Advanced Brain Tumor Imaging

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4022

Special Issue Editors

1. Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland
2. Faculty of Biomedical Sciences, Università della Svizzera Italiana, 6900 Lugano, Switzerland
Interests: meta-analysis; PET; nuclear medicine; systematic reviews; brain tumor imaging
Special Issues, Collections and Topics in MDPI journals
Dr. Barbara Muoio
E-Mail Website
Guest Editor
Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland
Interests: PET/CT; neurooncology; cancer radiotherapy; medical oncology; brain tumors

Special Issue Information

Dear Colleagues,

According to the recent World Health Organization (WHO) classification, brain tumors include a variety of different tumor types originating from the central nervous system. Furthermore, the brain may be involved in the metastatic spread of tumors arising from other anatomical sites.

Imaging methods may be extremely useful for diagnosis, monitoring, treatment response assessment, and for obtaining prognostic information in patients with brain tumors.

Imaging methods used to assess brain tumors are extremely varied, including conventional techniques of morphological imaging and functional imaging techniques.

This Special Issue aims to gather articles concerning advanced imaging techniques in brain tumors. This includes, but is not limited to, advanced magnetic resonance imaging (MRI) techniques and positron emission tomography (PET) with different radiopharmaceuticals.

Prof. Dr. Giorgio Treglia
Dr. Barbara Muoio
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

  • brain tumors
  • gliomas
  • brain metastases
  • meningioma
  • neuroimaging
  • magnetic resonance
  • PET
  • MRI

Published Papers (5 papers)

