Opposed-phase Research Articles

Quantitative biomarkers for distinguishing bone metastasis and benign bone marrow lesions using turbo spin echo T1- and T2-weighted Dixon imaging at 3.0 T

ObjectiveTo assess the diagnostic performance and calculate the optimal threshold for quantitative biomarkers to differentiate bone metastasis and benign bone marrow lesions using turbo spin echo (TSE) Dixon images with a 3.0 T scanner. Materials and methodsEach 100 patients diagnosed with bone metastases and variable benign bone marrow lesions on spine MRI were included retrospectively. Images included in-phase (IP), opposed-phase (OP), water images (WI), and fat images (FI) by the TSE Dixon technique with T1WI and T2WI using a 3.0 T scanner. Regions of interest (ROI) of the lesions were manually drawn by two musculoskeletal radiologists independently, and the average signal intensity was recorded. The signal reduction rate from IP to OP (%drop) and a fat fraction (%fat) were calculated. ResultsAll biomarkers showed a significant difference between metastatic and benign lesions (P < 0.001). When comparing the AUCs, the %drop of T1WI had the highest AUC (0.934). Although the AUC of %fat from T2WI was significantly lower than that of other biomarkers, the %drop of T2WI was not significantly different from the %drop of T1WI (p = 0.339). The optimal threshold of %drop to differentiate metastatic and benign lesions was 22.0 in T1WI and 15.9 in T2WI. The inter-reader agreement was excellent for all biomarkers (0.82–0.86). ConclusionWhile %drop of T1WI showed the highest diagnostic performance to differentiate bone metastasis from benign lesions, the %drop of T2WI showed a comparable ability using a threshold 15.9.

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network

We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comprised 100 participants with renal dysfunction (RD; eGFR < 45 mL/min/1.73 m2) and 70 without (non-RD; eGFR ≥ 45 mL/min/1.73 m2). The model was applied to the right, left, and both kidneys; it was first evaluated on the non-RD group data and subsequently on the combined data of the RD and non-RD groups. For bilateral kidney segmentation of the non-RD group, the best performance was obtained when using IP image, with a Dice score of 0.902 ± 0.034, average surface distance of 1.46 ± 0.75 mm, and a difference of − 27 ± 21 mL between ground-truth and automatically computed volume. Slightly worse results were obtained for the combined data of the RD and non-RD groups and for unilateral kidney segmentation, particularly when segmenting the right kidney from the OP images. Our 3D CNN-assisted automatic segmentation tools can be utilized in future studies on total kidney volume measurements and various image analyses of a large number of patients with CKD.

Impact of fat on the apparent T1 value of the liver: assessment by water-only derived T1 mapping.

To determine the impact of fat on the apparent T1 value of the liver using water-only derived T1 mapping. 3-T MRI included 2D Look-Locker T1 mapping and proton density fat fraction (PDFF) mapping. T1 values of the liver were compared among T1 maps obtained by in-phase (IP), opposed-phase (OP), and Dixon water sequences using paired t-test. The correlation between T1 values of the liver on each T1 map and PDFF was assessed using Spearman correlation coefficient. The absolute differences between T1 value of the liver on Dixon water images and that on IP or OP images were also correlated with PDFF. One hundred sixty-two patients (median age, 70 [range, 24-91] years, 90 men) were retrospectively evaluated. The T1 values of the liver on each T1 map were significantly different (p < 0.001). The T1 value of the liver on IP images was significantly negatively correlated with PDFF (r = - 0.438), while the T1 value of the liver on OP images was slightly positively correlated with PDFF (r = 0.164). The T1 value of the liver on Dixon water images was slightly negatively correlated with PDFF (r = - 0.171). The absolute differences between T1 value of the liver on Dixon water images and that on IP or OP images were significantly correlated with PDFF (r = 0.606, 0.722; p < 0.001). Fat correction for the apparent T1 value by water-only derived T1 maps will be helpful for accurately evaluating the T1 value of the liver. Fat-corrected T1 mapping of the liver with the water component only obtained from the 2D Dixon Look-Locker sequence could be useful for accurately evaluating the T1 value of the liver without the impact of fat in daily clinical practice. • The T1 values of the liver on the conventional T1 maps are significantly affected by the presence of fat. • The apparent T1 value of the liver on water-only derived T1 maps would be slightly impacted by the presence of fat. • Fat correction for the apparent T1 values is necessary for the accurate assessment of the T1 values of the liver.

