Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy

Inter- and intra-tumoral heterogeneity on [68Ga]Ga-DOTA-TATE/[68Ga]Ga-DOTA-TOC PET/CT predicts response to [177Lu]Lu-DOTA-TATE PRRT in neuroendocrine tumor patients

BACKGROUND

Indices of tumor heterogeneity on somatostatin receptor PET/CT scans may potentially serve as predictive biomarkers of treatment efficacy in neuroendocrine tumor (NET) patients undergoing [177Lu]Lu-DOTA-TATE PRRT.

METHODS

NET patients who underwent [177Lu]Lu-DOTA-TATE therapy at the University of Iowa from August 2018 to February 2021 were retrospectively evaluated. Radiomic features on the pre-PRRT somatostatin receptor PET/CT were evaluated using a custom MIM Software® LesionID workflow. Conventional PET/CT metrics of tumor burden, such as somatostatin receptor expression and tumor volume, were calculated in addition to the indices of tumor heterogeneity for each lesion (intra-lesional) and then summarized across all lesions throughout the body (inter-lesional). Endpoints included post-PRRT 24-month time to progression (TTP) and overall survival (OS). Cox regression models were used to assess the predictive ability of the imaging factors on post-PRRT 24-month TTP and OS. LASSO-penalized Cox regression was used to build a multivariable model for each outcome.

RESULTS

Eighty patients with a mean age of 65.1 years were included, with most (71.3%) completing 4 cycles of PRRT. Median TTP was 19.1 months, and OS at 60 months was 50%. A large degree of variability between patients was evidenced for imaging features related to somatostatin receptor expression. On multivariable analysis, total receptor expression and mean liver-corrected SUVmean were selected for 24-month TTP. The model was not able to significantly predict progression (C-statistic = 0.58, 95% CI 0.50-0.62). Total receptor expression and mean skewness were selected for OS. The resulting model was able to significantly predict death (C-statistic = 0.62, 95% CI 0.53-0.67), but the predictive ability was limited, as evidenced by the low C-statistic.

CONCLUSIONS

Our exploratory analysis provides preliminary results showing that imaging indices of inter- and intra-tumor heterogeneity from pretreatment PET/CT images may potentially predict treatment efficacy in NET patients undergoing [177Lu]Lu-DOTA-TATE therapy. However, prospective evaluation in a larger cohort is needed to further assess whether a comprehensive characterization of tumor heterogeneity within a patient can help guide treatment decisions.

Models using comprehensive, lesion-level, longitudinal [68Ga]Ga-DOTA-TATE PET-derived features lead to superior outcome prediction in neuroendocrine tumor patients treated with [177Lu]Lu-DOTA-TATE

PURPOSE

Somatostatin receptor (SSTR) imaging features are predictive of treatment outcome for neuroendocrine tumor (NET) patients receiving peptide receptor radionuclide therapy (PRRT). However, comprehensive (all metastatic lesions), longitudinal (temporal variation), and lesion-level measured features have never been explored. Such features allow for capturing the heterogeneity in disease response to treatment. Furthermore, models combining these features are lacking. In this work we evaluated the predictive power of comprehensive, longitudinal, lesion-level 68GA-SSTR-PET features combined with a multivariate linear regression (MLR) model.

METHODS

This retrospective study enrolled NET patients treated with [177Lu]Lu-DOTA-TATE and imaged with [68Ga]Ga-DOTA-TATE at baseline and post-therapy. All lesions were segmented, anatomically labeled, and longitudinally matched. Lesion-level uptake and variation in uptake were measured. Patient-level features were engineered and selected for modeling of progression-free survival (PFS). The model was validated via concordance index, patient classification (ROC analysis), and survival analysis (Kaplan-Meier and Cox proportional hazards). The MLR was benchmarked against single feature predictions.

RESULTS

Thirty-six NET patients were enrolled and stratified into poor and good responders (PFS ≥ 25 months). Four patient-level features were selected, the MLR concordance index was 0.826, and the AUC was 0.88 (0.85 specificity, 0.81 sensitivity). Survival analysis led to significant patient stratification (p<.001) and hazard ratio (3⨯10-5). Lastly, in a benchmark study, the MLR modeling approach outperformed all the single feature predictors.

CONCLUSION

Comprehensive, lesion-level, longitudinal 68GA-SSTR-PET analysis, combined with MLR modeling, leads to excellent predictions of PRRT outcome in NET patients, outperforming non-comprehensive, patient-level, and single time-point feature predictions.

MESSAGE

Neuroendocrine tumor, peptide receptor radionuclide therapy, Somatostatin Receptor Imaging, Outcome Prediction, Treatment Response Assessment.

Preoperative assessment of lymph nodal metastases with [68Ga]Ga-DOTATOC PET radiomics for improved surgical planning in well-differentiated pancreatic neuroendocrine tumours

PURPOSE

Accurate identification of lymph node (LN) metastases is pivotal for surgical planning of pancreatic neuroendocrine tumours (PanNETs); however, current imaging techniques have sub-optimal diagnostic sensitivity. Aim of this study is to investigate whether [68Ga]Ga-DOTATOC PET radiomics might improve the identification of LN metastases in patients with non-functioning PanNET (NF-PanNET) referred to surgical intervention.

METHODS

Seventy-two patients who performed preoperative [68Ga]Ga-DOTATOC PET between December 2017 and March 2022 for NF-PanNET. [68Ga]Ga-DOTATOC PET qualitative assessment of LN metastases was measured using diagnostic balanced accuracy (bACC), sensitivity (SN), specificity (SP), positive and negative predictive values (PPV, NPV). SUVmax, SUVmean, Somatostatin receptor density (SRD), total lesion SRD (TLSRD) and IBSI-compliant radiomic features (RFs) were obtained from the primary tumours. To predict LN involvement, these parameters were engineered, selected and used to train different machine learning models. Models were validated using tenfold repeated cross-validation and control models were developed. Models' bACC, SN, SP, PPV and NPV were collected and compared (Kruskal-Wallis, Mann-Whitney).

RESULTS

LN metastases were detected in 29/72 patients at histology. [68Ga]Ga-DOTATOC PET qualitative examination of LN involvement provided bACC = 60%, SN = 24%, SP = 95%, PPV = 78% and NPV = 65%. The best-performing radiomic model provided a bACC = 70%, SN = 77%, SP = 61%, PPV = 60% and NPV = 83% (outperforming the control model, p < 0.05*).

CONCLUSION

In this study, [68Ga]Ga-DOTATOC PET radiomics allowed to increase diagnostic sensitivity in detecting LN metastases from 24 to 77% in NF-PanNET patients candidate to surgery. Especially in case of micrometastatic involvement, this approach might assist clinicians in a better patients' stratification.

Liver Imaging in Gastroenteropancreatic Neuroendocrine Neoplasms

ABSTRACT

The incidence of neuroendocrine neoplasms (NENs) has gradually increased over the past few decades with the majority of patients presenting with metastases on initial presentation. The liver is the most common site of initial metastatic disease, and the presence of liver metastasis is an independent prognostic factor associated with a negative outcome. Because NENs are heterogenous neoplasms with variable differentiation, grading, and risk of grade transformation over time, accurate diagnosis and management of neuroendocrine liver lesions are both important and challenging. This is particularly so with the multiple liver-directed treatment options available. In this review article, we discuss the diagnosis, treatment, and response evaluation of NEN liver metastases.

Recent developments in the diagnosis of pancreatic neuroendocrine neoplasms

INTRODUCTION

Pancreatic Neuroendocrine Neoplasms (PanNENs) are characterized by a highly heterogeneous clinical and biological behavior, making their diagnosis challenging. PanNENs diagnostic work-up mainly relies on biochemical markers, pathological examination, and imaging evaluation. The latter includes radiological imaging (i.e. computed tomography [CT] and magnetic resonance imaging [MRI]), functional imaging (i.e. 68Gallium [68 Ga]Ga-DOTA-peptide PET/CT and Fluorine-18 fluorodeoxyglucose [18F]FDG PET/CT), and endoscopic ultrasound (EUS) with its associated procedures.

AREAS COVERED

This review provides a comprehensive assessment of the recent advancements in the PanNENs diagnostic field. PubMed and Embase databases were used for the research, performed from inception to October 2023.

EXPERT OPINION

A deeper understanding of PanNENs biology, recent technological improvements in imaging modalities, as well as progresses achieved in molecular and cytological assays, are fundamental players for the achievement of early diagnosis and enhanced preoperative characterization of PanNENs. A multimodal diagnostic approach is required for a thorough disease assessment.

