3D Technique Research Articles

3D Amplified Single-Cell RNA and Protein Imaging Identifies Oncogenic Transcript Subtypes in B-Cell Acute Lymphoblastic Leukemia.

Simultaneous in situ detection of transcript and protein markers at the single-cell level is essential for gaining a better understanding of tumor heterogeneity and for predicting and monitoring treatment responses. However, the limited accessibility to advanced 3D imaging techniques has hindered their rapid implementation. Here, we present a 3D single-cell imaging technique, termed 3D digital rolling circle amplification (4DRCA), capable of the multiplexed and amplified simultaneous digital quantification of single-cell RNAs and proteins using standard fluorescence microscopy and off-the-shelf reagents. We generated spectrally distinguishable DNA amplicons from molecular markers through an integrative protocol combining single-cell RNA and protein assays and directly enumerated the amplicons by leveraging an open-source algorithm for 3D deconvolution with a custom-built automatic gating algorithm. With 4DRCA, we were able to simultaneously quantify surface protein markers and cytokine transcripts in T-lymphocytes. We also show that 4DRCA can distinguish BCR-ABL1 fusion transcript positive B-cell acute lymphoblastic leukemia cells with or without CD19 protein expression. The accessibility and extensibility of 4DRCA render it broadly applicable to other cell-based diagnostic workflows, enabling sensitive and accurate single-cell RNA and protein profiling.

(117) Interrater Agreement and Feasibility of Three-Dimensional Photography for Curvature Assessment in Peyronie's Disease

Abstract Introduction Curvature assessment is an iterative aspect of the evaluation of Peyronie’s Disease (PD); its accuracy is subject to patient erection quality and clinician technique. Prior studies have shown promising results when using 3D modeling software in curvature assessment, yet none have applied the technology to human subjects with complex PD in an authentic clinical scenario. Objective To evaluate the feasibility of using 3D modeling to assess penile deformity in PD patients. Methods MirrorMe3D is a HIPPA-compliant iOS mobile and web-based platform designed for 3D anatomical modeling. 2 trained urology fellows (coders 1 and 2) were trained to create models using the app by acquiring ≥ 12 images of the target obtained in a multiplanar, 360-degree fashion. Participants verbally consented to deidentified penile photography during their clinic visit for penile curvature assessment with Doppler ultrasound (CADUS). Photographs were obtained prior to performing DUS with the patient in the supine position and using a commercially available clip-on ring light and custom 3D-printed holder device placed over the penis base for stabilization. 3D models were generated upon completion of the visit and screened for quality. Curvature assessment on the 3D images included curvature direction, location, degrees, and other defects identified via visual inspection of the digital model. Results 7 unique, quality 3D images were generated using 15-20 photos per participant (Figure 1). The time required to obtain images was 1-2 minutes. Once the 3D image was developed, the curvature assessment took about 5 minutes. Quantitative results are summarized in Table 1. We observed a high rate of agreement in terms of primary direction of curvature and an acceptable variance rate when evaluating degrees of curvature within a margin of 10°; of note, coders were in agreement with each other to within a 10° margin 100% of the time (7/7 patients). We also observed a high agreement rate when evaluating the presence of absence of tapering but low agreement when assessing for the presence of indentation and hourglass deformity. Regarding the penis stabilizer, our experience suggests that it may alter the base of the penis anatomy, but it improves capture of the organ with diminished interference from surrounding anatomy (scrotum, abdomen). Factors influencing the quality of the image were exam room set-up, patient anxiety about losing an erection, lighting, and body hair. Conclusions 3D image-based PD assessment can be implemented with minimal impact to visit efficiency. The 3D technique does not appear to reproduce complex PD measurements obtained by CADUS; however, future studies will evaluate the utility of employing this technology to a larger cohort and also to monitor treatment effect in complex PD patients. Disclosure No.

Fabrication Method for Shape-Controlled 3D Tissue Using High-Porosity Porous Structure.

