Diffusion-weighted Imaging Sequences Research Articles

Difference in Image Information Between DWI Sequence and DWI Blade for Optimization of Axial Brain

Background: Diffusion Weighted Image (DWI) sequence that utilizes the movement of molecules due to random thermal motion. The aim of this research is to determine the difference in image information between DWI sequence and DWI BLADE on axial brain MRI images for optimization and to find the most optimal sequence between DWI and DWI BLADE on axial brain MRI images. Method: This study used a quantitative experimental research that aims to determine image information and optimize brain MRI examinations between DWI sequence and DWI BLADE using the MRI Siemens Magnetom Amira 1.5 T at Dr. Oen Kandang Sapi Hospital Solo in May-June 2023. The sample consisted of 11 MRI assessments through visual grading analysis to provide interpretations related to image clarity information, thus obtaining the optimal use of DWI and DWI Blade sequences. Results: Based on the research and discussion results, it can be concluded that there is a difference in anatomical image information between DWI sequence with BLADE and without BLADE on axial brain MRI examinations, with a significance value of 0.00 (p<0.05), indicating a difference in anatomical image information in the cortex cerebri, thalamus, cerebellum, basal ganglia, and a significance value of 1.000 (p<0.05) for artifact information, indicating no difference in artifact image information between DWI sequences with BLADE and without BLADE. Conclusion: DWI BLADE sequence provides better anatomical image information compared to DWI sequence without BLADE in axial brain MRI examinations.

Variation of b Value for Axial DWI Prostate MR Imaging in Cancer: Which b Value is Optimal?

Background: Diffusion Weighted Imaging (DWI) is a technique that visualizes the movement of water molecules from areas of higher to lower concentration. In DWI sequences, the b-value parameter affects the signal intensity in the images. The objective of this study is to describe the differences in anatomical image information between b-value variations of 1500s/mm2, 2000s/mm2, and 2500s/mm2 in MRI prostate case cancer and to determine the most optimal b-value. Method: This study used a pre-exeachimental approach with a 1.5T Philips MRI machine at a private hospital in South Jakarta from March to April 2023. The sample consisted of 12 Prostate MRI images with DWI sequences and different b-values. Visual grading assessment was eachformed by three radiology specialists, and the data were analyzed using the Friedman test in SPSS. Results: The results showed a significant difference in anatomical image information based on the b-value variations used, with a p-value of 0.05 (0.02). The highest mean rank was obtained from the Friedman test for the b-value of 2000s/mm2. Conclusion: The significant difference in anatomical image information occurred due to differences in signal intensity and noise levels. Prostate cancer tissues appeared more hyperintense with lower noise in images with higher b-values, and vice versa. Additionally, the b-value of 2000s/mm2 resulted in the most optimal signal intensity and noise level. In conclusion, the use of b-value variations in axial DWI images of prostate cancer Prostate MRI to differences in anatomical image information, with the most optimal image information observed at a b-value of 2000s/mm2.

Prediction of pathological complete response in locally advanced head and neck squamous cell carcinoma treated with neoadjuvant chemo-immunotherapy using volumetric multisequence MRI histogram analysis.

This study aimed to develop a multisequence MRI-based volumetric histogram metrics model for predicting pathological complete response (pCR) in advanced head and neck squamous cell carcinoma (HNSCC) patients undergoing neoadjuvant chemo-immunotherapy (NCIT) and compare its predictive performance with AJCC staging and RECIST 1.1 criteria. Twenty-four patients with locally advanced HNSCC from a prospective phase II trial were enrolled for analysis. All patients underwent pre- and post-NCIT MRI examinations from which whole-tumor histogram features were extracted, including T1WI, T2WI, enhanced T1WI (T1Gd), diffusion-weighted imaging (DWI) sequences, and their corresponding apparent diffusion coefficient (ADC) maps. The pathological results divided the patients into pathological complete response (pCR) and non-pCR (N-pCR) groups. Delta features were calculated as the percentage change in histogram features from pre- to post-treatment. After data reduction and feature selection, logistic regression was used to build prediction models. ROC analysis was performed to assess the diagnostic performance. Eleven of 24 patients achieved pCR. Pre_T2_original_firstorder_Minimum, Post_ADC_original_firstorder_MeanAbsoluteDeviation, and Delta_T1Gd_original_firstorder_Skewness were associated with achieving pCR after NCIT. The Combined_Model demonstrated the best predictive performance (AUC 0.95), outperforming AJCC staging (AUC 0.52) and RECIST 1.1 (AUC 0.72). The Pre_Model (AUC 0.83) or Post-Model (AUC 0.83) had a better predictive ability than AJCC staging. Multisequence MRI-based volumetric histogram analysis can non-invasively predict the pCR status of HNSCC patients undergoing NCIT. The use of histogram features extracted from pre- and post-treatment MRI exhibits promising predictive performance and offers a novel quantitative assessment method for evaluating pCR in HNSCC patients receiving NCIT.

