Computer-aided position planning of miniplates to treat facial bone defects

Application of 3D Printing Technology in the Treatment of Hoffa's Fracture Nonunion

Objective  To evaluate a proposed three-dimensional (3D) printing process of a biomodel developed with the aid of fused deposition modeling (FDM) technology based on computed tomography (CT) scans of an individual with nonunion of a coronal femoral condyle fracture (Hoffa's fracture). Materials and Methods  Thus, we used CT scans, which enable the evaluation of the 3D volumetric reconstruction of the anatomical model, as well as of the architecture and bone geometry of sites with complex anatomy, such as the joints. In addition, it enables the development of the virtual surgical planning (VSP) in a computer-aided design (CAD) software. This technology makes it possible to print full-scale anatomical models that can be used in surgical simulations for training and in the choice of the best placement of the implant according to the VSP. In the radiographic evaluation of the osteosynthesis of the Hoffa's fracture nonunion, we assessed the position of the implant in the 3D-printed anatomical model and in the patient's knee. Results  The 3D-printed anatomical model showed geometric and morphological characteristics similar to those of the actual bone. The position of the implants in relation to the nonunion line and anatomical landmarks showed great accuracy in the comparison of the patient's knee with the 3D-printed anatomical model. Conclusion  The use of the virtual anatomical model and the 3D-printed anatomical model with the additive manufacturing (AM) technology proved to be effective and useful in planning and performing the surgical treatment of Hoffa's fracture nonunion. Thus, it showed great accuracy in the reproducibility of the virtual surgical planning and the 3D-printed anatomical model.

An Overview of 3D Anatomical Model Printing in Orthopedic Trauma Surgery

Introduction

3D object printing technology is a resource increasingly used in medicine in recent years, mainly incorporated in surgical areas like orthopedics. The models made by 3D printing technology provide surgeons with an accurate analysis of complex anatomical structures, allowing the planning, training, and surgery simulation. In orthopedic surgery, this technique is especially applied in oncological surgeries, bone, and joint reconstructions, and orthopedic trauma surgeries. In these cases, it is possible to prototype anatomical models for surgical planning, simulating, and training, besides printing of instruments and implants.

Purpose

The purpose of this paper is to describe the acquisition and processing from computed tomography images for 3D printing, to describe modeling and the 3D printing process of the biomodels in real size. This paper highlights 3D printing with the applicability of the 3D biomodels in orthopedic surgeries and shows some examples of surgical planning in orthopedic trauma surgery.

Patients and Methods

Four examples were selected to demonstrate the workflow and rationale throughout the process of planning and printing 3D models to be used in a variety of situations in orthopedic trauma surgeries. In all cases, the use of 3D modeling has impacted and improved the final treatment strategy.

Conclusion

The use of the virtual anatomical model and the 3D printed anatomical model with the additive manufacturing technology proved to be effective and useful in planning and performing the surgical treatment of complex articular fractures, allowing surgical planning both virtual and with the 3D printed anatomical model, besides being useful during the surgical time as a navigation instrument.

Osseous Union after Mandible Reconstruction with Fibula Free Flap Using Manually Bent Plates vs. Patient-Specific Implants: A Retrospective Analysis of 89 Patients

The aim of this monocentric, retrospective clinical study was to evaluate the status of osseous union in uni- and poly-segmental mandible reconstructions regarding conventional angle-stable manually bent osteosynthesis plates (Unilock 2.0 mm) versus titan laser-melted PSI patient-specific implant’s (PSI). The clinical impact of PSI’s high stiffness fixation methods on bone healing and regeneration is still not well addressed. The special interest was in evaluating the ossification of junctions between mandible and fibula and between osteotomized fibula free flap (FFF) segments. Panoramic radiograph (OPT), computed tomography (CT) scans, or cone-beam CTs (CBCT) of patients who underwent successful FFF for mandible reconstruction from January 2005 to December 2020 were analyzed. A total number of 89 cases (28 females (31.5%), 61 males (68.5%), mean age 58.2 ± 11.3 years, range: 22.8–82.7 years) fulfilled the chosen inclusion criteria for analysis (conventional: n = 44 vs. PSI: n = 45). The present study found an overall incomplete ossification (IOU) rate of 24.7% (conventional: 13.6% vs. PSI: 35.6%; p = 0.017) for mandible to fibula and intersegmental junctions. Between osteotomized FFF segments, an IOU rate of 16% was found in the PSI-group, while no IOU was recorded in the conventional group (p = 0.015). Significant differences were registered for IOU rates in poly-segmental (p = 0.041), and lateral (p = 0.016) mandibular reconstructions when PSI was used. Multivariate logistic regression analysis identified plate exposure and type of plate used as independent risk factors for IOU. Previous or adjuvant radiotherapy did not impact incomplete osseous union in the evaluated study sample. PSI is more rigid than bent mini-plates and shields functional mechanical stimuli, and is the main reason for increasing the rate of incomplete ossification. To enhance the functional stimulus for ossification it has to be discussed if patient-specific implants can be designed to be thinner, and should be divided into segmental plates. This directs chewing forces through the bone and improves physiological bone remodeling.

