Evidence map›Paper›PMID 41549183›Full record

ReviewThe international journal of cardiovascular imaging2026

Multimodal imaging of acquired aortic diseases: clinical efficacy, comparative analysis, and future perspectives.

Chang Li, Chizhuai Liu

Abstract readReview
In one paragraph

Review in The international journal of cardiovascular 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
–field-weighted citation impact
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

2 authors.

Chang LiHenan Medical University, Xinxiang, Henan, 453003, China.
Chizhuai LiuDepartment of General Surgery II, Zhongshan City People's Hospital, Zhongshan, 528402, Guangdong, China. L60375@yeah.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aortic diseases, particularly acute aortic syndromes (AAS) and aortic aneurysms (AA), represent critical cardiovascular conditions with high mortality rates requiring precise imaging for diagnosis and management. This review provides a comprehensive analysis of current imaging diagnostic techniques, focusing specifically on acquired thoracic and abdominal aortic pathologies. We first evaluate the comparative efficacy of Computed Tomography Angiography (CTA) and Magnetic Resonance Imaging (MRI) in the diagnosis of AAS (including aortic dissection, intramural hematoma, and penetrating atherosclerotic ulcer), highlighting the role of artificial intelligence in optimizing segmentation and detection. Subsequently, we discuss aortic aneurysms, emphasizing the shift from simple diameter-based assessment to functional risk stratification incorporating calcification scoring, inflammatory imaging, and hemodynamic parameters. Furthermore, the review addresses postoperative imaging surveillance, particularly for endoleak detection following endovascular aneurysm repair (EVAR). We conclude that while CTA remains the gold standard for emergency diagnosis due to its speed and spatial resolution, MRI offers superior value in functional assessment and radiation-free long-term follow-up. The integration of multimodal imaging and AI-driven analysis is essential for achieving precision medicine in the management of acquired aortic diseases.

Indexed as

Acute Aortic SyndromeAortic Aneurysm, AbdominalAortic Aneurysm, ThoracicAortic DiseasesAortographyComputed Tomography AngiographyMagnetic Resonance AngiographyMagnetic Resonance ImagingMultimodal ImagingArtificial IntelligenceEndovascular Aneurysm RepairForecastingHumansPenetrating Atherosclerotic UlcerPredictive Value of TestsPrognosisAcute aortic syndromeAortic aneurysmAortic diseasesArtificial intelligenceMultimodal imaging

Identifiers

PMID41549183
PMCPMC13053396

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.