Digital Transformation in Musculoskeletal Diagnostics and Imaging

Dear Colleagues,

It is a pleasure to invite you to contribute to the upcoming Special Issue, "Digital Transformation of Medical Imaging in the Musculoskeletal System," in Applied Sciences. This issue aims to spotlight the rapid evolution and clinical integration of digital technologies in musculoskeletal imaging, encompassing fields such as orthopaedics, traumatology, spine surgery, and sports medicine.

We are particularly interested in high-quality original research, comprehensive reviews, and forward-looking perspectives that examine how innovations—ranging from artificial intelligence and 3D imaging to augmented reality and blockchain—are reshaping diagnostic strategies, surgical planning, and patient management.

As the field moves towards precision, efficiency, and personalization, this Special Issue offers a timely platform to share breakthroughs, debate challenges, and propose future directions for digital musculoskeletal imaging. We warmly welcome contributions that will help shape the next chapter of this exciting transformation, and look forward to hearing from you.

Sincerely,

Wojciech Glinkowski MD, MBA,PhD
Guest Editor

Over the past four decades, medical imaging has evolved from analog systems to AI-powered platforms offering advanced imaging capabilities. This digital transformation has impacted musculoskeletal medicine, including orthopedics, traumatology, spine surgery, and sports medicine, improving diagnostics, surgical planning, and patient management. Technologies such as artificial intelligence (AI), machine learning (ML), augmented reality (AR), 3D printing, and blockchain are contributing to the advancement of musculoskeletal imaging by increasing the accuracy of image analysis and enabling real-time, data-driven decision-making. The integration of AI improves radiographic analysis by enabling the automatic detection of fractures, degenerative diseases, and soft tissue injuries. AI-based algorithms can segment musculoskeletal structures, aiding in early diagnosis and risk stratification. Deep learning-based reconstruction techniques improve image quality while reducing radiation exposure in computed tomography and magnetic resonance imaging. This Special Issue aims to showcase how AI, ML, deep learning, augmented and virtual reality (AR/VR), 3D printing, and blockchain are redefining diagnostic imaging and preoperative and even intraoperative planning. Three-dimensional imaging and printing support patient-specific preoperative planning and implant customization, while AR/VR technologies offer intraoperative guidance through image-based navigation. Blockchain and cloud platforms improve data security and remote access, promoting collaboration in emergency situations. However, challenges remain in data standardization, system interoperability, and the ethical implementation of artificial intelligence. We invite you to submit articles addressing these challenges and presenting the latest innovations in musculoskeletal imaging. Original research, reviews, and case studies highlighting clinical applications, workflow impact, and patient-centered care strategies are welcome. Three-dimensional (3D) imaging and printing are accelerating preoperative planning and the design of patient-specific implants. High-resolution 3D reconstruction enables visualization of complex pathologies, surgical simulation, and optimization of implant fit. AR and VR applications improve intraoperative navigation, facilitating precise procedures with real-time digital overlays. Blockchain technology provides secure, decentralized data storage, ensuring tamper-proof image sharing, system interoperability, and greater patient data privacy. Cloud-based imaging platforms using artificial intelligence support remote diagnostics and collaboration, accelerating decision-making in emergency situations. Despite advances, challenges remain in diagnostic imaging, data standardization, platform interoperability, and AI ethics. This Special Issue discusses advances in digital medical imaging in musculoskeletal medicine, highlighting innovative solutions and clinical applications. Thanks to digital technologies, this field is evolving towards more precise, efficient, and patient-oriented imaging.

Dr. Wojciech Glinkowski
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. Applied Sciences 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 2400 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.

• Digital medical imaging
• Musculoskeletal system
• Orthopaedic imaging
• Artificial intelligence (AI)
• Machine learning (ML)
• 3D imaging and printing
• Augmented reality (AR)
• Virtual reality (VR)
• Deep learning
• Blockchain in healthcare
• Diagnostic radiology
• Preoperative planning
• Image-guided surgery
• Imaging interoperability
• Precision medicine
• Cloud-based diagnostics
• Spinal imaging
• Sports medicine imaging
• Ethical AI in healthcare
• Radiological workflow