scholarly journals Prevalence of metacarpophalangeal sesamoid bones of the hand in Turkish population

2021 ◽  
Vol 32 (2) ◽  
pp. 391-396
Author(s):  
Emre Ergen ◽  
Özgür Yılmaz ◽  
Bünyamin Arı ◽  
Erkay Nacar ◽  
Ayla Özaydoğdu Çimen ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Communication System ◽  
Turkish Population ◽  
Ct Images ◽  
Sesamoid Bone ◽  
Significant Difference ◽  
Sesamoid Bones ◽  
Picture Archiving ◽  
Recorded Data ◽  
Picture Archiving And Communication

Objectives: This study aims to investigate the prevalence and location of the metacarpophalangeal (MCP) sesamoid bones using computed tomography (CT) images. Patients and methods: A total of 767 hands of 735 patients (503 males, 232 females; mean age: 36.9±17.0 years; range, 18 to 105 years) obtained from picture archiving and communication system were retrospectively analyzed between January 2016 and December 2019. The sesamoid bones of MCP joints I, II, III, IV, and V were recorded. Data including age, sex, side, number, pathologies, and location of the sesamoid bones were recorded. Results: The prevalence of sesamoid bones was found to be 100%, 37.61%, 1.17%, 0.5%, and 80% in MCP I, II, III, IV, and V, respectively. There was no significant correlation between the sex of the patient and presence of sesamoid bone at MCP II or MCP V (p>0.970 and p=0.176, respectively). The presence of sesamoid bone at MCP II was statistically significantly correlated with the presence of sesamoid bone at MCP V (p<0.001). There was no statistically significant difference in the side and sesamoid prevalence in the remaining 703 patients (p>0.05). Conclusion: The prevalence of MCP V sesamoid bone is higher than previous studies from our country. The CT of hand can be used to determine sesamoid fractures and degenerative conditions of sesamoids.

scholarly journals Comparing Computed Tomography–Derived Augmented Reality Holograms to a Standard Picture Archiving and Communication Systems Viewer for Presurgical Planning: Feasibility Study

10.2196/18367 ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. e18367
Author(s):  
David Dallas-Orr ◽  
Yordan Penev ◽  
Robert Schultz ◽  
Jesse Courtier
Keyword(s):  
Computed Tomography ◽  
Augmented Reality ◽  
Communication Systems ◽  
Intraclass Correlation ◽  
Planning System ◽  
Measurement Tool ◽  
Presurgical Planning ◽  
Significant Difference ◽  
Picture Archiving ◽  
Picture Archiving And Communication

Background Picture archiving and communication systems (PACS) are ubiquitously used to store, share, and view radiological information for preoperative planning across surgical specialties. Although traditional PACS software has proven reliable in terms of display accuracy and ease of use, it remains limited by its inherent representation of medical imaging in 2 dimensions. Augmented reality (AR) systems present an exciting opportunity to complement traditional PACS capabilities. Objective This study aims to evaluate the technical feasibility of using a novel AR platform, with holograms derived from computed tomography (CT) imaging, as a supplement to traditional PACS for presurgical planning in complex surgical procedures. Methods Independent readers measured objects of predetermined, anthropomorphically correlated sizes using the circumference and angle tools of standard-of-care PACS software and a newly developed augmented reality presurgical planning system (ARPPS). Results Measurements taken with the standard PACS and the ARPPS showed no statistically significant differences. Bland-Altman analysis showed a mean difference of 0.08% (95% CI –4.20% to 4.36%) for measurements taken with PACS versus ARPPS’ circumference tools and –1.84% (95% CI –6.17% to 2.14%) for measurements with the systems’ angle tools. Lin’s concordance correlation coefficients were 1.00 and 0.98 for the circumference and angle measurements, respectively, indicating almost perfect strength of agreement between ARPPS and PACS. Intraclass correlation showed no statistically significant difference between the readers for either measurement tool on each system. Conclusions ARPPS can be an effective, accurate, and precise means of 3D visualization and measurement of CT-derived holograms in the presurgical care timeline.

scholarly journals Comparing Computed Tomography–Derived Augmented Reality Holograms to a Standard Picture Archiving and Communication Systems Viewer for Presurgical Planning: Feasibility Study (Preprint)

