Root Mean Square Coefficient Of Variation Research Articles

Reproducibility of CT-based opportunistic vertebral volumetric bone mineral density measurements from an automated segmentation framework

BackgroundTo investigate the reproducibility of automated volumetric bone mineral density (vBMD) measurements from routine thoracoabdominal computed tomography (CT) assessed with segmentations by a convolutional neural network and automated correction of contrast phases, on diverse scanners, with scanner-specific asynchronous or scanner-agnostic calibrations.MethodsWe obtained 679 observations from 278 CT scans in 121 patients (77 males, 63.6%) studied from 04/2019 to 06/2020. Observations consisted of two vBMD measurements from Δdifferent reconstruction kernels (n = 169), Δcontrast phases (n = 133), scan Δsessions (n = 123), Δscanners (n = 63), or Δall of the aforementioned (n = 20), and observations lacking scanner-specific calibration (n = 171). Precision was assessed using root-mean-square error (RMSE) and root-mean-square coefficient of variation (RMSCV). Cross-measurement agreement was assessed using Bland-Altman plots; outliers within 95% confidence interval of the limits of agreement were reviewed.ResultsRepeated measurements from Δdifferent reconstruction kernels were highly precise (RMSE 3.0 mg/cm3; RMSCV 1.3%), even for consecutive scans with different Δcontrast phases (RMSCV 2.9%). Measurements from different Δscan sessions or Δscanners showed decreased precision (RMSCV 4.7% and 4.9%, respectively). Plot-review identified 12 outliers from different scan Δsessions, with signs of hydropic decompensation. Observations with Δall differences showed decreased precision compared to those lacking scanner-specific calibration (RMSCV 5.9 and 3.7, respectively).ConclusionAutomatic vBMD assessment from routine CT is precise across varying setups, when calibrated appropriately. Low precision was found in patients with signs of new or worsening hydropic decompensation, what should be considered an exclusion criterion for both opportunistic and dedicated quantitative CT.Relevance statementAutomated CT-based vBMD measurements are precise in various scenarios, including cross-session and cross-scanner settings, and may therefore facilitate opportunistic screening for osteoporosis and surveillance of BMD in patients undergoing routine clinical CT scans.Key PointsArtificial intelligence-based tools facilitate BMD measurements in routine clinical CT datasets.Automated BMD measurements are highly reproducible in various settings.Reliable, automated opportunistic osteoporosis diagnostics allow for large-scale application.Graphical

Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions.

Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk. However, it provides only 2-D representation of bone and is associated with other technical limitations. Thus, alternative methods are needed. To develop and evaluate an ultra-low dose (ULD) hip CT-based automated method for assessment of volumetric bone mineral density (vBMD) at proximal femoral subregions. An automated method was developed to segment the proximal femur in ULD hip CT images and delineate femoral subregions. The computational pipeline consists of deep learning (DL)-based computation of femur likelihood map followed by shape model-based femur segmentation and finite element analysis-based warping of a reference subregion labeling onto individual femur shapes. Finally, vBMD is computed over each subregion in the target image using a calibration phantom scan. A total of 100 participants (50 females) were recruited from the Genetic Epidemiology of COPD (COPDGene) study, and ULD hip CT imaging, equivalent to 18 days of background radiation received by U.S. residents, was performed on each participant. Additional hip CT imaging using a clinical protocol was performed on 12 participants and repeat ULD hip CT was acquired on another five participants. ULD CT images from 80 participants were used to train the DL network; ULD CT images of the remaining 20 participants as well as clinical and repeat ULD CT images were used to evaluate the accuracy, generalizability, and reproducibility of segmentation of femoral subregions. Finally, clinical CT and repeat ULD CT images were used to evaluate accuracy and reproducibility of ULD CT-based automated measurements of femoral vBMD. Dice scores of accuracy (n=20), reproducibility (n=5), and generalizability (n=12) of ULD CT-based automated subregion segmentation were 0.990, 0.982, and 0.977, respectively, for the femoral head and 0.941, 0.970, and 0.960, respectively, for the femoral neck. ULD CT-based regional vBMD showed Pearson and concordance correlation coefficients of 0.994 and 0.977, respectively, and a root-mean-square coefficient of variation (RMSCV) (%) of 1.39% with the clinical CT-derived reference measure. After 3-digit approximation, each of Pearson and concordance correlation coefficients as well as intraclass correlation coefficient (ICC) between baseline and repeat scans were 0.996 with RMSCV of 0.72%. Results of ULD CT-based bone analysis on 100 participants (age (mean±SD) 73.6±6.6 years) show that males have significantly greater (p<0.01) vBMD at the femoral head and trochanteric regions than females, while females have moderately greater vBMD (p=0.05) at the medial half of the femoral neck than males. Deep learning, combined with shape model and finite element analysis, offers an accurate, reproducible, and generalizable algorithm for automated segmentation of the proximal femur and anatomic femoral subregions using ULD hip CT images. ULD CT-based regional measures of femoral vBMD are accurate and reproducible and demonstrate regional differences between males and females.

Reliability and changes in knee cartilage T2 relaxation time from 6 to 24 months after anatomic anterior cruciate ligament reconstruction.

The objectives of this study were to evaluate the reliability of cartilage T2 relaxation time measurements and to identify focal changes in T2 relaxation on the affected knee from 6 to 24 months after anatomic anterior cruciate ligament reconstruction (ACLR). Data from 41 patients who received anatomic ACLR were analyzed. A bilateral 3.0-T MRI was acquired 6 and 24 months after ACLR. T2 relaxation time was measured in subregions of the femoral condyle and the tibial plateau. The root-mean-square coefficient of variation (RMSCV) was calculated to evaluate the reliability of T2 relaxation time in the contralateral knee. Subregion changes in the affected knee T2 relaxation time were identified using the contralateral knee as a reference. The superficial and full thickness layers of the central and inner regions showed good reliability. Conversely, the outer regions on the femoral side and regions in the deep layers showed poor reliability. T2 relaxation time increased in only 3 regions on the affected knee when controlling for changes in the contralateral knee, while changes in T2 relaxation time were identified in 14 regions when not using the contralateral knee as a reference. In conclusion, evaluation of cartilage degeneration by T2 relaxation time after ACLR is most reliable for central and inner cartilage regions. Cartilage degeneration occurs in the central and outer regions of the lateral femoral condyle from 6 to 24 months after anatomic ACLR.

Long-term reproducibility of opportunistically assessed vertebral bone mineral density and texture features in routine clinical multi-detector computed tomography using an automated segmentation framework.

To investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in a single scanner environment. Patients who underwent two routine clinical thoraco-abdominal MDCT exams at a single scanner with a time interval of 6 to 26 months (n=203, 131 males; time interval mean, 13 months; median, 12 months) were included in this observational study. Exclusion criteria were metabolic and hematological disorders, bone metastases, use of bone-active medications, and history of osteoporotic vertebral fractures (VFs) or prior diagnosis of osteoporosis. A convolutional neural network (CNN)-based framework was used for automated spine labeling and segmentation (T5-L5), asynchronous Hounsfield unit (HU)-to-BMD calibration, and correction for the intravenous contrast medium phase. Vertebral vBMD and six texture features [varianceglobal, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP)] were extracted for mid- (T5-T8) and lower thoracic (T9-T12), and lumbar vertebrae (L1-L5), respectively. Relative annual changes were calculated in texture features and vBMD for each vertebral level and sorted by sex, and changes were checked for statistical significance (P<0.05) using paired t-tests. Root mean square coefficient of variation (RMSCV) and root mean square error (RMSE) were calculated as measures of variability. SRE, LRE, RLN, and RP exhibited substantial reproducibility with RMSCV-values below 2%, for both sexes and at all spine levels, while vBMD was less reproducible (RMSCV =11.9-16.2%). Entropy showed highest variability (RMSCV =4.34-7.69%) due to statistically significant increases [range, mean ± standard deviation: (4.40±5.78)% to (8.36±8.66)%, P<0.001]. RMSCV of varianceglobal ranged from 1.60% to 3.03%. Opportunistic assessment of texture features in a single scanner environment using the presented CNN-based framework yields substantial reproducibility, outperforming vBMD reproducibility. Lowest scan-rescan variability was found for higher-order texture features. Further studies are warranted to determine, whether microarchitectural changes to the trabecular bone may be assessed through texture features.

Short-Term Precision and Repeatability of Radiofrequency Echographic Multi Spectrometry (REMS) on Lumbar Spine and Proximal Femur: An In Vivo Study.

To determine the short-term intra-operator precision and inter-operator repeatability of radiofrequency echographic multi-spectrometry (REMS) at the lumbar spine (LS) and proximal femur (FEM). All patients underwent an ultrasound scan of the LS and FEM. Both precision and repeatability, expressed as root-mean-square coefficient of variation (RMS-CV) and least significant change (LSC) were obtained using data from two consecutive REMS acquisitions by the same operator or two different operators, respectively. The precision was also assessed in the cohort stratified according to BMI classification. The mean (±SD) age of our subjects was 48.9 ± 6.8 for LS and 48.3 ± 6.1 for FEM. Precision was assessed on 42 subjects at LS and 37 subjects on FEM. Mean (±SD) BMI was 24.71 ± 4.2 for LS and 25.0 ± 4.84 for FEM. Respectively, the intra-operator precision error (RMS-CV) and LSC resulted in 0.47% and 1.29% at the spine and 0.32% and 0.89% at the proximal femur evaluation. The inter-operator variability investigated at the LS yielded an RMS-CV error of 0.55% and LSC of 1.52%, whereas for the FEM, the RMS-CV was 0.51% and the LSC was 1.40%. Similar values were found when subjects were divided into BMI subgroups. REMS technique provides a precise estimation of the US-BMD independent of subjects' BMI differences.

Comparison of the Discovery A and Stratos DR densitometers for assessing whole-body and regional bone mineral density and body composition.

The agreement between the Stratos DR and Discovery A densitometers was assessed for measurements of whole-body (WB) and regional fat mass (FM), fat-free soft tissue (FFST) and bone mineral density (BMD). Moreover, the precision of the Stratos DR was also evaluated. Fifty participants (35 women, 70%) were measured consecutively, once on the Discovery A and once on the Stratos DR. In a subgroup of participants (n = 29), two successive measurements with the Stratos DR were also performed. FM, FFSTand BMD measured with the two devices were highly correlated, with a coefficient of correlation ranging from 0.80 to 0.99. Bland-Altman analyses indicated significant bias between the two devices for all measurements. Thus, compared to the Discovery A, the Stratos DR underestimated WB BMD and WB and regional FM and FFST, with the exception of trunk FM and visceral adipose tissue (VAT), which were overestimated. Precision error for the Stratos DR, when expressed as root mean square-coefficient of variation (RMS-CV%) for FM, was 1.4% for WB, 3.0% for the gynoid and android regions, and 15.9% for VAT. The RMS-CV% for FFST was 1.0% for WB. The root mean square of standard deviationfor WB BMD was 0.018 g/cm², corresponding to a 1.4% CV. The least significant change was 0.050 g/cm² (SD), and 4.0% was considered to be a significant biological change. Differences between the Stratos DR and Discovery A measurements are significant and require the use of translational cross-calibration equations. For most of the BMD and body composition parameters, our results demonstrated good Stratos DR precision.

DLCO Biologic Quality-Control Findings From a Multi-Center Global Study.

The 2017 American Thoracic Society/European Respiratory Society (ATS/ERS) diffusing capacity of the lung for carbon monoxide (DLCO) standards specify a control rule for assessing biologic quality control (BioQC) but have limited guidance on how to establish expected values for control rule variables. This study aimed to determine expected values for DLCO BioQC using coefficient of variation (CV) and compare that the mean ± 2 SD control rule yields the same precision as mean ± 12% of the mean. DLCO BioQC data were collected from a multi-center inhaled medication study. This descriptive study spanned 42 months ending in 2018. The annual DLCO CV was based upon 10 DLCO values separated by at least 5 d. The root mean square CV (RMSCV) was computed for each year and Friedman test evaluated within subject annual CV changes. Ninetieth percentile values were computed for annual control rule limits/mean DLCO. Of 217 BioQCs, the study's first year had 168 subjects with fewer in subsequent years. Annual CV values from RMSCV were 5.3, 4.5, and 4.6% in years 1, 2, and 3, respectively. No change was seen in the CV for those subjects with data for all 3 years, n = 24, P = .07. The 90th percentile of measurements 2 SD/mean DLCO were 15, 12.4, and 11% in years 1, 2, and 3, respectively. A DLCO BioQC CV ≤ 6% is achievable across multiple sites, technologists, and brands of equipment. This CV value assures that measurements for control rule variables emerge from an expected range. A control rule of mean ± 2 SD appeared to yield similar results as the mean ± 12% of the mean rule reported in the 2017 ATS/ERS DLCO standards.

T2 mapping of healthy knee cartilage: multicenter multivendor reproducibility.

T2 mapping is increasingly used to quantify cartilage degeneration in knee osteoarthritis (OA), yet reproducibility studies in a multicenter setting are limited. The purpose of this study was to determine the longitudinal reproducibility and multicenter variation of cartilage T2 mapping, using various MRI equipment and acquisition protocols. In this prospective multicenter study, four traveling, healthy human subjects underwent T2 mapping twice at five different centers with a 6-month-interval. Centers had various MRI scanners, field strengths, and T2 mapping acquisition protocols. Mean T2 values were calculated in six cartilage regions of interest (ROIs) as well as an average value per patient. A phantom was scanned once at each center. To evaluate longitudinal reproducibility, intraclass correlation coefficients (ICC), root-mean-square coefficient of variation (RMS-CV), and a Bland-Altman plot were used. To assess the variation of in vivo and phantom T2 values across centers, ANOVA was performed. ICCs of the T2 mapping measurements per ROI and the ROI's combined ranged from 0.73 to 0.91, indicating good to excellent longitudinal reproducibility. RMS-CVs ranged from 1.1% to 1.5% (per ROI) and 0.6% to 1.6% (ROIs combined) across the centers. A Bland-Altman plot did not reveal a systematic error. Evident, but consistent, discrepancies in T2 values were observed across centers, both in vivo and in the phantom. The results of this study suggest that T2 mapping can be used to longitudinal assess cartilage degeneration in multicenter studies. Given the differences in absolute cartilage T2 values across centers, absolute T2 values derived from various centers in multicenter multivendor trials should not be pooled.