Shape-controlled 3D tissues resemble natural living tissues in human and animal bodies and are essential materials for developing and improving technologies in regenerative medicine, drug discovery, and biological robotics. In previous studies, shape-controlled 3D tissues were fabricated using scaffold structures or 3D bioprinting techniques. However, controlling the shape of 3D tissues without leaving non-natural materials inside the 3D tissue and efficiently fabricating them remains challenging. In this paper, we propose a novel method for fabricating shape-controlled 3D tissues free of non-natural materials using a flexible high-porosity porous structure (HPPS). The HPPS consisted of a micromesh with pore sizes of 14.87 ± 1.83 μm, lattice widths of 2.24 ± 0.10 μm, thicknesses of 9.96 ± 0.92 μm, porosity of 69.06 ± 3.30%, and an I-shaped microchamber of depth 555.26 ± 11.17 μm. U-87 human glioma cells were cultured in an I-shaped HPPS microchamber for 48 h. After cultivation, the 3D tissue was released within a few seconds while maintaining its I-shape. Specific chemicals, such as proteolytic enzymes, were not used. Moreover, the viability of the released cells composed of shape-controlled 3D tissues free of non-natural materials was above 90%. Therefore, the proposed fabrication method is recommended for shape-controlled 3D tissues free of non-natural materials without applying significant stresses to the cells.

Selection as Tapping: An evaluation of 3D input techniques for timing tasks in musical Virtual Reality

While numerous studies have examined 3D interaction techniques for Virtual Reality (VR) across various tasks and scenarios, limited research has focused on music-related applications. However, the most common input techniques in consumer VR systems have been developed outside of the musical domain. Therefore they have not been tested in tasks where synchronization with auditory stimuli and timing plays a crucial role. There is a lack of empirical knowledge about performance and user experience. This paper presents a comparison of five selection input techniques for VR employing the tapping paradigm commonly utilized in the research on sensorimotor synchronization. We assess asynchrony and timing variance as well as user experience, encompassing factors such as ease of use, workload, and cybersickness of such techniques. The study involved 30 participants, both with and without musical expertise, and encompassed the examination of all techniques using one and two hands. Our analysis yielded several key findings: (1) different input techniques yielded distinct outcomes regarding timing asynchrony and variance; (2) the choice of interaction metaphor significantly influenced the user experience; (3) tracking stability emerged as a critical factor. Building upon these insights, we identified essential considerations for selecting the most suitable technique for music creation in VR and proposed design guidelines and future research directions in this domain.

Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images

Detection of abnormalities within the inner ear is a challenging task even for experienced clinicians. In this study, we propose an automated method for automatic abnormality detection to provide support for the diagnosis and clinical management of various otological disorders. We propose a framework for inner ear abnormality detection based on deep reinforcement learning for landmark detection which is trained uniquely in normative data. In our approach, we derive two abnormality measurements: Dimage and Uimage. The first measurement, Dimage, is based on the variability of the predicted configuration of a well-defined set of landmarks in a subspace formed by the point distribution model of the location of those landmarks in normative data. We create this subspace using Procrustes shape alignment and Principal Component Analysis projection. The second measurement, Uimage, represents the degree of hesitation of the agents when approaching the final location of the landmarks and is based on the distribution of the predicted Q-values of the model for the last ten states. Finally, we unify these measurements in a combined anomaly measurement called Cimage. We compare our method’s performance with a 3D convolutional autoencoder technique for abnormality detection using the patch-based mean squared error between the original and the generated image as a basis for classifying abnormal versus normal anatomies. We compare both approaches and show that our method, based on deep reinforcement learning, shows better detection performance for abnormal anatomies on both an artificial and a real clinical CT dataset of various inner ear malformations with an increase of 11.2% of the area under the ROC curve. Our method also shows more robustness against the heterogeneous quality of the images in our dataset.

Microinstrumentation for Brain Organoids.

Brain organoids are three-dimensional aggregates of self-organized differentiated stem cells that mimic the structure and function of human brain regions. Organoids bridge the gaps between conventional drug screening models such as planar mammalian cell culture, animal studies, and clinical trials. They can revolutionize the fields of developmental biology, neuroscience, toxicology, and computer engineering. Conventional microinstrumentation for conventional cellular engineering, such as planar microfluidic chips; microelectrode arrays (MEAs); and optical, magnetic, and acoustic techniques, has limitations when applied to three-dimensional (3D) organoids, primarily due to their limits with inherently two-dimensional geometry and interfacing. Hence, there is an urgent need to develop new instrumentation compatible with live cell culture techniques and with scalable 3D formats relevant to organoids. This review discusses conventional planar approaches and emerging 3D microinstrumentation necessary for advanced organoid-machine interfaces. Specifically, this article surveys recently developed microinstrumentation, including 3D printed and curved microfluidics, 3D and fast-scan optical techniques, buckling and self-folding MEAs, 3D interfaces for electrochemical measurements, and 3D spatially controllable magnetic and acoustic technologies relevant to two-way information transfer with brain organoids. This article highlights key challenges that must be addressed for robust organoid culture and reliable 3D spatiotemporal information transfer.

