Skull Modeling Research Articles

Numerical Investigation of Layered Homogeneous Skull Model for Simulations of Transcranial Focused Ultrasound

Background and ObjectivesThe influence of the intracranial pressure field must be discussed with the development of a single-element transducer for low-intensity transcranial focused ultrasound because the skull plays a significant role in blocking and dispersing ultrasound wave propagation. Ultrasound propagation is mainly affected by the structure and acoustic properties of the skull; thus, we aimed to investigate the impact of simplifying the acoustic properties of the skull on the simulation of the transcranial pressure field to present guidance for efficient skull modeling in full-wave simulations. Materials and MethodsWe constructed a three-dimensional computational model for ultrasound transmission with the same structure but varying acoustic properties of the skull. The structural information and heterogeneous acoustic properties of the skull were acquired from computed tomography images, and we segmented the skull into three layers (3 L), including spongy and compact bones. We then assigned homogeneous acoustic properties to a single layer (1 L) or 3 L of the skull. In addition, we investigated the influence of different types of transducers and different ultrasound frequencies (1.1 MHz, 0.5 MHz, and 0.25 MHz) on the intracranial pressure field to provide a comparison of the heterogenous and homogeneous models. ResultsWe indicated the importance of numerical simulations in estimating the intracranial pressure field of the skull owing to beam distortions. When we simplified the skull model, both the 1 L and 3 L models showed contours of the acoustic focus comparable to those of the heterogeneous model. When we evaluated the peak pressure and volume of the acoustic focus, the 1 L model produced a better estimation of peak pressure with a difference <10%, and the 3 L model is suitable to obtain smaller errors in the volume of the acoustic focus. ConclusionsIn conclusion, we examined the possibility of simplification of skull models using 1 L and 3 L homogeneous properties in the numerical simulation for focused ultrasound. The results show that the layered homogeneous model can provide characteristics comparable to those of the acoustic focus in heterogeneous models.

A Neural Implant Design Toolbox for Nonhuman Primates.

This paper describes an in-house method of 3D brain and skull modeling from magnetic resonance imaging (MRI) tailored for nonhuman primate (NHP) neurosurgical planning. This automated, computational software-based technique provides an efficient way of extracting brain and skull features from MRI files as opposed to traditional manual extraction techniques using imaging software. Furthermore, the procedure provides a method for visualizing the brain and craniotomized skull together for intuitive, virtual surgical planning. This generates a drastic reduction in time and resources from those required by past work, which relied on iterative 3D printing. The skull modeling process creates a footprint that is exported into modeling software to design custom-fit cranial chambers and headposts for surgical implantation. Custom-fit surgical implants minimize gaps between the implant and the skull that could introduce complications, including infection or decreased stability. By implementing these pre-surgical steps, surgical and experimental complications are reduced. These techniques can be adapted for other surgical processes, facilitating more efficient and effective experimental planning for researchers and, potentially, neurosurgeons.

Influence of layered skull modeling on the frequency sensitivity and target accuracy in simulations of transcranial current stimulation.

With the development of electrical stimulation technology, especially the emergence of temporally interfering (TI) stimulation, it is necessary to discuss the influence of current frequency on stimulation intensity. Accurate skull modeling is important for transcranial current stimulation (tCS) simulation prediction because of its large role in dispersing current. In this study, we simulated different frequencies of transcranial alternating current stimulation (tACS) and TI stimulation in single‐layer and layered skull model, compared the electric field via error parameters such as the relative difference measure and relative magnification factor. Pearson correlation analysis and t‐test were used to measure the differences in envelope amplitude. The results showed that the intensity of electric field in the brain generated by per unit of stimulation current will increase with current frequency, and the layered skull model had a better response to frequency. An obvious pattern difference was found between the electric fields of the layered and single‐layer skull individualized models. For TI stimulation, the Pearson correlation coefficient between the envelope distribution of the layered skull model and the single‐layer skull was only 0.746 in the individualized model, which is clearly lower than the correlation coefficient of 0.999 determined from the spherical model. Higher carrier frequencies seemed to be easier to generate a large enough brain electric field envelope in TI stimulation. In conclusion, we recommend using layered skull models instead of single‐layer skull models in tCS (particularly TI stimulation) simulation studies in order to improve the accuracy of the prediction of stimulus intensity and stimulus target.

