Diffusion-weighted Imaging Technique Research Articles

Advanced breast diffusion-weighted imaging: what are the next steps? A proposal from the EUSOBI International Breast Diffusion-weighted Imaging working group.

This study by the EUSOBI International Breast Diffusion-weighted Imaging (DWI) working group aimed to evaluate the current and future applications of advanced DWI in breast imaging. A literature search and a comprehensive survey of EUSOBI members to explore the clinical use and potential of advanced DWI techniques and a literature search were involved. Advanced DWI approaches such as intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion tensor imaging (DTI) were assessed for their current status and challenges in clinical implementation. Although a literature search revealed an increasing number of publications and growing academic interest in advanced DWI, the survey revealed limited adoption of advanced DWI techniques among EUSOBI members, with 32% using IVIM models, 17% using non-Gaussian diffusion techniques for kurtosis analysis, and only 8% using DTI. A variety of DWI techniques are used, with IVIM being the most popular, but less than half use it, suggesting that the study identified a gap between the potential benefits of advanced DWI and its actual use in clinical practice. The findings highlight the need for further research, standardization and simplification to transition advanced DWI from a research tool to regular practice in breast imaging. The study concludes with guidelines and recommendations for future research directions and clinical implementation, emphasizing the importance of interdisciplinary collaboration in this field to improve breast cancer diagnosis and treatment. Advanced DWI in breast imaging, while currently in limited clinical use, offers promising improvements in diagnosis, staging, and treatment monitoring, highlighting the need for standardized protocols, accessible software, and collaborative approaches to promote its broader integration into routine clinical practice. Increasing number of publications on advanced DWI over the last decade indicates growing research interest. EUSOBI survey shows that advanced DWI is used primarily in research, not extensively in clinical practice. More research and standardization are needed to integrate advanced DWI into routine breast imaging practice.

Advances in Imaging for Metastatic Epidural Spinal Cord Compression: A Comprehensive Review of Detection, Diagnosis, and Treatment Planning.

Metastatic epidural spinal cord compression (MESCC) is a critical oncologic emergency caused by the invasion of metastatic tumors into the spinal epidural space, leading to compression of the spinal cord. If not promptly diagnosed and treated, MESCC can result in irreversible neurological deficits, including paralysis, significantly impacting the patient's quality of life. Early detection and timely intervention are crucial to prevent permanent damage. Imaging modalities play a pivotal role in the diagnosis, assessment of disease extent, and treatment planning for MESCC. Magnetic resonance imaging (MRI) is the current gold standard due to its superior ability to visualize the spinal cord, epidural space, and metastatic lesions. However, recent advances in imaging technologies have enhanced the detection and management of MESCC. Innovations such as functional MRI, diffusion-weighted imaging (DWI), and hybrid techniques like positron emission tomography-computed tomography (PET-CT) and PET-MRI have improved the accuracy of diagnosis, particularly in detecting early metastatic changes and guiding therapeutic interventions. This review provides a comprehensive analysis of the evolution of imaging techniques for MESCC, focusing on their roles in detection, diagnosis, and treatment planning. It also discusses the impact of these advances on clinical outcomes and future research directions in imaging modalities for MESCC. Understanding these advancements is critical for optimizing the management of MESCC and improving patient prognosis.

Imaging of Ulcerative Colitis: The Role of Diffusion-Weighted Magnetic Resonance Imaging.

