Significant Difference In Apparent Diffusion Coefficient Research Articles

Analysis of the clinical diagnostic capabilities of kidney imaging biomarkers based on diffusion-weighted imaging and ASL-perfusion data

Acute kidney failure is a polyetiological disease that is often occurs in patients, which requires a rapid therapeutic response to avoid progression of the condition. Magnetic resonance imaging of the kidneys (MRI) improves the understanding and assessment of pathological processes, supplementing the mandatory diagnostic minimum information in the study of kidney pathology.Objective. To evaluate the clinical diagnostic capabilities of kidney imaging biomarkers using diffusion-weighted imaging (DWI) and ASL-perfusion data for intensive care unit patients.Materials and methods. At the first Clinical Hospital in Smolensk 54 patients were examined who were inpatient treatment and in the intensive care unit. All patients underwent ultrasound examination of the kidneys with assessment of blood flow in the main kidney vessels, MRI of the kidneys, with DWI of the kidney parenchyma and ASL-perfusion included in the study protocol. MRI was carried with assessed b-factor 800 and was drawn apparent diffusion coefficient (ADC) maps. When carried ASL perfusion, the field of view covered the area of the parenchyma of both kidneys. The reference method was glomerular filtration rate for all of the patients. The control group was represented by healthy people (n=59). Consent to participate in the study was obtained from patients or their legal representatives. All stages of the study comply with the normative and regulatory documentation of Ministry of Health ща the Russian Federation.Results. It was concluded that there is a significant difference in ADC for prerenal causes and in ASL for renal causes. In 9 (16.7 %) patients, kidney ADC was 1.5±0.3 mm2/sec, ASL – perfusion – ≤ 250 ml/100g/min, compared with the control group. In this group, negative dynamics were observed within a week, тnegative laboratory dynamics correlates with radiation-based kidney biomarkers (r=0,965).Conclusion. The criteria of DWI and ASL-perfusion allow us to suspect or confirm the cause of acute kidney failure. A high correlation has been established between radiation biomarkers and laboratory criteria of functional damages (r=0.998), direct correlation between imaging biomarkers and organic kidney disease (r=0,901). These biomarkers make it possible to predict the first stage of acute kidney failure (AUROC 0,995, DI 0,867–0,999).

Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS.

To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical cohort. Seventy participants with bladder cancer who underwent MRI between August 2022 and February 2023 with a protocol containing standard T2-weighted imaging (T2WIS), standard diffusion-weighted imaging (DWIS), fast T2WI with DLR (T2WIDL), and fast DWI with DLR (DWIDL) were enrolled in this prospective study. Imaging quality was evaluated by measuring signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and qualitative image quality scoring. Additionally, the apparent diffusion coefficient (ADC) of bladder lesions derived from DWIS and DWIDL was measured and VI-RADS scoring was performed. Paired t-test or paired Wilcoxon signed-rank test were performed to compare image quality score, SNR, CNR, and ADC between standard sequences and fast sequences with DLR. The diagnostic performance for VI-RADS was assessed using the areaunder the receiver operating characteristiccurve(AUC). Compared to T2WIS and DWIS, T2WIDL and DWIDL reduced the acquisition time from 5:57min to 3:13min and showed significantly higher SNR, CNR, qualitative image quality score of overall image quality, image sharpness, and lesion conspicuity. There were no significant differences in ADC and AUC of VI-RADS between standard sequences and fast sequences with DLR. The application of DLR to T2WI and DWI reduced examination time and significantly improved image quality, maintaining ADC and the diagnostic performance of VI-RADS for evaluating muscle invasion in bladder cancer.

Diffusion Weighted Magnetic Resonance Imaging of Spinal Cord Injuries After Instrumented Fusion Stabilization.

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising technique for assessing spinal cord injury (SCI) that has historically been challenged by the presence of metallic stabilization hardware. This study leverages recent advances in metal-artifact resistant multi-spectral DW-MRI to enable diffusion quantification throughout the spinal cord even after fusion stabilization. Twelve participants with cervical spinal cord injuries treated with fusion stabilization and 49 asymptomatic able-bodied control participants underwent multi-spectral DW-MRI evaluation. Apparent diffusion coefficient (ADC) values were calculated in axial cord sections. Statistical modeling assessed ADC differences across cohorts and within distinct cord regions of the SCI participants (at, above, or below injured level). Computed models accounted for subject demographics and injury characteristics. ADC was found to be elevated at injured levels compared with non-injured levels (z = 3.2, p = 0.001), with ADC at injured levels decreasing over time since injury (z = -9.2, p < 0.001). Below the injury level, ADC was reduced relative to controls (z = -4.4, p < 0.001), with greater reductions after more severe injuries that correlated with lower extremity motor scores (z = 2.56, p = 0.012). No statistically significant differences in ADC above the level of injury were identified. By enabling diffusion analysis near fusion hardware, the multi-spectral DW-MRI technique allowed intuitive quantification of cord diffusion changes after SCI both at and away from injured levels. This demonstrates the approach's potential for assessing post-surgical spinal cord integrity throughout stabilized regions.

Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies

PurposeThe purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI). MethodsForty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student’s t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student’s t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar’s test. ResultsDR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05). ConclusionRDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.

Quantification of cross-vendor variation in ADC measurements in vendor-specific prostate MRI-protocols

PurposeThe purpose of this study was to quantify the variability of Apparent Diffusion Coefficient (ADC) and test if there were statistically significant differences in ADC between MRI systems and sequences. MethodWith a two-chamber cylindrical ADC phantom with fixed ADC values (1,000 and 1,600x10−6 mm2/s) a single-shot (ss) Echo Planar Imaging (EPI), a multi-shot EPI, a reduced field of view DWI (zoom) and a Turbo Spin Echo DWI sequence were tested in six MRI systems from three vendors at 1.5 T and 3 T. Technical parameters were according to Prostate Imaging Reporting and Data System Version 2.1. ADC maps were calculated by vendor specific algorithms. Absolute and relative differences in ADC from the phantom-ADC were calculated and differences between sequences were tested. ResultsAt 3 T absolute differences from phantom given ADC (∼1,000 and ∼ 1,600x10−6 mm2/s) were −83 – 42x10−6 mm2/s (-8.3%-4.2%) and −48 – 15x10−6 mm2/s (-3%-0.9%), respectively and at 1.5 T absolute differences were −81 – 26x10−6 mm2/s (-2.6%-8.1%) and −74 – 67x10−6 mm2/s (-4.6%-4.2%), respectively.Significant statistical differences in ADC measurements were identified between vendors in all sequences except for ssEPI and zoom at 3 T in the 1,600x10−6 mm2/s phantom chamber. Significant differences were also identified between ADC measurements at 1.5 T and 3 T in some of the sequences and vendors, but not all. ConclusionThe variation of ADC between different MRI systems and prostate specific DWI sequences is limited in this phantom study and without apparent clinical relevance. However, prospective multicenter studies of prostate cancer patients are needed for further investigation.

Multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE) in diffusion-weighted imaging for rectal MRI: a quantitative and qualitative analysis at multiple b-values.

To compare four diffusion-weighted imaging (DWI) sequences for image quality, rectal contour, and lesion conspicuity, and to assess the difference in their signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC). In this retrospective study of 36 consecutive patients who underwent 3.0T rectal MRI from January-June 2020, DWI was performed with single-shot echo planar imaging (ss-EPI) (b800 s/mm2), multiplexed sensitivity encoding (MUSE) (b800 s/mm2), MUSE (b1500 s/mm2), and field-of-view optimized and constrained undistorted single-shot (FOCUS) (b1500 s/mm2). Two radiologists independently scored image quality using a 5-point Likert scale. Inter-reader agreement was assessed using the weighted Cohen's к. SNR, CNR, and ADC measurements were compared using the paired t-test. For both readers, MUSE b800 scored significantly higher for image quality, rectal contour, and lesion conspicuity compared to ss-EPI; MUSE b800 also scored significantly higher for image quality and rectal contour compared to all other sequences. Lesion conspicuity was equally superior for MUSE b800 and MUSE b1500 compared to the other two sequences. There was good to excellent inter-reader agreement for all qualitative features (к = 0.72-0.88). MUSE b800 had the highest SNR; MUSE b1500 had the highest CNR. A significant difference in ADC was observed between ss-EPI compared to the other sequences (p < 0.001) and between MUSE b800 and FOCUS. No significant difference in ADC was found between MUSE b1500 and FOCUS b1500. MUSE b800 improved image quality over ss-EPI and both MUSE b800 and b1500 showed better tumor conspicuity compared to conventional ss-EPI.

Multimodal Imaging Response after the Singular or Combination Treatments of Vascular Endothelial Growth Factor Inhibitor and Immune Checkpoint Inhibitor.