The impact of CT image parameters and skull heterogeneity modeling on the accuracy of transcranial focused ultrasound simulations

Objective. Low-intensity transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation (NIBS) technique. TUS can reach deeper areas and target smaller regions in the brain than other NIBS techniques, but its application in humans is hampered by the lack of a straightforward and reliable procedure to predict the induced ultrasound exposure. Here, we examined how skull modeling affects computer simulations of TUS. Approach. We characterized the ultrasonic beam after transmission through a sheep skull with a hydrophone and performed computed tomography (CT) image-based simulations of the experimental setup. To study the skull model’s impact, we varied: CT acquisition parameters (tube voltage, dose, filter sharpness), image interpolation, segmentation parameters, acoustic property maps (speed-of-sound, density, attenuation), and transducer-position mismatches. We compared the impact of modeling parameter changes on model predictions and on measurement agreement. Spatial-peak intensity and location, total power, and the Gamma metric (a measure for distribution differences) were used as quantitative criteria. Modeling-based sensitivity analysis was also performed for two human head models. Main results. Sheep skull attenuation assignment and transducer positioning had the most important impact on spatial peak intensity (overestimation up to 300%, respectively 30%), followed by filter sharpness and tube voltage (up to 20%), requiring calibration of the mapping functions. Positioning and skull-heterogeneity-structure strongly affected the intensity distribution (gamma tolerances exceeded in 80%, respectively 150%, of the focus-volume in water), necessitating image-based personalized modeling. Simulation results in human models consistently demonstrate a high sensitivity to the skull-heterogeneity model, attenuation tuning, and transducer shifts, the magnitude of which depends on the underlying skull structure complexity. Significance. Our study reveals the importance of properly modeling the skull-heterogeneity and its structure and of accurately reproducing the transducer position. The results raise red flags when translating modeling approaches among clinical sites without proper standardization and/or recalibration of the imaging and modeling parameters.

Material response characterization of three poly jet printed materials used in a high fidelity human infant skull

Abstract This present study seeks to improve the infant head model biofidelity by providing a range of 3D printable candidate materials tested at different temperatures and strain rates so as to tailor materials properties to match the specific age-dependent infant skull being modeled. Mechanical properties of the three polypropylene polymers named VeroWhitePlus (RGD835 VW), TangoBlackPlus (FLX980), and RigidLightGrey25 (RGD8510-DM), were applied using a PolyJet 3D printer to replicating the comparative paediatric skull (cranial bone, fontanelles, sutures) mechanical properties. Quasi-static tensile tests were carried out for VeroWhitePlus, RigidLightGrey25 and TangoBlackPlus PolyJet polymers at two different speeds, and 3 temperatures. Strain rate and temperature dependence on elastic modulus and flow stress is evident. Mechanical properties of the PolyJet polymers indicate appropriate response for biocompatibility in modeling infant skull. Temperature dependence of the mechanical properties of the PolyJet polymers indicate a unique method to fine tune the mechanical response for specific age-dependent infant skull modeling.

Head phantoms for electroencephalography and transcranial electric stimulation: a skull material study.

Physical head phantoms allow the assessment of source reconstruction procedures in electroencephalography and electrical stimulation profiles during transcranial electric stimulation. Volume conduction in the head is strongly influenced by the skull, which represents the main conductivity barrier. Realistic modeling of its characteristics is thus important for phantom development. In the present study, we proposed plastic clay as a material for modeling the skull in phantoms. We analyzed five clay types varying in granularity and fractions of fire clay, each with firing temperatures from 550°C to 950°C. We investigated the conductivity of standardized clay samples when immersed in a 0.9% sodium chloride solution with time-resolved four-point impedance measurements. To test the reusability of the clay model, these measurements were repeated after cleaning the samples by rinsing in deionized water for 5 h. We found time-dependent impedance changes for approximately 5 min after immersion in the solution. Thereafter, the conductivities stabilized between 0.0716 S/m and 0.0224 S/m depending on clay type and firing temperatures. The reproducibility of the measurement results proved the effectiveness of the rinsing procedure. Clay provides formability, is permeable to ions, can be adjusted in conductivity value and is thus suitable for the skull modeling in phantoms.

