Google maps for tissues: Multiscale imaging of biological systems and disease

MRI of kidney size matters

OBJECTIVE

To highlight progress and opportunities of measuring kidney size with MRI, and to inspire research into resolving the remaining methodological gaps and unanswered questions relating to kidney size assessment.

MATERIALS AND METHODS

This work is not a comprehensive review of the literature but highlights valuable recent developments of MRI of kidney size.

RESULTS

The links between renal (patho)physiology and kidney size are outlined. Common methodological approaches for MRI of kidney size are reviewed. Techniques tailored for renal segmentation and quantification of kidney size are discussed. Frontier applications of kidney size monitoring in preclinical models and human studies are reviewed. Future directions of MRI of kidney size are explored.

CONCLUSION

MRI of kidney size matters. It will facilitate a growing range of (pre)clinical applications, and provide a springboard for new insights into renal (patho)physiology. As kidney size can be easily obtained from already established renal MRI protocols without the need for additional scans, this measurement should always accompany diagnostic MRI exams. Reconciling global kidney size changes with alterations in the size of specific renal layers is an important topic for further research. Acute kidney size measurements alone cannot distinguish between changes induced by alterations in the blood or the tubular volume fractions-this distinction requires further research into cartography of the renal blood and the tubular volumes.

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification

Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore, this approach holds significant potential in supporting MRI data-driven preclinical investigations into the intricate mechanisms underlying renal pathophysiology. The integration of deep learning algorithms is crucial in achieving rapid and precise segmentation of the kidney from temporally resolved parametric MRI, facilitating the use of kidney size as a meaningful (pre)clinical biomarker for renal disease. To explore this potential, we employed dynamic parametric T2 mapping of the kidney in rats in conjunction with a custom-tailored deep dilated U-Net (DDU-Net) architecture. The architecture was trained, validated, and tested on manually segmented ground truth kidney data, with benchmarking against an analytical segmentation model and a self-configuring no new U-Net. Subsequently, we applied our approach to in vivo longitudinal MRI data, incorporating interventions that emulate clinically relevant scenarios in rats. Our approach achieved high performance metrics, including a Dice coefficient of 0.98, coefficient of determination of 0.92, and a mean absolute percentage error of 1.1% compared with ground truth. The DDU-Net enabled automated and accurate quantification of acute changes in kidney size, such as aortic occlusion (-8% ± 1%), venous occlusion (5% ± 1%), furosemide administration (2% ± 1%), hypoxemia (-2% ± 1%), and contrast agent-induced acute kidney injury (11% ± 1%). This approach can potentially be instrumental for the development of dynamic parametric MRI-based tools for kidney disorders, offering unparalleled insights into renal pathophysiology.

Accurate exclusion of kidney regions affected by susceptibility artifact in blood oxygenation level-dependent (BOLD) images using deep-learning-based segmentation

Susceptibility artifact (SA) is common in renal blood oxygenation level-dependent (BOLD) images, and including the SA-affected region could induce much error in renal oxygenation quantification. In this paper, we propose to exclude kidney regions affected by SA in gradient echo images with different echo times (TE), based on a deep-learning segmentation approach. For kidney segmentation, a ResUNet was trained with 4000 CT images and then tuned with 60 BOLD images. Verified by a Monte Carlo simulation, the presence of SA leads to a bilinear pattern for the segmented area of kidney as function of TE, and the segmented kidney in the image of turning point's TE would exclude SA-affected regions. To evaluate the accuracy of excluding SA-affected regions, we compared the SA-free segmentations by the proposed method against manual segmentation by an experienced user for BOLD images of 35 subjects, and found DICE of 93.9% ± 3.4%. For 10 kidneys with severe SA, the DICE was 94.5% ± 1.7%, for 14 with moderate SA, 92.8% ± 4.7%, and for 46 with mild or no SA, 94.3% ± 3.8%. For the three sub-groups of kidneys, correction of SA led to a decrease of R2* of 8.5 ± 2.8, 4.7 ± 1.8, and 1.6 ± 0.9 s-1, respectively. In conclusion, the proposed method is capable of segmenting kidneys in BOLD images and at the same time excluding SA-affected region in a fully automatic way, therefore can potentially improve both speed and accuracy of the quantification procedure of renal BOLD data.

Reliable kidney size determination by magnetic resonance imaging in pathophysiological settings

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.

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system

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/mm²), 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/mm² 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 system and shows its potential for examining diffusion compartments associated with renal pathophysiology including ITV fraction and different degrees of fibrosis.

Ophthalmic Magnetic Resonance Imaging: Where Are We (Heading To)?