Visual and whole-body quantitative analyses of 68 Ga-DOTATATE PET/CT for prognosis of outcome after PRRT with 177Lu-DOTATATE

BACKGROUND

Somatostatin receptors (SSTR) represent an ideal target for nuclear theranostics applications in neuroendocrine tumors (NET). Studies suggest that high uptake on SSTR-PET is associated with response to SSTR peptide receptor radionuclide therapy (PRRT). The purpose of this study was to evaluate the role of baseline whole-body (WB) 68 Ga-DOTATATE PET/CT (SSTR-PET) quantitative parameters, and the presence of NET lesions without uptake on SSTR-PET, as outcome prognosticator in patients with NET treated with PRRT.

METHODS

Patients with NET who underwent at least 4 177Lu-DOTATATE PRRT cycles between 07/2016 and 03/2021 were included in this retrospective analysis if they fulfilled the following inclusion criteria: SSTR-PET within 6 months of 1st PRRT cycle, follow-up CT and/or MRI performed > 6 months after the 4th cycle of PRRT. The SSTR-PET analysis consisted of a visual and a quantitative analysis done independently by two board-certified physicians. The visual analysis assessed the presence of NET lesions visible on the SSTR-PET co-registered CT. The quantitative analysis consisted in contouring all SSTR-avid lesions on SSTR-PET and extracting WB quantitative parameters: SUVmean (WB-SUVmean), SUVmax of the lesion with highest uptake (H-SUVmax), and tumor volume (WB-TV). WB-SSTR-PET parameters and the presence of SSTR-PET-negative lesions were correlated to radiologic response (assessed by RECIST 1.1 criteria) and progression-free survival (PFS). Fisher's exact test, Mann-Whitney's U test and Kaplan-Meier curves with Cox-regression analysis were used for the statistical analysis.

RESULTS

Forty patients (F/M: 21/19; 34/40 with gastro-entero-pancreatic (GEP) NET, 6/40 with non-GEP NET) were included in the analysis. The median follow-up period after the 4th PRRT cycle was 25.7 months (range 15.2-59.1). Fourteen/40 (35%) patients showed radiologic response (RECIST PR). PFS event was observed in 17/40 (42.5%) patients. Thirteen/40 (32.5%) patients had SSTR-PET-negative lesions at baseline. Higher WB-SUVmean and H-SUVmax were associated with better response (p = 0.015 and 0.005, respectively). The presence of SSTR-PET-negative lesions and lower WB-SUVmean were associated with shorter PFS (p = 0.026 and 0.008, respectively).

CONCLUSION

Visual and quantitative analyses of baseline SSTR-PET can yield valuable information to prognosticate outcomes after 177Lu-DOTATATE PRRT.

Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens

Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

Essentials of Theranostics: A Guide for Physicians and Medical Physicists

Radiopharmaceutical therapies (RPTs) are gaining increased interest with the recent emergence of novel safe and effective theranostic agents, improving outcomes for thousands of patients. The term theranostics refers to the use of diagnostic and therapeutic agents that share the same molecular target; a major step toward precision medicine, especially for oncologic applications. The authors dissect the fundamentals of theranostics in nuclear medicine. First, they explain the radioactive decay schemes and the characteristics of emitted electromagnetic radiation used for imaging, as well as particles used for therapeutic purposes, followed by the interaction of the different types of radiation with tissue. These concepts directly apply to clinical RPTs and play a major role in the efficacy and toxicity profile of different radiopharmaceutical agents. Personalized dosimetry is a powerful tool that can help estimate patient-specific absorbed doses, in tumors as well as normal organs. Dosimetry in RPT is an area of active investigation, as most of what we know about the relationship between delivered dose and tissue damage is extrapolated from external-beam radiation therapy; more research is needed to understand this relationship as it pertains to RPTs. Tumor heterogeneity is increasingly recognized as an important prognostic factor. Novel molecular imaging agents, often in combination with fluorine 18-fluorodeoxyglucose, are crucial for assessment of target expression in the tumor and potential hypermetabolic disease that may lack the molecular target expression. ©RSNA, 2023 Test Your Knowledge questions are available in the supplemental material.

Prediction of 177Lu-DOTATATE Therapy Outcomes in Neuroendocrine Tumor Patients Using Semi-Automatic Tumor Delineation on 68Ga-DOTATATE PET/CT

BACKGROUND

Treatment of metastatic neuroendocrine tumors (NET) with 177Lu-DOTATATE peptide receptor radionuclide therapy (PRRT) results in favorable response only in a subset of patients. We investigated the prognostic value of quantitative pre-treatment semi-automatic 68Ga-DOTATATE PET/CT analysis in NET patients treated with PRRT.

METHODS

The medical records of 94 NET patients who received at least one cycle of PRRT at a single institution were retrospectively reviewed. On each pre-treatment 68Ga-DOTATATE PET/CT, the total tumor volume (TTV), maximum tumor standardized uptake value for the patient (SUVmax), and average uptake in the lesion with the lowest radiotracer uptake (SUVmin) were determined with a semi-automatic tumor delineation method. Progression-free survival (PFS) and overall survival (OS) among the patients were compared based on optimal cutoff values for the imaging parameters.

RESULTS

On Kaplan-Meier analysis and univariate Cox regression, significantly shorter PFS was observed in patients with lower SUVmax, lower SUVmin, and higher TTV. On multivariate Cox regression, lower SUVmin and higher TTV remained predictive of shorter PFS. Only higher TTV was found to be predictive of shorter OS on Kaplan-Meier and Cox regression analyses. In a post hoc Kaplan-Meier analysis, patients with at least one high-risk feature (low SUVmin or high TTV) showed shorter PFS and OS, which may be the most convenient parameter to measure in clinical practice.

CONCLUSIONS

The tumor volume and lowest lesion uptake on 68Ga-DOTATATE PET/CT can predict disease progression following PRRT in NET patients, with the former also predictive of overall survival. NET patients at risk for poor outcomes following PRRT can be identified with semi-automated quantitative analysis of 68Ga-DOTATATE PET/CT.

A Machine Learning Approach Using [18F]FDG PET-Based Radiomics for Prediction of Tumor Grade and Prognosis in Pancreatic Neuroendocrine Tumor

PURPOSE

We sought to develop and validate machine learning (ML) models for predicting tumor grade and prognosis using 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography (PET)-based radiomics and clinical features in patients with pancreatic neuroendocrine tumors (PNETs).

PROCEDURES

A total of 58 patients with PNETs who underwent pretherapeutic [18F]FDG PET/computed tomography (CT) were retrospectively enrolled. PET-based radiomics extracted from segmented tumor and clinical features were selected to develop prediction models by the least absolute shrinkage and selection operator feature selection method. The predictive performances of ML models using neural network (NN) and random forest algorithms were compared by the areas under the receiver operating characteristic curves (AUROCs) and validated by stratified five-fold cross validation.

RESULTS

We developed two separate ML models for predicting high-grade tumors (Grade 3) and tumors with poor prognosis (disease progression within two years). The integrated models consisting of clinical and radiomic features with NN algorithm showed the best performances than the other models (stand-alone clinical or radiomics models). The performance metrics of the integrated model by NN algorithm were AUROC of 0.864 in the tumor grade prediction model and AUROC of 0.830 in the prognosis prediction model. In addition, AUROC of the integrated clinico-radiomics model with NN was significantly higher than that of tumor maximum standardized uptake model in predicting prognosis (P < 0.001).

CONCLUSIONS

Integration of clinical features and [18F]FDG PET-based radiomics using ML algorithms improved the prediction of high-grade PNET and poor prognosis in a non-invasive manner.

Image-Guided Precision Medicine in the Diagnosis and Treatment of Pheochromocytomas and Paragangliomas

In this comprehensive review, we aimed to discuss the current state-of-the-art medical imaging for pheochromocytomas and paragangliomas (PPGLs) diagnosis and treatment. Despite major medical improvements, PPGLs, as with other neuroendocrine tumors (NETs), leave clinicians facing several challenges; their inherent particularities and their diagnosis and treatment pose several challenges for clinicians due to their inherent complexity, and they require management by multidisciplinary teams. The conventional concepts of medical imaging are currently undergoing a paradigm shift, thanks to developments in radiomic and metabolic imaging. However, despite active research, clinical relevance of these new parameters remains unclear, and further multicentric studies are needed in order to validate and increase widespread use and integration in clinical routine. Use of AI in PPGLs may detect changes in tumor phenotype that precede classical medical imaging biomarkers, such as shape, texture, and size. Since PPGLs are rare, slow-growing, and heterogeneous, multicentric collaboration will be necessary to have enough data in order to develop new PPGL biomarkers. In this nonsystematic review, our aim is to present an exhaustive pedagogical tool based on real-world cases, dedicated to physicians dealing with PPGLs, augmented by perspectives of artificial intelligence and big data.

Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs)

Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs.

