Diffusion-weighted Magnetic Resonance Imaging Research Articles

Optimal timing of ultra-early diffusion-weighted MRI in out-of-hospital cardiac arrest patients based on a retrospective multicenter cohort study

Diffusion-weighted magnetic resonance imaging (DW-MRI) performed before target temperature management, within 6 h of return of spontaneous circulation (ROSC), is defined as ultra-early DW-MRI. In previous studies, high-signal intensity (HSI) on ultra-early DW-MRI can predict poor neurological outcomes (Cerebral Performance Category 3–5 at 6-months post-ROSC). We aimed to assess the optimal-timing for ultra-early DW-MRI to avoid false-negative outcomes post out-of-hospital cardiac arrest, considering cardiopulmonary resuscitation (CPR) factors. The primary outcomes were HSI in the cerebral cortex or deep gray matter on ultra-early DW-MRI. The impact of CPR factors and ROSC to DW-MRI scan-interval on HSI-presence was assessed. Of 206 included patients, 108 exhibited HSI-presence, exclusively associated with poor neurological outcomes. In multivariate regression analysis, ROSC to DW-MRI scan-interval (adjusted odds ratio [aOR], 1.509; 95% confidence interval (CI): 1.113–2.046; P = 0.008), low-flow time (aOR, 1.176; 95%CI: 1.121–1.233; P < 0.001), and non-shockable rhythm (aOR, 9.974; 95%CI: 3.363–29.578; P < 0.001) were independently associated with HSI-presence. ROSC to DW-MRI scan-interval cutoff of ≥ 2.2 h was particularly significant in low-flow time ≤ 21 min or shockable rhythm group. In conclusion, short low-flow time and shockable rhythm require a longer ROSC to DW-MRI scan-interval. Prolonged low-flow time and non-shockable rhythm reduce the need to consider scan-interval.

A Case of Growing Chronic Subdural Hematoma with Niveau Formation Showing an Enhanced Subdural Hyperintense Band on Magnetic Resonance Diffusion-weighted Imaging Over Time.

This case report describes an 84-year-old female patient with a growing chronic subdural hematoma (CSDH) that showed an enhanced subdural hyperintense band (SHB) on magnetic resonance (MR) diffusion-weighted imaging over time, indicating that it reflects fresh bleeding from the outer membrane covering the hematoma. The presence of SHB on MR diffusion-weighted imaging of CSDH, possibly reflecting hemorrhagic diathesis of the outer membrane, might be a predictor of enlargement of CSDH.

Preventive treatment effects on brain structures and functions in patients with chronic migraine: A multimodel magnetic resonance imaging study.

Patients with chronic migraine (CM) often exhibit structural and functional alterations in pain-matrix regions, but it remains unclear how preventive treatment affects these changes. Therefore, this study aimed to investigate the structural and functional changes in pain-matrix regions in CM patients after 6-month treatment. A total of 24 patients with CM and 15 healthy controls were recruited for this study. Patients were divided into responder group (N = 9) and non-responder group (N = 15). After completing the Migraine Disability Assessment (MIDAS) questionnaire, all patients underwent whole-brain high-resolution T1-weighted images, diffusion-weighted imaging, and resting-state functional magnetic resonance imaging at baseline and 6-month follow-up. Whole brain gray matter volume and white matter diffusion indices were analyzed using voxel-based analysis. Structural and functional connectivity analyses were performed to understand brain changes in patients after 6-month preventive treatment. The responder group exhibited significantly higher MIDAS scores than the non-responder group at baseline, but no significant difference between the two groups at follow-up. No significant interval change was noted in gray matter volume, white matter diffusion indices, and structural connectivity in CM patients after 6-month treatment. Nonetheless, the functional connectivity was significantly increased between occipital, temporal lobes and cerebellum, and was significantly decreased between parietal and temporal lobes after 6-month preventive treatment. We concluded that resting-state functional connectivity was suitable for investigating the preventive treatment effect on CM patients.