Studierfenster: an Open Science Cloud-Based Medical Imaging Analysis Platform

Imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI) are widely used in diagnostics, clinical studies, and treatment planning. Automatic algorithms for image analysis have thus become an invaluable tool in medicine. Examples of this are two- and three-dimensional visualizations, image segmentation, and the registration of all anatomical structure and pathology types. In this context, we introduce Studierfenster (www.studierfenster.at): a free, non-commercial open science client-server framework for (bio-)medical image analysis. Studierfenster offers a wide range of capabilities, including the visualization of medical data (CT, MRI, etc.) in two-dimensional (2D) and three-dimensional (3D) space in common web browsers, such as Google Chrome, Mozilla Firefox, Safari, or Microsoft Edge. Other functionalities are the calculation of medical metrics (dice score and Hausdorff distance), manual slice-by-slice outlining of structures in medical images, manual placing of (anatomical) landmarks in medical imaging data, visualization of medical data in virtual reality (VR), and a facial reconstruction and registration of medical data for augmented reality (AR). More sophisticated features include the automatic cranial implant design with a convolutional neural network (CNN), the inpainting of aortic dissections with a generative adversarial network, and a CNN for automatic aortic landmark detection in CT angiography images. A user study with medical and non-medical experts in medical image analysis was performed, to evaluate the usability and the manual functionalities of Studierfenster. When participants were asked about their overall impression of Studierfenster in an ISO standard (ISO-Norm) questionnaire, a mean of 6.3 out of 7.0 possible points were achieved. The evaluation also provided insights into the results achievable with Studierfenster in practice, by comparing these with two ground truth segmentations performed by a physician of the Medical University of Graz in Austria. In this contribution, we presented an online environment for (bio-)medical image analysis. In doing so, we established a client-server-based architecture, which is able to process medical data, especially 3D volumes. Our online environment is not limited to medical applications for humans. Rather, its underlying concept could be interesting for researchers from other fields, in applying the already existing functionalities or future additional implementations of further image processing applications. An example could be the processing of medical acquisitions like CT or MRI from animals [Clinical Pharmacology & Therapeutics, 84(4):448–456, 68], which get more and more common, as veterinary clinics and centers get more and more equipped with such imaging devices. Furthermore, applications in entirely non-medical research in which images/volumes need to be processed are also thinkable, such as those in optical measuring techniques, astronomy, or archaeology.

A review on patient-specific facial and cranial implant design using Artificial Intelligence (AI) techniques

INTRODUCTION

Researchers and engineers have found their importance in healthcare industry including recent updates in patient-specific implant (PSI) design. CAD/CAM technology plays an important role in the design and development of Artificial Intelligence (AI) based implants.The across the globe have their interest focused on the design and manufacturing of AI-based implants in everyday professional use can decrease the cost, improve patient's health and increase efficiency, and thus many implant designers and manufacturers practice.

AREAS COVERED

The focus of this study has been to manufacture smart devices that can make contact with the world as normal people do, understand their language, and learn to improve from real-life examples. Machine learning can be guided using a heavy amount of data sets and algorithms that can improve its ability to learn to perform the task. In this review, artificial intelligence (AI), deep learning, and machine-learning techniques are studied in the design of biomedical implants.

EXPERT OPINION

The main purpose of this article was to highlight important AI techniques to design PSIs. These are the automatic techniques to help designers to design patient-specific implants using AI algorithms such as deep learning, machine learning, and some other automatic methods.

A review on computer-aided design and manufacturing of patient-specific maxillofacial implants

Introduction: Various prefabricated maxillofacial implants are used in the clinical routine for the surgical treatment of patients. In addition to these prefabricated implants, customized CAD/CAM implants become increasingly important for a more precise replacement of damaged anatomical structures. This paper reviews the design and manufacturing of patient-specific implants for the maxillofacial area.Areas covered: The contribution of this publication is to give a state-of-the-art overview in the usage of customized facial implants. Moreover, it provides future perspectives, including 3D printing technologies, for the manufacturing of patient-individual facial implants that are based on patient's data acquisitions, like Computed Tomography (CT) or Magnetic Resonance Imaging (MRI).Expert opinion: The main target of this review is to present various designing software and 3D manufacturing technologies that have been applied to fabricate facial implants. In doing so, different CAD designing software's are discussed, which are based on various methods and have been implemented and evaluated by researchers. Finally, recent 3D printing technologies that have been applied to manufacture patient-individual implants will be introduced and discussed.

Computer-Based 3D Simulations to Formulate Preoperative Planning of Bridge Crane Technique for Thoracic Ossification of the Ligamentum Flavum

Background

The bridge crane technique is a novel surgical technique for the treatment of thoracic ossification of the ligamentum flavum (TOLF), but its preoperative planning has not been studied well, which limits the safety and efficacy of surgery to some extent. The purpose of this study was to investigate the method of application and effect of computer-aided preoperative planning (CAPP) on the bridge crane technique for TOLF.