Magnetic resonance imaging (MRI) has emerged as a promising and appealing alternative to endoscopy in the objective assessment of patients with inflammatory bowel disease (IBD). Diffusion-weighted imaging (DWI) is a specialized imaging technique that enables the mapping of water molecule diffusion within biological tissues, eliminating the need for intravenous gadolinium contrast injection. It is expanding the capability of traditional MRI sequences in Ulcerative Colitis (UC). Recently, there has been growing interest in the application of intravoxel incoherent motion (IVIM) imaging in the field of IBD. This technique combines diffusion and perfusion information, making it a valuable tool for assessing IBD treatment response. Previous studies have extensively studied the use of DWI techniques for evaluating the severity of activity in IBD. However, the majority of these studies have primarily focused on Crohn's disease (CD), with only a limited number of reports specifically examining UC. Therefore, this review briefly introduces the basics of DWI and IVIM imaging and conducts a review of relevant studies that have investigated its application in UC to show whether these techniques are useful techniques for evaluating patients with UC in terms of detection, characterization, and quantification of disease activity. Through the extensive literature survey, most of these studies indicate that DWI proves valuable in the differential diagnosis of UC and could be used as an effective modality for staging UC.

Optimization of motion-corrected liver diffusion-weighted imaging at 3 Tesla (3T): incorporating complex averaging and reparametrized sinc fatsat pulse with optimized water excitation pulse.

In liver diffusion-weighted imaging (DWI), single-shot echo-planar imaging (SS-EPI) sequences are susceptible to motion artifacts, resulting in image blurring and decreased lesion detection rates. This study aimed to develop and optimize a motion-corrected (MOCO) technique for liver DWI at 3 Tesla (3T). The technique incorporates motion correction, complex averaging, and a combination of a reparametrized sinc fatsat pulse with an optimized water excitation pulse. This prospective cross-sectional study performed at Fujian Medical University Union Hospital included 42 healthy volunteers who underwent four SS-EPI DWI sequences on a 3T magnetic resonance imaging (MRI) system between January 2023 and March 2023. The sequences included a navigator-triggered (NT) MOCO-DWI, two free-breathing (FB) MOCO-DWI, and an FB conventional DWI (FB cDWI) sequence. Motion correction and complex averaging were performed for both MOCO-DWI sequences, and fat suppression was achieved using either a sinc fatsat pulse with optimized water excitation or a conventional spectral attenuated inversion recovery (SPAIR) pulse. Liver signal-to-noise ratio (SNR) was measured at b=1,000 s/mm2. Qualitative parameters were independently evaluated by three radiologists using 5-point Likert scales. Quantitative parameters were assessed using the Kolmogorov-Smirnov test, and variance homogeneity was assessed using Levene's test. Regarding the qualitative analysis, the Friedman test was used to compare subjective scores among the four techniques. The SNRs of the liver were significantly higher with FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm2 (P<0.05). In the superior-inferior direction, the SNRs of the inferior level of the liver were higher than those of the superior level in NT MOCO-DWI. The qualitative results showed significantly higher ratings for NT MOCO-DWI and FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm2 (P<0.05). Regarding the apparent diffusion coefficient (ADC) quantification, the ADC values of the left lobe were higher than those of the right lobe in all four techniques. The proposed EPI DWI technique, incorporating motion correction, complex averaging, and a modified fat suppression scheme using spectral fat saturation and binomial water excitation, was found to be clinically feasible for liver MRI. The FB MOCO-DWI sequence, with its superior SNR and excellent image quality, is recommended for liver DW imaging at 3T in clinical routine.

Alterations of apparent diffusion coefficient from ultra high b-values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy.