A comparative study of boost dose delivery techniques in breast cancer radiotherapy optimising efficacy and minimising toxicity.

The present study aims to compare three techniques for delivering a boost absorbed dose: conventional reduced tangential (3D), volumetric modulated arc therapy (VMAT) and fields forward-planned technique boost (3DF). The study included 15 postoperative breast cancer patients who received a boost absorbed dose following breast-conserving surgery. The conformity index and homogeneity index were used to evaluate treatment outcomes, along with the average absorbed dose received by organs at risk (OAR). All the calculated dosimetric plans are carried out using Monaco Treatment Planning System (TPS). VMAT offers superior conformity, dose homogeneity and target coverage, it is associated with higher absorbed doses to OAR such as the heart and lung. In contrast, the 3D and 3DF techniques exhibit advantages in reducing absorbed doses to critical structures, potentially minimising the risk of cardiac and pulmonary complications. Each technique has its advantages and disadvantages. The choice of technique should be individualised, taking into account patient-specific factors and treatment goals and involves a multidisciplinary approach.

Designing a 3D gestural interface to support user interaction with time-oriented data as immersive 3D radar charts

The design of intuitive three-dimensional user interfaces is vital for interaction in virtual reality, allowing to effectively close the loop between a human user and the virtual environment. The utilization of 3D gestural input allows for useful hand interaction with virtual content by directly grasping visible objects, or through invisible gestural commands that are associated with corresponding features in the immersive 3D space. The design of such interfaces remains complex and challenging. In this article, we present a design approach for a three-dimensional user interface using 3D gestural input with the aim to facilitate user interaction within the context of Immersive Analytics. Based on a scenario of exploring time-oriented data in immersive virtual reality using 3D Radar Charts, we implemented a rich set of features that is closely aligned with relevant 3D interaction techniques, data analysis tasks, and aspects of hand posture comfort. We conducted an empirical evaluation (n=12)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(n=12)$$\\end{document}, featuring a series of representative tasks to evaluate the developed user interface design prototype. The results, based on questionnaires, observations, and interviews, indicate good usability and an engaging user experience. We are able to reflect on the implemented hand-based grasping and gestural command techniques, identifying aspects for improvement in regard to hand detection and precision as well as emphasizing a prototype’s ability to infer user intent for better prevention of unintentional gestures.

Automatic Vertebral Rotation Angle Measurement of 3D Vertebrae Based on an Improved Transformer Network.

The measurement of vertebral rotation angles serves as a crucial parameter in spinal assessments, particularly in understanding conditions such as idiopathic scoliosis. Historically, these angles were calculated from 2D CT images. However, such 2D techniques fail to comprehensively capture the intricate three-dimensional deformities inherent in spinal curvatures. To overcome the limitations of manual measurements and 2D imaging, we introduce an entirely automated approach for quantifying vertebral rotation angles using a three-dimensional vertebral model. Our method involves refining a point cloud segmentation network based on a transformer architecture. This enhanced network segments the three-dimensional vertebral point cloud, allowing for accurate measurement of vertebral rotation angles. In contrast to conventional network methodologies, our approach exhibits notable improvements in segmenting vertebral datasets. To validate our approach, we compare our automated measurements with angles derived from prevalent manual labeling techniques. The analysis, conducted through Bland-Altman plots and the corresponding intraclass correlation coefficient results, indicates significant agreement between our automated measurement method and manual measurements. The observed high intraclass correlation coefficients (ranging from 0.980 to 0.993) further underscore the reliability of our automated measurement process. Consequently, our proposed method demonstrates substantial potential for clinical applications, showcasing its capacity to provide accurate and efficient vertebral rotation angle measurements.

Quantitative Skeletal Imaging and Image-Based Modeling in Pediatric Orthopaedics.

Musculoskeletal imaging serves a critical role in clinical care and orthopaedic research. Image-based modeling is also gaining traction as a useful tool in understanding skeletal morphology and mechanics. However, there are fewer studies on advanced imaging and modeling in pediatric populations. The purpose of this review is to provide an overview of recent literature on skeletal imaging modalities and modeling techniques with a special emphasis on current and future uses in pediatric research and clinical care. While many principles of imaging and 3D modeling are relevant across the lifespan, there are special considerations for pediatric musculoskeletal imaging and fewer studies of 3D skeletal modeling in pediatric populations. Improved understanding of bone morphology and growth during childhood in healthy and pathologic patients may provide new insight into the pathophysiology of pediatric-onset skeletal diseases and the biomechanics of bone development. Clinical translation of 3D modeling tools developed in orthopaedic research is limited by the requirement for manual image segmentation and the resources needed for segmentation, modeling, and analysis. This paper highlights the current and future uses of common musculoskeletal imaging modalities and 3D modeling techniques in pediatric orthopaedic clinical care and research.

