Designing a cranial implant to restore the protective and aesthetic function of the patient's skull is a challenging process that requires a substantial amount of manual work, even for an experienced clinician. While computer-assisted approaches with various levels of required user interaction exist to aid this process, they are usually only validated on either a single type of simple synthetic defect or a very limited sample of real defects. The work presented in this paper aims to address two challenges: (i) design a fully automatic 3D shape reconstruction method that can address diverse shapes of real skull defects in various stages of healing and (ii) to provide an open dataset for optimization and validation of anatomical reconstruction methods on a set of synthetically broken skull shapes. We propose an application of the multi-scale cascade architecture of convolutional neural networks to the reconstruction task. Such an architecture is able to tackle the issue of trade-off between the output resolution and the receptive field of the model imposed by GPU memory limitations. Furthermore, we experiment with both generative and discriminative models and study their behavior during the task of anatomical reconstruction. The proposed method achieves an average surface error of 0.59mm for our synthetic test dataset with as low as 0.48mm for unilateral defects of parietal and temporal bone, matching state-of-the-art performance while being completely automatic. We also show that the model trained on our synthetic dataset is able to reconstruct real patient defects.
A simple hemispherical phantom has been designed and prepared for the EURADOS intercomparison exercise on (241)Am activity determination in the skull (2011-13). The phantom consists of three parts that substitute bone and soft tissues. (241)Am is deposited on the surfaces of the bone-substituting part. The design and assumed composition of phantom parts are discussed. A preparation of the voxel representation of the phantom is described. The spectrum of a real measurement of the physical phantom agrees well with the simulation. The physical phantom, and its voxel representation, is provided to the participants of the intercomparison exercise.
- MeSH
- Americium analysis MeSH
- Equipment Design MeSH
- Phantoms, Imaging MeSH
- Photons MeSH
- Calibration MeSH
- Bone and Bones MeSH
- Skull radiation effects MeSH
- Monte Carlo Method MeSH
- Radiation Monitoring methods MeSH
- Tomography, X-Ray Computed MeSH
- Polyurethanes chemistry MeSH
- Radiometry methods standards MeSH
- Reproducibility of Results MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic MeSH
BACKGROUND: Endoscopic endonasal transsphenoidal approaches are broadly used nowadays for a vast spectrum of pathologies sited in the anterior and middle cranial fossa. The usage of neuronavigation systems (neuronavigation) in these surgeries is crucial for improving orientations deeply inside the skull and increasing patient safety. METHODS: The aim of this study was to assess the use of optical neuronavigation, together with an intraoperative O-arm O2 imaging system, in a group of patients with hypophyseal adenoma that underwent a transnasal transsphenoidal surgery, and correlate the accuracy and its deviation during the navigational process against the use of conventional neuronavigation that uses preoperative MRI and CT scans. The overall group consisted of six patients, between 39 and 78 years old, with a diagnosis of hypophyseal adenoma. Patients were treated with an endoscopic transsphenoidal technique and all of them underwent preoperative MRI and CT scans of the brain. These images were used in the neuronavigation system StealthStation S7® during the surgery, where we defined two bony anatomical landmarks, such as a vomer or the origin of an intrasphenoidal septum, in each operated patient. The tip of the navigational instrument, under endoscopic control, pointed to these landmarks and the distance between the tip and the bony structure was measured on the neuronavigation system. Afterwards, intraoperative 3D x-ray imaging was performed via the mobile system O-arm O2® system with automatic transfer into the navigational system. Under endoscopic guidance, we localized the identical bony anatomical landmarks used in the previous measurement and re-measured the distance between the tip and bony landmark in images acquired by the O-arm. The results of both measurements were statistically compared. RESULTS: The mean error of accuracy during conventional neuronavigation with usage of preoperative CT and MRI scans was 2.65 mm. During the neuronavigation, with utilization of intraoperative 3D O-arm images, the mean error of accuracy 0 mm. These mean errors of accuracy (both measurement methods were compared by nonparametric Wilcoxon test) had a statistically significant difference (p = 0.043). CONCLUSIONS: Based on this preliminary clinical study, we conclude that the O-arm is capable of providing intraoperative x-ray 3D images in sufficient spatial resolution in a clinically feasible acquisition. The mean error of accuracy during intraoperative navigation, based on 3D O-arm scans at the skull base, is significantly lower compared to the usage of navigation using conventional presurgical CT and MRI images. This suggests the suitability of this method for utilization during endoscopic endonasal skull base approaches.
- MeSH
- Adenoma * diagnostic imaging surgery MeSH
- Skull Base * diagnostic imaging surgery MeSH
- Surgery, Computer-Assisted * methods MeSH
- Adult MeSH
- Pituitary Gland * diagnostic imaging surgery MeSH
- Middle Aged MeSH
- Humans MeSH
- Magnetic Resonance Imaging MeSH
- Pituitary Neoplasms * diagnostic imaging surgery MeSH
- Neuronavigation methods MeSH
- Intraoperative Period MeSH
- Pilot Projects MeSH
- Tomography, X-Ray Computed MeSH
- Prospective Studies MeSH
- Aged MeSH
- Transanal Endoscopic Surgery * methods MeSH
- Imaging, Three-Dimensional MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Sex estimation is one of the crucial trends in cases of findings of unknown skeletal remains in forensics and bioarchaeology. The changing nature of sexual dimorphism (population specificity, secular trend, other external and internal factors influence) brings challenges to developing new methods; and there are new aims to be independent of these changes such, as the method by Musilová et al. (2016). These methods need to be evaluated on different datasets to determine if they are truly reliable among populations from different places and times, in the case of bioarchaeology. This study assessed the application of the aforementioned method on non-European contemporary and ancient populations to identify the reliability of the method on this separate dataset. The study sample consisted of 96 CT scans of skulls from contemporary Egyptians and 54 3D models of skulls from the Egyptian Old Kingdom Period (2700-2180 BC). The classifier method, previously tested on both Czech and French populations, yielded high accuracies (over 90 %) for sex estimation. For the contemporary Egyptian skull sample, the classifier was able to determine males versus females with an 89.59 % accuracy rate and an AUC value (area under the curve - a measure of the combined specificity and sensitivity of the test) of 0.99; this proves that the classifier is reliable even with a lower degree of accuracy. Conversely, the Old Kingdom Period sample yielded a lower level of accuracy at around 70 % (61.11 %, precisely), although with an AUC value of 0.92, the result is not considered reliable.
The virtual approach in physical and forensic anthropology is increasingly used to further analyze human remains, but also to propose new didactic means for visualization and dissemination of scientific results. Computerized facial approximation (FA) offers an alternative to manual methods, but usually requires a complete facial skeleton to allow for the estimation of the facial appearance of an individual. This paper presents the case of Tycho Brahe, Danish astronomer born during the XVIth century, whose remains were reanalyzed at the occasion of a short exhumation in 2010. Cranial remains of Brahe were poorly preserved, with only a partial facial skeleton, and virtual anthropology tools were used to estimate the missing parts of his skull. This 3D restoration was followed by a FA using TIVMI-AFA3D, subsequently textured with graphic tools. The result provided an interesting estimate that was compared with portraits of the astronomer. The impact of the missing data estimation was investigated by performing FAs on 10 complete test subjects and the same 10 subjects after cropping and estimating 50% of the landmarks (reproducing the preservation state of Tycho Brahe's cranial remains). The comparison between the FA based on the complete and incomplete skulls of the same subject produced a visual assessment of the estimation impact on FAs which is relatively low. This procedure is an alternative to manual methods and offers a reproducible estimate of a face based on incomplete cranial remains. Although the case report concerns a historical individual, the robust automatic estimation of missing landmarks followed by a FA has value for forensic caseworks as a support to the identification process.
- MeSH
- Anatomic Landmarks MeSH
- History, 16th Century MeSH
- History, 17th Century MeSH
- Skull anatomy & histology MeSH
- Humans MeSH
- Face anatomy & histology MeSH
- Image Processing, Computer-Assisted * MeSH
- Software * MeSH
- Forensic Anthropology methods MeSH
- Famous Persons MeSH
- Imaging, Three-Dimensional MeSH
- Check Tag
- History, 16th Century MeSH
- History, 17th Century MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Historical Article MeSH
The disconnect between preclinical and clinical results underscores the imperative for establishing good animal models, then gleaning all available data on efficacy, safety, and potential toxicities associated with a device or drug. Mini pigs are a commonly used animal model for testing orthopedic and dental devices because their skeletons are large enough to accommodate human-sized implants. The challenge comes with the analyses of their hard tissues: current methods are time-consuming, destructive, and largely limited to histological observations made from the analysis of very few tissue sections. We developed and employed cryo-based methods that preserved the microarchitecture and the cellular/molecular integrity of mini pig hard tissues, then demonstrated that the results of these histological, histochemical, immunohistochemical, and dynamic histomorphometric analyses e.g., mineral apposition rates were comparable with similar data from preclinical rodent models. Thus, the ability to assess static and dynamic bone states increases the translational value of mini pig and other large animal model studies. In sum, this method represents logical means to minimize the number of animals in a study while simultaneously maximizing the amount of information collected from each specimen.
- MeSH
- Calcification, Physiologic MeSH
- Cryopreservation methods MeSH
- Cryoultramicrotomy methods MeSH
- Skull cytology MeSH
- Swine, Miniature MeSH
- Specimen Handling methods MeSH
- Polyethylene Glycols MeSH
- Swine MeSH
- Bone Remodeling MeSH
- Sucrose MeSH
- Carboxymethylcellulose Sodium MeSH
- Animals MeSH
- Check Tag
- Male MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
The skull, along with the pelvic bone, serves an important source of clues as to the sex of human skeletal remains. The frontal bone is one of the most significant sexually dimorphic structures employed in anthropological research, especially when studied by methods of virtual anthropology. For this reason, many new methods have been developed, but their utility for other populations remains to be verified. In the present study, we tested one such approach-the landmark-free method of Bulut et al. (2016) for quantifying sexually dimorphic differences in the shape of the frontal bone, developed using a sample of the Turkish population. Our study builds upon this methodology and tests its utility for the Czech population. We evaluated the shape of the male and female frontal bone using 3D morphometrics, comparing virtual models of frontal bones and corresponding software-generated spheres. To do so, we calculated the relative size of the frontal bone area deviating from the fitted sphere by less than 1 mm and used these data to estimate the sex of individuals. Using our sample of the Czech population, the method estimated the sex correctly in 72.8% of individuals. This success rate is about 5% lower than that achieved with the Turkish sample. This method is therefore not very suitable for estimating the sex of Czech individuals, especially considering the significantly greater success rates of other approaches.
- MeSH
- Frontal Bone anatomy & histology diagnostic imaging MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Tomography, X-Ray Computed MeSH
- Computer Simulation * MeSH
- Image Processing, Computer-Assisted MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Forensic Anthropology MeSH
- Support Vector Machine MeSH
- Sex Determination by Skeleton methods MeSH
- Imaging, Three-Dimensional * MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Czech Republic MeSH
Cíl: Sledovat, zda se sklon linie SN mění v průběhu růstu , pomocí superimpozice stabilních struktur báze lební na dvou profilových snímcích. Zjistit rozsah změn v závisloti na délce časového intervalu. Materiál a metodika: Dvě skupiny rostoucích pacientů. Skupina A tvoří profilové snímky zhotovené v časovém intervalu do dvou let (střední hodnota 1, 5 let, směrodatná odchylka = o, 43) a skupinu B tvoří snímky zhotovené v intervalu od dvou do čtyř let (střední hodnota 2, 8 roků, směrodatná odchylka = 0,73). Linie SN byla vyznačena na profilových snímcích. Dva snímky stejného pacienta byly překryty tak, aby souhlasily stabilní struktury kramální báze a byla měřena deviace SN linie. Měření, včetně označení linie SN, bylo opakováno po dvou týdnech, aniž byl znám výsledek prvního měření, aby se vyloučila chyba měření .Výsledek Studentova t- testu byl negativní. Chyba měření byla 10, 3°. Výsledky: Ve skupině A byla střední hodnota O, 44° (SD = O, 57°). Ve skupině B byla linie SN na druhých snímcích v posteriorotaci v průměru o 1, 58° (SD = O, 94°). Rozdíl mezi oběma skupinami byl vysoce signifikantní. Dvojice profilových snímků, zhotovených v průběhu dvou let, mohou být překrývány na linii SN. Růstové změny této linie v tomto časovém horizontu se blíží chybě měření. Snímky zhotovené v intervalu delším než dva roky musí být překrývány na stabilních strukturách kraniální báze.
