REnal Flow and Microstructure AnisotroPy (REFMAP) MRI in Normal and Peritumoral Renal Tissue

Liu, Andrea L.; Mikheev, Artem; Rusinek, Henry; Huang, William C.; Wysock, James S.; Babb, James S.; Feiweier, Thorsten; Stoffel, David R.; Chandarana, Hersh; Sigmund, Eric E.

doi:10.1002/jmri.25940

Cited by 12 publications

(9 citation statements)

References 37 publications

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“…For each b value range, the maximum and average b values were also computed. Monoexponential DWI studies provided ADC values [20,21,43,[47][48][49][50][51][52][53][54][55][56][57][58][59][60][61], DTI studies provided MD and FA values [29,32,33,38,42,45,[62][63][64][65][66][67][68][69][70][71] and IVIM studies provided D, f and D* values [20,21,28,29,32,42,43,54,55,68,[71][72][73][74][75][76]…”

Section: Literature Review and Data Extractionmentioning

confidence: 99%

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Ljimani

Caroli

Laustsen

et al. 2019

Magn Reson Mater Phy

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101

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Objectives Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization. Materials and methods Reported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ≥ 75% agreement. Results Correlations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65-74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided. Discussion The consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field.

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Section: Literature Review and Data Extractionmentioning

confidence: 99%

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Ljimani

Caroli

Laustsen

et al. 2019

Magn Reson Mater Phy

Self Cite

101

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“…MRI provides important information regarding the renal vascular anatomy, correlation of the tumor with the collecting system, its vicinity to the renal hilum, and the endophytic-exophytic nature of the tumor, which help predict the difficulties of performing a PN (39). Moreover, MRI may provide information regarding intrarenal differences in blood flow, perfusion, oxygenation, and structural properties of kidney tissue (40). If these images could be superimposed real time during robotic PN, similarly to what is done for MRI-fusion prostatic biopsy, guidance during tumor resection would be largely facilitated, allowing exact tumor resection with maximal renal preservation.…”

Section: What the Urologist Expects From A Renal Mrimentioning

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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“…The diffusion (diffusion coefficient, D ) and perfusion parameters (perfusion‐related pseudo‐diffusion coefficient, D * , and perfusion fraction, f ) are typically estimated from IVIM signals using a double‐exponential model with an assumption that the movement of water can be described by hindered diffusion in extravascular tissue and flow in capillary networks . Recent studies have indicated that IVIM‐MRI can detect the direction‐dependent flows in the heart, kidney, skeletal muscle and brain as D * and f in anisotropic capillary networks depend on the direction of the diffusion gradient . The directional sensitivity of the IVIM signal to flow may allow characterization and monitoring of the direction‐dependent flow network in cerebral vasculature, especially in small animal models of ischemia.…”

Section: Introductionmentioning

confidence: 99%

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

et al. 2020

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This study aimed to demonstrate a reliable automatic segmentation method for independently separating reduced diffusion and decreased perfusion areas in ischemic stroke brains using constrained nonnegative matrix factorization (cNMF) pattern recognition in directional intravoxel incoherent motion MRI (IVIM-MRI). First, the feasibility of cNMF-based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for S 0 -normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from S 0 -normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM-MRI experiments (x, y and z diffusion-gradient directions, 20 b values at 7 T) were performed for normal (n = 4), sacrificed (n = 1, no flow) and ischemic stroke models (n = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double-exponential fitting. Consistent with the simulation, the double-exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion-gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF-based pattern recognition.

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REnal Flow and Microstructure AnisotroPy (REFMAP) MRI in Normal and Peritumoral Renal Tissue

Abstract: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Cited by 12 publications

References 37 publications

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

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

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

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