3D visualization and printing: An "Anatomical Engineering" trend revealing underlying morphology via innovation and reconstruction towards future of veterinary anatomy.

The amalgamation of veterinary anatomy, technology and innovation has led to development of latest technological advancement in the field of veterinary medicine, i.e., three-dimensional (3D) imaging and reconstruction. 3D visualization technique followed by 3D reconstruction has been proven to enhance non-destructive 3D visualization grossly or microscopically, e.g., skeletal muscle, smooth muscle, ligaments, cartilage, connective tissue, blood vessels, nerves, lymph nodes, and glands. The core aim of this manuscript is to document non-invasive 3D visualization methods being adopted currently in veterinary anatomy to reveal underlying morphology and to reconstruct them by 3D softwares followed by printing, its applications, current challenges, trends and future opportunities. 3D visualization methods such as MRI, CT scans and micro-CT scans are utilised in revealing volumetric data and underlying morphology at microscopic levels as well. This will pave a way to transform and re-invent the future of teaching in veterinary medicine, in clinical cases as well as in exploring wildlife anatomy. This review provides novel insights into 3D visualization and printing as it is the future of veterinary anatomy, thus making it spread to become the plethora of opportunities for whole veterinary science.

Virtual registration of comminuted bone fracture and preoperative assessment of reconstructed bone model using the Procrustes algorithm based on CT dataset.

A research work was undergone in a virtual bone reduction process for reconstruction of the comminuted pelvic bone fracture using a CT scan dataset of patients. This includes segmentation, 3D model optimization and bone registration technique. The accuracy of the reconstructed bone model was validated using Finite Element Method. Analysed and applied various segmentation techniques to segregate the injured bone structure. The ICP (Iterative Closest Point), Procrustes algorithm and Canny edge detection algorithm were applied to understand the bone registration process for surgery in detail. The average RMS error, mean absolute distance, mean absolute deviation, and mean signed distance of the reconstructed bone model using proposed algorithms involving 10 patient datasets in a group were found to be 1.77, 1.48, 1.51 and -0.31 mm respectively. The calculated RMS error value proved minimal error in semi-automatic registration than other existing automatic registration techniques. Therefore, the proposed approach is suitable for virtual bone reduction for comminuted pelvic bone fracture. This method could also be implemented for various other bone fracture reconstruction requirements.

Generation of Self-Induced Myocardial Ischemia in Large-Sized Cardiac Spheroids without Alteration of Environmental Conditions Recreates Fibrotic Remodeling and Tissue Stiffening Revealed by Constriction Assays.

A combination of human-induced pluripotent stem cells (hiPSCs) and 3D microtissue culture techniques allows the generation of models that recapitulate the cardiac microenvironment for preclinical research of new treatments. In particular, spheroids represent the simplest approach to culture cells in 3D and generate gradients of cellular access to the media, mimicking the effects of an ischemic event. However, previous models required incubation under low oxygen conditions or deprived nutrient media to recreate ischemia. Here, we describe the generation of large spheroids (i.e., larger than 500 μm diameter) that self-induce an ischemic core. Spheroids were generated by coculture of cardiomyocytes derived from hiPSCs (hiPSC-CMs) and primary human cardiac fibroblast (hCF). In the proper medium, cells formed aggregates that generated an ischemic core 2 days after seeding. Spheroids also showed spontaneous cellular reorganization after 10 days, with hiPSC-CMs located at the center and surrounded by hCFs. This led to an increase in microtissue stiffness, characterized by the implementation of a constriction assay. All in all, these phenomena are hints of the fibrotic tissue remodeling secondary to a cardiac ischemic event, thus demonstrating the suitability of these spheroids for the modeling of human cardiac ischemia and its potential application for new treatments and drug research.