Finite Element Analysis-Based Vertebral Bone Strength Prediction Using MDCT Data: How Low Can We Go?

Objective: To study the impact of dose reduction in MDCT images through tube current reduction or sparse sampling on the vertebral bone strength prediction using finite element (FE) analysis for fracture risk assessment.Methods: Routine MDCT data covering lumbar vertebrae of 12 subjects (six male; six female; 74.70 ± 9.13 years old) were included in this study. Sparsely sampled and virtually reduced tube current–based MDCT images were computed using statistical iterative reconstruction (SIR) with reduced dose levels at 50, 25, and 10% of the tube current and original projections, respectively. Subject-specific static non-linear FE analyses were performed on vertebra models (L1, L2, and L3) 3-D-reconstructed from those dose-reduced MDCT images to predict bone strength. Coefficient of correlation (R2), Bland-Altman plots, and root mean square coefficient of variation (RMSCV) were calculated to find the variation in the FE-predicted strength at different dose levels, using high-intensity dose-based strength as the reference.Results: FE-predicted failure loads were not significantly affected by up to 90% dose reduction through sparse sampling (R2 = 0.93, RMSCV = 8.6% for 50%; R2 = 0.89, RMSCV = 11.90% for 75%; R2 = 0.86, RMSCV = 11.30% for 90%) and up to 50% dose reduction through tube current reduction method (R2 = 0.96, RMSCV = 12.06%). However, further reduction in dose with the tube current reduction method affected the ability to predict the failure load accurately (R2 = 0.88, RMSCV = 22.04% for 75%; R2 = 0.43, RMSCV = 54.18% for 90%).Conclusion: Results from this study suggest that a 50% radiation dose reduction through reduced tube current and a 90% radiation dose reduction through sparse sampling can be used to predict vertebral bone strength. Our findings suggest that the sparse sampling–based method performs better than the tube current–reduction method in generating images required for FE-based bone strength prediction models.

Repeatability and discrimination validity of cartilage imaging biomarkers for experimental medicine studies of knee osteoarthritis

PURPOSE The utility of magnetic resonance imaging (MRI) quantitative imaging biomarkers (QIBs) of cartilage in experimental medicine studies of potential disease modifying osteoarthritis treatments (DMOATs) is uncertain due to the small sample sizes and short follow-up involved. To be relevant to such studies, candidate QIBs must demonstrate acceptable repeatability, discriminative ability and responsiveness. The purpose of this study was to evaluate test-retest repeatability and discriminative ability of 4 cartilage QIBs at the knee (thickness, T1rho, T2 and delayed gadolinium enhanced MRI of cartilage [dGEMRIC]) to assess their utility in experimental medicine studies. METHODS We imaged 9 participants with mild-moderate knee osteoarthritis (OA), characterised by radiographs with medial tibiofemoral predominant disease and Kellgren-Lawrence grades 2-3, and 4 healthy volunteers (HVs) matched for age, sex and body mass index. Participants were imaged at baseline and 1 month. MR studies were performed on a 3T system (MR 750, GE Healthcare) and were split into 2 sessions. The first MR session included a 3-dimensional spoiled gradient echo (3D SPGR) sequence and T1rho and T2 mapping sequences. At the end of this session, we administered an intravenous gadolinium based contrast agent (Dotarem, Guerbet LLC) at double dose (0.2 mmol/kg). Participants then performed 10 minutes of exercise on a stationary cycle to facilitate contrast penetration into the joint for dGEMRIC. The second MR session began 90 minutes following injection of contrast agent and consisted of T1 mapping using a variable flip angle technique. MR pulse sequence details are provided in table 1. We performed surface based analysis of cartilage parameters using Stradwin software (http://mi.eng.cam.ac.uk/~rwp/stradwin). In brief, this consists of semi-automated thickness measurement on 3D SPGR images, with generation of accurate inner and outer cartilage surfaces. Following rigid registration of the compositional (T1rho, T2, dGEMRIC) data to the 3D SPGR images, the same surfaces were used to sample the compositional data. This analysis pipeline allows each parameter to be measured at ~5,000 surface vertices per participant. We assessed overall (pooled OA and HV data) test-retest repeatability by calculating the root-mean-square coefficient of variation (RMS-CV) and the smallest detectable change (SDC) for each parameter. We assessed overall discriminative validity by estimating effect sizes for the difference in the mean value of each parameter in OA participants and HVs. We also mapped the test-retest errors and mean difference in each parameter between groups onto a representative surface for each cartilage region. RESULTS Participant characteristics are provided in table 2. RMS-CVs, SDCs and effect size estimates are provided in table 3. Overall test-retest RMS-CV values ranged from 2.5% (T1rho) to 10.3% (dGEMRIC). The largest overall effect size was demonstrated for dGEMRIC (-1.3, 90% confidence interval [CI] -2.3 to -0.2), followed by thickness (-0.67, 90% CI -1.5 to 0.3), T1rho and T2 (both 0.61, 90% CI -0.4 to 1.5). Mapping of test-retest errors and between-group differences to a representative surface revealed substantial spatial heterogeneity in these metrics for all parameters (figure 1). This suggests that surface based approaches may offer improved sensitivity over traditional region of interest based measurements. CONCLUSION This study demonstrates that cartilage QIBs may be useful in experimental medicine studies of knee osteoarthritis. Statistical approaches reflecting the spatial heterogeneity of changes in cartilage should be used to provide an indication of where significant results are located, not just whether an average value is significantly different. Future work will evaluate responsiveness of these cartilage QIBs.

