Echo-planar Imaging Sequence Research Articles

Assessment of Motor Cortex in Active, Passive and Imagery Wrist Movement Using Functional MRI.

Background: Functional Magnetic resonance imaging (fMRI) measures the small fluctuation of blood flow happening during task-fMRI in brain regions.Objective: This research investigated these active, imagery and passive movements in volunteers design to permit a comparison of their capabilities in activating the brain areas.Material and Methods: In this applied research, the activity of the motor cortex during the right-wrist movement was evaluated in 10 normal volunteers under active, passive, and imagery conditions. T2* weighted, three-dimensional functional images were acquired using a BOLD sensitive gradient-echo EPI (echo planar imaging) sequence with echo time (TE) of 30 ms and repetition time (TR) of 2000 ms. The functional data, which included 248 volumes per subject and condition, were acquired using the blocked design paradigm. The images were analyzed by the SPM12 toolbox, MATLAB software.Results: The findings determined a significant increase in signal intensity of the motor cortex while performing the test compared to the rest time (p< 0.05). It was also observed that the active areas in hand representation of the motor cortex are different in terms of locations and the number of voxels in different wrist directions. Moreover, the findings showed that the position of active centers in the brain is different in active, passive, and imagery conditions. Conclusion: Results confirm that primary motor cortex neurons play an essential role in the processing of complex information and are designed to control the direction of movement. It seems that the findings of this study can be applied for rehabilitation studies.

Single shot zonal oblique multislice SE-EPI diffusion-weighted imaging with low to ultra-high b-values for the differentiation of benign and malignant vertebral spinal fractures

PurposeTo investigate the diagnostic yield of low to ultra-high b-values for the differentiation of benign from malignant vertebral fractures using a state-of-the-art single-shot zonal-oblique-multislice spin-echo echo-planar diffusion-weighted imaging sequence (SShot ZOOM SE-EPI DWI). Materials and Methods66 patients (34 malignant, 32 benign) were examined on 1.5 T MR scanners. ADC maps were generated from b-values of 0,400; 0,1000 and 0,2000s/mm2. ROIs were placed into the fracture of interest on ADC maps and trace images and into adjacent normal vertebral bodies on trace images. The ADC of fractures and the Signal-Intensity-Ratio (SIR) of fractures relative to normal vertebral bodies on trace images were considered quantitative metrics. The appearance of the fracture of interest was graded qualitatively as iso-, hypo-, or hyperintense relative to normal vertebrae. ResultsADC achieved an area under the curve (AUC) of 0.785/0.698/0.592 for b = 0,400/0,1000/0,2000s/mm2 ADC maps respectively. SIR achieved an AUC of 0.841/0.919/0.917 for b = 400/1000/2000s/mm2 trace images respectively. In qualitative analyses, only b = 2000s/mm2 trace images were diagnostically valuable (sensitivity:1, specificity:0.794). Machine learning models incorporating all qualitative and quantitative metrics achieved an AUC of 0.95/0.98/0.98 for b-values of 400/1000/2000s/mm2 respectively. The model incorporating only qualitative metrics from b = 2000s/mm2 achieved an AUC of 0.97. ConclusionBy using quantitative and qualitative metrics from SShot ZOOM SE-EPI DWI, benign and malignant vertebral fractures can be differentiated with high diagnostic accuracy. Importantly qualitative analysis of ultra-high b-value images may suffice for differentiation as well.

