Proton Density-weighted Magnetic Resonance Imaging Research Articles

Pretreatment with nano-silver extends the post-harvest longevity of gladiolus cut flowers by reducing free water mobility

The water content of cut flowers is a significant factor in their post-harvest quality. In this study, we examine the efficacy of silver nanoparticles (NS) on the longevity of cut gladiolus, with a focus on water state and distribution. We used Low-field nuclear magnetic resonance (LF-NMR) technology to identify three water fractions with different transverse relaxation times (T2) values: bound water T21 (<10 ms), intermediate immobilized water T22 (10–100 ms), and the slowest component free water T23 (>10 ms). During the opening process, T23 increased at stages 2 and 3 and then decreased, T22 decreased slowly, and T21 remained unchanged. Free water values were consistently higher than bound water and immobilized water and reached their maximum from stage 2 until stage 4, when the petals were extended and began to wilt. The vascular bundles responsible for transporting water had higher water content, as detected by proton density-weighted magnetic resonance imaging (MRI). Bound water and free water with NS pretreatments in bracts were initially lower but then two days later the signal amplitude of each water state exceeded those of the control, indicating that the treatment enhanced the water-holding capacity over time. Furthermore, NS pretreatments reduced the free water mobility of the cut flowers and inhibited stem decay. Additionally, we found that NS can enter the stem and are primarily transported upward along the xylem with water using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) technology. Overall, our findings indicate that NS pretreatment reduces free water in gladiolus cut flowers, enhancing their water retention and prolonging their vase life.

Association Between MRI Signal Intensity of the Repaired Lateral Meniscus and Residual Anterolateral Knee Laxity After ACL Reconstruction.

Anterolateral knee laxity (ALLx) has been linked to tears of the lateral meniscus (LM) and anterior cruciate ligament (ACL) injury. To investigate the longitudinal relationship between the signal intensity (SI) of the repaired LM on magnetic resonance imaging (MRI) and residual ALLx after ACL reconstruction (ACLR). Cohort study; Level of evidence, 3. Included were 87 patients who underwent double-bundle ACLR and lateral meniscal repair (mean age, 23.5 years; body mass index, 23.7 kg/m2; 56 women) at a single institution between 2010 and 2019. Proton density-weighted (PDW) and T2-weighted (T2W) MRI was performed at 3, 6, and 12 months postoperatively, and the SI ratio (SIR) was calculated as (SI of the repaired LM)/(SI of the posterior cruciate ligament). At the 12-month follow-up, ALLx was evaluated using the pivot-shift test; an International Knee Documentation Committee grade ≥1 indicated residual ALLx. Overall, 12 patients (13.8%) exhibited ALLx at 12 months postoperatively. At 3 months postoperatively, the SIR on PDW images (SIR-PDW) was significantly higher in patients with ALLx versus those without ALLx (1.98 ± 0.77 vs 1.49 ± 0.52, respectively; P = .007); there was no difference in the SIR on T2W images between the groups. SIR-PDW at 3 months postoperatively was correlated negatively with patient age (r = -0.308, P = .004). When patients were stratified into a younger (≤22 years; n = 53; ALLx = 7 [13.2%]) and an older (>22 years; n = 34; ALLx = 5 [14.7%]) group, the area under the receiver operating characteristic curves (AUCs) for SIR-PDW in the younger group were statistically significant for predicting the prevalence of ALLx at all follow-up times (AUCs, 0.733-0.788) with optimal cutoff values of 2.00 at 3 months, 1.50 at 6 months, and 1.50 at 12 months. Logistic regression analysis revealed that if younger patients consistently had higher SIR-PDW values than the cutoff values, they were more likely to have residual ALLx (odds ratios, 10.24-23.57). For younger patients who underwent both ACLR and lateral meniscal repair, higher MRI SI of the repaired LM was associated with a higher prevalence of residual ALLx.

