Value of intravoxel incoherent motion for differential diagnosis of renal tumors

Zhu, Qi; Zhu, Wei; Ye, Jing; Wu, Jingtao; Chen, Wenxin; Hao, Zhihua

doi:10.1177/0284185118778884

Cited by 11 publications

(3 citation statements)

References 22 publications

(28 reference statements)

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“…A variety of new MRI techniques, including intravoxel incoherent motion, diffusion kurtosis imaging, texture analysis, arterial spin labelling, and blood oxygenation level-dependent MRI are being investigated for renal mass characterization, evaluation of RCC aggressiveness, and assessment of response to treatment, although validation is needed (122)(123)(124)(125)(126)(127)(128)(129)(130)(131)(132)(133)(134)(135)(136)(137)(138). Proton MR spectroscopy, although computationally demanding, may help in characterizing renal masses, by providing information on their biochemical milieu (139)(140)(141)(142).…”

Section: Future Perspectivesmentioning

confidence: 99%

Cross-sectional imaging assessment of renal masses with emphasis on MRI

et al. 2021

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Magnetic resonance imaging (MRI) is a useful complementary imaging tool for the diagnosis and characterization of renal masses, as it provides both morphologic and functional information. A core MRI protocol for renal imaging should include a T1-weighted sequence with in- and opposed-phase images (or, alternatively with DIXON technique), T2-weighted and diffusion-weighted images as well as a dynamic contrast-enhanced sequence with subtraction images, followed by a delayed post-contrast T1-weighted sequence. The main advantages of MRI over computed tomography include increased sensitivity for contrast enhancement, less sensitivity for detection of calcifications, absence of pseudoenhancement, and lack of radiation exposure. MRI may be applied for renal cystic lesion characterization, differentiation of renal cell carcinoma (RCC) from benign solid renal tumors, RCC histologic grading, staging, post-treatment follow-up, and active surveillance of patients with treated or untreated RCC.

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Section: Future Perspectivesmentioning

confidence: 99%

Cross-sectional imaging assessment of renal masses with emphasis on MRI

et al. 2021

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“…The diagnostic accuracy of standard MRI with opposed-phase and in-phase gradient-echo (GRE) sequences for the differentiation of mf-AML and RCC was poor (11). Accordingly, some functional MRI techniques have been investigated, including diffusion-weighted imaging (DWI) (11)(12)(13)(14)(15)(16), chemical-shift MRI (17,18), diffusion kurtosis imaging (19). However, differentiation of mf-AML from RCC remains challenging due to limitations of low inter-observer agreement and unsatisfactory diagnostic accuracy and specificity.…”

Section: Introductionmentioning

confidence: 99%

MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study

et al. 2022

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ObjectivesStandard magnetic resonance imaging (MRI) techniques are different to distinguish minimal fat angiomyolipoma (mf-AML) with minimal fat from renal cell carcinoma (RCC). Here we aimed to evaluate the diagnostic performance of MRI-based radiomics in the differentiation of fat-poor AMLs from other renal neoplasms.MethodsA total of 69 patients with solid renal tumors without macroscopic fat and with a pathologic diagnosis of RCC (n=50) or mf-AML (n=19) who underwent conventional MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were included. Clinical data including age, sex, tumor location, urine creatinine, and urea nitrogen were collected from medical records. The apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured from renal tumors. We used the ITK-SNAP software to manually delineate the regions of interest on T2-weighted imaging (T2WI) and IVIM-DWI from the largest cross-sectional area of the tumor. We extracted 396 radiomics features by the Analysis Kit software for each MR sequence. The hand-crafted features were selected by using the Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO). Diagnostic models were built by logistic regression analysis. Receiver operating characteristic curve analysis was performed using five-fold cross-validation and the mean area under the curve (AUC) values were calculated and compared between the models to obtain the optimal model for the differentiation of mf-AML and RCC. Decision curve analysis (DCA) was used to evaluate the clinical utility of the models.ResultsClinical model based on urine creatinine achieved an AUC of 0.802 (95%CI: 0.761-0.843). IVIM-based model based on f value achieved an AUC of 0.692 (95%CI: 0.627-0.757). T2WI-radiomics model achieved an AUC of 0.883 (95%CI: 0.852-0.914). IVIM-radiomics model achieved an AUC of 0.874 (95%CI: 0.841-0.907). Combined radiomics model achieved an AUC of 0.919 (95%CI: 0.894-0.944). Clinical-radiomics model yielded the best performance, with an AUC of 0.931 (95%CI: 0.907-0.955). The calibration curve and DCA confirmed that the clinical-radiomics model had a good consistency and clinical usefulness.ConclusionThe clinical-radiomics model may be served as a noninvasive diagnostic tool to differentiate mf-AML with RCC, which might facilitate the clinical decision-making process.

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“…To facilitate the standardization and validation of renal DWI, consensus-based technical recommendations are currently being developed by an international, multidisciplinary group of renal imaging researchers as part of the European Cooperation in Science and Technology (COST) action ‘PARENCHIMA’ (www.renalmri.org). This is motivated by the relevance of renal DWI having been demonstrated in numerous preclinical and clinical studies with applications such as AKI 13 , characterization of renal masses 14 , tumors 15–18 , lesions 19,20 and cysts 21 , as well as the assessment of renal fibrosis 22–25 , allograft pathophysiology 26,27 , diabetic nephropathy 28 , and functional changes in AKI and CKD 29,30 .…”

Section: Introductionmentioning

confidence: 99%

Diffusion-weighted Renal MRI at 9.4 Tesla Using RARE to Improve Anatomical Integrity

Periquito

Paul

Huelnhagen

et al. 2019

Sci Rep

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Diffusion-weighted magnetic resonance imaging (DWI) is a non-invasive imaging technique sensitive to tissue water movement. By enabling a discrimination between tissue properties without the need of contrast agent administration, DWI is invaluable for probing tissue microstructure in kidney diseases. DWI studies commonly make use of single-shot Echo-Planar Imaging (ss-EPI) techniques that are prone to suffering from geometric distortion. The goal of the present study was to develop a robust DWI technique tailored for preclinical magnetic resonance imaging (MRI) studies that is free of distortion and sensitive to detect microstructural changes. Since fast spin-echo imaging techniques are less susceptible to B0 inhomogeneity related image distortions, we introduced a diffusion sensitization to a split-echo Rapid Acquisition with Relaxation Enhancement (RARE) technique for high field preclinical DWI at 9.4 T. Validation studies in standard liquids provided diffusion coefficients consistent with reported values from the literature. Split-echo RARE outperformed conventional ss-EPI, with ss-EPI showing a 3.5-times larger border displacement (2.60 vs. 0.75) and a 60% higher intra-subject variability (cortex = 74%, outer medulla = 62% and inner medulla = 44%). The anatomical integrity provided by the split-echo RARE DWI technique is an essential component of parametric imaging on the way towards robust renal tissue characterization, especially during kidney disease.

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Value of intravoxel incoherent motion for differential diagnosis of renal tumors

Cited by 11 publications

References 22 publications

Cross-sectional imaging assessment of renal masses with emphasis on MRI

Cross-sectional imaging assessment of renal masses with emphasis on MRI

MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study

Diffusion-weighted Renal MRI at 9.4 Tesla Using RARE to Improve Anatomical Integrity

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