Assessment of DICOM Viewers Capable of Loading Patient-specific 3D Models Obtained by Different Segmentation Platforms in the Operating Room

Area of Focus in 3D Volumetry and Botulinum Toxin A Injection for Giant Diaphragmatic Hernia with Loss of Domain: A Case Report with Video Illustration

Background

Chronic giant diaphragmatic hernia is a severe disease with challenging diagnosis and treatment. Given the risk of loss of domain, the use of botulinum toxin A is an option but has been minimally studied in diaphragmatic hernia surgery.

Case Report

We present a case of a giant diaphragmatic hernia in a 66-years-old patient who showed a 12-year history of progressive chronic respiratory insufficiency. There were not notion of traumatic injuries. The CT-scan showed a giant diaphragmatic hernia with herniation of small bowel, right liver, omentum and transverse colon.

Method

We assessed the risk of loss of domain using a 3D volumetry based on the Sabbagh score and decided to use Botox injection before laparoscopic reduction of the hernia due to the high risk of complications related to the loss of domain. A computed tomography was performed 24 months after surgery and showed no evidence of recurrence. The patient presented an excellent functional result with a normal physical activity.

Conclusion

This report is among the first to highlight the utility of 3D reconstruction in assessing the risk associated with loss of domain and in preparing the abdominal wall with botulinum toxin A for diaphragmatic hernia repair.

BlueLight: An Open Source DICOM Viewer Using Low-Cost Computation Algorithm Implemented with JavaScript Using Advanced Medical Imaging Visualization

Recently, WebGL has been widely used in numerous web-based medical image viewers to present advanced imaging visualization. However, in the scenario of medical imaging, there are many challenges of computation time and memory consumption that limit the use of advanced image renderings, such as volume rendering and multiplanar reformation/reconstruction, in low-cost mobile devices. In this study, we propose a client-side rendering low-cost computation algorithm for common two- and three-dimensional medical imaging visualization implemented by pure JavaScript. Particularly, we used the functions of cascading style sheet transform and combinate with Digital Imaging and Communications in Medicine (DICOM)-related imaging to replace the application programming interface with high computation to reduce the computation time and save memory consumption while launching medical imaging interpretation on web browsers. The results show the proposed algorithm significantly reduced the consumption of central and graphics processing units on various web browsers. The proposed algorithm was implemented in an open-source web-based DICOM viewer BlueLight; the results show that it has sufficient rendering performance to display 3D medical images with DICOM-compliant annotations and has the ability to connect to image archive via DICOMweb as well.Keywords: WebGL, DICOMweb, Multiplanar reconstruction, Volume rendering, DICOM, JavaScript, Zero-footprint.

[Automatic modeling of the knee joint based on artificial intelligence]

Objective

To investigate an artificial intelligence (AI) automatic segmentation and modeling method for knee joints, aiming to improve the efficiency of knee joint modeling.

Methods

Knee CT images of 3 volunteers were randomly selected. AI automatic segmentation and manual segmentation of images and modeling were performed in Mimics software. The AI-automated modeling time was recorded. The anatomical landmarks of the distal femur and proximal tibia were selected with reference to previous literature, and the indexes related to the surgical design were calculated. Pearson correlation coefficient ( r) was used to judge the correlation of the modeling results of the two methods; the consistency of the modeling results of the two methods were analyzed by DICE coefficient.

Results

The three-dimensional model of the knee joint was successfully constructed by both automatic modeling and manual modeling. The time required for AI to reconstruct each knee model was 10.45, 9.50, and 10.20 minutes, respectively, which was shorter than the manual modeling [(64.73±17.07) minutes] in the previous literature. Pearson correlation analysis showed that there was a strong correlation between the models generated by manual and automatic segmentation ( r=0.999, P<0.001). The DICE coefficients of the 3 knee models were 0.990, 0.996, and 0.944 for the femur and 0.943, 0.978, and 0.981 for the tibia, respectively, verifying a high degree of consistency between automatic modeling and manual modeling.

Conclusion

The AI segmentation method in Mimics software can be used to quickly reconstruct a valid knee model.

Validation and accuracy evaluation of automatic segmentation for knee joint pre-planning

BACKGROUND

Proper use of three-dimensional (3D) models generated from medical imaging data in clinical preoperative planning, training and consultation is based on the preliminary proved accuracy of the replication of the patient anatomy. Therefore, this study investigated the dimensional accuracy of 3D reconstructions of the knee joint generated from computed tomography scans via automatic segmentation by comparing them with 3D models generated through manual segmentation.

