This article is based on my talk at the meeting "3rd Advances in Craniosynostosis: Basic Science to Clinical Practice", held at University College, London, on 25 August 2023. It describes my contribution, together with that of my research team and external collaborators, to the field of craniofacial development. This began with my PhD research on the effects of excess vitamin A in rat embryos, which led to a study of normal as well as abnormal formation of the cranial neural tube. Many techniques for analysing morphogenetic change became available to me over the years: whole embryo culture, scanning and transmission electron microscopy, cell division analysis, immunohistochemistry and biochemical analysis of the extracellular matrix. The molecular revolution of the 1980s, and key collaborations with international research teams, enabled functional interpretation of some of the earlier morphological observations and required a change of experimental species to the mouse. Interactions between the molecular and experimental analysis of craniofacial morphogenesis in my laboratory with specialists in molecular genetics and clinicians brought my research journey near to my original aim: to contribute to a better understanding of the causes of human congenital anomalies.
{"title":"A journey in the world of craniofacial development: From 1968 to the future.","authors":"Gillian Morriss-Kay","doi":"10.1111/joa.14057","DOIUrl":"https://doi.org/10.1111/joa.14057","url":null,"abstract":"<p><p>This article is based on my talk at the meeting \"3rd Advances in Craniosynostosis: Basic Science to Clinical Practice\", held at University College, London, on 25 August 2023. It describes my contribution, together with that of my research team and external collaborators, to the field of craniofacial development. This began with my PhD research on the effects of excess vitamin A in rat embryos, which led to a study of normal as well as abnormal formation of the cranial neural tube. Many techniques for analysing morphogenetic change became available to me over the years: whole embryo culture, scanning and transmission electron microscopy, cell division analysis, immunohistochemistry and biochemical analysis of the extracellular matrix. The molecular revolution of the 1980s, and key collaborations with international research teams, enabled functional interpretation of some of the earlier morphological observations and required a change of experimental species to the mouse. Interactions between the molecular and experimental analysis of craniofacial morphogenesis in my laboratory with specialists in molecular genetics and clinicians brought my research journey near to my original aim: to contribute to a better understanding of the causes of human congenital anomalies.</p>","PeriodicalId":14971,"journal":{"name":"Journal of Anatomy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Germán Montoya-Sanhueza, Nigel C. Bennett, Radim Šumbera
Whether the forelimb-digging apparatus of tooth-digging subterranean mammals has similar levels of specialization as compared to scratch-diggers is still unknown. We assessed the scapular morphology and forelimb musculature of all four solitary African mole rats (Bathyergidae): two scratch-diggers, Bathyergus suillus and Bathyergus janetta, and two chisel-tooth diggers, Heliophobius argenteocinereus and Georychus capensis. Remarkable differences were detected: Bathyergus have more robust neck, shoulder, and forearm muscles as compared to the other genera. Some muscles in Bathyergus were also fused and often showing wider attachment areas to bones, which correlate well with its more robust and larger scapula, and its wider and medially oriented olecranon. This suggests that shoulder, elbow, and wrist work in synergy in Bathyergus for generating greater out-forces and that the scapula and proximal ulna play fundamental roles as pivots to maximize and accommodate specialized muscles for better (i) glenohumeral and scapular stabilization, (ii) powerful shoulder flexion, (iii) extension of the elbow and (iv) flexion of the manus and digits. Moreover, although all bathyergids showed a similar set of muscles, Heliophobius lacked the m. tensor fasciae antebrachii (aiding with elbow extension and humeral retraction), and Heliophobius and Georychus lacked the m. articularis humeri (aiding with humeral adduction), indicating deeper morphogenetic differences among digging groups and suggesting a relatively less specialized scratch-digging ability. Nevertheless, Heliophobius and Bathyergus shared some similar adaptations allowing scratch-digging. Our results provide new information about the morphological divergence within this family associated with the specialization to distinct functions and digging behaviors, thus contributing to understand the mosaic of adaptations emerging in phylogenetically and ecologically closer subterranean taxa. This and previous anatomical studies on the Bathyergidae will provide researchers with a substantial basis on the form and function of the musculoskeletal system for future kinematic investigations of digging behavior, as well as to define potential indicators of scratch-digging ability.