A radiomic signature based on magnetic resonance imaging to determine adrenal Cushing's syndrome.

The aim of this study was to develop radiomics signature-based magnetic resonance imaging (MRI) to determine adrenal Cushing's syndrome (ACS) in adrenal incidentalomas (AI). A total of 50 patients with AI were included in this study. The patients were grouped as nonfunctional adrenal incidentaloma (NFAI) and ACS. The lesions were segmented on unenhanced T1-weighted (T1W) in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3-Tesla MRIs. The LASSO regression model was used for the selection of potential predictors from 111 texture features for each sequence. The radiomics scores were compared between the groups. The median radiomics score in T1W-Op for the NFAI and ACS were -1.17 and -0.17, respectively (p < 0.001). Patients with ACS had significantly higher radiomics scores than NFAI patients in all phases (p < 0.001 for all). The AUCs for radiomics scores in T1W-Op, T1W-Ip, and T2W were 0.862 (95% CI: 0.742-0.983), 0.892 (95% CI: 0.774-0.999), and 0.994 (95% CI: 0.982-0.999), respectively. The developed MRI-based radiomic scores can yield high AUCs for prediction of ACS.

The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model

We evaluated a multiclass classification model to predict estimated glomerular filtration rate (eGFR) groups in chronic kidney disease (CKD) patients using magnetic resonance imaging (MRI) texture analysis (TA). We identified 166 CKD patients who underwent MRI comprising Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images, apparent diffusion coefficient (ADC) maps, and T2* maps. The patients were divided into severe, moderate, and control groups based on eGFR borderlines of 30 and 60 mL/min/1.73 m2. After extracting 93 texture features (TFs), dimension reduction was performed using inter-observer reproducibility analysis and sequential feature selection (SFS) algorithm. Models were created using linear discriminant analysis (LDA); support vector machine (SVM) with linear, rbf, and sigmoid kernels; decision tree (DT); and random forest (RF) classifiers, with synthetic minority oversampling technique (SMOTE). Models underwent 100-time repeat nested cross-validation. Overall performances of our classification models were modest, and TA based on T1-weighted IP/OP/WO images provided better performance than those based on ADC and T2* maps. The most favorable result was observed in the T1-weighted WO image using RF classifier and the combination model was derived from all T1-weighted images using SVM classifier with rbf kernel. Among the selected TFs, total energy and energy had weak correlations with eGFR.

Diagnostic Accuracy of Standalone T2 Dixon Sequence Compared with Conventional MRI in Sacroiliitis.

Aim The aim of this article was to assess the profile of T2-weighted (T2W) multipoint Dixon sequence and conventional sequences in magnetic resonance imaging (MRI) of sacroiliac joints for the diagnosis of active and chronic sacroiliitis. Settings and Design Prospective observational study. Materials and Methods Thirty-seven patients with sacroiliitis underwent MRI with conventional coronal oblique short tau inversion recovery, T1W sequences, and T2W multipoint Dixon sequences. T1 fat-saturated postcontrast sequences were added in active cases. Comparisons were made between conventional and T2 Dixon sequences both quantitatively and qualitatively. Statistical Analysis Paired t -test was used to study the difference in contrast–noise ratio (CNR) between two groups. Chi-squared analysis with p -value of ≤ 0.05 was used to test the significant association of different sequences. Results Water only images had highest mean CNR (296.35 ± 208.28) for the detection of bone marrow edema/osteitis. T1W (186.09 ± 96.96) and opposed-phase (OP) images (279.22 ± 188.40) had highest mean CNR for the detection of subchondral sclerosis and periarticular fat deposition, respectively. OP images ( p -value <0.001) followed by fat-only (FO) images ( p -value = 0.001) were superior to T1W sequences in detecting periarticular fat deposition. In-phase (IP) images in detecting subchondral sclerosis and IP and FO images in detecting cortical erosions were comparable to conventional T1W sequences ( p -value < 0.001). Conclusions T2 Dixon sequences are superior or comparable to conventional MR sequences in detection of sacroiliitis, except ankylosis. Hence, Dixon can be used as a single sequence to replace the multiple sequences used in conventional imaging protocol of acute sacroiliac joints due to higher image quality. It can be used as an additional sequence in case of chronic sacroiliitis to increase the confidence and accuracy of diagnosis.

