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Diagnostics
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Brain MRI: Current Development and Applications
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Brain MRI: Current Development and Applications

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1303

Special Issue Editor

Dr. Hung-Chieh Chen

E-Mail Website
Guest Editor
1. Division of Neuroradiology, Department of Radiology, Taichung Veterans General Hospital, Taichung 40705, Taiwan
2. School of Medicine, National Yang-Ming Chiao Tung University, Taipei 11221, Taiwan
Interests: neuroimaging; diagnostic neuroradiology; pediatric neuroradiology; spine images
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the latest advancements in brain MRI technology and its critical applications in modern neurology. We invite manuscripts exploring innovative diagnostic approaches for neurological disorders, including early detection of neurodegenerative diseases, precise tumor characterization, and identification of subtle vascular abnormalities. Of particular interest are studies showcasing novel high-resolution imaging techniques that enhance visualization of brain structures and connectivity. Beyond the advancements in imaging techniques, another pivotal area of interest is the integration of cutting-edge technologies that further enhance the diagnostic capabilities of MRI. We welcome research on the integration of artificial intelligence with MRI, demonstrating improvements in image analysis and diagnostic accuracy. Additionally, we seek contributions highlighting MRI's role in evaluating treatment efficacy. Such research could offer insights into therapeutic responses and guide personalized medical interventions. Join us in exploring how these breakthroughs are reshaping our understanding of brain health, disease management, and treatment optimization. Your research can contribute significantly to this exciting and rapidly evolving field.

Dr. Hung-Chieh Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neuroimaging
  • diagnostic MRI
  • artificial intelligence
  • neurological disorders

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Published Papers (2 papers)

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Research

17 pages, 2173 KB  
Article
AI-Augmented Quantitative MRI Predicts Spontaneous Intracranial Hypotension
by Yi-Jhe Huang, Jyh-Wen Chai, Wen-Hsien Chen, Hung-Chieh Chen and Da-Chuan Cheng
Diagnostics 2025, 15(18), 2339; https://doi.org/10.3390/diagnostics15182339 - 15 Sep 2025
Viewed by 229
Abstract
Background/Objectives: Spontaneous intracranial hypotension (SIH), caused by spinal cerebrospinal fluid (CSF) leakage, commonly presents with orthostatic headache and CSF hypovolemia. While CSF dynamics in the cerebral aqueduct are well studied, alterations in spinal CSF flow remain less defined. We aimed to quantitatively [...] Read more.
Background/Objectives: Spontaneous intracranial hypotension (SIH), caused by spinal cerebrospinal fluid (CSF) leakage, commonly presents with orthostatic headache and CSF hypovolemia. While CSF dynamics in the cerebral aqueduct are well studied, alterations in spinal CSF flow remain less defined. We aimed to quantitatively assess spinal CSF flow at C2 using phase-contrast (PC) MRI enhanced by artificial intelligence (AI) and to evaluate its utility for diagnosing SIH and predicting responses to epidural blood patch (EBP). Methods: We enrolled 31 patients with MRI-confirmed SIH and 26 age- and sex-matched healthy volunteers (HVs). All participants underwent ECG-gated cine PC-MRI at the C2 level and whole-spine MR myelography. AI-based segmentation using YOLOv4 and a pulsatility-based algorithm was used to extract quantitative CSF flow metrics. Between-group comparisons were analyzed using Mann–Whitney U tests, and receiver operating characteristic (ROC) analysis was used to evaluate diagnostic and predictive performance. Results: Compared to HVs, SIH patients showed significantly reduced CSF flow parameters across all metrics, including upward/downward mean flow, peak flow, total flow per cycle, and absolute stroke volume (all p < 0.001). ROC analysis revealed excellent diagnostic accuracy for multiple parameters, particularly downward peak flow (AUC = 0.844) and summation of peak flow (AUC = 0.841). Importantly, baseline CSF flow metrics significantly distinguished patients who required one versus multiple epidural blood patches (EBPs) (all p < 0.001). ROC analysis demonstrated that several parameters achieved near-perfect to perfect accuracy in predicting EBP success, with AUCs up to 1.0 and 100% sensitivity/specificity. Conclusions: AI-enhanced PC-MRI enables the robust, quantitative evaluation of spinal CSF dynamics in SIH. These flow metrics not only differentiate SIH patients from healthy individuals but also predict response to EBP treatment with high accuracy. Quantitative CSF flow analysis may support both diagnosis and personalized treatment planning in SIH. Full article
(This article belongs to the Special Issue Brain MRI: Current Development and Applications)
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16 pages, 3367 KB  
Article
Sound Localization Training and Induced Brain Plasticity: An fMRI Investigation
by Ranjita Kumari, Sukhan Lee, Pradeep Kumar Anand and Jitae Shin
Diagnostics 2025, 15(12), 1558; https://doi.org/10.3390/diagnostics15121558 - 18 Jun 2025
Viewed by 751
Abstract
Background/Objectives: Neuroimaging techniques have been increasingly utilized to explore neuroplasticity induced by various training regimens. Magnetic resonance imaging (MRI) enables to study these changes non-invasively. While visual and motor training have been widely studied, less is known about how auditory training affects brain [...] Read more.
Background/Objectives: Neuroimaging techniques have been increasingly utilized to explore neuroplasticity induced by various training regimens. Magnetic resonance imaging (MRI) enables to study these changes non-invasively. While visual and motor training have been widely studied, less is known about how auditory training affects brain activity. Our objective was to investigate the effects of sound localization training on brain activity and identify brain regions exhibiting significant changes in activation pre- and post-training to understand how sound localization training induces plasticity in the brain. Method: Six blindfolded participants each underwent 30-minute sound localization training sessions twice a week for three weeks. All participants completed functional MRI (fMRI) testing before and after the training. Results: fMRI scans revealed that sound localization training led to increased activation in several cortical areas, including the superior frontal gyrus, superior temporal gyrus, middle temporal gyrus, parietal lobule, precentral gyrus, and postcentral gyrus. These regions are associated with cognitive processes such as auditory processing, spatial working memory, planning, decision-making, error detection, and motor control. Conversely, a decrease in activation was observed in the left middle temporal gyrus, a region linked to language comprehension and semantic memory. Conclusions: These findings suggest that sound localization training enhances neural activity in areas involved in higher-order cognitive functions, spatial attention, and motor execution, while potentially reducing reliance on regions involved in basic sensory processing. This study provides evidence of training-induced neuroplasticity, highlighting the brain’s capacity to adapt through targeted auditory training intervention. Full article
(This article belongs to the Special Issue Brain MRI: Current Development and Applications)
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