Auricular dimensions in computed-tomography: Unveiling the relationship between ear dimensions, age, and sex using three-dimensional volume rendering reconstructions

Abstract

BACKGROUND

The auricle, or auricula, defines the visible boundaries of the external ear and is essential in forensic investigations, including facial reconstruction and human remains identification. Beyond its forensic significance, auricular morphology attracts interest from various fields, such as medicine and industry. The size of the ears is culturally associated with health and longevity, while surgical techniques for ear reconstruction address both congenital and aesthetic concerns.

AIM

To determine whether known correlations with various measurements and observations regarding sex and age could also be established through computed tomography (CT).

METHODS

Computed tomography scans of the head from 342 females and 329 males aged 18 to 97 years (mean = 60 ± 19 years) were included in this study. Different auricular lengths, widths and perimeters were measured for both sides. Additionally, the preauricular area was assessed using three-dimensional volume rendering technique images.

RESULTS

The measured auricular dimensions in centimeters are presented as mean values (right/left) for males (length 1 6.91 ± 0.51/6.93 ± 0.52; length 2 2.83 ± 0.35/2.84 ± 0.34; width 1 3.94 ± 0.32/4.01 ± 0.36; width 2 3.51 ± 0.34/3.46 ± 0.31; perimeter 17.66 ± 1.25/17.71 ± 1.28) and females (length 1 6.44 ± 0.5/6.48 ± 0.51; length 2 2.7 ± 0.32/2.71 ± 0.33; width 1 3.6 ± 0.32/3.68 ± 0.31; width 2 3.3 ± 0.3/3.26 ± 0.27; perimeter 16.36 ± 1.2/16.46 ± 1.2). A positive correlation with age was shown in all measurements, with the highest value for perimeter in both, males (r-value: right/left: 0.49/0.47) and females (r-value: right/left: 0.53/0.53). After confounding factors were excluded, the preauricular vertical line was first seen at 45 years. The mean age for males with preauricular vertical lines was 66.65 ± 10.92 years (95%CI: 63.99-69.3), while without vertical lines, it was 44.48 ± 16.15 years (95%CI: 41.21-47.74); for females, it was 70.18 ± 12.44 years (95%CI: 68.9-71.46) with and 47.87 ± 17.09 years (95%CI: 45.96-49.78) without vertical lines.

CONCLUSION

In this study, we pioneered the use of CT volumetric data to examine human auricle morphology and we achieved a precise 3D (pre-) auricular assessment. Sex-specific positive correlations between ear dimensions and age, as well as the mean age for the appearance of preauricular lines, were identified, providing valuable insights into the capabilities of modern CT devices.

Key Words: Auricular morphology; Anterior tragal crease; Aging; Computed tomography; Volume rendering technique; Facial recognition

Core Tip: This study utilized computed tomography volumetric datasets to investigate human auricular morphology across a diverse age range (18 to 97 years) in 671 subjects (342 females, 329 males). Our findings reveal significant positive correlations between auricular dimensions and age, with ear perimeter showing the strongest correlation (r-value: 0.47-0.53) in both sexes. Notably, the emergence of preauricular vertical lines was observed at a mean age of 66.65 years for males and 70.18 years for females. Overall, the study results provide insights that could impact clinical practices, enhance research methodologies, advance facial recognition technology, improve forensic identification, and inform surgical approaches.

INTRODUCTION

The auricle or auricula defines the visible anatomic boundaries of the external ear. Auricle morphology plays a crucial role in forensic investigations, such as facial reconstruction, identification of human remains, and, historically, even for paternity confirmation[1]. However, the study of auricles extends beyond the forensic aspect, attracting interest from various fields, including the spiritual, medical, and industrial domains.

In some cultures, the size of the ears is believed to be an indicator of health and longevity[2-4]. However, the external ear mostly stands as a pivotal facial feature, alongside the eyes, nose, and mouth, contributing significantly to our overall appearance[2,5,6]. Surgical methodologies have been meticulously developed for ear reconstruction, addressing congenital or acquired malformations, as well as aesthetic considerations[5,7-12]. Concurrently, industrial interests, including those of hearing aid developers, actively contribute to ongoing research on ear morphology.