Soluble B-cell maturation antigen levels for disease monitoring in oligo- and non-secretory relapsed multiple myeloma

Soluble B-cell maturation antigen (sBCMA) is overexpressed on multiple myeloma (MM) cells. We investigated whether sBCMA levels correlated with other myeloma tumor volume indicators and its utility in monitoring oligo-secretory/non-secretory (O-S/Non-S) MM. In 115 patients with newly diagnosed MM, sBCMA was compared with M-protein levels, bone marrow plasma cells (BMPCs), circulating tumor cells (CTCs), and total diffusion volume (tDV; estimated by whole-body diffusion-weighted magnetic resonance imaging) at diagnosis. sBCMA levels increased significantly with International Staging System stage, chromosome 1q21 gain/amplification and CTC levels. sBCMA also correlated strongly with %BMPC (r = 0.65), moderately with tDV (r = 0.55) and paraprotein levels (involved immunoglobulin in IgG and IgA subtypes, r = 0.44 and 0.4; involved free light-chain levels in light-chain-only MM, r = 0.61, all P < 0.05). Longitudinal changes in sBCMA were consistent with disease status in both 17 O-S/Non-S and other secretory MM cases. Furthermore, sBCMA levels increased as early as 6 months pre-relapse in almost all O-S/Non-S relapsed patients. Thus, sBCMA correlates strongly with total tumor volume in MM, as assessed using different modalities. We suggest that sBCMA is useful, not only for monitoring responses in patients with O-S/Non-S MM but also for early relapse detection and prediction.

Diffusion MRI with Machine Learning

Abstract Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural connectivity. It is widely used for clinical assessment of disease and injury, and for neuroscience research. Analyzing the dMRI data to extract useful information for medical and scientific purposes can be challenging. The dMRI measurements may suffer from strong noise and artifacts, and may exhibit high inter-session and inter-scanner variability in the data, as well as inter-subject heterogeneity in brain structure. Moreover, the relationship between measurements and the phenomena of interest can be highly complex. Recent years have witnessed increasing use of machine learning methods for dMRI analysis. This manuscript aims to assess these efforts, with a focus on methods that have addressed data preprocessing and harmonization, microstructure mapping, tractography, and white matter tract analysis. We study the main findings, strengths, and weaknesses of the existing methods and suggest topics for future research. We find that machine learning may be exceptionally suited to tackle some of the difficult tasks in dMRI analysis. However, for this to happen, several shortcomings of existing methods and critical unresolved issues need to be addressed. There is a pressing need to improve evaluation practices, to increase the availability of rich training datasets and validation benchmarks, as well as model generalizability, reliability, and explainability concerns.

Deep learning reconstruction of diffusion-weighted brain MRI for evaluation of patients with acute neurologic symptoms

Purpose: We aimed to evaluate whether the deep-learning (DL) accelerated diffusion weighted image (DWI) is clinically feasible for evaluating patients with acute neurologic symptoms, regarding its shorter study time and acceptable image quality. Materials and methods: In this retrospective study, brain images obtained at DWI with a b-value of 0 s/mm2 and DWI with a b-value of 1000 s/mm2 (DWI 1000) from 321 consecutive patients with acute stroke-like symptom were reconstructed with and without DL algorithm. We compare the diagnostic performance between DL-DWI and conventional DWI for detecting brain lesions, including acute infarction. We assessed the diagnostic accuracy of conventional DWI and DL-DWI and compared the results. Qualitative analysis based on image quality was assessed and compared using a five-point visual scoring system. Apparent diffusion coefficients (ADCs) from DWI with and without DL were also compared. Results: The mean acquisition time for the DL-DWI (49 s) was significantly shorter (P < 0.001) than conventional DWI (165 s). Both DWI with and without DL showed similar performance in diagnosing brain lesions especially sensitivity (98.8% in both DWI and DL-DWI) and specificity (99.5% in both DWI and DL-DWI). Overall image quality, gray-white matter and deep gray matter differentiation of two sequences were similar. DL DWI showed more artifacts than DWI. Lesion conspicuity, especially smaller than 5 mm, was better with DL DWI than conventional DWI (p = 0.03). ADC values of white matter, deep gray matter, and pons with DL were lower than conventional DWI. Conclusions: Compared to conventional DWI, DL-DWI achieved comparable image quality and brain lesion visualization for acute neurological symptoms, with a significantly shorter scan time.

