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Diagnostics
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Brain Imaging
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Brain Imaging

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

Deadline for manuscript submissions: closed (20 July 2019) | Viewed by 42527

Special Issue Editors

Prof. Dr. David Moratal

E-Mail Website
Guest Editor
Department of Electronic Engineering & Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Cami de Vera, s/n, 46022 Valencia, Spain
Interests: medical imaging; image-based biomarkers; magnetic resonance imaging (MRI); neuroimaging; machine learning; texture analysis; brain connectivity; functional MRI; multimodal image analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Santiago Canals

E-Mail Website
Guest Editor
Plasticity of Brain Networks, Cellular and Systems Neurobiology, Instituto de Neurociencias, 03550 San Juan de Alicante, Spain
Interests: magnetic resonance imaging (MRI); neuroimaging; machine learning; brain connectivity; functional MRI; multimodal image analysis; network analysis

Special Issue Information

Dear Colleagues,

Brain imaging or neuroimaging refers to the use of non-invasive or minimally-invasive techniques to either directly or indirectly image the structure or function of the nervous system, being a powerful discipline within medicine, neuroscience, and psychology.

In this Special Issue, we intend to collect experiences of leading scientists and invite front-line researchers and authors to submit original research and review articles on neuroimaging. This Special Issue intends also to be a resource tool for people who are new to the world of brain imaging.

Potential topics of this Special Issue include, but are not limited to, the use of technology as well as novel image processing algorithms to image the nervous system by means of:

  • Head MRI
  • Tensor brain imaging
  • Functional MRI
  • Phase-contrast MRI
  • MR angiography
  • Multimodal imaging

Papers must present novel results, or the advancement of previously published data, and the matter should be dealt with scientific rigor.

Prof. Dr. David Moratal
Dr. Santiago Canals
Guest Editors

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

  • MRI
  • Biomarker
  • Image analysis
  • Medical imaging
  • Head MRI
  • Tensor brain imaging
  • fMRI
  • Functional MRI
  • Phase-contrast MRI
  • MR angiography
  • Multimodal imaging

Published Papers (7 papers)