Magnetic resonance imaging fingerprints of status epilepticus: A case-control study.

Status epilepticus (SE) is frequently associated with peri-ictal magnetic resonance imaging (MRI) abnormalities (PMA). However, the anatomical distribution of these alterations has not been systematically studied. The aim of this study was to assess the localization patterns of PMA in patients with SE. In this prospective case-control study, we compared the distribution and combinations of diffusion-restricted PMA to diffusion-restricted lesions caused by other neurological conditions. All patients of the SE group and the control group underwent MRI including a diffusion-weighted imaging sequence. Patients with SE were imaged within 48 h after its onset. We enrolled 201 patients (51 with SE and 150 controls). The most frequent locations of PMA in SE were cortex (25/51, 49%), followed by hippocampus (20/51, 39%) and pulvinar of thalamus (10/51, 20%). In the control group, the cortex was involved in 80 of 150 (53%), white matter in 53 of 150 (35%), and basal ganglia in 33 of 150 (22%). In the control group, the pulvinar of thalamus was never affected and hippocampal structures were rarely involved (7/150, 5%). Involvement of the pulvinar of thalamus and the hippocampus had high specificity for SE at 100% (95% confidence interval [CI] = 98-100) and 95% (95% CI = 91-98), respectively. The sensitivity, however, was low for both locations (pulvinar of thalamus: 20%, 95% CI = 10-33; hippocampus: 39%, 95% CI = 26-54). Diffusion-restricted MRI lesions observed in the pulvinar of thalamus and hippocampus are strongly associated with SE. These changes may help physicians in diagnosing SE-related changes on MRI in an acute setting, especially in cases of equivocal clinical and electroencephalographic manifestations of SE.

Repeatability quantification of brain diffusion-weighted imaging for future clinical implementation at a low-field MR-linac

BackgroundLongitudinal assessments of apparent diffusion coefficients (ADCs) derived from diffusion-weighted imaging (DWI) during intracranial radiotherapy at magnetic resonance imaging-guided linear accelerators (MR-linacs) could enable early response assessment by tracking tumor diffusivity changes. However, DWI pulse sequences are currently unavailable in clinical practice at low-field MR-linacs. Quantifying the in vivo repeatability of ADC measurements is a crucial step towards clinical implementation of DWI sequences but has not yet been reported on for low-field MR-linacs. This study assessed ADC measurement repeatability in a phantom and in vivo at a 0.35 T MR-linac.MethodsEleven volunteers and a diffusion phantom were imaged on a 0.35 T MR-linac. Two echo-planar imaging DWI sequence variants, emphasizing high spatial resolution (“highRes”) and signal-to-noise ratio (“highSNR”), were investigated. A test–retest study with an intermediate outside-scanner-break was performed to assess repeatability in the phantom and volunteers’ brains. Mean ADCs within phantom vials, cerebrospinal fluid (CSF), and four brain tissue regions were compared to literature values. Absolute relative differences of mean ADCs in pre- and post-break scans were calculated for the diffusion phantom, and repeatability coefficients (RC) and relative RC (relRC) with 95% confidence intervals were determined for each region-of-interest (ROI) in volunteers.ResultsBoth DWI sequence variants demonstrated high repeatability, with absolute relative deviations below 1% for water, dimethyl sulfoxide, and polyethylene glycol in the diffusion phantom. RelRCs were 7% [5%, 12%] (CSF; highRes), 12% [9%, 22%] (CSF; highSNR), 9% [8%, 12%] (brain tissue ROIs; highRes), and 6% [5%, 7%] (brain tissue ROIs; highSNR), respectively. ADCs measured with the highSNR variant were consistent with literature values for volunteers, while smaller mean values were measured for the diffusion phantom. Conversely, the highRes variant underestimated ADCs compared to literature values, indicating systematic deviations.ConclusionsHigh repeatability of ADC measurements in a diffusion phantom and volunteers’ brains were measured at a low-field MR-linac. The highSNR variant outperformed the highRes variant in accuracy and repeatability, at the expense of an approximately doubled voxel volume. The observed high in vivo repeatability confirms the potential utility of DWI at low-field MR-linacs for early treatment response assessment.

Effect of Phase Encoding Direction on Image Quality in Single-Shot EPI Diffusion-Weighted Imaging of the Breast.

In breast diffusion-weighted imaging (DWI), distortion and physiologic artifacts affect clinical interpretation. Image quality can be optimized by addressing the effect of phase encoding (PE) direction on these artifacts. To compare distortion artifacts in breast DWI acquired with different PE directions and polarities, and to discuss their clinical implications. Prospective. Eleven healthy volunteers (median age: 47 years old; range: 22-74 years old) and a breast phantom. Single-shot echo planar DWI and three-dimensional fast gradient echo sequences at 3 T. All DWI data were acquired with left-right, right-left, posterior-anterior, and anterior-posterior PE directions. In phantom data, displacement magnitude was evaluated by comparing the location of landmarks in anatomical and DWI images. Three breast radiologists (5, 17, and 23 years of experience) assessed the presence or absence of physiologic artifacts in volunteers' DWI datasets and indicated their PE-direction preference. Analysis of variance with post-hoc tests were used to assess differences in displacement magnitude across DWI datasets and observers. A binomial test and a chi-squared test were used to evaluateif each in vivo DWI dataset had an equal probability (25%) of being preferred by radiologists. Inter-reader agreement was evaluated using Gwet's AC1 agreement coefficient. A P-value <0.05 was considered statistically significant. In the phantom study, median displacement was the significantly largest in posterior-anterior data. While the displacement in the anterior-posterior and left-right data were equivalent (P = 0.545). In the in vivo data, there were no physiological artifacts observed in any dataset, regardless of PE direction. In the reader study, there was a significant preference for the posterior-anterior datasets which were selected 94% of the time. There was good agreement between readers (0.936). This study showed the impact of PE direction on distortion artifacts in breast DWI. In healthy volunteers, the posterior-to-anterior PE direction was preferred by readers. 2 TECHNICAL EFFICACY: Stage 1.

Value of diffusion kurtosis MR imaging and conventional diffusion weighed imaging for evaluating response to first-line chemotherapy in unresectable pancreatic cancer

ObjectiveTo investigate the diagnostic value of diffusion kurtosis magnetic resonance imaging (DKI) and conventional diffusion-weighted imaging (DWI) for evaluating the response to first-line chemotherapy in unresectable pancreatic cancer.Materials and methodsWe retrospectively analyzed 21 patients with clinically and pathologically confirmed unresected pancreatic cancer who received palliative chemotherapy. Three-tesla MRI examinations containing DWI sequences with b values of 0, 100, 700, 1400, and 2100 s/mm2 were performed before and after chemotherapy. Parameters included the apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), and mean diffusional kurtosis (MK). The performances of the DWI and DKI parameters in distinguishing the response to chemotherapy were evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Overall survival (OS) was calculated from the date of first treatment to the date of death or the latest follow-up date.ResultsThe ADCchange and MDchange were significantly higher in the responding group (PR group) than in the nonresponding group (non-PR group) (ADCchange: 0.21 ± 0.05 vs. 0.11 ± 0.09, P = 0.02; MDchange: 0.37 ± 0.24 vs. 0.10 ± 0.12, P = 0.002). No statistical significance was shown when comparing ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost between the PR and non-PR groups. The ROC curve analysis indicated that MDchange (AUC = 0.898, cutoff value = 0.7143) performed better than ADCchange (AUC = 0.806, cutoff value = 0.1369) in predicting the response to chemotherapy.ConclusionThe ADCchange and MDchange demonstrated strong potential for evaluating the response to chemotherapy in unresectable pancreatic cancer. The MDchange showed higher specificity in the classification of PR and non-PR than the ADCchange. Other parameters, including ADCpre, ADCpost, MKpre, MKpost, MKchange, MDpre, and MDpost, are not suitable for response evaluation. The combined model SUMchange demonstrated superior performance compared to the individual DWI and DKI models. Further experiments are needed to evaluate the potential of DWI and DKI parameters in predicting the prognosis of patients with unresectable pancreatic cancer.

Prediction of underweight, short stature, and microcephaly based on brain diffusion-weighted imaging sequence in neonates with stage.2 of hypoxic-ischemic encephalopathy: A follow-up study.

