Positron Emission Tomography Tumor Research Articles

Legumain-Triggered Macrocyclization of Radiofluorinated Tracer for Enhanced PET Imaging.

Enhancing the accumulation and retention of small-molecule probes in tumors is an important way to achieve accurate cancer diagnosis and therapy. Enzyme-stimulated macrocyclization of small molecules possesses great potential for enhanced positron emission tomography (PET) imaging of tumors. Herein, we reported an 18F-labeled radiotracer [18F]AlF-RSM for legumain detection in vivo. The tracer was prepared by a one-step aluminum-fluoride-restrained complexing agent ([18F]AlF-RESCA) method with high radiochemical yield (RCY) (88.35 ± 3.93%) and radiochemical purity (RCP) (>95%). More notably, the tracer can be transformed into a hydrophobic macrocyclic molecule under the joint action of legumain and reductant. Simultaneously, the tracer could target legumain-positive tumors and enhance accumulation and retention in tumors, resulting in the amplification of PET imaging signals. The enhancement of radioactivity enables PET imaging of legumain activity with high specificity. We envision that, by combining this highly efficient 18F-labeled strategy with our intramolecular macrocyclization reaction, a range of radiofluorinated tracers can be designed for tumor PET imaging and early cancer diagnosis in the future.

Lysosome-targeting and legumain-triggered 68Ga-labeled probe for enhanced tumor PET imaging

Legumain is overexpressed in diverse tumors, serving as a significant tumor biomarker. Our study aimed to develop a new positron emission tomography (PET) probe [68Ga]Ga-NOTA-SF-AANM for imaging the expression level of legumain in vivo. The radio-labeling of [68Ga]Ga-NOTA-SF-AANM was accomplished within 15 min. The probe has good stability in vitro. NOTA-SF-AANM exhibited rapid response to recombinant human legumain enzyme, enabling intramolecular condensation cyclization. Cellular uptake and lysosomal co-localization experiments demonstrated that the probe was able to differentiate specifically between MDA-MB-468 and PC-3 cancer cells with varying degrees of legumain expression. PET imaging displayed a significant and persistent signal (3.59 ± 0.30 %ID/mL at 60 min) in MDA-MB-468 tumors, while PC-3 tumors exhibited lower radioactivity (1.08 ± 0.35 %ID/mL at 60 min), further validating the specific targeting of [68Ga]Ga-NOTA-SF-AANM towards legumain. [68Ga]Ga-NOTA-SF-AANM is a promising tool for precise diagnosis of legumain-related diseases due to its advantages in radio-labeling and accurate monitoring of legumain expression levels.

Multi-Modal Ensemble Deep Learning in Head and Neck Cancer HPV Sub-Typing.

Oropharyngeal Squamous Cell Carcinoma (OPSCC) is one of the common forms of heterogeneity in head and neck cancer. Infection with human papillomavirus (HPV) has been identified as a major risk factor for OPSCC. Therefore, differentiating the HPV-positive and negative cases in OPSCC patients is an essential diagnostic factor influencing future treatment decisions. In this study, we investigated the accuracy of a deep learning-based method for image interpretation and automatically detected the HPV status of OPSCC in routinely acquired Computed Tomography (CT) and Positron Emission Tomography (PET) images. We introduce a 3D CNN-based multi-modal feature fusion architecture for HPV status prediction in primary tumor lesions. The architecture is composed of an ensemble of CNN networks and merges image features in a softmax classification layer. The pipeline separately learns the intensity, contrast variation, shape, texture heterogeneity, and metabolic assessment from CT and PET tumor volume regions and fuses those multi-modal features for final HPV status classification. The precision, recall, and AUC scores of the proposed method are computed, and the results are compared with other existing models. The experimental results demonstrate that the multi-modal ensemble model with soft voting outperformed single-modality PET/CT, with an AUC of 0.76 and F1 score of 0.746 on publicly available TCGA and MAASTRO datasets. In the MAASTRO dataset, our model achieved an AUC score of 0.74 over primary tumor volumes of interest (VOIs). In the future, more extensive cohort validation may suffice for better diagnostic accuracy and provide preliminary assessment before the biopsy.

Nuclear medicine techniques in paediatric body oncology: Present and future

Modern nuclear medicine techniques combining anatomical and functional imaging have transformed our ability to diagnose, stage and prognosticate in paediatric oncology. Progress in the use of positron emission tomography (PET) in children with cancer has been relatively restrained compared to adults due to radiation concerns, limited research, availability, and the practical challenges associated with imaging young children. However, there have been several developments in the last decade and the role of molecular imaging in paediatric oncology will only broaden with forthcoming novel tracers and molecular radiotherapy. This review article summarises the practical aspects of nuclear imaging in paediatric oncology, discusses the main imaging methods including PET and single photon emission computed tomography (SPECT), appraises the available established and novel tracers, and summarises the evidence behind molecular imaging in paediatric lymphoma, neuroblastoma, sarcomas, thyroid cancer and other tumours. 18F-FDG PET/CT is the established method for staging and response assessment after induction chemotherapy in paediatric Hodgkin lymphoma and has high sensitivity for the detection of bone marrow disease, reducing the need for bone marrow biopsy in some cases. 123I-mIBG planar with SPECT imaging remains the mainstay for neuroblastoma imaging, however there is a well-established role for 18F-FDG PET/CT in mIBG non-avid disease, and 18F-DOPA and 68Ga-DOTA PET tracers have shown promising results as upcoming alternatives. 18F-FDG PET/CT is advocated in the staging assessment of rhabdomyosarcoma and has been shown to have excellent sensitivity in the detection of bone metastases in osteosarcoma and Ewing sarcoma, although standard chest CT is still recommended for the detection of lung metastases. The role of PET in germ cell tumours, hepatoblastoma, Wilms tumour and Langerhans cell histiocytosis is complementary to standard techniques.

In vitro and in vivo characterization of [64Cu][Cu(elesclomol)] as a novel theranostic agent for hypoxic solid tumors

PurposeHypoxic tumors are associated with therapy resistance and poor cancer prognosis, but methods to detect and counter tumor hypoxia remain insufficient. Our purpose was to investigate 64Cu(II)-elesclomol ([64Cu][Cu(ES)]) as a novel theranostic agent for hypoxic tumors, by implementing an improved production method and assessing its therapeutic and diagnostic potential compared to the established Cu-64 radiopharmaceuticals [64Cu]CuCl2 and [diacetyl-bis(N4-methylthiosemicarbazone) [64Cu][Cu(ATSM)].MethodsCu-64 was produced using a biomedical cyclotron at 12 MeV with the reaction 64Ni(p,n)64Cu, followed by synthesis of [64Cu]CuCl2, [64Cu][Cu(ATSM)], and [64Cu][Cu(ES)]. In vitro therapeutic effects were assessed in both normoxic and hypoxic cells (22Rv1 and PC3 prostate cancer cells, and U-87MG glioblastoma cells) using the clonogenic assay and analyzing cellular uptake and internalization. In vivo therapeutic effects were assessed in 22Rv1 xenografts in BALB/cAnN-Foxn1nu/nu/Rj mice receiving a single or multiple doses of radiopharmaceutical, before their feasibility to detect tumor hypoxia was assessed by positron emission tomography (PET) in 22Rv1 and U-87MG xenografts.ResultsIn vitro and in vivo studies demonstrated that [64Cu][Cu(ES)] reduced cell survival and inhibited tumor growth more effectively than [64Cu][Cu(ATSM)] and [64Cu]CuCl2. Hypoxia increased the cellular uptake and internalization of [64Cu][Cu(ES)] and [64Cu][Cu(ATSM)]. [64Cu][Cu(ES)]-PET tumor hypoxia detection was feasible and also revealed an unexpected finding of uptake in the brain.ConclusionTo the best of our knowledge, this is the first time that ES is radiolabeled with [64Cu]CuCl2 to [64Cu][Cu(ES)]. We demonstrated superior therapeutic effects of [64Cu][Cu(ES)] compared to [64Cu][Cu(ATSM)] and [64Cu]CuCl2 and that [64Cu][Cu(ES)]-PET is feasible. [64Cu][Cu(ES)] is a promising theranostic agent for hypoxic solid tumors.

Comparison of machine learning approaches for POD24 prediction based on pretreatment PET in follicular lymphoma patients (on behalf of CALYM/LYSA groups)

Introduction: Follicular Lymphoma (FL) is the second most common non-Hodgkin lymphoma in adults and is heterogeneous with 20% of poor-outcome patients relapsing/progressing within 24 months (POD24) of first treatment start (Casulo et al., JCO 2015). Early identification of those POD24 patients is critical but remains elusive. We initiated a collaboration between the academic CALYM Carnot Institute and the private company Euranova aiming at developing interpretable artificial intelligence (AI) models based on Positron Emission Tomography (PET) images to predict POD24. Methods: The dataset was based on the LYSA group RELEVANCE (RE) trial (Morshhauser et al, NEJM 2018) and on real-life (RL) datasets from two french hospitals (Dijon, Toulouse). Patients with FL diagnosis confirmation on biopsy, high tumor burden criteria (GELF >0) and PET images were enrolled in this retrospective study (Table 1). The input data, including PET images, tumor segmentation masks if available, and clinical data, are hosted on CALYM’s cloud based data lake Lymphoma Data Hub. After quality controls and data preprocessing, several POD24 predictive models based on pretreatment images were developed. A deep convolutional neural network with 3D ResNet architecture pretrained on 3D medical images and enriched with clinical data was trained on PET images with a binary cross entropy loss. A machine learning (ML) model based on the XGBoost boosting algorithm was trained on tabular radiomics features after extraction of 851 radiomics features for each tumor and features aggregation at patient’s level by using only the 3 tumors with largest volumes. Models were cross-validated on the RE cohort with leave-one-out method and tested on the RL cohorts (Figure 1). Results: The ML approach achieved more promising results than the deep learning (DL) model on the RE cohort with an AUC of 0.61 for ML vs. 0.56 for DL. Interestingly, in this ML model, SUVmax and new radiomics features, such as major axis length, came out as the most predictive features. For now the external validation of the ML model on RL cohorts is slightly more limited with an AUC of 0.51. Improvement of this result is expected owing to the ongoing enrichment of the cohort with additional external data. Finally, regarding the treatment’s impact on the model’s performance, preliminary data showed better results when training on the R-CHOP cohort only. Validation is underway, and will be presented at the meeting. Keywords: Bioinformatics, Computational and Systems Biology, Indolent non-Hodgkin lymphoma, PET-CT No conflicts of interests pertinent to the abstract.

Comparison of Diagnostic PET and 4D CT-Based Tumor Delineation for Oligometastatic Lung Tumors

<h3>Purpose/Objective(s)</h3> Stereotactic body raiation therapy (SBRT) is increasingly used to treat oligometastatic tumors. To account for internal motion, 4D-CT is commonly used for lung SBRT. Biology-guided radiotherapy (BgRT) is an emerging concept that may allow for reduction of treatment volumes using positron emission tomography (PET) signal guidance. Benchtop testing of BgRT technology suggests target delineation on a single respiratory phase with 5 mm biology-guided margin may be sufficient, however this has not been clinically validated. We tested our hypothesis that PET-based tumor delineation would result in smaller target volumes than 4D-CT. <h3>Materials/Methods</h3> We retrospectively reviewed a single-institution lung radiotherapy database to identify patients with oligometastatic lung tumors treated with ablative doses of biologically effective dose (BED10) >=100 Gy. We included patients treated from 2015-2020 with a diagnostic PET performed within 30 days of CT simulation. Tumors were contoured on the diagnostic PET using an auto-threshold of 40% of the lesion SUVmax, followed by manual editing to include CT-based tumor accounting for possible PET signal misregistration. A 5 mm isotropic expansion was applied to generate the planning target volume (PTV). We compared these to existing 4D CT-based tumor volumes accounting for internal motion and their associated PTVs. <h3>Results</h3> Of 102 patients with oligometastatic lung tumors, we included 13 patients with 15 lung tumors. There were 7 female and 6 male patients, with a median age of 72 (range 52 – 89) at the time of treatment. Primary tumor types included 4 colorectal, 2 head and neck, 1 non-small cell lung cancer, 1 melanoma, and 5 other cancer types. Patients were treated to 50 to 54 Gy in 3 to 5 fractions. Median time from diagnostic PET scan to CT simulation was 17 days (range 0 – 27). Median lesion diameter was 1.2 cm (IQR 0.9 – 1.7) with median SUVmax of 5.4 (IQR 4.0 – 7.7). Diagnostic PET-based tumor contours had a median volume of 2.5 cc (IQR 1.7 – 3.1 cc), whereas 4D CT-based tumor contours had a median volume of 3.0 cc (IQR 2.4 – 9.9 cc). Diagnostic PET-based PTV had a median volume of 10.4 cc (IQR 8.4 – 12.6 cc), whereas 4D CT-based PTV had a median volume of 11.8 cc (IQR 10.8 – 31.5). <h3>Conclusion</h3> Diagnostic PET-based tumor delineation resulted in smaller tumor and planning target volumes compared to 4D-based tumor delineation. This data will serve as a benchmark for future research focusing on imaging modality concordance and clinical impact of reduced biology-guided margins in BgRT for oligometastatic patients undergoing lung SBRT.

Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma.

Simple SummaryGlioblastoma (GBM), the most common malignant adult primary brain tumour, has a prognosis of ~12–15 months. Poor prognosis is partly due to the inability to accurately define the extent of tumour infiltration; currently demarcated using magnetic resonance imaging (MRI) sequences (e.g., post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced (DCE-MRI)). Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) may depict GBM better than MRI. This prospective pilot study aimed to explore the relationship of 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients with GBM undergoing standard-of-care adjuvant chemoradiotherapy. A parallel mouse glioma model was used to investigate the relationship between 18F-fluciclovine PET, MRI and tumour biology. Clinical results showed that GBM volume on 18F-fluciclovine PET tended to be larger than Gd-T1 and DCE-MRI in patients with shorter overall survival (OS) but smaller in patients with longer OS. The preclinical study confirmed that 18F-fluciclovine uptake reflected biologically active tumour. Results suggest that 18F-fluciclovine PET may better define GBM infiltration than MRI.Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1–6) and grouped according to overall survival (OS)—short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.

Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization.

Positron Emission Tomography (PET) has become a preferred imaging modality for cancer diagnosis, radiotherapy planning, and treatment responses monitoring. Accurate and automatic tumor segmentation is the fundamental requirement for these clinical applications. Deep convolutional neural networks have become the state-of-the-art in PET tumor segmentation. The normalization process is one of the key components for accelerating network training and improving the performance of the network. However, existing normalization methods either introduce batch noise into the instance PET image by calculating statistics on batch level or introduce background noise into every single pixel by sharing the same learnable parameters spatially. In this paper, we proposed an attentive transformation (AT)-based normalization method for PET tumor segmentation. We exploit the distinguishability of breast tumor in PET images and dynamically generate dedicated and pixel-dependent learnable parameters in normalization via the transformation on a combination of channel-wise and spatial-wise attentive responses. The attentive learnable parameters allow to re-calibrate features pixel-by-pixel to focus on the high-uptake area while attenuating the background noise of PET images. Our experimental results on two real clinical datasets show that the AT-based normalization method improves breast tumor segmentation performance when compared with the existing normalization methods.

18F]BIBD-239: 18F-Labeled ER176, a Positron Emission Tomography Tracer Specific for the Translocator Protein.

[11C]ER176 has adequate sensitivity to image the human brain translocator protein (TSPO) in all three genotypes by positron emission tomography (PET). However, its clinical application is limited by the short half-life of 11C (20.38 min). To overcome the deficiency of [11C]ER176 and keep the pharmacophore features of ER176 to the maximum extent, we designed four fluorine-labeled ER176 derivatives using the deuterium method. In vitro competition binding confirmed that the designed compounds had high affinity for TSPO. Biodistribution experiments showed that tissues with high expression of TSPO had high uptake of these compounds, as well as that the compound showed high brain penetration and mild defluorination in vivo. Therefore, [18F]BIBD-239 with simple synthesis conditions was selected for further biological evaluation. Theoretical simulations showed that BIBD-239 and ER176 have similar binding modes and sites to Ala147-TSPO and Thr147-TSPO, which indicated that the tracers may have consistent sensitivity to the three affinity genotypes. In vitro autoradiography and in vivo PET studies of the ischemic rat brain showed dramatically higher uptake of [18F]BIBD-239 on the lesion site compared to the contralateral side with good brain kinetics. Additionally, [18F]BIBD-239 provided clear tumor PET images in a GL261 glioma model. Importantly, PET imaging and liquid chromatography-high-resolution mass spectrometry (LC-HRMS) results showed that in vivo defluorination and other metabolites of [18F]BIBD-239 did not interfere with brain imaging. Conclusively, [18F]BIBD-239, similar to ER176 with low polymorphism sensitivity, has simple labeling conditions, high labeling yield, high affinity, and high specificity for TSPO, and it is planned for further evaluation in higher species.

Likely Common Role of Hypoxia in Driving 18F-FDG Uptake in Cancer, Myocardial Ischemia, Inflammation and Infection.

First introduced in 1976, 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) has become an indispensable tool for diagnosis and prognostic evaluation of tumors, heart disease, as well as other conditions, including inflammation and infection. Because 18F-FDG can accurately reflect the glucose metabolism level of organs and tissues, it is known as a "century molecule" and is currently the main agent for PET imaging. The degree of 18F-FDG uptake by cells is related to both the rate of glucose metabolism and glucose transporter expression. These, in turn, are strongly influenced by hypoxia, in which cells meet their energy needs through glycolysis, and 18F-FDG uptake increased due to hypoxia. 18F-FDG uptake is a complex process, and hypoxia may be one of the fundamental driving forces. The correct interpretation of 18F-FDG uptake in PET imaging can help clinics make treatment decisions more accurately and effectively. In this article, we review the application of 18F-FDG PET in tumors, myocardium, and inflammation. We discuss the relationship between 18F-FDG uptake and hypoxia, the possible mechanism of 18F-FDG uptake caused by hypoxia, and the associated clinical implications.

Morphologically homogeneous, pH-responsive gold nanoparticles for non-invasive imaging of HeLa cancer

Gold nanoparticles (AuNPs) have been widely used as nanocarriers in drug delivery to improve the efficiency of chemotherapy treatment and enhance early disease detection. The advantages of AuNPs include their excellent biocompatibility, easy modification and functionalization, facile synthesis, low toxicity, and controllable particle size. This study aimed to synthesize a conjugated citraconic anhydride link between morphologically homogeneous AuNPs and doxorubicin (DOX) (DOX-AuNP). The carrier was radiolabeled for tumor diagnosis using positron emission tomography (PET). The systemically designed DOX-AuNP was cleaved at the citraconic anhydride linker site under the mild acidic conditions of a cancer cell, thereby releasing DOX. Subsequently, the AuNPs aggregated via electrostatic attraction. HeLa cancer cells exhibited a high uptake of the radiolabeled DOX-AuNP. Moreover, PET tumor images were obtained using radiolabeled DOX-AuNP in cancer xenograft mouse models. Therefore, DOX-AuNP is expected to provide a valuable insight into the use of radioligands to detect tumors using PET.

A Phantom Study to Investigate Robustness and Reproducibility of Grey Level Co-Occurrence Matrix (GLCM)-Based Radiomics Features for PET

Quantification and classification of heterogeneous radiotracer uptake in Positron Emission Tomography (PET) using textural features (termed as radiomics) and artificial intelligence (AI) has the potential to be used as a biomarker of diagnosis and prognosis. However, textural features have been predicted to be strongly correlated with volume, segmentation and quantization, while the impact of image contrast and noise has not been assessed systematically. Further continuous investigations are required to update the existing standardization initiatives. This study aimed to investigate the relationships between textural features and these factors with 18F filled torso NEMA phantom to yield different contrasts and reconstructed with different durations to represent varying levels of noise. The phantom was also scanned with heterogeneous spherical inserts fabricated with 3D printing technology. All spheres were delineated using: (1) the exact boundaries based on their known diameters; (2) 40% fixed; and (3) adaptive threshold. Six textural features were derived from the gray level co-occurrence matrix (GLCM) using different quantization levels. The results indicate that homogeneity and dissimilarity are the most suitable for measuring PET tumor heterogeneity with quantization 64 provided that the segmentation method is robust to noise and contrast variations. To use these textural features as prognostic biomarkers, changes in textural features between baseline and treatment scans should always be reported along with the changes in volumes.

Modern Management of High-risk Soft Tissue Sarcoma With Neoadjuvant Chemoradiation: A Single-center Experience.

Neoadjuvant chemoradiation (NA-CRT), followed by resection of high-risk soft tissue sarcoma (STS), may offer good disease control and toxicity outcomes. We report on a single institution's modern NA-CRT experience. Delay to surgical resection, resection margin status, extent of necrosis, tumor cell viability, presence of hyalinization, positron emission tomography (PET)/computed tomography data, and treatment toxicities were collected. Using the Kaplan-Meier survival analysis, 5-year overall survival, disease-free survival, distant metastasis-free survival, and local control (LC) were estimated. Clinicopathologic features and PET/computed tomography avidity changes were assessed for their potential predictive impact using the log-rank test. From 2011 to 2018, 37 consecutive cases of localized high-risk STS were identified. Twenty-nine patients underwent ifosfamide-based NA-CRT to a median dose of 50 Gy before en bloc resection. At a median follow-up of 40.3 months, estimated 5-year overall survival was 86.1%, disease-free survival 70.2%, distant metastasis-free survival 75.2%, and LC 86.7%. Following NA-CRT, a median reduction of 54.7% was observed in tumor PET avidity; once resected, median tumor necrosis of 60.0% with no viable tumor cells was detected in 13.8% of the cases. Posttreatment resection margins were negative in all patients, with 27.6% having a margin of ≤1 mm. Delays of over 6 weeks following the end of radiation treatment to surgical resection occurred in 20.7% cases and was suggestive of inferior LC (92.8% vs. 68.6%, P=0.025). This single-institution series of NA-CRT demonstrates favorable disease control. Delay in surgical resection was associated with inferior LC, a finding that deserves further evaluation in a larger cohort. Level III-retrospective cohort study.

Effect of uncertainties in quantitative 18 F-FDG PET/CT imaging feedback for intratumoral dose-response assessment and dose painting by number.

Intratumoral dose response can be detected using serial fluoro-2-deoxyglucose-(FDG) positron emission tomography (PET)/computed tomography (CT) imaging feedback during treatment and used to guide adaptive dose painting by number (DPbN). However, to reliably implement this technique, the effect of uncertainties in quantitative PET/CT imaging feedback on tumor voxel dose-response assessment and DPbN needs to be determined and reduced. Three major uncertainties, induced by (a) PET imaging partial volume effect (PVE) and (b) tumor deformable image registration (DIR), and (c) variation of the time interval between FDG injection and PET image acquisition (TI), were determined using serial FDG-PET/CT images acquired during chemoradiotherapy of 18 head and neck cancer patients. PET imaging PVE was simulated using the discrepancy between with and without iterative deconvolution-based PVE corrections. Effect of tumor DIR uncertainty was simulated using the discrepancy between two DIR algorithms, including one with and one without soft-tissue mechanical correction for the voxel displacement. The effect of TI variation was simulated using linear interpolation on the dual-point PET/CT images. Tumor voxel pretreatment metabolic activity (SUV0 ) and dose-response matrix (DRM) discrepancies induced by each of the three uncertainties were quantified, respectively. Adverse effects of tumor voxel SUV0 and DRM discrepancies on tumor control probability (TCP) in DPbN were assessed. Partial volume effect and TI variations of 10 mins induced a mean±standard deviation (SD) of tumor voxel SUV0 discrepancies to be -0.7%±9.2% and 0%±4.8%, respectively. Tumor voxel DRM discrepancies induced by PVE, tumor DIR discrepancy, and TI variations were 0.6%±8.9%, 1.7%±9.1%, and 0%±7%, respectively. Partial volume effect induced SUV0 and DRM discrepancies correlated significantly with the tumor shape and FDG uptake heterogeneity. Tumor DIR uncertainty-induced DRM discrepancy correlated significantly with the tumor volume and shrinkage during treatment. Among the three uncertainties, PVE dominated the adverse effects on the TCP, with a mean±SD of TCP reduction to be 12.7%±9.8% for all tumors if no compensation was applied for. Effect of uncertainties in quantitative FDG-PET/CT imaging feedback on intratumoral dose-response quantification was not negligible. These uncertainties primarily caused by PVE and tumor DIR were highly dependent on individual tumor shape, volume, shrinkage during treatment, and pretreatment SUV heterogeneity, which can be managed individually. The adverse effects of these uncertainties could be minimized by using proper PVE corrections and DIR methods and compensated for in the clinical implementation of DPbN.

Early 18F-FDG-PET Response During Radiation Therapy for HPV-Related Oropharyngeal Cancer May Predict Disease Recurrence

Early indication of treatment outcome may guide therapeutic de-escalation strategies in patients with human papillomavirus (HPV)-related oropharyngeal cancer (OPC). This study investigated the relationships between tumor volume and 18F-fluorodeoxyglucose positron emission tomography (PET) parameters before and during definitive radiation therapy with treatment outcomes. Patients undergoing definitive (chemo)radiation for HPV-related/p16-positive OPC were prospectively enrolled on an institutional review board-approved study. 18F-fluorodeoxyglucose PET/computed tomography scans were performed at simulation and after 2 weeks at a dose of ∼20 Gy. Tumor volume and standardized uptake value (SUV) characteristics were measured. SUV was normalized to blood pool uptake. Tumor volume and PET parameters associated with recurrence were identified through recursive partitioning (RPART). Recurrence-free survival (RFS) and overall survival (OS) curves between RPART-identified cohorts were estimated using the Kaplan-Meier method, and Cox models were used to estimate the hazard ratios (HRs). From 2012 to 2016, 62 patients with HPV-related OPC were enrolled. Median follow-up was 4.4 years. RPART identified patients with intratreatment SUVmax (normalized to blood pool SUVmean) <6.7 or SUVmax (normalized to blood pool SUVmean) ≥6.7 with intratreatment SUV40% ≥2.75 as less likely to recur. For identified subgroups, results of Cox models showed unadjusted HRs for RFS and OS (more likely to recur vs less likely) of 7.33 (90% confidence interval [CI], 2.97-18.12) and 6.09 (90% CI, 2.22-16.71), respectively, and adjusted HRs of 6.57 (90% CI, 2.53-17.05) and 5.61 (90% CI, 1.90-16.54) for RFS and OS, respectively. PET parameters after 2 weeks of definitive radiation therapy for HPV-related OPC are associated with RFS and OS, thus potentially informing an adaptive treatment approach.

