Standard 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.

Abstract TMP52: Modern Thin-Slice CT Perfusion Has High Sensitivity for Supratentorial Lacunar Stroke

Background: Lacunar stroke is a common form of ischaemic stroke with mechanisms poorly understood compared to large vessel stroke. Access to gold standard MRI is often limited in the acute setting. Acute diagnosis of lacunar stroke is difficult with conventional CT, as non-contrast CT and CT angiography have poor sensitivity. Previous studies have demonstrated only low to moderate sensitivity of CT perfusion (CTP). Aims: To test the accuracy of thin-slice CTP to detect lacunar stroke and compare the clinical and radiological characteristics to better understand the limitations of CTP for diagnosis of lacunar stroke. Methods: We reviewed thin-slice CTP (slice thickness &lt;=3mm) of cases presenting with an acute lacunar syndrome without large/medium vessel occlusion, or perfusion lesion detected by automated analysis. Cases presented to two comprehensive stroke centres in Sydney and Newcastle, NSW, Australia, between 2019 and 2022. CTP was reviewed by two independent reviewers, blinded to follow-up MRI but not the clinical syndrome. CTP and DWI were registered to a standard template and DWI lesions were manually segmented. CTP was further reviewed adjacent to DWI, and raw CTP values within the lesion was calculated. Results: We reviewed 394 cases of acute lacunar syndrome including 82 stroke mimics, 48 infratentorial and 250 supratentorial infarcts. Overall sensitivity was 76% and varied by infarct location. Sensitivity was lowest for brainstem (46%), moderate for thalamic (69%) and high for infarcts within the lenticulostriate perforator territory (84%). Factors associated with reduced sensitivity include small infarct volume, increased noise, or artefact, and infratentorial location. Conclusion: Thin-slice CTP has high sensitivity for detection of supratentorial lacunar infarcts however is more susceptible to noise and imaging artefact than larger infarcts. Advanced processing techniques show promise to improve overall diagnosis of lacunar stroke.

Short repetition time diffusion-weighted imaging improves visualization of prostate cancer.

This study aimed to assess whether short repetition time (TR) diffusion-weighted imaging (DWI) could improve diffusion contrast in patients with prostate cancer (PCa) compared with long TR (conventional) reference standard DWI. Our Institutional Review Board approved this retrospective study and waived the need for informed consent. Twenty-five patients with suspected PCa underwent multiparametric magnetic resonance imaging (mp-MRI) using a 3.0-T system. DWI was performed with TR of 1850ms (short) and 6000ms (long) with b-values of 0, 1000, and 2000s/mm2. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), visual score, apparent diffusion coefficient (ADC), and diagnostic performance were compared between short and long TR DWI for both b-values. The statistical tests included paired t-test for SNR and CNR; Wilcoxon signed-rank test for VA; Pearson's correlation and Bland-Altman plot analysis for ADC; and McNemar test and receiver operating characteristic analysis and Delong test for diagnostic performance. Regarding b1000, CNR and visual score were significantly higher in short TR compared with long TR (P = .003 and P = .002, respectively), without significant difference in SNR (P = .21). Considering b2000, there was no significant difference in visual score between short and long TR (P = .07). However, SNR and CNR in long TR were higher (P = .01 and P = .04, respectively). ADC showed significant correlations, without apparent bias for ADC between short and long TR for both b-values. For diagnostic performance of DWI between short and long TR for both b-values, one out of five readers noted a significant difference, with the short TR for both b-values demonstrating superior performance. Our data showed that the short TR DWI1000 may provide better image quality than did the long TR DWI1000 and may improve visualization and diagnostic performance of PCa for readers.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm

PurposeOur study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis.MethodsEighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWISD and ADCSD), DWI and ADC signal intensity ratio (DWISIR and ADCSIR), mean ADC and minimum ADC value (ADCmean and ADCmin) and ADC value standard deviation (ADCVSD). Univariate and multivariate logistic regression were conducted to identify independent predictors, and develop a prediction model. We performed receiver operating characteristic (ROC) analysis to determine the optimal threshold of risk factors, and constructed combined threshold models. Our study calculated diagnostic performance including area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and unnecessary biopsy rate of all models were calculated and compared them with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) result.ResultsTwo independent predictors of malignant nodules were identified by multivariate analysis: DWISIR (P = 0.007) and ADCmin (P < 0.001). The AUCs for multivariate prediction model, combined DWISIR and ADCmin thresholds model, combined DWISIR and ADCSIR thresholds model and ACR-TIRADS were 0.946 (0.896–0.996), 0.875 (0.759–0.991), 0.777 (0.648–0.907) and 0.722 (0.588–0.857). The combined DWISIR and ADCmin threshold model had the lowest unnecessary biopsy rate of 0%, compared with 56.3% for ACR-TIRADS.ConclusionQuantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.

