Squared Coefficient Of Variation Research Articles

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.

Evaluation of automated anthropometrics produced by smartphone-based machine learning: a comparison with traditional anthropometric assessments.

Automated visual anthropometrics produced by mobile applications are accessible and cost effective with the potential to assess clinically relevant anthropometrics without a trained technician present. Thus, the aim of this study was to evaluate the precision and agreement of smartphone-based automated anthropometrics against reference tape measurements. Waist and hip circumference (WC; HC), waist:hip ratio (WHR) and waist:height ratio (W:HT) were collected from 115 participants (69 F) using a tape measure and two smartphone applications (MeThreeSixty®, myBVI®) across multiple smartphone types. Precision metrics were used to assess test-retest precision of the automated measures. Agreement between the circumferences produced by each mobile application and the reference were assessed using equivalence testing and other validity metrics. All mobile applications across smartphone types produced reliable estimates for each variable with intraclass correlation coefficients ≥ 0·93 (all P < 0·001) and root mean square coefficient of variation between 0·5 and 2·5 %. Precision error for WC and HC was between 0·5 and 1·9 cm. WC, HC, and W:HT estimates produced by each mobile application demonstrated equivalence with the reference tape measurements using 5 % equivalence regions. Mean differences via paired t-tests were significant for all variables across each mobile application (all P < 0·050) showing slight underestimation for WC and slight overestimation for HC which resulted in a lack of equivalence for WHR compared with the reference tape measure. Overall, the results of our study support the use of WC and HC estimates produced from automated mobile applications, but also demonstrates the importance of accurate automation for WC and HC estimates given their influence on other anthropometric assessments and clinical health markers.

AGREEMENT AND PRECISION OF FEMOROTIBIAL CARTILAGE TRANSVERSE RELAXATION TIME (T2) OBTAINED AT FOUR DIFFERENT MAGNETIC FIELD STRENGTHS

Spin-spin (transverse) relaxation time (T2) is considered to reflect cartilage composition, such as hydration, collagen content and orientation. It can be computed from multi-echo spin-echo (MESE) MRI and is associated with age, sex, and structural joint pathology. Cartilage T2 is dependent on the magnetic field strength. Lower field strength is characterized by lower signal to noise ratios (SNR) compared to standard 1.5Tesla (T) and 3T systems, resulting in longer acquisition times, while access to ultra-high field 7T MRI is still limited. A direct comparative evaluation of cartilage T2 across different field strengths has not been performed to date. To analyze the agreement and the intra-reader test-retest precision of laminar femorotibial cartilage T2, acquired from four different scanner models with 0.55T,1.5T, 3T, and 7T. Six healthy volunteers (5 female, age 21.5±3.5 y) without knee pain had two MESE MRIs acquired each, with repositioning of the knee between test and retest scans, using a 1) MAGNETOM Free.Max 0.55T (acquisition matrix (AM) 304 × 248, slice thickness [ST] 3mm, TR 3020ms, 6 echoes from 16.1 to 96.6ms, acquisition time (AT) 14 min 56 sec) 2) MAGNETOM Sola 1.5T (AM 384 × 384, ST 3mm, TR 2700ms, 7 echoes from 11.7 to 81.9ms, AT 10 min 31 sec) 3) MAGNETOM Vida 3T (AM 384 × 384, ST 3mm, TR 3210ms, 9 echoes from 11.5 to 103.5ms, AT 8 min 17 sec) 4) MAGNETOM Terra 7T (AM 384 × 384, ST 3mm, TR 4490ms, 9 echoes from 8.1 to 72.9ms, AT 8 min 22 sec) (Fig. 1). The field of view was 12 × 12cm for all MESE MRIs. Segmentation of the medial and lateral femorotibial compartment cartilage (MFTC/LFTC) was performed manually by an expert reader; the T2 values were computed for each voxel using custom software. The cartilage layers were divided into the top 50% (superficial [sf]) and bottom 50% (deep) layer, based on the local distance between the cartilage surface and bone interface. The test-retest precision across the entire femorotibial joint (FTJ), the MFTC, and the LFTC was measured using the root mean square coefficient of variation (RMS CV in %). The absolute values of laminar T2 were compared between field strengths using ANOVA, with Bonferroni-Dunn post-hoc correction. The RMS CV across the FTJ was lowest at 3T (0.9%/1.4% sf/deep) and greatest at 0.55T (3.2%/4.0%). The RMS CV was 1.3%/3.4% at 1.5T and 2.3%/1.4% at 7T. Sf RMS CV at 0.55/1.5/3/7T was 3.9/1.7/1.0/3.5% for the MFTC, and 3.0/1.7/1.2/2.7% for the LFTC. The deep layer RMS CV was 5.4/3.4/3.1/2.6% for the MFTC and 5.0/4.1/1.1/2.9% for the LFTC. Sf and deep layer T2 differed significantly between field strengths for the FTJ, the MFTC, and the LFTC (all p<0.001). Both sf and deep layer T2 across the FTJ, the MFTC and also the LFTC were shortest at 7T and longest at 0.55T (Fig. 2). Interestingly, T2 was shorter at 1.5T than at 3T, but this difference reached statistical significance only for the deep layer in the FTJ and in the MFTC (Fig. 2). Based on the protocols implemented in this study, laminar cartilage T2 systematically varied with magnetic field strength. The shortest values were observed at 7T, and the longest at 0.55T. These findings suggest that cartilage T2 measurements in multicenter studies are not directly comparable when different field strengths (potentially also different manufacturer and scanner models) are included. The test-retest precision error was lowest at 3T and highest at 0.55T, suggesting that, in clinical studies, measurements should be performed at 3T. However, test-retest precision is highly dependent on the protocol and might be improved for lower field strengths, applying different acquisition parameters (e.g. longer acquisition times and higher resolution). Implementation on the 7T magnet may require further improvement to leverage the full potential benefit of the higher field strength.

