Software development for quantitative analysis of brain amyloid PET

Differential centiloid scale normalization techniques: comparison between hybrid PET/MRI and independently acquired MRI

OBJECTIVE

Centiloid (CL) scales play an important role in semiquantitative analyses of amyloid-β (Aβ) PET. CLs are derived from the standardized uptake value ratio (SUVR), which needs Aβ positron emission tomography (PET) normalization processing. There are two methods to collect the T1-weighted imaging (T1WI) for normalization: (i) anatomical standardization using simultaneously acquired T1WI (PET/MRI), usually adapted to PET images from PET/MRI scanners, and (ii) T1WI from a separate examination (PET + MRI), usually adapted to PET images from PET/CT scanners. This study aimed to elucidate the correlations and differences in CLs between when using the above two T1WI collection methods.

METHODS

Among patients who underwent Aβ PET/MRI (using 11C-Pittuberg compound B (11C-PiB) or 18F-flutemetamol (18F-FMM)) at our institution from 2015 to 2023, we selected 49 patients who also underwent other additional MRI examinations, including T1WI for anatomic standardization within 3 years. Thirty-one of them underwent 11C-PiB PET/MRI, and 18 participants underwent 18F-FMM PET/MRI. Twenty-five of them, additional MRI acquisition parameters were identical to simultaneous MRI during PET, and 24 participants were different. After normalization using PET/MRI or PET + MRI method each, SUVR was measured using the Global Alzheimer's Association Initiative Network cerebral cortical and striatum Volume of Interest templates (VOI) and whole cerebellum VOI. Subsequently, CLs were calculated using the previously established equations for each Aβ PET tracer.

RESULTS

Between PET/MRI and PET + MRI methods, CLs correlated linearly in 11C-PiB PET (y = 1.00x - 0.11, R2 = 0.999), 18F-FMM PET (y = 0.97x - 0.12, 0.997), identical additional MRI acquisition (y = 1.00x + 0.33, 0.999), different acquisition (y = 0.98x - 0.43, 0.997), and entire study group (y = 1.00x - 0.24, 0.999). Wilcoxon signed-rank test revealed no significant differences: 11C-PiB (p = 0.49), 18F-FMM (0.08), and whole PET (0.46). However, significant differences were identified in identical acquisition (p = 0.04) and different acquisition (p = 0.02). Bland-Altman analysis documented only a small bias between PET/MRI and PET + MRI in 11C-PiB PET, 18F-FMM PET, identical additional MRI acquisition, different acquisition, and whole PET (- 0.05, 0.67, - 0.30, 0.78, and 0.21, respectively).

CONCLUSIONS

Anatomical standardizations using PET/MRI and using PET + MRI can lead to almost equivalent CL. The CL values obtained using PET/MRI or PET + MRI normalization methods are consistent and comparable in clinical studies.

Enhancing Cerebral Amyloid Angiopathy-Related Inflammation Diagnosis With PET Using Pittsburgh Compound B

ABSTRACT

Cerebral amyloid angiopathy-related inflammation is a rare encephalopathy characterized by inflammation against amyloid protein accumulated in cerebral small vessels. A 50-year-old man was presented with a subacute consciousness disorder. Brain MRI revealed high intensity lesions in the white matter of the right parietal and occipital lobes on fluid-attenuated inversion recovery sequences and cerebral microbleeds in the right parietal and occipital lobes on T2*-weighted images. Pittsburgh compound B-PET demonstrated accumulation in the right temporoparietal lobe, confirming a potential diagnosis of probable cerebral amyloid angiopathy-related inflammation without brain biopsy. Steroid pulse therapy was initiated, with good results.

Comparison of consistency in centiloid scale among different analytical methods in amyloid PET: the CapAIBL, VIZCalc, and Amyquant methods

OBJECTIVE

The Centiloid (CL) scale is a standardized measure for quantifying amyloid deposition in amyloid positron emission tomography (PET) imaging. We aimed to assess the agreement among 3 CL calculation methods: CapAIBL, VIZCalc, and Amyquant.

METHODS

This study included 192 participants (mean age: 71.5 years, range: 50-87 years), comprising 55 with Alzheimer's disease, 65 with mild cognitive impairment, 13 with non-Alzheimer's dementia, and 59 cognitively normal participants. All the participants were assessed using the three CL calculation methods. Spearman's rank correlation, linear regression, Friedman tests, Wilcoxon signed-rank tests, and Bland-Altman analysis were employed to assess data correlations, linear associations, method differences, and systematic bias, respectively.

RESULTS

Strong correlations (rho = 0.99, p < .001) were observed among the CL values calculated using the three methods. Scatter plots and regression lines visually confirmed these strong correlations and met the validation criteria. Despite the robust correlations, a significant difference in CL value between CapAIBL and Amyquant was observed (36.1 ± 39.7 vs. 34.9 ± 39.4; p < .001). In contrast, no significant differences were found between CapAIBL and VIZCalc or between VIZCalc and Amyquant. The Bland-Altman analysis showed no observable systematic bias between the methods.

CONCLUSIONS

The study demonstrated strong agreement among the three methods for calculating CL values. Despite minor variations in the absolute values of the Centiloid scores obtained using these methods, the overall agreement suggests that they are interchangeable.

PET/MRI multimodality imaging to evaluate changes in glymphatic system function and biomarkers of Alzheimer's disease

The glymphatic system is considered to play a pivotal role in the clearance of disease-causing proteins in neurodegenerative diseases. This study employed MR diffusion tensor imaging (DTI) to evaluate glymphatic system function and its correlation with brain amyloid accumulation levels measured using [11C]Pittsburgh compound-B (PiB) PET/MRI. Fifty-six patients with mild cognitive impairment and early Alzheimer's disease (AD: 70 ± 11 y) underwent [11C]PiB PET/MRI to assess amyloid deposition and were compared with 27 age-matched cognitively normal volunteers (CN: 69 ± 10y). All participants were evaluated for cognitive function using the Mini Mental State Examination (MMSE) before [11C]PiB PET/MRI. DTI images were acquired during the PET/MRI scan with several other MR sequences. The DTI analysis along the perivascular space index (DTI-ALPS index) was calculated to estimate the functional activity of the glymphatic system. Centiloid scale was applied to quantify amyloid deposition levels from [11C]PiB PET images. All patients in the AD group showed positive [11C]PiB accumulation, whereas all CN participants were negative. ALPS-index for all subjects linearly correlated with PiB centiloid, MMSE scores, and hippocampal volume. The correlation between the ALPS-index and PiB accumulation was more pronounced than with any other biomarkers. These findings suggest that glymphatic system dysfunction is a significant factor in the early stages of Alzheimer's disease.

Deep Learning-Driven Estimation of Centiloid Scales from Amyloid PET Images with 11C-PiB and 18F-Labeled Tracers in Alzheimer's Disease

BACKGROUND

Standard methods for deriving Centiloid scales from amyloid PET images are time-consuming and require considerable expert knowledge. We aimed to develop a deep learning method of automating Centiloid scale calculations from amyloid PET images with 11C-Pittsburgh Compound-B (PiB) tracer and assess its applicability to 18F-labeled tracers without retraining.

METHODS

We trained models on 231 11C-PiB amyloid PET images using a 50-layer 3D ResNet architecture. The models predicted the Centiloid scale, and accuracy was assessed using mean absolute error (MAE), linear regression analysis, and Bland-Altman plots.

RESULTS

The MAEs for Alzheimer's disease (AD) and young controls (YC) were 8.54 and 2.61, respectively, using 11C-PiB, and 8.66 and 3.56, respectively, using 18F-NAV4694. The MAEs for AD and YC were higher with 18F-florbetaben (39.8 and 7.13, respectively) and 18F-florbetapir (40.5 and 12.4, respectively), and the error rate was moderate for 18F-flutemetamol (21.3 and 4.03, respectively). Linear regression yielded a slope of 1.00, intercept of 1.26, and R2 of 0.956, with a mean bias of -1.31 in the Centiloid scale prediction.

