Pattern Recognition Methods in 1H MRS Monitoring In Vivo of Normal Appearing Cerebellar Tissue After Treatment of Posterior Fossa Tumors

2009 ◽  
pp. 171-175 ◽  
Author(s):  
Łukasz Boguszewicz ◽  
Sławomir Blamek ◽  
Maria Sokół
Keyword(s):  
Pattern Recognition ◽  
Posterior Fossa ◽  
Posterior Fossa Tumors ◽  
1H Mrs ◽  
Pattern Recognition Methods ◽  
Cerebellar Tissue

Pattern Recognition Methods for Optimizing Multivariate Tissue Signatures in Diagnostic Ultrasound

1986 ◽  
Vol 8 (3) ◽  
pp. 165-180 ◽  
Author(s):  
Michael F. Insana ◽  
Robert F. Wagner ◽  
Brian S. Garra ◽  
Reza Momenan ◽  
Thomas H. Shawker
Keyword(s):  
Pattern Recognition ◽  
Normal Liver ◽  
Classification Performance ◽  
Diagnostic Tools ◽  
Pattern Recognition Methods ◽  
Statistical Pattern ◽  
Diagnostic Modalities ◽  
Cost Of Misclassification ◽  
The Cost

Described is a supervised parametric approach to the detection and classification of disease from acoustic data. Statistical pattern recognition techniques are implemented to design the best ultrasonic tissue signature from a set of measurements and for a given task, and to rate its performance in a way that can be compared with other diagnostic tools. In this paper, we considered combinations of four ultrasonic tissue parameters to discriminate, in vivo, between normal liver and chronic active hepatitis. The separation between normal and diseased samples was made by application of the Bayes decision rule for minimum risk which includes the prior probability for the presence of disease and the cost of misclassification. Large differences in classification performance of various tissue parameter combinations were demonstrated using the Hotelling trace criterion (HTC) and receiver operating characteristic (ROC) analysis. The ability of additional measurements to increase or decrease discriminability, even measurements from other diagnostic modalities, can be evaluated directly in this manner.

scholarly journals FSMP-06. IN VIVO MONITORING OF LDHA EXPRESSION IN GLIOBLASTOMA USING QUANTITATIVE EXCHANGED-LABEL TURNOVER 1H MRS TECHNIQUE

2020 ◽  
Vol 3 (Supplement_1) ◽  
pp. i17-i17
Author(s):  
Puneet Bagga ◽  
Laurie Rich ◽  
Mohammad Haris ◽  
Neil Wilson ◽  
Mitch Schnall ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Lactate Production ◽  
Deuterium Labeling ◽  
1H Mrs ◽  
In Vivo Monitoring ◽  
Lactate Turnover ◽  
Crucial Information ◽  
Specialized Hardware

Abstract Most cancers, including glioblastomas (GBMs), rely extensively on glycolysis to support growth, proliferation, and survival. A hallmark of this elevated glycolysis is overexpression of Lactate dehydrogenase-A (LDHA) protein leading to increased uptake of glucose and overproduction of lactate. Various clinical trials using LDHA as a target for diagnosis and treatment have yielded encouraging results. However, in vivo monitoring of LDHA expression has been challenging due to either requirement of administration of radioactive substrates or specialized hardware. In this presentation, we will demonstrate a new method-quantitative exchanged-label turnover MRS (QELT, or simply qMRS)-that increases the sensitivity of magnetic resonance-based metabolic mapping without the requirement for specialized hardware. qMRS relies on the administration of deuterated (2H-labeled) substrates to track the production of downstream metabolites. Since 2H is invisible on 1H MRS, replacement of 1H with 2H due to metabolic turnover leads to an overall reduction in 1H MRS signal for the corresponding metabolites. We applied our qMRS technique to monitor the rate of lactate production in a preclinical GBM model. Infusion of [6,6’-2H2]glucose led to downstream deuterium labeling of lactate, thereby resulting in a reduction in the 1.33 ppm lactate-CH3 peak on 1H MRS over time. The subtraction of post-administration 1H MR spectra from the pre-infusion spectra aided in the determination of the kinetics of the lactate turnover. We believe that the detection and quantification of lactate production kinetics may provide crucial information regarding tumor LDHA expression non-invasively in GBMs without requiring biopsies. Hence, qMRS is expected to open up new opportunities to probe LDHA expression differences in a variety of gliomas, including GBMs and astrocytomas. This method takes advantage of the universal availability and ease of implementation of 1H MRS on all clinical and preclinical magnetic resonance scanners.

scholarly journals 81 IN VIVO PROTON MAGNETIC RESONANCE SPECTROSCOPY (1H-MRS) IN CYSTIC LEUCOMALACIA OF INFANCY

1994 ◽  
Vol 36 (1) ◽  
pp. 16A-16A
Author(s):  
Floris Groenendaal ◽  
Paula Eken ◽  
Jeroen Van Der Grond ◽  
Karin Rademaker ◽  
Linda S De Vries
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Proton Magnetic Resonance ◽  
Proton Magnetic Resonance Spectroscopy ◽  
Resonance Spectroscopy ◽  
1H Mrs
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