Proton Density-weighted Images Research Articles

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

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

A 3D pseudo-continuous arterial spin labeling study of altered cerebral blood flow correlation networks in mild cognitive impairment and Alzheimer's disease.

To investigate the abnormalities of the three-dimensional pseudo-continuous arterial spin labeling (3D PCASL) based cerebral blood flow (CBF) correlation networks in mild cognitive impairment (MCI) and Alzheimer's disease (AD). 3D PCASL images of 53 cognitive normal (CN) subjects, 43 subjects with MCI, and 30 subjects with AD were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Whole-brain CBF maps were calculated using PCASL and proton density-weighted images (PDWI). The 246 regional CBF values, including the cortex and subcortex, were obtained after registering the Brainnetome Atlas to the individual CBF maps. The Pearson correlation coefficient between every two regions across subjects was calculated to construct the CBF correlation network. Then the topologies of CBF networks with regard to global properties (global network efficiency, clustering coefficient, characteristic path length, and small-world properties), hub regions, nodal properties (betweenness centrality, BC), and connections were compared among CN, MCI, and AD. Significant changes in the global and nodal properties were observed in the permutation tests, and connections with significant differences survived after the z-statistic and false discovery rate (FDR) correction. The CBF correlation networks of CN, MCI, and AD all showed small-world properties. Compared with CN, global efficiency decreased significantly in AD. Significant differences in nodal properties and a loss of hub regions are noted in the middle temporal lobe in both MCI and AD. In the frontal lobe, BC is reduced in MCI while it is increased in the occipital lobe in AD. The identified altered hub regions with significant differences in MCI and AD were mainly distributed in the hippocampus and entorhinal cortex. In addition, disrupted hub regions in AD with significantly decreased connections were mainly found in the precuneus/posterior cingulate cortex (PCC) and hippocampus-cortical cortex. Noninvasive 3D PCASL-based CBF correlation networks are capable of showing changes in topological organization in subjects with MCI and AD, and the observed disruption in the topological organization may underlie cognitive decline in MCI and AD.

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.

Deep learning-based reconstruction enhances image quality and improves diagnosis in magnetic resonance imaging of the shoulder joint.

Accelerated magnetic resonance imaging sequences reconstructed using the vendor-provided Recon deep learning algorithm (DL-MRI) were found to be more likely than conventional magnetic resonance imaging (MRI) sequences to detect subacromial (SbA) bursal thickening. However, the extent of this thickening was not extensively explored. This study aimed to compare the image quality of DL-MRI with conventional MRI sequences reconstructed via conventional pipelines (Conventional-MRI) for shoulder examinations and evaluate the effectiveness of DL-MRI in accurately demonstrating the degree of SbA bursal and subcoracoid (SC) bursal thickening. This prospective cross-sectional study enrolled 41 patients with chronic shoulder pain who underwent 3-T MRI (including both Conventional-MRI and accelerated MRI sequences) of the shoulder between December 2022 and April 2023. Each protocol consisted of oblique axial, coronal, and sagittal images, including proton density-weighted imaging (PDWI) with fat suppression (FS) and oblique coronal T1-weighted imaging (T1WI) with FS. The image quality and degree of artifacts were assessed using a 5-point Likert scale for both Conventional-MRI and DL-MRI. Additionally, the degree of SbA and SC bursal thickening, as well as the relative signal-to-noise ratio (rSNR) and relative contrast-to-noise ratio (rCNR) were analyzed using the paired Wilcoxon test. Statistical significance was defined as P<0.05. The utilization of accelerated sequences resulted in a remarkable 54.7% reduction in total scan time. Overall, DL-MRI exhibited superior image quality scores and fewer artifacts compared to Conventional-MRI. Specifically, DL-MRI demonstrated significantly higher measurements of SC bursal thickenings in the oblique sagittal PDWI sequence compared to Conventional-MRI [3.92 (2.83, 5.82) vs. 3.74 (2.92, 5.96) mm, P=0.028]. Moreover, DL-MRI exhibited higher detection of SbA bursal thickenings in the oblique coronal PDWI sequence [2.61 (1.85, 3.46) vs. 2.48 (1.84, 3.25) mm], with a notable trend towards significant differences (P=0.071). Furthermore, the rSNRs of the muscle in DL-MRI images were significantly higher than those in Conventional-MRI images across most sequences (P<0.001). However, the rSNRs of bone on Conventional-MRI of oblique axial and oblique coronal PDWI sequences showed adverse results [oblique axial: 1.000 (1.000, 1.000) vs. 0.444 (0.367, 0.523); and oblique coronal: 1.000 (1.000, 1.000) vs. 0.460 (0.387, 0.631); all P<0.001]. Additionally, all DL-MRI images exhibited significantly greater rSNRs and rCNRs compared to accelerated MRI sequences reconstructed using traditional pipelines (P<0.001). In conclusion, the utilization of DL-MRI enhances image quality and improves diagnostic capabilities, making it a promising alternative to Conventional-MRI for shoulder imaging.

Faster acquisition of magnetic resonance imaging sequences of the knee via deep learning reconstruction: a volunteer study

To evaluate whether deep learning reconstruction (DLR) can accelerate the acquisition of magnetic resonance imaging (MRI) sequences of the knee for clinical use. Using a 1.5-T MRI scanner, sagittal fat-suppressed T2-weighted imaging (fs-T2WI), coronal proton density-weighted imaging (PDWI), and coronal T1-weighted imaging (T1WI) were performed. DLR was applied to images with a number of signal averages (NSA) of 1 to obtain 1DLR images. Then 1NSA, 1DLR, and 4NSA images were compared subjectively, and by noise (standard deviation of intra-articular water or medial meniscus) and contrast-to-noise ratio between two anatomical structures or between an anatomical structure and intra-articular water. Twenty-seven healthy volunteers (age: 40.6±11.9 years) were enrolled. Three 1DLR image sequences were obtained within 200 s (approximately 12 minutes for 4NSA image). According to objective evaluations, PDWI 1DLR images showed the smallest noise and significantly higher contrast than 1NSA and 4NSA images. For fs-T2WI, smaller noise and higher contrast were observed in the order of 4NSA, 1DLR, and 1NSA images. According to the subjective analysis, structure visibility, image noise, and overall image quality were significantly better for PDWI 1DLR than 1NSA images; moreover, the visibility of the meniscus and bone, image noise, and overall image quality were significantly better for 1DLR than 4NSA images. Fs-T2WI and T1WI 1DLR images showed no difference between 1DLR and 4NSA images. Compared to PDWI 4NSA images, PDWI 1DLR images were of higher quality, while the quality of fs-T2WI and T1WI 1DLR images was similar to that of 4NSA images.

Primary anterior cruciate ligament repair-morphological and quantitative assessment by 7-T MRI and clinical outcome after 1.5 years.

The purpose of this study was to assess morphological and quantitative changes of the anterior cruciate ligament (ACL) and cartilage after ACL repair. 7T MRI of the knee was acquired in 31 patients 1.5 years after ACL repair and in 13 controls. Proton density-weighted images with fat saturation (PD-fs) were acquired to assess ACL width, signal intensity, elongation, and fraying. T2/T2* mapping was performed for assessment of ACL and cartilage. Segmentation of the ACL, femoral, and tibial cartilage was carried out at 12 ROIs. The outcome evaluation consisted of the Lysholm Knee Score and International Knee Documentation Committee (IKDC) subjective score and clinical examination. ACL showed a normal signal intensity in 96.8% and an increased width in 76.5% after repair. Fraying occurred in 22.6% without having an impact on the clinical outcome (Lysholm score: 90.39 ± 9.75, p= 0.76 compared to controls). T2 analysis of the ACL revealed no difference between patients and controls (p= 0.74). Compared to controls, assessment of the femoral and tibial cartilage showed a significant increase of T2* times in all ROIs, except at the posterolateral femur. Patients presented a good outcome in clinical examination with a Lysholm score of 87.19 ± 14.89 and IKDC of 80.23 ± 16.84. T2 mapping results suggest that the tissue composition of the ACL after repair is similar to that of a native ACL after surgery, whereas the ACL exhibits an increased width. Fraying of the ACL can occur without having any impact on functional outcomes. T2* analysis revealed early degradation at the cartilage. MRI represents a noninvasive diagnostic tool for the morphological and compositional assessment of the anterior cruciate ligament after repair, whereas knowledge about post-surgical alterations is crucial for adequate imaging interpretation. • There has been renewed interest in repairing the anterior cruciate ligament with a proximally torn ligament. • T2 times of the anterior cruciate ligament do not differ between anterior cruciate ligament repair patients and controls. • T2 mapping may serve as a surrogate for the evaluation of the anterior cruciate ligament after repair.

