The choice of an appropriate imaging technique to quantify bone, muscle, or muscle adiposity needs to be guided by a thorough understanding of its competitive advantages over other modalities balanced by its limitations. This review details the technical machinery and methods behind peripheral quantitative computed tomography (pQCT), high-resolution (HR)-pQCT, and magnetic resonance imaging (MRI) that drive successful depiction of bone and muscle morphometry, densitometry, and structure. It discusses a number of image acquisition settings, the challenges associated with using one versus another, and compares the risk-benefits across the different modalities. Issues related to all modalities including partial volume artifact, beam hardening, calibration, and motion assessment are also detailed. The review further provides data and images to illustrate differences between methods to better guide the reader in selecting an imaging method strategically. Overall, investigators should be cautious of the impact of imaging parameters on image signal or contrast-to-noise-ratios, and the need to report these settings in future publications. The effect of motion should be assessed on images and a decision made to exclude prior to segmentation. A more standardized approach to imaging bone and muscle on pQCT and MRI could enhance comparability across studies and could improve the quality of meta-analyses.
CNAANI J, WONG A & THOMSON J D [Dep Zool, Univ Toronto, Ont, Canada]: Effect of Group Size on Ovarian Development in Bumblebee Workers (Hymenoptera: Apidae: Bombus). - Entomol Gener 29(2/4): 305-314; Stuttgart 2007-01. --- [Note] Isolated bumblebee workers. Bombus impatiens Cresson 1863, developed their ovaries to produce laying-sized eggs in 11 days, but did so 5 days faster in queenless groups of 2-12 that they came to dominate. In groups larger than pairs, reproductive dominance (as measured by oocyte length) was distributed continuously in a graded hierarchy, rather than dichotomously. In groups, workers at a particular dominance rank position developed larger oocytes as group size increased, indicating that a focal bee's stimulus for reproductive development depends on the number of other bees that are subordinate to it. Attempts to relate ovarian development to visible behavioral manifestations of dominance were inconclusive because antagonistic interaction were infrequent.
Previous studies have shown that inter- and intramuscular fat, together, relate with knee osteoarthritis symptoms and disease features. However, the manual methods of fat and muscle segmentation from MR images are tedious and limit the feasibility of examining intra-muscular fat within separate muscle groups of the thigh. For this reason, it remains unclear whether fat within specific knee flexor, extensor, adductors or abductors contribute differentially to knee symptoms and trajectories of change in symptoms. To investigate how intramuscular fat within separate muscle groups of the thigh differentially predict knee symptoms and faster progression of knee symptoms over 5 years. This was an individual-level longitudinal study of 134 participants of the Osteoarthritis Initiative randomly selected among those who had thigh MR images available at the 24-month visit (v03). A total of 15 transaxial intermediate weighted turbo spin echo image slices were examined. A fully convolutional neural network was trained to segment all thigh muscle groups using manually traced annotations (3D Slicer) verified by two radiologists. Original training (N=134) and CNN-predicted (N=235) muscle group output masks were both subjected through the iterative threshold -seeking algorithm (ITSA) that we previously developed to quantify fat volume and percentages. All algorithms and computations were completed within Python 3.8.8(Jupyter). Group-based trajectory modeling (GBTM) identified and classified participants according to patterns of change in KOOS and WOMAC scores from 36 to 84 months (v05 – v09). Binary logistic regression models examined how fat volume (absolute and percentage, per standard deviation higher) within each muscle group predicted rapidly worsening symptoms versus relatively unchanged symptom levels. General linear models also predicted 36-month (v05) symptom values using single unit exposure contrasts (1cm3 larger fat or muscle volume). All models adjusted for age, BMI, use of NSAIDs, and 20-m walking pace. Among 134 individuals (mean age: 64±9yrs; BMI: 30.09±4.67kg/m2), GBTM identified 3 classes of pain trajectory patterns with more rapid progression being a distinct class compared to two groups showing unchanging symptom levels (Figure 1). A higher absolute (+7.03cm3) and relative (0.06%) amount of intramuscular fat within the adductor muscles was associated with a higher odds of having rapid pain progression as measured by KOOS knee pain (OR: ranged from 1.57 to 1.65, concordance(C)=0.81) or WOMAC total score (OR: ranged from 1.45 to 1.56, C=0.63). A similar pattern was observed for a lower hamstring muscle volume (OR: 2.54(95%CI: 1.15,5.59)). On a linear scale, each 1 cm3 larger fat volume within the rectus femoris was associated with 3.02(4.74,1.30) percentage points lower KOOS knee pain (more pain), 1.60(2.94,0.27) percentage points lower KOOS knee symptoms, and 2.51(1.17,3.85) points higher in WOMAC total score (more pain). A greater distribution of fat and smaller muscle volume within the adductors was predictive of a higher rate of pain worsening. However, a similar pattern of higher fat and lower muscle volume within the rectus femoris muscles was primarily responsible for worse absolute knee pain and symptoms within the next 12 months. CIHR PJT156274. Arthritis Society Ken Smith Stars Career Development Award. None of the authors have disclosures. CORRESPONDENCE ADDRESS: [email protected]
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