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Diagnostics
Special Issues
The Role of Radiology Imaging in Oncology
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The Role of Radiology Imaging in Oncology

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 April 2023) | Viewed by 22491

Special Issue Editors

Dr. Marta Zerunian

E-Mail Website
Guest Editor
Department of Surgical and Medical Sciences and Translational Medicine, Sapienza-University of Rome, 00189 Rome, Italy
Interests: oncologic imaging; quantitative imaging; artificial intelligence application; MRI; radiomics
Special Issues, Collections and Topics in MDPI journals
Dr. Domenico De Santis

E-Mail Website
Guest Editor
Department of Medical Surgical Sciences and Translational Medicine, Sapienza University of Rome, Radiology Unit—Sant’Andrea University Hospital, Via di Grottarossa, 1035, 00189 Rome, Italy
Interests: chest CT; radiomics; lung cancer; tuberculosis; multidetector computed tomography; texture analysis; oncology; precision medicine; lung imaging

Special Issue Information

Dear Colleagues,

Currently, radiology imaging plays a pivotal role in diagnosis and patient follow-up in the oncology field. In fact, thanks to different imaging modalities (X-ray, mammography, ultrasound, computed tomography, magnetic resonance imaging), there are multiple strategies to detect tumors and help other medical subspecialties to choose the best patient treatment options. In fact, due to the incredibly fast technological radiology innovations, we have improved tumor diagnosis to the next level, moving ever closer to precision medicine.

Innovations such as radiomics, artificial intelligence, and quantitative imaging are perfectly integrated with radiology imaging, and scientific research in the oncology field is necessary to explore all the possibilities we have to improve our diagnostic accuracy in tumor diagnosis and characterization. More comprehensive tumor diagnosis will enable dedicated treatment options such as immunotherapy or target therapy tailored to specific imaging characteristics, to reduce non-responder patients and improve survival.

The aim of this Special Issue is to collect innovative research in oncology imaging according to the most recent radiological innovations.

In line with the aim of the journal, we encourage authors to submit original research based on new radiological imaging developments in oncologic imaging.

We invite authors from different radiological imaging subspecialties to share their advancements in knowledge in different types of tumors, with both original works and review articles on tumor diagnosis, characterization, and follow-up.

Dr. Marta Zerunian
Dr. Domenico De Santis
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.

Keywords

  • imaging diagnosis
  • quantitative imaging
  • oncologic imaging
  • artificial intelligence
  • radiomics

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Published Papers (4 papers)

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Research

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13 pages, 2262 KiB  
Article
Vascular Enlargement as a Predictor of Nodal Involvement in Bladder Cancer
by Alessandra Borgheresi, Andrea Agostini, Francesca Sternardi, Elisa Cesari, Fiammetta Ventura, Letizia Ottaviani, Rocco Francesco Delle Fave, Eugenio Pretore, Alessia Cimadamore, Alessandra Filosa, Andrea Benedetto Galosi and Andrea Giovagnoni
Diagnostics 2023, 13(13), 2227; https://doi.org/10.3390/diagnostics13132227 - 30 Jun 2023
Cited by 2 | Viewed by 1665
Abstract
In bladder cancer (BC), the evaluation of lymph node (LN) involvement at preoperative imaging lacks specificity. Since neoangiogenesis is paired with lymphatic involvement, this study aims to evaluate the presence of perivesical venous ectasia as an indirect sign of LN involvement, together with [...] Read more.
In bladder cancer (BC), the evaluation of lymph node (LN) involvement at preoperative imaging lacks specificity. Since neoangiogenesis is paired with lymphatic involvement, this study aims to evaluate the presence of perivesical venous ectasia as an indirect sign of LN involvement, together with other conventional CT findings. All the patients who underwent radical cystectomy (RC) for BC between January 2017 and December 2019 with available preoperative contrast-enhanced CT (CECT) within 1 month before surgery were included. Patients without available pathological reports (and pTNM stage) or who underwent neoadjuvant treatments and palliative RC were excluded. Two readers in blind assessed the nodal shape and hilum, the short axis, and the contrast enhancement of suspicious pelvic LNs, the Largest Venous Diameter (LVD) efferent to the lesion, and the extravesical tumor invasion. In total, 38 patients (33 males) were included: 17 pT2, 17 pT3, 4 pT4; pN+: 20/38. LN short axis > 5 mm, LN enhancement, and LVD > 3 mm were significantly correlated with N+ at pathology. LVD > 3 mm had a significantly higher sensitivity and specificity (≥90%, AUC = 0.949) and was an independent predictor (p = 0.0016). Full article
(This article belongs to the Special Issue The Role of Radiology Imaging in Oncology)
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12 pages, 1378 KiB  
Article
Whole-Tumor ADC Texture Analysis Is Able to Predict Breast Cancer Receptor Status
by Madalina Szep, Roxana Pintican, Bianca Boca, Andra Perja, Magdalena Duma, Diana Feier, Flavia Epure, Bogdan Fetica, Dan Eniu, Andrei Roman, Sorin Marian Dudea and Angelica Chiorean
Diagnostics 2023, 13(8), 1414; https://doi.org/10.3390/diagnostics13081414 - 14 Apr 2023
Cited by 5 | Viewed by 2043
Abstract
There are different breast cancer molecular subtypes with differences in incidence, treatment response and outcome. They are roughly divided into estrogen and progesterone receptor (ER and PR) negative and positive cancers. In this retrospective study, we included 185 patients augmented with 25 SMOTE [...] Read more.
There are different breast cancer molecular subtypes with differences in incidence, treatment response and outcome. They are roughly divided into estrogen and progesterone receptor (ER and PR) negative and positive cancers. In this retrospective study, we included 185 patients augmented with 25 SMOTE patients and divided them into two groups: the training group consisted of 150 patients and the validation cohort consisted of 60 patients. Tumors were manually delineated and whole-volume tumor segmentation was used to extract first-order radiomic features. The ADC-based radiomics model reached an AUC of 0.81 in the training cohort and was confirmed in the validation set, which yielded an AUC of 0.93, in differentiating ER/PR positive from ER/PR negative status. We also tested a combined model using radiomics data together with ki67% proliferation index and histological grade, and obtained a higher AUC of 0.93, which was also confirmed in the validation group. In conclusion, whole-volume ADC texture analysis is able to predict hormonal status in breast cancer masses. Full article
(This article belongs to the Special Issue The Role of Radiology Imaging in Oncology)
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12 pages, 1070 KiB  
Article
The Role of mpMRI in the Assessment of Prostate Cancer Recurrence Using the PI-RR System: Diagnostic Accuracy and Interobserver Agreement in Readers with Different Expertise
by Chiara Bergaglio, Veronica Giasotto, Michela Marcenaro, Salvina Barra, Marianna Turazzi, Matteo Bauckneht, Alessandro Casaleggio, Francesca Sciabà, Carlo Terrone, Guglielmo Mantica, Marco Borghesi, Alessio Signori, Bruno Spina, Nataniele Piol, Elisa Zanardi, Giuseppe Fornarini and Jeries Paolo Zawaideh
Diagnostics 2023, 13(3), 387; https://doi.org/10.3390/diagnostics13030387 - 20 Jan 2023
Cited by 11 | Viewed by 3124
Abstract
Background: treated prostate cancer (PCa) patients develop biochemical recurrence (BCR) in 27–53% of cases; the role of MRI in this setting is still controversial. In 2021 a panel of experts proposed a “Prostate Imaging-Recurrence Reporting” (PI-RR) score, aiming to standardize the reporting. The [...] Read more.
Background: treated prostate cancer (PCa) patients develop biochemical recurrence (BCR) in 27–53% of cases; the role of MRI in this setting is still controversial. In 2021 a panel of experts proposed a “Prostate Imaging-Recurrence Reporting” (PI-RR) score, aiming to standardize the reporting. The aim of our study is to evaluate the reproducibility of the PI-RR scoring system among readers with different expertise. Methods: in this monocentric, retrospective observational study, the images of patients who underwent MRI with BCR from January 2017 to January 2022 were analyzed by two radiologists and a radiology resident. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were obtained. Interobserver agreement was calculated. The percentage of the PI-RR score of 3 was estimated to find out the proportion of uncertain exams reported among the readers. Results: a total of seventy-six patients were included in our study: eight previously treated with RT and sixty-eight who underwent surgery. The accuracy range was 75–80%, the sensitivity 68.4–71.1%, the specificity 81.6–89.5%, PPV 78.8–87.1%, and NPV 72.1–75.6%. The inter-reader agreement using a binary evaluation (PI-RR ≥ 3 as positive mpMRI) demonstrated a correlation coefficient (k) of 0.74 (95% CI: 0.62–0.87). The percentage for the PI-RR score of 3 was 6.6% for reader one, 14.5% for reader two, and 2.6% for reader three. Conclusion: this study confirmed the good accuracy of mpMRI in the detection of local recurrence of PCa and the good reproducibility of PI-RR score among all readers, confirming it to be a promising tool for the standardization of the assessment of patients with BCR. Full article
(This article belongs to the Special Issue The Role of Radiology Imaging in Oncology)
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Review

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19 pages, 16680 KiB  
Review
Imaging in Gastric Cancer: Current Practice and Future Perspectives
by Teresa Giandola, Cesare Maino, Giuseppe Marrapodi, Michele Ratti, Maria Ragusi, Vittorio Bigiogera, Cammillo Talei Franzesi, Rocco Corso and Davide Ippolito
Diagnostics 2023, 13(7), 1276; https://doi.org/10.3390/diagnostics13071276 - 28 Mar 2023
Cited by 14 | Viewed by 14700
Abstract
Gastric cancer represents one of the most common oncological causes of death worldwide. In order to treat patients in the best possible way, the staging of gastric cancer should be accurate. In this regard, endoscopy ultrasound (EUS) has been considered the reference standard [...] Read more.
Gastric cancer represents one of the most common oncological causes of death worldwide. In order to treat patients in the best possible way, the staging of gastric cancer should be accurate. In this regard, endoscopy ultrasound (EUS) has been considered the reference standard for tumor (T) and nodal (N) statuses in recent decades. However, thanks to technological improvements, computed tomography (CT) has gained an important role, not only in the assessment of distant metastases (M status) but also in T and N staging. In addition, magnetic resonance imaging (MRI) can contribute to the detection and staging of primary gastric tumors thanks to its excellent soft tissue contrast and multiple imaging sequences without radiation-related risks. In addition, MRI can help with the detection of liver metastases, especially small lesions. Finally, positron emission tomography (PET) is still considered a useful diagnostic tool for the staging of gastric cancer patients, with a focus on nodal metastases and peritoneal carcinomatosis. In addition, it may play a role in the treatment of gastric cancer in the coming years thanks to the introduction of new labeling peptides. This review aims to summarize the most common advantages and pitfalls of EUS, CT, MRI and PET in the TNM staging of gastric cancer patients. Full article
(This article belongs to the Special Issue The Role of Radiology Imaging in Oncology)
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