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Diagnostics
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Exploring of Diagnostic Approaches in Neuro-Related Diseases
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Exploring of Diagnostic Approaches in Neuro-Related Diseases

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

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 14529

Special Issue Editor

Prof. Dr. Dong-Hoon Lee

E-Mail Website
Guest Editor
1. Department of Radiological Science, College of Health Sciences, Yonsei University, Wonju, Gangwon 26493, Korea
2. Department of Radiation Convergence Engineering, College of Health Sciences, Yonsei University, Wonju, Gangwon 26493, Korea
Interests: neuro-related diseases; neuroimaging; psychiatric disorders; aging; anti-aging; biomarkers; diagnosis; translational research; clinical research

Special Issue Information

Dear Colleagues,

The objective of the Special Issue is to secure diagnostic approaches that are relevant to any neuro-related disease through the observation of qualitative and quantitative investigations. Specifically, it aims to comprehensively cover all aspects of physiatric disorders, aging-/anti-aging-related diseases, and mental disorders and to validate them by emphasizing new diagnostic approaches and applications to preclinical models and clinical cases. In addition, we will specifically focus on the relevance of neuro-related diseases for early detection and the direction of treatment strategies. We welcome the submission of original research articles, review articles, brief communications, or comments on established diagnostic approaches, including novel imaging methods.

Prof. Dr. Dong-Hoon Lee
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

  • neuro-related diseases
  • neuroimaging
  • psychiatric disorders
  • aging
  • anti-aging
  • biomarkers
  • diagnosis
  • translational research
  • clinical research

Published Papers (6 papers)

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Research

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9 pages, 2007 KiB  
Article
Magnetic Resonance Imaging and Spectroscopy Analysis in a Pelizaeus–Merzbacher Disease Rat Model
by Maho Ishikawa, Reika Sawaya, Miki Hirayama, Junpei Ueda and Shigeyoshi Saito
Diagnostics 2022, 12(8), 1864; https://doi.org/10.3390/diagnostics12081864 - 2 Aug 2022
Viewed by 1487
Abstract
Pelizaeus–Merzbacher disease (PMD) is an X-linked recessive disorder of the central nervous system. We performed 7 Tesla magnetic resonance imaging of the brain in Tama rats, a rodent PMD model, and control rats, as well as evaluated the diagnostic values. In the white [...] Read more.
Pelizaeus–Merzbacher disease (PMD) is an X-linked recessive disorder of the central nervous system. We performed 7 Tesla magnetic resonance imaging of the brain in Tama rats, a rodent PMD model, and control rats, as well as evaluated the diagnostic values. In the white matter of the Tama rats, the T2 values were prolonged, which is similar to that observed in patients with PMD (60.7 ± 1.8 ms vs. 51.6 ± 1.3 ms, p < 0.0001). The apparent diffusion coefficient values in the white matter of the Tama rats were higher than those of the control rats (0.68 ± 0.03 × 10−3 mm2/s vs. 0.64 ± 0.03 × 10−3 mm2/s, p < 0.05). In proton magnetic resonance spectroscopy, the N-acetylaspartate (6.97 ± 0.12 mM vs. 5.98 ± 0.25 mM, p < 0.01) and N-acetylaspartate + N-acetylaspartylglutamate values of the Tama rats were higher (8.22 ± 0.17 mM vs. 7.14 ± 0.35 mM, p < 0.01) than those of the control rats. The glycerophosphocholine + phosphocholine values of the Tama rats were lower than those of the control rats (1.04 ± 0.09 mM vs. 1.45 ± 0.04 mM, p < 0.001). By using Luxol fast blue staining, we confirmed dysmyelination in the Tama rats. These results are similar to those of patients with PMD and other PMD animal models. Full article
(This article belongs to the Special Issue Exploring of Diagnostic Approaches in Neuro-Related Diseases)
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12 pages, 2449 KiB  
Article
Challenges in Rare Diseases Diagnostics: Incontinentia Pigmenti with Heterozygous GBA Mutation
by Snežana Minić, Dušan Trpinac, Ivana Novaković, Nataša Cerovac, Danijela Dobrosavljević Vukojević and Jérémie Rosain
Diagnostics 2022, 12(7), 1711; https://doi.org/10.3390/diagnostics12071711 - 14 Jul 2022
Cited by 2 | Viewed by 1642
Abstract
Rare diseases represent a diagnostic challenge due to their number, variety of clinical phenomena, and possibility of a simultaneous presence of two or more diseases. An illustration of this challenge is an occurrence of a late diagnosis of a proband initially diagnosed with [...] Read more.
Rare diseases represent a diagnostic challenge due to their number, variety of clinical phenomena, and possibility of a simultaneous presence of two or more diseases. An illustration of this challenge is an occurrence of a late diagnosis of a proband initially diagnosed with West syndrome, later revealed to be caused by Incontinentia pigmenti (IP). Furthermore, 20 years later, it was discovered that the proband was also a carrier of a heterozygous GBA gene mutation. The methods used in diagnostics were as follows: IKBKG gene analysis, the X-chromosome inactivation assay, analyses of the genes relevant for neurodegeneration, WES analysis, analysis of biochemical parameters typical for Gaucher disease (GD), and autoantibodies including IFN-α2a and IFN-ω. To avoid overlooking IP and other possible rare disease diagnoses, carefully searching for dermatological signs in these conditions is recommended. It is important that the diagnostic criteria are based on quality and extensive data from multiple studies of each rare disease. Establishing precise diagnostic criteria for as many rare diseases as possible and establishing a publicly accessible database of rare diseases with a search possibility according to phenotypic abnormalities and genetic mutations would greatly facilitate and speed up the establishment of an accurate diagnosis. Full article
(This article belongs to the Special Issue Exploring of Diagnostic Approaches in Neuro-Related Diseases)
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15 pages, 3113 KiB  
Article
Prediction of Intraparenchymal Hemorrhage Progression and Neurologic Outcome in Traumatic Brain Injury Patients Using Radiomics Score and Clinical Parameters
by Yun-Ju Shih, Yan-Lin Liu, Jeon-Hor Chen, Chung-Han Ho, Cheng-Chun Yang, Tai-Yuan Chen, Te-Chang Wu, Ching-Chung Ko, Jonathan T. Zhou, Yang Zhang and Min-Ying Su
Diagnostics 2022, 12(7), 1677; https://doi.org/10.3390/diagnostics12071677 - 10 Jul 2022
Cited by 5 | Viewed by 2536
Abstract
(1) Background: Radiomics analysis of spontaneous intracerebral hemorrhages on computed tomography (CT) images has been proven effective in predicting hematoma expansion and poor neurologic outcome. In contrast, there is limited evidence on its predictive abilities for traumatic intraparenchymal hemorrhage (IPH). (2) Methods: A [...] Read more.
(1) Background: Radiomics analysis of spontaneous intracerebral hemorrhages on computed tomography (CT) images has been proven effective in predicting hematoma expansion and poor neurologic outcome. In contrast, there is limited evidence on its predictive abilities for traumatic intraparenchymal hemorrhage (IPH). (2) Methods: A retrospective analysis of 107 traumatic IPH patients was conducted. Among them, 45 patients (42.1%) showed hemorrhagic progression of contusion (HPC) and 51 patients (47.7%) had poor neurological outcome. The IPH on the initial CT was manually segmented for radiomics analysis. After feature extraction, selection and repeatability evaluation, several machine learning algorithms were used to derive radiomics scores (R-scores) for the prediction of HPC and poor neurologic outcome. (3) Results: The AUCs for R-scores alone to predict HPC and poor neurologic outcome were 0.76 and 0.81, respectively. Clinical parameters were used to build comparison models. For HPC prediction, variables including age, multiple IPH, subdural hemorrhage, Injury Severity Score (ISS), international normalized ratio (INR) and IPH volume taken together yielded an AUC of 0.74, which was significantly (p = 0.022) increased to 0.83 after incorporation of the R-score in a combined model. For poor neurologic outcome prediction, clinical variables of age, Glasgow Coma Scale, ISS, INR and IPH volume showed high predictability with an AUC of 0.92, and further incorporation of the R-score did not improve the AUC. (4) Conclusion: The results suggest that radiomics analysis of IPH lesions on initial CT images has the potential to predict HPC and poor neurologic outcome in traumatic IPH patients. The clinical and R-score combined model further improves the performance of HPC prediction. Full article
(This article belongs to the Special Issue Exploring of Diagnostic Approaches in Neuro-Related Diseases)
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Review

