Lateral Corticospinal Tract and Dorsal Column Damage: Predictive Relationships With Motor and Sensory Scores at Discharge From Acute Rehabilitation After Spinal Cord Injury.

OBJECTIVE: To determine if lateral corticospinal tract (LCST) integrity demonstrates a significant predictive relationship with future ipsilateral lower extremity motor function (LEMS) and if dorsal column (DC) integrity demonstrates a significant predictive relationship with future light touch (LT) sensory function post spinal cord injury (SCI) at time of discharge from inpatient rehabilitation. DESIGN: Retrospective analyses of imaging and clinical outcomes. SETTING: University and academic hospital. PARTICIPANTS: A total of 151 participants (N=151) with SCI. INTERVENTIONS: Inpatient rehabilitation. MAIN OUTCOME MEASURES: LEMS and LT scores at discharge from inpatient rehabilitation. RESULTS: In 151 participants, right LCST spared tissue demonstrated a significant predictive relationship with right LEMS percentage recovered (ß=0.56; 95% confidence interval [CI], 0.37-0.73; R=0.43; P<.001). Left LCST spared tissue demonstrated a significant predictive relationship with left LEMS percentage recovered (ß=0.66; 95% CI, 0.50-0.82; R=0.51; P<.001). DC spared tissue demonstrated a significant predictive relationship with LT percentage recovered (ß=0.69; 95% CI, 0.52-0.87; R=0.55; P<.001). When subgrouping the participants into motor complete vs incomplete SCI, motor relationships were no longer significant, but the sensory relationship remained significant. Those who had no voluntary motor function but recovered some also had significantly greater LCST spared tissue than those who did not recover motor function. CONCLUSIONS: LCST demonstrated significant moderate predictive relationships with lower extremity motor function at the time of discharge from inpatient rehabilitation, in an ipsilesional manner. DC integrity demonstrated a significant moderate predictive relationship with recovered function of LT. With further development, these neuroimaging methods might be used to predict potential deficits after SCI and to provide corresponding targeted interventions.

MRI-Based Quantitative Osteoporosis Imaging at the Spine and Femur.

Osteoporosis is a systemic skeletal disease with a high prevalence worldwide, characterized by low bone mass and microarchitectural deterioration, predisposing an individual to fragility fractures. Dual-energy X-ray absorptiometry (DXA) has been the clinical reference standard for diagnosing osteoporosis and for assessing fracture risk for decades. However, other imaging modalities are of increasing importance to investigate the etiology, treatment, and fracture risk. The purpose of this work is to review the available literature on quantitative magnetic resonance imaging (MRI) methods and related findings in osteoporosis at the spine and proximal femur as the clinically most important fracture sites. Trabecular bone microstructure analysis at the proximal femur based on high-resolution MRI allows for a better prediction of osteoporotic fracture risk than DXA-based bone mineral density (BMD) alone. In the 1990s, T2 * mapping was shown to correlate with the density and orientation of the trabecular bone. Recently, quantitative susceptibility mapping (QSM), which overcomes some of the limitations of T2 * mapping, has been applied for trabecular bone quantifications at the spine, whereas ultrashort echo time (UTE) imaging provides valuable surrogate markers of cortical bone quantity and quality. Magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) enable the quantitative assessment of the nonmineralized bone compartment through extraction of the bone marrow fat fraction (BMFF). Furthermore, CSE-MRI allows for the differentiation of osteoporotic vs. pathologic fractures, which is of high clinical relevance. Lastly, advanced postprocessing and image analysis tools, particularly considering statistical parametric mapping and region-specific BMFF distributions, have high potential to further improve MRI-based fracture risk assessments at the spine and hip. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2.

Gray matter segmentation of the spinal cord with active contours in MR images.