Dixon chemical shift MR sequences for demonstrating of bone marrow vertebral metastasis

BackgroundThis study aimed to investigate the diagnostic performance and clinical utility of different MR Dixon sequences in the characterization of vertebral metastasis in a patient with a history of malignant neoplasm and compare the results with 18-F FDG PET CT. Patients were subjected to MR imaging of the dorsal and lumbosacral spine (1.5 T MR machine) using conventional MR, T2 Dixon and T1 post-contrast Dixon.ResultsThis study involved 40 patients (45% female and 55% male) with 161 metastatic lesions and median age 61.5 years. The sensitivities of T1 post-contrast water-only (WO), fat-only (FO) and opposed-phase (OP) Dixon for diagnosis of vertebral metastasis were 92.6%, 89.4% and 83.1%, respectively, while the sensitivity of T2 (WO, OP) Dixon was 78.3% with 100% specificity for both T1 and T2 Dixon. There were excellent positive clinical utilities of T1 post-contrast WO (0.925), FO (0.894) and OP (0.826) Dixon with the good positive clinical utility of T2 Dixon (0.783) for lesion finding. There were fair negative clinical utilities of T1 WO (0.636) and FO (0.553) Dixon with poor negative clinical utilities of T1 OP (0.429), T2 WO and OP (0.375) Dixon for lesion screening. 15% was the best in-phase/opposed-phase ratio for differentiation between metastatic and benign vertebral lesions.ConclusionsMR Dixon techniques are sensitive and specific for the diagnosis of vertebral metastasis. T1 post-contrast and T2 Dixons have excellent and good positive clinical utilities for lesion finding with fair and poor negative clinical utilities for lesion screening, respectively.

A machine learning approach to distinguishing between non-functioning and autonomous cortisol secreting adrenal incidentaloma on magnetic resonance imaging using texture analysis.

To investigate the possibility of distinguishing between nonfunctioning adrenal incidentalomas (NFAI) and autonomous cortisol secreting adrenal incidentalomas (ACSAI) with a model created with magnetic resonance imaging (MRI)-based radiomics and clinical features. In this study, 100 adrenal lesions were evaluated. The lesions were segmented on unenhanced T1-weighted in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3Tesla MRIs. The LASSO regression model was used to select potential predictors from 108 texture features for each sequence. Subsequently, a combined radiomics score and clinical features were created and compared. A significant difference was found between median rad-scores for ACSAI and NFAI in training and test sets (p < 0.05 for all sequences). Multivariate logistic regression analysis revealed that the length of the tumor (OR = 1.09, p = 0.007) was an independent risk factor related to ACSAI. Multivariate logistic regression analysis was used for building clinical-radiomics (combined) models. The Op, IP, and IP plus T2-W model had a higher performance with area under curve (AUC) 0.758, 0.746, and 0.721 on the test dataset, respectively. ACSAI can be distinguished from NFAI with high accuracy on unenhanced MRI. Radiomics analysis and the model constructed by machine learning algorithms seem superior to another radiologic assessment method. The inclusion of chemical shift MRI and the length of the tumor in the radiomics model could increase the power of the test.

Automated Measurement of Pancreatic Fat Deposition on Dixon MRI Using nnU-Net.

