Image-derived Input Function Method Research Articles

Feasibility of Renal Blood Flow Measurement Using 64Cu-ATSM PET/MRI: A Quantitative PET and MRI Study.

This study aimed to evaluate the renal blood flow (RBF) in patients with chronic kidney disease (CKD) using 64Cu(II)-diacetyl-bis(4-methylthiosemicarbazonate) (64Cu-ATSM) for positron emission tomography (PET)/magnetic resonance imaging (MRI). We included five healthy controls (HCs) and ten patients with CKD. The estimated glomerular filtration rate (eGFR) was calculated from the serum creatinine (cr) and cystatin C (cys) levels. The estimated RBF (eRBF) was calculated using the eGFR, hematocrit, and filtration fraction. A single dose of 64Cu-ATSM (300-400 MBq) was administered for RBF evaluation, and a 40 min dynamic PET scan was performed with simultaneous arterial spin labeling (ASL) imaging. PET-RBF images were obtained from the dynamic PET images at 3 min after injection using the image-derived input function method. The mean eRBF values calculated from various eGFR values differed significantly between the patients and HCs; both groups also differed significantly in terms of the RBF values (mL/min/100 g) measured using PET (151 ± 20 vs. 124 ± 22, p < 0.05) and ASL-MRI (172 ± 38 vs. 125 ± 30, p < 0.001). The ASL-MRI-RBF was positively correlated with the eRBFcr-cys (r = 0.858, p < 0.001). The PET-RBF was positively correlated with the eRBFcr-cys (r = 0.893, p < 0.001). The ASL-RBF was positively correlated with the PET-RBF (r = 0.849, p < 0.001). 64Cu-ATSM PET/MRI demonstrated the reliability of PET-RBF and ASL-RBF by comparing them with eRBF. This is the first study to demonstrate that 64Cu-ATSM-PET is useful for assessing the RBF and is well correlated with ASL-MRI.

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.

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.

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.

Image Quantification for TSPO PET with a Novel Image-Derived Input Function Method.

There is a growing interest in using 18F-DPA-714 PET to study neuroinflammation and microglial activation through imaging the 18-kDa translocator protein (TSPO). Although quantification of 18F-DPA-714 binding can be achieved through kinetic modeling analysis with an arterial input function (AIF) measured with blood sampling procedures, the invasiveness of such procedures has been an obstacle for wide application. To address these challenges, we developed an image-derived input function (IDIF) that noninvasively estimates the arterial input function from the images acquired for 18F-DPA-714 quantification. Methods: The method entails three fully automatic steps to extract the IDIF, including a segmentation of voxels with highest likelihood of being the arterial blood over the carotid artery, a model-based matrix factorization to extract the arterial blood signal, and a scaling optimization procedure to scale the extracted arterial blood signal into the activity concentration unit. Two cohorts of human subjects were used to evaluate the extracted IDIF. In the first cohort of five subjects, arterial blood sampling was performed, and the calculated IDIF was validated against the measured AIF through the comparison of distribution volumes from AIF (VT,AIF) and IDIF (VT,IDIF). In the second cohort, PET studies from twenty-eight healthy controls without arterial blood sampling were used to compare VT,IDIF with VT,REF measured using a reference region-based analysis to evaluate whether it can distinguish high-affinity (HAB) and mixed-affinity (MAB) binders. Results: In the arterial blood-sampling cohort, VT derived from IDIF was found to be an accurate surrogate of the VT from AIF. The bias of VT, IDIF was −5.8 ± 7.8% when compared to VT,AIF, and the linear mixed effect model showed a high correlation between VT,AIF and VT, IDIF (p < 0.001). In the nonblood-sampling cohort, VT, IDIF showed a significance difference between the HAB and MAB healthy controls. VT, IDIF and standard uptake values (SUV) showed superior results in distinguishing HAB from MAB subjects than VT,REF. Conclusions: A novel IDIF method for 18F-DPA-714 PET quantification was developed and evaluated in this study. This IDIF provides a noninvasive alternative measurement of VT to quantify the TSPO binding of 18F-DPA-714 in the human brain through dynamic PET scans.

Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET

BackgroundArterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic 18F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (CP*(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated CP*(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling.MethodsThe Feng 18F-FDG plasma concentration model was applied to estimate AIF parameters (n = 23). AIF normalization used either AUC(0–60 min) or CP*(0), estimated from an exponential fit. CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV). iDV was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15–45, 30–60, 45–75, 60–90 min) (PBIFAUC) and estimated CP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak Ki values.ResultsThe IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and Ki comparison, 30–60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimated Ki (− 6 ± 8 to − 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30–60), and PBIFiDV were 0.91, 0.94, and 0.90, respectively. The bias of Ki was − 9 ± 10%, − 1 ± 8%, and 3 ± 9%, respectively.ConclusionsBoth PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.

