Evaluation of growth and development period according to spheno-occipital synchondrosis fusion stages in cone-beam computed tomography with ImageJ program

Abstract

Spheno-occipital synchondrosis (SOS) is an important growth area in the craniofacial skeleton. It has been explored in research relate to age assessment and forensic medicine due to its closure in the postnatal period. The aim of this study is to evaluate the growth and development period of SOS on cone-beam computed tomography (CBCT) images with pseudo-color imaging depend on fusion stages. In this cross-sectional retrospective study, 280 CBCT sagittal sections’ images (163 women, 117 men) were used to evaluate the SOS fusion stages by dividing them into five categories. ImageJ version 1.3 software was used to analyze. SOS stages and histogram analyzes were evaluated. The significance level was set at p = 0.05. In the evaluation of synchondrosis stages according to gender and age, the incidence of stages 4 and 5 in individuals aged 15–25 years was statistically significantly higher (p < 0.01) compared to stages 1 and 2 in individuals aged 5–14 years. The mean minimum, maximum and open histogram values of synchondroses in the same age group were also statistically significantly higher (p < 0.05). In the assessment of synchondrosis maturation using three-way ROC analysis, histogram analyses indicated Stage 1 for data below 68.33, Stage 3 for data above 104.5, and Stage 2 for values in between. ImageJ histogram analysis can numerically reveal radiographic differences between SOS fusion stages and can perform staging on pseudo-colored cross-sectional CBCT images. Different image processing software can reveal differences between phases through false coloring.

Introduction

Spheno-ethmoidal synchondrosis (SES), spheno-occipital synchondrosis (SOS) and intersphenoid synchondrosis (ISS) present along the midline in the cranial base are important growth centers of the craniofacial skeleton^1,2. These are temporary cartilage joints of endochondral origin².

The SOS is a groove that extends from the clivus to the pharyngeal surface of the cranial base.^3,4. It is located between the sphenoid bone and the basilar portion of the occipital bone.⁵. SOS represents a significant area of development within the craniofacial skeleton. It has been investigated in studies pertaining to age assessment and forensic medicine due to its proximity in the postnatal period.^3,6. The initiation of SOS ossification has been demonstrated to affect the severity of midface hypoplasia in individuals with craniofacial syndrome⁷. The extension of the cranial base axis and its influence on dentoalveolar development render SOS a significant structure. While SOS growing, the maxilla ascends and advances in relation to the mandible. Consequently, face height and depth augment^3–5. This orthodontically significant condition has been demonstrated to induce a minor abrupt extension of the SOS in young persons during fast maxillary development⁵. The spheno-ethmoidal synchondrosis (SES), spheno-occipital synchondrosis (SOS), and intersphenoid synchondrosis (ISS) situated along the midline of the cranial base are crucial growth areas of the craniofacial skeleton. Assessing spheno-occipital synchondrosis (SOS) fusion stages can inform clinical decision-making in orthodontics and maxillofacial surgery, such as determining optimal timing for growth-modification therapies and surgical interventions⁸.

Ossification of the SOS initiates from the endocranial surface and the superior portion of the groove. Subsequently, it advances toward the ectocranial surface and descends. This fusion often concludes around two years earlier in females than in males. No notable disparity was observed between genders regarding the advancement of fusion post age 16. The union of the sphenoid and occipital bones is fully accomplished by the age of 25⁹.

The quantitative evaluation of bone alterations has been enabled by advancements in image analysis techniques supported by modern digital technologies. Anatomical regions exhibiting varying tissue thicknesses are transformed into digital data and rendered in color utilizing the software. Pseudo-coloring with ImageJ software (Wayne Rasband, US National Institutes of Health-NIH, Maryland, Bethesda, USA) is a widely employed image processing method for this particular objective. This software is an intuitive and straightforward scientific image processing application. The light and dark shades of the same scale can be ascertained based on the energy level color gradients and transformed into a color spectrum (pseudo-coloring) perceivable by the human eye^10,11.