Test–retest precision and longitudinal cartilage thickness loss in the IMI-APPROACH cohort

To investigate the test-retest precision and to report the longitudinal change in cartilage thickness, the percentage of knees with progression and the predictive value of the machine-learning-estimated structural progression score (s-score) for cartilage thickness loss in the IMI-APPROACH cohort - an exploratory, 5-center, 2-year prospective follow-up cohort. Quantitative cartilage morphology at baseline and at least one follow-up visit was available for 270 of the 297 IMI-APPROACH participants (78% females, age: 66.4±7.1 years, body mass index (BMI): 28.1±5.3kg/m2, 55% with radiographic knee osteoarthritis (OA)) from 1.5T or 3T MRI. Test-retest precision (root mean square coefficient of variation) was assessed from 34 participants. To define progressor knees, smallest detectable change (SDC) thresholds were computed from 11 participants with longitudinal test-retest scans. Binary logistic regression was used to evaluate the odds of progression in femorotibial cartilage thickness (threshold:-211μm) for the quartile with the highest vs the quartile with the lowest s-scores. The test-retest precision was 69μm for the entire femorotibial joint. Over 24 months, mean cartilage thickness loss in the entire femorotibial joint reached-174μm (95% CI: [-207,-141]μm, 32.7% with progression). The s-score was not associated with 24-month progression rates by MRI (OR: 1.30, 95% CI: [0.52, 3.28]). IMI-APPROACH successfully enrolled participants with substantial cartilage thickness loss, although the machine-learning-estimated s-score was not observed to be predictive of cartilage thickness loss. IMI-APPROACH data will be used in subsequent analyses to evaluate the impact of clinical, imaging, biomechanical and biochemical biomarkers on cartilage thickness loss and to refine the machine-learning-based s-score. NCT03883568.

Improving the performance of planning and controlling raw material inventory in food industry

This paper discusses the inefficient and inaccurate raw material supply at a food company which results in a backlog. This means the overstock occurs so that the improvement of inventory control needs to be done. ABC classification is firstly utilized as input for Material Requirements Planning (MRP). This paper focuses on four products which are classified into A class. Then, this paper discusses the Triple Exponential Smoothing as the forecasting method. Aggregate planning is also conducted for better production planning. The results of aggregate planning provide solutions to increase the workforce to balance production capacity by the number of demands. Squared Coefficient of Variation (SCV) calculations indicates the demand follows a static pattern. Therefore, the appropriate lot sizing method is the Economic Order Quantity (EOQ) to carry out the production needs. Finally, this paper uses capacity planning using Rough-Cut Capacity Planning (RCCP) and Capacity Requirement Planning (CRP) methods. As a result, the capacity meets the Master Production Schedule (MPS) as well as MRP and they are feasible to be implemented.

Bounds on the mean and squared coefficient of variation of phase-type distributions

AbstractWe consider a class of phase-type distributions (PH-distributions), to be called the MMPP class of PH-distributions, and find bounds of their mean and squared coefficient of variation (SCV). As an application, we have shown that the SCV of the event-stationary inter-event time for Markov modulated Poisson processes (MMPPs) is greater than or equal to unity, which answers an open problem for MMPPs. The results are useful for selecting proper PH-distributions and counting processes in stochastic modeling.

Adding marrow R2∗ to proton density fat fraction improves the discrimination of osteopenia and osteoporosis in postmenopausal women assessed with 3D FACT sequence.

To evaluate the role of three-dimensional Fat Analysis & Calculation Technique sequence in improving the diagnostic accuracy for the detection of osteopenia and osteoporosis by simultaneous quantification of proton density fat fraction (PDFF) and fat-corrected R2∗. Fat Analysis & Calculation Technique imaging of lumbar spine was obtained in 99 postmenopausal women including 52 normal bone mass, 29 osteopenia, and 18 osteoporosis. The diagnostic performance of PDFF and R2∗ in the differentiation of different bone-density groups was evaluated with the receiver operating characteristic curve. The reproducibility of PDFF and R2∗ measures was satisfactory with the root mean square coefficient of variation, 2.16% and 2.70%, respectively. The intra- and interobserver agreements for the PDFF and R2∗ were excellent with the intraclass correlation coefficient > 0.9 for all. There were significant differences in PDFF and R2∗ among the three groups (P < 0.05). Bone density had a moderate inverse correlation with PDFF (r = -0.659) but a positive association with R2∗ (r = 0.508, P < 0.001). Adjusted for age, years since menopause and body mass index, odds ratios (95% confidence interval) for osteopenia and osteoporosis per standard deviation higher marrow PDFF and R2∗ were 2.9 (1.4-5.8) and 0.4 (0.2-0.8), respectively. The areas under the curve were 0.821 for PDFF, 0.784 for R2∗, and 0.922 for both combined for the detection of osteoporosis (P < 0.05). Similar results were obtained in distinguishing osteopenia from healthy controls. Simultaneous estimation of marrow R2∗ and PDFF improves the discrimination of osteopenia and osteoporosis in comparison with the PDFF or R2∗ alone.

Quantitative Three-dimensional Assessment of Knee Joint Space Width from Weight-bearing CT.

Background Imaging of structural disease in osteoarthritis has traditionally relied on MRI and radiography. Joint space mapping (JSM) can be used to quantitatively map joint space width (JSW) in three dimensions from CT images. Purpose To demonstrate the reproducibility, repeatability, and feasibility of JSM of the knee using weight-bearing CT images. Materials and Methods Two convenience samples of weight-bearing CT images of left and right knees with radiographic Kellgren-Lawrence grades (KLGs) less than or equal to 2 were acquired from 2014 to 2018 and were analyzed retrospectively with JSM to deliver three-dimensional JSW maps. For reproducibility, images of three sets of knees were used for novice training, and then the JSM output was compared against an expert's assessment. JSM was also performed on 2-week follow-up images in the second cohort, yielding three-dimensional JSW difference maps for repeatability. Statistical parametric mapping was performed on all knee imaging data (KLG, 0-4) to show the feasibility of a surface-based analysis in three dimensions. Results Reproducibility (in 20 individuals; mean age, 58 years ± 7 [standard deviation]; mean body mass index, 28 kg/m2 ± 6; 14 women) and repeatability (in nine individuals; mean age, 53 years ± 6; mean body mass index, 26 kg/m2 ± 4; seven women) reached their lowest performance at a smallest detectable difference less than ±0.1 mm in the central medial tibiofemoral joint space for individuals without radiographically demonstrated disease. The average root mean square coefficient of variation was less than 5% across all groups. Statistical parametric mapping (33 individuals; mean age, 57 years ± 7; mean body mass index, 27 kg/m2 ± 6; 23 women) showed that the central-to-posterior medial joint space was significantly narrower by 0.5 mm for each incremental increase in the KLG (threshold P < .05). One knee (KLG, 2) demonstrated a baseline versus 24-month change in its three-dimensional JSW distribution that was beyond the smallest detectable difference across the lateral joint space. Conclusion Joint space mapping of the knee using weight-bearing CT images is feasible, demonstrating a relationship between the three-dimensional joint space width distribution and structural joint disease. It is reliably learned by novice users, can be personalized for disease phenotypes, and can be used to achieve a smallest detectable difference that is at least 50% smaller than that reported to be achieved at the highest performance level in radiography. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Roemer in this issue.

