Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET.

Evaluation of metabolic tumor volume (MTV) changes using amino acid PET has become an important tool for response assessment in brain tumor patients. MTV is usually determined by manual or semiautomatic delineation, which is laborious and may be prone to intra- and interobserver variability. The goal of our study was to develop a method for automated MTV segmentation and to evaluate its performance for response assessment in patients with gliomas. Methods: In total, 699 amino acid PET scans using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) from 555 brain tumor patients at initial diagnosis or during follow-up were retrospectively evaluated (mainly glioma patients, 76%). 18F-FET PET MTVs were segmented semiautomatically by experienced readers. An artificial neural network (no new U-Net) was configured on 476 scans from 399 patients, and the network performance was evaluated on a test dataset including 223 scans from 156 patients. Surface and volumetric Dice similarity coefficients (DSCs) were used to evaluate segmentation quality. Finally, the network was applied to a recently published 18F-FET PET study on response assessment in glioblastoma patients treated with adjuvant temozolomide chemotherapy for a fully automated response assessment in comparison to an experienced physician. Results: In the test dataset, 92% of lesions with increased uptake (n = 189) and 85% of lesions with iso- or hypometabolic uptake (n = 33) were correctly identified (F1 score, 92%). Single lesions with a contiguous uptake had the highest DSC, followed by lesions with heterogeneous, noncontiguous uptake and multifocal lesions (surface DSC: 0.96, 0.93, and 0.81 respectively; volume DSC: 0.83, 0.77, and 0.67, respectively). Change in MTV, as detected by the automated segmentation, was a significant determinant of disease-free and overall survival, in agreement with the physician's assessment. Conclusion: Our deep learning-based 18F-FET PET segmentation allows reliable, robust, and fully automated evaluation of MTV in brain tumor patients and demonstrates clinical value for automated response assessment.

The impact of brain lesions on health-related quality of life in patients with WHO CNS grade 3 or 4 glioma: a lesion-function and resting-state fMRI analysis.

PURPOSE: In glioma patients, tumor development and multimodality therapy are associated with changes in health-related quality of life (HRQoL). It is largely unknown how different types and locations of tumor- and treatment-related brain lesions, as well as their relationship to white matter tracts and functional brain networks, affect HRQoL. METHODS: In 121 patients with pretreated gliomas of WHO CNS grades 3 or 4, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET, resting-state functional MRI (rs-fMRI) and self-reported HRQoL questionnaires (EORTC QLQ-C30/BN20) were obtained. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and lesions with pathologically increased FET uptake were delineated. Effects of tumor lateralization, involvement of white matter tracts or resting-state network nodes by different types of lesions and within-network rs-fMRI connectivity were analyzed in terms of their interaction with HRQoL scores. RESULTS: Right hemisphere gliomas were associated with significantly less favorable outcomes in physical, role, emotional and social functioning, compared with left-sided tumors. Most functional HRQoL scores correlated significantly with right-sided white-matter tracts involvement by T2/FLAIR hyperintensities and with loss of within-network functional connectivity of right-sided nodes. Tumors of the left hemisphere caused significantly more communication deficits. CONCLUSION: In pretreated high-grade gliomas, right hemisphere lesions are associated with reduced HRQoL scores in most functional domains except communication ability, compared to tumors of the left hemisphere. These relationships are mainly observed for T2/FLAIR lesions involving structural and functional networks in the right hemisphere. The data suggest that sparing the right hemisphere from treatment-related tissue damage may improve HRQoL in glioma patients.

Alterations in white matter fiber density associated with structural MRI and metabolic PET lesions following multimodal therapy in glioma patients.

Background: In glioma patients, multimodality therapy and recurrent tumor can lead to structural brain tissue damage characterized by pathologic findings in MR and PET imaging. However, little is known about the impact of different types of damage on the fiber architecture of the affected white matter. Patients and methods: This study included 121 pretreated patients (median age, 52 years; ECOG performance score, 0 in 48%, 1-2 in 51%) with histomolecularly characterized glioma (WHO grade IV glioblastoma, n=81; WHO grade III anaplastic astrocytoma, n=28; WHO grade III anaplastic oligodendroglioma, n=12), who had a resection, radiotherapy, alkylating chemotherapy, or combinations thereof. After a median follow-up time of 14 months (range, 1-214 months), anatomic MR and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET images were acquired on a 3T hybrid PET/MR scanner. Post-therapeutic findings comprised resection cavities, regions with contrast enhancement or increased FET uptake and T2/FLAIR hyperintensities. Local fiber density was determined from high angular-resolution diffusion-weighted imaging and advanced tractography methods. A cohort of 121 healthy subjects selected from the 1000BRAINS study matched for age, gender and education served as a control group. Results: Lesion types differed in both affected tissue volumes and relative fiber densities compared to control values (resection cavities: median volume 20.9 mL, fiber density 16% of controls; contrast-enhanced lesions: 7.9 mL, 43%; FET uptake areas: 30.3 mL, 49%; T2/FLAIR hyperintensities: 53.4 mL, 57%, p<0.001). In T2/FLAIR-hyperintense lesions caused by peritumoral edema due to recurrent glioma (n=27), relative fiber density was as low as in lesions associated with radiation-induced gliosis (n=13, 48% vs. 53%, p=0.17). In regions with pathologically increased FET uptake, local fiber density was inversely related (p=0.005) to the extent of uptake. Total fiber loss associated with contrast-enhanced lesions (p=0.006) and T2/FLAIR hyperintense lesions (p=0.013) had a significant impact on overall ECOG score. Conclusions: These results suggest that apart from resection cavities, reduction in local fiber density is greatest in contrast-enhancing recurrent tumors, but total fiber loss induced by edema or gliosis has an equal detrimental effect on the patients' performance status due to the larger volume affected.

MRI Analysis Of the Water Content Change In the Brain During Acute Ethanol Consumption Via Quantitative Water Mapping.

AIMS: Alcohol consumption influences the water balance in the brain. While the impact of chronic alcohol misuse on cerebral water content has been the subject of several studies, less is known about the effects of acute alcohol misuse, with contradictory results in the literature. Therefore, we investigated the effects of acute alcohol intoxication on cerebral water content using a precise quantitative magnetic resonance imaging (MRI) sequence. METHODS: In a prospective study, we measured cerebral water content in 20 healthy volunteers before alcohol consumption and after reaching a breath alcohol concentration of 1 ‰. A quantitative MRI water mapping sequence was conducted on a clinical 3 T system. Non-alcoholic fluid input and output were documented and accounted for. Water content was assessed for whole brain, grey and white matter and more specifically for regions known to be affected by acute or chronic alcohol misuse (occipital and frontal lobes, thalamus and pons). Changes in the volume of grey and white matter as well as the whole brain were examined. RESULTS: Quantitative cerebral water content before and after acute alcohol consumption did not differ significantly (P ≥ 0.07), with changes often being within the range of measurement accuracy. Whole brain, white and grey matter volume did not change significantly (P ≥ 0.12). CONCLUSION: The results of our study show no significant water content or volume change in the brain after recent alcohol intake in healthy volunteers. This accounts for the whole brain, grey and white matter, occipital and frontal lobes, thalamus and pons.

Case Report: Disruption of Resting-State Networks and Cognitive Deficits After Whole Brain Irradiation for Singular Brain Metastasis.