Deep Learning k-Space-to-Image Reconstruction Facilitates High Spatial Resolution and Scan Time Reduction in Diffusion-Weighted Imaging Breast MRI.

For time-consuming diffusion-weighted imaging (DWI) of the breast, deep learning-based imaging acceleration appears particularly promising. To investigate a combined k-space-to-image reconstruction approach for scan time reduction and improved spatial resolution in breast DWI. Retrospective. 133 women (age 49.7 ± 12.1 years) underwent multiparametric breast MRI. 3.0T/T2 turbo spin echo, T1 3D gradient echo, DWI (800 and 1600 sec/mm2 ). DWI data were retrospectively processed using deep learning-based k-space-to-image reconstruction (DL-DWI) and an additional super-resolution algorithm (SRDL-DWI). In addition to signal-to-noise ratio and apparent diffusion coefficient (ADC) comparisons among standard, DL- and SRDL-DWI, a range of quantitative similarity (e.g., structural similarity index [SSIM]) and error metrics (e.g., normalized root mean square error [NRMSE], symmetric mean absolute percent error [SMAPE], log accuracy error [LOGAC]) was calculated to analyze structural variations. Subjective image evaluation was performed independently by three radiologists on a seven-point rating scale. Friedman's rank-based analysis of variance with Bonferroni-corrected pairwise post-hoc tests. P < 0.05 was considered significant. Both DL- and SRDL-DWI allowed for a 39% reduction in simulated scan time over standard DWI (5 vs. 3 minutes). The highest image quality ratings were assigned to SRDL-DWI with good interreader agreement (ICC 0.834; 95% confidence interval 0.818-0.848). Irrespective of b-value, both standard and DL-DWI produced superior SNR compared to SRDL-DWI. ADC values were slightly higher in SRDL-DWI (+0.5%) and DL-DWI (+3.4%) than in standard DWI. Structural similarity was excellent between DL-/SRDL-DWI and standard DWI for either b value (SSIM ≥ 0.86). Calculation of error metrics (NRMSE ≤ 0.05, SMAPE ≤ 0.02, and LOGAC ≤ 0.04) supported the assumption of low voxel-wise error. Deep learning-based k-space-to-image reconstruction reduces simulated scan time of breast DWI by 39% without influencing structural similarity. Additionally, super-resolution interpolation allows for substantial improvement of subjective image quality. 4 TECHNICAL EFFICACY: Stage 1.

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.

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

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

Shortening Acquisition Time and Improving Image Quality for Pelvic MRI Using Deep Learning Reconstruction for Diffusion-Weighted Imaging at 1.5 T

To determine the impact on acquisition time reduction and image quality of a deep learning (DL) reconstruction for accelerated diffusion-weighted imaging (DWI) of the pelvis at 1.5 Tcompared to standard DWI. A total of 55 patients (mean age, 61±13 years; range, 27-89; 20 men, 35 women) were consecutively included in this retrospective, monocentric study between February and November 2022. Inclusion criteria were (1) standard DWI (DWIS) in clinically indicated magnetic resonance imaging (MRI) at 1.5 Tand (2) DL-reconstructed DWI (DWIDL). All patients were examined using the institution's standard MRI protocol according to their diagnosis including DWI with two different b-values (0and 800s/mm2) and calculation of apparent diffusion coefficient (ADC) maps. Image quality was qualitatively assessed by four radiologists using a visual 5-point Likert scale (5= best) for the following criteria: overall image quality, noise level, extent of artifacts, sharpness, and diagnostic confidence. The qualitative scores for DWIS and DWIDL were compared with the Wilcoxon signed-rank test. The overall image quality was evaluated to be significantly superior in DWIDL compared to DWIS for b =0s/mm2, b =800s/mm2, and ADC maps by all readers (P<.05). The extent of noise was evaluated to be significantly less in DWIDL compared to DWIS for b =0s/mm2, b=800s/mm2, and ADC maps by all readers (P<.001). No significant differences were found regarding artifacts, lesion detectability, sharpness of organs, and diagnostic confidence (P>.05). Acquisition time for DWIS was 2:06minutes, and simulated acquisition time for DWIDL was 1:12minutes. DL image reconstruction improves image quality, and simulation results suggest that a reduction in acquisition time for diffusion-weighted MRI of the pelvis at 1.5 Tis possible.