Skull Modeling Effects in Conductivity Estimates Using Parametric Electrical Impedance Tomography.

To estimate scalp, skull, compact bone, and marrow bone electrical conductivity values based on electrical impedance tomography (EIT) measurements, and to determine the influence of skull modeling details on the estimates. We collected EIT data with 62 current injection pairs and built five 6-8 million finite element (FE) head models with different grades of skull simplifications for four subjects, including three whose head models serve as Atlases in the scientific literature and in commercial equipment (Colin27 and EGI's Geosource atlases). We estimated electrical conductivity of the scalp, skull, marrow bone, and compact bone tissues for each current injection pair, each model, and each subject. Closure of skull holes in FE models, use of simplified four-layer boundary element method-like models, and neglecting the CSF layer produce an overestimation of the skull conductivity of 10%, 10%-20%, and 20%-30%, respectively (accumulated overestimation of 50%-70%). The average extracted conductivities are 288±53 (the scalp), 4.3±0.08 (the compact bone), and 5.5±1.25 (the whole skull) mS/m. The marrow bone estimates showed large dispersion. Present EIT estimates for the skull conductivity are lower than typical literature reference values, but previous in vivo EIT results are likely overestimated due to the use of simpler models. Typical literature values of 7-10mS/m for skull conductivity should be replaced by the present estimated values when using detailed skull head models. We also provide subject specific conductivity estimates for widely used Atlas head models.

The Effect of Head Model Simplification on Beamformer Source Localization.

Beamformers are a widely-used tool in brain analysis with magnetoencephalography (MEG) and electroencephalography (EEG). For the construction of the beamformer filters realistic head volume conductor modeling is necessary for accurately computing the EEG and MEG leadfields, i.e., for solving the EEG and MEG forward problem. In this work, we investigate the influence of including realistic head tissue compartments into a finite element method (FEM) model on the beamformer's localization ability. Specifically, we investigate the effect of including cerebrospinal fluid, gray matter, and white matter distinction, as well as segmenting the skull bone into compacta and spongiosa, and modeling white matter anisotropy. We simulate an interictal epileptic measurement with white sensor noise. Beamformer filters are constructed with unit gain, unit array gain, and unit noise gain constraint. Beamformer source positions are determined by evaluating power and excess sample kurtosis (g2) of the source-waveforms at all source space nodes. For both modalities, we see a strong effect of modeling the cerebrospinal fluid and white and gray matter. Depending on the source position, both effects can each be in the magnitude of centimeters, rendering their modeling necessary for successful localization. Precise skull modeling mainly effected the EEG up to a few millimeters, while both modalities could profit from modeling white matter anisotropy to a smaller extent of 5–10 mm. The unit noise gain or neural activity index beamformer behaves similarly to the array gain beamformer when noise strength is sufficiently high. Variance localization seems more robust against modeling errors than kurtosis.

The accuracy of patient specific implant prebented with 3D-printed rapid prototype model for orbital wall reconstruction

BackgroundThis study evaluated the accuracy of blow out fracture reduction using 3D-printed rapid prototyping (RP) skull modeling. Patients and methodsRetrospective review was performed for 82 patients who underwent post-traumatic orbital wall fracture reduction between 2012 and 2014. Patients were divided into two groups according to the use of 3D-printed RP skull model reproduced by mirroring technique, onto which a titanium mesh was anatomically molded. Using computed tomographic scans, the areas of pre- and post-operative orbital wall defect, the layout angles of the titanium mesh, and the gap lengths between the implant and fracture margin were compared between the two groups. ResultsOf the 82 patients identified, 46 and 36 were diagnosed with medial and inferior orbital wall fractures, respectively. Bone defect area of the RP group was significantly reduced in comparison with that of the conventional group (8.03 ± 3.5% versus 18.7 ± 15.41% for medial wall fractures, 7.14 ± 5.74% versus 12.8 ± 4.92% for inferior wall fractures, respectively, p < 0.01). Satisfactory results were achieved regarding the layout angles and the gap lengths, presenting significantly reduced values in the RP group compared to that in the conventional group (p < 0.01). ConclusionsMore accurate restoration of traumatic orbital wall fractures can be achieved using patient-specific 3D-printed RP skull models.