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.

High order concentrated matrix-exponential distributions

This paper presents matrix-exponential (ME) distributions, whose squared coefficient of variation (SCV) is very low. Currently, there is no symbolic construction available to obtain the most concentrated ME distributions, and the numerical optimization-based approaches to construct them have many pitfalls. We present a numerical optimization-based procedure which avoids numerical issues.

Age-Dependent Control of Shoulder Muscles During a Reach-and-Lift Task.

Aging affects fatigability and is a risk factor for incurring a fatigue-related injury in the neck/shoulder region. Age-related changes in the electromyographical features of motor control may be partly responsible. Young (N = 17) and older (N = 13) adults completed a reach-and-lift task at their self-selected speed, before and after a fatiguing task targeting the neck/shoulder. Electromyography amplitude (root mean square), amplitude variability (root mean square coefficient of variation [CV]), functional connectivity (normalized mutual information [NMI]), and functional connectivity variability (NMI CV) were extracted from several muscles and analyzed for effects and interactions of age using general estimating equation models. Root mean square CV and deltoid NMI CV increased from pre- to postfatigue (ps < .05). Upper trapezius-deltoid NMI decreased for young, but increased for older adults, while the opposite response was found for lower trapezius-deltoid NMI (ps < .05). Older adults seem to adapt to fatigue in reach-and-lift movement with a cranial shift in control of the scapula.

Digital anthropometry via three-dimensional optical scanning: evaluation of four commercially available systems.

Digital anthropometry is increasingly accessible due to commercial availability of three-dimensional optical scanners (3DO). One hundred and seventy-nine participants were assessed by four 3DO systems (FIT3D®, Size Stream®, Styku®, and Naked Labs®) in duplicate, air displacement plethysmography (ADP), and dual-energy x-ray absorptiometry (DXA). Test-retest precision was evaluated, and validity of total and regional volumes was established. All scanners produced precise estimates, with root mean square coefficient of variation (RMS-%CV) of 1.1-1.3% when averaged across circumferences and 1.9-2.3% when averaged across volumes. Precision for circumferences generally decreased in the order of: hip, waist and thigh, chest, neck, and arms. Precision for volumes generally decreased in the order of: total body volume (BV), torso, legs, and arms. Total BV was significantly underestimated by Styku® (constant error [CE]: -10.1 L; root mean square error [RMSE]: 10.5 L) and overestimated by Size Stream® (CE: 8.0 L; RMSE: 8.3 L). Total BV did not differ between ADP and FIT3D® (CE: -3.9 L; RMSE: 4.2 L) or DXA BV equations (CE: 0-1.4 L; RMSE: 0.7-1.5 L). Torso volume was overestimated and leg and arm volumes were underestimated by all 3DO. No total or regional 3DO volume estimates exhibited equivalence with reference methods using 5% equivalence regions, and proportional bias of varying magnitudes was observed. All 3DO produced precise anthropometric estimates, although variability in specific precision estimates was observed. 3DO BV estimates did not exhibit equivalence with reference methods. Conversely, DXA-derived total BV exhibited superior validity and equivalence with ADP.