Pancreatic fat accumulation may cause or aggravate the process of acute pancreatitis, β-cell dysfunction, T2DM disease, and even be associated with pancreatic tumors. The pathophysiology of fatty pancreas remains overlooked and lacks effective imaging diagnostics. To automatically measure the distribution of pancreatic fat deposition on Dixon MRI in multicenter/population datasets using nnU-Net models. Retrospective. A total of 176 obese/nonobese subjects (90 males, 86 females; mean age, 27.2 ± 19.7) were enrolled, including a training set (N=132) and a testing set (N=44). A 3 T and 1.5T/gradient echo T1 dual-echo Dixon. The segmentation results of four types of nnU-Net models were compared using dice similarity coefficient (DSC), positive predicted value (PPV), and sensitivity. The ground truth was the manual delineation by two radiologists according to in-phase (IP) and opposed-phase (OP) images. The group difference of segmentation results of four models were assessed by the Kruskal-Wallis H test with Dunn-Bonferroni comparisons. The interobserver agreement of pancreatic fat fraction measurements across three observers and test-retest reliability of human and machine were assessed by intragroup correlation coefficient (ICC). P < 0.05 was considered statistically significant. The three-dimensional (3D) dual-contrast model had significantly improved performance than 2D dual-contrast (DSC/sensitivity) and 3D one-contrast (IP) models (DSC/PPV/sensitivity) and had less errors than 3D one-contrast (OP) model according to higher DSC and PPV (not significant), with a mean DSC of 0.9158, PPV of 0.9105 and sensitivity of 0.9232 in the testing set. The test-retest ICC of this model was above 0.900 in all pancreatic regions, exceeded human. 3D Dual-contrast nnU-Net aided segmentation of pancreas on Dixon images appears to be adaptable to multicenter/population datasets. It fully automates the assessment of pancreatic fat distribution and has high reliability. 3 TECHNICAL EFFICACY: Stage 3.

Comparison of in-phase and opposed-phase T1W gradient echo and T2W fast spin echo dixon chemical shift imaging for the assessment of non-neoplastic, benign neoplastic and malignant marrow lesions.

The objective of this study is to compare T1-weighted gradient echo (T1W GrE: control technique) chemical shift imaging (CSI) with T2-weighted fast spin echo (T2W FSE: experimental technique) CSI for differentiating non-neoplastic and neoplastic marrow lesions. Patients undergoing MRI for various marrow lesions were investigated with T1W GrE and T2W FSE Dixon CSI. Signal intensity (SI) change between in-phase (IP) and opposed-phase (OP) sequences was calculated, and SI drop > 20% considered to represent non-neoplastic lesions while SI drop < 20% considered to represent neoplastic lesions. Final diagnosis was based on imaging features (n = 42) or histology (n = 43) and classified as non-neoplastic, benign neoplastic, and malignant neoplastic. Inter-observer and inter-technique agreement between 2 readers was calculated. The study included 85 patients (44 males and 41 females; mean age 41.1years, range 2-83years). Final diagnosis included 19 (22.4%) non-neoplastic lesions, 27 (31.8%) benign neoplasms, and 39 (45.9%) malignant neoplasms. On T1W GrE CSI, 19-21 lesions were classed as non-neoplastic and 64-66 as neoplastic, while on T2W FSE Dixon CSI, 22-24 lesions were classed as non-neoplastic and 61-64 as neoplastic. Lesion classification matched between the 2 techniques in 91.8-96.5% of cases. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of T1W GrE CSI for differentiating non-neoplastic and neoplastic marrow lesions were 66.7-72.2%, 88.1-89.6%, 61.9-63.2%, 90.9-92.2%, and 84.7%, and of T2W FSE Dixon CSI were 72.2-77.8%, 85.1-86.6%, 58.3-59.1%, 92.1-93.4%, and 83.5%. T1W GrE CSI and T2W FSE Dixon CSI produce similar results in the assessment of non-neoplastic and neoplastic marrow lesions.

