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1.
Diabetes Care ; 47(3): 393-400, 2024 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-38151474

RESUMO

OBJECTIVE: This multicenter prospective cohort study compared pancreas volume as assessed by MRI, metabolic scores derived from oral glucose tolerance testing (OGTT), and a combination of pancreas volume and metabolic scores for predicting progression to stage 3 type 1 diabetes (T1D) in individuals with multiple diabetes-related autoantibodies. RESEARCH DESIGN AND METHODS: Pancreas MRI was performed in 65 multiple autoantibody-positive participants enrolled in the Type 1 Diabetes TrialNet Pathway to Prevention study. Prediction of progression to stage 3 T1D was assessed using pancreas volume index (PVI), OGTT-derived Index60 score and Diabetes Prevention Trial-Type 1 Risk Score (DPTRS), and a combination of PVI and DPTRS. RESULTS: PVI, Index60, and DPTRS were all significantly different at study entry in 11 individuals who subsequently experienced progression to stage 3 T1D compared with 54 participants who did not experience progression (P < 0.005). PVI did not correlate with metabolic testing across individual study participants. PVI declined longitudinally in the 11 individuals diagnosed with stage 3 T1D, whereas Index60 and DPTRS increased. The area under the receiver operating characteristic curve for predicting progression to stage 3 from measurements at study entry was 0.76 for PVI, 0.79 for Index60, 0.79 for DPTRS, and 0.91 for PVI plus DPTRS. CONCLUSIONS: These findings suggest that measures of pancreas volume and metabolism reflect distinct components of risk for developing stage 3 type 1 diabetes and that a combination of these measures may provide superior prediction than either alone.


Assuntos
Diabetes Mellitus Tipo 1 , Humanos , Diabetes Mellitus Tipo 1/diagnóstico , Estudos Prospectivos , Pâncreas/diagnóstico por imagem , Pâncreas/metabolismo , Fatores de Risco , Autoanticorpos , Imageamento por Ressonância Magnética
2.
BMC Med Imaging ; 22(1): 5, 2022 01 05.
Artigo em Inglês | MEDLINE | ID: mdl-34986790

RESUMO

Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). Studies investigating pancreas volume are underway to assess pancreas volume in large clinical databases and studies, but manual pancreas annotation is time-consuming and subjective, preventing extension to large studies and databases. This study develops deep learning for automated pancreas volume measurement in individuals with diabetes. A convolutional neural network was trained using manual pancreas annotation on 160 abdominal magnetic resonance imaging (MRI) scans from individuals with T1D, controls, or a combination thereof. Models trained using each cohort were then tested on scans of 25 individuals with T1D. Deep learning and manual segmentations of the pancreas displayed high overlap (Dice coefficient = 0.81) and excellent correlation of pancreas volume measurements (R2 = 0.94). Correlation was highest when training data included individuals both with and without T1D. The pancreas of individuals with T1D can be automatically segmented to measure pancreas volume. This algorithm can be applied to large imaging datasets to quantify the spectrum of human pancreas volume.


Assuntos
Aprendizado Profundo , Diabetes Mellitus Tipo 1/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Pâncreas/diagnóstico por imagem , Adolescente , Algoritmos , Diabetes Mellitus Tipo 1/patologia , Humanos , Imageamento Tridimensional/métodos , Masculino , Tamanho do Órgão , Pâncreas/patologia , Estudos Retrospectivos
3.
PLoS One ; 16(8): e0256029, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34428220

RESUMO

Magnetic resonance imaging (MRI) has detected changes in pancreas volume and other characteristics in type 1 and type 2 diabetes. However, differences in MRI technology and approaches across locations currently limit the incorporation of pancreas imaging into multisite trials. The purpose of this study was to develop a standardized MRI protocol for pancreas imaging and to define the reproducibility of these measurements. Calibrated phantoms with known MRI properties were imaged at five sites with differing MRI hardware and software to develop a harmonized MRI imaging protocol. Subsequently, five healthy volunteers underwent MRI at four sites using the harmonized protocol to assess pancreas size, shape, apparent diffusion coefficient (ADC), longitudinal relaxation time (T1), magnetization transfer ratio (MTR), and pancreas and hepatic fat fraction. Following harmonization, pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time were reproducible, with coefficients of variation less than 10%. In contrast, non-standardized image processing led to greater variation in MRI measurements. By using a standardized MRI image acquisition and processing protocol, quantitative MRI of the pancreas performed at multiple locations can be incorporated into clinical trials comparing pancreas imaging measures and metabolic state in individuals with type 1 or type 2 diabetes.


Assuntos
Imageamento por Ressonância Magnética/métodos , Imageamento por Ressonância Magnética/normas , Pâncreas/diagnóstico por imagem , Adulto , Imagem de Difusão por Ressonância Magnética/métodos , Feminino , Voluntários Saudáveis , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Imagens de Fantasmas , Estudos Prospectivos , Reprodutibilidade dos Testes
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