Introduction: Long-term survivors of whole brain radiation (WBRT) are at significant risk for developing cognitive deficits, but knowledge about the underlying pathophysiological mechanisms is limited. Therefore, we here report a rare case with a singular brain metastasis treated by resection and WBRT that survived for more than 10 years where we investigated the integrity of brain networks using resting-state functional MRI. Methods: A female patient with a left frontal non-small cell lung cancer (NSCLC) brain metastasis had resection and postoperative WBRT (30.0 in 3.0 Gy fractions) and stayed free from brain metastasis recurrence for a follow-up period of 11 years. Structural magnetic resonance imaging (MRI) and amino acid [O-(2-[18F]fluoroethyl)-L-tyrosine] positron emission tomography (FET PET) were repeatedly acquired. At the last follow up, neurocognitive functions and resting-state functional connectivity (RSFC) using resting-state fMRI were assessed. Within-network and inter-network connectivity of seven resting-state networks were computed from a connectivity matrix. All measures were compared to a matched group of 10 female healthy subjects. Results: At the 11-year follow-up, T2/FLAIR MR images of the patient showed extended regions of hyper-intensities covering mainly the white mater of the bilateral dorsal frontal and parietal lobes while sparing most of the temporal lobes. Compared to the healthy subjects, the patient performed significantly worse in all cognitive domains that included executive functions, attention and processing speed, while verbal working memory, verbal episodic memory, and visual working memory were left mostly unaffected. The connectivity matrix showed a heavily disturbed pattern with a widely distributed, scattered loss of RSFC. The within-network RSFC revealed a significant loss of connectivity within all seven networks where the dorsal attention and fronto-parietal control networks were affected most severely. The inter-network RSFC was significantly reduced for the visual, somato-motor, and dorsal and ventral attention networks. Conclusion: As demonstrated here in a patient with a metastatic NSCLC and long-term survival, WBRT may lead to extended white matter damage and cause severe disruption of the RSFC in multiple resting state networks. In consequence, executive functioning which is assumed to depend on the interaction of several networks may be severely impaired following WBRT apart from the well-recognized deficits in memory function.

Lesion-Function Analysis from Multimodal Imaging and Normative Brain Atlases for Prediction of Cognitive Deficits in Glioma Patients.

Cognitive deficits are common in glioma patients following multimodality therapy, but the relative impact of different types and locations of treatment-related brain damage and recurrent tumors on cognition is not well understood. In 121 WHO Grade III/IV glioma patients, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine FET-PET, and neuropsychological testing were performed at a median interval of 14 months (range, 1-214 months) after therapy initiation. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and FET-PET positive tumor sites were semi-automatically segmented and elastically registered to a normative, resting state (RS) fMRI-based functional cortical network atlas and to the JHU atlas of white matter (WM) tracts, and their influence on cognitive test scores relative to a cohort of matched healthy subjects was assessed. T2/FLAIR hyperintensities presumably caused by radiation therapy covered more extensive brain areas than the other lesion types and significantly impaired cognitive performance in many domains when affecting left-hemispheric RS-nodes and WM-tracts as opposed to brain tissue damage caused by resection or recurrent tumors. Verbal episodic memory proved to be especially vulnerable to T2/FLAIR abnormalities affecting the nodes and tracts of the left temporal lobe. In order to improve radiotherapy planning, publicly available brain atlases, in conjunction with elastic registration techniques, should be used, similar to neuronavigation in neurosurgery.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes.

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Evaluation of FET PET Radiomics Feature Repeatability in Glioma Patients.

Amino acid PET using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine (FET) has attracted considerable interest in neurooncology. Furthermore, initial studies suggested the additional diagnostic value of FET PET radiomics in brain tumor patient management. However, the conclusiveness of radiomics models strongly depends on feature generalizability. We here evaluated the repeatability of feature-based FET PET radiomics. A test-retest analysis based on equivalent but statistically independent subsamples of FET PET images was performed in 50 newly diagnosed and histomolecularly characterized glioma patients. A total of 1,302 radiomics features were calculated from semi-automatically segmented tumor volumes-of-interest (VOIs). Furthermore, to investigate the influence of the spatial resolution of PET on repeatability, spherical VOIs of different sizes were positioned in the tumor and healthy brain tissue. Feature repeatability was assessed by calculating the intraclass correlation coefficient (ICC). To further investigate the influence of the isocitrate dehydrogenase (IDH) genotype on feature repeatability, a hierarchical cluster analysis was performed. For tumor VOIs, 73% of first-order features and 71% of features extracted from the gray level co-occurrence matrix showed high repeatability (ICC 95% confidence interval, 0.91-1.00). In the largest spherical tumor VOIs, 67% of features showed high repeatability, significantly decreasing towards smaller VOIs. The IDH genotype did not affect feature repeatability. Based on 297 repeatable features, two clusters were identified separating patients with IDH-wildtype glioma from those with an IDH mutation. Our results suggest that robust features can be obtained from routinely acquired FET PET scans, which are valuable for further standardization of radiomics analyses in neurooncology.