METHODS

Three unpaired, fresh-frozen right legs were investigated. Three-dimensional models of the femur and the tibia of each leg were manually segmented using a commercial software and compared in terms of geometrical accuracy with the 3D models automatically segmented using proprietary software. Bony landmarks were identified and used to calculate clinically relevant distances: femoral epicondylar distance; posterior femoral epicondylar distance; femoral trochlear groove length; tibial knee center tubercle distance (TKCTD). Pearson's correlation coefficient and Bland and Altman plots were used to evaluate the level of agreement between measured distances.

RESULTS

Differences between parameters measured on 3D models manually and automatically segmented were below 1 mm (range: -0.06 to 0.72 mm), except for TKCTD (between 1.00 and 1.40 mm in two specimens). In addition, there was a significant strong correlation between measurements.

CONCLUSIONS

The results obtained are comparable to those reported in previous studies where accuracy of bone 3D reconstruction was investigated. Automatic segmentation techniques can be used to quickly reconstruct reliable 3D models of bone anatomy and these results may contribute to enhance the spread of this technology in preoperative and operative settings, where it has shown considerable potential.

Free DICOM-Viewers for Veterinary Medicine : Survey and Comparison of Functionality and User-Friendliness of Medical Imaging PACS-DICOM-Viewer Freeware for Specific Use in Veterinary Medicine Practices

There is increasing prevalence of digital diagnostic imaging in veterinary medicine with a progressive need to use medical imaging software. As Digital Imaging and Communications in Medicine (DICOM)-viewers for veterinary use do not require medical device approval in many countries, freeware viewers might be a practical alternative. The aim of this study was to identify and evaluate free DICOM-viewer software for veterinary purposes. The functionality and user-friendliness of various DICOM-viewers from the internet were analyzed and compared. Inclusion criteria for the evaluation were free availability, PACS (picture archiving and communication system)-connectivity, and stand-alone and client-based software. Based on this, eight viewers were found: Ginkgo CADx, Horos, K-PACS, MAYAM, MITO, OsiriX Lite, RadiAnt, Synedra personal. In these DICOM-viewers, 14 core tools were tested and rated on a score from 1 to 10 by multiple observers with different levels of training, using studies of four imaging modalities. Criteria were functionality and user-friendliness. For each viewer, the total number of a predefined set of 47 important tools was counted. The ranking based on functionality and user-friendliness of 14 core tools (mean score in brackets) was as follows: 1. Horos/OsiriX Lite (8.96), 2. RadiAnt (8.90), 3. K-PACS (8.02), 4. Synedra (7.43), 5. MAYAM (6.05), 6. Ginkgo CADx (5.53), 7. MITO (3.74). The DICOM-viewers offered between 20 and 44 tools of the predefined important tool set and are sufficient for most veterinary purposes. An increasing number of tools did not necessarily impair user-friendliness, if the user interface is well designed. Based on the results of this study, veterinarians will find suitable free DICOM-viewers for their individual needs. In combination with PACS-freeware, this allows veterinary practices to run a low-budget digital imaging environment.

Comprehensive Review of 3D Segmentation Software Tools for MRI Usable for Pelvic Surgery Planning

Patient-specific 3D modeling is the first step towards image-guided surgery, the actual revolution in surgical care. Pediatric and adolescent patients with rare tumors and malformations should highly benefit from these latest technological innovations, allowing personalized tailored surgery. This study focused on the pelvic region, located at the crossroads of the urinary, digestive, and genital channels with important vascular and nervous structures. The aim of this study was to evaluate the performances of different software tools to obtain patient-specific 3D models, through segmentation of magnetic resonance images (MRI), the reference for pediatric pelvis examination. Twelve software tools freely available on the Internet and two commercial software tools were evaluated using T2-w MRI and diffusion-weighted MRI images. The software tools were rated according to eight criteria, evaluated by three different users: automatization degree, segmentation time, usability, 3D visualization, presence of image registration tools, tractography tools, supported OS, and potential extension (i.e., plugins). A ranking of software tools for 3D modeling of MRI medical images, according to the set of predefined criteria, was given. This ranking allowed us to elaborate guidelines for the choice of software tools for pelvic surgical planning in pediatric patients. The best-ranked software tools were Myrian Studio, ITK-SNAP, and 3D Slicer, the latter being especially appropriate if nerve fibers should be included in the 3D patient model. To conclude, this study proposed a comprehensive review of software tools for 3D modeling of the pelvis according to a set of eight criteria and delivered specific conclusions for pediatric and adolescent patients that can be directly applied to clinical practice.