Imaging techniques enable the precise evaluation of growth and developmental processes, the early detection of pathological changes, and the detailed analysis of anatomical structures. These capabilities contribute to the development of more personalized, targeted, and effective treatment plans. Additionally, the detailed data obtained from these methods serve as a reliable guide in forensic applications, such as identity verification, age estimation, and the assessment of craniofacial anomalies. These techniques not only enhance clinical decision-making processes but also provide a scientific foundation for forensic investigations. In this context, the aim of this study is to analyze the fusion stages of the spheno-occipital synchondrosis using cone-beam computed tomography (CBCT) images processed with ImageJ software. The study seeks to evaluate these fusion stages to understand growth and developmental phases better and to contribute the findings to both clinical applications and forensic practices.

Material and methods

Sample

This cross-sectional retrospective study utilized 280 CBCT pictures (163 females, 117 males) acquired for several diagnostic purposes between 2020 and 2023 to assess the SOS fusion stages, categorizing them into five distinct stages¹² (Fig. 1). The requisite ethical approval for the research was obtained from the Non-Pharmaceutical and Medical Device Research Ethics Committee of Necmettin Erbakan University Faculty of Dentistry (Approval Number: 2023/307). All modifications were executed in compliance with the principles established in the Declaration of Helsinki.

Fig. 1.

Stages of spheno-occipital synchondrosis (A) Stage 1; (B) Stage 2; (C) Stage 3; (D) Stage 4; (E) Stage 5.

A one-tailed independent samples t-test analysis, utilizing a 95% confidence interval (1-α), 95% test power (1-β), and an effect size of d = 0.518, established that the minimum requisite sample size for each group is 85¹³.

The study contained high-quality CBCT pictures of patients aged 6 to 25 years exhibiting SOS in sagittal areas. The study’s exclusion criteria encompass diagnostically inadequate CBCT images, substandard image quality, presence of artifacts, patients over 25 years of age, craniofacial abnormalities, and a history of trauma or surgery in the maxillofacial region. Syndromic illnesses affect the maxillofacial region in patients following cancer surgery and the prevalence of common pathologies in the maxillofacial area.

Radiographic examination

Exposure settings of 90 kVp, 17.5 s scan duration at 5 mA, and 0.250 mm voxel resolution were acquired from three distinct CBCT machines: J Morita MFG. Corp., 3D Accuitomo 170, Kyoto, Japan; Newtom Go 2D/3D/CEPH, Bologna, Italy; and Newtom Giano HR, Bologna, Italy. The 3D data in DICOM format was analyzed using 3D Slicer software on a 3.7 MP, 68 cm, 2560 × 1440 resolution, 27-inch color Ultra Sharp LED TFT display (Dell, Dell Inc., Round Rock, TX, USA). Two-dimensional images were acquired from the sagittal axis portion where the SOS exhibited the greatest fusion in the analyzed images. To ensure proper viewing and consistency, the contrast and brightness of the photos were adjusted to 600dpi using image processing software.

ImageJ program

ImageJ version 1.3 software (Wayne Rasband, US National Institutes of Health-NIH, Maryland, Bethesda, USA) was utilized to analyze 2D images stored in TIFF format. ImageJ is a complimentary public domain software available for download at http://rsb.info.nih.gov/ij/download.html.

To enhance the differentiation in the color spectrum, cross-sectional images imported into ImageJ using the File/Open command were modified to the maximum contrast 32-bit setting permitted by the software, utilizing the Image/Type/32-bit command. The Image/Zoom/Maximize command was employed to streamline the area selection procedure and to identify the region of interest (ROI) at the optimal place. The Process/Noise/Despeckle command was employed to generate a spectrum conducive to assessing synchondrosis by enhancing the blurred image and diminishing noise in cross-sectional images. The ultimate pseudo color representation of the cross-sectional images was acquired for analysis using the Image/Lookup Tables/Spectrum command, and areas of interest (ROI) measuring 30 × 25 pixels were designated. The spectrum was ultimately transformed into numerical data using the Analyze/Histogram function. To standardize ROI, the boundaries were defined as follows: the superior aspect of the sella turcica above, the upper portion of the first vertebra below, the anterior wall of the sphenoid sinus anteriorly, and posteriorly, a perpendicular line drawn from the anterior wall of the foramen magnum to the superior edge of the cross-sectional image (Fig. 2).

Fig. 2.

