Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.7
3.0
Journals
JCM
Special Issues
Recent Advancements in Nuclear Medicine and Radiology
share announcement

Recent Advancements in Nuclear Medicine and Radiology

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nuclear Medicine & Radiology".

Deadline for manuscript submissions: 25 December 2024 | Viewed by 2415

Special Issue Editor

Prof. Dr. Adriaan A. Lammertsma

E-Mail Website
Guest Editor
Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Interests: PET; PET physics; PET data analysis; tracer kinetic modeling

Special Issue Information

Dear Colleagues,

In 1895, Wilhelm Conrad Röntgen discovered X-rays; a year later, Henri Becquerel described “mysterious” rays, later termed as radioactivity, originating from uranium. Both types of radiation rapidly found their way in medicine, stimulated of course by Röntgen's first "medical" X-ray image of his wife's hand (with ring), taken on 22 December 1895. Now, more than 125 years later, radiology is firmly embedded in the diagnostic pathway of nearly all diseases. To a lesser extent, the same is true for nuclear medicine. In addition, imaging of molecular interactions plays an increasingly important role in unravelling disease mechanisms. Over the years, there has been substantial progress in imaging equipment, resulting in state-of-the-art CT, MRI, SPECT and PET scanners. Such progress is still ongoing, with large axial field of view (total body) PET scanners being the latest major development. In parallel with these developments in imaging instrumentation, image analysis techniques have similarly evolved with artificial intelligence. Better scanners, more refined analytical techniques and a wider range of radiopharmaceuticals have resulted in an ever increasing number of clinical applications.

This Special Issue, ‘Recent Advancements in Nuclear Medicine and Radiology’ aims to present an exclusive collection of comprehensive reviews and invites researchers to submit their review papers covering the novel developments and advancements in nuclear medicine and radiology.

Prof. Dr. Adriaan A. Lammertsma
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 Clinical Medicine 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

  • PET
  • SPECT
  • CT
  • MRI
  • AI
  • image analysis
  • kinetic analysis

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

10 pages, 1492 KiB  
Article
Unsupervised Pattern Analysis to Differentiate Multiple Sclerosis Phenotypes Using Principal Component Analysis on Various MRI Sequences
by Chris W. J. van der Weijden, Milena S. Pitombeira, Débora E. Peretti, Kenia R. Campanholo, Guilherme D. Kolinger, Carolina M. Rimkus, Carlos Alberto Buchpiguel, Rudi A. J. O. Dierckx, Remco J. Renken, Jan F. Meilof, Erik F. J. de Vries and Daniele de Paula Faria
J. Clin. Med. 2024, 13(17), 5234; https://doi.org/10.3390/jcm13175234 - 4 Sep 2024
Viewed by 803
Abstract
Background: Multiple sclerosis (MS) has two main phenotypes: relapse-remitting MS (RRMS) and progressive MS (PMS), distinguished by disability profiles and treatment response. Differentiating them using conventional MRI is challenging. Objective: This study explores the use of scaled subprofile modelling using principal [...] Read more.
Background: Multiple sclerosis (MS) has two main phenotypes: relapse-remitting MS (RRMS) and progressive MS (PMS), distinguished by disability profiles and treatment response. Differentiating them using conventional MRI is challenging. Objective: This study explores the use of scaled subprofile modelling using principal component analysis (SSM/PCA) on MRI data to distinguish between MS phenotypes. Methods: MRI scans were performed on patients with RRMS (n = 30) and patients with PMS (n = 20), using the standard sequences T1w, T2w, T2w-FLAIR, and the myelin-sensitive sequences magnetisation transfer (MT) ratio (MTR), quantitative MT (qMT), inhomogeneous MT ratio (ihMTR), and quantitative inhomogeneous MT (qihMT). Results: SSM/PCA analysis of qihMT images best differentiated PMS from RRMS, with the highest specificity (87%) and positive predictive value (PPV) (83%), but a lower sensitivity (67%) and negative predictive value (NPV) (72%). Conversely, T1w data analysis showed the highest sensitivity (93%) and NPV (89%), with a lower PPV (67%) and specificity (53%). Phenotype classification agreement between T1w and qihMT was observed in 57% of patients. In the subset with concordant classifications, the sensitivity, specificity, PPV, and NPV were 100%, 88%, 90%, and 100%, respectively. Conclusions: SSM/PCA on MRI data revealed distinctive patterns for MS phenotypes. Optimal discrimination occurred with qihMT and T1w sequences, with qihMT identifying PMS and T1w identifying RRMS. When qihMT and T1w analyses align, MS phenotype prediction improves. Full article
(This article belongs to the Special Issue Recent Advancements in Nuclear Medicine and Radiology)
►▼ Show Figures

Figure 1

16 pages, 3598 KiB  
Article
Bone Metabolism and Dental Implant Insertion as a Correlation Affecting on Marginal Bone Remodeling: Texture Analysis and the New Corticalization Index, Predictor of Marginal Bone Loss—3 Months of Follow-Up
by Tomasz Wach, Piotr Szymor, Grzegorz Trybek, Maciej Sikora, Adam Michcik and Marcin Kozakiewicz
J. Clin. Med. 2024, 13(11), 3212; https://doi.org/10.3390/jcm13113212 - 30 May 2024
Cited by 1 | Viewed by 950
Abstract
Background/Objectives: The general condition of implantology patients is crucial when considering the long- and short-term survival of dental implants. The aim of the research was to evaluate the correlation between the new corticalization index (CI) and patients’ condition, and its impact on marginal [...] Read more.
Background/Objectives: The general condition of implantology patients is crucial when considering the long- and short-term survival of dental implants. The aim of the research was to evaluate the correlation between the new corticalization index (CI) and patients’ condition, and its impact on marginal bone loss (MBL) leading to implant failure, using only radiographic (RTG) images on a pixel level. Method: Bone near the dental implant neck was examined, and texture features were analyzed. Statistical analysis includes analysis of simple regression where the correlation coefficient (CC) and R2 were calculated. Detected relationships were assumed to be statistically significant when p < 0.05. Statgraphics Centurion version 18.1.12 (Stat Point Technologies, Warrenton, VA, USA) was used to conduct the statistical analyses. Results: The research revealed a correlation between MBL after 3 months and BMI, PTH, TSH, Ca2+ level in blood serum, phosphates in blood serum, and vitamin D. A correlation was also observed between CI and PTH, Ca2+ level in blood serum, vitamin D, LDL, HDL, and triglycerides on the day of surgery. After 3 months of the observation period, CI was correlated with PTH, TSH, Ca2+ level in blood serum, and triglycerides. Conclusion: The results of the research confirm that the general condition of patients corresponds with CI and MBL. A patient’s general condition has an impact on bone metabolism around dental implants. Implant insertion should be considered if the general condition of the patient is not stable. However, CI has not yet been fully investigated. Further studies are necessary to check and categorize the impact of corticalization on marginal bone loss near dental implants. Full article
(This article belongs to the Special Issue Recent Advancements in Nuclear Medicine and Radiology)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop