High-resolution Diffusion-weighted Imaging Research Articles

High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance.

Majority of men with low-risk prostate cancer can be managed with active surveillance (AS). This study evaluates a high-resolution diffusion-weighted imaging (HR-DWI) technique to predict adverse biopsy histology (AH), defined as Gleason score ≥7 on any biopsy or ≥3 increase in number of positive biopsy cores on systematic biopsies. We test the hypothesis that high-grade disease and progressing disease undergo subtle changes during even short intervals that can be detected by HR-DWI. In a prospective clinical trial, serial multiparametric MRIs, incorporating HR-DWI and standard DWI (S-DWI) were performed approximately 12 months apart prior to prostate biopsy (n = 59). HR-DWI, which uses reduced field-of-view and motion compensation techniques, was compared with S-DWI. HR-DWI had a 3-fold improvement in spacial resolution compared with S-DWI as confirmed using imaging phantoms. For detecting AH, multiparametric MRI using HR-DWI had a sensitivity of 75% and specificity of 83.9%, and MRI using S-DWI had a sensitivity of 71.4% and specificity of 54.8%. The AUC for HR-DWI was significantly higher (0.794 vs. 0.631, P = 0.014). Secondary analyses of univariable predictors of AH showed tumor size increase [OR 16.8; 95% confidence interval (CI): 4.06-69.48; P < 0.001] and apparent diffusion coefficient (ADC) decrease (OR 5.06; 95% CI: 1.39-18.38; P = 0.014) on HR-DWI were significant predictors of AH. HR-DWI outperforms S-DWI in predicting AH. Patient with AH have tumors that change in size and ADC that could be detected using HR-DWI. Future studies with longer follow-up should assess HR-DWI for predicting disease progression during AS. We report on a prospective clinical trial using a MRI that has three times the resolution of standard MRI. During AS for prostate cancer, two high-resolution MRIs performed approximately a year apart can detect tumor changes that predict the presence of aggressive cancers that should be considered for curative therapy such as prostatectomy or radiation.

Unenhanced Breast MRI With Diffusion-Weighted Imaging for Breast Cancer Detection: Effects of Training on Performance and Agreement of Subspecialty Radiologists.

To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm² was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive. The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4-79.9), 90.8% (95% CI: 85.6-94.2), and 83.5% (95% CI: 78.6-87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8-97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9-89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1-79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52-0.63) before training and 0.68 (95% CI: 0.62-0.74) after training, with a difference of 0.11 (95% CI: 0.02-0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69-0.74) before training and 0.79 (95% CI: 0.76-0.80) after training (P = 0.002). Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.

Risk prediction of CISS classification in endovascular treatment of basilar artery stenosis

ObjectiveTo investigate the incidence of ischemic stroke complications after endovascular treatment for basilar artery stenosis used preoperative high-resolution magnetic resonance vascular wall imaging (HRMR/VWI) and diffusion-weighted imaging (DWI). MethodsThe clinical data of 47 patients with severe symptomatic basilar artery stenosis (stenosis rate ≥70 %) treated with endovascular therapy at the Neuro-interventional Center from December 2017 to December 2021 were retrospectively analyzed. High-resolution magnetic resonance angiography (HRMR VWI) and DWI were used to evaluate the location of atherosclerotic plaque at basilar artery stenosis and the distribution of cerebral infarction lesions in all patients before surgery.According to the CISS classification system for ischemic stroke, patients were divided into a perforation group and a hypoperfusion group, and the general situation, plaque distribution, and incidence of ischemic stroke complications 7 days after endovascular treatment in the two groups were analyzed. ResultsThere was no significant difference in baseline data between the two groups. After 7 days of intravascular treatment, the incidence of ischemic stroke was higher in the perforation group (20.0 %) than in the hypoperfusion group (0.0 %), and the difference was statistically significant (P = 0.027). A significant association was found between the perforation group and the hypoperfusion group for the incidence of ischemic stroke at 7 days (P = 0.003, OR = 2.347; 95 % CI = 2.056–4.268). There were a higher proportion of ventral plaques (74.1 %) and a lower proportion of dorsal plaques (33.3 %) in the hypoperfusion group, which were 15.0 % and 90.0 % in the perforation group, respectively (χ2 = 16.045, P < 0.001; χ2 = 15.092, P < 0.001). There was no significant difference in the proportion of left and right plaques between the two groups. ConclusionsThe risk of ischemic stroke is greater in patients with perforator artery obstruction undergoing endovascular therapy, and lower in patients with hypoperfusion/embolus removal.

