Evidence map›Paper›PMID 42762375›Full record

ArticleMagma (New York, N.Y.)2026

Evaluating boost diffusion sampling for improved abdominal imaging using prototype slice-specific shimming method.

Wenwen Fan, Qinglei Shi, Peng Wang, Haolin Qin, Wenbo Cao, Fangqin Gao, Stemmer Alto, Sijie Hu, Lijuan Wan, Peihua Wu and 4 more

Abstract read
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In one paragraph

Article in Magma (New York, N.Y.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

14 authors.

Wenwen Fan *Department of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Qinglei Shi *Chinese University of Hong Kong (Shenzhen) School of Medicine, Shenzhen Research Institute of Big Data, Shenzhen, 518172, China.
Peng Wang *Department of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Haolin QinChinese University of Hong Kong (Shenzhen) School of Medicine, Shenzhen Research Institute of Big Data, Shenzhen, 518172, China.
Wenbo CaoDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Fangqin GaoSiemens Shenzhen Magnetic Resonance, Ltd., Guangdong, 518172, China.
Stemmer AltoSHS AG, Magnetic Resonance, R&D, 91052, Erlangen, Germany.
Sijie HuDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Lijuan WanDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Peihua WuDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Tongsuo LuDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Yu LangDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Renzhi WangChinese University of Hong Kong (Shenzhen) School of Medicine, Shenzhen Research Institute of Big Data, Shenzhen, 518172, China. wangrenzhi@cuhk.edu.cn.
Hongmei ZhangDepartment of Radiology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. 13581968865@163.com.

Funding

Supported by National High Level Hospital Clinical Research Funding and Beijing Hope Run Special Fund of Cancer Foundation of China LC2022B22supported by University Development Fund - Research Start-up Grant UDF01002496
6 · The paper itself

Abstract

objectTo determine whether prototype integrated slice-specific shimming (iShim) diffusion-weighted imaging (DWI) combined with Boost diffusion sampling improves image quality and diagnostic performance for focal liver lesions compared with conventional DWI and alternative iShim sampling schemes. MATERIALS AND

methodsEighty-five patients with focal liver lesions underwent 3T MRI with conventional DWI and iShim-DWI using Boost, flow-compensated (FC), monopolar (Mono), FC with five lobes (FC5), and stimulated echo acquisition mode (Steam) sampling at b-values of 0 and 1000 s/mm². Two radiologists independently scored six image-quality features. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) were measured. Interreader agreement, between-sequence differences, ADC correlations and agreement, and diagnostic performance for differentiating benign from malignant lesions were assessed.

resultsBoost iShim-DWI yielded significantly better artifact, diagnostic-confidence, and total-image-quality scores than all other sequences (p < 0.05) and achieved the highest lesion SNR, liver SNR, and CNR (p < 0.05). Interreader agreement was excellent (ICC = 0.839-0.953). ADC values correlated strongly across sequences (rₛ = 0.812-0.961, p < 0.001). Boost iShim-DWI achieved the highest diagnostic performance (AUC = 0.942; 95% CI 0.897-0.988). Discussion: Boost iShim-DWI improves liver DWI image quality while preserving ADC comparability and may enhance differentiation of benign and malignant focal liver lesions.

Indexed as

Diffusion magnetic resonance imagingImage enhancementIntegrated slice-specific dynamic shimming (iShim)Liver neoplasmsMagnetic resonance imaging

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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.