Estimation of Geotechnical Parameters for Coal Exploration from Quasi-3D Electrical Resistivity Measurements

Geotechnical parameters are crucial for mine planning and operation at different stages of development. However, estimating these parameters requires a large number of boreholes and subsequent detailed analysis of the samples, making it a cumbersome exercise. Moreover, even after conducting these studies, it is not possible to cover the entire operational area. To address this issue, this study presents an indirect method of estimating geotechnical parameters through mathematical relations using resistivity data. The present study incorporated 2D and 3D subsurface imaging techniques for exploring coal reserves and analyzing geotechnical parameters that define subsurface soil properties. Electrical resistivity tomography (ERT) was utilized for data acquisition, employing a Dipole–dipole array with a multielectrode ABEM Terrameter LS instrument. Six parallel profiles were conducted, each 400 m in length, with an inter-electrode spacing of 10 m and a spacing of 50 m between profiles. These profiles were combined into a 3D dataset referred to as quasi-3D ERT. The inversion process for both 2D and 3D data was performed using the Res2dinv and Res3dinv programs, respectively. This study overcame the challenges of 2D resistivity sections by evaluating horizontal depth slices in the x-z plane from layers 1 to 10, reaching a depth of 81.2 m. The geotechnical parameters, including cohesion, friction angle, moisture content, and plastic index, were derived from the resistivity data. The ERT method proved to be cost-effective and efficient in determining soil properties over a large area compared with traditional laboratory analysis of borehole samples. Additionally, the variation of geotechnical parameters with resistivity values exhibited unique characteristics. The results from both the 2D and quasi-3D ERT were well correlated with the borehole data. Such studies are valuable for resource exploration and mine planning purposes.

Reconstruction of synthetic aperture radar data using hybrid compressive sensing and deep neural network algorithm

SummaryThe reconstruction of reflectivity profile of the synthetic aperture radar (SAR) is an important field of research. SAR tomography is an advanced 3D imaging technique for the spectrum estimation in the elevation direction for each azimuth resolution cell. This work presents the processing chain for the tomographic reconstruction from ALOS PALSAR data for an urban region. First, the data are preprocessed by removing the speckle noise followed by atmospheric phase screen and topographic correction. Then the SAR images are stacked together with one master image and the remaining slave images on the baseline value. After the images are coregistered, the interferogram is generated from the image to obtain the difference of the phase value. Then the proposed super resolution SAR (SRS) algorithm is attempted for TomoSAR processing, which combines the functionality of modern machine learning method like deep learning with parametric block‐based compressive sensing approach. Finally, a 3D image is reconstructed from the input data. Evaluation is carried out by comparing the results of the proposed method with other spectrum estimation methods such as nonlinear least square, Capon, and multisignal classification. The normal baseline of the interferometric fringes is about 368.54 m. The proposed SRS algorithm gives improved results with less mean elevation error of 1.8 m and the less standard deviation error of 4.85 m. Finally, the result reveals that the SRS algorithm performed better than other TomoSAR algorithms with the less relative error 0.003.

The Perception of Depth and Form in Fine Arts, Video Games and Medicine.

Medical imaging technology has greatly improved over the last 40 years. A good example of this is the improved 3D reconstruction capabilities of CTs, which enable photorealistic reconstructions. This technological advancement has also taken place in the computer industry, and the development of modern graphics cards has fueled progress in video games. In art, many of the techniques used to improve three-dimensionality have been known for centuries. At first sight, these fields seem unrelated, but there is actually considerable confluence. This paper focuses on three areas: fine arts, video games and radiology. The art section illustrates different drawing techniques used to create three-dimensionality. The section on video games shows the development of video games from the 1980s to the present day. Finally, the medical imaging section focuses on the first 3D radiography reconstructions in the 1980s and the improvements to the present day. Contemporary video games and 3D reconstructions of CTs enable photorealistic impressions of 3D anatomical structures. An important factor is shadow casting and light, which has been known in fine arts for centuries. The effect on the observer of photorealistic 3D reconstructions in video games and in medical imaging can be largely explained by the knowledge of 3D techniques in drawings and paintings.

High-Voltage Electrostatic Field Hydrogel Microsphere 3D Culture System Improves Viability and Liver-like Properties of HepG2 Cells.

