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Advances in Neuro-Oncological Imaging (Volume II)
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Advances in Neuro-Oncological Imaging (Volume II)

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: closed (1 May 2025) | Viewed by 2547

Special Issue Editors

Dr. Julia Furtner

E-Mail Website
Guest Editor
Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
Interests: neuroimaging; radiomics/radiogenomics in context of brain tumors; MRI; PET; PET/MRI
Special Issues, Collections and Topics in MDPI journals
Dr. Anna Sophie Berghoff

E-Mail Website
Guest Editor
Division of Oncology, Department of Medicine I, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
Interests: neuro-oncology; biomarkers; clinical studies; immunotherapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are excited to invite you to contribute to this Special Issue, which is the second edition of "Advances in Neuro-Oncological Imaging" (https://www.mdpi.com/journal/cancers/special_issues/Neuro_Oncological).

Central nervous system tumors have a significant impact on patient quality of life, as well as the healthcare system due to the profound level of impairment that is already evident in the early stage of the disease, posing a tremendous medical and socioeconomic burden. The most widely used method for identifying and monitoring brain and spinal cord tumors is non-invasive imaging techniques on a qualitative or quantitative basis.

This Special Issue of Cancers aims to highlight imaging techniques that can provide new insights into tumor detection, diagnosis, molecular profiling, prognosis or the prediction of response to treatment in primary and secondary CNS tumors.

We are pleased to invite you to submit original research articles and reviews, with a focus on novel aspects of diverse neuro-oncological imaging research fields such as advanced MRI (including hyperpolarized MRI, CEST imaging, MR fingerprinting, quantitative MRI), PET, neuro-oncological imaging biomarkers, radiomics or multi-omic approaches, as well as functional MRI or intraoperative MRI.

We look forward to receiving your contributions.

Dr. Julia Furtner
Dr. Anna Sophie Berghoff
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 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

  • central nervous system (CNS) tumors
  • brain tumors
  • spinal cord tumors
  • magnetic resonance imaging (MRI)
  • positron emission tomography (PET)
  • intraoperative MRI
  • imaging biomarkers
  • metabolic imaging
  • radiomics
  • machine learning

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

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15 pages, 1840 KiB  
Article
The Role of Amide Proton Transfer (APT)-Weighted Imaging in Glioma: Assessment of Tumor Grading, Molecular Profile and Survival in Different Tumor Components
by Gonçalo Borges de Almeida, Riccardo Pascuzzo, Francesca Mambrin, Domenico Aquino, Mattia Verri, Marco Moscatelli, Massimiliano Del Bene, Francesco DiMeco, Antonio Silvani, Bianca Pollo, Marina Grisoli and Fabio Martino Doniselli
Cancers 2024, 16(17), 3014; https://doi.org/10.3390/cancers16173014 - 29 Aug 2024
Cited by 1 | Viewed by 1373
Abstract
Amide Proton Transfer-weighted (APTw) imaging is a molecular MRI technique used to quantify protein concentrations in gliomas, which have heterogeneous components with varying cellularity and metabolic activity. This study aimed to assess the correlation between the component-specific APT signal of the neoplasm and [...] Read more.
Amide Proton Transfer-weighted (APTw) imaging is a molecular MRI technique used to quantify protein concentrations in gliomas, which have heterogeneous components with varying cellularity and metabolic activity. This study aimed to assess the correlation between the component-specific APT signal of the neoplasm and WHO grade, molecular profile and survival status. Sixty-one patients with adult-type diffuse gliomas were retrospectively analyzed. APT values were semi-automatically extracted from tumor solid and, whenever present, necrotic components. APT values were compared between groups stratified by WHO grade, IDH-mutation, MGMT promoter methylation and 1- and 2-year survival status using Wilcoxon rank-sum test, adjusting for multiple comparisons. Overall survival (OS) was analyzed in the subgroup of 48 patients with grade 4 tumors using Cox proportional-hazards models. Random-effects models were used to assess inter-subject heterogeneity of the mean APT values in each tumor component. APT values of the solid component significantly differed between patients with grades 2–3 and 4 tumors (mean 1.58 ± 0.50 vs. 2.04 ± 0.56, p = 0.028) and correlated with OS after 1 year (1.81 ± 0.58 in survivors vs. 2.17 ± 0.51 in deceased patients, p = 0.030). APT values did not differ by IDH-mutation, MGMT methylation, and 2-year survival status. Within grade 4 glioma patients, higher APT kurtosis of the solid component was a negative prognostic factor (hazard ratio = 1.60, p = 0.040). Mean APT values of the necrosis showed high inter-subject variability, although most necrotic tumors were grade 4 and IDH wildtype. In conclusion, APTw imaging in the solid component provided metrics associated with glioma grade and survival status but showed weak correlation with IDH-mutation and MGMT promoter methylation status, in contrast to previous works. Further research is needed to understand APT signal variability within the necrotic component of high-grade gliomas. Full article
(This article belongs to the Special Issue Advances in Neuro-Oncological Imaging (Volume II))
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Review

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28 pages, 11887 KiB  
Review
Radiological Predictors of Cognitive Impairment in Paediatric Brain Tumours Using Multiparametric Magnetic Resonance Imaging: A Review of Current Practice, Challenges and Future Directions
by Simon Dockrell, Martin G. McCabe, Ian Kamaly-Asl, John-Paul Kilday and Stavros M. Stivaros
Cancers 2025, 17(6), 947; https://doi.org/10.3390/cancers17060947 - 11 Mar 2025
Viewed by 659
Abstract
Paediatric brain tumours and their treatments are associated with long-term cognitive impairment. While the aetiology of cognitive impairment is complex and multifactorial, multiparametric Magnetic Resonance Imaging (MRI) can identify many risk factors including tumour location, damage to eloquent structures and tumour phenotype. Hydrocephalus [...] Read more.
Paediatric brain tumours and their treatments are associated with long-term cognitive impairment. While the aetiology of cognitive impairment is complex and multifactorial, multiparametric Magnetic Resonance Imaging (MRI) can identify many risk factors including tumour location, damage to eloquent structures and tumour phenotype. Hydrocephalus and raised intracranial pressure can be observed, along with risk factors for post-operative paediatric cerebellar mutism syndrome or epilepsy. MRI can also identify complications of surgery or radiotherapy and monitor treatment response. Advanced imaging sequences provide valuable information about tumour and brain physiology, but clinical use is limited by extended scanning times and difficulties in processing and analysis. Brain eloquence classifications exist, but focus on adults with neurological deficits and are outdated. For the analysis of childhood tumours, limited numbers within tumour subgroups and the investigation of long-term outcomes necessitate using historical scans and/or multi-site collaboration. Variable imaging quality and differing acquisition parameters limit the use of segmentation algorithms and radiomic analysis. Harmonisation can standardise imaging in collaborative research, but can be challenging, while data-sharing produces further logistical challenges. Consequently, most research consists of small single-centre studies limited to regional analyses of tumour location. Technological advances reducing scanning times increase the feasibility of clinical acquisition of high-resolution standardised imaging including advanced physiological sequences. The RAPNO and SIOPE paediatric brain tumour imaging guidelines have improved image standardisation, which will benefit future collaborative imaging research. Modern machine learning techniques provide more nuanced approaches for integration and analysis of the complex and multifactorial data involved in cognitive outcome prediction. Full article
(This article belongs to the Special Issue Advances in Neuro-Oncological Imaging (Volume II))
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