Better performance of cerebral blood volume images synthesized from arterial spin labeling and standard MRI in separating glioblastoma recurrence from treatment response than arterial spin labeling.

Danyang Wu, Yongsheng Pan, Yunxiao Zhou, Cuiyan Wang, Jingzhen He, Jiaxin Xiang, Bao Wang

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Article in Frontiers in oncology, 2025. 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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7 authors.

Danyang WuDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, China.

Yongsheng PanSchool of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, China.

Yunxiao ZhouDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, China.

Cuiyan WangDepartment of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.

Jingzhen HeDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, China.

Jiaxin XiangMR Research Collaboration, Siemens Healthineers Ltd., Shanghai, China.

Bao WangDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebral blood volume (CBV) maps play an important role in the differential diagnosis between glioblastoma recurrence and treatment response. However, it needs high injective velocity. This study aimed to synthesize CBV maps from arterial spin labeling (ASL) and standard MRI sequences using a deep learning method and to validate its discriminating value. A total of 744 MRI scans from 364 patients were included in this retrospective, single-institution study. A three-dimensional (3D) incrementable encoder-decoder network (IEDN) designed for an asymmetrical sample size was trained to synthesize the CBV maps from ASL and the standard MRIs. The synthetic performance was evaluated quantitatively using the structural similarity index (SSIM) and the peak signal-to-noise ratio (PSNR) and qualitatively using a four-point Likert scale (from 0 to 3). In 96 patients suspected of glioblastoma recurrence

Indexed as

arterial spin labelingcerebral blood volumeglioblastomamagnetic resonance imagingtumor recurrence

Identifiers

PMID40978027

DOI10.3389/fonc.2025.1647254

PMCPMC12443552

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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.