89Zr-durvalumab PD-L1 PET in recurrent or metastatic (R/M) squamous cell carcinoma of the head and neck.

3573 Background: Immune checkpoint inhibitors (ICI) targeting programmed cell death protein-1/ligand-1 (PD-1/PD-L1) have shown activity in R/M squamous cell carcinoma of the head and neck (SCCHN). Positron-emission-tomography (PET) with 89Zr-labeled anti-PD-L1 antibodies could aid in predicting response to ICI. We present the dose-finding results of the first-in-human 89Zr-durvalumab PD-L1 PET-imaging in patients with SCCHN participating in the ongoing phase II PINCH study (NCT03829007). Methods: Following baseline [18F]FDG-PET and CT/MRI imaging, patients with incurable R/M SCCHN received 37 MBq 89Zr-durvalumab and protein dose 2mg, 10mg or 50mg durvalumab. 89Zr-durvalumab PD-L1 PET-scan was acquired day 5 post-injection. Plasma pharmacokinetic analyses were performed at day 0 and 5. Standardized uptake values (SUV, mean ± SD) were measured in [18F]FDG-positive tumor lesion, liver, spleen, bone marrow and bloodpool. PD-L1-expression was assessed on archival tumor tissue using the Ventana PD-L1 (SP263) assay. Results: 14 patients were enrolled and no adverse events were reported. High tracer-retention was observed in liver and spleen, most prominent in patients receiving 2 or 10mg durvalumab. 89Zr-durvalumab accumulation within tumors and between patients was heterogeneous and not all [18F]FDG-positive lesions showed 89Zr-durvalumab uptake. Tumor lesions were visualized best using 10 or 50mg durvalumab (SUVpeak 2mg: 3.86 ± 0.79, 10mg: 7.46 ± 2.18, 50mg: 5.57 ± 1.74). Tumor-to-blood-ratios for 10mg durvalumab were highest (2mg: 2.27 ± 0.33, 10mg: 3.44 ± 0.76, 50mg: 1.73 ± 0.99; p = 0.019). PK-analyses confirmed visual prolonged tracer-retention in bloodpool with increasing protein dose. PD-L1-expression was equally distributed amongst dose-groups. Conclusions: This is the first study to show feasibility of 89Zr-durvalumab PD-L1 PET in SCCHN patients, demonstrating the highest tumor-to-blood radio with a total dose of 10mg durvalumab. So far, no correlation of tumor PD-L1 expression with 89Zr-durvalumab-uptake and PD-L1 expression on archival tissue was found. Next step will be to correlate 89Zr-durvalumab PD-L1 PET tumor uptake with durvalumab treatment response in the phase 2 part of the PINCH study. Clinical trial information: NCT03829007 .

Association between gastrin-releasing peptide receptor expression as assessed with [68Ga]Ga-RM2 PET/CT and histopathological tumor regression after neoadjuvant chemotherapy in primary breast cancer