The human face uniquely reflects the aging process and is influenced by factors such as a physiological decline in skin elasticity and structural changes in subcutaneous tissue[13,14]. External factors, such as ultraviolet radiation, diseases, and drug abuse, also play a significant role[5,15,16]. The effect of age on ear size has been well-documented in literature, yet interest in understanding the age- and sex-related dimensions of the external ears persists[3,5,6,9,17-23].

This profound understanding of the aging process holds significant potential for aiding identification, even years after an incident occurs[24]. Notably, facial recognition software has evolved to incorporate auricular analysis, augmenting traditional eye, mouth, and nose detection. This enhancement facilitates superior facial recognition, even in scenarios involving obscured facial features or features captured at oblique angles[5,24-29].

Beyond ear size, scientific attention has been directed toward specific skin creases, such as diagonal lobular or anterior tragal creases (ATCs), which have been associated with coronary artery disease and atherosclerotic conditions[21,30-33].

To date, available data mainly rely on forensic measurements or quantitative assessments of living humans. To our knowledge, there is currently no published evidence that has assessed ear dimensions using an approach with computed tomography (CT) volumetric data.

MATERIALS AND METHODS

The questionnaire and methodology for this retrospective study were approved by the local institutional Ethics Committee “Ethikkomission Nordwest-und Zentralschweiz” (February 24, 2023, BASEC-Nr. 2023-00260).

Study population

Data were sourced from the clinic’s internal radiology information system, which was retrospectively searched for all CT scans from the head, including the ears, between January 1, 2022 and January 1, 2023. Each patient was assigned a study-specific identification number for coding purposes.

We initially included all patients from the mentioned one-year cohort, resulting in a total of 5707 participants based on referrals for a CT scan of the head. However, participants were excluded from the study before evaluation if they met any of the following primary criteria: (1) Refused/declined general consent: Participants who refused general consent for their medical data to be used for research purposes were excluded from the study (n = 411); and (2) Age under 18: Minor patients under the age of 18 were excluded from the study (n = 67). During the evaluation, the following secondary exclusion criteria were applied: (1) Incomplete mapping: Participants with partially or incompletely imaged ears were excluded from the study (n = 3093); (2) Foreign bodies: Individuals with foreign bodies in the auricle region from one or both ears which led to artifacts that prevented measurement, were also excluded from the study (n = 43); (3) Exogenous factors: Deformation/bending of the external ears proved to be caused by exogenous factors, such as positioning in the CT or medical installations, led to exclusion (n = 1394); and (4) Unavailable CT-datasets: For different reasons, no CT datasets were available at the time of the study for some participants; therefore, these individuals were excluded from the study (n = 28).

Scan protocol and post-processing

The patients underwent CT examinations of the head for various reasons using dedicated standardized clinical scan protocols. In all acquisitions, automatic tube current modulation and automatic tube voltage selection were activated according to our standardized predefined scan protocol individualization. Scan parameters varied because of the different study modalities and scan indications. Post-processing and all measurements were performed using Syngo.via^® software for multimodality reading (Syngo.via, Siemens Healthcare GmbH 2009-2021, VB60, Erlangen, Germany), with the ruler preferably used for measuring lengths and widths, and the multi-point measurement tool used for measuring circumferences. The latter was primarily defined by predefined landmarks, as well as any necessary intermediate points, to ensure the auricle's dimensions were captured as accurately as possible.

Preliminary assessment of measurement method

Images were reconstructed using multiplanar reconstructions (MPR) and the 3D volumetric rendering technique (VRT). As an axis-corrected measurement was possible in MPR, we assumed more precise values in comparison with VRT estimation. The analysis of 100 VRT and MPR measurements each showed a high agreement of size estimation between both reconstruction methods, with a concordance correlation coefficient according to Lin (p_c) of 0.992 and an accuracy of 0.999. VRT reconstruction had the additional advantage of visualizing both preauricular vertical lines and possible exclusion factors, such as deformities of the auricles. For these reasons and because of easier handling, size estimations were finally measured using VRT reconstructions.

Evaluation of the ears

A trained reader with 2.5 years of cross-sectional imaging experience performed ear measurements under the supervision of a senior consultant radiologist (18 years of experience). According to the literature, specific anatomical landmarks were employed for a standardized auricular assessment in 3D-VRT CT-datasets[19,24,35,36]; the measurement points of superaurale (sa), postaurale (pa), preaurale superior/inferior (pra sup/inf), tragion (t), and subaurale (sba), as well as the areas of the superior/inferior base (base sup/inf) were utilized to measure the lengths and widths of both ears (Figure 1 and Table 1).

Figure 1 Example of predefined landmarks and resulting measurements visualized in a volume rendering image of the right ear. For the sake of clarity, the representation of the perimeter was omitted.

Table 1 Standardization for auricular size assessment using predefined anatomical landmarks.

Measurement	Definition
Length 1	Distance between sa and sba in cm
Length 2	Distance between t and sba in cm
Width 1	Distance between pa and base sup (at the vertical level from pra sup) while distance line needs to be orthogonal to length1 in cm
Width 2	Distance between t and pa in cm
Perimeter	Auricular perimeter measured through distance lines including sa, pa, sba, pra inf, t and pra sup in cm

sa: Superaurale; sba: Subaurale; t: Tragion; pa: Postaurale; sup: Superior; inf: Inferior; pra: Preaurale

Niemitz et al[21] employed a two-step process to ascertain the periodicity of ear growth. According to this approach, we utilized a sex-specific overall mean size, calculated for each age, to determine distinct growth rates with the following formula:

Growth rate (%) = [(mean size) oldest/(mean size) youngest]^{(1⁄(period of time)-1)×100}

The identification of preauricular vertical lines intended to represent the ATC was conducted utilizing 3D VRT images. Distinctions were made between no, one, and at least two vertical lines (Figure 2).

Figure 2 Preauricular assessment (colored area) of the anterior tragal crease utilizing volume rendering technique of the external ear. A: No vertical line in a 22 years old female; B: One vertical crease in a 68 years old male (red arrow); C: Two vertical creases in a 90 years old male (red arrows).

Statistical analysis

Age served as the independent variable, while ear measurements and the assessment of preauricular vertical lines were designated as the dependent variables. Descriptive statistics were used for the analysis of ear dimensions and the presence of preauricular vertical lines. t-test for independent samples, calculation of Lins concordance correlation coefficient, Cohen’s kappa, and intraclass correlation coefficient (ICC, class 3); and linear regression analysis were performed in JASP Team (2023; Version 0.17.3) and Microsoft Excel^® (Microsoft Office Professional Plus 2019).

RESULTS

Patient population

After the application of these exclusion criteria, a final cohort of 671 participants, comprising 329 males and 342 females with an age range of 18-97 years (mean = 60 ± 19 years) was included in the analysis. The mean age for males was 58.45 ± 19 years, while that for females was 61.69 ± 18.9 years.

Measurement of the ears

Reliability tests (n = 50) demonstrated excellent intrareader reliability, with ICC (two-way random mixed effects; consistency; single measures) values of 0.99 (95%CI: 0.986-0.995) for length1, 0.91 (95%CI: 0.848-0.949) for width1, and 0.98 (95%CI: 0.965-0.989) for the perimeter as well as with substantial agreement for preauricular vertical lines (k = 0.64).

A significant (P < 0.001) sex-specific positive correlation with age was shown for all ear measurements (r-values: 0.29-0.53), with the highest value for perimeter in both males (r-values: right/left ear: 0.49/0.47) and females (r-values: right/left ear: 0.53/0.53), as seen in Figure 3. The t-tests for independent samples showed significant differences (P = 0.006) between the left and right ears for width2 but not for the other measurements (P = 0.27-0.96). Significant differences between males and females with P values < 0.001 for length 1, length 2, width 1 and the perimeters for both ears were observed (Figure 4 and Figure 5).