P097 Direct measurement of electric fields in human and monkeys during transcranial electric stimulation

Introduction Transcranial electric stimulation (TES) is an emerging technique to non-invasively modulate brain function. However, the spatiotemporal distribution of electric fields during TES remains poorly understood. Objectives In this study we perform direct intracranial measurements of the electric field generated by transcranial alternating current (tACS) in epilepsy patients and cebus monkeys and evaluate the capacity of finite element method (FEM) models to predict the spatial distribution of measured electric fields. Methods Two presurgical epilepsy patients, with ca. 100 intracranially implanted electrodes participated in a single TES session. Two sponge electrodes (25 cm2) were attached over the left and right temporal cortex and a current of 1 mA with a frequency of 1 Hz was applied for 2 min. In two cebus monkeys three electrodes, with a total of 32 contacts were permanently implanted with posterior-anterior orientation. In multiple sessions intracranial EEG was recorded during TES. We varied the frequency of stimulation from 1–150 Hz and computed amplitude and phase relationships of recorded voltages. We constructed FEM models with increasing anatomical complexity for one epilepsy patient and compared the measured and simulated electric fields. Results Voltage magnitude slightly decreased with stimulation frequency up to 10% and small phase differences between electrode contacts up to a few degrees were observed. Electric field strengths were strongest in superficial brain regions with maximum values of 0.5 mV/mm ( Download : Download high-res image (1MB) Download : Download full-size image Fig. 1). Comparison of measured and simulated potentials and electric fields showed very high correlation values for the potentials (r = 0.95) and correlations of r = 0.7 for the electric fields. Evaluating the predictive value of increasingly complex FEM models highlighted the importance of accurate skull modeling especially in the vicinity of skull defects ( Download : Download high-res image (746KB) Download : Download full-size image Fig. 2). Conclusion We conducted a comprehensive evaluation of intracranial electric field during TES in both human patients and monkeys. Our results indicate that TES currents spread in a linear ohmic manner and capacitive effects are small indicating that the quasi-static approximation is well justified in the low frequency range. The spatial variation of the electric fields can be captured using realistic FEM models.

Forward and inverse effects of the complete electrode model in neonatal EEG.

This paper investigates finite element method-based modeling in the context of neonatal electroencephalography (EEG). In particular, the focus lies on electrode boundary conditions. We compare the complete electrode model (CEM) with the point electrode model (PEM), which is the current standard in EEG. In the CEM, the voltage experienced by an electrode is modeled more realistically as the integral average of the potential distribution over its contact surface, whereas the PEM relies on a point value. Consequently, the CEM takes into account the subelectrode shunting currents, which are absent in the PEM. In this study, we aim to find out how the electrode voltage predicted by these two models differ, if standard size electrodes are attached to a head of a neonate. Additionally, we study voltages and voltage variation on electrode surfaces with two source locations: 1) next to the C6 electrode and 2) directly under the Fz electrode and the frontal fontanel. A realistic model of a neonatal head, including a skull with fontanels and sutures, is used. Based on the results, the forward simulation differences between CEM and PEM are in general small, but significant outliers can occur in the vicinity of the electrodes. The CEM can be considered as an integral part of the outer head model. The outcome of this study helps understanding volume conduction of neonatal EEG, since it enlightens the role of advanced skull and electrode modeling in forward and inverse computations.NEW & NOTEWORTHY The effect of the complete electrode model on electroencephalography forward and inverse computations is explored. A realistic neonatal head model, including a skull structure with fontanels and sutures, is used. The electrode and skull modeling differences are analyzed and compared with each other. The results suggest that the complete electrode model can be considered as an integral part of the outer head model. To achieve optimal source localization results, accurate electrode modeling might be necessary.

The Role of Skull Modeling in EEG Source Imaging for Patients with Refractory Temporal Lobe Epilepsy.

We investigated the influence of different skull modeling approaches on EEG source imaging (ESI), using data of six patients with refractory temporal lobe epilepsy who later underwent successful epilepsy surgery. Four realistic head models with different skull compartments, based on finite difference methods, were constructed for each patient: (i) Three models had skulls with compact and spongy bone compartments as well as air-filled cavities, segmented from either computed tomography (CT), magnetic resonance imaging (MRI) or a CT-template and (ii) one model included a MRI-based skull with a single compact bone compartment. In all patients we performed ESI of single and averaged spikes marked in the clinical 27-channel EEG by the epileptologist. To analyze at which time point the dipole estimations were closer to the resected zone, ESI was performed at two time instants: the half-rising phase and peak of the spike. The estimated sources for each model were validated against the resected area, as indicated by the postoperative MRI. Our results showed that single spike analysis was highly influenced by the signal-to-noise ratio (SNR), yielding estimations with smaller distances to the resected volume at the peak of the spike. Although averaging reduced the SNR effects, it did not always result in dipole estimations lying closer to the resection. The proposed skull modeling approaches did not lead to significant differences in the localization of the irritative zone from clinical EEG data with low spatial sampling density. Furthermore, we showed that a simple skull model (MRI-based) resulted in similar accuracy in dipole estimation compared to more complex head models (based on CT- or CT-template). Therefore, all the considered head models can be used in the presurgical evaluation of patients with temporal lobe epilepsy to localize the irritative zone from low-density clinical EEG recordings.

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.

Influence of Skull Modeling Approaches on EEG Source Localization

Electroencephalographic source localization (ESL) relies on an accurate model representing the human head for the computation of the forward solution. In this head model, the skull is of utmost importance due to its complex geometry and low conductivity compared to the other tissues inside the head. We investigated the influence of using different skull modeling approaches on ESL. These approaches, consisting in skull conductivity and geometry modeling simplifications, make use of X-ray computed tomography (CT) and magnetic resonance (MR) images to generate seven different head models. A head model with an accurately segmented skull from CT images, including spongy and compact bone compartments as well as some air-filled cavities, was used as the reference model. EEG simulations were performed for a configuration of 32 and 128 electrodes, and for both noiseless and noisy data. The results show that skull geometry simplifications have a larger effect on ESL than those of the conductivity modeling. This suggests that accurate skull modeling is important in order to achieve reliable results for ESL that are useful in a clinical environment. We recommend the following guidelines to be taken into account for skull modeling in the generation of subject-specific head models: (i) If CT images are available, i.e., if the geometry of the skull and its different tissue types can be accurately segmented, the conductivity should be modeled as isotropic heterogeneous. The spongy bone might be segmented as an erosion of the compact bone; (ii) when only MR images are available, the skull base should be represented as accurately as possible and the conductivity can be modeled as isotropic heterogeneous, segmenting the spongy bone directly from the MR image; (iii) a large number of EEG electrodes should be used to obtain high spatial sampling, which reduces the localization errors at realistic noise levels.

Modeling the human skull using FEM – effects of errors and simplifications

We used computer simulations to investigate finite element models [1] of the human skull in EEG source analysis. In the first part, we present a systematic investigation on the accuracy of different ways to account for the layered skull structure. We investigated local models, where each skull location was modeled differently, and global models, where the skull was assumed to be homogeneous, both using isotropic as well as anisotropic conductivity assumptions. We determined errors both in the forward calculation and the reconstructed dipole position [2]. In the second part, we investigate the effect of a number of common errors and limitations in skull modeling, using both forward and inverse simulations. Test models included erroneous skull holes, local errors in skull thickness, modeling cavities as compact bone, downward extension of the volume conductor and simplifying the inferior skull and the inferior skull and scalp as layers of constant thickness.

Single-Layer Skull Approximations Perform Well in Transcranial Direct Current Stimulation Modeling

In modeling the effect of transcranial direct current stimulation, the representation of the skull is an important factor. In a spherical model, we compared a realistic skull modeling approach, in which the skull consisted of three isotropic layers, to anisotropic and isotropic single-layer approximations. We simulated direct current stimulation for a range of conductivity values and investigated differences in the resulting current densities. Our results demonstrate that both approximation methods perform well, provided that the optimal conductivity values are used. We found that for both the anisotropic and the isotropic approximations the optimal conductivity values are largely dictated by the equivalent radial conductivity of the three-layered skull.

