RESUMO
BACKGROUND: We present a pilot study on the feasibility of the application and advantages of online, noninvasive breath gas analysis (BGA) by proton transfer reaction quadrupole mass spectrometry for the screening of gestational diabetes mellitus (GDM) in 52 pregnant women by means of an oral glucose tolerance test (OGTT). SUBJECTS AND METHODS: We collected and identified samples of end-tidal breath gas from patients during OGTT. Time evolution parameters of challenge-responsive volatile organic compounds (VOCs) in human breath gas were estimated. Multivariate analysis of variance and permutation analysis were used to assess feasibility of BGA as a diagnostic tool for GDM. RESULTS: Standard OGTT diagnosis identified pregnant women as having GDM (n = 8), impaired glucose tolerance (n = 12), and normal glucose tolerance (n = 32); a part of this latter group was further subdivided into a "marginal" group (n = 9) because of a marginal high 1-h or 2-h OGTT value. We observed that OGTT diagnosis (four metabolic groups) could be mapped into breath gas data. The time evolution of oxidation products of glucose and lipids, acetone metabolites, and thiols in breath gas after a glucose challenge was correlated with GDM diagnosis (P = 0.035). Furthermore, basal (fasting) values of dimethyl sulfide and values of methanol in breath gas were inversely correlated with phenotype characteristics such as homeostasis model assessment of insulin resistance index (R = -0.538; P = 0.0002, P(corrected) = 0.0034) and pregestational body mass index (R = -0.433; P = 0.0013, P(corrected) = 0.022). CONCLUSIONS: Noninvasive BGA in challenge response studies was successfully applied to GDM diagnosis and offered an insight into metabolic pathways involved. We propose a new approach to the identification of diagnosis thresholds for GDM screening.
Assuntos
Glicemia/metabolismo , Testes Respiratórios , Diabetes Gestacional/metabolismo , Hemoglobinas Glicadas/metabolismo , Espectrometria de Massas/métodos , Compostos Orgânicos Voláteis/metabolismo , Adulto , Índice de Massa Corporal , Diabetes Gestacional/diagnóstico , Jejum/sangue , Estudos de Viabilidade , Feminino , Teste de Tolerância a Glucose , Humanos , Resistência à Insulina , Programas de Rastreamento , Fenótipo , Projetos Piloto , GravidezRESUMO
A novel strategy to perform tomographic image reconstruction is presented, based on the integration of a priori information about the target image. Such information may come from a different imaging tool or a synthetic model. For a given image quality, providing a priori image information reduces the amount of image information to be reconstructed. According to the data processing inequality this requires less input data or physical measurements, therefore reducing exposure to ionising radiation. A prototype algorithm is described, consisting of a penalized ART where some a priori edge information is encoded in an inhomogeneous, anisotropic smoothing kernel. The algorithm is tested on a 2-dimensional set-up based on the Shepp-Logan phantom.