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.

Background: The use of rigid multi-exponential models (with a priori predefined numbers of components) is common practice for diffusion-weighted MRI (DWI) analysis of the kidney. This approach may not accurately reflect renal microstructure, as the data are forced to conform to the a priori assumptions of simplified models. This work examines the feasibility of less constrained, data-driven non-negative least squares (NNLS) continuum modelling for DWI of the kidney tubule system in simulations that include emulations of pathophysiological conditions.Methods: Non-linear least squares (LS) fitting was used as reference for the simulations. For performance assessment, a threshold of 5% or 10% for the mean absolute percentage error (MAPE) of NNLS and LS results was used. As ground truth, a tri-exponential model using defined volume fractions and diffusion coefficients for each renal compartment (tubule system: D tubules , f tubules ; renal tissue: D tissue , f tissue ; renal blood: D blood , f blood ;) was applied. The impact of: (I) signal-to-noise ratio (SNR) =40-1,000, (II) number of b-values (n=10-50), (III) diffusion weighting (b-range small =0-800 up to b-range large =0-2,180 s/mm 2 ), and (IV) fixation of the diffusion coefficients D tissue and D blood was examined. NNLS was evaluated for baseline and pathophysiological conditions, namely increased tubular volume fraction (ITV) and renal fibrosis (10%: grade I, mild) and 30% (grade II, moderate).Results: NNLS showed the same high degree of reliability as the non-linear LS. MAPE of the tubular volume fraction (f tubules ) decreased with increasing SNR. Increasing the number of b-values was beneficial for f tubules precision. Using the b-range large led to a decrease in MAPE ftubules compared to b-range small . The use of a medium b-value range of b=0-1,380 s/mm 2 improved f tubules precision, and further b max increases beyond this range yielded diminishing improvements. Fixing D blood and D tissue significantly reduced MAPE ftubules and provided near perfect distinction between baseline and ITV conditions. Without constraining the number of renal compartments in advance, NNLS was able to detect the (fourth) fibrotic compartment, to differentiate it from the other three diffusion components, and to distinguish between 10% vs. 30% fibrosis.Conclusions: This work demonstrates the feasibility of NNLS modelling for DWI of the kidney tubule

BackgroundGlioblastoma multiforme is the most common and most aggressive malign brain tumor. The 5-year survival rate after tumor resection and adjuvant chemoradiation is only 10 %, with almost all recurrences occurring in the initially treated site. Attempts to improve local control using a higher radiation dose were not successful so that alternative additive treatments are urgently needed. Given the strong rationale for hyperthermia as part of a multimodal treatment for patients with glioblastoma, non-invasive radio frequency (RF) hyperthermia might significantly improve treatment results.MethodsA non-invasive applicator was constructed utilizing the magnetic resonance (MR) spin excitation frequency for controlled RF hyperthermia and MR imaging in an integrated system, which we refer to as thermal MR. Applicator designs at RF frequencies 300 MHz, 500 MHz and 1GHz were investigated and examined for absolute applicable thermal dose and temperature hotspot size. Electromagnetic field (EMF) and temperature simulations were performed in human voxel models. RF heating experiments were conducted at 300 MHz and 500 MHz to characterize the applicator performance and validate the simulations.ResultsThe feasibility of thermal MR was demonstrated at 7.0 T. The temperature could be increased by ~11 °C in 3 min in the center of a head sized phantom. Modification of the RF phases allowed steering of a temperature hotspot to a deliberately selected location. RF heating was monitored using the integrated system for MR thermometry and high spatial resolution MRI. EMF and thermal simulations demonstrated that local RF hyperthermia using the integrated system is feasible to reach a maximum temperature in the center of the human brain of 46.8 °C after 3 min of RF heating while surface temperatures stayed below 41 °C. Using higher RF frequencies reduces the size of the temperature hotspot significantly.ConclusionThe opportunities and capabilities of thermal magnetic resonance for RF hyperthermia interventions of intracranial lesions are intriguing. Employing such systems as an alternative additive treatment for glioblastoma multiforme might be able to improve local control by “fighting fire with fire”. Interventions are not limited to the human brain and might include temperature driven targeted drug and MR contrast agent delivery and help to understand temperature dependent bio- and physiological processes in-vivo.

Aim Kidney diseases constitute a major health challenge, which requires noninvasive imaging to complement conventional approaches to diagnosis and monitoring. Several renal pathologies are associated with changes in kidney size, offering an opportunity for magnetic resonance imaging (MRI) biomarkers of disease. This work uses dynamic MRI and an automated bean‐shaped model (ABSM) for longitudinal quantification of pathophysiologically relevant changes in kidney size. Methods A geometry‐based ABSM was developed for kidney size measurements in rats using parametric MRI (T2, T2* mapping). The ABSM approach was applied to longitudinal renal size quantification using occlusion of the (a) suprarenal aorta or (b) the renal vein, (c) increase in renal pelvis and intratubular pressure and (d) injection of an X‐ray contrast medium into the thoracic aorta to induce pathophysiologically relevant changes in kidney size. Results The ABSM yielded renal size measurements with accuracy and precision equivalent to the manual segmentation, with >70‐fold time savings. The automated method could detect a ~7% reduction (aortic occlusion) and a ~5%, a ~2% and a ~6% increase in kidney size (venous occlusion, pelvis and intratubular pressure increase and injection of X‐ray contrast medium, respectively). These measurements were not affected by reduced image quality following administration of ferumoxytol. Conclusion Dynamic MRI in conjunction with renal segmentation using an ABSM supports longitudinal quantification of changes in kidney size in pathophysiologically relevant experimental setups mimicking realistic clinical scenarios. This can potentially be instrumental for developing MRI‐based diagnostic tools for various kidney disorders and for gaining new insight into mechanisms of renal pathophysiology.