Early Treatment Response Assessment Using 18F-FET PET Compared with Contrast-Enhanced MRI in Glioma Patients After Adjuvant Temozolomide Chemotherapy.

The goal of this study was to compare the value of contrast-enhanced MRI and O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET for response assessment in glioma patients after adjuvant temozolomide chemotherapy (TMZ). Methods: After biopsy or resection and completion of radiotherapy with concomitant TMZ, 41 newly diagnosed and histomolecularly characterized glioma patients (glioblastoma, 90%; age range, 20-79 y) were subsequently treated with adjuvant TMZ. MR and 18F-FET PET imaging were performed at baseline and after the second cycle of adjuvant TMZ. We obtained 18F-FET metabolic tumor volumes (MTVs) as well as mean and maximum tumor-to-brain ratios (TBRmean and TBRmax, respectively). Threshold values of 18F-FET PET parameters to predict outcome were established by receiver-operating-characteristic analyses using a median progression-free survival (PFS) of ≥ 9 mo and overall survival (OS) of ≥ 15 mo as reference. MRI response assessment was based on the Response Assessment in Neuro-Oncology (RANO) working group criteria. The predictive value of changes of 18F-FET PET and MRI parameters on survival was evaluated subsequently using univariate and multivariate survival estimates. Results: After 2 cycles of adjuvant TMZ chemotherapy, a treatment-induced reduction of MTV and TBRmax predicted a significantly longer PFS and OS (both P ≤ 0.03; univariate survival analyses) whereas RANO criteria were not significant (P > 0.05). Multivariate survival analysis revealed that TBRmax changes predicted a prolonged PFS (P = 0.012) and changes of MTV a prolonged OS (P = 0.005) independent of O6-methylguanine-DNA-methyltransferase promoter methylation and other strong prognostic factors. Conclusion: Changes of 18F-FET PET parameters appear to be helpful for identifying responders to adjuvant TMZ early after treatment initiation.

FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation.

Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBRmax) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted.

Investigating obesity-associated brain inflammation using quantitative water content mapping.

There is growing evidence that obesity is associated with inflammation in the brain, which could contribute to the pathogenesis of obesity. In humans, it is challenging to detect brain inflammation in vivo. Recently, quantitative magnetic resonance imaging (qMRI) has emerged as a tool for characterising pathophysiological processes in the brain with reliable and reproducible measures. Proton density imaging provides quantitative assessment of the brain water content, which is affected in different pathologies, including inflammation. We enrolled 115 normal weight, overweight and obese men and women (body mass index [BMI] range 20.1-39.7 kg m-2 , age range 20-75 years, 60% men) to acquire cerebral water content mapping in vivo using MRI at 3 Tesla. We investigated potential associations between brain water content with anthropometric measures of obesity, body fat distribution and whole-body metabolism. No global changes in water content were associated with obesity. However, higher water content values in the cerebellum, limbic lobe and sub-lobular region were detected in participants with higher BMI, independent of age. More specifically, the dorsal striatum, hypothalamus, thalamus, fornix, anterior limb of the internal capsule and posterior thalamic radiation showed the strongest relationship with BMI, independent of age. In a subgroup with available measurements (n = 50), we identified visceral adipose tissue to be the strongest tested link between higher water content values and obesity. Individuals with metabolic syndrome had the highest water content values in the hypothalamus and the fornix. There is accumulating evidence that inflammation of the hypothalamus contributed to obesity-associated insulin resistance in that area. Whether brain inflammation is a cause or consequence of obesity in humans still needs to be investigated using a longitudinal study design. Using qMRI, we were able to detect marked water content changes in young and older obese adults, which is most likely the result of chronic low-grade inflammation.

Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment.

BACKGROUND: Progressive cognitive decline following multimodal neurooncological treatment is a common observation in patients suffering from malignant glioma. Alterations of the default-mode network (DMN) represent a possible source of impaired neurocognitive functioning and were analyzed in these patients. METHODS: Eighty patients (median age, 51 years) with glioma (WHO grade IV glioblastoma, n = 57; WHO grade III anaplastic astrocytoma, n = 13; WHO grade III anaplastic oligodendroglioma, n = 10) and ECOG performance score 0-1 underwent resting-state functional MRI (rs-fMRI) and neuropsychological testing at a median interval of 13 months (range, 1-114 months) after initiation of therapy. For evaluation of structural and metabolic changes after treatment, anatomical MRI and amino acid PET using O-(2-[18F]fluoroethyl)-L-tyrosine (FET) were simultaneously acquired to rs-fMRI on a hybrid MR/PET scanner. A cohort of 80 healthy subjects matched for gender, age, and educational status served as controls. RESULTS: The connectivity pattern within the DMN (12 nodes) of the glioma patients differed significantly from that of the healthy subjects but did not depend on age, tumor grade, time since treatment initiation, presence of residual/recurrent tumor, number of chemotherapy cycles received, or anticonvulsive medication. Small changes in the connectivity pattern were observed in patients who had more than one series of radiotherapy. In contrast, structural tissue changes located at or near the tumor site (including resection cavities, white matter lesions, edema, and tumor tissue) had a strong negative impact on the functional connectivity of the adjacent DMN nodes, resulting in a marked dependence of the connectivity pattern on tumor location. In the majority of neurocognitive domains, glioma patients performed significantly worse than healthy subjects. Correlation analysis revealed that reduced connectivity in the left temporal and parietal DMN nodes was associated with low performance in language processing and verbal working memory. Furthermore, connectivity of the left parietal DMN node also correlated with processing speed, executive function, and verbal as well as visual working memory. Overall DMN connectivity loss and cognitive decline were less pronounced in patients with higher education. CONCLUSION: Personalized treatment strategies for malignant glioma patients should consider the left parietal and temporal DMN nodes as vulnerable regions concerning neurocognitive outcome.

Prediction of survival in patients with IDH-wildtype astrocytic gliomas using dynamic O-(2-[18F]-fluoroethyl)-L-tyrosine PET.

PURPOSE: Integrated histomolecular diagnostics of gliomas according to the World Health Organization (WHO) classification of 2016 has refined diagnostic accuracy and prediction of prognosis. This study aimed at exploring the prognostic value of dynamic O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET in newly diagnosed, histomolecularly classified astrocytic gliomas of WHO grades III or IV. METHODS: Before initiation of treatment, dynamic FET PET imaging was performed in patients with newly diagnosed glioblastoma (GBM) and anaplastic astrocytoma (AA). Static FET PET parameters such as maximum and mean tumour/brain ratios (TBRmax/mean), the metabolic tumour volume (MTV) as well as the dynamic FET PET parameters time-to-peak (TTP) and slope, were obtained. The predictive ability of FET PET parameters was evaluated concerning the progression-free and overall survival (PFS, OS). Using ROC analyses, threshold values for FET PET parameters were obtained. Subsequently, univariate Kaplan-Meier and multivariate Cox regression survival analyses were performed to assess the predictive power of these parameters for survival. RESULTS: Sixty patients (45 GBM and 15 AA patients) of two university centres were retrospectively identified. Patients with isocitrate dehydrogenase (IDH)-mutant or O6-methylguanine-DNA-methyltransferase (MGMT) promoter-methylated tumours had a significantly longer PFS and OS (both P < 0.001). Furthermore, ROC analysis of IDH-wildtype glioma patients (n = 45) revealed that a TTP > 25 min (AUC, 0.90; sensitivity, 90%; specificity, 87%; P < 0.001) was highly prognostic for longer PFS (13 vs. 7 months; P = 0.005) and OS (29 vs. 12 months; P < 0.001). In contrast, at a lower level of significance, TBRmax, TBRmean, and MTV were only prognostic for longer OS (P = 0.004, P = 0.038, and P = 0.048, respectively). Besides complete resection and a methylated MGMT promoter, TTP remained significant in multivariate survival analysis (all P ≤ 0.02), indicating an independent predictor for OS. CONCLUSIONS: Our data suggest that dynamic FET PET allows the identification of patients with longer OS among patients with newly diagnosed IDH-wildtype GBM and AA.