Subcortical nuclei such as the thalamus and striatum have been shown to be related to seizure modulation and termination, especially in drug-resistant epilepsy. Enhance diffusion-weighted imaging (eDWI) technique and tri-component model have been used in previous studies to calculate apparent diffusion coefficient from ultra high b-values (ADCuh). This study aimed to explore the alterations of ADCuh in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. Twenty-nine patients with MRI-negative drug-resistant epilepsy and 18 healthy controls underwent eDWI scan with 15 b-values (0-5000 s/mm2). The eDWI parameters including standard ADC (ADCst), pure water diffusion (D), and ADCuh were calculated from the 15 b-values. Regions-of-interest (ROIs) analyses were conducted in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus. ADCst, D, and ADCuh values were compared between the MRI-negative drug-resistant epilepsy patients and controls using multivariate generalized linear models. Inter-rater reliability was assessed using the intra-class correlation coefficient (ICC) and Bland-Altman (BA) analysis. False discovery rate (FDR) method was applied for multiple comparisons correction. ADCuh values in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus in MRI-negative drug-resistant epilepsy were significantly higher than those in the healthy control subjects (all p < 0.05, FDR corrected). The alterations of the ADCuh values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy might reflect abnormal membrane water permeability in MRI-negative drug-resistant epilepsy. ADCuh might be a sensitive measurement for evaluating subcortical nuclei-related brain damage in epilepsy patients. This study aimed to explore the alterations of apparent diffusion coefficient calculated from ultra high b-values (ADCuh) in the subcortical nuclei such as the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. The bilateral thalamus and striatum showed higher ADCuh in epilepsy patients than healthy controls. These findings may add new evidences of subcortical nuclei abnormalities related to water and ion hemostasis in epilepsy patients, which might help to elucidate the underlying epileptic neuropathophysiological mechanisms and facilitate the exploration of therapeutic targets.

Monoexponential and advanced diffusion-weighted imaging for hepatic fibrosis staging based on high inter-examiner reliability.

To determine the diagnostic efficiencies of multiple diffusion-weighted imaging (DWI) techniques for hepatic fibrosis (HF) staging under the premise of high inter-examiner reliability. Participants with biopsy-confirmed HF were recruited and divided into the early HF (EHF) and advanced HF (AHF) groups; healthy volunteers (HVs) served as controls. Two examiners analyzed intravoxel incoherent motion (IVIM) using the IVIM-DWI and diffusion kurtosis imaging (DKI) models. Intravoxel incoherent motion-DWI, DKI, and diffusion tensor imaging parameters with intraclass correlation coefficients (ICCs) of ≥0.6 were used to create regression models: HVs vs. EHF and EHF vs. AHF. We enrolled 48 HVs, 59 EHF patients, and 38 AHF patients. Mean, radial, and axial kurtosis; fractional anisotropy; mean, radial, and axial diffusivity; and α exhibited excellent reliability (ICCs: 0.80-0.98). Fractional anisotropy of kurtosis, f, and apparent diffusion coefficient showed good reliability (ICCs: 0.69-0.92). The real (0.58-0.67), pseudo- (0.27-0.76), and distributed diffusion coefficients (0.58-0.67) showed low reliability. In the HVs versus (vs.) EHF model, α (p=0.008) and ADC (p=0.011) presented statistical differences (area under curve [AUC]: 0.710). In the EHF vs. AHF model, α (p=0.04) and distributed diffusion coefficient (p=0.02) presented significant differences (AUC: 0.758). Under the premise of high inter-examiner reliability, DWI and IVIM-derived stretched-exponential model parameters may help stage HF.

Beyond the surface: how ex-vivo diffusion-weighted imaging reveals large animal brain microstructure and connectivity.

Diffusion-weighted Imaging (DWI) is an effective and state-of-the-art neuroimaging method that non-invasively reveals the microstructure and connectivity of tissues. Recently, novel applications of the DWI technique in studying large brains through ex-vivo imaging enabled researchers to gain insights into the complex neural architecture in different species such as those of Perissodactyla (e.g., horses and rhinos), Artiodactyla (e.g., bovids, swines, and cetaceans), and Carnivora (e.g., felids, canids, and pinnipeds). Classical in-vivo tract-tracing methods are usually considered unsuitable for ethical and practical reasons, in large animals or protected species. Ex-vivo DWI-based tractography offers the chance to examine the microstructure and connectivity of formalin-fixed tissues with scan times and precision that is not feasible in-vivo. This paper explores DWI's application to ex-vivo brains of large animals, highlighting the unique insights it offers into the structure of sometimes phylogenetically different neural networks, the connectivity of white matter tracts, and comparative evolutionary adaptations. Here, we also summarize the challenges, concerns, and perspectives of ex-vivo DWI that will shape the future of the field in large brains.