Comparison of segmentation software packages for in-hospital 3D print workflow

Purpose: In-hospital three-dimensional (3D) printing of patient-specific pathologies is increasingly being used in daily care. However, the efficiency of the current conversion from image to print is often obstructed due to limitations associated with segmentation software. Therefore, there is a need for comparison of several clinically available tools. A comparative study has been conducted to compare segmentation performance of Philips IntelliSpace Portal^® (PISP), Mimics Innovation Suite (MIS), and DICOM to PRINT^® (D2P). Approach: These tools were compared with respect to segmentation time and 3D mesh quality. The dataset consisted of three computed tomography (CT)-scans of acetabular fractures (ACs), three CT-scans of tibia plateau fractures (TPs), and three CTA-scans of abdominal aortic aneurysms (AAAs). Independent-samples t -tests were performed to compare the measured segmentation times. Furthermore, 3D mesh quality was assessed and compared according to representativeness and usability for the surgeon. Results: Statistically significant differences in segmentation time were found between PISP and MIS with respect to the segmentation of ACs ( p = < 0.001 ) and AAAs ( p = 0.031 ). Furthermore, statistically significant differences in segmentation time were found between PISP and D2P for segmentations of AAAs ( p = 0.008 ). There were no statistically significant differences in segmentation time for TPs. The accumulated mesh quality scores were highest for segmentations performed in MIS, followed by D2P. Conclusion: Based on segmentation time and mesh quality, MIS and D2P are capable of enhancing the in-hospital 3D print workflow. However, they should be integrated with the picture archiving and communication system to truly improve the workflow. In addition, these software packages are not open source and additional costs must be incurred.

Evaluation of Free, Open-source, Web-based DICOM Viewers for the Indian National Telemedicine Service (eSanjeevani)

The Digital Image and Communications in Medicine (DICOM) viewer is a very useful component in telemedicine applications. Owing to increased demand, adoption, and prospects of browser-based software in the recent past, web-based DICOM viewers have gained significant ground. There are myriad web-based DICOM viewers which are open source and are available free of cost as stand-alone applications. These freely available tools have rich functionality like the commercial ones. To find an optimal DICOM viewer for integration with a web-based telemedicine solution is quite a challenge, and no research has gone into assessing these freely available DICOM viewers. This research assessed a range of web-based, open-source, and freely available DICOM viewers from the perspective of their integration with the Indian National Telemedicine Solution (eSanjeevani). To introduce teleradiology module in eSanjeevani, a study is carried out to enable viewing of radiological images through DICOM viewer. eSanjeevani is being prepared for a national roll-out at 155,000 health and wellness centers across rural India by the Ministry of Health and Family Welfare (Government of India) under the Ayushman Bharat Scheme (the world's largest health insurance scheme). In total, 13 free, open-source, and web-based DICOM viewers were identified for evaluation; however, only six were shortlisted as assessed. This study can serve as a one-stop source for researchers looking for a suitable DICOM viewer for their healthcare IT applications.

How many streamlines are required for reliable probabilistic tractography? Solutions for microstructural measurements and neurosurgical planning

Diffusion MRI tractography is commonly used to delineate white matter tracts. These delineations can be used for planning neurosurgery or for identifying regions of interest from which microstructural measurements can be taken. Probabilistic tractography produces different delineations each time it is run, potentially leading to microstructural measurements or anatomical delineations that are not reproducible. Generating a sufficiently large number of streamlines is required to avoid this scenario, but what constitutes "sufficient" is difficult to assess and so streamline counts are typically chosen in an arbitrary or qualitative manner. This work explores several factors influencing tractography reliability and details two methods for estimating this reliability. The first method automatically estimates the number of streamlines required to achieve reliable microstructural measurements, whilst the second estimates the number of streamlines required to achieve a reliable binarised trackmap than can be used clinically. Using these methods, we calculated the number of streamlines required to achieve a range of quantitative reproducibility criteria for three anatomical tracts in 40 Human Connectome Project datasets. Actual reproducibility was checked by repeatedly generating the tractograms with the calculated numbers of streamlines. We found that the required number of streamlines varied strongly by anatomical tract, image resolution, number of diffusion directions, the degree of reliability desired, the microstructural measurement of interest, and/or the specifics on how the tractogram was converted to a binary volume. The proposed methods consistently predicted streamline counts that achieved the target reproducibility. Implementations are made available to enable the scientific community to more-easily achieve reproducible tractography.

Starviewer and its comparison with other open-source DICOM viewers using a novel hierarchical evaluation framework

METHODS

The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible.

RESULTS

Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8).

CONCLUSIONS

Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models.

A Systematic Review of Three-Dimensional Printing in Liver Disease

The purpose of this review is to analyse current literature related to the clinical applications of 3D printed models in liver disease. A search of the literature was conducted to source studies from databases with the aim of determining the applications and feasibility of 3D printed models in liver disease. 3D printed model accuracy and costs associated with 3D printing, the ability to replicate anatomical structures and delineate important characteristics of hepatic tumours, and the potential for 3D printed liver models to guide surgical planning are analysed. Nineteen studies met the selection criteria for inclusion in the analysis. Seventeen of them were case reports and two were original studies. Quantitative assessment measuring the accuracy of 3D printed liver models was analysed in five studies with mean difference between 3D printed models and original source images ranging from 0.2 to 20%. Fifteen studies provided qualitative assessment with results showing the usefulness of 3D printed models when used as clinical tools in preoperative planning, simulation of surgical or interventional procedures, medical education, and training. The cost and time associated with 3D printed liver model production was reported in 11 studies, with costs ranging from US$13 to US$2000, duration of production up to 100 h. This systematic review shows that 3D printed liver models demonstrate hepatic anatomy and tumours with high accuracy. The models can assist with preoperative planning and may be used in the simulation of surgical procedures for the treatment of malignant hepatic tumours.

[Digital OR: better planning and communication]

At the center of digital ENT surgery are four primary technological developments: in addition to the potential of a digitalized operating room (OR), these are modern navigation approaches, planning software, and robotics-based assistance systems. In the OR of the future, not only will data enrichment and information integration play a role, but so will the incorporation of high-tech medical devices. Their use and the information they generate are simplified, while at the same time, further clinical data are optimized before, during, and after the surgical procedure. Specially designed intuitive user interfaces, automated workflows, and advanced imaging techniques allow the full potential of diagnostic, surgical, and postoperative patient data to be exploited. New surgical planning technology helps ENT surgeons to more easily evaluate complex anatomical structures and more accurately and quickly diagnose conditions. Based on an adaptable anatomical software model, a multitude of anatomical structures can be identified and segmented as objects. The high accuracy and consistency of identification of these objects make segmentation an integral part of precise treatment planning. With modern planning software, in 3D patient images, tumors and structures at risk can be accurately contoured, trajectories planned, and CT and MR images fused and subsequently easily accessed in the OR for further use. This serves as a guide during surgery and ultimately results in improved patient safety and more efficient routine clinical workflows.

Advantages and Disadvantages in Image Processing with Free Software in Radiology

Currently, there are sophisticated applications that make it possible to visualize medical images and even to manipulate them. These software applications are of great interest, both from a teaching and a radiological perspective. In addition, some of these applications are known as Free Open Source Software because they are free and the source code is freely available, and therefore it can be easily obtained even on personal computers. Two examples of free open source software are Osirix Lite® and 3D Slicer®. However, this last group of free applications have limitations in its use. For the radiological field, manipulating and post-processing images is increasingly important. Consequently, sophisticated computing tools that combine software and hardware to process medical images are needed. In radiology, graphic workstations allow their users to process, review, analyse, communicate and exchange multidimensional digital images acquired with different image-capturing radiological devices. These radiological devices are basically CT (Computerised Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), etc. Nevertheless, the programs included in these workstations have a high cost which always depends on the software provider and is always subject to its norms and requirements. With this study, we aim to present the advantages and disadvantages of these radiological image visualization systems in the advanced management of radiological studies. We will compare the features of the VITREA2® and AW VolumeShare 5® radiology workstation with free open source software applications like OsiriX® and 3D Slicer®, with examples from specific studies.

