Conventional Diffusion-weighted Imaging Research Articles

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.

Does the apparent diffusion coefficient from diffusion-weighted MRI imaging aid in the characterization of malignant soft tissue tumors and sarcomas.

To identify trends in apparent diffusion coefficient (ADC) measurements from diffusion-weighted imaging (DWI) with respect to tumor type classification and other tumor characteristics whether common malignant soft tissue tumors can be distinguished. A consecutive series of extremity malignant soft tissue tumors and soft tissue sarcomas (STS) among 78 adult patients with conventional MRI and DWI were included. Each case was evaluated with respect to T1/T2 signal alterations and heterogeneity, presence of peritumoral edema, necrosis, cystic changes, internal hemorrhage, and maximum longitudinal dimension blinded to the histology. The ADC mean and minimum were obtained using a free-hand region of interest of the whole tumor and the darkest (lowest signal area) ADC area of the tumor. Kruskal-Wallis and Wilcoxon Rank-Sum Tests were used to determine associations and significance between tumor subtypes. Intraclass correlation (ICC) and kappa calculations were utilized to assess inter-reader agreements for ADC values and reader diagnosis. Liposarcomas showed more heterogenous T1W images with hyperintense T1W signal when compared to tumors not classified as liposarcoma (P = 0.046 and P = 0.010, respectively). Liposarcomas were relatively consistent in demonstrating an absence of hemorrhage (81.8%) while undifferentiated pleomorphic sarcomas consistently showed intralesional hemorrhage (90%). When comparing individual tumor classifications against the rest of the samples, lymphomas registered lower mean and minimum ADC values in the whole tumor and in themost hypointense area of the tumor for both readers (P < 0.05). The interobserver agreement between the two readers was good to excellent for all four ADC measurements (ICC = 0.65-0.98). Diffusion-weighted imaging generated ADC measurements are reproducible but currently offer limited insight in being able to differentiate among different malignant soft tissue tumor and sarcoma histologies.T1W and T2W signal characteristics also offer limited insight indifferentiating between soft tissue malignancies.

Comparison of ZOOMit-DWI sequence and conventional DWI sequence in endometrial cancer.

Magnetic resonance diffusion-weighted imaging (DWI) has important clinical value in diagnosis and curative effect evaluation on endometrial carcinoma. How to improve the detection rate of endometrial small lesions by DWI is the research focus of MRI technology. This study aims to analyze the image quality of small field MRI ZOOMit-DWI sequence and conventional single-shot echo-planar imaging (SS-EPI) DWI sequence in the scanning of endometrial carcinoma, and to explore the clinical value of ZOOMit-DWI sequence. A total of 37 patients with endometrial carcinoma diagnosed by operation and pathology in the Second Xiangya Hospital of Central South University from July 2019 to May 2021 were collected. All patients were scanned with MRI ZOOMit-DWI sequence and SS-EPI DWI sequence before operation. Two radiologists subjectively evaluated the anatomical details, artifacts, geometric deformation and focus definition of the 2 groups of DWI images. At the same time, the signal intensity were measured and the signal-to-noise ratio (SNR), contrast to noise ratio (CNR), and apparent diffusion coefficient (ADC) of the 2 DWI sequences were calculated for objective evaluation. The differences of subjective score, objective score and ADC value of the 2 DWI sequences were analyzed. The SNR of the ZOOMit-DWI group was significantly higher than that of the SS-EPI DWI group (301.96±141.85 vs 94.66±41.26), and the CNR of the ZOOMit-DWI group was significantly higher than that of the SS-EPI DWI group (185.05±105.45 vs 57.91±31.54, P<0.05). There was no significant difference in noise standard deviation between the ZOOMit-DWI group and the SS-EPI DWI group (P>0.05). The subjective score of anatomical detail and focus definition in the ZOOMit-DWI group was significantly higher than that of the SS-EPI DWI group (both P<0.05). The subjective score of artifacts and geometric deformation of ZOOMit-DWI group was significantly lower than that of the SS-EPI DWI group (both P<0.05). ADC had no significant difference between the ZOOMit-DWI group and the SS-EPI DWI group (P>0.05). The image quality of ZOOMit-DWI is significantly higher than that of conventional SS-EPI DWI. In the MRI DWI examination of endometrial carcinoma, ZOOMit-DWI can effectively reduce the geometric deformation and artifacts of the image, which is more conducive to clinical diagnosis and treatment.

Apparent Diffusion Coefficient in the Differentiation of Common Pediatric Brain Tumors in the Posterior Fossa: Different Region-of-Interest Selection Methods for Time Efficiency, Measurement Reproducibility, and Diagnostic Utility.

This study aimed to explore the diagnostic ability of apparent diffusion coefficient (ADC) values obtained from different region of interest (ROI) measurements in tumor parenchyma for differentiating posterior fossa tumors (PFTs) and the correlations between ADC values and Ki-67. Seventy-three pediatric patients with PFTs who underwent conventional diffusion-weighted imaging were recruited in this study. Five different ROIs were manually drawn by 2 radiologists (ROI-polygon, ROI-3 sections, ROI-3-5 ovals, ROI-more ovals, and ROI-whole). The interreader/intrareader repeatability, time required, diagnostic ability, and Ki-67 correlation analysis of the ADC values based on these ROI strategies were calculated. Both interreader and intrareader reliabilities were excellent for ADC values among the different ROI strategies (intraclass correlation coefficient, 0.899-0.992). There were statistically significant differences in time consumption among the 5 ROI selection methods ( P < 0.001). The time required for the ROI-3-5 ovals was the shortest (32.23 ± 5.14 seconds), whereas the time required for the ROI-whole was the longest (204.52 ± 92.34 seconds). The diagnostic efficiency of the ADC values showed no significant differences among the different ROI measurements ( P > 0.05). The ADC value was negatively correlated with Ki-67 ( r = -0.745 to -0.798, all P < 0.0001). The ROI-3-5 ovals method has the best interobserver repeatability, the shortest amount of time spent, and the best diagnostic ability. Thus, it is considered an effective measurement to produce ADC values in the evaluation of pediatric PFTs.

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI). To compare conventional bpMRIs (CL-bpMRI) with bpMRIs including a deep learning-accelerated T2WI (DL-bpMRI) in diagnosing prostate cancer. Retrospective. Eighty consecutive men, mean age 66 years (47-84) with suspected prostate cancer or prostate cancer on active surveillance who had a prostate MRI from December 28, 2020 to April 28, 2021 were included. Follow-up included prostate biopsy or stability of prostate-specific antigen (PSA) for 1 year. A 3 T MRI. Conventional axial and coronal T2 turbo spin echo (CL-T2), 3-fold deep learning-accelerated axial and coronal T2-weighted sequence (DL-T2), diffusion weighted imaging (DWI) with b=50 sec/mm2 , 1000 sec/mm2 , calculated b=1500 sec/mm2 . CL-bpMRI and DL-bpMRI including the same conventional diffusion-weighted imaging (DWI) were presented to three radiologists (blinded to acquisition method) and to a deep learning computer-assisted detection algorithm (DL-CAD). The readers evaluated image quality using a 4-point Likert scale (1=nondiagnostic, 4=excellent) and graded lesions using Prostate Imaging Reporting and Data System (PI-RADS) v2.1. DL-CAD identified and assigned lesions of PI-RADS 3 or greater. Quality metrics were compared using Wilcoxon signed rank test, and area under the receiver operating characteristic curve (AUC) were compared using Delong's test. P=0.05. Eighty men were included (age: 66 ± 9 years; 17/80 clinically significant prostate cancer). Overall image quality results by the three readers (CL-T2, DL-T2) are reader 1: 3.72 ± 0.53, 3.89 ± 0.39 (P=0.99); reader 2: 3.33 ± 0.82, 3.31 ± 0.74 (P=0.49); reader 3: 3.67 ± 0.63, 3.51 ± 0.62. In the patient-based analysis, the reader results of AUC are (CL-bpMRI, DL-bpMRI): reader 1: 0.77, 0.78 (P=0.98), reader 2: 0.65, 0.66 (P=0.99), reader 3: 0.57, 0.60 (P=0.52). Diagnostic statistics from DL-CAD (CL-bpMRI, DL-bpMRI) are sensitivity (0.71, 0.71, P=1.00), specificity (0.59, 0.44, P = 0.05), positive predictive value (0.23, 0.24, P=0.25), negative predictive value (0.88, 0.88, P=0.48). Deep learning-accelerated T2-weighted imaging may potentially be used to decrease acquisition time for bpMRI. 3. Stage 2.

Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions.

Whole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions. To compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis. Fifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance. The ADCmean, ADCmedian, D mean and D median values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kapp mean, Kapp median, Kapp SD, Kapp kurtosis and Dapp skewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and D median (p = 0.031) were identified as independent predictors of lung cancer. D median showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a D median of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively. Whole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and D median shows the best performance in the differential diagnosis of solitary pulmonary lesions.

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

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

A Multicompartmental Diffusion Model for Improved Assessment of Whole-Body Diffusion-weighted Imaging Data and Evaluation of Prostate Cancer Bone Metastases

Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10-3, 2.8 × 10-3, and >3.0 ×10-2 mm2/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

Estimation of white matter hyperintensities with synthetic MRI myelin volume fraction in patients with multiple sclerosis and non-multiple-sclerosis white matter hyperintensities: A pilot study among the Indian population

&lt;abstract&gt;&lt;sec&gt; &lt;title&gt;AIM&lt;/title&gt; &lt;p&gt;Synthetic MRI (SyMRI) works on the MDME sequence, which acquires the relaxation properties of the brain and helps to measure the accurate tissue properties in 6 minutes. The aim of this study was to evaluate the synthetic MRI (SyMRI)-generated myelin (MyC) to white matter (WM) ratio, the WM fraction (WMF), MyC partial maps performing normative brain volumetry to investigate MyC loss in multiple sclerosis (MS) patients with white-matter hyperintensites (WMHs) and non-MS patients with WMHs in a clinical setting.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;MATERIALS and METHODS&lt;/title&gt; &lt;p&gt;Synthetic MRI images were acquired from 15 patients with MS, and from 15 non-MS patients on a 3T MRI scanner (Discovery MR750w; GE Healthcare; Milwaukee, USA) using MAGiC, a customized version of SyntheticMR's SyMRI® IMAGE software marketed by GE Healthcare under a license agreement. Fast multi-delay multi-echo acquisition was performed with a 2D axial pulse sequence with different combinations of echo time (TEs) and saturation delay times. The total image acquisition time was 6 minutes. SyMRI image analysis was done using SyMRI software (SyMRI Version: 11.3.6; Synthetic MR, Linköping, Sweden). SyMRI data were used to generate the MyC partial maps and WMFs to quantify the signal intensities of test group and control group, andcontrol group , and their mean values were recorded. All patients also underwent conventional diffusion-weighted imaging, i.e., T1w and T2w imaging.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;RESULTS&lt;/title&gt; &lt;p&gt;The results showed that the WMF was significantly lower in the test group than in the control group (38.8% vs 33.2%, p &amp;lt; 0.001). The Mann-Whitney U nonparametric t-test revealed a significant difference in the mean myelin volume between the test group and the control group (158.66 ± 32.31 vs. 138.29 ± 29.28, p = 0.044). Also, there were no significant differences in the gray matter fraction and intracranial volume between the test group and the control group.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;CONCLUSIONS&lt;/title&gt; &lt;p&gt;We observed MyC loss in test group using quantitative SyMRI. Thus, myelin loss in MS patients can be quantitatively evaluated using SyMRI.&lt;/p&gt; &lt;/sec&gt;&lt;/abstract&gt;

Non-invasive evaluation of the pathological and functional characteristics of chronic kidney disease by diffusion kurtosis imaging and intravoxel incoherent motion imaging: comparison with conventional DWI.

To explore the diagnostic performance of diffusion kurtosis imaging (DKI) and incoherent intravoxel movement (IVIM) in evaluating the clinical and pathological characteristics in chronic kidney disease (CKD) compared to conventional diffusion-weighted imaging (DWI). Forty-nine CKD patients and 24 healthy volunteers were included in this retrospective study from September 2020 to September 2021. All participants underwent MRI examinations before percutaneous renal biopsy. Coronal T2WI, axial T1WI and T2WI, and DWI (including IVIM and DKI) sequences obtained in one scan. We measured the apparent diffusion coefficient (ADC), true diffusion coefficient (Dt), pseudo-diffusion coefficient (Dp), perfusion fraction (fp), mean kurtosis (MK), and mean diffusivity (MD) values. One-way analysis of variance, correlation analysis, and receiver operating characteristic curve analysis were used in our study. Cortex and medulla ADC, MK, Dt, fp were significantly different between the healthy volunteers and CKD stages 1-2 (all p < 0.05). All diffusion parameters showed significant differences between CKD stages 1-2 and CKD stages 3-5 (all p < 0.05). Except for the uncorrelation between MDMedulla and vascular lesion score, all other diffusion parameters were low-to-moderately related to clinical and pathological indicators. fpMedulla was the best parameter to differentiate healthy volunteers from CKD stages 1-2. MKCortex was the best parameter to differentiate CKD stages 1-2 from that CKD stages 3-5. Renal cortex and medulla fp, Dt, and MK can provide more valuable information than ADC values for the evaluation of clinical and pathological characteristics of CKD patients, and thus can provide auxiliary diagnosis for fibrosis assessment and clinical management of CKD patients. IVIM and DKI can provide more diagnostic valuable information for CKD patients than conventional DWI.

