Automated screening of metabolic disorders using pattern recognition of GC-MS full scan spectra from urine organic acids

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Title Automated screening of metabolic disorders using pattern recognition of GC-MS full scan spectra from urine organic acids
Publication Type thesis
School or College School of Medicine
Department Biomedical Informatics
Author Crockett, David K.
Date 2002-08
Description Analysis of organic acids in urine is a valuable tool in the diagnosis of the inborn errors of metabolism known as organic acidurias. This test is commonly ordered in newborns with symptoms such as lethargy, failure to thrive, hepatic failure, and suspected familial disorders. A drawback of published methods is the overwhelming amount of data to examine for each patient, prior to the final laboratory report. Physicians will wait as long as two weeks for these time critical results. The goal of this research was to develop and export system to automate the process of screening for metabolic disorders of urine organic acids. The Xaminer® pattern recognition software (ThermoFinnigan, San Jose, CA) was adapted to predict and identify patterns of urine organic acid disorders. The gas chromatography-mass spectrometry (GC-MS) full scan spectra of organic acids were used to build the pattern match library and train the software to recognized methylmalonic aciduria (MMA) and associated vitamin B12 deficiency, as well as, a subset of fatty acid oxidation defects (FAOD), including medium chain acyl-CoA dehydrogenase (MCAD) deficiency. Patient data files were de-identified and reprocessed using the expert system. The expert system results were compared to the original laboratory findings. From a total of 2573 samples, the original laboratory findings were 20 positives for MMA and 29 positives for FAOD. The Xaminer software identified 17 of the 20 MMA positives, plus 4 additional candidate samples that matched the search pattern criteria. The software found 26 of the 29 FAOD positives. Five additional samplers found to be candidates for FAOD. Software analysis time averaged less than 10 seconds per sample. This expert system can use pattern recognition of full scan GC-MS data to aid in patient screening for MMA and fatty acid oxidation disorders. The performance of Xaminer shows promise for refining or expanding the reference library to include other metabolic disorders as well.
Type Text
Publisher University of Utah
Subject Metabolism Errors; Fatty Acid Oxidation Disorders; Urine Organic Acids
Subject MESH Diagnosis; Infant, Newborn; Disease; Automatic Data Processing; Urobilin; Urinalysis
Dissertation Institution University of Utah
Dissertation Name MS
Language eng
Relation is Version of Digital reproduction of "Automated screening of metabolic disorders using pattern recognition of GC-MS full scan spectra from urine organic acids." Spencer S. Eccles Health Sciences Library. Print version of "Automated screening of metabolic disorders using pattern recognition of GC-MS full scan spectra from urine organic acids." available at J. Willard Marriott Library Special Collection. RB6.5 2002 .C76.
Rights Management © David K. Crockett,
Format application/pdf
Format Medium application/pdf
Format Extent 311,844 bytes
Identifier undthes,4710
Source Original: University of Utah Spencer S. Eccles Health Sciences Library (no longer available).
Master File Extent 311,929 bytes
ARK ark:/87278/s6xd13d1
Setname ir_etd
ID 190413
Reference URL https://collections.lib.utah.edu/ark:/87278/s6xd13d1
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