This study aims to dynamically assess tumor changes after variable treatments with vascular endothelial growth factor (VEGF) inhibitor and/or immune checkpoint inhibitor (ICI) using multimodal imaging of MRI and 18F-FDG PET/CT in a hepatocellular carcinoma (HCC) mice model. Based on different treatments, 24 mice were randomly divided into four groups: control (isotype-matched IgG antibody 10 mg/kg), VEGF inhibitor (sorafenib 50 mg/kg), ICI (anti-PD-L1 antibody 10 mg/kg), and combination groups (sorafenib 50 mg/kg + anti-PD-L1 antibody 10 mg/kg). Quantitative imaging assessments, including volume transfer constant (Ktrans), apparent diffusion coefficient (ADC), lactate/choline ratio, and the maximum standardized 18F-FDG uptake value ratio of tumor to muscle (SUVtumor/SUVmuscle ratio), were acquired at different time points (before treatment and 7, 14, and 21 days after treatment). Quantitative data were presented as the mean ± standard errors and two-way repeated-measure ANOVA tests were performed for intergroup and intertime point comparisons. After 21 days from the initiation of therapies, combination group showed the lowest tumor volume and weight, followed by ICI, VEGF inhibitor, and control group, with no significance between the VEGF inhibitor and control groups. In addition, Ktrans values significantly decreased, and the lactate/choline ratio and SUVtumor/SUVmuscle ratio were significantly elevated in the VEGF inhibitor group. ADC significantly increased in the ICI and combination groups, with no significant differences in ADC observed between the control and VEGF inhibitor groups, which showed a similar dynamic change to the tumor volume. Furthermore, Ktrans, lactate/choline ratio, and ADC were significantly correlated with CD31+ area, hypoxyprobe+ area, and apoptosis, respectively. Our results suggest that the singular treatment and combination of the VEGF inhibitor and ICI treatments for HCC present different multimodal imaging changes in accordance with the specific histopathological features. These findings might facilitate the formulation of better treatment response criteria; besides, we find ADC is probably an indicator easily to obtain for treatment response evaluation.

Magnetic resonance spectroscopy associations with clinicopathologic features of estrogen-dependent endometrial cancer

BackgroundWe studied the magnetic resonance spectroscopy (MRS) associations with clinicopathologic features of estrogen-dependent endometrial cancer (type I EC).MethodsTotally 45 patients with type I EC who underwent preoperative multi-voxel MRS at 3.0 T were enrolled. The mean ratio of the Cho peak integral to the unsuppressed water peak integral (Cho/water) of the tumor was calculated. The Cho/water and apparent diffusion coefficient (ADC) of type I EC with and without local invasion, as well as with different levels of Ki-67 staining index (SI) (≤ 40% and > 40%), were compared. Correlation test was used to examine the relationship of Cho/water, as well as mean ADC, with Ki-67 SI, tumor stage, and tumor grade.ResultsThe mean Cho/water of EC with Ki-67 SI ≤ 40% (2.28 ± 0.93) × 10−3 was lower than that with Ki-67 SI > 40% (4.08 ± 1.00) × 10−3 (P < 0.001). The mean Cho/water of EC with deep and superficial myometrial invasion was (3.41 ± 1.26) × 10−3 and (2.43 ± 1.11) × 10−3, respectively (P = 0.011). There was no significant difference in Cho/water between type I EC with and without cervical invasioin ([2.68 ± 1.00] × 10−3 and [2.77 ± 1.28] × 10−3, P = 0.866). The mean Cho/water of type I EC with and without lymph node metastasis was (4.02 ± 1.90) × 10−3 and (2.60 ± 1.06) × 10−3, respectively (P = 0.014). The Cho/water was positively correlated with the Ki-67 SI (r = 0.701, P < 0.001). There were no significant differences in ADC among groups (all P > 0.05).ConclusionMRS is helpful for preoperative assessment of clinicopathological features of type I EC.

The Utility of ADC First-Order Histogram Features for the Prediction of Metachronous Metastases in Rectal Cancer: A Preliminary Study.

