Tissue-specific imaging is a robust methodology to differentiate in vivo T1 black holes with advanced multiple sclerosis-induced damage.
AJNR Am J Neuroradiol
; 30(7): 1394-401, 2009 Aug.
Article
en En
| MEDLINE
| ID: mdl-19406765
ABSTRACT
BACKGROUND AND PURPOSE:
Brains of patients with multiple sclerosis (MS) characteristically have "black holes" (BHs), hypointense lesions on T1-weighted (T1W) spin-echo (SE) images. Although conventional MR imaging can disclose chronic BHs (CBHs), it cannot stage the degree of their pathologic condition. Tissue-specific imaging (TSI), a recently introduced MR imaging technique, allows selective visualization of white matter (WM), gray matter (GM), and CSF on the basis of T1 values of classes of tissue. We investigated the ability of TSI-CSF to separate CBHs with longer T1 values, which likely represent lesions containing higher levels of destruction and unbound water. MATERIALS ANDMETHODS:
Eighteen patients with MS, who had already undergone MR imaging twice (24 months apart) on a 1.5T scanner, underwent a 3T MR imaging examination. Images acquired at 1.5T included sequences of precontrast and postcontrast T1W SE, T2-weighted (T2W) SE, and magnetization transfer (MT). Sequences obtained at 3T included precontrast and postcontrast T1W SE, T2W SE, T1 inversion recovery prepared fast spoiled gradient recalled-echo (IR-FSPGR) and TSI. A BH on the 3T-IR-FSPGR was defined as a CBH if seen as a hypointense, nonenhancing lesion with a corresponding T2 abnormality for at least 24 months. CBHs were separated into 2 groups those visible as hyperintensities on TSI-CSF (group A), and those not appearing on the TSI-CSF (group B).RESULTS:
Mean MT ratios of group-A lesions (0.22 +/- 0.06, 0.13-0.35) were lower (F(1,13) = 60.39; P < .0001) than those of group-B lesions (0.32 +/- 0.03, 0.27-0.36).CONCLUSIONS:
Group-A lesions had more advanced tissue damage; thus, TSI is a potentially valuable method for qualitative and objective identification.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
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Encéfalo
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Interpretación de Imagen Asistida por Computador
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Aumento de la Imagen
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Esclerosis Múltiple
Tipo de estudio:
Diagnostic_studies
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Prognostic_studies
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Qualitative_research
Límite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
AJNR Am J Neuroradiol
Año:
2009
Tipo del documento:
Article
País de afiliación:
Estados Unidos