Pharmacokinetic modeling of a novel hypoxia PET tracer [18F]HX4 in patients with non-small cell lung cancer

Hypoxia-Targeted Dose Painting in Radiotherapy

Hypoxia (oxygen deprivation) occurs in most solid malignancies, albeit with considerable heterogeneity. Hypoxia is associated with an aggressive cancer phenotype by promotion of genomic instability, evasion of anti-cancer therapies including radiotherapy and enhancement of metastatic risk. Therefore, hypoxia results in poor cancer outcomes. Targeting hypoxia to improve cancer outcomes is an attractive therapeutic strategy. Hypoxia-targeted dose painting escalates radiotherapy dose to hypoxic sub-volumes, as quantified and spatially mapped using hypoxia imaging. This therapeutic approach could overcome hypoxia-induced radioresistance and improve patient outcomes without the need for hypoxia-targeted drugs. This article will review the premise and underpinning evidence for personalized hypoxia-targeted dose painting. It will present data on relevant hypoxia imaging biomarkers, highlight the challenges and potential benefit of this approach and provide recommendations for future research priorities in this field. Personalized hypoxia-based radiotherapy de-escalation strategies will also be addressed.

Advances in PET and MRI imaging of tumor hypoxia

Tumor hypoxia is a complex and evolving phenomenon both in time and space. Molecular imaging allows to approach these variations, but the tracers used have their own limitations. PET imaging has the disadvantage of low resolution and must take into account molecular biodistribution, but has the advantage of high targeting accuracy. The relationship between the signal in MRI imaging and oxygen is complex but hopefully it would lead to the detection of truly oxygen-depleted tissue. Different ways of imaging hypoxia are discussed in this review, with nuclear medicine tracers such as [¹⁸F]-FMISO, [¹⁸F]-FAZA, or [⁶⁴Cu]-ATSM but also with MRI techniques such as perfusion imaging, diffusion MRI or oxygen-enhanced MRI. Hypoxia is a pejorative factor regarding aggressiveness, tumor dissemination and resistance to treatments. Therefore, having accurate tools is particularly important.

Kinetic Evaluation of the Hypoxia Radiotracers [18F]FMISO and [18F]FAZA in Dogs with Spontaneous Tumors Using Dynamic PET/CT Imaging

Purpose

We evaluated the kinetics of the hypoxia PET radiotracers, [18F]fluoromisonidazole ([18F]FMISO) and [18F]fluoroazomycin-arabinoside ([18F]FAZA), for tumor hypoxia detection and to assess the correlation of hypoxic kinetic parameters with static imaging measures in canine spontaneous tumors.

Methods

Sixteen dogs with spontaneous tumors underwent a 150-min dynamic PET scan using either [18F]FMISO or [18F]FAZA. The maximum tumor-to-muscle ratio (TMR_max) > 1.4 on the last image frame was used as the standard threshold to determine tumor hypoxia. The tumor time-activity curves were analyzed using irreversible and reversible two-tissue compartment models and graphical methods. TMR_max was compared with radiotracer trapping rate (k ₃), influx rate (K _i), and distribution volume (V _T).

Results

Tumor hypoxia was detected in 7/8 tumors in the [18F]FMISO group and 4/8 tumors in the [18F]FAZA group. All hypoxic tumors were detected at > 120 min with [18F]FMISO and at > 60 min with [18F]FAZA. [18F]FAZA showed better fit with the reversible model. TMR_max was strongly correlated with the irreversible parameters (k ₃ and K _i) for [18F]FMISO at > 90 min and with the reversible parameter (V _T) for [18F]FAZA at > 120 min.

Conclusions

Our results showed that [18F]FAZA provided a promising alternative radiotracer to [18F]FMISO with detecting the presence of tumor hypoxia at an earlier time (60 min), consistent with its favorable faster kinetics. The strong correlation between TMR_max over the 90-150 min and 120-150 min timeframes with [18F]FMISO and [18F]FAZA, respectively, with kinetic parameters associated with tumor hypoxia for each radiotracer, suggests that a static scan measurement (TMR_max) is a good alternative to quantify tumor hypoxia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13139-022-00780-4.

New PET Tracers: Current Knowledge and Perspectives in Lung Cancer

PET/CT with the tracer 2-[¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG) has improved diagnostic imaging in cancer and is routinely used for diagnosing, staging and treatment planning in lung cancer patients. However, pitfalls of [¹⁸F]FDG-PET/CT limit the use in specific settings. Additionally, lung cancer is still the leading cause of cancer associated death and has high risk of recurrence after curative treatment. These circumstances have led to the continuous search for more sensitive and specific PET tracers to optimize lung cancer diagnosis, staging, treatment planning and evaluation. The objective of this review is to present and discuss current knowledge and perspectives of new PET tracers for use in lung cancer. A literature search was performed on PubMed and clinicaltrials.gov, limited to the past decade, excluding case reports, preclinical studies and studies on established tracers such as [¹⁸F]FDG and DOTATE. The most relevant papers from the search were evaluated. Several tracers have been developed targeting specific tumor characteristics and hallmarks of cancer. A small number of tracers have been studied extensively and evaluated head-to-head with [¹⁸F]FDG-PET/CT, whereas others need further investigation and validation in larger clinical trials. At this moment, none of the tracers can replace [¹⁸F]FDG-PET/CT. However, they might serve as supplementary imaging methods to provide more knowledge about biological tumor characteristics and visualize intra- and inter-tumoral heterogeneity.

Phantom Validation of a Conservation of Activity-Based Partial Volume Correction Method for Arterial Input Function in Dynamic PET Imaging

Dynamic PET (dPET) imaging can be utilized to perform kinetic modelling of various physiologic processes, which are exploited by the constantly expanding range of targeted radiopharmaceuticals. To date, dPET remains primarily in the research realm due to a number of technical challenges, not least of which is addressing partial volume effects (PVE) in the input function. We propose a series of equations for the correction of PVE in the input function and present the results of a validation study, based on a purpose built phantom. ¹⁸F-dPET experiments were performed using the phantom on a set of flow tubes representing large arteries, such as the aorta (1" 2.54 cm ID), down to smaller vessels, such as the iliac arteries and veins (1/4" 0.635 cm ID). When applied to the dPET experimental images, the PVE correction equations were able to successfully correct the image-derived input functions by as much as 59 ± 35% in the presence of background, which resulted in image-derived area under the curve (AUC) values within 8 ± 9% of ground truth AUC. The peak heights were similarly well corrected to within 9 ± 10% of the scaled DCE-CT curves. The same equations were then successfully applied to correct patient input functions in the aorta and internal iliac artery/vein. These straightforward algorithms can be applied to dPET images from any PET-CT scanner to restore the input function back to a more clinically representative value, without the need for high-end Time of Flight systems or Point Spread Function correction algorithms.

Principles of Tracer Kinetic Analysis in Oncology, Part I: Principles and Overview of Methodology

Learning Objectives: On successful completion of this activity, participants should be able to describe (1) describe principles of PET tracer kinetic analysis for oncologic applications; (2) list methods used for PET kinetic analysis for oncology; and (3) discuss application of kinetic modeling for cancer-specific diagnostic needs.Financial Disclosure: This work was supported by KL2 TR001879, R01 CA211337, R01 CA113941, R33 CA225310, Komen SAC130060, R50 CA211270, and K01 DA040023. Dr. Pantel is a consultant or advisor for Progenics and Blue Earth Diagnostics and is a meeting participant or lecturer for Blue Earth Diagnostics. Dr. Mankoff is on the scientific advisory boards of GE Healthcare, Philips Healthcare, Reflexion, and ImaginAb and is the owner of Trevarx; his wife is the chief executive officer of Trevarx. The authors of this article have indicated no other relevant relationships that could be perceived as a real or apparent conflict of interest.CME Credit: SNMMI is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing education for physicians. SNMMI designates each JNM continuing education article for a maximum of 2.0 AMA PRA Category 1 Credits. Physicians should claim only credit commensurate with the extent of their participation in the activity. For CE credit, SAM, and other credit types, participants can access this activity through the SNMMI website (http://www.snmmilearningcenter.org) through March 2025PET enables noninvasive imaging of regional in vivo cancer biology. By engineering a radiotracer to target specific biologic processes of relevance to cancer (e.g., cancer metabolism, blood flow, proliferation, and tumor receptor expression or ligand binding), PET can detect cancer spread, characterize the cancer phenotype, and assess its response to treatment. For example, imaging of glucose metabolism using the radiolabeled glucose analog ¹⁸F-FDG has widespread applications to all 3 of these tasks and plays an important role in cancer care. However, the current clinical practice of imaging at a single time point remote from tracer injection (i.e., static imaging) does not use all the information that PET cancer imaging can provide, especially to address questions beyond cancer detection. Reliance on tracer measures obtained only from static imaging may also lead to misleading results. In this 2-part continuing education paper, we describe the principles of tracer kinetic analysis for oncologic PET (part 1), followed by examples of specific implementations of kinetic analysis for cancer PET imaging that highlight the added benefits over static imaging (part 2). This review is designed to introduce nuclear medicine clinicians to basic concepts of kinetic analysis in oncologic imaging, with a goal of illustrating how kinetic analysis can augment our understanding of in vivo cancer biology, improve our approach to clinical decision making, and guide the interpretation of quantitative measures derived from static images.

Non-invasive imaging prediction of tumor hypoxia: A novel developed and externally validated CT and FDG-PET-based radiomic signatures

BACKGROUND

Tumor hypoxia increases resistance to radiotherapy and systemic therapy. Our aim was to develop and validate a disease-agnostic and disease-specific CT (+FDG-PET) based radiomics hypoxia classification signature.

MATERIAL AND METHODS

A total of 808 patients with imaging data were included: N = 100 training/N = 183 external validation cases for a disease-agnostic CT hypoxia classification signature, N = 76 training/N = 39 validation cases for the H&N CT signature and N = 62 training/N = 36 validation cases for the Lung CT signature. The primary gross tumor volumes (GTV) were manually defined by experts on CT. In order to dichotomize between hypoxic/well-oxygenated tumors a threshold of 20% was used for the [¹⁸F]-HX4-derived hypoxic fractions (HF). A random forest (RF)-based machine-learning classifier/regressor was trained to classify patients as hypoxia-positive/ negative based on radiomic features.

RESULTS

A 11 feature "disease-agnostic CT model" reached AUC's of respectively 0.78 (95% confidence interval [CI], 0.62-0.94), 0.82 (95% CI, 0.67-0.96) and 0.78 (95% CI, 0.67-0.89) in three external validation datasets. A "disease-agnostic FDG-PET model" reached an AUC of 0.73 (0.95% CI, 0.49-0.97) in validation by combining 5 features. The highest "lung-specific CT model" reached an AUC of 0.80 (0.95% CI, 0.65-0.95) in validation with 4 CT features, while the "H&N-specific CT model" reached an AUC of 0.84 (0.95% CI, 0.64-1.00) in validation with 15 CT features. A tumor volume-alone model was unable to significantly classify patients as hypoxia-positive/ negative. A significant survival split (P = 0.037) was found between CT-classified hypoxia strata in an external H&N cohort (n = 517), while 117 significant hypoxia gene-CT signature feature associations were found in an external lung cohort (n = 80).

CONCLUSION

The disease-specific radiomics signatures perform better than the disease agnostic ones. By identifying hypoxic patients our signatures have the potential to enrich interventional hypoxia-targeting trials.

E. coli nitroreductase NfsA is a reporter gene for non-invasive PET imaging in cancer gene therapy applications

The use of reporter genes to non-invasively image molecular processes inside cells has significant translational potential, particularly in the context of systemically administered gene therapy vectors and adoptively administered cells such as immune or stem cell based therapies. Bacterial nitroreductase enzymes possess ideal properties for reporter gene imaging applications, being of non-human origin and possessing the ability to metabolize a range of clinically relevant nitro(hetero)cyclic substrates. Methods: A library of eleven Escherichia coli nitroreductase candidates were screened for the ability to efficiently metabolize 2-nitroimidazole based positron emission tomography (PET) probes originally developed as radiotracers for hypoxic cell imaging. Several complementary methods were utilized to detect formation of cell-entrapped metabolites, including various in vitro and in vivo models to establish the capacity of the 2-nitroimidazole PET agent EF5 to quantify expression of a nitroreductase candidate. Proof-of-principle PET imaging studies were successfully conducted using ¹⁸F-HX4. Results: Recombinant enzyme kinetics, bacterial SOS reporter assays, anti-proliferative assays and flow cytometry approaches collectively identified the major oxygen-insensitive nitroreductase NfsA from E. coli (NfsA_Ec) as the most promising nitroreductase reporter gene. Cells expressing NfsA_Ec were demonstrably labelled with the imaging agent EF5 in a manner that was quantitatively superior to hypoxia, in monolayers (2D), multicellular layers (3D), and in human tumor xenograft models. EF5 retention correlated with NfsA_Ec positive cell density over a range of EF5 concentrations in 3D in vitro models and in xenografts in vivo and was predictive of in vivo anti-tumor activity of the cytotoxic prodrug PR-104. Following PET imaging with ¹⁸F-HX4, a significantly higher tumor-to-blood ratio was observed in two xenograft models for NfsA_Ec expressing tumors compared to the parental tumors thereof, providing verification of this reporter gene imaging approach. Conclusion: This study establishes that the bacterial nitroreductase NfsA_Ec can be utilized as an imaging capable reporter gene, with the ability to metabolize and trap 2-nitroimidazole PET imaging agents for non-invasive imaging of gene expression.

Kinetic modeling and parametric imaging with dynamic PET for oncological applications: general considerations, current clinical applications, and future perspectives

Dynamic PET (dPET) studies have been used until now primarily within research purposes. Although it is generally accepted that the information provided by dPET is superior to that of conventional static PET acquisitions acquired usually 60 min post injection of the radiotracer, the duration of dynamic protocols, the limited axial field of view (FOV) of current generation clinical PET systems covering a relatively small axial extent of the human body for a dynamic measurement, and the complexity of data evaluation have hampered its implementation into clinical routine. However, the development of new-generation PET/CT scanners with an extended FOV as well as of more sophisticated evaluation software packages that offer better segmentation algorithms, automatic retrieval of the arterial input function, and automatic calculation of parametric imaging, in combination with dedicated shorter dynamic protocols, will facilitate the wider use of dPET. This is expected to aid in oncological diagnostics and therapy assessment. The aim of this review is to present some general considerations about dPET analysis in oncology by means of kinetic modeling, based on compartmental and noncompartmental approaches, and parametric imaging. Moreover, the current clinical applications and future perspectives of the modality are outlined.

Approaches to PET Imaging of Glioblastoma

Glioblastoma multiforme (GBM) is the deadliest type of brain tumor, affecting approximately three in 100,000 adults annually. Positron emission tomography (PET) imaging provides an important non-invasive method of measuring biochemically specific targets at GBM lesions. These powerful data can characterize tumors, predict treatment effectiveness, and monitor treatment. This review will discuss the PET imaging agents that have already been evaluated in GBM patients so far, and new imaging targets with promise for future use. Previously used PET imaging agents include the tracers for markers of proliferation ([11C]methionine; [18F]fluoro-ethyl-L-tyrosine, [18F]Fluorodopa,[18F]fluoro-thymidine, and [18F]clofarabine), hypoxia sensing ([18F]FMISO, [18F]FET-NIM, [18F]EF5, [18F]HX4, and [64Cu]ATSM), and ligands for inflammation. As cancer therapeutics evolve toward personalized medicine and therapies centered on tumor biomarkers, the development of complimentary selective PET agents can dramatically enhance these efforts. Newer biomarkers for GBM PET imaging are discussed, with some already in use for PET imaging other cancers and neurological disorders. These targets include Sigma 1, Sigma 2, programmed death ligand 1, poly-ADP-ribose polymerase, and isocitrate dehydrogenase. For GBM, these imaging agents come with additional considerations such as blood-brain barrier penetration, quantitative modeling approaches, and nonspecific binding.

Hypoxia and hypoxia response-associated molecular markers in esophageal cancer: A systematic review

PURPOSE

In this systematic review, the existing evidence of available hypoxia-associated molecular response biomarkers in esophageal cancer (EC) patients is summarized and set into the context of the role of hypoxia in the prediction of esophageal cancer, treatment response and treatment outcome.

METHODS

A systematic literature search was performed in Web of Science, MEDLINE, and PubMed databases using the keywords: hypoxia, esophagus, cancer, treatment outcome and treatment response. Eligible publications were independently evaluated by two reviewers. In total, 22 out of 419 records were included for systematic review. The described search strategy was applied weekly, with the last update being performed on April 3rd, 2017.

RESULTS

In esophageal cancer, several (non-)invasive biomarkers for hypoxia could be identified. Independent prognostic factors for treatment response include HIF-1α, CA IX, GLUT-1 overexpression and elevated uptake of the PET-tracer ¹⁸F-fluoroerythronitroimidazole (¹⁸F-FETNIM). Hypoxia-associated molecular responses represents a clinically relevant phenomenon in esophageal cancer and detection of elevated levels of hypoxia-associated biomarkers and tends to be associated with poor treatment outcome (i.e., overall survival, disease-free survival, complete response and local control).

CONCLUSION

Evaluation of tumor micro-environmental conditions, such as intratumoral hypoxia, is important to predict treatment outcome and efficacy. Promising non-invasive imaging-techniques have been suggested to assess tumor hypoxia and hypoxia-associated molecular responses. However, extensive validation in EC is lacking. Hypoxia-associated markers that are independent prognostic factors could potentially provide targets for novel treatment strategies to improve treatment outcome. For personalized hypoxia-guided treatment, safe and reliable makers for tumor hypoxia are needed to select suitable patients.