Voxel-based Relaxometry Research Articles

Association of cartilage [formula omitted] and [formula omitted] relaxation time measurement with hip osteoarthritis progression: A 5-year longitudinal study using voxel-based relaxometry and Z-score normalization

ObjectiveTo study the longitudinal changes of cartilage T1ρ and T2 relaxation time measurements in hip-OA patients. MethodsA calibration study compared two scanner data, Scanner-1 (GE Discovery MR750 3.0T) with unilateral acquisition protocol and Scanner-2 (GE Signa Premier 3.0T) with bilateral acquisition protocol, using nine subjects(average age ​= ​40.33 ​± ​13.53 years, 5 females), including one hip-OA subject. Quantified parameters from the Scanner-2 were adjusted using voxel-based relaxometry(VBR) and Z-score normalization to reduce the inter-scanner variability. Eighteen hip-OA Subjects (age ​= ​53.11 ​± ​14.96 years, 12 females) were recruited to the longitudinal variability study from 2016, comprising five assessments at 1-year intervals. Baseline to 3rd-year data used unilateral acquisition with Scanner-1, while 4th-year data used bilateral acquisition with Scanner-2. A linear mixed-effects model(LME) assessed trajectory analyses, with acquisition year, age, sex, body mass index(BMI), and Kellgren-Lawrence(KL) score as predictor variables and cartilage mean T1ρ and T2 values as outcomes. ResultsVBR analysis after Z-score normalization showed that only a few of the whole cartilage voxels had significant differences in T1ρ(femur-2.36 ​% and acetabular-3.23 ​%) and T2 (femur-2.30 ​% and acetabular-2.94 ​%) values between the scanners. The LME analysis showed that the BMI predictor variable was significantly correlated with the femur T1ρ (p ​< ​0.0001) and T2 (p ​< ​0.0001) and acetabular T1ρ (p ​< ​0.0001) and T2 (p ​< ​0.0001) cartilage region. ConclusionThe calibration study demonstrated the effectiveness of VBR and Z-score normalization in reducing inter-scanner variability. The longitudinal study revealed a significant correlation between T1ρ and T2 values of the cartilage and BMI; also the T1ρ and T2 values increased over time in some of the cartilage subregions.

Baseline cartilage T1ρ and T2 predicted patellofemoral joint cartilage lesion progression and patient-reported outcomes after ACL reconstruction.

This study aims to determine if baseline T1ρ and T2 will predict cartilage morphological lesion progression in the patellofemoral joint (PFJ) and patient-reported outcomes at 2-year after anterior cruciate ligament (ACL) reconstruction (ACLR). Thirty-nine ACL-injured patients were studied at baseline and two-year after ACLR. 3 T MR T1ρ and T2 images and Knee Injury and Osteoarthritis Outcome Score (KOOS) were acquired at both time points. Voxel-based relaxometry (VBR) technique was used to detect local cartilage abnormalities. Patients were divided into progression and non-progression groups based on changes of the whole-organ magnetic resonance imaging scoring (WORMS) grading of cartilage in PFJ from baseline to 2-year, and into lower (more pain) and higher (less pain) KOOS pain groups based on 2-year KOOS pain scores, separately. Voxel-based analyses of covariance were used to compare T1ρ and T2 values at baseline between the defined groups. Using VBR analysis, the progression group at 2-year showed higher T1ρ and T2 compared with the non-progression group at baseline, with the medial femoral condyle showing the largest areas with significant differences. At two-year, 56% of patients were able to recover with respect to KOOS pain. The lower KOOS pain group at 2-year showed significantly elevated T1ρ and T2 in the patella at baseline compared with the higher KOOS pain group. In conclusion, baseline T1ρ and T2 mapping, combined with VBR analysis, may help identify ACLR patients at high risk of developing progressive PFJ cartilage lesions and worse clinical symptoms 2-year after surgery.

Automatic hip abductor muscle fat fraction estimation and association with early OA cartilage degeneration biomarkers.

