RMI combines image information with spectral data in each pixel to imprint a digital molecular stain, unique to each sample, without the use of reagents. Images are acquired from tissue samples illuminated by a laser in a microscope and then analyzed by chemometric-based classification algorithms.
According to the study, RMI has shown promise in differentiating disease states in tissue, especially in the kidney and prostate.
ChemImage of Pittsburgh currently is conducting and presenting research on how RMI can discriminate between two challenging kidney disease diagnoses -- oncocytoma, a benign condition, and chromophobe renal cell carcinoma, a malignant one -- and predict progression in prostate cancer, where slow-growing prostate cancer is difficult to differentiate from more aggressive forms.
Stanford researchers on path to novel molecular imaging technique, April 10, 2008
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