{"title":"Functional and morphological divergence in the forelimb musculoskeletal system of scratch-digging subterranean mammals (Rodentia: Bathyergidae)","authors":"Germán Montoya-Sanhueza, Nigel C. Bennett, Radim Šumbera","doi":"10.1111/joa.14058","DOIUrl":"10.1111/joa.14058","url":null,"abstract":"<p>Whether the forelimb-digging apparatus of tooth-digging subterranean mammals has similar levels of specialization as compared to scratch-diggers is still unknown. We assessed the scapular morphology and forelimb musculature of all four solitary African mole rats (Bathyergidae): two scratch-diggers, <i>Bathyergus suillus</i> and <i>Bathyergus janetta</i>, and two chisel-tooth diggers, <i>Heliophobius argenteocinereus</i> and <i>Georychus capensis</i>. Remarkable differences were detected: <i>Bathyergus</i> have more robust neck, shoulder, and forearm muscles as compared to the other genera. Some muscles in <i>Bathyergus</i> were also fused and often showing wider attachment areas to bones, which correlate well with its more robust and larger scapula, and its wider and medially oriented olecranon. This suggests that shoulder, elbow, and wrist work in synergy in <i>Bathyergus</i> for generating greater out-forces and that the scapula and proximal ulna play fundamental roles as pivots to maximize and accommodate specialized muscles for better (i) glenohumeral and scapular stabilization, (ii) powerful shoulder flexion, (iii) extension of the elbow and (iv) flexion of the manus and digits. Moreover, although all bathyergids showed a similar set of muscles, <i>Heliophobius</i> lacked the m. tensor fasciae antebrachii (aiding with elbow extension and humeral retraction), and <i>Heliophobius</i> and <i>Georychus</i> lacked the m. articularis humeri (aiding with humeral adduction), indicating deeper morphogenetic differences among digging groups and suggesting a relatively less specialized scratch-digging ability. Nevertheless, <i>Heliophobius</i> and <i>Bathyergus</i> shared some similar adaptations allowing scratch-digging. Our results provide new information about the morphological divergence within this family associated with the specialization to distinct functions and digging behaviors, thus contributing to understand the mosaic of adaptations emerging in phylogenetically and ecologically closer subterranean taxa. This and previous anatomical studies on the Bathyergidae will provide researchers with a substantial basis on the form and function of the musculoskeletal system for future kinematic investigations of digging behavior, as well as to define potential indicators of scratch-digging ability.</p>","PeriodicalId":14971,"journal":{"name":"Journal of Anatomy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11306765/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isaac S Walton, Emma McCann, Astrid Weber, Jenny E V Morton, Peter Noons, Louise C Wilson, Rosanna C Ching, Deirdre Cilliers, David Johnson, Julie M Phipps, Deborah J Shears, Gregory P L Thomas, Steven A Wall, Stephen R F Twigg, Andrew O M Wilkie
The RUNT-related transcription factor RUNX2 plays a critical role in osteoblast differentiation, and alterations to gene dosage cause distinct craniofacial anomalies. Uniquely amongst the RUNT-related family, vertebrate RUNX2 encodes a polyglutamine/polyalanine repeat (Gln23-Glu-Ala17 in humans), with the length of the polyalanine component completely conserved in great apes. Surprisingly, a frequent 6-amino acid deletion polymorphism, p.(Ala84_Ala89)del, occurs in humans (termed 11A allele), and a previous association study (Cuellar et al. Bone 137:115395;2020) reported that the 11A variant was significantly more frequent in non-syndromic sagittal craniosynostosis (nsSag; allele frequency [AF] = 0.156; 95% confidence interval [CI] 0.126-0.189) compared to non-syndromic metopic craniosynostosis (nsMet; AF = 0.068; 95% CI 0.045-0.098). However, the gnomAD v.2.1.1 control population used by Cuellar et al. did not display Hardy-Weinberg equilibrium, hampering interpretation. To re-examine this association, we genotyped the RUNX2 11A polymorphism in 225 individuals with sporadic nsSag as parent-child trios and 164 singletons with sporadic nsMet, restricting our analysis to individuals of European ancestry. We compared observed allele frequencies to the non-transmitted alleles in the parent-child trios, and to the genome sequencing data from gnomAD v.4, which display Hardy-Weinberg equilibrium. Observed AFs (and 95% CI) were 0.076 (0.053-0.104) in nsSag and 0.082 (0.055-0.118) in nsMet, compared with 0.062 (0.042-0.089) in non-transmitted parental alleles and 0.065 (0.063-0.067) in gnomAD v.4.0.0 non-Finnish European control genomes. In summary, we observed a non-significant excess, compared to gnomAD data, of 11A alleles in both nsSag (relative risk 1.18, 95% CI 0.83-1.67) and nsMet (relative risk 1.29, 95% CI 0.87-1.92), but we did not replicate the much higher excess of RUNX2 11A alleles in nsSag previously reported (p = 0.0001).