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Research

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10 pages, 1691 KiB  
Article
Link-Level Functional Connectivity Neuroalterations in Autism Spectrum Disorder: A Developmental Resting-State fMRI Study
by Lluis Borràs-Ferrís, Úrsula Pérez-Ramírez and David Moratal
Diagnostics 2019, 9(1), 32; https://doi.org/10.3390/diagnostics9010032 - 21 Mar 2019
Cited by 15 | Viewed by 5271
Abstract
Autism spectrum disorder (ASD) is a neurological and developmental disorder whose late diagnosis is based on subjective tests. In seeking for earlier diagnosis, we aimed to find objective biomarkers via analysis of resting-state functional MRI (rs-fMRI) images obtained from the Autism Brain Image [...] Read more.
Autism spectrum disorder (ASD) is a neurological and developmental disorder whose late diagnosis is based on subjective tests. In seeking for earlier diagnosis, we aimed to find objective biomarkers via analysis of resting-state functional MRI (rs-fMRI) images obtained from the Autism Brain Image Data Exchange (ABIDE) database. Thus, we estimated brain functional connectivity (FC) between pairs of regions as the statistical dependence between their neural-related blood-oxygen-level-dependent (BOLD) signals. We compared FC of individuals with ASD and healthy controls, matched by age and intelligence quotient (IQ), and split into three age groups (50 children, 98 adolescents, and 32 adults), from a developmental perspective. After estimating the correlation, we observed hypoconnectivities in children and adolescents with ASD between regions belonging to the default mode network (DMN). Concretely, in children, FC decreased between the left middle temporal gyrus and right frontal pole (p = 0.0080), and between the left orbitofrontal cortex and right superior frontal gyrus (p = 0.0144). In adolescents, this decrease was observed between bilateral postcentral gyri (p = 0.0012), and between the right precuneus and right middle temporal gyrus (p = 0.0236). These results help to gain a better understanding of the involved regions on autism and its connection with the affected superior cognitive brain functions. Full article
(This article belongs to the Special Issue Brain Imaging)
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10 pages, 796 KiB  
Article
Evaluation of the Performance of 18F-Fluorothymidine Positron Emission Tomography/Computed Tomography (18F-FLT-PET/CT) in Metastatic Brain Lesions
by Alexandra Nikaki, Vassilios Papadopoulos, Varvara Valotassiou, Roxani Efthymiadou, George Angelidis, Ioannis Tsougos, Vassilios Prassopoulos and Panagiotis Georgoulias
Diagnostics 2019, 9(1), 17; https://doi.org/10.3390/diagnostics9010017 - 26 Jan 2019
Cited by 5 | Viewed by 4739
Abstract
18F-fluorothymidine (18F-FLT) is a radiolabeled thymidine analog that has been reported to help monitor tumor proliferation and has been studied in primary brain tumors; however, knowledge about 18F-FLT positron emission tomography/computed tomography (PET/CT) in metastatic brain lesions is limited. The purpose of this [...] Read more.
18F-fluorothymidine (18F-FLT) is a radiolabeled thymidine analog that has been reported to help monitor tumor proliferation and has been studied in primary brain tumors; however, knowledge about 18F-FLT positron emission tomography/computed tomography (PET/CT) in metastatic brain lesions is limited. The purpose of this study is to evaluate the performance of 18F-FLT-PET/CT in metastatic brain lesions. A total of 20 PET/CT examinations (33 lesions) were included in the study. Semiquantitative analysis was performed: standard uptake value (SUV) with the utilization of SUVmax, tumor-to-background ratio (T/B), SUVpeak, SUV1cm3, SUV0.5cm3, SUV50%, SUV75%, PV50% (volume × SUV50%), and PV75% (volume × SUV75%) were calculated. Sensitivity, specificity, and accuracy for each parameter were calculated. Optimal cutoff values for each parameter were obtained. Using a receiver operating characteristic (ROC) curve analysis, the optimal cutoff values of SUVmax, T/B, and SUVpeak for discriminating active from non-active lesions were found to be 0.615, 4.21, and 0.425, respectively. In an ROC curve analysis, the area under the curve (AUC) is higher for SUVmax (p-value 0.017) compared to the rest of the parameters, while using optimal cutoff T/B shows the highest sensitivity and accuracy. PVs (proliferation × volumes) did not show any significance in discriminating positive from negative lesions. 18F-FLT-PET/CT can detect active metastatic brain lesions and may be used as a complementary tool. Further investigation should be performed. Full article
(This article belongs to the Special Issue Brain Imaging)
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14 pages, 2579 KiB  
Article
Evaluating Functional Connectivity Alterations in Autism Spectrum Disorder Using Network-Based Statistics
by Aitana Pascual-Belda, Antonio Díaz-Parra and David Moratal
Diagnostics 2018, 8(3), 51; https://doi.org/10.3390/diagnostics8030051 - 07 Aug 2018
Cited by 16 | Viewed by 6808
Abstract
The study of resting-state functional brain networks is a powerful tool to understand the neurological bases of a variety of disorders such as Autism Spectrum Disorder (ASD). In this work, we have studied the differences in functional brain connectivity between a group of [...] Read more.
The study of resting-state functional brain networks is a powerful tool to understand the neurological bases of a variety of disorders such as Autism Spectrum Disorder (ASD). In this work, we have studied the differences in functional brain connectivity between a group of 74 ASD subjects and a group of 82 typical-development (TD) subjects using functional magnetic resonance imaging (fMRI). We have used a network approach whereby the brain is divided into discrete regions or nodes that interact with each other through connections or edges. Functional brain networks were estimated using the Pearson’s correlation coefficient and compared by means of the Network-Based Statistic (NBS) method. The obtained results reveal a combination of both overconnectivity and underconnectivity, with the presence of networks in which the connectivity levels differ significantly between ASD and TD groups. The alterations mainly affect the temporal and frontal lobe, as well as the limbic system, especially those regions related with social interaction and emotion management functions. These results are concordant with the clinical profile of the disorder and can contribute to the elucidation of its neurological basis, encouraging the development of new clinical approaches. Full article
(This article belongs to the Special Issue Brain Imaging)
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14 pages, 2678 KiB  
Article
ALTEA: A Software Tool for the Evaluation of New Biomarkers for Alzheimer’s Disease by Means of Textures Analysis on Magnetic Resonance Images
by Carlos López-Gómez, Rafael Ortiz-Ramón, Enrique Mollá-Olmos, David Moratal and For the Alzheimer’s Disease Neuroimaging Initiative
Diagnostics 2018, 8(3), 47; https://doi.org/10.3390/diagnostics8030047 - 19 Jul 2018
Cited by 7 | Viewed by 6571
Abstract
The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has [...] Read more.
The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images. This intuitive tool was used to analyze textures of circular and spherical regions situated in the right and left hippocampi of a cohort of 105 patients: 35 AD patients, 35 patients with early mild cognitive impairment (EMCI) and 35 cognitively normal (CN) subjects. A total of 25 statistical texture parameters derived from the histogram, the Gray-Level Co-occurrence Matrix and the Gray-Level Run-Length Matrix, were extracted from each region and analyzed statistically to study their predictive capacity. Several textural parameters were statistically significant (p < 0.05) when differentiating AD subjects from CN and EMCI patients, which indicates that texture analysis could help to identify the presence of AD. Full article
(This article belongs to the Special Issue Brain Imaging)
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Review