Enhancing diffusion-weighted prostate MRI through self-supervised denoising and evaluation

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique that provides information about the Brownian motion of water molecules within biological tissues. DWI plays a crucial role in stroke imaging and oncology, but its diagnostic value can be compromised by the inherently low signal-to-noise ratio (SNR). Conventional supervised deep learning-based denoising techniques encounter challenges in this domain as they necessitate noise-free target images for training. This work presents a novel approach for denoising and evaluating DWI scans in a self-supervised manner, eliminating the need for ground-truth data. By leveraging an adapted version of Stein’s unbiased risk estimator (SURE) and exploiting a phase-corrected combination of repeated acquisitions, we outperform both state-of-the-art self-supervised denoising methods and conventional non-learning-based approaches. Additionally, we demonstrate the applicability of our proposed approach in accelerating DWI scans by acquiring fewer image repetitions. To evaluate denoising performance, we introduce a self-supervised methodology that relies on analyzing the characteristics of the residual signal removed by the denoising approaches.

Magnetic resonance imaging and tractography of sensorimotor tracts in fetuses with intraventricular hemorrhage: feasibility and added prognostic value.

To assess the feasibility, characteristics and prognostic value of prenatal visualization of the corticospinal tracts (CSTs) using diffusion-weighted magnetic resonance imaging (MRI)-based tractography in fetuses with intraventricular hemorrhage (IVH). This was a retrospective single-center cohort study of singleton fetuses diagnosed with IVH on MRI from January 2011 to December 2018. The left and right CSTs were reconstructed according to an in-utero diffusion tensor imaging sequence using a multi-region of interest (ROI) deterministic tractography approach. The CSTs were segmented by two polygonal ROI: at the level of the posterior limb of the internal capsule and the crus cerebri. The morphology and integrity of the CSTs were assessed visually. Internal capsule and crus cerebri apparent diffusion coefficient and fractional anisotropy values were measured. Postnatal motor function data were obtained from the parents using the functional status scale. A total of 35 fetuses with IVH (mean gestational age, 29.1 ± 5.1 (range, 19.9-38.9) weeks) were included in the analysis. Parenchymal involvement on T2-weighted sequences was demonstrated in 19(54%) of the cohort. CST involvement correlated significantly with the presence of parenchymal damage on T2-weighted imaging (P = 0.02). Among liveborn cases, the rate of motor impairment was 14% (1/7) in children with intact CSTs compared with 100% (5/5) in cases in which the CSTs were impaired (P = 0.015). Fetal corticospinal tractography is feasible technically and offers valuable prognostic information. It enhances parental counseling by providing insights into potential motor outcome, underscoring its utility in complementing fetal neurosonography in cases of prenatal IVH. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

A controlled study of MR DWI, FS-PDW, and CE-T1W imaging for the evaluation of the internal opening of anal fistulas.