Whole-tumor histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for soft tissue sarcoma: correlation with HIF-1alpha expression.

To investigate the correlation of histogram metrics from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with HIF-1alpha expression in soft tissue sarcoma (STS). We enrolled 71 patients with STS who underwent 3.0-T MRI, including conventional MRI, DWI, and DCE-MRI sequences. Location, maximum tumor diameter, envelope, T2-weighted tumor heterogeneity, peritumoral edema, peritumoral enhancement, necrosis, tail-like pattern, bone invasion, and vessel/nerve invasion and/or encasement were determined using conventional MRI images. The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), Ktrans, Kep, and Ve maps. Independent-samples t test and one-way ANOVA were used for testing the differences between normally distributed categorical data with HIF-1alpha expression. Pearson and Spearman correlations and multiple linear regression analyses were performed to determine the correlations between histogram metrics and HIF-1alpha expression. Survival curves were plotted using the Kaplan-Meier method. Regarding conventional MRI features, only highly heterogeneous on T2-weighted images (55.6 ± 19.9% vs. 45.4 ± 20.5%, p = 0.041) and more than 50% necrotic area (57.3 ± 20.4% vs. 43.9 ± 19.7%, p = 0.002) were prone to indicate STS with higher HIF-1alpha expression. Histogram metrics obtained from ADC (mean, median, 10th, and 25th percentile values), Ktrans (mean, median, 75th, and 90th percentile values), and Kep (90th percentile values) were significantly correlated with HIF-1alpha expression. Multiple linear regression analysis demonstrated that more than 50% necrosis, ADCskewness, Ktrans90th, and grade III were independently associated with HIF-1alpha expression. DWI and DCE-MRI histogram parameters were significantly correlated with HIF-1alpha expression in STS. • DWI and DCE-MRI histogram parameters are correlated with HIF-1alpha expression in STS. • More than 50% necrosis, ADCskewness, Ktrans90th, and grade III were independently associated with HIF-1alpha expression in STS.

Diffusion kurtosis imaging in patients with tissue-negative transient ischemic attack.

Approximately 50-60% of patients with a clinical transient ischemic attack (TIA) do not have diffusion-weighted imaging (DWI) evidence of cerebral ischemia. The purpose of this study was to assess the added diagnostic value of diffusion kurtosis imaging (DKI) in the evaluation of patients with TIA who have normal DWI findings. From September 2014 to May 2017, a total of 179 consecutive patients with suspected TIA were eligible for enrollment in our study. The inclusion criteria were a confirmed diagnosis of TIA confirmed by a stroke neurologist, MRI (including DWI and DKI) within 24 h after symptom onset, no stroke history, and no DWI lesion. A follow-up DWI was performed to establish stroke recurrence within a period of 90 days. A total of 98 patients who had no lesions on the baseline DWI were included for data analysis. Of these 98 patients, 31 (31.6%) had positive findings on the initial DKI. In 29 of the 31 (93.5%) patients, the location of the abnormality observed on DKI was consistent with the clinical symptoms. During the 90-day follow-up period, 14 (14.3%) patients developed recurrent stroke. The prevalence of recurrent stroke was higher in the DKI-positive group than in the DKI-negative group (29.0% vs. 7.5%, p = 0.01). A comparison between the patients with and without recurrent stroke showed that an abnormality on the baseline DKI was associated with stroke recurrence. Furthermore, 8 of the 9 stroke patients in the DKI-positive group developed a new ischemic lesion in the artery territory corresponding to the initial DKI abnormality. The new findings suggest the predictive value of DKI on the recurrence of stroke in the patients with TIA who have negative findings on conventional DWI.

