CT-based sex estimation on human femora using statistical shape modeling

Age estimation from iliac auricular surface using Bayesian inference and principal component analysis: a CT-based study in an Indian population

Age estimation constitutes one of the pillars of human identification. The auricular surface of the ilium presents as a durable and robust structure within the human skeletal framework, capable of enabling accurate age estimation in older adults. Amongst different documented auricular age estimation methods, the Buckberry-Chamberlain method offers greater objectivity through its component-based approach. The present study aimed to test the applicability of the Buckberry-Chamberlain method in an Indian population through a CT-based examination of the auricular surface. CT scans of 435 participants undergoing CT examinations following the advice of their treating physicians were scrutinized for different age-related auricular changes. Three of the five morphological features described by Buckberry-Chamberlain could be appreciated on CT scans, and thus further statistical analysis was restricted to these features. Transition analysis coupled with Bayesian inference was undertaken individually for each feature to enable age estimation from individual features, while circumventing age mimicry. A Bayesian analysis of individual features yielded highest accuracy percentages (98.64%) and error rates (12.99 years) with macroporosity. Transverse organization and apical changes yielded accuracy percentages of 91.67% and 94.84%, respectively, with inaccuracy computations of 10.18 years and 11.74 years, respectively. Summary age models, i.e. multivariate age estimation models, derived by taking this differential accuracy and inaccuracy into consideration yielded a reduced inaccuracy value of 8.52 years. While Bayesian analysis undertaken within the present study enables age estimation from individual morphological features, summary age models appropriately weigh all appreciable features to yield more accurate and reliable estimates of age.

A new method for sex estimation based on femoral cross-sectional geometry measurements and its validation using recent and ancient populations

Estimating sex is a fundamental task in biological and forensic anthropology. This study aimed to develop new methods for sex estimation based on femoral cross-sectional geometry (CSG) variables and to test their applicability in recent and ancient assemblages. The sample was divided into a study group (living individuals, N = 124) for creating sex prediction equations and two test groups: living individuals (N = 31) and prehistoric individuals (N = 34). The prehistoric sample was divided into three subgroups according to subsistence strategy (hunter-gatherers, early farmers that also hunted, and farmers and herders). Femoral CSG variables (size, strength, and shape) were measured from CT images using dedicated software. Discriminant functions for sex estimation were calculated for various bone completeness scenarios and validated using the test groups. Size and strength parameters were sexually dimorphic, while shape was not. Discriminant functions for sex estimation produced success rates in the living sample between 83.9 and 93.5%; the distal shaft yielded the highest results. Success rates were lower among the prehistoric test sample, with better results (83.3%) for the mid-Holocene population (farmers and herders) than for earlier groups (e.g., hunter-gatherers; < 60%). These results were compared with those obtained using other methods for sex estimation based on various skeletal elements. This study provides new, reliable, and simple methods with high success rates for sex estimation based on femoral CSG variables obtained automatically from CT images. Discriminant functions were created for various conditions of femoral completeness. However, these functions should be used carefully in past populations from different settings.

Finite element analysis of medial closing and lateral opening wedge osteotomies of the distal femur in relation to hinge fractures

PURPOSE

Intraoperative hinge fractures in distal femur osteotomies represent a risk factor for loss of alignment and non-union. Using finite element analysis, the goal of this study was to investigate the influence of different hinge widths and osteotomy corrections on hinge fractures in medial closed-wedge and lateral open-wedge distal femur osteotomies.

METHODS

The hinge was located at the proximal margin of adductor tubercle for biplanar lateral open-wedge and at the upper border of the lateral femoral condyle for biplanar medial closed-wedge distal femur osteotomies, corresponding to optimal hinge positions described in literature. Different hinge widths (5, 7.5, 10 mm) were created and the osteotomy correction was opened/closed by 5, 7.5 and 10 mm. Tensile and compressive strain of the hinge was determined in a finite element analysis and compared to the ultimate strain of cortical bone to assess the hinge fracture risk.

RESULTS

Doubling the correction from 5 to 10 mm increased mean tensile and compressive strain by 50% for lateral open-wedge and 48% for medial closed-wedge osteotomies. A hinge width of 10 mm versus 5 mm showed increased strain in the hinge region of 61% for lateral open-wedge and 32% for medial closed-wedge osteotomies. Medial closed-wedge recorded a higher fracture risk compared to lateral open-wedge osteotomies due to a larger hinge cross-section area (60-67%) for all tested configurations. In case of a 5 mm hinge, medial closed-wedge recorded 71% higher strain in the hinge region compared to lateral open-wedge osteotomies.

