COMPUTER-AIDED MODELING AND ADDITIVE MANUFACTURING FABRICATION OF PATIENT-SPECIFIC MANDIBULAR IMPLANT

With the recent advances in computer-aided technologies and their breach into the medical field, there can be seen more and more successful outcomes, especially in the files of reconstructive prosthetic surgery. With the application of advanced tools for reconstruction of complex shape such as human anatomy, it allowed accurate and fast design of complex implants as a substitution for deformed or damaged regions in the field of maxillofacial surgery. Design, in compliance with application of additive manufacturing (AM) technologies, is starting to gain more recognition as a tool for fast and accurate delivery of patient-specific 3D implants. This paper present a case study where such 3D technologies are used to design and fabricate a patient-specific mandibular implant. Tools for design of complex anatomical surfaces, such as mandible are presented and demonstrated in this paper. As the verification stage, AM technologies are used for visual inspection and surgical procedure planning of the designed 3D model of the mandibular implant

An Innovative Photogrammetric System for 3D Digitization of Dental Models

This paper presents an innovative system for 3D reconstruction of a physical dental model. The innovative system is based on close-range photogrammetry and enables the projection of digital light texture on the objects surface. It is based on the application of mirrors that direct the digital light texture to the vertical surfaces of the physical model. In this way, high coverage of the object is achieved, and 3D reconstruction from one set of photographs is possible. 3D digitization, verification and comparison of the proposed methodology was performed on dental models that are characterized by extremely complex surfaces. It was performed by comparing the proposed approach with active stereovision, and the efficiency was evaluated in relation to the reference 3D model obtained by the structured light 3D scanner. The comparison of the results was performed on the basis of the mean deviation and standard deviation for the 3D model with combined teeth and for the 3D model with metal caps. The absolute mean deviations for the 3D model with combined teeth are 0.004-0.021 mm, with a standard deviation of 0.055-0.058 mm, and for the 3D model with metal caps absolute mean deviations are 0.015-0.033 mm, with a standard deviation of 0.095-0.113 mm, respectively. Absolute minimum values of mean deviation of 0.004 mm and standard deviations of 0.055 mm were obtained by 3D model with combined teeth,which was reconstructed by the proposed innovative approach. The obtained results indicate a higher accuracy of the innovative approach in relation to the use of a commercial 3D scanner that uses active stereovision principle

Multi-Criteria Evaluation of Design Complexity for Patient-Specific Bone Graft

With the rise of modern computer-aided technologies, their use in various different fields is becoming more and more apparent, but more profoundly in the field of medicine. The use of such technology enables the design of complex anatomical structures, often found in different areas of medicine. Maxillofacial and oral fields are becoming more and more popular with the use of such technologies, all leaning toward designing and fabrication of patient-specific implants from a biocompatible material. The level of complexity in personal graft design depends on criteria that describe the bone graft\u27s various properties. This research applies multi-criteria decision aiding in selection of patient-specific bone graft optimal design.Twelve different patient-specific bone-grafts designs have been evaluated by four decision makers who expressed their preferences with direct weighting and revised Simos procedure. Well known VIKOR method was used for multi-criteria decision aiding and the final results verified that the fully curved shape graft design is the least complex while the complex shape is the most demanding from the graft design perspective

Fuzzy Hybrid Method for the Reconstruction of 3D Models Based on CT/MRI Data

This research proposes a hybrid method for improving the segmentation accuracy of reconstructed 3D models from computed tomography/magnetic resonance imaging (CT/MRI) data. A semi-automatic hybrid method based on combination of Fuzzy C-Means clustering (FCM) and region growing (RG) is proposed. In this approach, FCM is used in the first stage as a preprocessing step in order to classify and improve images by assigning pixels to the clusters for which they have the maximum membership, and manual selection of the membership intensity map with the best contrast separation. Afterwards, automatic seed selection is performed for RG, for which a new parameter standard deviation (STD) of pixel intensities, is included. It is based on the selection of an initial seed inside a region with maximum value of STD. To evaluate the performance of the proposed method, it was compared to several other segmentation methods. Experimental results show that the proposed method overall provides better results compared to other methods in terms of accuracy. The average sensitivity and accuracy rates for cone-beam computed tomography CBCT 1 and CBCT 2 datasets are 99 %, 98.4 %, 47.2 % and 89.9 %, respectively. For MRI 1 and MRI 2 datasets, the average sensitivity and accuracy values are 99.1 %, 100 %, 75.6 % and 99.6 %, respectively. The average values for the Dice coefficient and Jaccard index for the CBCT 1 and CBCT 2 datasets are 95.88, 0.88, 0.6, and 0.51, respectively, while for MRI 1 and MRI 2 datasets, average values are 0.96, 0.93, 0.81 and 0.7, respectively, which confirms the high accuracy of the proposed method