IntroductionThe gastrin-releasing peptide receptor is overexpressed in breast cancer (BC) tissue and can be visualized by positron emission tomography (PET) using the GRPR antagonist [68Ga]Ga-RM2. This study assessed tumor binding of RM2 before and after neoadjuvant chemotherapy (NAC) in primary BC with reference to residual tumor size in the resected specimen. Materials and methodsIn this retrospective study, five female patients with biopsy-confirmed estrogen receptor (ER)-positive primary BC (one with bilateral tumors) underwent [68Ga]Ga-RM2 PET/CT before and after NAC. PET/CT was acquired 1 h after injection of 143–224 MBq [68Ga]Ga-RM2. Time from pre-NAC PET to beginning of NAC was 23 ± 4.9 days, from end of NAC to post-NAC PET 18.7 ± 6.3 days, and from post-NAC PET to surgery 9.5 ± 10.8 days. In vivo tumor uptake of [68Ga]Ga-RM2 was assessed before and after NAC and correlated with histopathological response. ResultsAll tumors (6/6) showed strongly increased [68Ga]Ga-RM2 uptake compared to normal breast tissue on pre-NAC PET (mean SUVmax 13.2 ± 7.3; mean SUVpeak 9.4 ± 4.4). [68Ga]Ga-RM2 uptake was significantly reduced on post-NAC PET in all primary tumors (mean SUVmax 2.3 ± 0.8, −79 ± 11%; p = 0.0125; mean SUVpeak 1.6 ± 0.4, −79 ± 10%; p = 0.0096). Residual tumor size in resected specimens correlated well with SUVmax (r = 0.91, p = 0.0057) and SUVpeak (r = 0.88, p = 0.0196) on [68Ga]Ga-RM2 PET/CT after NAC. Conclusion and implications for patient careIn this pilot study, residual uptake of [68Ga]Ga-RM2 in ER-positive primary BC correlated well with residual vital tumor size after NAC. This suggests that [68Ga]Ga-RM2 PET/CT merits further investigation for response assessment to NAC in patients with ER-positive BC.

Radiosynthesis and preclinical evaluation of [18F]FEM as a potential novel PET probe for tumor imaging

In the 21st century, the incidence and mortality of cancer, one of the most challenging diseases in the world, have rapidly increased. The purpose of this study was to develop 2-(2-[18F]fluoroethoxy)ethyl 4-methylbenzenesulfonate ([18F]FEM) as a positron emission tomography (PET) agent for tumor imaging. In this study, [18F]FEM was synthesized with a good radiochemical yield (45.4 ± 5.8%), high specific radioactivity (over 25 GBq/μmol), and commendable radiochemical purity (over 99%). The octanol/water partition coefficient of [18F]FEM was 1.44 ± 0.04. The probe demonstrated good stability in vitro (phosphate-buffered saline (PBS) and mouse serum (MS)), and binding specificity to five different tumor cell lines (A549, PC-3, HCC827, U87, and MDA-MB-231). PET imaging of tumor-bearing mice showed that [18F]FEM specifically accumulated at the tumor site of the five different tumor cell lines. The average tumor-to-muscle (T/M) ratio was over 2, and the maximum T/M values reached about 3.5. The biodistribution and dynamic PET imaging showed that most probes were metabolized by the liver, whereas a small part was metabolized by the kidney. Moreover, dynamic brain images and quantitative data showed [18F]FEM can quickly cross the blood brain barrier (BBB) and quickly fade out, thereby suggesting it may be a promising candidate probe for the imaging of brain tumors. The presented results demonstrated that [18F]FEM is a promising probe for tumor PET imaging.

An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study

The predominant application of positron emission tomography (PET) in the field of oncology and radiotherapy and the significance of medical imaging research have led to an urgent need for effective approaches to PET volume analysis and the development of accurate and robust volume analysis techniques to support oncologists in their clinical practice, including diagnosis, arrangement of appropriate radiotherapy treatment, and evaluation of patients' response to therapy. This paper proposes an efficient optimized ensemble classifier to tackle the problem of analysis of squamous cell carcinoma in patient PET volumes. This optimized classifier is based on an artificial neural network (ANN), fuzzy C-means (FCM), an adaptive neuro-fuzzy inference system (ANFIS), K-means, and a self-organizing map (SOM). Four ensemble classifier machines are proposed in this study. The first three are built using a voting approach, an averaging technique, and weighted averaging, respectively. The fourth, novel ensemble classifier machine is based on the combination of a modified particle swarm optimization (PSO) approach and weighted averaging. Experimental National Electrical Manufacturers Association and International Electrotechnical Commission (NEMA IEC) body phantom and clinical PET studies of participants with laryngeal squamous cell carcinoma are used for the evaluation of the proposed approach. Superior results were achieved using the new optimized ensemble classifier when compared with the results from the investigated classifiers and the non-optimized ensemble classifiers. The proposed approach identified the region of interest class (tumor) with an average accuracy of 98.11% in clinical datasets of patients with laryngeal tumors. This system supports the expertise of clinicians in PET tumor analysis.