scholarly journals A novel approach to 3D bone creation in minutes

2021 ◽  
Vol 103-B (6 Supple A) ◽  
pp. 81-86
Author(s):  
Mohamed R. Mahfouz ◽  
Emam E. Abdel Fatah ◽  
J. Michael Johnson ◽  
Richard D. Komistek
Keyword(s):  
Preoperative Planning ◽  
Mean Squared Error ◽  
Imaging Modality ◽  
Point Clouds ◽  
Patient Specific ◽  
Time Signal ◽  
Navigation Systems ◽  
3D Tracking ◽  
Transepicondylar Axis ◽  
The Us

Aims The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty. Methods Using an US system, which is fitted with an electromagnetic (EM) tracker that is integrated into the US probe, allows 3D tracking of the probe, femur, and tibia. The raw US radiofrequency (RF) signals are acquired and, using real-time signal processing, bone boundaries are extracted. Bone boundaries and the tracking information are fused in a 3D point cloud for the femur and tibia. Using a statistical shaping model, the patient-specific surface is reconstructed by optimizing bone geometry to match the point clouds. An accuracy analysis was conducted for 17 cadavers by comparing the 3D US models with those created using CT. US scans from 15 users were compared in order to examine the effect of operator variability on the output. Results The results revealed that the US bone models were accurate compared with the CT models (root mean squared error (RM)S: femur, 1.07 mm (SD 0.15); tibia, 1.02 mm (SD 0.13). Additionally, femoral landmarking proved to be accurate (transepicondylar axis: 1.07° (SD 0.65°); posterior condylar axis: 0.73° (SD 0.41°); distal condylar axis: 0.96° (SD 0.89°); medial anteroposterior (AP): 1.22 mm (SD 0.69); lateral AP: 1.21 mm (SD 1.02)). Tibial landmarking errors were slightly higher (posterior slope axis: 1.92° (SD 1.31°); and tubercle axis: 1.91° (SD 1.24°)). For implant sizing, 90% of the femora and 60% of the tibiae were sized correctly, while the remainder were only one size different from the required implant size. No difference was observed between moderate and skilled users. Conclusion The 3D US bone models were proven to be closely matched compared with CT and suitable for preoperative planning. The 3D US is radiation-free and offers numerous clinical opportunities for bone visualization rapidly during clinic visits, to enable preoperative planning with implant sizing. There is potential to extend its application to 3D dynamic ligament balancing, and intraoperative registration for use with robots and navigation systems. Cite this article: Bone Joint J 2021;103-B(6 Supple A):81–86.

Full tractography for detecting the position of cranial nerves in preoperative planning for skull base surgery: technical note

2020 ◽  
Vol 132 (5) ◽  
pp. 1642-1652 ◽  
Author(s):  
Timothee Jacquesson ◽  
Fang-Chang Yeh ◽  
Sandip Panesar ◽  
Jessica Barrios ◽  
Arnaud Attyé ◽  
...  
Keyword(s):  
Skull Base ◽  
Preoperative Planning ◽  
Skull Base Surgery ◽  
Cranial Nerves ◽  
Patient Specific ◽  
Small Scale ◽  
Skull Base Tumor ◽  
Skull Base Tumors ◽  
Brain White Matter ◽  
Human Connectome Project

OBJECTIVEDiffusion imaging tractography has allowed the in vivo description of brain white matter. One of its applications is preoperative planning for brain tumor resection. Due to a limited spatial and angular resolution, it is difficult for fiber tracking to delineate fiber crossing areas and small-scale structures, in particular brainstem tracts and cranial nerves. New methods are being developed but these involve extensive multistep tractography pipelines including the patient-specific design of multiple regions of interest (ROIs). The authors propose a new practical full tractography method that could be implemented in routine presurgical planning for skull base surgery.METHODSA Philips MRI machine provided diffusion-weighted and anatomical sequences for 2 healthy volunteers and 2 skull base tumor patients. Tractography of the full brainstem, the cerebellum, and cranial nerves was performed using the software DSI Studio, generalized-q-sampling reconstruction, orientation distribution function (ODF) of fibers, and a quantitative anisotropy–based generalized deterministic algorithm. No ROI or extensive manual filtering of spurious fibers was used. Tractography rendering was displayed in a tridimensional space with directional color code. This approach was also tested on diffusion data from the Human Connectome Project (HCP) database.RESULTSThe brainstem, the cerebellum, and the cisternal segments of most cranial nerves were depicted in all participants. In cases of skull base tumors, the tridimensional rendering permitted the visualization of the whole anatomical environment and cranial nerve displacement, thus helping the surgical strategy.CONCLUSIONSAs opposed to classical ROI-based methods, this novel full tractography approach could enable routine enhanced surgical planning or brain imaging for skull base tumors.