A new magnetic resonance imaging grading system for anterior cruciate ligament myxoid degeneration in osteoarthritis of the knee

BackgroundThis study aimed to investigate association between magnetic resonance imaging (MRI) and histological findings of degenerated anterior cruciate ligament (ACL) in knee osteoarthritis (OA), and based on this result, to develop a new ACL degeneration grading system by MRI that corresponds to histological findings of degenerated ACL. HypothesisMRI signal intensity of the ACL could correspond to histological findings of collagen degeneration. Patients and methodsA collection of 106 ACL specimens from 85 patients who underwent primary total knee arthroplasty was investigated for signal intensity of the ACL and muscle on axial Fat-saturated proton density-weighted MRI and MRI signal intensity ratio (ACL/muscle) was calculated. The correlation between ACL histological degeneration and MRI ACL/muscle signal intensity ratio was analyzed. The ACL was stratified into 3 grades based on signal intensity relative to muscle intensity (grade 1, low; grade 2, iso; and grade 3, high), and the extent to ACL degeneration in each MRI ACL degeneration grade was evaluated. ResultsCollagen degeneration (53.5±24.0%) and myxoid change (25.2±18.8%) in degenerated ACL significantly correlated with MRI signal intensity ratio of the ACL/muscle (r=0.62, p<0.0001; r=0.67, p<0.0001). ACL were assigned to grade 1 (n=22 [20.8%]), grade 2 (n=56 [52.8%]), and grade 3 (n=28 [26.4%]). ACL collagen degeneration was 34.8±18.4% in grade 1, 49.3±21.7% in grade 2, and 76.6±12.0% in grade 3. ACL myxoid change was 10.0±11.3% in grade 1, 21.3±14.1% in grade 2, and 45.0±15.3% in grade 3. DiscussionThe ACL/muscle signal intensity ratio on MRI correlated with the extent to ACL myxoid degeneration. The new MRI ACL degeneration grade is helpful to estimate the extent to ACL myxoid degeneration in knee OA. Level of evidenceIII; retrospective cohort study.

Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification.

Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landmark-based detection and quantification of hip abnormalities from magnetic resonance (MR) images. The framework relies on a novel idea of multi-landmark environment analysis with reinforcement learning. In particular, we merge the concepts of the graphical lasso and Morris sensitivity analysis with deep neural networks to quantitatively estimate the contribution of individual landmark and landmark subgroup locations to the other landmark locations. Convolutional neural networks for image segmentation are utilized to propose the initial landmark locations, and landmark detection is then formulated as a reinforcement learning (RL) problem, where each landmark-agent can adjust its position by observing the local MR image neighborhood and the locations of the most-contributive landmarks. The framework was validated on T1-, T2- and proton density-weighted MR images of 260 patients with the aim to measure the lateral center-edge angle (LCEA), femoral neck-shaft angle (NSA), and the anterior and posterior acetabular sector angles (AASA and PASA) of the hip, and derive the quantitative abnormality metrics from these angles. The framework was successfully tested using the UNet and feature pyramid network (FPN) segmentation architectures for landmark proposal generation, and the deep Q-network (DeepQN), deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and actor-critic policy gradient (A2C) RL networks for landmark position optimization. The resulting overall landmark detection error of 1.5 mm and angle measurement error of 1.4° indicates a superior performance in comparison to existing methods. Moreover, the automatically estimated abnormality labels were in 95% agreement with those generated by an expert radiologist.

Reliability and agreement of proton density-weighted vs. gadolinium-enhanced T1-weighted MRI in hand osteoarthritis. An OMERACT MRI special interest group reliability exercise

ObjectivesTo compare reliabilities of assessing synovitis in hand osteoarthritis (OA) using Magnetic Resonance Imaging (MRI) with/without gadolinium (Gd). MethodsThree readers scored synovitis on non-enhanced two-dimensional (2D) proton density (PD)-weighted MRI and Gd-enhanced (3D) MRI of hand joints in 20 patients. Inter-reader reliabilities were examined. ResultsReliability was good for Gd-enhanced MRI, but poor for non-enhanced PD-weighted MRI (intraclass correlation coefficient 0.83 and 0.21, respectively). Agreement between the two sequences was poor (weighted kappa 0.18). ConclusionGd-enhanced MRI was more reliable than PD-weighted MRI for assessing synovitis. Gd-enhancement, but also resolution and tissue contrast, might have contributed to this.