Simple SummaryMetachronous metastases are the main factors affecting survival in rectal cancer, and 15–25% of patients will develop them at a 5-year follow-up. Early identification of patients with higher risk of developing distant metachronous metastases would help to improve therapeutic protocols and could allow for a more accurate, personalized management. Apparent diffusion coefficient (ADC) represents an MRI quantitative biomarker, which can assess the diffusion characteristics of tissues, depending on the microscopic mobility of water, showing information related to tissue cellularity. First-order histogram-based features statistics describe the frequency distribution of intensity values within a region of interest, revealing microstructural alterations. In our study, we demonstrated that whole-tumor ADC first-order features may provide useful information for the assessment of rectal cancer prognosis, regarding the occurrence of metachronous metastases.This study aims the ability of first-order histogram-based features, derived from ADC maps, to predict the occurrence of metachronous metastases (MM) in rectal cancer. A total of 52 patients with pathologically confirmed rectal adenocarcinoma were retrospectively enrolled and divided into two groups: patients who developed metachronous metastases (n = 15) and patients without metachronous metastases (n = 37). We extracted 17 first-order (FO) histogram-based features from the pretreatment ADC maps. Student’s t-test and Mann–Whitney U test were used for the association between each FO feature and presence of MM. Statistically significant features were combined into a model, using the binary regression logistic method. The receiver operating curve analysis was used to determine the diagnostic performance of the individual parameters and combined model. There were significant differences in ADC 90th percentile, interquartile range, entropy, uniformity, variance, mean absolute deviation, and robust mean absolute deviation in patients with MM, as compared to those without MM (p values between 0.002–0.01). The best diagnostic was achieved by the 90th percentile and uniformity, yielding an AUC of 0.74 [95% CI: 0.60–0.8]). The combined model reached an AUC of 0.8 [95% CI: 0.66–0.90]. Our observations point out that ADC first-order features may be useful for predicting metachronous metastases in rectal cancer.

Magnetic resonance imaging apparent diffusion coefficient in lymphomas and its dependence on a number of technical and clinical factors

The purpose of this study was to determine the value of apparent diffusion coefficient (ADC) in various morphological variants of lymphomas, to study dependence of ADC on the anatomical location of lesions and technical scanning parameters to establish the usefulness in differentiating normal and involved lymph nodes (LN).Whole body MRI with diffusion-weighted imaging (DWI) was performed in 209 patients with lymphoma before treatment. A target LN was selected and ADC determined in each patient.The ADC value does not depend on the use of the parallel imaging technique (p= 0.56), higher when using built-in compared to superficial coil (p&lt; 0.0001), higher when using respiratory triggering than free breathing (p&lt; 0.02). The highest ADC values (х10-3mm2/s) were obtained in the involved LN of the lung hilar (1.429 ± 0.396) and mediastinum (1.338 ± 0.313), lower values (p&lt; 0.01) - in the LN of the abdomen (1.011 ± 0.298), axillary (0.840 ± 0.196), neck (0.834 ± 0.259), inguinal (0.753 ± 0.128) and iliac (0.738 ± 0.129). Depending on the morphological variant of lymphoma, the highest ADC value was obtained in Hodgkin lymphoma - 1.168 ± 0.372 (p&lt; 0.0002). ADC in diffuse large B-cell non-Hodgkin lymphoma was 0.951 ± 0.320, indolent non-Hodgkin lymphomas - 0.756 ± 0.246, mantle zone non-Hodgkin lymphoma - 0.759 ± 0.211.In conclusion, DWI in lymphoma should be performed using surface coil, parallel imaging, and free breathing. Statistically significant differences in ADC were found depending on the anatomical location of the lesions and the morphological variant of lymphoma. Given the dependence of ADC on various technical and clinical factors, it is not possible to establish a single threshold value for differentiating involved and normal LN. The use of the LN size criterion for this purpose is the most optimal in lymphoma.

Native T1-mapping and diffusion-weighted imaging (DWI) can be used to identify lung cancer pathological types and their correlation with Ki-67 expression.

BackgroundThis study aimed to explore the value of native T1-mapping and diffusion-weighted imaging (DWI) in differentiating the pathological types and degree of tumor differentiation of lung cancer and their correlation with Ki-67 protein expression.MethodsA total of 78 consecutive lung cancer patients who received chest magnetic resonance imaging (MRI) scans between May 2020 and June 2021 were enrolled in this study. Two radiologists independently analyzed the apparent diffusion coefficient (ADC) and T1 values for each lesion. The intraclass correlation coefficient (ICC) and Bland-Altman plots were generated to assess interobserver agreement of the T1 and ADC mean values in lesions. The difference in ADC and T1 values among different pathological types, as well as between high- and low-differentiated lung cancers were analyzed, and diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve analysis. The correlation between ADC value, T1 value, and Ki-67 protein expression index was determined.ResultsThe ADC and T1 values showed excellent interobserver agreement (ICC 0.820, 0.942, respectively). There was a significant difference in ADC values between small cell carcinoma and squamous carcinoma (P<0.05), and between small cell carcinoma and adenocarcinoma (P<0.05), but not between squamous carcinoma and adenocarcinoma (P>0.05). A significant difference in T1 values was observed between small cell carcinoma (P<0.05) and adenocarcinoma, and between squamous carcinoma (P<0.05) and adenocarcinoma, but not between squamous carcinoma and small cell carcinoma (P>0.05). There were statistically significant differences in ADC and T1 values between the moderately and highly differentiated group and the poorly differentiated group (P<0.05). ROC curve analysis showed that the T1 combined with ADC value had high diagnostic value for the degree of differentiation of the tumor [area under the curve (AUC) =0.912]. Pearson correlation analysis showed a significant positive correlation between T1 value and Ki-67 index (r=0.66, P<0.001) and a significant negative correlation between ADC value and Ki-67 index (r=−0.45, P<0.01).ConclusionsT1 and ADC values can be used to distinguish the pathological type and differentiation degree of lung cancer.

