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Semi-automated rapid quantification of brain vessel density utilizing fluorescent microscopy.
Bohn, Kaci A; Adkins, Chris E; Mittapalli, Rajendar K; Terrell-Hall, Tori B; Mohammad, Afroz S; Shah, Neal; Dolan, Emma L; Nounou, Mohamed I; Lockman, Paul R.
Afiliación
  • Bohn KA; Texas Tech University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Amarillo, TX 79106-1712, USA; Harding University, College of Pharmacy, Department of Pharmaceutical Sciences, Searcy, AR 72149-12230, USA.
  • Adkins CE; Texas Tech University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Amarillo, TX 79106-1712, USA; West Virginia University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Morgantown, WV 26506, USA.
  • Mittapalli RK; Texas Tech University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Amarillo, TX 79106-1712, USA.
  • Terrell-Hall TB; West Virginia University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Morgantown, WV 26506, USA.
  • Mohammad AS; West Virginia University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Morgantown, WV 26506, USA.
  • Shah N; West Virginia University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Morgantown, WV 26506, USA.
  • Dolan EL; West Virginia University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Morgantown, WV 26506, USA.
  • Nounou MI; Texas Tech University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Amarillo, TX 79106-1712, USA; Appalachian College of Pharmacy, Oakwood, VA 24631, USA; Alexandria University, Faculty of Pharmacy, Department of Pharmaceutics, Alexandria, Egypt.
  • Lockman PR; Texas Tech University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Amarillo, TX 79106-1712, USA; West Virginia University Health Sciences Center, School of Pharmacy, Department of Pharmaceutical Sciences, Morgantown, WV 26506, USA. Electronic address: prlockman@
J Neurosci Methods ; 270: 124-131, 2016 09 01.
Article en En | MEDLINE | ID: mdl-27321229
ABSTRACT

BACKGROUND:

Measurement of vascular density has significant value in characterizing healthy and diseased tissue, particularly in brain where vascular density varies among regions. Further, an understanding of brain vessel size helps distinguish between capillaries and larger vessels like arterioles and venules. Unfortunately, few cutting edge methodologies are available to laboratories to rapidly quantify vessel density. NEW

METHOD:

We developed a rapid microscopic method, which quantifies the numbers and diameters of blood vessels in brain. Utilizing this method we characterized vascular density of five brain regions in both mice and rats, in two tumor models, using three tracers.

RESULTS:

We observed the number of sections/mm(2) in various brain regions genu of corpus callosum 161±7, hippocampus 266±18, superior colliculus 300±24, frontal cortex 391±55, and inferior colliculus 692±18 (n=5 animals). Regional brain data were not significantly different between species (p>0.05) or when using different tracers (70kDa and 2000kDa Texas Red; p>0.05). Vascular density decreased (62-79%) in preclinical brain metastases but increased (62%) a rat glioma model. COMPARISON WITH EXISTING

METHODS:

Our values were similar (p>0.05) to published literature. We applied this method to brain-tumors and observed brain metastases of breast cancer to have a ∼2.5-fold reduction (p>0.05) in vessels/mm(2) compared to normal cortical regions. In contrast, vascular density in a glioma model was significantly higher (sections/mm(2) 736±84; p<0.05).

CONCLUSIONS:

In summary, we present a vascular density counting method that is rapid, sensitive, and uses fluorescence microscopy without antibodies.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Reconocimiento de Normas Patrones Automatizadas / Microscopía Fluorescente Límite: Animals / Female / Humans / Male Idioma: En Revista: J Neurosci Methods Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Reconocimiento de Normas Patrones Automatizadas / Microscopía Fluorescente Límite: Animals / Female / Humans / Male Idioma: En Revista: J Neurosci Methods Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos