Evidence map›Paper›PMID 39347934›Full record

ReviewThe international journal of cardiovascular imaging2026

Evolving capabilities of computed tomography imaging for transcatheter valvular heart interventions - new opportunities for precision medicine.

Vitaliy Androshchuk, Natalie Montarello, Nishant Lahoti, Samuel Joseph Hill, Can Zhou, Tiffany Patterson, Simon Redwood, Steven Niederer, Pablo Lamata, Adelaide De Vecchi and 1 more

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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

11 authors.

Vitaliy AndroshchukSchool of Cardiovascular Medicine & Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK. Vitaliy.Androshchuk@gstt.nhs.uk.
Natalie MontarelloCardiovascular Department, St Thomas' Hospital, King's College London, London, UK.
Nishant LahotiCardiovascular Department, St Thomas' Hospital, King's College London, London, UK.
Samuel Joseph HillSchool of Cardiovascular Medicine & Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Can ZhouCardiovascular Department, St Thomas' Hospital, King's College London, London, UK.
Tiffany PattersonCardiovascular Department, St Thomas' Hospital, King's College London, London, UK.
Simon RedwoodSchool of Cardiovascular Medicine & Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Steven NiedererSchool of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Pablo LamataSchool of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Adelaide De VecchiSchool of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Ronak RajaniCardiovascular Department, St Thomas' Hospital, King's College London, London, UK.

Funding

British Heart Foundation FS/CRTF/22/24328
6 · The paper itself

Abstract

The last decade has witnessed a substantial growth in percutaneous treatment options for heart valve disease. The development in these innovative therapies has been mirrored by advances in multi-detector computed tomography (MDCT). MDCT plays a central role in obtaining detailed pre-procedural anatomical information, helping to inform clinical decisions surrounding procedural planning, improve clinical outcomes and prevent potential complications. Improvements in MDCT image acquisition and processing techniques have led to increased application of advanced analytics in routine clinical care. Workflow implementation of patient-specific computational modeling, fluid dynamics, 3D printing, extended reality, extracellular volume mapping and artificial intelligence are shaping the landscape for delivering patient-specific care. This review will provide an insight of key innovations in the field of MDCT for planning transcatheter heart valve interventions.

Indexed as

Cardiac CatheterizationHeart Valve DiseasesHeart Valve Prosthesis ImplantationHeart ValvesMultidetector Computed TomographyPrecision MedicineClinical Decision-MakingDiffusion of InnovationHumansPatient SelectionPatient-Specific ModelingPredictive Value of TestsPrinting, Three-DimensionalRadiographic Image Interpretation, Computer-AssistedTreatment OutcomeWorkflowComputed tomographyTranscatheter valvular intervention

Identifiers

PMID39347934
PMCPMC12987856

What Socratic holds

Textmetadata
LicenceCC BY
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.