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15 pages, 917 KiB  
Review
The Molecular Effects of Ionizing Radiations on Brain Cells: Radiation Necrosis vs. Tumor Recurrence
by Vincenzo Cuccurullo, Giuseppe Danilo Di Stasio, Giuseppe Lucio Cascini, Gianluca Gatta and Cataldo Bianco
Diagnostics 2019, 9(4), 127; https://doi.org/10.3390/diagnostics9040127 - 24 Sep 2019
Cited by 35 | Viewed by 3901
Abstract
The central nervous system (CNS) is generally resistant to the effects of radiation, but higher doses, such as those related to radiation therapy, can cause both acute and long-term brain damage. The most important results is a decline in cognitive function that follows, [...] Read more.
The central nervous system (CNS) is generally resistant to the effects of radiation, but higher doses, such as those related to radiation therapy, can cause both acute and long-term brain damage. The most important results is a decline in cognitive function that follows, in most cases, cerebral radionecrosis. The essence of radio-induced brain damage is multifactorial, being linked to total administered dose, dose per fraction, tumor volume, duration of irradiation and dependent on complex interactions between multiple brain cell types. Cognitive impairment has been described following brain radiotherapy, but the mechanisms leading to this adverse event remain mostly unknown. In the event of a brain tumor, on follow-up radiological imaging often cannot clearly distinguish between recurrence and necrosis, while, especially in patients that underwent radiation therapy (RT) post-surgery, positron emission tomography (PET) functional imaging, is able to differentiate tumors from reactive phenomena. More recently, efforts have been done to combine both morphological and functional data in a single exam and acquisition thanks to the co-registration of PET/MRI. The future of PET imaging to differentiate between radionecrosis and tumor recurrence could be represented by a third-generation PET tracer already used to reveal the spatial extent of brain inflammation. The aim of the following review is to analyze the effect of ionizing radiations on CNS with specific regard to effect of radiotherapy, focusing the attention on the mechanism underling the radionecrosis and the brain damage, and show the role of nuclear medicine techniques to distinguish necrosis from recurrence and to early detect of cognitive decline after treatment. Full article
(This article belongs to the Special Issue Brain Imaging)
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17 pages, 6093 KiB  
Review
The Seven Deadly Sins of Measuring Brain Structural Connectivity Using Diffusion MRI Streamlines Fibre-Tracking
by Fernando Calamante
Diagnostics 2019, 9(3), 115; https://doi.org/10.3390/diagnostics9030115 - 06 Sep 2019
Cited by 56 | Viewed by 10549
Abstract
There is great interest in the study of brain structural connectivity, as white matter abnormalities have been implicated in many disease states. Diffusion magnetic resonance imaging (MRI) provides a powerful means to characterise structural connectivity non-invasively, by using a fibre-tracking algorithm. The most [...] Read more.
There is great interest in the study of brain structural connectivity, as white matter abnormalities have been implicated in many disease states. Diffusion magnetic resonance imaging (MRI) provides a powerful means to characterise structural connectivity non-invasively, by using a fibre-tracking algorithm. The most widely used fibre-tracking strategy is based on the step-wise generation of streamlines. Despite their popularity and widespread use, there are a number of practical considerations that must be taken into account in order to increase the robustness of streamlines tracking results, particularly when these methods are used to study brain structural connectivity, and the connectome. This review article describes what we consider the ‘seven deadly sins’ of mapping structural connections using diffusion MRI streamlines fibre-tracking, with particular emphasis on ‘sins’ that can be practically avoided and they can have an important impact in the results. It is shown that there are important ‘deadly sins’ to be avoided at every step of the pipeline, such as during data acquisition, during data modelling to estimate local fibre architecture, during the fibre-tracking process itself, and during quantification of the tracking results. The recommendations here are intended to inform users on potential important shortcomings of their current tracking protocols, as well as to guide future users on some of the key issues and decisions that must be faced when designing their processing pipelines. Full article
(This article belongs to the Special Issue Brain Imaging)
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Other

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9 pages, 3376 KiB  
Case Report
Complete and Durable Response to Combined Chemo/Radiation Therapy in EGFR Wild-Type Lung Adenocarcinoma with Diffuse Brain Metastases
by Davide Adriano Santeufemia, Giuseppe Palmieri, Antonio Cossu, Valli De Re, Laura Caggiari, Mariangela De Zorzi, Milena Casula, Maria Cristina Sini, Giovanni Baldino, Maria Filomena Dedola, Giuseppe Corona and Gianmaria Miolo
Diagnostics 2019, 9(2), 42; https://doi.org/10.3390/diagnostics9020042 - 11 Apr 2019
Cited by 1 | Viewed by 3998
Abstract
Most non-small-cell lung cancer (NSCLC) patients are likely to develop brain metastases during the course of their illness. Currently, no consensus on NSCLC patients’ treatment with brain metastasis has been established. Although whole brain radiotherapy prolongs the median survival time of approximately 4 [...] Read more.
Most non-small-cell lung cancer (NSCLC) patients are likely to develop brain metastases during the course of their illness. Currently, no consensus on NSCLC patients’ treatment with brain metastasis has been established. Although whole brain radiotherapy prolongs the median survival time of approximately 4 months, a cisplatin-pemetrexed combination may also represent a potential option in the treatment of asymptomatic NSCLC patients with brain metastases. Herein, we report the case of a non-smoker male patient with multiple, large and diffuse brain metastases from an “epidermal growth factor receptor (EGFR) wild-type” lung adenocarcinoma who underwent an overly aggressive chemo/radiation therapy. This approach led to a complete and durable remission of the disease and to a long survival of up to 58 months from diagnosis of primary tumor. The uncommon course of this metastatic disease induced us to describe its oncological management and to investigate the molecular features of the tumor. Full article
(This article belongs to the Special Issue Brain Imaging)
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