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Tomography
Special Issues
Imaging in Cancer Diagnosis
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Imaging in Cancer Diagnosis

A special issue of Tomography (ISSN 2379-139X). This special issue belongs to the section "Cancer Imaging".

Deadline for manuscript submissions: 25 April 2025 | Viewed by 2361

Special Issue Editor

Dr. Filippo Crimì

E-Mail Website
Guest Editor
Institute of Radiology, Department of Medicine—DIMED, University of Padua, 35128 Padua, Italy
Interests: MRI; PET; diagnostic imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Imaging is a fundamental tool in cancer diagnosis, as it plays a role in almost all clinical oncology protocols. The data that can be extracted from tissues are not only structural or morphological but also functional and metabolic.

The standardization of radiology reporting promoted by all major scientific societies aims to significantly reduce the need to perform invasive procedures such as biopsies with high risk of complications, especially in patients who, based on imaging assessment, have a low risk of having cancer. Therefore, the need for subspecialized radiologists in each field of oncologic imaging is critical to properly refer patients, and research in this field is increasing so as to improve patient care.

Artificial intelligence is emerging as a powerful new tool for tissue characterization from radiological images. Hence, its application in the diagnosis of cancer diseases is opening up new avenues that could broaden the spectrum of cancers that can be targeted earlier for therapy. From ultrasound to the most sophisticated MRI machines, these advances in imaging are driving changes that could revolutionize the way radiology is perceived.

The purpose of this Special Issue is to highlight new techniques that can improve the diagnostic capabilities of imaging in cancer, providing new tools for physicians and radiologists. We welcome submissions of original research articles, comprehensive reviews, and case reports focusing on the aforementioned topic.

Dr. Filippo Crimì
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. Tomography is an international peer-reviewed open access monthly 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 2400 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

  • CT
  • MRI
  • US
  • cancer
  • diagnosis

Published Papers (3 papers)

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Editorial

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4 pages, 188 KiB  
Editorial
Introduction to Special Issue Imaging in Cancer Diagnosis
by Chiara Zanon, Emilio Quaia and Filippo Crimì
Tomography 2024, 10(1), 101-104; https://doi.org/10.3390/tomography10010009 - 15 Jan 2024
Viewed by 867
Abstract
In the field of oncology, the precision of cancer imaging is the cornerstone of oncological patient care [...] Full article
(This article belongs to the Special Issue Imaging in Cancer Diagnosis)

Research

Jump to: Editorial

12 pages, 5522 KiB  
Article
Comprehensive CT Imaging Analysis of Primary Colorectal Squamous Cell Carcinoma: A Retrospective Study
by Eun Ju Yoon, Sang Gook Song, Jin Woong Kim, Hyun Chul Kim, Hyung Joong Kim, Young Hoe Hur and Jun Hyung Hong
Tomography 2024, 10(5), 674-685; https://doi.org/10.3390/tomography10050052 - 1 May 2024
Viewed by 330
Abstract
The aim of this study was to evaluate the findings of CT scans in patients with pathologically confirmed primary colorectal squamous-cell carcinoma (SCC). The clinical presentation and CT findings in eight patients with pathologically confirmed primary colorectal squamous-cell carcinoma were retrospectively reviewed by [...] Read more.
The aim of this study was to evaluate the findings of CT scans in patients with pathologically confirmed primary colorectal squamous-cell carcinoma (SCC). The clinical presentation and CT findings in eight patients with pathologically confirmed primary colorectal squamous-cell carcinoma were retrospectively reviewed by two gastrointestinal radiologists. Hematochezia was the most common symptom (n = 5). The tumors were located in the rectum (n = 7) and sigmoid colon (n = 1). The tumors showed circumferential wall thickening (n = 4), bulky mass (n = 3), or eccentric wall thickening (n = 1). The mean maximal wall thickness of the involved segment was 29.1 mm ± 13.4 mm. The degree of tumoral enhancement observed via CT was well enhanced (n = 4) or moderately enhanced (n = 4). Necrosis within the tumor was found in five patients. The mean total number of metastatic lymph nodes was 3.1 ± 3.3, and the mean short diameter of the largest metastatic lymph node was 16.6 ± 5.7 mm. Necrosis within the metastatic node was observed in six patients. Invasions to adjacent organs were identified in five patients (62.5%). Distant metastasis was detected in only one patient. In summary, primary SCCs that arise from the colorectum commonly present as marked invasive wall thickening or a bulky mass with heterogeneous well-defined enhancement, internal necrosis, and large metastatic lymphadenopathies. Full article
(This article belongs to the Special Issue Imaging in Cancer Diagnosis)
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11 pages, 949 KiB  
Article
The Relationship between Liver Volume, Clinicopathological Characteristics and Survival in Patients Undergoing Resection with Curative Intent for Non-Metastatic Colonic Cancer
by Josh McGovern, Charles Mackay, Rhiannon Freireich, Allan M. Golder, Ross D. Dolan, Paul G. Horgan, David Holroyd, Nigel B. Jamieson and Donald C. McMillan
Tomography 2024, 10(3), 349-359; https://doi.org/10.3390/tomography10030027 - 28 Feb 2024
Viewed by 686
Abstract
Introduction: The prognostic value of CT-derived liver volume in terms of cancer outcomes is not clear. The aim of the present study was to examine the relationship between liver area on a single axial CT-slice and the total liver volume in patients with [...] Read more.
Introduction: The prognostic value of CT-derived liver volume in terms of cancer outcomes is not clear. The aim of the present study was to examine the relationship between liver area on a single axial CT-slice and the total liver volume in patients with colonic cancer. Furthermore, we examine the relationship between liver volume, determined using this novel method, clinicopathological variables and survival. Methods: Consecutive patients who underwent potentially curative surgery for colonic cancer were identified from a prospectively maintained database. Maximal liver area on axial CT-slice (cm2) and total volume (cm3), were obtained by the manual segmentation of pre-operative CT-images in a PACS viewer. The maximal liver area was normalized for body height2 to create the liver index (LI) and values, categorized into tertiles. The primary outcome of interest was overall survival (OS). Relationships between LI and clinico-pathological variables were examined using chi-square analysis and binary logistic regression. The relationship between LI and OS was examined using cox proportional hazard regression. Results: A total of 359 patients were included. A total of 51% (n = 182) of patients were male and 73% (n = 261) were aged 65 years or older. 81% (n = 305) of patients were alive 3-years post-operatively. The median maximal liver area on the axial CT slice was 178.7 (163.7–198.4) cm2. The median total liver volume was 1509.13 (857.8–3337.1) cm3. Maximal liver area strongly correlated with total liver volume (R2 = 0.749). The median LI was 66.8 (62.0–71.6) cm2/m2. On multivariate analysis, age (p < 0.001), sex (p < 0.05), BMI (p < 0.001) and T2DM (p < 0.05) remained significantly associated with LI. On univariate analysis, neither LI (continuous) or LI (tertiles) were significantly associated with OS (p = 0.582 and p = 0.290, respectively). Conclusions: The simple, reliable method proposed in this study for quantifying liver volume using CT-imaging was found to have an excellent correlation between observers and provided results consistent with the contemporary literature. This method may facilitate the further examination of liver volume in future cancer studies. Full article
(This article belongs to the Special Issue Imaging in Cancer Diagnosis)
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