High-resolution Diffusion-weighted Imaging for the Diagnosis of Endometrial and Cervical Cancer

High-resolution Diffusion-weighted Imaging for the Diagnosis of Endometrial and Cervical Cancer

Detection of brain lesions after catheter ablation depends on imaging criteria: insights from AXAFA-AFNET 5 trial.

Left atrial catheter ablation is well established in patients with symptomatic atrial fibrillation (AF) but associated with risk of embolism to the brain. The present analysis aims to assess the impact of diffusion-weighted imaging (DWI) slice thickness on the rate of magnetic resonance imaging (MRI)-detected ischaemic brain lesions after ablation. AXAFA-AFNET 5 trial (NCT02227550) participants underwent MRI using high-resolution (hr) DWI (slice thickness: 2.5-3 mm) and standard DWI (slice thickness: 5-6 mm) within 3-48 h after ablation. In 321 patients with analysable brain MRI (mean age 64 years, 33% female, median CHA2DS2-VASc 2), hrDWI detected at least one acute brain lesion in 84 (26.2%) patients and standard DWI in 60 (18.7%; P < 0.01) patients. High-resolution diffusion-weighted imaging detected more lesions compared to standard DWI (165 vs. 104; P < 0.01). The degree of agreement for lesion confirmation using hrDWI vs. standard DWI was substantial (κ = 0769). Comparing the proportion of DWI-detected lesions, lesion distribution, and total lesion volume per patient, there was no difference in the cohort of participants undergoing MRI at 1.5 T (n = 52) vs. 3 T (n = 269). The pre-specified AXAFA-AFNET 5 sub-analysis revealed significantly increased rates of MRI-detected acute brain lesions using hrDWI instead of standard DWI in AF patients undergoing ablation. In comparison to DWI slice thickness, MRI field strength had a no significant impact in the trial. Comparing the varying rates of ablation-related MRI-detected brain lesions across previous studies has to consider these technical parameters. Future studies should use hrDWI, as feasibility was demonstrated in the multicentre AXAFA-AFNET 5 trial.

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.

Changes in the superior longitudinal fasciculus and anterior thalamic radiation in the left brain are associated with developmental dyscalculia.

Developmental dyscalculia is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood lowering the individual's quality of life. However, the neural correlates of developmental dyscalculia are poorly understood. This study aimed to identify brain structural connectivity alterations in developmental dyscalculia. All participants were recruited from a large scale, non-referred population sample in a longitudinal design. We studied 10 children with developmental dyscalculia (11.3 ± 0.7 years) and 16 typically developing peers (11.2 ± 0.6 years) using diffusion-weighted magnetic resonance imaging. We assessed white matter microstructure with tract-based spatial statistics in regions-of-interest tracts that had previously been related to math ability in children. Then we used global probabilistic tractography for the first time to measure and compare tract length between developmental dyscalculia and typically developing groups. The high angular resolution diffusion-weighted magnetic resonance imaging and crossing-fiber probabilistic tractography allowed us to evaluate the length of the pathways compared to previous studies. The major findings of our study were reduced white matter coherence and shorter tract length of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the developmental dyscalculia group. Furthermore, the lower white matter coherence and shorter pathways tended to be associated with the lower math performance. These results from the regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might be related to developmental dyscalculia in children.