Material/Methods

This retrospective multi-center included 40 patients with TOLF who underwent the bridge crane technique from 2016 to 2018. According to the utilization of CAPP, patients were divided into Group A (with CAPP, n=21) and Group B (without CAPP, n=19). Comparisons of clinical and radiological outcomes were carried out between the 2 groups.

Results

The patients in Group A had higher post-mJOA scores and IR of neurological function than those in Group B (p<0.05). Group A had shorter surgery time, fewer fluoroscopic images, and lower incidence of complications than Group B. In Group A, there was a high consistency of all the anatomical parameters between preoperative simulation and postoperative CT (p>0.05). In Group B, there were significant differences in 3 anatomical parameters between postoperative simulation and postoperative CT (p<0.05). In Group B, the patients with no complications had higher post-SVOR and lower SVRR and height of posterior suspension of LOC in postoperative CT than those in postoperative simulation (p<0.05).

Conclusions

CAPP can enable surgeons to control the decompression effect accurately and reduce the risk of related complications, which improves the safety and efficacy of surgery.

A review on multiplatform evaluations of semi-automatic open-source based image segmentation for cranio-maxillofacial surgery

BACKGROUND AND OBJECTIVES

Computer-assisted technologies, such as image-based segmentation, play an important role in the diagnosis and treatment support in cranio-maxillofacial surgery. However, although many segmentation software packages exist, their clinical in-house use is often challenging due to constrained technical, human or financial resources. Especially technological solutions or systematic evaluations of open-source based segmentation approaches are lacking. The aim of this contribution is to assess and review the segmentation quality and the potential clinical use of multiple commonly available and license-free segmentation methods on different medical platforms.

METHODS

In this contribution, the quality and accuracy of open-source segmentation methods was assessed on different platforms using patient-specific clinical CT-data and reviewed with the literature. The image-based segmentation algorithms GrowCut, Robust Statistics Segmenter, Region Growing 3D, Otsu & Picking, Canny Segmentation and Geodesic Segmenter were investigated in the mandible on the platforms 3D Slicer, MITK and MeVisLab. Comparisons were made between the segmentation algorithms and the ground truth segmentations of the same anatomy performed by two clinical experts (n = 20). Assessment parameters were the Dice Score Coefficient (DSC), the Hausdorff Distance (HD), and Pearsons correlation coefficient (r).

RESULTS

The segmentation accuracy was highest with the GrowCut (DSC 85.6%, HD 33.5 voxel) and the Canny (DSC 82.1%, HD 8.5 voxel) algorithm. Statistical differences between the assessment parameters were not significant (p < 0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the segmentation methods and the ground truth schemes. Functionally stable and time-saving segmentations were observed.

CONCLUSION

High quality image-based semi-automatic segmentation was provided by the GrowCut and the Canny segmentation method. In the cranio-maxillofacial complex, these segmentation methods provide algorithmic alternatives for image-based segmentation in the clinical practice for e.g. surgical planning or visualization of treatment results and offer advantages through their open-source availability. This is the first systematic multi-platform comparison that evaluates multiple license-free, open-source segmentation methods based on clinical data for the improvement of algorithms and a potential clinical use in patient-individualized medicine. The results presented are reproducible by others and can be used for clinical and research purposes.

Computed tomography data collection of the complete human mandible and valid clinical ground truth models

Image-based algorithmic software segmentation is an increasingly important topic in many medical fields. Algorithmic segmentation is used for medical three-dimensional visualization, diagnosis or treatment support, especially in complex medical cases. However, accessible medical databases are limited, and valid medical ground truth databases for the evaluation of algorithms are rare and usually comprise only a few images. Inaccuracy or invalidity of medical ground truth data and image-based artefacts also limit the creation of such databases, which is especially relevant for CT data sets of the maxillomandibular complex. This contribution provides a unique and accessible data set of the complete mandible, including 20 valid ground truth segmentation models originating from 10 CT scans from clinical practice without artefacts or faulty slices. From each CT scan, two 3D ground truth models were created by clinical experts through independent manual slice-by-slice segmentation, and the models were statistically compared to prove their validity. These data could be used to conduct serial image studies of the human mandible, evaluating segmentation algorithms and developing adequate image tools.

Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): guidelines for medical 3D printing and appropriateness for clinical scenarios

Medical three-dimensional (3D) printing has expanded dramatically over the past three decades with growth in both facility adoption and the variety of medical applications. Consideration for each step required to create accurate 3D printed models from medical imaging data impacts patient care and management. In this paper, a writing group representing the Radiological Society of North America Special Interest Group on 3D Printing (SIG) provides recommendations that have been vetted and voted on by the SIG active membership. This body of work includes appropriate clinical use of anatomic models 3D printed for diagnostic use in the care of patients with specific medical conditions. The recommendations provide guidance for approaches and tools in medical 3D printing, from image acquisition, segmentation of the desired anatomy intended for 3D printing, creation of a 3D-printable model, and post-processing of 3D printed anatomic models for patient care.