Added diagnostic values of three-dimensional high-resolution proton density-weighted magnetic resonance imaging for unruptured intracranial aneurysms in the circle-of-Willis: Comparison with time-of-flight magnetic resonance angiography.

Advanced imaging methods can enhance the identification of aneurysms of the infundibula, which can reduce unnecessary follow-ups or further work-up, fear, and anxiety in patients. This study aimed to evaluate the added diagnostic value of three-dimensional proton density-weighted vessel wall magnetic resonance imaging (3D-PD MRI) in identifying aneurysms from index lesions refer to vascular bulging lesions without vessels arising from the apex, observed using volume-rendered TOF-MRA in the circle-of-Willis compared with time-of-flight magnetic resonance angiography (TOF-MRA). Retrospective. A total of 299 patients who underwent 3D-PD MRI, digital subtraction angiography (DSA), and TOF-MRA between January 2012 and December 2016 were retrospectively enrolled in this study. 3 Tesla, 3D-PD MRI. Three neuroradiologists independently evaluated TOF-MRA and 3D-PD MRI combined with TOF-MRA for the determination of intracranial aneurysms in patients with index lesions within the circle of Willis. Final diagnoses were made by another neuroradiologist and neurointerventionist in consensus using DSA as the reference standard. The diagnostic performance and proportions of undetermined lesions on TOF-MRA and 3D-PD MRI with TOF-MRA were assessed based on the final diagnoses. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for the diagnosis of unruptured intracranial aneurysms were calculated for each imaging modality. Of 452 lesions identified on volume-rendered TOF-MRA images, 173 (38%) aneurysms and 276 (61%) infundibula were finally diagnosed on DSA. 3D-PD MRI with TOF-MRA showed superior diagnostic performance (p = .001; accuracy, 85.5% versus 95.4%), superior area under the receiver operating characteristic curve over TOF-MRA (p = .001; 0.837 versus 0.947), and a lower proportion of undetermined lesions than TOF-MRA (p = .001; 25.1% versus 2.3%). For unruptured intracranial aneurysms in the circle of Willis, 3D-PD MRI can complement TOF-MRA to improve diagnostic performance and lower the proportion of undetermined lesions.

Deep-learning-based image quality enhancement of compressed sensing magnetic resonance imaging of vessel wall: comparison of self-supervised and unsupervised approaches

While high-resolution proton density-weighted magnetic resonance imaging (MRI) of intracranial vessel walls is significant for a precise diagnosis of intracranial artery disease, its long acquisition time is a clinical burden. Compressed sensing MRI is a prospective technology with acceleration factors that could potentially reduce the scan time. However, high acceleration factors result in degraded image quality. Although recent advances in deep-learning-based image restoration algorithms can alleviate this problem, clinical image pairs used in deep learning training typically do not align pixel-wise. Therefore, in this study, two different deep-learning-based denoising algorithms—self-supervised learning and unsupervised learning—are proposed; these algorithms are applicable to clinical datasets that are not aligned pixel-wise. The two approaches are compared quantitatively and qualitatively. Both methods produced promising results in terms of image denoising and visual grading. While the image noise and signal-to-noise ratio of self-supervised learning were superior to those of unsupervised learning, unsupervised learning was preferable over self-supervised learning in terms of radiomic feature reproducibility.

