Image-derived Input Function Research Articles

Correlation between cardiac image-derived and arterial input functions for quantitative [18F]-FDOPA imaging in the dopaminergic system

Correlation between cardiac image-derived and arterial input functions for quantitative [18F]-FDOPA imaging in the dopaminergic system

Input function and modeling for determining bone metabolic flux using [18 F] sodium fluoride PET imaging: A step-by-step guide.

Studies of skeletal metabolism using measurements of bone metabolic flux (Ki ) obtained with [18 F] sodium fluoride ([18 F]NaF) positron emission tomography (PET) scans have been used in clinical research for the last 30 years. The technique has proven useful as an imaging biomarker in trials of novel drug treatments for osteoporosis and investigating other metabolic bone diseases, including chronic kidney disease mineral and bone disorder. It has also been shown to be valuable in metastatic bone disease in breast cancer patients and may have potential in other cancer types, such as prostate cancer, to assess early bone fracture risk. However, these studies have usually required a 60-min dynamic PET scan and measurement of the arterial input function (AIF), making them difficult to translate into the clinic for diagnostic purposes. We have previously proposed a simplified method that estimates the Ki value at an imaging site from a short (4-min) static scan and venous blood samples. A key advantage of this method is that, by acquiring a series of static scans, values of Ki can be quickly measured at multiple sites using a single injection of the tracer. To date, the widespread use of [18 F]NaF PET has been limited by the need to measure the AIF required for the mathematical modeling of tracer kinetics to derive Ki and other kinetic parameters. In this report, we review different methods of measuring the AIF, including direct arterial sampling, the use of a semi-population input function (SP-AIF), and image-derived input function, the latter two requiring only two or three venous blood samples obtained between 30 and 60min after injection. We provide an SP-AIF model and a spreadsheet for calculating Ki values using the static scan method that others can use to study bone metabolism in metabolic and metastatic bone diseases without requiring invasive arterial blood sampling. The method shortens scan times, simplifies procedures, and reduces the cost of multicenter trials without losing accuracy or precision.

Non‐invasive quantification and SUVR validation of [18F]‐florbetaben with total‐body EXPLORER PET

AbstractBackgroundKinetic modeling of brain amyloid deposition with [18F]‐florbetaben more accurately quantifies the binding density to amyloid plaques compared to standardized uptake ratios (SUVR) (Becker, JNM2013). The total‐body EXPLORER PET scanner with an axial field of view of 194cm supports the acquisition of a full human body in one scan and permits noninvasive Image‐Derived Input Functions (IDIFs) as an alternative to arterial blood sampling (Badawi, JNM 2019). Our aim is to quantify amyloid buildup with kinetic models that leverage dynamics in aorta IDIFs and the brain utilizing [18F]‐Florbetaben and validate with SUVR in an elderly cohort.MethodTwelve adults aged 66‐86 underwent dynamic total‐body 18F‐florbetaben PET for 110min, spatial resolution = 2.344mm, average tracer dose = 299.70 MBq. 8 cognitively‐normal, 3 Mild Cognitive Impairment (MCI), and 1 Alzheimer’s disease (AD). Regions of interests were drawn in the middle descending aorta and eroded to exclude the vessel walls to derive IDIFs (Fig.1). Next, regional brain analysis including PET image matching to previously acquired T1‐weighted MRI, normalization, and segmentation were performed in PMOD (v4.2) using the AAL atlas. PET SUVR (90‐110min) means were calculated from 7 index regions (lateral frontal, medial frontal, anterior cingulate, posterior cingulate, lateral temporal, lateral parietal, and precuneus) and the cerebellar gray matter. Dynamic time activity curves (TACs) from the same brain regions were fit to the two‐tissue compartment model (2TCM) using population metabolite‐corrected IDIFs; and the Multi‐linear Reference Tissue Model (MRTM) to calculate distribution volume ratio (DVR) with reference to cerebellar gray (Ichise, JCBFM 2003).ResultAmyloid‐positive patients showed the highest SUVR in brain index regions (Fig.2). High quality dynamic kinetic modeling was achieved (Fig.3), with high SUVR accumulation in index regions compared to cerebellum at later time points in amyloid‐positive cases. SUVR and DVR from kinetic models were strongly correlated; with slight overestimation of SUVR compared to DVR (Fig.4). DVR values from the MRTM were lower than (86.7% of) DVR quantified by 2TCM.ConclusionAbsolute quantification of amyloid binding from total‐body [18F]‐florbetaben PET data is feasible using aorta IDIFs with high agreement between dynamic binding parameters compared to SUVR in discriminating positive and negative scans.