Hypoxic-ischemic encephalopathy (HIE), caused due to reduced oxygenation and brain blood flow, occurs in 1-8 per 1000 live full-term births in developed countries and up to 26 per 1000 live in the developing world. The growth status of survivors of birth HIE has not been evaluated sufficiently. This study evaluated, the growth parameters (weight, height, and head circumference) of neonates with Sarnat stage.2 of HIE at 6, 10, and 12 months and its relationship with findings of neonatal brain diffusion-weighted imaging (DWI) sequence. Medical records and growth parameters of 35 neonates with gestational age 34 wk who were admitted with stage.2 of HIE in Neonatal Intensive Care Unit of Shahid Sadoughi hospital, Yazd, Iran from March 2021-March 2022, and its relationship with neonatal brain DWI sequence finding was evaluated. 15 girls and 20 boys with a mean birth weight of 2880.3 221.8 gr were evaluated. Conventional magnetic resonance imaging and DWI were found to be abnormal in 6 (17.1%) and 18 neonates (51.4%). The most abnormal finding of DWI was high signal in basal ganglia/thalamus in 9 neonates (25.7%). Abnormal DWI is more frequent in neonates with seizures and low birth weight. Hospital stay days were more prolonged in neonates with abnormal DWI. Microcephaly at 12 months was more frequent in children with abnormal DWI. In survivors of moderate neonatal HIE, abnormal brain DWI sequence might predict inappropriate head growth, and need close medical and nutritional interventions for growth improvement.

Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3.

For patients with PI-RADS v2.1 ≥ 3, prostate biopsy is strongly recommended. Due to the unsatisfactory positive rate of biopsy, improvements in clinically significant prostate cancer (csPCa) risk assessments are required. To develop and validate machine learning (ML) models based on clinical and imaging parameters for csPCa detection in patients with PI-RADS v2.1 ≥ 3. Retrospective. One thousand eighty-three patients with PI-RADS v2.1 ≥ 3, randomly split into training (70%, N = 759) and validation (30%, N = 324) datasets, and 147 patients enrolled prospectively for testing. 3.0 T scanners/T2-weighted fast spin echo sequence and DWI with diffusion-weighted single-shot gradient echo planar imaging sequence. The factors evaluated for csPCa detection were age, prostate specific antigen, prostate volume, and the diameter and location of the index lesion, PI-RADSv2.1. Five ML models for csPCa detection were developed: logistic regression (LR), extreme gradient boosting, random forest (RF), decision tree, and support vector machines. The csPCa was defined as Gleason grade ≥2. Univariable and multivariable LR analyses to identify parameters associated with csPCa. Area under the receiver operating characteristic curve (AUC), Brier score, and DeLong test were used to assess and compare the csPCa diagnostic performance with the LR model. The significance level was defined as 0.05. The RF model exhibited the highest AUC (0.880-0.904) and lowest Brier score (0.125-0.133) among the ML models in the validation and testing cohorts, however, there was no difference when compared to the LR model (P = 0.453 and 0.548). The sensitivity and negative predictive values in the validation and testing cohorts were 93.8%-97.6% and 82.7%-95.1%, respectively, at a threshold of 0.450 (99% sensitivity of the RF model). The RF model might help for assessing the risk of csPCa and preventing overdiagnosis and unnecessary biopsy for men with PI-RADSv2.1 ≥ 3. 3 TECHNICAL EFFICACY: Stage 2.

A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer.

To develop and validate a nomogram for the preoperative diagnosis of T2 and T3 stage rectal cancer using MRI radiomics features of mesorectal fat. The data of 288 patients with T2 and T3 stage rectal cancer were retrospectively collected. Radiomics features were extracted from the lesion region of interest (ROI) in the MRI high-resolution T2WI, apparent diffusion coefficient (ADC), and diffusion-weighted imaging (DWI) sequences. After using ICC inter-group consistency analysis and Pearson correlation analysis to reduce dimensions, LASSO regression analysis was performed to select features and calculate Rad-score for each sequence. Then, Combined_Radscore and nomogram were constructed based on the LASSO-selected features and clinical data for each sequence. Receiver operating characteristic curve (ROC) area under the curve (AUC) was used to evaluate the performance of the Rad-score model and nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical usability of the radiomics nomogram, which were combined with calibration curves to evaluate the prediction accuracy. The nomogram based on MRI-report T status and Combined_Radscore achieved AUCs of 0.921 and 0.889 in the training and validation cohorts, respectively. The nomogram can be stated that the radiomics nomogram based on multi-sequence MRI imaging of the mesorectal fat has excellent diagnosing performance for preoperative differentiation of T2 and T3 stage rectal cancer.

Improved diagnostic accuracy of readout-segmented echo-planar imaging for peripheral zone clinically significant prostate cancer: a retrospective 3T MRI study

This study compares the readout-segmented echo-planar imaging (rsEPI) from the conventional single-shot EPI (ssEPI) diffusion-weighted imaging (DWI) for the discrimination of patients with clinically significant prostate cancer (csPCa) within the peripheral zone (PZ) using apparent diffusion coefficient (ADC) maps and pathology report from magnetic resonance imaging (MRI)-targeted biopsy. We queried a retrospective monocentric database of patients with targeted biopsy. csPCa patients were defined as an International Society of Urological Pathology grade group ≥ 2. Group-level analyses and diagnostic accuracy of mean ADC values (ADCmean) within the tumor volume were assessed from Kruskal–Wallis tests and receiving operating characteristic curves, respectively. Areas under the curve (AUC) and optimal cut-off values were calculated. 159 patients (105 rsEPI, 54 ssEPI; mean age ± standard deviation: 65 ± 8 years) with 3T DWI, PZ lesions and targeted biopsy were selected. Both DWI sequences showed significantly lower ADCmean values for patients with csPCa. The rsEPI sequence better discriminates patients with csPCa (AUCrsEPI = 0.84, AUCssEPI = 0.68, p < 0.05) with an optimal cut-off value of 1232 μm2/s associated with a sensitivity–specificity of 97%-63%. Our study showed that the rsEPI DWI sequence enhances the discrimination of patients with csPCa.

Comparative study of stretched-exponential and kurtosis models of diffusion-weighted imaging in renal assessment to distinguish patients with primary aldosteronism from healthy controls.

To compare the ability of diffusion parameters obtained by stretched-exponential and kurtosis models of diffusion-weighted imaging (DWI) to distinguish between patients with primary aldosteronism (PA) and healthy controls (HCs) in renal assessment. A total of 44 participants (22 patients and 22 HCs) underwent renal MRI with an 11 b-value DWI sequence and a 3 b-value diffusion kurtosis imaging (DKI) sequence from June 2021 to April 2022. Binary logistic regression was used to construct regression models combining different diffusion parameters. Receiver-operating characteristic (ROC) curve analysis and comparisons were used to evaluate the ability of single diffusion parameters and combined diffusion models to distinguish between the two groups. A total of six diffusion parameters (including the cortical anomalous exponent term [α_Cortex], medullary fractional anisotropy [FA_Medulla], cortical FA [FA_Cortex], cortical axial diffusivity [Da_Cortex], medullary mean diffusivity [MD_Medulla] and medullary radial diffusivity [Dr_Medulla]) were included, and 10 regression models were studied. The area under the curve (AUC) of Dr_Medulla was 0.855, comparable to that of FA_Cortex and FA_Medulla and significantly higher than that of α_Cortex, Da_Cortex and MD_Medulla. The AUC of the Model_all parameters was 0.967, comparable to that of Model_FA (0.946) and Model_DKI (0.966) and significantly higher than that of the other models. The sensitivity and specificity of Model_all parameters were 87.2% and 95%, respectively. The Model_all parameters, Model_FA and Model_DKI were valid for differentiating between PA patients and HCs with similar differentiation efficacy and were superior to single diffusion parameters and other models.

Can the ADC Value Be Used as an Imaging “Biopsy” in Endometrial Cancer?

