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Diagnostic Assessment of Clinical Challenges in the Era of High...
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Diagnostic Assessment of Clinical Challenges in the Era of High Technology

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: closed (30 November 2023) | Viewed by 3210

Special Issue Editor

Dr. Giacomo Sica

E-Mail Website
Guest Editor
Department of Radiology, Monaldi Hospital, Azienda Ospedaliera dei Colli, 80131 Naples, Italy
Interests: computed tomography; magnetic resonance; cancer imaging; radiology; abdominal radiography; magnetic resonance imaging; diagnostic radiology; trauma; chest imaging; cardiac CT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since its first applications in medicine, diagnostic imaging has contributed to providing fundamental elements to support clinical diagnosis. Despite this, to date, there are still many unresolved clinical challenges in which imaging may not provide adequate support. In recent years, new CT and MR scanners and new postprocessing software have reached such high levels of technology and performance as to promise a revolution in the diagnostic field and in the support it provides to clinical challenges. For example, less time-consuming and more dose-saving CT scanners made it possible to significantly shorten diagnostic times in acute settings by supporting the high index of the clinical suspicion of a life-threatening disease requiring timely confirmation by a radiologist. However, clinical challenges may concern elective cases in which even in the absence of life-threatening conditions, the diagnosis is uncertain, as, for example, in the evaluation of oncological therapies supported, to date, by advanced imaging techniques. Finally, it is not possible to discuss the technological evolution applied to diagnostic imaging without remembering the acceleration of the integration of artificial intelligence, radiomics, and deep learning in diagnostic imaging and how these tools have become a hot topic in the post-pandemic era.

Dr. Giacomo Sica
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

  • emergency
  • oncological imaging
  • MRI
  • CT
  • radiomics
  • artificial intelligence
  • vascular imaging

Published Papers (3 papers)

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Research

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13 pages, 2044 KiB  
Article
Diagnostic Accuracy in Detecting Fungal Infection with Ultra-Low-Dose Computed Tomography (ULD-CT) Using Filtered Back Projection (FBP) Technique in Immunocompromised Patients
by Luigia D’Errico, Anita Ghali, Mini Pakkal, Micheal McInnis, Hatem Mehrez, Andre C. Schuh, John G. Kuruvilla, Mark Minden and Narinder S. Paul
J. Clin. Med. 2024, 13(6), 1704; https://doi.org/10.3390/jcm13061704 - 15 Mar 2024
Viewed by 1042
Abstract
Purpose: To compare the accuracy of ultra-low-dose (uLDCT) to standard-of-care low-dose chest CT (LDCT) in the detection of fungal infection in immunocompromised (IC) patients. Method and Materials: One hundred IC patients had paired chest CT scans performed with LDCT followed by uLDCT. The [...] Read more.
Purpose: To compare the accuracy of ultra-low-dose (uLDCT) to standard-of-care low-dose chest CT (LDCT) in the detection of fungal infection in immunocompromised (IC) patients. Method and Materials: One hundred IC patients had paired chest CT scans performed with LDCT followed by uLDCT. The images were independently reviewed by three chest radiologists who assessed the image quality (IQ), diagnostic confidence, and detection of major (macro nodules, halo sign, cavitation, consolidation) and minor (4–10 mm nodules, ground-glass opacity) criteria for fungal disease using a five-point Likert score. Discrepant findings were adjudicated by a fourth chest radiologist. Box–whisker plots were used to analyze IQ and diagnostic confidence. Inter-rater reliability was assessed using interclass correlation coefficients (ICCs). The statistical difference between LDCT and uLDCT results was assessed using Wilcoxon paired test. Results: Lung reconstructions had IQ and diagnostic confidence scores (mean ± std) of 4.52 ± 0.47 and 4.63 ± 0.51 for LDCT and 3.85 ± 0.77 and 4.01 ± 0.88 for uLDCT. The images were clinically acceptable except for uLDCT in obese patients (BMI ≥ 30 kg/m2), which had an IQ ranking from poor to excellent (scores 1 to 5). The accuracy in detecting major and minor radiological findings with uLDCT was 96% and 84% for all the patients. The inter-rater agreements were either moderate, good, or excellent, with ICC values of 0.51–0.96. There was no significant statistical difference between the uLDCT and LDCT ICC values (p = 0.25). The effective dose for uLDCT was one quarter that of LDCT (CTDIvol = 0.9 mGy vs. 3.7 mGy). Conclusions: Thoracic uLDCT, at a 75% dose reduction, can replace LDCT for the detection of fungal disease in IC patients with BMI < 30.0 kg/m2. Full article
(This article belongs to the Special Issue Diagnostic Assessment of Clinical Challenges in the Era of High Technology)
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Review

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24 pages, 11042 KiB  
Review
Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics
by Piero Trovato, Igino Simonetti, Alessio Morrone, Roberta Fusco, Sergio Venanzio Setola, Giuliana Giacobbe, Maria Chiara Brunese, Annarita Pecchi, Sonia Triggiani, Giuseppe Pellegrino, Giuseppe Petralia, Giacomo Sica, Antonella Petrillo and Vincenza Granata
J. Clin. Med. 2024, 13(2), 547; https://doi.org/10.3390/jcm13020547 - 18 Jan 2024
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Abstract
Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50–61% of all renal tumors are found incidentally. Methods: [...] Read more.
Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50–61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context. Full article
(This article belongs to the Special Issue Diagnostic Assessment of Clinical Challenges in the Era of High Technology)
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14 pages, 261 KiB  
Review
Application of Advanced Imaging to Prostate Cancer Diagnosis and Management: A Narrative Review of Current Practice and Unanswered Questions
by Elizabeth L. McKone, Elsa A. Sutton, Geoffrey B. Johnson and Ryan M. Phillips
J. Clin. Med. 2024, 13(2), 446; https://doi.org/10.3390/jcm13020446 - 13 Jan 2024
Viewed by 745
Abstract
Major advances in prostate cancer diagnosis, staging, and management have occurred over the past decade, largely due to our improved understanding of the technical aspects and clinical applications of advanced imaging, specifically magnetic resonance imaging (MRI) and prostate-cancer-specific positron emission tomography (PET). Herein, [...] Read more.
Major advances in prostate cancer diagnosis, staging, and management have occurred over the past decade, largely due to our improved understanding of the technical aspects and clinical applications of advanced imaging, specifically magnetic resonance imaging (MRI) and prostate-cancer-specific positron emission tomography (PET). Herein, we review the established utility of these important and exciting technologies, as well as areas of controversy and uncertainty that remain important areas for future study. There is strong evidence supporting the utility of MRI in guiding initial biopsy and assessing local disease. There is debate, however, regarding how to best use the imaging modality in risk stratification, treatment planning, and assessment of biochemical failure. Prostate-cancer-specific PET is a relatively new technology that provides great value to the evaluation of newly diagnosed, treated, and recurrent prostate cancer. However, its ideal use in treatment decision making, staging, recurrence detection, and surveillance necessitates further research. Continued study of both imaging modalities will allow for an improved understanding of their best utilization in improving cancer care. Full article
(This article belongs to the Special Issue Diagnostic Assessment of Clinical Challenges in the Era of High Technology)
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