Non‐invasive quantification and SUVR validation of [18F]‐florbetaben with total‐body EXPLORER PET

AbstractBackgroundKinetic modeling of brain amyloid deposition with [18F]‐florbetaben more accurately quantifies the binding density to amyloid plaques compared to standardized uptake ratios (SUVR) (Becker, JNM2013). The total‐body EXPLORER PET scanner with an axial field of view of 194cm supports the acquisition of a full human body in one scan and permits noninvasive Image‐Derived Input Functions (IDIFs) as an alternative to arterial blood sampling (Badawi, JNM 2019). Our aim is to quantify amyloid buildup with kinetic models that leverage dynamics in aorta IDIFs and the brain utilizing [18F]‐Florbetaben and validate with SUVR in an elderly cohort.MethodTwelve adults aged 66‐86 underwent dynamic total‐body 18F‐florbetaben PET for 110min, spatial resolution = 2.344mm, average tracer dose = 299.70 MBq. 8 cognitively‐normal, 3 Mild Cognitive Impairment (MCI), and 1 Alzheimer’s disease (AD). Regions of interests were drawn in the middle descending aorta and eroded to exclude the vessel walls to derive IDIFs (Fig.1). Next, regional brain analysis including PET image matching to previously acquired T1‐weighted MRI, normalization, and segmentation were performed in PMOD (v4.2) using the AAL atlas. PET SUVR (90‐110min) means were calculated from 7 index regions (lateral frontal, medial frontal, anterior cingulate, posterior cingulate, lateral temporal, lateral parietal, and precuneus) and the cerebellar gray matter. Dynamic time activity curves (TACs) from the same brain regions were fit to the two‐tissue compartment model (2TCM) using population metabolite‐corrected IDIFs; and the Multi‐linear Reference Tissue Model (MRTM) to calculate distribution volume ratio (DVR) with reference to cerebellar gray (Ichise, JCBFM 2003).ResultAmyloid‐positive patients showed the highest SUVR in brain index regions (Fig.2). High quality dynamic kinetic modeling was achieved (Fig.3), with high SUVR accumulation in index regions compared to cerebellum at later time points in amyloid‐positive cases. SUVR and DVR from kinetic models were strongly correlated; with slight overestimation of SUVR compared to DVR (Fig.4). DVR values from the MRTM were lower than (86.7% of) DVR quantified by 2TCM.ConclusionsAbsolute quantification of amyloid binding from total‐body [18F]‐florbetaben PET data is feasible using aorta IDIFs with high agreement between dynamic binding parameters compared to SUVR in discriminating positive and negative scans.

Investigation of image-derived input functions for non-invasive quantification of myelin density using [11C]MeDAS PET

Multiple sclerosis (MS) is an inflammatory demyelinating disease. Current treatments are focussed on immune suppression to modulate pathogenic activity that causes myelin damage. New treatment strategies are needed to prevent demyelination and promote remyelination. Development of such myelin repair therapies require a sensitive and specific biomarker for efficacy evaluation. Recently, it has been shown that quantification of myelin density is possible using [11C]MeDAS PET. This method, however, requires arterial blood sampling to generate an arterial input function (AIF). As the invasive nature of arterial sampling will reduce clinical applicability, the purpose of this study was to assess whether an image-derived input function (IDIF) can be used as an alternative way to facilitate its routine clinical use.Six healthy controls and 11 MS patients underwent MRI and [11C]MeDAS PET with arterial blood sampling. The application of both population-based whole blood-to-plasma conversion and metabolite corrections were assessed for the AIF. Next, summed images of the early time frames (0–70 s) and the frame with the highest blood-brain contrast were used to generate IDIFs. IDIFs were created using either the hottest 2, 4, 6 or 12 voxels, or an isocontour of the hottest 10% voxels of the carotid artery. This was followed by blood-to-plasma conversion and metabolite correction of the IDIF.The application of a population-based metabolite correction of the AIF resulted in high correlations of tracer binding (Ki) within subjects, but variable bias across subjects. All IDIFs had a sharper and higher peak in the blood curves than the AIF, most likely due to dispersion during blood sampling. All IDIF methods resulted in similar high correlations within subjects (r = 0.95–0.98), but highly variable bias across subjects (mean slope=0.90–1.09).Therefore, both the use of population based blood-plasma and metabolite corrections and the generation of the image-derived whole-blood curve resulted in substantial bias in [11C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [11C]MeDAS PET data is required, individual AIF needs to be used.

HYPR4D kernel method on TOF PET data with validations including image-derived input function

BackgroundPositron emission tomography (PET) images are typically noisy especially in dynamic imaging where the PET data are divided into a number of short temporal frames often with a low number of counts. As a result, image features such as contrast and time–activity curves are highly variable. Noise reduction in PET is thus essential. Typical noise reduction methods tend to not preserve image features/patterns (e.g. contrast and size dependent) accurately. In this work, we report the first application of our HYPR4D kernel method on time-of-flight (TOF) PET data (i.e. PSF-HYPR4D-K-TOFOSEM). The proposed HYPR4D kernel method makes use of the mean 4D high frequency features and inconsistent noise patterns over OSEM subsets as well as the low noise property of the early reconstruction updates to achieve prior-free de-noising. The method was implemented and tested on the GE SIGNA PET/MR and was compared to the TOF reconstructions with PSF resolution modeling available on the system, namely PSF-TOFOSEM with and without standard post filter and PSF-TOFBSREM (TOF Q.Clear) with various beta values (regularization strengths).ResultsResults from experimental contrast phantom and human subject data with various PET tracers showed that the proposed method provides more robust and accurate image features compared to other regularization methods. The preservation of contrast for the PSF-HYPR4D-K-TOFOSEM was observed to be better and less dependent on the contrast and size of the target structures as compared to TOF Q.Clear and PSF-TOFOSEM with filter. At the same contrast level, PSF-HYPR4D-K-TOFOSEM achieved better 4D noise suppression than other methods (e.g. >2 times lower noise than TOF Q.Clear at the highest contrast). We also present a novel voxel search method to obtain an image-derived input function (IDIF) and demonstrate that the obtained IDIF is the most quantitative w.r.t. the measured blood samples when the acquired data are reconstructed with PSF-HYPR4D-K-TOFOSEM.ConclusionsThe overall results support superior performance of the PSF-HYPR4D-K-TOFOSEM for TOF PET data and demonstrate that the proposed method is likely suitable for all imaging tasks including the generation of IDIF without requiring any prior information as well as further improving the effective sensitivity of the imaging system.

11C]glyburide PET imaging for quantitative determination of the importance of Organic Anion-Transporting Polypeptide transporter function in the human liver and whole-body

Organic Anion-Transporting Polypeptides (OATPs) are known to control the liver uptake of many drugs. Non-hepatic expression of OATPs has been reported although functional importance for whole-body pharmacokinetics (WBPK) remains unknown. Glyburide is a well described substrate of several hepatic and non-hepatic OATPs. Dynamic whole-body positron emission tomography (DWB-PET) with [11C]glyburide was performed in humans for determination of the importance of OATPs for liver uptake and WBPK. Seven healthy male subjects (24.7 ± 3.2 years) underwent [11C]glyburide PET scan with concomitant blood sampling. All subjects underwent baseline [11C]glyburide PET scan. Five subjects underwent a subsequent [11C]glyburide PET scan after infusion of the potent OATP inhibitor rifampicin (9 mg/kg i.v.). The transfer constant (kuptake) of [11C]glyburide from blood to the liver was estimated using the integration plot method. The tissue exposure of [11C]glyburide was described by the area under the time-activity curve (AUC) and corresponding tissue/blood ratio (AUCR). [11C]glyburide was barely metabolized in both the baseline and rifampicin conditions. Parent (unmetabolized) [11C]glyburide accounted for > 90 % of the plasma radioactivity. Excellent correlation was found between radioactive counting in arterial blood samples and in the image-derived input function, in both the baseline and rifampicin conditions (R2 = 97.9 %, p < 0.01). [11C]glyburide predominantly accumulated in the liver. Rifampicin decreased liver kuptake by 77.3 ± 7.3 %, which increased exposure in blood, kidneys, spleen, myocardium and brain (p < 0.05). No significant change in AUCR was observed except in the liver (p < 0.01). [11C]glyburide benefits from metabolic stability and high sensitivity to OATP inhibition which enables quantitative determination of OATP function. DWB-PET suggests negligible role for non-hepatic OATPs in controlling the tissue distribution of [11C]glyburide.

