Spine Imaging: Novel Image Acquisition Techniques and Analysis Tools

Dear Colleagues,

Imaging of the spine, including radiography, multi-detector computed tomography (MDCT), and magnetic resonance imaging (MRI), is one of the most frequently performed exams in clinical routine. This is due to the high prevalence of spinal disorders, e.g., degenerative spine disease, osteoporosis and associated vertebral fractures, traumatic injuries, and tumor diseases. Spine imaging plays a key role in diagnosis, therapy monitoring, and computer-assisted planning of surgical interventions in these disease entities.

The technical improvement of MDCT scanner hardware and the introduction of iterative image reconstruction in MDCT imaging allows a considerable reduction of radiation exposure for image acquisition. Furthermore, advanced analysis approaches, such as finite element analysis, can extract MDCT-based quantitative imaging biomarkers, e.g., for osteoporotic fracture risk prediction. Regarding MRI, considerable research effort has been undertaken to accelerate image acquisition. Furthermore, MRI-based quantitative imaging biomarkers such as the proton density fat fraction have emerged recently, furthering our understanding of the pathophysiological relationships of different anatomical compartments of the spine. Artificial intelligence (AI)-based algorithms may have the potential to assist the radiologist in diagnosis, as well as in automated segmentation of the spine and procedure planning of surgical interventions, in the near future.

In the light of these developments, this Special Issue welcomes original research and review articles. Specific topics of interest include investigations of the human spine ex and in vivo that demonstrate the following:

(I) Advances in image acquisition including radiography, dual-energy X-ray absorptiometry (DXA), multi-detector computed tomography (MDCT), and magnetic resonance imaging (MRI);

(II) Novel post-processing methods for image reconstruction or advanced analysis pipelines; and

(III) Advances in automated image segmentation and diagnostic support tools (particularly AI-based approaches).

Dr. Thomas Baum
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 250 words) can be sent to the Editorial Office for assessment.

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.