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Diagnostics
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Abdominal Imaging: Recent Advances and Future Trends
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Abdominal Imaging: Recent Advances and Future Trends

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

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 2953

Special Issue Editors

Dr. Giulia A. Zamboni

E-Mail Website
Guest Editor
Institute of Radiology, Department of Diagnostics and Public Health, Policlinico GB Rossi, University of Verona, 37134 Verona, Italy
Interests: pancreatic diseases; liver diseases; oncology; CT; MRI
Special Issues, Collections and Topics in MDPI journals
Dr. Maria Chiara Ambrosetti

E-Mail Website
Guest Editor
Radiology Unit, Department of Pathology and Diagnostics, Azienda Ospedaliera Universitaria Integrata, 37126 Verona, Italy
Interests: oncologic imaging; computed tomography; ultrasound

Special Issue Information

Dear Colleagues,

Many important organ systems, e.g., the hepatobiliary–pancreatic, gastrointestinal and genitourinary ones, are located in the abdomen, which can be affected by heterogeneous diseases, such as malignant and benign tumors and common and rare, acute and chronic non-neoplastic diseases. Imaging is used to initial diagnoses, which can be challenging sometimes. Moreover, it is pivotal for staging and treatment planning. The complexity of patients’ anatomy and of the diseases that can affect it and the increasing capabilities of state-of-the-art imaging and post-processing require the interpreting physician to be an expert. The role of radiomics and artificial intelligence in imaging is growing, and it is expected to grow even more in the near future. Therefore, radiologists and nuclear medicine physicians play an important role in managing patients.

In this Special Issue, we invite original research papers and comprehensive reviews on all aspects of abdominal imaging, from conventional and advanced imaging to post-processing, artificial intelligence and prognostication.

Prof. Dr. Giulia A. Zamboni
Dr. Maria Chiara Ambrosetti
Guest Editors

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.

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Published Papers (3 papers)

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Research

12 pages, 1214 KiB  
Article
Perfusion Computed Tomography for Assessing Pancreas Graft Volumetric Perfusion After Simultaneous Pancreas and Kidney Transplantation
by Ilya V. Dmitriev, Rustam Sh. Muslimov, Yuriy A. Anisimov, Svetlana P. Shchelykalina, Elena V. Grigorieva, Igor O. Shchekoturov, Natalya S. Serova and Sergey K. Ternovoy
Diagnostics 2024, 14(21), 2361; https://doi.org/10.3390/diagnostics14212361 - 23 Oct 2024
Viewed by 532
Abstract
Background: There is paucity of data in the available medical literature regarding the parameters of the volumetric perfusion of pancreas grafts. Methods: From 5 February 2016 to 23 December 2021, we performed perfusion computed tomography in 41 patients at different times after simultaneous [...] Read more.
Background: There is paucity of data in the available medical literature regarding the parameters of the volumetric perfusion of pancreas grafts. Methods: From 5 February 2016 to 23 December 2021, we performed perfusion computed tomography in 41 patients at different times after simultaneous pancreas and kidney transplantation. The study group consisted of 18 men (44%) and 23 women (56%) with a long history of type 1 diabetes mellitus complicated by terminal chronic renal failure. The results of the perfusion computed tomography of the pancreas graft were studied, and the effects of post-transplantation timing and graft revascularization peculiarities on volumetric perfusion parameters were evaluated. Results: The median arterial blood flow, arterial blood volume, and permeability of the pancreas graft were 115.1 [99.7;130.3] mL/100 mL/min, 46.7 [37.4;56.9] mL/min, and 8.6 [4.1;11.4] mL/100 mL/min, respectively. No statistically significant differences in the averaged perfusion values were found in the head, body, and tail of the pancreas graft. The post-transplantation timing and the number of arteries involved in graft revascularization did not have a significant effect on the volumetric perfusion of the graft. Conclusion: The volumetric perfusion results of the pancreas graft correspond to those obtained in the study of pancreatic perfusion in healthy participants. Full article
(This article belongs to the Special Issue Abdominal Imaging: Recent Advances and Future Trends)
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9 pages, 1716 KiB  
Article
Quantitative Edge Analysis Can Differentiate Pancreatic Carcinoma from Normal Pancreatic Parenchyma
by Maria Chiara Ambrosetti, Alberto Ambrosetti, Matilde Bariani, Giuseppe Malleo, Giancarlo Mansueto and Giulia A. Zamboni
Diagnostics 2024, 14(15), 1681; https://doi.org/10.3390/diagnostics14151681 - 2 Aug 2024
Viewed by 802
Abstract
This study aimed to introduce specific image feature analysis, focusing on pancreatic margins, and to provide a quantitative measure of edge irregularity, evidencing correlations with the presence/absence of pancreatic adenocarcinoma. We selected 50 patients (36 men, 14 women; mean age 63.7 years) who [...] Read more.
This study aimed to introduce specific image feature analysis, focusing on pancreatic margins, and to provide a quantitative measure of edge irregularity, evidencing correlations with the presence/absence of pancreatic adenocarcinoma. We selected 50 patients (36 men, 14 women; mean age 63.7 years) who underwent Multi-detector computed tomography (MDCT) for the staging of pancreatic adenocarcinoma of the tail of the pancreas. Computer-assisted quantitative edge analysis was performed on the border fragments in MDCT images of neoplastic and healthy glandular parenchyma, from which we obtained the root mean square deviation SD of the actual border from the average boundary line. The SD values relative to healthy and neoplastic borders were compared using a paired t-test. A significant SD difference was observed between healthy and neoplastic borders. A threshold SD value was also found, enabling the differentiation of adenocarcinoma with 96% specificity and sensitivity. We introduced a quantitative measure of boundary irregularity, which correlates with the presence/absence of pancreatic adenocarcinoma. Quantitative edge analysis can be promptly performed on select border fragments in MDCT images, providing a useful supporting tool for diagnostics and a possible starting point for machine learning recognition based on lower-dimensional feature space. Full article
(This article belongs to the Special Issue Abdominal Imaging: Recent Advances and Future Trends)
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11 pages, 885 KiB  
Article
Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline 18F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?
by Ricarda Hinzpeter, Seyed Ali Mirshahvalad, Roshini Kulanthaivelu, Andres Kohan, Claudia Ortega, Ur Metser, Amy Liu, Adam Farag, Elena Elimova, Rebecca K. S. Wong, Jonathan Yeung, Raymond Woo-Jun Jang and Patrick Veit-Haibach
Diagnostics 2024, 14(11), 1205; https://doi.org/10.3390/diagnostics14111205 - 6 Jun 2024
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Abstract
We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to [...] Read more.
We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients. Full article
(This article belongs to the Special Issue Abdominal Imaging: Recent Advances and Future Trends)
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