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Computer-Assisted Diagnosis and Personalized Treatment of Fracture
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Computer-Assisted Diagnosis and Personalized Treatment of Fracture

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Methodology, Drug and Device Discovery".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 3032

Special Issue Editor

Dr. Juan Jiménez-Delgado

E-Mail Website
Guest Editor
Department of Computer Sciences, Universidad de Jaén, 23071 Jaén, Spain
Interests: medical images; bone fractures; computer graphics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the convergence of computational sciences, medical imaging and artificial intelligence (AI) to revolutionize the diagnosis and personalized treatment of bone fractures. Contributions span diverse domains, from computer-assisted simulations and innovative medical data processing methods to advanced fracture analysis and surgical planning tools. The scope encompasses breakthroughs in representation, visualization and geometry modeling, while exploring the integration of computer graphics and engineering principles in fracture management. Articles cover topics such as automatic fracture generation, multiscale models and forensic analysis of fractures, also considering works that utilize AI for these topics. The issue also explores the intersection of technology and surgery aids, featuring operative planning tools, medical imaging advancements and the immersive potential of virtual reality in fracture diagnosis and patient education. This collection serves as a comprehensive guide for researchers, practitioners and medical professionals navigating the cutting edge of computer-assisted approaches to fractures, promising transformative advancements in the field.

Dr. Juan José Jiménez-Delgado
Guest Editor

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

  • fracture diagnosis
  • computer-assisted simulation
  • artificial intelligence in orthopedics
  • medical imaging advances
  • personalized fracture treatment
  • computational fracture analysis
  • surgical planning tools
  • virtual reality in orthopedics
  • forensic analysis of fractures
  • multiscale modeling of bone

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

10 pages, 932 KiB  
Article
Impact of Surgical Timing, Fasciotomy, and External Fixation on Infection Risk in Tibial Plateau Fractures
by Salvatore Risitano, Antonio Rea, Giorgia Garofalo, Francesco Onorato, Ahmed Elzeiny, Stefano Artiaco, Marcello Capella, Pier Francesco Indelli and Alessandro Massè
J. Pers. Med. 2025, 15(3), 108; https://doi.org/10.3390/jpm15030108 - 11 Mar 2025
Viewed by 506
Abstract
Background/Objectives: Tibial plateau fractures (TPFs) are commonly associated with complex patterns requiring advanced surgical strategies. High-energy trauma often results in severe soft tissue damage, complicating surgical outcomes. Despite advancements in soft tissue management, postoperative complications such as surgical site infections (SSIs) remain [...] Read more.
Background/Objectives: Tibial plateau fractures (TPFs) are commonly associated with complex patterns requiring advanced surgical strategies. High-energy trauma often results in severe soft tissue damage, complicating surgical outcomes. Despite advancements in soft tissue management, postoperative complications such as surgical site infections (SSIs) remain prevalent, with rates ranging from 9.9% to 30%. This study aims to analyze risk factors and surgical approaches influencing acute SSIs following TPF fixation. Methods: A retrospective analysis was conducted on 365 patients treated for TPFs with open or arthroscopy-assisted reduction and internal fixation (ORIF/ARIF) at a single center between January 2018 and December 2023. Inclusion criteria encompassed fractures classified by the Schatzker system and definitive management through ORIF/ARIF. Exclusion criteria included non-tibial plateau fractures, polytrauma, multiligament injuries and associated femoral fractures. Patient demographics, fracture patterns, surgical interventions, and postoperative complications were reviewed. Statistical analysis was performed using chi-square and ANOVA tests, with significance set at p < 0.05. Results: The final cohort included 364 patients (mean age: 45.4 ± 17.4 years; 59.2% male). High-energy fractures (Schatzker IV–VI) accounted for 47.7%, with 6.86% being open fractures. The mean interval to surgery was 14.9 ± 20.6 days. Superficial infections occurred in 21 cases (5.8%), predominantly at external fixator pin sites, while 15 cases (4.1%) involved deep infections. A statistically significant correlation was observed between SSIs and preoperative fasciotomy (p < 0.0001), damage control orthopedic protocols (p < 0.0001), and delays in definitive treatment of 10–30 days (p < 0.0001). No significant associations were found between infection rates and fracture type, dual surgical approaches, or the use of arthroscopy. Conclusions: External fixation, preoperative fasciotomy, and delayed definitive treatment are independent risk factors for SSIs following TPF fixation. High-energy injuries and soft tissue damage exacerbate infection risk. A personalized surgical approach, based on minimally invasive techniques and optimized surgical timing may mitigate these complications and significantly improve clinical outcomes in TPFs. Full article
(This article belongs to the Special Issue Computer-Assisted Diagnosis and Personalized Treatment of Fracture)
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18 pages, 1627 KiB  
Article
Exploring Fracture Patterns: Assessing Representation Methods for Bone Fracture Simulation
by Francisco Daniel Pérez-Cano, Gema Parra-Cabrera, Ivett Vilchis-Torres, José Javier Reyes-Lagos and Juan José Jiménez-Delgado
J. Pers. Med. 2024, 14(4), 376; https://doi.org/10.3390/jpm14040376 - 30 Mar 2024
Cited by 2 | Viewed by 1886
Abstract
Fracture pattern acquisition and representation in human bones play a crucial role in medical simulation, diagnostics, and treatment planning. This article presents a comprehensive review of methodologies employed in acquiring and representing bone fracture patterns. Several techniques, including segmentation algorithms, curvature analysis, and [...] Read more.
Fracture pattern acquisition and representation in human bones play a crucial role in medical simulation, diagnostics, and treatment planning. This article presents a comprehensive review of methodologies employed in acquiring and representing bone fracture patterns. Several techniques, including segmentation algorithms, curvature analysis, and deep learning-based approaches, are reviewed to determine their effectiveness in accurately identifying fracture zones. Additionally, diverse methods for representing fracture patterns are evaluated. The challenges inherent in detecting accurate fracture zones from medical images, the complexities arising from multifragmentary fractures, and the need to automate fracture reduction processes are elucidated. A detailed analysis of the suitability of each representation method for specific medical applications, such as simulation systems, surgical interventions, and educational purposes, is provided. The study explores insights from a broad spectrum of research articles, encompassing diverse methodologies and perspectives. This review elucidates potential directions for future research and contributes to advancements in comprehending the acquisition and representation of fracture patterns in human bone. Full article
(This article belongs to the Special Issue Computer-Assisted Diagnosis and Personalized Treatment of Fracture)
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