Evidence map›Paper›PMID 40244478›Full record

ArticleAbdominal radiology (New York)2025

DWI of the rectum with deep learning reconstruction: comparison of PROPELLER, reduced FOV, and conventional DWI.

Shohei Matsumoto, Takahiro Tsuboyama, Hiromitsu Onishi, Koki Kaketaka, Tetsuya Wakayama, Xinzeng Wang, Atsushi Nakamoto, Takashi Ota, Hideyuki Fukui, Toru Honda and 3 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Diffusion MRI of the Body: Beyond PGSE-EPI.Journal of magnetic resonance imaging : JMRI · 2026
    Review
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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

13 authors.

Shohei MatsumotoDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Takahiro TsuboyamaDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan. ttsuboyama@gmail.com.
Hiromitsu OnishiDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Koki KaketakaDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Tetsuya WakayamaGE HealthCare, Tokyo, Japan.
Xinzeng WangGE HealthCare, Texas, USA.
Atsushi NakamotoDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Takashi OtaDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Hideyuki FukuiDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Toru HondaDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Kengo KisoDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Koji ObaInterfaculty Initiative in Information Studies, The University of Tokyo, Tokyo, Japan.
Noriyuki TomiyamaDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo compare the image quality and diagnostic performance of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER), reduced field-of-view (rFOV), and conventional diffusion-weighted imaging (cDWI) combined with deep learning reconstruction (DLR) for evaluating rectal tumors.

methodsThis prospective study included 42 MRI examinations of 38 patients with rectal tumors who underwent initial staging and/or restaging MRI. PROPELLER-DWI, rFOV-DWI, and cDWI obtained with DLR were reviewed by two radiologists and compared for image quality and diagnostic performance for local tumor extent at staging and restaging and response to chemoradiotherapy at restaging.

resultsPROPELLER-DWI had significantly the least artifacts and distortions, but the worst perceptive noise, while rFOV-DWI had significantly the best sharpness for both readers (P < 0.01). For overall image quality and rectal/tumor conspicuity, PROPELLER-DWI and rFOV-DWI were significantly superior to cDWI in both readers (P < 0.01). The incidence of suboptimal image quality was significantly lower with PROPELLER-DWI and rFOV-DWI than with cDWI (5 and 1 patients with PROPELLER-DWI, 14 and 6 with rFOV-DWI, and 29 and 25 with cDWI by the 2 readers, P < 0.01). Although there were no significant differences in the accuracy of staging and restaging among the 3 types of DWI, inter-reader agreement was highest for PROPELLER-DWI (weighted kappa, 0.62-0.71) compared with cDWI (weighted kappa, 0.38-0.52) and rFOV-DWI (weighted kappa, 0.47-0.61).

conclusionsPROPELLER-DWI and rFOV-DWI with DLR may improve the image quality of rectal DWI by reducing artifacts and distortions or increasing sharpness, although the impact on diagnostic accuracy was not significant.

Indexed as

Deep LearningDiffusion Magnetic Resonance ImagingImage EnhancementImage Interpretation, Computer-AssistedRectal NeoplasmsAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedNeoplasm StagingProspective StudiesRectumDeep learning reconstructionDiffusion-weighted imagingMagnetic resonance imagingPeriodically rotated overlapping parallel lines with enhanced reconstructionRectal cancerReduced field-of-view

Identifiers

PMID40244478

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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.