The Potential Benefit by Application of Kinetic Analysis of PET in the Clinical Oncology

Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions

PURPOSE

This study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference.

METHODS

Dynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon's rank sum test, Spearman's rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05.

RESULTS

The quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P < 0.05), while a very high correlation was obtained between Ki-65 min and Ki-30 min (r = 0.977, P < 0.05). In the differential diagnosis of lung lesions, ROC analysis was performed on 146 histologically confirmed lesions, the area under the curve (AUC) of Ki-65 min, Ki-30 min, and SUVmax was 0.816, 0.816, and 0.709, respectively. According to the Delong test, no significant differences in the diagnostic accuracies were found between Ki-65 min and Ki-30 min (P > 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P < 0.05). In 73 (NSCLC) lesions with definite PD-L1 expression results, the Ki-65 min, Ki-30 min, and SUVmax in PD-L1 positivity were significantly higher than that in PD-L1 negativity (P < 0.05). And no significant differences in predicting PD-L1 positivity were found among Ki-65 min, Ki-30 min, and SUVmax (AUC = 0.704, 0.695, and 0.737, respectively, P > 0.05), according to the results of ROC analysis and Delong test.

CONCLUSIONS

This study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.

Comparison of tracer kinetic models for 68Ga-PSMA-11 PET in intermediate-risk primary prostate cancer patients

BACKGROUND

68Ga-PSMA-11 positron emission tomography enables the detection of primary, recurrent, and metastatic prostate cancer. Regional radiopharmaceutical uptake is generally evaluated in static images and quantified as standard uptake values (SUVs) for clinical decision-making. However, analysis of dynamic images characterizing both tracer uptake and pharmacokinetics may offer added insights into the underlying tissue pathophysiology. This study was undertaken to evaluate the suitability of various kinetic models for 68Ga-PSMA-11 PET analysis. Twenty-three lesions in 18 patients were included in a retrospective kinetic evaluation of 55-min dynamic 68Ga-PSMA-11 pre-prostatectomy PET scans from patients with biopsy-demonstrated intermediate- to high-risk prostate cancer. Three kinetic models-a reversible one-tissue compartment model, an irreversible two-tissue compartment model, and a reversible two-tissue compartment model, were evaluated for their goodness of fit to lesion and normal reference prostate time-activity curves. Kinetic parameters obtained through graphical analysis and tracer kinetic modeling techniques were compared for reference prostate tissue and lesion regions of interest.

RESULTS

Supported by goodness of fit and information loss criteria, the irreversible two-tissue compartment model optimally fit the time-activity curves. Lesions exhibited significant differences in kinetic rate constants (K1, k2, k3, Ki) and semiquantitative measures (SUV and %ID/kg) when compared with reference prostatic tissue. The two-tissue irreversible tracer kinetic model was consistently appropriate across prostatic zones.

CONCLUSIONS

An irreversible tracer kinetic model is appropriate for dynamic analysis of 68Ga-PSMA-11 PET images. Kinetic parameters estimated by Patlak graphical analysis or full compartmental analysis can distinguish tumor from normal prostate tissue.

Dose reduction in dynamic synaptic vesicle glycoprotein 2A PET imaging using artificial neural networks

Objective. Reducing dose in positron emission tomography (PET) imaging increases noise in reconstructed dynamic frames, which inevitably results in higher noise and possible bias in subsequently estimated images of kinetic parameters than those estimated in the standard dose case. We report the development of a spatiotemporal denoising technique for reduced-count dynamic frames through integrating a cascade artificial neural network (ANN) with the highly constrained back-projection (HYPR) scheme to improve low-dose parametric imaging.Approach. We implemented and assessed the proposed method using imaging data acquired with11C-UCB-J, a PET radioligand bound to synaptic vesicle glycoprotein 2A (SV2A) in the human brain. The patch-based ANN was trained with a reduced-count frame and its full-count correspondence of a subject and was used in cascade to process dynamic frames of other subjects to further take advantage of its denoising capability. The HYPR strategy was then applied to the spatial ANN processed image frames to make use of the temporal information from the entire dynamic scan.Main results. In all the testing subjects including healthy volunteers and Parkinson's disease patients, the proposed method reduced more noise while introducing minimal bias in dynamic frames and the resulting parametric images, as compared with conventional denoising methods.Significance. Achieving 80% noise reduction with a bias of -2% in dynamic frames, which translates into 75% and 70% of noise reduction in the tracer uptake (bias, -2%) and distribution volume (bias, -5%) images, the proposed ANN+HYPR technique demonstrates the denoising capability equivalent to a 11-fold dose increase for dynamic SV2A PET imaging with11C-UCB-J.

