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Special Issues
Novel Challenges and Advances in Orthopaedic and Trauma Surgery
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Novel Challenges and Advances in Orthopaedic and Trauma Surgery

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Clinical Medicine, Cell, and Organism Physiology".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 1482

Special Issue Editors

Dr. Dimitrios Kitridis

E-Mail
Guest Editor
1. 1st Orthopaedic Department, 424 Army General Training Hospital, Thessaloniki, Greece
2. 1st Orthopaedic Department, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: upper limb orthopaedic surgery; arthroscopy; orthopaedic trauma
Prof. Dr. Panagiotis Givissis

E-Mail Website
Guest Editor
1st Orthopaedic Department, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: upper limb orthopaedic surgery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few decades, major advancements in the diagnosis and treatment of patients with musculoskeletal disorders and trauma have taken place. Nevertheless, implant development, diagnostics, surgical treatment, and post-operative rehabilitation are subject to change and improvement.

The aim of this Special Issue is to share the knowledge and experience of authors regarding the diagnosis and treatment within the fields of orthopaedic and trauma surgery. Submissions related to individualised patient care, evolving diagnostics, new advances in surgical techniques, surgery-assisting technologies, and advanced protocols for improved rehabilitation are welcome.

We encourage the submission of original research articles, reviews (including systematic reviews), and communications focusing on the diagnosis and treatment of orthopaedics and trauma-related disorders. Articles discussing expert consensus, recommendations, guidelines, and promising surgical techniques are also welcome.

Dr. Dimitrios Kitridis
Prof. Dr. Panagiotis Givissis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • orthopaedic surgery
  • traumatology
  • musculoskeletal disorders
  • innovation in orthopaedics
  • individualised treatment
  • post-operative rehabilitation
  • clinical research

Published Papers (1 paper)

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Research

18 pages, 4644 KiB  
Article
Synthetic 3D Spinal Vertebrae Reconstruction from Biplanar X-rays Utilizing Generative Adversarial Networks
by Babak Saravi, Hamza Eren Guzel, Alisia Zink, Sara Ülkümen, Sebastien Couillard-Despres, Jakob Wollborn, Gernot Lang and Frank Hassel
J. Pers. Med. 2023, 13(12), 1642; https://doi.org/10.3390/jpm13121642 - 24 Nov 2023
Cited by 1 | Viewed by 1170
Abstract
Computed tomography (CT) offers detailed insights into the internal anatomy of patients, particularly for spinal vertebrae examination. However, CT scans are associated with higher radiation exposure and cost compared to conventional X-ray imaging. In this study, we applied a Generative Adversarial Network (GAN) [...] Read more.
Computed tomography (CT) offers detailed insights into the internal anatomy of patients, particularly for spinal vertebrae examination. However, CT scans are associated with higher radiation exposure and cost compared to conventional X-ray imaging. In this study, we applied a Generative Adversarial Network (GAN) framework to reconstruct 3D spinal vertebrae structures from synthetic biplanar X-ray images, specifically focusing on anterior and lateral views. The synthetic X-ray images were generated using the DRRGenerator module in 3D Slicer by incorporating segmentations of spinal vertebrae in CT scans for the region of interest. This approach leverages a novel feature fusion technique based on X2CT-GAN to combine information from both views and employs a combination of mean squared error (MSE) loss and adversarial loss to train the generator, resulting in high-quality synthetic 3D spinal vertebrae CTs. A total of n = 440 CT data were processed. We evaluated the performance of our model using multiple metrics, including mean absolute error (MAE) (for each slice of the 3D volume (MAE0) and for the entire 3D volume (MAE)), cosine similarity, peak signal-to-noise ratio (PSNR), 3D peak signal-to-noise ratio (PSNR-3D), and structural similarity index (SSIM). The average PSNR was 28.394 dB, PSNR-3D was 27.432, SSIM was 0.468, cosine similarity was 0.484, MAE0 was 0.034, and MAE was 85.359. The results demonstrated the effectiveness of this approach in reconstructing 3D spinal vertebrae structures from biplanar X-rays, although some limitations in accurately capturing the fine bone structures and maintaining the precise morphology of the vertebrae were present. This technique has the potential to enhance the diagnostic capabilities of low-cost X-ray machines while reducing radiation exposure and cost associated with CT scans, paving the way for future applications in spinal imaging and diagnosis. Full article
(This article belongs to the Special Issue Novel Challenges and Advances in Orthopaedic and Trauma Surgery)
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