<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1657-9550</journal-id>
<journal-title><![CDATA[Biosalud]]></journal-title>
<abbrev-journal-title><![CDATA[Biosalud]]></abbrev-journal-title>
<issn>1657-9550</issn>
<publisher>
<publisher-name><![CDATA[Universidad de Caldas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1657-95502018000200059</article-id>
<article-id pub-id-type="doi">10.17151/biosa.2018.17.2.5</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[UNA REVISIÓN DE TÉCNICAS BÁSICAS DE NEUROIMAGEN PARA EL DIAGNÓSTICO DE ENFERMEDADES NEURODEGENERATIVAS]]></article-title>
<article-title xml:lang="en"><![CDATA[A REVIEW OF BASIC NEUROIMAGING TECHNIQUES IN DIAGNOSIS OF NEURODEGENERATIVE DISEASES]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rueda-O.]]></surname>
<given-names><![CDATA[Andrea del Pilar]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Enríquez-S.]]></surname>
<given-names><![CDATA[Luis Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Pontificia Universidad Javeriana  ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Pontificia Universidad Javeriana  ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>07</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>07</month>
<year>2018</year>
</pub-date>
<volume>17</volume>
<numero>2</numero>
<fpage>59</fpage>
<lpage>90</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S1657-95502018000200059&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S1657-95502018000200059&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S1657-95502018000200059&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN Actualmente los trastornos neurodegenerativos representan un grave problema de salud pública con una prevalencia en ascenso mundial, si bien se ha tratado de armonizar criterios de diagnóstico para estas enfermedades, aún existen obstáculos que dificultan su correcta diferenciación, dando lugar a errores posteriores en etapas terapéuticas. El objeto de esta revisión pretende mostrar el potencial de tres técnicas de neuroimagen (tomografía por emisión de positrones, resonancia magnética de difusión, resonancia magnética estructural), en la identificación de biomarcadores que apoyen el proceso diagnóstico, en tres de las afecciones neurodegenerativas más comunes (enfermedad de Alzheimer, deterioro cognitivo leve, demencia frontotemporal). Se realizó una revisión mediante búsqueda electrónica de literatura. Se destaca el uso de bases de datos como ScienceDirect, PubMed, SciELO, IEEE, para localizar información sobre hallazgos estructurales y funcionales representativos y el poder diagnóstico de estas técnicas. Como lo confirman los estudios, las neuroimágenes ponen en evidencia su potencial para el establecimiento de patrones en la diferenciación de trastornos neurodegenerativos. La resonancia magnética estructural permanece como herramienta central de diagnóstico, en la identificación de patrones de atrofia corticales y subcorticales. Por otro lado, los avances en la tomografía por emisión de positrones han abierto la puerta a un diagnóstico ante-mortem, y una identificación preclínica temprana. Asimismo, el enfoque reciente de la resonancia magnética de difusión posibilita la caracterización de la integridad microestructural de la materia blanca cerebral y su relación con el deterioro cognitivo en el contexto de la enfermedad neurodegenerativa. Al integrar información de diferentes dominios se apoya las herramientas clínicamente aceptadas, garantizando mejor precisión del diagnóstico y la predicción de la aparición de la enfermedad. Los resultados demuestran que, a través de enfoques multimodales, colaboraciones multicentro, armonización de las metodologías y parámetros de adquisición, es posible incluir estas herramientas en el arsenal clínico para la identificación de estas enfermedades.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Currently, neurodegenerative disorders represent a serious public health problem, with an increasing prevalence worldwide. Even though there has been an attempt to harmonize the diagnostic criteria for these disorders, there are still obstacles that hinder their correct differentiation, leading to subsequent errors in therapeutic stages. This review aims to demonstrate the potential of three neuroimaging techniques (positron emission tomography, diffusion-weighted magnetic resonance, and structural magnetic resonance) in the identification of discriminating biomarkers that support the diagnostic process in three of the most common neurodegenerative disorders (Alzheimer&#8217;s disease, Mild Cognitive Impairment, frontotemporal dementia). A review was done via an electronic literature search. The use of ScienceDirect, PubMed, SciELO, and IEEE databases to find information on representative structural and functional findings, as well as the diagnostic power of these techniques, is highlighted. As the studies confirm, neuroimages show their potential to establish patterns in the differentiation of neurodegenerative disorders. The structural magnetic resonance remains as a central tool in the identification of cortical and subcortical atrophy patterns. On the other hand, advances in positron emission tomography have enabled not only antemortem diagnosis but also early preclinical identification. Likewise, the recent approach of diffusion magnetic resonance allows to characterizing the microstructural integrity of the cerebral white matter and its relationship with cognitive deterioration in the context of the neurodegenerative disorder. By integrating information from different domains, the clinically accepted tools are supported, guaranteeing better diagnostic accuracy and the prediction of the onset of the disorder. The results show that through multimodal approaches, multicenter collaborations, harmonization of methodologies and acquisition parameters it is possible to include these tools in the clinical repertoire for the identification of these disorders.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[neuroimagen]]></kwd>
<kwd lng="es"><![CDATA[biomarcadores]]></kwd>
<kwd lng="es"><![CDATA[imagen por resonancia magnética]]></kwd>
<kwd lng="es"><![CDATA[imagen de difusión por resonancia magnética]]></kwd>
<kwd lng="es"><![CDATA[tomografía de emisión de positrones]]></kwd>
<kwd lng="es"><![CDATA[enfermedad de Alzheimer]]></kwd>
<kwd lng="es"><![CDATA[deterioro cognitivo leve]]></kwd>
<kwd lng="es"><![CDATA[demencia frontotemporal]]></kwd>
<kwd lng="en"><![CDATA[diagnostic imaging]]></kwd>
<kwd lng="en"><![CDATA[biomarkers]]></kwd>
<kwd lng="en"><![CDATA[magnetic resonance imaging]]></kwd>
<kwd lng="en"><![CDATA[diffusion magnetic resonance imaging]]></kwd>
<kwd lng="en"><![CDATA[positron-emission tomography]]></kwd>
<kwd lng="en"><![CDATA[Alzheimer disease]]></kwd>
<kwd lng="en"><![CDATA[mild cognitive impairment]]></kwd>
<kwd lng="en"><![CDATA[frontotemporal dementia]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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