OBJECTIVE: Fully or partially automated spinal cord gray matter segmentation techniques for spinal cord gray matter segmentation will allow for pivotal spinal cord gray matter measurements in the study of various neurological disorders. The objective of this work was multi-fold: (1) to develop a gray matter segmentation technique that uses registration methods with an existing delineation of the cord edge along with Morphological Geodesic Active Contour (MGAC) models; (2) to assess the accuracy and reproducibility of the newly developed technique on 2D PSIR T1 weighted images; (3) to test how the algorithm performs on different resolutions and other contrasts; (4) to demonstrate how the algorithm can be extended to 3D scans; and (5) to show the clinical potential for multiple sclerosis patients. METHODS: The MGAC algorithm was developed using a publicly available implementation of a morphological geodesic active contour model and the spinal cord segmentation tool of the software Jim (Xinapse Systems) for initial estimate of the cord boundary. The MGAC algorithm was demonstrated on 2D PSIR images of the C2/C3 level with two different resolutions, 2D T2* weighted images of the C2/C3 level, and a 3D PSIR image. These images were acquired from 45 healthy controls and 58 multiple sclerosis patients selected for the absence of evident lesions at the C2/C3 level. Accuracy was assessed though visual assessment, Hausdorff distances, and Dice similarity coefficients. Reproducibility was assessed through interclass correlation coefficients. Validity was assessed through comparison of segmented gray matter areas in images with different resolution for both manual and MGAC segmentations. RESULTS: Between MGAC and manual segmentations in healthy controls, the mean Dice similarity coefficient was 0.88 (0.82-0.93) and the mean Hausdorff distance was 0.61 (0.46-0.76) mm. The interclass correlation coefficient from test and retest scans of healthy controls was 0.88. The percent change between the manual segmentations from high and low-resolution images was 25%, while the percent change between the MGAC segmentations from high and low resolution images was 13%. Between MGAC and manual segmentations in MS patients, the average Dice similarity coefficient was 0.86 (0.8-0.92) and the average Hausdorff distance was 0.83 (0.29-1.37) mm. CONCLUSION: We demonstrate that an automatic segmentation technique, based on a morphometric geodesic active contours algorithm, can provide accurate and precise spinal cord gray matter segmentations on 2D PSIR images. We have also shown how this automated technique can potentially be extended to other imaging protocols.

Spinal cord grey matter segmentation challenge.

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

Physical Activity for Strengthening Fracture Prone Regions of the Proximal Femur.

PURPOSE OF REVIEW: Physical activity improves proximal femoral bone health; however, it remains unclear whether changes translate into a reduction in fracture risk. To enhance any fracture-protective effects of physical activity, fracture prone regions within the proximal femur need to be targeted. RECENT FINDINGS: The proximal femur is designed to withstand forces in the weight-bearing direction, but less so forces associated with falls in a sideways direction. Sideways falls heighten femoral neck fracture risk by loading the relatively weak superolateral region of femoral neck. Recent studies exploring regional adaptation of the femoral neck to physical activity have identified heterogeneous adaptation, with adaptation principally occurring within inferomedial weight-bearing regions and little to no adaptation occurring in the superolateral femoral neck. There is a need to develop novel physical activities that better target and strengthen the superolateral femoral neck within the proximal femur. Design of these activities may be guided by subject-specific musculoskeletal modeling and finite-element modeling approaches.

Quantitative assessment of morphology, T1ρ, and T2 of shoulder cartilage using MRI.

OBJECTIVES: The aim of this study was to assess the feasibility of quantifying shoulder cartilage morphology and relaxometry in a clinically feasible scan time comparing different pulse sequences and assessing their reproducibility at 3 Tesla. METHODS: Three pulse sequences were compared for morphological assessments of shoulder cartilage thickness and volume (SPGR, MERGE, FIESTA), while a combined T1ρ-T2 sequence was optimized for relaxometry measurements. The shoulders of six healthy subjects were scanned twice with repositioning, and the cartilage was segmented and quantified. The degree of agreement between the three morphological sequences was assessed using Bland-Altman plots, while the morphological and relaxometry reproducibility were assessed with root-mean-square coefficients of variation (RMS-CVs) RESULTS: Bland-Altman plots indicated good levels of agreement between the morphological assessments of the three sequences. The reproducibility of morphological assessments yielded RMS-CVs between 4.0 and 17.7 %. All sequences correlated highly (R > 0.9) for morphologic assessments with no statistically significant differences. For relaxometry assessments of humeral cartilage, RMS-CVs of 6.4 and 10.6 % were found for T1ρ and T2, respectively. CONCLUSIONS: The assessment of both cartilage morphology and relaxometry is feasible in the shoulder with SPGR, humeral head, and T1ρ being the more reproducible morphological sequence, anatomic region, and quantitative sequence, respectively. KEY POINTS: • The thin cartilage morphology can be assessed in the shoulder in vivo. • Non-invasive biochemical assessment of shoulder cartilage is feasible in vivo using MRI.

Variable flip angle three-dimensional fast spin-echo sequence combined with outer volume suppression for imaging trabecular bone structure of the proximal femur.

BACKGROUND: To demonstrate the feasibility of using a variable flip angle three-dimensional fast spin-echo (3D VFA-FSE) sequence combined with outer volume suppression for imaging trabecular bone structure at the proximal femur in vivo at 3 Tesla. METHODS: The 3D VFA-FSE acquisition was optimized to minimize blurring and to provide high signal-to-noise ratio (SNR) from bone marrow. Outer volume suppression was achieved by applying three quadratic-phase radio-frequency pulses. The SNR and trabecular bone structures from 3D VFA-FSE were compared with those from previously demonstrated multiple-acquisition 3D balanced steady-state free precision (bSSFP) using theoretical simulations, ex vivo experiments, and in vivo experiments. RESULTS: Our simulation demonstrated that 3D VFA-FSE can provide at least 35% higher SNR than 3D bSSFP, which was confirmed by the ex vivo and in vivo experiments. The ex vivo experiments demonstrated a good correlation and agreement between bone structural paramters obtained with the two sequences. The proposed sequence depicted trabecular bone structure at the proxiaml femur in vivo well without visible suppression artifacts and provided a mean SNR of 11.0. CONCLUSION: The 3D VFA-FSE sequence combined with outer volume suppression can depict the trabecular bone structure of the proximal femur in vivo with minimal blurring and high SNR efficiency.

Validation of bone marrow fat quantification in the presence of trabecular bone using MRI.

BACKGROUND: To validate six-echo, chemical-shift based MRI with T2 * correction for the quantification of bone marrow fat content in the presence of trabecular bone. METHODS: Ten bone phantoms were made using trabecular bone cores extracted from the distal femur and proximal tibia of 20 human cadaveric knees. Bone marrow was removed from the cores and the marrow spaces were filled with water-fat gelatin to mimic bone marrow of known fat fractions. A chemical-shift based water-fat separation method with T2 * correction was used to generate fat fraction maps. The proton density fat fractions (PDFF) between marrow regions with and without bone were compared with the reference standard of known fat fraction using the squared Pearson correlation coefficient and unpaired t-test. RESULTS: Strong correlations were found between the known fat fraction and measured PDFF in marrow without trabecular bone (R(2) = 0.99; slope = 0.99, intercept = 0.94) as well as in marrow with trabecular bone (R(2) = 0.97; slope = 1.0, intercept = -3.58). Measured PDFF between regions with and without bone were not significantly different (P = 0.5). However, PDFF was systematically underestimated by -3.2% fat fraction in regions containing trabecular bone. CONCLUSION: Our implementation of a six-echo chemical-shift based MRI pulse sequence with T2 * correction provided an accurate means of determining fat content in bone marrow in the presence of trabecular bone.

Quantitative assessment of fat infiltration in the rotator cuff muscles using water-fat MRI.

PURPOSE: To evaluate a chemical shift-based fat quantification technique in the rotator cuff muscles in comparison with the semiquantitative Goutallier fat infiltration classification (GC) and to assess their relationship with clinical parameters. MATERIALS AND METHODS: The shoulders of 57 patients were imaged using a 3T MR scanner. The rotator cuff muscles were assessed for fat infiltration using GC by two radiologists and an orthopedic surgeon. Sequences included oblique-sagittal T1-, T2-, and proton density-weighted fast spin echo, and six-echo gradient echo. The iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) was used to measure fat fraction. Pain and range of motion of the shoulder were recorded. RESULTS: Fat fraction values were significantly correlated with GC grades (P < 0.0001, κ >0.9) showing consistent increase with GC grades (grade = 0, 0%-5.59%; grade = 1, 1.1%-9.70%; grade = 2, 6.44%-14.86%; grade = 3, 15.25%-17.77%; grade = 4, 19.85%-29.63%). A significant correlation between fat infiltration of the subscapularis muscle quantified with IDEAL versus 1) deficit in internal rotation (Spearman Rank Correlation Coefficient [SRC] = 0.39, 95% confidence interval [CI] 0.13-0.60, P < 0.01) and 2) pain (SRC coefficient = 0.313, 95% CI 0.049-0.536, P = 0.02) was found but was not seen between the clinical parameters and GC grades. Additionally, only quantitative fat infiltration measures of the supraspinatus muscle were significantly correlated with a deficit in abduction (SRC coefficient = 0.45, 95% CI 0.20-0.60, P < 0.01). CONCLUSION: An accurate and highly reproducible fat quantification in the rotator cuff muscles using water-fat magnetic resonance imaging (MRI) techniques is possible and significantly correlates with shoulder pain and range of motion.