Shortened duration whole body 18F-FDG PET Patlak imaging on the Biograph Vision Quadra PET/CT using a population-averaged input function

BackgroundExcellent performance characteristics of the Vision Quadra PET/CT, e.g. a substantial increase in sensitivity, allow for precise measurements of image-derived input functions (IDIF) and tissue time activity curves. Previously we have proposed a method for a reduced 30 min (as opposed to 60 min) whole body 18F-FDG Patlak PET imaging procedure using a previously published population-averaged input function (PIF) scaled to IDIF values at 30–60 min post-injection (p.i.). The aim of the present study was to apply this method using the Vision Quadra PET/CT, including the use of a PIF to allow for shortened scan durations.MethodsTwelve patients with suspected lung malignancy were included and received a weight-based injection of 18F-FDG. Patients underwent a 65-min dynamic PET acquisition which were reconstructed using European Association of Nuclear Medicine Research Ltd. (EARL) standards 2 reconstruction settings. A volume of interest (VOI) was placed in the ascending aorta (AA) to obtain the IDIF. An external PIF was scaled to IDIF values at 30–60, 40–60, and 50–60 min p.i., respectively, and parametric 18F-FDG influx rate constant (Ki) images were generated using a t* of 30, 40 or 50 min, respectively. Herein, tumour lesions as well as healthy tissues, i.e. liver, muscle tissue, spleen and grey matter, were segmented.ResultsGood agreement between the IDIF and corresponding PIF scaled to 30–60 min p.i. and 40–60 min p.i. was obtained with 7.38% deviation in Ki. Bland–Altman plots showed excellent agreement in Ki obtained using the PIF scaled to the IDIF at 30–60 min p.i. and at 40–60 min p.i. as all data points were within the limits of agreement (LOA) (− 0.004–0.002, bias: − 0.001); for the 50–60 min p.i. Ki, all except one data point fell in between the LOA (− 0.021–0.012, bias: − 0.005).ConclusionsParametric whole body 18F-FDG Patlak Ki images can be generated non-invasively on a Vision Quadra PET/CT system. In addition, using a scaled PIF allows for a substantial (factor 2 to 3) reduction in scan time without substantial loss of accuracy (7.38% bias) and precision (image quality and noise interference).

Direct dynamic tomographic reconstruction without explicit blood input function

With dynamic positron emission tomography (PET), we study the metabolic processes by monitoring the uptake of a radioactive tracer. The goal is to reconstruct the time-activity curves (TACs) of the voxels, from which the relevant kinetic parameters can be obtained. These curves are assumed to have the algebraic form of a pre-determined kinetic model. Plausible algebraic forms have a limited number of free parameters and thus can be used even for low-statistic measurements. The kinetic model typically involves the amount of radiotracer in the blood, which should be determined either by direct measurement or by extracting it from the PET data using image-derived or model-based methods. However, the direct measurement of the blood concentration is complicated, and the results of the image-derived and the model-based methods are also not reliable because of the partial volume effect and the unknown fraction of blood in the voxels. Moreover, in direct dynamic tomography, the kinetic model is fit from the very beginning of the reconstruction, thus the blood input function is needed even before the image-derived or model-based approaches can provide it. In this paper, we propose a method that is based on compartmental modeling and the Feng blood input function model defined by a fourth-order exponential equation with a pair of repeated eigenvalues, but does not require the blood input function and the fraction of blood parameters explicitly. Thus, the model can be used in cases when we wish to have the robustness and advantages of compartmental modeling, but no blood input function measurement is available. The test results show that the added error in the TACs of not knowing the blood input is reduced in comparison with the spline-based TAC representation. The method can be applied in reference tissue analysis and in image-derived input function approaches.

Radiosynthesis of 20-[18F]fluoroarachidonic acid for PET-MR imaging: Biological evaluation in ApoE4-TR mice

Dysreglulated brain arachidonic acid (AA) metabolism is involved in chronic inflammation and is influenced by apolipoprotein E4 (APOE4) genotype, the strongest genetic risk factor of late-onset Alzheimer's disease (AD). Visualization of AA uptake and distribution in the brain can offer insight into neuroinflammation and AD pathogenesis. Here we present a novel synthesis and radiosynthesis of 20-[18F]fluoroarachidonic acid ([18F]-FAA) for PET imaging using a convergent route and a one-pot, single-purification radiolabeling procedure, and demonstrate its brain uptake in human ApoE4 targeted replacement (ApoE4-TR) mice. By examining p38 phosphorylation in astrocytes, we found that fluorination of AA at the ω-position did not significantly alter its biochemical role in cells. The brain incorporation coefficient (K*) of [18F]-FAA was estimated via multiple methods by using an image-derived input function from the right ventricle of the heart as a proxy of the arterial input function and brain tracer concentrations assessed by dynamic PET-MR imaging. This new synthetic approach should facilitate the practical [18F]-FAA production and allow its translation into clinical use, making investigations of dysregulation of lipid metabolism more feasible in the study of neurodegenerative diseases.

