Background:Very limited information is available regarding the accuracy and applicability of various ultrasonography parameters [abdominal circumference (AC), biparietal diameter (BPD), femur length (FL), and head circumference (HC)]-based fetal weight estimation models for Indian population. The objective of this study was to systematically evaluate commonly used fetal weight estimation models to determine their appropriateness for an Indian population.Methods:Retrospective data of 300 pregnant women was collected from a tertiary care center in Bengaluru, India. The inclusion criteria were a live singleton pregnancy, gestational age ≥ 34 weeks, and last ultrasound scan to delivery duration ≤ 7 days. Cases with suspected fetal growth restriction or malformation were excluded. For each case, fetal weight was estimated using 34 different models. The models specifically designed for low birth weight, small for gestation age, or macrosomic babies were excluded. The models were ranked based on their mean percentage error (MPE) and its standard deviation (random error). A model with the least MPE and random error ranking was considered as the best model.Results:In total, 149 cases were found suitable for the study. Out of 34, only 12 models had MPE within ± 10% and only seven models had random error < 10%. Most of the Western population-based models had a tendency to overestimate the fetal weight. Based on MPE and random error ranking, the Woo’s (AC-BPD) model was found to be the best, followed by Jordaan (AC), Combs (AC-HC-FL), Hadlock (AC-HC), and Hadlock-3 (AC-HC-FL) models. It was observed that the models based on just AC and AC-BPD combinations had statistically significant lesser MPE than the models based on all other combinations (p < 0.05).Conclusion:It was observed that the existing models have higher errors on Indian population than on their native populations. This points toward limitations in direct application of these models on Indian population without due consideration. Therefore, it is recommended that clinicians should exert caution in interpretation of fetal weight estimations based on these models. Moreover, this study highlights a need of models based on native Indian population.

The fALFF appears to be a noninvasive measure that characterizes spontaneous BOLD fluctuations and shows stronger amplitudes in the slow-3 subband of patients with NOE relative first-seizure subjects and healthy controls. A larger study population with follow-up is required to determine whether fALFF holds promise as a potential biomarker for identifying subjects at increased risk to develop epilepsy.

In many brain diseases it can be qualitatively observed that spatial patterns in blood oxygenation level dependent (BOLD) activation maps appear more (diffusively) distributed than in healthy controls. However, measures that can quantitatively characterize this spatial distributiveness in individual subjects are lacking. In this study, we propose a number of spatial heterogeneity measures to characterize brain activation maps. The proposed methods focus on different aspects of heterogeneity, including the shape (compactness), complexity in the distribution of activated regions (fractal dimension and co-occurrence matrix), and gappiness between activated regions (lacunarity). To this end, functional MRI derived activation maps of a language and a motor task were obtained in language impaired children with (Rolandic) epilepsy and compared to age-matched healthy controls. Group analysis of the activation maps revealed no significant differences between patients and controls for both tasks. However, for the language task the activation maps in patients appeared more heterogeneous than in controls. Lacunarity was the best measure to discriminate activation patterns of patients from controls (sensitivity 74%, specificity 70%) and illustrates the increased irregularity of gaps between activated regions in patients. The combination of heterogeneity measures and a support vector machine approach yielded further increase in sensitivity and specificity to 78% and 80%, respectively. This illustrates that activation distributions in impaired brains can be complex and more heterogeneous than in normal brains and cannot be captured fully by a single quantity. In conclusion, heterogeneity analysis has potential to robustly characterize the increased distributiveness of brain activation in individual patients.

OBJECTIVE:To examine body size and fat measurements of babies born in rural India and compare them with white Caucasian babies born in an industrialised country. DESIGN: Community-based observational study in rural India, and comparison with data from an earlier study in the UK, measured using similar methods. SUBJECTS: A total of 631 term babies born in six rural villages, near the city of Pune, Maharashtra, India, and 338 term babies born in the Princess Anne Hospital, Southampton, UK. MEASUREMENTS: Maternal weight and height, and neonatal weight, length, head, mid-upper-arm and abdominal circumferences, subscapular and triceps skinfold thicknesses, and placental weight. RESULTS: The Indian mothers were younger, lighter, shorter and had a lower mean body mass index (BMI) (mean age, weight, height and BMI: 21.4 y, 44.6 kg, 1.52 m, and 18.2 kg/m 2 ) than Southampton mothers (26.8 y, 63.6 kg, 1.63 m and 23.4 kg/m 2 ). They gave birth to lighter babies (mean birthweight: 2.7 kg compared with 3.5 kg). Compared to Southampton babies, the Indian babies were small in all body measurements, the smallest being abdominal circumference (s.d. score: À2.38; 95% CI: À2.48 to À2.29) and mid-arm circumference (s.d. score: À1.82; 95% CI: À1.89 to À1.75), while the most preserved measurement was the subscapular skinfold thickness (s.d. score: À0.53; 95% CI: À0.61 to À0.46). Skinfolds were relatively preserved in the lightest babies (below the 10th percentile of birthweight) in both populations. CONCLUSIONS: Small Indian babies have small abdominal viscera and low muscle mass, but preserve body fat during their intrauterine development. This body composition may persist postnatally and predispose to an insulin-resistant state.

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