Evidence map›Paper›PMID 42021109›Full record

ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2026

Image Quality and Diagnostic Performance of Accelerated T2-weighted Imaging of Prostate with Deep Learning Reconstruction: A Comparative Study.

Daigo Kobayashi, Yoshiko Ueno, Takahiro Tsuboyama, Shintaro Horii, Naoya Ebisu, Keitaro Sofue, Tomoaki Terakawa, Izumi Imaoka, Takamichi Murakami

Abstract readComparative Study
In one paragraph

Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. The Role of MRI in the Clinical Management of Urologic and Nephrological Disorders.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Daigo KobayashiDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.
Yoshiko UenoDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.ORCID http://orcid.org/0000-0003-1785-1234
Takahiro TsuboyamaDepartment of Diagnostic Radiology, Kindai University Faculty of Medicine, Sakai Osaka, Japan.
Shintaro HoriiDivision of Radiological Technology, Department of Radiology, Kobe University Hospital, Kobe Hyogo, Japan.
Naoya EbisuDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.
Keitaro SofueDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.
Tomoaki TerakawaDepartment of Urology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.
Izumi ImaokaDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.
Takamichi MurakamiDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe Hyogo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo compare accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction (DLR-TSE) with conventional T2-weighted TSE (conv-TSE) and accelerated TSE without DLR (non-DLR-TSE), and to evaluate image quality and diagnostic performance of Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1)-based T2 scoring in prostate MRI.

methodsThis single-center retrospective study included 60 patients who underwent prostate MRI with all 3 T2-weighted image sets acquired in the same examination. Qualitative image quality was independently assessed by 2 radiologists using 6 parameters on a 5-point Likert scale. Quantitative metrics included apparent SNR (aSNR), apparent contrast-to-noise ratio (aCNR), and contrast ratio (CR). Diagnostic performance of PI-RADS T2 scores for transition zone lesions was evaluated using receiver operating characteristic (ROC) analysis, sensitivity, specificity, and accuracy. Noninferiority of DLR-TSE relative to conv-TSE was tested with predefined margins. Inter-reader agreement was assessed using weighted kappa statistics.

resultsDLR-TSE demonstrated noninferiority to conv-TSE for all qualitative parameters and quantitative metrics for both readers. Both DLR-TSE and conv-TSE showed significantly higher image quality scores and quantitative values than non-DLR-TSE. For PI-RADS T2 scoring, DLR-TSE achieved diagnostic performance comparable to conv-TSE. For reader 1, the area under the ROC curve (AUC) was identical for DLR-TSE and conv-TSE (0.83; 95%CI 0.69-0.95), and significantly higher than for non-DLR-TSE (0.70; 95%CI 0.56-0.83). Specificity and overall accuracy were markedly reduced with non-DLR-TSE for both readers, whereas sensitivity did not differ significantly among methods. Inter-reader agreement was substantial to almost perfect for DLR-TSE and conv-TSE, and lower for non-DLR-TSE. DLR-TSE reduced acquisition time by approximately 60% compared with conv-TSE.

conclusionAccelerated T2-weighted imaging with DLR allows substantial reduction in scan time while maintaining image quality, diagnostic performance, and inter-reader agreement comparable to those of conventional T2-weighted imaging. DLR-TSE may serve as a practical option for improving examination efficiency in clinical prostate MRI.

Indexed as

Deep LearningImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedMagnetic Resonance ImagingProstateProstatic NeoplasmsAgedAged, 80 and overHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesROC CurveSensitivity and SpecificitySignal-To-Noise Ratioaccelerated imagingdeep learning reconstructionProstate Imaging Reporting and Data System (PI-RADS)prostate magnetic resonance imagingT2-weighted imaging

Identifiers

PMID42021109
PMCPMC13547664

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Registered trials

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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.