The aim of this study was to develop an automatic segmentation method for hip abductor muscles and find their fat fraction associations with early stage hip osteoarthritis (OA) cartilage degeneration biomarkers. This Institutional Review Board approved, Health Insurance Portability and Accountability Act compliant prospective study recruited 61 patients with evidence of hip OA or Femoroacetabular Impingement (FAI). Magnetic resonance (MR) images were acquired for cartilage segmentation, T1ρ and T2 relaxation times computation and grading of cartilage lesion scores. A 3D V-Net (Dice loss, Adam optimizer, learning rate = 1e-4 , batch size = 3) was trained to segment the three muscles (gluteus medius, gluteus minimus, and tensor fascia latae). The V-Net performance was measured using Dice, distance maps between manual and automatic masks, and Bland-Altman plots of the fat fractions and volumes. Associations between muscle fat fraction and T1ρ , T2 relaxation times values were found using voxel based relaxometry (VBR). A p < 0.05 was considered significant. The V-Net had a Dice of 0.90, 0.88, and 0.91 (GMed, GMin, and TFL). The VBR results found associations of fat fraction of all three muscles in early stage OA and FAI patients with T1ρ , T2 relaxation times. Using an automatic, validated segmentation model, the associations derived between OA biomarkers and muscle fat fractions provide insight into early changes that occur in OA, and show that hip abductor muscle fat is associated with markers of cartilage degeneration.

Multiparametric MRI characterization of knee articular cartilage and subchondral bone shape in collegiate basketball players.

Magnetic resonance imaging (MRI) is commonly used to evaluate the morphology of the knee in athletes with high‐knee impact; however, complex repeated loading of the joint can lead to biochemical and structural degeneration that occurs before visible morphological changes. In this study, we utilized multiparametric quantitative MRI to compare morphology and composition of articular cartilage and subchondral bone shape between young athletes with high‐knee impact (basketball players; n = 40) and non‐knee impact (swimmers; n = 25). We implemented voxel‐based relaxometry to register all cases to a single reference space and performed a localized compositional analysis of T 1ρ‐ and T 2‐relaxation times on a voxel‐by‐voxel basis. Additionally, statistical shape modeling was employed to extract differences in subchondral bone shape between the two groups. Evaluation of cartilage composition demonstrated a significant prolongation of relaxation times in the medial femoral and tibial compartments and in the posterolateral femur of basketball players in comparison to relaxation times in the same cartilage compartments of swimmers. The compositional analysis also showed depth‐dependent differences with prolongation of the superficial layer in basketball players. For subchondral bone shape, three total modes were found to be significantly different between groups and related to the relative sizes of the tibial plateaus, intercondylar eminences, and the curvature and concavity of the patellar lateral facet. In summary, this study identified several characteristics associated with a high‐knee impact which may expand our understanding of local degenerative patterns in this population.

Patellar Malalignment Is Associated With Patellofemoral Lesions and Cartilage Relaxation Times After Hamstring Autograft Anterior Cruciate Ligament Reconstruction

Background: There is growing evidence suggesting a link between patellofemoral joint (PFJ) osteoarthritis in anterior cruciate ligament (ACL)–reconstructed knees and altered joint alignment. Purpose: To determine whether patellar alignment differs between participants with and without ACL reconstruction (ACLR) and to identify possible associations between patellar alignment and PFJ osteoarthritis features over 3 years. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 37 participants with ACLR (sex, 23 male; mean ± SD age, 28.1 ± 7.4 years) and 20 healthy controls (13 male; 30.4 ± 4.8 years) participated. Patients underwent magnetic resonance imaging: (1) sagittal T2-weighted fat-saturated fast spin echo images to calculate patellar alignment, (2) sagittal 3-dimensional intermediate-weighted fast spin echo Cube sequence for clinical morphological grading (modified Whole-Organ Magnetic Resonance Imaging Score [WORMS]), and (3) sagittal combined T1ρ/T2 mapping sequence for performing voxel-based relaxometry. Patellar alignment of the ACLR knees were assessed at 6 months (baseline). One-way analysis of variance was used to compare patellar alignment among the ACLR (at 6 months), contralateral, and control knees. Within the ACLR group, a logistic regression model was used to identify if patellar alignment measures at baseline were risk factors for worsening of PFJ structural changes over 3 years. Statistical parametric mapping was used to evaluate the longitudinal associations between patellar alignment and cartilage relaxation times at 3 years. Results: When compared with control knees, ACLR knees exhibited a laterally and anteriorly displaced patella (P = .045 and P = .041), less flexion (P = .031), and less lateral spin (P = .012). Furthermore, excessive lateral displacement was a significant predictor of worsening of WORMS (P = .050). Lateral displacement was positively correlated with increased T1ρ and T2 in the patellar and trochlear cartilage at 3 years. Patellar lateral spin revealed similar negative findings. Conclusion: Participants with ACLR exhibited a laterally and anteriorly displaced patella, less flexion, and less lateral spin when compared with healthy controls. Excessive patellar lateral displacement was the strongest predictor to the development of PFJ osteoarthritis features longitudinally.

Altered tibiofemoral position following ACL reconstruction is associated with cartilage matrix changes: A voxel-based relaxometry analysis.

The purpose of this study was to analyze the relationship between postsurgical tibial translation (TT) and tibial rotation (TR) with cartilage matrix changes using quantitative magnetic resonance imaging, specifically voxel-based relaxometry with T1ρ and T2 mapping sequences. Knee magnetic resonance imaging's (MRI's) of 51 patients with unilateral anterior cruciate ligament injury, no concomitant ligamentous injury, history of osteoarthritis (OA), and previous knee surgery were scanned prior to surgery. Thirty-four patients completed follow-up MRI scans at 6-month, 1- and 2-year post-reconstruction and were included in this study. Knee biomechanics, T1ρ, and T2 were calculated using an in-house Matlab program. Compared to the contralateral knee, the injured knee demonstrated significantly increased anterior TT at baseline (P < .001), 6-month (P < .001), 1- (P = .001), and 2-year (P < .001). Furthermore, patients were divided into groups based on TT at 6-month. When compared to patients with normal TT, those with increased anterior TT at 6-month displayed significantly longer T1ρ and T2 relaxation times in 10.4% and 7.4% of the voxels in the injured medial tibia at 1-year, respectively, as well as 12.4% and 9.8% of the voxels in the injured medial tibia at 2-year, respectively. Our results demonstrate an association between abnormal tibiofemoral position and early degradative changes to the articular cartilage matrix of the injured knee. Clinical significance: These findings suggest that altered tibiofemoral position following ACL reconstruction is associated with early degeneration of knee cartilage. Future prospective studies employing longer follow-up times are warranted to evaluate the relationship between abnormal tibiofemoral position and the early onset of posttraumatic OA.

Lumbar intervertebral disc characterization through quantitative MRI analysis: An automatic voxel-based relaxometry approach.

PurposeTo develop an automated pipeline based on convolutional neural networks to segment lumbar intervertebral discs and characterize their biochemical composition using voxel‐based relaxometry, and establish local associations with clinical measures of disability, muscle changes, and other symptoms of lower back pain.MethodsThis work proposes a new methodology using MRI (n = 31, across the spectrum of disc degeneration) that combines deep learning–based segmentation, atlas‐based registration, and statistical parametric mapping for voxel‐based analysis of T1ρ and T2 relaxation time maps to characterize disc degeneration and its associated disability.ResultsAcross degenerative grades, the segmentation algorithm produced accurate, high‐confidence segmentations of the lumbar discs in two independent data sets. Manually and automatically extracted mean disc T1ρ and T2 relaxation times were in high agreement for all discs with minimal bias. On a voxel‐by‐voxel basis, imaging‐based degenerative grades were strongly negatively correlated with T1ρ and T2, particularly in the nucleus. Stratifying patients by disability grades revealed significant differences in the relaxation maps between minimal/moderate versus severe disability: The average T1ρ relaxation maps from the minimal/moderate disability group showed clear annulus nucleus distinction with a visible midline, whereas the severe disability group had lower average T1ρ values with a homogeneous distribution.ConclusionThis work presented a scalable pipeline for fast, automated assessment of disc relaxation times, and voxel‐based relaxometry that overcomes limitations of current region of interest–based analysis methods and may enable greater insights and associations between disc degeneration, disability, and lower back pain.

Six-month post-surgical elevations in cartilage T1rho relaxation times are associated with functional performance 2 years after ACL reconstruction.

The current study looks to: (i) investigate postural stability following anterior cruciate ligament (ACL) reconstruction, as assessed by Y-Balance Test, by comparing single-leg balance of the injured limb against those of controls and the uninjured limb; (ii) analyze the relationship between postural stability symmetry with localized cartilage matrix changes and the Knee Injury and Osteoarthritis Outcome Score (KOOS). Bilateral knee MRI of 36 patients who underwent ACL reconstruction were performed before surgery, 6 months, 1 year, and 2 years, postoperatively. Postural stability was evaluated based on Y-Balance Test at 1 and 2 years. ACL patients were also split into three groups based on postural stability symmetry at 2 years and symmetry thresholds associated with elevated risks of lower extremity injury. Voxel-based relaxometry employing analysis of covariance was used to analyze localized differences in cartilage composition at all time-points (using quantitative magnetic resonance [MR] T1ρ and T2 mapping) between the three groups. The ACL patients displayed no significant deficits in postural stability. Compared with symmetric patients, those with asymmetric postural stability at 2 years had significantly prolonged cartilage T1ρ-indicating deterioration of the cartilage matrix-specifically in the injured knee's medial tibia as early as 6-month post-reconstruction. Prolonged T1ρ in asymmetric patients persisted up to 2 years, where the group also reported worse KOOS. Our results demonstrate an association between early stages of cartilage matrix deterioration and postural stability symmetry that may manifest in elevated lower extremity injury risk and worse patient-reported outcomes. Quantitative MR, in combination with local analysis performed with voxel-based relaxometry, is a tool to further study this relationship. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:1132-1140, 2020.

