Submit to Cancers Review for Cancers Propose a Special Issue

Journal Browser

Advanced Oncologic Imaging

Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Causes, Screening and Diagnosis".

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 55582

Share This Special Issue

Special Issue Editors

Prof. Dr. Mirko D'Onofrio

E-Mail Website
Guest Editor

Department of Radiology, G.B. Rossi University Hospital, University of Verona, 37129 Verona, Italy
Interests: MRI abdominal imaging; oncologic imaging; radiofrequency ablation; CT; ultrasound; pancreatic cancer; biopsy
Special Issues, Collections and Topics in MDPI journals

Prof. Maria Antonietta Bali

E-Mail
Guest Editor

Department of Radiology, Institut Jules Bordet, 1 Rue Héger-Bordet, 1000 – Bruxelles, Belgium

Prof. Maxime Ronot

E-Mail
Guest Editor

Department of Radiology, Hopital Beaujon, Paris, France

Special Issue Information

Dear Colleagues,

Imaging diagnosis can be assisted by computed analysis. Tumor-specific aspect is one of the possible representations of human cancer at imaging, while others come from the analysis of data acquired during examination. At present, new parameters can be evaluated using computer-assisted imaging analysis that would be otherwise invisible. These new parameters are inside the images but not visible during standard radiological evaluation and reporting. Therefore, new imaging analysis can be used for oncologic evaluations and response to therapy. For example, texture analysis supplies an evaluation of tumor heterogeneity by imaging and analyzing pixel or voxel gray level distributions and relationships in the image, also giving information on the tumor microenvironment. In particular, texture analysis that evaluates pixel values, variations, and distributions could predict tumor pathologic grade, features, relapse risk, response to therapy, and therefore patients’ overall survival and prognosis. In summary, the computed analysis of imaging could cover new significant roles, such as the evaluation of tumor aggressiveness and prognostic prediction.

The aim of this Special Issue is to present the most common advanced oncologic imaging on CT and MRI, from texture analysis to quantification imaging on MRI, showing examples of computer-assisted imaging analysis adding value that is useful for diagnosis and oncology patient management.

Prof. Mirko D'Onofrio
Prof. Maria Antonietta Bali
Prof. Maxime Ronot
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. Cancers 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 2900 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

oncologic imaging
CT, texture analysis
MRI, DWI
cancer imaging
tumor grade and aggressiveness
cancer prognosis
assessment of tumor response

Published Papers (13 papers)

Download All Papers

Research

Jump to: Review, Other

15 pages, 1671 KiB

Open AccessArticle

Using Genomics Feature Selection Method in Radiomics Pipeline Improves Prognostication Performance in Locally Advanced Esophageal Squamous Cell Carcinoma—A Pilot Study

by Chen-Yi Xie, Yi-Huai Hu, Joshua Wing-Kei Ho, Lu-Jun Han, Hong Yang, Jing Wen, Ka-On Lam, Ian Yu-Hong Wong, Simon Ying-Kit Law, Keith Wan-Hang Chiu, Jian-Hua Fu and Varut Vardhanabhuti

Cancers 2021, 13(9), 2145; https://doi.org/10.3390/cancers13092145 - 29 Apr 2021

Cited by 17 | Viewed by 3265

Abstract

Purpose: To evaluate the prognostic value of baseline and restaging CT-based radiomics with features associated with gene expression in esophageal squamous cell carcinoma (ESCC) patients receiving neoadjuvant chemoradiation (nCRT) plus surgery. Methods: We enrolled 106 ESCC patients receiving nCRT from two institutions. Gene expression profiles of 28 patients in the training set were used to detect differentially expressed (DE) genes between patients with and without relapse. Radiomic features that were correlated to DE genes were selected, followed by additional machine learning selection. A radiomic nomogram for disease-free survival (DFS) prediction incorporating the radiomic signature and prognostic clinical characteristics was established for DFS estimation and validated. Results: The radiomic signature with DE genes feature selection achieved better performance for DFS prediction than without. The nomogram incorporating the radiomic signature and lymph nodal status significantly stratified patients into high and low-risk groups for DFS (p < 0.001). The areas under the curve (AUCs) for predicting 5-year DFS were 0.912 in the training set, 0.852 in the internal test set, 0.769 in the external test set. Conclusions: Genomics association was useful for radiomic feature selection. The established radiomic signature was prognostic for DFS. The radiomic nomogram could provide a valuable prediction for individualized long-term survival. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