Multimodal analysis using [11C]PiB-PET/MRI for functional evaluation of patients with Alzheimer\u2019s disease

BackgroundMultimodal PET/MRI image data simultaneously obtained from patients with early-stage of Alzheimer’s disease (eAD) were assessed in order to observe pathophysiologic and functional changes, as well as alterations of morphology and connectivity in the brain. Fifty-eight patients with mild cognitive impairment and early dementia (29 males, 69 ± 12 years) underwent [11C]Pittsburgh compound-B (PiB) PET/MRI with 70-min PET and MRI scans. Sixteen age-matched healthy controls (CTL) (9 males, 68 ± 11 years) were also studied with the same scanning protocol. Cerebral blood flow (CBF) was calculated from the early phase PET images using the image-derived input function method. A standardized uptake value ratio (SUVr) was calculated from 50 to 70 min PET data with a reference region of the cerebellar cortex. MR images such as 3D-T1WI, resting-state functional MRI (RS-fMRI), diffusion tensor image (DTI), and perfusion MRI acquired during the dynamic PET scan were also analyzed to evaluate various brain functions on MRI.ResultsTwenty-seven of the 58 patients were determined as eAD based on the results of PiB-PET and clinical findings, and a total of 43 subjects’ data including CTL were analyzed in this study. PiB SUVr values in all cortical regions of eAD were significantly greater than those of CTL. The PiB accumulation intensity was negatively correlated with cognitive scores. The regional PET-CBF values of eAD were significantly lower in the bilateral parietal lobes and right temporal lobe compared with CTL, but not in MRI perfusion; however, SPM showed regional differences on both PET- and MRI-CBF. SPM analysis of RS-fMRI delineated regional differences between the groups in the anterior cingulate cortex and the left precuneus. VBM analysis showed atrophic changes in the AD group in a part of the bilateral hippocampus; however, analysis of fractional anisotropy calculated from DTI data did not show differences between the two groups.ConclusionMultimodal analysis conducted with various image data from PiB-PET/MRI scans showed differences in regional CBF, cortical volume, and neuronal networks in different regions, indicating that pathophysiologic and functional changes in the AD brain can be observed from various aspects of neurophysiologic parameters. Application of multimodal brain images using PET/MRI would be ideal for investigating pathophysiologic changes in patients with dementia and other neurodegenerative diseases.

Noninvasive method for measurement of cerebral blood flow using O-15 water PET/MRI with ASL correlation

PurposeA noninvasive image derived input function (IDIF) method was applied to estimate arterial input function from brain H215O-PET/MRI images for the measurement of cerebral blood flow (CBF) because of difficulty in arterial blood sampling during PET/MRI scans. To evaluate accuracy and reproducibility of radioactivity in the internal carotid arteries (ICA) for the IDIF method, a new phantom using a skull bone was applied in the cross-calibration process between the scanner and a gamma-well counter. MethodsEleven healthy volunteers (9 males, 43.9 ± 10.9y) underwent PET/MRI studies with a 3-min H215O-PET and several MRI scans including arterial spin labeling (ASL) perfusion MRI. PET images were reconstructed as dynamic data using two sets of reconstruction parameters, which were determined by basic assessment of radioactivity concentration reproducibility in the tubes of the phantom. The IDIF method extracted the time-activity curves of the ICA from several image slices in the PET data. CBF images were calculated using the autoradiographic (ARG) method and a one-tissue compartment model (1-TCM). ResultsThe global means of CBF from the ARG, 1-TCM, and ASL-MRI were 44.8 ± 4.3, 47.9 ± 5.9 and 57.9 ± 8.6 (mL/min/100 g), respectively. CBF from ASL-MRI was significantly greater compared with CBF from H215O-PET (P < 0.001). However, these CBF values were significantly correlated with each other in the scatter plots (P < 0.05). ConclusionsNoninvasive measurement of CBF using H215O-PET/MRI and IDIF with the cross-calibration method with a skull phantom experiment provided reasonable quantitative values. The IDIF method allowed reliable estimation of arterial radioactivity concentration, which is useful for clinical application. The ASL-MRI perfusion image from the simultaneous acquisition tended to overestimate CBF.

Image-derived input function in PET brain studies

Image-derived input function (IDIF) from carotid arteries is an elegant alternative to full arterial blood sampling for brain PET studies. However, a recent study using blood-free IDIFs found that this method is particularly vulnerable to patient motion. The present study used both simulated and clinical [11C](R)-rolipram data to assess the robustness of a blood-based IDIF method (a method that is ultimately normalized with blood samples) with regard to motion artifacts. The impact of motion on the accuracy of IDIF was first assessed with an analytical simulation of a high-resolution research tomograph using a numerical phantom of the human brain, equipped with internal carotids. Different degrees of translational (from 1 to 20 mm) and rotational (from 1 to 15°) motions were tested. The impact of motion was then tested on the high-resolution research tomograph dynamic scans of three healthy volunteers, reconstructed with and without an online motion correction system. IDIFs and Logan-distribution volume (VT) values derived from simulated and clinical scans with motion were compared with those obtained from the scans with motion correction. In the phantom scans, the difference in the area under the curve (AUC) for the carotid time-activity curves was up to 19% for rotations and up to 66% for translations compared with the motionless simulation. However, for the final IDIFs, which were fitted to blood samples, the AUC difference was 11% for rotations and 8% for translations. Logan-VT errors were always less than 10%, except for the maximum translation of 20 mm, in which the error was 18%. Errors in the clinical scans without motion correction appeared to be minor, with differences in AUC and Logan-VT always less than 10% compared with scans with motion correction. When a blood-based IDIF method is used for neurological PET studies, the motion of the patient affects IDIF estimation and kinetic modeling only minimally.

Development of FDG-PET quantitative procedures without blood sampling

This study was to compare our input function estimation methods with the standard blood sampling and other competing methods. We have developed two input function estimation methods, namely simplified simultaneous estimation method and regression estimated input function method for FDG-PET model. The derivation of input functions from both methods requires no blood sample. Our results show that both methods have high correlation with the standard blood sampling method using nonlinear least squares method for parameter estimation. There were no significant differences in error percentage among the proposed methods and the existing methods such as image derived input function method, standard input function method, and simultaneous estimation method. Accordingly, our methods can reliably measure cerebral metabolic rate of glucose and provide patients and physicians with simple and noninvasive ways in FDG-PET quantitative studies.