Approaching expert-level accuracy for differentiating ACL tear types on MRI with deep learning

Treatment for anterior cruciate ligament (ACL) tears depends on the condition of the ligament. We aimed to identify different tear statuses from preoperative MRI using deep learning-based radiomics with sex and age. We reviewed 862 patients with preoperative MRI scans reflecting ACL status from Hunan Provincial People’s Hospital. Based on sagittal proton density-weighted images, a fully automated approach was developed that consisted of a deep learning model for segmenting ACL tissue (ACL-DNet) and a deep learning-based recognizer for ligament status classification (ACL-SNet). The efficacy of the proposed approach was evaluated by using the sensitivity, specificity and area under the receiver operating characteristic curve (AUC) and compared with that of a group of three orthopedists in the holdout test set. The ACL-DNet model yielded a Dice coefficient of 98% ± 6% on the MRI datasets. Our proposed classification model yielded a sensitivity of 97% and a specificity of 97%. In comparison, the sensitivity of alternative models ranged from 84 to 90%, while the specificity was between 86 and 92%. The AUC of the ACL-SNet model was 99%, demonstrating high overall diagnostic accuracy. The diagnostic performance of the clinical experts as reflected in the AUC was 96%, 92% and 88%, respectively. The fully automated model shows potential as a highly reliable and reproducible tool that allows orthopedists to noninvasively identify the ACL status and may aid in optimizing different techniques, such as ACL remnant preservation, for ACL reconstruction.

A new modified MR dual precision positioning of thin-slice oblique sagittal fat suppression proton density weighted imaging: its diagnostic accuracy in anterior cruciate ligament injury

To evaluate the diagnostic accuracy of a new modified MR dual precision positioning of thin-slice oblique sagittal fat suppression proton density-weighted imaging (DPP-TSO-Sag-FS-PDWI) sequence in detecting ACL injuries and its grades compared to standard sequences using arthroscopy as the standard reference. 42 patients enrolled in this retrospective study received the 1.5-T MRI with standard sequences and the new modified DPP-TSO-Sag-FS-PDWI sequence, and their arthroscopy results was recorded. The Mc Nemer-Bowker and weighted Kappa was performed to compare the consistency of MRI diagnosis with arthroscopic results. Finally, the diagnostic accuracy was calculated based on the true positive, true negative, false negative and false positive values. The diagnostic consistency of the DPP-TSO-Sag-FS-PDWI were higher than standard sequences for both reader 1 (K = 0.876 vs. 0.620) and reader 2 (K = 0.833 vs. 0.683) with good diagnostic repeatability (K = 0.794 vs. 0.598). Furthermore, the DPP-TSO-Sag-FS-PDWI can classify and diagnose three grades of ACL injury [the sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value were more than 84%], especially for grade II injury as the PPV was superior for reader 1 (92.3% vs. 53.9%) and reader 2 (84.6% vs. 69.2%). The new modified DPP-TSO-Sag-FS-PDWI sequence can display the ACL injury on one or continuous levels by maximizing the acquisition of complete ligament shape and true anatomical images, and excluding the influence of anatomical differences between individuals. It can improve the diagnostic accuracy with good repeatability and classify three grades of the ACL injury.

