Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease - A simultaneous resting-state FDG-PET/fMRI study

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Hybrid PET/MRI was used to explore network segregation and glucose metabolism in AD.

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DMN, CEN, and SN showed reduced segregation in AD.

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In salience network, segregation coupled with glucose metabolism in CN group.

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The coupled segregation and glucose metabolism in CN disappeared in MCI and AD.

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Reduced segregation and hypometabolism were associated with cognitive impairments.

The aberrant organization and functioning of three core neurocognitive networks (NCNs), i.e., default-mode network (DMN), central executive network (CEN), and salience network (SN), are among the prominent features in Alzheimer’s disease (AD). The dysregulation of both intra- and inter-network functional connectivities (FCs) of the three NCNs contributed to AD-related cognitive and behavioral abnormalities. Brain functional network segregation, integrating intra- and inter-network FCs, is essential for maintaining the energetic efficiency of brain metabolism. The association of brain functional network segregation, together with glucose metabolism, with age-related cognitive decline was recently shown. Yet how these joint functional-metabolic biomarkers relate to cognitive decline along with mild cognitive impairment (MCI) and AD remains to be elucidated. In this study, under the framework of the triple-network model, we performed a hybrid FDG-PET/fMRI study to evaluate the concurrent changes of resting-state brain intrinsic FCs and glucose metabolism of the three NCNs across cognitively normal (CN) (N = 24), MCI (N = 21), and AD (N = 21) groups. Lower network segregation and glucose metabolism were observed in all three NCNs in patients with AD. More interestingly, in the SN, the coupled relationship between network segregation and glucose metabolism existed in the CN group (r = 0.523, p = 0.013) and diminished in patients with MCI (r = 0.431, p = 0.065) and AD (r = 0.079, p = 0.748). Finally, the glucose metabolism of the DMN (r = 0.380, p = 0.017) and the network segregation of the SN (r = 0.363, p = 0.023) were significantly correlated with the general cognitive status of the patients. Our findings suggest that the impaired SN segregation and its uncoupled relationship with glucose metabolism contribute to the cognitive decline in AD.

Simultaneous FET-PET and contrast-enhanced MRI based on hybrid PET/MR improves delineation of tumor spatial biodistribution in gliomas: a biopsy validation study

Purpose

Glioma treatment planning requires precise tumor delineation, which is typically performed with contrast-enhanced (CE) MRI. However, CE MRI fails to reflect the entire extent of glioma. O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) PET may detect tumor volumes missed by CE MRI. We investigated the clinical value of simultaneous FET-PET and CE MRI in delineating tumor extent before treatment planning. Guided stereotactic biopsy was used to validate the findings.

Methods

Conventional MRI and ¹⁸F-FET PET were performed simultaneously on a hybrid PET/MR in 33 patients with histopathologically confirmed glioma. Tumor volumes were quantified using a tumor-to-brain ratio ≥ 1.6 (V_PET) and a visual threshold (V_CE). We visually assessed abnormal areas on FLAIR images and calculated Dice’s coefficient (DSC), overlap volume (OV), discrepancy-PET, and discrepancy-CE. Additionally, several stereotactic biopsy samples were taken from “matched” or “mismatched” FET-PET and CE MRI regions.

Results

Among 31 patients (93.94%), FET-PET delineated significantly larger tumor volumes than CE MRI (77.84 ± 51.74 cm³ vs. 34.59 ± 27.07 cm³, P < 0.05). Of the 21 biopsy samples obtained from regions with increased FET uptake, all were histopathologically confirmed as glioma tissue or tumor infiltration, whereas only 13 showed enhancement on CE MRI. Among all patients, the spatial similarity between V_PET and V_CE was low (average DSC 0.56 ± 0.22), while the overlap was high (average OV 0.95 ± 0.08). The discrepancy-CE and discrepancy-PET were lower than 10% in 28 and 0 patients, respectively. Eleven patients showed V_PET partially beyond abnormal signal areas on FLAIR images.

Conclusion

The metabolically active biodistribution of gliomas delineated with FET-PET significantly exceeds tumor volume on CE MRI, and histopathology confirms these findings. Our preliminary results indicate that combining the anatomic and molecular information obtained from conventional MRI and FET-PET would reveal a more accurate glioma extent, which is critical for individualized treatment planning.

Electronic supplementary material

The online version of this article (10.1007/s00259-019-04656-2) contains supplementary material, which is available to authorized users.

Clinical evaluation of whole-body oncologic PET with time-of-flight and point-spread function for the hybrid PET/MR system

PURPOSE

Hybrid positron emission tomography/magnetic resonance (PET/MR) imaging is a new multimodality imaging technology that can provide structural and functional information simultaneously. The aim of this study was to investigate the effects of the time-of-flight (TOF) and point-spread function (PSF) on small lesions observed in PET/MR images from clinical patient image sets.

MATERIALS AND METHODS

This study evaluated 54 small lesions in 14 patients who had undergone ¹⁸F-fluorodeoxyglucose (FDG) PET/MR. Lesions up to 30mm in diameter were included. The PET data were reconstructed with a baseline ordered-subsets expectation-maximization (OSEM) algorithm, OSEM+PSF, OSEM+TOF and OSEM+TOF+PSF. PET image quality and small lesions were visually evaluated and scored by a 3-point scale. A quantitative analysis was then performed using the mean and maximum standardized uptake value (SUV) of the small lesions (SUV_mean and SUV_max). The lesions were divided into two groups according to the long-axis diameter and the location respectively and evaluated with each reconstruction algorithm. We also evaluated the background signal by analyzing the SUV_liver.

RESULTS

OSEM+TOF+PSF provided the highest value and OSEM+TOF or PSF showed a higher value than OSEM for the visual assessment and quantitative analysis. The combination of TOF and PSF increased the SUV_mean by 26.6% and the SUV_max by 30.0%. The SUV_liverwas not influenced by PSF or TOF. For the OSEM+TOF+PSF model, the change in SUV_mean and SUV_max for lesions <10mm in diameter was 31.9% and 35.8%, and 24.5% and 27.6% for lesions 10-30mm in diameter, respectively. The abdominal lesions obtained the higher SUV than those of chest on the images with TOF and/or PSF.

CONCLUSION

Application of TOF and PSF significantly increased the SUV of small lesions in hybrid PET/MR images, potentially improving small lesion detectability.