Anal fistula (AF) is an abnormal tunnel under the skin connecting the anal canal in the colon to the skin of buttocks. Fat-suppressed (FS) proton density-weighted (PDW) imaging is mainly used for the diagnosis of diseases involving bones and joints. Until now, its value in the diagnosis of anal fistula has been rarely reported. To compare three magnetic resonance imaging (MRI) sequences - diffusion-weighted imaging (DWI), FS-PDW), and contrast-enhanced (CE) T1-weighted (T1W) imaging - for the diagnostic value of the internal opening of AF. MRI scans of 132 patients suspected of having AF between December 2021 and April 2023 were retrospectively analyzed. In total, 65 patients who underwent preoperative MRI and were treated surgically were included. The lesion conspicuity and accuracy for featuring AF were calculated by evaluating the three imaging datasets DWI, FS-PDW, and CE-T1W imaging, with surgical findings serving as the reference standard for the presence of fistulas. The statistical analysis included the application of the chi-square test and Kruskal-Wallis test. In 65 patients with AF, 87 internal openings of AF were confirmed. In terms of the diagnostic accuracy of the internal openings, both FS-PDW and CE-T1W imaging sequences were significantly better than DWI sequences, and the difference was statistically significant (P < 0.05). The FS-PDW imaging sequence showed comparable diagnostic performance of the internal opening of AF to CE-T1W imaging, which can provide an important diagnostic basis for clinical procedures.

Diffusion-Weighted MRI Over Standard MRI for Differential Diagnosis between Mucopyocele and Mucoceles.

To determine the accuracy of conventional and diffusion-weighted (DWI) MRI for the differential diagnosis between mucopyocele and mucocele using surgical diagnosis as a reference. This retrospective study included patients referred to our institution between March 2017 and February 2024 for paranasal sinus MRI to characterize an expansile non-enhanced sinus filling on CT. The T1 and T2 signal intensities were recorded, as well as the presence of restriction diffusion, of the penumbra sign, the double rim sign, and the presence of parietal micro-abscesses. Quantitative apparent diffusion coefficient values were also recorded. The study included 74 patients aged 18 to 88 years (mean age: 60.4 ± 17.7 years). Of these, 43 had a mucopyocele and 31 had a mucocele. The T1 high signal intensity was different amongst groups as an hypersignal was present in 35.5% of mucoceles and only 4.7% of mucopyoceles (p = 0.02). The T2 signal did not differ between the two groups (p = 0.59). The double rim sign and the presence of parietal micro-abscesses demonstrated 96.8% and 100% specificities, respectively, but were predominantly located in the maxillary sinus. The penumbra sign exhibited a sensitivity of 60.5% and a specificity of 67.7%. All mucopyoceles exhibited a diffusion restriction with an apparent diffusion coefficient of less than 0.78 × 10-3 mm2/s. DWI is the most useful MRI tool for the accurate differential diagnosis between mucopyocele and mucocele in non-enhanced sinus fillings. III (case-control study) Laryngoscope, 2024.

Measurement of apparent diffusion coefficient (ADC) in fetal organs and placenta using 3 Tesla magnetic resonance imaging (MRI) across gestational ages

Diffusion-weighted imaging (DWI) is a technique used to probe the random microscopic motion of water protons in living tissue, represented by a parameter measurement of apparent diffusion coefficient (ADC) values. This study aimed to measure the ADC values of various fetal organs and placenta using 3T at various gestational ages. This was a prospective observational study. A total of 103 singleton pregnancies from 20 to 38 weeks of gestational age were included. Diffusion-weighted imaging was performed in the axial plane from the fetal head to the trunk with the following parameters: TR: 2000–2500 ms; TE: 88 ms; FOV: 250 mm; 256 matrix; slice thickness: 4 mm with a 0 mm gap; acquisition time: 1 min, 18 s. Diffusion gradient values were b = 0 and b = 700 s/mm2. ADC was measured in fetal brain regions (frontal white matter, occipital white matter, centrum semiovale, pons, thalamus, cerebellum, and fetal organs (lungs, kidney, and placenta). ANOVA was used to calculate the mean ADC values. Karl Pearson’s coefficient of correlation was used to evaluate the correlation between ADC values and increasing gestational age. The mean ADC values of brain regions were: frontal white matter (1.64 ± 0.08 × 10− 3 mm2 /s, F-39.10,p-<0.001), occipital white matter (1.64 ± 0.06 × 10− 3 mm2/s, F-26.14, p-<0.001), centrum semiovale (1.62 ± 0.03 × 10− 3 mm2/s, F-49.88,p-<0.001, pons (1.23 ± 0.09 × 10− 3 mm2/s F-9.14,p-<0.001) ), Thalamus (1.21 ± 0.07 × 10− 3 mm2/s, F-13.54,p-<0.001) and cerebellum (1.36 ± 0.10 × 10− 3 mm2 /s, F-4.19,p-<0.001). The mean ADC values of fetal organs were lung (1.92 ± 0.15 × 10− 3 mm2 /s, F-28.24, p-<0.001), kidney (1.34 ± 0.11 × 10− 3 mm2 /s, F-1.05, p- 0.37) and placenta (1.94 ± 0.11 × 10− 3 mm2 /s, F-160.33, p-<0.001). White-matter regions showed a significant positive correlation with increasing gestational age. Statistically, a negative correlation was observed between increasing gestational age and ADC measurements obtained in the thalamus, cerebellum, pons, and kidney. This will be one of the first few studies to provide the ADC values of the fetal brain and fetal organs using 3T MRI. The current study shows that diffusion-weighted MRI can offer a promising technique to evaluate the structural development of fetal organs and can potentially lead to a biomarker for predicting the functionality of the fetal organs in abnormalities.

