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

Free-Breathing Non-Contrast T1ρ Dispersion MRI of Myocardial Interstitial Fibrosis in Comparison with Extracellular Volume Fraction

BACKGROUND

Myocardial fibrosis is a common feature in various cardiac diseases. It causes adverse cardiac remodeling and is associated with poor clinical outcomes. Late gadolinium enhancement (LGE) and extracellular volume fraction (ECV) are the standard MRI techniques for detecting focal and diffuse myocardial fibrosis. However, these contrast-enhanced techniques require the administration of gadolinium contrast agents, which is not applicable to patients with gadolinium contraindications. To eliminate the need of contrast agents, we develop and apply an endogenous free-breathing T1ρ dispersion imaging technique (FB-MultiMap) for diagnosing diffuse myocardial fibrosis in a cohort with suspected cardiomyopathies.

METHODS

The proposed FB-MultiMap technique, enabling T2, T1ρ and their difference (myocardial fibrosis index, mFI) quantification in a single scan was developed in phantoms and 15 healthy subjects. In the clinical study, 55 patients with suspected cardiomyopathies were imaged using FB-MultiMap, conventional native T1 mapping, LGE, and ECV imaging. The accuracy of the endogenous parameters for predicting increased ECV was evaluated using receiver operating characteristic (ROC) curve analysis. In addition, the correlation of native T1, T1ρ, and mFI with ECV was respectively assessed using Pearson correlation coefficients.

RESULTS

FB-MultiMap showed a good agreement with conventional separate breath-hold mapping techniques in phantoms and healthy subjects. Considering all the patients, T1ρ was more accurate than mFI and native T1 for predicting increased ECV, with area under the curve (AUC) values of 0.91, 0.79 and 0.75, respectively, and showed stronger correlation with ECV (correlation coefficient r: 0.72 vs. 0.52 vs. 0.40). In the subset of 47 patients with normal T2 values, the diagnostic performance of mFI was significantly strengthened (AUC=0.90, r=0.83), outperforming T1ρ and native T1.

CONCLUSION

The proposed free-breathing T1ρ dispersion imaging technique enabling simultaneous quantification of T2, T1ρ and mFI in a single scan has shown great potential for diagnosing diffuse myocardial fibrosis in patients with complex cardiomyopathies without contrast agents.

Synthetic Knee MRI T1p Maps as an Avenue for Clinical Translation of Quantitative Osteoarthritis Biomarkers

A 2D U-Net was trained to generate synthetic T1p maps from T2 maps for knee MRI to explore the feasibility of domain adaptation for enriching existing datasets and enabling rapid, reliable image reconstruction. The network was developed using 509 healthy contralateral and injured ipsilateral knee images from patients with ACL injuries and reconstruction surgeries acquired across three institutions. Network generalizability was evaluated on 343 knees acquired in a clinical setting and 46 knees from simultaneous bilateral acquisition in a research setting. The deep neural network synthesized high-fidelity reconstructions of T1p maps, preserving textures and local T1p elevation patterns in cartilage with a normalized mean square error of 2.4% and Pearson's correlation coefficient of 0.93. Analysis of reconstructed T1p maps within cartilage compartments revealed minimal bias (-0.10 ms), tight limits of agreement, and quantification error (5.7%) below the threshold for clinically significant change (6.42%) associated with osteoarthritis. In an out-of-distribution external test set, synthetic maps preserved T1p textures, but exhibited increased bias and wider limits of agreement. This study demonstrates the capability of image synthesis to reduce acquisition time, derive meaningful information from existing datasets, and suggest a pathway for standardizing T1p as a quantitative biomarker for osteoarthritis.

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.