Evaluation of Refocus Flip Angle for Three-dimensional Proton Density-weighted Turbo Spin-echo Imaging in Cerebrovascular Black Blood MRA and Comparison with Three-dimensional Time-of-flight MRA

The three-dimensional time-of-flight (3D-TOF), which is currently the most common acquisition technique of intracranial magnetic resonance angiography (MRA), may result in poor branch visualization due to reduced blood flow velocity. Proton density-weighted volume isotropic turbo spin-echo acquisition (PDVISTA) is less susceptible to these factors and has been reported to be useful in assessing cerebral vasospasm after subarachnoid hemorrhage. In this study, we investigated the effect of refocus flip angle (RFA) for PDVISTA on the contrast between blood vessels and background brain tissue using flow velocity phantom and clinical images, assuming the usefulness of PDVISTA in daily clinical practice. The phantom experiments showed that the contrast ratio significantly improved with decreasing RFA; however, considering the signal-to-noise ratio, RFA 80° was determined as optimal for clinical use. Visual assessment was performed on PDVISTA (RFA 80°) and conventional 3D-TOF MRA clinical images, which suggested the superiority of PDVISTA over 3D-TOF in the delineation of peripheral branches of cerebral vessels. The results suggest that PDVISTA is useful not only for subarachnoid hemorrhage patients but also in daily clinical practice.

Appropriate intradeltoid muscle needle penetration depth in vaccine administration: an MRI study in Thailand.

The objective of this study was to evaluate the appropriate vaccination needle penetration depth into the deltoid muscle to avoid injection-site complications from an inappropriate injection depth and/or injection site in the Thai population. This was a retrospective study using axial proton density-weighted images of MRI shoulders at the level of 2 fingerbreadths below the acromion process to measure the combined thickness of the skin, subcutaneous fat pad and deltoid muscle to evaluate the percentage of injections into the deltoid muscle with various needle penetration depths. There were 509 MRI shoulder images of 222 males and 287 females (265 right shoulders and 244 left shoulders). The average body mass index and age were 24.54 ± 3.54 kg/m2 and 64.81 ± 10.20 years, respectively. Using a needle penetration depth of 12.7 mm (0.5 inches) achieved 100% of injections into the deltoid muscle. We recommend advancing the entire length of a 0.5-inch needle perpendicular to the skin at 2 fingerbreadths below the acromion process for adult intradeltoid vaccinations. This approach ensures optimal vaccine delivery and minimizes the risk of injection-related injuries.

Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning

To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagittal proton density-weighted images and to distinguish between three common types of knee synovitis. This retrospective study included 376 consecutive patients with pathologically confirmed knee synovitis (rheumatoid arthritis, gouty arthritis, and pigmented villonodular synovitis) from two institutions. A semantic segmentation model was trained on manually annotated sagittal proton density-weighted images. The segmentation results of the regions of interest and patients' sex and age were used to classify knee synovitis after feature processing. Classification by the DLmethod was compared tothe classification performed by radiologists. Data of the 376 patients (mean age, 42±15 years; 216 men) were separated into a training set (n=233), an internal test set (n=93), and an external test set (n=50). The automated segmentation model showed good performance (mean accuracy: 0.99 and 0.99 in the internal and external test sets). On the internal test set, the DL model performed better than the senior radiologist (accuracy: 0.86 vs. 0.79; area under the curve [AUC]: 0.83 vs. 0.79). On the external test set, the DL diagnostic model based on automatic segmentation performed as well or better than senior and junior radiologists (accuracy: 0.79 vs. 0.79 vs. 0.73; AUC: 0.76 vs. 0.77 vs. 0.70). DL models for segmentation of SCand IPFD can accurately classify knee synovitis and aid radiologic diagnosis.