The Role of Diffusion-Weighted MRI in Correlation with Contrast-Enhanced MRI and Histopathology in the Evaluation of Focal Liver Lesions

The Role of Diffusion-Weighted MRI in Correlation with Contrast-Enhanced MRI and Histopathology in the Evaluation of Focal Liver Lesions

Assessing tumor microstructure with time-dependent diffusion imaging: Considerations and feasibility on clinical MRI and MRI-Linac.

Quantitative imaging biomarkers (QIBs) can characterize tumor heterogeneity and provide information for biological guidance in radiotherapy (RT). Time-dependent diffusion MRI (TDD-MRI) derived parameters are promising QIBs, as they describe tissue microstructure with more specificity than traditional diffusion-weighted MRI (DW-MRI). Specifically, TDD-MRI can provide information about both restricted diffusion and diffusional exchange, which are the two time-dependent effects affecting diffusion in tissue, and relevant in tumors. However, exhaustive modeling of both effects can require long acquisitions and complex model fitting. Furthermore, several introduced TDD-MRI measurements can require high gradient strengths and/or complex gradient waveforms that are possibly not available in RT settings. In this study, we investigated the feasibility of a simple analysis framework for the detection of restricted diffusion and diffusional exchange effects in the TDD-MRI signal. To promote the clinical applicability, we use standard gradient waveforms on a conventional 1.5 T MRI system with moderate gradient strength (Gmax=45 mT/m), and on a hybrid 1.5 T MRI-Linac system with low gradient strength (Gmax=15 mT/m). Restricted diffusion and diffusional exchange were simulated in geometries mimicking tumor microstructure to investigate the DW-MRI signal behavior and to determine optimal experimental parameters. TDD-MRI was implemented using pulsed field gradient spin echo with the optimized parameters on a conventional MRI system and a MRI-Linac. Experiments in green asparagus and 10 patients with brain lesions were performed to evaluate the time-dependent diffusion (TDD) contrast in the source DW-images. Simulations demonstrated how the TDD contrast was able to differentiate only dominating diffusional exchange in smaller cells from dominating restricted diffusion in larger cells. The maximal TDD contrast in simulations with typical cancer cell sizes and in asparagus measurements exceeded 5% on the conventional MRI but remained below 5% on the MRI-Linac. In particular, the simulated TDD contrast in typical cancer cell sizes (r=5-10µm) remained below or around 2% with the MRI-Linac gradient strength. In patients measured with the conventional MRI, we found sub-regions reflecting either dominating restricted diffusion or dominating diffusional exchange in and around brain lesions compared to the noisy appearing white matter. On the conventional MRI system, the TDD contrast maps showed consistent tumor sub-regions indicating different dominating TDD effects, potentially providing information on the spatial tumor heterogeneity. On the MRI-Linac, the available TDD contrast measured in asparagus showed the same trends as with the conventional MRI but remained close to typical measurement noise levels when simulated in common cancer cell sizes. On conventional MRI systems with moderate gradient strengths, the TDD contrast could potentially be used as a tool to identify which time-dependent effects to include when choosing a biophysical model for more specific tumor characterization.