9 pages, 2165 KiB

Open AccessArticle

CT Simplified Radiomic Approach to Assess the Metastatic Ductal Adenocarcinoma of the Pancreas

by Mirko D’Onofrio, Riccardo De Robertis, Gregorio Aluffi, Camilla Cadore, Alessandro Beleù, Nicolò Cardobi, Giuseppe Malleo, Erminia Manfrin and Claudio Bassi

Cancers 2021, 13(8), 1843; https://doi.org/10.3390/cancers13081843 - 13 Apr 2021

Cited by 4 | Viewed by 1715

Abstract

The aim of this study was to perform a simplified radiomic analysis of pancreatic ductal adenocarcinoma based on qualitative and quantitative tumor features and to compare the results between metastatic and non-metastatic patients. A search of our radiological, surgical, and pathological databases identified 1218 patients with a newly diagnosed pancreatic ductal adenocarcinoma who were referred to our Institution between January 2014 and December 2018. Computed Tomography (CT) examinations were reviewed analyzing qualitative and quantitative features. Two hundred eighty-eight patients fulfilled the inclusion criteria and were included in this study. Overall, metastases were present at diagnosis in 86/288 patients, while no metastases were identified in 202/288 patients. Ill-defined margins and a hypodense appearance on portal-phase images were significantly more common among patients with metastases compared to non-metastatic patients (p < 0.05). Metastatic tumors showed a significantly larger size and significantly lower arterial index, perfusion index, and permeability index compared to non-metastatic tumors (p < 0.05). In the management of pancreatic ductal adenocarcinoma, early detection and correct staging are key elements. The study of computerized tomography characteristics of pancreatic ductal adenocarcinoma showed substantial differences, both qualitative and quantitative, between metastatic and non-metastatic disease. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

16 pages, 3341 KiB

Open AccessArticle

Atypical Response Patterns in Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors—Navigating the Radiologic Potpourri

by Alvin Wong, Balamurugan Vellayappan, Lenith Cheng, Joseph J. Zhao, Vaishnavi Muthu, Yugarajah Asokumaran, Jia-Li Low, Matilda Lee, Yi-Qing Huang, Nesaretnam Barr Kumarakulasinghe, Natalie Ngoi, Cheng-Nang Leong, Wynne Chua and Yee-Liang Thian

Cancers 2021, 13(7), 1689; https://doi.org/10.3390/cancers13071689 - 02 Apr 2021

Cited by 7 | Viewed by 2726

Abstract

Background: Atypical response patterns have been a topic of increasing relevance since the advent of immune checkpoint inhibitors (ICIs), challenging the traditional RECIST (Response Evaluation Criteria in Solid Tumors) method of tumor response assessment. Newer immune-related response criteria can allow for the evolution of radiologic pseudoprogression, but still fail to capture the full range of atypical response patterns encountered in clinical reporting. Methods: We did a detailed lesion-by-lesion analysis of the serial imaging of 46 renal cell carcinoma (RCC) patients treated with ICIs with the aim of capturing the full range of radiologic behaviour. Results: Atypical response patterns observed included pseudoprogression (n = 15; 32.6%), serial pseudoprogression (n = 4; 8.7%), dissociated response (n = 22; 47.8%), abscopal response (n = 9; 19.6%), late response (n = 5; 10.9%), and durable response after cessation of immunotherapy (n = 2; 4.3%). Twenty-four of 46 patients (52.2%) had at least one atypical response pattern and 18 patients (39.1%) had multiple atypical response patterns. Conclusions: There is a high incidence of atypical response patterns in RCC patients receiving ICIs and the study contributes to the growing literature on the abscopal effect. The recognition of these interesting and overlapping radiologic patterns challenges the oncologist to tweak treatment options such that the clinical benefits of ICIs are potentially maximized. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

12 pages, 2172 KiB

Open AccessArticle

Role of Repeat PET/CT Imaging in Head and Neck Cancer Following Initial Incomplete PET/CT Response to Chemoradiation

by Austin J. Iovoli, Mark K. Farrugia, Sung Jun Ma, Jon M. Chan, Michael R. Markiewicz, Ryan McSpadden, Kimberly E. Wooten, Vishal Gupta, Moni A. Kuriakose, Wesley L. Hicks, Jr. and Anurag K. Singh

Cancers 2021, 13(6), 1461; https://doi.org/10.3390/cancers13061461 - 23 Mar 2021

Cited by 9 | Viewed by 2320

Abstract

Despite waiting 13 weeks to perform a PET/CT scan after completion of chemoradiation for head and neck squamous cell carcinoma (HNSCC), equivocal findings are often found that make assessing treatment response difficult. This retrospective study examines the utility of a repeat PET/CT scan in HNSCC patients following an incomplete response on initial post-treatment imaging. For this cohort of 350 patients, initial PET/CT was performed 13 weeks after completion of treatment. For select patients with an incomplete response, repeat PET/CT was performed a median of 91 days later. Primary endpoints were conversion rate to complete response (CR) and the predictive values of repeat PET/CT imaging. Of 179 patients who did not have an initial complete response, 57 (32%) received a repeat PET/CT scan. Among these patients, 26 of 57 (48%) had a CR on repeat PET/CT. In patients with CR conversion, there were no cases of disease relapse. The sensitivity, specificity, PPV, and NPV for the repeat PET/CT for locoregional disease were 100%, 59%, 42%, and 100%. Repeat PET/CT in HNSCC patients with an incomplete post-treatment scan can be valuable in obtaining diagnostic clarity. This can reduce the incidence of unnecessary biopsies and neck dissections. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

12 pages, 1402 KiB

Open AccessArticle

Dynamic Contrast-Enhanced MRI of Prostate Lesions of Simultaneous [⁶⁸Ga]Ga-PSMA-11 PET/MRI: Comparison between Intraprostatic Lesions and Correlation between Perfusion Parameters

by Jing Zhao, Avan Kader, Dilyana B. Mangarova, Julia Brangsch, Winfried Brenner, Bernd Hamm and Marcus R. Makowski

Cancers 2021, 13(6), 1404; https://doi.org/10.3390/cancers13061404 - 19 Mar 2021

Cited by 7 | Viewed by 3365

Abstract

We aimed to retrospectively compare the perfusion parameters measured from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of prostate benign lesions and malignant lesions to determine the relationship between perfusion parameters. DCE-MRI was performed in patients with PCa who underwent simultaneous [⁶⁸Ga]Ga-prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/MRI. Six perfusion parameters (arrival time (AT), time to peak (TTP), wash-in slope (W-in), wash-out slope (W-out), peak enhancement intensity (PEI), and initial area under the 60-s curve (iAUC)), and a semi-quantitative parameter, standardized uptake values maximum (SUVmax) were calculated by placing regions of interest in the largest area of the lesions. The DCE-MRI parameters between prostate benign and malignant lesions were compared. The DCE-MRI parameters in both the benign and malignant lesions subgroup with SUVmax ≤ 3.0 and SUVmax > 3.0 were compared. The correlation of DCE-MRI parameters was investigated. Malignant lesions demonstrated significantly shorter TTP and higher SUVmax than did benign lesions. In the benign and malignant lesions subgroup, perfusion parameters of lesions with SUVmax ≤ 3.0 show no significant difference to those with SUVmax > 3.0. DCE-MRI perfusion parameters show a close correlation with each other. DCE-MRI parameters reflect the perfusion characteristics of intraprostatic lesions with malignant lesions, demonstrating significantly shorter TTP. There is a moderate to strong correlation between DCE-MRI parameters. Semi-quantitative analysis reflects that malignant lesions show a significantly higher SUVmax than benign lesions. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

