Clinical significance of visually equivocal amyloid PET findings from the Alzheimer's Disease Neuroimaging Initiative cohort

Improving diagnostic precision in amyloid brain PET imaging through data-driven motion correction

BACKGROUND

Head motion during brain positron emission tomography (PET)/computed tomography (CT) imaging degrades image quality, resulting in reduced reading accuracy. We evaluated the performance of a head motion correction algorithm using 18F-flutemetamol (FMM) brain PET/CT images.

METHODS

FMM brain PET/CT images were retrospectively included, and PET images were reconstructed using a motion correction algorithm: (1) motion estimation through 3D time-domain signal analysis, signal smoothing, and calculation of motion-free intervals using a Merging Adjacent Clustering method; (2) estimation of 3D motion transformations using the Summing Tree Structural algorithm; and (3) calculation of the final motion-corrected images using the 3D motion transformations during the iterative reconstruction process. All conventional and motion-corrected PET images were visually reviewed by two readers. Image quality was evaluated using a 3-point scale, and the presence of amyloid deposition was interpreted as negative, positive, or equivocal. For quantitative analysis, we calculated the uptake ratio (UR) of 5 specific brain regions, with the cerebellar cortex as a reference region. The results of the conventional and motion-corrected PET images were statistically compared.

RESULTS

In total, 108 sets of FMM brain PET images from 108 patients (34 men and 74 women; median age, 78 years) were included. After motion correction, image quality significantly improved (p < 0.001), and there were no images of poor quality. In the visual analysis of amyloid deposition, higher interobserver agreements were observed in motion-corrected PET images for all specific regions. In the quantitative analysis, the UR difference between the conventional and motion-corrected PET images was significantly higher in the group with head motion than in the group without head motion (p = 0.016).

CONCLUSIONS

The motion correction algorithm provided better image quality and higher interobserver agreement. Therefore, we suggest that this algorithm be adopted as a routine post-processing protocol in amyloid brain PET/CT imaging and applied to brain PET scans with other radiotracers.

Longitudinal change in ATN biomarkers in cognitively normal individuals

BACKGROUND

Biomarkers for amyloid, tau, and neurodegeneration (ATN) have predictive value for clinical progression, but it is not clear how individuals move through these stages. We examined changes in ATN profiles over time, and investigated determinants of change in A status, in a sample of cognitively normal individuals presenting with subjective cognitive decline (SCD).

METHODS

We included 92 individuals with SCD from the SCIENCe project with [¹⁸F]florbetapir PET (A) available at two time points (65 ± 8y, 42% female, MMSE 29 ± 1, follow-up 2.5 ± 0.7y). We additionally used [¹⁸F]flortaucipir PET for T and medial temporal atrophy score on MRI for N. Thirty-nine individuals had complete biomarker data at baseline and follow-up, enabling the construction of ATN profiles at two time points. All underwent extensive neuropsychological assessments (follow-up time 4.9 ± 2.8y, median number of visits n = 4). We investigated changes in biomarker status and ATN profiles over time. We assessed which factors predisposed for a change from A- to A+ using logistic regression. We additionally used linear mixed models to assess change from A- to A+, compared to the group that remained A- at follow-up, as predictor for cognitive decline.

RESULTS

At baseline, 62% had normal AD biomarkers (A-T-N- n = 24), 5% had non-AD pathologic change (A-T-N+ n = 2,) and 33% fell within the Alzheimer's continuum (A+T-N- n = 9, A+T+N- n = 3, A+T+N+ n = 1). Seventeen subjects (44%) changed to another ATN profile over time. Only 6/17 followed the Alzheimer's disease sequence of A → T → N, while 11/17 followed a different order (e.g., reverted back to negative biomarker status). APOE ε4 carriership inferred an increased risk of changing from A- to A+ (OR 5.2 (95% CI 1.2-22.8)). Individuals who changed from A- to A+, showed subtly steeper decline on Stroop I (β - 0.03 (SE 0.01)) and Stroop III (- 0.03 (0.01)), compared to individuals who remained A-.

CONCLUSION

We observed considerable variability in the order of ATN biomarkers becoming abnormal. Individuals who became A+ at follow-up showed subtle decline on tests for attention and executive functioning, confirming clinical relevance of amyloid positivity.

A 4-Year Follow-Up of Subjects with Visually Equivocal Amyloid Positron Emission Tomography Findings from the Alzheimer's Disease Neuroimaging Initiative Cohort

Background

To date, the clinical significance of visually equivocal amyloid positron emission tomography (PET) has not been well established.

Objective

We studied the clinical significance of equivocal amyloid PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Methods

Subjects with F-18 florbetapir PET scans at baseline who were followed up for 4 years were selected. Clinical characteristics, imaging biomarkers, cognitive function, and rate of conversion to AD were compared in subjects with visually equivocal findings.

Results

Of 249 subjects who completed the follow-up, 153 (61.4%), 20 (8.0%), and 129 (30.5%) were F-18 florbetapir-negative, -equivocal, and -positive, respectively. The mean standardized uptake value ratios (SUVR) of F-18 florbetapir PET were 0.75 ± 0.04, 0.85 ± 0.10, and 1.00 ± 0.09 for each group (p <0.001 between groups), and 15.0%, 70.0%, and 98.7% of patients were quantitatively above the positive threshold. The change in the SUVR of F-18 florbetapir PET was higher in the equivocal (6.09 ± 3.61%, p <0.001) and positive (3.13 ± 4.38%, p <0.001) groups than the negative group (0.88 ± 4.28%). Among the subjects with normal or subjective memory impairment and mild cognitive impairment, 5.3% with negative amyloid PET and 37.5% with positive amyloid PET converted to AD over the 4-year period. None of the equivocal amyloid PET subjects converted to AD during this period.

Conclusion

Approximately 8% of subjects from the ADNI cohort showed visually equivocal amyloid PET scans with intermediate load and rapid accumulation of amyloid, but did not convert to AD during the 4-year follow-up.

Restoration of amyloid PET images obtained with short-time data using a generative adversarial networks framework

Our purpose in this study is to evaluate the clinical feasibility of deep-learning techniques for F-18 florbetaben (FBB) positron emission tomography (PET) image reconstruction using data acquired in a short time. We reconstructed raw FBB PET data of 294 patients acquired for 20 and 2 min into standard-time scanning PET (PET_20m) and short-time scanning PET (PET_2m) images. We generated a standard-time scanning PET-like image (sPET_20m) from a PET_2m image using a deep-learning network. We did qualitative and quantitative analyses to assess whether the sPET_20m images were available for clinical applications. In our internal validation, sPET_20m images showed substantial improvement on all quality metrics compared with the PET_2m images. There was a small mean difference between the standardized uptake value ratios of sPET_20m and PET_20m images. A Turing test showed that the physician could not distinguish well between generated PET images and real PET images. Three nuclear medicine physicians could interpret the generated PET image and showed high accuracy and agreement. We obtained similar quantitative results by means of temporal and external validations. We can generate interpretable PET images from low-quality PET images because of the short scanning time using deep-learning techniques. Although more clinical validation is needed, we confirmed the possibility that short-scanning protocols with a deep-learning technique can be used for clinical applications.

Prognostic value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography in newly diagnosed multiple myeloma: a systematic review and meta-analysis

OBJECTIVES

We performed a systematic review and meta-analysis on the prognostic values of ¹⁸F-FDG PET/CT in patients with newly diagnosed multiple myeloma (MM).

METHODS

PubMed and Embase were searched until July 10, 2019, for studies that reported the prognostic significance of ¹⁸F-FDG PET in patients with newly diagnosed MM, with overall (OS) and progression-free survival (PFS) included as outcomes. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were meta-analytically pooled using a random-effects model.

RESULTS

Fifteen studies (1670 patients) were included for qualitative synthesis. Among multiple PET parameters, the presence of extramedullary disease (EMD), more than three focal lesions (FLs), and high FDG uptake were widely evaluated and significantly associated with shorter OS and PFS in most of the included studies. Among 11 studies included in quantitative synthesis, the overall HRs of EMD, more than three FLs, and high FDG uptake on PFS were 2.12 (95% CI, 1.52-2.96), 2.38 (95% CI, 1.84-3.07), and 2.02 (95% CI, 1.51-2.68), respectively. The pooled HRs of those three parameters on OS were 2.37 (95% CI, 1.77-3.16), 3.29 (95% CI, 2.38-4.56), and 2.28 (95% CI, 1.67-3.13). No statistical differences were found across parameters for either PFS (p = 0.6822) or OS (p = 0.2147).

CONCLUSIONS

Pretreatment ¹⁸F-FDG PET/CT is a significant predictor for disease progression and survival in patients with MM. It may be a useful prognostic biomarker capable of accurate risk stratification and application in clinical decision-making for newly diagnosed MM.

KEY POINTS

• There remain unmet clinical needs for reliable prognostic biomarkers in patients with newly diagnosed multiple myeloma. • This meta-analysis shows that the presence of extramedullary disease, more than three focal lesions, and high FDG uptake from baseline ¹⁸F-FDG PET are significant prognostic factors. • These imaging biomarkers might help the accurate stratification of patient prognosis which is required for choosing an appropriate therapeutic strategy in clinical practice.

Which MCI Patients Should be Included in Prodromal Alzheimer Disease Clinical Trials?

BACKGROUND

Prodromal Alzheimer disease (AD) clinical trials enroll patients with mild cognitive impairment (MCI) meeting biomarker criteria, but specific enrollment criteria vary among trials.

METHODS

We used data from AD Neuroimaging Initiative (ADNI) MCI participants to assess AD biomarker eligibility, variation in trial outcome measures, and statistical power.

RESULTS

Most (65%) participants meet eligibility criteria based on low cerebrospinal fluid amyloid beta (Aβ). Relative to trials enrolling exclusively based on low cerebrospinal fluid Aβ, trials including participants with a high ratio of phosphorylated tau to Aβ would include an additional 15% of participants. Fewer (34% to 62%) participants met criteria for Aβ and tau. Differences in clinical and demographic characteristics of modeled trial samples were minimal. Those with low Aβ and high tau showed the greatest change over time on outcome measures.

CONCLUSIONS

Eligibility rates for prodromal trials vary depending on the specific biomarker criteria, though differences in demographics and the variation associated with outcome measures are minimal. Broadening inclusion criteria beyond amyloid alone may facilitate recruitment but include patients showing slower progression over time. Biomarker criteria selection should be informed by the goal of enrolling individuals most likely to utilize and benefit from the intervention under investigation in a particular setting.