CONCLUSIONS

We propose a deep learning means of directly predicting the Centiloid scale from amyloid PET images in a native space. Transferring the model trained on 11C-PiB directly to 18F-NAV4694 without retraining was feasible.

Performance of plasma Aβ42/40, measured using a fully automated immunoassay, across a broad patient population in identifying amyloid status

BACKGROUND

Plasma biomarkers have emerged as promising screening tools for Alzheimer's disease (AD) because of their potential to detect amyloid β (Aβ) accumulation in the brain. One such candidate is the plasma Aβ42/40 ratio (Aβ42/40). Unlike previous research that used traditional immunoassay, recent studies that measured plasma Aβ42/40 using fully automated platforms reported promising results. However, its utility should be confirmed using a broader patient population, focusing on the potential for early detection.

METHODS

We recruited 174 participants, including healthy controls (HC) and patients with clinical diagnoses of AD, frontotemporal lobar degeneration, dementia with Lewy bodies/Parkinson's disease, mild cognitive impairment (MCI), and others, from a university memory clinic. We examined the performance of plasma Aβ42/40, measured using the fully automated high-sensitivity chemiluminescence enzyme (HISCL) immunoassay, in detecting amyloid-positron emission tomography (PET)-derived Aβ pathology. We also compared its performance with that of Simoa-based plasma phosphorylated tau at residue 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL).

RESULTS

Using the best cut-off derived from the Youden Index, plasma Aβ42/40 yielded an area under the receiver operating characteristic curve (AUC) of 0.949 in distinguishing visually assessed 18F-Florbetaben amyloid PET positivity. The plasma Aβ42/40 had a significantly superior AUC than p-tau181, GFAP, and NfL in the 167 participants with measurements for all four biomarkers. Next, we analyzed 99 participants, including only the HC and those with MCI, and discovered that plasma Aβ42/40 outperformed the other plasma biomarkers, suggesting its ability to detect early amyloid accumulation. Using the Centiloid scale (CL), Spearman's rank correlation coefficient between plasma Aβ42/40 and CL was -0.767. Among the 15 participants falling within the CL values indicative of potential future amyloid accumulation (CL between 13.5 and 35.7), plasma Aβ42/40 categorized 61.5% (8/13) as Aβ-positive, whereas visual assessment of amyloid PET identified 20% (3/15) as positive.

CONCLUSION

Plasma Aβ42/40 measured using the fully automated HISCL platform showed excellent performance in identifying Aβ accumulation in the brain in a well-characterized cohort. This equipment may be useful for screening amyloid pathology because it has the potential to detect early amyloid pathology and is readily applied in clinical settings.

Relationship between the tau protein and choroid plexus volume in Alzheimer's disease

Tau protein accumulation in the brain is thought to be one of the causes of Alzheimer's disease (AD). Recent studies found that the choroid plexus (CP) has a role in β-amyloid and tau protein clearance in the brain. We evaluated the relationships between CP volume and the ß-amyloid and tau protein depositions. Participants were 20 patients with AD and 35 healthy subjects who underwent MRI and PET scanning using the ß-amyloid tracer 11C-PiB and the tau/inflammatory tracer 18F-THK5351. We computed the volume of the CP and estimated the relationships between the CP volume and ß-amyloid and tau protein/inflammatory deposition by Spearman's correlation test. The CP volume was significantly positively correlated with both the standardized uptake value ratio (SUVR) of 11C-PiB and the SUVR of 18F-THK5351 in all participants. The CP volume was also significantly positively correlated with the SUVR of 18F-THK5351in patients with AD. Our data suggested that the volume of the CP was a good biomarker for the evaluation of tau deposition and neuroinflammation.

Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease

INTRODUCTION

Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET).

METHODS

Seventy-one participants underwent multi-shell diffusion MRI, ¹⁸F-THK5351 PET, ¹¹C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores.

