Statistical Models to Assess Leg Muscle Mass in Ambulatory Children With Spastic Cerebral Palsy Using Dual-Energy X-Ray Absorptiometry

Gurka vs Slaughter equations to estimate the fat percentage in children with cerebral palsy from all subtypes and levels of the Gross Motor Function Classification System

BACKGROUND

Body composition assessment in children with cerebral palsy (CP) is a challenge, specially the fat percentage. There are different methods that can be used to estimate the fat percentage in this population, such as anthropometric equations, but there is still a need to determine which is the best and most accurate. The purpose of the study was to determine the method that best estimates the fat percentage in children from all CP subtypes and levels of the Gross Motor Function Classification System (GMFCS).

METHODS

Analytical cross-sectional study in which 108 children with CP diagnosed by a pediatric neurologist were included with any type of dysfunction and from all levels of the GFMCS. Slaughter equation, Gurka equation and Bioelectrical impedance analysis (BIA) as reference method, were used. Groups were stratified by sex, CP subtypes, GMFCS level and Tanner stage. Median differences, Kruskal-Wallis, Mann-Whitney U test, Spearman's correlation coefficients and simple regressions were used, also multivariate models were performed.

RESULTS

The Slaughter equation differed from the other methods in the total population and when it was compared by sex, CP subtypes, gross motor function and Tanner stage. The Gurka equation showed significant differences by sex and gross motor function. Gurka equation correlated positively and significantly with BIA to estimate the fat percentage in all the CP subtypes and levels of the GMFCS. Tricipital skinfold (TSF), arm fat area (AFA) and weight for age index (W/A) showed the highest variability with respect to fat percentage.

CONCLUSION

Gurka equation is more appropriate and accurate than Slaughter equation to estimate the fat percentage in children with CP from all subtypes and levels of the GMFCS.

Current and emerging artificial intelligence applications for pediatric musculoskeletal radiology

Artificial intelligence (AI) is playing an ever-increasing role in radiology (more so in the adult world than in pediatrics), to the extent that there are unfounded fears it will completely take over the role of the radiologist. In relation to musculoskeletal applications of AI in pediatric radiology, we are far from the time when AI will replace radiologists; even for the commonest application (bone age assessment), AI is more often employed in an AI-assist mode rather than an AI-replace or AI-extend mode. AI for bone age assessment has been in clinical use for more than a decade and is the area in which most research has been conducted. Most other potential indications in children (such as appendicular and vertebral fracture detection) remain largely in the research domain. This article reviews the areas in which AI is most prominent in relation to the pediatric musculoskeletal system, briefly summarizing the current literature and highlighting areas for future research. Pediatric radiologists are encouraged to participate as members of the research teams conducting pediatric radiology artificial intelligence research.

The Effect of Robot-Assisted Gait Training on Locomotor Function and Functional Capability for Daily Activities in Children with Cerebral Palsy: A Single-Blinded, Randomized Cross-Over Trial

Purpose: The effectiveness of robot-assisted gait training (RAGT) in children with cerebral palsy (CP), especially in terms of improving the performance of daily activities, remains unclear. Therefore, we aimed to investigate the effectiveness of RAGT in children with CP. Methods: In this single-center, single-blinded, randomized cross-over trial, we enrolled 20 children with CP with Gross Motor Function Classification System (GMFCS) levels II–IV (13 males; age range, 6.75 ± 2.15 years). The participants were randomized into the RAGT/standard care (SC) (n = 10) and SC/RAGT/SC sequence groups (n = 10). Using a Walkbot-K system, the RAGT program comprised 3 × 30-min sessions/week for 6 weeks with a continued SC program. The SC program comprised 2–4 conventional physiotherapy sessions/week for 6 weeks. The Gross Motor Function Measure-88 (GMFM-88), the pediatric functional independence measure (WeeFIM), and the Canadian occupational performance measure (COPM) scores were assessed pre- and post-RAGT or SC periods and treatment, period, follow-up, and carry-over effects were analyzed. Energy expenditure and body composition were measured pre- and post-RAGT. Results: Significant treatment effects were observed in dimensions D and E of the GMFM (D: p = 0.018; E: p = 0.021) scores, WeeFIM mobility subtotal (p = 0.007), and COPM performance (p < 0.001) and satisfaction (p = 0.001) measure scores. The period, follow-up, and carry-over effects were not statistically significant. The gross energy cost significantly decreased (p = 0.041) and the skeletal muscle mass increased (p = 0.014) at post-RAGT assessment. The factors associated with functional outcomes showed significant improvements in the GMFM D scores and were mainly observed in children with GMFCS levels II–III compared to those classified at level IV (p = 0.038). Conclusion: RAGT had training benefits for children with CP. Specifically, it improved locomotor function and functional capability for daily activities. These effects were better in ambulatory children with CP. However, as SC interventions continued during the RAGT period, these improvements may be also related to multiple treatment effects.

Preferential deficit of fat-free soft tissue in the appendicular region of children with cerebral palsy and proposed statistical models to capture the deficit

BACKGROUND

Cerebral palsy (CP) is a neurological disorder characterized by a profound skeletal muscle deficit. However, whether there is a regional-specific skeletal muscle deficit in children with CP is unknown. The purpose of this study was to determine whether fat-free soft tissue mass (FFST), a commonly used surrogate for skeletal muscle mass, is more compromised in the limbs than in the trunk in children with CP. A second purpose was to determine whether physical characteristics can be used to accurately estimate appendicular FFST (AFFST) in children with CP.

METHODS

Forty-two children with CP (4-13 y) and 42 typically developing children matched to children with CP for sex, age and race were studied. Whole body FFST (FFST_whole), FFST in the upper limbs (FFST_upper), FFST in the lower limbs (FFST_lower), the ratio of AFFST to height (AFFST/ht), the ratio of AFFST to height² (AFFST/ht²) and non-appendicular FFST were estimated from dual-energy X-ray absorptiometry. Statistical models were developed to estimate AFFST, AFFST/ht and AFFST/ht² in both groups of children, and the leave-one-out method was used to validate the models.

RESULTS

Children with CP had 21% lower FFST_whole, 30% lower AFFST, 34% lower FFST_lower, 14% lower non-appendicular FFST, 23% lower AFFST/ht, 19% lower AFFST/ht² and 9% lower AFFST/FFST_whole (all p < 0.05). Statistical models developed using data from typically developing children overestimated AFFST, AFFST/ht and AFFST/ht² by 35%, 30% and 21% (all p < 0.05), respectively, in children with CP. Separate models developed using data from children with CP yielded better accuracy, with the estimated results highly correlated (r² = 0.78, 0.66 and 0.50, respectively; all p < 0.001) and not different from calculated AFFST, AFFST/ht and AFFST/ht² (all p > 0.99). However, when the difference in estimated values and measured values of AFFST, AFFST/ht and AFFST/ht² were plotted against measured values, there was an inverse relationship (r = -0.38, -0.47 and -0.61, respectively, all p < 0.05).

CONCLUSION

Children with CP have a remarkable deficit in FFST that is more pronounced in the appendicular than in the non-appendicular region and more pronounced in the lower than in the upper limbs. Preliminary models developed using data from children with CP can provide reasonable estimates of AFFST and indexes of AFFST relative to height, but further development of the models may be needed.