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Assessment of renal function using magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses
BACKGROUND: The incidence of chronic kidney disease (CKD) is high, and is easy to develop into end-stage renal disease (ESRD), which requires kidney dialysis or kidney transplantation. Therefore, we want to explore the clinical value of magnetic resonance quantitative histogram analysis based on spa...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8640904/ https://www.ncbi.nlm.nih.gov/pubmed/34926658 http://dx.doi.org/10.21037/atm-21-2299 |
Sumario: | BACKGROUND: The incidence of chronic kidney disease (CKD) is high, and is easy to develop into end-stage renal disease (ESRD), which requires kidney dialysis or kidney transplantation. Therefore, we want to explore the clinical value of magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses (SLEEK) in assessing renal function in the early stage. METHODS: One hundred and twenty-nine patients underwent abdominal MRI examination, including a coronal SLEEK sequence. The patients were divided into the control group [CG, 47 cases, estimated glomerular filtration rate (eGFR) >90], the mild renal function impairment (mRI) group (48 cases, eGFR =60–90), and the moderate to severe renal function impairment (m-sRI) group (34 cases, eGFR <60). Two experienced radiologists delineated cortex and medulla regions of interest (ROIs) on SLEEK images to obtain cortex and medulla quantitative histogram parameters [Mean, Median, Percentiles (5(th), 10(th), 25(th), 75(th), and 90(th)), Skewness, Kurtosis, and Entropy] using FireVoxel. These histogram parameters were compared by proper statistical methods such as one-way analysis of variance, the χ(2) test, and receiver operating characteristic (ROC) curve analysis. RESULTS: Four histogram parameters (Inhomogeneity(cortex), Skewness(cortex), Kurtosis(medulla), and Entropy(medulla)) differed significantly between the CG and the mRI group. One medulla (Entropy(medulla)) and nine cortex (Mean(cortex), Median(cortex), Kurtosis(cortex), Entropy(cortex), and 5(th), 10(th), 25(th), 75(th), and 90(th) Percentile(cortex)) histogram parameters were significantly different between the m-RI and m-sRI groups. The most relevant parameter to eGFR was Inhomogenity(cortex) (r=−0.450, P<0.001). Inhomogeneity(cortex) had the largest area under the curve (AUC) for differentiating the mRI group from the CG (AUC =0.718; 95% CI: 0.616–0.806), while 25(th) Percentile(cortex) generated the largest AUC (AUC =0.786; 95% CI: 0.681–0.869) for differentiating the mRI and m-sRI groups. CONCLUSIONS: Quantitative histogram parameters based on a SLEEK sequence can be used to supplement renal dysfunction assessment. Cortex histogram parameters are more valuable for evaluating renal function than medulla histogram parameters. |
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