With colleague Nathalie Agar at Boston's Brigham and Women's Hospital, he already has demonstrated the feasibility of grading brain tumors using the lipid profiles they produce in a mass spectrometer (see "Mass Spec Imaging: From Bench to Bedside," scim.ag/1dCjmPx).ag/1dCjmPx
In this work, a methodology is proposed to segment and classify the brain tumor using magnetic resonance images (MRI).
For imaging of the mouse brain tumor using MALDI mass spectrometry, 10 primary human glioblastoma cells (NS276) were stereotactically injected into the right striatum of an 8-week old, NOD/SCID male mouse (Charles River Laboratories) as previously described.
One is a more effective way to deliver drugs to the site of a brain tumor using a catheter.
Detection of brain tumor using a segmentation based approach is critical in cases, where survival of a subject depends on an accurate and timely clinical diagnosis.
Logistic regression and ROC analysis may be useful in the characterization and grading of brain tumors using parametric combinations, however the discrimination accuracy and specificity may be further improved, especially for tumors that present similar histo-pathological profiles, if sophisticated machine learning algorithms are used.
Stereotactic radiosurgery has been in use for several decades in treating brain tumors using a rigid frame fixed to the head to allow precise spatial positioning of target lesions.
RNA samples were prepared from human brain tumors using TRIZOL (Invitrogen, Carlsbad, CA, USA).
Immunoblotting was carried out on 30 samples of brain tumors using SDS-polyacrylamide gel electrophoresis and Western-blotting.
We examined the mRNA and protein expression of human ZIC1, ZIC2, ZIC3, ZIC4 and ZIC5 genes in meningiomas in comparison to other brain tumors, using RT-PCR, analysis of published microarray data, and immunostaining.