Advanced diffusion imaging of abdominal organs in different hydration states of the human body: stability of biomarkers

BackgroundMR diffusion weighted imaging (DWI) may provide important information regarding the pathophysiology of parenchymal abdominal organs. The purpose of our study was to investigate the stability of imaging biomarkers of diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in abdominal parenchymal organs regarding two body hydration states. MethodsTen healthy volunteers twice underwent DWI of abdominal organs using a double-refocused spin-echo echo-planar imaging sequences with 11 different b-values (ranging from 0 to 1,500 s/mm2): after 4 h of fluid deprivation; 45 min following 1000 ml of water intake. Four different diffusion models were evaluated and compared: standard DWI, DKI with mono-exponential fitting, multistep algorithm with variable b-value threshold for IVIM, combined IVIM-Kurtosis; in four abdominal organs: kidneys, liver, spleen and psoas muscle. ResultsDiffusion parameters from all four models remained similar for the renal parenchyma before and after the water challenge. Significant differences were found for the liver, spleen, and psoas muscle. The largest effects were seen for: the liver parenchyma after the water challenge by means of IVIM model's true diffusion (p < 0.02); the spleen, for IVIM's perfusion fraction (p < 0.03), the psoas muscle for the ADC value (p < 0.02). ConclusionsHerein, we showed that diffusion parameters of the kidney remain remarkably stable regarding the hydration status. This may be attributed to the kidney-specific compensatory mechanisms. For the liver, spleen and psoas muscle the diffusion parameters were sensitive to changes of the hydration. This phenomenon needs to be considered when evaluating diffusion data of these organs.

Retrospective Distortion and Motion Correction for Free-Breathing DW-MRI of the Kidneys Using Dual-Echo EPI and Slice-to-Volume Registration.

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 B0 field inhomogeneities degrade the image quality, reduce the accuracy of quantitative imaging markers, and impede their subsequent clinical applicability. 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. Prospective. Ten healthy volunteers (ages 29-38, four females). 3T; DW-MR dual-echo echo-planar imaging (EPI) sequence (10 b-values and 17 directions) and a T2 volume. The distortion correction was evaluated subjectively (Likert scale 0-5) and numerically with cross-correlation between the DW images at b = 0 s/mm2 and a T2 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 comparisons were done using Wilcoxon tests. The proposed method improved the Likert scores by 1.1 ± 0.8 (P < 0.05), the cross-correlation with the T2 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). 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. 2 TECHNICAL EFFICACY STAGE: 1.

Diffusion tensor imaging of oral carcinoma: Clinical evaluation and comparison with histopathological findings

PurposeThis study aims to assess the usefulness of diffusion tensor imaging (DTI) as a noninvasive method for the evaluation of histological grade and lymph node metastasis in patients with oral carcinoma (OC). Materials and methodsThirty-six consecutive patients with histologically confirmed OC underwent examination by 3-T MRI. DTI was performed using a single-shot echo-planar imaging sequence with b values of 0 and 1000 s/mm2 and motion-probing gradients in 12 noncollinear directions. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps were compared with histopathological findings. The DTI parameters were correlated with the histological grade of the OCs based on the World Health Organization grading criteria and the presence or absence of lymph node metastasis. ResultsThe FA values (0.275 ± 0.058) of OC were significantly lower than those of normal tongue, muscle, and parotid glands (P < 0.001 for all), and the MD, AD, and RD values (1.220 ± 0.149, 1.434 ± 0.172, and 1.019 ± 0.165 × 10−3 mm2/s, respectively) were significantly higher than their respective normal values (P < 0.001 for all). Significant inverse correlations with histological grades were shown for FA, MD, AD, and RD values in OC patients (r = −0.862, r = −0.797, r = −0.747, and r = −0.844, respectively; P < 0.001 for all). In addition, there was a significant difference in the FA values of metastatic and nonmetastatic lymph nodes (0.186 vs. 0.276), MD (0.923 vs. 1.242 × 10−3 mm2/s), AD (1.246 vs. 1.621 × 10−3 mm2/s), and RD (0.792 vs. 1.100 × 10−3 mm2/s; P < 0.001 for all). ConclusionsDTI may be clinically useful for the noninvasive evaluation of histological grade and lymph node metastasis in OC patients.

Factors Affecting Image Quality and Lesion Evaluability in Breast Diffusion-weighted MRI: Observations from the ECOG-ACRIN Cancer Research Group Multisite Trial (A6702).

The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84). Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.

