Intraperitoneal Delivery of Iopamidol to Assess Extracellular pH of Orthotopic Pancreatic Tumor Model by CEST-MRI.

The extracellular pH (pHe) of solid tumors is often acidic, as a consequence of the Warburg effect, and an altered metabolic state is often associated with malignancy. It has been shown that acidosis can promote tumor progression; thus, many therapeutic strategies have been adopted against tumor metabolism; one of these involves alkalinization therapies to raise tumor pH to inhibit tumor progression, improve immune surveillance, and overcome resistance to chemotherapies. Chemical exchange saturation transfer-magnetic resonance imaging (CEST-MRI) is a noninvasive technique that can measure pH in vivo using pH-sensitive contrast agents. Iopamidol, an iodinated contrast agent, clinically used for computed tomography (CT), contains amide group protons with pH-dependent exchange rates that can reveal the pHe of the tumor microenvironment. In this study, we optimized intraperitoneal (IP) delivery of iopamidol to facilitate longitudinal assessments of orthotopic pancreatic tumor pHe by CEST-MRI. Following IV-infusion and IP-bolus injections, we compared the two protocols for assessing tumor pH. Time-resolved CT imaging was used to evaluate the uptake of iopamidol in the tumor, revealing that IP-bolus delivered a high amount of contrast agent 40 min postinjection, which was similar to the amounts reached with the IV-infusion protocol. As expected, both IP and IV injection protocols produced comparable measurements of tumor pHe, showing no statistically significant difference between groups (p=0.16). In addition, we showed the ability to conduct longitudinal monitoring of tumor pHe using CEST-MRI with the IP injection protocol, revealing a statistically significant increase in tumor pHe following bicarbonate administration (p < 0.001). In conclusion, this study shows the capability to measure pHe using an IP delivery of iopamidol into orthotopic pancreatic tumors, which is important to conduct longitudinal studies.

Noise-Based Image Harmonization Significantly Increases Repeatability and Reproducibility of Radiomics Features in PET Images: A Phantom Study.

For multicenter clinical studies, characterizing the robustness of image-derived radiomics features is essential. Features calculated on PET images have been shown to be very sensitive to image noise. The purpose of this work was to investigate the efficacy of a relatively simple harmonization strategy on feature robustness and agreement. A purpose-built texture pattern phantom was scanned on 10 different PET scanners in 7 institutions with various different image acquisition and reconstruction protocols. An image harmonization technique based on equalizing a contrast-to-noise ratio was employed to generate a "harmonized" alongside a "standard" dataset for a reproducibility study. In addition, a repeatability study was performed with images from a single PET scanner of variable image noise, varying the binning time of the reconstruction. Feature agreement was measured using the intraclass correlation coefficient (ICC). In the repeatability study, 81/93 features had a lower ICC on the images with the highest image noise as compared to the images with the lowest image noise. Using the harmonized dataset significantly improved the feature agreement for five of the six investigated feature classes over the standard dataset. For three feature classes, high feature agreement corresponded with higher sensitivity to the different patterns, suggesting a way to select suitable features for predictive models.

In Vivo Imaging of Rat Vascularity with FDG-Labeled Erythrocytes.

Microvascular disease is frequently found in major pathologies affecting vital organs, such as the brain, heart, and kidneys. While imaging modalities, such as ultrasound, computed tomography, single photon emission computed tomography, and magnetic resonance imaging, are widely used to visualize vascular abnormalities, the ability to non-invasively assess an organ's total vasculature, including microvasculature, is often limited or cumbersome. Previously, we have demonstrated proof of concept that non-invasive imaging of the total mouse vasculature can be achieved with 18F-fluorodeoxyglucose (18F-FDG)-labeled human erythrocytes and positron emission tomography/computerized tomography (PET/CT). In this work, we demonstrate that changes in the total vascular volume of the brain and left ventricular myocardium of normal rats can be seen after pharmacological vasodilation using 18F-FDG-labeled rat red blood cells (FDG RBCs) and microPET/CT imaging. FDG RBC PET imaging was also used to approximate the location of myocardial injury in a surgical myocardial infarction rat model. Finally, we show that FDG RBC PET imaging can detect relative differences in the degree of drug-induced intra-myocardial vasodilation between diabetic rats and normal controls. This FDG-labeled RBC PET imaging technique may thus be useful for assessing microvascular disease pathologies and characterizing pharmacological responses in the vascular bed of interest.

Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma.

Rationale: Hypoxic regions (habitats) within tumors are heterogeneously distributed and can be widely variant. Hypoxic habitats are generally pan-therapy resistant. For this reason, hypoxia-activated prodrugs (HAPs) have been developed to target these resistant volumes. The HAP evofosfamide (TH-302) has shown promise in preclinical and early clinical trials of sarcoma. However, in a phase III clinical trial of non-resectable soft tissue sarcomas, TH-302 did not improve survival in combination with doxorubicin (Dox), possibly due to a lack of patient stratification based on hypoxic status. Therefore, we used magnetic resonance imaging (MRI) to identify hypoxic habitats and non-invasively follow therapies response in sarcoma mouse models. Methods: We developed deep-learning (DL) models to identify hypoxia, using multiparametric MRI and co-registered histology, and monitored response to TH-302 in a patient-derived xenograft (PDX) of rhabdomyosarcoma and a syngeneic model of fibrosarcoma (radiation-induced fibrosarcoma, RIF-1). Results: A DL convolutional neural network showed strong correlations (>0.76) between the true hypoxia fraction in histology and the predicted hypoxia fraction in multiparametric MRI. TH-302 monotherapy or in combination with Dox delayed tumor growth and increased survival in the hypoxic PDX model (p<0.05), but not in the RIF-1 model, which had a lower volume of hypoxic habitats. Control studies showed that RIF-1 resistance was due to hypoxia and not other causes. Notably, PDX tumors developed resistance to TH-302 under prolonged treatment that was not due to a reduction in hypoxic volumes. Conclusion: Artificial intelligence analysis of pre-therapy MR images can predict hypoxia and subsequent response to HAPs. This approach can be used to monitor therapy response and adapt schedules to forestall the emergence of resistance.

Lipophilicity Determines Routes of Uptake and Clearance, and Toxicity of an Alpha-Particle-Emitting Peptide Receptor Radiotherapy.

Lipophilicity is explored in the biodistribution (BD), pharmacokinetics (PK), radiation dosimetry (RD), and toxicity of an internally administered targeted alpha-particle therapy (TAT) under development for the treatment of metastatic melanoma. The TAT conjugate is comprised of the chelator DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate), conjugated to melanocortin receptor 1 specific peptidic ligand (MC1RL) using a linker moiety and chelation of the 225Ac radiometal. A set of conjugates were prepared with a range of lipophilicities (log D 7.4 values) by varying the chemical properties of the linker. Reported are the observations that higher log D 7.4 values are associated with decreased kidney uptake, decreased absorbed radiation dose, and decreased kidney toxicity of the TAT, and the inverse is observed for lower log D 7.4 values. Animals administered TATs with lower lipophilicities exhibited acute nephropathy and death, whereas animals administered the highest activity TATs with higher lipophilicities lived for the duration of the 7 month study and exhibited chronic progressive nephropathy. Changes in TAT lipophilicity were not associated with changes in liver uptake, dose, or toxicity. Significant observations include that lipophilicity correlates with kidney BD, the kidney-to-liver BD ratio, and weight loss and that blood urea nitrogen (BUN) levels correlated with kidney uptake. Furthermore, BUN was identified as having higher sensitivity and specificity of detection of kidney pathology, and the liver enzyme alkaline phosphatase (ALKP) had high sensitivity and specificity for detection of liver damage associated with the TAT. These findings suggest that tuning radiopharmaceutical lipophilicity can effectively modulate the level of kidney uptake to reduce morbidity and improve both safety and efficacy.

Preclinical evaluation of [225Ac]Ac-DOTA-TATE for treatment of lung neuroendocrine neoplasms.

