Spatially constrained kinetic modeling with dual reference tissues improves 18F-flortaucipir PET in studies of Alzheimer disease

15 Years of Longitudinal Genetic, Clinical, Cognitive, Imaging, and Biochemical Measures in DIAN

This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimer's disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.

Exploring the nigrostriatal and digestive interplays in Parkinson's disease using dynamic total-body [11C]CFT PET/CT

PURPOSE

Dynamic total-body imaging enables new perspectives to investigate the potential relationship between the central and peripheral regions. Employing uEXPLORER dynamic [11C]CFT PET/CT imaging with voxel-wise simplified reference tissue model (SRTM) kinetic modeling and semi-quantitative measures, we explored how the correlation pattern between nigrostriatal and digestive regions differed between the healthy participants as controls (HC) and patients with Parkinson's disease (PD).

METHODS

Eleven participants (six HCs and five PDs) underwent 75-min dynamic [11C]CFT scans on a total-body PET/CT scanner (uEXPLORER, United Imaging Healthcare) were retrospectively enrolled. Time activity curves for four nigrostriatal nuclei (caudate, putamen, pallidum, and substantia nigra) and three digestive organs (pancreas, stomach, and duodenum) were obtained. Total-body parametric images of relative transporter rate constant (R1) and distribution volume ratio (DVR) were generated using the SRTM with occipital lobe as the reference tissue and a linear regression with spatial-constraint algorithm. Standardized uptake value ratio (SUVR) at early (1-3 min, SUVREP) and late (60-75 min, SUVRLP) phases were calculated as the semi-quantitative substitutes for R1 and DVR, respectively.

RESULTS

Significant differences in estimates between the HC and PD groups were identified in DVR and SUVRLP of putamen (DVR: 4.82 ± 1.58 vs. 2.58 ± 0.53; SUVRLP: 4.65 ± 1.36 vs. 2.84 ± 0.67; for HC and PD, respectively, both p < 0.05) and SUVREP of stomach (1.12 ± 0.27 vs. 2.27 ± 0.65 for HC and PD, respectively; p < 0.01). In the HC group, negative correlations were observed between stomach and substantia nigra in both the R1 and SUVREP values (r=-0.83, p < 0.05 for R1; r=-0.94, p < 0.01 for SUVREP). Positive correlations were identified between pancreas and putamen in both DVR and SUVRLP values (r = 0.94, p < 0.01 for DVR; r = 1.00, p < 0.001 for SUVRLP). By contrast, in the PD group, no correlations were found between the aforementioned target nigrostriatal and digestive areas.

CONCLUSIONS

The parametric images of R1 and DVR generated from the SRTM model, along with SUVREP and SUVRLP, were proposed to quantify dynamic total-body [11C]CFT PET/CT in HC and PD groups. The distinction in correlation patterns of nigrostriatal and digestive regions between HC and PD groups identified by R1 and DVR, or SUVRs, may provide new insights into the disease mechanism.

Automated extraction of the arterial input function from brain images for parametric PET studies

BACKGROUND

Accurate measurement of the arterial input function (AIF) is crucial for parametric PET studies, but the AIF is commonly derived from invasive arterial blood sampling. It is possible to use an image-derived input function (IDIF) obtained by imaging a large blood pool, but IDIF measurement in PET brain studies performed on standard field of view scanners is challenging due to lack of a large blood pool in the field-of-view. Here we describe a novel automated approach to estimate the AIF from brain images.

RESULTS

Total body 18F-FDG PET data from 12 subjects were split into a model adjustment group (n = 6) and a validation group (n = 6). We developed an AIF estimation framework using wavelet-based methods and unsupervised machine learning to distinguish arterial and venous activity curves, compared to the IDIF from the descending aorta. All of the automatically extracted AIFs in the validation group had similar shape to the IDIF derived from the descending aorta IDIF. The average area under the curve error and normalised root mean square error across validation data were - 1.59 ± 2.93% and 0.17 ± 0.07.

CONCLUSIONS

Our automated AIF framework accurately estimates the AIF from brain images. It reduces operator-dependence, and could facilitate the clinical adoption of parametric PET.

Kinetic analysis of cardiac dynamic 18F-Florbetapir PET in healthy volunteers and amyloidosis patients: A pilot study

Objectives

This study aimed to explore the potential of full dynamic PET kinetic analysis in assessing amyloid binding and perfusion in the cardiac region using 18F-Florbetapir PET, establishing a quantitative approach in the clinical assessment of cardiac amyloidosis disease.