The relationship between high-signal intensity changes in the glenohumeral joint capsule on MRI and clinical shoulder symptoms

Background/objectiveHigh-signal intensity changes in the glenohumeral joint capsule on T2-and proton density-weighted magnetic resonance imaging are known as characteristic finding that is often observed in patients with frozen shoulder. We investigated the associations between high-signal intensity changes in the joint capsule on magnetic resonance imaging and the presence of rotator cuff tears and shoulder symptoms in patients with shoulder pain. MethodsThe medical records of 230 patients with shoulder pain who underwent magnetic resonance imaging at our hospital were reviewed. Patients were divided into three groups according to the presence and/or degree of rotator cuff tears (none, partial, or complete). The frequency of high-signal intensity changes in the joint capsule and its relationship with shoulder symptoms and the severity of rotator cuff tears were assessed. By quantitatively evaluating the intensity on MRI, the ratio between the joint capsule and the long head of the biceps (HSIC ratio) was calculated and compared with 15 healthy subjects. ResultsHigh-signal intensity changes were diagnosed in 165 (72%) patients, and it was significantly associated with night pain and range of motion limitation (p < 0.01). High-signal intensity changes were present in 66 patients (70%) with no rotator cuff tears, in 69 (71%) with partial rotator cuff tears, and in 36 (80%) with complete rotator cuff tears, without differences in their occurrence (p = 0.60), but were significantly associated with night pain in all the groups (p < 0.01) without differences in tear severity (p = 0.63). The ratio in the high-signal intensity changes (HSIC) positive group was approximately six times higher than that in the HSIC-negative and control groups (P < 0.01). Multivariate logistic regression analysis revealed that night pain is significantly associated with high-signal intensity changes (p < 0.01). ConclusionShoulder pain is a common and reliable clinical finding in patients with high–signal intensity changes, regardless of the presence and/or degree of rotator cuff tears, Such changes may indicate night pain and range of motion limitation in patients.

Extracellular resistance is sensitive to tissue sodium status; implications for bioimpedance-derived fluid volume parameters in chronic kidney disease

Multifrequency bioimpedance spectroscopy (BIS) is an established method for assessing fluid status in chronic kidney disease (CKD). However, the technique is lacking in predictive value and accuracy. BIS algorithms assume constant tissue resistivity, which may vary with changing tissue ionic sodium concentration (Na+). This may introduce significant inaccuracies to BIS outputs. To investigate this, we used 23Na magnetic resonance imaging (MRI) to measure Na+ in muscle and subcutaneous tissues of 10 healthy controls (HC) and 20 patients with CKD 5 (not on dialysis). The extracellular (Re) and intracellular (Ri) resistance, tissue capacitance, extracellular (ECW) and total body water (TBW) were measured using BIS. Tissue water content was assessed using proton density-weighted MRI with fat suppression. BIS-derived volume indices were comparable in the two groups (OH: HC − 0.4 ± 0.9 L vs. CKD 0.5 ± 1.9 L, p = 0.13). However, CKD patients had higher Na+ (HC 21.2 ± 3.0, CKD 25.3 ± 7.4 mmol/L; p = 0.04) and significantly lower Re (HC 693 ± 93.6, CKD 609 ± 74.3 Ohms; p = 0.01); Ri and capacitance did not vary. Na+ showed a significant inverse linear relationship to Re (rs = − 0.598, p < 0.01) but not Ri. This relationship of Re (y) and Na+ (x) is described through equation y = − 7.39x + 814. A 20% increase in tissue ionic Na+ is likely to overestimate ECW by 1.2–2.4L. Tissue Na+ concentration has a significant inverse linear relationship to Re. BIS algorithms to account for this effect could improve prediction accuracy of bioimpedance derived fluid status in CKD.

Detection of fluid secretion of three-dimensional reconstructed eccrine sweat glands by magnetic resonance imaging.

We previously showed three-dimensional (3D) reconstructed eccrine sweat glands have similar structures as native eccrine sweat glands, but whether the 3D reconstructed sweat glands appropriately secrete fluid is still unknown. In this study, Matrigel-embedded human eccrine sweat gland cells or Matrigel alone were implanted into the groin subcutis of the nude mice. Ten weeks post-implantation, images of the subcutaneously formed plugs, as well as footpads of rats, pre- and post-pilocarpine/normal saline (NS) injection were acquired using a fat-suppressed proton density-weighted magnetic resonance imaging (MRI) sequence at 7.0T, and the regions of interest (ROIs) in plugs and rat footpads were analysed and graphed. A significant increase in the ROI mean proton intensity occurred in both 3D reconstructed and native eccrine sweat glands after pilocarpine injection. The mean proton intensity had no noticeable changes in ROIs of Matrigel plugs between pre- and post-pilocarpine injection, and in ROIs of rat footpads between pre- and post-NS injection. In conclusion, the 3D reconstructed sweat glands possess fluid secretion, which is detectable by fat-suppressed proton density-weighted MRI.