Changes in diffusion MRI and clinical motor function after physical/occupational therapies in toddler-aged children with spastic unilateral cerebral palsy.

Diffusion-weighted magnetic resonance imaging (DMRI) is a potential tool to assess changes in brain connectivity and microstructure resulting from physical and occupational therapy in young children with cerebral palsy. This works was carried out to assess whether DMRI can detect changes after 36 weeks of physical and occupational therapy in the microstructure and connectivity of the brains of children with cerebral palsy and determine whether imaging findings correlate with changes in clinical measures of motor function. Five children underwent anatomical MRI and DMRI and evaluations of motor function skills at baseline and after 36 weeks of intensive or once-weekly physical and occupational Perception-Action Approach therapies. Diffusion tensor imaging and constrained spherical deconvolution methods were used to calculate fractional anisotropy (FA) and fiber orientation distribution functions (fODFs), respectively. The fODFs were used to generate tractograms of the cerebrospinal tract (CST). After 36 weeks of physical and occupational therapy, all children showed increases in motor function. No changes were observed in anatomical MRI before and after therapy but CST tractography did show small differences indicating possible altered microstructure and connectivity in the brain. FA values along the CSTs, however, showed no significant changes. Reliable longitudinal DMRI can be employed in toddler-aged children with CP and DMRI has the potential to monitor neuroplastic changes in white matter microstructure. However, there is a high variability between subjects and clinical improvements were not always correlated with measures of FA along the CST.

Role of Magnetic Resonance Spectroscopy and Diffusion-weighted Imaging in the Evaluation of Supratentorial Brain Tumours with Histopathology Correlation at a Tertiary Care Hospital: An Observational Study

Abstract Background: Traditional magnetic resonance imaging (MRI) may face challenges in accurately discerning supratentorial malignancies. However, advanced techniques such as diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) have significantly enhanced diagnostic accuracy. Thus, the study aimed to evaluate the effectiveness of these non-invasive diagnostic methods in patients with suspected intracranial lesions. Materials and Methods: In this prospective observational study at Osmania General and Allied Hospitals, 40 eligible patients were enrolled. After applying the inclusion and exclusion criteria, MRI examinations were conducted at two hospitals utilising GE 1.5T and PHILIPS 1.5T 32-channel machines. Standardised brain sequences, encompassing T1- and T2-weighted scans, DWI, gradient-recalled echo and fluid-attenuated inversion recovery imaging, were systematically performed. In addition, post-contrast administration and contrast-enhanced MRS were employed. Results: In this study, a higher tumour incidence was observed in males (52%) compared to females (48%). The choline/creatine (CHO/Cr) ratio revealed more cases below 1.5 and fewer at the 3.1–3.5 level. Perilesional CHO/Cr ratio had the highest cases (21) at 1.1–2.0 and the lowest (2) at 3.1–4.0. Further analysis revealed significant differences in the mean CHO/Cr ratio amongst primary low-grade (1.8), primary high-grade (3.91) and metastatic tumours (7.23). The mean choline/N-acetyl aspartate (NAA) ratio also differed significantly amongst these tumour types, with choline/NAA and CHO/Cr ratios indicating statistical significance in distinguishing primary low-grade tumours. In addition, mean apparent diffusion coefficient values showed significant differences between primary low-grade tumours (1.1), primary high-grade tumours (0.87) and metastasis (0.855). Conclusion: This study underscores gender-related differences in supratentorial tumour susceptibility and highlights distinct tumour distributions based on grades. These findings emphasise the significance of considering gender, age and histopathological attributes when evaluating supratentorial tumours.