18 kDa translocator protein positron emission tomography facilitates early and robust tumor detection in the immunocompetent SB28 glioblastoma mouse model.

The 18 kDa translocator protein (TSPO) receives growing interest as a biomarker in glioblastoma. Mouse models can serve as an important tool for the investigation of biomarkers in glioblastoma, but several glioblastoma models indicated only low TSPO-PET signals in contrast to high TSPO-PET signals of human glioblastoma. Thus, we aimed to investigate TSPO-PET imaging in the syngeneic immunocompetent SB28 mouse model, which is thought to closely represent the tumor microenvironment (TME) of human glioblastoma. Dynamic TSPO-PET/CT imaging was performed for 60 min after injection of 13.6 ± 4.2 MBq [18F]GE-180. Contrast enhanced CT (ceCT) was acquired prior to PET and served for assessment of tumor volumes and attenuation correction. SB28 and sham mice were imaged at an early (week-1; n = 6 SB28, n = 6 sham) and a late time-point (week-3; n = 8 SB28, n = 9 sham) after inoculation. Standard of truth ex vivo tumor volumes were obtained for SB28 mice at the late time-point. Tracer kinetics were analyzed for the lesion site and the carotid arteries to establish an image derived input function (IDIF). TSPO-PET and ceCT lesion volumes were compared with ex vivo volumes by calculation of root-mean-square-errors (RMSE). Volumes of distribution (VTmax/mean) in the lesion were calculated using carotid IDIF and standardized uptake values (SUVmax/mean) were obtained for a 40-60 min time frame. Higher uptake rate constants (K1) were observed for week-1 SB28 tumor lesions when compared to week-3 SB28 tumor lesions. Highest agreement between TSPO-PET lesion volumes and ex vivo tumor volumes was achieved with a 50% maximum threshold (RMSE-VT: 39.7%; RMSE-SUV: 34.4%), similar to the agreement of ceCT tumor volumes (RMSE: 30.1%). Lesions of SB28 mice had higher PET signal when compared to sham mice at week-1 (VTmax 6.6 ± 2.9 vs. 3.9 ± 0.8, p = 0.035; SUVmax 2.3 ± 0.5 vs. 1.2 ± 0.1, p < 0.001) and PET signals remained at a similar level at week-3 (VTmax 5.0 ± 1.6 vs. 2.7 ± 0.8, p = 0.029; SUVmax 1.9 ± 0.5 vs. 1.2 ± 0.2, p = 0.0012). VTmax correlated with SUVmax (R 2 = 0.532, p < 0.001). TSPO-PET imaging of immunocompetent SB28 mice facilitates early detection of tumor signals over sham lesions. SB28 tumors mirror high TSPO-PET signals of human glioblastoma and could serve as a valuable translational model to study TSPO as an imaging biomarker.

Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [18F]-FDG datasets from a long axial FOV PET scanner

BackgroundAccurate kinetic modeling of 18F-fluorodeoxyglucose ([18F]-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples, but the introduction of long axial field of view (LAFOV) PET systems enables the use of non-invasive image-derived input functions (IDIFs) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition, which is impractical in a busy clinical setting. Population-based input functions (PBIFs) have previously shown potential in accurate Patlak analysis of [18F]-FDG datasets and can enable the use of shortened dynamic imaging protocols. Here, we exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore the use of PBIF with abbreviated protocols in [18F]-FDG total body kinetic modeling.MethodsDynamic PET data were acquired in 24 oncological subjects for 65 min following the administration of [18F]-FDG. IDIFs were extracted from the descending thoracic aorta, and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIFs) were generated by scaling the PBIF with the AUC of IDIF curve tails using various portions of image data (35–65, 40–65, 45–65, 50–65, and 55–65 min post-injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumor lesions and cerebral gray matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on the accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t* = 35 min were used as reference, and mean bias and precision (standard deviation of bias) were calculated to assess the relative performance of different sPBIFs. A comparison of parametric images generated using IDIF and sPBIFs was also performed.ResultsThere was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P > 0.05). Excellent agreement was shown between Patlak Ki estimates obtained using sPBIF and IDIF. Using the sPBIF55–65 with the Patlak model, 20 min of PET data (i.e., 45 to 65 min post-injection) achieved < 15% precision error in Ki estimates in tumor lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 min of PET data as reference, Patlak Ki images generated using sPBIF55–65 with 20 min of PET data (t* = 45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB.ConclusionWe demonstrate the feasibility of performing accurate [18F]-FDG Patlak analysis using sPBIFs with only 20 min of PET data from a LAFOV PET scanner.

Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease.

The non-invasive quantification of the cerebral metabolic rate for glucose (CMRGlc) and the characterization of cerebral metabolism in the cerebrovascular territories are helpful in understanding ischemic cerebrovascular disease (ICVD). Firstly, we investigated a non-invasive quantification approach based on an image-derived input function (IDIF) in ICVD. Second, we studied the metabolic changes in CMRGlc after surgical intervention. We evaluated the hypothesis that the IDIF method based on the unilateral internal carotid artery could address challenges in ICVD quantification. The CMRGlc and standardized uptake value ratio (SUVR) were used to measure glucose metabolism activity. Healthy controls showed no significant differences in CMRGlc values between bilateral and unilateral IDIF measurements (intraclass correlation coefficient [ICC]: 0.91-0.98). Patients with ICVD showed significantly increased CMRGlc values after surgical intervention for all territories (percentage changes: 7.4%-22.5%). In contrast, SUVR showed minor differences between postoperative and preoperative patients, indicating that it was a poor biomarker for the diagnosis of ICVD. A significant association between CMRGlc and the National Institutes of Health Stroke Scale (NIHSS) scores was observed (r=-0.54). Our findings suggested that IDIF could be a valuable tool for CMRGlc quantification in patients with ICVD and may advance personalized precision interventions.

Population-based input function (PBIF) applied to dynamic whole-body 68Ga-DOTATOC-PET/CT acquisition.

To validate a population-based input function (PBIF) model that alleviates the need for scanning since injection time in dynamic whole-body (WBdyn) PET. Thirty-seven patients with suspected/known well-differentiated neuroendocrine tumors were included (GAPETNET trial NTC03576040). All WBdyn 68Ga-DOTATOC-PET/CT acquisitions were performed on a digital PET system (one heart-centered 6 min-step followed by nine WB-passes). The PBIF model was built from 20 image-derived input functions (IDIFs) obtained from a respective number of patients' WBdyn exams using an automated left-ventricle segmentation tool. All IDIF peaks were aligned to the median time-to-peak, normalized to patient weight and administrated activity, and then fitted to an exponential model function. PBIF was then applied to 17 independent patient studies by scaling it to match the respective IDIF section at 20-55 min post-injection time windows corresponding to WB-passes 3-7. The ratio of area under the curves (AUCs) of IDIFs and PBIF3-7 were compared using a Bland-Altman analysis (mean bias ± SD). The Patlak-estimated mean Ki for physiological uptake (Ki-liver and Ki-spleen) and tumor lesions (Ki-tumor) using either IDIF or PBIF were also compared. The mean AUC ratio (PBIF/IDIF) was 0.98 ± 0.06. The mean Ki bias between PBIF3-7 and IDIF was -2.6 ± 6.2% (confidence interval, CI: -5.8; 0.6). For Ki-spleen and Ki-tumor, low relative bias with low SD were found [4.65 ± 7.59% (CI: 0.26; 9.03) and 3.70 ± 8.29% (CI: -1.09; 8.49) respectively]. For Ki-liver analysis, relative bias and SD were slightly higher [7.43 ± 13.13% (CI: -0.15; 15.01)]. Our study showed that the PBIF approach allows for reduction in WBdyn DOTATOC-PET/CT acquisition times with a minimum gain of 20 min.

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

PurposeEfforts have been made both to avoid invasive blood sampling and to shorten the scan duration for dynamic positron emission tomography (PET) imaging. A total-body scanner, such as the uEXPLORER PET/CT, can relieve these challenges through the following features: First, the whole-body coverage allows for noninvasive input function from the aortic arteries; second, with a dramatic increase in sensitivity, image quality can still be maintained at a high level even with a shorter scan duration than usual. We implemented a dual-time-window (DTW) protocol for a dynamic total-body 18F-FDG PET scan to obtain multiple kinetic parameters. The DTW protocol was then compared to several other simplified quantification methods for total-body FDG imaging that were proposed for conventional setup.MethodsThe research included 28 patient scans performed on an uEXPLORER PET/CT. By discarding the corresponding data in the middle of the existing full 60-min dynamic scan, the DTW protocol was simulated. Nonlinear fitting was used to estimate the missing data in the interval. The full input function was obtained from 15 subjects using a hybrid approach with a population-based image-derived input function. Quantification was carried out in three areas: the cerebral cortex, muscle, and tumor lesion. Micro- and macro-kinetic parameters for different scan durations were estimated by assuming an irreversible two-tissue compartment model. The visual performance of parametric images and region of interest-based quantification in several parameters were evaluated. Furthermore, simplified quantification methods (DTW, Patlak, fractional uptake ratio [FUR], and standardized uptake value [SUV]) were compared for similarity to the reference net influx rate Ki.ResultsKi and K1 derived from the DTW protocol showed overall good consistency (P < 0.01) with the reference from the 60-min dynamic scan with 10-min early scan and 5-min late scan (Ki correlation: 0.971, 0.990, and 0.990; K1 correlation: 0.820, 0.940, and 0.975 in the cerebral cortex, muscle, and tumor lesion, respectively). Similar correlationss were found for other micro-parameters. The DTW protocol had the lowest bias relative to standard Ki than any of the quantification methods, followed by FUR and Patlak. SUV had the weakest correlation with Ki. The whole-body Ki and K1 images generated by the DTW protocol were consistent with the reference parametric images.ConclusionsUsing the DTW protocol, the dynamic total-body FDG scan time can be reduced to 15 min while obtaining accurate Ki and K1 quantification and acceptable visual performance in parametric images. However, the trade-off between quantification accuracy and protocol implementation feasibility must be considered in practice. We recommend that the DTW protocol be used when the clinical task requires reliable visual assessment or quantifying multiple micro-parameters; FUR with a hybrid input function may be a more feasible approach to quantifying regional metabolic rate with a known lesion position or organs of interest.

Clinical validation of a population-based input function for 20-min dynamic whole-body 18F-FDG multiparametric PET imaging

PurposeContemporary PET/CT scanners can use 70-min dynamic whole-body (D-WB) PET to generate more quantitative information about FDG uptake than just the SUV by generating parametric images of FDG metabolic rate (MRFDG). The analysis requires the late (50–70 min) D-WB tissue data combined with the full (0–70 min) arterial input function (AIF). Our aim was to assess whether the use of a scaled population-based input function (sPBIF) obviates the need for the early D-WB PET acquisition and allows for a clinically feasible 20-min D-WB PET examination.MethodsA PBIF was calculated based on AIFs from 20 patients that were D-WB PET scanned for 120 min with simultaneous arterial blood sampling. MRFDG imaging using PBIF requires that the area under the curve (AUC) of the sPBIF is equal to the AUC of the individual patient’s input function because sPBIF AUC bias translates into MRFDG bias. Special patient characteristics could affect the shape of their AIF. Thus, we validated the use of PBIF in 171 patients that were divided into 12 subgroups according to the following characteristics: diabetes, cardiac ejection fraction, blood pressure, weight, eGFR and age. For each patient, the PBIF was scaled to the aorta image-derived input function (IDIF) to calculate a sPBIF, and the AUC bias was calculated.ResultsWe found excellent agreement between the AIF and IDIF at all times. For the clinical validation, the use of sPBIF led to an acceptable AUC bias of 1–5% in most subgroups except for patients with diabetes or patients with low eGFR, where the biases were marginally higher at 7%. Multiparametric MRFDG images based on a short 20-min D-WB PET and sPBIF were visually indistinguishable from images produced by the full 70-min D-WB PET and individual IDIF.ConclusionsA short 20-min D-WB PET examination using PBIF can be used for multiparametric imaging without compromising the image quality or precision of MRFDG. The D-WB PET examination may therefore be used in clinical routine for a wide range of patients, potentially allowing for more precise quantification in e.g. treatment response imaging.

Error-prone protein synthesis recapitulates early symptoms of Alzheimer disease in aging mice.