Differentiation Image Quality of MRI Shoulder Joint with Variation RF Coils

Image Quality of Magnetic Resonance Imaging (MRI) has several factors including SNR dan CNR. Influence Factors of SNR depends on the coil used. MRI shoulder joints in several hospitals can be done with different RF Coil, there are M coil flex and shoulder coil. Are there differences in image quality with MRI shoulder joints between the two coils. This study was conducted to determine differentiation SNR and CNR between them in the coronal proton density sequence of MR shoulder joint. This research was quantitative research with an experimental approach. Scanning was done by using Flex M Coil and shoulder coil with 10 samples. The quality image evaluated of SNR and CNR, data were analyzed using paired t-test with α = 5%. The results of the research showed significant differentiation of image quality between using Flex M Coil and shoulder coil in coronal proton density-weighted of MRI Shoulder Joint with p-value SNR &lt; 0,001 and CNR = 0,002. The average of SNR and CNR using shoulder coil is higher than using flex M coil, so the shoulder coil has the better image quality of coronal proton density-weighted MRI shoulder joint.

Denoise diffusion-weighted images using higher-order singular value decomposition

Noise usually affects the reliability of quantitative analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI), especially at high b-values and/or high spatial resolution. Higher-order singular value decomposition (HOSVD) has recently emerged as a simple, effective, and adaptive transform to exploit sparseness within multidimensional data. In particular, the patch-based HOSVD denoising has demonstrated superb performance when applied to T1-, T2-, and proton density-weighted MRI data. In this study, we aim to investigate the feasibility of denoising DW data using the HOSVD transform. With the low signal-to-noise ratio in typical DW data, the patch-based HOSVD denoising suffers from stripe artifacts in homogeneous regions because of the HOSVD bases learned from the noisy patches. To address this problem, we propose a novel denoising method. It first introduces a global HOSVD-based denoising as a prefiltering stage to guide the subsequent patch-based HOSVD denoising stage. The HOSVD bases from the patch groups in prefiltered images are then used to transform the noisy patch groups in original DW data. Experiments were performed using simulated and in vivo DW data. Results show that the proposed method significantly reduces stripe artifacts compared with conventional patch-based HOSVD denoising methods, and outperforms two state-of-the-art denoising methods in terms of denoising quality and diffusion parameters estimation.

Metal artifact reduction in MRI-based cervical cancer intracavitary brachytherapy

Magnetic resonance imaging (MRI) plays an increasingly important role in brachytherapy planning for cervical cancer. Yet, metal tandem, ovoid intracavitary applicators, and fiducial markers used in brachytherapy cause magnetic susceptibility artifacts in standard MRI. These artifacts may impact the accuracy of brachytherapy treatment and the evaluation of tumor response by misrepresenting the size and location of the metal implant, and distorting the surrounding anatomy and tissue. Metal artifact reduction sequences (MARS) with high bandwidth RF selective excitations and turbo spin-echo readouts were developed for MRI of orthopedic implants. In this study, metal artifact reduction was applied to brachytherapy of cervical cancer using the orthopedic metal artifact reduction (O-MAR) sequence. O-MAR combined MARS features with view angle tilting and slice encoding for metal artifact correction (SEMAC) to minimize in-plane and through-plane susceptibility artifacts. O-MAR improved visualization of the tandem tip on T2 and proton density weighted (PDW) imaging in phantoms and accurately represented the diameter of the tandem. In a pilot group of cervical cancer patients (N = 7), O-MAR significantly minimized the blooming artifact at the tip of the tandem in PDW MRI. There was no significant difference observed in artifact reduction between the weak (5 kHz, 7 z-phase encodes) and medium (10 kHz, 13 z-phase encodes) SEMAC settings. However, the weak setting allowed a significantly shorter acquisition time than the medium setting. O-MAR also reduced susceptibility artifacts associated with metal fiducial markers so that they appeared on MRI at their true dimensions.

RETRACTED ARTICLE: Hermite-based texture feature extraction for classification of humeral head in proton density-weighted MR images

The objective of this research is to develop a computer-based diagnosis system which is capable of recognizing normal and edematous humeral head images by using texture features derived from Hermite transform. The performance of Hermite-based texture features in classification of humeral bone was compared with curvelet, contourlet and gray level co-occurrence matrix-based texture feature descriptors. To measure the performance of the extracted features, we deployed MLP (multilayer perceptron), SVM (support vector machine) and KNN (K-nearest neighbors) methods and demonstrated their power in differentiating the normal and abnormal regions. The proposed approach was tested on our own dataset which consists of 79 normal and 91 edematous humeral heads in PD (proton density)-weighted MR (magnetic resonance) images. The highest classification accuracy of Hermite-based method was 98.23% by MLP. In most cases, Hermite-based texture features surpassed the results of other proposed methods under all of the three classifiers. Our results suggest that the proposed system is a promising tool for classification of edematous and normal bone from PD-weighted MR images. This study is unique in the literature of using PD-weighted MR images and Hermite transform to classify bone edema .

Lumen segmentation in magnetic resonance images of the carotid artery

Investigation of the carotid artery plays an important role in the diagnosis of cerebrovascular events. Segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images is the first step towards evaluating any possible cardiovascular diseases like atherosclerosis. However, the automatic segmentation of the lumen is still a challenge due to the low quality of the images and the presence of other elements such as stenosis and malformations that compromise the accuracy of the results. In this article, a method to identify the location of the lumen without user interaction is presented. The proposed method uses the modified mean roundness to calculate the circularity index of the regions identified by the K-means algorithm and return the one with the maximum value, i.e. the potential lumen region. Then, an active contour is employed to refine the boundary of this region. The method achieved an average Dice coefficient of 0.78±0.14 and 0.61±0.21 in 181 3D-T1-weighted and 181 proton density-weighted MR images, respectively. The results show that this method is promising for the correct identification and location of the lumen even in images corrupted by noise.

MRI analysis of tibial PCL attachment in a large population of adult patients: reference data for anatomic PCL reconstruction.

BackgroundConsistent reference data used for anatomic posterior cruciate ligament (PCL) reconstruction is not well defined. Quantitative guidelines defining the location of PCL attachment would aid in performing anatomic PCL reconstruction. The purpose was to characterize anatomic parameters of the PCL tibial attachment based on magnetic resonance imaging (MRI) in a large population of adult knees.MethodsThe PCL tibial attachment site was examined in 736 adult knees with an intact PCL using 3.0-T proton density–weighted sagittal MRI. The outcomes measured were the anterior-posterior diameter (APD) of the tibial plateau; angle between the tibial plateau and the posterior tibial ‘shelf’ (the slope where the PCL tibial attachment site was) (PTS); length of the PTS; proximal, central, and distal PCL attachment positions as well as the width of the PCL attachment site; and vertical dimension of the PCL attachment site inferior from the tibial plateau.ResultsThe average APD of the tibia plateau was 33.6 ± 3.5 mm, yielding significant differences between males (35.5 ± 3.0 mm) and females (31.6 ± 2.7 mm), P <.05, and there was a significantly decreasing trend with increasing age in males (P <.05). Mean angle between the tibial plateau and the PTS was 122.4° ± 8.1°, and subgroup analysis showed that the young group had a differently smaller angle (120.9° ± 7.5°) than the middle-aged (123.7° ± 8.2°) and the old (123.4° ± 7.7°) in males population, while there were no significant differences between sexes (P >.05). The proximal, central positions and width of the PCL attachment site were 13.4 ± 3.0 mm, 17.8 ± 3.0 mm and 9.6 ± 2.4 mm along the PTS, with significant differences between males and females (P <.05), and accounted for 60.0 % ± 9.1 %, 80.0 % ± 4.6 % and 43.3 % ± 9.7 % of the PTS respectively, with no significant differences between sexes and among age groups (all P >.05).ConclusionsThis study provides reference data of the tibial PCL attachment based on MRI in the sagittal orientation. In analysis of retrospective data from a large population of adult patients, the quantitative values can be used as references to define the inserted angle and depth of the drill guide, and the exact position and size of the tibial PCL tunnel for performing arthroscopic anatomic PCL reconstruction.