Diffusion-weighted, intravoxel incoherent motion, and diffusion kurtosis tensor MR imaging in chronic kidney diseases: Correlations with histology

ObjectivesTo probe the correlations of parameters derived from standard DWI and its extending models including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) with the pathological and functional alterations in CKD. Material and methodsSeventy-nine CKD patients with renal biopsy and 10 volunteers were performed with DWI, IVIM, diffusion kurtosis tensor imaging (DKTI) scanning. Correlations between imaging results and the pathological damage [glomerulosclerosis index (GSI) and tubulointerstitial fibrosis index (TBI)], as well as eGFR, 24 h urinary protein and Scr) were evaluated.CKD patients were divided into 2 groups: group 1: both GSI and TBI scores <2 points (61 cases); group 2: both GSI and TBI scores ≥2 points (18 cases). ResultsThere were significant difference in cortical and medullary MD, and cortical D among 3 groups and between group 1 and 2. Cortical and medullary MD, cortical D, and medullary FA were negatively correlated with GSI score (r = −0.322 to −0.386, P < 0.05). Cortical and medullary MD and D, medullary FA were also negatively correlated with TBI score (r = −0.257 to −0.395, P < 0.05). These parameters were all correlated with eGFR and Scr. Cortical MD and D showed the highest AUC of 0.790 and 0.745 in discriminating mild and moderate-severe glomerulosclerosis and tubular interstitial fibrosis, respectively. ConclusionsThe corrected diffusion-related indices, including cortical and medullary D and MD, as well as medullary FA were superior to ADC, perfusion-related and kurtosis indices for evaluating the severity of renal pathology and function in CKD patients.

Accelerated diffusion-weighted imaging of the prostate using deep learning image reconstruction: A retrospective comparison with standard diffusion-weighted imaging

PurposeRoutine multiparametric MRI of the prostate reduces overtreatment and increases sensitivity in the diagnosis of the most common solid cancer in men. However, the capacity of MRI systems is limited. Here we investigate the ability of deep learning image reconstruction to accelerate time consuming diffusion-weighted imaging (DWI) acquisition while maintaining diagnostic image quality. MethodIn this retrospective study, raw data of DWI sequences of consecutive patients undergoing MRI of the prostate at a tertiary care hospital in Germany were reconstructed using standard and deep learning reconstruction. To simulate a shortening of acquisition times by 39 %, one instead of two and six instead of ten averages were used in the reconstruction of b = 0 and 1000 s/mm2 images, respectively. Image quality was assessed by three radiologists and objective image quality metrics. ResultsAfter the application of exclusion criteria, 35 out of 147 patients examined between September 2022 and January 2023 were included in this study. The radiologists perceived less image noise on deep learning reconstructed images at b = 0 s/mm2 images and ADC maps with good inter-reader agreement. Signal-to-noise ratios were similar overall with discretely reduced values in the transitional zone after deep learning reconstruction. ConclusionsAn acquisition time reduction of 39 % without loss in image quality is feasible in DWI of the prostate when using deep learning image reconstruction.

Novel deep-learning-based diffusion weighted imaging sequence in 1.5 T breast MRI

PurposeThis study aimed to assess the technical feasibility, the impact on image quality, and the acquisition time (TA) of a new deep-learning-based reconstruction algorithm in diffusion weighted imaging (DWI) of breast magnetic resonance imaging (MRI). MethodsRetrospective analysis of 55 female patients who underwent breast DWI at 1.5 T. Raw data were reconstructed using a deep-learning (DL) reconstruction algorithm on a subset of the acquired averages, therefore a reduction of TA. Clinically used standard DWI sequence (DWIStd) and the DL-reconstructed images (DWIDL) were compared. Two radiologists rated the image quality of b800 and ADC images, using a Likert-scale from 1 to 5 with 5 being considered perfect image quality. Signal intensities were measured by placing a region of interest (ROI) at the same position in both sequences. ResultsTA was reduced by 40 % in DWIDL, compared to DWIStd, DWIDL improved noise and sharpness while maintaining contrast, the level of artifacts, and diagnostic confidence. There were no differences regarding the signal intensity values of the apparent diffusion coefficient (ADC), (p = 0.955), b50-values (p = 0.070) and b800-values (p = 0.415) comparing standard and DL-imaging. Lesion assessment showed no differences regarding the number of lesions in ADC and DWI (both p = 1.000) and regarding the lesion diameter in DWI (p = 0.961;0.972) and ADC (p = 0.961;0.972). ConclusionsThe novel deep-learning-based reconstruction algorithm significantly reduces TA in breast DWI, while improving sharpness, reducing noise, and maintaining a comparable level of image quality, artifacts, contrast, and diagnostic confidence. DWIDL does not influence the quantifiable parameters.