Dixon-based thorax synthetic CT generation using Generative Adversarial Network

PurposeGeneration of synthetic Computed Tomography (sCT) images from Magnetic Resonance (MR) is an imperative, yet not fully resolved task for attenuation correction in Positron Emission Tomography (PET)/MR and treatment planning in MR-only radiation therapy. Herein, we propose a Generative Adversarial Networks (GAN) model to generate quantitatively accurate sCT from Dixon thorax MR data. Materials/methodsPaired image sets of Dixon MR and corresponding CT volumes from fourteen subjects were used. In-phase (IP) MR images were registered to the CT images using REGGUI. The resulting deformation field was applied to the three other [opposed-phase (OP), fat, water] MR images. Image processing was implemented in MATLAB 2016b (MathWorks) using COMKAT Image Tool. Manual contouring was performed on the CT images using MIM (version 6.6.10, MIM Software Inc., Cleveland, OH) software, to delineate the left lung, right lung, vertebral body, and spinal cord. The proposed RU-cGAN model incorporates ResNet and U-Net in the generator of a conditional GAN. Results from Vgg16, Vgg19, and ResNet were used as references for comparison. The four networks were trained using two strategies. In the first, the four Dixon MR images were used as input features. In the second strategy, only fat and water images were used. ResultsRegardless of whether the input consists of two or four images types, sCT generated using RU- cGAN had the best agreement with the measured CT for all the metrics, having Mean Absolute Prediction Error (MAPE) ​< ​80 Hounsfield Units and generated in 2.1–2.85 ​s. At the level of the lungs, MAPE and Root Mean Squared Error using four inputs yielded statistically better results when compared to 2 inputs. ConclusionRU-cGAN provides a rapid and accurate method for thorax sCT generation while obviating the bone-specific UTE pulse sequence and only requiring limited training data.

A Novel Radial Basis Neural Network-Leveraged Fast Training Method for Identifying Organs in MR Images.

We propose a new method for fast organ classification and segmentation of abdominal magnetic resonance (MR) images. Magnetic resonance imaging (MRI) is a new type of high-tech imaging examination fashion in recent years. Recognition of specific target areas (organs) based on MR images is one of the key issues in computer-aided diagnosis of medical images. Artificial neural network technology has made significant progress in image processing based on the multimodal MR attributes of each pixel in MR images. However, with the generation of large-scale data, there are few studies on the rapid processing of large-scale MRI data. To address this deficiency, we present a fast radial basis function artificial neural network (Fast-RBF) algorithm. The importance of our efforts is as follows: (1) The proposed algorithm achieves fast processing of large-scale image data by introducing the ε-insensitive loss function, the structural risk term, and the core-set principle. We apply this algorithm to the identification of specific target areas in MR images. (2) For each abdominal MRI case, we use four MR sequences (fat, water, in-phase (IP), and opposed-phase (OP)) and the position coordinates (x, y) of each pixel as the input of the algorithm. We use three classifiers to identify the liver and kidneys in the MR images. Experiments show that the proposed method achieves a higher precision in the recognition of specific regions of medical images and has better adaptability in the case of large-scale datasets than the traditional RBF algorithm.

Chemical shift imaging with in-phase and opposed-phase sequences at 3T: what is the optimal threshold, measurement method, and diagnostic accuracy for characterizing marrow signal abnormalities?

To determine the threshold signal drop on 3-T chemical shift imaging (CSI), with in-phase (IP) and opposed-phase (OP) sequences, for accurately identifying bone marrow replacement with 100% sensitivity, and determine a clinically useful measurement method for deriving such a threshold. From a convenience series of 157 MRIs, 36 cases with histologically proven marrow-replacing lesions and 22 sites of red marrow (histologically proven (2) or with minimum 6-month stability) with 3-Tesla CSI were included. Two musculoskeletal radiologists performed two measurement methods (first: multiple algorithmic ROIs at the top, middle, and bottom of lesions (M-ROI); second: an ROI was drawn where there appeared to be the least opposed-phase signal reduction qualitatively/visually (Q-ROI)). Lesional and red marrow signal change (%,[(IP-OP)signal/IP signal]*100) was determined. Statistical analyses included Student's t test, Cohen's kappa, and receiver operator characteristic curve generation. By M-ROI, lesion signal change was -0.508% (confidence interval (CI) = -5.537:4.521) and 1.348% (CI = -3.541:6.311) for readers 1 and 2. By Q-ROI, lesion signal change was -11.03% (CI = -17.01:- 5.046) and - 5.657% (CI = -12.36:1.048) for readers 1 and 2. For all M-ROI and Q-ROI measurement strategies, signal change between lesional tissue and red marrow was significantly different (p < 0.0001). QROI produced the best composite sensitivities and specificities with a maximized Youden index of 0.955-1. A threshold signal drop of 25% with Q-ROI produced at least 100%/86% sensitivity/specificity for both readers for identifying marrow replacement. For 3-T CSI, a single visually targeted measurement using a 25% threshold is accurate for identifying marrow-replacing lesions.

