Midfacial growth patterns in males from newborn to 5 years old based on computed tomography

Evteev, Andrej; Anikin, Anatoliy; Satanin, Leonid

doi:10.1002/ajhb.23132

Cited by 13 publications

(25 citation statements)

References 97 publications

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“…) and present higher morphological variability (Evteev et al. ), especially in older age groups as sexual dimorphism is inducing morphological changes in those areas (Freidline et al. ; Holton et al.…”

Section: Discussionmentioning

confidence: 99%

“…6), as they 'diffuse' mechanical loads across the skull (Popowics & Herring, 2007). Areas such as the upper face and nasal region that are under fewer functional constraints show more consistently forming fields (Martinez-Maza et al 2013) and present higher morphological variability (Evteev et al 2018), especially in older age groups as sexual dimorphism is inducing morphological changes in those areas (Freidline et al 2016;Holton et al 2016). Although interindividual variability in the percentages of bone resorption is high, particularly in younger age groups, overall the general patterns of bone modeling remain very similar from age groups 2-4 in this European sample (Fig.…”

Section: Interindividual and Intrapopulation Variabilitymentioning

confidence: 99%

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Ontogeny of the human maxilla: a study of intra‐population variability combining surface bone histology and geometric morphometrics

et al. 2019

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Bone modeling is the process by which bone grows in size and models its shape via the cellular activities of the osteoblasts and osteoclasts that respectively form and remove bone. The patterns of expression of these two activities, visible on bone surfaces, are poorly understood during facial ontogeny in Homo sapiens; this is due mainly to small sample sizes and a lack of quantitative data. Furthermore, how microscopic activities are related to the development of morphological features, like the uniquely human‐canine fossa, has been rarely explored. We developed novel techniques for quantifying and visualizing variability in bone modeling patterns and applied these methods to the human maxilla to better understand its development at the micro‐ and macroscopic levels. We used a cross‐sectional ontogenetic series of 47 skulls of known calendar age, ranging from birth to 12 years, from a population of European ancestry. Surface histology was employed to record and quantify formation and resorption on the maxilla, and digital maps representing each individual's bone modeling patterns were created. Semilandmark geometric morphometric (GM) methods and multivariate statistics were used to analyze facial growth. Our results demonstrate that surface histology and GM methods give complementary results, and can be used as an integrative approach in ontogenetic studies. The bone modeling patterns specific to our sample are expressed early in ontogeny, and fairly constant through time. Bone resorption varies in the size of its fields, but not in location. Consequently, absence of bone resorption in extinct species with small sample sizes should be interpreted with caution. At the macroscopic level, maxillary growth is predominant in the top half of the bone where bone formation is mostly present. Our results suggest that maxillary growth in humans is highly constrained from early stages in ontogeny, and morphological changes are likely driven by changes in osteoblastic and osteoclastic rates of expression rather than differences in the bone modeling patterns (i.e. changes in location of formation and resorption). Finally, the results of the micro‐ and macroscopic analyses suggest that the development of the canine fossa results from a combination of bone resorption and bone growth in the surrounding region.

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Section: Discussionmentioning

confidence: 99%

Section: Interindividual and Intrapopulation Variabilitymentioning

confidence: 99%

Ontogeny of the human maxilla: a study of intra‐population variability combining surface bone histology and geometric morphometrics

et al. 2019

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“…The HMH‐based method is also widely used in geometric morphometrics due to its accuracy (Bauer, Benazzi, Darlas, & Harvati, ; Coquerelle et al, ; Evteev, Anikin, & Satanin, ; Gröning, Fagan, & O’Higgins, , ; Rivera & Mirazón Lahr, ; Senck & Coquerelle, ; Stoessel, Gunz, David, & Spoor, ). In the original paper describing this approach, the means of 10 HMH values along various randomly selected slices were used to obtain the global threshold (Coleman & Colbert, ).…”