Three-dimensional (3D) hepatocyte models have become a research hotspot for evaluating drug metabolism and hepatotoxicity. Compared to two-dimensional (2D) cultures, 3D cultures are better at mimicking the morphology and microenvironment of hepatocytes in vivo. However, commonly used 3D culture techniques are not suitable for high-throughput drug screening (HTS) due to their high cost, complex handling, and inability to simulate cell-extracellular matrix (ECM) interactions. This article describes a method for rapid and reproducible 3D cell cultures with ECM-cell interactions based on 3D culture instrumentation to provide more efficient HTS. We developed a microsphere preparation based on a high-voltage electrostatic (HVE) field and used sodium alginate- and collagen-based hydrogels as scaffolds for 3D cultures of HepG2 cells. The microsphere-generating device enables the rapid and reproducible preparation of bioactive hydrogel microspheres. This 3D culture system exhibited better cell viability, heterogeneity, and drug-metabolizing activity than 2D and other 3D culture models, and the long-term culture characteristics of this system make it suitable for predicting long-term liver toxicity. This system improves the overall applicability of HepG2 spheroids in safety assessment studies, and this simple and controllable high-throughput-compatible method shows potential for use in drug toxicity screening assays and mechanistic studies.

Ray tracing-based construction of 3D background model for real-time stereoscopic rendering of live immersive video

Immersive video stored in multiview video-plus-depth format can provide viewers with vivid immersive experiences. However, rendering such video in real time in immersive environments remains a challenging task due to the high resolution and refresh rate demanded by recent extended reality displays. An essential issue in this immersive rendering is the disocclusion problem that inevitably occurs when virtual views are synthesized via the de facto standard 3D warping technique. In this paper, we present a novel virtual view synthesis framework that, from a live immersive video stream, renders stereoscopic images in real time for a freely moving virtual viewer. The main difference from previous approaches is that the surrounding background environment of the immersive video’s virtual scene is progressively reproduced on the fly directly in the 3D space while the input stream is being rendered. To allow this, we propose a new 3D background modeling scheme that, based on GPU-accelerated real-time ray tracing, efficiently and incrementally builds the background model in compact 3D triangular mesh. Then, we demonstrate that the 3D background environment can effectively alleviate the critical disocclusion problem in the immersive rendering, eventually reducing spatial and temporal aliasing artifacts. It is also suggested that the 3D representation of background environment enables extension of the virtual environment of immersive video by interactively adding 3D visual effects during rendering.

Beyond Reality: Exploring the effect of different virtual reality environments on visual assessment of cakes

Visual assessment triggers physiological, emotional, and cognitive responses in consumer behavior. This confluence of signals can be influenced by context, which plays a crucial role in eating behavior. The strategies used to evoke scenarios that enhance ecological validity in sensory experiences have evolved in the last years to include immersive technologies and virtual reality (VR) to simulate the complexity of the real world and predict consumer preferences. This study explored VR's effect on visual liking and hedonic responses of five virtual cakes in two virtual contexts designed with advanced 3D modeling and photogrammetry techniques to ensure high realism and immersion. Although the virtual contexts themselves did not impact liking ratings, the variables “context-cake,“ ”age,“ and “subjective hunger” had a significant effect on the visual liking of cakes. A Check-All-That-Apply (CATA) questionnaire showed significant differences in responses for various terms related to the intrinsic and extrinsic characteristics of the five cakes. Finally, the internal preference map separated two consumer patterns of visual liking: traditional versus innovative.

General Algorithm Applicability in Determining DBS Lead Orientation: Adapting 2D and 3D X-Ray Techniques for SenSightTM Leads

Introduction: With recent advancements in deep brain stimulation (DBS), directional leads featuring segmented contacts have been introduced, allowing for targeted stimulation of specific brain regions. Given that manufacturers employ diverse markers for lead orientation, our investigation focuses on the adaptability of the 2017 techniques proposed by the Cologne research group for lead orientation determination. Methods: We tailored the two separate 2D and 3D X-ray-based techniques published in 2017 and originally developed for C-shaped markers, to the dual-marker of the Medtronic SenSight™ lead. In a retrospective patient study, we evaluated their feasibility and consistency by comparing the degree of agreement between the two methods. Results: The Bland-Altman plot showed favorable concordance without any noticeable systematic errors. The mean difference was 0.79°, with limits of agreement spanning from 21.4° to −19.8°. The algorithms demonstrated high reliability, evidenced by an intraclass correlation coefficient of 0.99 (p < 0.001). Conclusion: The 2D and 3D algorithms, initially formulated for discerning the circular orientation of a C-shaped marker, were adapted to the marker of the Medtronic SenSight™ lead. Statistical analyses revealed a significant level of agreement between the two methods. Our findings highlight the adaptability of these algorithms to different markers, achievable through both low-dose intraoperative 2D X-ray imaging and standard CT imaging.