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Research

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12 pages, 1041 KiB  
Article
Predicting the Consistency of Pituitary Macroadenomas: The Utility of Diffusion-Weighted Imaging and Apparent Diffusion Coefficient Measurements for Surgical Planning
Diagnostics 2024, 14(5), 493; https://doi.org/10.3390/diagnostics14050493 - 25 Feb 2024
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Abstract
Understanding the consistency of pituitary macroadenomas is crucial for neurosurgeons planning surgery. This retrospective study aimed to evaluate the utility of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) as non-invasive imaging modalities for predicting the consistency of pituitary macroadenomas. This could [...] Read more.
Understanding the consistency of pituitary macroadenomas is crucial for neurosurgeons planning surgery. This retrospective study aimed to evaluate the utility of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) as non-invasive imaging modalities for predicting the consistency of pituitary macroadenomas. This could contribute to appropriate surgical planning and therefore reduce the likelihood of incomplete resections. The study included 45 patients with pathologically confirmed pituitary macroadenomas. Conventional MRI sequences, DWIs, ADC maps, and pre- and post-contrast MRIs were performed. Two neuroradiologists assessed all of the images. Neurosurgeons assessed the consistency of the tumor macroscopically, and histopathologists examined it microscopically. The MRI findings were compared with postoperative data. According to the operative data, macroadenomas were divided into the two following categories based on their consistency: aspirable (n = 27) and non-aspirable tumors (n = 18). A statistically significant difference in DWI findings was found when comparing macroadenomas of different consistencies (p < 0.001). Most aspirable macroadenomas (66.7%) were hyperintense according to DWI and hypointense on ADC maps, whereas most non-aspirable macroadenomas (83.3%) were hypointense for DWI and hyperintense on ADC maps. At a cut-off value of 0.63 × 10−3 mm2/s, the ADC showed a sensitivity of 85.7% and a specificity of 75% for the detection of non-aspirable macroadenomas (AUC, 0.946). The study concluded that DWI should be routinely performed in conjunction with ADC measurements in the preoperative evaluation of pituitary macroadenomas. This approach may aid in surgical planning, ensure that appropriate techniques are utilized, and reduce the risk of incomplete resection. Full article
(This article belongs to the Special Issue Advanced Brain Tumor Imaging)
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9 pages, 2226 KiB  
Article
The Correlation of In Vivo MR Spectroscopy and Ex Vivo 2-Hydroxyglutarate Concentration for the Prediction of Isocitrate Dehydrogenase Mutation Status in Diffuse Glioma
Diagnostics 2023, 13(17), 2791; https://doi.org/10.3390/diagnostics13172791 - 29 Aug 2023
Cited by 1 | Viewed by 724
Abstract
Isocitrate dehydrogenase (IDH) mutation status is an important biomarker in the glioma-defining subtype and corresponding prognosis. This study proposes a straightforward method for 2-hydroxyglutarate (2-HG) quantification by MR spectroscopy for IDH mutation status detection and directly compares in vivo 2-HG MR spectroscopy with [...] Read more.
Isocitrate dehydrogenase (IDH) mutation status is an important biomarker in the glioma-defining subtype and corresponding prognosis. This study proposes a straightforward method for 2-hydroxyglutarate (2-HG) quantification by MR spectroscopy for IDH mutation status detection and directly compares in vivo 2-HG MR spectroscopy with ex vivo 2-HG concentration measured in resected tumor tissue. Eleven patients with suspected lower-grade glioma (ten IDH1; one IDHwt) were prospectively included. Preoperatively, 3T point-resolved spectroscopy (PRESS) was acquired; 2-HG was measured as the percentage elevation of Glx3 (the sum of 2-HG and Glx) compared to Glx4. IDH mutation status was assessed by immunochemistry or direct sequencing. The ex vivo 2-HG concentration was determined in surgically obtained tissue specimens using gas chromatography–mass spectrometry. Pearson correlation was used for assessing the correlation between in vivo MR spectroscopy and ex vivo 2-HG concentration. MR spectroscopy was positive for 2-HG in eight patients, all of whom had IDH1 tumors. A strong correlation (r = 0.80, p = 0.003) between 2-HG MR spectroscopy and the ex vivo 2-HG concentration was found. This study shows in vivo 2-HG MR spectroscopy can non-invasively determine IDH status in glioma and demonstrates a strong correlation with ex vivo 2-HG concentration in patients with lower-grade glioma. Full article
(This article belongs to the Special Issue Advanced Brain Tumor Imaging)
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13 pages, 2678 KiB  
Article
Prediction of Glioma Grade and IDH Status Using 18F-FET PET/CT Dynamic and Multiparametric Texture Analysis
Diagnostics 2023, 13(15), 2604; https://doi.org/10.3390/diagnostics13152604 - 05 Aug 2023
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Abstract
Mutations in isocitrate dehydrogenase (IDH) represent an independent predictor of better survival in patients with gliomas. We aimed to assess grade and IDH mutation status in patients with untreated gliomas, by evaluating the respective value of 18F-FET PET/CT via dynamic and texture [...] Read more.
Mutations in isocitrate dehydrogenase (IDH) represent an independent predictor of better survival in patients with gliomas. We aimed to assess grade and IDH mutation status in patients with untreated gliomas, by evaluating the respective value of 18F-FET PET/CT via dynamic and texture analyses. A total of 73 patients (male: 48, median age: 47) who underwent an 18F-FET PET/CT for initial glioma evaluation were retrospectively included. IDH status was available in 61 patients (20 patients with WHO grade 2 gliomas, 41 with grade 3–4 gliomas). Time–activity curve type and 20 parameters obtained from static analysis using LIFEx© v6.30 software were recorded. Respective performance was assessed using receiver operating characteristic curve analysis and stepwise multivariate regression analysis adjusted for patients’ age and sex. The time–activity curve type and texture parameters derived from the static parameters showed satisfactory-to-good performance in predicting glioma grade and IDH status. Both time–activity curve type (stepwise OR: 101.6 (95% CI: 5.76–1791), p = 0.002) and NGLDM coarseness (stepwise OR: 2.08 × 1043 (95% CI: 2.76 × 1012–1.57 × 1074), p = 0.006) were independent predictors of glioma grade. No independent predictor of IDH status was found. Dynamic and texture analyses of 18F-FET PET/CT have limited predictive value for IDH status when adjusted for confounding factors. However, they both help predict glioma grade. Full article
(This article belongs to the Special Issue Advanced Brain Tumor Imaging)
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13 pages, 962 KiB  
Systematic Review
Diagnostic Accuracy of PET with 18F-Fluciclovine ([18F]FACBC) in Detecting High-Grade Gliomas: A Systematic Review and Meta-Analysis
Diagnostics 2023, 13(24), 3610; https://doi.org/10.3390/diagnostics13243610 - 06 Dec 2023
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Abstract
Background: 18F-Fluciclovine ([18F]FACBC) has been recently proposed as a synthetic radiolabeled amino acid for positron emission tomography (PET) imaging in patients with brain neoplasms. Our aim is to evaluate the diagnostic performance of [18F]FACBC PET in high-grade glioma [...] Read more.
Background: 18F-Fluciclovine ([18F]FACBC) has been recently proposed as a synthetic radiolabeled amino acid for positron emission tomography (PET) imaging in patients with brain neoplasms. Our aim is to evaluate the diagnostic performance of [18F]FACBC PET in high-grade glioma (HGG) patients, taking into account the literature data. Methods: A comprehensive literature search was performed. We included original articles evaluating [18F]FACBC PET in the detection of HGG before therapy and for the suspicion of tumor recurrence. Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR−), and diagnostic odds ratios (DOR), including 95% confidence intervals (95% CI), were measured. Statistical heterogeneity and publication bias were also assessed. Results: ten studies were included in the review and eight in the meta-analysis (113 patients). Regarding the identification of HGG, the sensitivity of [18F]FACBC PET ranged between 85.7% and 100%, with a pooled estimate of 92.9% (95% CI: 84.4–96.9%), while the specificity ranged from 50% to 100%, with a pooled estimate of 70.7% (95% CI: 47.5–86.5%). The pooled LR+, LR−, and DOR of [18F]FACBC PET were 2.5, 0.14, and 37, respectively. No significant statistical heterogeneity or publication bias were found. Conclusions: evidence-based data demonstrate the good diagnostic accuracy of [18F]FACBC PET for HGG detection. Due to the still limited data, further studies are warranted to confirm the promising role of [18F]FACBC PET in this context. Full article
(This article belongs to the Special Issue Advanced Brain Tumor Imaging)
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13 pages, 1754 KiB  
Case Report
Intracranial Inflammatory Myofibroblastic Tumor: A Literature Review and a Rare Case Misdiagnosed as Acoustic Neuroma
Diagnostics 2023, 13(17), 2725; https://doi.org/10.3390/diagnostics13172725 - 22 Aug 2023
Viewed by 890
Abstract
Inflammatory myofibroblastic tumor (IMT) stands as a rare neoplasm, initially documented by Bahadori and Liebow in 1973; however, its biological behavior and underlying pathogenesis continue to elude comprehensive understanding. Throughout the years, this tumor has been designated by various alternative names, including pseudosarcomatoid [...] Read more.
Inflammatory myofibroblastic tumor (IMT) stands as a rare neoplasm, initially documented by Bahadori and Liebow in 1973; however, its biological behavior and underlying pathogenesis continue to elude comprehensive understanding. Throughout the years, this tumor has been designated by various alternative names, including pseudosarcomatoid myofibroblastoma, fibromyxoid transformation, and plasma cell granuloma among others. In 2002, the World Health Organization (WHO) officially classified it as a soft tissue tumor and designated it as IMT. While IMT primarily manifests in the lungs, the common clinical symptoms encompass anemia, low-grade fever, limb weakness, and chest pain. The mesentery, omentum, and retroperitoneum are subsequent sites of occurrence with intracranial involvement being exceedingly rare. Due to the absence of specific clinical symptoms and characteristic radiographic features, diagnosing intracranial inflammatory myofibroblastic tumor (IIMT) remains challenging. Successful instances of pharmacological treatment for IIMT indicate that surgery may not be the sole therapeutic recourse, thus underscoring the imperative of an accurate diagnosis and apt treatment selection to improve patient outcomes. Full article
(This article belongs to the Special Issue Advanced Brain Tumor Imaging)
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