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

Three-dimensional vessel wall imaging with 1.5-T MRI to visualize invisible occluded cerebral artery.

Endovascular thrombectomy (EVT) is performed for acute ischemic stroke (AIS) caused by large vessel occlusion; therefore, preoperative visualization of the occluded invisible vessel course reduces complications and ensures success. Three-dimensional (3D) proton density-weighted (PDW) vessel wall imaging (VWI) using variable refocusing flip angle pulse-turbo spin-echo sequences (VRFA-TSE) with 3.0-T magnetic resonance imaging (MRI) can provide this information. To assess the effectiveness of 3D PDW-VWI using 1.5-T MRI without VRFA function. Five consecutive patients with AIS caused by large vessel occlusion underwent EVT in our institute. VWI with 1.5-T MRI using 3D PDW-fast spin echo (FSE) technique was added to conventional brain imaging. PDW-FSE was successfully performed in all cases. 3D PDW-FSE was useful to visualize both the anterior and posterior circulations by clearly revealing invisible vessels but could not demonstrate the length and size of the clot in all five cases. 3D PDW-FSE with 1.5-T MRI without VRFA could clearly depict the course of the invisible occluded artery and might support favorable outcomes after EVT in patients with AIS.

Mask Region-Based Convolutional Neural Network segmentation of the humerus and scapula from proton density-weighted axial shoulder magnetic resonance images.

This study aimed to evaluate the effectiveness of Mask Region-Based Convolutional Neural Network (R-CNN) in humerus and scapula segmentation. The study included 665 axial proton density (PD)-weighted magnetic resonance images of 665 consecutive shoulder instability patients (412 males, 253 females; mean age: 27±5.2 years; range, 18 to 42 years) between January 2011 and December 2014. Mask R-CNN was used to automatically segment humerus and scapula regions simultaneously. Segmentation success of Mask R-CNN was compared to the manual segmentation results of an orthopedic surgeon. Statistical evaluation was done with the Dice coefficient and the mean average precision) score. According to the humeral head structure three groups were generated: the healthy humeral head group, the edematous humeral head group, and the Hill-Sachs group (humeral heads with Hill-Sachs lesions). In the test images, 81 humeral heads were healthy, 100 were edematous, and 38 had a Hill-Sachs lesion. According to the Dice metric, the overall success rate of Mask R-CNN configuration was 96.47 and 93.87% for the segmentation of the humeral head and scapula, respectively, and 95.86 and 92.35% for an intersection over union of 0.5 according to the mean average precision. According to the Dice metric, the segmentation success of the humerus and scapula of the healthy group was 94.58 and 97.42%, the segmentation success of the edematous humerus group was 93.56 and 96.53%, and the segmentation success of the Hill-Sachs group was 93.47 to 95.48%. The segmentation success of scapula in the case of discontinuity was 92.86% according to Dice metric. Mask R-CNN-based humerus and scapula segmentation provided promising results compared to manual segmentation of an expert. Mask R-CNN overcomes the problem of discontinuous edges and Rician noise in axial PD-weighted shoulder magnetic resonance imaging.

Quantitative study of supraspinatus tendon injury grading based on synthetic magnetic resonance imaging