Fracture of ankle: MRI using opposed-phase imaging obtained from turbo spinecho modified Dixon image shows improved sensitivity.

To evaluate if opposed-phase (OP) imaging obtained from the turbo spin echo (TSE) modified Dixon (mDixon) technique can increase the sensitivity of MRI for diagnosing ankle fractures. This study included 95 CT-confirmed ankle fractures with additional MRI of the ankle using a TSE modified Dixon (mDixon) technique. Two groups of images were analyzed independently: Group 1-imaging group without OP imaging; Group 2-imaging group with OP imaging. Readers assessed the images using a 4-point confidence score to detect fractures. During the first review session, the fracture site was blinded. For the second review session, the fracture site was provided. Sensitivity and positive-predictive value were calculated. In both sessions, the sensitivity for Group2 was significantly greater than that for Group 1 (Session 1: 76.3% vs 62.6%, p < 0.0001; Session 2: 80.5% vs 65.3%, p < 0.0001). The positive-predictive value of Group2 was significantly lower in both sessions 1 and 2 (Session 1: 85.8% vs 97.5%, p < 0.0001; Session 2: 90.5% vs 96.9%, p = 0.0068). Among the 28 false-negative fractures missed in Group 1 (Session 1), 12 (9 minimal displaced and 4 small diameter fractures) were identified in Group 2 (Session 1). While 8.9% showed lower movement, 33.6% showed upper movement in Group2 compared with Group 1. Possible causes of false-positive lesions were subcutaneous fat, bone marrow edema, and intraosseous vessel mimic fractures. OP imaging obtained using the modified Dixon technique provided better sensitivity and improved descriptions of fractures, especially for minimal displaced fractures and small diameter fractures. However, caution is required when diagnosing fractures with OP imaging because pseudofractures can appear as a result of adjacent bone marrow edema, vascular structures, or subcutaneous fat lobules. Advances in knowledge: In MRI, minimal displaced or small chip bone fracture maybe missed, OP imaging obtained using the mDixon technique provided better sensitivity and improved descriptions of fractures using the black boundary artifact.

Modified dixon-based renal dynamic contrast-enhanced MRI facilitates automated registration and perfusion analysis.

PurposeRenal dynamic contrast‐enhanced (DCE) MRI provides information on renal perfusion and filtration. However, clinical implementation is hampered by challenges in postprocessing as a result of misalignment of the kidneys due to respiration. We propose to perform automated image registration using the fat‐only images derived from a modified Dixon reconstruction of a dual‐echo acquisition because these provide consistent contrast over the dynamic series.MethodsDCE data of 10 hypertensive patients was used. Dual‐echo images were acquired at 1.5 T with temporal resolution of 3.9 s during contrast agent injection. Dixon fat, water, and in‐phase and opposed‐phase (OP) images were reconstructed. Postprocessing was automated. Registration was performed both to fat images and OP images for comparison. Perfusion and filtration values were extracted from a two‐compartment model fit.ResultsAutomatic registration to fat images performed better than automatic registration to OP images with visible contrast enhancement. Median vertical misalignment of the kidneys was 14 mm prior to registration, compared to 3 mm and 5 mm with registration to fat images and OP images, respectively (P = 0.03). Mean perfusion values and MR‐based glomerular filtration rates (GFR) were 233 ± 64 mL/100 mL/min and 60 ± 36 mL/minute, respectively, based on fat‐registered images. MR‐based GFR correlated with creatinine‐based GFR (P = 0.04) for fat‐registered images. For unregistered and OP‐registered images, this correlation was not significant.ConclusionAbsence of contrast changes on Dixon fat images improves registration in renal DCE MRI and enables automated postprocessing, resulting in a more accurate estimation of GFR. Magn Reson Med 80:66–76, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Contrast-Enhanced Dixon Fat-Water Separation Imaging of the Spine: Added Value of Fat, In-Phase and Opposed-Phase Imaging in Marrow Lesion Detection.

