Diagnostic Trial for Tumors Using ^1H-NMR Spectroscopy
| Project/Area Number |
03671112
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Laboratory medicine
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| Research Institution | Iwate Medical University |
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Principal Investigator |
YOSHIOKA Yoshichika Iwate Medical University, 2nd Department of Physiology, Lecturer, 医学部, 講師 (00174897)
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| Co-Investigator(Kenkyū-buntansha) |
TAMAKAWA Yoshiharu Iwate Medical University, Center for Radiological Science, Professor, 医学部, 教授 (30006770)
YASUDA Naoki Iwate Medical University, 2nd Department of Physiology, Professor, 医学部, 教授 (20201824)
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| Project Period (FY) |
1991 – 1992
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| Project Status |
Completed (Fiscal Year 1992)
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| Budget Amount *help |
¥200,000 (Direct Cost: ¥200,000)
Fiscal Year 1992: ¥200,000 (Direct Cost: ¥200,000)
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| Keywords | Magnetic Resonance Spectroscopy / Brain Tumor / Lung Cancer / Differential Diagnosis / Discriminant Analysis / NMR / Tissue Characterization / Pattern Recognition / NMR / magnetic resonance spectroscopy / brain tumor / lung cancer / differential diagnosis / tissue characterization / discriminant analysis / pattern recognition |
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| Research Abstract |
Proton nuclear magnetic resonance (NMR) spectroscopy was employed to examine the correlation between the NMR spectral patterns and histological types and/or the degree of differentiation of human brain tumors and lung cancers. Among several substances clearly identified in the spectra of both normal and tumor tissues, the peak areas for cholines, creatines, glycine and alanine, and the ratios thereof were Profitably applied as parameters to discriminate different tumor tissues. Discriminant factor analysis was applied to evaluate the predictive value of these parameters. By this analysis it was found that the normal brain and brain tumors could be differentiated with 93% accuracy, the three glioma types(low grade astrocytoma, glioblastoma, ependymoma) with 80% accuracy, and meningioma and neurinoma with 100% accuracy. This accuracy corresponds to the probability of classifying a new case into correct tissue type. The normal lung and lung cancer could be differentiated with 91% accuracy, and the four lung cancer types (squamous cell carcinoma, adenocarcinoma, large cell and small cell) with 82% accuracy. When focussing the differential diagnosis between squamous cell carcinoma and adenocarcinoma only, the total correct rate was 95%. These data suggested that NMR spectroscopy might yield clinically useful information and might be applicable to the differential diagnosis of tumors.
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Report
(3 results)
Research Products
(12 results)