RUNT 相关转录因子 RUNX2 在成骨细胞分化过程中起着关键作用,基因剂量的改变会导致不同的颅面异常。在 RUNT 相关家族中,脊椎动物 RUNX2 编码一个多谷氨酰胺/多丙氨酸重复序列(人类为 Gln23-Glu-Ala17),其多丙氨酸成分的长度在类人猿中完全保留。令人惊讶的是,在人类中经常出现一种 6 氨基酸缺失多态性 p.(Ala84_Ala89)del(称为 11A 等位基因),之前的一项关联研究(Cuellar et al.之前的关联研究(Cuellar et al. Bone 137:115395;2020)报告称,与非综合畸形偏位颅骨发育不良(nsMet; AF = 0.068; 95% CI 0.045-0.098)相比,11A等位基因在非综合畸形矢状颅颅骨发育不良(nsSag; 等位基因频率 [AF] = 0.156; 95% 置信区间 [CI] 0.126-0.189)中的出现频率明显更高。然而,Cuellar等人使用的gnomAD v.2.1.1对照人群并没有显示出Hardy-Weinberg平衡,从而影响了解释。为了重新研究这种关联,我们对225名散发性nsSag亲子三人组和164名散发性nsMet单人组中的RUNX2 11A多态性进行了基因分型,分析对象仅限于欧洲血统的个体。我们将观察到的等位基因频率与亲子三人组中未传播的等位基因频率以及 gnomAD v.4 中的基因组测序数据进行了比较,后者显示了哈代-温伯格平衡(Hardy-Weinberg equilibrium)。在 nsSag 和 nsMet 中,观察到的等位基因频率(及 95% CI)分别为 0.076(0.053-0.104)和 0.082(0.055-0.118),而在未传播的亲代等位基因中,观察到的等位基因频率为 0.062(0.042-0.089),在 gnomAD v.4.0.0 非芬兰欧洲对照基因组中,观察到的等位基因频率为 0.065(0.063-0.067)。总之,与 gnomAD 数据相比,我们在 nsSag(相对风险为 1.18,95% CI 为 0.83-1.67)和 nsMet(相对风险为 1.29,95% CI 为 0.87-1.92)中都观察到了 11A 等位基因的非显著过量,但我们并没有复制之前报道的 nsSag 中 RUNX2 11A 等位基因的过量(p = 0.0001)。
{"title":"Reassessing the association: Evaluation of a polyalanine deletion variant of RUNX2 in non-syndromic sagittal and metopic craniosynostosis.","authors":"Isaac S Walton, Emma McCann, Astrid Weber, Jenny E V Morton, Peter Noons, Louise C Wilson, Rosanna C Ching, Deirdre Cilliers, David Johnson, Julie M Phipps, Deborah J Shears, Gregory P L Thomas, Steven A Wall, Stephen R F Twigg, Andrew O M Wilkie","doi":"10.1111/joa.14052","DOIUrl":"https://doi.org/10.1111/joa.14052","url":null,"abstract":"<p><p>The RUNT-related transcription factor RUNX2 plays a critical role in osteoblast differentiation, and alterations to gene dosage cause distinct craniofacial anomalies. Uniquely amongst the RUNT-related family, vertebrate RUNX2 encodes a polyglutamine/polyalanine repeat (Gln<sub>23</sub>-Glu-Ala<sub>17</sub> in humans), with the length of the polyalanine component completely conserved in great apes. Surprisingly, a frequent 6-amino acid deletion polymorphism, p.(Ala84_Ala89)del, occurs in humans (termed 11A allele), and a previous association study (Cuellar et al. Bone 137:115395;2020) reported that the 11A variant was significantly more frequent in non-syndromic sagittal craniosynostosis (nsSag; allele frequency [AF] = 0.156; 95% confidence interval [CI] 0.126-0.189) compared to non-syndromic metopic craniosynostosis (nsMet; AF = 0.068; 95% CI 0.045-0.098). However, the gnomAD v.2.1.1 control population used by Cuellar et al. did not display Hardy-Weinberg equilibrium, hampering interpretation. To re-examine this association, we genotyped the RUNX2 11A polymorphism in 225 individuals with sporadic nsSag as parent-child trios and 164 singletons with sporadic nsMet, restricting our analysis to individuals of European ancestry. We compared observed allele frequencies to the non-transmitted alleles in the