The Role of Diffusion-Weighted MRI and Apparent Diffusion Coefficient in Assessment of Diabetic Kidney Disease: Preliminary Experience Study

Osman, Nasr Mohamed M.; Kader, Moustafa Abdel; Nasr, Taghreed A E L Aziz; Sharawy, Mohamed Ahmed; Keryakos, Hesham Kamal Habeeb

doi:10.2147/ijnrd.s254022

Cited by 7 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, for the diagnosis of early and mild fibrosis, using SWE as an example, there is not yet a consensus among centers on the diagnostic threshold of parameters. Eight studies [ 7 , 23 , 26 , 28 , 31 , 34–36 ] utilized MRI techniques to detect RF, and commonly used techniques, such as diffusion-weighted imaging/apparent diffusion coefficient (DWI/ADC), intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and gadolinium-enhanced imaging, were compared with pathological diagnoses to assess the severity of fibrosis. The studies suggested that MRI was more effective in assessing moderate to severe fibrosis.…”

Section: Resultsmentioning

confidence: 99%

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

Wan,

Wang,

et al. 2024

Renal Failure

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

Wan,

Wang,

et al. 2024

Renal Failure

View full text Add to dashboard Cite

“…Li et al evaluated renal blood flow in CKD using arterial spin labeling perfusion, which reported an AUC for cortical blood flow of 0.98 (sensitivity =84.85%, specificity =100%) ( 41 ). A recent study reported that the AUC of mean apparent diffusion coefficient (ADC) values for detecting mild impairment of DKD was 0.93 (sensitivity =100%, specificity =80%) ( 42 ). However, in another study, the AUC for identifying diabetic kidneys from healthy controls using the mean ADC values was only 0.674 (95% CI: 0.560–0.775; sensitivity =52.5%, specificity =80%) ( 43 ).…”

Section: Discussionmentioning

confidence: 99%

Spectral computed tomography parameters could be surrogate imaging markers to detect early perfusion changes in diabetic kidneys

Zheng,

Mu,

Qin

et al. 2023

Quant Imaging Med Surg

View full text Add to dashboard Cite

Background Kidney microvasculopathy is the baseline pathophysiological feature of diabetic kidney disease (DKD). We aimed to evaluate the spectral computed tomography (CT) parameters for detecting renal perfusion changes among diabetic patients. Methods From August 2020 to June 2022, 34 patients (age, 57.7±10.7 years; male, 20) clinically diagnosed with type 2 diabetes mellitus (DM) and 19 DM-free individuals (age, 48.1±16.9 years; male, 12) were selected for analysis. The series participants formed the DM group and control group, respectively. Spectral parameters, including effective atomic number (Z eff ), iodine density (ID), normalized iodine density (NID) and the slope of the energy spectrum curves (λ), between the 2 groups were analyzed using independent samples t -test. Receiver operator characteristic (ROC) curves were used to evaluate the diagnostic performance of spectral parameters for detecting renal perfusion changes. Results The results indicate that in both cortical and medullary phases, the values of Z eff , ID, NID, and λ 40–70 for the renal cortex of the DM group were significantly higher than those in the control group (P<0.05). In the cortex phase, the diagnostic efficacy of cortical spectral CT parameters discriminating DM patients from controls was as follows: the area under ROC curve (AUC) of ID value was 0.816 [95% confidence interval (CI): 0.679–0.921] at the optimal cutoff value 4.14, the AUC of Z eff value was 0.800 (95% CI: 0.668–0.901) at the optimal cutoff value 9.26, the AUC of λ 40–70 value was 0.822 (95% CI: 0.675–0.918) at the optimal cutoff value 8.26, and the AUC of NID value was 0.851 (95% CI: 0.684–0.926) at the optimal cutoff value 0.37. In medullary phase: the AUC of ID value was 0.769 (95% CI: 0.617–0.846) at the optimal cutoff value 5.08, the AUC of Z eff value was 0.763 (95% CI: 0.614–0.837) at the optimal cutoff value 9.58, the AUC of λ 40–70 value was 0.766 (95% CI: 0.617–0.839) at the optimal cutoff value 10.07, and the AUC of NID value was 0.79 (95% CI: 0.623–0.855) at the optimal cutoff value 1.37. Conclusions Spectral CT could serve as an alternative protocol for the early identification of kidney injury in diabetic patients.

show abstract

Multiparametric quantitative renal MRI in children and young adults: comparison between healthy individuals and patients with chronic kidney disease

et al. 2022

View full text Add to dashboard Cite

The Role of Diffusion-Weighted MRI and Apparent Diffusion Coefficient in Assessment of Diabetic Kidney Disease: Preliminary Experience Study

Cited by 7 publications

References 23 publications

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

Noninvasive diagnosis of interstitial fibrosis in chronic kidney disease: a systematic review and meta-analysis

Spectral computed tomography parameters could be surrogate imaging markers to detect early perfusion changes in diabetic kidneys

Multiparametric quantitative renal MRI in children and young adults: comparison between healthy individuals and patients with chronic kidney disease

Contact Info

Product

Resources

About