Feature-based PET/MRI radiomics in patients with brain tumors.

Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET, thereby providing additional, potentially relevant diagnostic information for clinical decision-making. Because the computation of these features is performed highly automated on medical images acquired during routine follow-up, radiomics offers this information at low cost. Further, the radiomics features can be used alone or combined with other clinical or histomolecular parameters to generate predictive or prognostic mathematical models. These models can then be applied for various important diagnostic indications in neuro-oncology, for example, to noninvasively predict relevant biomarkers in glioma patients, to differentiate between treatment-related changes and local brain tumor relapse, or to predict treatment response. In recent years, amino acid PET has become an important diagnostic tool in patients with brain tumors. Therefore, the number of studies in patients with brain tumors investigating the potential of PET radiomics or combined PET/MRI radiomics is steadily increasing. This review summarizes current research regarding feature-based PET as well as combined PET/MRI radiomics in neuro-oncology.

Differentiation of treatment-related changes from tumour progression: a direct comparison between dynamic FET PET and ADC values obtained from DWI MRI.

BACKGROUND: Following brain cancer treatment, the capacity of anatomical MRI to differentiate neoplastic tissue from treatment-related changes (e.g., pseudoprogression) is limited. This study compared apparent diffusion coefficients (ADC) obtained by diffusion-weighted MRI (DWI) with static and dynamic parameters of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation of treatment-related changes from tumour progression. PATIENTS AND METHODS: Forty-eight pretreated high-grade glioma patients with anatomical MRI findings suspicious for progression (median time elapsed since last treatment was 16 weeks) were investigated using DWI and dynamic FET PET. Maximum and mean tumour-to-brain ratios (TBRmax, TBRmean) as well as dynamic parameters (time-to-peak and slope values) of FET uptake were calculated. For mean ADC calculation, regions-of-interest analyses were performed on ADC maps calculated from DWI coregistered with the contrast-enhanced MR image. Diagnoses were confirmed neuropathologically (21%) or clinicoradiologically. Diagnostic performance was evaluated using receiver-operating-characteristic analyses or Fisher's exact test for a combinational approach. RESULTS: Ten of 48 patients had treatment-related changes (21%). The diagnostic performance of FET PET was significantly higher (threshold for both TBRmax and TBRmean, 1.95; accuracy, 83%; AUC, 0.89 ± 0.05; P < 0.001) than that of ADC values (threshold ADC, 1.09 × 10-3 mm2/s; accuracy, 69%; AUC, 0.73 ± 0.09; P = 0.13). The addition of static FET PET parameters to ADC values increased the latter's accuracy to 89%. The highest accuracy was achieved by combining static and dynamic FET PET parameters (93%). Moreover, in contrast to ADC values, TBRs <1.95 at suspected progression predicted a significantly longer survival (P = 0.01). CONCLUSIONS: Data suggest that static and dynamic FET PET provide valuable information concerning the differentiation of early treatment-related changes from tumour progression and outperform ADC measurement for this highly relevant clinical question.

Influence of Dexamethasone on O-(2-[18F]-Fluoroethyl)-L-Tyrosine Uptake in the Human Brain and Quantification of Tumor Uptake.