Materials & methods

The distribution volume ratios (DVRs) and the relative transport rate constant (R1), were estimated by a pseudo-simplified reference tissue model (pSRTM2) and pseudo-Logan plot (pLogan plot) with kidney reference for the region of interest-based and voxel-wise-based analyses. The parametric images generated using the pSRTM2 and linear regression with spatially constrained (LRSC) algorithm were then evaluated. Semi-quantitative analyses include standardized uptake value ratios at the early phase (SUVREP, 0.5-5 min) and late phase (SUVRLP, 50-60 min) were also calculated.

Results

Ten participants [7 healthy controls (HC) and 3 cardiac amyloidosis (CA) subjects] underwent a 60-min dynamic 18F-Florbetapir PET scan. The DVRs estimated from pSRTM2 and Logan plot were significantly increased (HC vs CA; DVRpSRTM2: 0.95 ± 0.11 vs 2.77 ± 0.42, t'(2.13) = 7.39, P = 0.015; DVRLogan: 0.80 ± 0.12 vs 2.90 ± 0.55, t'(2.08) = 6.56, P = 0.020), and R1 were remarkably decreased in CA groups, as compared to HCs (HC vs CA; 1.08 ± 0.37 vs 0.56 ± 0.10, t'(7.63) = 3.38, P = 0.010). The SUVREP and SUVRLP were highly correlated to R1 (r = 0.97, P < 0.001) and DVR(r = 0.99, P < 0.001), respectively. The DVRs in the total myocardium region increased slightly as the size of FWHM increased and became stable at a Gaussian filter ≥6 mm. The secular equilibrium of SUVR was reached at around 50-min p.i. time.

Conclusion

The DVR and R1 estimated from cardiac dynamic 18F-Florbetapir PET using pSRTM with kidney pseudo-reference tissue are suggested to quantify cardiac amyloid deposition and relative perfusion, respectively, in amyloidosis patients and healthy controls. We recommend a dual-phase scan: 0.5-5 min and 50-60 min p.i. as the appropriate time window for clinically assessing cardiac amyloidosis and perfusion measurements using 18F-Florbetapir PET.

Comparison of parametric imaging and SUV imaging with [68 Ga]Ga-PSMA-11 using dynamic total-body PET/CT in prostate cancer

PURPOSE

Standardized uptake value (SUV) has been prevalently used to measure [68 Ga]Ga-PSMA-11 activity in prostate cancer, but it is susceptible to multiple factors. Parametric imaging allows for absolute quantification of tracer uptake and provides a better diagnostic accuracy that is crucial for lesion detection. However, the clinical significance of total-body parametric imaging of [68 Ga]Ga-PSMA-11 remains to be fully assessed. Therefore, the aim of our study is to delve into the diagnostic implications of total-body parametric imaging of [68 Ga]Ga-PSMA-11 PET/CT for patients with prostate cancer.

METHODS

Twenty prostate cancer patients were included and underwent a dynamic total-body [68 Ga]Ga-PSMA-11 PET/CT scan. An irreversible two-tissue compartment model (2T3k) was fitted for each tissue time-to-activity curve, and the net influx rate (Ki) was obtained. The image quality and semi-quantitative analysis of lesion-to-background ratio (LBR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between parametric images and SUV images.

RESULTS

Kinetic modeling using 2T3k demonstrated favorable model fitting in both normal organs and lesions. All of the lesions detected on SUV images (55-60 min) could be detected on Ki images. The correlation between Ki, SUVmean, and SUVmax in both normal organs and pathological lesions was found to be positive and statistically significant. Conversely, a moderate positive correlations were found between Ki and K1 (R = 0.69, P < 0.001; R = 0.61, P < 0.001) and Ki and k3 (R = 0.69, P < 0.001; R = 0.62, P < 0.001), in normal organs and pathological lesions, respectively. Visual assessment in Ki images showed less image noise and higher lesions conspicuity compared to SUV images. Ki image-derived LBR, SNR, and CBR of pathological lesions including primary tumors (PTs), lymph node metastases (LNMs) and bone metastases (BMs), exhibited remarkably higher folds (1.4-3.6 folds) compared to those derived from SUV of corresponding lesions.

CONCLUSIONS

Total-body parametric imaging of [68 Ga]Ga-PSMA-11 enhanced lesion contrast and improved lesion detectability compared to SUV images. This may potentially serve as an imaging biomarker and theranostic tool for precise diagnosis and treatment evaluation in prostate cancer patients.

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.

Motion correction and its impact on quantification in dynamic total-body 18F-fluorodeoxyglucose PET

Background

The total-body positron emission tomography (PET) scanner provides an unprecedented opportunity to scan the whole body simultaneously, thanks to its long axial field of view and ultrahigh temporal resolution. To fully utilize this potential in clinical settings, a dynamic scan would be necessary to obtain the desired kinetic information from scan data. However, in a long dynamic acquisition, patient movement can degrade image quality and quantification accuracy.