Steps of Pseudocolor Imaging and Histogram Analysis with ImageJ (A) Images were adjusted to the widest contrast 32-bit option allowed by the program, again with the Image/Type/32-bit command. (B) Image/Zoom/Maximize command was used to facilitate the region selection process and to select the region of interest (ROI) in the most appropriate position. (C) The Process/Noise/Despeckle command was used to create a spectrum suitable for evaluating synchondrosis by increasing the blurred image and reducing the noise in cross-sectional images. (D) The final pseudo color form of the cross-sectional images was obtained for analysis with the Image/Lookup Tables/Spectrum command. (E) Finally, the spectrum was converted to numerical data with the Analyze/Histogram command.)

Each image was assessed two weeks apart by two evaluators with 7 (S.U.) and 10 years (C.E.) of expertise. Cronbach’s alpha coefficients for intra-observer reliability ranged from 0.90 to 0.95, signifying a good level of consistency among measures. Cronbach’s alpha coefficients for inter-observer reliability varied from 0.85 to 0.91, signifying robust inter-observer agreement.

Statistical analysis

Data analysis was conducted using IBM SPSS Statistics v29 (IBM Corp., Armonk, NY, USA). Descriptive statistics included the calculation of medians and interquartile ranges. Comparative analyses were performed using the Mann–Whitney U test, Friedman test, and ROC (Receiver Operating Characteristic) curve analysis. ROC analysis was employed to determine the cut-off points distinguishing the fusion stages of the spheno-occipital synchondrosis, particularly when histogram values demonstrated statistically significant differences between stages. A significance level of p = 0.05 was adopted.

Intra- and inter-observer reliabilities were assessed using Cronbach’s alpha coefficients. The results indicated strong reliability, with intra-observer reliability ranging from 0.90 to 0.95 and inter-observer reliability ranging from 0.85 to 0.91.

Results

The SOS fusion stages provide valuable insights for orthodontists in determining the timing of growth-modification therapies. For instance, advanced fusion stages (Stages 4 and 5) suggest the closure of craniofacial growth windows, which may influence the decision to use growth-dependent interventions like maxillary expansion or functional appliances. By contrast, earlier fusion stages (Stages 1 and 2) indicate ongoing skeletal growth, allowing orthodontists to time interventions to maximize outcomes. This data-driven approach helps reduce the risks of initiating treatments too early or too late, optimizing patient care. On the other hand, for maxillofacial surgeons, SOS maturation stages can guide preoperative planning by providing an estimate of skeletal stability and growth potential. In younger patients with incomplete SOS fusion (Stages 1–3), procedures such as distraction osteogenesis or skeletal reconstructions may require careful consideration of future growth^14,15.

Of the total participants, 263 were able to assess synchondrosis patency using the Image J program and 17 were not (Table 1). Table 1 includes the minimum, maximum and mean histogram values for open and closed synchondroses. The mean age of participants was 15.28 ± 5.18 years. In the evaluation of synchondrosis stages according to gender and age, the incidence of stages 4 and 5 in individuals aged 15–25 years was statistically significantly higher (p < 0.01) compared to stages 1 and 2 in individuals aged 5–14 years (Table 2). Stage 1 was significantly more common in males and stage 5 in females (p < 0.01) (Table 2). Females exhibited earlier fusion stages compared to males, consistent with hormonal and genetic influences on skeletal growth.

Table 1.

Demographic Distribution and Mean Synchondrosis Histogram Values According to Gender and Age Categories.

	n	Synchondrosis Evaluation with Image J			Histogram of Synchondrosis
		Yes	None	p value	Minimum	p value	Maximum	p value	Open	p value	Closed	p value
Overall	280	263	17		15.27 ± 20.99		151.57 ± 44.44		74.81 ± 22.23		94.77 ± 27.35
Age
5–14 years	129	115a	14b	0.002**	18.56 ± 22.26	0.009**	148.30 ± 43.35	0.013*	73.43 ± 22.27	0.025*	93.72 ± 27.02	0.585
15–25 years	151	148a	3b		12.46 ± 19.46		154.36 ± 45.30		88.90 ± 16.89		95.24 ± 27.57
Gender
Male	117	108	9	0.448	16.98 ± 21.33	0.218	151.03 ± 45.18	0.490	69.57 ± 20.52	0.008**	93.43 ± 24.15	0.433
Female	163	155	8		14.05 ± 20.72		151.95 ± 44.03		81.80 ± 22.70		95.44 ± 28.88
Stage						0.054		0.135		0.002**		0.468
Stage 1	55	50a	5a	0.001**	19.73 ± 21.47		144.55 ± 49.44		67.36 ± 21.33
Stage 2	60	50a	10b		18.30 ± 23.57		153.87 ± 33.81		78.74 ± 20.25		97.11 ± 23.98
Stage 3	12	12a	0a		17.09 ± 26.12		162.00 ± 15.57		88.55 ± 24.74		98.53 ± 22.83
Stage 4	47	46a	1a		10.86 ± 18.56		162.66 ± 41.97				97.87 ± 25.94
Stage 5	106	105	1a		13.00 ± 19.19		147.8 ± 49.39				92.44 ± 29.39