Fuzzy Hybrid Method for the Reconstruction of 3D Models Based on CT/MRI Data

This research proposes a hybrid method for improving the segmentation accuracy of reconstructed 3D models from computed tomography/magnetic resonance imaging (CT/MRI) data. A semi-automatic hybrid method based on combination of Fuzzy C-Means clustering (FCM) and region growing (RG) is proposed. In this approach, FCM is used in the first stage as a preprocessing step in order to classify and improve images by assigning pixels to the clusters for which they have the maximum membership, and manual selection of the membership intensity map with the best contrast separation. Afterwards, automatic seed selection is performed for RG, for which a new parameter standard deviation (STD) of pixel intensities, is included. It is based on the selection of an initial seed inside a region with maximum value of STD. To evaluate the performance of the proposed method, it was compared to several other segmentation methods. Experimental results show that the proposed method overall provides better results compared to other methods in terms of accuracy. The average sensitivity and accuracy rates for cone-beam computed tomography CBCT 1 and CBCT 2 datasets are 99 %, 98.4 %, 47.2 % and 89.9 %, respectively. For MRI 1 and MRI 2 datasets, the average sensitivity and accuracy values are 99.1 %, 100 %, 75.6 % and 99.6 %, respectively. The average values for the Dice coefficient and Jaccard index for the CBCT 1 and CBCT 2 datasets are 95.88, 0.88, 0.6, and 0.51, respectively, while for MRI 1 and MRI 2 datasets, average values are 0.96, 0.93, 0.81 and 0.7, respectively, which confirms the high accuracy of the proposed method

Computer-aided methods for single stage fibrous dysplasia excision and reconstruction in the zygomatico-orbital complex

Computer Aided Design and Additive Manufacture (CAD/AM) technologies are sufficiently refined and meet the necessary regulatory requirements for routine incorporation into the medical field, with long-standing application in surgeries of the maxillofacial and craniofacial region. They have resulted in better medical care for patients, and faster, more accurate procedures. Despite ever-growing evidence about the advantages of computer aided planning, CAD and AM in surgery, detailed reporting on critical design decisions that enable methodological replication, and the development and establishment of guidelines to ensure safety, are limited. This paper presents a novel application of CAD and AM to a single stage resection and reconstruction of fibrous dysplasia in the zygoma and orbit. It is reported in sufficient fidelity to permit methods replication and design guideline developments in future cases, wherever they occur in the world. The collaborative approach included engineers, designers, surgeons and prosthetists to design patient-specific cutting guides and a custom implant. An iterative design process was used, until the desired shape and function were achieved, for both of the devices. The surgery followed the CAD plan precisely and without problems. Immediate post-operative subjective clinical judgements were of an excellent result. At 19 months post-op, a CT scan was undertaken to verify the clinical and technical outcomes. Dimensional analysis showed maximum deviation of 4.73 mm from the plan to the result, while CAD-Inspection showed that the deviations range between -0.1 and -0.8 mm, and that the majority of deviations are located around the –0.3 mm. Improvements are suggested and conclusions drawn regarding the design decisions considered critical to a successful outcome for this type of procedure in the future

Computational Analysis Reveals the Temporal Acquisition of Pathway Alterations during the Evolution of Cancer

Cancer metastasis is the lethal developmental step in cancer, responsible for the majority of cancer deaths. To metastasise, cancer cells must acquire the ability to disseminate systemically and to escape an activated immune response. Here, we endeavoured to investigate if metastatic dissemination reflects acquisition of genomic traits that are selected for. We acquired mutation and copy number data from 8332 tumours representing 19 cancer types acquired from The Cancer Genome Atlas and the Hartwig Medical Foundation. A total of 827,344 non-synonymous mutations across 8332 tumour samples representing 19 cancer types were timed as early or late relative to copy number alterations, and potential driver events were annotated. We found that metastatic cancers had a significantly higher proportion of clonal mutations and a general enrichment of early mutations in p53 and RTK/KRAS pathways. However, while individual pathways demonstrated a clear time-separated preference for specific events, the relative timing did not vary between primary and metastatic cancers. These results indicate that the selective pressure that drives cancer development does not change dramatically between primary and metastatic cancer on a genomic level, and is mainly focused on alterations that increase proliferation

Prioritization of Biomarker Targets in Human Umbilical Cord Blood: Identification of Proteins in Infant Blood Serving as Validated Biomarkers in Adults

Background: Early diagnosis represents one of the best lines of defense in the fight against a wide array of human diseases. Umbilical cord blood (UCB) is one of the first easily available diagnostic biofluids and can inform about the health status of newborns. However, compared with adult blood, its diagnostic potential remains largely untapped

