Diffusion-weighted Imaging Acquisition Research Articles

Partial Fourier in the presence of respiratory motion in prostate diffusion-weighted echo planar imaging.

To investigate the effect of respiratory motion in terms of signal loss in prostate diffusion-weighted imaging (DWI), and to evaluate the usage of partial Fourier in a free-breathing protocol in a clinically relevant b-value range using both single-shot and multi-shot acquisitions. A controlled breathing DWI acquisition was first employed at 3T to measure signal loss from deep breathing patterns. Single-shot and multi-shot (2-shot) acquisitions without partial Fourier (no pF) and with partial Fourier (pF) factors of 0.75 and 0.65 were employed in a free-breathing protocol. The apparent SNR and ADC values were evaluated in 10 healthy subjects to measure if low pF factors caused low apparent SNR or overestimated ADC. Controlled breathing experiments showed a difference in signal coefficient of variation between shallow and deep breathing. In free-breathing single-shot acquisitions, the pF 0.65 scan showed a significantly (p < 0.05) higher apparent SNR than pF 0.75 and no pF in the peripheral zone (PZ) of the prostate. In the multi-shot acquisitions in the PZ, pF 0.75 had a significantly higher apparent SNR than 0.65 pF and no pF. The single-shot pF 0.65 scan had a significantly lower ADC than single-shot no pF. Deep breathing patterns can cause intravoxel dephasing in prostate DWI. For single-shot acquisitions at a b-value of 800s/mm2, any potential risks of motion-related artefacts at low pF factors (pF 0.65) were outweighed by the increase in signal from a lower TE, as shown by the increase in apparent SNR. In multi-shot acquisitions however, the minimum pF factor should be larger, as shown by the lower apparent SNR at low pF factors.

A framework for optimizing the acquisition protocol multishell diffusion-weighted imaging for multimodel assessment.

Complementary aspects of tissue microstructure can be studied with diffusion-weighted imaging (DWI). However, there is no consensus on how to design a diffusion acquisition protocol for multiple models within a clinically feasible time. The purpose of this study is to provide a flexible framework that is able to optimize the shell acquisition protocol given a set of DWI models. Eleven healthy subjects underwent an extensive DWI acquisition protocol, including 15 candidate shells, ranging from 10 to 3500 s/mm2. The proposed framework aims to determine the optimized acquisition scheme (OAS) with a data-driven procedure minimizing the squared error of model-estimated parameters. We tested the proposed method over five heterogeneous DWI models exploiting both low and high b-values (i.e., diffusion tensor imaging [DTI], free water, intra-voxel incoherent motion [IVIM], diffusion kurtosis imaging [DKI], and neurite orientation dispersion and density imaging [NODDI]). A voxel-level and region of interest (ROI)-level analysis was conducted over the white matter and in 48 fiber bundles, respectively. Results showed that acquiring data for the five abovementioned models via OAS requires 14 min, compared with 35 min for the joint recommended acquisition protocol. The parameters derived from the reference acquisition scheme and the OAS are comparable in terms of estimated values, noise, and tissue contrast. Furthermore, the power analysis showed that the OAS retains the potential sensitivity to group-level differences in the parameters of interest, with the exception of the free water model. Overall, there is a linear correspondence (R2= 0.91) between OAS and reference-derived parameters. In conclusion, the proposed framework optimizes the shell acquisition scheme for a given set of DWI models (i.e., DTI, free water, IVIM, DKI, and NODDI), combining low and high b-values while saving acquisition time.