The superscript letters 'a', 'b’ indicate which groups differ statistically from each other.

n: Number.

*: p < 0.05.

**: p < 0.01.

Table 2.

Distribution of Sychondrosis Categorization According to Age and Gender.

	Age Group			Gender
	5–14 years	15–25 years	p value	Male	Female	p value
Stage
Stage 1	55a	0b	0.000**	40a	15b	0.000**
Stage 2	54a	6b		29a	31a
Stage 3	7a	5a		3a	9a
Stage 4	7a	40b		21a	26a
Stage 5	6a	100b		24a	82b

The superscript letters 'a', 'b' indicates which groups differ statistically from each other.

** p < 0.01.

When age-related evaluation was made, the rate of unevaluated synchondrosis openings in the 5–14 age group was found to be statistically significantly higher than in the 15–25 age group (p < 0.01) (Table 1). The mean minimum, maximum and open histogram values of synchondroses in the same age group were also statistically significantly higher (p < 0.05) (Table 1).

In the gender-based analysis, except for the mean open synchondrosis histogram, no statistically significant difference was found in other histogram parameters according to gender (p > 0.05) (Table 1). The mean open synchondrosis histogram value was significantly higher in female participants compared to male participants (p < 0.01) (Table 1).

In the evaluation according to the synchondrosis stages, the rate of not assessing synchondrosis openness with Image J was statistically higher in individuals with Stage 2 synchondrosis (p < 0.01) (Table 1). During the transition from Stage 1 to Stage 3, an increase in the mean open synchondrosis histogram value was observed (p < 0.01) (Table 1).

Histogram cut-off values distinguished SOS stages: below 68.33 for Stage 1, between 68.33 and 104.5 for Stage 2, and above 104.5 for Stage 3. These thresholds facilitate stage identification and have implications for age estimation in clinical and forensic settings. ROC analyses yielded moderate discrimination (AUC: 0.655–0.715). In the evaluation made in terms of age groups, it was found that the histogram results obtained with cut-off values above 74.33 indicated individuals in the 15–25 age range. In the ROC analysis specific to this age range, the AUC value was calculated as 0.715 (Table 3).

Table 3.

Cut Points, Sensitivity and Specificity Statistics According to Histogram Results for Age and Stage Prediction Data in Individuals with Open Synchondrosis.

	Cutpoint	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	Youden’s index	AUC	Metric Score
Stage 1 and 2	68.33	55.1	72.55	65.85	62.71	0.277	0.655	1.28
Stage 2 and 3	104.5	41.67	92.16	55.56	87.04	0.338	0.652	0.338
Age Groups	73.33	90	57.84	17.31	98.33	0.478	0.715	1.48

%: Percent; PPV: Positive Predictive Value; NPV: Negative Predictive Value; AUC: Area Under Curve.

Beyond statistical findings, these cut-off values facilitate differentiation of developmental stages, potentially aiding clinicians in age estimation and forensic experts in legal contexts.

Discussion

In orthodontics, SOS staging can assist clinicians in determining the optimal timing for growth modification therapies, such as maxillary expansion or skeletal anchorage systems. Accurate assessment of skeletal maturity ensures that interventions are aligned with the patient’s developmental stage, maximizing their effectiveness and minimizing potential complications. Similarly, in maxillofacial surgery, SOS fusion stages can guide surgical planning by providing insights into craniofacial growth patterns and stability, particularly in procedures involving skeletal reconstruction or corrective surgery^14,15. Further, the ability to estimate age based on SOS fusion stages offers significant utility in forensic medicine. In cases where age determination is required—such as assessing criminal liability or identifying unidentified remains—the findings of this study can assist forensic experts in providing reliable age estimations within the critical 5–25-year age range. The age thresholds identified in this study align with international legal standards, such as defining the age of criminal responsibility, further solidifying the relevance of this method in forensic investigations. Investigating the detection of this significant anatomical structure through pseudocoloring and histogram analysis is believed to enhance the literature as an additional evaluation tool for optimal timing in orthodontic treatments, orthognathic surgery planning, early diagnosis and treatment of craniosynostosis or midface hypoplasia, and forensic age estimation.

