Evidence map›Paper›PMID 42082648›Full record

Articlenpj biomedical innovations2026

Diagnoses of pulmonary embolism from non-contrast 4DCT using image processing-derived quantitative perfusion scores.

Hsu-Ting Kuo, Yi-Kuan Liu, Debarghya Chaki, Girish Nair, Danielle Turner-Lawrence, Craig Stevens, Jorge Cisneros, Edward Castillo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in npj biomedical innovations, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Hsu-Ting KuoDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Yi-Kuan LiuDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Debarghya ChakiDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Girish NairDivision of Pulmonary and Critical Care, University of Kentucky, Lexington, KY, USA.
Danielle Turner-LawrenceDepartment of Emergency Medicine, William Beaumont University Hospital, Royal Oak, MI, USA.
Craig StevensDepartment of Radiation Oncology, William Beaumont University Hospital, Royal Oak, MI, USA.
Jorge CisnerosDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Edward CastilloDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA. Edward.Castillo@utexas.edu.

Funding

CT-Derived Functional Imaging for Predicting Disease Progression in COPDR01HL169869 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI Edward Castillo, Girish Balachandran Nair · 2024 to 2026
$1.1M
NHLBI NIH HHS R01 HL169869
6 · The paper itself

Abstract

Computed tomography pulmonary angiography (CTPA) is the gold standard for pulmonary embolism (PE) diagnosis, but patients with iodinated contrast allergies or renal insufficiency are often ineligible. CT-derived perfusion (CTP) is a novel, non-contrast method to quantify pulmonary perfusion from an inhale/exhale CT image pair (4DCT). The resulting CT-P information can be used to identify hypo-perfused regions associated with PE. This pilot study introduces a thresholding approach that estimates the number of lung lobes with perfusion deficits according to optimally selected CTP thresholds. The number of lobes indicated as low-functioning provides a score to categorize patients as PE-positive, negative, or inconclusive. We trained and validated the model on a retrospective dataset of 123 suspected PE patients, achieving 72% accuracy, 75% sensitivity, and 69% specificity, with 17% of cases inconclusive. To our knowledge, this is the first PE diagnostic model from non-contrast 4DCT, showing the feasibility of non-contrast PE diagnosis strategies.

Identifiers

PMID42082648
PMCPMC13139421

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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.