Three-Dimensional Isotropic Fat-Suppressed Proton Density-Weighted MRI at 3 Tesla Using a T/R-Coil Can Replace Multiple Plane Two-Dimensional Sequences in Knee Imaging

To evaluate whether a 3 D proton density-weighted fat-suppressed sequence (PDwFS) of the knee is able to replace multiplanar 2D-PDwFS. 52 patients (26 men, mean age: 41.9 ± 14.5years) underwent magnetic resonance imaging (MRI) of the knee at 3.0 Tesla using a T/R-coil. The imaging protocol included 3 planes of 2D-PDwFS (acquisition time (AT): 6:40 min; voxel sizes: 0.40 - 0.63 × 0.44 - 0.89 × 3mm³) and a 3D-PDwFS (AT: 6:31 min; voxel size: 0.63 × 0.68 × 0.63mm³). Homogeneity of fat suppression (HFS), artifacts, and image sharpness (IS) were evaluated on a 5-point scale (5[excellent] - 1[non-diagnostic]). The sum served as a measure for the overall image quality (OIQ). Contrast ratios (CR) compared to popliteal muscle were calculated for the meniscus (MEN), anterior (ACL) and posterior cruciate ligaments (PCL). In 13patients who underwent arthroscopic knee surgery, two radiologists evaluated the presence of meniscal, ligamental and cartilage lesions to estimate the sensitivity and specificity of lesion detection. The CR was higher in theACL, PCL and MEN in 3D- PDwFS compared to 2D-PDwFS (p < 0.01 for ACL and PCL; p = 0.07 for MEN). Compared to 2 D images, the OIQ was rated higher in 3D-PDwFS images (p < 0.01) due to fewer artifacts and HFS despite the lower IS (p < 0.01). The sensitivity and specificity of lesion detection in 3D- and 2D-PDwFS were similar. Compared to standard multiplanar 2D-PDwFS knee imaging, isotropic high spatial resolution 3D-PDwFS of the knee at 3.0 T can be acquired with high image quality in a reasonable scan time. Multiplanar reformations in arbitrary planes may serve as an additional benefit of 3D-PDwFS. • 3D-PDwFS of the knee is acquired with high image quality• 3D-PDwFS can be achieved in only one measurement with a reasonable scan time• 3D-PDwFS with the advantage of multiplanar reformation may replace 2D-PD-weighted knee MRI Citation Format: • Homsi R, Gieseke J, Luetkens JA et al. Three-Dimensional Isotropic Fat-Suppressed Proton Density-Weighted MRI at 3 Tesla Using a T/R-Coil Can Replace Multiple Plane Two-Dimensional Sequences in Knee Imaging. Fortschr Röntgenstr 2016; 188: 949 - 956.

Magnetic Resonance Venous Volume Measurements in Peripheral Artery Disease (from ELIMIT)