B1-insensitive T2 mapping of healthy thigh muscles using a T2-prepared 3D TSE sequence.

PurposeTo propose a T2-prepared 3D turbo spin echo (T2prep 3D TSE) sequence for B1-insensitive skeletal muscle T2 mapping and compare its performance with 2D and 3D multi-echo spin echo (MESE) for T2 mapping in thigh muscles of healthy subjects.MethodsThe performance of 2D MESE, 3D MESE and the proposed T2prep 3D TSE in the presence of transmit B1 and B0 inhomogeneities was first simulated. The thigh muscles of ten young and healthy subjects were then scanned on a 3 T system and T2 mapping was performed using the three sequences. Transmit B1-maps and proton density fat fraction (PDFF) maps were also acquired. The subjects were scanned three times to assess reproducibility. T2 values were compared among sequences and their sensitivity to B1 inhomogeneities was compared to simulation results. Correlations were also determined between T2 values, PDFF and B1.ResultsThe left rectus femoris muscle showed the largest B1 deviations from the nominal value (from 54.2% to 92.9%). Significant negative correlations between T2 values and B1 values were found in the left rectus femoris muscle for 3D MESE (r = -0.72, p<0.001) and 2D MESE (r = -0.71, p<0.001), but not for T2prep 3D TSE (r = -0.32, p = 0.09). Reproducibility of T2 expressed by root mean square coefficients of variation (RMSCVs) were equal to 3.5% in T2prep 3D TSE, 2.6% in 3D MESE and 2.4% in 2D MESE. Significant differences between T2 values of 3D sequences (T2prep 3D TSE and 3D MESE) and 2D MESE were found in all muscles with the highest values for 2D MESE (p<0.05). No significant correlations were found between PDFF and T2 values.ConclusionA strong influence of an inhomogeneous B1 field on the T2 values of 3D MESE and 2D MESE was shown, whereas the proposed T2prep 3D TSE gives B1-insensitive and reproducible thigh muscle T2 mapping.

Human runners exhibit a least variable gait speed

ABSTRACTThis study characterises the relationship between gait variability and speed in runners using data from trunk accelerations in each axis.Twelve participants of varying fitness ran on the treadmill with three sessions of six randomly ordered self-selected speeds. A VO2max test was conducted on the fourth session. Running gait was tracked with inertial sensors. The occurrence of a mid-range speed was analysed for the anterior–posterior, vertical and lateral directional coefficient of variation (CV) of root mean square (RMS) acceleration data.One participant with noisy gait signals was omitted. The results show all remaining participants consistently showed significant quadratic U-shaped relationships between vertical RMS CV acceleration and speed. Neither anterior–posterior nor lateral RMS CV acceleration were clearly related to speed. These least variable gait speeds were similar to estimates of optimal speed derived from minimum cost of transport with speed.In conclusion, there exists a mid-range speed for each runner with the least variable gait in the vertical direction, and this occurred significantly more often than would be expected by chance (P < 0.05). However, there are no prominent patterns for the anterior–posterior and lateral directions. This finding supports anecdotal evidence from runners and coaches concerning gait consistency.

Definition for Rheumatoid Arthritis Erosions Imaged with High Resolution Peripheral Quantitative Computed Tomography and Interreader Reliability for Detection and Measurement.