The magnetic resonance characteristics of sinonasal rhabdomyosarcoma in adults: analysis of 27 cases and comparison with pathological subtypes

BackgroundSinonasal rhabdomyosarcoma (RMS) in adults is extremely rare, and early diagnosis and treatment are crucial to improve the patient’s prognosis. The purpose of this study was to evaluate the magnetic resonance imaging (MRI) findings of sinonasal RMS in adults and analyze the correlations between the imaging features and pathological subtypes.MethodsWe reviewed 27 patients with pathologically proven RMS of the nasal cavity and paranasal sinuses, including embryonal RMS (ERMS) in 14 patients, alveolar RMS (ARMS) in seven patients, and mixed-type RMS in six patients. Conventional MRI was performed in all 27 patients, and high-resolution diffusion-weighted imaging was conducted in 25 patients. The tumor location, size, morphological features, signal intensity, texture, contrast enhancement characteristics, lymph node metastases, apparent diffusion coefficients (ADCs), and involvement of local soft tissues were independently assessed by two authors.ResultsOn MR imaging, sinonasal RMS appeared isointense on T1-weighted imaging in 21 cases (77.8%) and heterogeneously hyperintense on T2-weighted imaging in 18 patients (66.7%). After enhancement, the tumors were heterogeneously enhanced in 24 cases (88.9%). Botryoid enhancement with multiple small rings resembling bunches of grapes was found in 15 cases (55.6%). Mucosal invasion of the maxillary sinus was identified in 51.9% patients. Skull and orbit involvement were found in 55.6% and 81.5% patients, respectively. Lymph node metastasis was seen in 18 cases (66.7%). There were significant differences in botryoid enhancement (P = 0.044) and skull involvement (P = 0.044) among different histological subtypes. The mean ADC value of RMS was 0.73 ± 0.082 × 10–3 mm2/s, and there was no significant difference among different histological subtypes.ConclusionsSome characteristic MRI findings such as botryoid enhancement in the ethmoid sinus, involvement of the orbit and skull, and a lower ADC value can provide important clues for preoperative diagnosis of sinonasal RMS in adults. Further, botryoid enhancement was more common in ERMS, while skull involvement was more common in ARMS.

High-resolution multi-shot diffusion imaging of structural networks in healthy neurocognitive aging

Healthy neurocognitive aging has been associated with the microstructural degradation of white matter pathways that connect distributed gray matter regions, assessed by diffusion-weighted imaging (DWI). However, the relatively low spatial resolution of standard DWI has limited the examination of age-related differences in the properties of smaller, tightly curved white matter fibers, as well as the relatively more complex microstructure of gray matter. Here, we capitalize on high-resolution multi-shot DWI, which allows spatial resolutions < 1 mm3 to be achieved on clinical 3T MRI scanners. We assessed whether traditional diffusion tensor-based measures of gray matter microstructure and graph theoretical measures of white matter structural connectivity assessed by standard (1.5 mm3 voxels, 3.375 μl volume) and high-resolution (1 mm3 voxels, 1μl volume) DWI were differentially related to age and cognitive performance in 61 healthy adults 18–78 years of age. Cognitive performance was assessed using an extensive battery comprising 12 separate tests of fluid (speed-dependent) cognition. Results indicated that the high-resolution data had larger correlations between age and gray matter mean diffusivity, but smaller correlations between age and structural connectivity. Moreover, parallel mediation models including both standard and high-resolution measures revealed that only the high-resolution measures mediated age-related differences in fluid cognition. These results lay the groundwork for future studies planning to apply high-resolution DWI methodology to further assess the mechanisms of both healthy aging and cognitive impairment.

Heterotopic connectivity of callosal dysgenesis in mice and humans.

The corpus callosum (CC), the largest brain commissure and the primary white matter pathway for interhemispheric cortical connectivity, was traditionally viewed as a predominantly homotopic structure, connecting mirror areas of the cortex. However, new studies verified that most callosal commissural fibers are heterotopic. Recently, we reported that ~75% of the callosal connections in the brains of mice, marmosets, and humans are heterotopic, having an essential role in determining the global properties of brain networks. In the present study, we leveraged high-resolution diffusion-weighted imaging and graph network modeling to investigate the relationship between heterotopic and homotopic callosal fibers in human subjects and in a spontaneous mouse model of Corpus Callosum Dysgenesis (CCD), a congenital developmental CC malformation that leads to widespread whole-brain reorganization. Our results show that the CCD brain is more heterotopic than the normotypical brain, with both mouse and human CCD subjects displaying highly variable heterotopicity maps. CCD mice have a clear heterotopicity cluster in the anterior CC, while hypoplasic humans have strongly variable patterns. Graph network-based connectivity profile showed a direct impact of heterotopic connections on CCD brains altering several network-based statistics. Our collective results show that CCD directly alters heterotopic connections and brain connectivity.

