Hypoglycemia activates compensatory mechanism of glucose metabolism of brain

Assessing the Effect of Various Blood Glucose Levels on 18F-FDG Activity in the Brain, Liver, and Blood Pool

Studies have extensively analyzed the effect of hyperglycemia on ¹⁸F-FDG uptake in normal tissues and tumors. In this study, we measured SUV in the brain, liver, and blood pool in normoglycemia, hyperglycemia, and hypoglycemia to understand the effect of blood glucose on ¹⁸F-FDG uptake and to develop a formula to correct SUV. Methods: Whole-body ¹⁸F-FDG PET/CT images of adults were selected for analysis. Brain SUV_max, blood-pool SUV_mean, and liver SUV_mean were measured at blood glucose ranges of 61-70, 71-80, 81-90, 91-100, 101-110, 111-120, 121-130, 131-140, 141-150, 151-160, 161-170, 171-180, 181-190, 191-200, and 201 mg/dL and above. At each blood glucose range, 10 PET images were analyzed (total, 150). The mean (±SD) SUV of the brain, liver, and blood pool at each blood glucose range was calculated, and blood glucose and SUV curves were generated. Because brain and tumors show a high expression of glucose transporters 1 and 3, we generated an SUV correction formula based on percentage reduction in brain SUV_max with increasing blood glucose level. Results: Mean brain SUV_max gradually decreased with increasing blood glucose level, starting after a level of 110 mg/dL. The approximate percentage reduction in brain SUV_max was 20%, 35%, 50%, 60%, and 65% at blood glucose ranges of 111-120, 121-140, 141-160, 161-200, and 201 mg/dL and above, respectively. In the formula we generated, measured SUV_max is multiplied by a reduction factor of 1.25, 1.5, 2, 2.5, and 2.8 for the blood glucose ranges of 111-120, 121-140, 141-160, 161-200, and 201 mg/dL and above, respectively, to correct SUV. Brain SUV_max did not differ between hypoglycemic and normoglycemic patients (P > 0.05). SUV_mean in the blood pool and liver was lower in hypoglycemic patients (P < 0.05) and did not differ between hyperglycemic (P > 0.05) and normoglycemic patients. Conclusion: Hyperglycemia gradually reduces brain ¹⁸F-FDG uptake, starting after a blood glucose level of 110 mg/dL. Hyperglycemia does not affect ¹⁸F-FDG activity in the liver or blood pool. Hypoglycemia does not seem to affect brain ¹⁸F-FDG uptake but appears to reduce liver and blood-pool activity. The simple formula we generated can be used to correct SUV in hyperglycemic adults in selected cases.

Effects of glucose, insulin, and insulin resistance on cerebral 18F-FDG distribution in cognitively normal older subjects

Background

Increasing plasma glucose levels and insulin resistance can alter the distribution pattern of fluorine-18-labeled fluorodeoxyglucose (¹⁸F-FDG) in the brain and relatively reduce ¹⁸F-FDG uptake in Alzheimer's disease (AD)-related hypometabolic regions, leading to the appearance of an AD-like pattern. However, its relationship with plasma insulin levels is unclear. We aimed to compare the effects of plasma glucose levels, plasma insulin levels and insulin resistance on the appearance of the AD-like pattern in ¹⁸F-FDG images.

Methods

Fifty-nine cognitively normal older subjects (age = 75.7 ± 6.4 years) underwent ¹⁸F-FDG positron emission tomography along with measurement of plasma glucose and insulin levels. As an index of insulin resistance, the Homeostasis model assessment of Insulin Resistance (HOMA-IR) was calculated.

Results

Plasma glucose levels, plasma insulin levels, and HOMA-IR were 102.2 ± 8.1 mg/dL, 4.1 ± 1.9 μU/mL, and 1.0 ± 0.5, respectively. Whole-brain voxelwise analysis showed a negative correlation of ¹⁸F-FDG uptake with plasma glucose levels in the precuneus and lateral parietotemporal regions (cluster-corrected p < 0.05), and no correlation with plasma insulin levels or HOMA-IR. In the significant cluster, ¹⁸F-FDG uptake decreased by approximately 4–5% when plasma glucose levels increased by 20 mg/dL. In the precuneus region, volume-of-interest analysis confirmed a negative correlation of ¹⁸F-FDG uptake with plasma glucose levels (r = -0.376, p = 0.002), and no correlation with plasma insulin levels (r = 0.156, p = 0.12) or HOMA-IR (r = 0.096, p = 0.24).

Conclusion

This study suggests that, of the three parameters, plasma glucose levels have the greatest effect on the appearance of the AD-like pattern in ¹⁸F-FDG images.

Plasma Glucose Levels Affect Cerebral 18F-FDG Distribution in Cognitively Normal Subjects With Diabetes

PURPOSE

Increased plasma glucose levels can relatively reduce F-FDG uptake in Alzheimer disease (AD)-related regions and alter the cerebral distribution pattern of F-FDG, resulting in the appearance of an AD-like pattern. However, the relationship between the reversibility of the AD-like pattern and plasma glucose levels is uncertain.

METHODS

Four cognitively normal elderly subjects with diabetes underwent longitudinal F-FDG PET more than 5 times at various levels of plasma glucose. F-FDG data were proportionally scaled with a global normalization method and used in volume of interest-based and voxelwise analyses. Volumes of interest were placed on representative AD-related regions: precuneus/posterior cingulate (PP), lateral parietal cortex, and frontal cortex.