Figure 3  Correlation between auricular perimeter and patient age for both males (n = 329) and females (n = 342).

Figure 4 Raincloud plot depicting the significant (P < 0.001) differences of length 1, length 2, perimeter and width 1 between males (m) and females (w) for the left ear. A: Length 1 left; B: Length 2 left; C: Perimeter left; D: Width 1 left.

Figure 5 Raincloud plot depicting the significant (P < 0.001) differences of length 1, length 2, perimeter, and width 1 between males (m) and females (w) for the right ear. A: Length 1 right; B: Length 2 right; C: Perimeter right; D: Width 1 right.

The quantitative results of auricle measurements for both males and females can be found in Table 2 and Table 3, respectively. The average growth rates were determined with an age specific mean size for lenght 1, length 2, width 1, and the perimeter (Table 4).

Table 2 Quantitative results for size measurements in cm for males (n = 329) in total and for each age group, mean ± SD/ 95%CI.

Side	Measurement (cm)	Total	18-30 year (n = 35)	31-50 year (n = 63)	51-70 year (n = 140)	71-90 year (n = 83)	> 91 year (n = 8)
Right ear	Length 1	6.91 ± 0.51	6.44 ± 0.34	6.66 ± 0.48	6.97 ± 0.46	7.17 ± 0.43	7.29 ± 0.5
		6.47-7.36	6.17-6.71	6.28-7.04	6.61-7.34	6.82-7.51	6.93-7.66
	Length 2	2.83 ± 0.35	2.51 ± 0.23	2.73 ± 0.34	2.84 ± 0.32	3 ± 0.31	3.09 ± 0.29
		2.44-3.22	2.19-2.83	2.26-3.21	2.4-3.29	2.57-3.42	2.76-3.42
	Width 1	3.94 ± 0.32	3.36 ± 0.2	3.86 ± 0.29	3.98 ± 0.3	4.06 ± 0.31	4.19 ± 0.39
		3.58-4.31	3.40-3.86	3.54-4.18	3.37-4.32	3.76-4.36	3.81-4.57
	Width 2	3.51 ± 0.34	3.34 ± 0.27	3.4 ± 0.26	3.51 ± 0.32	3.66 ± 0.35	3.76 ± 0.44
		3.14-3.89	3.03-3.65	3.11-3.69	3.15-3.87	3.26-4.05	3.26-4.25
	Perimeter	17.66 ± 1.25	16.36 ± 0.78	17.11 ± 1.13	17.81 ± 1.1	18.26 ± 1.11	18.7 ± 1.48
		17.05-18.27	15.98-16.74	16.54-17.68	17.27-18.35	17.71-18.8	18.02-19.39
Left ear	Length 1	6.93 ± 0.52	6.46 ± 0.37	6.7 ± 0.5	6.98 ± 0.48	7.19 ± 0.46	7.29 ± 0.56
		6.47-7.39	6.17-6.76	6.3-7.1	6.59-7.36	6.82-7.55	6.87-7.71
	Length 2	2.84 ± 0.34	2.54 ± 0.23	2.76 ± 0.35	2.85 ± 0.31	2.97 ± 0.32	3.1 ± 0.32
		2.45-3.22	2.22-2.86	2.27-3.24	2.43-3.28	2.54-3.41	2.73-3.46
	Width 1	4.01 ± 0.36	3.69 ± 0.25	3.91 ± 0.32	4.05 ± 0.33	4.13 ± 0.35	4.4 ± 0.38
		3.61-4.42	3.41-3.97	3.55-4.27	3.68-4.42	3.78-4.48	4.03-4.78
	Width 2	3.46 ± 0.31	3.32 ± 0.24	3.36 ± 0.24	3.47 ± 0.32	3.57 ± 0.33	3.72 ± 0.32
		3.11-3.82	3.05-3.6	3.09-3.64	3.11-3.835	3.2-3.94	3.35-4.08
	Perimeter	17.71 ± 1.28	16.47 ± 0.82	17.21 ± 1.16	17.84 ± 1.21	18.29 ± 1.12	18.76 ± 1.38
		17.1-18.32	16.07-16.87	16.62-17.79	17.25-18.44	17.74-18.84	18.12-19.39