Impact of point-spread function reconstruction on dynamic and static 18F-DOPA PET/CT quantitative parameters in glioma

BACKGROUND

Quantification of dynamic and static parameters extracted from 3,4-dihydroxy-6-[¹⁸F]-fluoro-L-phenylalanine (¹⁸F-DOPA, FDOPA) positron emission tomography (PET)/computed tomography (CT) plays a critical role for glioma assessment. The objective of the present study was to investigate the impact of point-spread function (PSF) reconstruction on these quantitative parameters.

METHODS

Fourteen patients with untreated gliomas and investigated with FDOPA PET/CT were analyzed. The distribution of the 14 cases was as follows: 6 astrocytomas-isocitrate dehydrogenase-mutant; 2 oligodendrogliomas/1p19q-codeleted-isocitrate dehydrogenase-mutant; and 6 isocitrate dehydrogenase-wild-type glioblastomas. A 0-20-min dynamic images (8×15, 2×30, 2×60, and 3×300 s post-injection) and a 0-20-min static image were reconstructed with and without PSF. Tumoral volumes-of-interest were generated on all of the PET series and the background volumes-of-interest were generated on the 0-20-min static image with and without PSF. Static parameters (SUVmax and SUVmean) of the tumoral and the background volumes-of-interest and kinetic parameters (K1 and k2) of the tumoral volumes-of-interest extracted from using full kinetic analysis were provided. PSF and non-PSF quantitative parameters values were compared.

RESULTS

Thirty-three tumor volumes-of-interest and 14 background volumes-of-interest were analyzed. PSF images provided higher tumor SUVmax than non-PSF images for 23/33 VOIs [median SUVmax =3.0 (range, 1.4-10.2) with PSF vs. 2.7 (range, 1.4-9.1) without PSF; P<0.001] and higher tumor SUVmean for 13/33 volumes-of-interest [median SUVmean =2.0 (range, 0.8-7.6) with PSF vs. 2.0 (range, 0.8-7.4) without PSF; P=0.002]. K1 and k2 were significantly lower with PSF than without PSF [respectively median K1 =0.077 mL/ccm/min (range, 0.043-0.445 mL/ccm/min) with PSF vs. 0.101 mL/ccm/min (range, 0.055-0.578 mL/ccm/min) without PSF; P<0.001 and median k2 =0.070 min^-1 (range, 0.025-0.146 min^-1) with PSF vs. 0.081 min^-1 (range, 0.027-0.180 min^-1) without PSF; P<0.001]. Background SUVmax and SUVmean were statistically unaffected [respectively median SUVmax =1.7 (range, 1.3-2.0) with PSF vs. 1.7 (range, 1.3-1.9) without PSF; P=0.346 and median SUVmean =1.5 (range, 1.0-1.8) with PSF vs. 1.5 (range, 1.0-1.7) without PSF; P=0.371].

CONCLUSIONS

The present study confirms that PSF significantly increases tumor activity concentrations measured on PET images. PSF algorithms for quantitative PET/CT analysis should be used with caution, especially for quantification of kinetic parameters.

Additive Value of Dynamic FDOPA PET/CT for Glioma Grading

Purpose: The aim of this study was to assess the value of the FDOPA PET kinetic parameters extracted using full kinetic analysis for tumor grading with neuronavigation-guided biopsies as reference in patients with newly-diagnosed gliomas.

Methods: Fourteen patients with untreated gliomas were investigated. Twenty minutes of dynamic positron-emission tomography (PET) imaging and a 20-min static image 10 min after injection were reconstructed from a 40-min list-mode acquisition immediately after FDOPA injection. Tumors volume-of-interest (VOI) were generated based on the MRI-guided brain biopsies. Static parameters (TBRmax and TBRmean) and kinetic parameters [K1 and k2 using full kinetic analysis with the reversible single-tissue compartment model with blood volume parameter and the time-to-peak (TTP)] were extracted. Performances of each parameter for differentiating low-grade gliomas (LGG) from high-grade gliomas (HGG) were evaluated by receiver-operating characteristic analyses (area under the curve; AUC).

Results: Thirty-two tumoral VOI were analyzed. K1, k2, and TTP were significantly higher for HGG than for LGG (median K1-value = 0.124 vs. 0.074 ml/ccm/min, p = 0.025, median k2-value = 0.093 vs. 0.063 min⁻¹, p = 0.025, and median TTP-value = 10.0 vs. 15.0 min, p = 0.025). No significant difference was observed for the static parameters. The AUC for the kinetic parameters was higher than the AUC for the static parameters (respectively, AUC_K1 = 0.787, AUC_k2 = 0.785, AUC_TTP = 0.775, AUC_TBRmax = 0.551, AUC_TBRmean = 0.575), significantly compared to TBRmax (respectively, p = 0.001 for K1, p = 0.031 for k2, and p = 0.029 for TTP).

Conclusion: The present study suggests an additive value of FDOPA PET/CT kinetic parameters for newly-diagnosed gliomas grading.

Cross-validation of a non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography

Kinetic modeling of positron emission tomography (PET) data can assess index rate of uptake, metabolism and predict disease progression more accurately than conventional static PET. However, it requires knowledge of the time-course of the arterial blood radioactivity concentration, called the arterial input function (AIF). The gold standard to acquire the AIF is by invasive means. The purpose of this study was to validate a previously developed dual readout scintillating fiber-based non-invasive positron detector, hereinafter called non-invasive detector (NID), developed to determine the AIF for dynamic PET measured from the human radial artery. The NID consisted of a 3 m long plastic scintillating fiber with each end coupled to a 5 m long transmission fiber followed by a silicon photomultiplier. The scintillating fiber was enclosed inside the grooves of a plastic cylindrical shell. Two sets of experiments were performed to test the NID against a previously validated microfluidic positron detector. A closed-loop microfluidic system combined with a wrist phantom was used. During the first experiment, the three PET radioisotopes ¹⁸F, ¹¹C and ⁶⁸Ga were tested. After optimizing the detector, a second series of tests were performed using only ¹⁸F and ¹¹C. The maximum pulse amplitude to electronic noise ratio was 52 obtained with ¹¹C. Linear regressions showed a linear relation between the two detectors. These preliminary results show that the NID can accurately detect positrons from a patient's wrist and has the potential to non-invasively measure the AIF during a dynamic PET scan. The accuracy of these measurements needs to be determined.

Quantitative Evaluation of Tumor Early Response to a Vascular-Disrupting Agent with Dynamic PET

PURPOSE

The purpose of this study is to evaluate the early response of tumors to a vascular-disrupting agent (VDA) VEGF121/recombinant toxin gelonin (rGel) using dynamic [(18)F]FPPRGD2 positron emission tomography (PET) and kinetic parameter estimation.

PROCEDURES

Two tumor xenograft models: U87MG (highly vascularized) and A549 (moderately vascularized), were selected, and both were randomized into treatment and control groups. Sixty-minute dynamic PET scans with [(18)F]FPPRGD2 that targets to integrin αvβ3 were performed at days 0 (baseline), 1, and 3 since VEGF121/rGel treatment started. Dynamic PET-derived binding potential (BPND) and parametric maps were compared with tumor uptake (%ID/g) and the static PET image at 1 h after the tracer administration.

RESULTS

The growth of U87MG tumor was obviously delayed upon VEGF121/rGel treatment. A549 tumor was not responsive to the same treatment. BPND of treated U87MG tumors decreased significantly at day 1 (p < 0.05), and the difference was more significant at day 3 (p < 0.01), compared with the control group. However, the tracer uptake (%ID/g) derived from static images at 1-h time point did not show significant difference between the treated and control tumors until day 3. Little difference in tracer uptake (%ID/g) or BPND was found between treated and control A549 tumors. Considering the tracer retention in tumor and the slower clearance due to damaged tumor vasculature after treatment, BPND representing the actual specific binding portion appears to be more sensitive and accurate than the semiquantitative parameters (such as %ID/g) derived from static images to assess the early response of tumor to VDA treatment.

CONCLUSIONS

Quantitative analysis based on dynamic PET with [(18)F]FPPRGD2 shows advantages in distinguishing effective from ineffective treatment during the course of VEGF121/rGel therapy at early stage and is therefore more sensitive in assessing therapy response than static PET.

Kinetic modeling in PET imaging of hypoxia

Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia.