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Background: A lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences., Purpose: To evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI)., Study Type: Retrospective., Population: Publicly available diffusion atlases, based on 60 healthy women (age 18-45 years) with normal prenatal care, from 23 and 35 weeks of gestation., Field Strength/sequence: 3.0 Tesla/DTI acquired with diffusion-weighted echo planar imaging (EPI)., Assessment: We performed whole-brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small-worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality., Statistical Tests: Linear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. The t-tests were used to assess SW. P-values were corrected using Holm-Bonferroni method. A corrected P-value <0.05 was considered statistically significant., Results: Network analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32-7.37), LE (5.43%/week, 95% CI 3.63-7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes., Data Conclusion: Extensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation., Level of Evidence: 3 TECHNICAL EFFICACY: Stage 2., (© 2023 International Society for Magnetic Resonance in Medicine.)

Complex engineered systems are often equipped with suites of sensors and ancillary devices that monitor their performance and maintenance needs. MRI scanners are no different in this regard. Some of the ancillary devices available to support MRI equipment, the ones of particular interest here, have the distinction of actually participating in the image acquisition process itself. Most commonly, such devices are used to monitor physiological motion or variations in the scanner's imaging fields, allowing the imaging and/or reconstruction process to adapt as imaging conditions change. "Classic" examples include electrocardiography (ECG) leads and respiratory bellows to monitor cardiac and respiratory motion, which have been standard equipment in scan rooms since the early days of MRI. Since then, many additional sensors and devices have been proposed to support MRI acquisitions. The main physical properties that they measure may be primarily "mechanical" (eg acceleration, speed, and torque), "acoustic" (sound and ultrasound), "optical" (light and infrared), or "electromagnetic" in nature. A review of these ancillary devices, as currently available in clinical and research settings, is presented here. In our opinion, these devices are not in competition with each other: as long as they provide useful and unique information, do not interfere with each other and are not prohibitively cumbersome to use, they might find their proper place in future suites of sensors. In time, MRI acquisitions will likely include a plurality of complementary signals. A little like the microbiome that provides genetic diversity to organisms, these devices can provide signal diversity to MRI acquisitions and enrich measurements. Machine-learning (ML) algorithms are well suited at combining diverse input signals toward coherent outputs, and they could make use of all such information toward improved MRI capabilities. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1., (© 2022 International Society for Magnetic Resonance in Medicine.)

Background: Diffusion-weighted MRI (DW-MRI) of the kidneys is a technique that provides information about the microstructure of renal tissue without requiring exogenous contrasts such as gadolinium, and it can be used for diagnosis in cases of renal disease and assessing response-to-therapy. However, physiological motion and large geometric distortions due to main B 0 field inhomogeneities degrade the image quality, reduce the accuracy of quantitative imaging markers, and impede their subsequent clinical applicability., Purpose: To retrospectively correct for geometric distortion for free-breathing DW-MRI of the kidneys at 3T, in the presence of a nonstatic distortion field due to breathing and bulk motion., Study Type: Prospective., Subjects: Ten healthy volunteers (ages 29-38, four females)., Field Strength/sequence: 3T; DW-MR dual-echo echo-planar imaging (EPI) sequence (10 b-values and 17 directions) and a T 2 volume., Assessment: The distortion correction was evaluated subjectively (Likert scale 0-5) and numerically with cross-correlation between the DW images at b = 0 s/mm 2 and a T 2 volume. The intravoxel incoherent motion (IVIM) and diffusion tensor (DTI) model-fitting performance was evaluated using the root-mean-squared error (nRMSE) and the coefficient of variation (CV%) of their parameters., Statistical Tests: Statistical comparisons were done using Wilcoxon tests., Results: The proposed method improved the Likert scores by 1.1 ± 0.8 (P < 0.05), the cross-correlation with the T 2 reference image by 0.13 ± 0.05 (P < 0.05), and reduced the nRMSE by 0.13 ± 0.03 (P < 0.05) and 0.23 ± 0.06 (P < 0.05) for IVIM and DTI, respectively. The CV% of the IVIM parameters (slow and fast diffusion, and diffusion fraction for IVIM and mean diffusivity, and fractional anisotropy for DTI) was reduced by 2.26 ± 3.98% (P = 6.971 × 10 -2 ), 11.24 ± 26.26% (P = 6.971 × 10 -2 ), 4.12 ± 12.91% (P = 0.101), 3.22 ± 0.55% (P < 0.05), and 2.42 ± 1.15% (P < 0.05)., Data Conclusion: The results indicate that the proposed Di + MoCo method can effectively correct for time-varying geometric distortions and for misalignments due to breathing motion. Consequently, the image quality and precision of the DW-MRI model parameters improved., Level of Evidence: 2 TECHNICAL EFFICACY STAGE: 1., (© 2020 International Society for Magnetic Resonance in Medicine.)