PURPOSE: O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) is an established positron emission tomography (PET) tracer for brain tumor imaging. This study explores the influence of dexamethasone therapy on [18F]FET uptake in the normal brain and its influence on the maximum and mean tumor-to-brain ratio (TBR). PROCEDURES: [18F]FET PET scans of 160 brain tumor patients were evaluated (80 dexamethasone treated, 80 untreated; each group with 40 men/40 women). The standardized uptake value of [18F]FET uptake in the normal brain (SUVbrain) in the different groups was compared. Nine patients were examined repeatedly with and without dexamethasone therapy. RESULTS: SUVbrain of [18F]FET uptake was significantly higher in dexamethasone-treated patients than in untreated patients (SUVbrain 1.33 ± 0.1 versus 1.06 ± 0.16 in male and 1.45 ± 0.25 versus 1.31 ± 0.28 in female patients). Similar results were observed in patients with serial PET scans. Furthermore, compared to men, a significantly higher SUVbrain was found in women, both with and without dexamethasone treatment. There were no significant differences between the different groups for TBRmax and TBRmean, which could have been masked by the high standard deviation. In a patient with a stable brain metastasis investigated twice with and without dexamethasone, the TBRmax and the biological tumor volume (BTV) decreased considerably after dexamethasone due to an increased SUVbrain. CONCLUSION: Dexamethasone treatment appears to increase the [18F]FET uptake in the normal brain. An effect on TBRmax, TBRmean, and BTV cannot be excluded which should be considered especially for treatment monitoring and the estimation of BTV using [18F]FET PET.

What magnetic resonance imaging reveals - A systematic review of the relationship between type II diabetes and associated brain distortions of structure and cognitive functioning.

Due to its increasing prevalence, Type 2 diabetes mellitus (T2DM) represents a major health challenge for modern society. Despite it being of fundamental interest, only a few MRI studies have conducted statistical analyses to draw scientifically valid conclusions about the complex interplay of T2DM and its associated clinical, structural, functional, metabolite, as well as cognitive distortions. Therefore, a systematic review of 68 manuscripts, following the PRISMA guidelines, was conducted. Notably, although the associations between imaging, clinical, and cognitive variables are not fully homogeneous, findings show a clear trend towards a link between altered brain structure and a decline in cognitive processing ability. The results of the review highlight the heterogeneity of the methods used across manuscripts in terms of assessed clinical variables, imaging, and data analysis methods. This is particularly significant as, if the subjects' criteria are not carefully considered, results are easily prone to confounding factors.

FET PET reveals considerable spatial differences in tumour burden compared to conventional MRI in newly diagnosed glioblastoma.

PURPOSE: Areas of contrast enhancement (CE) on MRI are usually the target for resection or radiotherapy target volume definition in glioblastomas. However, the solid tumour mass may extend beyond areas of CE. Amino acid PET can detect parts of the tumour that show no CE. We systematically investigated tumour volumes delineated by amino acid PET and MRI in patients with newly diagnosed, untreated glioblastoma. METHODS: Preoperatively, 50 patients with neuropathologically confirmed glioblastoma underwent O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET, and fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced MRI. Areas of CE were manually segmented. FET PET tumour volumes were segmented using a tumour-to-brain ratio of ≥1.6. The percentage overlap volumes, and Dice and Jaccard spatial similarity coefficients (DSC, JSC) were calculated. FLAIR images were evaluated visually. RESULTS: In 43 patients (86%), the FET tumour volume was significantly larger than the CE volume (21.5 ± 14.3 mL vs. 9.4 ± 11.3 mL; P < 0.001). Forty patients (80%) showed both increased uptake of FET and CE. In these 40 patients, the spatial similarity between FET uptake and CE was low (mean DSC 0.39 ± 0.21, mean JSC 0.26 ± 0.16). Ten patients (20%) showed no CE, and one of these patients showed no FET uptake. In five patients (10%), increased FET uptake was present outside areas of FLAIR hyperintensity. CONCLUSION: Our results show that the metabolically active tumour volume delineated by FET PET is significantly larger than tumour volume delineated by CE. Furthermore, the results strongly suggest that the information derived from both imaging modalities should be integrated into the management of patients with newly diagnosed glioblastoma.

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

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-[18F]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.

Predicting IDH genotype in gliomas using FET PET radiomics.

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-[18F]fluoroethyl)-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.