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Diagnostics
Special Issues
Advances in Plastic Surgery: Diagnosis, Management and Prognosis
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Advances in Plastic Surgery: Diagnosis, Management and Prognosis

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 358

Special Issue Editor

Dr. Konstantinos Seretis

E-Mail Website
Guest Editor
Department of Plastic Surgery, Medical School, University of Ioannina, Ioannina, Greece
Interests: plastic surgery; hand surgery; breast reconstruction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce a new Special Issue in Diagnostics, titled "Advances in Plastic Surgery: Diagnosis, Treatment and Prognosis". This Special Issue focuses on the medical field of plastic surgery, which covers the treatment of injuries; the disease management of skin, muscles, and bones; and the correction of congenital or acquired tissue and organ defects and deformities.

The scope of the application of plastic surgery is extensive, encompassing not only craniofacial surgery, maxillofacial plastic surgery, facial and neck deformity correction, and cosmetic surgery but also hand surgery, limb and trunk plastic surgery, genitourinary plastic surgery, and rehabilitation treatment. Its core treatment method is autologous tissue transplantation, with the application of allografts, xenografts, or tissue substitutes also common in the repair of various tissue defects or deformities. With the rapid advancement of medical technology, plastic surgery’s surgical techniques continue to evolve (through the use of 3D printing and robotic surgery), greatly enhancing the precision, safety, and effectiveness of these surgeries. In this process, diagnosis and prognosis assessments play important roles. They are not only the prerequisites for formulating treatment plans but also important bases for evaluating surgical outcomes and predicting patients' future health conditions.

This Special Issue aims to present readers with the latest advancements in diagnosis, treatment, and prognosis within plastic surgery. Original articles and review papers are welcome.

Dr. Konstantinos Seretis
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. Diagnostics is an international peer-reviewed open access semimonthly 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

  • plastic surgery
  • breast reconstruction
  • skin graft
  • diagnosis
  • prognosis
 

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

Published Papers (1 paper)

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Research

15 pages, 2862 KB  
Article
Deep Learning-Based Prediction Model of Surgical Indication of Nasal Bone Fracture Using Waters’ View
by Dong Yun Lee, Soo A Lim and Su Rak Eo
Diagnostics 2025, 15(18), 2386; https://doi.org/10.3390/diagnostics15182386 - 19 Sep 2025
Viewed by 83
Abstract
Background/Objectives: The nasal bone is critical to both the functional integrity and esthetic contour of the facial skeleton. Nasal bone fractures constitute the most prevalent facial fracture presentation in emergency departments. The identification of these fractures and the determination of immediate intervention requirements [...] Read more.
Background/Objectives: The nasal bone is critical to both the functional integrity and esthetic contour of the facial skeleton. Nasal bone fractures constitute the most prevalent facial fracture presentation in emergency departments. The identification of these fractures and the determination of immediate intervention requirements pose significant challenges for inexperienced residents, potentially leading to oversight. Methods: A retrospective analysis was conducted on facial trauma patients undergoing cranial radiography (Waters’ view) during initial emergency department assessment between March 2008 and July 2022. This study incorporated 2099 radiographic images. Surgical indications comprised the displacement angle, interosseous gap size, soft tissue swelling thickness, and subcutaneous emphysema. A deep learning-based artificial intelligence (AI) algorithm was designed, trained, and validated for fracture detection on radiographic images. Model performance was quantified through accuracy, precision, recall, and F1 score. Hyperparameters included the batch size (20), epochs (70), 50-layer network architecture, Adam optimizer, and initial learning rate (0.001). Results: The deep learning AI model employing segmentation labeling demonstrated 97.68% accuracy, 82.2% precision, 88.9% recall, and an 85.4% F1 score in nasal bone fracture identification. These outcomes informed the development of a predictive algorithm for guiding conservative versus surgical management decisions. Conclusions: The proposed AI-driven algorithm and criteria exhibit high diagnostic accuracy and operational efficiency in both detecting nasal bone fractures and predicting surgical indications, establishing its utility as a clinical decision-support tool in emergency settings. Full article
(This article belongs to the Special Issue Advances in Plastic Surgery: Diagnosis, Management and Prognosis)
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