Background: The tumor histological grade is closely related to the prognosis of patients with endometrial cancer (EC). Multiparametric MRI, including diffusion-weighted imaging (DWI), provides information about the cellular density that may be useful to differentiate between benign and malignant uterine lesions. However, correlations between apparent diffusion coefficient (ADC) values and histopathological grading in endometrial cancer remain controversial. Material and methods: We retrospectively evaluated 92 patients with endometrial cancers, including both endometrioid adenocarcinomas (64) and non-endometrioid adenocarcinomas (28). All patients underwent DWI procedures, and mean ADC values were calculated in a region of interest. These values were then correlated with the tumor grading offered by the histopathological examination, which was considered the gold standard. In this way, the patients were divided into three groups (G1, G2, and G3). The ADC values were then compared to the results offered by the biopsy to see if the DWI sequence and ADC map could replace this procedure. We also compared the mean ADC values to the myometrial invasion (&lt;/&gt;50%) and lymphovascular space invasion. Results: We have divided the ADC values into three categories corresponding to three grades: &gt;0.850 × 10−3 mm2/s (ADC1), 0.730–0.849 × 10−3 mm2/s (ADC2) and &lt;0.730 × 10−3 mm2/s (ADC3). The diagnostic accuracy of the ADC value was 85.71% for ADC1, 75.76% for ADC2, and 91.66% for ADC3. In 77 cases out of 92, the category in which they were placed using the ADC value corresponded to the result offered by the histopathological exam with an accuracy of 83.69%. For only 56.52% of patients, the biopsy result included the grading system. For each grading category, the mean ADC value showed better results than the biopsy; for G1 patients, the mean ADC value had an accuracy of 85.71% compared to 66.66% in the biopsy, G2 had 75.76% compared to 68.42%, and G3 had 91.66 compared to 75%. For both deep myometrial invasion and lymphovascular space invasion, there is a close, inversely proportional correlation with the mean ADC value. Conclusions: Mean endometrial tumor ADC on MR-DWI is inversely related to the histological grade, deep myometrial invasion and lymphovascular space invasion. Using this method, the patients could be better divided into risk categories for personalized treatment.

Reproducibility of Diffusion MRI-Based Tractography in the Fetal Brain.

Tractography based on diffusion MRI (dMRI) is a useful tool to study white matter of the developing brain. However, its application in fetal brains is limited due to motion artifacts and low resolution of in utero dMRI, leading to reduced reliability, which was scarcely investigated in previous studies. To identify reliably traceable fibers in fetal brains and assess whether reproducibility varies with gestational age (GA) and varies between brain regions. Prospective cohort study. A total of 44 healthy fetuses with GAs between 25 and 37 (31 ± 6). 3-T, diffusion-weighted echo-planar imaging sequence (2-5 repeated dMRI scans within the same session per subject). We fitted dMRI with constrained spherical deconvolution model and conducted tractography on eight fibers. We extracted volume, fractional anisotropy, and fiber count for each fiber and assessed the reproducibility of these metrics between repeated scans within each subject. Data were divided into two age-based subgroups (≤30 weeks, N = 28, and >30 weeks, N = 16) for further tests. The reproducibility were compared between fibers by analysis of variance and two-sample t tests. Multiple comparisons were corrected by the false discovery rate (5% was accepted). The reproducibility of the anterior thalamic radiation, inferior longitudinal fasciculus (ILF), genu of the corpus callosum (GCC), and body of the corpus callosum (BCC) significantly decreased with advancing GA (correlation coefficient = 0.525-0.823), as confirmed by group comparisons between fetuses in early GA (≤30 weeks) and late GA (>30 weeks) groups. Corticospinal tract, inferior fronto-occipital fasciculus, and GCC showed high reproducibility for fiber count (weighted dice average = 0.846 vs. 0.814), while BCC and ILF exhibited the lowest reproducibility in both age groups. The study indicates that the reliability of fetal brain tractography depends on GA and varies among different fibers. 2 TECHNICAL EFFICACY: Stage 2.

Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas.

To prospectively evaluate the usefulness of T1-weighted imaging (T1WI) and diffusion-weighted imaging (DWI) sequences in predicting the consistency of macroadenomas. In addition, to determine their values ​​as prognostic factors of surgical outcomes. Patients with pituitary macroadenoma and surgical indication were included. All patients underwent pre-surgical magnetic resonance imaging (MRI) that included the sequences T1WI before and after contrast administration and DWI with the apparent diffusion coefficient (ADC) map. Post-surgical MRI was performed at least 3months after surgery. The consistency of the macroadenomas was evaluated at surgery, and they were grouped into soft and intermediate/hard adenomas. Mean ADC values, signal on T1WI and the ratio of tumor ADC values ​​to pons (ADCR) were compared with tumor consistency and grade of surgical resection. A total of 80 patients were included. A softened consistency was found at surgery in 53 patients and hardened in 27 patients. The median ADC in the soft consistency group was 0.532 × 10-3 mm2/sec (0.306-1.096 × 10-3 mm2/sec), and in the intermediate/hard consistency group was 0.509 × 10-3 mm2/sec (0.308-0.818 × 10-3 mm2/sec). There was no significant difference between the median values ​​of ADC, ADCR and signal on T1W between the soft and hard tumor groups, or between patients with and without tumor residue. Our results did not show usefulness of the DWI and T1WI for assessing the consistency of pituitary macroadenomas, nor as a predictor of the degree of surgical resection.

