ArticleScientific reports2021
The feasibility of deep learning-based synthetic contrast-enhanced CT from nonenhanced CT in emergency department patients with acute abdominal pain.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- [Applications of artificial intelligence in radiology].Radiologie (Heidelberg, Germany) · 2024Pooled it
- Applications of deep learning to reduce the need for iodinated contrast media for CT imaging: a systematic review.International journal of computer assisted radiology and surgery · 2023Pooled it
- Deep learning for synthetic contrast-enhanced CT and MRI: a scoping review.European radiology · 2026Article
- A Task-Prompt-Guided Dual-Decoder Framework with Large Language Models for Multi-Phase Contrast CT Synthesis from Non-Contrast CT.Journal of imaging · 2026Article
- Clinical feasibility and image quality assessment of deep learning-based virtual contrast enhancement from photon-counting computed tomography.Journal of clinical imaging science · 2026Article
- RegGAN-based contrast-free CT enhances esophageal cancer assessment: multicenter validation of automated tumor segmentation and T-staging.La Radiologia medica · 2025Article
- CT-based synthetic iodine map generation using conditional denoising diffusion probabilistic model.Medical physics · 2024Article
- CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model.Physics in medicine and biology · 2024Article
- Clinical feasibility of deep learning based synthetic contrast enhanced abdominal CT in patients undergoing non enhanced CT scans.Scientific reports · 2024Article
- Time conditioning for arbitrary contrast phase generation in interventional computed tomography.Physics in medicine and biology · 2024Article
- Artificial intelligence in interventional radiology: state of the art.European radiology experimental · 2024Review
- Multi-phase synthetic contrast enhancement in interventional computed tomography for guiding renal cryotherapy.International journal of computer assisted radiology and surgery · 2023Article
- Synthetic Post-Contrast Imaging through Artificial Intelligence: Clinical Applications of Virtual and Augmented Contrast Media.Pharmaceutics · 2022Review
- Virtual contrast enhancement for CT scans of abdomen and pelvis.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2022Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our objective was to investigate the feasibility of deep learning-based synthetic contrast-enhanced CT (DL-SCE-CT) from nonenhanced CT (NECT) in patients who visited the emergency department (ED) with acute abdominal pain (AAP). We trained an algorithm generating DL-SCE-CT using NECT with paired precontrast/postcontrast images. For clinical application, 353 patients from three institutions who visited the ED with AAP were included. Six reviewers (experienced radiologists, ER1-3; training radiologists, TR1-3) made diagnostic and disposition decisions using NECT alone and then with NECT and DL-SCE-CT together. The radiologists' confidence in decisions was graded using a 5-point scale. The diagnostic accuracy using DL-SCE-CT improved in three radiologists (50%, P = 0.023, 0.012, < 0.001, especially in 2/3 of TRs). The confidence of diagnosis and disposition improved significantly in five radiologists (83.3%, P < 0.001). Particularly, in subgroups with underlying malignancy and miscellaneous medical conditions (MMCs) and in CT-negative cases, more radiologists reported increased confidence in diagnosis (83.3% [5/6], 100.0% [6/6], and 83.3% [5/6], respectively) and disposition (66.7% [4/6], 83.3% [5/6] and 100% [6/6], respectively). In conclusion, DL-SCE-CT enhances the accuracy and confidence of diagnosis and disposition regarding patients with AAP in the ED, especially for less experienced radiologists, in CT-negative cases, and in certain disease subgroups with underlying malignancy and MMCs.
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