High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy

Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss.In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6–1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3rd order of spherical harmonics. Image reconstruction was performed using static ΔB0 field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm2 in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

Diagnostic accuracy of MRI for evaluating myometrial invasion in endometrial cancer: a comparison of MUSE-DWI, rFOV-DWI, and DCE-MRI.

To compare the image quality of high-resolution diffusion-weighted imaging (DWI) using multiplexed sensitivity encoding (MUSE) versus reduced field-of-view (rFOV) techniques in endometrial cancer (EC) and to compare the diagnostic performance of these techniques with that of dynamic contrast-enhanced (DCE) MRI for assessing myometrial invasion of EC. MUSE-DWI and rFOV-DWI were obtained preoperatively in 58 women with EC. Three radiologists assessed the image quality of MUSE-DWI and rFOV-DWI. For 55 women who underwent DCE-MRI, the same radiologists assessed the superficial and deep myometrial invasion using MUSE-DWI, rFOV-DWI, and DCE-MRI. Qualitative scores were compared using the Wilcoxon signed-rank test. Receiver operating characteristic analysis was performed to compare the diagnostic performance. Artifacts, sharpness, lesion conspicuity, and overall quality were significantly better with MUSE-DWI than with rFOV-DWI (p < 0.05). The area under the curve (AUC) of MUSE-DWI, rFOV-DWI, and DCE-MRI for the assessment of myometrial invasion were not significantly different except for significantly higher AUC of MUSE-DWI than that of DCE-MRI for superficial myometrial invasion (0.76 for MUSE-DWI and 0.64 for DCE-MRI, p = 0.049) and for deep myometrial invasion (0.92 for MUSE-DWI and 0.80 for DCE-MRI, p = 0.022) in one observer, and that of rFOV-DWI for deep myometrial invasion in another observer (0.96 for MUSE-DWI and 0.89 for rFOV-MRI, p = 0.048). MUSE-DWI exhibits better image quality than rFOV-DWI. MUSE-DWI and rFOV-DWI shows almost equivalent diagnostic performance compared to DCE-MRI for assessing superficial and deep myometrial invasion in EC although MUSE-DWI may be helpful for some radiologists.

Histogram analysis of multi-model high-resolution diffusion-weighted MRI in breast cancer: correlations with molecular prognostic factors and subtypes.

To investigate the correlations between quantitative diffusion parameters and prognostic factors and molecular subtypes of breast cancer, based on a single fast high-resolution diffusion-weighted imaging (DWI) sequence with mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) models. A total of 143 patients with histopathologically verified breast cancer were included in this retrospective study. The multi-model DWI-derived parameters were quantitatively measured, including Mono-ADC, IVIM-D, IVIM-D*, IVIM-f, DKI-Dapp, and DKI-Kapp. In addition, the morphologic characteristics of the lesions (shape, margin, and internal signal characteristics) were visually assessed on DWI images. Next, Kolmogorov-Smirnov test, Mann-Whitney U test, Spearman's rank correlation, logistic regression, receiver operating characteristic (ROC) curve, and Chi-squared test were utilized for statistical evaluations. The histogram metrics of Mono-ADC, IVIM-D, DKI-Dapp, and DKI-Kapp were significantly different between estrogen receptor (ER)-positive vs. ER-negative groups, progesterone receptor (PR)-positive vs. PR-negative groups, Luminal vs. non-Luminal subtypes, and human epidermal receptor factor-2 (HER2)-positive vs. non-HER2-positive subtypes. The histogram metrics of Mono-ADC, DKI-Dapp, and DKI-Kapp were also significantly different between triple-negative (TN) vs. non-TN subtypes. The ROC analysis revealed that the area under the curve considerably improved when the three diffusion models were combined compared with every single model, except for distinguishing lymph node metastasis (LNM) status. For the morphologic characteristics of the tumor, the margin showed substantial differences between ER-positive and ER-negative groups. Quantitative multi-model analysis of DWI showed improved diagnostic performance for determining the prognostic factors and molecular subtypes of breast lesions. The morphologic characteristics obtained from high-resolution DWI can be identifying ER statuses of breast cancer.