Section: Discussionmentioning

confidence: 99%

“…This study suggested that at least 100 and ideally thousands of randomly drawn lines should be used when selecting a global threshold for skulls. Otherwise, lines should be drawn on pre‐defined regions like as Evteev et al () instead of random selection. Thus, it might be difficult to apply this method to a complex object such as a skull unless to some extent high‐resolution images are available.…”

Section: Discussionmentioning

confidence: 99%

Effects of different segmentation methods on geometric morphometric data collection from primate skulls

Ito

2019

Methods Ecol Evol

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An increasing number of studies are analysing the shapes of objects using geometric morphometrics with tomographic data, which are often segmented and transformed to three‐dimensional (3D) surface models before measurement. This study aimed to evaluate the effects of different image segmentation methods on geometric morphometric data collection using computed tomography data collected from non‐human primate skulls. Three segmentation methods based on a visually selected threshold, a half‐maximum height protocol and a gradient and watershed algorithm were compared. For each method, the efficiency of surface reconstruction, the accuracy of landmark placement and the level of variation in shape and size compared with various levels of biological variation were evaluated. The visual‐based method inflated the surface in high‐density anatomical regions, whereas the half‐maximum height protocol resulted in a large number of artificial holes and erosion. However, the gradient‐based method mitigated these issues and generated the most efficient surface model. The segmentation method used had a much smaller effect on shape and size variation than interspecific and inter‐individual differences. However, this effect was statistically significant and not negligible when compared with intra‐individual (fluctuating asymmetric) variation. Although the gradient‐based method is not widely used in geometric morphometric analyses, it may be one of promising options for reconstructing 3D surfaces. When evaluating small variations, such as fluctuating asymmetry, care should be taken around combining 3D data that were obtained using different segmentation methods.

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“…Ê òàêîìó aeå âûâîäó ïðèõîäèò è àâñòðàëèéñêèé ó÷åíûé Ê. Ñòåôàí, êîòîðûé â ñâîåé ñòàòüå ñîïîñòàâèë ÷åòûðå ñàìûõ ðàñïðîñòðàíåííûõ ìåòîäèêè âîññòàíîâëåíèÿ íîñîâîé îáëàñòè. Èññëåäîâàòåëüñêèì ìàòåðèàëîì ïîñëóaeèëè 59 ëàòåðàëüíûõ ðåíòãåíîãðàìì, 29 ìóaeñêèõ è 30 aeåíñêèõ, ïðèíàäëåaeàùèõ ñîâðåìåííûì áåëûì àâñòðàëèéöàì [Stephan, 2003] [Evteev et al, 2018].…”

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Craniofacial correlations of the middle part of the face based on computed tomograms

Rasskazova¹,

Russia²,

Veselovskaya³

et al. 2020

MUAB

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Ðåêîíñòðóêöèÿ ëèöà ïî ÷åðåïó øèðîêî èñïîëüçóåòñÿ â ïàëåîàíòðîïîëîãèè, â êðèìèíàëèñòèêå äëÿ èäåíòèôèêàöèè íåîïîçíàííûõ êîñòíûõ îñòàíêîâ, â ìóçåéíîì äåëå ïðè âîññòàíîâëåíèè îáëèêà èñòîðè÷åñêèõ ëèö è ïðåäñòàâèòåëåé äðåâíèõ ïîïóëÿöèé.Ñî âðåìåí ñîçäàíèÿ íàó÷íîãî ìåòîäà àíòðî-ïîëîãè÷åñêîé ðåêîíñòðóêöèè Ì.Ì. Ãåðàñèìîâûì [Ãåðàñèìîâ, 1949] ìíîãèå çàêîíîìåðíîñòè âçàèìî-

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Midfacial growth patterns in males from newborn to 5 years old based on computed tomography

Cited by 13 publications

References 97 publications

Ontogeny of the human maxilla: a study of intra‐population variability combining surface bone histology and geometric morphometrics

Ontogeny of the human maxilla: a study of intra‐population variability combining surface bone histology and geometric morphometrics

Effects of different segmentation methods on geometric morphometric data collection from primate skulls

Craniofacial correlations of the middle part of the face based on computed tomograms

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