Non-contrast enhanced MRI for efficiency evaluation of high-intensity focused ultrasound in adenomyosis ablation

Objective To investigate the value of T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) in evaluating the therapeutic effect of high-intensity focused ultrasound (HIFU) in adenomyosis ablation. Material and methods One hundred eighty-nine patients with adenomyosis were treated with HIFU. The ablation areas on T2WI and DWI sequences were classified into different types: type I, relatively ill-defined rim or unrecognizable; subtype IIa, well-defined rim with hyperintensity; subtype IIb, well-defined rim with hypointensity. The volume of ablation areas on T2WI (VT2WI) and DWI (VDWI) was measured and compared with the non-perfused volume (NPV), and linear regression was conducted to analyze their correlation with NPV. Results The VT2WI of type I and type II (subtype IIa and subtype IIb) were statistically different from the corresponding NPV (p = 0.004 and 0.024, respectively), while no significant difference was found between the VDWI of type I and type II with NPV (p = 0.478 and 0.561, respectively). In the linear regression analysis, both VT2WI and VDWI were positively correlated with NPV, with R 2 reaching 0.96 and 0.97, respectively. Conclusions Both T2WI and DWI have the potential for efficient evaluation of HIFU treatment in adenomyosis, and DWI can be a replacement for CE-T1WI to some extent.

MRI Assessment of Cerebral White Matter Microvascular Hemodynamics Across the Adult Lifespan.

Changes in cerebral hemodynamics with aging are important for understanding age-related variation in neuronal health. While many prior studies have focused on gray matter, less is known regarding white matter due in part to measurement challenges related to the lower vascular density in white matter. To investigate the impact of age and sex on white matter hemodynamics in a Human Connectome Project in Aging (HCP-A) cohort using tract-based spatial statistics (TBSS). Retrospective cross-sectional. Six hundred seventy-eight typically aging individuals (381 female), aged 36-100 years. Multi-delay pseudo-continuous arterial spin labeling (ASL) and diffusion-weighted pulsed-gradient spin-echo echo planar imaging sequences at 3.0 T. A skeleton of mean fractional anisotropy (FA) was produced using TBSS. This skeleton was used to project ASL-derived cerebral blood flow (CBF) and arterial transit time (ATT) measures onto white matter tracts. General linear models were applied to white matter FA, CBF, and ATT maps, while covarying for age and sex. Threshold-free cluster enhancement multiple comparisons correction was performed for the effects of age and sex, thresholded at PFWE < 0.05. CBF, ATT, and FA were compared between sex for each tract using analysis of covariance, with multiple comparisons correction for the number of tracts at PFDR < 0.05. Significantly lower white matter CBF and significantly prolonged white matter ATTs were associated with older age. These effects were widespread across tracts for ATT. Significant (PFDR < 0.05) sex differences in ATT were observed across all tracts, and significant sex differences in CBF were observed in all tracts except the bilateral uncinate fasciculus. Females demonstrated significantly higher CBF compared to males across the lifespan. Few tracts demonstrated significant sex differences in FA. This study identified significant sex- and age-associated differences in white matter hemodynamics across tracts. 3 TECHNICAL EFFICACY: Stage 3.

Correlation of visual field deficits and q-ball high-resolution fiber tractography of the optic radiation for adjacently located intracerebral lesions: preliminary results from a single-center prospective study

Visual field deficits (VFDs) are common in patients with temporal and occipital lobe lesions. Diffusion tensor fiber tractography (DTI-FT) is widely used for surgery planning to reduce VFDs. Q-ball high-resolution fiber tractography (QBI-HRFT) improves upon DTI. This study aims to evaluate the effectiveness of DTI-FT and QBI-HRFT for surgery planning near the optic radiation (OR) as well as the correlation between VFDs, the nearest distance from the lesion to the OR fiber bundle (nD-LOR), and the lesion volume (LV). This ongoing prospective clinical trial collects clinical and imaging data of patients with lesions in deterrent areas. The present subanalysis included eight patients with gliomas near the OR. Probabilistic HRFT based on QBI-FT and conventional DTI-FT were performed for OR reconstruction based on a standard diffusion-weighted magnetic resonance imaging sequence in clinical use. Quantitative analysis was used to evaluate the lesion volume (LV) and nD-LOR. VFDs were determined based on standardized automated perimetry. We included eight patients (mean age 51.7 years [standard deviation (SD) 9.5]) with lesions near the OR. Among them, five, two, and one patients had temporodorsal, occipital, and temporal lesions, respectively. Four patients had normal vision preoperatively, while four patients had preexisting VFD. QBI-FT analysis indicated that patients with VFD exhibited a significantly smaller median nD-LOR (mean, −4.5; range −7.0; −2.3) than patients without VFD (mean, 7.4; range −4.3; 27.2) (p = 0.050). There was a trend towards a correlation between tumor volume and nD-LOR when QBI-FT was used (rs = −0.6; p = 0.056). A meticulous classification of the spatial relationship between the lesions and OR according to DTI-FT and QBI-FT was performed. The results indicated that the most prevalent orientations were the FT bundles located laterally and intrinsically in relation to the tumor. Compared with conventional DTI-FT, QBI-FT suggests reliable and more accurate results when correlated to preoperative VFDs and might be preferred for preoperative planning and intraoperative use of nearby lesions, particularly for those with larger volumes. A detailed analysis of localization, surgical approach together with QBI-FT and DTI-FT could reduce postoperative morbidity regarding VFDs. The display of HRFT techniques intraoperatively within the navigation system should be pursued for this issue.