Peak width of skeletonized mean diffusivity and cognitive performance in cerebral amyloid angiopathy.

Cerebral Amyloid Angiopathy (CAA) is a cerebral small vessel disease that can lead to microstructural disruption of white matter (WM), which can be measured by the Peak Width of Skeletonized Mean Diffusivity (PSMD). We hypothesized that PSMD measures would be increased in patients with CAA compared to healthy controls (HC), and increased PSMD is associated with lower cognitive scores in patients with CAA. Eighty-one probable CAA patients without cognitive impairment who were diagnosed with Boston criteria and 23 HCs were included. All subjects underwent an advanced brain MRI with high-resolution diffusion-weighted imaging (DWI). PSMD scores were quantified from a probabilistic skeleton of the WM tracts in the mean diffusivity (MD) image using a combination of fractional anisotropy (FA) and the FSL Tract-Based Spatial Statistics (TBSS) algorithm (www.psmd-marker.com). Within CAA cohort, standardized z-scores of processing speed, executive functioning and memory were obtained. The mean of age and sex were similar between CAA patients (69.6 ± 7.3, 59.3% male) and HCs (70.6 ± 8.5, 56.5% male) (p = 0.581 and p = 0.814). PSMD was higher in the CAA group [(4.13 ± 0.94) × 10-4 mm2/s] compared to HCs [(3.28 ± 0.51) × 10-4 mm2/s] (p < 0.001). In a linear regression model corrected for relevant variables, diagnosis of CAA was independently associated with increased PSMD compared to HCs (ß = 0.45, 95% CI 0.13-0.76, p = 0.006). Within CAA cohort, higher PSMD was associated with lower scores in processing speed (p < 0.001), executive functioning (p = 0.004), and memory (0.047). Finally, PSMD outperformed all other MRI markers of CAA by explaining most of the variance in models predicting lower scores in each cognitive domain. Peak Width of Skeletonized Mean Diffusivity is increased in CAA, and it is associated with worse cognitive scores supporting the view that disruption of white matter has a significant role in cognitive impairment in CAA. As a robust marker, PSMD can be used in clinical trials or practice.

High-resolution diffusion-weighted imaging compared with conventional diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging with regard to image quality and assessment of breast cancer morphology

To evaluate the image quality and tumor morphology depiction ability of high resolution (HR) diffusion- weighted imaging (f-DWI) in comparison to conventional DWI (c-DWI) and dynamic contrast- enhanced magnetic resonance imaging (DCE-MRI) in the primary breast cancer setting. The f-DWI, c-DWI, and DCE-MRIs of 160 malignant breast masses were evaluated retrospectively by two independent radiologists. Data on image quality [sharpness, distortion, and perceived signalto- noise ratio (SNR)], apparent diffusion coefficient (ADC) value, lesion size, and tumor morphology (shape, margin, and internal pattern) obtained on f-DWI, c-DWI, and DCE-MRI were compared. Consistency between the readers and imaging methods for morphological parameters was analyzed. The ADC values measured on f-DWI were significantly lower than those measured on c-DWI for both readers (P < 0.001 for each), whereas mean lesion size was significantly larger in c-DWI than in f-DWI and DCE-MRI for both readers (P < 0.001 for each). Higher consistency values were obtained for f-DWI compared with c-DWI when correlated with DCE-MRI for each morphological parameter. The least distorted images were obtained using DCE-MRI compared with c-DWI and f-DWI for both readers, whereas the highest distortion scores were obtained using c-DWI. Sharpness and perceived SNR scores were rated as significantly higher for f-DWI and DCE-MRI images compared with c-DWI by both readers (P < 0.001 for all). The concordance between c-DWI and DCE-MRI was fair to slight (κ = 0.15 to 0.41), whereas concordance between f-DWI and DCE-MRI was significantly better (κ = 0.68 to 0.87) for each reader and for all morphological parameters (P < 0.001). The highest concordance between the readers was achieved in margin assessment (κ = 0.87 to 0.89) regardless of the MRI method, followed by shape and internal pattern parameters (κ = 0.63 to 0.79). The results demonstrated that f-DWI produces higher-quality images than c-DWI, enabling the morphological features to be identified in similar detail to that offered by HR DCE-MRI. Accordingly, f-DWI, as a method that highly correlates with DCE in determining the morphological characteristics of breast cancers, seems to have potential in the evaluation of breast tumors in patients for whom the use of contrast media is contraindicated.

Undersampled single-shell to MSMT fODF reconstruction using CNN-based ODE solver

Background and Objective: Diffusion MRI (dMRI) has been considered one of the most popular non-invasive techniques for studying the human brain’s white matter (WM). dMRI is used to delineate the brain’s microstructure by approximating the WM region’s fiber tracts. The achieved fiber tracts can be utilized to assess mental diseases like Multiple sclerosis, ADHD, Seizures, Intellectual disability, and others. New techniques such as high angular resolution diffusion-weighted imaging (HARDI) have been developed, providing precise fiber directions, and overcoming the limitation of traditional DTI. Unlike Single-shell, Multi-shell HARDI provides tissue fractions for white matter, gray matter, and cerebrospinal fluid, resulting in a Multi-shell Multi-tissue fiber orientation distribution function (MSMT fODF). This MSMT fODF comes up with more precise fiber directions than a Single-shell, which helps to get correct fiber tracts. In addition, various multi-compartment diffusion models, including as CHARMED and NODDI, have been developed to describe the brain tissue microstructural information. This type of model requires multi-shell data to obtain more specific tissue microstructural information. However, a major concern with multi-shell is that it takes a longer scanning time restricting its use in clinical applications. In addition, most of the existing dMRI scanners with low gradient strengths commonly acquire a single b-value (shell) upto b=1000s/mm2 due to SNR (Signal-to-noise ratio) reasons and severe imaging artifacts.Methods: To address this issue, we propose a CNN-based ordinary differential equations solver for the reconstruction of MSMT fODF from under-sampled and fully sampled Single-shell (b=1000s/mm2) dMRI. The proposed architecture consists of CNN-based Adams-Bash-forth and Runge-Kutta modules along with two loss functions, including L1 and total variation.Results: We have shown quantitative results and visualization of fODF, fiber tracts, and structural connectivity for several brain regions on the publicly available HCP dataset. In addition, the obtained angular correlation coefficients for white matter and full brain are high, showing the proposed network’s utility.Finally, we have also demonstrated the effect of noise by adjusting SNR from 5 to 50 and observed the network robustness.Conclusion: We can conclude that our model can accurately predict MSMT fODF from under-sampled or fully sampled Single-shell dMRI volumes.

Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image

PurposeTo evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS). MethodsTwo experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses. ResultsThe area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83–0.95) for reader 1, and 0.89 (95% CI: 0.82–0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively. ConclusionOur results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.

Effect of Imaging Parameters for High-resolution Diffusion-weighted Imaging on Signal-to-noise Ratio and ADC in Prostate Examination

Readout-segmented echo-planar imaging (readout segmentation of long variable echo trains [RESOLVE]) can be set to higher resolution than single-shot echo planar imaging, but there is concern that the signal-to-noise ratio (SNR) is low. The purpose was to examine the effect of imaging parameters (repetition time: TR, number of excitations: NEX) for RESOLVE on SNR and apparent diffusion coefficient (ADC) value in 1.5 T MRI, assuming a prostate examination. We imaged eight healthy male volunteers at a b value of 800 s/mm2. SNR and ADC value were calculated by setting the ROI in the transition zone (TZ) and the peripheral zone (PZ) of the prostate. Then, 3 radiologists visually evaluated the graininess. In TZ, there was no significant difference in SNR with changing TR. In PZ, SNR increased with increasing TR. In PZ, median SNR was 8.1 [6.9-9.3] at TR=11000 ms and NEX=2. On the other hand, at TR=5000 ms and NEX=3,4, median SNRs were 8.5 [7.5-9.3] and 9.8 [8.8-11.2]. Moreover, NEX=5 with median SNR of 11.1 [10.7-11.7] was significant (p<0.008). Setting more NEX was more effective in increasing SNR. In addition, visual evaluation showed similar results. The ADC value in TZ was around 1404×10-6 mm2/s, and the ADC value in PZ was around 1469×10-6 mm2/s. There were no significant differences under each condition. In conclusion, NEX is more effective than TR for improving SNR both quantitatively and visually in PZ.

High-resolution Diffusion-weighted Imaging of the Prostate Using Multiplexed Sensitivity-encoding: Comparison with the Conventional and Reduced Field-of-view Techniques.

To compare objective and subjective image quality, lesion conspicuity, and apparent diffusion coefficient (ADC) of high-resolution multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) with conventional DWI (c-DWI) and reduced FOV DWI (rFOV-DWI) in prostate MRI. Forty-seven patients who underwent prostate MRI, including c-DWI, rFOV-DWI, and MUSE-DWI, were retrospectively evaluated. SNR and ADC of normal prostate tissue and contrast-to-noise ratio (CNR) and ADC of prostate cancer (PCa) were measured and compared between the three sequences. Image quality and lesion conspicuity were independently graded by two radiologists using a 5-point scale and compared between the three sequences. The SNR of normal prostate tissue was significantly higher with rFOV-DWI than with the other two DWI techniques (P ≤ 0.01). The CNR of the PCa was significantly higher with rFOV-DWI than with MUSE-DWI (P < 0.05). The ADC of normal prostate tissue measured by rFOV-DWI was lower than that measured by MUSE-DWI and c-DWI (P < 0.01), while there was no difference in the ADC of cancers. In the qualitative analysis, MUSE-DWI showed significantly higher scores than rFOV-DWI and c-DWI for visibility of anatomy and overall image quality in both readers, and significantly higher scores for distortion in one of the two readers (P < 0.001). There was no difference in lesion conspicuity between the three sequences. High-resolution MUSE-DWI showed higher image quality and reduced distortion compared to c-DWI, while maintaining a wide FOV and similar ADC quantification, although no difference in lesion conspicuity was observed.

Technical note: Revised projections onto convex sets reconstruction of multi-shot diffusion-weighted imaging.

High-resolution diffusion-weighted imaging (DWI) is usually achieved through multi-shot acquisitions and parallel imaging-based reconstructions. Multiple POCS (projections onto convex sets) based algorithms have been proposed for DWI reconstructions. However, the slow convergence of POCS and the suboptimal quality of the reconstructed images limit their applications. In this study, a revised POCS algorithm for multi-shot DWI reconstruction is proposed based on FISTA (fast iterative shrinkage-thresholding algorithm) to achieve faster convergence and higher accuracy. In FISTA, the next iteration is computed based on two previous iterations, instead of only the previous one, to improve the convergence speed. This scheme is adopted into the relevant POCS-based algorithms, including POCSENSE (POCS-based sensitivity-encoding), POCSMUSE (POCS-based multiplexed sensitivity-encoding), iPOCSMUSE (iterative POCSMUSE), and POCS-ICE (POCS-enhanced inherent correction of motion-induced phase errors) to address the slow convergence problem. Simulations and in vivo experiments were performed to evaluate the performance of the proposed method. Experimental results show that the proposed method enables faster convergence compared to the original POCS. For example, for a spiral DWI simulation using eight-shot interleaves and having SNR of 20dB, the iteration number needed for the revised POCS-ICE decreases by about 70% to achieve approximately the same nRMSE level as POCS-ICE. Additionally, it improves image quality in terms of fewer artifacts compared with the original POCS. The revised DWI reconstruction methods can achieve higher convergence rates than the original POCS-based algorithms and higher image quality with the same iteration numbers. As such, the proposed method can serve as a practical and efficient reconstruction method for multi-shot DWI.