Comparison of Diffusion-weighted MRI using Singe-Shot Echo-planar Imaging (SS-EPI) and Split Acquisition of Fast Spin Echo Signal (SPLICE) Imaging, a non-EPI technique, in Tumors of the Head and Neck.

Diffusion-weighted imaging (DWI) using single-shot echo planar imaging (DW-EPI) is susceptible to distortions around air-filled cavities and dental fillings, typical for the head and neck area. Non-EPI, Split acquisition of fast spin echo signals for diffusion imaging (DWSPLICE) could reduce these distortions and enhance image quality, thereby potentially improving recurrence assessment in squamous cell carcinoma (SCC) of the head and neck region. This study evaluated whether DW-SPLICE is a viable alternative to DW-EPI through quantitative and qualitative analyses. The DW-SPLICE sequence was incorporated into the standard 3.0T head and neck MRI protocol with DW-EPI. Retrospective analysis was conducted on two subgroups: firstly benign or malignant lesions, and secondly post-treatment SCC recurrence. In both subgroups Image quality and distortion were scored by two independent radiologists, blinded for DW-technique, and evaluated using mixed-effect linear models. Lesion apparent diffusion coefficient (ADC) values were assessed with inter-class correlation (ICC) and Bland-Altman analyses. DWI's delineation geometric similarity to T1-weighted post-contrast (T1Wc) MRI was evaluated using the Dice Similarity Coefficient (DSC) before and after registration. Recurrence in post-treatment SCC scans was evaluated by the same two radiologists blinded for DW-technique. Recurrence detection rates were then compared between DW-SPLICE and DW-EPI using mixed logistic regression at six months and at one-year post-scan follow-up data. From August 2020 to January 2022, 55 benign or malignant lesion scans (55 patients) and 74 post-treatment SCC scans (66 patients) were analyzed. DW-SPLICE scored better on image quality and showed less overall distortion than DW-EPI (0.04<p<0.001). There was high ADC measurement reliability (ICC=0.93, p<0.001), though a proportional bias was also observed (β=0.11, p=0.03), indicating the bias increases as ADC values rise. DWSPLICE exhibited greater geometric similarity to T1Wc before registration (DSC 0.63 vs 0.47, p<0.001) and outperformed DW-EPI by more accurately identifying recurrences after one year (OR=0.96, p=0.05) but not after six months (OR=0.72, p=0.13). DW-SPLICE surpasses DW-EPI on image distortion and quality and improves diagnostic reliability for detecting recurrent or residual SCC on 3T MRI of the HN. Consistent use of one method for follow-up is advised, as ADC values are not completely interchangeable. Integrating DW-SPLICE can significantly improve tumor assessments in clinical practice. ANTs = Advanced Normalization Tools; DSC = Dice Similarity Coefficient; DW-EPI = Diffusion-weighted single-shot echo planar imaging; DW-MS-EPI = Diffusion-weighted multi-shot echo planar imaging; DW-SPLICE = Diffusion-weighted split acquisition of fast spin echo signals for diffusion imaging; DW-TSE = Diffusion-weighted Turbo Spin Echo; ICC = Intraclass Correlation Coefficient; ROC = Receiver Operating Characteristic; SCC = Squamous cell carcinoma; T1WIc = T1 weighted imaging with gadolinium contrast.

Cerebral Embolic Protection: Is There a Benefit for Left Atrial and Mitral Valve Procedures?