Table 3 Quantitative results for size measurements in cm for females (n = 342) in total and for each age group, mean ± SD/ 95%CI.

Side	Measurement (cm)	Total	18-30 year (n = 18)	31-50 year (n = 85)	51-70 year (n = 101)	71-90 year (n = 122)	> 91 year (n = 16)
Right ear	Length 1	6.44 ± 0.5	6.03 ± 0.34	6.15 ± 0.43	6.43 ± 0.43	6.66 ± 0.44	6.93 ± 0.51
		6.05-6.84	5.74-6.33	5.77-6.52	6.09-6.78	6.3-7.01	6.56-7.31
	Length 2	2.7 ± 0.32	2.43 ± 0.2	2.53 ± 0.26	2.67 ± 0.27	2.84 ± 0.32	3.05 ± 0.26
		2.26-3.15	2.15-2.71	2.18-2.89	2.3-3.04	2.48-3.2	2.76-3.35
	Width 1	3.6 ± 0.32	3.44 ± 0.18	3.39 ± 0.26	3.63 ± 0.34	3.72 ± 0.27	3.79 ± 0.29
		3.24-3.96	3.23-3.64	3.09-3.68	3.25-4.01	3.42-4.02	3.5-4.07
	Width 2	3.3 ± 0.3	3.12 ± 0.2	3.14 ± 0.26	3.28 ± 0.25	3.44 ± 0.29	3.47 ± 0.43
		2.96-3.65	2.85-3.4	2.85-3.43	2.94-3.63	3.1-3.77	2.98-3.96
	Perimeter	16.36 ± 1.2	15.39 ± 0.79	15.59 ± 0.96	16.37 ± 1.1	16.88 ± 1.05	17.57 ± 1.21
		15.73-16.99	14.98-15.8	15.08-16.09	15.79-16.94	16.37-17.4	17-18.15
Left ear	Length 1	6.48 ± 0.51	6.08 ± 0.37	6.17 ± 0.41	6.44 ± 0.41	6.71 ± 0.49	7.04 ± 0.39
		6.07-6.88	5.75-6.4	5.85-6.5	6.11-6.76	6.34-7.07	6.74-7.33
	Length 2	2.71 ± 0.33	2.4 ± 0.23	2.55 ± 0.26	2.67 ± 0.29	2.85 ± 0.32	3.06 ± 0.27
		2.25-3.17	2.08-2.72	2.26-2.85	2.27-3.08	2.48-3.21	2.75-3.36
	Width 1	3.68 ± 0.31	3.55 ± 0.24	3.48 ± 0.26	3.7 ± 0.3	3.79 ± 0.29	3.91 ± 0.21
		3.33-4.03	3.28-3.83	3.19-3.77	3.28-4.11	3.46-4.11	3.71-4.11
	Width 2	3.26 ± 0.27	3.17 ± 0.23	3.12 ± 0.22	3.25 ± 0.24	3.34 ± 0.27	3.48 ± 0.26
		2.96-3.56	2.86-3.49	2.87-3.37	2.92-3.59	3.03-3.64	3.18-3.77
	Perimeter	16.46 ± 1.2	15.62 ± 0.92	15.66 ± 0.96	16.44 ± 1.01	16.98 ± 1.12	17.74 ± 0.92
		15.83-17.08	15.14-16.1	15.19-16.13	15.9-17	16.45-17.51	17.3-18.17

Table 4 Descriptive results for average sex-specific growth rates for both ears, (%/year).