Prognostic Value of Somatostatin Receptor-Derived Volumetric Parameters from a Hybrid Standardized Uptake Value Thresholding Method in Patients with 68Ga-DOTATATE-Avid Stage IV Neuroendocrine Neoplasms: A Preliminary Study

INTRODUCTION

The ability of PET/CT imaging to delineate neuroendocrine neoplasms (NENs) and predict prognosis in affected patients is often compromised by substantial uptake heterogeneity. We hereby proposed a hybrid standardized uptake value (SUV) thresholding algorithm to extract volumetric parameters from somatostatin receptor (SSTR) PET/CT imaging and investigate their prognostic performance in patients with 68Ga-DOTATATE-avid stage IV NENs.

METHODS

For 38 retrospectively enrolled patients, we used either fixed SUV thresholding of normal liver parenchyma (method A), 41% of the SUVmax for each lesion (method B), or a hybrid method (method A for liver metastases; fixed SUV threshold of normal bone for bone metastases; method B for primary tumors and other metastases) to quantify the whole-body SSTR-expressing tumor volume (SRETVwb) and total lesion SSTR expression (TLSREwb). Patient survival was also recorded and analyzed.

RESULTS

PET/CT images revealed heterogeneous uptake of 68Ga-DOTATATE at primary and metastatic sites. Progression-free survival (PFS) and overall survival (OS) were negatively correlated with the extent of liver or bone metastases (p < 0.05), but not significantly correlated with tumor grade or 18F-FDG PET/CT positivity. By the hybrid method, PFS was significantly shorter in patients with high SRETVwb, and OS was significantly shorter in those with high SRETVwb and TLSREwb (p < 0.05). However, when derived from method A or method B, neither SRETVwb nor TLSREwb could predict patient outcomes.

CONCLUSION

Compared with other methods used in 68Ga-DOTATATE-avid stage IV NENs, our hybrid SUV thresholding method demonstrated robustness, with greater precision, reliability, and prognostic power.

Tumour Heterogeneity and the Consequent Practical Challenges in the Management of Gastroenteropancreatic Neuroendocrine Neoplasms

Tumour heterogeneity is a common phenomenon in neuroendocrine neoplasms (NENs) and a significant cause of treatment failure and disease progression. Genetic and epigenetic instability, along with proliferation of cancer stem cells and alterations in the tumour microenvironment, manifest as intra-tumoural variability in tumour biology in primary tumours and metastases. This may change over time, especially under selective pressure during treatment. The gastroenteropancreatic (GEP) tract is the most common site for NENs, and their diagnosis and treatment depends on the specific characteristics of the disease, in particular proliferation activity, expression of somatostatin receptors and grading. Somatostatin receptor expression has a major role in the diagnosis and treatment of GEP-NENs, while Ki-67 is also a valuable prognostic marker. Intra- and inter-tumour heterogeneity in GEP-NENS, however, may lead to inaccurate assessment of the disease and affect the reliability of the available diagnostic, prognostic and predictive tests. In this review, we summarise the current available evidence of the impact of tumour heterogeneity on tumour diagnosis and treatment of GEP-NENs. Understanding and accurately measuring tumour heterogeneity could better inform clinical decision making in NENs.

CT-based radiomics to distinguish progressive from stable neuroendocrine liver metastases treated with somatostatin analogues: an explorative study

BACKGROUND

Accurate response evaluation in patients with neuroendocrine liver metastases (NELM) remains a challenge. Radiomics has shown promising results regarding response assessment.

PURPOSE

To differentiate progressive (PD) from stable disease (SD) with radiomics in patients with NELM undergoing somatostatin analogue (SSA) treatment.

MATERIAL AND METHODS

A total of 46 patients with histologically confirmed gastroenteropancreatic neuroendocrine tumors (GEP-NET) with ≥1 NELM and ≥2 computed tomography (CT) scans were included. Response was assessed with Response Evaluation Criteria in Solid Tumors (RECIST1.1). Hepatic target lesions were manually delineated and analyzed with radiomics. Radiomics features were extracted from each NELM on both arterial-phase (AP) and portal-venous-phase (PVP) CT. Multiple instance learning with regularized logistic regression via LASSO penalization (with threefold cross-validation) was used to classify response. Three models were computed: (i) AP model; (ii) PVP model; and (iii) AP + PVP model for a lesion-based and patient-based outcome. Next, clinical features were added to each model.

RESULTS

In total, 19 (40%) patients had PD. Median follow-up was 13 months (range 1-50 months). Radiomics models could not accurately classify response (area under the curve 0.44-0.60). Adding clinical variables to the radiomics models did not significantly improve the performance of any model.

CONCLUSION

Radiomics features were not able to accurately classify response of NELM on surveillance CT scans during SSA treatment.

Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers

Gastrointestinal (GI) cancers, consisting of a wide spectrum of pathologies, have become a prominent health issue globally. Despite medical imaging playing a crucial role in the clinical workflow of cancers, standard evaluation of different imaging modalities may provide limited information. Accurate tumor detection, characterization, and monitoring remain a challenge. Progress in quantitative imaging analysis techniques resulted in "radiomics", a promising methodical tool that helps to personalize diagnosis and treatment optimization. Radiomics, a sub-field of computer vision analysis, is a bourgeoning area of interest, especially in this era of precision medicine. In the field of oncology, radiomics has been described as a tool to aid in the diagnosis, classification, and categorization of malignancies and to predict outcomes using various endpoints. In addition, machine learning is a technique for analyzing and predicting by learning from sample data, finding patterns in it, and applying it to new data. Machine learning has been increasingly applied in this field, where it is being studied in image diagnosis. This review assesses the current landscape of radiomics and methodological processes in GI cancers (including gastric, colorectal, liver, pancreatic, neuroendocrine, GI stromal, and rectal cancers). We explain in a stepwise fashion the process from data acquisition and curation to segmentation and feature extraction. Furthermore, the applications of radiomics for diagnosis, staging, assessment of tumor prognosis and treatment response according to different GI cancer types are explored. Finally, we discussed the existing challenges and limitations of radiomics in abdominal cancers and investigate future opportunities.

Nuclear Medicine and Radiological Imaging of Pancreatic Neuroendocrine Neoplasms: A Multidisciplinary Update

Pancreatic neuroendocrine neoplasms (panNENs) are part of a large family of tumors arising from the neuroendocrine system. PanNENs show low-intermediate tumor grade and generally high somatostatin receptor (SSTR) expression. Therefore, panNENs benefit from functional imaging with ⁶⁸Ga-somatostatin analogues (SSA) for diagnosis, staging, and treatment choice in parallel with morphological imaging. This narrative review aims to present conventional imaging techniques and new perspectives in the management of panNENs, providing the clinicians with useful insight for clinical practice. The ⁶⁸Ga-SSA PET/CT is the most widely used in panNENs, not only fr diagnosis and staging purpose but also to characterize the biology of the tumor and its responsiveness to SSAs. On the contrary, the ¹⁸F-Fluordeoxiglucose (FDG) PET/CT is not employed systematically in all panNEN patients, being generally preferred in G2-G3, to predict aggressiveness and progression rate. The combination of ⁶⁸Ga-SSA PET/CT and ¹⁸F-FDG PET/CT can finally suggest the best therapeutic strategy. Other radiopharmaceuticals are ⁶⁸Ga-exendin-4 in case of insulinomas and ¹⁸F-dopamine (DOPA), which can be helpful in SSTR-negative tumors. New promising but still-under-investigation radiopharmaceuticals include radiolabeled SSTR antagonists and ¹⁸F-SSAs. Conventional imaging includes contrast enhanced CT and multiparametric MRI. There are now enriched by radiomics, a new non-invasive imaging approach, very promising to early predict tumor response or progression.

The Role of 68 Ga-DOTA-SSA PET/CT in the Management and Prediction of Peptide Receptor Radionuclide Therapy Response for Patients With Neuroendocrine Tumors : A Systematic Review and Meta-analysis

PURPOSE

The aim of this study was to identify and evaluate the role of 68 Ga-DOTA-somatostatin analog (SSA) PET/CT in guiding treatment for patients with neuroendocrine tumors (NETs) based on published literature, with specific focus on the ability of PET/CT to impact clinical management and predict peptide receptor radionuclide therapy (PRRT) response.

PATIENTS AND METHODS

A systematic literature search of articles up to December 2021 was performed using PubMed and Scopus. Eligible studies included ≥10 patients with confirmed or suspected NETs who had undergone pretreatment staging 68 Ga-DOTA-SSA PET/CT. A meta-analysis using the random-effects model was conducted to determine the overall change in management after PET/CT, whereas PET/CT-derived parameters that correlated with PRRT outcome were summarized from studies that assessed its predictive capabilities.

RESULTS

A total of 39 studies were included in this systemic review, of which 2266 patients from 24 studies were included for meta-analysis. We showed that PET/CT resulted in a change in clinical management in 36% (95% confidence interval, 31%-41%; range, 3%-66%) of patients. Fifteen studies consisting of 618 patients examined the prognostic ability of 68 Ga-DOTA-SSA PET/CT for PRRT. Of those, 8 studies identified a higher pretreatment SUV to favor PRRT, and 4 identified PET-based radiomic features for somatostatin receptor heterogeneity to be predictive of PRRT response.