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.

Computed high-b-value high-resolution DWI improves solid lesion detection in IPMN of the pancreas

ObjectivesTo examine the effect of high-b-value computed diffusion-weighted imaging (cDWI) on solid lesion detection and classification in pancreatic intraductal papillary mucinous neoplasm (IPMN), using endoscopic ultrasound (EUS) and histopathology as a standard of reference.MethodsEighty-two patients with known or suspected IPMN were retrospectively enrolled. Computed high-b-value images at b = 1000 s/mm2 were calculated from standard (b = 0, 50, 300, and 600 s/mm2) DWI images for conventional full field-of-view (fFOV, 3 × 3 × 4 mm3 voxel size) DWI. A subset of 39 patients received additional high-resolution reduced-field-of-view (rFOV, 2.5 × 2.5 × 3 mm3 voxel size) DWI. In this cohort, rFOV cDWI was compared against fFOV cDWI additionally. Two experienced radiologists evaluated (Likert scale 1–4) image quality (overall image quality, lesion detection and delineation, fluid suppression within the lesion). In addition, quantitative image parameters (apparent signal-to-noise ratio (aSNR), apparent contrast-to-noise ratio (aCNR), contrast ratio (CR)) were assessed. Diagnostic confidence regarding the presence/absence of diffusion-restricted solid nodules was assessed in an additional reader study.ResultsHigh-b-value cDWI at b = 1000 s/mm2 outperformed acquired DWI at b = 600 s/mm2 regarding lesion detection, fluid suppression, aCNR, CR, and lesion classification (p =  < .001–.002). Comparing cDWI from fFOV and rFOV revealed higher image quality in high-resolution rFOV-DWI compared to conventional fFOV-DWI (p ≤ .001–.018). High-b-value cDWI images were rated non-inferior to directly acquired high-b-value DWI images (p = .095–.655).ConclusionsHigh-b-value cDWI may improve the detection and classification of solid lesions in IPMN. Combining high-resolution imaging and high-b-value cDWI may further increase diagnostic precision.Clinical relevance statementThis study shows the potential of computed high-resolution high-sensitivity diffusion-weighted magnetic resonance imaging for solid lesion detection in pancreatic intraductal papillary mucinous neoplasia (IPMN). The technique may enable early cancer detection in patients under surveillance.Key Points• Computed high-b-value diffusion-weighted imaging (cDWI) may improve the detection and classification of intraductal papillary mucinous neoplasms (IPMN) of the pancreas.• cDWI calculated from high-resolution imaging increases diagnostic precision compared to cDWI calculated from conventional-resolution imaging.• cDWI has the potential to strengthen the role of MRI for screening and surveillance of IPMN, particularly in view of the rising incidence of IPMNs combined with now more conservative therapeutic approaches.

Comparison of Diagnostic Performance and Image Quality between Topup-Corrected and Standard Readout-Segmented Echo-Planar Diffusion-Weighted Imaging for Cholesteatoma Diagnostics

This study compares the diagnostic performance and image quality of single-shot turbo spin-echo DWI (tseDWI), standard readout-segmented DWI (rsDWI), and a modified rsDWI version (topupDWI) for cholesteatoma diagnostics. Thirty-four patients with newly suspected unilateral cholesteatoma were examined on a 1.5 Tesla MRI scanner. Diagnostic performance was evaluated by calculating and comparing the sensitivity and specificity using histopathological results as the standard of reference. Image quality was independently reviewed by two readers using a 5-point Likert scale evaluating image distortions, susceptibility artifacts, image resolution, lesion conspicuity, and diagnostic confidence. Twenty-five cholesteatomas were histologically confirmed after surgery and originated in the study group. TseDWI showed the highest sensitivity with 96% (95% confidence interval (CI): 88-100%), followed by topupDWI with 92% (95% CI: 81-100%) for both readers. The sensitivity for rsDWI was 76% (95% CI: 59-93%) for reader 1 and 84% (95% CI: 70-98%) for reader 2, respectively. Both tseDWI and topupDWI revealed a specificity of 100% (95% CI: 66-100%) and rsDWI of 89% (95% CI: 52-100%). Both tseDWI and topupDWI showed fewer image distortions and susceptibility artifacts compared to rsDWI. Image resolution was consistently rated best for topupDWI, followed by rsDWI, which both outperformed tseDWI. TopupDWI and tseDWI showed comparable results for lesions' conspicuity and diagnostic confidence, both outperforming rsDWI. Modified readout-segmented DWI using the topup-correction method is preferable to standard rsDWI and may be regarded as an accurate alternative to single-shot turbo spin-echo DWI in cholesteatoma diagnostics.

