Monoexponential, biexponential, stretched-exponential and kurtosis models of diffusion-weighted imaging in kidney assessment: comparison between patients with primary aldosteronism and healthy controls

Wen, Deying; Xu, Chunsheng; Deng, Liping; Yan, Weijie; Peng, Pengfei; Yue, Xun; Tang, Lu; Xi, Wu; Chen, Tao; Ren, Yan; Sun, Jiayu

doi:10.1007/s00261-023-03833-0

Cited by 2 publications

(5 citation statements)

References 38 publications

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Section: Methodsmentioning

confidence: 99%

“…Based on a previous study [ 33 ], the following six parameters that differed significantly between PA patients and healthy individuals were selected to construct the model: α, FA and Da in the cortex (α_Cortex, FA_Cortex and Da_Cortex) and FA, MD and Dr in the medulla (FA_Medulla, MD_Medulla and Dr_Medulla). (1) Five models based on the classification of the nature of the diffusion parameters were developed: Model_α, Model_FA (including FA_Cortex and FA_Medulla), Model_D (including Da_Cortex, MD_Medulla and Dr_Medulla), Model_DKI (including FA_Cortex, Da_Cortex, FA_Medulla, MD_Medulla and Dr_Medulla) and Model_all parameters (including all six parameters).…”

Section: Methodsmentioning

confidence: 99%

“…The relevant diffusion parameters of the stretched-exponential model and DKI were measured separately using the region of interest (ROI) technique as reported in previous study [33]. The placement of the ROIs is shown in Fig 1 . All the image measurements were performed by two independent observers who had no knowledge of the clinical diagnosis.…”

Section: Image Analysismentioning

confidence: 99%

Section: Regression Models For Differentiating Effectivenessmentioning

confidence: 99%

“…Our previous study [ 33 ] reported significant differences in certain DKI-derived parameters (including FA and Da in the cortex; FA, MD and Dr in the medulla) and a stretched-exponential model-derived parameter (cortical α) between PA patients and healthy control participants. To our knowledge, this is the first study to evaluate the kidneys of PA patients using the stretched-exponential and kurtosis models of DWI.…”

Section: Introductionmentioning

confidence: 99%

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Comparative study of stretched-exponential and kurtosis models of diffusion-weighted imaging in renal assessment to distinguish patients with primary aldosteronism from healthy controls

Wen,

Peng,

Yue

et al. 2024

PLoS ONE

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Purpose To compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment. Materials and methods A total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups. Results A total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively. Conclusion The Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Image Analysismentioning

confidence: 99%

Section: Regression Models For Differentiating Effectivenessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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