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Diagnostics
Volume 15
Issue 13
10.3390/diagnostics15131649
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Article

Assessing Sternal Dimensions for Sex Classification: Insights from a Greek Computed Tomography-Based Study

by
Konstantina Vatzia
1,
Michail Fanariotis
2,
Maciej Bugajski
3,
Ioannis V. Fezoulidis
4,
Maria Piagkou
5,*,
Marianna Vlychou
4,
George Triantafyllou
5,
Ioannis Vezakis
6,
George Botis
6,
Stavroula Papadodima
7,
George Matsopoulos
6 and
Katerina Vassiou
8
1
Faculty of Medicine, University of Thessaly, Biopolis, 41110 Larissa, Greece
2
Department of Radiology, Sykehuset Telemark HF, 3710 Skien Telemark, Norway
3
Maria Sklodowska-Curie Institute of Oncology, 31-125 Krakow, Poland
4
Department of Radiology, University Hospital of Larissa, Biopolis, 41110 Larissa, Greece
5
Department of Anatomy, School of Medicine, Faculty of Health Sciences, National and Kapodistrian University of Athens, 11527 Goudi, Greece
6
Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
7
Department of Forensic Medicine and Toxicology, School of Medicine, National and Kapodistrian University of Athens, 11527 Goudi, Greece
8
Department of Anatomy, Faculty of Medicine, University of Thessaly, Biopolis, 41110 Larissa, Greece
*
Author to whom correspondence should be addressed.
Diagnostics 2025, 15(13), 1649; https://doi.org/10.3390/diagnostics15131649 (registering DOI)
Submission received: 1 June 2025 / Revised: 25 June 2025 / Accepted: 26 June 2025 / Published: 27 June 2025
(This article belongs to the Special Issue New Perspectives in Forensic Diagnosis)
Versions Notes

Abstract

Background/Objectives: This study aimed to assess the potential of sternal morphometric parameters derived from multidetector computed tomography (MDCT) for sex estimation in a contemporary Greek population. A secondary objective was to develop and evaluate statistical and machine learning models based on these measurements for forensic identification. Methods: Sternal measurements were obtained from chest MDCT scans of 100 Greek adults (50 males, 50 females). Morphometric variables included total sternum length, surface area, angle, and index (SL, SSA, SA, and SI); manubrium length, width, thickness, and index (MBL, MBW, MBT, and MBI); sternal body length, width, thickness, and index (SBL, SBW, SBT, and SBI); and xiphoid process length and thickness (XPL and XPT). Logistic regression and a Random Forest classifier were applied to assess the predictive accuracy of these parameters. Results: Both models showed high classification performance. Logistic regression identified MBL and SBL as the most predictive variables, yielding 91% overall accuracy, with 92% sensitivity and 90% specificity. The Random Forest model achieved comparable results (91% accuracy, 88% sensitivity, 93% specificity), ranking SSA as the most influential feature. Conclusions: MDCT-derived sternal morphometry provides a reliable, non-invasive method for sex estimation. Parameters such as MBL, SBL, and SSA demonstrate strong discriminatory power and support the development of population-specific standards for forensic applications.
Keywords: sternum; sex determination; morphometry; anatomy; forensic anthropology; computed tomography; variation sternum; sex determination; morphometry; anatomy; forensic anthropology; computed tomography; variation

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MDPI and ACS Style

Vatzia, K.; Fanariotis, M.; Bugajski, M.; Fezoulidis, I.V.; Piagkou, M.; Vlychou, M.; Triantafyllou, G.; Vezakis, I.; Botis, G.; Papadodima, S.; et al. Assessing Sternal Dimensions for Sex Classification: Insights from a Greek Computed Tomography-Based Study. Diagnostics 2025, 15, 1649. https://doi.org/10.3390/diagnostics15131649

AMA Style

Vatzia K, Fanariotis M, Bugajski M, Fezoulidis IV, Piagkou M, Vlychou M, Triantafyllou G, Vezakis I, Botis G, Papadodima S, et al. Assessing Sternal Dimensions for Sex Classification: Insights from a Greek Computed Tomography-Based Study. Diagnostics. 2025; 15(13):1649. https://doi.org/10.3390/diagnostics15131649

Chicago/Turabian Style

Vatzia, Konstantina, Michail Fanariotis, Maciej Bugajski, Ioannis V. Fezoulidis, Maria Piagkou, Marianna Vlychou, George Triantafyllou, Ioannis Vezakis, George Botis, Stavroula Papadodima, and et al. 2025. "Assessing Sternal Dimensions for Sex Classification: Insights from a Greek Computed Tomography-Based Study" Diagnostics 15, no. 13: 1649. https://doi.org/10.3390/diagnostics15131649

APA Style

Vatzia, K., Fanariotis, M., Bugajski, M., Fezoulidis, I. V., Piagkou, M., Vlychou, M., Triantafyllou, G., Vezakis, I., Botis, G., Papadodima, S., Matsopoulos, G., & Vassiou, K. (2025). Assessing Sternal Dimensions for Sex Classification: Insights from a Greek Computed Tomography-Based Study. Diagnostics, 15(13), 1649. https://doi.org/10.3390/diagnostics15131649

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