MR diffusion and dynamic-contrast enhanced imaging to distinguish meningioma, paraganglioma, and schwannoma in the cerebellopontine angle and jugular foramen.

Differentiation ofmeningiomas, paragangliomas, and schwannomasin the cerebellopontine angle and jugular foramen remainschallengingwhen conventional MRI findings are inconclusive.This study aimed to assess the clinical utility of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) findings for tumor type differentiation and to identify the most significant diagnostic parameters. This retrospective study included 57 patients with pathologically confirmedmeningiomas, paragangliomas, and schwannomas, diagnosedbetweenJanuary 2018 and August 2021. DWI and DCE-MRI were obtained before surgery. The apparent diffusion coefficient (ADC)and DCE-MRI parameterswere calculated. The Kruskal-Wallis H test and post hoc test with Bonferroni correction and receiver operating characteristic curve were used for statistical analysis. There were 20 meningiomas (6 men; 62.3±17.8 years), 23 paragangliomas (3 men; 51.6±17.0 years), and 14 schwannomas (7 men; 37.7±20.0 years). Vp showed a significant difference in each comparison (p < .001, <.001, and <.001, respectively), Ve showed significant differences both in meningiomas and paragangliomas, and paragangliomas and schwannomas (p < .001 and .017, respectively), and Ktrans showed significant differences both in meningiomas and paragangliomas, and meningiomas and schwannomas (p = .0018 and <.001, respectively), though there was no significant difference in ADC. Vp diagnostic performance values for each pair of tumors were area under the curve of 0.89-1.00, with cutoff values of 0.14-0.27. DCE-MRI can provide promising parameters to differentiate meningiomas, paragangliomas, and schwannomas in the cerebellopontine angle and jugular foramen.

Meta-Analysis of Apparent Diffusion Coefficient in Pediatric Medulloblastoma, Ependymoma, and Pilocytic Astrocytoma.

Medulloblastoma, ependymoma, and pilocytic astrocytoma are common pediatric posterior fossa tumors. These tumors show overlapping characteristics on conventional MRI scans, making diagnosis difficult. To investigate whether apparent diffusion coefficient (ADC) values differ between tumor types and to identify optimum cut-off values to accurately classify the tumors using different performance metrics. Systematic review and meta-analysis. Seven studies reporting ADC in pediatric posterior fossa tumors (115 medulloblastoma, 68 ependymoma, and 86 pilocytic astrocytoma) were included following PubMed and ScienceDirect searches. Diffusion weighted imaging (DWI) was performed on 1.5 and 3T across multiple institution and vendors. The combined mean and standard deviation of ADC were calculated for each tumor type using a random-effects model, and the effect size was calculated using Hedge's g. Sensitivity/specificity, weighted classification accuracy, balanced classification accuracy. A P value < 0.05 was considered statistically significant, and a Hedge's g value of >1.2 was considered to represent a large difference. The mean (± standard deviation) ADCs of medulloblastoma, ependymoma, and pilocytic astrocytoma were 0.76 ± 0.16, 1.10 ± 0.10, and 1.49 ± 0.16 mm2 /sec× 10-3 . To maximize sensitivity and specificity using the mean ADC, the cut-off was found to be 0.96 mm2 /sec× 10-3 for medulloblastoma and ependymoma and 1.26 mm2 /sec× 10-3 for ependymoma and pilocytic astrocytoma. The meta-analysis showed significantly different ADC distributions for the three posterior fossa tumors. The cut-off values changed markedly (up to 7%) based on the performance metric used and the prevalence of the tumor types. There were significant differences in ADC between tumor types. However, it should be noted that only summary statistics from each study were analyzed and there were differences in how regions of interest were defined between studies. 1 TECHNICAL EFFICACY: Stage 3.