	Sex	Length 1	Length 2	Width 1	Perimeter
Right ear	Male	0.14	0.25	0.13	0.14
	Female	0.19	0.27	0.16	0.19
Left ear	Male	0.14	0.25	0.20	0.15
	Female	0.19	0.29	0.14	0.17

Evaluation of preauricular vertical lines

Preauricular vertical lines were counted only if they were clearly visible in the VRT images on both sides[31]. Additionally, the VRT was utilized to identify external conditions that could potentially lead to false positive results, such as skin wrinkling caused by certain factors (e.g. wearing any type of medical mouth-to-nose covering, n = 226; oxygen nasal prongs, n = 19; oxygen mask, n = 1; combinations thereof, n = 5). The substantial impact of these confounding factors is illustrated in Figure 6, in which the minimum age for detecting preauricular vertical lines increased from 22 years (Figure 6A) to 45 years (Figure 6B) after excluding datasets with these factors. After the exclusion of the detected confounding factors, preauricular lines were detected at a mean age of 66.65 ± 10.92 years (95%CI: 63.13-70.17; n = 37) for males (Figure 7A) and 70.18 ± 12.44 years (95%CI: 65.57-74.79; n = 28) for females (Figure 7B).

Figure 6 Evaluation of preauricular vertical lines. A: Without excluding ears with confounding factors (n = 671); B: With confounding factors excluded (n = 159).

Figure 7 Sex-specific evaluation of the preauricular vertical lines with confounding factors excluded. A: Men (n = 77); B: Women (n = 82).

DISCUSSION

Initiating an exploratory investigation, we examined human auricular morphology using CT volumetric rendering datasets. Unlike previous approaches relying on direct ear measurements or indirect methods, such as photographs and laser scans, our innovative use of MPR and 3D VRT allowed for the meticulous assessment of 3D soft-tissue ear dimensions with excellent intra-reader agreement[34].

Our study had several limitations. First, we did not consider ethnic background as a potential factor influencing auricle dimensions[2,11,20,24]. Second, we excluded children who were known to initially demonstrate high auricular growth rates[21]. These factors need to be considered in future research, thus enhancing the accuracy and applicability of our findings.

The fact that facial morphology changes with increasing age is not only due to growth processes in younger years but also to the ongoing changes in skin, soft tissue, bones, and cartilage. For example, facial morphology can be visibly altered by the redistribution of subcutaneous fat tissue or by changing ratios between elastic and collagenous fibers[5,15].

Our work demonstrated the feasibility of CT estimation of ear measurements and revealed interesting trends in ear dimensions concerning age and sex, confirming a statistically significant correlation between ear measurements and age for both males and females, as described in previous research[12,20,22,35]. Similar to Tan et al[3], we were also able to demonstrate that the ears continued to increase in size with advancing age, while the perimeter exhibited the strongest correlation (r-values: 0.47-0.53, Figure 3), irrespective of sex. Conversely, width 2 demonstrated weaker correlations (r-values: 0.29-0.44) and a significant difference between the left and right ear. These observed differences in dimensions may be a result of the substantial variability associated with the anatomical landmarks utilized for width 2. Regarding the other measurements, no significant differences between the right and left ears were found, which was the same finding by Japatti et al[6] and Alexander et al[20].

Prior studies that focused on young to middle-aged populations and determined mean ear lengths, which were comparable to our measurement of length 1, ranged from approximately 62 to 65 mm for males and 57 to 64 mm for females[2,6,12,20,21,24,35]. While our comprehensive measurements spanned a wider age range of 18 to 97 years, we recorded high mean length 1 sizes of 69 mm for males and 64 mm for females, again highlighting the correlation between age and ear length (Table 2 and Table 3).

Significant biometric differences between males and females have been observed in some studies[11,21,22]. However, these disparities have not been confirmed in others[6,9,12]. Significant differences between male and female ear sizes emerged in our study, in contrast to the findings of some previous research. In our opinion, a sex-specific size difference in ears between males and females is plausible, which is why we attribute the discrepant results of the aforementioned study to other influencing factors, such as ethnicity and study population size.

