Double-input compartmental modeling and spectral analysis for the quantification of positron emission tomography data in oncology

Spatial heterogeneity of radiolabeled choline positron emission tomography in tumors of patients with non-small cell lung cancer: first-in-patient evaluation of [18F]fluoromethyl-(1,2-2H4)-choline

Purpose: The spatio-molecular distribution of choline and its metabolites in tumors is highly heterogeneous. Due to regulation of choline metabolism by hypoxic transcriptional signaling and other survival factors, we envisage that detection of such heterogeneity in patient tumors could provide the basis for advanced localized therapy. However, non-invasive methods to assess this phenomenon in patients are limited. We investigated such heterogeneity in Non-Small Cell Lung Cancer (NSCLC) with [18F]fluoromethyl-(1,2-2H4) choline ([18F]D4-FCH) and positron emission tomography/computed tomography (PET/CT). Experimental design: [18F]D4-FCH (300.5±72.9MBq [147.60-363.6MBq]) was administered intravenously to 17 newly diagnosed NSCLC patients. PET/CT scans were acquired concurrently with radioactive blood sampling to permit mathematical modelling of blood-tissue transcellular rate constants. Comparisons were made with biopsy-derived choline kinase-α (CHKα) expression and diagnostic [18F]fluorodeoxyglucose ([18F]FDG) scans. Results: Oxidation of [18F]D4-FCH to [18F]D4-fluorobetaine was suppressed (48.58±0.31% parent at 60 min) likely due to the deuterium isotope effect embodied within the design of the radiotracer. Early (5 min) and late (60 min) images showed specific uptake of tracer in all 51 lesions (tumors, lymph nodes and metastases) from 17 patients analyzed. [18F]D4-FCH-derived uptake (SUV60max) in index primary lesions (n=17) ranged between 2.87-10.13; lower than that of [18F]FDG PET [6.89-22.64]. Mathematical modelling demonstrated net irreversible uptake of [18F]D4-FCH at steady-state, and parametric mapping of the entire tumor showed large intratumorally heterogeneity in radiotracer retention, which is likely to have influenced correlations with biopsy-derived CHKα expression. Conclusions: [18F]D4-FCH is detectable in NSCLC with large intratumorally heterogeneity, which could be exploited in the future for targeting localized therapy.

Does whole-body Patlak 18F-FDG PET imaging improve lesion detectability in clinical oncology?

PURPOSE

Single-pass whole-body (WB) ¹⁸F-FDG PET/CT imaging is routinely employed for the clinical assessment of malignant, infectious, and inflammatory diseases. Our aim in this study is the systematic clinical assessment of lesion detectability in multi-pass WB parametric imaging enabling direct imaging of the highly quantitative ¹⁸F-FDG influx rate constant K_i, as a complement to standard-of-care standardized uptake value (SUV) imaging for a range of oncologic studies.

METHODS

We compared SUV and K_i images of 18 clinical studies of different oncologic indications (lesion characterization and staging) including standard-of-care SUV and dynamic WB PET protocols in a single session. The comparison involved both the visual assessment and the quantitative evaluation of SUV_mean, SUV_max, K_imean, K_imax, tumor-to-background ratio (TBR_SUV, TBR_Ki), and contrast-to-noise ratio (CNR_SUV, CNR_Ki) quality metrics.

RESULTS

Overall, both methods provided good-quality images suitable for visual interpretation. A total of 118 lesions were detected, including 40 malignant (proven) and 78 malignant (unproven) lesions. Of those, 111 were detected on SUV and 108 on K_i images. One proven malignant lesion was detected only on K_i images whereas none of the proven malignant lesions was visible only on SUV images. The proven malignant lesions had overall higher K_i TBR and CNR scores. One unproven lesion, which was later confirmed as benign, was detected only on the SUV images (false-positive). Overall, our results from 40 proven malignant lesions suggested improved sensitivity (from 92.5 to 95%) and accuracy (from 90.24 to 95.12%) and potentially enhanced specificity with K_i over SUV imaging.

CONCLUSION

Oncologic WB Patlak K_i imaging may achieve equivalent or superior lesion detectability with reduced false-positive rates when complementing standard-of-care SUV imaging.

KEY POINTS

• The whole-body spatio-temporal distribution of ¹⁸ F-FDG uptake may reveal clinically useful information on oncologic diseases to complement the standard-of-care SUV metric. • Parametric imaging resulted in less false-positive indications of non-specific ¹⁸ F-FDG uptake relative to SUV. • Parametric imaging may achieve equivalent or superior ¹⁸ F-FDG lesion detectability than standard-of-care SUV imaging in oncology.

Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications

In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.

Imaging tumor metabolism using positron emission tomography

Positron emission tomography (PET) is an extraordinarily sensitive clinical imaging modality for interrogating tumor metabolism. Radiolabeled PET substrates can be traced at subphysiological concentrations, allowing noninvasive imaging of metabolism and intratumoral heterogeneity in systems ranging from advanced cancer models to patients in the clinic. There are a wide range of novel and more established PET radiotracers, which can be used to investigate various aspects of the tumor, including carbohydrate, amino acid, and fatty acid metabolism. In this review, we briefly discuss the more established metabolic tracers and describe recent work on the development of new tracers. Some of the unanswered questions in tumor metabolism are considered alongside new technical developments, such as combined PET/magnetic resonance imaging scanners, which could provide new imaging solutions to some of the outstanding diagnostic challenges facing modern cancer medicine.

Assessment of simplified methods to measure 18F-FLT uptake changes in EGFR-mutated non-small cell lung cancer patients undergoing EGFR tyrosine kinase inhibitor treatment

3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) PET/CT provides a noninvasive assessment of proliferation and, as such, could be a valuable imaging biomarker in oncology. The aim of the present study was to assess the validity of simplified quantitative parameters of (18)F-FLT uptake in non-small cell lung cancer (NSCLC) patients before and after the start of treatment with a tyrosine kinase inhibitor (TKI).

METHODS

Ten patients with metastatic NSCLC harboring an activating epidermal growth factor receptor mutation were included in this prospective observational study. Patients underwent (15)O-H2O and (18)F-FLT PET/CT scanning on 3 separate occasions: within 7 d before treatment, and 7 and 28 d after the first therapeutic dose of a TKI (gefitinib or erlotinib). Dynamic scans were acquired and venous blood samples were collected during the (18)F-FLT scan to measure parent fraction and plasma and whole-blood radioactivity concentrations. Simplified measures (standardized uptake value [SUV] and tumor-to-blood ratio [TBR]) were correlated with fully quantitative measures derived from kinetic modeling.

RESULTS

Twenty-nine of thirty (18)F-FLT PET/CT scans were evaluable. According to the Akaike criterion, a reversible 2-tissue model with 4 rate constants and blood volume parameter was preferred in 84% of cases. Relative therapy-induced changes in SUV and TBR correlated with those derived from kinetic analyses (r(2) = 0.83-0.97, P < 0.001, slope = 0.72-1.12). (18)F-FLT uptake significantly decreased at 7 and 28 d after the start of treatment compared with baseline (P < 0.01). Changes in (18)F-FLT uptake were not correlated with changes in perfusion, as measured using (15)O-H2O.

CONCLUSION

SUV and TBR could both be used as surrogate simplified measures to assess changes in (18)F-FLT uptake in NSCLC patients treated with a TKI, at the cost of a small underestimation in uptake changes or the need for a blood sample and metabolite measurement, respectively.

A novel description of FDG excretion in the renal system: application to metformin-treated models

This paper introduces a novel compartmental model describing the excretion of 18F-fluoro-deoxyglucose (FDG) in the renal system and a numerical method based on the maximum likelihood for its reduction. This approach accounts for variations in FDG concentration due to water re-absorption in renal tubules and the increase of the bladder's volume during the FDG excretion process. From the computational viewpoint, the reconstruction of the tracer kinetic parameters is obtained by solving the maximum likelihood problem iteratively, using a non-stationary, steepest descent approach that explicitly accounts for the Poisson nature of nuclear medicine data. The reliability of the method is validated against two sets of synthetic data realized according to realistic conditions. Finally we applied this model to describe FDG excretion in the case of animal models treated with metformin. In particular we show that our approach allows the quantitative estimation of the reduction of FDG de-phosphorylation induced by metformin.

SAKE: a new quantification tool for positron emission tomography studies

In dynamic positron emission tomography (PET) studies, spectral analysis (SA) refers to a data-driven quantification method, based on a single-input single-output model for which the transfer function is described by a sum of exponential terms. SA allows to quantify numerosities, amplitudes and eigenvalues of the transfer function allowing, in this way, to separate kinetic components of the tissue tracer activity with minimal model assumptions. The SA model can be solved with a linear estimator alone or with numerical filters, resulting in different types of SA approaches. Once estimated the number, amplitudes and eigenvalues of the transfer function, one can distinguish the presence in the system of irreversible and/or reversible components as well as derive parameters of physiological significance. These characteristics make it an appealing alternative method to compartmental models which are widely used for the quantitative analysis of dynamic studies acquired with PET. However, despite its applicability to a large number of PET tracers, its implementation is not straightforward and its utilization in the nuclear medicine community has been limited especially by the lack of an user-friendly software application. In this paper we proposed SAKE, a computer program for the quantitative analysis of PET data through the main SA methods. SAKE offers a unified pipeline of analysis usable also by people with limited computer knowledge but with high interest in SA.

Introduction to the analysis of PET data in oncology

Several reviews on specific topics related to positron emission tomography (PET) ranging in complexity from introductory to highly technical have already been published. This introduction to the analysis of PET data was written as a simple guide of the different phases of analysis of a given PET dataset, from acquisition to preprocessing, to the final data analysis. Although sometimes issues specific to PET in neuroimaging will be mentioned for comparison, most of the examples and applications provided will refer to oncology. Due to the limitations of space we couldn't address each issue comprehensively but, rather, we provided a general overview of each topic together with the references that the interested reader should consult. We will assume a familiarity with the basic principles of PET imaging.

Modeling and Simulation of 4D PET-CT and PET-MR Images

The driving force in the research and development of new hybrid PET-CT/MR imaging scanners is the production of images with optimum quality, accuracy, and resolution. However, the acquisition process is limited by several factors. Key issues are the respiratory and cardiac motion artifacts that occur during an imaging session. In this article the necessary tools for modeling and simulation of realistic high-resolution four-dimensional PET-CT and PET-MR imaging data are described. Beyond the need for four-dimensional simulations, accurate modeling of the acquisition process can be included within the reconstruction algorithms assisting in the improvement of image quality and accuracy of estimation of physiologic parameters from four-dimensional hybrid PET imaging.

PET imaging: implications for the future of therapy monitoring with PET/CT in oncology

Among the methods based on molecular imaging, the measure of the tracer uptake variation between a baseline and follow-up scan with the SUV and [(18)F]FDG-PET/CT is a very powerful tool for assessing response to treatment in oncology. However, the development of new targeted therapeutics and tissue pharmacokinetic evaluation of existing ones are increasingly requiring therapy monitoring with alternative tracers and indicators. In parallel, the potential predictive and prognostic value of other image-derived parameters, such as tumour volume and textural features, relating to tumoral heterogeneity, has recently emerged from several works.