ArticleMedicine2020
Reduced field-of-view diffusion-weighted imaging (DWI) in patients with gastric cancer: Comparison with conventional DWI techniques at 3.0T: A preliminary study.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Radiomics signature for predicting postoperative disease-free survival of patients with gastric cancer: development and validation of a predictive nomogram.Diagnostic and interventional radiology (Ankara, Turkey) · 2022Trial
- Multi-orientation and prone-position ZOOMit diffusion-weighted imaging for predicting T stage in distal gastric cancer.European radiology · 2025Article
- Diffusion-weighted magnetic resonance imaging of the pancreas: A narrative review.World journal of radiology · 2025Review
- Reduced Field-of-view Diffusion-Weighted Magnetic Resonance Imaging for Detecting Early Gastric Cancer: A Pilot Study Comparing Diagnostic Performance with MDCT and fFOV DWI.Current medical imaging · 2025Article
- Synthesizing High b-Value Diffusion-Weighted Imaging of Gastric Cancer Using an Improved Vision Transformer CycleGAN.Bioengineering (Basel, Switzerland) · 2024Article
- Stability and repeatability of diffusion-weighted imaging (DWI) of normal pancreas on 5.0 Tesla magnetic resonance imaging (MRI).Scientific reports · 2023Article
- The different faces of metastatic melanoma in the gastrointestinal tract.Insights into imaging · 2022Review
- The importance of MRI for rectal cancer evaluation.Surgical oncology · 2022Review
- Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T.Scientific reports · 2022Article
- Article
- Diffusion-Weighted Imaging in Oncology: An Update.Cancers · 2020Review
- Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To evaluate the qualitative image quality and quantitative apparent diffusion coefficient (ADC) value of reduced field-of view (rFOV) and full field-of-view (fFOV) diffusion-weighted imaging (DWI) sequences at 3.0 T in patients with gastric cancer.Fifty-three patients (37 males, 16 females; mean age, 63.3 ± 10.3 years) with 60 lesions with gastric cancer who underwent magnetic resonance (MR) scans, including both rFOV-DWI and fFOV-DWI, were retrospectively analyzed. Two observers subjectively evaluated image quality for both the fFOV-DWI and rFOV-DWI sequences regarding the anatomic details, distortion, lesion conspicuity, artifacts, and overall image quality. The mean ADC values of gastric cancer were calculated. The Wilcoxon test and paired samples t test were used. Interobserver agreement was assessed using kappa statistics.The mean scores based on the 2 observers demonstrated significant differences in image quality in terms of anatomic details, distortion, lesion conspicuity, artifacts and overall image quality at both b values between rFOV-DWI and fFOV-DWI (P < .05) in the whole gastric area. rFOV-DWI yielded significantly better scores in image quality at b = 800 seconds/mm (P < .05) in patients with esophagogastric junction cancers, but there were no significant differences in the gastric corpus and gastric antrum region. The mean tumor ADC values of rFOV-DWI were significantly lower than those of fFOV-DWI (1.237 ± 0.228 × 10-3 mm/second vs 1.683 ± 0.322 × 10-3 mm/second, P < .001).rFOV-DWI yielded significantly better image quality (anatomic details, distortion, lesion conspicuity, artifacts, overall image quality) and more accurate ADC measurements than fFOV-DWI did.
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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.