A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer.

To establish a predictive model based on multisequence magnetic resonance imaging (MRI) using deep learning to identify wild-type (WT) epidermal growth factor receptor (EGFR), EGFR exon 19 deletion (19Del), and EGFR exon 21-point mutation (21L858R) simultaneously. A total of 399 patients with proven brain metastases of non-small cell lung cancer (NSCLC) were retrospectively enrolled and divided into training (n = 306) and testing (n = 93) cohorts separately based on two timepoints. All patients underwent 3.0-T brain MRI including T2-weighted, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and contrast-enhanced T1-weighted sequences. Radiomics features were extracted from each lesion based on four sequences. An algorithm combining radiomics approach with graph convolutional networks architecture (Radio-GCN) was designed for the prediction of EGFR mutation status and subtype. The area under the curve (AUC) at receiver operating characteristic analysis was used to evaluate the predication capabilities of each model. We extracted 1,290 radiomics features from each MRI sequence. The AUCs of the Radio-GCN model for identifying EGFR 19Del, 21L858R, and WT for the lesion-wise analysis were 0.996 ± 0.004, 0.971 ± 0.013, and 1.000 ± 0.000 on the independent testing cohort separately. It also yielded AUCs of 1.000 ± 0.000, 0.991 ± 0.009, and 1.000 ± 0.000for predicting EGFR mutations respectively for the patient-wise analysis. The κ coefficients were 0.735 and 0.812, respectively. The constructed Radio-GCN model is a new potential tool to predict the EGFR mutation status and subtype in NSCLC patients with brain metastases. The study demonstrated that a deep learning approach based on multisequence MRI can help to predict the EGFR mutation status in NSCLC patients with brain metastases, which is beneficial to guide a personalized treatment. • This is the first study to predict the EGFR mutation subtype simultaneously. • The Radio-GCN model holds the potential to be used as a diagnostic tool. • This study provides an imaging surrogate for identifying the EGFR mutation subtype.

The Spectrum of Magnetic Resonance Enterography Findings and the Role of Diffusion-Weighted Imaging in Patients with Active Crohn's Disease.

The goal of this study was to evaluate magnetic resonance enterography (MRE) findings and assess the role of diffusion-weighted imaging (DWI) in patients suffering from active Crohn's disease. This retrospective study included a total number of 76 patients diagnosed with active Crohn's disease, as established by the Crohn's Disease Activity Index (CDAI). The study consisted of 30 women and 46 men, ranging in age from 13 to 72 years. All participants underwent MRE with DWI sequences. The study was conducted at Imam Khomeini hospital in Tehran between 2013 and 2018. The imaging modality utilized for the study included a 3-T SIGNA Excite MRE machine and a Siemens Magnetom 3-T magnetic resonance imaging (MRI) machine. Bowel wall restriction was observed in less than half of the patients, and no significant correlation was found with extramural findings such as mesenteric edema. The study did not reveal any meaningful association between diffusion restriction and specific mural enhancement patterns, mesenteric lymphadenopathy with or without enhancement, or the length of the affected segments (P>0.05). The most common findings observed in MRI were ileum thickness in 72.4% of patients, mesenteric lymphadenopathy without enhancement in 46.1%, ileocecal thickness in 42.1%, DWI findings in 42.1%, the presence of a comb sign in 36.8%, and jejunum thickness in 30.3% of patients. MRE findings are useful in the evaluation of Crohn's disease activity.