CONCLUSIONS

Along with its diagnostic abilities, 68 Ga-DOTA-SSA PET/CT can impact treatment decision-making and may predict PRRT response in patients with NETs. More robust studies should be conducted to better elucidate the prognostic role of somatostatin receptor PET/CT in optimizing treatment for clinical outcome.

Neuroendocrine Tumors and Peptide Receptor Radionuclide Therapy: When Is the Right Time?

Since its approval in 2018 by the US Food and Drug Administration, peptide receptor radionuclide therapy (PRRT) has become a mainstay in the treatment of neuroendocrine tumors. Lutetium-177-DOTATATE, the only approved agent, is indicated for the treatment of gastroenteropancreatic-neuroendocrine tumors. Although patient selection appears straightforward with somatostatin receptor-positron emission tomography, there is considerable complexity when deciding which patients to treat and when to start PRRT. Herein, we review the many factors that affect patient selection, focusing on the optimal patients to treat. Although significant effort has been expended to determine which patients benefit the most from PRRT, a validated predictive biomarker remains elusive. Although PRRT has been used for more than 2 decades in Europe and standards of care exist for safe treatment, there remain numerous questions regarding when PRRT should be used relative to other treatments. It is important to remember that multidisciplinary discussions are essential. Currently, there are a number of ongoing studies looking to assess the efficacy of PRRT compared with other treatment options and to optimize treatment through combination therapy, different dosing strategies, or use of different radionuclides and radioligands.

GEP-NET radiomics: a systematic review and radiomics quality score assessment

OBJECTIVE

The number of radiomics studies in gastroenteropancreatic neuroendocrine tumours (GEP-NETs) is rapidly increasing. This systematic review aims to provide an overview of the available evidence of radiomics for clinical outcome measures in GEP-NETs, to understand which applications hold the most promise and which areas lack evidence.

METHODS

PubMed, Embase, and Wiley/Cochrane Library databases were searched and a forward and backward reference check of the identified studies was executed. Inclusion criteria were (1) patients with GEP-NETs and (2) radiomics analysis on CT, MRI or PET. Two reviewers independently agreed on eligibility and assessed methodological quality with the radiomics quality score (RQS) and extracted outcome data.

RESULTS

In total, 1364 unique studies were identified and 45 were included for analysis. Most studies focused on GEP-NET grade and differential diagnosis of GEP-NETs from other neoplasms, while only a minority analysed treatment response or long-term outcomes. Several studies were able to predict tumour grade or to differentiate GEP-NETs from other lesions with a good performance (AUCs 0.74-0.96 and AUCs 0.80-0.99, respectively). Only one study developed a model to predict recurrence in pancreas NETs (AUC 0.77). The included studies reached a mean RQS of 18%.

CONCLUSION

Although radiomics for GEP-NETs is still a relatively new area, some promising models have been developed. Future research should focus on developing robust models for clinically relevant aims such as prediction of response or long-term outcome in GEP-NET, since evidence for these aims is still scarce.

KEY POINTS

• The majority of radiomics studies in gastroenteropancreatic neuroendocrine tumours is of low quality. • Most evidence for radiomics is available for the identification of tumour grade or differentiation of gastroenteropancreatic neuroendocrine tumours from other neoplasms. • Radiomics for the prediction of response or long-term outcome in gastroenteropancreatic neuroendocrine tumours warrants further research.

Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers

The objective of this review was to summarize published radiomics studies dealing with infradiaphragmatic cancers, blood malignancies, melanoma, and musculoskeletal cancers, and assess their quality. PubMed database was searched from January 1990 to February 2022 for articles performing radiomics on PET imaging of at least 1 specified tumor type. Exclusion criteria includd: non-oncological studies; supradiaphragmatic tumors; reviews, comments, cases reports; phantom or animal studies; technical articles without a clinically oriented question; studies including <30 patients in the training cohort. The review database contained PMID, first author, year of publication, cancer type, number of patients, study design, independent validation cohort and objective. This database was completed twice by the same person; discrepant results were resolved by a third reading of the articles. A total of 162 studies met inclusion criteria; 61 (37.7%) studies included >100 patients, 13 (8.0%) were prospective and 61 (37.7%) used an independent validation set. The most represented cancers were esophagus, lymphoma, and cervical cancer (n = 24, n = 24 and n = 19 articles, respectively). Most studies focused on 18F-FDG, and prognostic and response to treatment objectives. Although radiomics and artificial intelligence are technically challenging, new contributions and guidelines help improving research quality over the years and pave the way toward personalized medicine.

Predictive Factors for Resistant Disease with Medical/Radiologic/Liver-Directed Anti-Tumor Treatments in Patients with Advanced Pancreatic Neuroendocrine Neoplasms: Recent Advances and Controversies

Simple Summary

Tumor resistance, both primary and acquired, is leading to increased complexity in the nonsurgical treatment of patients with advanced panNENs, which would be greatly helped by reliable prognostic/predictive factors. The importance in identifying resistance is being contributed to by the increased array of possible treatments available for treating resistant advanced disease; the variable clinical course as well as response to any given treatment approach of patients within one staging or grading system, the advances in imaging which are providing increasing promising results/parameters that correlate with grading/outcome/resistance, the increased understanding of the molecular pathogenesis providing promising prognostic markers, all of which can contribute to selecting the best treatment to overcome resistance disease. Several factors have been identified that have prognostic/predictive value for identifying development resistant disease and affecting overall survival (OS)/PFS with various nonsurgical treatments of patients with advanced panNENs. Prognostic factors identified for patients with advanced panNENs for both OS/PFSs include various clinically-related factors (clinical, laboratory/biological markers, imaging, treatment-related factors), pathological factors (histological, classification, grading) and molecular factors. Particularly important prognostic factors for the different treatment modalities studies are the recent grading systems. Most prognostic factors for each treatment modality for OS/PFS are not specific for a given treatment option. These advances have generated several controversies and new unanswered questions, particularly those related to their possible role in predicting the possible sequence of different anti-tumor treatments in patients with different presentations. Each of these areas is reviewed in this paper.

Abstract

Purpose: Recent advances in the diagnosis, management and nonsurgical treatment of patients with advanced pancreatic neuroendocrine neoplasms (panNENs) have led to an emerging need for sensitive and useful prognostic factors for predicting responses/survival. Areas covered: The predictive value of a number of reported prognostic factors including clinically-related factors (clinical/laboratory/imaging/treatment-related factors), pathological factors (histological/classification/grading), and molecular factors, on therapeutic outcomes of anti-tumor medical therapies with molecular targeting agents (everolimus/sunitinib/somatostatin analogues), chemotherapy, radiological therapy with peptide receptor radionuclide therapy, or liver-directed therapies (embolization/chemoembolization/radio-embolization (SIRTs)) are reviewed. Recent findings in each of these areas, as well as remaining controversies and uncertainties, are discussed in detail, particularly from the viewpoint of treatment sequencing. Conclusions: The recent increase in the number of available therapeutic agents for the nonsurgical treatment of patients with advanced panNENs have raised the importance of prognostic factors predictive for therapeutic outcomes of each treatment option. The establishment of sensitive and useful prognostic markers will have a significant impact on optimal treatment selection, as well as in tailoring the therapeutic sequence, and for maximizing the survival benefit of each individual patient. In the paper, the progress in this area, as well as the controversies/uncertainties, are reviewed.

[68Ga]DOTATOC PET/CT Radiomics to Predict the Response in GEP-NETs Undergoing [177Lu]DOTATOC PRRT: The “Theragnomics” Concept

Despite impressive results, almost 30% of NET do not respond to PRRT and no well-established criteria are suitable to predict response. Therefore, we assessed the predictive value of radiomics [68Ga]DOTATOC PET/CT images pre-PRRT in metastatic GEP NET. We retrospectively analyzed the predictive value of radiomics in 324 SSTR-2-positive lesions from 38 metastatic GEP-NET patients (nine G1, 27 G2, and two G3) who underwent restaging [68Ga]DOTATOC PET/CT before complete PRRT with [177Lu]DOTATOC. Clinical, laboratory, and radiological follow-up data were collected for at least six months after the last cycle. Through LifeX, we extracted 65 PET features for each lesion. Grading, PRRT number of cycles, and cumulative activity, pre- and post-PRRT CgA values were also considered as additional clinical features. [68Ga]DOTATOC PET/CT follow-up with the same scanner for each patient determined the disease status (progression vs. response in terms of stability/reduction/disappearance) for each lesion. All features (PET and clinical) were also correlated with follow-up data in a per-site analysis (liver, lymph nodes, and bone), and for features significantly associated with response, the Δradiomics for each lesion was assessed on follow-up [68Ga]DOTATOC PET/CT performed until nine months post-PRRT. A statistical system based on the point-biserial correlation and logistic regression analysis was used for the reduction and selection of the features. Discriminant analysis was used, instead, to obtain the predictive model using the k-fold strategy to split data into training and validation sets. From the reduction and selection process, HISTO_Skewness and HISTO_Kurtosis were able to predict response with an area under the receiver operating characteristics curve (AUC ROC), sensitivity, and specificity of 0.745, 80.6%, 67.2% and 0.722, 61.2%, 75.9%, respectively. Moreover, a combination of three features (HISTO_Skewness; HISTO_Kurtosis, and Grading) did not improve the AUC significantly with 0.744. SUVmax. However, it could not predict response to PRRT (p = 0.49, AUC 0.523). The presented preliminary “theragnomics” model proved to be superior to conventional quantitative parameters to predict the response of GEP-NET lesions in patients treated with complete [177Lu]DOTATOC PRRT, regardless of the lesion site.