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15 pages, 1864 KiB  
Review
Role of Diffusion Tensor Imaging in the Diagnosis of Traumatic Axonal Injury in Individual Patients with a Concussion or Mild Traumatic Brain Injury: A Mini-Review
by Sung-Ho Jang and Min-Jye Cho
Diagnostics 2022, 12(7), 1580; https://doi.org/10.3390/diagnostics12071580 - 29 Jun 2022
Viewed by 2313
Abstract
Present review paper aims to understand role of diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) in diagnosis of traumatic axonal injury (TAI), induced by head trauma, in individual patients with a concussion or mild traumatic brain injury (mTBI). Precise information on [...] Read more.
Present review paper aims to understand role of diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) in diagnosis of traumatic axonal injury (TAI), induced by head trauma, in individual patients with a concussion or mild traumatic brain injury (mTBI). Precise information on presence and severity of TAI in brain is necessary for determining appropriate therapeutic strategies. Several hundred DTI-based studies have reported TAI in concussion or mTBI. Majority of these DTI-based studies have been performed in a group of patients, whereas case studies that have reported TAI in individual patients with a concussion or mTBI are fewer. Summary of these DTI-based studies for individual patients is as follows: DTI can be used as a non-invasive tool for determining presence and severity of TAI in individual patients with concussion or mTBI. However, for diagnosis of TAI in an individual patient, several conditions are required to be met: no past history of head trauma, presence of possible conditions for TAI occurrence during head trauma, development of new clinical features after head trauma, and DTI observed abnormality of a neural structure that coincides with a newly developed clinical feature. However, further studies for a more precise diagnosis of TAI in individual patients should be encouraged. Full article
(This article belongs to the Special Issue Exploring of Diagnostic Approaches in Neuro-Related Diseases)
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10 pages, 653 KiB  
Review
Role of Diffusion Tensor Imaging in Diagnosis and Estimation of Shunt Effect for Hydrocephalus in Stroke Patients: A Narrative Review
by Sung-Ho Jang and Min-Jye Cho
Diagnostics 2022, 12(6), 1314; https://doi.org/10.3390/diagnostics12061314 - 25 May 2022
Cited by 1 | Viewed by 1941
Abstract
Hydrocephalus is a dilatation of the brain ventricular system by the accumulation of cerebrospinal fluid within the ventricle caused by impaired cerebrospinal fluid circulation or clearance. A diagnosis of hydrocephalus at the chronic stage of stroke has been mainly made by clinical features [...] Read more.
Hydrocephalus is a dilatation of the brain ventricular system by the accumulation of cerebrospinal fluid within the ventricle caused by impaired cerebrospinal fluid circulation or clearance. A diagnosis of hydrocephalus at the chronic stage of stroke has been mainly made by clinical features and radiologic findings on brain computed tomography and magnetic resonance imaging. On the other hand, it could not determine the effect of hydrocephalus or shunt effect on the periventricular neural structures. By contrast, these effects on the periventricular neural structures can be estimated using diffusion tensor imaging (DTI). This article reviewed 10 DTI-based studies related to the diagnosis and estimation of the shunt effect for hydrocephalus in stroke patients. These studies suggest that DTI could be a useful diagnostic and estimation tool of the shunt effect for hydrocephalus in stroke patients. In particular, some studies suggested that fractional anisotropy value in the periventricular white matter could be a diagnostic biomarker for hydrocephalus. As a result, the role of DTI in diagnosing and estimating the shunt effect for hydrocephalus in stroke patients appears to be promising. However, the number of studies and patients of all reviewed studies were limited (10 studies including a total of 58 stroke patients with heterogenous brain pathologies). Full article
(This article belongs to the Special Issue Exploring of Diagnostic Approaches in Neuro-Related Diseases)
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9 pages, 664 KiB  
Review
Insights into the Anti-Aging Prevention and Diagnostic Medicine and Healthcare
by Seung-Cheol Ok
Diagnostics 2022, 12(4), 819; https://doi.org/10.3390/diagnostics12040819 - 26 Mar 2022
Cited by 4 | Viewed by 4138
Abstract
Aging is an irreversible and natural phenomenon that occurs as a person ages. Anti-aging medicine applies advanced science and medical technology to early detection, prevention, treatment, and reversal of age-related dysfunctions, disorders, and diseases. Therefore, anti-aging diagnostic medicine and healthcare are important factors [...] Read more.
Aging is an irreversible and natural phenomenon that occurs as a person ages. Anti-aging medicine applies advanced science and medical technology to early detection, prevention, treatment, and reversal of age-related dysfunctions, disorders, and diseases. Therefore, anti-aging diagnostic medicine and healthcare are important factors in helping the elderly population lead healthy and active lives. However, it is challenging to diagnose various aging and related diseases accurately through various forms of anti-aging diagnostic medicine and health management. It may not be treated appropriately, so many older people are making various efforts to prevent aging themselves in advance. Therefore, anti-aging medicine and health care have been developed in various forms, from health checkups to alternative medicine and biophysical technology beyond simple clinical medicine, and are being applied to demand the needs of the elderly. This review intends to explore and characterize various applications related to anti-aging medicine and healthcare in the elderly. In addition, economic, medical, and ethical considerations arising from the relationship between the increase in the elderly population and the continuous development of anti-aging medicine can be considered. Full article
(This article belongs to the Special Issue Exploring of Diagnostic Approaches in Neuro-Related Diseases)
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