Endometrial carcinoma detection with 3.0 Tesla imaging: which sequence is more useful.

Detection of endometrial cancer (EC) is crucial in pre-operative EC management. The study aimed at determining the most reliable sequence in magnetic resonance imaging (MRI) evaluation at the EC. Different sequences were compared using histopathological results as the gold standard. In this retrospective study, 62 women diagnosed with EC were examined using 3 Tesla MR and post-hysterectomy histopathological examination. The MRI protocol included diffusion-weighted imaging (DWI), T2 weighted images, Dynamic Contrast T1 weighted images, and ZOOMit DWI. Apparent diffusion coefficient (ADC) maps were also obtained. ADC maps were calculated for both DWI and ZOOMit DWI. All serial images were analyzed by endometrial distance to account for myometrial invasion and tumor size. All sequences and histopathological results were compared using the paired sample t-test. In all 32 women, post-hysterectomy histopathological confirmation was obtained. Mean myometrial invasion values were not significantly different after comparing DWI, ZOOM it DWI, and Dynamic contrast enhancement (DCE)-T1WI (p=0.054, p=0.039). The first strong correlation was found between DWI and ZOOMit DWI (0.943). The second was between ZOOMit DWI and DCE-T1 WI (0.949). Comparing each set of sequences, no statistically significant differences in tumor size (p > 0.05) were found. Also, no statistically significant differences between images and histopathological size were found. The ADC values of ZOOMit DWI indicated that this method detected significant differences between EC histological subtypes. Each sequence is essential and valuable, whereas priorities may vary depending on the desired information. The most valuable sequences for the myometrial invasion were ZOOMit and conventional DWI. T2WI and DCE T1 WI were more valuable sequences the size of EC.

Diffusion-Weighted MR Imaging of the Optic Nerve Can Improve the Detection of Post-Laminar Optic Nerve Invasion from Retinoblastoma.

Post-laminar optic nerve invasion (PLONI) is a high-risk factor for the metastasis of retinoblastoma (RB). Unlike conventional MRI, diffusion-weighted imaging (DWI) reflects histopathological features, and may aid the assessment of PLONI. To determine the value of conventional MRI plus DWI in detecting PLONI in RB patients. Retrospective. Eighty-three RB patients, including 28 with histopathologically proven PLONI and 55 without PLONI. 3.0 T, precontrast axial T1-weighted and T2-weighted imaging, DWI, and postcontrast axial, coronal, and oblique-sagittal T1-weighted imaging. PLONI was assessed using post-enucleation histology and preoperative MRI features (optic nerve signal intensity, enlargement, and enhancement on conventional MRI, and apparent diffusion coefficient [ADC] of the optic nerve on DWI) evaluated by three observers. MRI features suggesting the presence of PLONI were identified using univariable and multivariable analyses. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to analyze diagnostic performance. Optic nerve enhancement and low ADC of the optic nerve were significant indicators of PLONI. ROC curve analysis showed that the AUC of the combination of these two features for detecting PLONI was 0.87 (95% confidence interval [CI]: 0.78-0.93). The diagnostic performance of this model was significantly superior to that of optic nerve enhancement alone (0.76, 95% CI: 0.65-0.85) and marginally superior to that of the ADC of the affected optic nerve (0.78, 95% CI: 0.68-0.87, P=0.051). Conventional MRI combined with DWI can improve the detection of PLONI in RB patients over conventional MRI alone. 3 Technical Efficacy: Stage 2.

Optimising diffusion-weighted imaging of the thyroid gland using dedicated surface coil