Although not the main objective of this study, we observed more ear piercings, indicating the wearing of earrings visible in VRT, in females (n = 57) than in males (n = 9). Overall, this observation may have resulted in a convergence of ear length with age in some cases and could also be reflected in our measured growth rates. Here, we determined a slightly elevated annual growth rate for females than for males, but our study was not designed to statistically evaluate the effects of earrings on growth rates.

Determining and analyzing the growth rates of various ear dimensions also revealed other interesting patterns. Particularly noteworthy was length 2’s pronounced growth rate for both males (max. 0.25%/year) and females (max. 0.29%/year), implying that certain ear regions, such as the earlobe, undergo more significant changes than other areas during the aging process (Table 4). By contrast, the comparatively modest growth rate of width1 (male 0.13%/year; female 0.16%/year) suggested an imbalance in the size growth between length and width, as previously shown by Sforza et al[24].

Niemitz et al[21] expected a preauricular vertical line to be an indicator of advanced age. Other authors have suggested an association with arteriosclerotic diseases[30-33]. We utilized VRT to explore the preauricular area and identify anterior tragus creases (Figure 2) and potential confounding elements, such as skin wrinkling caused by wearing a mask. After these confounding factors are accounted for, the minimum age for detecting preauricular vertical lines significantly increased from 22 to 45 years (Figure 6). As depicted in Figure 7, on average, females appear to have preauricular vertical lines at a mean age 70 years (95%CI: 65.57–74.79), while in males, this feature is seen at approximately 67 years (95%CI: 63.13–70.17). Since our study design doesn’t account for clinical history, we focused on assessing the possible correlation between patient age and preauricular skin wrinkles using 3D volume rendering of CT datasets. However, a correlation with the age is not an indication of a connection with cardiovascular diseases, even though these also tend to appear later in life. If CT datasets are to be used to demonstrate a possible correlation between preauricular lines and cardiovascular diseases, follow-up studies will be required that specifically take the medical history of the participants into account[36].

Facial recognition based on frontal facial characteristics is considered reliable[26,27,37]. However, in cases involving profile images or when individuals are wearing masks, a situation that has become more common due to the coronavirus disease 2019 pandemic, alternative approaches, such as using unique ear dimensions for identification have been proposed[25,38,39]. In recent years, artificial intelligence and deep learning have significantly advanced facial recognition technology, shifting from traditional 2D methods to more sophisticated 3D techniques. These modern approaches, along with the use of 3D datasets generated from imaging devices like CT or MRI, hold great potential for improving accuracy. The continuous advancement of these imaging methods allows for increasingly precise measurements and reconstructions, which will likely enhance interest from both technical and computational sciences[40]. Already, our assessment of the presence of anterior tragus creases highlights the mechanical impact of wearing masks, particularly in the preauricular area. The facial and auricular morphology is highly complex, and from the authors’ perspective, many additional influencing factors, such as changes in facial musculature, could also be considered. These and other impact factors should be considered in future plans for identifying individuals based on auricular morphology, especially when databases rely on profile pictures without wearing masks[24].

CONCLUSION

In this study, we pioneered the use of CT volumetric data to quantitatively evaluate human auricle morphology, departing from conventional methods. Our analysis spanned a remarkably wide age range, from 18 to 97 years, and revealed intriguing trends in ear dimensions. We observed sex-specific positive correlations between ear measurements and age, with significant differences between males and females. Through the assessment of preauricular vertical lines, we were able to identify the sex-specific minimum and mean ages at which these lines typically developed. Overall, our study demonstrated that precise visualization and measurement of the body surface are achievable through CT volumetric datasets. Thus, it can provide valuable insights into the characterization of human faces and help identify individuals or corpses, assist in presurgical planning for facelifts, and may also be suitable for diagnosing certain diseases.