Predictive and Prognostic Role of Pre-Therapy and Interim 68Ga-DOTATOC PET/CT Parameters in Metastatic Advanced Neuroendocrine Tumor Patients Treated with PRRT

Simple Summary

Although a significant improvement has been achieved in the management of metastatic neuroendocrine tumor (NET), disease progression is observed in 20–30% of patients treated with peptide receptor radionuclide therapy (PRRT). Therefore, the early identification of patients who are at high risk of treatment failure is important to avoid futile therapy toxicities. The aim of this study was to identify biomarkers derived from baseline and interim 68Ga-DOTATOC PET/CT in patients undergoing PRRT. In 46 metastatic NET patients with available baseline and interim PET, only baseline total tumor volume (bTV) was able to discriminate responders to PRRT (partial response or stable disease) vs. non-responders. Patients with high bTV had also the worst overall survival. bTV, an imaging biomarker, integrated in the initial workup of NET patients could improve risk stratification and contribute to a tailored therapy approach.

Abstract

Peptide receptor radionuclide therapy (PRRT) is an effective therapeutic option in patients with metastatic neuroendocrine tumor (NET). However, PRRT fails in about 15–30% of cases. Identification of biomarkers predicting the response to PRRT is essential for treatment tailoring. We aimed to evaluate the predictive and prognostic role of semiquantitative and volumetric parameters obtained from the 68Ga-DOTATOC PET/CT before therapy (bPET) and after two cycles of PRRT (iPET). A total of 46 patients were included in this retrospective analysis. The primary tumor was 78% gastroenteropancreatic (GEP), 13% broncho-pulmonary and 9% of unknown origin. 35 patients (76.1%) with stable disease or partial response after PRRT were classified as responders and 11 (23.9%) as non-responders. Logistic regression analysis identified that baseline total volume (bTV) was associated with therapy outcome (OR 1.17; 95%CI 1.02–1.32; p = 0.02). No significant association with PRRT response was observed for other variables. High bTV was confirmed as the only variable independently associated with OS (HR 12.76, 95%CI 1.53–107, p = 0.01). In conclusion, high bTV is a negative predictor for PRRT response and is associated with worse OS rates. Early iPET during PRRT apparently does not provide information useful to change the management of NET patients.

The association between lesion tracer uptake on 68Ga-DOTATATE PET with morphological response to 177Lu-DOTATATE therapy in patients with progressive metastatic neuroendocrine tumors

PURPOSE

To determine in a group of patients with progressive metastatic neuroendocrine tumors (PM-NETs) treated with 177Lu-DOTATATE whether a correlation exists between somatostatin receptor (SSTR)-2 expression in various tumors on baseline 68Ga-DOTATATE PET and their response to therapy. A secondary aim was to determine whether an association exists between tumor product of diameter (POD) and PET-derived Krenning score.

MATERIALS METHODS

Patients treated PM-NETs who had SSTR-2 overexpression (SSTR-RADS 5) on screening 68Ga-DOTATATE PET and CT at baseline and 3 months after therapy completion were included. Marker lesions on baseline CT were reassessed on CT after therapy using adapted Southwest Oncology Group solid tumor evaluation criteria. For each lesion, bidimensional diameter on CT and SSTR expression on PET (SSTR-RADS uptake score & PET-derived Krenning score) were recorded. Logistic regression models fitted through generalized estimating equations were used to assess for an association between SSTR expression and response to therapy, or lesion's POD.

RESULTS

Forty-one patients with SSTR-RADS 5 PM-NETs treated with 177Lu-DOTATATE were included. There were 135 marker lesions (mean 3.2 lesions/patient) with Krenning score of 4 (n = 74), 3 (n = 44) or 2 (n = 17). There was no association found between SSTR-2 expression, as determined by SSTR-RADS uptake score or PET-derived Krenning score, and POD or response to therapy.

CONCLUSION

In patients with SSTR-RADS 5 PM-NETs treated with 177Lu-DOTATATE, there was similar response to therapy for all lesions with PET-generated Krenning score ≥2. No correlation was found between lesion's POD and level of tracer uptake.

Gallium-68-somatostatin receptor PET/CT parameters as potential prognosticators for clinical time to progression after peptide receptor radionuclide therapy: a cohort study

Background

Early [⁶⁸Ga]Ga-DOTA-TOC PET/CT imaging after peptide receptor radionuclide therapy (PRRT) in neuroendocrine neoplasm patients is often used as a prognosticator for survival, but lacks validity. This study investigates the prognostic value of changes in PET parameters after PRRT.

Methods

Baseline and follow-up [⁶⁸Ga]Ga-DOTA-TOC PET/CT scans of all patients treated with PRRT were delineated automatically. Total lesion somatostatin receptor expression (TL-SSTR) and somatostatin receptor expressing tumor volume (SSTR-TV) were used as covariates in Cox proportional hazard models to predict time-to-new treatment.

Results

In twenty patients, median time-to-new treatment was 19.3 months (range [3.8; 36.2]). Absolute and percentual changes in both PET parameters were not associated with time-to-new treatment. A significant relation between independent baseline and follow-up SSTR-TV and follow-up TL-SSTR, and time-to-new treatment was identified.

Conclusions

Automatically derived [⁶⁸Ga]Ga-DOTA-TOC PET/CT parameters are easy to acquire and may be of prognostic value after completing PRRT. Acquiring SSTR-TV or TL-SSTR parameters at baseline and during follow-up can be of value in identifying a patient’s prognosis.

Current update on imaging for pancreatic neuroendocrine neoplasms

Pancreatic neuroendocrine neoplasms (panNEN) are a heterogeneous group of tumors with differing pathological, genetic, and clinical features. Based on clinical findings, they may be categorized into functioning and nonfunctioning tumors. Adoption of the 2017 World Health Organization classification system, particularly its differentiation between grade 3, well-differentiated pancreatic neuroendocrine tumors (panNET) and grade 3, poorly-differentiated pancreatic neuroendocrine carcinomas (panNEC) has emphasized the role imaging plays in characterizing these lesions. Endoscopic ultrasound can help obtain biopsy specimen and assess tumor margins and local spread. Enhancement patterns on computed tomography (CT) and magnetic resonance imaging (MRI) may be used to classify panNEN. Contrast enhanced MRI and diffusion-weighted imaging have been reported to be useful for characterization of panNEN and quantifying metastatic burden. Current and emerging radiotracers have broadened the utility of functional imaging in evaluating panNEN. Fluorine-18 fluorodeoxyglucose positron emission tomography (PET)/CT and somatostatin receptor imaging such as Gallium-68 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid–octreotate PET/CT may be useful for improved identification of panNEN in comparison to anatomic modalities. These new techniques can also play a direct role in optimizing the selection of treatment for individuals and predicting tumor response based on somatostatin receptor expression. In addition, emerging methods of radiomics such as texture analysis may be a potential tool for staging and outcome prediction in panNEN, however further investigation is required before clinical implementation.

Added Value of Tomoelastography for Characterization of Pancreatic Neuroendocrine Tumor Aggressiveness Based on Stiffness

Simple Summary

The prediction of pancreatic neuroendocrine tumor (PNET) aggressiveness is important for treatment planning. The aim of this study was to evaluate the diagnostic performance of magnetic resonance elastography (MRE) with tomoelastography postprocessing (tomoelastography) in differentiating PNET from healthy pancreatic tissue and to correlate PNET stiffness with aggressiveness using asphericity derived from positron emission tomography (PET) as reference. In this prospective study we showed in a group of 13 patients with PNET that tomoelastography detected PNET by increased stiffness (p < 0.01) with a high diagnostic performance (AUC = 0.96). PNET was positively correlated with PET derived asphericity (r = 0.81). Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.