From a forensic science perspective, determining whether an individual is a child, or a young adult is crucial for various reasons, primarily including legal responsibilities, criminal liability, and the protection of children. There are numerous methods used to make this distinction and to determine age. A review conducted in 2002 suggested that the SOS could be used for this distinction¹⁶. The age of criminal responsibility varies significantly from country to country; however, the upper age limit for considering a person as a child is generally accepted to be 12–14 years worldwide¹⁷. Therefore, in our study, we formed groups within the age ranges of 5–14 and 15–25 years.

Although direct age assessment using SOS closure may be impractical, age ranges can be inferred from the stages of SOS closure. In a retrospective study conducted in 2010 on individuals aged 15–25, all individuals over the age of 15 were observed to be in Stage 4 or 5, except for two individuals aged 16 who were observed in Stages 1 and 3, respectively¹⁸. Another study conducted in 2014 on 638 individuals aged 10–25 found that Stage 1 was observed in only one individual over the age of 15. Similarly, in our study, Stage 1 was not detected in individuals over the age of 15. Additionally, in the same study, Stages 4 and 5 were not detected in individuals under the age of 14. Similarly, our findings revealed that the prevalence of Stages 4 and 5 was statistically significantly higher in individuals over the age of 15 (p < 0.01). This suggests a clear age-related progression in synchondrosis maturation, with advanced stages predominantly occurring in older age groups.

Research indicates that the fusion of the SOS occurs at different rates between genders, with females typically exhibiting earlier maturation than males. For instance, Shirley and Jantz¹⁹ found that complete fusion at the basilar synchondrosis occurs well before the age of 25, with females beginning this process approximately four years earlier than males, aligning closely with the onset of puberty. This observation is supported by Akhlaghi et al.²⁰, who noted that the stage of fusion serves as a biological age indicator and varies significantly between sexes. Further, in a study conducted in China in 2022 among individuals aged 6to25, it was found that the closure of the SOS in females occurred significantly earlier than in males. In the study, which utilized a four-stage classification system, Stage 4 was more frequently observed in females, while Stage 1 was significantly more common in males²¹. In this study, involving the same age group but utilizing a different classification system, it was revealed that Stage 1 was more prevalent among men, whereas Stage 5 was more prevalent among women. Upon comparing our classification of participants in the study with that of Al-Gumaei et al.²¹, it is evident that Stage 4 and Stage 5 closely resemble Stage 4 in their research. The study results exhibit significant consistency regarding gender and stage. Also, in another study, which used CBCT images of individuals aged 7–25 to estimate age based on SOS closure stages, a 0/1/2/3 staging system was employed. Stage 3, defined as complete closure, was found to be significantly higher in females²². These results show the significance of gender and the underlying mechanisms that may influence treatment planning.

The observed gender differences in the fusion stages of the SOS can be attributed to several biological mechanisms (involve hormonal influences and genetic factors), including hormonal influences, the timing of epiphyseal plate closure, and variations in growth rates. Funato et al.²³ discussed the role of specific transcription factors, such as TBX1, in regulating chondrocyte maturation within the SOS, which may be differentially expressed between genders. Additionally, the influence of growth hormone on craniofacial bone development, as reviewed by Litsas²⁴, suggests that hormonal variations could further contribute to the observed differences in synchondrosis maturation rates. Also, sex-related hormones estrogen and testosterone are critical in regulating bone growth, particularly in craniofacial regions. For example, Padzys et al. demonstrated the role of estrogen in enhancing nasal breathing efficiency in females, contributing to better craniofacial adaptation compared to males²⁵. Similarly, Fujita et al. highlighted the importance of sex hormones in maintaining bone volume, with estrogen and androgen significantly influencing mandibular condyle modeling during early development²⁶. Matthews et al. discussed how prenatal testosterone-to-estrogen ratios influence craniofacial structures, with these effects becoming more pronounced during puberty²⁷. Another study showing hormonal influence on developmental stages, further supported Matthews et al.²⁹, indicating that increased testosterone levels contribute to the lateral growth of male facial features, such as the cheekbones and mandible, thus explaining sexual dimorphism in craniofacial morphology²⁸. Further, when we deep look into the intrauterine hormonal influence, the “Twin Testosterone Transfer” hypothesis presented by Patel et al. highlights how prenatal exposure to sex hormones can masculinize dental traits in female co-twins, providing insights into the early hormonal impacts on craniofacial development²⁹. Beyond structural growth, hormonal effects extend to functional aspects. Cairns explored estrogen’s role in modulating trigeminal nerve excitability, which may explain sex-related differences in craniofacial pain perception³⁰.