Abstract 89: Portable, Low-Field Magnetic Resonance Imaging: Determining Mismatch Following Acute Ischemic Stroke

Background and Aims: Treatment options for acute ischemic stroke (AIS) are uniquely dependent on the time of stroke onset. Intravenous thrombolysis must be administered within 4.5 hours of symptoms commencing, yet a subset of patients wake-up with symptoms and time of onset is unknown. Mismatch between fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) MRI can be used to qualify wake-up strokes for thrombolysis. This has been shown to lead to improved functional outcomes in multicenter trials (WAKE-UP, MR-WITNESS). However, access to MRI is a barrier to differential diagnosis and subsequent treatment. Recent advances in portable, low-field MRI (LF-MRI) offer a solution to increase access to MRI technologies and circumvent the limitations of conventional systems. As such, in this pilot study, we sought to establish the utility of portable LF-MRI to identify DWI-FLAIR mismatch following AIS. Methods: Patients with a diagnosis of AIS presenting to Emergency Department or Intensive Care Unit of the Yale New Haven Hospital or Massachusetts General Hospital from January 2020 to June 2023 underwent DWI and FLAIR acquisition on a 0.064T MRI (Hyperfine Research Inc.) at &lt;4.5 hours ( n =7), 4.5-6 hours ( n =7), and 6-48 hours ( n =110) since last known well (LKW). Conventional high-field (HF) MR images were acquired within 72 hours of LF-MRI. HF-DWI images were co-registered to LF-FLAIR and the hyperintense DWI stroke lesion segmented and superimposed on the FLAIR. The segmentation was mirrored to the contralateral hemisphere of the LF-FLAIR to establish a FLAIR signal intensity ratio (SIR). Results: The FLAIR SIR on images &lt;4.5 hours since LKW was 0.98±0.08. The SIR for cases 4.5-6 hours was 1.34±0.33. Cases 6-48 hours produced a SIR of 1.56±0.36. The SIR at &lt;4.5 hours was significantly less than that observed &gt;6 hours since LKW ( p =0.03). Conclusion: This pilot study demonstrates that a 0.064T portable MRI is capable of distinguishing hyperacute stroke from later stroke onset using FLAIR SIR. Future research is needed in a larger cohort to determine if this imaging technology can be used to guide thrombolysis in the setting of wake-up stroke.

Abstract 128: Multi-Direction Diffusion Weighted Imaging on Portable, Low-Field Magnetic Resonance Imaging

Background and aims: Portable, low-field (LF) MRI has the potential to improve access to expeditious, definitive brain imaging and facilitate diagnosis of acute stroke. Currently available diffusion-weighted imaging (DWI) protocols at LF are limited to a single diffusion direction due to acquisition duration. However, single-direction diffusion has reduced sensitivity for detecting acute ischemic infarcts, particularly small lesions residing in white matter tracts. The purpose of this study was to establish the feasibility of acquiring multi-direction DWI compared with single-direction counterparts on LF-MRI. Methods: Patients presenting with a diagnosis of acute ischemic stroke between July and September 2023 were eligible. Consented patients underwent DWI acquisition on a 0.064T LF-MRI (Mk1.9; Hyperfine Research Inc). Three diffusion directions (x, y, and z) were acquired with a b weighting of 900 s/mm 2 and a single acquisition with a b 0 s/mm 2 . The b 900 images were co-registered to the b 0, trace and apparent diffusion coefficient (ADC) maps calculated, and the final images interpolated at 1 mm 3 . Results: Ten patients presenting to the Massachusetts General Hospital with acute ischemic stroke were consented and imaged within 72 hours of last known well. The total acquisition time was 14 minutes, with all subjects able to tolerate the scan duration. Ischemic lesions as small as 0.1 mL were detectable on the LF-MRI (17.5 +/- 18.2 mL). An example of each diffusion direction individually, the combined trace, and corresponding ADC maps are shown in Figure 1, compared with conventional high-field (HF) diffusion images acquired within 30 minutes of the LF acquisition. Conclusion: Multi-direction DWI imaging is feasible on a 0.064T LF-MRI scanner. Our experience suggests further modifications to the pulse sequence and scanner configuration may facilitate a reduction in acquisition time, improve resolution, or both.