CONCLUSION

Due to morphological features of the medial femoral condyle, finite element analysis suggests that lateral-open wedge osteotomies are the preferable option if larger corrections are intended, as a thicker hinge can remain without an increased hinge fracture risk.

Reconstruction of full femora from partial bone fragments for anthropological analyses using statistical shape modeling

OBJECTIVES

Due to taphonomic processes such as burial, fire, or animal activity, bones are often found incomplete, which can pose problematic for establishing the biological profile of the deceased using anthropological methods. The aim of this study is to test the feasibility of using statistical shape modeling (SSM) to reconstruct full femora from simulated partial femora and determine the accuracy of the reconstruction. Moreover, we assess the accuracy of sex estimation and the degree of stature error added based on the reconstructed femur using different anthropological methods.

METHODS

A total of 42 (28 female, 14 female) 3D models of left femora extracted from computed tomography (CT) scans were used. We performed a leave-one-out cross-validation (LOOCV) where 41 bones were used to build the SSM and one bone was used for testing. This bone was cut in 1 cm steps proximally, distally and from both ends up to 10 cm, reconstructed using SSM, and tested using the methods established by Stewart and Purkait (2005), Trotter and Gleser (1952), as well as a method based on SSM. with landmarks being automatically identified.

RESULTS

The error induced by reconstructing the femur to the length measurements was low, which translated into useful stature estimations (single sided cuts up to 10 cm: 0.4-1.1%, double sided<2% for cuts shorter than 6 cm). Using Purkaits method for sex estimation on reconstructed bones looked promising as well (single sided: 90.5% when compared to applying Purkaits method on the original bone, double sided 78.6% (10 cm cut) to 97.6% (1-3 cm cuts)) Using SSM for sex classification looked promising as well (single sided cut: 81-85.7%, double sided cut: 59.5-85.3%) CONCLUSION: SSM can be used to reconstruct fragmented femora. These reconstructions can be used for sex and stature estimations, at the cost of lower accuracy. Using SSM might give investigators an additional tool to gain information about the biological profile of a deceased in cases where the fragmentation of a femur does not allow for using other anthropological methods.

3D Geometric Shape Reconstruction for Revision TKA and UKA Knees Using Gaussian Process Regression

Revision knee surgery is complicated by distortion of previous components and removal of additional bone, potentially causing misalignment and inappropriate selection of implants. In this study, we reconstructed the native femoral and tibial surface shapes in simulated total/unicompartmental knee arthroplasty (TKA/UKA) for 20 femurs and 20 tibias using a statistical inference method based on Gaussian Process regression. Compared to the true geometry, the average absolute errors (mean absolute distances) in the prediction of resected femur bones in TKA, medial UKA, and lateral UKA were 1.0 ± 0.3 mm, 1.0 ± 0.3 mm, and 0.8 ± 0.2 mm, respectively, while those in the prediction of tibia resections in the corresponding surgeries were 1.0 ± 0.4 mm, 0.8 ± 0.2 mm, and 0.7 ± 0.2 mm, respectively. Furthermore, it was found that the prediction accuracy depends on the size and gender of the resected bone. For example, the prediction accuracy for UKA cuts was significantly better than that for TKA cuts (p < 0.05). The female and male cuts were often overfit and underfit, respectively. The data indicated that this reconstruction approach can be a viable option for planning of revision surgeries, especially when contralateral anatomy is pathological or cannot be available.

Adult sex estimation from the minimum supero-inferior femoral neck diameter in a contemporary osteological sample from Buenos Aires, Argentina

Sex estimation of adult skeletons is an important step in forensic analysis. Although the femur has been metrically studied for sex assessment around the world, very limited information is actually available on modern populations of Argentina. In this paper, the estimation of sex based on the metric evaluation of the supero-inferior femoral neck diameter (SID) in a reference osteological collection from the contemporary Chacarita Cemetery of Buenos Aires City (Argentina), is evaluated. Protocols generated using SID in other three reference skeletal samples are also tested on this collection. One hundred and sixty-four individuals of both sexes and between 24 and 96 years old are analyzed. Inter and intra observer errors suggest that the replicability of the procedure is adequate. The sectioning point calculated from the direct measurements is 30.86 mm and results show a high degree of dimorphism. The proportions of correct sex discrimination and the likelihoods of correct allocation obtained with the direct measurements, along with the results of a discriminant function, a binary logistic regression and a Bayesian approach, are all higher than 0.85 (0.85-0.93 for females, 0.88-0.91 for males). When the formulae from other samples are used in the Chacarita Collection, the percentages of correct estimations range between 72.41% and 81.03% for females and between 80.46% and 88.50% for males, while the likelihoods are between 0.73 and 0.81 for females and between 0.79 and 0.82 for males. As the values for the estimations obtained using the statistical procedures generated in the present research are higher than those available for other collections, the method is more adequate to use in the analysis of contemporary skeletal remains from Buenos Aires and surrounding areas. The trends identified highlight the importance of population-specific metric methodologies in forensic contexts and deserve future testing in contemporary samples from neighbouring regions.