The integration of ImageJ histogram analysis into clinical workflows represents a step forward in utilizing digital tools for diagnostics. This technique allows practitioners to go beyond qualitative assessments and incorporate quantitative imaging data into their decision-making processes. While ImageJ was utilized in this study due to its open-source accessibility, user-friendly interface, and extensive plugin support for fractal analysis, it is important to acknowledge alternative software options and their comparative features. For instance, MATLAB offers advanced capabilities for fractal and texture analysis through customized algorithms, providing greater flexibility in data processing and statistical modeling. However, MATLAB requires programming expertise and a paid license, which may limit its accessibility in some settings³¹. Similarly, Fractalyse, a specialized software for fractal dimension calculation, offers simplified workflows for specific fractal methods but lacks the versatility and broad image processing functionalities provided by ImageJ³². Another tool, BoneJ, an ImageJ plugin, offers advanced features specifically tailored for bone morphometric analyses, though it may present a steeper learning curve for beginners³³. In our study, we further enhanced the analysis by applying pseudocolor techniques within ImageJ, which facilitated better visualization of structural differences and improved contrast in trabecular patterns. Compared to these alternatives, ImageJ stands out for its balance between ease of use, adaptability, and cost-effectiveness, although it may have limitations in terms of processing very large datasets and handling highly complex custom analyses³⁴. The pseudo-color imaging approach demonstrated in this study offers a cost-effective and non-invasive method for evaluating craniofacial growth, which could be integrated into routine diagnostics alongside other imaging modalities.

Histogram analysis plays a significant role in dentistry, particularly in the enhancement and interpretation of dental images. One of the primary applications of histogram analysis in dentistry is image enhancement. For instance, Ahmad et al.³⁵ conducted a comparative analysis of several image enhancement techniques, including adaptive histogram equalization (AHE) and contrast limited adaptive histogram equalization (CLAHE), specifically for dental X-ray images. Their findings indicated that these techniques significantly improve the visibility of dental structures, which is crucial for accurate diagnosis and treatment planning. Similarly, Economopoulos et al. ³⁶ proposed a histogram registration method to correct contrast discrepancies in dental images, demonstrating the effectiveness of histogram-based approaches in enhancing image quality for better clinical outcomes. A study conducted in 2021 demonstrated that buccal and palatal dilacerations could be evaluated using histogram analysis with pseudo-color imaging ³⁷. In the field of dentistry, the ImageJ software is primarily used for fractal analysis to assess bone trabeculation. The use of this software, similar to our study, is rarely found in literature. A study conducted in 2017 using this software on immunohistochemistry images of precancerous and cancerous lesions achieved statistically significant successful results, particularly in the diagnosis of oral lichen planus³⁸. The results of our study are similar in terms of the success of SOS staging.

Our study used three-way ROC analysis to assess synchondrosis maturation. Histogram analyses identified data below 68.33 as Stage 1, above 104.5 as Stage 3, and values in between as Stage 2. Stage 1–2 and Stage 2–3 AUC values were 0.655 and 0.652, respectively. Histogram findings with cut-off values over 74.33 were related with 15–25-year-olds, whose ROC analysis generated an AUC value of 0.715. Similarly, pseudo-color imaging histogram analysis indicated statistically significant differences between Stages 1, 2, and 3, suggesting mathematical degrees can be used for staging. A study conducted in 2022 using the pseudo-color imaging technique on hand-wrist radiographs determined that growth-development stages could be similarly assessed³⁹. Another study conducted in 2021 found that in the staging of liver fibrosis using T1 mapping, the AUC, sensitivity, and specificity values were 0.811, 61.0, 100.0 for the first stage; 0.560, 77.4, 46.0 for the second stage; 0.52, 78.1, 37.9 for the third stage; and 0.51, 100.0, 15.2 for the fourth stage⁴⁰.

