A Novel Method for the Approximation of Humeral Head Retrotorsion Based on Three-Dimensional Registration of the Bicipital Groove

BACKGROUND The accurate restoration of premorbid anatomy is key for the success of reconstructive surgeries of the proximal part of the humerus. The bicipital groove has been proposed as a landmark for the prediction of humeral head retrotorsion. We hypothesized that a novel method based on bilateral registration of the bicipital groove yields an accurate approximation of the premorbid anatomy of the proximal part of the humerus. METHODS Three-dimensional (3D) triangular surface models were created from computed tomographic data of 100 paired humeri (50 cadavers). Segments of the distal part of the humerus and the humeral shaft of prespecified lengths were defined. A surface registration algorithm was applied to superimpose the models onto the mirrored contralateral humeral model based on the defined segments. We evaluated the 3D proximal humeral contralateral registration (p-HCR) errors, defined as the difference in 3D rotation of the humeral head between the models when superimposed. For comparison, we quantified the landmark-based retrotorsion (LBR) error, defined as the intra-individual difference in retrotorsion, measured with a landmark-based 3D method. RESULTS The mean 3D p-HCR error using the most proximal humeral shaft (bicipital groove) segment for the registration was 2.8° (standard deviation [SD], 1.5°; range, 0.6° to 7.4°). The mean LBR error of the reference method was 6.4° (SD, 5.9°; range, 0.5° to 24.0°). CONCLUSIONS Bilateral 3D registration of the bicipital groove is a reliable method for approximating the premorbid anatomy of the proximal part of the humerus. CLINICAL RELEVANCE The accurate approximation of the premorbid anatomy is a key for the successful restoration of the premorbid anatomy of the proximal part of the humerus

Restoration of the Patient-Specific Anatomy of the Proximal and Distal Parts of the Humerus: Statistical Shape Modeling Versus Contralateral Registration Method

BACKGROUND In computer-assisted reconstructive surgeries, the contralateral anatomy is established as the best available reconstruction template. However, existing intra-individual bilateral differences or a pathological, contralateral humerus may limit the applicability of the method. The aim of the study was to evaluate whether a statistical shape model (SSM) has the potential to predict accurately the pretraumatic anatomy of the humerus from the posttraumatic condition. METHODS Three-dimensional (3D) triangular surface models were extracted from the computed tomographic data of 100 paired cadaveric humeri without a pathological condition. An SSM was constructed, encoding the characteristic shape variations among the individuals. To predict the patient-specific anatomy of the proximal (or distal) part of the humerus with the SSM, we generated segments of the humerus of predefined length excluding the part to predict. The proximal and distal humeral prediction (p-HP and d-HP) errors, defined as the deviation of the predicted (bone) model from the original (bone) model, were evaluated. For comparison with the state-of-the-art technique, i.e., the contralateral registration method, we used the same segments of the humerus to evaluate whether the SSM or the contralateral anatomy yields a more accurate reconstruction template. RESULTS The p-HP error (mean and standard deviation, 3.8° ± 1.9°) using 85% of the distal end of the humerus to predict the proximal humeral anatomy was significantly smaller (p = 0.001) compared with the contralateral registration method. The difference between the d-HP error (mean, 5.5° ± 2.9°), using 85% of the proximal part of the humerus to predict the distal humeral anatomy, and the contralateral registration method was not significant (p = 0.61). The restoration of the humeral length was not significantly different between the SSM and the contralateral registration method. CONCLUSIONS SSMs accurately predict the patient-specific anatomy of the proximal and distal aspects of the humerus. The prediction errors of the SSM depend on the size of the healthy part of the humerus. CLINICAL RELEVANCE The prediction of the patient-specific anatomy of the humerus is of fundamental importance for computer-assisted reconstructive surgeries

Defense mechanisms against acid exposure by dental enamel formation, saliva and pancreatic juice production.