Objective: To investigate the diagnostic value of quantitative parameters of synthetic magnetic resonance imaging (SyMRI) in the grade of supraspinatus tendon injury. Methods: Ninety-seven patients with clinical definite of supraspinatus tendon injury from July 2021 to July 2022 in General Hospital of Ningxia Medical University were prospectively collected (case group), including 54 males and 43 females, with an age of 29 to 56 (37.4±9.6) years. According to the results of shoulder arthroscopy, the case group were divided into three subgroups included tendinopathy group (37 cases, grade Ⅱ), partial tear group (34 cases, grade Ⅲ) and complete tear group (26 cases, grade Ⅳ). During the same period, 28 normal rotator cuff volunteers without supraspinatus tendon injury were recruited (control group), including 16 males and 12 females, aged 23 to 49 (36.1±7.2) years, and marked as grade Ⅰ. All the subjects underwent MRI scan of articulatio humeri included T1-weighted imaging(T1WI) fast spin echo(FSE) sequences in axial view, T2-weighted imaging(T2WI) fat suppression(FS) sequences in axial view, T2WI FS sequences in oblique coronal view, proton density-weighted (PDW) imaging in oblique sagittal view and SyMRI in oblique coronal view. The supraspinatus tendon was divided into lateral, medial and middle subregions according to its shape in oblique coronal T2WI view, two radiologists measured the T1, T2 and PD values of the supraspinatus tendon. The interclass correlation coefficient (ICC) were used to compare the consistency between and within observers. One-way analysis of variance or Kruskal-Wallis H test were used to compare the differences of quantitative parameters in different grades, the multivariate logistic regression model was used to analyze the risk factors of supraspinatus tendon injury grade, and the receiver operating characteristic (ROC) curves and area under curve (AUC) was drawn and calculated to evaluate the diagnostic efficacy. The Spearman correlation was used to analyze the correlation between the quantitative values and grades of supraspinatus tendon injury. Results: The ICC values of T1, T2 and PD values for the three subregions of the supraspinatus tendon were greater than 0. 700. The differences of T1 values in the lateral subregion, T2 values in the lateral and middle subregions were statistically significant in the overall comparison across different grades (all P<0. 001).The differences of T1 values in the middle and medial subregions, T2 values in the medial subregion and PD values in the lateral, middle and medial subregions were not statistically significant in the overall comparison of different grades (all P>0. 05). Multiple logistic regression model analysis showed that T2 values in the lateral and middle subregions were related factors for the grade of supraspinatus tendon injury[ OR (95%CI):1.123 (1.037-1.216), 0.122 (1.151-1.197);all P<0.001 ]. The AUC of the T2 values in lateral subregion diagnosing grade Ⅰ vs grade Ⅳ, grade Ⅱ vs grade Ⅳ and grade Ⅲ vs grade Ⅳ were 0.891(95%CI: 0.801-0.981), 0.797(95%CI: 0.680-0.914), 0.723(95%CI: 0.594-0.853) (all P<0.001), and the AUC of the T2 values in middle subregion diagnosing grade Ⅰ vs Ⅳ, grade Ⅱ vs Ⅳ, grade Ⅱ vs Ⅲ, and grade Ⅰ vs Ⅲ were 0.946 (95%CI: 0.849-0.989), 0.886 (95%CI: 0.809-0.962), 0.746 (95%CI: 0.631-0.861), 0.843 (95%CI: 0.745-0.941)(all P<0.001). The T2 values in the lateral and middle subregions were positively correlated with the grade of supraspinatus tendon injury (r=0.542, 0.615; both P<0.001), while T1 values and T2 values in the medial subregions were not significantly correlated with the grade of supraspinatus tendon injury (both P>0.05). Conclusion: SyMRI has high clinical application value in the grading of supraspinatus tendon injury, especially T2 value can be used as an effective quantitative parameter for the grading of supraspinatus tendon injury.

In vivo MRI is sensitive to remyelination in a nonhuman primate model of multiple sclerosis.

Remyelination is crucial to recover from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral inflammatory demyelinating lesions, we investigated whether MRI is sensitive to, and can characterize, remyelination. In six animals followed with multisequence 7 T MRI, 31 focal lesions, predicted to be demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in four of six marmosets and 45% of lesions. Radiological-pathological comparison showed that MRI had high statistical sensitivity (100%) and specificity (90%) for detecting remyelination. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents.

Impact of Vasodilation on Oxygen-Enhanced Functional Lung MRI at 0.55 T.

