ArticleInsights into imaging2024
Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion.
Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Artificial intelligence and radiomics in bladder cancer MRI: a scoping review of applications, performance, and barriers to clinical translation.Abdominal radiology (New York) · 2026Article
- Intravoxel incoherent motion imaging with improved image quality by deep learning reconstruction for prediction of lymph-vascular space invasion in patients with cervical cancer.Abdominal radiology (New York) · 2026Article
- Deep learning reconstruction versus conventional parallel imaging for sagittal T2-weighted MRI in cervical cancer: a comparison of acceleration factors.Abdominal radiology (New York) · 2026Article
- Histopathological Basis of Peritumoral Enhancement in Muscle-invasive Bladder Cancer.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- Impact of deep learning-based MRI reconstruction on image quality and apparent diffusion coefficient measurements in patients with intracranial tumors: a prospective intra-individual study.Quantitative imaging in medicine and surgery · 2026Article
- Coronal reduced field-of-view diffusion-weighted imaging improves image quality and T staging of upper tract urothelial carcinoma compared with conventional axial DWI: a retrospective study.Abdominal radiology (New York) · 2026Article
- VI-RADS quality score: development and proposal of a scoring system by the American College of Radiology VI-RADS Steering Committee.European radiology · 2026Article
- Deep learning reconstruction accelerated reduced field-of-view DWI in rectal cancer: mucosa-submucosa-muscularis visualization and T staging.European radiology experimental · 2026Article
- Comparative analysis of image quality and diagnostic performance among SS-EPI, MS-EPI, and rFOV DWI in bladder cancer.Japanese journal of radiology · 2025Article
- Deep Learning-accelerated MRI in Body and Chest.Journal of computer assisted tomographyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS.
methodsEighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOV
resultsThe AUC of the rFOV
conclusionsrFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy. CRITICAL RELEVANCE STATEMENT: The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality. KEY POINTS: Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI.
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.