A new quantitative 3D approach to imaging of structural joint disease

Imaging of joints with 2D radiography has not been able to detect therapeutic success in research trials while 3D imaging, used regularly in the clinic, has not been approved for this purpose. We present a new 3D approach to this challenge called joint space mapping (JSM) that measures joint space width in 3D from standard clinical computed tomography (CT) data, demonstrating its analysis steps, technical validation, and reproducibility. Using high resolution peripheral quantitative CT as gold standard, we show a marginal over-estimation in accuracy of +0.13 mm and precision of ±0.32 mm. Inter-operator reproducibility bias was near-zero at −0.03 mm with limits of agreement ±0.29 mm and a root mean square coefficient of variation 7.5%. In a technical advance, we present results from across the hip joint in 3D with optimum validation and reproducibility metrics shown at inner joint regions. We also show JSM versatility using different imaging data sets and discuss potential applications. This 3D mapping approach provides information with greater sensitivity than reported for current radiographic methods that could result in improved patient stratification and treatment monitoring.

Measuring Marrow Density and Area Using Peripheral Quantitative Computed Tomography at the Tibia: Precision in Young and Older Adults and Individuals With Spinal Cord Injury

The objective of this study was to compare the test-retest precision error for peripheral quantitative computed tomography (pQCT)-derived marrow density and marrow area segmentation at the tibia using 3 software packages. A secondary analysis of pQCT data in young adults (n = 18, mean ± standard deviation 25.4 ± 3.2 yr), older adults (n = 47, 71.8 ± 8.2 yr), and individuals with spinal cord injury (C1–T12 American Spinal Injury Association Impairment Scale, classes A–C; n = 19, 43.5 ± 8.6 yr) was conducted. Repeat scans of the tibial shaft (66%) were performed using pQCT (Stratec XCT2000). Test-retest precision errors (root mean square standard deviation and root mean square coefficient of variation [RMSCV%]) for marrow density (mg/cm3) and marrow area (mm2) were reported for the watershed-guided manual segmentation method (SliceOmatic version 4.3 [Sliceo-WS]) and the 2 threshold-based edge detection methods (Stratec version 6.0 [Stratec-TB] and BoneJ version 1.3.14 [BoneJ-TB]). Bland-Altman plots and 95% limits of agreement were computed to evaluate test-retest discrepancies within and between methods of analysis and subgroups. RMSCV% for marrow density segmentation was >5% for all methods across subgroups (Stratec-TB: 12.2%–28.5%, BoneJ-TB: 14.5%–25.2%, and Sliceo-WS: 10.9%–23.0%). RMSCV% for marrow area segmentation was within 5% for all methods across subgroups (Stratec-TB: 1.9%–4.4%, BoneJ-TB: 2.6%–5.1%, and Sliceo-WS: 2.4%–4.5%), except using BoneJ-TB in older adults. Intermethod discrepancies in marrow density appeared to be present across the range of marrow density values and did not differ by subgroup. Intermethod discrepancies varied to a greater extent for marrow area and were found to be more frequently at mid- to higher-range values for those with spinal cord injury. Precision error for pQCT-derived marrow density segmentation exceeded 5% for all methods of analysis across a range of bone mineral densities and fat infiltration, whereas precision error for marrow area segmentation ranged from 2% to 5%. Further investigation is necessary to determine alternative acquisition and analysis methods for pQCT-derived marrow segmentation.

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.

Intra- and inter-observer reliability of quantitative analysis of the infra-patellar fat pad and comparison between fat- and non-fat-suppressed imaging—Data from the osteoarthritis initiative

