science Foundation of China NSFC no. 82173623Peking Union Medical College Hospital Research Funding for Postdoc kyfyjj202412
6 · The paper itself

Abstract

purposeTo compare intrapulmonary vessel volume (IPVV) on computed tomography pulmonary angiography (CTPA) between vasculitis patients with pulmonary vascular involvement and CTPA-negative subjects.

methodsThis study included 207 vasculitis patients with pulmonary vascular involvement between March 2019 and November 2024 and 202 CTPA-negative subjects between February 2019 and February 2025. A computer-aided pulmonary vascular segmentation algorithm was employed to automatically measure total intrapulmonary vessel volume (TIPVV), intrapulmonary arterial vessel volume (IPVVa) and intrapulmonary venous vessel volume (IPVVv). Additionally, IPVVs were analyzed and compared within five specific vessel diameter groups: 0.8–1.6 mm, 1.6–2.4 mm, 2.4–3.2 mm, 3.2–4.0 mm, and > 4.0 mm.

resultsTIPVV and IPVVv showed no significant differences between groups. The IPVVa measured in CTPA-negative subjects was 47.79 (42.48, 54.10) mL·m− 2, while that in vasculitis patients with pulmonary vascular involvement was 44.86 (39.33, 52.58) mL·m− 2. The IPVVa in vasculitis patients with pulmonary vascular involvement was significantly lower than that in CTPA-negative subjects (p < 0.01). In pulmonary arteries with diameters of 0.8–1.6 mm and 2.4–3.2 mm, the IPVVa in vasculitis patients with pulmonary vascular involvement was lower than that in CTPA-negative subjects (p < 0.05). In pulmonary veins with diameters of 1.6–2.4 mm and 3.2–4.0 mm, the IPVVv in vasculitis patients with pulmonary vascular involvement was higher than that in CTPA-negative subjects (p < 0.05).

conclusionsThe computer-aided pulmonary vascular segmentation algorithm can automatically measure IPVV, enabling quantitative assessment of small pulmonary vessel involvement in vasculitis.

Indexed as

Computed Tomography AngiographyLungPulmonary ArteryPulmonary VeinsVasculitisAdultAgedAlgorithmsFemaleHumansMaleMiddle AgedRetrospective StudiesComputed tomographyThree-dimensionalVasculitis

Identifiers

PMID42010396
PMCPMC13231555

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Registered trials

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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.