Beyond fat suppression (FS), the efficacy of (fat-water separation or Dixon [FWD]) Dixon imaging in gadolinium-enhanced spine imaging has yet to be validated. This study evaluated enhanced opposed-phase (OP) and fat-only (FO) images along with water-only (WO; FS) images against traditional unenhanced techniques and rated the incremental value of in-phase imaging in patients with presumed neoplastic focal spine lesions. A retrospective cohort study of 36 subjects with focal spine lesions imaged with FWD was evaluated qualitatively and quantitatively. Enhanced OP, WO, and FO images were of significant value in detection of osseous lesions, surpassing the lesion conspicuity with conventional techniques both qualitatively and quantitatively, although the impact of in-phase imaging was limited. Water-only imaging performed well for FS. Contrast-enhanced FO, WO, and OP outperform traditional techniques, providing reliable lesion characterization and highest conspicuity. In-phase imaging offered limited impact on the subjective assessment of enhancement. The added value and robustness of FWD, particularly the unique contrast provided by FO imaging, suggests consideration for routine use for postgadolinium spine imaging.

SU‐E‐J‐219: A Dixon Based Pseudo‐CT Generation Method for MR‐Only Radiotherapy Treatment Planning of the Pelvis and Head and Neck

Purpose:To develop an image processing method for MRI‐based generation of electron density maps, known as pseudo‐CT (pCT), without usage of model‐ or atlas‐based segmentation, and to evaluate the method in the pelvic and head‐neck region against CT.Methods:CT and MRI scans were obtained from the pelvic region of four patients in supine position using a flat table top only for CT. Stratified CT maps were generated by classifying each voxel based on HU ranges into one of four classes: air, adipose tissue, soft tissue or bone.A hierarchical region‐selective algorithm, based on automatic thresholding and clustering, was used to classify tissues from MR Dixon reconstructed fat, In‐Phase (IP) and Opposed‐Phase (OP) images. First, a body mask was obtained by thresholding the IP image. Subsequently, an automatic threshold on the Dixon fat image differentiated soft and adipose tissue. K‐means clustering on IP and OP images resulted in a mask that, via a connected neighborhood analysis, allowing the user to select the components corresponding to bone structures.The pCT was estimated through assignment of bulk HU to the tissue classes. Bone‐only Digital Reconstructed Radiographs (DRR) were generated as well. The pCT images were rigidly registered to the stratified CT to allow a volumetric and voxelwise comparison. Moreover, pCTs were also calculated within the head‐neck region in two volunteers using the same pipeline.Results:The volumetric comparison resulted in differences &lt;1% for each tissue class. A voxelwise comparison showed a good classification, ranging from 64% to 98%. The primary misclassified classes were adipose/soft tissue and bone/soft tissue. As the patients have been imaged on different table tops, part of the misclassification error can be explained by misregistration.Conclusion:The proposed approach does not rely on an anatomy model providing the flexibility to successfully generate the pCT in two different body sites.This research is founded by ZonMw IMDI Programme, project name: “RASOR sharp: MRI based radiotherapy planning using a single MRI sequence”, project number: 10‐104003010

Chemical shift imaging: preliminary experience as an alternative sequence for defining the extent of a bone tumor.