Quantitative evaluation of lumbar spine osteoporosis by apparent diffusion coefficient and signal intensity ratio of magnetic resonance diffusion-weighted magnetic resonance imaging

To investigate the application value of apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) of MR diffusion-weighted imaging (DWI) in quantitative evaluation of lumbar spine osteoporosis. A total of 175 patients with lumbar spine diseases who received dualenergy X-ray absorption (DXA) bone mineral density (BMD), routine MRI and DWI of the lumbar spine from May 2017 to October 2019 were selected. According to the T-value of DXA, the patients were divided into osteoporosis group (64 cases), osteopenia group (53 cases) and normal bone mass group (58 cases). The ADC and SIR values of L2-L4 were measured and compared among the three groups and the correlation between ADC, SIR and BMD was analyzed. The ROC curve was used to evaluate the differential diagnosis value of ADC and SIR for osteoporosis, osteopenia and normal bone mass. There were statistically significant differences in ADC and SIR values among three groups (F=41.386, 37.114, all P=0.000). The ADC value of the osteoporosis group was lower than that of the osteopenia group and the normal bone mass group, and the difference was statistically significant (t=3.540, 9.069, P=0.001, 0.000);the SIR value of the osteoporosis group was higher than that of the osteopenia group and the normal bone mass group, and the difference was statistically significant (t=5.083, 8.523, all P=0.000). Spearman correlation analysis showed that ADC value was positively correlated with BMD (r=0.313, P=0.004);SIR value was negatively correlated with BMD (r=- 0.589, P=0.000). Receiver operator characteristic (ROC) curve analysis showed that the area under curve (AUC), sensitivity andspecificity of ADC and SIR in the diagnosis of lumbar osteoporosis and osteopenia were 0.742, 89.1% , 52.8% and 0.729, 89.1%, 50.9% respectively (P=0.000);the AUC, sensitivity and specificity of ADC and SIR in the diagnosis of lumbar osteoporosis and normal bone mass were 0.815, 100.0%, 50.0% and 0.856, 65.6%, 93.1%, respectively (P=0.000);the AUC, sensitivity and specificity of ADC and SIR in the diagnosis of lumbar osteoporosis were 0.78, 89.1%, 51.4% and 0.795, 50.0% and 94.6% respectively (P=0.000);All have a certain diagnostic value. ADC and SIR can better reflect the BMD of patients with lumbar diseases, and can quantitatively evaluate the vertebral body of osteoporosis, which play an important role in the diagnosis of lumbar osteoporosis.

Diffusion Tensor Imaging Features of the Auditory Pathways in Patients With Vestibular Schwannoma After Gamma Knife Radiosurgery.

ObjectiveIn this study, we aimed to investigate whether there is any change in diffusion tensor imaging (DTI) parameters in ipsilateral and contralateral auditory pathways after Gamma Knife radiosurgery (GKR) in patients with vestibular schwannoma (VS) and the relationship between radiosurgery variables.MethodsSixty-six patients were evaluated with MRI and DTI before and after GKR. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were measured from the bilateral lateral lemniscus (LL), inferior colliculus (IC), medial geniculate body (MGB), and Heschl's gyrus (HG).ResultsThere was no significant difference in ADC and FA values obtained from bilateral LL, IC, and MGB before and after radiosurgery. However, there was a significant difference between pretreatment and post-radiosurgery contralateral HG ADC values. The ADC values obtained from the contralateral HG and IC positively correlated with the duration after radiosurgery. As the duration after radiosurgery increases, the difference between the ADC values obtained from ipsilateral and contralateral HG also increases.ConclusionThe high ADC values in the contralateral HG after radiosurgery may indicate microstructural alterations such as demyelination and axonal loss. Radiation exposure doses to the brainstem and cochlea are the most important factors that can cause microstructural damage to the auditory pathways. When planning radiosurgery, extreme care should be taken to prevent the harmful effects of radiation on the auditory pathways.

Improving the characterization of meningioma microstructure in proton therapy from conventional apparent diffusion coefficient measurements using Monte Carlo simulations of diffusion MRI.