In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T

BackgroundDiffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed. MethodsA multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated. ResultsThe SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above. ConclusionThe single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.

Associations between IVIM histogram parameters and histopathology in rectal cancer

PurposeHistogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC). MethodsSeventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm2. Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD). ResultsThere were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=−0.50, p=.04 and r=−0.55, p=.02, respectively. MVD correlated well with parameters derived from f. ConclusionIVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.

Diffusion tensor-based fiber tracking of the male urethral sphincter complex in patients undergoing radical prostatectomy: a feasibility study

ObjectivesTo study the diffusion tensor-based fiber tracking feasibility to access the male urethral sphincter complex of patients with prostate cancer undergoing Retzius-sparing robot-assisted laparoscopic radical prostatectomy (RS-RARP).MethodsTwenty-eight patients (median age of 64.5 years old) underwent 3 T multiparametric-MRI of the prostate, including an additional echo-planar diffusion tensor imaging (DTI) sequence, using 15 diffusion-encoding directions and a b value = 600 s/mm2. Acquisition parameters, together with patient motion and eddy currents corrections, were evaluated. The proximal and distal sphincters, and membranous urethra were reconstructed using the deterministic fiber assignment by continuous tracking (FACT) algorithm, optimizing fiber tracking parameters. Tract length and density, fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) were computed. Regional differences between structures were accessed by ANOVA, or nonparametric Kruskal–Wallis test, and post-hoc tests were employed, respectively, TukeyHSD or Dunn’s.ResultsThe structures of the male urethral sphincter complex were clearly depicted by fiber tractography using optimized acquisition and fiber tracking parameters. The use of eddy currents and subject motion corrections did not yield statistically significant differences on the reported DTI metrics. Regional differences were found between all structures studied among patients, suggesting a quantitative differentiation on the structures based on DTI metrics.ConclusionsThe current study demonstrates the technical feasibility of the proposed methodology, to study in a preoperative setting the male urethral sphincter complex of prostate cancer patients candidates for surgical treatment. These findings may play a role on a more accurate prediction of the RS-RARP post-surgical urinary continence recovery rate.

Detecting Task Functional MRI Activation Using the Multiband Multiecho (MBME) Echo-Planar Imaging (EPI) Sequence.

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) has been widely applied to detect brain activations. Recent advances in multiband (MB) and multiecho (ME) techniques have greatly improved fMRI methods. MB imaging improves temporal and/or spatial resolution, while ME imaging has been shown to improve BOLD sensitivity. This study aimed to evaluate the novel MBME echo planar imaging (EPI) sequence utilizing MB and ME simultaneously to determine if the MBME outperform the MB single echo (MBSE) sequence for task fMRI. To compare the performance of MBME with MBSE in a task fMRI study. Prospective. A total of 29 healthy volunteers aged 20-46 years (9 male, 20 female). MBSE and MBME gradient-echo EPI sequences were applied at 3T. Additional T1 -weighted magnetization-prepared rapid acquisition with gradient echo (MPRAGE) was collected. A checkerboard visual task was presented during the functional MBSE and MBME scans. The MBME or MBSE signal was evaluated using the temporal signal-to-noise ratio (tSNR). Task activation was evaluated using the z-score, volume, sensitivity, and specificity. Test-retest metrics of task activation were examined with the Dice coefficient (DC) and intraclass correlation coefficient (ICC) on subjects with repeated scans. A linear mixed-effects model was used to compared MBME and MBSE activation at the voxel base. The paired t-test was used to compare tSNR, activation z-score, and volume, along with sensitivity, specificity, and DC between MBSE and MBME. While similar task activation was detected in the visual cortex, MBME showed higher activation volume and higher sensitivity compared with MBSE (P < 0.05). ICC was higher for MBME than MBSE, while there was a trend of differences in DC (P = 0.08). MBME resulted in higher task fMRI activation volume and sensitivity without losing specificity. Reliability was also higher for MBME scans compared with MBSE. 1 TECHNICAL EFFICACY STAGE: 1.

Fiber Bragg Grating Sensors for Performance Evaluation of Fast Magnetic Resonance Thermometry on Synthetic Phantom.

The increasing recognition of minimally invasive thermal treatment of tumors motivate the development of accurate thermometry approaches for guaranteeing the therapeutic efficacy and safety. Magnetic Resonance Thermometry Imaging (MRTI) is nowadays considered the gold-standard in thermometry for tumor thermal therapy, and assessment of its performances is required for clinical applications. This study evaluates the accuracy of fast MRTI on a synthetic phantom, using dense ultra-short Fiber Bragg Grating (FBG) array, as a reference. Fast MRTI is achieved with a multi-slice gradient-echo echo-planar imaging (GRE-EPI) sequence, allowing monitoring the temperature increase induced with a 980 nm laser source. The temperature distributions measured with 1 mm-spatial resolution with both FBGs and MRTI were compared. The root mean squared error (RMSE) value obtained by comparing temperature profiles showed a maximum error of 1.2 °C. The Bland-Altman analysis revealed a mean of difference of 0.1 °C and limits of agreement 1.5/−1.3 °C. FBG sensors allowed to extensively assess the performances of the GRE-EPI sequence, in addition to the information on the MRTI precision estimated by considering the signal-to-noise ratio of the images (0.4 °C). Overall, the results obtained for the GRE-EPI fully satisfy the accuracy (~2 °C) required for proper temperature monitoring during thermal therapies.

Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit.

Diffusion kurtosis imaging (DKI) quantifies the non-Gaussian diffusion of water within tissue microstructure. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. To assess the reproducibility in whole-brain high-resolution DKI at varying b-values. Retrospective. In all, 44 individuals from the test-retest Human Connectome Project (HCP) database and 12 3D-printed phantoms. Diffusion-weighted multiband echo-planar imaging sequence at 3T and 9.4T. magnetization-prepared rapid acquisition gradient echo at 3T for in vivo structural data only. From HCP data with b-values = 1000, 2000, 3000 s/mm2 (dataset A), two additional datasets with b-values = 1000, 3000 s/mm2 (dataset B) and b-values = 1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in white matter (WM) and gray matter (GM) based on whole-brain and regions of interest (ROIs). DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate the presence of systematic biases. Repeated measures analysis of variance was used for statistical comparison. Datasets A and B exhibited lower DKI CoVs (<20%) compared to C (<50%) in both WM and GM ROIs (all P < 0.05). This effect varies between DKI and DTI parameters (P < 0.005). Whole-brain fitting residuals were consistent across datasets (P > 0.05), but lower residuals in dataset B were detected for the WM ROIs (P < 0.001). A similar trend was observed for the phantom data CoVs (<7.5%) at varying fiber orientations for datasets A and B. Finally, dataset C was characterized by higher residuals across the different fiber crossings (P < 0.05). The study demonstrates that high reproducibility can still be achieved within a reasonable scan time, specifically dataset B, supporting the potential of DKI for aiding clinical tools in detecting microstructural changes.

On the dependence of the cardiac motion artifact on the breathing cycle in liver diffusion-weighted imaging.