To investigate chemical shift imaging (CSI) with in-phase and opposed-phase (OP) gradient-echo sequences as an alternative sequence to spin-echo T1 imaging for defining intra-medullary skeletal tumor extent. This retrospective HIPAA-compliant study was approved by our institutional institutional review board (IRB). Twenty-three subjects with histologically-proven tumors (17 appendicular, 6 axial) underwent magnetic resonance imaging (MRI) with T1-weighted spin echo (T1SE), fluid-sensitive, CSI, and contrast-enhanced T1 sequences. One observer recorded intra-medullary tumor extent (millimeters), with 153 total measurements on each sequence. Red marrow grade [0 (none), 1 (<50%), 2 (50-75%) and 3 (>75%)] in each bone was recorded. Tumor extent on different sequences was compared (Student's t-test); the impact of red marrow grade on measurements was assessed (Spearman's correlation coefficient). There was good agreement between measurements of tumor extent on T1SE and CSI sequences in all cases (T1SE-CSI measurement difference range 0-13.2 mm, P>0.05). Measurements from other sequences were significantly different from those of T1SE (P<0.05). As red marrow grade in the bone increased, a significant increase in measurement difference obtained on T1SE and CSI sequences was observed (P<0.001). CSI is a potential alternative technique to T1SE imaging for defining the intra-medullary extent of a bone tumor, possibly especially useful in regions with abundant red marrow. CSI could be an alternative technique to T1SE imaging for defining the intra-medullary extent of bone tumor by abundant red marrow in the surrounding bone.

Corticomedullary differentiation of the kidney: Evaluation with noncontrast‐enhanced steady‐state free precession (SSFP) MRI with time‐spatial labeling inversion pulse (time‐SLIP)

To assess whether noncontrast-enhanced steady-state free precession (SSFP) magnetic resonance imaging (MRI) with time-spatial labeling inversion pulse (Time-SLIP) can improve the visibility of corticomedullary differentiation of the normal kidney. A series of noncontrast-enhanced SSFP MRI with Time-SLIP were performed in 20 patients by using various inversion times (TIs); 500-1800 msec in increments of 100 msec. In-phase (IP) and opposed-phase (OP) MR images were also obtained. The signal intensity (SI) of the renal cortex and medulla was measured to calculate corticomedullary contrast ratio (SI of cortex/medulla). Additionally, the visibility of corticomedullary differentiation was visually categorized using a four-point scale. In SSFP with Time-SLIP, corticomedullary contrast ratio was highest with TI of 1200 msec in eight subjects (40%), followed by 1100 msec in seven (35%) and 1000 msec in three (15%). The corticomedullary contrast ratio in SSFP with optimal Time-SLIP (4.93 ± 1.25) was significantly higher (P < 0.001) than those of IP (1.46 ± 0.12) and OP (1.43 ± 0.14). The visibility of corticomedullary differentiation was significantly better (P < 0.001) in SSFP images with Time-SLIP (averaged grade = 4.0) than in IP images (averaged grade = 2.63) and OP images (averaged grade = 2.05). SSFP MRI with Time-SLIP can improve the visibility of renal corticomedullary differentiation without using contrast agents.

Feasibility of dual gradient-echo in-phase and opposed-phase magnetic resonance imaging for the evaluation of epicardial fat

Dual gradient-echo in-phase (IP) and opposed-phase (OP) magnetic resonance imaging (MRI) can evaluate small amounts of fat, and is widely used for imaging abdominal organs. Epicardial fat has recently been revealed as having an important role in the development of heart disease, but IPOP-MRI has not been widely applied in this field, probably because of cardiac motion artifacts. To demonstrate the feasibility of IPOP-MRI with electrocardiography (ECG)-gating for evaluation of epicardial fat in the normal human heart, compared to black-blood T1-weighted imaging (T1WI). Ten healthy volunteers were studied. Epicardial fat volume was quantitatively evaluated on OP-from-IP subtraction images and T1-weighted images. Epicardial fat was clearly visualized on the subtraction images as hyperintense areas that corresponded to regions identified as epicardial fat on the T1-weighted images. Epicardial fat volume correlated well between the two methods (r = 0.93, P <0.0001), and tended to be larger on the subtraction images than on the T1-weighted images (91.4 ± 30.1 vs. 84.1 ± 30.5 mL, P = 0.07). IPOP-MRI with ECG-gating may be a useful alternative method to black-blood T1WI for evaluation of epicardial fat.