ArticleQuantitative imaging in medicine and surgery2026
Vendor-agnostic versus vendor-specific boost methods in low-concentration contrast-enhanced computed tomography of the abdomen.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Contrast media-related adverse events pose serious risks, not only due to allergic reactions but also for patients with renal failure, older age, heart failure, and diabetes mellitus. Various efforts have been made to maximize vascular contrast enhancement (CE) using low-concentration contrast media. This study aimed to compare quantitative and qualitative image characteristics between vendor-agnostic and vendor-specific CE boost methods in low-concentration contrast medium settings against standard-concentration contrast medium settings. Methods: This retrospective study including 160 patients compared two concentrations of iodinated contrast media-350 mg I/mL (standard-concentration group) and 270 mg I/mL (low-concentration group) who underwent contrast-enhanced abdominal computed tomography (CT). Vendor-agnostic and vendor-specific boost methods were applied to the CT images of the low-concentration group. Quantitative [image noise, CT attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise power spectrum, and image sharpness] and qualitative (Likert scale rating by two radiologists) measures of image quality were evaluated in abdominal vessels and liver lesions. Results: The present study included 80 patients in the standard-concentration and 80 patients in the low-concentration group, respectively. There were no significant differences in age (P=0.75), sex (P=0.99), and body mass index (P=0.98) between the two groups. Both vendor-agnostic and vendor-specific CE-boost methods significantly reduced image noise (P<0.001) and improved CT attenuation, SNR, and CNR in both vessels and liver lesions (all P<0.001) in the low-concentration group compared to the corresponding values in the standard-concentration group. The vendor-specific boost method was more effective in suppressing high-frequency noise (P<0.001), whereas the vendor-agnostic boost method yielded sharper images (0.31±0.02 Conclusions: Although vendor-agnostic and vendor-specific CE-boost methods effectively enhanced image quality and CT attenuation in low-concentration contrast medium settings, subjective image analysis revealed lower ratings due to increased artificial appearance. The vendor-agnostic method provided superior image sharpness, whereas the vendor-specific method more effectively reduced structured noise and achieved higher subjective ratings for overall image quality, artificial suppression, and natural image appearance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.