parent-child trios, and to the genome sequencing data from gnomAD v.4, which display Hardy-Weinberg equilibrium. Observed AFs (and 95% CI) were 0.076 (0.053-0.104) in nsSag and 0.082 (0.055-0.118) in nsMet, compared with 0.062 (0.042-0.089) in non-transmitted parental alleles and 0.065 (0.063-0.067) in gnomAD v.4.0.0 non-Finnish European control genomes. In summary, we observed a non-significant excess, compared to gnomAD data, of 11A alleles in both nsSag (relative risk 1.18, 95% CI 0.83-1.67) and nsMet (relative risk 1.29, 95% CI 0.87-1.92), but we did not replicate the much higher excess of RUNX2 11A alleles in nsSag previously reported (p = 0.0001).</p>","PeriodicalId":14971,"journal":{"name":"Journal of Anatomy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tareq Abdel-Alim, Franz Tapia Chaca, Irene M J Mathijssen, Clemens M F Dirven, Wiro J Niessen, Eppo B Wolvius, Marie-Lise C van Veelen, Gennady V Roshchupkin
Background: Craniosynostosis, a congenital condition characterized by the premature fusion of cranial sutures, necessitates objective methods for evaluating cranial morphology to enhance patient treatment. Current subjective assessments often lead to inconsistent outcomes. This study introduces a novel, quantitative approach to classify craniosynostosis and measure its severity.
Methods: An artificial neural network was trained to classify normocephalic, trigonocephalic, and scaphocephalic head shapes based on a publicly available dataset of synthetic 3D head models. Each 3D model was converted into a low-dimensional shape representation based on the distribution of normal vectors, which served as the input for the neural network, ensuring complete patient anonymity and invariance to geometric size and orientation. Explainable AI methods were utilized to highlight significant features when making predictions. Additionally, the Feature Prominence (FP) score was introduced, a novel metric that captures the prominence of distinct shape characteristics associated with a given class. Its relationship with clinical severity scores was examined using the Spearman Rank Correlation Coefficient.
Results: The final model achieved excellent test accuracy in classifying the different cranial shapes from their low-dimensional representation. Attention maps indicated that the network's attention was predominantly directed toward the parietal and temporal regions, as well as toward the region signifying vertex depression in scaphocephaly. In trigonocephaly, features around the temples were most pronounced. The FP score showed a strong positive monotonic relationship with clinical severity scores in both scaphocephalic (ρ = 0.83, p < 0.001) and trigonocephalic (ρ = 0.64, p < 0.001) models. Visual assessments further confirmed that as FP values rose, phenotypic severity became increasingly evident.
