Evidence map›Paper›PMID 42447445›Full record

ArticleMagnetic resonance in medicine2026

Joint Reconstruction of Multiple b-Values and Multiple Directions for Accelerating Diffusion Kurtosis Imaging.

Jian Lyu, Li Guo, Wen Zhong, Zhongbiao Xu, Hai Zhao, Mingyong Gao, Zhifeng Xu, Zhifeng Chen, Hua Guo

Abstract read
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Article in Magnetic resonance in medicine, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jian LyuDepartment of the Radiation Oncology Physics, Foshan Key Laboratory of Precision Therapy in Oncology and Neurology, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.
Li GuoClinical Research Center, Foshan Key Laboratory of Precision Therapy in Oncology and Neurology, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.ORCID https://orcid.org/0009-0008-9569-3052
Wen ZhongCenter for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China.
Zhongbiao XuDepartment of Radiotherapy, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, Guangdong, China.
Hai ZhaoDepartment of Radiology, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.
Mingyong GaoDepartment of Radiology, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.
Zhifeng XuDepartment of Radiology, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.ORCID https://orcid.org/0000-0002-9198-9031
Zhifeng ChenInstitute of Research and Clinical Innovations, Neusoft Medical Systems Co., Ltd., Hangzhou, Zhejiang, China.
Hua GuoCenter for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0002-0482-1493

Funding

CAS Superconducting Research Project SCZX-0301Fo Shan Shi Zi Chou Jing Fei Lei Ke Ji Chuang Xin Xiang Mu 2520001002972Guangdong Basic and Applied Basic Research Foundation 2024A1515140147GuangDong Province Health Bureau A2024571National Natural Science Foundation of China 62101144National Natural Science Foundation of China 82302297National Natural Science Foundation of China 82572950
6 · The paper itself

Abstract

purposeWhile multishot interleaved echo-planar imaging (iEPI) enables higher resolution diffusion kurtosis imaging (DKI) compared to single-shot EPI, its clinical application is hindered by the lengthy acquisition time. This study proposes a novel model-based reconstruction approach to accelerate iEPI DKI acquisition. THEORY AND

methodsThe proposed model-based framework directly estimates DKI tensors from k-space data through joint reconstruction of all k-space data across multiple b values and diffusion directions. It incorporates the intrinsic DKI signal model as a prior and integrates two key components: (1) total variation (TV) regularization to suppress noise in DKI tensor maps, and (2) a physically relevant (PhyR) constraint to ensure biologically plausible parameter estimates, termed mDKI-TV-PhyR. The performance of mDKI-TV-PhyR is compared with its two variants (mDKI and mDKI-TV) and conventional reconstruction-fitting pipelines using both simulated and in vivo data with 4-fold in-plane undersampling.

resultsCompared to the conventional methods, the proposed mDKI-TV-PhyR method achieves lower RMSE for all DKI parameters. Bland-Altman analysis shows the smallest bias for FA and MK, as well as the narrowest limits of agreement for FA and MD. Compared to mDKI-TV, mDKI-TV-PhyR produces MK maps without "black holes," exhibits improved stability across all DKI parameters, and achieves lower FA bias.

conclusionThe proposed method shows substantial promise for clinical applications where both temporal efficiency and spatial resolution are paramount.

Indexed as

Diffusion Magnetic Resonance ImagingImage EnhancementAlgorithmsBrainComputer SimulationDiffusion Tensor ImagingEcho-Planar Imagingdiffusion kurtosis imaginginterleaved EPI DWImodel‐based reconstructionphysically relevant constrainttotal variation

Identifiers

PMID42447445
PMCPMC13527290

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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.