2020 ◽  
Author(s):  
David Dallas-Orr ◽  
Yordan Penev ◽  
Robert Schultz ◽  
Jesse Courtier
Keyword(s):  
Computed Tomography ◽  
Augmented Reality ◽  
Communication Systems ◽  
Intraclass Correlation ◽  
Planning System ◽  
Measurement Tool ◽  
Presurgical Planning ◽  
Significant Difference ◽  
Picture Archiving ◽  
Picture Archiving And Communication

BACKGROUND Picture archiving and communication systems (PACS) are ubiquitously used to store, share, and view radiological information for preoperative planning across surgical specialties. Although traditional PACS software has proven reliable in terms of display accuracy and ease of use, it remains limited by its inherent representation of medical imaging in 2 dimensions. Augmented reality (AR) systems present an exciting opportunity to complement traditional PACS capabilities. OBJECTIVE This study aims to evaluate the technical feasibility of using a novel AR platform, with holograms derived from computed tomography (CT) imaging, as a supplement to traditional PACS for presurgical planning in complex surgical procedures. METHODS Independent readers measured objects of predetermined, anthropomorphically correlated sizes using the circumference and angle tools of standard-of-care PACS software and a newly developed augmented reality presurgical planning system (ARPPS). RESULTS Measurements taken with the standard PACS and the ARPPS showed no statistically significant differences. Bland-Altman analysis showed a mean difference of 0.08% (95% CI –4.20% to 4.36%) for measurements taken with PACS versus ARPPS’ circumference tools and –1.84% (95% CI –6.17% to 2.14%) for measurements with the systems’ angle tools. Lin’s concordance correlation coefficients were 1.00 and 0.98 for the circumference and angle measurements, respectively, indicating almost perfect strength of agreement between ARPPS and PACS. Intraclass correlation showed no statistically significant difference between the readers for either measurement tool on each system. CONCLUSIONS ARPPS can be an effective, accurate, and precise means of 3D visualization and measurement of CT-derived holograms in the presurgical care timeline.

scholarly journals Multi-Cycle-Consistent Adversarial Networks for Edge Denoising of Computed Tomography Images

2021 ◽  
Vol 17 (4) ◽  
pp. 1-16
Author(s):  
Xiaowe Xu ◽  
Jiawei Zhang ◽  
Jinglan Liu ◽  
Yukun Ding ◽  
Tianchen Wang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Denoising ◽  
Ct Images ◽  
High Dose ◽  
Ct Image ◽  
Paired Data ◽  
High Quality ◽  
Computed Tomography Images ◽  
Significant Difference ◽  
Global Cycle

As one of the most commonly ordered imaging tests, the computed tomography (CT) scan comes with inevitable radiation exposure that increases cancer risk to patients. However, CT image quality is directly related to radiation dose, and thus it is desirable to obtain high-quality CT images with as little dose as possible. CT image denoising tries to obtain high-dose-like high-quality CT images (domain Y ) from low dose low-quality CT images (domain X ), which can be treated as an image-to-image translation task where the goal is to learn the transform between a source domain X (noisy images) and a target domain Y (clean images). Recently, the cycle-consistent adversarial denoising network (CCADN) has achieved state-of-the-art results by enforcing cycle-consistent loss without the need of paired training data, since the paired data is hard to collect due to patients’ interests and cardiac motion. However, out of concerns on patients’ privacy and data security, protocols typically require clinics to perform medical image processing tasks including CT image denoising locally (i.e., edge denoising). Therefore, the network models need to achieve high performance under various computation resource constraints including memory and performance. Our detailed analysis of CCADN raises a number of interesting questions that point to potential ways to further improve its performance using the same or even fewer computation resources. For example, if the noise is large leading to a significant difference between domain X and domain Y , can we bridge X and Y with a intermediate domain Z such that both the denoising process between X and Z and that between Z and Y are easier to learn? As such intermediate domains lead to multiple cycles, how do we best enforce cycle- consistency? Driven by these questions, we propose a multi-cycle-consistent adversarial network (MCCAN) that builds intermediate domains and enforces both local and global cycle-consistency for edge denoising of CT images. The global cycle-consistency couples all generators together to model the whole denoising process, whereas the local cycle-consistency imposes effective supervision on the process between adjacent domains. Experiments show that both local and global cycle-consistency are important for the success of MCCAN, which outperforms CCADN in terms of denoising quality with slightly less computation resource consumption.

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