13 pages, 2394 KiB

Open AccessArticle

Structured Reporting Using CEUS LI-RADS for the Diagnosis of Hepatocellular Carcinoma (HCC)—Impact and Advantages on Report Integrity, Quality and Interdisciplinary Communication

by Thomas Geyer, Johannes Rübenthaler, Constantin Marschner, Malte von Hake, Matthias P. Fabritius, Matthias F. Froelich, Thomas Huber, Dominik Nörenberg, Johannes Rückel, Maximilian Weniger, Corinna Martens, Laura Sabel, Dirk-André Clevert and Vincent Schwarze

Cancers 2021, 13(3), 534; https://doi.org/10.3390/cancers13030534 - 31 Jan 2021

Cited by 6 | Viewed by 2495

Abstract

Background: Our retrospective single-center study aims to evaluate the impact of structured reporting (SR) using a CEUS LI-RADS template on report quality compared to conventional free-text reporting (FTR) in contrast-enhanced ultrasound (CEUS) for the diagnosis of hepatocellular carcinoma (HCC). Methods: We included 50 patients who underwent CEUS for HCC staging. FTR created after these examinations were compared to SR retrospectively generated by using template-based online software with clickable decision trees. The reports were evaluated regarding report completeness, information extraction, linguistic quality and overall report quality by two readers specialized in internal medicine and visceral surgery. Results: SR significantly increased report completeness with at least one key feature missing in 31% of FTR vs. 2% of SR (p < 0.001). Information extraction was considered easy in 98% of SR vs. 86% of FTR (p = 0.004). The trust of referring physicians in the report was significantly increased by SR with a mean of 5.68 for SR vs. 4.96 for FTR (p < 0.001). SR received significantly higher ratings regarding linguistic quality (5.79 for SR vs. 4.83 for FTR (p < 0.001)) and overall report quality (5.75 for SR vs. 5.01 for FTR (p < 0.001)). Conclusions: Using SR instead of conventional FTR increases the overall quality of reports in CEUS examinations of HCC patients and may represent a valuable tool to facilitate clinical decision-making and improve interdisciplinary communication in the future. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

17 pages, 3090 KiB

Open AccessArticle

Quantitative Imaging Parameters of Contrast-Enhanced Micro-Computed Tomography Correlate with Angiogenesis and Necrosis in a Subcutaneous C6 Glioma Model

by Lízbeth Ayala-Domínguez, Enrique Pérez-Cárdenas, Alejandro Avilés-Salas, Luis Alberto Medina, Marcela Lizano and María-Ester Brandan

Cancers 2020, 12(11), 3417; https://doi.org/10.3390/cancers12113417 - 18 Nov 2020

Cited by 2 | Viewed by 2365

Abstract

The aim of this work was to systematically obtain quantitative imaging parameters with static and dynamic contrast-enhanced (CE) X-ray imaging techniques and to evaluate their correlation with histological biomarkers of angiogenesis in a subcutaneous C6 glioma model. Enhancement (E), iodine concentration (C_I), and relative blood volume (rBV) were quantified from single- and dual-energy (SE and DE, respectively) micro-computed tomography (micro-CT) images, while rBV and volume transfer constant (K^trans) were quantified from dynamic contrast-enhanced (DCE) planar images. C_I and rBV allowed a better discernment of tumor regions from muscle than E in SE and DE images, while no significant differences were found for rBV and K^trans in DCE images. An agreement was found in rBV for muscle quantified with the different imaging protocols, and in C_I and E quantified with SE and DE protocols. Significant strong correlations (Pearson r > 0.7, p < 0.05) were found between a set of imaging parameters in SE images and histological biomarkers: E and C_I in tumor periphery were associated with microvessel density (MVD) and necrosis, E and C_I in the complete tumor with MVD, and rBV in the tumor periphery with MVD. In conclusion, quantitative imaging parameters obtained in SE micro-CT images could be used to characterize angiogenesis and necrosis in the subcutaneous C6 glioma model. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

17 pages, 5236 KiB

Open AccessArticle

Advanced Fusion Imaging and Contrast-Enhanced Imaging (CT/MRI–CEUS) in Oncology

by Vincent Schwarze, Johannes Rübenthaler, Constantin Marschner, Matthias Philipp Fabritius, Johannes Rueckel, Nicola Fink, Daniel Puhr-Westerheide, Eva Gresser, Matthias Frank Froelich, Moritz Ludwig Schnitzer, Nils Große Hokamp, Saif Afat, Michael Staehler, Thomas Geyer and Dirk-André Clevert

Cancers 2020, 12(10), 2821; https://doi.org/10.3390/cancers12102821 - 30 Sep 2020

Cited by 17 | Viewed by 2771

Abstract

Fusion imaging depicts an innovative technique that facilitates combining assets and reducing restrictions of advanced ultrasound and cross-sectional imaging. The purpose of the present retrospective study was to evaluate the role of fusion imaging for assessing hepatic and renal lesions. Between 02/2011–08/2020, 92 patients in total were included in the study, of which 32 patients had hepatic lesions, 60 patients had renal lesions. Fusion imaging was technically successful in all patients. No adverse side effects upon intravenous (i.v.) application of SonoVue^® (Bracco, Milan, Italy) were registered. Fusion imaging could clarify all 11 (100%) initially as indeterminate described hepatic lesions by computed tomography/magnetic resonance imaging (CT/MRI). Moreover, 5/14 (36%) initially suspicious hepatic lesions could be validated by fusion imaging, whereas in 8/14 (57%), malignant morphology was disproved. Moreover, fusion imaging allowed for the clarification of 29/30 (97%) renal lesions initially characterized as suspicious by CT/MRI, of which 19/30 (63%) underwent renal surgery, histopathology revealed malignancy in 16/19 (84%), and benignity in 3/19 (16%). Indeterminate findings could be elucidated by fusion imaging in 20/20 (100%) renal lesions. Its accessibility and repeatability, even during pregnancy and in childhood, its cost-effectiveness, and its excellent safety profile, make fusion imaging a promising instrument for the thorough evaluation of hepatic and renal lesions in the future. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

14 pages, 2818 KiB

Open AccessArticle

Follow-Up 18F-FDG PET/CT versus Contrast-Enhanced CT after Ablation of Liver Metastases of Colorectal Carcinoma—A Cost-Effectiveness Analysis

by Moritz L. Schnitzer, Matthias F. Froelich, Felix G. Gassert, Thomas Huber, Eva Gresser, Vincent Schwarze, Dominik Nörenberg, Andrei Todica and Johannes Rübenthaler

Cancers 2020, 12(9), 2432; https://doi.org/10.3390/cancers12092432 - 27 Aug 2020

Cited by 8 | Viewed by 2388

Abstract

Purpose: After a percutaneous ablation of colorectal liver metastases (CRLM), follow-up investigations to evaluate potential tumor recurrence are necessary. The aim of this study was to analyze whether a combined 18F-Fluordesoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) scan is cost-effective compared to a contrast-enhanced computed tomography (CE-CT) scan for detecting local tumor progression. Materials and Methods: A decision model based on Markov simulations that estimated lifetime costs and quality-adjusted life years (QALYs) was developed. Model input parameters were obtained from the recent literature. Deterministic sensitivity analysis of diagnostic parameters based on a Monte-Carlo simulation with 30,000 iterations was performed. The willingness-to-pay (WTP) was set to $100,000/QALY. Results: In the base-case scenario, CE-CT resulted in total costs of $28,625.08 and an efficacy of 0.755 QALYs, whereas 18F-FDG PET/CT resulted in total costs of $29,239.97 with an efficacy of 0.767. Therefore, the corresponding incremental cost-effectiveness ratio (ICER) of 18F-FDG PET/CT was $50,338.96 per QALY indicating cost-effectiveness based on the WTP threshold set above. The results were stable in deterministic and probabilistic sensitivity analyses. Conclusion: Based on our model, 18F-FDG PET/CT can be considered as a cost-effective imaging alternative for follow-up investigations after percutaneous ablation of colorectal liver metastases. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

14 pages, 4320 KiB

Open AccessArticle

Diffusion-Weighted MRI and Diffusion Kurtosis Imaging to Detect RAS Mutation in Colorectal Liver Metastasis

by Vincenza Granata, Roberta Fusco, Chiara Risi, Alessandro Ottaiano, Antonio Avallone, Alfonso De Stefano, Robert Grimm, Roberta Grassi, Luca Brunese, Francesco Izzo and Antonella Petrillo

Cancers 2020, 12(9), 2420; https://doi.org/10.3390/cancers12092420 - 26 Aug 2020

Cited by 46 | Viewed by 2907

Abstract

Objectives: To detect RAS mutation in colorectal liver metastasis by Diffusion-Weighted Magnetic Resonance Imaging (DWI-MRI) - and Diffusion Kurtosis imaging (DKI)-derived parameters. Methods: In total, 106 liver metastasis (60 metastases with RAS mutation) in 52 patients were included in this retrospective study. Diffusion and perfusion parameters were derived by DWI (apparent diffusion coefficient (ADC), basal signal (S0), pseudo-diffusion coefficient (DP), perfusion fraction (FP) and tissue diffusivity (DT)) and DKI data (mean of diffusion coefficient (MD) and mean of diffusional Kurtosis (MK)). Wilcoxon–Mann–Whitney U tests for non-parametric variables and receiver operating characteristic (ROC) analyses were calculated with area under ROC curve (AUC). Moreover, pattern recognition approaches (linear classifier, support vector machine, k-nearest neighbours, decision tree), with features selection methods and a leave-one-out cross validation approach, were considered. Results: A significant discrimination between the group with RAS mutation and the group without RAS mutation was obtained by the standard deviation value of MK (MK STD), by the mean value of MD, and by that of FP. The best results were reached by MK STD with an AUC of 0.80 (sensitivity of 72%, specificity of 85%, accuracy of 79%) using a cut-off of 203.90 × 10⁻³, and by the mean value of MD with AUC of 0.80 (sensitivity of 84%, specificity of 73%, accuracy of 77%) using a cut-off of 1694.30 mm²/s × 10⁻⁶. Considering all extracted features or the predictors obtained by the features selection method (the mean value of S0, the standard deviation value of MK, FP and of DT), the tested pattern recognition approaches did not determine an increase in diagnostic accuracy to detect RAS mutation (AUC of 0.73 and 0.69, respectively). Conclusions: Diffusion-Weighted imaging and Diffusion Kurtosis imaging could be used to detect the RAS mutation in liver metastasis. The standard deviation value of MK and the mean value of MD were the more accurate parameters in the RAS mutation detection, with an AUC of 0.80. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

17 pages, 2413 KiB

Open AccessArticle

Contrast-Enhanced Ultrasound (CEUS) for Follow-Up of Bosniak 2F Complex Renal Cystic Lesions—A 12-Year Retrospective Study in a Specialized European Center

by Johannes Rübenthaler, Saša Čečatka, Matthias Frank Froelich, Matthias Stechele, Constantin Marschner, Bastian Oliver Sabel, Florian Bogner, Moritz Ludwig Schnitzer, Daniel Overhoff, Nils Große Hokamp, Michael Staehler, Vincent Schwarze and Dirk-André Clevert

Cancers 2020, 12(8), 2170; https://doi.org/10.3390/cancers12082170 - 04 Aug 2020

Cited by 11 | Viewed by 16583

Abstract

Bosniak 2F renal cystic lesions feature morphologic characteristics between Bosniak I and III categories, the majority of which remain benign. However, a minor part of Bosniak 2F lesions may progress to malignancy. The purpose of this study was to assess Bosniak 2F cystic lesions during follow-up examinations by CEUS. One-hundred-and-twelve out of 364 patients with Bosniak 2F lesions underwent follow-up CEUS examinations between February 2008 and February 2020. Twelve out of 364 patients underwent renal surgery without follow-up CEUS. The progression rate of Bosniak 2F renal lesions detected by CEUS accounted for 7.1% (8/112 patients) after a mean of 12.9 months. The first follow-up CEUS revealed 75% of progressions (6/8), the remaining 25% (2/8) of progressions were detected during second follow-up CEUS. Underlying clear-cell renal cell carcinoma was histopathologically validated in 5/8 progressive complex cystic renal lesions. Stable sonomorphologic features were observed in 92.1% (104/112 patients). CEUS depicts a promising diagnostic imaging modality in the diagnostic work-up and follow-up of complex renal cystic lesions at higher spatial and temporal resolutions than CT or MRI. Its excellent safety profile, its easy and repeatable accessibility, and low financial costs render CEUS an attractive and powerful alternative imaging tool for monitoring complex renal cystic lesions. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

Review

Jump to: Research, Other

28 pages, 10223 KiB

Open AccessReview

Diffusion-Weighted Imaging in Oncology: An Update

by Carmelo Messina, Rodolfo Bignone, Alberto Bruno, Antonio Bruno, Federico Bruno, Marco Calandri, Damiano Caruso, Pietro Coppolino, Riccardo De Robertis, Francesco Gentili, Irene Grazzini, Raffaele Natella, Paola Scalise, Antonio Barile, Roberto Grassi, Domenico Albano and on behalf of the Young SIRM Working Group

Cancers 2020, 12(6), 1493; https://doi.org/10.3390/cancers12061493 - 08 Jun 2020

Cited by 81 | Viewed by 8587

Abstract

To date, diffusion weighted imaging (DWI) is included in routine magnetic resonance imaging (MRI) protocols for several cancers. The real additive role of DWI lies in the “functional” information obtained by probing the free diffusivity of water molecules into intra and inter-cellular spaces that in tumors mainly depend on cellularity. Although DWI has not gained much space in some oncologic scenarios, this non-invasive tool is routinely used in clinical practice and still remains a hot research topic: it has been tested in almost all cancers to differentiate malignant from benign lesions, to distinguish different malignant histotypes or tumor grades, to predict and/or assess treatment responses, and to identify residual or recurrent tumors in follow-up examinations. In this review, we provide an up-to-date overview on the application of DWI in oncology. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

Other

Jump to: Research, Review

11 pages, 1001 KiB

Open AccessCommentary

An Overview of Artificial Intelligence Applications in Liver and Pancreatic Imaging

by Nicolò Cardobi, Alessandro Dal Palù, Federica Pedrini, Alessandro Beleù, Riccardo Nocini, Riccardo De Robertis, Andrea Ruzzenente, Roberto Salvia, Stefania Montemezzi and Mirko D’Onofrio

Cancers 2021, 13(9), 2162; https://doi.org/10.3390/cancers13092162 - 30 Apr 2021

Cited by 9 | Viewed by 2724

Abstract

Artificial intelligence (AI) is one of the most promising fields of research in medical imaging so far. By means of specific algorithms, it can be used to help radiologists in their routine workflow. There are several papers that describe AI approaches to solve different problems in liver and pancreatic imaging. These problems may be summarized in four different categories: segmentation, quantification, characterization and image quality improvement. Segmentation is usually the first step of successive elaborations. If done manually, it is a time-consuming process. Therefore, the semi-automatic and automatic creation of a liver or a pancreatic mask may save time for other evaluations, such as quantification of various parameters, from organs volume to their textural features. The alterations of normal liver and pancreas structure may give a clue to the presence of a diffuse or focal pathology. AI can be trained to recognize these alterations and propose a diagnosis, which may then be confirmed or not by radiologists. Finally, AI may be applied in medical image reconstruction in order to increase image quality, decrease dose administration (referring to computed tomography) and reduce scan times. In this article, we report the state of the art of AI applications in these four main categories. Full article

(This article belongs to the Special Issue Advanced Oncologic Imaging)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Advanced Oncologic Imaging

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (13 papers)

Research

Review

Other

Further Information

Guidelines

MDPI Initiatives

Follow MDPI