The infra-patellar fat pad (IPFP), as intra-articular adipose tissue represents a potential source of pro-inflammatory cytokines and its size has been suggested to be associated with osteoarthritis (OA) of the knee. This study examines inter- and intra-observer reliability of fat-suppressed (fs) and non-fat-suppressed (nfs) MR imaging for determination of IPFP morphological measurements as novel biomarkers.The IPFP of nine right knees of healthy Osteoarthritis Initiative participants was segmented by five readers, using fs and nfs baseline sagittal MRIs. The intra-observer reliability was determined from baseline and 1-year follow-up images. All segmentations were quality controlled (QC) by an expert reader. Reliability was expressed as root mean square coefficient of variation (RMS CV%).After QC, the inter-observer reliability for fs (nfs) imaging was 2.0% (1.1%) for IPFP volume, 2.1%/2.5% (1.6%/1.8%) for anterior/posterior surface areas, 1.8% (1.8%) for depth, and 2.1% (2.4%) for maximum sagittal area. The intra-observer reliability was 3.1% (5.0%) for volume, 2.3%/2.8% (2.5%/2.9%) for anterior/posterior surfaces, 1.9% (3.5%) for depth, and 3.3% (4.5%) for maximum sagittal area. IPFP volume from nfs images was systematically greater (+7.3%) than from fs images, but highly correlated (r=0.98).The results suggest that quantitative measurements of IPFP morphology can be performed with satisfactory reliability when expert QC is implemented. The IPFP is more clearly depicted in nfs images, and there is a small systematic off-set versus analysis from fs images. However, the high linear relationship between fs and nfs imaging suggests that fs images can be used to analyze IPFP morphology, when nfs images are not available.

Introducing MULTICOVA: �Multiple Trichotomous Coefficient of Variation Analysis� the Advanced Post Hoc Test of the Tri�Squared Coefficient of Variation

Introducing MULTICOVA: �Multiple Trichotomous Coefficient of Variation Analysis� the Advanced Post Hoc Test of the Tri�Squared Coefficient of Variation

Measurement of muscle and fat in postmenopausal women: precision of previously reported pQCT imaging methods

Peripheral quantitative computed tomography (pQCT) imaging has been used to quantify muscle area and density as well as intermuscular adipose tissue (IMAT) and subcutaneous adipose tissue (SAT) area in the lower and upper limb. Numerous protocols have been reported to derive these soft-tissue outcomes, but their precision has not been assessed in community-dwelling postmenopausal women. The objective of this study was to compare the precision of previously reported analysis protocols for quantifying muscle area and density, as well as IMAT and SAT area in postmenopausal women.Six image analysis protocols using two available software suites (Stratec XCT, BoneJ) were identified from the pQCT literature. Analysis protocols were applied to a sample of 35 older female adults (mean age 73.7; SD 7.2years), randomly selected from a population based-cohort and scanned twice within an average of 9.7 (SD 3.6) days. Relative precision was calculated as absolute values and as a percentage of the sample mean (root mean square coefficient of variation; CV%RMS). Soft-tissue outcomes across protocols were compared on their log-transformed coefficients of variation using multilevel linear models and Tukey contrasts.For most protocols, CV%RMS for muscle area, density, and SAT area ranged between 2.1 and 3.7%, 0.7 and 1.9%, and 2.4 and 6.4%, respectively. Precision for IMAT area varied considerably, from 3 to 42%. Consideration of these study results will aid in the selection of appropriate image analysis protocols for pQCT-derived soft-tissue outcomes in postmenopausal women.

Optimal Dynamic Pricing with Demand Model Uncertainty: A Squared-Coefficient-of-Variation Rule for Learning and Earning

We consider a price-setting firm that sells a product over a continuous time horizon. The firm is uncertain about the sensitivity of demand to price adjustments, and continuously updates its prior belief on an unobservable sensitivity parameter by observing the demand responses to prices. The firm’s objective is to minimize the infinite-horizon discounted loss, relative to a clairvoyant that knows the unobservable sensitivity parameter. Using partial differential equations theory, we characterize the optimal pricing policy, and then derive a formula for the optimal learning premium that projects the value of learning onto prices. We compare and contrast the optimal pricing policy with the myopic pricing policy, and quantify the cost of myopically neglecting to charge a learning premium in prices. We show that the optimal learning premium for a firm that looks far into the future is the squared coefficient of variation (SCV) in the firm’s posterior belief. Based on this principle, we design a simple variant of the myopic policy, namely the SCV rule, and prove that this policy is long-run average optimal.

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.