High-resolution peripheral quantitative computed tomography (HR-pQCT) sensitively detects erosions in rheumatoid arthritis (RA); however, nonpathological cortical bone disruptions are potentially misclassified as erosive. Our objectives were to set and test a definition for pathologic cortical bone disruptions in RA and to standardize reference landmarks for measuring erosion size. HR-pQCT images of metacarpophalangeal joints of RA and control subjects were used in an iterative process to achieve consensus on the definition and reference landmarks. Independent readers (n = 11) applied the definition to score 58 joints and measure pathologic erosions in 2 perpendicular multiplanar reformations for their maximum width and depth. Interreader reliability for erosion detection and variability in measurements between readers [root mean square coefficient of variation (RMSCV), intraclass correlation (ICC)] were calculated. Pathologic erosions were defined as cortical breaks extending over a minimum of 2 consecutive slices in perpendicular planes, with underlying trabecular bone loss and a nonlinear shape. Interreader agreement for classifying pathologic erosions was 90.2%, whereas variability for width and depth erosion assessment was observed (RMSCV perpendicular width 12.3%, axial width 20.6%, perpendicular depth 24.0%, axial depth 22.2%; ICC perpendicular width 0.206, axial width 0.665, axial depth 0.871, perpendicular depth 0.783). Mean erosion width was 1.84 mm (range 0.16-8.90) and mean depth was 1.86 mm (range 0.30-8.00). We propose a new definition for erosions visualized with HR-pQCT imaging. Interreader reliability for erosion detection is good, but further refinement of selection of landmarks for erosion size measurement, or automated volumetric methods, will be pursued.

T1ρ Hip Cartilage Mapping in Assessing Patients With Cam Morphology: How Can We Optimize the Regions of Interest?

T1ρ MRI has been shown feasible to detect the biochemical status of hip cartilage, but various region-of-interest strategies have been used, compromising the reproducibility and comparability between different institutions and studies. The purposes of this study were (1) to determine representative regions of interest (ROIs) for cartilage T1ρ mapping in hips with a cam deformity; and (2) to assess intra- and interobserver reliability for cartilage T1ρ mapping in hips with a cam deformity. The local ethics committee approved this prospective study with written informed consent obtained. Between 2010 and 2013, in 54 hips (54 patients), T1ρ 1.5-T MRI was performed. Thirty-eight hips (38 patients; 89% male) with an average age of 35 ± 7.5 years (range, 23-51 tears) were diagnosed with a cam deformity; 16 hips (16 patients; 87% male) with an average age of 34 ± 7 years (range, 23-47 years) were included in the control group. Of the 38 patients with a cam deformity, 20 were pain-free and 18 symptomatic patients underwent surgery after 6 months of failed nonsurgical management of antiinflammatories and physical therapy. Exclusion criteria were radiologic sings of osteoarthritis with Tönnis Grade 2 or higher as well as previous hip surgery. Three region-of-interest (ROI) selections were analyzed: Method 1: as a whole; Method 2: as 36 to 54 small ROIs (sections of 30° in the sagittal plane and 3 mm in the transverse plane); Method 3a: as six ROIs (sections of 90° in the sagittal plane and one-third of the acetabular depth in the transverse plane: the anterosuperior and posterosuperior quadrants, divided into lateral, intermediate, and medial thirds); and Method 3b: as the ratio (anterosuperior over posterosuperior quadrant). ROIs in Method 3 represent the region of macroscopic cartilage damage, described in intraoperative findings. To asses interobserver reliability, 10 patients were analyzed by two observers (HA, GM). For intraobserver reliability, 20 hip MRIs were analyzed twice by one observer (HA). To assess interscan reliability, three patients underwent two scans within a time period of 2 weeks and were analyzed twice by one observer (HA). T1ρ values were compared using Student's t test. Interclass correlation coefficient (ICC) and root mean square coefficient of variation (RMS-CV) were used to analyze intraobserver, interobserver, and interscan reliability. Patients with a cam deformity showed increased T1ρ values in the whole hip cartilage (mean: 34.0 ± 3.8 ms versus 31.4 ± 3.0 ms; mean difference: 2.5; 95% confidence interval [CI], 4.7-0.4; p = 0.019; Method 1), mainly anterolateral (2), in the lateral and medial thirds of the anterosuperior quadrant (mean: 32.3 ± 4.9 ms versus 29.4 ± 4.1 ms; mean difference: 3.0; 95% CI, 5.8-0.2; p = 0.039 and mean 36.5 ± 5.6 ms versus 32.6 ± 3.8 ms; mean difference: 3.8; 95% CI, 6.9-0.8; p = 0.014), and in the medial third of the posterosuperior quadrant (mean: 34.4 ± 5.5 ms versus 31.1 ± 3.9 ms; mean difference: 3.1; 95% CI, 6.2-0.1; p = 0.039) (3a). The ratio was increased in the lateral third (mean: 1.00 ± 0.12 versus 0.90 ± 0.15; mean difference: 0.10; 95% CI, 0.18-0.2; p = 0.018) (3b). ICC and RMS-CV were 0.965 and 4% (intraobserver), 0.953 and 4% (interobserver), and 0.988 (all p < 0.001) and 9% (inter-MR scan), respectively. Cartilage T1ρ MRI mapping in hips is feasible at 1.5 T with strong inter-, intraobserver, and inter-MR scan reliability. The six ROIs (Method 3) showed a difference of T1ρ values anterolateralquadrant, consistent with the dominant area of cartilage injury in cam femoroacetabular impingement, and antero- and posteromedial, indicating involvement of the entire hip cartilage health. The six ROIs (Method 3) have been shown feasible to assess cartilage damage in hips with a cam deformity using T1ρ MRI. We suggest applying this ROI selection for further studies using quantitative MRI for assessment of cartilage damage in hips with a cam deformity to achieve better comparability and reproducibility between different studies. The application of this ROI selection on hips with other deformities (eg, pincer deformity, developmental dysplasia of the hip, and acetabular retroversion) has to be analyzed and potentially adapted. Level III, diagnostic study.

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

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. 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. 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. • 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.

In vivo measurement reproducibility of femoral neck microarchitectural parameters derived from 3T MR images.

To evaluate the within-day and between-day measurement reproducibility of in vivo 3D MRI assessment of trabecular bone microarchitecture of the proximal femur. This Health Insurance Portability and Accountability Act (HIPPA)-compliant, Institutional Review Board (IRB)-approved study was conducted on 11 healthy subjects (mean age = 57.4 ± 14.1 years) with written informed consent. All subjects underwent a 3T MRI hip scan in vivo (0.234 × 0.234 × 1.5 mm) at three timepoints: baseline, second scan same day (intrascan), and third scan 1 week later (interscan). We applied digital topological analysis and volumetric topological analysis to compute the following microarchitectural parameters within the femoral neck: total bone volume, bone volume fraction, markers of trabecular number (skeleton density), connectivity (junctions), plate-like structure (surfaces), plate width, and trabecular thickness. Reproducibility was assessed using root-mean-square coefficient of variation (RMS-CV) and intraclass correlation coefficient (ICC). The within-day RMS-CVs ranged from 2.3% to 7.8%, and the between-day RMS-CVs ranged from 4.0% to 7.3% across all parameters. The within-day ICCs ranged from 0.931 to 0.989, and the between-day ICCs ranged from 0.934 to 0.971 across all parameters. These results demonstrate high reproducibility for trabecular bone microarchitecture measures derived from 3T MR images of the proximal femur. The measurement reproducibility is within a range suitable for clinical cross-sectional and longitudinal studies in osteoporosis.

MR T1ρ quantification of cartilage focal lesions in acutely injured knees: correlation with arthroscopic evaluation

ObjectiveQuantitative T1ρ MRI has been suggested as a promising tool to detect changes in cartilage composition that are characteristic of cartilage damage and degeneration. The objective of this study was to evaluate the capability of MR T1ρ to detect cartilage lesions as evaluated by arthroscopy in acutely ACL-injured knees and to compare with the Whole-Organ Magnetic Resonance Imaging Score (WORMS) using clinical standard MRI. MethodTen healthy controls (mean age 35) with no ACL injury or history of osteoarthritis (OA) and 10 patients with acute ACL injuries (mean age 39) were scanned at 3 Tesla (3T). ACL patients underwent ACL reconstruction, where focal lesions were graded according to an Outerbridge grading system during arthroscopic evaluation. Normalized MR T1ρ values (T1ρ z-scores normalized to control values in matched regions) in full thickness, and superficial and deep layers of cartilage were compared between defined sub-compartments with and without focal lesions. Intraclass (ICC) correlation and the root mean square coefficient of variation (RMS-CV) were performed to evaluate the inter-observer reproducibility of T1ρ quantification. Sub-compartments of cartilage were also evaluated using WORMS scoring and compared to their Outerbridge score respectively. ResultsThe inter-observer ICC and the RMS-CV of the sub-compartment T1ρ quantification were 0.961 and 3.9%, respectively. The average T1ρ z-scores were significantly increased in sub-compartments with focal lesions compared to those without focal lesions and to the control cohort (p<0.05). ConclusionOur results indicate that T1ρ provided a better diagnostic capability than clinical standard MRI grading in detecting focal cartilage abnormalities after acute injuries. Quantitative MRI may have great potential in detecting cartilage abnormalities and degeneration non-invasively, which are occult with standard morphological MRI.

Precision of High-Resolution Peripheral Quantitative Computed Tomography Measurement Variables: Influence of Gender, Examination Site, and Age

High-resolution peripheral quantitative computed tomography (HR-pQCT) is increasingly being used in the research setting to assess the effects of osteoporosis treatments and disease on trabecular and cortical bone compartments. Further in-depth study of HR-pQCT measurement variables is essential to ensure study strength and statistical confidence when designing large multicenter studies. Duplicate HR-pQCT examinations of the distal radius and tibia were performed in 180 healthy men and women ages 16-18, 30-32, and >70 years. HR-pQCT images were processed using standard and extended cortical bone analysis techniques. Biomechanical properties of bone were assessed using finite element analysis. Percent root mean square coefficient of variation (RMSCV) was calculated for each measurement variable. Age, site, and gender influences on measurement variability were investigated using variance ratio tests. Smaller precision errors were observed for densitometric (0.2-5.5%) than for microstructural (1.2-7.0%), extended cortical bone (3.4-20.3%), and biomechanical (0.3-9.9%) measures at both the radius and tibia. Tibial measurements (RMSCVs = 0.2-7.4%) tended to be more precise than radial measurements (RMSCVs = 0.7-20.3%). Variability was influenced by age, site, and gender (all p < 0.05). HR-pQCT measurements for the tibia were more precise than those for the radius, and this may be explained by the larger bone volumes examined and the reduced likelihood of movement artifact. The greater measurement variability observed for older volunteers may be due to the loss of bone density and microstructural integrity with age.

Simultaneous acquisition of T1ρand T2quantification in knee cartilage: Repeatability and diurnal variation

To develop a robust sequence that combines T1ρ and T2 quantifications and to examine the in vivo repeatability and diurnal variation of T1ρ and T2 quantifications in knee cartilage. Six healthy volunteers were scanned in the morning and afternoon on 2 days using a combined T1ρ and T2 quantification sequence developed in this study. Repeatability of T1ρ and T2 quantification was estimated using root-mean-square coefficients-of-variation (RMS-CV). T1ρ and T2 values from morning scans were compared to those from afternoon scans using paired t-tests. The overall RMS-CV of in vivo T1ρ and T2 quantification was 5.3% and 5.2%, respectively. The RMS-CV of am scans was 4.2% and 5.0% while the RMS-CV of pm scans was 6.0% and 6.3% for T1ρ and T2 , respectively. No significant difference was found between T1ρ or T2 values in the morning and in the afternoon. A sequence that combines T1ρ and T2 quantification with scan time less than 10 minutes and is robust to B0 and B1 inhomogeneity was developed with excellent repeatability. For a cohort with low-level daily activity, although no significant diurnal variation of cartilage MR relaxation times was observed, the afternoon scans had inferior repeatability compared to morning scans.

Multicenter precision of cortical and trabecular bone quality measures assessed by high-resolution peripheral quantitative computed tomography

High-resolution peripheral quantitative computed tomography (HR-pQCT) has recently been introduced as a clinical research tool for in vivo assessment of bone quality. The utility of this technology to address important skeletal health questions requires translation to standardized multicenter data pools. Our goal was to evaluate the feasibility of pooling data in multicenter HR-pQCT imaging trials. Reproducibility imaging experiments were performed using structure and composition-realistic phantoms constructed from cadaveric radii. Single-center precision was determined by repeat scanning over short-term (<72 hours), intermediate-term (3-5 months), and long-term intervals (28 months). Multicenter precision was determined by imaging the phantoms at nine different HR-pQCT centers. Least significant change (LSC) and root mean squared coefficient of variation (RMSCV) for each interval and across centers was calculated for bone density, geometry, microstructure, and biomechanical parameters. Single-center short-term RMSCVs were <1% for all parameters except cortical thickness (Ct.Th) (1.1%), spatial variability in cortical thickness (Ct.Th.SD) (2.6%), standard deviation of trabecular separation (Tb.Sp.SD) (1.8%), and porosity measures (6% to 8%). Intermediate-term RMSCVs were generally not statistically different from short-term values. Long-term variability was significantly greater for all density measures (0.7% to 2.0%; p < 0.05 versus short-term) and several structure measures: cortical thickness (Ct.Th) (3.4%; p < 0.01 versus short-term), cortical porosity (Ct.Po) (15.4%; p < 0.01 versus short-term), and trabecular thickness (Tb.Th) (2.2%; p < 0.01 versus short-term). Multicenter RMSCVs were also significantly higher than short-term values: 2% to 4% for density and micro-finite element analysis (µFE) measures (p < 0.0001), 2.6% to 5.3% for morphometric measures (p < 0.001), whereas Ct.Po was 16.2% (p < 0.001). In the absence of subject motion, multicenter precision errors for HR-pQCT parameters were generally less than 5%. Phantom-based multicenter precision was comparable to previously reported in in vivo single-center precision errors, although this was approximately two to five times worse than ex vivo short-term precision. The data generated from this study will contribute to the future design and validation of standardized procedures that are broadly translatable to multicenter study designs.