Conclusion: This study presents an innovative and accessible AI-based method for quantifying cranial shape that mitigates the need for adjustments due to age-specific size variations or differences in the spatial orientation of the 3D images, while ensuring complete patient privacy. The proposed FP score strongly correlates with clinical severity scores and has the potential to aid in clinical decision-making and facilitate multi-center collaborations. Future work will focus on validating the model with larger patient datasets and exploring the potential of the FP score for broader applications. The publicly available source code facilitates easy implementation, aiming to advance craniofacial care and research.
{"title":"Quantifying dysmorphologies of the neurocranium using artificial neural networks.","authors":"Tareq Abdel-Alim, Franz Tapia Chaca, Irene M J Mathijssen, Clemens M F Dirven, Wiro J Niessen, Eppo B Wolvius, Marie-Lise C van Veelen, Gennady V Roshchupkin","doi":"10.1111/joa.14061","DOIUrl":"https://doi.org/10.1111/joa.14061","url":null,"abstract":"<p><strong>Background: </strong>Craniosynostosis, a congenital condition characterized by the premature fusion of cranial sutures, necessitates objective methods for evaluating cranial morphology to enhance patient treatment. Current subjective assessments often lead to inconsistent outcomes. This study introduces a novel, quantitative approach to classify craniosynostosis and measure its severity.</p><p><strong>Methods: </strong>An artificial neural network was trained to classify normocephalic, trigonocephalic, and scaphocephalic head shapes based on a publicly available dataset of synthetic 3D head models. Each 3D model was converted into a low-dimensional shape representation based on the distribution of normal vectors, which served as the input for the neural network, ensuring complete patient anonymity and invariance to geometric size and orientation. Explainable AI methods were utilized to highlight significant features when making predictions. Additionally, the Feature Prominence (FP) score was introduced, a novel metric that captures the prominence of distinct shape characteristics associated with a given class. Its relationship with clinical severity scores was examined using the Spearman Rank Correlation Coefficient.</p><p><strong>Results: </strong>The final model achieved excellent test accuracy in classifying the different cranial shapes from their low-dimensional representation. Attention maps indicated that the network's attention was predominantly directed toward the parietal and temporal regions, as well as toward the region signifying vertex depression in scaphocephaly. In trigonocephaly, features around the temples were most pronounced. The FP score showed a strong positive monotonic relationship with clinical severity scores in both scaphocephalic (ρ = 0.83, p < 0.001) and trigonocephalic (ρ = 0.64, p < 0.001) models. Visual assessments further confirmed that as FP values rose, phenotypic severity became increasingly evident.</p><p><strong>Conclusion: </strong>This study presents an innovative and accessible AI-based method for quantifying cranial shape that mitigates the need for adjustments due to age-specific size variations or differences in the spatial orientation of the 3D images, while ensuring complete patient privacy. The proposed FP score strongly correlates with clinical severity scores and has the potential to aid in clinical decision-making and facilitate multi-center collaborations. Future work will focus on validating the model with larger patient datasets and exploring the potential of the FP score for broader applications. The publicly available source code facilitates easy implementation, aiming to advance craniofacial care and research.</p>","PeriodicalId":14971,"journal":{"name":"Journal of Anatomy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marius Didziokas, Erwin Pauws, Lars Kölby, Roman H Khonsari, Mehran Moazen
X-ray Computed Tomography (CT) images are widely used in various fields of natural, physical, and biological sciences. 3D reconstruction of the images involves segmentation of the structures of interest. Manual segmentation has been widely used in the field of biological sciences for complex structures composed of several sub-parts and can be a time-consuming process. Many tools have been developed to automate the segmentation process, all with various limitations and advantages, however, multipart segmentation remains a largely manual process. The aim of this study was to develop an open-access and user-friendly tool for the automatic segmentation of calcified tissues, specifically focusing on craniofacial bones. Here we describe BounTI, a novel segmentation algorithm which preserves boundaries between separate segments through iterative thresholding. This study outlines the working principles behind this algorithm, investigates the effect of several input parameters on its outcome, and then tests its versatility on CT images of the craniofacial system from different species (e.g. a snake, a lizard, an amphibian, a mouse and a human skull) with various scan qualities. The case studies demonstrate that this algorithm can be effectively used to segment the craniofacial system of a range of species automatically. High-resolution microCT images resulted in more accurate boundary-preserved segmentation, nonetheless significantly lower-quality clinical images could still be segmented using the proposed algorithm. Methods for manual intervention are included in this tool when the scan quality is insufficient to achieve the desired segmentation results. While the focus here was on the craniofacial system, BounTI can be used to automatically segment any hard tissue. The tool presented here is available as an Avizo/Amira add-on, a stand-alone Windows executable, and a Python library. We believe this accessible and user-friendly segmentation tool can benefit the wider anatomical community.