Abstract

Purpose: To evaluate the diagnostic performance of tomoelastography in differentiating pancreatic neuroendocrine tumors (PNETs) from healthy pancreatic tissue and to assess the prediction of tumor aggressiveness by correlating PNET stiffness with PET derived asphericity. Methods: 13 patients with PNET were prospectively compared to 13 age-/sex-matched heathy volunteers (CTR). Multifrequency MR elastography was combined with tomoelastography-postprocessing to provide high-resolution maps of shear wave speed (SWS in m/s). SWS of pancreatic neuroendocrine tumor (PNET-T) were compared with nontumorous pancreatic tissue in patients with PNET (PNET-NT) and heathy pancreatic tissue (CTR). The diagnostic performance of tomoelastography was evaluated by ROC-AUC analysis. PNET-SWS correlations were calculated with Pearson’s r. Results: SWS was higher in PNET-T (2.02 ± 0.61 m/s) compared to PNET-NT (1.31 ± 0.18 m/s, p < 0.01) and CTR (1.26 ± 0.09 m/s, p < 0.01). An SWS-cutoff of 1.46 m/s distinguished PNET-T from PNET-NT (AUC = 0.89; sensitivity = 0.85; specificity = 0.92) and a cutoff of 1.49 m/s differentiated pancreatic tissue of CTR from PNET-T (AUC = 0.96; sensitivity = 0.92; specificity = 1.00). The SWS of PNET-T was positively correlated with PET derived asphericity (r = 0.81; p = 0.01). Conclusions: Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.

Quantitative 68Ga-DOTATATE PET/CT Parameters for the Prediction of Therapy Response in Patients with Progressive Metastatic Neuroendocrine Tumors Treated with 177Lu-DOTATATE

The aim of this study was to determine whether quantitative PET parameters on baseline 68Ga-DOTATATE PET/CT and interim PET (iPET) performed before the second cycle of therapy are predictive of the therapy response and progression-free survival (PFS). Methods: Ninety-one patients with well-differentiated neuroendocrine tumors (mean Ki-67 index, 8.3%) underwent 68Ga-DOTATATE PET/CT to determine suitability for peptide receptor radionuclide therapy as part of a prospective multicenter study. The mean follow-up was 12.2 mo. Of the 91 patients, 36 had iPET. The tumor metrics evaluated were marker lesion-based measures (mean SUVmax and ratio of the mean lesion SUVmax to the SUVmax in the liver or the SUVmax in the spleen), segmented 68Ga-DOTATATE tumor volumes (DTTVs), SUVmax and SUVmean obtained with the liver and spleen as thresholds, and heterogeneity parameters (coefficient of variation, kurtosis, and skewness). The Wilcoxon rank sum test was used for the association between continuous variables and the therapy response, as determined by the clinical response. Univariable and multivariable Cox proportional hazards models were used for the association with PFS. Results: There were 71 responders and 20 nonresponders. When marker lesions were used, higher mean SUVmax and ratio of the mean lesion SUVmax to the SUVmax in the liver were predictors of the therapy response (P = 0.018 and 0.024, respectively). For DTTV parameters, higher SUVmax and SUVmean obtained with the liver as a threshold and lower kurtosis were predictors of a favorable response (P = 0.025, 0.0055, and 0.031, respectively). The latter also correlated with a longer PFS. The iPET DTTV SUVmean obtained with the liver as a threshold and the ratio of mean SUVmax obtained from target lesions at iPET to baseline PET correlated with the therapy response (P = 0.024 and 0.048, respectively) but not PFS. From the multivariable analysis with adjustment for age, primary site, and Ki-67 index, the mean SUVmax (P = 0.019), ratio of the mean lesion SUVmax to the SUVmax in the liver (P = 0.018), ratio of the mean lesion SUVmax to the SUVmax in the spleen (P = 0.041), DTTV SUVmean obtained with the liver (P = 0.0052), and skewness (P = 0.048) remained significant predictors of PFS. Conclusion: The degree of somatostatin receptor expression and tumor heterogeneity, as represented by several metrics in our analysis, were predictive of the therapy response or PFS. Changes in these parameters after the first cycle of peptide receptor radionuclide therapy did not correlate with clinical outcomes.

PRRT: identikit of the perfect patient

Peptide receptor radionuclide therapy (PRRT) has been strengthened since the publication of NETTER-1. Nevertheless, the correct positioning in the therapeutic algorithm is debated, and no optimal sequence has yet been standardized. Possible criteria to predict the response to PRRT in neuroendocrine tumors (NET) have been proposed. The aim of this review is to define the perfect identity of the eligible patient who can mostly benefit from this therapy. Possible predictive criteria which have been analysed were: primary tumor site, grading, tumor burden, FDG PET and ⁶⁸Ga-PET uptake. Primary tumor site and ⁶⁸Ga-PET uptake do not play a pivotal role in predicting the response, while tumor burden, FDG PET uptake and grading seem to represent predictive/prognostic factors for response to PRRT. The heterogeneity in trial designs, patient populations, type of radionuclides, previous therapies and measurement of outcomes, inevitably limits the strength of our conclusions, therefore care must be taken in applying these results to clinical practice. In conclusion, the perfect patient, selected by ⁶⁸Ga-PET uptake, will likely have a relatively limited liver tumor burden, a ki67 index <20% and will respond to PRRT irrespective to primary tumor. Nevertheless, we have mostly prognostic than predictive factors to predict the efficacy of PRRT in individual patients, while a promising tool could be the NETest. However, to date, the identikit of the perfect patient for PRRT is a puzzle without some pieces and still we cannot disregard a multidisciplinary discussion of the individual case to select the patients who will mostly benefit from PRRT.

Rapid Progression After 177Lu-DOTATATE in Patients With Neuroendocrine Tumors

ABSTRACT

Peptide receptor radionuclide therapy (PRRT) is a treatment option for somatostatin receptor-positive, unresectable or metastatic neuroendocrine tumors (NETs). Despite high disease control rates seen with PRRT, a subset of the NET population seems to have a short progression-free interval. We hypothesize that patients with NETs with rapid progression post-PRRT may have mixed low- and high-grade cell populations, and PRRT treats the lower-grade component, allowing the more aggressive high-grade component to progress.We report 7 patients with biopsy-proven NET who received PRRT with 177Lu-DOTATATE at the Stanford Cancer Center who had evidence of progressive disease (PD) on or within 6 months of therapy.All patients had primary pancreatic, metastatic, well-differentiated NET on diagnosis and were heavily pretreated before receiving PRRT. Two patients had PD while on PRRT; 5 had PD within 6 months of completing PRRT. The median time from the last cycle to PD was 3.2 months (range, 1.1-4.6 months). The median progression-free survival was 7.7 months (95% confidence interval, 5.7-9.8 months). Three patients had a repeat biopsy post-PRRT, 2 of which demonstrated higher disease grade compared with their initial pathology. Further evaluation in larger patient cohorts is warranted to elucidate predictive factors of PRRT response/nonresponse to enable better patient selection.

Neuroendocrine Tumors: Imaging Perspective

This article summarizes the role of PET imaging for detection, characterization, and theranostic/therapy planning for neuroendocrine tumors. Topics in this article span overall imaging accuracy with mostly ⁶⁸Ga-DOTA-peptide imaging as well as basic principles of individualized dosimetry. There is also some discussion around further specialized approaches in dosimetry in theranostics. In addition, an overview of the literature on functional imaging in neuroendocrine tumors and the current understanding of imaging-derived clinical outcome prediction are presented.

The overriding role of surgery and tumor grade for long-term survival in patients with gastroenteropancreatic neuroendocrine neoplasms: A population-based cohort study

Background

Gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) comprise a heterogeneous disease group. Factors that affect long‐term survival remain uncertain. Complete population‐representative cohorts with long‐term follow‐up are scarce.

Aim

To evaluate factors of importance for the long‐term survival.

Methods and results

An Observational population‐based study on consecutive GEP‐NEN patients diagnosed from 2003 to 2013, managed according to national guidelines. Univariable and multivariable survival analyses were performed to evaluate overall survival (OS) and to identify independent prognostic factors. One hundred ninety eligible patients (males, 58.9%) (median age, 60.0 years; range, 10.0–94.2 years) were included. The small bowel, appendix, and pancreas were the most common tumor locations. The World Health Organization (WHO) tumor grade 1–3 distributions varied according to the primary location and disease stage. Primary surgery with curative intent was performed in 66% of the patients. The median OS of the study population was 183 months with 5‐ and 10‐year OS rates of 66% and 57%, respectively. Only age, WHO tumor grade, and primary surgical treatment were independent prognostic factors for OS.

Conclusion

The outcomes of GEP‐NEN patients are related to several factors including age and primary surgical treatment. WHO tumor grading, based on the established criteria, should be routine in clinical practice. This may improve clinical decision‐making and allow the comparison of outcomes among different centers.

Imaging and liquid biopsy in the prediction and evaluation of response to PRRT in neuroendocrine tumors: implications for patient management

Purpose

The aim of this narrative review is to give an overview on current and emerging imaging methods and liquid biopsy for prediction and evaluation of response to PRRT. Current limitations and new perspectives, including artificial intelligence, are discussed.