Assessing post-traumatic changes in cartilage using T1ρ dispersion parameters

Degeneration of cartilage can be studied non-invasively with quantitative MRI. A promising parameter for detecting early osteoarthritis in articular cartilage is T_1ρ, which can be tuned via the amplitude of the spin-lock pulse. By measuring T_1ρ at several spin-lock amplitudes, the dispersion of T_1ρ is obtained. The aim of this study is to find out if the dispersion contains diagnostically relevant information complementary to a T_1ρ measurement at a single spin-lock amplitude. To this end, five differently acquired dispersion parameters are utilized; A, B, τ_c, T_1ρ/T₂, and R₂ - R_1ρ. An open dataset of an equine model of post-traumatic cartilage was utilized to assess the T_1ρ dispersion parameters for the evaluation of cartilage degeneration. Firstly, the parameters were compared for their sensitivity in detecting degenerative changes. Secondly, the relationship of the dispersion parameters to histological and biomechanical reference parameters was studied. Parameters A, T_1ρ/T₂, and R₂ - R_1ρ were found to be sensitive to lesion-induced changes in the cartilage within sample. Strong correlations of several dispersion parameters with optical density, as well as with collagen fibril angle were found. Most of the dispersion parameters correlated strongly with individual T_1ρ values. The results suggest that dispersion parameters can in some cases provide a more accurate description of the biochemical composition of cartilage as compared to conventional MRI parameters. However, in most cases the information given by the dispersion parameters is more of a refinement than complementary to conventional quantitative MRI.

Noncontrast T1ρ dispersion imaging is sensitive to diffuse fibrosis: A cardiovascular magnetic resonance study at 3T in hypertrophic cardiomyopathy

PURPOSE

To determine the sensitivity of a noncontrast T1 dispersion cardiovascular magnetic resonance technique for detecting diffuse fibrosis in hypertrophic cardiomyopathy (HCM).

METHODS

Thirty-two adult HCM patients and ten age- and gender-matched healthy volunteers were prospectively included in this study. Patients and controls underwent cine, T1ρ-mapping, and pre- and post-contrast T1-mapping imaging using a 3-T magnetic resonance system. Myocardial extracellular volume fraction (ECV) maps were obtained using pre- and post-contrast T1 maps to determine reference values for diffuse fibrosis. Myocardial T1ρ and T1ρ dispersion maps called myocardial fibrosis index (mFI) maps provided 570 myocardial segments for Pearson or Spearman correlation analysis. The left ventricle myocardia of the HCM patients were divided into 16 segments that were further classified as either normal-thickness myocardium (<15 mm) (HCM-N) or hypertrophic myocardium (≥15 mm) (HCM-H).

RESULTS

ECV and mFI values increased progressively on a per-segment basis from healthy controls to the HCM-N group and then to the HCM-H group (ECV: 27.4 ± 2.8% vs. 31.1 ± 4.2% vs. 37.6 ± 6.9%, respectively [P < 0.0001]; mFI: 6.1 ± 0.9 ms vs. 8 ± 1.9 ms vs. 11 ± 3.3 ms, respectively [P < 0.0001]). There was a strong positive correlation between the segmented ECV and the mFI (r = 0.878). The mFI was equally or significantly better than the ECV for differentiating fibrosis content in HCM-N and HCM-H according to their receiver operating characteristic curves.

CONCLUSION

A T1ρ dispersion imaging mFI can sensitively detect diffuse myocardial fibrosis in HCM, even in HCM-N.

Magnetization-prepared spoiled gradient-echo snapshot imaging for efficient measurement of R2 -R1ρ in knee cartilage

PURPOSE

To validate the potential of quantifying R₂ -R_1ρ using one pair of signals with T_1ρ preparation and T₂ preparation incorporated to magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) acquisition and to find an optimal preparation time (T_prep ) for in vivo knee MRI.

METHODS

Bloch equation simulations were first performed to assess the accuracy of quantifying R₂ -R_1ρ using T_1ρ - and T₂ -prepared signals with an equivalent T_prep . For validation of this technique in comparison to the conventional approach that calculates R₂ -R_1ρ after estimating both T₂ and T_1ρ , phantom experiments and in vivo validation with five healthy subjects and five osteoarthritis patients were performed at a clinical 3T scanner.

RESULTS

Bloch equation simulations demonstrated that the accuracy of this efficient R₂ -R_1ρ quantification method and the optimal T_prep can be affected by image signal-to-noise ratio (SNR) and tissue relaxation times, but quantification can be closest to the reference with an around 25 ms T_prep for knee cartilage. Phantom experiments demonstrated that the proposed method can depict R₂ -R_1ρ changes with agarose gel concentration. With in vivo data, significant correlation was observed between cartilage R₂ -R_1ρ measured from the conventional and the proposed methods, and a T_prep of 25.6 ms provided the most agreement by Bland-Altman analysis. R₂ -R_1ρ was significantly lower in patients than in healthy subjects for most cartilage compartments.

CONCLUSION

As a potential biomarker to indicate cartilage degeneration, R₂ -R_1ρ can be efficiently measured using one pair of T_1ρ -prepared and T₂ -prepared signals with an optimal T_prep considering cartilage relaxation times and image SNR.

Multi-vendor multi-site T1ρ and T2 quantification of knee cartilage

OBJECTIVE

To develop 3D T_1ρ and T₂ imaging based on the same sequence structure on MR systems from multiple vendors, and to evaluate intra-site repeatability and inter-site inter-vendor reproducibility of T_1ρ and T₂ measurements of knee cartilage.

METHODS

3D magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (3D MAPSS) were implemented on MR systems from Siemens, GE and Philips. Phantom and human subject data were collected at four sites using 3T MR systems from the three vendors with harmonized protocols. Phantom data were collected by means of different positioning of the coil. Volunteers were scanned and rescanned after repositioning. Two traveling volunteers were scanned at all sites. Data were transferred to one site for centralized processing.

RESULTS

Intra-site average coefficient of variations (CVs) ranged from 1.09% to 3.05% for T_1ρ and 1.78-3.30% for T₂ in phantoms, and 1.60-3.93% for T_1ρ and 1.44-4.08% for T₂ in volunteers. Inter-site average CVs were 5.23% and 6.45% for MAPSS T_1ρ and T₂, respectively in phantoms, and 8.14% and 10.06% for MAPSS T_1ρ and T₂, respectively, In volunteers.

CONCLUSION

This study showed promising results of multi-site, multi-vendor reproducibility of T_1ρ and T₂ values in knee cartilage. These quantitative measures may be applied in large-scale multi-site, multi-vendor trials with controlled sequence structure and scan parameters and centralized data processing.

An order parameter without magic angle effect (OPTIMA) derived from R 1 ρ dispersion in ordered tissue

PURPOSE

MR R₂ imaging of ordered tissue exhibits the magic angle effect, potentially masking subtle pathological changes in cartilage. This work aimed to develop an orientation-independent order parameter (S) exclusively sensitive to collagen degeneration.

METHODS

A theory was developed based on R 1 ρ dispersion coupled with a simplified molecular motion model in which anisotropic R 2 a ( θ ) became directly proportional to correlation time τ b θ and S could be derived. This new parameter was validated with ex vivo R 1 ρ dispersion reported on orientated (n = 4), enzymatically depleted bovine cartilage (n = 6), and osteoarthritic human knee specimens (n = 14) at 9.4 Tesla, which was further demonstrated on 1 healthy human knee in vivo at 3 Tesla.

RESULTS

τ b θ from orientation-dependent R 1 ρ dispersion revealed a significantly high average correlation (r = 0.89 ± 0.05, P < 0.05) with R 2 a (θ) on cartilage samples and a moderate correlation (r = 0.48, P < 0.001) for the human knee in vivo. The derived S (10^-3 ) significantly decreased in advanced osteoarthritis (1.64 ± 0.03 vs. 2.30 ± 0.11, P < 0.001) and collagen-depleted samples (1.30 ± 0.11 vs. 2.12 ± 0.12, P < 0.001) when compared with early osteoarthritis and the control, respectively.

CONCLUSION

The proposed order parameter could be a potentially useful orientation-independent MR biomarker for collagen alterations in cartilage and other highly structured tissues.

A unique anisotropic R2 of collagen degeneration (ARCADE) mapping as an efficient alternative to composite relaxation metric (R2 -R1 ρ ) in human knee cartilage study

PURPOSE

Anisotropic transverse R₂ (1/T₂ ) relaxation of water proton is sensitive to cartilage degenerative changes. The purpose is to develop an efficient method to extract this relaxation metric in clinical studies.

METHODS

Anisotropic R₂ can be measured inefficiently by standard R₂ mapping after removing an isotropic contribution obtained from R_{1 ρ} mapping. In the proposed method, named as a unique anisotropic R₂ of collagen degeneration (ARCADE) mapping, an assumed uniform isotropic R₂ was estimated at magic angle locations in the deep cartilage, and an anisotropic R₂ was thus isolated in a single T2W sagittal image. Five human knees from 4 volunteers were studied with standard R₂ and R_{1 ρ} mappings at 3T, and anisotropic R₂ derived from ARCADE on the T2W (TE = 48.8 ms) image from R₂ mapping was compared with the composite relaxation (R₂ - R_{1 ρ} ) using statistical analysis including Student's t-test and Pearson's correlation coefficient.

RESULTS

Anisotropic R₂ (1/s) from ARCADE was highly positively correlated with but not significantly different from standard R₂ - R_{1 ρ} (1/s) in the segmented deep (r = 0.83 ± 0.06; 8.3 ± 2.9 vs. 7.3 ± 1.9, P = .50) and the superficial (r = 0.82 ± 0.05; 3.5 ± 2.4 vs. 4.5 ± 1.6, P = .39) zones. However, after eliminating systematic errors by the normalization in terms of zonal contrast, anisotropic R₂ was significantly higher (60.2 ± 18.5% vs. 38.4 ± 16.6%, P < .01) than R₂ - R_{1 ρ} as predicted.

CONCLUSION

The proposed anisotropic R₂ mapping could be an efficient alternative to the conventional approach, holding great promise in providing both high-resolution morphological and more sensitive transverse relaxation imaging from a single T2W scan in a clinical setting.

Translation of morphological and functional musculoskeletal imaging

In an effort to develop quantitative biomarkers for degenerative joint disease and fill the void that exists for diagnosing, monitoring, and assessing the extent of whole joint degeneration, the past decade has been marked by a greatly increased role of noninvasive imaging. This coupled with recent advances in image processing and deep learning opens new possibilities for promising quantitative techniques. The clinical translation of quantitative imaging was previously hampered by tedious non-scalable and subjective image analysis. Osteoarthritis (OA) diagnosis using X-rays can be automated by the use of deep learning models and pilot studies showed feasibility of using similar techniques to reliably segment multiple musculoskeletal tissues and detect and stage the severity of morphological abnormalities in magnetic resonance imaging (MRI). Automation and more advanced feature extraction techniques have applications on larger more heterogeneous samples. Analyses based on voxel based relaxometry have shown local patterns in relaxation time elevations and local correlations with outcome variables. Bone cartilage interactions are also enhanced by the analysis of three-dimensional bone morphology and the potential for the assessment of metabolic activity with simultaneous Positron Emission Tomography (PET)/MR systems. Novel techniques in image processing and deep learning are augmenting imaging to be a source of quantitative and reliable data and new multidimensional analytics allow us to exploit the interactions of data from various sources. In this review, we aim to summarize recent advances in quantitative imaging, the application of image processing and deep learning techniques to study knee and hip OA. ©2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res XX:XX-XX, 2018.

Towards prevention of post-traumatic osteoarthritis: report from an international expert working group on considerations for the design and conduct of interventional studies following acute knee injury

OBJECTIVE

There are few guidelines for clinical trials of interventions for prevention of post-traumatic osteoarthritis (PTOA), reflecting challenges in this area. An international multi-disciplinary expert group including patients was convened to generate points to consider for the design and conduct of interventional studies following acute knee injury.

DESIGN

An evidence review on acute knee injury interventional studies to prevent PTOA was presented to the group, alongside overviews of challenges in this area, including potential targets, biomarkers and imaging. Working groups considered pre-identified key areas: eligibility criteria and outcomes, biomarkers, injury definition and intervention timing including multi-modality interventions. Consensus agreement within the group on points to consider was generated and is reported here after iterative review by all contributors.

RESULTS

The evidence review identified 37 studies. Study duration and outcomes varied widely and 70% examined surgical interventions. Considerations were grouped into three areas: justification of inclusion criteria including the classification of injury and participant age (as people over 35 may have pre-existing OA); careful consideration in the selection and timing of outcomes or biomarkers; definition of the intervention(s)/comparator(s) and the appropriate time-window for intervention (considerations may be particular to intervention type). Areas for further research included demonstrating the utility of patient-reported outcomes, biomarkers and imaging outcomes from ancillary/cohort studies in this area, and development of surrogate clinical trial endpoints that shorten the duration of clinical trials and are acceptable to regulatory agencies.

CONCLUSIONS

These considerations represent the first international consensus on the conduct of interventional studies following acute knee joint trauma.

Osteoarthritis year in review 2017: updates on imaging advancements

OBJECTIVE

This narrative review covers original research publications related to imaging advancements in osteoarthritis (OA) published in the English language between 1^st April 2016 and 30^th April 2017.

METHODS

Relevant human studies (excluding pre-clinical and in vitro studies), were searched and selected from PubMed database using the search terms of "osteoarthritis (OA)" in combination with "radiography", "magnetic resonance imaging (MRI)", "computed tomography (CT)", "ultrasound", "positron emission tomography (PET)," "single-photon emission computed tomography (SPECT)," and "scintigraphy". The included studies were sorted according to their relevance, novelty, and impact. Original research articles with both imaging advancements and novel clinical information were discussed in this review.

RESULTS

A large portion of the published studies were focused on MRI-based semi-quantitative and quantitative (morphological and structural) metrics of the knee joint to assess OA-related structural damages. New imaging technologies, such as PET, have been investigated for OA diagnosis and characterization, the delineation of predictive factors for OA progression, and to monitor the treatment responses.

CONCLUSION

Advanced imaging modalities play a pivotal role in OA research, and make a significant contribution to our understanding of OA diagnosis, pathogenesis, risk stratification, and prognosis.

Effect of intra-articular injection of intermediate-weight hyaluronic acid on hip and knee cartilage: in-vivo evaluation using T2 mapping

OBJECTIVES

We used T2 mapping to quantify the effect of intra-articular hyaluronic acid administration (IAHAA) on cartilage with correlation to clinical symptoms.

METHODS

One hundred two patients with clinical and MRI diagnosis of hip or knee grade I-III chondropathy were prospectively included. All patients received a standard MRI examination of the affected hip/knee (one joint/patient) and T2-mapping multiecho sequence for cartilage evaluation. T2 values of all slices were averaged and used for analysis. One month after MR evaluation 72 patients (38 males; mean age 51±10 years) underwent IAHAA. As a control group, 30 subjects (15 males; 51 ± 9 years) were not treated. MR and WOMAC evaluation was performed at baseline and after 3, 9, and 15 months in all patients.

RESULTS

T2 mapping in hyaluronic acid (HA) patients showed a significant increase in T2 relaxation times from baseline to the first time point after therapy in knees (40.7 ± 9.8 ms vs. 45.8 ± 8.6 ms) and hips (40.9 ± 9.7 ms; 45.9 ± 9.5 ms) (p < 0.001). At the 9- and 15-month evaluations, T2 relaxation dropped to values similar to the baseline ones (p < 0.001 vs. 3 month). The correlation between T2 increase and pain reduction after IAHAA was statistically significant (r = 0.54, p < 0.01) in patients with grade III chondropathy.

CONCLUSIONS

T2 mapping can be used to evaluate the effect over time of IAHAA in patients with hip and knee chondropathy.

KEY POINTS

• T2 relaxation times change over time after hyaluronic acid intra-articular administration • T2 relaxation times of the medial femoral condyle correlate with WOMAC variation • T2 relaxation times are different between Outerbridge I and II-III.

MRI and biomechanics multidimensional data analysis reveals R2 -R1ρ as an early predictor of cartilage lesion progression in knee osteoarthritis

PURPOSE

To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.

MATERIALS AND METHODS

We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T_1ρ and T₂ and R₂ -R_1ρ (1/T₂ -1/T_1ρ ) acquired at 3T and whole-organ magnetic resonance imaging score morphological grading. Topological data analysis (TDA) and Kolmogorov-Smirnov test were adopted for data integration, analysis, and hypothesis generation. Regression models were used for hypothesis testing.

RESULTS

The results of the TDA showed a network composed of three main patient subpopulations, thus potentially identifying new phenotypes. T₂ and T_1ρ values (T₂ lateral femur P = 1.45*10^-8 , T_1ρ medial tibia P = 1.05*10^-5 ), the presence of femoral cartilage defects (P = 0.0013), lesions in the meniscus body (P = 0.0035), and race (P = 2.44*10^-4 ) were key markers in the subpopulation classification. Within one of the subpopulations we observed an association between the composite metric R₂ -R_1ρ and the longitudinal progression of cartilage lesions.

CONCLUSION

The analysis presented demonstrates some of the complex multitissue biochemical and biomechanical interactions that define joint degeneration and OA using a multidimensional approach, and potentially indicates that R₂ -R_1ρ may be an imaging biomarker for early OA.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:78-90.

A non-contrast CMR index for assessing myocardial fibrosis

PURPOSE

Safe, sensitive, and non-invasive imaging methods to assess the presence, extent, and turnover of myocardial fibrosis are needed for early stratification of risk in patients who might develop heart failure after myocardial infarction. We describe a non-contrast cardiac magnetic resonance (CMR) approach for sensitive detection of myocardial fibrosis using a canine model of myocardial infarction and reperfusion.

METHODS

Seven dogs had coronary thrombotic occlusion of the left anterior descending coronary arteries followed by fibrinolytic reperfusion. CMR studies were performed at 7days after reperfusion. A CMR spin-locking T₁ρ mapping sequence was used to acquire T₁ρ dispersion data with spin-lock frequencies of 0 and 511Hz. A fibrosis index map was derived on a pixel-by-pixel basis. CMR native T₁ mapping, first-pass myocardial perfusion imaging, and post-contrast late gadolinium enhancement imaging were also performed for assessing myocardial ischemia and fibrosis. Hearts were dissected after CMR for histopathological staining and two myocardial tissue segments from the septal regions of adjacent left ventricular slices were qualitatively assessed to grade the extent of myocardial fibrosis.

RESULTS

Histopathology of 14 myocardial tissue segments from septal regions was graded as grade 1 (fibrosis area, <20% of a low power field, n=9), grade 2 (fibrosis area, 20-50% of field, n=4), or grade 3 (fibrosis area, >50% of field, n=1). A dramatic difference in fibrosis index (183%, P<0.001) was observed by CMR from grade 1 to 2, whereas differences were much smaller for T₁ρ (9%, P=0.14), native T₁ (5.5%, P=0.12), and perfusion (-21%, P=0.05).

CONCLUSION

A non-contrast CMR index based on T₁ρ dispersion contrast was shown in preliminary studies to detect and correlate with the extent of myocardial fibrosis identified histopathologically. A non-contrast approach may have important implications for managing cardiac patients with heart failure, particularly in the presence of impaired renal function.

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

BACKGROUND

Quantitative MR, including T_1ρ 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 T_1ρ. 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 T_1ρ maps in subjects with OA and subjects six months after ACL reconstruction (ACLR).

METHODS

T_1ρ 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 T_1ρ 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.

RESULTS

Global prolongation of the Z-score was observed in both OA and ACL subjects compared to controls [higher values in 1^st 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 2^nd principal component (PC2); P=0.008], while ACL reconstructed subjects showed T_1ρ prolongation specifically in the cartilage superficial layer (lower values in PC2; P<0.0001). T_1ρ 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 6^th principal component (PC6); P=0.007].

CONCLUSIONS

This study is the first example of T_1ρ 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.