Extracting Voxel-Based Cartilage Relaxometry Features in Hip Osteoarthritis Subjects Using Principal Component Analysis.

MRI-based relaxation time measurements provide quantitative assessment of cartilage biochemistry. Identifying distinctive relaxometry features in hip osteoarthritis (OA) might provide important information on regional disease variability. First, to incorporate fully automatic voxel-based relaxometry (VBR) with principal component analysis (PCA) to extract distinctive relaxometry features in subjects with radiographic hip OA and nondiseased controls. Second, to use the identified features to further distinguish subjects with cartilage compositional abnormalities. Cross-sectional. Thirty-three subjects with radiographic hip OA (20 males; age, 50.2 ± 13.3 years) and 55 controls participated (28 males; 41.3 ± 12.0 years). A 3.0T scanner using 3D SPGR, combined T1ρ /T2 , and fast spin echo sequences. Pelvic radiographs, patients' self-reported symptoms, physical function, and cartilage morphology were analyzed. Cartilage relaxation times were quantified using traditional regions of interest and VBR approaches. PCA was performed on VBR data to identify distinctive relaxometry features, and were subsequently used to identify a subgroup of subjects from the controls that exhibited compositional abnormalities. Chi-square and independent t-tests were used to compare group characteristics. Logistic regression models were used to identify the possible principal components (PCs) that were able to predict OA vs. control classification. In T1ρ assessment, OA subjects demonstrated higher T1ρ values in the posterior hip region and deep cartilage layer when compared with controls (P = 0.012 and 0.001, respectively). In T2 assessment, OA subjects exhibited higher T2 values in the posterior hip region (P < 0.001). Based on the PC score classification, 16 subjects without radiographic evidence of OA demonstrated relaxometry patterns similar to OA subjects, and exhibited worse physical function (P = 0.003) and cartilage lesions (P = 0.009-0.032) when compared with the remaining controls. The study identified distinctive cartilage relaxometry features that were able to discriminate subjects with and without radiographic hip OA effectively. 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1708-1719.

Diagnosing osteoarthritis from T2 maps using deep learning: an analysis of the entire Osteoarthritis Initiative baseline cohort

We aim to study to what extent conventional and deep-learning-based T2 relaxometry patterns are able to distinguish between knees with and without radiographic osteoarthritis (OA). T2 relaxation time maps were analyzed for 4,384 subjects from the baseline Osteoarthritis Initiative (OAI) Dataset. Voxel Based Relaxometry (VBR) was used for automatic quantification and voxel-based analysis of the differences in T2 between subjects with and without radiographic OA. A Densely Connected Convolutional Neural Network (DenseNet) was trained to diagnose OA from T2 data. For comparison, more classical feature extraction techniques and shallow classifiers were used to benchmark the performance of our algorithm's results. Deep and shallow models were evaluated with and without the inclusion of risk factors. Sensitivity and Specificity values and McNemar test were used to compare the performance of the different classifiers. The best shallow model was obtained when the first ten Principal Components, demographics and pain score were included as features (AUC=77.77%, Sensitivity=67.01%, Specificity=71.79%). In comparison, DenseNet trained on raw T2 data obtained AUC=83.44%, Sensitivity=76.99%, Specificity=77.94%. McNemar test on two misclassified proportions form the shallow and deep model showed that the boost in performance was statistically significant (McNemar's chi-squared=10.33, degree of freedom (DF)=1, P-value=0.0013). In this study, we presented a Magnetic Resonance Imaging (MRI)-based data-driven platform using T2 measurements to characterize radiographic OA. Our results showed that feature learning from T2 maps has potential in uncovering information that can potentially better diagnose OA than simple averages or linear patterns decomposition.

Local associations between knee cartilage T1ρ and T2 relaxation times and patellofemoral joint stress during walking: A voxel-based relaxometry analysis

BackgroundThis study aimed to utilize voxel-based relaxometry (VBR) to examine local correlations between patellofemoral joint (PFJ) stress during gait and PFJ cartilage relaxation times. MethodsEighty-three subjects with and without PFJ osteoarthritis (OA) underwent knee magnetic resonance (MR) images using fast spin-echo, T1ρ and T2 relaxation time sequences. Patellar and trochlear cartilage relaxation times were computed for each voxel. Peak PFJ stress was computed during the stance phase from three-dimensional gait analysis. Statistical Parametric Mapping was used to perform VBR analyses. Pearson partial correlations were used to evaluate the associations between peak PFJ stress and cartilage relaxation times while controlling for age, sex, and body mass index. ResultsA higher percentage of the trochlear cartilage (15.9–29.1%) showed significant positive correlations between PFJ stress and T1ρ and T2 than the patellar cartilage (7.4–13.6%). Average correlation coefficient (R) of the voxels showing significant positive correlations ranged from 0.27 to 0.29. Subcompartment analysis revealed a higher percentage of lateral compartment cartilage (trochlea: 30.2–34.7%, patella: 8.1–14.8%) showed significant correlations between peak PFJ stress and T1ρ and T2 than the medial compartment cartilage (trochlea: 7.1–27.2%, patella: 5.5–5.9%). Subgroup analysis showed that larger percentages of PFJ cartilage demonstrated significant positive correlations with PFJ stress in subjects with PFJ OA than those without PFJ OA. ConclusionsThe findings of this study suggest that peak PFJ stress has a greater influence on the biochemical composition of the trochlear than the patellar cartilage, and the lateral than the medial PFJ compartment.

3D Correlation Mapping between Changes in Cartilage T1ρ and Thickness Over 1-year after ACL Reconstruction using Atlas-based Methods

Purpose: Subjects with anterior cruciate ligament (ACL) injury are at risk for post-traumatic osteoarthritis (PTOA). T1ρ MRI has been used to detect early degeneration after ACL injury and reconstruction. Previous studies also revealed significant changes in cartilage thickness after ACL injury, with thickness increasing in some compartments while decreasing in other compartments. However, the correlation between the change in T1ρ and the change in cartilage thickness has not been demonstrated. A better understanding of these correlations will help with staging the cartilage degeneration status after ACL injury. Very recently, a novel atlas-based method was developed which permits voxel-based relaxometry analysis (VBR). The goal of this study was to apply the atlas-based method to evaluate the local voxel-by-voxel correlation between changes in T1ρ and changes in thickness from baseline to 6-months and 1-year after ACL reconstruction (ACLR). Methods: Bilateral knees were scanned using a 3T MRI scanner for twenty-five patients with ACL injuries prior to surgical reconstruction (baseline, BL), and 6-months (6M) and 1-year (1Y) after ACLR (age = 28.4 ± 8.2 years, BMI = 23.8± 2.7 kg/m2, 10 female). The imaging protocol included the 3D MAPSS T1ρ/T2 sequence used for cartilage relaxation times quantification and high-resolution 3D FSE (CUBE) used for WORMS grading and semi-automatic cartilage segmentation. Those segmentations were used to define a voxel based thickness map for each subject. An atlas based registration approach was then used to morph all the T1ρ-weighted images and the thickness maps to the same reference space, and T1ρ maps were computed in the atlas space allowing for voxel-by-voxel correspondence between T1ρ and thickness. Longitudinal changes in cartilage thickness and T1ρ, as well as the local Pearson correlation coefficients between changes in T1ρ and changes in thickness were calculated voxel-by-voxel. Both analyses were adjusted for age, gender and BMI. The level of significance was set at p<0.05. Percentage of significant voxel (PSV, %) with positive or negative correlation and the mean value of correlation coefficients (R) were calculated in each compartment. Results: Significant increases of T1ρ in MFC and trochlea, and significant decreases of T1ρ in patella were observed; while significant increases of cartilage thickness in patella and significant decreases of cartilage thickness in trochlea were observed (Fig. 1 A–B). The most significant correlation between changes in T1ρ and changes in thickness was observed in patella, LFC, trochlea and MFC (Fig. 1C). In the patella, significant negative correlation was found between changes in T1ρ and changes in thickness from BL to 6M (38.4% voxels, R=−0.536) and from BL to 1Y (15.1% voxels, R=−0.590) (Tab1). This correlation was primarily the result of a decrease in T1ρ and an increase in thickness, while in other compartments, the negative correlations primarily resulted from an increase in T1ρ and a decrease in thickness. From 6M to 1Y, in LFC, a large decrease of the positive correlation PSV (from 11.2% to 2.5%) and a slight increase of negative correlation PSV were observed. There is an increasing trend of the total cartilage WORMS scores from BL (2.0±2.1) to 6M (2.2±2.1) and 1Y (2.4±2.3), but the increase was not significant. Conclusions: In this study, the local correlation between changes in cartilage matrix composition and changes in cartilage thickness was analyzed voxel-by-voxel using a novel 3D atlas-based method. Significant correlations were observed between ΔT1ρ and ΔΤhickness from BL to 6M and 1Y after ACLR. A positive correlation with increase in T1ρ and thickness may suggest the cartilage is at very early stages of degeneration with tissue swelling; while a negative correlation with increase in T1ρ and decrease in thickness may suggest later stages that cartilage begins to experience tissue loss. From 6M to 1Y, there is a general trend of decreasing positive correlation percentage while an increasing negative correlation percentage (Figure 2) in the femoral condyles and trochlea, suggests a progression of cartilage degeneration, confirmed by change in WORMS. In patella, the negative correlation was driven by the decrease of T1ρ and increase of thickness, which may be associated with changes in loading to patella-femoral joint (PFJ) as well as changes in activities after ACLR. Longer follow-up analysis is warranted to better understand cartilage degeneration progression after ACL injury. Funding from NIH/NIAMS P50 AR060752.

Principal component analysis-T1ρ voxel based relaxometry of the articular cartilage: a comparison of biochemical patterns in osteoarthritis and anterior cruciate ligament subjects

Quantitative MR, including T1ρ mapping, has been extensively used to probe early biochemical changes in knee articular cartilage of subjects with osteoarthritis (OA) and others at risk for cartilage degeneration, such as those with anterior cruciate ligament (ACL) injury and reconstruction. However, limited studies have been performed aimed to assess the spatial location and patterns of T1ρ. In this study we used a novel voxel-based relaxometry (VBR) technique coupled with principal component analysis (PCA) to extract relevant features so as to describe regional patterns and to investigate their similarities and differences in T1ρ maps in subjects with OA and subjects six months after ACL reconstruction (ACLR). T1ρ quantitative MRI images were collected for 180 subjects from two separate cohorts. The OA cohort included 93 osteoarthritic patients and 25 age-matched controls. The ACLR-6M cohort included 52 patients with unilateral ACL tears who were imaged 6 months after ACL reconstruction, and 10 age-matched controls. Non-rigid registration on a single template and local Z-score conversion were adopted for T1ρ spatial and intensity normalization of all the images in the dataset. PCA was used as a data dimensionality reduction to obtain a description of all subjects in a 10-dimensional feature space. Logistic linear regression was used to identify distinctive features of OA and ACL subjects. Global prolongation of the Z-score was observed in both OA and ACL subjects compared to controls [higher values in 1st principal component (PC1); P=0.01]. In addition, relaxation time differences between superficial and deep cartilage layers of the lateral tibia and trochlea were observed to be significant distinctive features between OA and ACL subjects. OA subjects demonstrated similar values between the two cartilage layers [higher value in 2nd principal component (PC2); P=0.008], while ACL reconstructed subjects showed T1ρ prolongation specifically in the cartilage superficial layer (lower values in PC2; P<0.0001). T1ρ elevation located outside of the weight-bearing area, located in the posterior and anterior aspects of the lateral femoral compartment, was also observed to be a key feature in distinguishing OA subjects from controls [higher value in 6th principal component (PC6); P=0.007]. This study is the first example of T1ρ local/regional pattern analysis and data-driven feature extraction in knees with cartilage degeneration. Our results revealed similarities and differences between OA and ACL relaxation patterns that could be potentially useful to better understand the pathogenesis of post-traumatic cartilage degeneration and the identification of imaging biomarkers for the early stratification of subjects at risk for developing post-traumatic OA.

Composite metric R2 - R1ρ (1/T2 - 1/T1ρ ) as a potential MR imaging biomarker associated with changes in pain after ACL reconstruction: A six-month follow-up.

This study looked to investigate a new quantitative metric, R2 - R1ρ (1/T2 - 1/T1ρ ), using magnetic resonance (MR) images and voxel-based relaxometry (VBR) for detecting early cartilage degeneration and explore the association with patient-reported outcomes measures (PROMs) in patients 6 months after ACL reconstruction. Sixty-four patients from three sites were bilaterally scanned on a 3T MR with a combined T1ρ /T2 protocol to calculate R1ρ (1/T1ρ ) and R2 (1/T2 ) values at baseline and 6 months after reconstructive surgery. Non-rigid registration was applied to align images onto a template, allowing VBR to determine VBR rate differences and explore cross-sectional and longitudinal differences between injured and uninjured knees, generating Statistical Parametric Maps (SPMs). Baseline R2 - R1ρ differences were further correlated with change in PROMs from the Knee Injury and Osteoarthritis Outcome Score (KOOS) from baseline to 6 months. Cross-sectional results demonstrated low relaxation rate differences in the injured patella (baseline: 21%, p = 0.01; 6-months: 18%, p = 0.02), lateral tibia (baseline: 25%, p = 0.01; 6-months: 24%, p = 0.01), and weight-bearing regions of the tibia and femur. The uninjured patella showed significant longitudinal changes (17%, p = 0.02). R2 - R1ρ differences showed significant correlations with KOOS PROMs, particularly in the lateral tibia, patella, and trochlea. R2 - R1ρ difference VBR analyses provide new and highly sensitive parameters for assessing early cartilage degeneration in patients after ACL injury by integrating findings from both T1ρ and T2 , commonly used relaxation time parameters, into a single metric. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:718-729, 2017.