Improving bone strength prediction in human proximal femur specimens through geometrical characterization of trabecular bone microarchitecture and support vector regression.

We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose, volumes of interest were extracted from the head, neck, and trochanter of 146 ex vivo proximal femur specimens on multidetector computer tomography. The trabecular bone captured was characterized with (1) statistical moments of the BMD distribution, (2) geometrical features derived from the scaling index method (SIM), and (3) morphometric parameters, such as bone fraction, trabecular thickness, etc. Feature sets comprising DXA BMD and such supplemental features were used to predict the failure load (FL) of the specimens, previously determined through biomechanical testing, with multiregression and support vector regression. Prediction performance was measured by the root mean square error (RMSE); correlation with measured FL was evaluated using the coefficient of determination R2. The best prediction performance was achieved by a combination of DXA BMD and SIM-derived geometric features derived from the femoral head (RMSE: 0.869 ± 0.121, R2: 0.68 ± 0.079), which was significantly better than DXA BMD alone (RMSE: 0.948 ± 0.119, R2: 0.61 ± 0.101) (p < 10-4). For multivariate feature sets, SVR outperformed multiregression (p < 0.05). These results suggest that supplementing standard DXA BMD measurements with sophisticated femoral trabecular bone characterization and supervised learning techniques can significantly improve biomechanical strength prediction in proximal femur specimens.

Computational anatomy in the study of bone structure.

Osteoporosis is a major public health threat for millions of Americans with billions of dollars per year of national direct costs for osteoporotic fractures. Osteoporosis results in a decrease in overall bone mass and subsequent increase in the risk of bone fracture. Bone strength arises from the combination of bone size and shape, the distribution of bone mass throughout the structure, and the quality of the bone material. Advances in medical imaging have enabled a comprehensive assessment of bone structure through the analysis of high-resolution scans of relevant anatomical sites, eg, the proximal femur. However, conventional imaging analysis techniques use predefined regions of interest that do not take full advantage of such scans. Recently, computational anatomy, a set of imaging-based analysis algorithms, has emerged as a promising technique in studies of osteoporosis. Computational anatomy enables analyses that are not biased to one particular region and provide a more complete assessment of the whole structure. In this article, we review studies that have used computational anatomy to investigate the structure of the proximal femur in relation to age, fracture, osteoporotic treatment, and spaceflight effects.

Changes in knee cartilage T2 values over 24 months in subjects with and without risk factors for knee osteoarthritis and their association with focal knee lesions at baseline: data from the osteoarthritis initiative.

PURPOSE: To examine the changes in knee cartilage T2 values over 24 months in subjects with and without risk factors for knee osteoarthritis (OA) and their association with focal knee lesions at baseline. MATERIALS AND METHODS: Forty-one subjects without and 101 subjects with OA risk factors (such as history of knee injury or surgery) were selected from the Osteoarthritis Initiative database (age: 45-55 years, no radiographic OA in the right knee). Baseline magnetic resonance imaging (MRI) of the right knee were assessed for prevalence and grade of focal knee lesions. Right knee cartilage T2 measurements were performed in five compartments (patella, medial/lateral femur/tibia) at baseline and at 24-month follow-up. RESULTS: Compared to subjects without OA risk factors, those with OA risk factors showed no significant differences in baseline prevalence and grade of focal knee lesions (P > .05), but had significantly higher T2 values in the medial femur compartment at both timepoints (P < 0.05). T2 values averaged over all five compartments increased significantly over 24 months in both groups, but differences in T2 increase between the groups were not significant. Subjects with cartilage lesions showed significantly higher T2 values compared to subjects without cartilage lesions at both timepoints, but no accelerated T2 increase over 24 months (P > 0.05). CONCLUSION: Cartilage T2 values significantly increased over 24 months in subjects with and without OA risk factors, but neither the presence of OA risk factors nor the presence of cartilage lesions at baseline were associated with these T2 increases.

Characterization of the regional distribution of skeletal muscle adipose tissue in type 2 diabetes using chemical shift-based water/fat separation.

PURPOSE: To show the feasibility of assessing the spatial distribution of skeletal muscle adipose tissue using chemical shift-based water/fat separation and to characterize differences in calf intermuscular adipose tissue (IMAT) compartmentalization in patients with type 2 diabetes mellitus (T2DM) compared to healthy age-matched controls. MATERIALS AND METHODS: A chemical shift-based water/fat separation approach using a multiecho 3D spoiled gradient echo sequence was applied in a study of 64 patients, including 35 healthy controls and 29 subjects with T2DM. Masks were defined based on manual segmentations to compute fat volume within different compartments, including regions of subcutaneous adipose tissue (SAT) and six muscular regions. IMAT was divided into two compartments representing fat within the muscular regions (intraMF) and fat between the muscular regions (interMF). Two-sample Student's t-tests were used to compare fat volumes between the two groups. RESULTS: The subjects with T2DM had a lower volume of SAT compared to the healthy controls (P = 4 × 10(-5) ). There was no statistically significant difference in the IMAT volume between the two groups. However, the intraMF volume normalized by the IMAT volume was higher in the diabetics compared to the controls (P = 0.006). CONCLUSION: Chemical shift-based water/fat separation enables the quantification of fat volume within localized muscle regions, showing that the IMAT regional distribution is significantly different in T2DM compared to normal controls.

Imaging techniques to study diabetic bone disease.

PURPOSE OF REVIEW: This review article presents the most recent research on bone fragility in individuals with diabetes from a medical imaging perspective. RECENT FINDINGS: The widespread availability of dual-energy X-ray absorptiometry (DXA) and trabecular bone score (TBS) software has led to recent assessments of bone fragility with this texture parameter in several studies of type 2 diabetes mellitus (T2D), but in few of type 1 diabetes mellitus (T1D). Although most studies show a trend of reduced TBS values in T2D independent of areal bone mineral density (aBMD) of the lumbar spine, some studies also show the limitations of TBS in both T2D and T1D. Given the limitations of DXA to assess bone strength and investigate the etiology of bone fragility in diabetes, more investigators are incorporating three-dimensional (3D) medical imaging techniques in their studies. Recent use of 3D medical imaging to assess bone fragility in the setting of diabetes has been mostly limited to a few cross-sectional studies predominantly incorporating high-resolution peripheral quantitative computed tomography (HR-pQCT). Although HR-pQCT studies indicate higher tibial cortical porosity in subjects with T2D, results are inconsistent in T1D due to differences in study designs, sample sizes, and subject characteristics, among other factors. With respect to central CT, recent studies support a previous finding in the literature indicating femoral neck geometrical impairments in subjects with T2D and provide encouraging results for the incorporation of finite element analysis (FEA) to assess bone strength in studies of T2D. In the recent literature, there are no studies assessing bone fragility in T1D with QCT, and only two studies used pQCT reporting tibial and radial impairments in young women and children with T1D, respectively. Magnetic resonance imaging (MRI) has not been recently used in diabetic studies of bone fragility. SUMMARY: As bone fragility in diabetes is not explained by DXA-derived aBMD and given the limitations of cross-sectional studies, it is imperative to use 3D imaging techniques for longitudinal assessments of the density, quality, and microenvironment of bone to improve our understanding of the effects of diabetes on bone and reduce the risk of fracture in this large and vulnerable population of subjects with diabetes.

Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk.

Osteoporosis is a highly prevalent systemic skeletal disease that is characterized by low bone mass and microarchitectural bone deterioration. It predisposes to fragility fractures that can occur at various sites of the skeleton, but vertebral fractures (VFs) have been shown to be particularly common. Prevention strategies and timely intervention depend on reliable diagnosis and prediction of the individual fracture risk, and dual-energy X-ray absorptiometry (DXA) has been the reference standard for decades. Yet, DXA has its inherent limitations, and other techniques have shown potential as viable add-on or even stand-alone options. Specifically, three-dimensional (3 D) imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), are playing an increasing role. For CT, recent advances in medical image analysis now allow automatic vertebral segmentation and value extraction from single vertebral bodies using a deep-learning-based architecture that can be implemented in clinical practice. Regarding MRI, a variety of methods have been developed over recent years, including magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) that enable the extraction of a vertebral body's proton density fat fraction (PDFF) as a promising surrogate biomarker of bone health. Yet, imaging data from CT or MRI may be more efficiently used when combined with advanced analysis techniques such as texture analysis (TA; to provide spatially resolved assessments of vertebral body composition) or finite element analysis (FEA; to provide estimates of bone strength) to further improve fracture prediction. However, distinct and experimentally validated diagnostic criteria for osteoporosis based on CT- and MRI-derived measures have not yet been achieved, limiting broad transfer to clinical practice for these novel approaches. KEY POINTS:: · DXA is the reference standard for diagnosis and fracture prediction in osteoporosis, but it has important limitations.. · CT- and MRI-based methods are increasingly used as (opportunistic) approaches.. · For CT, particularly deep-learning-based automatic vertebral segmentation and value extraction seem promising.. · For MRI, multiple techniques including spectroscopy and chemical shift imaging are available to extract fat fractions.. · Texture and finite element analyses can provide additional measures for vertebral body composition and bone strength.. CITATION FORMAT: · Sollmann N, Kirschke JS, Kronthaler S et al. Imaging of the Osteoporotic Spine - Quantitative Approaches in Diagnostics and for the Prediction of the Individual Fracture Risk. Fortschr Röntgenstr 2022; 194: 1088 - 1099.

Cartilage in anterior cruciate ligament-reconstructed knees: MR imaging T1{rho} and T2--initial experience with 1-year follow-up.

PURPOSE: To longitudinally evaluate cartilage matrix changes by using magnetic resonance (MR) imaging T1(ρ) (T1 relaxation time in rotating frame) and T2 quantification and to study the relationship between meniscal damage and cartilage degeneration in anterior cruciate ligament (ACL)-reconstructed knees. MATERIALS AND METHODS: This was an institutional review board-approved, HIPAA-compliant study. Informed consent was obtained. Twelve patients with acute ACL injuries were imaged with 3.0-T MR imaging at baseline (after injury and prior to ACL reconstruction) and 1 year after ACL reconstruction. Ten age-matched healthy subjects were studied as controls. Cartilage T1(ρ) and T2 were quantified in full thickness, superficial, and deep layers of defined subcompartments at baseline and follow-up in ACL-injured knees and were compared with measures acquired in matched regions of control knees. Meniscal lesions were graded by using modified subscores of the Whole-Organ Magnetic Resonance Imaging Score system. RESULTS: T1(ρ) values of the posterolateral tibial cartilage in ACL-injured knees were significantly elevated at baseline compared with T1(ρ)values of control knees and were not fully recovered at 1-year follow-up. T1(ρ) values of weight-bearing medial femorotibial cartilage in ACL-injured knees were significantly elevated at 1-year follow-up compared with those of control knees. No significant differences in T2 values between ACL-injured and control knees were found. Patients with lesions in the posterior horn of the medial meniscus showed a greater increase of T1(ρ) and T2 from baseline to follow-up in adjacent cartilage than patients without lesions in the medial meniscus. CONCLUSION: Quantitative MR imaging T1(ρ) and T2 enable detection of changes in the cartilage matrix of ACL-reconstructed knees as early as 1 year after ACL reconstruction.

Atlas-based knee cartilage assessment.

Magnetic resonance imaging analysis of knee cartilage properties at corresponding anatomic locations could be a valuable tool in studies of knee osteoarthritis by enabling accurate comparisons at practically any region. A technique of this kind is presented in this study. The proposed technique is based on gray-level bone matching using affine transformations and free-form deformations thus eliminating the need of bone segmentations and landmark matching. Sixteen subjects of the osteoarthritis initiative with knee osteoarthritis (10 from baseline; 6 from 24-month follow-up) were included in this study. Baseline subjects were used to create a gray-level atlas of the patella with its corresponding mean cartilage thickness and T2 maps. Follow-up subjects were used to validate atlas-based point-to-point cartilage comparisons. All registrations were qualitatively evaluated with fused gray-level images of registered patellas. Quantitative evaluation was performed based on mean values of minimum Euclidean distances between matched bone-cartilage interfaces. A mean distance of 0.554 mm was obtained between the subjects used to build the atlas, and a mean distance of 0.633 mm was found between the atlas and validation subjects. The technique can be applied to other anatomical regions and with other cartilage measures. Qualitative and quantitative results demonstrate the accuracy of the technique and warrant its application in larger cross-sectional and longitudinal studies of osteoarthritis.

Longitudinal analysis of MRI T2 knee cartilage laminar organization in a subset of patients from the osteoarthritis initiative: a texture approach.

Cartilage magnetic resonance imaging T(2) relaxation time is sensitive to hydration, collagen content, and tissue anisotropy, and a potential imaging-based biomarker for knee osteoarthritis. This longitudinal pilot study presents an improved cartilage flattening technique that facilitates texture analysis using gray-level co-occurrence matrices parallel and perpendicular to the cartilage layers, and the application of this technique to the knee cartilage of 13 subjects of the osteoarthritis initiative at baseline, 1-year follow-up, and 2-year follow-up. Cartilage flattening showed minimum distortion (∼ 0.5 ms) of mean T(2) values between nonflattened and flattened T(2) maps. Gray-level co-occurrence matrices texture analysis of flattened T(2) maps detected a cartilage laminar organization at baseline, 1-year follow-up, and 2-year follow-up by yielding significant (P < 0.05) differences between texture parameters perpendicular and parallel to the cartilage layers. Tendencies showed higher contrast, dissimilarity, angular second moment, and energy perpendicular to the cartilage layers; and higher homogeneity, entropy, variance, and correlation parallel to them. Significant (P < 0.05) longitudinal texture changes were also detected reflecting subtle signs of a laminar disruption. Tendencies showed decreasing contrast, dissimilarity, and entropy; and increasing homogeneity, energy, and correlation. Results of this study warrant further investigation to complete the assessment of the usefulness of the presented methodology in the study of knee osteoarthritis.

Generation of an atlas of the proximal femur and its application to trabecular bone analysis.

Automatic placement of anatomically corresponding volumes of interest and comparison of parameters against a standard of reference are essential components in studies of trabecular bone. Only recently, in vivo MR images of the proximal femur, an important fracture site, could be acquired with high-spatial resolution. The purpose of this MRI trabecular bone study was two-fold: (1) to generate an atlas of the proximal femur to automatically place anatomically corresponding volumes of interest in a population study and (2) to demonstrate how mean models of geodesic topological analysis parameters can be generated to be used as potential standard of reference. Ten females were used to generate the atlas and geodesic topological analysis models, and 10 females were used to demonstrate the atlas-based trabecular bone analysis. All alignments were based on three-dimensional (3D) multiresolution affine transformations followed by 3D multiresolution free-form deformations. Mean distances less than 1 mm between aligned femora, and sharp edges in the atlas and in fused gray-level images of registered femora indicated that the anatomical variability was well accommodated and explained by the free-form deformations.

Evaluation of bone bruises and associated cartilage in anterior cruciate ligament-injured and -reconstructed knees using quantitative t(1ρ) magnetic resonance imaging: 1-year cohort study.

PURPOSE: To quantitate bone marrow edema-like lesions (BMELs) and the radiologic properties of cartilage in knees with acute anterior cruciate ligament (ACL) injuries using T(1ρ) magnetic resonance imaging over a 1-year period. METHODS: Nine patients with ACL injuries were studied. Magnetic resonance imaging scans were acquired within 8 weeks of the injury, after which ACL reconstruction surgery was performed. Images were then acquired 0.5, 6, and 12 months after reconstructions. The volume and signal intensity of BMELs were quantified at baseline and follow-up examinations. T(1ρ) values were quantified in cartilage overlying the BMEL (OC) and compared with surrounding cartilage at all time points. RESULTS: BMELs were most commonly found in the lateral tibia and lateral femoral condyle. Nearly 50% of BMELs resolved over a 1-year period. The T(1ρ) values of the OC in the lateral tibia, medial tibia, and medial femoral condyle were elevated compared with respective regions in surrounding cartilage at all time points; the difference was significant only in the lateral tibia (P < .05). The opposite results were found in the lateral femoral condyle. For the medial tibia and medial femoral condyle, none of the time periods was significantly different. The percent increase in T(1ρ) values of OC in the lateral tibia was significantly correlated with BMEL volume (r = 0.74, P < .05). At 1 year, the OC in the lateral tibia, medial tibia, and medial femoral condyle showed increased T(1ρ) values despite improvement of BMEL. CONCLUSIONS: In patients after ACL tear and reconstruction, (1) the cartilage overlying BMEL in the lateral tibia experiences persistent T(1ρ) signal changes immediately after acute injuries and at 1-year follow-up despite BMEL improvement, (2) the superficial layers of the overlying cartilage show greater matrix damage than the deep layers, and (3) the volume of the BMEL may predict the severity of the overlying matrix's damage in the lateral tibia. T(1ρ) is capable of quantitatively and noninvasively monitoring this damage and detecting early cartilage changes in the lateral tibia over time. LEVEL OF EVIDENCE: Level IV, therapeutic case series.