The first seriatim study of human growth and middle aging

Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning

PURPOSE

Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted images (T2WIs) has been widely used in radiology. This study aimed to simulate a rule-based workflow using a stacked deep learning model and evaluate age estimation accuracy.

METHODS

The age estimation system involved two stacked neural networks: a target network-to extract five myelination-related images from the whole brain, and an age estimation network from extracted T1- and T2WIs separately. A dataset was constructed from 119 children aged below 2 years with two MRI systems. A four-fold cross-validation method was adopted. The correlation coefficient (CC), mean absolute error (MAE), and root mean squared error (RMSE) of the corrected chronological age of full-term birth, as well as the mean difference and the upper and lower limits of 95% agreement, were measured. Generalization performance was assessed using datasets acquired from different MR images. Age estimation was performed in Sturge-Weber syndrome (SWS) cases.

RESULTS

There was a strong correlation between estimated age and corrected chronological age (MAE: 0.98 months; RMSE: 1.27 months; and CC: 0.99). The mean difference and standard deviation (SD) were -0.15 and 1.26, respectively, and the upper and lower limits of 95% agreement were 2.33 and -2.63 months. Regarding generalization performance, the performance values on the external dataset were MAE of 1.85 months, RMSE of 2.59 months, and CC of 0.93. Among 13 SWS cases, 7 exceeded the limits of 95% agreement, and a proportional bias of age estimation based on myelination acceleration was exhibited below 12 months of age (P = 0.03).

CONCLUSION

Stacked deep learning models automated the rule-based workflow in radiology and achieved highly accurate age estimation in infants and children up to 2 years of age.

The first Seriatum study of growth by R. E. Scammon

Richard E. Scammon's article, "The First Seriatim Study of Human Growth," provided one of the best-known visuals in the field of human biology. Scammon resurrected longitudinal height data of one child from Buffon's Histoire Naturelle, converted them to metric, and plotted these measurements as a function of age. The result was the first graph of one individual's growth curve from birth to 18 years of age. This image was subsequently reproduced in numerous texts on human growth and biology. Published in 1927, Scammon's article provides a snapshot of the state of growth research at the time and gives a (literal) picture of the future of human biology. The graph of the growth of one child symbolizes the importance of process and variation in biological anthropology.

The first seriatim study into old age for weight, stature and BMI: the Fels Longitudinal Study

PURPOSE

To document the serial status of measures of weight, stature and BMI from birth into old age.

METHODS

Longitudinal measures of weight, stature and BMI were taken from birth to 76 years of age for 5 men and 7 women as part of the Fels Longitudinal Study.

RESULTS

Sex-specific plots of means for weight, stature and BMI are presented that describe the changes and sex differences in these measurements between birth (or the first year of life) into old age. These serial data demonstrate a continuous increase in body weight through much of adulthood and a small decline in stature starting in late middle age. The plots for BMI indicate the early onset of overweight and subsequent obesity early in adulthood and its continuance into old age for men and women.

CONCLUSIONS

These are the first plots of serial means for weight, stature and BMI measured from the same group of individuals from birth into old age. These findings demonstrate the changes in these measurements through childhood and maturity into old age. Similar data are needed for individuals from other racial/ethnic groups and countries in order to understand the aging process better.

Effects of patient age on postorthodontic stability in Class II, division 1 malocclusions

The increase in the proportion of adults in the typical orthodontic practice merits closer scrutiny of the treatment differences involved in adult vis-à-vis adolescent patients. Orthodontic treatment in the adolescent relies heavily on growth; in the adult, the practitioner must reposition teeth within the nongrowing arches. This difference may create the potential for greater postretention relapse in the adult; alternatively, continued growth in the subadult might detract from stability of the case. Two samples of Class II, Division 1 cases, all treated by one specialist, were examined an average of 5 years out of treatment. One group had been treated during adolescence (approximately 12 years of age), the other in adulthood (approximately 28 years). The orthodontic corrections were stable in both groups, but for different reasons: Posttreatment changes in the bony and dental structures of the adults were minimal. Bony changes (i.e., continued midface and mandibular growth) were appreciable in adolescents, and this growth--notably growth of the mandible--compensated for unfavorable drift of the dental elements (primarily mesial shift of the maxillary molar) after treatment. In sum, orthodontic corrections in adults were found to be at least as stable as those in the conventional adolescent patient.