Methods

A literature review of PubMed/Medline was performed with representative keywords. The search included articles published online through August 31, 2020. All searches were restricted to English language manuscripts.

Results

Peptide radio receptor therapy (PRRT) is a prospectively evaluated and approved therapy option in neuroendocrine tumors (NETs). Different ligands targeting the somatostatin receptor (SSTR) are used as theranostic pairs for imaging NET and for PRRT. Response assessment in prospective trials often relies on the morphological RECIST 1.1 criteria, based on lesion size in CT or MRI. The role of SSTR-PET and quantitative uptake parameters and volumetric data is still not defined. Monoanalyte tumor marker chromogranin A has a limited value for response assessment after PRRT. New emerging liquid biopsy techniques are offering prediction of response to PRRT and prognostic value.

Conclusions

New response criteria for NET patients undergoing PRRT will comprise multiparametric hybrid imaging and blood-based multianalyte markers. This represents tumor biology and heterogeneity.

Radiomics in pancreatic neuroendocrine tumors: methodological issues and clinical significance

PURPOSE

To present the state-of-art of radiomics in the context of pancreatic neuroendocrine tumors (PanNETs), with a focus on the methodological and technical approaches used, to support the search of guidelines for optimal applications. Furthermore, an up-to-date overview of the current clinical applications of radiomics in the field of PanNETs is provided.

METHODS

Original articles were searched on PubMed and Science Direct with specific keywords. Evaluations of the selected studies have been focused mainly on (i) the general radiomic workflow and the assessment of radiomic features robustness/reproducibility, as well as on the major clinical applications and investigations accomplished so far with radiomics in the field of PanNETs: (ii) grade prediction, (iii) differential diagnosis from other neoplasms, (iv) assessment of tumor behavior and aggressiveness, and (v) treatment response prediction.

RESULTS

Thirty-one articles involving PanNETs radiomic-related objectives were selected. In regard to the grade differentiation task, yielded AUCs are currently in the range of 0.7-0.9. For differential diagnosis, the majority of studies are still focused on the preliminary identification of discriminative radiomic features. Limited information is known on the prediction of tumors aggressiveness and of treatment response.

CONCLUSIONS

Radiomics is recently expanding in the setting of PanNETs. From the analysis of the published data, it is emerging how, prior to clinical application, further validations are necessary and methodological implementations require optimization. Nevertheless, this new discipline might have the potential in assisting the current urgent need of improving the management strategies in PanNETs patients.

Strategies Towards Improving Clinical Outcomes of Peptide Receptor Radionuclide Therapy

PURPOSE OF REVIEW

Peptide receptor radionuclide therapy (PRRT) with [177Lu-DOTA0,Tyr3] octreotate is an effective and safe second- or third-line treatment option for patients with low-grade advanced gastroenteropancreatic (GEP) neuroendocrine neoplasms (NEN). In this review, we will focus on possible extensions of the current use of PRRT and on new approaches which could further improve its treatment efficacy and safety.

RECENT FINDINGS

Promising results were published regarding PRRT in other NENs, including lung NENs or high-grade NENs, and applying PRRT as neoadjuvant or salvage therapy. Furthermore, a diversity of strategic approaches, including dosimetry, somatostatin receptor antagonists, somatostatin receptor upregulation, radiosensitization, different radionuclides, albumin binding, alternative renal protection, and liver-directed therapy in combination with PRRT, have the potential to improve the outcome of PRRT. Also, novel biomarkers are presented that could predict response to PRRT. Multiple preclinical and early clinical studies have shown encouraging potential to advance the clinical outcome of PRRT in NEN patients. However, at this moment, most of these strategies have not yet reached the clinical setting of randomized phase III trials.

Predictive and Prognostic Impact of Blood-Based Inflammatory Biomarkers in Patients with Gastroenteropancreatic Neuroendocrine Tumors Commencing Peptide Receptor Radionuclide Therapy

Tumor microenvironment inflammation contributes to the proliferation and survival of malignant cells, angiogenesis, metastasis, subversion of adaptive immunity, and reduced treatment response. We aimed to evaluate the early predictive and prognostic significance of markers of systemic inflammation in patients receiving somatostatin-receptor targeted peptide receptor radionuclide therapy (PRRT). This retrospective observational cohort study included 33 patients with advanced gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) treated with PRRT. Pretreatment blood-based inflammatory biomarkers, e.g., C-reactive protein levels (CRP), white blood cell count (WBC), and absolute neutrophil count (ANC), were documented and inflammation indexes, e.g., neutrophil-lymphocyte ratio (NLR) and Platelet × CRP multiplier (PCM), were calculated. Tumor burden was determined using [⁶⁸Ga]Ga-DOTA-TATE PET/CT before enrollment and every 2 cycles thereafter until progression. Therapy response was assessed using RECIST 1.1, including its volumetric modification. Inflammatory biomarkers and inflammatory indexes demonstrated marked heterogeneity among patients, and were significantly higher in non-responders (e.g., CRP (p < 0.001), ANC (p = 0.002), and PCM (p < 0.001)). Change in whole-body tumor burden after two cycles of PRRT was significantly associated with CRP (p = 0.0157) and NLR (p = 0.0040) in multivariate regression analysis. A cut-off of 2.5 mg/L for CRP (AUC = 0.84, p = 0.001) revealed a significant outcome difference between patients with adversely high vs. low CRP (median PFS 508 days vs. not yet reached (HR = 4.52; 95% CI, 1.27 to 16.18; p = 0.02)). Tumor-driven systemic inflammatory networks may be associated with treatment response, change in tumor burden, and prognosis in patients with GEP-NETs receiving PRRT.

Impact of segmentation and discretization on radiomic features in 68Ga-DOTA-TOC PET/CT images of neuroendocrine tumor

OBJECTIVE

To identify the impact of segmentation methods and intensity discretization on radiomic features (RFs) extraction from 68Ga-DOTA-TOC PET images in patients with neuroendocrine tumors.

METHODS

Forty-nine patients were retrospectively analyzed. Tumor contouring was performed manually by four different operators and with a semi-automatic edge-based segmentation (SAEB) algorithm. Three SUVmax fixed thresholds (20, 30, 40%) were applied. Fifty-one RFs were extracted applying two different intensity rescale factors for gray-level discretization: one absolute (AR60 = SUV from 0 to 60) and one relative (RR = min-max of the VOI SUV). Dice similarity coefficient (DSC) was calculated to quantify segmentation agreement between different segmentation methods. The impact of segmentation and discretization on RFs was assessed by intra-class correlation coefficients (ICC) and the coefficient of variance (COVL). The RFs' correlation with volume and SUVmax was analyzed by calculating Pearson's correlation coefficients.

RESULTS

DSC mean value was 0.75 ± 0.11 (0.45-0.92) between SAEB and operators and 0.78 ± 0.09 (0.36-0.97), among the four manual segmentations. The study showed high robustness (ICC > 0.9): (a) in 64.7% of RFs for segmentation methods using AR60, improved by applying SUVmax threshold of 40% (86.5%); (b) in 50.9% of RFs for different SUVmax thresholds using AR60; and (c) in 37% of RFs for discretization settings using different segmentation methods. Several RFs were not correlated with volume and SUVmax.

CONCLUSIONS

RFs robustness to manual segmentation resulted higher in NET 68Ga-DOTA-TOC images compared to 18F-FDG PET/CT images. Forty percent SUVmax thresholds yield superior RFs stability among operators, however leading to a possible loss of biological information. SAEB segmentation appears to be an optimal alternative to manual segmentation, but further validations are needed. Finally, discretization settings highly impacted on RFs robustness and should always be stated.

A Systematic Review of PET Textural Analysis and Radiomics in Cancer

Background: Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies. Methods: PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted. Results: A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20–1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1–286). Conclusions: PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.

68Ga-DOTATOC PET/CT-Based Radiomic Analysis and PRRT Outcome: A Preliminary Evaluation Based on an Exploratory Radiomic Analysis on Two Patients

Aim: This work aims to evaluate whether the radiomic features extracted by 68Ga-DOTATOC-PET/CT of two patients are associated with the response to peptide receptor radionuclide therapy (PRRT) in patients affected by neuroendocrine tumor (NET).

Methods: This is a pilot report in two NET patients who experienced a discordant response to PRRT (responder vs. non-responder) according to RECIST1.1. The patients presented with liver metastasis from the rectum and pancreas G3-NET, respectively. Whole-body total-lesion somatostatin receptor-expression (TLSREwb-50) and somatostatin receptor-expressing tumor volume (SRETV wb-50) were obtained in pre- and post-PRRT PET/CT. Radiomic analysis was performed, extracting 38 radiomic features (RFs) from the patients' lesions. The Mann–Whitney test was used to compare RFs in the responder patient vs. the non-responder patient. Pearson correlation and principal component analysis (PCA) were used to evaluate the correlation and independence of the different RFs.