Whole-body diffusion magnetic resonance imaging with simultaneous multi-slice excitation in children and adolescents

BackgroundWhole-body magnetic resonance imaging (WB-MRI) is an increasingly used guideline-based imaging modality for oncological and non-oncological pathologies during childhood and adolescence. While diffusion-weighted imaging (DWI), a part of WB-MRI, enhances image interpretation and improves sensitivity, it also requires the longest acquisition time during a typical WB-MRI scan protocol. Interleaved short tau inversion recovery (STIR) DWI with simultaneous multi-slice (SMS) acquisition is an effective way to speed up examinations.ObjectiveIn this study of children and adolescents, we compared the acquisition time, image quality, signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) values of an interleaved STIR SMS-DWI sequence with a standard non-accelerated DWI sequence for WB-MRI.Materials and methodsTwenty children and adolescents (mean age: 13.9 years) who received two WB-MRI scans at a maximum interval of 18 months, consisting of either standard DWI or SMS-DWI MRI, respectively, were included. For quantitative evaluation, the signal-to-noise ratio (SNR) was determined for b800 images and ADC maps of seven anatomical regions. Image quality evaluation was independently performed by two experienced paediatric radiologists using a 5-point Likert scale. The measurement time per slice stack, pause between measurements including shim and total measurement time of DWI for standard DWI and SMS-DWI were extracted directly from the scan data.ResultsWhen including the shim duration, the acquisition time for SMS-DWI was 43% faster than for standard DWI. Qualitatively, the scores of SMS-DWI were higher in six locations in the b800 images and four locations in the ADC maps. There was substantial agreement between both readers, with a Cohen’s kappa of 0.75. Quantitatively, the SNR in the b800 images and the ADC maps did not differ significantly from one another.ConclusionWhole body-MRI with SMS-DWI provided equivalent image quality and reduced the acquisition time almost by half compared to the standard WB-DWI protocol.

Computed diffusion-weighted imaging in patients with transient neurovascular symptoms with and without ischemic infarction

PurposeDetection of ischemic lesions in patients with transient neurovascular symptoms is relevant for the estimation of the risk of a subsequent stroke and etiological classification. To improve detection rates, different technical approaches have been used, such as diffusion-weighted imaging (DWI) with high b-values or higher magnetic field strength. Here, we sought to investigate the value of computed DWI (cDWI) with high b-values in these patients. MethodsFrom an MRI report database we identified patients with transient neurovascular symptoms who underwent repeated MRI including DWI. cDWI was calculated with a monoexponential model with high b-values (2000, 3000, and 4000 s/mm2) and compared to the routinely used standard DWI with regard to presence of ischemic lesions and lesion detectability. ResultOverall 33 patients with transient neurovascular symptoms (71 [IQR 57–83.5] years; 21 [63.6%] male) were included. On DWI, acute ischemic lesions were observed in 22 (78.6%). Acute ischemic lesions were observed in 17 (51.5%) patients on initial DWI, and in 26 (78.8%) patients on follow-up DWI. Lesion detectability was rated significantly better on cDWI at 2000s/mm2 compared to standard DWI. In 2 (9.1%) patients, cDWI at 2000s/mm2 revealed an acute ischemic lesion proven on follow-up standard DWI which was not detected with certainty on the initial standard DWI. ConclusioncDWI might be a valuable addition to routinely acquired standard DWI in patients with transient neurovascular symptoms since its use might result in improved ischemic lesion detection. A b-value of 2000s/mm2 seems most promising for clinical practice.

Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion in differentiating invasive placentas.