To assess the feasibility of applying field-of-view (FOV) optimised and constrained undistorted single-shot (FOCUS) diffusion-weighted imaging (DWI) in the thyroid gland by comparing its image quality with conventional DWI (C-DWI) qualitatively and quantitatively using a dedicated surface coil exclusively designed for the thyroid gland at 3 T magnetic resonance imaging (MRI). In this prospective study, 32 healthy volunteers who had undergone 3 T the thyroid gland MRI with FOCUS-DWI and C-DWI were enrolled. Two independent reviewers assessed the overall image quality, artefacts, sharpness, and geometric distortion based on a five-point Likert scale. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) were quantified for both sequences. Interobserver agreement, qualitative scores, and quantitative parameters were compared between two sequences. Agreement between the two readers was good for FOCUS-DWI (κ=0.714-0.778) and moderate to good for C-DWI (κ=0.525-0.672) in qualitative image quality assessment. Qualitatively, image quality (overall image quality, artefacts, sharpness, and geometric distortion) was significantly better in FOCUS-DWI than that in the C-DWI (all p<0.05); however, quantitatively, FOCUS-DWI had significantly lower SNRs (p<0.001) and CNRs (p=0.012) compared with C-DWI. The ADC value on FOCUS-DWI was significantly higher than that on C-DWI (p<0.001). FOCUS-DWI depicted the thyroid gland with significantly better image quality qualitatively and less ghost artefacts, but had significantly lower SNR and CNR quantitatively, compared with C-DWI, suggesting that both DWI sequences have advantages and could be chosen for different purposes.

A comparative study of functional MRI in predicting response of regional nodes to induction chemotherapy in patients with nasopharyngeal carcinoma.

PurposeTo identify and compare the value of functional MRI (fMRI) in predicting the early response of metastatic cervical lymph nodes (LNs) to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) patients.MethodsThis prospective study collected 94 metastatic LNs from 40 consecutive NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion-weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and dynamic contrast-enhanced magnetic resonance imaging were performed before and after IC. The parameter maps apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), Dslow, Dfast, perfusion fraction (PF), Ktrans, Ve, and Kep) of the metastatic nodes were calculated by the Functool postprocessing software. All LNs were classified as the responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between the RG and the NRG. The significant parameters are fitted by logistic regression analysis to produce new predictive factor (PRE)–predicted probabilities. Logistic regression analysis and receiver operating characteristic (ROC) curves were performed to further identify and compare the efficacy of the parameters.ResultsAfter IC, the mean values of ADC, MD, and Dslow significantly increased, while MK, Dfast, and Ktrans values decreased dramatically, while no significant difference was detected in Ve and Kep. Compared with NRG, PF-pre and Ktrans-pre values in the RG were higher statistically. The areas under the ROC for the pretreatment PF, Ktrans, and PRE were 0.736, 0.722, and 0.810, respectively, with the optimal cutoff value of 222 × 10-4, 934 × 10-3/min, and 0.6624, respectively.ConclusionsThe pretreatment fMRI parameters PF and Ktrans showed promising potential in predicting the response of the metastatic LNs to IC in NPC patients.Clinical Trial RegistrationThis study was approved by the ethics board of the Chinese PLA General Hospital, and registered on 30 January 2021, in the Chinese Clinical Trial Registry; http://www.chictr.org.cn/showproj.aspx?proj=121198, identifier (ChiCTR2100042863).

Diffusion and perfusion MRI parameters in the evaluation of placenta accreta spectrum disorders in patients with placenta previa.

To evaluate the placental function by monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in patients with placenta previa. A total of 62 patients with placenta accreta spectrum (PAS) disorders and 11 patients with normal placentas were retrospectively enrolled, who underwent conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI). The apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, mean 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. Comparisons between patients with PAS disorders and patients with normal placentas demonstrated that MD mean, D mean, and D* mean values in patients with PAS disorders were significantly higher than those in patients with normal placentas (p < 0.05). Comparisons between patients with accreta, increta, and percreta, and patients with normal placentas showed that the D mean was significantly higher in patients with placenta increta and percreta than in patients with normal placentas (p < 0.05). The accreta lesions in PAS disorders had deceased cellularity and increased blood movement. The alteration of placental cellularity was more prominent in placenta increta and percreta.

Clinical feasibility of accelerated diffusion weighted imaging of the abdomen with deep learning reconstruction: Comparison with conventional diffusion weighted imaging

