Background
Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by ...machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors.
Methods
This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases.
Results
Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80–90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods.
Conclusion
Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.
This guideline provides recommendations for the use of PET imaging in gliomas. The review examines established clinical benefit in glioma patients of PET using glucose ((18)F-FDG) and amino acid ...tracers ((11)C-MET, (18)F-FET, and (18)F-FDOPA). An increasing number of studies have been published on PET imaging in the setting of diagnosis, biopsy, and resection as well radiotherapy planning, treatment monitoring, and response assessment. Recommendations are based on evidence generated from studies which validated PET findings by histology or clinical course. This guideline emphasizes the clinical value of PET imaging with superiority of amino acid PET over glucose PET and provides a framework for the use of PET to assist in the management of patients with gliomas.
Abstract
The management of patients with glioma usually requires multimodality treatment including surgery, radiotherapy, and systemic therapy. Accurate neuroimaging plays a central role for ...radiotherapy planning and follow-up after radiotherapy completion. In order to maximize the radiation dose to the tumor and to minimize toxic effects on the surrounding brain parenchyma, reliable identification of tumor extent and target volume delineation is crucial. The use of positron emission tomography (PET) for radiotherapy planning and monitoring in gliomas has gained considerable interest over the last several years, but Class I data are not yet available. Furthermore, PET has been used after radiotherapy for response assessment and to distinguish tumor progression from pseudoprogression or radiation necrosis. Here, the Response Assessment in Neuro-Oncology (RANO) working group provides a summary of the literature and recommendations for the use of PET imaging for radiotherapy of patients with glioma based on published studies, constituting levels 1-3 evidence according to the Oxford Centre for Evidence-based Medicine.
Mutations in the isocitrate dehydrogenase (IDH mut) gene have gained paramount importance for the prognosis of glioma patients. To date, reliable techniques for a preoperative evaluation of IDH ...genotype remain scarce. Therefore, we investigated the potential of O-(2-
Ffluoroethyl)-L-tyrosine (FET) PET radiomics using textural features combined with static and dynamic parameters of FET uptake for noninvasive prediction of IDH genotype. Prior to surgery, 84 patients with newly diagnosed and untreated gliomas underwent FET PET using a standard scanner (15 of 56 patients with IDH mut) or a dedicated high-resolution hybrid PET/MR scanner (11 of 28 patients with IDH mut). Static, dynamic and textural parameters of FET uptake in the tumor area were evaluated. Diagnostic accuracy of the parameters was evaluated using the neuropathological result as reference. Additionally, FET PET and textural parameters were combined to further increase the diagnostic accuracy. The resulting models were validated using cross-validation. Independent of scanner type, the combination of standard PET parameters with textural features increased significantly diagnostic accuracy. The highest diagnostic accuracy of 93% for prediction of IDH genotype was achieved with the hybrid PET/MR scanner. Our findings suggest that the combination of conventional FET PET parameters with textural features provides important diagnostic information for the non-invasive prediction of the IDH genotype.
In glioma patients, complete resection of the contrast-enhancing portion is associated with improved survival, which, however, cannot be achieved in a considerable number of patients. Here, we ...evaluated the prognostic value of O-(2-
F-fluoroethyl)-L-tyrosine (FET) PET in not completely resectable glioma patients with minimal or absent contrast enhancement before temozolomide chemoradiation. Dynamic FET PET scans were performed in 18 newly diagnosed patients with partially resected (n = 8) or biopsied (n = 10) IDH-wildtype astrocytic glioma before initiation of temozolomide chemoradiation. Static and dynamic FET PET parameters, as well as contrast-enhancing volumes on MRI, were calculated. Using receiver operating characteristic analyses, threshold values for which the product of paired values for sensitivity and specificity reached a maximum were obtained. Subsequently, the prognostic values of FET PET parameters and contrast-enhancing volumes on MRI were evaluated using univariate Kaplan-Meier and multivariate Cox regression (including the MTV, age, MGMT promoter methylation, and contrast-enhancing volume) survival analyses for progression-free and overall survival (PFS, OS). On MRI, eight patients had no contrast enhancement; the remaining patients had minimal contrast-enhancing volumes (range, 0.2-5.3 mL). Univariate analyses revealed that smaller pre-irradiation FET PET tumor volumes were significantly correlated with a more favorable PFS (7.9 vs. 4.2 months; threshold, 14.8 mL; P = 0.012) and OS (16.6 vs. 9.0 months; threshold, 23.8 mL; P = 0.002). In contrast, mean tumor-to-brain ratios and time-to-peak values were only associated with a longer PFS (P = 0.048 and P = 0.045, respectively). Furthermore, the pre-irradiation FET PET tumor volume remained significant in multivariate analyses (P = 0.043), indicating an independent predictor for OS. Our results suggest that pre-irradiation FET PET parameters have a prognostic impact in this subgroup of patients.
The number of positron-emission tomography (PET) tracers used to evaluate patients with brain tumors has increased substantially over the last years. For the management of patients with brain tumors, ...the most important indications are the delineation of tumor extent (e.g., for planning of resection or radiotherapy), the assessment of treatment response to systemic treatment options such as alkylating chemotherapy, and the differentiation of treatment-related changes (e.g., pseudoprogression or radiation necrosis) from tumor progression. Furthermore, newer PET imaging approaches aim to address the need for noninvasive assessment of tumoral immune cell infiltration and response to immunotherapies (e.g., T-cell imaging). This review summarizes the clinical value of the landscape of tracers that have been used in recent years for the above-mentioned indications and also provides an overview of promising newer tracers for this group of patients.
Abstract
Over the past decades, a variety of PET tracers have been used for the evaluation of patients with brain tumors. For clinical routine, the most important clinical indications for PET imaging ...in patients with brain tumors are the identification of neoplastic tissue including the delineation of tumor extent for the further diagnostic and therapeutic management (ie, biopsy, resection, or radiotherapy planning), the assessment of response to a certain anticancer therapy including its (predictive) effect on the patients’ outcome and the differentiation of treatment-related changes (eg, pseudoprogression and radiation necrosis) from tumor progression at follow-up. To serve medical professionals of all disciplines involved in the diagnosis and care of patients with brain tumors, this review summarizes the value of PET imaging for the latter-mentioned 3 clinically relevant indications in patients with glioma, meningioma, and brain metastases.
Purpose
Perfusion-weighted MRI (PWI) and O-(2-
18
Ffluoroethyl-)-
l
-tyrosine (
18
FFET) PET are both applied to discriminate tumor progression (TP) from treatment-related changes (TRC) in patients ...with suspected recurrent glioma. While the combination of both methods has been reported to improve the diagnostic accuracy, the performance of a sequential implementation has not been further investigated. Therefore, we retrospectively analyzed the diagnostic value of consecutive PWI and
18
FFET PET.
Methods
We evaluated 104 patients with WHO grade II–IV glioma and suspected TP on conventional MRI using PWI and dynamic
18
FFET PET. Leakage corrected maximum relative cerebral blood volumes (rCBV
max
) were obtained from dynamic susceptibility contrast PWI. Furthermore, we calculated static (i.e., maximum tumor to brain ratios; TBR
max
) and dynamic
18
FFET PET parameters (i.e., Slope). Definitive diagnoses were based on histopathology (
n
= 42) or clinico-radiological follow-up (
n
= 62). The diagnostic performance of PWI and
18
FFET PET parameters to differentiate TP from TRC was evaluated by analyzing receiver operating characteristic and area under the curve (AUC).
Results
Across all patients, the differentiation of TP from TRC using rCBV
max
or
18
FFET PET parameters was moderate (AUC = 0.69–0.75;
p
< 0.01). A rCBV
max
cutoff > 2.85 had a positive predictive value for TP of 100%, enabling a correct TP diagnosis in 44 patients. In the remaining 60 patients, combined static and dynamic
18
FFET PET parameters (TBR
max
, Slope) correctly discriminated TP and TRC in a significant 78% of patients, increasing the overall accuracy to 87%. A subgroup analysis of isocitrate dehydrogenase (IDH) mutant tumors indicated a superior performance of PWI to
18
FFET PET (AUC = 0.8/< 0.62,
p
< 0.01/≥ 0.3).
Conclusion
While marked hyperperfusion on PWI indicated TP,
18
FFET PET proved beneficial to discriminate TP from TRC when PWI remained inconclusive. Thus, our results highlight the clinical value of sequential use of PWI and
18
FFET PET, allowing an economical use of diagnostic methods. The impact of an
IDH
mutation needs further investigation.
Routine diagnostics and treatment monitoring of brain tumors is usually based on contrast-enhanced MRI. However, the capacity of conventional MRI to differentiate tumor tissue from posttherapeutic ...effects following neurosurgical resection, chemoradiation, alkylating chemotherapy, radiosurgery, and/or immunotherapy may be limited. Metabolic imaging using PET can provide relevant additional information on tumor metabolism, which allows for more accurate diagnostics especially in clinically equivocal situations. This review article focuses predominantly on the amino acid PET tracers
C-methyl-l-methionine (MET),
-(2-
Ffluoroethyl)-l-tyrosine (FET) and 3,4-dihydroxy-6-
F-fluoro-l-phenylalanine (FDOPA) and summarizes investigations regarding monitoring of brain tumor therapy.
Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of ...PET using O-(2-18F-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.
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