Fragmented skull modeling using heat kernels

We develop a geometric reassembly algorithm that composes a 3D model from its fragments. One important application of this work is skull completion and modeling in archeology and forensics. Our reassembly algorithm employs a scale-space representation of shape based on the heat kernel, which only depends on the intrinsic geometry of the surfaces. Partial matching can then be conducted effectively. The entire assembly pipeline has three steps: (1) fragment-template matching based on heat-kernel; (2) matching refinement based on RANSAC and assembly computation; (3) assembly refinement using least square transformation error (LSTE) of break-curves. The main contribution of this paper is presenting novel algorithms for the first two steps. Experimental results on scanned skull fragments demonstrate the efficacy and robustness of our algorithm.

Modeling of the human skull in EEG source analysis

We used computer simulations to investigate finite element models of the layered structure of the human skull in EEG source analysis. Local models, where each skull location was modeled differently, and global models, where the skull was assumed to be homogeneous, were compared to a reference model, in which spongy and compact bone were explicitly accounted for. In both cases, isotropic and anisotropic conductivity assumptions were taken into account. We considered sources in the entire brain and determined errors both in the forward calculation and the reconstructed dipole position. Our results show that accounting for the local variations over the skull surface is important, whereas assuming isotropic or anisotropic skull conductivity has little influence. Moreover, we showed that, if using an isotropic and homogeneous skull model, the ratio between skin/brain and skull conductivities should be considerably lower than the commonly used 80:1. For skull modeling, we recommend (1) Local models: if compact and spongy bone can be identified with sufficient accuracy (e.g., from MRI) and their conductivities can be assumed to be known (e.g., from measurements), one should model these explicitly by assigning each voxel to one of the two conductivities, (2) Global models: if the conditions of (1) are not met, one should model the skull as either homogeneous and isotropic, but with considerably higher skull conductivity than the usual 0.0042 S/m, or as homogeneous and anisotropic, but with higher radial skull conductivity than the usual 0.0042 S/m and a considerably lower radial:tangential conductivity anisotropy than the usual 1:10.

Three dimensional methylacrylate and wax skull modeling preparing cranioplasty in the treatment of complex craniosynostosis and skull malformation

Three dimensional methylacrylate and wax skull modeling preparing cranioplasty in the treatment of complex craniosynostosis and skull malformation

Biochemical and Genetic Analysis of ANK in Arthritis and Bone Disease

Mutations in the progressive ankylosis gene (Ank/ANKH) cause surprisingly different skeletal phenotypes in mice and humans. In mice, recessive loss-of-function mutations cause arthritis, ectopic crystal formation, and joint fusion throughout the body. In humans, some dominant mutations cause chondrocalcinosis, an adult-onset disease characterized by the deposition of ectopic joint crystals. Other dominant mutations cause craniometaphyseal dysplasia, a childhood disease characterized by sclerosis of the skull and abnormal modeling of the long bones, with little or no joint pathology. Ank encodes a multiple-pass transmembrane protein that regulates pyrophosphate levels inside and outside tissue culture cells in vitro, but its mechanism of action is not yet clear, and conflicting models have been proposed to explain the effects of the human mutations. Here, we test wild-type and mutant forms of ANK for radiolabeled pyrophosphate-transport activity in frog oocytes. We also reconstruct two human mutations in a bacterial artificial chromosome and test them in transgenic mice for rescue of the Ank null phenotype and for induction of new skeletal phenotypes. Wild-type ANK stimulates saturable transport of pyrophosphate ions across the plasma membrane, with half maximal rates attained at physiological levels of pyrophosphate. Chondrocalcinosis mutations retain apparently wild-type transport activity and can rescue the joint-fusion phenotype of Ank null mice. Craniometaphyseal dysplasia mutations do not transport pyrophosphate and cannot rescue the defects of Ank null mice. Furthermore, microcomputed tomography revealed previously unappreciated phenotypes in Ank null mice that are reminiscent of craniometaphyseal dysplasia. The combination of biochemical and genetic analyses presented here provides insight into how mutations in ANKH cause human skeletal disease.