Oxygen-enhanced magnetic resonance imaging (OE-MRI) can be used to assess regional lung function without ionizing radiation. Inhaled oxygen acts as a T1-shortening contrast agent to increase signal in T1-weighted (T1w) images. However, increase in proton density from pulmonary hyperoxic vasodilation may also contribute to the measured signal enhancement. Our aim was to quantify the relative contributions of the T1-shortening and vasodilatory effects of oxygen to signal enhancement in OE-MRI in both swine and healthy volunteers. We imaged 14 anesthetized female swine (47 ± 8 kg) using a prototype 0.55 T high-performance MRI system while experimentally manipulating oxygenation and blood volume independently through oxygen titration, partial occlusion of the vena cava for volume reduction, and infusion of colloid fluid (6% hydroxyethyl starch) for volume increase. Ten healthy volunteers were imaged before, during, and after hyperoxia. Two proton density-weighted (PDw) and 2 T1w ultrashort echo time images were acquired per experimental state. The median PDw and T1w percent signal enhancement (PSE), compared with baseline room air, was calculated after image registration and correction for lung volume changes. Differences in median PSE were compared using Wilcoxon signed rank test. The PSE in PDw images after 100% oxygen was similar in swine (1.66% ± 1.41%, P = 0.01) and in healthy volunteers (1.99% ± 1.79%, P = 0.02), indicating that oxygen-induced pulmonary vasodilation causes ~2% lung proton density increase. The PSE in T1w images after 100% oxygen was also similar (swine, 9.20% ± 1.68%, P < 0.001; healthy volunteers, 10.10% ± 3.05%, P < 0.001). The PSE in T1w enhancement was oxygen dose-dependent in anesthetized swine, and we measured a dose-dependent PDw image signal increase from infused fluids. The contribution of oxygen-induced vasodilation to T1w OE-MRI signal was measurable using PDw imaging and was found to be ~2% in both anesthetized swine and in healthy volunteers. This finding may have implications for patients with regional or global hypoxia or vascular dysfunction undergoing OE-MRI and suggest that PDw imaging may be useful to account for oxygen-induced vasodilation in OE-MRI.

Distribution of intraperitoneally administered deuterium-labeled water in aquaporin-4-knockout mouse brain after middle cerebral artery occlusion.

As the movement of water in the brain is known to be involved in neural activity and various brain pathologies, the ability to assess water dynamics in the brain will be important for the understanding of brain function and the diagnosis and treatment of brain diseases. Aquaporin-4 (AQP4) is a membrane channel protein that is highly expressed in brain astrocytes and is important for the movement of water molecules in the brain. In this study, we investigated the contribution of AQP4 to brain water dynamics by administering deuterium-labeled water (D2O) intraperitoneally to wild-type and AQP4 knockout (AQP4-ko) mice that had undergone surgical occlusion of the middle cerebral artery (MCA). Water dynamics in the infarct region and on either side of the anterior cerebral artery (ACA) was monitored with proton-density-weighted imaging (PDWI) performed on a 7T animal MRI. D2O caused a negative signal change quickly after administration. The AQP4-ko mice showed a delay of the time-to-minimum in both the contralateral and ipsilateral ACA regions compared to wild-type mice. Also, only the AQP4- ko mice showed a delay of the time-to-minimum in the ipsilateral ACA region compared to the contralateral side. In only the wild-type mice, the signal minimum in the ipsilateral ACA region was higher than that in the contralateral ACA region. In the infarct region, the signal attenuation was slower for the AQP4-ko mice in comparison to the wild-type mice. These results suggest that AQP4 loss affects water dynamics in the ACA region not only in the infarct region. Dynamic PDWI after D2O administration may be a useful tool for showing the effects of AQP4 in vivo.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging Findings of Infrapatellar Fat Pad Signal Abnormalities: Comparison Between Symptomatic and Asymptomatic Knee Osteoarthritis