PURPOSE: There is significant interest in the development of targeted alpha-particle therapies (TATs) for treatment of solid tumors. The metal chelator-peptide conjugate, DOTA-TATE, loaded with the ß-particle emitting radionuclide 177Lu ([177Lu]Lu-DOTA-TATE) is now standard care for neuroendocrine tumors that express the somatostatin receptor 2 (SSTR2) target. A recent clinical study demonstrated efficacy of the corresponding [225Ac]Ac-DOTA-TATE in patients that were refractory to [177Lu]Lu-DOTA-TATE. Herein, we report the radiosynthesis, toxicity, biodistribution (BD), radiation dosimetry (RD), and efficacy of [225Ac]Ac-DOTA-TATE in small animal models of lung neuroendocrine neoplasms (NENs). METHODS: [225Ac]Ac-DOTA-TATE was synthesized and characterized for radiochemical yield, purity and stability. Non-tumor-bearing BALB/c mice were tested for toxicity and BD. Efficacy was determined by single intravenous injection of [225Ac]Ac-DOTA-TATE into SCID mice-bearing human SSTR2 positive H727 and H69 lung NENs. RD was calculated using the BD data. RESULTS: [225Ac]Ac-DOTA-TATE was synthesized with 98% yield, 99.8% purity, and displayed 97% stability after 2 days incubation in human serum at 37 °C. All animals in the toxicity study appeared healthy 5 months post injection with no indications of toxicity, except that animals that received ≥111 kBq of [225Ac]Ac-DOTA-TATE had chronic progressive nephropathy. BD studies revealed that the primary route of elimination is by the renal route. RD calculations determined pharmacokinetics parameters and absorbed α-emission dosages from 225Ac and its daughters. For both tumor models, a significant tumor growth delay and time to experimental endpoint were observed following a single administration of [225Ac]Ac-DOTA-TATE relative to controls. CONCLUSIONS: These results suggest significant potential for the clinical translation of [225Ac]Ac-DOTA-TATE for lung NENs.

Biodistribution and Multicompartment Pharmacokinetic Analysis of a Targeted α Particle Therapy.

Targeted α particle therapy (TAT) is ideal for treating disease while minimizing damage to surrounding nontargeted tissues due to short path length and high linear energy transfer (LET). We developed a TAT for metastatic uveal melanoma, targeting the melanocortin-1 receptor (MC1R), which is expressed in 94% of uveal melanomas. Two versions of the therapy are being investigated: 225Ac-DOTA-Ahx-MC1RL (225Ac-Ahx) and 225Ac-DOTA-di-d-Glu-MC1RL (225Ac-di-d-Glu). The biodistribution (BD) from each was studied and a multicompartment pharmacokinetic (PK) model was developed to describe drug distribution rates. Two groups of 16 severe combined immunodeficient (SCID) mice bearing high MC1R expressing tumors were intravenously injected with 225Ac-Ahx or 225Ac-di-d-Glu. After injection, four groups (n = 4) were euthanized at 24, 96, 144, and 288 h time points for each cohort. Tumors and 13 other organs were harvested at each time point. Isomeric γ spectra were measured in tissue samples using a scintillation γ detector and converted to α activity using factors for γ ray abundance per α decay. Time activity curves were calculated for each organ. A five-compartment PK model was built with the following compartments: blood, tumor, normal tissue, kidney, and liver. This model is characterized by a system of five ordinary differential equations using mass action kinetics, which describe uptake, intercompartmental transitions, and clearance rates. The ordinary differential equations were simultaneously solved and fit to experimental data using a genetic algorithm for optimization. The BD data show that both compounds have minimal distribution to organs at risk other than the kidney and liver. The PK parameter estimates had less than 5% error. From these data, 225Ac-Ahx showed larger and faster uptake in the liver. Both compounds had comparable uptake and clearance rates for other compartments. The BD and PK behavior for two targeted radiopharmaceuticals were investigated. The PK model fit the experimental data and provided insight into the kinetics of the compounds systematically.

Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images.

Quantitative imaging biomarkers (QIBs) provide medical image-derived intensity, texture, shape, and size features that may help characterize cancerous tumors and predict clinical outcomes. Successful clinical translation of QIBs depends on the robustness of their measurements. Biomarkers derived from positron emission tomography images are prone to measurement errors owing to differences in image processing factors such as the tumor segmentation method used to define volumes of interest over which to calculate QIBs. We illustrate a new Bayesian statistical approach to characterize the robustness of QIBs to different processing factors. Study data consist of 22 QIBs measured on 47 head and neck tumors in 10 positron emission tomography/computed tomography scans segmented manually and with semiautomated methods used by 7 institutional members of the NCI Quantitative Imaging Network. QIB performance is estimated and compared across institutions with respect to measurement errors and power to recover statistical associations with clinical outcomes. Analysis findings summarize the performance impact of different segmentation methods used by Quantitative Imaging Network members. Robustness of some advanced biomarkers was found to be similar to conventional markers, such as maximum standardized uptake value. Such similarities support current pursuits to better characterize disease and predict outcomes by developing QIBs that use more imaging information and are robust to different processing factors. Nevertheless, to ensure reproducibility of QIB measurements and measures of association with clinical outcomes, errors owing to segmentation methods need to be reduced.