Principal component regression-based contrast-enhanced ultrasound evaluation system for the management of BI-RADS US 4A breast masses: objective assistance for radiologists

A portion of detected breast masses might be overrated by using the Breast Imaging-Reporting and Data System ultrasonography (BI-RADS US) lexicon. A principal component regression-based contrast-enhanced ultrasound (PCR-CEUS) evaluation system was built to quantitatively illustrate whether CEUS could help radiologists to differentiate 4A masses. The PCR-CEUS evaluation system, based on principal component analysis (PCA) and logistic regression, was verified by random assignment into training and test sets and shown to reduce the data dimension and avoid collinearity in CEUS variables. This prospective study consecutively collected 238 patients with 238 4A masses confirmed pathologically. All enrolled patients accepted CEUS examination. The diagnostic performance of senior and junior radiologists, PCR-CEUS and combined methods was compared. The PCR-CEUS system had consistent diagnostic performance in both the training and test sets, with an area under the curve (AUC) of 0.831 (0.765-0.897), 0.798 (0.7034-0.892) and 0.854 (0.765-0.943) (all P > 0.05). The AUC of the combined diagnostic model (PCR-CEUS + Senior radiologists) was higher than that of senior radiologists, and the combined model had higher sensitivity (0.875 (0.781-0.969) vs. 0.729 (0.603-0.855)) without compromising specificity. Furthermore, the AUC and specificity of the combined model (PCR-CEUS + Junior radiologists) (0.852 (0.787-0.916)) was higher than that of junior radiologists (0.665 (0.592-0.737) (P < 0.00001)). PCR-CEUS demonstrated good ability in differentiating malignant BI-RADS-US 4A masses and was helpful for both senior and junior radiologists.

Potential use of deep learning techniques for postmortem imaging

The use of postmortem computed tomography in forensic medicine, in addition to conventional autopsy, is now a standard procedure in several countries. However, the large number of cases, the large amount of data, and the lack of postmortem radiology experts have pushed researchers to develop solutions that are able to automate diagnosis by applying deep learning techniques to postmortem computed tomography images. While deep learning techniques require a good understanding of image analysis and mathematical optimization, the goal of this review was to provide to the community of postmortem radiology experts the key concepts needed to assess the potential of such techniques and how they could impact their work.

Secular evolution of femoral morphology from a clinical perspective

INTRODUCTION

Intramedullary nailing is the surgical method of choice for the treatment of proximal femur or femoral shaft fractures. Implant manufacturers aim to design implants fitting for the broadest possible population segment. As complete morphological data sets of long bones are not widely available, anatomical collections of historical dry bone specimens may represent abundant additional sources of morphological three-dimensional (3D) data for implant design, provided they are consistent with present populations. This study aims to investigate secular trends and age-related changes of femoral morphology of the Caucasian population over the past 800 years.

MATERIALS AND METHODS

Computer graphical measurements of 3D-datasets of right and left femora derived from computed tomography (CT) scans, representative of the present Caucasian population, were compared to computer graphical measurements of 3D-datasets of right and left femora derived from CT scans of specimens from a historical medieval European bone collection.

RESULTS

Clinically relevant parameters of historical medieval European femora were found mostly consistent with correlative data of the present Caucasian population. Additionally, for some of the evaluated parameters, particularly anteversion, morphological differences significantly correlated to individual age and sex could be identified, whereas other parameters such as caput-collum-diaphyseal angle or radius of anterior femoral bowing were not correlated to individual age or sex.

CONCLUSION

The findings suggest that more recent historical specimen collections may be a convenient and easily accessible source of new 3D morphological data, as well as to complement existing data, to be used by researchers and manufacturers for the development of intramedullary femoral nails.