Longitudinal study using voxel-based relaxometry: Association between cartilage T1ρ and T2 and patient reported outcome changes in hip osteoarthritis.

To study the local distribution of hip cartilage T1ρ and T2 relaxation times and their association with changes in patient reported outcome measures (PROMs) using a fully automatic, local, and unbiased method in subjects with and without hip osteoarthritis (OA). The 3 Tesla MRI studies of the hip were obtained for 37 healthy controls and 16 subjects with radiographic hip OA. The imaging protocol included a three-dimensional (3D) SPGR sequence and a combined 3D T1ρ and T2 sequence. Quantitative cartilage analysis was compared between a traditional region of interest (ROI)-based method and a fully automatic voxel-based relaxometry (VBR) method. Additionally, VBR was used to assess local T1ρ and T2 differences between subjects with and without OA, and to evaluate the association between T1ρ and T2 and 18-month changes PROMs. Results for the two methods were consistent in the acetabular (R = 0.79; coefficients of variation [CV] = 2.9%) and femoral cartilage (R = 0.90; CV = 2.6%). VBR revealed local patterns of T1ρ and T2 elevation in OA subjects, particularly in the posterosuperior acetabular cartilage (T1ρ : P = 0.02; T2 : P = 0.038). Overall, higher T1ρ and T2 values at baseline, particularly in the anterosuperior acetabular cartilage (T1ρ : Rho = -0.42; P = 0.002; T2 : Rho = -0.44; P = 0.002), were associated with worsening PROMS at 18-month follow-up. VBR is an accurate and robust method for quantitative MRI analysis in hip cartilage. VBR showed the capability to detect local variations in T1ρ and T2 values in subjects with and without osteoarthritis, and voxel based correlations demonstrated a regional dependence between baseline T1ρ and T2 values and changes in PROMs. 1 J. MAGN. RESON. IMAGING 2017;45:1523-1533.

Baseline cartilage quality is associated with voxel-based T1ρ and T2 following ACL reconstruction: A multicenter pilot study.

In this multi-center study, voxel-based relaxometry (VBR), a novel technique to automatically quantify localized cartilage change, was used to investigate T1ρ and T2 relaxation times of patients with anterior cruciate ligament (ACL) tears at the time of injury and 6 months after reconstructive surgery. Sixty-four ACL-injured patients from three sites underwent bilateral 3T MR T1ρ and T2 mapping; 56 patients returned 6 months after surgery. Cross-sectional and longitudinal VBR comparisons of relaxation times were calculated. Noyes Score (NS) clinical grades of cartilage lesions were noted at both times and correlated with relaxation times. Lastly, patients were divided into two groups based on baseline NS grades in the injured knee. T1ρ times of each group were assessed with VBR and compared. Results illustrate the feasibility of VBR for efficiently analyzing data from patients at different sites. Significant relaxation time elevations at baseline were observed in the injured knee compared to the uninjured, particularly in the posterolateral tibia (pLT). Longitudinally, a decrease was observed in the pLT and patella, while an increase was noted in the trochlea. Stratifying patients by baseline lesion presence revealed T1ρ increased more 6 months after surgery in patients with lesions. Such findings propose that the presence of cartilage lesions at baseline are associated with the longitudinal progression of T1ρ and T2 after ACL injury, and may contribute to early cartilage degeneration. Furthermore, the speed and localized specificity of automatic VBR analysis may translate well for clinical application, as seen in this multicenter study. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:688-698, 2017.

Elevation in PFJ cartilage T1ρ is associated with excessive mechanical loading and worst patient reported outcomes: A local voxel-based relaxometry analysis

Elevation in PFJ cartilage T1ρ is associated with excessive mechanical loading and worst patient reported outcomes: A local voxel-based relaxometry analysis

T1ρ and T2 relaxation times are associated with progression of hip osteoarthritis

To evaluate whether baseline T1ρ and T2 relaxation times of hip cartilage are associated with magnetic resonance imaging (MRI) based progression of hip osteoarthritis (OA) at 18 months. 3T MRI studies of the hip were obtained at baseline and 18-month follow-up for 54 subjects without evidence of severe OA at baseline [Kellgren-Lawrence (KL) score of 0-3]. 2D fast spin-echo sequences were used for semi-quantitative morphological scoring of cartilage lesions and a combined T1ρ/T2 sequence was used to quantitatively assess cartilage composition. Progression of hip OA was defined based on incident or progression of morphological semi-quantitative grade at 18 months. Baseline T1ρ and T2 relaxation times were compared between progressors and non-progressors using one-way analysis of variance and Mann-Whitney U tests and used to predict progression with binary logistic regression after adjusting for age, gender, body mass index, and KL score. Additionally, a novel voxel-based relaxometry technique was used to compare the spatial distribution of baseline T1ρ and T2 between progressors and non-progressors. Significantly higher baseline T1ρ and T2 values were observed in hip OA progressors compared to non-progressors, particularly in the posterosuperior and anterior aspects of the femoral cartilage. Logistic regression showed that higher baseline T1ρ or T2 values in the femoral cartilage were significantly associated with progression of femoral cartilage lesions at 18 months. T1ρ and T2 relaxation parameters are associated with morphological cartilage degeneration at 18 months and may serve as potential imaging biomarkers for progression of cartilage lesions in hip OA.

Fully automatic analysis of the knee articular cartilageT1ρrelaxation time using voxel-based relaxometry

To develop and compare with the classical region of interest (ROI)-based approach a fully automatic, local, and unbiased way of studying the knee T1ρ relaxation time by creating an atlas and using voxel-based relaxometry (VBR) in osteoarthritis (OA) and anterior cruciate ligament (ACL) subjects. In this study 110 subjects from two cohorts: 1) Mild OA 40 patients with mild-OA Kellgren-Lawrence (KL) ≤ 2 and 15 controls KL ≤ 1; 2) ACL cohort (a model for early OA): 40 ACL-injured patients imaged prior to ACL reconstruction and 1-year postsurgery and 15 controls are analyzed. All the subjects were acquired at 3T with a protocol that includes: 3D-FSE (CUBE) and 3D-T1ρ . A nonrigid registration technique was applied to align all the images on a single template. This allows for performing VBR to assess local statistical differences of T1ρ values using z-score analysis. VBR results were compared with those obtained with classical ROI-based technique. ROI-based results from atlas-based segmentation were consistent with classical ROI-based method (coefficient of variation [CV] = 3.83%). Voxel-based group analysis revealed local patterns that were overlooked by the ROI-based approach; eg, VBR showed posterior lateral femur and posterior lateral tibia significant T1ρ elevations in ACL-injured patients (sample mean z-score=9.7 and 10.3). Those elevations were overlooked by the classical ROI-based approach (sample mean z-score=1.87 and -1.73) CONCLUSION: VBR is a feasible and accurate tool for the local evaluation of the biochemical composition of knee articular cartilage. VBR is capable of detecting specific local patterns on T1ρ maps in OA and ACL subjects.

T2 relaxation time alterations underlying neurocognitive deficits in alcohol-use disorders (AUD) in an Indian population: A combined conventional ROI and voxel-based relaxometry analysis

Long-term heavy alcohol consumption has traditionally been associated with impaired cognitive abilities, such as deficits in abstract reasoning, problem solving, verbal fluency, memory, attention, and visuospatial processing. The present study aimed at exploring these neuropsychological deficits in alcohol-use disorders (AUD) in an Indian population using the Postgraduate Institute Battery of Brain Dysfunction (PGIBBD) and their possible correlation with alterations in T2 relaxation times (T2-RT), using whole-brain voxel-based relaxometry (VBR) and conventional region of interest (ROI) approach. Multi-echo T2 mapping sequence was performed on 25 subjects with AUD and 25 healthy controls matched for age, education, and socioeconomic status. Whole-brain T2-RT measurements were conducted using VBR and conventional ROI approach. The study was carried out on a 3T whole-body MR scanner. Post processing for VBR and ROI analysis was performed using SPM 8 software and vendor-provided software, respectively. A PGIBBD test battery was conducted on all subjects to assess their cognitive abilities, and the results were reported as raw scores. VBR and ROI results revealed that AUD subjects showed prolonged T2-RTs in cerebellum bilaterally, parahippocampal gyrus bilaterally, right anterior cingulate cortex, left superior temporal gyrus, left middle frontal gyrus, and left calcarine gyrus. A significant correlation was also observed between the neuropsychological test raw scores and alterations in T2-RT in AUD subjects. Our results are consistent with previous studies suggesting tissue disruption or gliosis or demyelination as a possible reason for prolonged T2-RTs. This damage to brain tissue, which is evident as prolonged T2-RT, could possibly be associated with impaired cognitive abilities noticeable in AUD subjects.