Development of Targeted Alpha Particle Therapy for Solid Tumors.

Targeted alpha-particle therapy (TAT) aims to selectively deliver radionuclides emitting α-particles (cytotoxic payload) to tumors by chelation to monoclonal antibodies, peptides or small molecules that recognize tumor-associated antigens or cell-surface receptors. Because of the high linear energy transfer (LET) and short range of alpha (α) particles in tissue, cancer cells can be significantly damaged while causing minimal toxicity to surrounding healthy cells. Recent clinical studies have demonstrated the remarkable efficacy of TAT in the treatment of metastatic, castration-resistant prostate cancer. In this comprehensive review, we discuss the current consensus regarding the properties of the α-particle-emitting radionuclides that are potentially relevant for use in the clinic; the TAT-mediated mechanisms responsible for cell death; the different classes of targeting moieties and radiometal chelators available for TAT development; current approaches to calculating radiation dosimetry for TATs; and lead optimization via medicinal chemistry to improve the TAT radiopharmaceutical properties. We have also summarized the use of TATs in pre-clinical and clinical studies to date.

A Monte Carlo Method for Determining the Response Relationship between Two Commonly Used Detectors to Indirectly Measure Alpha Particle Radiation Activity.

Using targeted ligands to deliver alpha-emitting radionuclides directly to tumor cells has become a promising therapeutic strategy. To calculate the radiation dose to patients, activities of parent and daughter radionuclides must be measured. Scintillation detectors can be used to quantify these activities; however, activities found in pre-clinical and clinical studies can exceed their optimal performance range. Therefore, a method of correcting scintillation detector measurements at higher activities was developed using Monte Carlo modeling. Because there are currently no National Institute of Standards and Technology traceable Actinium-225 (225Ac) standards available, a well-type ionization chamber was used to measure 70.3 ± 7.0, 144.3 ± 14.4, 222.0 ± 22.2, 299.7 ± 30.0, 370.0 ± 37.0, and 447.7 ± 44.7 kBq samples of 225Ac obtained from Oak Ridge National Lab. Samples were then placed in a well-type NaI(Tl) scintillation detector and spectra were obtained. Alpha particle activity for each species was calculated using gamma abundance per alpha decay. MCNP6 Monte Carlo software was used to simulate the 4π-geometry of the NaI(Tl) detector. Using the ionization chamber reading as activity input to the Monte Carlo model, spectra were obtained and compared to NaI(Tl) spectra. Successive simulations of different activities were run until a spectrum minimizing the mean percent difference between the two was identified. This was repeated for each sample activity. Ionization chamber calibration measurements showed increase in error from 3% to 10% as activities decreased, resulting from decreasing detection efficiency. Measurements of 225Ac using both detector types agreed within 7% of Oak Ridge stated activities. Simulated Monte Carlo spectra of 225Ac were successfully generated. Activities obtained from these spectra differed with ionization chamber readings up to 156% at 147.7 kBq. Simulated spectra were then adjusted to correct NaI(Tl) measurements to be within 1%. These were compared to ionization chamber readings and a response relationship was determined between the two instruments. Measurements of 225Ac and daughter activity were conducted using a NaI(Tl) scintillation detector calibrated for energy and efficiency and an ionization chamber calibrated for efficiency using a surrogate calibration reference. Corrections provided by Monte Carlo modeling improve the accuracy of activity quantification for alpha-particle emitting radiopharmaceuticals in pre-clinical and clinical studies.

Multiparametric MRI and Coregistered Histology Identify Tumor Habitats in Breast Cancer Mouse Models.