RESULTS

Volume of interest-based analyses showed negative correlations of plasma glucose levels with F-FDG uptake in the PP (r = -0.79, P < 0.001), lateral parietal cortex (r = -0.62, P = 0.002), and frontal cortex (r = -0.73, P < 0.001), controlling for the effects of interindividual differences and age. Voxelwise analyses also showed negative correlations between the 2 factors in the PP and medial frontal areas (P < 0.05, familywise error rate corrected).

CONCLUSIONS

This study indicates that the distribution pattern of F-FDG changes depending on plasma glucose levels in an individual and that the AD-like pattern can appear or disappear with increasing or decreasing plasma glucose levels, respectively.

Reduced uptake of 18F-FDG and 15O-H2O in Alzheimer's disease-related regions after glucose loading

Increased plasma glucose levels are known to reduce fluorine-18-labeled fluorodeoxyglucose ((18)F-FDG) uptake in Alzheimer's disease (AD)-related regions, resulting in the appearance of an AD-like pattern. However, the relationships of its appearance with cerebral blood flow and insulin levels are uncertain. We performed (18)F-FDG and oxygen-15-labeled water ((15)O-H2O) positron emission tomography in the fasting and glucose-loading conditions on nine young healthy volunteers with no cognitive impairments. Measurement of plasma glucose and insulin levels confirmed that all subjects were free of insulin resistance, and that glucose loading significantly increased plasma glucose and insulin levels. Fluorine-18-labeled fluorodeoxyglucose and (15)O-H2O images were compared between the two conditions, focusing on AD-related regions: precuneus/posterior cingulate (PP), lateral parietal cortex (LPC), and frontal cortex (FC). Volume-of-interest analyses showed significantly lower uptake of both (18)F-FDG and (15)O-H2O in PP, LPC, and FC after glucose loading (P<0.05). Whole-brain voxel-wise analyses also revealed the PP, LPC, and FC areas where uptake of both (18)F-FDG and (15)O-H2O decreased (P<0.05, familywise error rate-corrected). We concluded that increased plasma glucose and insulin levels can cause the appearance of the AD-like pattern in both (18)F-FDG and (15)O-H2O images, and this phenomenon can occur even in subjects without insulin resistance.

Relationship between Alzheimer disease-like pattern of 18F-FDG and fasting plasma glucose levels in cognitively normal volunteers

Increased plasma glucose (PG) levels can alter the cerebral distribution pattern of (18)F-FDG uptake and reduce (18)F-FDG uptake, especially in the precuneus. The (18)F-FDG distribution pattern in cognitively normal subjects is described as an Alzheimer disease (AD)-like pattern. The aim of this study was to determine the fasting PG levels that can reduce (18)F-FDG uptake in the precuneus.

METHODS

Fifty-one cognitively normal volunteers (mean age ± SD, 69.7 ± 5.9 y) underwent (18)F-FDG PET scanning and were divided into 2 groups according to the level of fasting PG at the time of PET scanning: control (n = 31, 80 mg/dL ≤ fasting PG < 100 mg/dL) and impaired fasting glucose (IFG) (n = 20, 100 mg/dL ≤ fasting PG < 110 mg/dL). (18)F-FDG uptake was compared between the 2 groups using voxelwise analyses with a global normalization method and volume-of-interest (VOI)-based analyses. VOIs were placed on the precuneus, posterior cingulate, and visual cortex, and the ratio of the uptake value on the precuneus VOI to that on the visual cortex VOI (PreCne/VC ratios) and to that on the posterior cingulate VOI (PreCne/PostCin ratios) was calculated.

RESULTS

Whole-brain voxelwise analyses showed that (18)F-FDG uptake in the precuneus was significantly lower in the IFG group (P < 0.05, familywise error rate-corrected) than in the control group. VOI analyses showed significantly lower PreCne/VC ratios (P = 0.002) and PreCne/PostCin ratios (P = 0.004) in the IFG group than in the control group.

CONCLUSION

The present study confirmed that increased fasting PG levels decrease (18)F-FDG uptake, especially in the precuneus, as in the AD-like pattern. Furthermore, the study provided initial evidence that the AD-like pattern can appear even in an individual with a mildly higher level of fasting PG (100-110 mg/dL).

Glucose transport to the brain: a systems model

Glucose transport to the brain involves sophisticated interactions of solutes, transporters, enzymes, and cell signaling processes, within an intricate spatial architecture. The dynamics of the transport are influenced by the adaptive nature of the blood-brain barrier (BBB), the semi-impermeable membranes of brain capillaries. As both the gate and the gatekeeper between blood-borne nutrients and brain tissue, the BBB helps govern brain homeostasis. Glucose in the blood must cross the BBB's luminal and abluminal membranes to reach neural tissue. A robust representation of the glucose transport mechanism can highlight a target for brain therapeutic intervention, help characterize mechanisms behind several disease phenotypes, or suggest a new delivery route for drugs. The challenge for researchers is understanding the relationships between influential physiological variables in vivo, and using that knowledge to predict how alterations or interventions affect glucose transport. This paper reviews factors influencing glucose transport and approaches to representing blood-to-brain glucose transport including in vitro, in vivo, and kinetic models. Applications for different models are highlighted, while their limitations in answering arising questions about the human in vivo BBB lead to a discussion of an alternate approach. A developing complex systems simulation is introduced, initiating a single platform to represent the dynamics of glucose transport across the adapting human blood-brain barrier.