Assessment of Hypoxia in Breast Cancer: Emerging Functional MR Imaging and Spectroscopy Techniques and Clinical Applications.

Breast cancer is one of the most prevalent forms of cancer affecting women worldwide. Hypoxia, a condition characterized by insufficient oxygen supply in tumor tissues, is closely associated with tumor aggressiveness, resistance to therapy, and poor clinical outcomes. Accurate assessment of tumor hypoxia can guide treatment decisions, predict therapy response, and contribute to the development of targeted therapeutic interventions. Over the years, functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS) techniques have emerged as promising noninvasive imaging options for evaluating hypoxia in cancer. Such techniques include blood oxygen level-dependent (BOLD) MRI, oxygen-enhanced MRI (OE) MRI, chemical exchange saturation transfer (CEST) MRI, and proton MRS (1H-MRS). These may help overcome the limitations of the routinely used dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) techniques, contributing to better diagnosis and understanding of the biological features of breast cancer. This review aims to provide a comprehensive overview of the emerging functional MRI and MRS techniques for assessing hypoxia in breast cancer, along with their evolving clinical applications. The integration of these techniques in clinical practice holds promising implications for breast cancer management. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Diagnostic accuracy of diffusion-weighted imaging and perfusion-weighted imaging with dynamic susceptibility contrast in differentiating World Health Organization Grade-I meningioma from high-grade meningioma with histopathology as gold standard

Abstract Background: Conventional magnetic resonance imaging may not be able to distinguish between the benign and malignant forms of meningioma. It has some limitations such as differentiating the grades of malignant meningioma. Diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) techniques can help to overcome these problems. Aims: The aim of this study was to study the diagnostic accuracy of DWI and PWI with dynamic susceptibility contrast in the differentiating World Health Organization Grade-I meningioma from high-grade meningioma with histopathology as the gold standard. Settings and Design: A hospital-based diagnostic evaluation study was carried out at the Department of Radio Diagnosis, Malla Reddy Institute of Medical Sciences, Hyderabad. Materials and Methods: Fifty cases of suspected meningioma were included in the study. The histopathology was the gold standard in this diagnostic evaluation study. DWI and PWI with dynamic susceptibility contrast results were compared against the gold standard. Statistical Analysis: Sensitivity, specificity, positive predictive value, and the negative predictive value were calculated to study the efficacy of DWI compared to histopathology as the gold standard. Results: The males (24%) were lesser than the females (76%). The female-to-male ratio was 3.2:1. The diagnostic accuracy values of apparent diffusion coefficient (ADC) with 0.6 as cutoff were sensitivity = 81.8%, specificity = 97.4%, positive predictive value = 90%, negative predictive value = 95%, and area under curve = 0.98 (95% confidence interval = 0.93–0.99) P = 0.0003. Thus, DWI using ADC with 0.6 as cutoff was found to be a very good diagnostic noninvasive tool. The diagnostic accuracy values of relative cerebral blood volume (rCBV) with 0.6 as cutoff were sensitivity = 90.5%, specificity = 98.7%, positive predictive value = 91.8%, and negative predictive value = 98.5%. Thus, DWI using rCBV with 2.52 as cutoff was found to be a very good diagnostic noninvasive tool. Conclusion: The ADC with cutoff of 0.6 and rCBV with cutoff value of 2.52 yield very good sensitivity, specificity, positive predictive value, and the negative predictive value as compared to histopathology. Hence, they can be used as noninvasive technique in differentiating Grade I meningioma from that of high-grade meningioma.

Use of Multimodality Imaging in the Evaluation of Patients With Spondyloarthropathies and Sacroiliitis.