PurposeThe purpose of this study was to investigate whether the cardiac motion artifact that regularly appears in diffusion-weighted imaging of the left liver lobe might be reduced by acquiring images in inspiration, when the coupling between heart and liver might be minimal.Materials and methods43 patients with known or suspected focal liver lesions were examined at 1.5 T with breath hold acquisition, once in inspiration and once in expiration. Data were acquired with a diffusion-weighted echo planar imaging sequence and two b-values (b50 = 50 s/mm² and b800 = 800 s/mm²). The severity of the cardiac motion artifact in the left liver lobe was rated by two experienced radiologists for both b-values with a 5 point Likert scale. Additionally, the normalized signal S(b800)/S(b50) in the left liver lobe was computed. The Wilcoxon signed-rank test was used comparing the scores of the two readers obtained in inspiration and expiration, and to compare the normalized signal in inspiration and expiration.ResultsThe normalized signal in inspiration was slightly higher than in expiration (0.349±0.077 vs 0.336±0.058), which would indicate a slight reduction of the cardiac motion artifact, but this difference was not significant (p = 0.24). In the qualitative evaluation, the readers did not observe a significant difference for b50 (reader 1: p = 0.61; reader 2: p = 0.18). For b800, reader 1 observed a significant difference of small effect size favouring expiration (p = 0.03 with a difference of mean Likert scores of 0.27), while reader 2 observed no significant difference (p = 0.62).ConclusionAcquiring the data in inspiration does not lead to a markedly reduced cardiac motion artifact in diffusion-weighted imaging of the left liver lobe and is in this regard not to be preferred over acquiring the data in expiration.

Simultaneous Transcranial Magnetic Stimulation and Functional Magnetic Resonance Imaging: Aspects of Technical Implementation

The simultaneous transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) offers a unique opportunity to non-invasively stimulate brain circuits while simultaneously monitoring changes in brain activity. However, to take advantage of this multimodal technique, some technical issues need to be considered/addressed. In this work, we evaluated technical issues associated with the setup and utilization of this multimodal tool, such as the use of a large single-channel radio frequency (rf) coil, and the artifacts induced by TMS when interleaved with the echo-planar imaging (EPI) sequence. We demonstrated that good image quality can be achieved with this rf coil and that the adoption of axial imaging orientation in conjunction with a safe interval of 100 ms, between the TMS pulse and imaging acquisition, is a suitable combination to eliminate potential image artifacts when using the combined TMS-fMRI technique in 3-T MRI scanners.

Investigation of intravoxel incoherent motion tensor imaging for the characterization of the in vivo human heart

To investigate intravoxel incoherent motion (IVIM) tensor imaging of the in vivo human heart and elucidate whether the estimation of IVIM tensors is affected by the complexity of pseudo-diffusion components in myocardium. The cardiac IVIM data of 10 healthy subjects were acquired using a diffusion weighted spin-echo echo-planar imaging sequence along 6 gradient directions with 10 b values (0~400 s/mm2 ). The IVIM data of left ventricle myocardium were fitted to the IVIM tensor model. The complexity of myocardial pseudo-diffusion components was reduced through exclusion of low b values (0 and 5 s/mm2 ) from the IVIM curve-fitting analysis. The fractional anisotropy, mean fraction/mean diffusivity, and Westin measurements of pseudo-diffusion tensors (fp and D*) and self-diffusion tensor (D), as well as the angle between the main eigenvector of fp (or D*) and that of D, were computed and compared before and after excluding low b values. The fractional anisotropy values of fp and D* without low b value participation were significantly higher (P < .001) than those with low b value participation, but an opposite trend was found for the mean fraction/diffusivity values. Besides, after removing low b values, the angle between the main eigenvector of fp (or D*) and that of D became small, and both fp and D* tensors presented significant decrease of spherical components and significant increase of linear components. The presence of multiple pseudo-diffusion components in myocardium indeed influences the estimation of IVIM tensors. The IVIM tensor model needs to be further improved to account for the complexity of myocardial microcirculatory network and blood flow.

Development of fast multi‐slice apparent T1 mapping for improved arterial spin labeling MRI measurement of cerebral blood flow

To develop fast multi-slice apparent T1 (T1app ) mapping for accurate cerebral blood flow (CBF) quantification with arterial spin labeling (ASL) MRI. Fast multi-slice T1app was measured using a modified inversion recovery echo planar imaging (EPI) sequence with simultaneous application of ASL tagging radiofrequency (RF) and gradient pulses. The fast multi-slice T1app measurement was compared with the single-slice T1app imaging approach, repeated per slice. CBF was assessed in healthy adult Wistar rats (N = 5) and rats with acute stroke 24 hours after a transient middle cerebral artery occlusion (N = 5). The fast multi-slice T1app measurement was in good agreement with that of a single-slice T1app imaging approach (Lin's concordance correlation coefficient = 0.92). CBF calculated using T1app reasonably accounted for the finite labeling RF duration, whereas the routine T1 -normalized ASL MRI underestimated the CBF, particularly at short labeling durations. In acute stroke rats, the labeling time and the CBF difference (ΔCBF) between the contralateral normal area and the ischemic lesion were significantly correlated when using T1 -normalized perfusion calculation (R = 0.844, P = .035). In comparison, T1app -normalized ΔCBF had little labeling time dependence based on the linear regression equation of ΔCBF = -0.0247*τ + 1.579 mL/g/min (R = -0.352, P = .494). Our study found fast multi-slice T1app imaging improves the accuracy and reproducibility of CBF measurement.

Prediction of Gleason Grade Group of Prostate Cancer on Multiparametric MRI using Deep Machine Learning Models

The Gleason Grade (GG) Group system has been introduced recently for more accurate stratification of prostate cancer (PCa). The grading system is based on the histologic patterns which is accessed from needle core biopsy, therefore it could be negatively impacted by the intratumor heterogeneity. We aim to develop a deep learning algorithm to predict GG groups using multiparametric magnetic resonance images (mp-MRI). We studied a retrospective collection of 201 patients with 320 lesions from the SPIE-AAPM-NCI PROSTATEx Challenge (https://doi.org/10.7937/K9TCIA.2017.MURS5CL), among which 98 patients with 110 lesions with GG available from biopsy. And the number of lesions in each subgroup was 36, 39, 20, 8, and 7, respectively, for GG 1-5. The images were acquired on two different types of Siemens 3T MR scanners. T2W images were acquired using a turbo spin echo sequence and had a resolution of around 0.5 mm in plane and a slice thickness of 3.6 mm. The DWI series were acquired with a single-shot echo planar imaging sequence with a resolution of 2 mm in-plane and 3.6 mm slice thickness and with diffusion-encoding gradients in three directions. Three b-values were acquired (50, 400, and 800 s/mm2), and subsequently, the ADC map was calculated by the scanner software. Image pre-processing included registration and normalization. Image rotation and scaling were also used to increase the sample size and re-balance the number of lesions in various GG. To prevent over-fitting on a small sample size, we implemented a transfer learning model by carrying over the features learned from the malignancy classification of 320 lesions from our previous model into the GG prediction. And we replaced the end-to-end convolutional neural network (CNN) training model with a combination of feature extraction using CNN and classification using weighted extreme learning machine (wELM). Features from the best performing model were extracted to represent each lesion, and those from the last convolutional layer were found constantly better than from all other layers. Based on 3-fold cross validation, the average validation results for sensitivity, specificity, positive predictive value, and negative predictive value for differentiation of each GG (1-5) were (1, 0.99, 0.97, 1), (0.69, 0.85, 0.73, 0.83), (0.9, 0.69, 0.46, 0.97), (0.89, 0.64, 0.16, 0.99), and (1, 0.78, 0.39, 1), respectively. GG4 had the highest false positive values. GG 3 was often misclassified as GG 4. Results of GG3-5 vs. GG1-2 were (0.82, 0.87, 0.76, 0.92). The stratification of GG4-5 vs. GG1-3 was (0.87, 0.81, 0.42, 0.98). This work has made substantial progress tackling the challenging task of GG prediction from mp-MRI due to a smaller and unbalanced data size by transferring knowledge from a malignancy classification task we developed earlier. The combined feature extraction using deep learning model and weighted extreme learning machine classifier has shown promising results for the GG prediction. This work was supported by a Research Scholar Grant, RSG-15-137-01-CCE from the American Cancer Society.

Altered Dynamic Functional Connectivity in Patients With Mitochondrial Encephalomyopathy With Lactic Acidosis and Stroke-Like Episodes (MELAS) at Acute and Chronic Stages: Shared and Specific Brain Connectivity Abnormalities.

Mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) is a rare maternally inherited genetic disease; however, little is known about its underlying brain basis. Furthermore, the dynamic functional connectivity (dFC) of brain networks in MELAS has not been explored. To investigate the abnormalities of dFC in patients with MELAS at the acute and chronic stages, and to determine the possible relations between dynamic connectivity alterations and volumes of stroke-like lesions (SLLs). Prospective. Twenty-two MELAS patients at the acute stage, 23 MELAS patients at the chronic stage, and 22 healthy controls. Single-shot gradient-recalled echo planar imaging (EPI) sequence at 3T. Dynamic FC states were estimated using the sliding window approach and k-means clustering analyses. Combined with graph theory, the topological properties of the dFC network were also accessed. Permutation test, Pearson correlation coefficient, and false discovery rate correction. We identified four dFC states and found that MELAS patients (especially at the acute stage) spent more time in a state with weaker connectivity (state 1) and less time in states with stronger connectivity. In addition, volumes of acute SLLs were positively correlated with mean dwell time in state 1 (r = 0.539, P < 0.05) and negatively correlated with the number of transitions (r = -0.520, P < 0.05). Furthermore, MELAS patients at the acute stage exhibited significantly increased global efficiency (P < 0.01) and decreased local efficiency (P < 0.001) compared to the controls and the patients at the chronic stage. Patients at the chronic stage only showed significantly (P < 0.001) decreased local efficiency compared to the controls. Our findings suggest similar and distinct dFC alterations in MELAS patents at the acute and chronic stages, providing novel insights for understanding the neuropathological mechanisms of MELAS. Level of Evidence 2 Technical Efficacy Stage Stage 2 J. MAGN. RESON. IMAGING 2021;53:427-436.

Simultaneous multi-slice spin- and gradient-echo dynamic susceptibility-contrast perfusion-weighted MRI of gliomas.

Although combined spin- and gradient-echo (SAGE) dynamic susceptibility-contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T1 -shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi-band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR2 *(t) and ΔR2 (t) curves were derived to calculate dynamic signal-to-noise ratio (dSNR), ΔR2 *- and ΔR2 -based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal-appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal-appearing gray matter were not statistically significant between the two protocols. ΔR2 *- and ΔR2 -rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors.

Diffusion tensor imaging of rectal carcinoma: Clinical evaluation and its correlation with histopathological findings

ObjectiveThis study sought to assess the feasibility of diffusion tensor imaging (DTI) to noninvasively evaluate histological grade and lymph node metastasis in patients with rectal carcinoma (RC). MethodsThirty-seven consecutive patients with histologically confirmed RC were examined by 1.5-T MRI. DTI was performed using a single-shot echo-planar imaging sequence with b values of 0 and 1000 s/mm2 and motion-probing gradients in nine noncollinear directions. Fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) maps were compared with histopathological findings. ResultsThe FA values (0.357 ± 0.047) of the RCs were significantly lower than those of the normal rectal wall, muscle, prostate, and uterus (P < 0.001 for all), while the AD, MD, and RD values (1.221 ± 0.131, 0.804 ± 0.075, and 0.667 ± 0.057 × 10−3 mm2/s, respectively) were also significantly lower than their respective normal values (P < 0.001 for all). The FA, AD, MD, and RD values for RC additionally showed significant inverse correlations with histological grades (r = −0.781, r = −0.750, r = −0.718, and r = −0.682, respectively; P < 0.001 for all). Further, the FA (0.430 vs. 0.611), AD (1.246 vs. 1.608 × 10−3 mm2/s), MD (0.776 vs. 1.036 × 10−3 mm2/s), and RD (0.651 vs. 0.824 × 10−3 mm2/s) (P < 0.001 for all) of the metastatic and nonmetastatic lymph nodes were significantly different. ConclusionsDTI may be clinically useful for the noninvasive evaluation of histological grade and lymph node metastasis in patients with RC.