Regional gray matter-dedicated SUVR with 3D-MRI detects positive amyloid deposits in equivocal amyloid PET images

Evaluation of amyloid PET positivity using machine learning on 18F-FDG PET images

BACKGROUND

Since the approval of disease-modifying drugs for Alzheimer's disease, the demand for amyloid positron emission tomography (PET) scans, which are crucial for determining treatment eligibility, is expected to increase significantly. We thus investigated the ability of an algorithm to predict amyloid accumulation from 18F-fluorodeoxyglucose (FDG)-PET images for use in amyloid PET screening.

METHODS

We analyzed the images of 194 subjects with cognitive disorders who had undergone brain FDG-PET, amyloid PET using Pittsburgh compound-B (11C-PiB), and MRI scans at Kindai University Hospital between 2011 and 2018. Among them, 108 subjects showed positive amyloid accumulation; the other 86 did not. For the 108 positive cases, the input values were the region of interest-based calculated from the automatic anatomical labeling template, which divides the brain into 120 regions, and applied to the anatomically standardized FDG-PET images of each subject. We then used a support vector machine (SVM) machine learning algorithm and conducted a tenfold cross-validation to assess the algorithm's accuracy for predicting amyloid accumulation from FDG-PET images.

RESULTS

We observed 81.5% accuracy, 78.5% sensitivity, 84.6% specificity, and an area under the curve (AUC) of 0.846 during training. The validation results for the trained model revealed 85.9% accuracy, 88.4% sensitivity, 81.0% specificity, and an AUC of 0.918.

CONCLUSION

These results indicate that the performance of our algorithm to predict amyloid accumulation from 18FDG-PET images is adequate for use in amyloid PET scan screenings.

Expression of regional brain amyloid-β deposition with [18F]Flutemetamol in Centiloid scale -a multi-site study

PURPOSE

The Centiloid project helps calibrate the quantitative amyloid-β (Aβ) load into a unified Centiloid (CL) scale that allows data comparison across multi-site. How the smaller regional amyloid converted into CL has not been attempted. We first aimed to express regional Aβ deposition in CL using [18F]Flutemetamol and evaluate regional Aβ deposition in CL with that in standardized uptake value ratio (SUVr). Second, we aimed to determine the presence or absence of focal Aβ deposition by measuring regional CL in equivocal cases showing negative global CL.

METHODS

Following the Centiloid project pipeline, Level-1 replication, Level-2 calibration, and quality control were completed to generate corresponding Centiloid conversion equations to convert SUVr into Centiloid at regional levels. In equivocal cases, the regional CL was compared with visual inspection to evaluate regional Aβ positivity.

RESULTS

14 out of 16 regional conversions from [18F]Flutemetamol SUVr to Centiloid successfully passed the quality control, showing good reliability and relative variance, especially precuneus/posterior cingulate and prefrontal regions with good stability for Centiloid scaling. The absence of focal Aβ deposition could be detected by measuring regional CL, showing a high agreement rate with visual inspection. The regional Aβ positivity in the bilateral anterior cingulate cortex was most prevalent in equivocal cases.

CONCLUSION

The expression of regional brain Aβ deposition in CL with [18F]Flutemetamol has been attempted in this study. Equivocal cases had focal Aβ deposition that can be detected by measuring regional CL.

Semiquantitative Approach to Amyloid Positron Emission Tomography Interpretation in Clinical Practice

Objective  Amyloid positron emission tomography (PET) plays a vital role in the in vivo detection of β-amyloid accumulation in Alzheimer's disease. Increasingly, trainees and infrequent readers are relying on semiquantitative analyses to support clinical diagnostic efforts. Our objective was to determine if the visual assessment of amyloid PET may be facilitated by relying on semiquantitative analysis. Methods  We conducted a retrospective review of [ ¹⁸ F]-florbetaben PET/computed tomographies (CTs) from 2016 to 2018. Visual interpretation to determine Aβ+ status was conducted by two readers blinded to each other's interpretation. Scans were then post-processed utilizing the MIMneuro software, which generated regional-based semiquantitative Z-scores indicating cortical Aβ-burden. Results  Of 167 [ ¹⁸ F]-florbetaben PET/CTs, 92/167 (reader-1) and 101/167 (reader-2) were positive for amyloid deposition (agreement = 92.2%, κ = 0.84). Additional nine scans were identified as possible Aβ-positive based solely on semiquantitative analyses. Largest semiquantitative differences were identified in the left frontal lobe (Z = 7.74 in Aβ + ; 0.50 in Aβ - ). All unilateral regions showed large statistically significant differences in Aβ-burden ( P ≤ 2.08E-28). Semiquantitative scores were highly sensitive to Aβ+ status and accurate in their ability to identify amyloid positivity, defined as a positive scan by both readers (AUC ≥ 0.90 [0.79-1.00]). Spread analyses suggested that amyloid deposition was most severe in the left posterior cingulate gyrus. The largest differences between Aβ +/Aβ- were in the left frontal lobe. Analyses using region-specific cutoffs indicated that the presence of amyloid in the temporal and anterior cingulate cortex, while exhibiting relatively low Z-scores, was most common. Conclusion  Visual assessment and semiquantitative analysis provide highly congruent results, thereby enhancing reader confidence and improving scan interpretation. This is particularly relevant, given recent advances in amyloid-targeting disease-modifying therapeutics.

High-Resolution Silicon Photomultiplier Time-of-Flight Dedicated Head PET System for Clinical Brain Studies

We acquired brain ¹⁸F-FDG and ¹⁸F-flutemetamol PET images using a time-of-flight system dedicated to the head (dhPET) and a conventional whole-body PET/CT (wbPET) system and evaluated the clinical superiority of dhPET over wbPET. Methods: There were 18 subjects for the ¹⁸F-FDG PET study and 17 subjects for the ¹⁸F-flutemetamol PET study. ¹⁸F-FDG PET images were first obtained using wbPET, followed by dhPET. ¹⁸F-flutemetamol PET images were first obtained using wbPET, followed by dhPET. Images acquired using dhPET and wbPET were compared by visual inspection, voxelwise analysis, and SUV ratio (SUVR). Results: All ¹⁸F-FDG and ¹⁸F-flutemetamol images acquired using dhPET were judged as visually better than those acquired using wbPET. The voxelwise analysis demonstrated that accumulations in the cerebellum, in the lateral occipital cortices, and around the central sulcus area in dhPET ¹⁸F-FDG images were lower than those in wbPET ¹⁸F-FDG images, whereas accumulations around the ventricle systems were higher in dhPET ¹⁸F-FDG images than those in wbPET ¹⁸F-FDG images. Accumulations in the cerebellar dentate nucleus, in the midbrain, in the lateral occipital cortices, and around the central sulcus area in dhPET images were lower than those in wbPET images, whereas accumulations around the ventricle systems were higher in dhPET ¹⁸F-flutemetamol images than those in wbPET ¹⁸F-flutemetamol images. The mean cortical SUVRs of ¹⁸F-FDG and ¹⁸F-flutemetamol dhPET images were significantly higher than those of ¹⁸F-FDG and ¹⁸F-flutemetamol wbPET images, respectively. Conclusion: The dhPET images had better image quality by visual inspection and higher SUVRs than wbPET images. Although there were several regional accumulation differences between dhPET and wbPET images, understanding this phenomenon will enable full use of the features of this dhPET system in clinical practice.