Spondyloarthropathy (SpA) is one of the most common causes of low back pain. It is caused by inflammatory arthritis in the spine, manifesting in various forms such as psoriatic arthritis (PsA), ankylosing spondylitis (AS), and sacroiliitis. A comprehensive systematic literature search was done to evaluate and compare MRI, CT, single-photon emission CT, PET, ultrasound (US) imaging, low-dose CT, and diffusion-weighted imaging (DWI) techniques in assessing SpAs. The search strategy was constructed by an analysis of key terms from relevant articles in MEDLINE ProQuest, Embase, and PubMed. The key terms used to search for these articles were "SpA," "sacroiliitis," "spondylitis," "psoriatic arthritis," "MRI," "CT scan," "x-ray," "magnetic resonance imaging," "computed tomography," "bone density," and "ultrasound." A total of 1,131 articles published in English between January 1, 2003, and October 15, 2023 were identified and screened for eligibility by members of the research team, which resulted in 69 total articles selected for the final review. US has played an important role in visualizing joint inflammation and enthesitis (inflammation of the enthesis), which are common features of PsA. Although MRI and CT are considered more reliable modalities for diagnosing active sacroiliitis, US imaging with Doppler flow can also be useful in conjunction with CT images to visualize abnormal blood flow in the sacroiliac joints, as well as other joints affected by inflammatory arthritis. MRI provides increased diagnostic confidence in the diagnosis of sacroiliitis in active AS patients when compared to CT. CT is more sensitive than plain radiographs. The PET activity score showed a good correlation in diagnosing inflammatory sacroiliitis but lacked in identifying structural lesions. CT has high diagnostic accuracy, but it exposes patients to a high radiation dose. MRI visualizes joint and tissue inflammation, bone, and bone marrow change and can identify peripheral inflammation in soft tissue and joints in patients diagnosed with PsA. MRI can also visualize bone marrow changes and subchondral edema, which can aid in the early diagnosis of ankylosing SpA and gauge disease severity. DWI and short-tau inversion recovery imaging are both MRI techniques used in detecting sacroiliitis. MRI and CT are shown to be reliable imaging modalities for the diagnosis of sacroiliitis; however, it was found that Doppler US played an accurate role in the diagnosis as well. MRI visualizes joints and tissue with the most precision, making it useful in evaluating patients with PsA, while PET CT is useful in the diagnosis of inflammatory sacroiliitis patients. There is limited literature available comparing the multiple modalities of imaging available for each SpA. The review's objective is to analyze imaging findings in patients diagnosed with sacroiliitis and SpAs. The findings in this literature review are valuable for properly assessing and diagnosing patients suffering from SpAs.

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.

Detecting microvascular invasion in hepatocellular carcinoma using the impeded diffusion fraction technique to sense macromolecular coordinated water.

Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size. The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164). IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy.

Thin-slice reverse encoding distortion correction DWI facilitates visualization of non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma and surrounding normal structures

BackgroundTo evaluate the clinical usefulness of thin-slice echo-planar imaging (EPI)-based diffusion-weighted imaging (DWI) with an on-console distortion correction technique, termed reverse encoding distortion correction DWI (RDC-DWI), in patients with non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma.MethodsPatients with non-functioning PitNET/pituitary adenoma who underwent 3-T RDC-DWI between December 2021 and September 2022 were retrospectively enrolled. Image quality was compared among RDC-DWI, DWI with correction for distortion induced by B0 inhomogeneity alone (B0-corrected-DWI), and original EPI-based DWI with anterior-posterior phase-encoding direction (AP-DWI). Susceptibility artifact, anatomical visualization of cranial nerves, overall tumor visualization, and visualization of cavernous sinus invasion were assessed qualitatively. Quantitative assessment of geometric distortion was performed by evaluation of anterior and posterior displacement between each DWI and the corresponding three-dimensional T2-weighted imaging. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient values were measured.ResultsSixty-four patients (age 70.8 ± 9.9 years [mean ± standard deviation]; 33 females) with non-functioning PitNET/pituitary adenoma were evaluated. In terms of susceptibility artifacts in the frontal and temporal lobes, visualization of left trigeminal nerve, overall tumor visualization, and anterior displacement, RDC-DWI performed the best and B0-corrected-DWI performed better than AP-DWI. The right oculomotor and right trigeminal nerves were better visualized by RDC-DWI than by B0-corrected-DWI and AP-DWI. Visualization of cavernous sinus invasion and posterior displacement were better by RDC-DWI and B0-corrected-DWI than by AP-DWI. SNR and CNR were the highest for RDC-DWI.ConclusionsRDC-DWI achieved excellent image quality regarding susceptibility artifact, geometric distortion, and tumor visualization in patients with non-functioning PitNET/pituitary adenoma.Relevance statementRDC-DWI facilitates excellent visualization of the pituitary region and surrounding normal structures, and its on-console distortion correction technique is convenient. RDC-DWI can clearly depict cavernous sinus invasion of PitNET/pituitary adenoma even without contrast medium.Key points• RDC-DWI is an EPI-based DWI technique with a novel on-console distortion correction technique.• RDC-DWI corrects distortion due to B0 field inhomogeneity and eddy current.• We evaluated the usefulness of thin-slice RDC-DWI in non-functioning PitNET/pituitary adenoma.• RDC-DWI exhibited excellent visualization in the pituitary region and surrounding structures.• In addition, the on-console distortion correction of RDC-DWI is clinically convenient.Graphical

Evaluation of multiplexed sensitivity encoding diffusion-weighted imaging in detecting uterine lesions: Image quality optimization

PurposeTo compare the image quality of multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) and single-shot echo-planar imaging (SS-EPI-DWI) techniques in uterine MRI. MethodsEighty-eight eligible patients underwent MUSE-DWI and SS-EPI-DWI examinations simultaneously using a 3.0 T MRI system. Two radiologists independently performed quantitative and qualitative analysis of the two groups of images using a double-blind method. The weighted Kappa test was used to evaluate the interobserver agreement. Wilcoxon's rank sum test was used for qualitative parameters, and paired t-test was used for quantitative parameters. Spearman rank correlation analysis was used to obtained correlation between pathological results and mean apparent diffusion coefficient (ADC) value. ResultsThe qualitative and quantitative analysis of the images by the two radiologists were in good or excellent agreement, with weighted kappa value ranging from 0.636 to 0.981. The scores of total subjective image quality (15.4 ± 0.99) and signal-to-noise ratio (158.99 ± 60.71) of MUSE-DWI were significantly higher than those of SS-EPI-DWI (12.93 ± 1.62 P < 0.001; 130.23 ± 48.29 P < 0.05). It effectively reduced image distortion and artifact, and had better lesion conspicuity. There was no significant difference in contrast-to-noise ratio score and average ADC values between the two DWI sequences. The average ADC values of the two DWI sequences were highest in the normal uterus group and lowest in the endometrial cancer group, with statistically significant differences among groups (P < 0.01). In addition, the average ADC values of the two DWI sequences were negatively correlated with the type of lesions, decreasing with the malignancy of the lesions (r = −0.805 P < 0.01, r = −0.815 P < 0.01). ConclusionCompared to SS-EPI-DWI, MUSE-DWI can significantly reduce distortion, artifacts, and fuzziness in MRI of uterine lesions, which is more conducive to lesion detection.

The value of varying diffusion curvature MRI for assessing the microvascular invasion of hepatocellular carcinoma.

Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC). 74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power. MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10-3 vs 0.572 ± 0.148 × 10-3mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10-3 vs 1.471 ± 0.322 × 10-3mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve. VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making.

State of the art in the diagnostic evaluation of osteomyelitis: exploring the role of advanced MRI sequences-a narrative review.

Osteomyelitis, a severe bone infection caused mainly by pyogenic organisms, poses diagnostic challenges due to its non-specific magnetic resonance imaging (MRI) manifestations. Conventional MRI, though the imaging modality of choice, often exhibits signal abnormalities with overlapping differential diagnoses, potentially leading to overestimation of infection extent and duration. To address these limitations, advanced MRI sequences, including dynamic contrast-enhanced (DCE) MRI, 1H magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), and Dixon techniques have emerged as promising alternatives. This narrative review explores the potential role of these sequences in aiding the differential diagnosis of osteomyelitis. We used the PubMed database to search for relevant articles using the MeSH keywords: (osteomyelitis) AND (advanced MRI sequences) and we manually selected the most suitable studies to include in our review. Articles outside of original studies were also included. Only records in English or French were considered. In particular, DWI is useful for characterizing fluid collections, distinguishing bone infarcts, and bacterial skull base osteomyelitis from neoplastic lesions. Moreover, DWI assists in differentiating diabetic foot osteomyelitis (DFO) from Charcot neuro-osteoarthropathy, facilitates the diagnosis of pediatric acute osteoarticular infections, and aids in distinguishing osteomyelitis from Modic I degenerative changes. Additionally, DWI proves valuable in monitoring spinal infections and distinguishing pedal osteomyelitis from other conditions, even in patients with renal impairment. DCE-MRI enhances MRI specificity by assessing contrast uptake over time, providing valuable insights into inflammatory microenvironments. It aids in detecting DFO, differentiating it from acute Charcot arthropathy, and distinguishing osteomyelitis from neuropathic arthropathy. Moreover, DCE-MRI shows potential in assessing response to antibiotic therapy in spinal infections. Dixon acquisition improves image quality and facilitates the detection of bone marrow abnormalities, aiding in the differentiation of diabetic foot from osteomyelitis. It also assists in distinguishing osteomyelitis from neuropathic arthropathy and provides valuable information in evaluating the diabetic foot. Proton MR spectroscopy, a well-established modality, offers metabolic information that can differentiate malignant from benign lesions. The role of advanced MRI techniques in evaluating osteomyelitis remains to be fully defined, and further research is required to explore its potential utility in this context. In conclusion, the incorporation of advanced MRI sequences has shown promise in improving the differential diagnosis of osteomyelitis. Future investigations exploring combinations of these techniques and their clinical applications hold significant potential to enhance diagnostic accuracy and patient outcomes.

Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer.

This study systematically reviewed the role of diffusion-weighted imaging (DWI) in the assessment of molecular prognostic biomarkers in breast cancer, focusing on the correlation of apparent diffusion coefficient (ADC) with hormone receptor status and prognostic biomarkers. Our meta-analysis includes data from 52 studies examining ADC values in relation to estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki-67 status. The results indicated significant differences in ADC values among different receptor statuses, with ER-positive, PgR-positive, HER2-negative, and Ki-67-positive tumors having lower ADC values compared to their negative counterparts. This study also highlights the potential of advanced DWI techniques such as intravoxel incoherent motion and non-Gaussian DWI to provide additional insights beyond ADC. Despite these promising findings, the high heterogeneity among the studies underscores the need for standardized DWI protocols to improve their clinical utility in breast cancer management.

Diffusion-weighted imaging compared to dynamic MRI in early response assessment of locoregional therapy (by trans-arterial chemoembolization & microwave ablation) of hepatocellular carcinoma

BackgroundPurpose of this study is to compare between dynamic contrast-enhanced and diffusion-weighted MRI imaging techniques in early response assessment of hepatocellular carcinoma (HCC) after transcatheter chemoembolization and microwave ablation.MethodsRetrospective study was done over a period of 36 months (June 2015–June 2018). The study was conducted on 69 cases; 61 patients were males and 8 were females patients age ranged from 45 to 72 years (median 60). All patients suffered from liver cirrhosis secondary to chronic viral hepatitis. They underwent diffusion-weighted MR imaging and subtraction dynamic MR imaging techniques after trans-arterial chemoembolization (TACE) and microwave ablation (MWA). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and overall agreement were calculated for both the dynamic and the DWI images. Apparent diffusion coefficients (ADCs) were calculated searching for a cutoff value using the receiver operating characteristic curve (ROC).ResultsOur study results revealed moderate accuracy of diffusion MRI in the diagnosis of complete ablation (no residue) less than that of dynamic and subtraction sequences with 71.43% sensitivity, 88.52% specificity, 83.3% PPV and 79.4% NPV. This is attributed to that diffusion MR study is not able to detect small enhancing tumor foci that appears clearly on dynamic and subtraction MR studies. Also, these results are attributed to false positive results on diffusion study corresponding to liquefactive necrosis with hemorrhagic component post-ablation.ConclusionsOur study concluded that subtraction and dynamic MRI had more accuracy than diffusion compared to our follow-up results. So combined subtraction dynamic MR study and diffusion is the main technique of early evaluation of post-interventional therapy of HCC to avoid pitfalls of diffusion study.

Readout-Segmented Echoplanar (RESOLVE) Diffusion-Weighted Imaging on 3T MRI in Detection of Cholesteatoma-Our Experience.

Background Several research studies have demonstrated the utility of diffusion-weighted imaging (DWI) in detecting middle ear cholesteatomas, especially with the non-echoplanar imaging (non-EPI) DWI technique. REadout Segmentation Of Long Variable Echo trains (RESOLVE), a multishot-EPI DWI, has better spatial resolution at a thinner section acquisition with reduced image distortion compared to the single-shot-EPI DWI technique. Purpose In this study, we evaluated the diagnostic ability of RESOLVE -DWI in middle ear cholesteatomas with surgical and histopathological support. Patients and Methods Fifty patients with clinical suspicion of primary cholesteatoma or postoperative recurrence were subjected to routine sequences and RESOLVE-DWI on magnetic resonance imaging (MRI). Thirty-eight patients had unilateral disease, while 12 patients had bilateral disease. The bilateral temporal bones of 50 patients were evaluated on MRI. The results attained by RESOLVE-DWI were correlated with intraoperative and histopathological findings. Results RESOLVE-DWI truly detected 55 of the 58 surgically proven cholesteatomas. RESOLVE-DWI could not detect three cholesteatoma lesions due to their small size and falsely diagnosed one case each of impacted wax and non-cholesteatomatous otitis media as cholesteatoma. With a 95% confidence interval, RESOLVE-DWI showed 94.8% sensitivity, 95.2% specificity, 96% positive predictive value, 93% negative predictive value, and 95% diagnostic accuracy in cholesteatoma detection. Conclusion RESOLVE-DWI is a sensitive and specific DWI technique for detecting middle ear cholesteatoma. However, RESOLVE-DWI has limitations in the diagnosis of small (<3 mm) cholesteatomas.

Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers.

Background: this study aimed to utilize various diffusion-weighted imaging (DWI) techniques, including mono-exponential DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for the preoperative grading of rectal cancer. Methods: 85 patients with rectal cancer were enrolled in this study. Mann-Whitney U tests or independent Student's t-tests were conducted to identify DWI-derived parameters that exhibited significant differences. Spearman or Pearson correlation tests were performed to assess the relationships among different DWI-derived biological markers. Subsequently, four machine learning classifier-based models were trained using various DWI-derived parameters as input features. Finally, diagnostic performance was evaluated using ROC analysis with 5-fold cross-validation. Results: With the exception of the pseudo-diffusion coefficient (Dp), IVIM-derived and DKI-derived parameters all demonstrated significant differences between low-grade and high-grade rectal cancer. The logistic regression-based machine learning classifier yielded the most favorable diagnostic efficacy (AUC: 0.902, 95% Confidence Interval: 0.754-1.000; Specificity: 0.856; Sensitivity: 0.925; Youden Index: 0.781). Conclusions: utilizing multiple DWI-derived biological markers in conjunction with a strategy employing multiple machine learning classifiers proves valuable for the noninvasive grading of rectal cancer.