scholarly journals Demographics associated with US healthcare disparities are exacerbated by the telemedicine surge during the COVID-19 pandemic

2021 ◽  
pp. 1357633X2110259
Author(s):  
Kristin N Gmunder ◽  
Jose W Ruiz ◽  
Dido Franceschi ◽  
Maritza M Suarez
Keyword(s):  
Income Tax ◽  
Healthcare Disparities ◽  
Descriptive Statistics ◽  
Internal Revenue Service ◽  
Patient Specific ◽  
Postal Code ◽  
The Us ◽  
Hispanic Patients ◽  
The Impact ◽  
Racial Ethnic

Introduction As coronavirus disease 2019 (COVID-19) hit the US, there was widespread and urgent implementation of telemedicine programs nationwide without much focus on the impact on patient populations with known existing healthcare disparities. To better understand which populations cannot access telemedicine during the coronavirus disease 2019 pandemic, this study aims to demographically describe and identify the most important demographic predictors of telemedicine visit completion in an urban health system. Methods Patient de-identified demographics and telemedicine visit data ( N = 362,764) between March 1, 2020 and October 31, 2020 were combined with Internal Revenue Service 2018 individual income tax data by postal code. Descriptive statistics and mixed effects logistic regression were used to determine impactful patient predictors of telemedicine completion, while adjusting for clustering at the clinical site level. Results Many patient-specific demographics were found to be significant. Descriptive statistics showed older patients had lower rates of completion ( p < 0.001). Also, Hispanic patients had statistically significant lower rates ( p < 0.001). Overall, minorities (racial, ethnic, and language) had decreased odds ratios of successful telemedicine completion compared to the reference. Discussion While telemedicine use continues to be critical during the coronavirus disease 2019 pandemic, entire populations struggle with access—possibly widening existing disparities. These results contribute large datasets with significant findings to the limited research on telemedicine access and can help guide us in improving telemedicine disparities across our health systems and on a wider scale.

scholarly journals CNN-BASED PLACE RECOGNITION TECHNIQUE FOR LIDAR SLAM

2020 ◽  
Vol XLIV-M-2-2020 ◽  
pp. 117-122
Author(s):  
Y. Yang ◽  
S. Song ◽  
C. Toth
Keyword(s):  
Urban Areas ◽  
Recognition Task ◽  
Dead Reckoning ◽  
Point Clouds ◽  
Navigation Systems ◽  
Place Recognition ◽  
3D Point Clouds ◽  
Localization And Mapping ◽  
Sensing Platform ◽  
3D Descriptors

Abstract. Place recognition or loop closure is a technique to recognize landmarks and/or scenes visited by a mobile sensing platform previously in an area. The technique is a key function for robustly practicing Simultaneous Localization and Mapping (SLAM) in any environment, including the global positioning system (GPS) denied environment by enabling to perform the global optimization to compensate the drift of dead-reckoning navigation systems. Place recognition in 3D point clouds is a challenging task which is traditionally handled with the aid of other sensors, such as camera and GPS. Unfortunately, visual place recognition techniques may be impacted by changes in illumination and texture, and GPS may perform poorly in urban areas. To mitigate this problem, state-of-art Convolutional Neural Networks (CNNs)-based 3D descriptors may be directly applied to 3D point clouds. In this work, we investigated the performance of different classification strategies utilizing a cutting-edge CNN-based 3D global descriptor (PointNetVLAD) for place recognition task on the Oxford RobotCar dataset.

scholarly journals Current Practice in Preoperative Virtual and Physical Simulation in Neurosurgery

2020 ◽  
Vol 7 (1) ◽  
pp. 7 ◽  
Author(s):  
Elisa Mussi ◽  
Federico Mussa ◽  
Chiara Santarelli ◽  
Mirko Scagnet ◽  
Francesca Uccheddu ◽  
...  
Keyword(s):  
Clinical Practice ◽  
3D Printing ◽  
Surgical Planning ◽  
Physical Simulation ◽  
Planning Process ◽  
Preoperative Planning ◽  
Cost Effective ◽  
Patient Specific ◽  
Anatomical Models ◽  
Standard Clinical Practice

In brain tumor surgery, an appropriate and careful surgical planning process is crucial for surgeons and can determine the success or failure of the surgery. A deep comprehension of spatial relationships between tumor borders and surrounding healthy tissues enables accurate surgical planning that leads to the identification of the optimal and patient-specific surgical strategy. A physical replica of the region of interest is a valuable aid for preoperative planning and simulation, allowing the physician to directly handle the patient’s anatomy and easily study the volumes involved in the surgery. In the literature, different anatomical models, produced with 3D technologies, are reported and several methodologies were proposed. Many of them share the idea that the employment of 3D printing technologies to produce anatomical models can be introduced into standard clinical practice since 3D printing is now considered to be a mature technology. Therefore, the main aim of the paper is to take into account the literature best practices and to describe the current workflow and methodology used to standardize the pre-operative virtual and physical simulation in neurosurgery. The main aim is also to introduce these practices and standards to neurosurgeons and clinical engineers interested in learning and implementing cost-effective in-house preoperative surgical planning processes. To assess the validity of the proposed scheme, four clinical cases of preoperative planning of brain cancer surgery are reported and discussed. Our preliminary results showed that the proposed methodology can be applied effectively in the neurosurgical clinical practice both in terms of affordability and in terms of simulation realism and efficacy.

Cone-Beam Computed Tomography Allows Accurate Registration to Surgical Navigation Systems: A Multidevice Phantom Study

2019 ◽  
Vol 33 (6) ◽  
pp. 691-699 ◽  
Author(s):  
Benjamin J. Talks ◽  
Karan Jolly ◽  
Hanna Burton ◽  
Hitesh Koria ◽  
Shahzada K. Ahmed
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Surgical Navigation ◽  
Imaging Modality ◽  
Field Of View ◽  
Cone Beam ◽  
Navigation Systems ◽  
Registration Error ◽  
Surgical Navigation Systems ◽  
Phantom Head

Background Cone-beam computed tomography (CBCT) is a fast imaging technique with a substantially lower radiation dosage than conventional multidetector computed tomography (MDCT) for sinus imaging. Surgical navigation systems are increasingly being used in endoscopic sinus and skull base surgery, reducing perioperative morbidity. Objective To investigate CBCT as a low-radiation imaging modality for use in surgical navigation. Methods The required field of view was measured from the tip of the nose to the posterior clinoid process anteroposteriorly and the nasolabial angle to the roof of the frontal sinus superoinferiorly on 50 consecutive MDCT scans (male = 25; age = 17–85 years). A phantom head was manufactured by 3-dimensional printing and imaged using 3 CBCT scanners (Carestream, J Morita, and NewTom), a conventional MDCT scanner (Siemens), and highly accurate laser scanner (FARO). The phantom head was registered to 3 surgical navigation systems (Brainlab, Stryker, and Medtronic) using scans from each system. Results The required field of view (mean ± standard deviation) was measured as 107 ± 7.6 mm anteroposteriorly and 90.3 ± 9.6 mm superoinferiorly. Image error deviations from the laser scan (median ± interquartile range) were comparable for MDCT (0.19 ± 0.09 mm) and CBCT (CBCT 1: 0.15 ± 0.11 mm; CBCT 2: 0.33 ± 0.18 mm; and CBCT 3: 0.13 ± 0.13 mm) scanners. Fiducial registration error and target registration error were also comparable for MDCT- and CBCT-based navigation. Conclusion CBCT is a low-radiation preoperative imaging modality suitable for use in surgical navigation.

scholarly journals P.120 Rapid intraoperative reconstruction of cranial implants for craniotomy procedures: a feasibility study

2019 ◽  
Vol 46 (s1) ◽  
pp. S45
Author(s):  
K Beaulieu ◽  
M Kunz ◽  
R Alkins
Keyword(s):  
Imaging Modality ◽  
Bone Flap ◽  
Patient Specific ◽  
Great Promise ◽  
Surface Model ◽  
Bone Implants ◽  
Scanning Time ◽  
Rapid Generation ◽  
Cranial Implants ◽  
Cost Efficient