It is well-recognized that solid tumors are genomically, anatomically, and physiologically heterogeneous. In general, more heterogeneous tumors have poorer outcomes, likely due to the increased probability of harboring therapy-resistant cells and regions. It is hypothesized that the genomic and physiologic heterogeneity are related, because physiologically distinct regions will exert variable selection pressures leading to the outgrowth of clones with variable genomic/proteomic profiles. To investigate this, methods must be in place to interrogate and define, at the microscopic scale, the cytotypes that exist within physiologically distinct subregions ("habitats") that are present at mesoscopic scales. MRI provides a noninvasive approach to interrogate physiologically distinct local environments, due to the biophysical principles that govern MRI signal generation. Here, we interrogate different physiologic parameters, such as perfusion, cell density, and edema, using multiparametric MRI (mpMRI). Signals from six different acquisition schema were combined voxel-by-voxel into four clusters identified using a Gaussian mixture model. These were compared with histologic and IHC characterizations of sections that were coregistered using MRI-guided 3D printed tumor molds. Specifically, we identified a specific set of MRI parameters to classify viable-normoxic, viable-hypoxic, nonviable-hypoxic, and nonviable-normoxic tissue types within orthotopic 4T1 and MDA-MB-231 breast tumors. This is the first coregistered study to show that mpMRI can be used to define physiologically distinct tumor habitats within breast tumor models. SIGNIFICANCE: This study demonstrates that noninvasive imaging metrics can be used to distinguish subregions within heterogeneous tumors with histopathologic correlation.

Cochlear pharmacokinetics - Micro-computed tomography and learning-prediction modeling for transport parameter determination.

Inner ear disorders such as sensorineural deafness and genetic diseases may one day be treated with local drug delivery to the inner ear. Current pharmacokinetic models have been based on invasive methods to measure drug concentrations, limiting them in spatial resolution, and restricting the research to larger rodents. We developed an intracochlear pharmacokinetic model based on an imaging, learning-prediction (LP) paradigm for learning transport parameters in the murine cochlea. This was achieved using noninvasive micro-computed tomography imaging of the cochlea during in vivo infusion of a contrast agent at the basal end of scala tympani through a cochleostomy. Each scan was registered in 3-D to a cochlear atlas to segment the cochlear regions with high accuracy, enabling concentrations to be extracted along the length of each scala. These spatio-temporal concentration profiles were used to learn a concentration dependent diffusion coefficient, and transport parameters between the major scalae and to clearance. The LP model results are comparable to the current state of the art model, and can simulate concentrations for cases involving different infusion molecules and different drug delivery protocols. Forward simulation results with pulsatile delivery suggest the pharmacokinetic model can be used to optimize drug delivery protocols to reduce total drug delivered and the potential for toxic side effects. While developed in the challenging murine cochlea, the processes are scalable to larger animals and different drug infusion paradigms.

Erratum: Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network.

[This corrects the article DOI: 10.1117/1.JMI.5.1.011016.].

Melanocortin 1 Receptor-Targeted α-Particle Therapy for Metastatic Uveal Melanoma.

New effective therapies are greatly needed for metastatic uveal melanoma, which has a very poor prognosis with a median survival of less than 1 y. The melanocortin 1 receptor (MC1R) is expressed in 94% of uveal melanoma metastases, and a MC1R-specific ligand (MC1RL) with high affinity and selectivity for MC1R was previously developed. Methods: The 225Ac-DOTA-MC1RL conjugate was synthesized in high radiochemical yield and purity and was tested in vitro for biostability and for MC1R-specific cytotoxicity in uveal melanoma cells, and the lanthanum-DOTA-MC1RL analog was tested for binding affinity. Non-tumor-bearing BALB/c mice were tested for maximum tolerated dose and biodistribution. Severe combined immunodeficient mice bearing uveal melanoma tumors or engineered MC1R-positive and -negative tumors were studied for biodistribution and efficacy. Radiation dosimetry was calculated using mouse biodistribution data and blood clearance kinetics from Sprague-Dawley rat data. Results: High biostability, MC1R-specific cytotoxicity, and high binding affinity were observed. Limiting toxicities were not observed at even the highest administered activities. Pharmacokinetics and biodistribution studies revealed rapid blood clearance (<15 min), renal and hepatobillary excretion, MC1R-specific tumor uptake, and minimal retention in other normal tissues. Radiation dosimetry calculations determined pharmacokinetics parameters and absorbed α-emission dosages from 225Ac and its daughters. Efficacy studies demonstrated significantly prolonged survival and decreased metastasis burden after a single administration of 225Ac-DOTA-MC1RL in treated mice relative to controls. Conclusion: These results suggest significant potential for the clinical translation of 225Ac-DOTA-MC1RL as a novel therapy for metastatic uveal melanoma.

In vivo positron emission tomographic blood pool imaging in an immunodeficient mouse model using 18F-fluorodeoxyglucose labeled human erythrocytes.

99m-Technetium-labeled (99mTc) erythrocyte imaging with planar scintigraphy is widely used for evaluating both patients with occult gastrointestinal bleeding and patients at risk for chemotherapy-induced cardiotoxicity. While a number of alternative radionuclide-based blood pool imaging agents have been proposed, none have yet to achieve widespread clinical use. Here, we present both in vitro and small animal in vivo imaging evidence that the high physiological expression of the glucose transporter GLUT1 on human erythrocytes allows uptake of the widely available radiotracer 2-deoxy-2-(18F)fluoro-D-glucose (FDG), at a rate and magnitude sufficient for clinical blood pool positron emission tomographic (PET) imaging. This imaging technique is likely to be amenable to rapid clinical translation, as it can be achieved using a simple FDG labeling protocol, requires a relatively small volume of phlebotomized blood, and can be completed within a relatively short time period. As modern PET scanners typically have much greater count detection sensitivities than that of commonly used clinical gamma scintigraphic cameras, FDG-labeled human erythrocyte PET imaging may not only have significant advantages over 99mTc-labeled erythrocyte imaging, but may have other novel blood pool imaging applications.

Structure and properties of DOTA-chelated radiopharmaceuticals within the 225Ac decay pathway.

The successful delivery of toxic cargo directly to tumor cells is of primary importance in targeted (α) particle therapy. Complexes of radioactive atoms with the 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelating agent are considered as effective materials for such delivery processes. The DOTA chelator displays high affinity to radioactive metal isotopes and retains this capability after conjugation to tumor targeting moieties. Although the α-decay chains are well defined for many isotopes, the stability of chelations during the decay process and the impact of released energy on their structures remain unknown. The radioactive isotope 225Ac is an α-particle emitter that can be easily chelated by DOTA. However, 225Ac has a complex decay chain with four α-particle emissions during decay of each radionuclide. To advance our fundamental understanding of the consequences of α-decay on the stability of tumor-targeted 225Ac-DOTA conjugate radiopharmaceuticals, we performed first principles calculations of the structure, stability, and electronic properties of the DOTA chelator to the 225Ac radioactive isotope, and the initial daughters in the decay chain, 225Ac, 221Fr, 217At and 213Bi. Our calculations show that the atomic positions, binding energies, and electron localization functions are affected by the interplay between spin-orbit coupling, weak dispersive interactions, and environmental factors. Future empirical measurements may be guided and interpreted in light of these results.

Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network.

Positron emission tomography (PET) is a quantitative imaging modality, but the computation of standardized uptake values (SUVs) requires several instruments to be correctly calibrated. Variability in the calibration process may lead to unreliable quantitation. Sealed source kits containing traceable amounts of [Formula: see text] were used to measure signal stability for 19 PET scanners at nine hospitals in the National Cancer Institute's Quantitative Imaging Network. Repeated measurements of the sources were performed on PET scanners and in dose calibrators. The measured scanner and dose calibrator signal biases were used to compute the bias in SUVs at multiple time points for each site over a 14-month period. Estimation of absolute SUV accuracy was confounded by bias from the solid phantoms' physical properties. On average, the intrascanner coefficient of variation for SUV measurements was 3.5%. Over the entire length of the study, single-scanner SUV values varied over a range of 11%. Dose calibrator bias was not correlated with scanner bias. Calibration factors from the image metadata were nearly as variable as scanner signal, and were correlated with signal for many scanners. SUVs often showed low intrascanner variability between successive measurements but were also prone to shifts in apparent bias, possibly in part due to scanner recalibrations that are part of regular scanner quality control. Biases of key factors in the computation of SUVs were not correlated and their temporal variations did not cancel out of the computation. Long-lived sources and image metadata may provide a check on the recalibration process.

Evaluation of radiofluorinated carboximidamides as potential IDO-targeted PET tracers for cancer imaging.

IDO1 is an enzyme catalyzing the initial and rate-limiting step in the catabolism of tryptophan along the kynurenine pathway. IDO1 expression could suppress immune responses by blocking T-lymphocyte proliferation locally, suggesting a role of IDO in the regulation of immune responses. The goal of this study was to evaluate the potential of radiofluorinated carboximidamides as selective PET radioligands for IDO1. Specific binding correlated with IDO1 expression as measured through in vitro, microPET experiments. Specific accumulation of the new radiotracer [18F]IDO49 was observed in IDO1-expressing tumors and confirmed by Western blot and IHC analyses. These results suggest that [18F]IDO49 has substantial potential as an imaging agent that targets IDO1 in tumors, and therefore may be utilized as a companion diagnostic for IDO1 targeted therapies.

Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data.

PURPOSE: Radiomics utilizes a large number of image-derived features for quantifying tumor characteristics that can in turn be correlated with response and prognosis. Unfortunately, extraction and analysis of such image-based features is subject to measurement variability and bias. The challenge for radiomics is particularly acute in Positron Emission Tomography (PET) where limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options confound quantitative feature metrics. Extracted feature quality is also affected by tumor segmentation methods used to define regions over which to calculate features, making it challenging to produce consistent radiomics analysis results across multiple institutions that use different segmentation algorithms in their PET image analysis. Understanding each element contributing to these inconsistencies in quantitative image feature and metric generation is paramount for ultimate utilization of these methods in multi-institutional trials and clinical oncology decision making. METHODS: To assess segmentation quality and consistency at the multi-institutional level, we conducted a study of seven institutional members of the National Cancer Institute Quantitative Imaging Network. For the study, members were asked to segment a common set of phantom PET scans acquired over a range of imaging conditions as well as a second set of head and neck cancer (HNC) PET scans. Segmentations were generated at each institution using their preferred approach. In addition, participants were asked to repeat segmentations with a time interval between initial and repeat segmentation. This procedure resulted in overall 806 phantom insert and 641 lesion segmentations. Subsequently, the volume was computed from the segmentations and compared to the corresponding reference volume by means of statistical analysis. RESULTS: On the two test sets (phantom and HNC PET scans), the performance of the seven segmentation approaches was as follows. On the phantom test set, the mean relative volume errors ranged from 29.9 to 87.8% of the ground truth reference volumes, and the repeat difference for each institution ranged between -36.4 to 39.9%. On the HNC test set, the mean relative volume error ranged between -50.5 to 701.5%, and the repeat difference for each institution ranged between -37.7 to 31.5%. In addition, performance measures per phantom insert/lesion size categories are given in the paper. On phantom data, regression analysis resulted in coefficient of variation (CV) components of 42.5% for scanners, 26.8% for institutional approaches, 21.1% for repeated segmentations, 14.3% for relative contrasts, 5.3% for count statistics (acquisition times), and 0.0% for repeated scans. Analysis showed that the CV components for approaches and repeated segmentations were significantly larger on the HNC test set with increases by 112.7% and 102.4%, respectively. CONCLUSION: Analysis results underline the importance of PET scanner reconstruction harmonization and imaging protocol standardization for quantification of lesion volumes. In addition, to enable a distributed multi-site analysis of FDG PET images, harmonization of analysis approaches and operator training in combination with highly automated segmentation methods seems to be advisable. Future work will focus on quantifying the impact of segmentation variation on radiomics system performance.

Sensitivity of Image Features to Noise in Conventional and Respiratory-Gated PET/CT Images of Lung Cancer: Uncorrelated Noise Effects.

The effect of noise on image features has yet to be studied in depth. Our objective was to explore how significantly image features are affected by the addition of uncorrelated noise to an image. The signal-to-noise ratio and noise power spectrum were calculated for a positron emission tomography/computed tomography scanner using a Ge-68 phantom. The conventional and respiratory-gated positron emission tomography/computed tomography images of 31 patients with lung cancer were retrospectively examined. Multiple sets of noise images were created for each original image by adding Gaussian noise of varying standard deviation equal to 2.5%, 4.0%, and 6.0% of the maximum intensity for positron emission tomography images and 10, 20, 50, 80, and 120 Hounsfield units for computed tomography images. Image features were extracted from all images, and percentage differences between the original image and the noise image feature values were calculated. These features were then categorized according to the noise sensitivity. The contour-dependent shape descriptors averaged below 4% difference in positron emission tomography and below 13% difference in computed tomography between noise and original images. Gray level size zone matrix features were the most sensitive to uncorrelated noise exhibiting average differences >200% for conventional and respiratory-gated images in computed tomography and 90% in positron emission tomography. Image feature differences increased as the noise level increased for shape, intensity, and gray-level co-occurrence matrix features in positron emission tomography and for gray-level co-occurrence matrix and gray-level size zone matrix features in conventional computed tomography. Investigators should be aware of the noise effects on image features.