Infrapatellar fat pad (IPFP) proton density-weighted images (PdWI) hyperintense regions on MRI are an important imaging feature of knee osteoarthritis (KOA) and are thought to represent inflammation which may induce knee pain. The aim of the study was to compare the intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) findings of PdWI hyperintense regions of IPFP between symptomatic and asymptomatic KOA and to determine whether IVIM-DWI parameters can be used as an objective biomarker for symptomatic KOA. In total, 84 patients with symptomatic KOA, 43 asymptomatic KOA persons, and 30 healthy controls with MRI were retrospectively reviewed. Demographic, IPFP-synovitis, Western Ontario and McMaster Osteoarthritis Index (WOMAC) pain sub-score, IPFP volume and depth and quantitative parameters of IVIM-DWI were collected. The chi-square test, Binary logistic regression and receiver operating characteristic curve (ROC) analysis were used for diagnostic performance comparison. The IPFP volume and depth were statistically significant differences between the non-KOA and sKOA groups (p<0.05). The IPFP PdWI hyperintense regions demonstrated significantly higher values of D and D* in the symptomatic KOA compared to those in the asymptomatic KOA (1.51±0.47 vs. 1.73±0.40 for D and 19.24±6.44 vs. 27.09±9.75 for D*) (both p<0.05). Multivariate logistic regression analyses showed that Higher D and D* values of IPFP hyperintense region were significantly associated with higher risks of knee pain (OR: 1.97; 95% CI: 1.21-3.19; p=0.006 for D and OR: 1.24; 95% CI: 1.09-1.41; p=0.001 for D*). Sensitivity and specificity of D value for symptomatic KOA were 80.28% and 83.33%, with an AUC of 0.78 (0.68-0.86). D* value had the sensitivity with 92.96% and a specificity of 58.33%, with an AUC of 0.82 (0.73-0.89) for symptomatic KOA. IVIM-DWI can be used as an additional functional imaging technique to study IPFP with signal abnormalities on PdWI, and the D and D* values may have potential value to predict the symptom in mild-to-moderate KOA patients.

Evaluation of condylar osseous changes using a wireless detector with proton density–weighted imaging sequences

Cone-beam computed tomography (CBCT) is the gold standard for evaluating condylar osseous changes. However, the radiation risk and low soft-tissue resolution of CBCT make it unsuitable for evaluating soft tissue such as the articular disc and lateral pterygoid muscle. This study aimed to qualitatively and quantitatively evaluate the feasibility and advantages of using wireless detectors (WD) with proton density-weighted imaging (PDWI) sequences to image condyle changes in patients with temporomandibular disorders (TMD). This study involved 20 patients (male =8, female =12; mean age 31.65 years, SD 12.68 years) with TMD. All participants underwent a closed oblique sagittal PDWI scan with head/neck coupling coiling (HNCC) and wireless detector-HNCC (WD-HNCC) on a 3.0 T magnetic resonance imaging (MRI) scanner. Subsequently, the changes in the condyle bones in the scanned images for the 2 image types were scored subjectively and compared qualitatively. The contrast-to-noise ratio (CNR) of the 2 types of scanned images was compared quantitatively. The comparison of CNR differences between the 2 types of images was performed using the paired t-test. The kappa statistic was used to test the consistency of quantitative analyses of MRI images between observers. The subjective scores of condylar osseous changes in the 2 types of images were compared by paired rank-sum test. A P value <0.05 was considered statistically significant. A total of 40 condyles from 20 patients were scanned. Among them, 8 condyles showed no bone changes, and the other 32 condyles demonstrated condylar osseous changes of varying degrees and nature. These 32 condyles were used in the subsequent analysis. As compared to images acquired by HNCC in the PDWI sequence, the WD-HNCC images more clearly showed mandibular osteophyte, bone cortical erosion, subcortical cystic focus, and bone cortical hyperplasia and thickening. In addition, the WD-HNCC was demonstrated to improve image CNR by 158.9% compared to HNCC (28.17±16.01 vs. 10.88±6.53; t=8.63; P=0.001). WD-HNCC in PDWI sequences is suitable for imaging the condylar bone changes of patients with TMD and significantly improves the image quality.