Sleep Patterns and Prospective Diffusion Weighted Imaging Biomarkers: the Sleep and Dementia Consortium (SDC)

AbstractBackgroundAdequate sleep is necessary to maintain brain health, with sleep disturbances associated with higher Alzheimer’s disease (AD) risk. Diffusion‐weighted imaging (DWI) metrics are increasingly recognized as useful neuroimaging biomarkers to detect AD‐related white matter degeneration. We assessed the relationship between sleep patterns and prospective DWI metrics in the Sleep and Dementia Consortium (SDC). The SDC studies associations between polysomnography (PSG)‐derived sleep with dementia risk and cognitive and MRI endophenotypes.MethodThe SDC includes five community‐based cohorts, two of which have DWI acquisitions: The Framingham Heart Study (FHS) and the Atherosclerosis Risk in Communities study (ARIC). Dementia‐free participants who underwent both PSG and DWI‐MRI were selected, including 354 FHS participants (56.6±7.1y, 57%W), and 184 ARIC participants (61.6±5.0y, 52%W). The MRI session was approximately 15 years after the PSG on average (FHS:17.0±1.3y; ARIC:15.8±0.8y). Fractional anisotropy (FA) and mean diffusivity (MD) were considered for both cohorts, in addition to free‐water (FW) in the FHS. Sleep metrics were harmonized centrally, distributed for cohort‐specific linear regressions, and study‐level estimates were pooled in random effects meta‐analyses. Analyses were adjusted for demographics, obesity, time between PSG and MRI, antidepressants and sedative medication usage. An interaction term by APOE4 allele carrier status in regression models was used to test its moderating effect.ResultIn the FHS, sleep fragmentation was associated with DWI measures in the expected direction: Higher Wake After Sleep Onset and lower Sleep Maintenance Efficiency were associated with lower FA (β±SE = ‐0.17±0.09,p = 0.04; β±SE = 0.23±0.10,p = 0.03), higher MD (β±SE = 0.15±0.07,p = 0.04; β±SE = ‐0.20±0.09,p = 0.03), and higher FW (β±SE = 0.17±0.07,p = 0.02; β±SE = ‐0.22±0.08,p = 0.008). Meta‐analysis of FHS and ARIC revealed significant pooled effects between lower Sleep Maintenance Efficiency and lower FA (β±SE = 0.17±0.08,p = 0.04). In the FHS, APOE4 allele significantly moderated the association between REM sleep proportion with FA and MD, where lower REM sleep percentage was associated with higher MD (β±SE = ‐4.89±1.95,p = 0.02) and lower FA (β±SE = 4.93±2.26,p = 0.03) in APOE4 carriers only.ConclusionIn the SDC, sleep fragmentation was associated with MRI markers of poorer white matter integrity 15 years later. Less REM sleep was associated with poorer white matter integrity in APOE4 allele carriers only, suggesting that disrupted sleep architecture may contribute and interact with neurodegenerative processes to affect brain integrity.

Highly accelerated multi-shot intravoxel incoherent motion diffusion-weighted imaging in brain enabled by parametric POCS-based multiplexed sensitivity encoding.

Recently, intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has also been demonstrated as an imaging tool for applications in neurological and neurovascular diseases. However, the use of single-shot diffusion-weighted echo-planar imaging for IVIM DWI acquisition leads to suboptimal data quality: for instance, geometric distortion and deteriorated image quality at high spatial resolution. Although the recently commercialized multi-shot acquisition methods, such as multiplexed sensitivity encoding (MUSE), can attain high-resolution and high-quality DWI with signal-to-noise ratio (SNR) performance superior to that of the conventional parallel imaging method, the prolonged scan time associated with multi-shot acquisition is impractical for routine IVIM DWI. This study proposes an acquisition and reconstruction framework based on parametric-POCSMUSE to accelerate the four-shot IVIM DWI with 70% reduction of total scan time (13 min 8 s versus 4 min 8 s). First, the four-shot IVIM DWI scan with 17 b values was accelerated by acquiring only one segment per b value except for b values of 0 and 600 s/mm2 . Second, an IVIM-estimation scheme was integrated into the parametric-POCSMUSE to enable joint reconstruction of multi-b images from under-sampled four-shot IVIM DWI data. In vivo experiments on both healthy subjects and patients show that the proposed framework successfully produced multi-b DW images with significantly higher SNRs and lower reconstruction errors than did the conventional acceleration method based on parallel imaging. In addition, the IVIM quantitative maps estimated from the data produced by the proposed framework showed quality comparable to that of fully sampled MUSE-reconstructed images, suggesting that the proposed framework can enable highly accelerated multi-shot IVIM DWI without sacrificing data quality. In summary, the proposed framework can make multi-shot IVIM DWI feasible in a routine MRI examination, with reasonable scan time and improved geometric fidelity.

Intravoxel incoherent motion magnetic resonance imaging reconstruction from highly under-sampled diffusion-weighted PROPELLER acquisition data via physics-informed residual feedback unrolled network

Objective. The acquisition of diffusion-weighted images for intravoxel incoherent motion (IVIM) imaging is time consuming. This work aims to accelerate the scan through a highly under-sampling diffusion-weighted turbo spin echo PROPELLER (DW-TSE-PROPELLER) scheme and to develop a reconstruction method for accurate IVIM parameter mapping from the under-sampled data. Approach . The proposed under-sampling DW-TSE-PROPELLER scheme for IVIM imaging is that a few blades per b-value are acquired and rotated along the b-value dimension to cover high-frequency information. A physics-informed residual feedback unrolled network (PIRFU-Net) is proposed to directly estimate distortion-free and artifact-free IVIM parametric maps (i.e., the perfusion-free diffusion coefficient D and the perfusion fraction f) from highly under-sampled DW-TSE-PROPELLER data. PIRFU-Net used an unrolled convolution network to explore data redundancy in the k-q space to remove under-sampling artifacts. An empirical IVIM physical constraint was incorporated into the network to ensure that the signal evolution curves along the b-value follow a bi-exponential decay. The residual between the realistic and estimated measurements was fed into the network to refine the parametric maps. Meanwhile, the use of synthetic training data eliminated the need for genuine DW-TSE-PROPELLER data. Main results . The experimental results show that the DW-TSE-PROPELLER acquisition was six times faster than full k-space coverage PROPELLER acquisition and within a clinically acceptable time. Compared with the state-of-the-art methods, the distortion-free D and f maps estimated by PIRFU-Net were more accurate and had better-preserved tissue boundaries on a simulated human brain and realistic phantom/rat brain/human brain data. Significance . Our proposed method greatly accelerates IVIM imaging. It is capable of directly and simultaneously reconstructing distortion-free, artifact-free, and accurate D and f maps from six-fold under-sampled DW-TSE-PROPELLER data.

Diffusion-weighted magnetic resonance imaging in early central retinal artery occlusion.

Restricted retinal diffusion (RDR) has recently been recognized as a frequent finding on standard diffusion-weighted imaging (DWI) in central retinal artery occlusion (CRAO). However, data on early DWI signal evolution are missing. Consecutive CRAO patients with DWI performed within 24 h after onset of visual impairment were included in a bicentric, retrospective cross-sectional study. Two blinded neuroradiologists assessed randomized DWI scans for the presence of retinal ischemia. RDR detection rates, false positive ratings, and interrater agreement were evaluated for predefined time groups. Sixty eight CRAO patients (68.4 ± 16.8 years; 25 female) with 72 DWI scans (76.4% 3 T, 23.6% 1.5 T) were included. Mean time-delay between onset of CRAO and DWI acquisition was 13.4 ± 7.0 h. Overall RDR detection rates ranged from 52.8% to 62.5% with false positive ratings in 4.2%-8.3% of cases. RDR detection rates were higher in DWI performed 12-24 h after onset, when compared with DWI acquired within the first 12 h (79.5%vs 39.3%, p < 0.001). The share of false positive ratings was highest for DWI performed within the first 6 h of symptom onset (up to 14.3%). Interrater reliability was "moderate" for DWI performed within the first 18 h (κ = 0.57-0.58), but improved for DWI acquired between 18 and 24 h (κ = 0.94). DWI-based detection of retinal ischemia in early CRAO is likely to be time-dependent with superior diagnostic accuracy for DWI performed 12-24 h after onset of visual impairment.

Applications of Diffusion-Weighted MRI to the Musculoskeletal System.

Diffusion-weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application-specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2-70 msec) and the need for sub-millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion-weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.

Tuning the optimal diffusion-weighted MRI parameters on a 0.35-T MR-Linac for clinical implementation: A phantom study.

This study aims to assess the quality of a new diffusion-weighted imaging (DWI) sequence implemented on an MR-Linac MRIdian system, evaluating and optimizing the acquisition parameters to explore the possibility of clinically implementing a DWI acquisition protocol in a 0.35-T MR-Linac. All the performed analyses have been carried out on two types of phantoms: a homogeneous 24-cm diameter polymethylmethacrylate (PMMA) sphere (SP) and a homemade phantom (HMP) constating in a PMMA cylinder filled with distilled water with empty sockets into which five cylindrical vials filled with five different concentrations of methylcellulose water solutions have been inserted. SP was used to evaluate the dependence of diffusion gradient inhomogeneity artifacts on gantry position. Four diffusion sequences with b-values of 500 s/mm2 and 3 averages have been acquired: three with diffusion gradients in the three main directions (phase direction, read direction, slice direction) and one with the diffusion gradients switched off. The dependence of diffusion image uniformity and SNR on the number of averages in the MR sequences was also investigated to determine the optimal number of averages. Finally, the ADC values of HMP have been computed and then compared between images acquired in the scanners at 0.35 and 1.5 T. In order to acquire high-quality artifact-free DWI images, the "slice" gradient direction has been identified to be the optimal one and 0° to be the best gradient angle. Both the SNR ratio and the uniformity increase with the number of averages. A threshold value of 80 for SNR and 85% for uniformity was adopted to choose the best number of averages. By making a compromise between time and quality and limiting the number of b-values, it is possible to reduce the acquisition time to 78 s. The Passing-Bablok test showed that the two methods, with 0.35 and 1.5 T scanners, led to similar results. The quality of the DWI has been accurately evaluated in relation to different sequence parameters, and optimal parameters have been identified to select a clinical protocol for the acquisition of ADC maps sustainable in the workflow of a hybrid radiotherapy system with a 0.35-T MRI scanner.

Denoising diffusion weighted imaging data using convolutional neural networks.

Diffusion weighted imaging (DWI) with multiple, high b-values is critical for extracting tissue microstructure measurements; however, high b-value DWI images contain high noise levels that can overwhelm the signal of interest and bias microstructural measurements. Here, we propose a simple denoising method that can be applied to any dataset, provided a low-noise, single-subject dataset is acquired using the same DWI sequence. The denoising method uses a one-dimensional convolutional neural network (1D-CNN) and deep learning to learn from a low-noise dataset, voxel-by-voxel. The trained model can then be applied to high-noise datasets from other subjects. We validated the 1D-CNN denoising method by first demonstrating that 1D-CNN denoising resulted in DWI images that were more similar to the noise-free ground truth than comparable denoising methods, e.g., MP-PCA, using simulated DWI data. Using the same DWI acquisition but reconstructed with two common reconstruction methods, i.e. SENSE1 and sum-of-square, to generate a pair of low-noise and high-noise datasets, we then demonstrated that 1D-CNN denoising of high-noise DWI data collected from human subjects showed promising results in three domains: DWI images, diffusion metrics, and tractography. In particular, the denoised images were very similar to a low-noise reference image of that subject, more than the similarity between repeated low-noise images (i.e. computational reproducibility). Finally, we demonstrated the use of the 1D-CNN method in two practical examples to reduce noise from parallel imaging and simultaneous multi-slice acquisition. We conclude that the 1D-CNN denoising method is a simple, effective denoising method for DWI images that overcomes some of the limitations of current state-of-the-art denoising methods, such as the need for a large number of training subjects and the need to account for the rectified noise floor.