Aim: To study whether the inclination of the SN line changes during the growth, with the superimposition of two-different cephalometric headfilms on the stable structures of the cranial base, and to investigate the extent of changes according the period of observation. Subject and method: Two groups of orthodontic patients in the process of growth. The A group cephalographs were made in the time interval up to two years (1, 5 year in mean; SD = 0, 43), at the B group in the time interval from 2 to 4 years (2, 8 years in mean; SD = 0, 73). The SN line was marked on the cephalographs. Two headfilms of the same patient were superimposed on stable structures of the cranial base, and the SN lines deviation was measured. The measurement, including the marking of SN line, was repeated after two weeks without the knowledge of the first measurement, in order to check the measurement error. The result of the statistical assessment by the Student s t-test was negative. The measurement error was 0,3°. Result: At Group A, the mean SN line inclination was 0, 44°(SD = 0, 57°). At B group, the SN line on the second cephalometric headfilms was posteriorated by 1. 58° in mean (SD = 0. 94°). The difference between both groups was highly significant. Conclusion: The pair of the cephalometric headfilms of the individual growing patient, carried out during two years, can be superimposed on the SN line. The growth changes of this line in this time horizon are close to the measurement error. The cephalometric headfilms of a growing patient made with a time period longer than two years must be superimposed on stable structures of the cranial base.
- MeSH
- Skull Base anatomy & histology growth & development MeSH
- Time Factors MeSH
- Publication type
- Congress MeSH
Correct virtual reconstruction of a defective skull is a prerequisite for successful cranioplasty and its automatization has the potential for accelerating and standardizing the clinical workflow. This work provides a deep learning-based method for the reconstruction of a skull shape and cranial implant design on clinical data of patients indicated for cranioplasty. The method is based on a cascade of multi-branch volumetric CNNs that enables simultaneous training on two different types of cranioplasty ground-truth data: the skull patch, which represents the exact shape of the missing part of the original skull, and which can be easily created artificially from healthy skulls, and expert-designed cranial implant shapes that are much harder to acquire. The proposed method reaches an average surface distance of the reconstructed skull patches of 0.67 mm on a clinical test set of 75 defective skulls. It also achieves a 12% reduction of a newly proposed defect border Gaussian curvature error metric, compared to a baseline model trained on synthetic data only. Additionally, it produces directly 3D printable cranial implant shapes with a Dice coefficient 0.88 and a surface error of 0.65 mm. The outputs of the proposed skull reconstruction method reach good quality and can be considered for use in semi- or fully automatic clinical cranial implant design workflows.
- MeSH
- Deep Learning * MeSH
- Skull diagnostic imaging surgery MeSH
- Humans MeSH
- Prostheses and Implants MeSH
- Plastic Surgery Procedures * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Assessing sex and population affinity is an important part of the process of biologically identifying unknown human remains, and the skull is usually one of the best structures for assessing both these components of the biological profile. Population affinity is known to be a hugely important variable when estimating sex because the manifestation of sexually dimorphic traits, body size or social and behavioural habits differs across populations. Therefore, for forensic purposes, the estimation of ancestry is a necessary step in the identification of bone remains. The present study improves on the results of a previously developed virtual method using the exocranial surface for sex estimation and assessing population affinity. The ability to assess these components of the biological profile was successfully tested on 208 individuals from two recent European populations. The original classifier was based on geometric morphometric analyses (CPD-DCA, PCA, SVM) and was able to assess the sex of individuals belonging to one French population with an accuracy exceeding 90 % Musilová et al. [1]. To improve the reliability of the method, the Czech population sample was added to the dataset, yielding the highest accuracy of 96.2 %; using the combined dataset, the reliability of the method was 91.8 %. Secondly, we used the same method utilizing inter-population differences to classify individuals based on the shape of the skull. The greatest accuracy rate was 92.8 %, which makes our method a promising tool for sex estimation and assessing population affinity.
- MeSH
- Principal Component Analysis MeSH
- White People MeSH
- Adult MeSH
- Skull diagnostic imaging MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Reproducibility of Results MeSH
- Aged MeSH
- Forensic Anthropology MeSH
- Machine Learning MeSH
- Support Vector Machine MeSH
- Sex Determination by Skeleton methods MeSH
- Imaging, Three-Dimensional MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Czech Republic MeSH
- France MeSH