The pancreas, the salivary glands and the dental enamel producing ameloblasts have marked developmental, structural and functional similarities. One of the most striking similarities is their bicarbonate-rich secretory product serving acid neutralization. An important difference between them is that while pancreatic juice and saliva are delivered into a lumen where they can be collected and analyzed, ameloblasts produce locally precipitating hydroxyapatite which cannot be easily studied. Interestingly, the ion and protein secretion by the pancreas, the salivary glands, and maturation ameloblasts are all two-step processes, of course with significant differences too. As they all have to defend against acid exposure by producing extremely large quantities of bicarbonate, the failure of this function leads to deteriorating consequences. The aim of the present review is to describe and characterize the defense mechanisms of the pancreas, the salivary glands and enamel-producing ameloblasts against acid exposure and to compare their functional capabilities to do this by producing bicarbonate

A scale-space curvature matching algorithm for the reconstruction of complex proximal humeral fractures

The optimal surgical treatment of complex fractures of the proximal humerus is controversial. It is proven that best results are obtained if an anatomical reduction of the fragments is achieved and, therefore, computer-assisted methods have been proposed for the reconstruction of the fractures. However, complex fractures of the proximal humerus are commonly accompanied with a relevant displacement of the fragments and, therefore, algorithms relying on the initial position of the fragments might fail. The state-of-the-art algorithm for complex fractures of the proximal humerus requires the acquisition of a CT scan of the (healthy) contralateral anatomy as a reconstruction template to address the displacement of the fragments. Pose-invariant fracture line based reconstruction algorithms have been applied successful for reassembling broken vessels in archaeology. Nevertheless, the extraction of the fracture lines and the necessary computation of their curvature are susceptible to noise and make the application of previous approaches difficult or even impossible for bone fractures close to the joints, where the cortical layer is thin. We present a novel scale-space representation of the curvature, permitting to calculate the correct alignment between bone fragments solely based on corresponding regions of the fracture lines. The fractures of the proximal humerus are automatically reconstructed based on iterative pairwise reduction of the fragments. The validation of the presented method was performed on twelve clinical cases, surgically treated after complex proximal humeral fracture, and by cadaver experiments. The accuracy of our approach was compared to the state-of-the-art algorithm for complex fractures of the proximal humerus. All reconstructions of the clinical cases resulted in an accurate approximation of the pre-traumatic anatomy. The accuracy of the reconstructed cadaver cases outperformed the current state-of-the-art algorithm

A novel registration-based approach for 3D assessment of posttraumatic distal humeral deformities

BACKGROUND: With current 3-dimensional (3D) computer-based methods for the assessment of deformities, a surface registration method is applied to superimpose a computer model of the pathological bone onto a mirrored computer model of the contralateral side. However, because of bilateral differences, especially in humeral torsion, such template-based approaches may introduce bias in the assessment of a distal humeral deformity. We hypothesized that a novel registration approach might prove superior to the current approach in reducing such bias, thus yielding improved accuracy of 3D assessment of distal humeral deformities. METHODS: Three-dimensional triangular surface models were generated from computed tomographic (CT) data of 100 paired humeri without a pathological condition. Humeral segments of varying, predetermined lengths, excluding the distal part of the humerus, were defined. A surface registration algorithm was applied to superimpose the humeral models of both sides based on each selected segment. Humeral contralateral registration (HCR) errors, defined as the residual differences in apparent 3D orientation between the distal parts, were evaluated. RESULTS: The mean HCR error (and standard deviation) using the distal-most humeral shaft segment to assess the angular orientation was 2.3° ± 1.1 (range, 0.5° to 5.8°). Including the humeral head in the surface registration algorithm, however, as is done currently, resulted in a higher HCR error (p 10° in 20% of the cases and between 5° and 10° in an additional 50% of the cases. By comparison, using the proposed distal-most humeral shaft segment, the HCR error was between 5° and 10° in only 2% of cases, and was never >10°. The proximal segments are nevertheless used in the proposed method for registering humeral length. CONCLUSIONS: The proposed new approach yields a deformity assessment that is less prone to bias arising from inherent bilateral differences and therefore is more accurate than current surface registration approaches. CLINICAL RELEVANCE: Accurate 3D assessment is of fundamental importance if computer-based methods are applied in the correction of posttraumatic deformities