The relation between the arterial and venous systems in patients with impaired lower extremity blood flow remains poorly described. The objective of this secondary analysis of the Effectiveness of Intensive Lipid Modification Medication in Preventing the Progression on Peripheral Artery Disease Trial was to determine the association between femoral vein (FV) volumes and measurements of peripheral artery disease. FV wall, lumen, and total volumes were quantified with fast spin-echo proton density-weighted magnetic resonance imaging scans in 79 patients with peripheral artery disease over 2 years. Reproducibility was excellent for FV total vessel (intraclass correlation coefficient 0.924, confidence interval 0.910 to 0.935) and lumen volumes (intraclass correlation coefficient 0.893, confidence interval 0.873 to 0.910). Baseline superficial femoral artery volumes were directly associatedwith FV wall (r= 0.46, p <0.0001), lumen (r= 0.42, p=0.0001),and totalvolumes (r=0.46, p <0.0001). The 2-year change in maximum walking time was inversely associated with the 24-month change in FV total volume (r=-0.45, p= 0.03). Inconclusion, FV volumes can be measured reliably with fast spin-echo proton density-weighted magnetic resonance imaging, and baseline superficial femoral artery plaque burden is positively associated with FV volumes, whereas the 2-year change in FV volumes and leg function show an inverse relation.

Three-Dimensional Intercondylar Notch Volumes in a Skeletally Immature Pediatric Population: A Magnetic Resonance Imaging–Based Anatomic Comparison of Knees With Torn and Intact Anterior Cruciate Ligaments

To determine whether 3-dimensional notch volume, measured with magnetic resonance imaging (MRI), differs significantly between knees with torn and intact anterior cruciate ligaments (ACLs) after sports injury in a skeletally immature pediatric population. MRI studies of 50 pediatric patients (age range, 10 to 17 years) with ACL tears were compared with 50 age- and sex-matched intact-ACL control patients. All patients had open physes and underwent MRI after a sports injury. Notch volume was calculated through manual segmentation of notch boundaries seen on axial 1.5-T proton density-weighted images. Two-dimensional (2D) measurements (notch width and notch width index) were made on coronal proton density-weighted MRI studies. Notch volume was compared between groups by use of the Mann-Whitney U test. Pearson correlation coefficients were also calculated between indices. Notch volume was significantly lower in knees with ACL tears than in control knees (5.5 ± 1.1 cm(3)v 6.4 ± 1.5 cm(3), P = .002), whereas 2D notch width and notch width index did not differ significantly between these groups. Girls had significantly smaller notch volumes than boys (5.4 ± 1.2 cm(3)v 6.5 ± 1.3 cm(3), P < .001). Notch volume was not correlated with age but was moderately correlated with 2D notch width (r = 0.485, P < .001). In adolescent patients with sports injuries, the 3-dimensional notch volume was significantly smaller in knees with ACL tears than in intact-ACL control knees. Notch volume was also significantly smaller in girls than in boys and did not vary significantly with age. Level III, case-control study.

Contour-Based Brain Segmentation Method for Magnetic Resonance Imaging Human Head Scans

The high-resolution magnetic resonance brain images often contain some nonbrain tissues (ie, skin, fat, muscle, neck, eye balls, etc) compared with the functional images such as positron emission tomography, single-photon emission computed tomography, and functional magnetic resonance imaging (MRI) scans, which usually contain few nonbrain tissues. Automatic segmentation of brain tissues from MRI scans remains a challenging task due to the variation in shape and size, use of different pulse sequences, overlapping signal intensities and imaging artifacts. This article presents a contour-based automatic brain segmentation method to segment the brain regions from T1-, T2-, and proton density-weighted MRI of human head scans. The proposed method consists of 2 stages. In stage 1, the brain regions in the middle slice is extracted. Many of the existing methods failed to extract brain regions in the lower and upper slices of the brain volume, where the brain appears in more than 1 connected region. To overcome this problem, in the proposed method, a landmark circle is drawn at the center of the extracted brain region of a middle slice and is likely to pass through all the brain regions in the remaining lower and upper slices irrespective of whether the brain is composed of 1 or more connected components. In stage 2, the brain regions in the remaining slices are extracted with reference to the landmark circle obtained in stage 1. The proposed method is robust to the variability of brain anatomy, image orientation, and image type, and it extracts the brain regions accurately in T1-, T2-, and proton density-weighted normal and abnormal brain images. Experimental results by applying the proposed method on 100 volumes of brain images show that the proposed method exhibits best and consistent performance than by the popular existing methods brain extraction tool, brain surface extraction, watershed algorithm, hybrid watershed algorithm, and skull stripping using graph cuts.