Background: The aim of this study was to investigate intraoperative methods to generate patient-specific PMMA bone implants during a craniotomy. The proposed methods combine a cost-efficient, and non-invasive structured light scanner (SLS) as an imaging modality and a prototype printer for rapid generation of implant molds. Methods: This simulation study was performed using retrospective data from three craniotomy patients. The extracted bone flap and the cranial defect were scanned using a SLS, which generates a 3D surface model of an object by projecting a series of light-patterns on it. Prototype printed implant models were generated using two different techniques. The molds were then used to shape PMMA bone implants. These implants were evaluated regarding their accuracy to reconstruct the natural skull anatomy and compared to freehand formed implants. Results: The patient-specific bone implants reconstructed the preoperative anatomy with an average RMS error of 1.37mm (StDev 0.27), compared to an error of 1.5mm (StDev 0.43) for the freehand shaped implants. On average the intraoperative scanning time was 4.7min. The average time to generate and print the implant molds was 204 min. Conclusions: Results of this study have shown great promise for the proposed method to be used for patient-specific bone flap reconstruction during craniotomies.

scholarly journals US/MRI fusion with new optical tracking and marker approach for interventional procedures inside the MRI suite

2016 ◽  
Vol 2 (1) ◽  
pp. 459-462
Author(s):  
Yeshaswini Nagaraj ◽  
Bjoern Menze ◽  
Michael Friebe
Keyword(s):  
Image Registration ◽  
Imaging Modality ◽  
Tracking System ◽  
Optical Tracking ◽  
Line Of Sight ◽  
Optical Tracking System ◽  
The Us ◽  
Phantom Studies ◽  
Inside Out ◽  
Dedicated Mri

AbstractInterventional MRI in closed bore high-field systems is a challenge due to limited space and the need of dedicated MRI compatible equipment and tools. A possible solution could be to perform an ultrasound procedure for guidance of the therapy tools outside the bore, but still on the MRI patient bed. That could track and subsequently combine the superior images of MRI with the real-time features of ultrasound. Conventional optical tracking systems suffer from line of sight issues and electromagnetic tracking does not perform well in the presence of magnetic fields. Hence, to overcome these issues a new optical tracking system called inside-out tracking is used. In this approach, the camera is directly attached to the US probe and the markers are placed onto the patient to achieve the location information of the US slice. The evaluation of our novel system of framed fusion markers can easily be adapted to various imaging modalities without losing image registration. To confirm this evaluation, phantom studies with MRI and US imaging were carried out using a point-registration algorithm along with a similarity measure for fusion. In the inside-out system approach, image registration was found to yield an accuracy of upto 4 mm, depending on the imaging modality and the employed marker arrangement and with that provides an accuracy that cannot be easily achieved by combining pre-operative MRI with live ultrasound.

Individual Tree Measurement in Tropical Environment using Terrestrial Laser Scanning

2015 ◽  
Vol 73 (5) ◽  
Author(s):  
Muhammad Zulkarnain Abdul Rahman ◽  
Zulkepli Majid ◽  
Md Afif Abu Bakar ◽  
Abd Wahid Rasib ◽  
Wan Hazli Wan Kadir
Keyword(s):  
Laser Scanning ◽  
Mean Squared Error ◽  
Tree Height ◽  
Point Clouds ◽  
Tree Crown ◽  
Individual Tree ◽  
Branch Diameter ◽  
Reference Tree ◽  
Crown Volume ◽  
Tree Branch

Detailed forest inventory and mensuration of individual trees have drawn attention of research society mainly to support sustainable forest management. This study aims at estimating individual tree attributes from high density point cloud obtained by terrestrial laser scanner (TLS). The point clouds were obtained over single reference tree and group of trees in forest area. The reference tree is treated as benchmark since detailed measurements of branch diameter were made on selected branches with different sizes and locations. Diameter at breast height (DBH) was measured for trees in forest. Furthermore tree height, height to crown base, crown volume and tree branch volume were also estimated for each tree. Branch diameter is estimated directly from the point clouds based on semi-automatic approach of model fitting i.e. sphere, ellipse and cylinder. Tree branch volume is estimated based on the volume of the fitted models. Tree height and height to crown base are computed using histogram analysis of the point clouds elevation. Tree crown volume is estimated by fitting a convex-hull on the tree crown. The results show that the Root Mean Squared Error (RMSE) of the estimated tree branch diameter does not have a specific trend with branch sizes and number of points used for fitting process. This explains complicated distribution of point clouds over the branches. Overall cylinder model produces good results with most branch sizes and number of point clouds for fitting. The cylinder fitting approach shows significantly better estimation results compared to sphere and ellipse fitting models.   

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