X 射线计算机断层扫描(CT)图像被广泛应用于自然、物理和生物科学的各个领域。图像的三维重建需要对相关结构进行分割。人工分割在生物科学领域被广泛应用于由多个子部分组成的复杂结构,而且可能是一个耗时的过程。目前已开发出许多工具来实现分割过程的自动化,这些工具都有不同的局限性和优点,但多部分分割在很大程度上仍然是一个手动过程。本研究的目的是开发一种开放访问、用户友好的钙化组织自动分割工具,尤其侧重于颅面骨骼。我们在此介绍一种新颖的分割算法 BounTI,该算法通过迭代阈值处理保留独立片段之间的边界。本研究概述了该算法背后的工作原理,研究了几个输入参数对其结果的影响,然后在不同物种(如蛇、蜥蜴、两栖动物、小鼠和人类头骨)的颅面部系统 CT 图像上测试了该算法在不同扫描质量下的通用性。案例研究表明,该算法可有效用于自动分割一系列物种的颅面系统。高分辨率的 microCT 图像可实现更精确的边界保留分割,但质量明显较低的临床图像仍可使用所提出的算法进行分割。当扫描质量不足以实现理想的分割结果时,该工具还包括人工干预方法。虽然这里的重点是颅面系统,但 BounTI 可用于自动分割任何硬组织。这里介绍的工具可作为 Avizo/Amira 的附加组件、独立的 Windows 可执行文件和 Python 库使用。我们相信这款方便易用的分割工具能让更多的解剖界人士受益。
{"title":"BounTI (boundary-preserving threshold iteration): A user-friendly tool for automatic hard tissue segmentation.","authors":"Marius Didziokas, Erwin Pauws, Lars Kölby, Roman H Khonsari, Mehran Moazen","doi":"10.1111/joa.14063","DOIUrl":"https://doi.org/10.1111/joa.14063","url":null,"abstract":"<p><p>X-ray Computed Tomography (CT) images are widely used in various fields of natural, physical, and biological sciences. 3D reconstruction of the images involves segmentation of the structures of interest. Manual segmentation has been widely used in the field of biological sciences for complex structures composed of several sub-parts and can be a time-consuming process. Many tools have been developed to automate the segmentation process, all with various limitations and advantages, however, multipart segmentation remains a largely manual process. The aim of this study was to develop an open-access and user-friendly tool for the automatic segmentation of calcified tissues, specifically focusing on craniofacial bones. Here we describe BounTI, a novel segmentation algorithm which preserves boundaries between separate segments through iterative thresholding. This study outlines the working principles behind this algorithm, investigates the effect of several input parameters on its outcome, and then tests its versatility on CT images of the craniofacial system from different species (e.g. a snake, a lizard, an amphibian, a mouse and a human skull) with various scan qualities. The case studies demonstrate that this algorithm can be effectively used to segment the craniofacial system of a range of species automatically. High-resolution microCT images resulted in more accurate boundary-preserved segmentation, nonetheless significantly lower-quality clinical images could still be segmented using the proposed algorithm. Methods for manual intervention are included in this tool when the scan quality is insufficient to achieve the desired segmentation results. While the focus here was on the craniofacial system, BounTI can be used to automatically segment any hard tissue. The tool presented here is available as an Avizo/Amira add-on, a stand-alone Windows executable, and a Python library. We believe this accessible and user-friendly segmentation tool can benefit the wider anatomical community.</p>","PeriodicalId":14971,"journal":{"name":"Journal of Anatomy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140957214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}