RESULTS

In AD-S group, there was a significant positive correlation between FW and ¹⁸F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between ¹⁸F-THK5351 and cognitive function in the same regions.

DISCUSSION

FW imaging could be a biomarker for tau in AD alongside clinical correlations.

Clinical impact of amyloid PET using 18F-florbetapir in patients with cognitive impairment and suspected Alzheimer's disease: a multicenter study

OBJECTIVE

Amyloid positron emission tomography (PET) can reliably detect senile plaques and fluorinated ligands are approved for clinical use. However, the clinical impact of amyloid PET imaging is still under investigation. The aim of this study was to evaluate the diagnostic impact and clinical utility in patient management of amyloid PET using ¹⁸F-florbetapir in patients with cognitive impairment and suspected Alzheimer's disease (AD). We also aimed to determine the cutoffs for amyloid positivity for quantitative measures by investigating the agreement between quantitative and visual assessments.

METHODS

Ninety-nine patients suspected of having AD underwent ¹⁸F-florbetapir PET at five institutions. Site-specialized physicians provided a diagnosis of AD or non-AD with a percentage estimate of their confidence and their plan for patient management in terms of medication, prescription dosage, additional diagnostic tests, and care planning both before and after receiving the amyloid imaging results. A PET image for each patient was visually assessed and dichotomously rated as either amyloid-positive or amyloid-negative by four board-certified nuclear medicine physicians. The PET images were also quantitatively analyzed using the standardized uptake value ratio (SUVR) and Centiloid (CL) scale.

RESULTS

Visual interpretation obtained 48 positive and 51 negative PET scans. The amyloid PET results changed the AD and non-AD diagnosis in 39 of 99 patients (39.3%). The change rates of 26 of the 54 patients (48.1%) with a pre-scan AD diagnosis were significantly higher than those of 13 of the 45 patients with a pre-scan non-AD diagnosis (χ² = 5.334, p = 0.0209). Amyloid PET results also resulted in at least one change to the patient management plan in 42 patients (42%), mainly medication (20 patients, 20%) and care planning (25 patients, 25%). Receiver-operating characteristic analysis determined the best agreement of the quantitative assessments and visual interpretation of PET scans to have an area under the curve of 0.993 at an SUVR of 1.19 and CL of 25.9.

CONCLUSION

Amyloid PET using ¹⁸F-florbetapir PET had a substantial clinical impact on AD and non-AD diagnosis and on patient management by enhancing diagnostic confidence. In addition, the quantitative measures may improve the visual interpretation of amyloid positivity.

Relationships Between the Deposition of Amyloid-β and Tau Protein and Glymphatic System Activity in Alzheimer’s Disease: Diffusion Tensor Image Study

Background: Amyloid-β (Aβ) and tau protein accumulation in the brain is thought to be one of the causes of Alzheimer’s disease (AD). Recent study found that the glymphatic system was waste drainage system in the brain and promoting the elimination of Aβ and tau protein. Objective: Objective: We evaluated the relationships between the glymphatic system activity and Aβ and tau protein deposition. Methods: Subjects were 21 patients with AD and 36 healthy subjects who underwent diffusion tensor imaging (DTI) scan and the positron emission tomography using with the Aβ tracer: 11C-PiB and the tau/inflammatory tracer: 18F-THK5351. We computed diffusion tensor image analysis along the perivascular space (DTI-ALPS) index as the proxy of glymphatic system activity and estimated the relationships between the DTI-ALPS index and Aβ and tau protein/inflammatory deposition. Results: We found significant negative correlations between DTI-ALPS index and the standard uptake value ratio (SUVR) of 11C-PiB in the bilateral temporal and left parietal cortices and left posterior cingulate gyrus in all subjects. Further, we detected significant negative correlations between DTI-ALPS index and the SUVR of 18F-THK5351 in the bilateral temporal cortices and right parietal cortex in all participants, too. Conclusion: Our data suggested that DTI-ALPS index was a good biomarker for the evaluation of Aβ and tau deposition and neuroinflammation, and this marker might be effective to estimate the glymphatic system activity.