Application of DKI and IVIM imaging in evaluating histologic grades and clinical stages of clear cell renal cell carcinoma

Abstract

PurposeTo evaluate the value of quantitative parameters derived from diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in differentiating histologic grades and clinical stages of clear cell renal cell carcinoma (ccRCC).Materials and methodsA total of 65 patients who were surgically and pathologically diagnosed as ccRCC were recruited in this study. In addition to routine renal magnetic resonance imaging examination, all patients underwent preoperative IVIM and DKI. The corresponding diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), kurtosis anisotropy (KA), and mean kurtosis (MK) values were obtained. Independent-samples t-test or Mann–Whitney U test was used for comparing the differences in IVIM and DKI parameters among different histologic grades and clinical stages. The diagnostic efficacy of IVIM and DKI parameters was evaluated using the receiver operating characteristic (ROC) curve. Spearman’s correlation analysis was used to separately analyze the correlation of each parameter with histologic grades and stages of ccRCC.ResultsThe D and MD values were significantly higher in low-grade ccRCC than high-grade ccRCC (all p < 0.001) and in low-stage than high-stage ccRCC (all p < 0.05), and the f value of high-stage ccRCC was lower than that of low-stage ccRCC (p = 0.007). The KA and MK values were significantly higher in low-grade than high-grade ccRCC (p = 0.000 and 0.000, respectively) and in low-stage than high-stage ccRCC (p = 0.000 and 0.000, respectively). The area under the curve (AUC) values of D, D*, f, MD, KA, MK, DKI, and IVIM+DKI values were 0.825, 0.598, 0.626, 0.792, 0.750, 0.754, 0.803, and 0.857, respectively, in grading ccRCC and 0.837, 0.719, 0.710, 0.787, 0.796, 0.784, 0.864, 0.823, and 0.916, respectively, in staging ccRCC. The AUC of IVIM was 0.913 in staging ccRCC. The D, D*, and MD values were negatively correlated with the histologic grades and clinical stages (all p < 0.05), and the KA and MK values showed a positive correlation with histologic grades and clinical stages (all p < 0.05). The f value was also negatively correlated with the ccRCC clinical stage (p = 0.008).ConclusionBoth the IVIM and DKI values can be used preoperatively to predict the degree of histologic grades and stages in ccRCC, and the D and MD values have better diagnostic performance in the grading and staging. Also, further slightly enhanced diagnostic efficacy was observed in the model with combined IVIM and DKI parameters.

Enhancing Diagnostic Precision: Evaluation of Preprocessing Filters in Simple Diffusion Kurtosis Imaging for Head and Neck Tumors

“…Several studies have demonstrated the clinical utility of three-axis imaging for DKI [ 18 , 38 , 39 ], and Rosenkrantz et al [ 39 ], in a review, summarized that three-axis imaging is sufficient for several imaging directions. As for imaging with a lower maximum b-value, several clinical studies have also shown the clinical utility of DKI with a lower maximum b-value [ 14 , 19 , 20 , 40 , 41 ] for clear cell renal cell carcinoma, head and neck cysts and tumors, rectal cancer, and prostate cancer. Clinical studies using a maximum b-value of 800 s/mm 2 for SDI have also shown that DKI is useful for diagnosing head and neck tumors [ 19 ] and cystic diseases [ 20 ].…”

“…Recently, diffusion kurtosis imaging (DKI), a type of restricted diffusion-weighted (RD) imaging, has garnered attention, and its usefulness in the clinical image-based diagnosis of neurodegenerative diseases, ischemic stroke, and tumors has been reported [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ]. Recently, the combination of intravoxel incoherent motion (IVIM) and amide proton transfer-weighted imaging in addition to DKI has been shown to improve the diagnostic performance by predicting lymph node metastasis in cervical cancer [ 13 ], in distinguishing among histological grades and clinical stages in clear cell renal cell carcinoma [ 14 ], and in predicting molecular subtypes in breast cancer [ 15 , 16 ].…”