Amino acid PET in neuro-oncology: applications in the clinic

Galldiks, Norbert; Langen, Karl‐Josef

doi:10.1080/14737140.2017.1302799

Cited by 25 publications

(20 citation statements)

References 27 publications

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“…Over the past years, several studies have demonstrated that amino acid PET alone is a potent imaging method for the identification of treatment-related changes such as pseudoprogression (Galldiks et al, 2015; Kebir et al, 2016a; Kebir et al, 2016b; Galldiks, 2017) or radiation injury (Ceccon et al, 2017; Galldiks et al, 2012; Lohmann et al, 2017) in patients with glioma and brain metastasis. For the differentiation of radiation injury from brain metastasis recurrence, the diagnostic accuracy of static (i.e., tumor/brain ratios) and dynamic FET PET parameters (i.e., time-to-peak values and the slope of time-activity curves) has been evaluated in a pilot study by Galldiks et al (2012).…”

Section: Discussionmentioning

confidence: 99%

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Lohmann

Köcher

Ceccon

et al. 2018

NeuroImage: Clinical

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121

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BackgroundThe aim of this study was to investigate the potential of combined textural feature analysis of contrast-enhanced MRI (CE-MRI) and static O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation between local recurrent brain metastasis and radiation injury since CE-MRI often remains inconclusive.MethodsFifty-two patients with new or progressive contrast-enhancing brain lesions on MRI after radiotherapy (predominantly stereotactic radiosurgery) of brain metastases were additionally investigated using FET PET. Based on histology (n = 19) or clinicoradiological follow-up (n = 33), local recurrent brain metastases were diagnosed in 21 patients (40%) and radiation injury in 31 patients (60%). Forty-two textural features were calculated on both unfiltered and filtered CE-MRI and summed FET PET images (20–40 min p.i.), using the software LIFEx. After feature selection, logistic regression models using a maximum of five features to avoid overfitting were calculated for each imaging modality separately and for the combined FET PET/MRI features. The resulting models were validated using cross-validation. Diagnostic accuracies were calculated for each imaging modality separately as well as for the combined model.ResultsFor the differentiation between radiation injury and recurrence of brain metastasis, textural features extracted from CE-MRI had a diagnostic accuracy of 81% (sensitivity, 67%; specificity, 90%). FET PET textural features revealed a slightly higher diagnostic accuracy of 83% (sensitivity, 88%; specificity, 75%). However, the highest diagnostic accuracy was obtained when combining CE-MRI and FET PET features (accuracy, 89%; sensitivity, 85%; specificity, 96%).ConclusionsOur findings suggest that combined FET PET/CE-MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.

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Section: Discussionmentioning

confidence: 99%

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Lohmann

Köcher

Ceccon

et al. 2018

NeuroImage: Clinical

Self Cite

121

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show abstract

“…Over the past years, several studies have demonstrated that amino acid PET alone is a potent imaging method for the identification of treatment-related changes such as pseudoprogression (Galldiks et al, 2015;Kebir et al, 2016a;Kebir et al, 2016b;Galldiks, 2017) or radiation injury (Ceccon et al, 2017;Galldiks et al, 2012;Lohmann et al, 2017) in patients with glioma and brain metastasis. For the differentiation of radiation injury from brain metastasis recurrence, the diagnostic accuracy of static (i.e., tumor/brain ratios) and dynamic FET PET parameters (i.e., time-to-peak values and the slope of time-activity Fig.…”

Section: Discussionmentioning

confidence: 99%

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Lohmann

Köcher

Ceccon

et al. 2019

57. Jahrestagung Der Deutschen Gesellschaft Für Nuklearmedizin

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Background: The aim of this study was to investigate the potential of combined textural feature analysis of contrast-enhanced MRI (CE-MRI) and static O-(2-[ 18 F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation between local recurrent brain metastasis and radiation injury since CE-MRI often remains inconclusive. Methods: Fifty-two patients with new or progressive contrast-enhancing brain lesions on MRI after radiotherapy (predominantly stereotactic radiosurgery) of brain metastases were additionally investigated using FET PET. Based on histology (n = 19) or clinicoradiological follow-up (n = 33), local recurrent brain metastases were diagnosed in 21 patients (40%) and radiation injury in 31 patients (60%). Forty-two textural features were calculated on both unfiltered and filtered CE-MRI and summed FET PET images (20-40 min p.i.), using the software LIFEx. After feature selection, logistic regression models using a maximum of five features to avoid overfitting were calculated for each imaging modality separately and for the combined FET PET/MRI features. The resulting models were validated using cross-validation. Diagnostic accuracies were calculated for each imaging modality separately as well as for the combined model. Results: For the differentiation between radiation injury and recurrence of brain metastasis, textural features extracted from CE-MRI had a diagnostic accuracy of 81% (sensitivity, 67%; specificity, 90%). FET PET textural features revealed a slightly higher diagnostic accuracy of 83% (sensitivity, 88%; specificity, 75%). However, the highest diagnostic accuracy was obtained when combining CE-MRI and FET PET features (accuracy, 89%; sensitivity, 85%; specificity, 96%). Conclusions: Our findings suggest that combined FET PET/CE-MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.

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“…PET/MRI allows for multiparametric imaging at the same time by combining conventional MRI, advanced MRI, and PET imaging, all images acquired under the same physiological conditions and the same iso-center for optimal realignment. However, the issue of attenuation correction is not fully solved [53][54][55].…”

Section: Plos Onementioning

confidence: 99%

Reference values of physiological 18F-FET uptake: Implications for brain tumor discrimination

Fuenfgeld¹,

Mächler²,

Fischer³

et al. 2020

PLoS ONE

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The aim of this study was to derive reference values of 18F-fluoro-ethyl-L-tyrosine positron emission tomography (18F-FET-PET) uptake in normal brain and head structures to allow for differentiation from tumor tissue. Materials and methods We examined the datasets of 70 patients (median age 53 years, range 15-79), whose dynamic 18F-FET-PET was acquired between January 2016 and October 2017. Maximum standardized uptake value (SUVmax), target-to-background standardized uptake value ratio (TBR), and time activity curve (TAC) of the 18F-FET-PET were assessed in tumor tissue and in eight normal anatomic structures and compared using the t-test and Mann-Whitney U-test. Correlation analyses were performed using Pearson or Spearman coefficients, and comparisons between several variables with Pearson's chi-squared tests and Kruskal-Wallis tests as well as the Benjamini-Hochberg correction. Results All analyzed structures showed an 18F-FET uptake higher than background (threshold: TBR > 1.5). The venous sinuses and cranial muscles exhibited a TBR of 2.03±0.46 (confidence interval (CI) 1.92-2.14), higher than the uptake of caudate nucleus, pineal gland, putamen, and thalamus (TBR 1.42±0.17, CI 1.38-1.47). SUVmax, TBR, and TAC showed no difference in the analyzed structures between subjects with high-grade gliomas and subjects with low-grade gliomas, except the SUV max of the pineal gland (t-tests of the pineal gland: SUVmax: p = 0.022; TBR: p = 0.411). No significant differences were found for gender and age.

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Amino acid PET in neuro-oncology: applications in the clinic

Cited by 25 publications

References 27 publications

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Reference values of physiological 18F-FET uptake: Implications for brain tumor discrimination

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