Evidence map›Paper›PMID 38910138›Full record

ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2025

Utility of Thin-slice Fat-suppressed Single-shot T2-weighted MR Imaging with Deep Learning Image Reconstruction as a Protocol for Evaluating the Pancreas.

Ryuji Shimada, Keitaro Sofue, Yoshiko Ueno, Tetsuya Wakayama, Takeru Yamaguchi, Eisuke Ueshima, Akiko Kusaka, Masatoshi Hori, Takamichi Murakami

Abstract read
In one paragraph

Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 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. Utility of Thin-slice Single-shot T2-weighted MR Imaging with Deep Learning Reconstruction as a Protocol for Evaluating Pancreatic Cystic Lesions.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Article
  2. Thin-slice TInsights into imaging · 2025
    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.

Ryuji ShimadaDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Keitaro SofueDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Yoshiko UenoDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Tetsuya WakayamaMR Collaborations and Development, GE Healthcare, Hino, Tokyo, Japan.
Takeru YamaguchiDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Eisuke UeshimaDepartment of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Akiko KusakaCenter for Radiology and Radiation Oncology, Kobe University Hospital, Kobe, Hyogo, Japan.
Masatoshi HoriDepartment 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 the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo T2WI with DLIR for evaluating pancreatic protocol.

methodsThis retrospective study included 42 patients (mean age, 70.2 years) with pancreatic cancer who underwent gadoxetic acid-enhanced MRI. Three fat-suppressed T2WI, including conventional fast-spin echo with 6 mm thickness (FSE 6 mm), single-shot fast-spin echo with 6 mm and 3 mm thickness (SSFSE 6 mm and SSFSE 3 mm), were acquired for each patient. For quantitative analysis, the SNRs of the upper abdominal organs were calculated between images with and without DLIR. The pancreas-to-lesion contrast on DLIR images was also calculated. For qualitative analysis, two abdominal radiologists independently scored the image quality on a 5-point scale in the FSE 6 mm, SSFSE 6 mm, and SSFSE 3 mm with DLIR.

resultsThe SNRs significantly improved among the three T2-weighted images with DLIR compared to those without DLIR in all patients (P < 0.001). The pancreas-to-lesion contrast of SSFSE 3 mm was higher than those of the FSE 6 mm (P < 0.001) and tended to be higher than SSFSE 6 mm (P = 0.07). SSFSE 3 mm had the highest image qualities regarding pancreas edge sharpness, pancreatic duct clarity, and overall image quality, followed by SSFSE 6 mm and FSE 6 mm (P < 0.0001).

conclusionSSFSE 3 mm with DLIR demonstrated significant improvements in SNRs of the pancreas, pancreas-to-lesion contrast, and image quality more efficiently than did SSFSE 6 mm and FSE 6 mm. Thin-slice fat-suppressed single-shot T2WI with DLIR can be easily implemented for pancreatic MR protocol.

Indexed as

Deep LearningImage Processing, Computer-AssistedMagnetic Resonance ImagingPancreasPancreatic NeoplasmsAdipose TissueAgedAged, 80 and overContrast MediaFemaleGadolinium DTPAHumansImage Interpretation, Computer-AssistedMaleMiddle AgedRetrospective StudiesContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPAartificial intelligencemagnetic resonance imagingpancreasT2-weighted

Identifiers

PMID38910138
PMCPMC12406158

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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.