Reduced field-of-view and multi-shot DWI acquisition techniques: Prospective evaluation of image quality and distortion reduction in prostate cancer imaging

ObjectivesTo prospectively compare image quality and apparent diffusion coefficient (ADC) quantification for reduced field-of-view (rFOV)- and multi-shot echo-planar imaging (msEPI)-based diffusion weighted imaging (DWI), using single-shot echo-planar-imaging (ssEPI) DWI as the reference. MethodsUnder IRB approval and after informed consent, msEPI, rFOV, and ssEPI DWI acquisitions were prospectively added to clinical prostate MRI exams at 3.0 T. Image distortion was quantitatively evaluated by root-mean-squared displacement (dr.m.s.). Histogram-based quantitative ADC parameters were compared in a sub-set of patients for proven sites of prostate cancer and matched non-cancerous prostate. Three radiologists also independently evaluated the DWI sequences for subjective image quality and distortion/artifact on a 5-point Likert scale. ResultsTwenty-five patients were included (15 with proven sites of cancer). Average dr.m.s. demonstrated a small but statistically significant reduction in distortion for both rFOV and msEPI relative to ssEPI. Quantitative ADC parameters for prostate tumors demonstrated no significant difference across the 3 DWI acquisitions and each acquisition demonstrated a statistically significant decrease in mean ADC for tumor compared to normal prostate. Qualitative reader assessment demonstrated favorable image quality for rFOV and msEPI, more notable for msEPI. ConclusionsrFOV and msEPI DWI techniques achieved reduction in image distortion, improvement in image quality, and maintained reproducible ADC quantification compared to the standard ssEPI.

Read-out Segmented Echo Planar Imaging with Two-Dimensional Navigator Correction (RESOLVE): An Alternative Sequence to Improve Image Quality on Diffusion-Weighted Imaging of Prostate.

We aimed to investigate if the use of read-out segmented echoplanar imaging with additional two-dimensional navigator correction (Readout Segmentation of Long Variable Echo, RESOLVE) for acquiring prostate diffusion-weighted imaging (DWI) improves image quality, compared to single-shot echoplanar imaging (ss-EPI). This single-center prospective study cohort included 162 males with suspected prostate cancer, who underwent 3 Tesla multiparametric MRI (3T-mpMRI). Two abdominal radiologists, blinded to the clinical information, separately reviewed each 3T-mpMRI study to rank geometrical distortion, degree of rectal distention, lesion conspicuity, and anatomic details delineation first on ss-EPI-DWI and later on RESOLVE-DWI using 5-point scales (1 = excellent, 5 = poor). The average of the ranking scores given by two readers was generated and used as the final score. There was good-to-excellent interreader agreement for scoring image quality parameters on both ss-EPI and RESOLVE. Geometrical distortion scores > 3 was seen in 12.3% (20/162) of ss-EPI images, with all having geometrical distortion score <3 on RESOLVE (p < .001). The mean image distortion score was significantly less on RESOLVE than ss-EPI (1.16 vs 1.61, p < .01 regardless of rectal gas, p< .05 when stratified by the degree of rectal distention ). RESOLVE was superior to ss-EPI for lesion conspicuity (mean 1.35 vs 1.53, p< .002) and anatomic delineation (2.60 vs 2.68, p< .001) of prostate on DWI. Compared to conventional ss-EPI, the use of RESOLVE for acquisition of prostate DWI resulted in significantly enhanced image quality and reduced geometrical distortion. RESOLVE could be an alternative or replacement of ss-EPI for acquiring prostate DWI with significantly less geometrical distortion and significantly improved lesion conspicuity and anatomic delineation.

Accelerated Breast Diffusion-weighted Imaging Using Multiband Sensitivity Encoding with the CAIPIRINHA Method: Clinical Experience at 3 T

Purpose To examine the clinical value of multiband (MB) sensitivity encoding (SENSE)-accelerated diffusion-weighted imaging (DWI) for breast imaging by performing quantitative and qualitative comparisons with conventional diffusion-weighted echo-planar imaging, or conventional DWI (cDWI). Materials and Methods In this prospective study (ClinicalTrials.gov identifier NCT03607552), women with breast cancer were recruited from July 2018 to July 2019 to undergo additional MB SENSE DWI during clinical 3-T breast MRI examinations. The cDWI and MB SENSE DWI acquisitions were assessed both quantitatively and qualitatively. Regions of interest were defined for tumorous and normal tissue, and the tumor apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR), and signal index (SI) were calculated for both DWI methods. Three readers independently reviewed the two acquisitions side by side and provided relative image quality scores. Tumor ADC, CNR, and SI measures were compared between cDWI and MB SENSE DWI acquisitions by using a paired t test, and reader preferences were evaluated by using the sign test. Results The study included 38 women (median age, 48 years; range, 28-83 years). Overall agreement was good between cDWI and MB SENSE DWI tumor ADC measures (intraclass correlation coefficient, 0.87 [95% CI: 0.75, 0.94]), and no differences were evident in the ADC (median, 0.93 × 10-3 mm2/sec vs 0.87 ×10-3 mm2/sec; P = .50), CNR (2.2 vs 2.3; P = .17), or SI (9.2 vs 9.2; P = .23) measurements. The image quality of cDWI and MB SENSE DWI acquisitions were considered equal for 51% of images (58 of 114), whereas MB SENSE DWI was preferred more often than cDWI (37% [42 of 114] vs 12% [14 of 114]; P < .001). The preference for MB SENSE DWI was most often attributed to better fat suppression. Conclusion MB SENSE can be used to accelerate breast DWI acquisition times without compromising the image quality or the fidelity of quantitative ADC measurements. Keywords: MR-Diffusion-weighted Imaging, Breast, Comparative Studies, Technology Assessment Clinical trial registration no. NCT03607552 © RSNA, 2022.

Tremor associated with similar structural networks in Parkinson's disease and essential tremor

IntroductionDespite substantial clinical and pathophysiological differences, the characteristics of tremor in Parkinson's disease (PD) and essential tremor (ET) patients bear certain similarities. The presented study delineates tremor-related structural networks in these two disorders. Methods42 non-advanced PD patients (18 tremor-dominant, 24 without substantial tremor), 17 ET, and 45 healthy controls underwent high-angular resolution diffusion-weighted imaging acquisition to reconstruct their structural motor connectomes as a proxy of the anatomical interconnections between motor network regions, implementing state-of-the-art globally optimised probabilistic tractography. ResultsWhen compared to healthy controls, ET patients exhibited higher structural connectivity in the cerebello-thalamo-cortical network. Interestingly, the comparison of tremor-dominant PD patients and PD patients without tremor yielded very similar results – higher structural connectivity in tremor-dominant PD sharing multiple nodes with the tremor network detected in ET, despite the generally lower structural connectivity between basal ganglia and frontal cortex in the whole PD group when compared to healthy controls. ConclusionThe higher structural connectivity of the cerebello-thalamo-cortical network seems to be the dominant tremor driver in both PD and ET. While it appears to be the only tremor-related network in ET, its combination with large scale hypoconnectivity in the frontal cortico-subcortical network in PD may explain different clinical features of tremor in these two disorders.

Diffusion-weighted imaging in prostate cancer.

Diffusion-weighted imaging (DWI), a key component in multiparametric MRI (mpMRI), is useful for tumor detection and localization in clinically significant prostate cancer (csPCa). The Prostate Imaging Reporting and Data System versions 2 and 2.1 (PI-RADS v2 and PI-RADS v2.1) emphasize the role of DWI in determining PIRADS Assessment Category in each of the transition and peripheral zones. In addition, several recent studies have demonstrated comparable performance of abbreviated biparametric MRI (bpMRI), which incorporates only T2-weighted imaging and DWI, compared with mpMRI with dynamic contrast-enhanced MRI. Therefore, further optimization of DWI is essential to achieve clinical application of bpMRI for efficient detection of csPC in patients with elevated PSA levels. Although DWI acquisition is routinely performed using single-shot echo-planar imaging, this method suffers from such as susceptibility artifact and anatomic distortion, which remain to be solved. In this review article, we will outline existing problems in standard DWI using the single-shot echo-planar imaging sequence; discuss solutions that employ newly developed imaging techniques, state-of-the-art technologies, and sequences in DWI; and evaluate the current status of quantitative DWI for assessment of tumor aggressiveness in PC.

In vivo restricted diffusion imaging (RDI) is sensitive to differences in axonal density in typical children and adults.

The ability to dissociate axonal density in vivo from other microstructural properties is important for the diagnosis and treatment of neurologic disease, and new methods to do so are being developed. We investigated one such method-restricted diffusion imaging (RDI)-to see whether it can more accurately replicate histological axonal density patterns in the corpus callosum (CC) of adults and children compared to diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and generalized q-sampling imaging (GQI) methods. To do so, we compared known axonal density patterns defined by histology to diffusion-weighted imaging (DWI) scans of 840 healthy 20- to 40-year-old adults, and to DWI scans of 129 typically developing 7-month-old to 18-year-old children and adolescents. Contrast analyses were used to compare pattern similarities between the in vivo metric and previously published histological density models. We found that RDI was effective at mapping axonal density of small (Cohen's d = 2.60) and large fiber sizes (Cohen's d = 2.84) in adults. The same pattern was observed in the developing sample (Cohen's d = 3.09 and 3.78, respectively). Other metrics, notably NODDI's intracellular volume fraction in adults and GQI generalized fractional anisotropy in children, were also sensitive metrics. In conclusion, the study showed that the novel RDI metric is sensitive to density of small and large axons in adults and children, with both single- and multi-shell acquisition DWI data. Its effectiveness and availability to be used on standard as well as advanced DWI acquisitions makes it a promising method in clinical settings.

Diffusion-weighted imaging of the abdomen using echo planar imaging with compressed SENSE: Feasibility, image quality, and ADC value evaluation

ObjectiveTo evaluate the feasibility, image quality, and apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with Compressed SENSE (EPICS-DWI) of the abdomen and to compare them with conventional single-shot EPI with parallel imaging (PI) technique (PI-DWI). Materials and MethodsThis prospective study included 46 participants with known or suspected upper abdominal diseases (19 men and 27 women, mean age, 68 years) who underwent MRI. DWI acquisition was performed using free-breathing two-dimensional fat-suppressed PI-DWI and EPICS-DWI with SENSE or compressed sensing (CS) factor, 3.0. Moreover, image noise and contour of liver and pancreas were qualitatively evaluated using a five-point scale. The mean ADC value and standard deviation (SD) of the liver, pancreas, and spleen were measured, and the coefficient of variation (CV) was calculated. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon test. ResultsThe mean image quality scores for image noise and contour of liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P < 0.0001). Moreover, the mean ADC values of the liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P < 0.0001), but that of spleen was not significantly different. The mean SD and CV of the liver, pancreas, and spleen were lower in EPICS-DWI compared with PI-DWI (P < 0.0001–0.032). ConclusionEPICS-DWI could be feasible in MRI of the abdomen and significantly improve image quality compared with PI-DWI in aggressive setting. ADC value measurements were higher in EPICS-DWI compared with PI-DWI.

The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review.

The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.

Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts.

The specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.