In the evaluation of SOS closure stages using pseudo-color imaging through ImageJ, images in Stage 2 were found to be significantly more challenging to assess compared to other stages. Although these images presented difficulties for clinical differentiation by observers, histogram analyses performed on these images yielded similar grayscale appearances and numerical values. There are similar studies in which tissue/bone density was evaluated using ImageJ, where higher histogram values were obtained, comparable to the findings of this study^41,42.

In this study, we utilized pseudocolor techniques with ImageJ to enhance the visualization and assessment of spheno-occipital synchondrosis. The application of pseudocolorization significantly improved the contrast in radiographic images, allowing for better differentiation of structural variations that may not be easily detectable in standard grayscale imaging. This technique facilitated the identification of subtle changes in bone density and growth plate morphology, which are critical for evaluating the maturation and fusion status of synchondroses. Beyond its application in dental and maxillofacial imaging, the pseudocolor approach holds significant promise in various fields, including forensic anthropology. By facilitating the evaluation of cranial base synchondroses, this technique can enhance age estimation accuracy, which is crucial for identifying skeletal remains and establishing demographic profiles in forensic contexts⁴³. Furthermore, the pseudocolor method may prove invaluable in orthopedic diagnostics, offering a non-invasive means to assess growth plate integrity and enabling the early detection of developmental anomalies. This capability is particularly important in pediatric populations, where timely intervention can prevent long-term complications⁴⁴. Overall, the enhanced imaging technique contributes to more precise skeletal assessments, potentially improving diagnostic accuracy and reliability in both clinical practice and research settings, thereby advancing our understanding of craniofacial development and pathology⁴⁵.

Despite the numerous contributions this study has made to clinical practice, it is important to acknowledge its limitations. Although all images in this study were obtained using a standardized protocol, which enhances the reliability and consistency of the results, several limitations must be acknowledged. The relatively small sample size may restrict the generalizability of the findings to broader populations, making it necessary to validate the results with larger, more diverse cohorts that include varying demographic and anatomical characteristics. Additionally, the study relied solely on a single-method approach using ImageJ software, limiting the ability to compare its performance against other advanced image processing tools or methodologies. Future research should include comparative analyses with alternative software to validate and optimize the methodology, potentially uncovering more robust or efficient approaches. Moreover, while this study primarily contributes to research-focused applications, it does not address the integration of these methods into routine clinical workflows. Investigating how these findings could be seamlessly implemented in clinical settings—such as orthodontics, maxillofacial surgery, and forensic investigations—may significantly enhance their practical utility and broaden their impact. Such explorations could bridge the gap between research and practice, ensuring these techniques are not only scientifically robust but also clinically actionable.

Conclusion

This study demonstrated that synchondrosis maturation stages can be reliably assessed by histogram analysis using ImageJ software. ImageJ’s pseudo-colour imaging technique allowed the differences between SOS fusion stages to be clearly distinguished and provided a quantitative method for radiographic evaluation. In histogram analysis, threshold values of 68.33 and 104.5 were determined for stage 1 and stage 3, respectively, with AUC values of 0.655 and 0.652, respectively, indicating moderate discrimination between the stages. The study also revealed that stages 4 and 5 were more common in individuals aged 15–25 years and that fusion occurred earlier in females than males. Although histogram analysis with ImageJ is an important tool in this study, further studies with larger sample groups and various imaging protocols are needed to increase the validity of these findings and to ensure generalizability to different populations.

Author contributions

C.E : Investigation, Prepared figures, Writing Original Draft, Review&Editing S.U. : Investigation, Data Curation, Literature Review, Prepared tables G.M. : Conceptualization, Methodology, Supervision, Review&Editing.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

Due to the regulations under the Personal Data Protection Law, the images of individuals are not available in publicly accessible repositories; however, anonymized data can be shared upon request. In cases where necessary, the data can be requested from the corresponding author (C.E.).

Declarations

Competing interests

The authors declare no competing interests.

Informed consent

Additional informed consent was obtained from all individual participants included in the study.