To investigate the diagnostic value of monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in distinguishing invasive placentas. A total of 53 patients with invasive placentas and 47 patients with noninvasive placentas undergoing conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were retrospectively enrolled. The mean, minimum, and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, diffusion kurtosis (MK), and diffusion coefficient (MD) from DKI and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured and compared from the volumetric analysis. Receiver operating characteristics (ROC) curve and logistic regression analyses were conducted to evaluate the diagnostic efficiency of different diffusion parameters for distinguishing invasive placentas. Comparisons between accreta lesions in patients with invasive placentas (AL) and lower 1/3 part of the placenta in patients with noninvasive placentas (LP) demonstrated that MD mean, D mean, and D* mean were significantly lower while ADC max and D max were significantly higher in invasive placentas (all p < 0.05). Multivariate analysis demonstrated that D mean, D max and D* mean differed significantly among all the studied parameters for invasive placentas. A combined use of these three parameters yielded an AUC of 0.86 with sensitivity, specificity, and accuracy of 84.91%, 76.60%, and 80%, respectively. The combined use of different IVIM parameters is helpful in distinguishing invasive placentas.

Diffusion kurtosis imaging as a biomarker of breast cancer.

DKI, which increases the sensitivity to complex tissue microstructure compared to standard DWI, has been applied in the breast, allowing to increase clinical performance in distinguishing malignant from benign lesions and in predicting prognosis or treatment response in breast cancer.

[Perifocal edema and glymphatic system dysfunction: quantitative assessment based on diffusion tensor magnetic resonance imaging].

Pathogenesis of peritumoral cerebral edema is unclear and potentially associated with glymphatic system dysfunction. Diffusion tensor MRI (DT-MRI) with analysis of ALPS (Analysis along the Perivascular Space) index may be valuable for assessment of edema. This approach visualizes fluid flow along perivascular spaces of deep cerebral veins. To assess glymphatic system function in supratentorial tumors and healthy volunteers using DT-MRI. There were 52 patients (59% men) aged 43 (28-64) years with supratentorial tumors (meningioma - 20, grade 3-4 glioma - 15, metastases - 9, lymphoma - 8). Tumors and perifocal edema did not involve deep cerebral veins. The control group included 6 healthy volunteers aged 34-66 years. MRI protocol (Signa HDxt, 3 T) contained standard T1, T2, T2FLAIR, DWI and post-contrast T1 (3D BRAVO). DT-MRI had the following parameters: TR=10 000 ms, TEmin=102 ms, FOV=240 mm, isotropic voxel size 3×3×3 mm3, 60 directions of diffusion gradients. Measurements were carried out at b-factor 0 and 1000 s/mm2. Analysis was carried out in the ReadyView software. Right- and left-sided ALPS indices were similar in the control group (p=0.917). Perifocal edema (regardless of histological type of tumor) in the ipsilateral hemisphere was accompanied by significantly lower ALPS index (p<0.005), while these values in contralateral (intact) hemisphere were similar in both groups (p=0.7). We found significantly lower ALPS index in deep parts of the affected hemisphere in patients with perifocal edema. These data can indicate the role of glymphatic system dysfunction in pathogenesis of this pathology.

Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis.

This study aimed to assess the applicability of the apparent diffusion coefficient (ADC) for differentiating nasopharyngeal carcinoma (NPC) from lymphomas in the head and neck region. Four databases, including PubMed, the Cochrane Library, EMBASE, and Web of Science, were searched systematically to find relevant literature. The search date was updated to 8 September 2022, with no starting time restriction. The methodological quality of the studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Firstly, a random-effects model was used in a meta-analysis of continuous variables with low heterogeneity to determine the overall effect size, which was reported as the standard mean difference (SMD). Then, bivariate random effects modelling was used to calculate the combined sensitivity and specificity. The area under the curve (AUC) for each diffusion parameter was calculated after constructing summary receiver operating characteristic curves. The presence of heterogeneity was evaluated using subgroup and meta-regression analysis. Twelve studies involving 181 lymphoma and 449 NPC lesions (N = 630) in the head and neck region were included, of which 5 studies provided sufficient data for pooling diagnostic test accuracy. A meta-analysis of the 12 studies using a random-effects model yielded an SMD of 1.03 (CI = 0.76-1.30; p = 0.00001), implying that NPC lesions had a significantly higher ADC value than lymphoma lesions. By pooling 5 standard DWI studies, the pooled sensitivity and specificity of ADC were 0.90 (95% CI: 0.82-0.95) and 0.63 (95% CI: 0.52-0.72), respectively. The area under the curve (AUC) calculated from the SROC curve was 0.74 (95% CI: 0.70-0.78). According to this systematic review and meta-analysis, nasopharyngeal carcinoma has a significantly higher ADC value than lymphomas. Furthermore, while ADC has excellent sensitivity for distinguishing these 2 types of tumours, its specificity is relatively low, yielding a moderate diagnostic performance. Further investigations with larger sample sizes are required.