PurposeTo assess the clinical feasibility of accelerated deep learning–reconstructed diffusion weighted imaging (DWI) and to compare its image quality and acquisition time with those of conventional DWI. MethodsSeventy-four consecutive patients who underwent 3 T abdominal magnetic resonance imaging (MRI) were retrospectively enrolled. DWI were acquired using both conventional DWI and DWI with deep-learning reconstruction (DL DWI). Image quality (overall image quality, anatomic sharpness and details, artifacts, noise, and lesion conspicuity) was scored by two radiologists and compared between two DWI sequences. The apparent diffusion coefficient (ADC) was measured in six locations of the liver parenchyma and focal lesions and compared between two DWI sequences. ResultsThe mean acquisition time for the DL DWI (216.87 ± 49.23 sec) was significantly shorter (P < 0.001) than for conventional DWI (358.69 ± 105.93 sec). DL DWI achieved higher scores than conventional DWI for all qualitative image quality parameters (P < 0.001). DL DWI had a more homogeneous distribution of ADC values throughout the liver, except for the left superior section, compared with conventional DWI. The standard deviations of the ADC values for all hepatic areas were significantly lower in DL DWI than in conventional DWI (all, P < 0.001). The ADC values for the liver parenchyma and focal hepatic lesions were lower in DL DWI than in conventional DWI. ConclusionsDL DWI is a feasible acquisition technique in clinical routines and provides improved image quality and simultaneously significant reduction in scan time compared with conventional DWI.

Computed diffusion-weighted magnetic resonance imaging with high b-values in the diagnosis of gallbladder lesions.

The diagnosis of gallbladder lesions remains challenging. The efficacy of computed diffusion-weighted imaging (DWI) with high b-values and apparent diffusion coefficient (ADC) for the diagnosis of gallbladder cancer remains unknown. We aimed to investigate the usefulness of computed DWI with high b-values and the combination of computed DWI and ADC in differentiating malignant and benign gallbladder lesions. Sixty patients (comprising 30 malignant and 30 benign lesions) who underwent magnetic resonance imaging for gallbladder lesions were included in this retrospective study. Qualitative evaluations were performed using conventional DWI with b1000, computed DWI with b1500, b1000 DWI/ADC, and computed b1500 DWI/ADC, and their diagnostic performances were compared. The sensitivity, specificity, and accuracy of computed b1500 DWI/ADC were 90% (27/30), 80% (24/30), and 85% (51/60), respectively. The accuracy of computed b1500 DWI/ADC was higher than that of conventional b1000 DWI (52%, 31/60, p < 0.001), computed b1500 DWI (72%, 43/60, p = 0.008), and b1000 DWI/ADC (78%, 47/60, p = 0.125). The specificity of computed b1500 DWI/ADC was also higher than that of conventional b1000 DWI (7%, 2/30, p < 0.001), computed b1500 DWI (47%, 14/30, p = 0.002), and b1000 DWI/ADC (67%, 20/30, p = 0.125). No significant difference was observed in the sensitivity between the groups. This study shows that computed DWI with high b-values combined with ADC can improve diagnostic performance when differentiating malignant and benign gallbladder lesions. Computed diffusion-weighted magnetic resonance imaging with high b-values in the diagnosis of gallbladder lesions. *Computed DWI with b1500 combined with ADC can improve diagnostic performance when differentiating gallbladder lesions compared with conventional methods (b1000 DWI).

Texture analysis of conventional magnetic resonance imaging and diffusion-weighted imaging for distinguishing sinonasal non-Hodgkin's lymphoma from squamous cell carcinoma.

To evaluate the value of texture analysis (TA) of conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in the differential diagnosis between sinonasal non-Hodgkin's lymphoma (NHL) and squamous cell carcinoma (SCC). Forty-two patients with sinonasal SCC and 30 patients with NHL were retrospectively enrolled. TAs were performed on T2-weighted image (T2WI), apparent diffusion coefficient (ADC) and contrast-enhanced T1-weighted image (T1WI). Texture parameters, including mean value, skewness, kurtosis, entropy and uniformity were obtained and compared between sinonasal SCC and NHL groups. Receiver-operating characteristic (ROC) curves and logistic regression analyses were used to evaluate the diagnostic value and identify the independent TA parameters. The mean value and entropy of ADC, and mean value of contrast-enhanced T1WI were significantly lower in the sinonasal NHL group than those in the SCC group (all P < 0.05). ROC analysis indicated that the entropy of ADC had the best diagnostic performance (AUC 0.832; Sensitivity 0.95; Specificity 0.67; Cutoff value 6.522). Logistic regression analysis showed that the entropy of ADC (P = 0.002, OR = 26.990) was the independent parameter for differentiating sinonasal NHL from SCC. TA parameters of conventional MRI and DWI, particularly the entropy value of ADC, might be useful in the differentiating diagnosis between sinonasal NHL and SCC.