Age-related neurodegenerative diseases (NDDs) are associated with the aggregation and propagation of specific pathogenic protein species (e.g., Aβ, α-synuclein). However, whether disruption of synaptic homeostasis results from protein misfolding per se rather than accumulation of a specific rogue protein is an unexplored question. Here, we show that error-prone translation, with its frequent outcome of random protein misfolding, is sufficient to recapitulate many early features of NDDs, including perturbed Ca2+ signaling, neuronal hyperexcitability, and mitochondrial dysfunction. Mice expressing the ribosomal ambiguity mutation Rps9 D95N exhibited disrupted synaptic homeostasis resulting in behavioral changes reminiscent of early Alzheimer disease (AD), such as learning and memory deficits, maladaptive emotional responses, epileptiform discharges, suppressed circadian rhythmicity, and sleep fragmentation, accompanied by hippocampal NPY expression and cerebral glucose hypometabolism. Collectively, our findings suggest that random protein misfolding may contribute to the pathogenesis of age-related NDDs, providing an alternative framework for understanding the initiation of AD.

Image-derived Input Function in brain [18F]FDG PET data: which alternatives to the carotid siphons?

Quantification of brain [18F] fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) data requires an input function. A noninvasive alternative to gold-standard arterial sampling is the image-derived input function (IDIF), typically extracted from the internal carotid arteries (ICAs), which are however difficult to segment and subjected to spillover effects. In this work, we evaluated the feasibility of extracting the IDIF from two different vascular sites, i.e., 1) common carotids (CCA) and 2) superior sagittal sinus (SSS), other than 3) ICA in a large group of glioma patients undergoing a dynamic [18F]FDG PET acquisition on a hybrid PET/MR scanner. Comparisons are drawn between the different IDIFs in terms of peak amplitude and shape, as well as between the estimates of fractional uptake rate (Kr) obtained from the different extraction sites in terms of a) grey/white matter average absolute values, b) ratio of grey-to-white matter, and c) spatial patterns for the hemisphere contralateral to the lesion. Clinical Relevance - This work points towards new feasible IDIF extraction sites (CCA in particular) which could allow for fully noninvasive absolute PET quantification in clinical populations.

Modeling venous plasma samples in [18F] FDG PET studies: a nonlinear mixed-effects approach.

The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant. In this work, we used the nonlinear mixed-effects modeling approach to develop a model which infers venous tracer kinetics by using venous samples obtained from a population of healthy individuals and integrating subject-specific covariates. Population parameters (fixed effects), their between-subject variability (random effects), and the effects of covariates were estimated. The selected model will allow to reliably infer venous tracer kinetics in subjects with missing measurements. Clinical relevance - The derived model will be relevant for fully noninvasive dynamic FDG PET quantification using image-derived input functions in both healthy and patient populations when hemodynamics is not impaired.

Cerebral Oxidative Stress in Early Alzheimer's Disease Evaluated by 64Cu-ATSM PET/MRI: A Preliminary Study.

Oxidative stress imaging using diacetyl-bis (N4-methylthiosemicarbazone) (Cu-ATSM) was applied to the evaluation of patients with early Alzheimer’s disease (eAD). Ten eAD patients (72 ± 9 years) and 10 age-matched healthy controls (HCs) (73 ± 9 years) participated in this study. They underwent dynamic PET/MRI using 11C-PiB and 64Cu-ATSM with multiple MRI sequences. To evaluate cerebral oxidative stress, three parameters of 64Cu-ATSM PET were compared: standardized uptake value (SUV), tracer influx rate (Kin), and a rate constant k3. The input functions were estimated by the image-derived input function method. The relative differences were analyzed by statistical parametric mapping (SPM) using SUV and Kin images. All eAD patients had positive and HC subjects had negative PiB accumulation, and MMSE scores were significantly different between them. The 64Cu-ATSM accumulation tended to be higher in eAD than in HCs for both SUV and Kin. When comparing absolute values, eAD patients had a greater Kin in the posterior cingulate cortex and a greater k3 in the hippocampus compared with lobar cortical values of HCs. In SPM analysis, eAD had an increased left operculum and decreased bilateral hippocampus and anterior cingulate cortex compared to HCs. 64Cu-ATSM PET/MRI and tracer kinetic analysis elucidated cerebral oxidative stress in the eAD patients, particularly in the cingulate cortex and hippocampus.