Magnetic resonance imaging of the eye and orbit (MReye) is a cross-domain research field, combining (bio)physics, (bio)engineering, physiology, data sciences and ophthalmology. A growing number of reports document technical innovations of MReye and promote their application in preclinical research and clinical science. Realizing the progress and promises, this review outlines current trends in MReye. Examples of MReye strategies and their clinical relevance are demonstrated. Frontier applications in ocular oncology, refractive surgery, ocular muscle disorders and orbital inflammation are presented and their implications for explorations into ophthalmic diseases are provided. Substantial progress in anatomically detailed, high-spatial resolution MReye of the eye, orbit and optic nerve is demonstrated. Recent developments in MReye of ocular tumors are explored, and its value for personalized eye models derived from machine learning in the treatment planning of uveal melanoma and evaluation of retinoblastoma is highlighted. The potential of MReye for monitoring drug distribution and for improving treatment management and the assessment of individual responses is discussed. To open a window into the eye and into (patho)physiological processes that in the past have been largely inaccessible, advances in MReye at ultrahigh magnetic field strengths are discussed. A concluding section ventures a glance beyond the horizon and explores future directions of MReye across multiple scales, including in vivo electrolyte mapping of sodium and other nuclei. This review underscores the need for the (bio)medical imaging and ophthalmic communities to expand efforts to find solutions to the remaining unsolved problems and technical obstacles of MReye, with the objective to transfer methodological advancements driven by MR physics into genuine clinical value.

Precision 3D-Printed Cell Scaffolds Mimicking Native Tissue Composition and Mechanics

Cellular dynamics are modeled by the 3D architecture and mechanics of the extracellular matrix (ECM) and vice versa. These bidirectional cell-ECM interactions are the basis for all vital tissues, many of which have been investigated in 2D environments over the last decades. Experimental approaches to mimic in vivo cell niches in 3D with the highest biological conformity and resolution can enable new insights into these cell-ECM interactions including proliferation, differentiation, migration, and invasion assays. Here, two-photon stereolithography is adopted to print up to mm-sized high-precision 3D cell scaffolds at micrometer resolution with defined mechanical properties from protein-based resins, such as bovine serum albumin or gelatin methacryloyl. By modifying the manufacturing process including two-pass printing or post-print crosslinking, high precision scaffolds with varying Young's moduli ranging from 7-300 kPa are printed and quantified through atomic force microscopy. The impact of varying scaffold topographies on the dynamics of colonizing cells is observed using mouse myoblast cells and a 3D-lung microtissue replica colonized with primary human lung fibroblast. This approach will allow for a systematic investigation of single-cell and tissue dynamics in response to defined mechanical and bio-molecular cues and is ultimately scalable to full organs.

Where to buy face masks? Survey of applications using Taiwan's open data in the time of coronavirus disease 2019

BACKGROUND

The coronavirus disease 2019 (COVID-19) had spread rapidly since late December 2019. Personal protective equipment was essential to prevent transmission. Owing to shortage of face masks, Taiwan government began to implement quasi rationing on February 6, 2020, by allowing each resident to purchase two masks in seven days. Taiwan National Health Insurance Administration offered online data with real-time updates on face mask availability in all contracted pharmacies and selected local health centers. Based on the open data, numerous software applications quickly emerged to assist the public in finding sales locations efficiently.

METHODS

Up until March 15, 2020, the Public Digital Innovation Space of Taiwan government had recorded 134 software applications of face mask availability, and 24 software applications were excluded due to defect, duplicate, and unavailability. These applications were analyzed according to platform, developer type, and display mode.

RESULTS

Of the 110 valid software applications, 67 (60.9%) applications were deployed on websites, followed by 21 (19.1%) on social networking sites, 19 (17.3%) as mobile applications, and 3 (2.7%) in other modes. Nearly two thirds (n = 70) of applications were developed by individuals, one third (n = 37) by commercial companies, only two applications by central and local governments, and one by a nongovernmental organization. With respect to the display mode, 47 (42.7%) applications adopted map-view only, 41 (37.3%) adopted table-view only, and 19 (17.3%) adopted both modes. Of the remaining three applications, two offered voice user interfaces and one used augmented reality.

CONCLUSION

Taiwan's open data strategy facilitated rapid development of software applications for information dissemination to the public during the COVID-19 crisis. The transparency of real-time data could help alleviate the panic of the public. The collaborative contributions from the grassroots in disasters were priceless treasures.

Probing renal blood volume with magnetic resonance imaging

Damage to the kidney substantially reduces life expectancy. Renal tissue hypoperfusion and hypoxia are key elements in the pathophysiology of acute kidney injury and its progression to chronic kidney disease. In vivo assessment of renal haemodynamics and tissue oxygenation remains a challenge. Blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) is sensitive to changes in the effective transversal relaxation time (T₂ *) in vivo, and is non-invasive and indicative of renal tissue oxygenation. However, the renal T₂ * to tissue pO₂ relationship is not governed exclusively by renal blood oxygenation, but is affected by physiological confounders with alterations in renal blood volume fraction (BVf) being of particular relevance. To decipher this interference probing renal BVf is essential for the pursuit of renal MR oximetry. Superparamagnetic iron oxide nanoparticle (USPIO) preparations can be used as MRI visible blood pool markers for detailing alterations in BVf. This review promotes the opportunities of MRI-based assessment of renal BVf. Following an outline on the specifics of renal oxygenation and perfusion, changes in renal BVf upon interventions and their potential impact on renal T₂ * are discussed. We also describe the basic principles of renal BVf assessment using ferumoxytol-enhanced MRI in the equilibrium concentration regimen. We demonstrate that ferumoxytol does not alter control of renal haemodynamics and oxygenation. Preclinical applications of ferumoxytol enhanced renal MRI as well as considerations for its clinical implementation for examining renal BVf changes are provided alongside practical considerations. Finally, we explore the future directions of MRI-based assessment of renal BVf.