Background: Evaluation of kidney function in newborns with hydronephrosis is important for clinical decisions. Dynamic contrast-enhanced (DCE) MRI can provide the necessary anatomical and functional information. Golden angle dynamic radial acquisition and compressed sensing reconstruction provides sufficient spatiotemporal resolution to achieve accurate parameter estimation for functional imaging of kidneys. However, bulk motion during imaging (rigid or nonrigid movement of the subject resulting in signal dropout) remains an unresolved challenge., Purpose: To evaluate a motion-compensated (MoCo) DCE-MRI technique for robust evaluation of kidney function in newborns. Our method includes: 1) motion detection, 2) motion-robust image reconstruction, 3) joint realignment of the volumes, and 4) tracer-kinetic (TK) model fitting to evaluate kidney function parameters., Study Type: Retrospective., Subjects: Eleven newborn patients (ages <6 months, 6 female)., Field Strength/sequence: 3T; dynamic "stack-of-stars" 3D fast low-angle shot (FLASH) sequence using a multichannel body-matrix coil., Assessment: We evaluated the proposed technique in terms of the signal-to-noise ratio (SNR) of the reconstructed images, the presence of discontinuities in the contrast agent concentration time curves due to motion with a total variation (TV) metric and the goodness of fit of the TK model, and the standard variation of its parameters., Statistical Tests: We used a paired t-test to compare the MoCo and no-MoCo results., Results: The proposed MoCo method successfully detected motion and improved the SNR by 3.3 (P = 0.012) and decreased TV by 0.374 (P = 0.017) across all subjects. Moreover, it decreased nRMSE of the TK model fit for the subjects with less than five isolated bulk motion events in 6 minutes (mean 1.53, P = 0.043), but not for the subjects with more frequent events or no motion (P = 0.745 and P = 0.683)., Data Conclusion: Our results indicate that the proposed MoCo technique improves the image quality and accuracy of the TK model fit for subjects who present isolated bulk motion events., Level of Evidence: 3 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;52:207-216., (© 2019 International Society for Magnetic Resonance in Medicine.)

Purpose: To evaluate the feasibility of using diffusion-weighted magnetic resonance imaging (DW-MRI) to assess the fetal lung apparent diffusion coefficient (ADC) at 3 Tesla (T)., Materials and Methods: Seventy-one pregnant women (32 second trimester, 39 third trimester) were scanned with a twice-refocused Echo-planar diffusion-weighted imaging sequence with 6 different b-values in 3 orthogonal diffusion orientations at 3T. After each scan, a region-of-interest (ROI) mask was drawn to select a region in the fetal lung and an automated robust maximum likelihood estimation algorithm was used to compute the ADC parameter. The amount of motion in each scan was visually rated., Results: When scans with unacceptable levels of motion were eliminated, the lung ADC values showed a strong association with gestational age (P < 0.01), increasing dramatically between 16 and 27 weeks and then achieving a plateau around 27 weeks., Conclusion: We show that to get reliable estimates of ADC values of fetal lungs, a multiple b-value acquisition, where motion is either corrected or considered, can be performed. J. Magn. Reson. Imaging 2016;44:1650-1655., (© 2016 International Society for Magnetic Resonance in Medicine.)