Evidence map›Paper›PMID 37178197›Full record

ArticleEuropean radiology2023

Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time.

Kaori Shiraishi, Takeshi Nakaura, Hiroyuki Uetani, Yasunori Nagayama, Masafumi Kidoh, Naoki Kobayashi, Kosuke Morita, Yuichi Yamahita, Yasuhito Tanaka, Hideo Baba and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.2field-weighted citation impact, top 4% of its field
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

15 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Accelerated Abdominal MRI: A Review of Current Methods and Applications.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Deep Learning-accelerated MRI in Body and Chest.Journal of computer assisted tomography
    Review
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

11 authors at 3 institutions in 1 country.

Kaori ShiraishiDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
Takeshi NakauraDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan. kff00712@nifty.com.ORCID http://orcid.org/0000-0002-9010-0341
Hiroyuki UetaniDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
Yasunori NagayamaDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
Masafumi KidohDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
Naoki KobayashiDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
Kosuke MoritaDepartment of Radiology, Kumamoto University Hospital, Kumamoto, Japan, Honjo 1-1-1, Kumamoto, Japan.
Yuichi YamahitaCanon Medical Systems Corporation, 70-1, Yanagi-Cho, Saiwai-Ku, Kawasaki-Shi, Kanagawa, 212-0015, Japan.
Yasuhito TanakaDepartment of Gastroenterology and Hepatology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Hideo BabaDepartment of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Toshinori HiraiDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
Kumamoto University · JPCanon (Japan) · JPKumamoto University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resonance cholangiopancreatography (MRCP) within a single breath-hold (BH) at 3 T magnetic resonance imaging (MRI).

methodsThis retrospective study included 32 patients with biliary and pancreatic disorders. BH images were reconstructed with and without DLR. The signal-to-noise ratio (SNR), contrast, contrast-to-noise ratio (CNR) between the common bile duct (CBD) and periductal tissues, and full width at half maximum (FWHM) of CBD on 3D-MRCP were evaluated quantitatively. Two radiologists scored image noise, contrast, artifacts, blur, and overall image quality of the three image types using a 4-point scale. Quantitative and qualitative scores were compared using the Friedman test and post hoc Nemenyi test.

resultsThe SNR and CNR were not significantly different when under respiratory gating- and BH-MRCP without DLR. However, they were significantly higher under BH with DLR than under respiratory gating (SNR, p = 0.013; CNR, p = 0.027). The contrast and FWHM of MRCP under BH with and without DLR were lower than those under respiratory gating (contrast, p < 0.001; FWHM, p = 0.015). Qualitative scores for noise, blur, and overall image quality were higher under BH with DLR than those under respiratory gating (blur, p = 0.003; overall, p = 0.008).

conclusionsThe combination of the 3D hybrid profile order technique and DLR is useful for MRCP within a single BH and does not lead to the deterioration of image quality and space resolution at 3 T MRI. CLINICAL RELEVANCE STATEMENT: Considering its advantages, this sequence might become the standard protocol for MRCP in clinical practice, at least at 3.0 T. KEY POINTS: • The 3D hybrid profile order can achieve MRCP within a single breath-hold without a decrease in spatial resolution. • The DLR significantly improved the CNR and SNR of BH-MRCP. • The 3D hybrid profile order technique with DLR reduces the deterioration of image quality in MRCP within a single breath-hold.

Indexed as

Cholangiopancreatography, Magnetic ResonanceDeep LearningHumansImaging, Three-DimensionalMagnetic Resonance ImagingRetrospective StudiesArtificial intelligenceDeep learningFast MR imagingMagnetic resonance cholangiopancreatographyRetrospective studies

Identifiers

PMID37178197
OpenAlexW4376504983

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.