This review aims to highlight the current evidence on the use of cerebral embolic protection devices (CEPD) in left atrial and transcatheter mitral valve procedures. It also aims to summarize the antithrombotic management of patients undergoing such procedures. Ischemic stroke is one of the most devastating complications of structural heart procedures. The manifestation of periprocedural stroke can range from asymptomatic and detectable only through brain imaging to major stroke with neurological deficits. CEP devices were initially developed to mitigate the risk of stroke associated with transcatheter aortic valve replacement (TAVR). However, the efficacy of such devices during different cardiac interventions is yet to be fully demonstrated, especially in left atrial appendage closure (LAAO), and mitral valve interventions. Few studies demonstrated that the risk of periprocedural strokes after LAAO and mitral valve interventions is not negligible and is highest during the periprocedural period and then falls. The majority of patients undergoing those procedures have cerebral ischemic injuries detected on diffusion-weighted magnetic resonance imaging (DW-MRI). Moreover, a reasonable number of those patients had debris embolization on the filters of the CEPD. Pharmacological therapy with antithrombotic agents before, during, or after structural heart interventions is crucial and should be tailored to each patient's risk of bleeding and ischemia. Close monitoring that includes a full neurological assessment and frequent follow-up visits with cardiac echocardiography are important. The risk of periprocedural stroke in left atrial and transcatheter mitral valve procedures is not negligible. Pharmacological therapy with antithrombotic agents before, during, or after structural heart interventions is important to mitigate the risk of stroke, especially the long-term risk. More prospective studies are needed to assess the efficacy of CEPD in such procedures.

Vendor-Specific Correction Software for Apparent Diffusion Coefficient Bias Due to Gradient Nonlinearity in Breast Diffusion-Weighted Imaging Using Ice-Water Phantom.

This study aimed to evaluate a vendor-specific correction software for apparent diffusion coefficient (ADC) bias due to gradient nonlinearity in breast diffusion-weighted magnetic resonance imaging using an ice-water phantom. The phantom consists of 5 plastic tubes with a length of 100 mm and a diameter of 15 mm, filled with distilled water and immersed in an ice-water bath. Diffusion-weighted images were acquired by echo-planar imaging sequence on a 3.0-T scanner. ADC maps with and without correction were calculated using 4 b -values (0, 100, 600, and 800 s/mm 2 ). The mean ADCs were measured using a rectangular profile with 5 × 40 pixels in the anterior-posterior (AP) and a square region of interest with 5 × 5 pixels in the right-left (RL) and superior-inferior (SI) directions on the ADC map. ADC was compared with and without correction using a paired t test. Additionally, ADC of the ice-water phantom was measured at the magnet isocenter. ADC increased in the AP and RL directions and decreased in the SI direction with increasing distance from the isocenter before correction. After the correction, ADC at the off-center positions in the AP, RL, and SI directions was reduced to within 5% of the expected value. There were significant differences in the ADC at the off-center positions without and with correction ( P < 0.001); however, ADC at the magnet isocenter did not vary after correction (1.08 ± 0.02 × 10 -3 mm 2 /s). The vendor-specific software corrected the ADC bias due to gradient nonlinearity at the off-center positions in the AP, RL, and SI directions. Therefore, the software will contribute to the accurate ADC assessment in breast DWI.

Robust, fast and accurate mapping of diffusional mean kurtosis

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.

Robust, fast and accurate mapping of diffusional mean kurtosis.

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning, and monitoring of many neurological diseases and disorders. However, robust, fast, and accurate estimation of kurtosis from clinically feasible data acquisitions remains a challenge. In this study, we first outline a new accurate approach of estimating mean kurtosis via the sub-diffusion mathematical framework. Crucially, this extension of the conventional DKI overcomes the limitation on the maximum b-value of the latter. Kurtosis and diffusivity can now be simply computed as functions of the sub-diffusion model parameters. Second, we propose a new fast and robust fitting procedure to estimate the sub-diffusion model parameters using two diffusion times without increasing acquisition time as for the conventional DKI. Third, our sub-diffusion-based kurtosis mapping method is evaluated using both simulations and the Connectome 1.0 human brain data. Exquisite tissue contrast is achieved even when the diffusion encoded data is collected in only minutes. In summary, our findings suggest robust, fast, and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion-weighted magnetic resonance imaging data acquisition time.