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Diagnostics
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Advances in Computed Tomography Imaging for Clinical Diagnosis—2nd Edition
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Advances in Computed Tomography Imaging for Clinical Diagnosis—2nd Edition

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 1646

Special Issue Editor

Dr. Ibrahim Yel

E-Mail Website
Guest Editor
Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, 60590 Frankfurt, Germany
Interests: computed tomography; magnetic resonance tomography; diagnostic imaging; medical imaging; musculoskeletal imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I would like to invite you to submit your work to the Special Issue on “Advances in Computed Tomography Imaging for Clinical Diagnosis—2nd Edition”. This Special Issue aims to present the latest developments in computed tomography (CT) imaging, including new image reconstruction methods and clinical applications, to enhance clinical diagnosis. Thanks to recent technological advancements, such as spectral imaging (including dual-energy CT and photon-counting CT) and artificial intelligence-based image analysis, the accuracy and diagnostic potential of CT imaging are continuing to improve.

With your contributions, this Special Issue will provide valuable insights into the current state and future directions of CT imaging for clinical diagnosis. We are excited to receive your contributions and believe your research on this topic will greatly benefit the medical imaging community. We look forward to your submissions and participation in this exciting Special Issue.

Dr. Ibrahim Yel
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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

  • computed tomography imaging
  • clinical diagnosis
  • dual-energy CT
  • photon-counting CT
  • image analysis

Published Papers (2 papers)

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Research

12 pages, 1827 KiB  
Article
Predictive Value of Dual-Energy CT-Derived Metrics for the Use of Bone Substitutes in Distal Radius Fracture Surgery
by Philipp Reschke, Vitali Koch, Scherwin Mahmoudi, Christian Booz, Ibrahim Yel, Jennifer Gotta, Adrian Stahl, Robin Reschke, Jan-Erik Scholtz, Simon S. Martin, Tatjana Gruber-Rouh, Katrin Eichler, Thomas J. Vogl and Leon D. Gruenewald
Diagnostics 2024, 14(7), 697; https://doi.org/10.3390/diagnostics14070697 - 26 Mar 2024
Viewed by 567
Abstract
(1) Background: Low bone mineral density (BMD) is a significant risk factor for complicated surgery and leads to the increased use of bone substitutes in patients with distal radius fractures (DRFs). No accepted model has yet been established to predict the use of [...] Read more.
(1) Background: Low bone mineral density (BMD) is a significant risk factor for complicated surgery and leads to the increased use of bone substitutes in patients with distal radius fractures (DRFs). No accepted model has yet been established to predict the use of bone substitutes to facilitate preoperative planning. (2) Methods: Unenhanced dual-energy CT (DECT) images of DRFs were retrospectively acquired between March 2016 and September 2020 using the internal PACS system. Available follow-up imaging and medical health records were reviewed to determine the use of bone substitutes. DECT-based BMD, trabecular Hounsfield units (HU), cortical HU, and cortical thickness ratio were measured in non-fractured segments of the distal radius. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) curves and associations of all metrics with the use of bone substitutes were evaluated using logistic regression models. (3) The final study population comprised 262 patients (median age 55 years [IQR 43–67 years]; 159 females, 103 males). According to logistic regression analysis, DECT-based BMD was the only metric significantly associated with the use of bone substitutes (odds ratio 0.96, p = 0.003). However, no significant associations were found for cortical HU (p = 0.06), trabecular HU (p = 0.33), or cortical thickness ratio (p = 0.21). ROC-curve analysis revealed that a combined model of all four metrics had the highest diagnostic accuracy with an area under the curve (AUC) of 0.76. (4) Conclusions: DECT-based BMD measurements performed better than HU-based measurements and cortical thickness ratio. The diagnostic performance of all four metrics combined was superior to that of the individual parameters. Full article
(This article belongs to the Special Issue Advances in Computed Tomography Imaging for Clinical Diagnosis—2nd Edition)
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11 pages, 1840 KiB  
Article
Dual-Energy CT Material Decomposition: The Value in the Detection of Lymph Node Metastasis from Breast Cancer
by Ibrahim Yel, Tommaso D’Angelo, Leon D. Gruenewald, Vitali Koch, Rejane Golbach, Scherwin Mahmoudi, Giorgio Ascenti, Alfredo Blandino, Thomas J. Vogl, Christian Booz and Giuseppe M. Bucolo
Diagnostics 2024, 14(5), 466; https://doi.org/10.3390/diagnostics14050466 - 21 Feb 2024
Cited by 1 | Viewed by 1035
Abstract
Purpose: To evaluate the diagnostic performance of a dual-energy computed tomography (DECT)-based material decomposition algorithm for iodine quantification and fat fraction analysis to detect lymph node metastases in breast cancer patients. Materials and Methods: 30 female patients (mean age, 63.12 ± 14.2 years) [...] Read more.
Purpose: To evaluate the diagnostic performance of a dual-energy computed tomography (DECT)-based material decomposition algorithm for iodine quantification and fat fraction analysis to detect lymph node metastases in breast cancer patients. Materials and Methods: 30 female patients (mean age, 63.12 ± 14.2 years) diagnosed with breast cancer who underwent pre-operative chest DECT were included. To establish a reference standard, the study correlated histologic repots after lymphadenectomy or confirming metastasis in previous/follow-up examinations. Iodine concentration and fat fraction were determined through region-of-interest measurements on venous DECT iodine maps. Receiver operating characteristic curve analysis was conducted to identify the optimal threshold for differentiating between metastatic and non-metastatic lymph nodes. Results: A total of 168 lymph nodes were evaluated, divided into axillary (metastatic: 46, normal: 101) and intramammary (metastatic: 10, normal: 11). DECT-based fat fraction values exhibited significant differences between metastatic (9.56 ± 6.20%) and non-metastatic lymph nodes (41.52 ± 19.97%) (p < 0.0001). Absolute iodine concentrations showed no significant differences (2.25 ± 0.97 mg/mL vs. 2.08 ± 0.97 mg/mL) (p = 0.7999). The optimal fat fraction threshold for diagnosing metastatic lymph nodes was determined to be 17.75%, offering a sensitivity of 98% and a specificity of 94%. Conclusions: DECT fat fraction analysis emerges as a promising method for identifying metastatic lymph nodes, overcoming the morpho-volumetric limitations of conventional CT regarding lymph node assessment. This innovative approach holds potential for improving pre-operative lymph node evaluation in breast cancer patients, offering enhanced diagnostic accuracy. Full article
(This article belongs to the Special Issue Advances in Computed Tomography Imaging for Clinical Diagnosis—2nd Edition)
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