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Novel Insights into Biology and Cancers

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A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (10 July 2022) | Viewed by 18313

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Prof. Dirk Clevert

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Guest Editor

Department of Radiology, University Hospital, LMU Munich, Munich, Germany

PD Dr. Matthias F. Frölich

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Guest Editor

Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Mannheim, Germany

Special Issue Information

Dear Colleagues,

Interdisciplinary and early detection of cancer is essential for a modern targeted therapy. For an integrated diagnosis and therapy, modern medicine has various radiological procedures available as a central component to monitor the diagnosis, therapy, and course of cancer. Among other factors, quantitative imaging biomarkers play an integral role in this. Modern (hybrid) imaging techniques allow us to follow the course of therapy down to the molecular level and redefine our understanding of successful therapy. In the context of the various global health systems, the economic aspects of these targeted approaches are also becoming increasingly important.

This Special Issue will focus on recent developments, current status, and novel insights in diagnosing and monitoring cancer, covering topics from recent technical developments to specific imaging techniques taking economical and health care perspectives into consideration.

Prof. Dirk Clevert
PD Dr. Matthias F. Frölich
Guest Editors

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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.

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Keywords

Oncologic imaging
CT, MRI, Artificial Intelligence
Cancer imaging
Tumor grade and aggressiveness
Cancer prognosis
Vascularization and microperfusion
Economic evaluation
Imaging biomarkers

Published Papers (7 papers)

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Research

14 pages, 1685 KiB

Open AccessArticle

Conversion Strategy in Left-Sided RAS/BRAF Wild-Type Metastatic Colorectal Cancer Patients with Unresectable Liver-Limited Disease: A Multicenter Cohort Study

by Stefano Granieri, Christian Cotsoglou, Alessandro Bonomi, Lisa Salvatore, Roberto Filippi, Olga Nigro, Fabio Gelsomino, Ina Valeria Zurlo, Ilaria Depetris, Riccardo Giampieri, Rossana Berardi, Cristina Morelli, Michele De Tursi, Michela Roberto, Elson Gjoni, Alessandro Germini, Nicola de Angelis, Riccardo Memeo, Antonio Facciorusso, Ornella Garrone, Daryl Ramai, Michele Ghidini and Alessandro Parisi Show full author list Hide full author list

Cancers 2022, 14(22), 5513; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14225513 - 09 Nov 2022

Cited by 3 | Viewed by 1816

Abstract

Colorectal cancer (CRC) patients frequently develop liver metastases. Different treatment strategies are available according to the timing of appearance, the burden of metastatic disease, and the performance status of the patient. Systemic treatment (ST) represents the cornerstone of metastatic disease management. However, in select cases, combined ST and surgical resection can lead to remarkable survival outcomes. In the present multicentric cohort study, we explored the efficacy of a conversion strategy in a selected population of left-sided RAS/BRAF wild-type CRC patients with liver-limited metastatic disease. Methods: The primary endpoint was to compare survival outcomes of patients undergoing ST not leading to surgery, liver resection after conversion ST, and hepatic resection with perioperative ST. Furthermore, we explored survival outcomes depending on whether the case was discussed within a multidisciplinary team. Results: Between 2012 and 2020, data from 690 patients respecting the inclusion criteria were collected. Among these, 272 patients were deemed eligible for the analysis. The conversion rate was 24.1% of cases. Fifty-six (20.6%) patients undergoing surgical resection after induction treatment (i.e., ultimately resectable) had a significant survival advantage compared to those receiving systemic treatment not leading to surgery (176 pts, 64.7%) (5-year OS 60.8% and 11.7%, respectively, Log Rank test p < 0.001; HR = 0.273; 95% CI: 0.16–0.46; p < 0.001; 5-year PFS 22.2% and 6.3%, respectively, Log Rank test p < 0.001; HR = 0.447; 95% CI: 0.32–0.63; p < 0.001). There was no difference in survival between ultimately resectable patients and those who had liver resection with perioperative systemic treatment (potentially resectable—40 pts) (5-year OS 71.1%, Log Rank test p = 0.311. HR = 0.671; 95% CI: 0.31–1.46; p = 0.314; 5-year PFS 25.7%, Log Rank test p = 0.305. HR = 0.782; 95% CI: 0.49–1.25; p = 0.306). Conclusions: In our selected population of left-sided RAS/BRAF wild-type colorectal cancer patients with liver-limited disease, a conversion strategy was confirmed to provide a survival benefit. Patients not deemed surgical candidates at the time of diagnosis and patients judged resectable with perioperative systemic treatment have similar survival outcomes. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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11 pages, 3781 KiB

Open AccessArticle

Novel Insights of T2-Weighted Imaging: Significance for Discriminating Lung Cancer from Benign Pulmonary Nodules and Masses

by Katsuo Usuda, Shun Iwai, Aika Yamagata, Yoshihito Iijima, Nozomu Motono, Munetaka Matoba, Mariko Doai, Keiya Hirata and Hidetaka Uramoto

Cancers 2021, 13(15), 3713; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13153713 - 23 Jul 2021

Cited by 2 | Viewed by 2538

Abstract

Diffusion-weighted imaging is useful for discriminating lung cancer from benign pulmonary nodules and masses (BPNMs), however the diagnostic capability is not perfect. The aim of this research was to clarify whether T2-weighted imaging (T2WI) is efficient in discriminating lung cancer from BPNMs, especially from pulmonary abscesses. A T2 contrast ratio (T2 CR) for a pulmonary nodule is defined as the ratio of T2 signal intensity of a pulmonary nodule divided by the T2 signal intensity of the rhomboid muscle. There were 52 lung cancers and 40 inflammatory BPNMs (mycobacteria disease 12, pneumonia 13, pulmonary abscess 9, other 6) and seven non-inflammatory BPNMs. The T2 CR (2.14 ± 0.63) of lung cancers was significantly lower than that (2.68 ± 1.04) of BPNMs (p = 0.0021). The T2 CR of lung cancers was significantly lower than that (2.93 ± 0.26) of pulmonary abscesses (p = 0.011). When the optical cutoff value of T2 CR was set as 2.44, the sensitivity was 0.827 (43/52), the specificity 0.596 (28/47), the accuracy 0.717 (71/99), the positive predictive value 0.694 (43/62), and the negative predictive value 0.757 (28/37). T2 CR of T2WI is useful in discriminating lung cancer from BPNMs. Pulmonary abscesses, which show strong restricted diffusion in DWI, can be differentiated from lung cancers using T2WI. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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14 pages, 2462 KiB

Open AccessArticle

Development and External Validation of Deep-Learning-Based Tumor Grading Models in Soft-Tissue Sarcoma Patients Using MR Imaging

by Fernando Navarro, Hendrik Dapper, Rebecca Asadpour, Carolin Knebel, Matthew B. Spraker, Vincent Schwarze, Stephanie K. Schaub, Nina A. Mayr, Katja Specht, Henry C. Woodruff, Philippe Lambin, Alexandra S. Gersing, Matthew J. Nyflot, Bjoern H. Menze, Stephanie E. Combs and Jan C. Peeken

Cancers 2021, 13(12), 2866; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13122866 - 08 Jun 2021

Cited by 23 | Viewed by 3296

Abstract

Background: In patients with soft-tissue sarcomas, tumor grading constitutes a decisive factor to determine the best treatment decision. Tumor grading is obtained by pathological work-up after focal biopsies. Deep learning (DL)-based imaging analysis may pose an alternative way to characterize STS tissue. In this work, we sought to non-invasively differentiate tumor grading into low-grade (G1) and high-grade (G2/G3) STS using DL techniques based on MR-imaging. Methods: Contrast-enhanced T1-weighted fat-saturated (T1FSGd) MRI sequences and fat-saturated T2-weighted (T2FS) sequences were collected from two independent retrospective cohorts (training: 148 patients, testing: 158 patients). Tumor grading was determined following the French Federation of Cancer Centers Sarcoma Group in pre-therapeutic biopsies. DL models were developed using transfer learning based on the DenseNet 161 architecture. Results: The T1FSGd and T2FS-based DL models achieved area under the receiver operator characteristic curve (AUC) values of 0.75 and 0.76 on the test cohort, respectively. T1FSGd achieved the best F1-score of all models (0.90). The T2FS-based DL model was able to significantly risk-stratify for overall survival. Attention maps revealed relevant features within the tumor volume and in border regions. Conclusions: MRI-based DL models are capable of predicting tumor grading with good reproducibility in external validation. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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17 pages, 3432 KiB

Open AccessArticle

Prognostic Assessment in High-Grade Soft-Tissue Sarcoma Patients: A Comparison of Semantic Image Analysis and Radiomics

by Jan C. Peeken, Jan Neumann, Rebecca Asadpour, Yannik Leonhardt, Joao R. Moreira, Daniel S. Hippe, Olena Klymenko, Sarah C. Foreman, Claudio E. von Schacky, Matthew B. Spraker, Stephanie K. Schaub, Hendrik Dapper, Carolin Knebel, Nina A. Mayr, Henry C. Woodruff, Philippe Lambin, Matthew J. Nyflot, Alexandra S. Gersing and Stephanie E. Combs

Cancers 2021, 13(8), 1929; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13081929 - 16 Apr 2021

Cited by 23 | Viewed by 2921

Abstract

Background: In patients with soft-tissue sarcomas of the extremities, the treatment decision is currently regularly based on tumor grading and size. The imaging-based analysis may pose an alternative way to stratify patients’ risk. In this work, we compared the value of MRI-based radiomics with expert-derived semantic imaging features for the prediction of overall survival (OS). Methods: Fat-saturated T2-weighted sequences (T2FS) and contrast-enhanced T1-weighted fat-saturated (T1FSGd) sequences were collected from two independent retrospective cohorts (training: 108 patients; testing: 71 patients). After preprocessing, 105 radiomic features were extracted. Semantic imaging features were determined by three independent radiologists. Three machine learning techniques (elastic net regression (ENR), least absolute shrinkage and selection operator, and random survival forest) were compared to predict OS. Results: ENR models achieved the best predictive performance. Histologies and clinical staging differed significantly between both cohorts. The semantic prognostic model achieved a predictive performance with a C-index of 0.58 within the test set. This was worse compared to a clinical staging system (C-index: 0.61) and the radiomic models (C-indices: T1FSGd: 0.64, T2FS: 0.63). Both radiomic models achieved significant patient stratification. Conclusions: T2FS and T1FSGd-based radiomic models outperformed semantic imaging features for prognostic assessment. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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11 pages, 1651 KiB

Open AccessArticle

Cost-Effectiveness Analysis of Local Ablation and Surgery for Liver Metastases of Oligometastatic Colorectal Cancer

by Matthias F. Froelich, Moritz L. Schnitzer, Nils Rathmann, Fabian Tollens, Marcus Unterrainer, Shereen Rennebaum, Max Seidensticker, Jens Ricke, Johannes Rübenthaler and Wolfgang G. Kunz

Cancers 2021, 13(7), 1507; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13071507 - 25 Mar 2021

Cited by 17 | Viewed by 2290

Abstract

Background: Colorectal cancer is among the most prevalent cancer entities worldwide, with every second patient developing liver metastases during their illness. For local treatment of liver metastases, a surgical approach as well as ablative treatment options, such as microwave ablation (MWA) and radiofrequency ablation (RFA), are available. The aim of this study is to evaluate the cost-effectiveness of RFA, MWA and surgery in the treatment of liver metastases of oligometastatic colorectal cancer (omCRC) that are amenable for all investigated treatment modalities. Methods: A decision analysis based on a Markov model assessed lifetime costs and quality-adjusted life years (QALY) related to the treatment strategies RFA, MWA and surgical resection. Input parameters were based on the best available and most recent evidence. Probabilistic sensitivity analyses (PSA) were performed with Monte Carlo simulations to evaluate model robustness. The percentage of cost-effective iterations was determined for different willingness-to-pay (WTP) thresholds. Results: The base-case analysis showed that surgery led to higher long-term costs compared to RFA and MWA (USD 41,848 vs. USD 36,937 vs. USD 35,234), while providing better long-term outcomes than RFA, yet slightly lower than MWA (6.80 vs. 6.30 vs. 6.95 QALYs for surgery, RFA and MWA, respectively). In PSA, MWA was the most cost-effective strategy for all WTP thresholds below USD 80,000 per QALY. Conclusions: In omCRC patients with liver metastases, MWA and surgery are estimated to provide comparable efficacy. MWA was identified as the most cost-effective strategy in intermediate resource settings and should be considered as an alternative to surgery in high resource settings. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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12 pages, 1394 KiB

Open AccessArticle

Supplemental ¹⁸F-FDG-PET/CT for Detection of Malignant Transformation of IPMN—A Model-Based Cost-Effectiveness Analysis

by Felix Bicu, Johann S. Rink, Matthias F. Froelich, Clemens C. Cyran, Johannes Rübenthaler, Emrullah Birgin, Manuel Röhrich and Fabian Tollens

Cancers 2021, 13(6), 1365; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13061365 - 18 Mar 2021

Cited by 1 | Viewed by 1612

Abstract

Accurate detection of malignant transformation and risk-stratification of intraductal papillary mucinous neoplasms (IPMN) has remained a diagnostic challenge. Preliminary findings have indicated a promising role of positron emission tomography combined with computed tomography and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG-PET/CT) in detecting malignant IPMN. Therefore, the aim of this model-based economic evaluation was to analyze whether supplemental FDG-PET/CT could be cost-effective in patients with IPMN. Decision analysis and Markov modeling were applied to simulate patients’ health states across a time frame of 15 years. CT/MRI based imaging was compared to a strategy with supplemental ¹⁸F-FDG-PET/CT. Cumulative costs in US-$ and outcomes in quality-adjusted life years (QALY) were computed based on input parameters extracted from recent literature. The stability of the model was evaluated by deterministic sensitivity analyses. In the base-case scenario, the CT/MRI-strategy resulted in cumulative discounted costs of USD $106,424 and 8.37 QALYs, while the strategy with supplemental FDG-PET/CT resulted in costs of USD $104,842 and a cumulative effectiveness of 8.48 QALYs and hence was cost-saving. A minimum specificity of FDG-PET/CT of 71.5% was required for the model to yield superior net monetary benefits compared to CT/MRI. This model-based economic evaluation indicates that supplemental ¹⁸F-FDG-PET/CT could have a favorable economic value in the management of IPMN and could be cost-saving in the chosen setting. Prospective studies with standardized protocols for FDG-PET/CT could help to better determine the value of FDG-PET/CT. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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14 pages, 2162 KiB

Open AccessArticle

Cost-Effectiveness of Digital Breast Tomosynthesis vs. Abbreviated Breast MRI for Screening Women with Intermediate Risk of Breast Cancer—How Low-Cost Must MRI Be?

by Fabian Tollens, Pascal A.T. Baltzer, Matthias Dietzel, Johannes Rübenthaler, Matthias F. Froelich and Clemens G. Kaiser

Cancers 2021, 13(6), 1241; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13061241 - 12 Mar 2021

Cited by 15 | Viewed by 2463

Abstract

Background: Digital breast tomosynthesis (DBT) and abbreviated breast MRI (AB-MRI) offer superior diagnostic performance compared to conventional mammography in screening women with intermediate risk of breast cancer due to dense breast tissue. The aim of this model-based economic evaluation was to analyze whether AB-MRI is cost-effective in this cohort compared to DBT. Methods: Decision analysis and Markov simulations were used to model the cumulative costs and quality-adjusted life-years (QALYs) over a time horizon of 30 years. Model input parameters were adopted from recent literature. Deterministic and probabilistic sensitivity analyses were applied to test the stability of the model. Results: In the base-case scenario, the costs of an AB-MRI examination were defined to equal the costs of a full protocol acquisition. Two-yearly screening of women with dense breasts resulted in cumulative discounted costs of $8798 and $9505 for DBT and AB-MRI, and cumulative discounted effects of 19.23 and 19.27 QALYs, respectively, with an incremental cost-effectiveness ratio of $20,807 per QALY gained in the base-case scenario. By reducing the cost of an AB-MRI examination below a threshold of $241 in sensitivity analyses, AB-MRI would become cost-saving compared to DBT. Conclusion: In comparison to DBT, AB-MRI can be considered cost-effective up to a price per examination of $593 in screening patients at intermediate risk of breast cancer. Full article

(This article belongs to the Special Issue Novel Insights into Biology and Cancers)

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