Methods

In this work, we demonstrated a motion correction framework and its importance in dynamic total-body FDG PET imaging. Dynamic FDG scans from 12 subjects acquired on a uEXPLORER PET/CT were included. In these subjects, 7 are healthy subjects and 5 are those with tumors in the thorax and abdomen. All scans were contaminated by motion to some degree, and for each the list-mode data were reconstructed into 1-min frames. The dynamic frames were aligned to a reference position by sequentially registering each frame to its previous neighboring frame. We parametrized the motion fields in-between frames as diffeomorphism, which can map the shape change of the object smoothly and continuously in time and space. Diffeomorphic representations of motion fields were derived by registering neighboring frames using large deformation diffeomorphic metric matching. When all pairwise registrations were completed, the motion field at each frame was obtained by concatenating the successive motion fields and transforming that frame into the reference position. The proposed correction method was labeled SyN-seq. The method that was performed similarly, but aligned each frame to a designated middle frame, was labeled as SyN-mid. Instead of SyN, the method that performed the sequential affine registration was labeled as Aff-seq. The original uncorrected images were labeled as NMC. Qualitative and quantitative analyses were performed to compare the performance of the proposed method with that of other correction methods and uncorrected images.

Results

The results indicated that visual improvement was achieved after correction of the SUV images for the motion present period, especially in the brain and abdomen. For subjects with tumors, the average improvement in tumor SUVmean was 5.35 ± 4.92% (P = 0.047), with a maximum improvement of 12.89%. An overall quality improvement in quantitative K_i images was also observed after correction; however, such improvement was less obvious in K₁ images. Sampled time–activity curves in the cerebral and kidney cortex were less affected by the motion after applying the proposed correction. Mutual information and dice coefficient relative to the reference also demonstrated that SyN-seq improved the alignment between frames over non-corrected images (P = 0.003 and P = 0.011). Moreover, the proposed correction successfully reduced the inter-subject variability in K_i quantifications (11.8% lower in sampled organs). Subjective assessment by experienced radiologists demonstrated consistent results for both SUV images and K_i images.

Conclusion

To conclude, motion correction is important for image quality in dynamic total-body PET imaging. We demonstrated a correction framework that can effectively reduce the effect of random body movements on dynamic images and their associated quantification. The proposed correction framework can potentially benefit applications that require total-body assessment, such as imaging the brain-gut axis and systemic diseases.

Tracer-specific reference tissues selection improves detection of 18 F-FDG, 18 F-florbetapir, and 18 F-flortaucipir PET SUVR changes in Alzheimer's disease

This study sought to identify a reference tissue‐based quantification approach for improving the statistical power in detecting changes in brain glucose metabolism, amyloid, and tau deposition in Alzheimer's disease studies. A total of 794, 906, and 903 scans were included for ¹⁸F‐FDG, ¹⁸F‐florbetapir, and ¹⁸F‐flortaucipir, respectively. Positron emission tomography (PET) and T1‐weighted images of participants were collected from the Alzheimer's disease Neuroimaging Initiative database, followed by partial volume correction. The standardized uptake value ratios (SUVRs) calculated from the cerebellum gray matter, centrum semiovale, and pons were evaluated at both region of interest (ROI) and voxelwise levels. The statistical power of reference tissues in detecting longitudinal SUVR changes was assessed via paired t‐test. In cross‐sectional analysis, the impact of reference tissue‐based SUVR differences between cognitively normal and cognitively impaired groups was evaluated by effect sizes Cohen's d and two sample t‐test adjusted by age, sex, and education levels. The average ROI t values of pons were 86.62 and 38.40% higher than that of centrum semiovale and cerebellum gray matter in detecting glucose metabolism decreases, while the centrum semiovale reference tissue‐based SUVR provided higher t values for the detection of amyloid and tau deposition increases. The three reference tissues generated comparable d images for ¹⁸F‐FDG, ¹⁸F‐florbetapir, and ¹⁸F‐flortaucipir and comparable t maps for ¹⁸F‐florbetapir and ¹⁸F‐flortaucipir, but pons‐based t map showed superior performance in ¹⁸F‐FDG. In conclusion, the tracer‐specific reference tissue improved the detection of ¹⁸F‐FDG, ¹⁸F‐florbetapir, and ¹⁸F‐flortaucipir PET SUVR changes, which helps the early diagnosis, monitoring of disease progression, and therapeutic response in Alzheimer's disease.