ArticleData in brief2023
Dataset on renal tumor diameter assessment by multiple observers in normal-dose and low-dose CT.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Uncertainty-Aware Framework for CT Radiation Dose Optimization in the Active Surveillance of Small Renal Masses: Clinical and Radiological Considerations.Diagnostics (Basel, Switzerland) · 2026Article
- Agreement between Routine-Dose and Lower-Dose CT with and without Deep Learning-based Denoising for Active Surveillance of Solid Small Renal Masses: A Multiobserver Study.Radiology. Imaging cancer · 2025Article
- Accuracy and reproducibility are essential in imaging-based size assessment of renal masses: comment on-"Renal mass imaging modalities: does body mass index (BMI) matter?"International urology and nephrology · 2025Article
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 at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computed tomography-based active surveillance is increasingly used to manage small renal tumors, regardless of patient age. However, there is an unmet need for decreasing radiation exposure while maintaining the necessary accuracy and reproducibility in radiographic measurements, allowing for detecting even minor changes in renal mass size. In this article, we present supplementary data from a multiobserver investigation. We explored the accuracy and reproducibility of low-dose CT (75% dose reduction) compared to normal-dose CT in assessing maximum axial renal tumor diameter. Open-access CT datasets from the 2019 Kidney and Kidney Tumor Segmentation Challenge were used. A web-based platform for assessing observer performance was used by six radiologist observers to obtain and provide data on tumor diameters and accompanying viewing settings, in addition to key images of each measurement and an interactive module for exploring diameter measurements. These data can serve as a baseline and inform future studies investigating and validating lower-dose CT protocols for active surveillance of small renal masses.
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.