Proton therapy could benefit from noninvasively gaining tumor microstructure information, at both planning and monitoring stages. The anatomical location of brain tumors, such as meningiomas, often hinders the recovery of such information from histopathology, and conventional noninvasive imaging biomarkers, like the apparent diffusion coefficient (ADC) from diffusion-weighted MRI (DW-MRI), are nonspecific. The aim of this study was to retrieve discriminative microstructural markers from conventional ADC for meningiomas treated with proton therapy. These markers were employed for tumor grading and tumor response assessment. DW-MRIs from patients affected by meningioma and enrolled in proton therapy were collected before (n=35) and 3 months after (n=25) treatment. For the latter group, the risk of an adverse outcome was inferred by their clinical history. Using Monte Carlo methods, DW-MRI signals were simulated from packings of synthetic cells built with well-defined geometrical and diffusion properties. Patients' ADC was modeled as a weighted sum of selected simulated signals. The weights that best described a patient's ADC were determined through an optimization procedure and used to estimate a set of markers of tumor microstructure: diffusion coefficient (D), volume fraction (vf), and radius (R). Apparent cellularity (ρapp ) was estimated from vf and R for an easier clinical interpretability. Differences between meningothelial and atypical subtypes, and low- and high-grade meningiomas were assessed with nonparametric statistical tests, whereas sensitivity and specificity with ROC analyses. Similar analyses were performed for patients showing low or high risk of an adverse outcome to preliminary evaluate response to treatment. Significant (P<0.05) differences in median ADC, D, vf, R, and ρapp values were found when comparing meningiomas' subtypes and grades. ROC analyses showed that estimated microstructural parameters reached higher specificity than ADC for subtyping (0.93 for D and vf vs 0.80 for ADC) and grading (0.75 for R vs 0.67 for ADC). High- and low-risk patients showed significant differences in ADC and microstructural parameters. The skewness of ρapp was the parameter with highest AUC (0.90) and sensitivity (0.75). Matching measured with simulated ADC yielded a set of potential imaging markers for meningiomas grading and response monitoring in proton therapy, showing higher specificity than conventional ADC. These markers can provide discriminative information about spatial patterns of tumor microstructure implying important advantages for patient-specific proton therapy workflows.

Differentiating malignant from benign salivary gland lesions: a multiparametric non-contrast MR imaging approach

The purpose of this study is to determine whether multiparametric non-contrast MR imaging including diffusion-weighted imaging (DWI), arterial spin labeling (ASL), and amide proton transfer (APT) weighted imaging can help differentiate malignant from benign salivary gland lesions. The study population consisted of 42 patients, with 31 benign and 11 malignant salivary gland lesions. All patients were evaluated using DWI, three-dimensional pseudo-continuous ASL, and APT-weighted imaging on 3 T MR imaging before treatment. Apparent diffusion coefficient (ADC), tumor blood flow (TBF), and APT-related signal intensity (APTSI) values within the lesion were compared between the malignant and benign lesions by Mann–Whitney U test. For each parameter, optimal cutoff values were chosen using a threshold criterion that maximized the Youden index for predicting malignant lesions. The performance of ADC, TBF, APTSI, individually and combined, was evaluated in terms of diagnostic ability for malignant lesions. Diagnostic performance was compared by McNemar test. APTSI was significantly higher in malignant lesions (2.18 ± 0.89%) than in benign lesions (1.57 ± 1.09%, p = 0.047). There was no significant difference in ADC or TBF between benign and malignant lesions (p = 0.155 and 0.498, respectively). The accuracy of ADC, TBF, and APTSI for diagnosing malignant lesions was 47.6%, 50.0%, and 66.7%, respectively; whereas the accuracy of the three parameters combined was 85.7%, which was significantly higher than that of each parameter alone (p = 0.001, 0.001, and 0.008, respectively). Therefore, the combination of ADC, TBF, and APTSI can help differentiate malignant from benign salivary gland lesions.

Disparate volumetric fluid shifts across cerebral tissue compartments with two different anesthetics

BackgroundLarge differences in glymphatic system transport—similar in magnitude to those of the sleep/wake cycle—have been observed during anesthesia with dexmedetomidine supplemented with low dose isoflurane (DEXM-I) in comparison to isoflurane (ISO). However, the biophysical and bioenergetic tissue status underlying glymphatic transport differences between anesthetics remains undefined. To further understand biophysical characteristics underlying these differences we investigated volume status across cerebral tissue compartments, water diffusivity, and T2* values in rats anesthetized with DEXM-I in comparison to ISO.MethodsUsing a crossover study design, a group of 12 Sprague Dawley female rats underwent repetitive magnetic resonance imaging (MRI) under ISO and DEXM-I. Physiological parameters were continuously measured. MRI included a proton density weighted (PDW) scan to investigate cerebrospinal fluid (CSF) and parenchymal volumetric changes, a multigradient echo scan (MGE) to calculate T2* maps as a measure of ‘bioenergetics’, and a diffusion scan to quantify the apparent diffusion coefficient (ADC).ResultsThe heart rate was lower with DEXM-I in comparison to ISO, but all other physiological variables were similar across scans and groups. The PDW images revealed a 1% parenchymal volume increase with ISO compared to DEXM-I comprising multiple focal tissue areas scattered across the forebrain. In contrast, with DEXM-I the CSF compartment was enlarged by ~ 6% in comparison to ISO at the level of the basal cisterns and peri-arterial conduits which are main CSF influx routes for glymphatic transport. The T2* maps showed brain-wide increases in T2* in ISO compared to DEXM-I rats. Diffusion-weighted images yielded no significant differences in ADCs across the two anesthesia groups.ConclusionsWe demonstrated CSF volume expansion with DEXM-I (in comparison to ISO) and parenchymal (GM) expansion with ISO (in comparison to DEXM-I), which may explain the differences in glymphatic transport. The T2* changes in ISO are suggestive of an increased bioenergetic state associated with excess cellular firing/bursting when compared to DEXM-I.

Evaluation of the relationship between corpus callosum and internal capsule and tuber load in patients with tuberous sclerosis complex by diffusion tensor imaging

Aim: To determine whether there are Diffusion Tensor Imaging (DTI) changes in the white matter pathways such as corpus callosum and internal capsule in patients with Tuberous sclerosis complex (TSC) and to investigate its relationship with tuber load. Materials and Methods: Our study included 17 children with TSC and 15 healthy controls. Total tuber load of the brain was calculated. Correlation between tuber load and ADC (Apparent diffusion coefficient) and FA (Fractional anisotropy) values at corpus callosum (CC) and internal capsule were investigated.Results: When patients with TSC were compared with control, there was a significant difference in ADC and FA values in the corpus callosum and internal capsule. There was a significant difference in FA values between the anterior and posterior limbs of the internal capsule on both sides. The ADC values of CC splenium were positively correlated with the total cerebral tuber load. Also, The FA values obtained from CC splenium were negatively correlated with the tuber load of the right cerebral hemisphere. Conclusion: Relationships between corpus callosum and internal capsule ADC and FA changes and tuber load show that microstructural damage develops in the white matter pathways. DTI parameters can be used as a more sensitive biomarker in the evaluation of the abnormal structure of white matter in patients with TSC. More comprehensive studies are needed to more clearly demonstrate the relationship between DTI properties of white matter and tuber load in TSC patients.

The value of bi-exponential and non-Gaussian distribution diffusion-weighted imaging in the differentiation of recurrent soft tissue neoplasms and post-surgical changes.

BackgroundMany researches focused on the quantitative mono-exponential diffusion-weighted imaging (DWI) in the assessment of soft tissue neoplasms (STN), but few focused on the value of bi-exponential and non-Gaussian DWI in the application of Recurrent Soft Tissue Neoplasms (RSTN). This study aimed to explore the feasibility of bi-exponential decay and non-Gaussian distribution DWI in the differentiation of RSTN and Post-Surgery Changes (PSC), and compared with mono-exponential DWI.MethodsThe clinical, mono-exponential, bi-exponential [intravoxel incoherent motion (IVIM)] and non-Gaussian [diffusion kurtosis imaging (DKI)] DWI imaging of a cohort of 27 patients [15 RSTN (22 masses), and 12 PSC (12 lesions)] with 34 masses, from Nov 01 2017 to Sep 30 2018, were reviewed. The differences of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK) values were compared between RSTN and PSC groups. The mono-, bi-exponential, and non-Gaussian distribution based predictive models for RSTN and PSC were built and compared. ROC curves were generated and compared by the DeLong test.ResultsIntra-class correlation coefficient (ICC) of all IVIM/DKI parameters was high (≥0.841). There were significant differences in ADC, D, f, MD, and MK values between RSTN and PSC, but no difference in D* value. The ADC_IVIM, D, f and MD values of RSTN were lower than those of PSC, but with higher MK value. The ADC_IVIM and D values did better than f value in differentiating these two groups (P<0.05). While there was no significant difference in AUCs among ADC_DKI, MD, and MK values. Also, no significant difference was detected in AUCs between bi-exponential and mono-exponential (P=0.38), or between mono-exponential and non-Gaussian distribution based prediction models (P=0.09).ConclusionsADC, D, f, MD, and MK values can be used in the differentiation of RSTN and PSC.