+ HEALTH Rationale and objectives To propose a new imaging biomarker, the pulmonary artery-to-vein volume difference (…± HEALTH Rationale and objectives The international application of artificial intelligence (AI) for lesion detection b…± HEALTH Rationale and objectives To address the challenge of preoperative prediction of synchronous liver metastasis…± HEALTH Objectives To conduct a nationwide survey among professionals working in oncology departments in China to inv…+ HEALTH The utilization of deep convolutional neural networks for the purpose of diagnosing diseases in the skin area…± HEALTH BACKGROUND . Gadolinium-based contrast agents remain essential for MRI but carry risks. Deep learning (DL) me…+ SCIENCE Gas Chromatography is a versatile separation technique widely used in analytical chemistry for constituent de…+ HEALTH Background Intracardiac echocardiography (ICE) facilitates left atrial (LA) reconstruction during atrial fibr…
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TRV-2026-0909Version 1 · Certified

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TRUVACE RECORD VERSION
record: TRV-2026-0909
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-27T06:06:27.402130Z
status: published
lens: g_space
sector: health
headline: Pulmonary Artery-to-Vein Volume Difference: A New Imaging Biomarker for Risk Stratification in Acute Pulmonary Embolism
dek: Rationale and objectives To propose a new imaging biomarker, the pulmonary artery-to-vein volume difference (PAVVD), and evaluate its efficacy in risk stratification of acute pulmonary embolism (APE) compared with traditional computed tomography pulmonary angiography (CTPA) parameters, as well as the impact of chronic pulmonary disease (CPD). Materials and methods This retrospective study included 134 patients with APE (high/intermediate-high risk, n = 46; intermediate-low/low risk, n = 88) from April 2023 to Ma…
gain_title: Automated AI quantification of pulmonary artery-to-vein volume difference achieved the highest discrimination for high/intermediate-high risk acute pulmonary embolism with low missed-diagnosis risk.
problem_title: (none)
trace_subject: (none)
gain_reading: Automated AI quantification of pulmonary artery-to-vein volume difference achieved the highest discrimination for high/intermediate-high risk acute pulmonary embolism with low missed-diagnosis risk.
gain_evidence: PAVVD exhibited the highest AUC (0.89, 95% CI: 0.83-0.95) for identifying high/intermediate-high risk APE
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers retrospectively analyzed 134 acute pulmonary embolism cases from April 2023 to March 2024, using commercial AI software to automatically measure a new biomarker, pulmonary artery-to-vein volume difference, alongside traditional CTPA parameters to stratify high/intermediate-high versus lower risk.

By the August 2026 publication date, the AI-derived PAVVD showed the strongest discriminative performance and net clinical benefit in low-to-moderate risk thresholds, suggesting utility as a complement to existing CTPA measures for emergency triage, though findings remain confined to a single retrospective cohort without prospective validation.
limitation: Retrospective single-cohort design with 134 patients limits generalizability and requires external validation.
tag: Evidence-backed gain
key_points: Retrospective study of 134 patients with APE from April 2023 to March 2024 compared PAVVD against traditional CTPA parameters. | Commercial AI software automatically quantified PAVVD, clot volume, and Qanadli score for analysis. | Decision curve analysis showed PAVVD yielded highest net benefit in low-to-moderate threshold probability range for emergency triage.
rundown: The study evaluated 134 APE patients split into high/intermediate-high risk (n=46) and intermediate-low/low risk (n=88) using commercial AI to quantify PAVVD and traditional CTPA metrics, comparing performance via AUC, sensitivity, specificity, NPV, NLR, and decision curve analysis.

Results reported PAVVD AUC 0.89 (95% CI 0.83-0.95), NPV 0.94 and NLR 0.13 indicating lowest missed diagnosis risk, with a noted crossover effect versus clot volume related to Qanadli score and multivariate regression to assess influence of chronic pulmonary disease.
sources:
- peer_reviewed | Academic Radiology | https://doi.org/10.1016/j.acra.2026.08.007 | 2026-08-25
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