Content Validity of Temporal Bone Models Printed Via Inexpensive Methods and Materials

HYPOTHESIS

Computed tomographic (CT) scans of the 3-D printed temporal bone models will be within 15% accuracy of the CT scans of the cadaveric temporal bones.

BACKGROUND

Previous studies have evaluated the face validity of 3-D-printed temporal bone models designed to train otolaryngology residents. The purpose of the study was to determine the content validity of temporal bone models printed using inexpensive printers and materials.

METHODS

Four cadaveric temporal bones were randomly selected and clinical temporal bone CT scans were obtained. Models were generated using previously described methods in acrylonitrile butadiene styrene (ABS) plastic using the Makerbot Replicator 2× and Hyrel printers. Models were radiographically scanned using the same protocol as the cadaveric bones. Four images from each cadaveric CT series and four corresponding images from the model CT series were selected, and voxel values were normalized to black or white. Scan slices were compared using PixelDiff software. Gross anatomic structures were evaluated in the model scans by four board certified otolaryngologists on a 4-point scale.

RESULTS

Mean pixel difference between the cadaver and model scans was 14.25 ± 2.30% at the four selected CT slices. Mean cortical bone width difference and mean external auditory canal width difference were 0.58 ± 0.66 mm and 0.55 ± 0.46 mm, respectively. Expert raters felt the mastoid air cells were well represented (2.5 ± 0.5), while middle ear and otic capsule structures were not accurately rendered (all averaged <1.8).

CONCLUSION

These results suggest that these models would be sufficient adjuncts to cadaver temporal bones for training residents in cortical mastoidectomies, but less effective for middle ear procedures.

A Survey of DICOM Viewer Software to Integrate Clinical Research and Medical Imaging

The digital imaging and communications in medicine (DICOM) protocol is the leading standard for image data management in healthcare. Imaging biomarkers and image-based surrogate endpoints in clinical trials and medical registries require DICOM viewer software with advanced functionality for visualization and interfaces for integration. In this paper, a comprehensive evaluation of 28 DICOM viewers is performed. The evaluation criteria are obtained from application scenarios in clinical research rather than patient care. They include (i) platform, (ii) interface, (iii) support, (iv) two-dimensional (2D), and (v) three-dimensional (3D) viewing. On the average, 4.48 and 1.43 of overall 8 2D and 5 3D image viewing criteria are satisfied, respectively. Suitable DICOM interfaces for central viewing in hospitals are provided by GingkoCADx, MIPAV, and OsiriX Lite. The viewers ImageJ, MicroView, MIPAV, and OsiriX Lite offer all included 3D-rendering features for advanced viewing. Interfaces needed for decentral viewing in web-based systems are offered by Oviyam, Weasis, and Xero. Focusing on open source components, MIPAV is the best candidate for 3D imaging as well as DICOM communication. Weasis is superior for workflow optimization in clinical trials. Our evaluation shows that advanced visualization and suitable interfaces can also be found in the open source field and not only in commercial products.

Automating Perforator Flap MRA and CTA Reporting

Surgical breast reconstruction after mastectomy requires precise perforator coordinates/dimensions, perforator course, and fat volume in a radiology report. Automatic perforator reporting software was implemented as an OsiriX Digital Imaging and Communications in Medicine (DICOM) viewer plugin. For perforator analysis, the user identifies a reference point (e.g., umbilicus) and marks each perforating artery/vein bundle with multiple region of interest (ROI) points along its course beginning at the muscle-fat interface. Computations using these points and analysis of image data produce content for the report. Post-processing times were compared against conventional/manual methods using de-identified images of 26 patients with surgically confirmed accuracy of perforator locations and caliber. The time from loading source images to completion of report was measured. Significance of differences in mean processing times for this automated approach versus the conventional/manual approach was assessed using a paired t test. The mean conventional reporting time for our radiologists was 76 ± 27 min (median 65 min) compared with 25 ± 6 min (median 25 min) using our OsiriX plugin (p < 0.01). The conventional approach had three reports with transcription errors compared to none with the OsiriX plugin. Otherwise, the reports were similar. In conclusion, automated reporting of perforator magnetic resonance angiography (MRA) studies is faster compared with the standard, manual approach, and transcription errors which are eliminated.

Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images

The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images.