Vesicle-Associated Membrane Protein 8 (VAMP8) is a SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) selectively required for sequential granule-to-granule fusion

Compound exocytosis is found in many cell types and is the major form of regulated secretion in acinar and mast cells. Its key characteristic is the homotypic fusion of secretory granules. These then secrete their combined output through a single fusion pore to the outside. The control of compound exocytosis remains poorly understood. Although soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) such as syntaxin 2, SNAP23 (synaptosome-associated protein of 23 kDa), and SNAP25 have been suggested to play a role, none has been proven. Vesicle-associated membrane protein 8 (VAMP8) is a SNARE first associated with endocytic processes but more recently has been suggested as an R-SNARE in regulated exocytosis. Secretion in acinar cells is reduced when VAMP8 function is inhibited and is less in VAMP8 knock-out mice. Based on electron microscopy experiments, it was suggested that VAMP8 may be involved in compound exocytosis. Here we have tested the hypothesis that VAMP8 controls homotypic granule-to-granule fusion during sequential compound exocytosis. We use a new assay to distinguish primary fusion events (fusion with the cell membrane) from secondary fusion events (granule-granule fusion). Our data show the pancreatic acinar cells from VAMP8 knock-out animals have a specific reduction in secondary granule fusion but that primary granule fusion is unaffected. Furthermore, immunoprecipitation experiments show syntaxin 2 association with VAMP2, whereas syntaxin 3 associates with VAMP8. Taken together our data indicate that granule-to-granule fusion is regulated by VAMP8 containing SNARE complexes distinct from those that regulate primary granule fusion

Increased Soluble PD-1 Predicts Response to Nivolumab plus Ipilimumab in Melanoma

SIMPLE SUMMARY: Checkpoint inhibitors have emerged as an effective therapy for patients with metastatic melanoma significantly improving survival for these patients. Despite this, many patients do not respond to the therapy and no current biomarkers can identify responders from non-responders. Using machine learning, we analysed cytokine levels in serially collected liquid biopsy to identify cytokine changes associated with response to checkpoint inhibitors in advanced-stage melanoma patients. The results presented here highlight that serial measurements of cytokine levels are a strong predictor of treatment response. Particularly, we demonstrate that high increases of soluble PD-1 measured from baseline to on-treatment is significantly associated with superior PFS in patients treated with nivolumab plus ipililumab. These results suggest that monitoring cytokine levels using serial samples is informative of treatment response and can improve guidance of treatment modality and the outcome of cancer patients. ABSTRACT: Background: Checkpoint inhibitors have revolutionized the treatment of metastatic melanoma, yielding long-term survival in a considerable proportion of the patients. Yet, 40–60% of patients do not achieve a long-term benefit from such therapy, emphasizing the urgent need to identify biomarkers that can predict response to immunotherapy and guide patients for the best possible treatment. Here, we exploited an unsupervised machine learning approach to identify potential inflammatory cytokine signatures from liquid biopsies, which could predict response to immunotherapy in melanoma. Methods: We studied a cohort of 77 patients diagnosed with unresectable advanced-stage melanoma undergoing treatment with first-line nivolumab plus ipilimumab or pembrolizumab. Baseline and on-treatment plasma samples were tested for levels of PD-1, PD-L1, IFNγ, IFNβ, CCL20, CXCL5, CXCL10, IL6, IL8, IL10, MCP1, and TNFα and analyzed by Uniform Manifold Approximation and Projection (UMAP) dimension reduction method and k-means clustering analysis. Results: Interestingly, using UMAP analysis, we found that treatment-induced cytokine changes measured as a ratio between baseline and on-treatment samples correlated significantly to progression-free survival (PFS). For patients treated with nivolumab plus ipilimumab we identified a group of patients with superior PFS that were characterized by significantly higher baseline-to-on-treatment increments of PD-1, PD-L1, IFNγ, IL10, CXCL10, and TNFα compared to patients with worse PFS. Particularly, a high PD-1 increment was a strong individual predictor for superior PFS (HR = 0.13; 95% CI 0.034–0.49; p = 0.0026). In contrast, decreasing levels of IFNγ and IL6 and increasing levels of CXCL5 were associated with superior PFS in the pembrolizumab group, although none of the cytokines were individually predictors for PFS. Conclusions: In short, our study demonstrates that a high increment of PD-1 is associated with superior PFS in advanced-stage melanoma patients treated with nivolumab plus ipilimumab. In contrast, decreasing levels of IFNγ and IL6, and increasing levels of CXCL5 are associated with response to pembrolizumab. These results suggest that using serial samples to monitor changes in cytokine levels early during treatment is informative for treatment response