Evidence map›Paper›PMID 42350814›Full record

ArticleInternational journal of legal medicine2026

Computed tomography as a solution to skeletal collection limitations: exploring cranial variation in the South African population.

Gabriele Christa Krüger, Richard L Jantz, Ericka N L'Abbé

Abstract read
In one paragraph

Article in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Gabriele Christa KrügerDepartment of Anatomy, Faculty of Health Sciences, University of Pretoria, Private Bag X323, Arcadia, 0007, South Africa. gabi.kruger@up.ac.za.ORCID http://orcid.org/0000-0002-3289-1122
Richard L JantzDepartment of Anthropology, University of Tennessee, Knoxville, TN, USA.ORCID http://orcid.org/0000-0003-1382-196X
Ericka N L'AbbéDepartment of Anatomy, Faculty of Health Sciences, University of Pretoria, Private Bag X323, Arcadia, 0007, South Africa.ORCID http://orcid.org/0000-0002-6722-8814

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal collections have provided the foundation for forensic anthropology in South Africa, offering invaluable reference material for developing and testing identification methods. However, these collections remain limited in both size and representativeness. Many are historically biased, restricted by donation practices, and unable to reflect the demographic and biological diversity of the country's modern population. Indian South Africans, in particular, are notably absent due to cultural and religious beliefs that discourage body donation. This study explores the use of computed tomography (CT) as an alternative to overcome these limitations. A total of 408 high-resolution head CT scans representing Black, Coloured, Indian, and White South Africans were analysed using inter-landmark distances and geometric morphometrics. Measurement repeatability was high, with both intra- and inter-observer errors falling well within accepted forensic thresholds (< 2 mm; <3.5%). Significant population-level differences in cranial form were identified (p < 0.01). Black South Africans were consistently the most clearly differentiated group, while Coloured and Indian South Africans showed the greatest overlap, reflecting shared population affinity and historical admixture. Cross-validated classification accuracies ranged between 62% and 64%, indicating that both linear and shape-based analyses can capture relevant cranial variation. These results confirm that CT-derived data are reliable for examining cranial variation within contemporary South African samples and provide access to larger and more diverse datasets than traditional skeletal collections. This study establishes the first cranial reference data incorporating Indian South Africans and demonstrates how CT scanning can support the development of inclusive, population-specific standards for forensic anthropology in South Africa.

Indexed as

SkullTomography, X-Ray ComputedAdultAnatomic LandmarksBlack PeopleCephalometryFemaleForensic AnthropologyHumansMaleMiddle AgedReproducibility of ResultsSouth AfricaSouthern African PeopleYoung AdultComputed tomographyCranial variationGeometric morphometricsIndian South AfricansInter-landmark distancesPopulation affinity

Identifiers

PMID42350814
PMCPMC13658363

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.