Results: TLSREwb-50 and SRETVwb-50 modifications correlate with RECIST1.1 response. A total of 28 RFs extracted on pre-therapy PET/CT showed significant differences between the two patients in the Mann–Whitney test (p < 0.05). A total of seven second-order features, with poor correlation with SUVmax and PET volume, were identified by the Pearson correlation matrix. Finally, the first two PCA principal components explain 83.8% of total variance.

Conclusion: TLSREwb-50 and SRETVwb-50 are parameters that might be used to predict and to assess the PET response to PRRT. RFs might have a role in defining inter-patient heterogeneity and in the prediction of therapy response. It is important to implement future studies with larger and more homogeneous patient populations to confirm the efficacy of these biomarkers.

Radiopharmaceuticals for Neuroendocrine Tumors

Neuroendocrine tumors (NETs) are a heterogeneous group of tumors that originate in endocrine tissues throughout the body. Peptide receptor radionuclide therapy (PRRT) has emerged as a promising therapeutic option for patients with locally advanced and/or metastatic disease refractory to standard of care treatment. The landmark international phase III NETTER-1 trial led to the approval of ¹⁷⁷Lu-DOTATATE (Lutathera) in the treatment of somatostatin receptor-positive gastroenteropancreatic NETs. Similarly, data from the multicenter, phase II Study IB12B led to the approval of meta-[¹³¹I]Iodo-Benzyl-Guanidine (^I31I-MIBG) for treatment of iobenguane scan-positive, unresectable, locally advanced or metastatic pheochromocytoma or paraganglioma. With the clinical approval of these novel radiopharmaceuticals for managing select patients with NETs, additional studies are needed to refine patient selection, predict and assess therapy response, and optimize radiopharmaceutical delivery and clinical outcomes.

The Challenge of Evaluating Response to Peptide Receptor Radionuclide Therapy in Gastroenteropancreatic Neuroendocrine Tumors: The Present and the Future

The NETTER-1 study has proven peptide receptor radionuclide therapy (PRRT) to be one of the most effective therapeutic options for metastatic neuroendocrine tumors (NETs), improving progression-free survival and overall survival. However, PRRT response assessment is challenging and no consensus on methods and timing has yet been reached among experts in the field. This issue is owed to the suboptimal sensitivity and specificity of clinical biomarkers, limitations of morphological response criteria in slowly growing tumors and necrotic changes after therapy, a lack of standardized parameters and timing of functional imaging and the heterogeneity of PRRT protocols in the literature. The aim of this article is to review the most relevant current approaches for PRRT efficacy prediction and response assessment criteria in order to provide an overview of suitable tools for safe and efficacious PRRT.

Role of PET/CT and Therapy Management of Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine neoplasms (panNENs) are heterogeneous neoplasms with neuroendocrine differentiation that show peculiar clinical and histomorphological features, with variable prognosis. In recent years, advances in knowledge regarding the pathophysiology and heterogeneous clinical presentation, as well as the availability of different diagnostic procedures for panNEN diagnosis and novel therapeutic options for patient clinical management, has led to the recognition of the need for an active multidisciplinary discussion for optimal patient care. Molecular imaging with positron emission tomography/computed tomography (PET/CT) has become indispensable for the management of panNENs. Several PET radiopharmaceuticals can be used to characterize either panNEN receptor expression or metabolism. The aim of this review is to offer an overview of all the currently used radiopharmaceuticals and of the new upcoming tracers for pancreatic neuroendocrine tumors (panNETs), and their clinical impact on therapy management. [68Ga]Ga-DOTA-peptide PET/CT (SSA-PET/CT) has high sensitivity, specificity, and accuracy and is recommended for the staging and restaging of any non-insulinoma well-differentiated panNEN cases to carry out detection of unknown primary tumor sites or early relapse and for evaluation of in vivo somatostatin receptors expression (SRE) to select patient candidates for peptide receptor radiometabolic treatment (PRRT) with 90Y or 177Lu and/or cold analogs. SSA-PET/CT also has a strong impact on clinical management, leading to a change in treatment in approximately a third of the cases. Its role for treatment response assessment is still under debate due to the lack of standardized criteria, even though some semiquantitative parameters seem to be able to predict response. [18F]FDG PET/CT generally shows low sensitivity in small growing and well-differentiated neuroendocrine tumors (NET; G1 and G2), while it is of utmost importance in the evaluation and management of high-grade NENs and also provides important prognostic information. When positive, [18F]FDG PET/CT impacts therapeutical management, indicating the need for a more aggressive treatment regime. Although FDG positivity does not exclude the patient from PRRT, several studies have demonstrated that it is certainly useful to predict response, even in this setting. The role of [18F]FDOPA for the study of panNET is limited by physiological uptake in the pancreas and is therefore not recommended. Moreover, it provides no information on SRE that has crucial clinical management relevance. Early acquisition of the abdomen and premedication with carbidopa may be useful to increase the accuracy, but further studies are needed to clarify its utility. GLP-1R agonists, such as exendin-4, are particularly useful for benign insulinoma detection, but their accuracy decreases in the case of malignant insulinomas. Being a whole-body imaging technique, exendin-PET/CT gives important preoperative information on tumor size and localization, which is fundamental for surgical planning as resection (enucleation of the lesion or partial pancreatic resection) is the only curative treatment. New upcoming tracers are under study, such as promising SSTR antagonists, which show a favorable biodistribution and higher tumor-to-background ratio that increases tumor detection, especially in the liver. [68Ga]pentixafor, an in vivo marker of CXCR4 expression associated with the behavior of more aggressive tumors, seems to only play a limited role in detecting well-differentiated NET since there is an inverse expression of SSTR2 and CXCR4 in G1 to G3 NETs with an elevation in CXCR4 and a decrease in SSTR2 expression with increasing grade. Other tracers, such as [68Ga]Ga-PSMA, [68Ga]Ga-DATA-TOC, [18F]SiTATE, and [18F]AlF-OC, are also under investigation.

Early response assessment and prediction of overall survival after peptide receptor radionuclide therapy

Background

Response after peptide receptor radionuclide therapy (PRRT) can be evaluated using anatomical imaging (CT/MRI), somatostatin receptor imaging ([⁶⁸Ga]Ga-DOTA-TATE PET/CT), and serum Chromogranin-A (CgA). The aim of this retrospective study is to assess the role of these response evaluation methods and their predictive value for overall survival (OS).

Methods

Imaging and CgA levels were acquired prior to start of PRRT, and 3 and 9 months after completion. Tumour size was measured on anatomical imaging and response was categorized according to RECIST 1.1 and Choi criteria. [⁶⁸Ga]Ga-DOTA-TATE uptake was quantified in both target lesions depicted on anatomical imaging and separately identified PET target lesions, which were either followed over time or newly identified on each scan with PERCIST-based criteria. Response evaluation methods were compared with Cox regression analyses and Log Rank tests for association with OS.

Results

A total of 44 patients were included, with median follow-up of 31 months (IQR 26–36 months) and median OS of 39 months (IQR 32mo-not reached)d. Progressive disease after 9 months (according to RECIST 1.1) was significantly associated with worse OS compared to stable disease [HR 9.04 (95% CI 2.10–38.85)], however not compared to patients with partial response. According to Choi criteria, progressive disease was also significantly associated with worse OS compared to stable disease [HR 6.10 (95% CI 1.38–27.05)] and compared to patients with partial response [HR 22.66 (95% CI 2.33–219.99)]. In some patients, new lesions were detected earlier with [⁶⁸Ga]Ga-DOTA-TATE PET/CT than with anatomical imaging. After 3 months, new lesions on [⁶⁸Ga]Ga-DOTA-TATE PET/CT which were not visible on anatomical imaging, were detected in 4/41 (10%) patients and in another 3/27 (11%) patients after 9 months. However, no associations between change in uptake on ⁶⁸Ga-DOTA-TATE PET/CT or serum CgA measurements and OS was observed.

Conclusions

Progression on anatomical imaging performed 9 months after PRRT is associated with worse OS compared to stable disease or partial response. Although new lesions were detected earlier with [⁶⁸Ga]Ga-DOTA-TATE PET/CT than with anatomical imaging, [⁶⁸Ga]Ga-DOTA-TATE uptake, and serum CgA after PRRT were not predictive for OS in this cohort with limited number of patients and follow-up time.

Investigating PSMA-Targeted Radioligand Therapy Efficacy as a Function of Cellular PSMA Levels and Intratumoral PSMA Heterogeneity

PURPOSE

Prostate-specific membrane antigen (PSMA) targeting radioligands deliver radiation to PSMA-expressing cells. However, the relationship between PSMA levels and intralesion heterogeneity of PSMA expression, and cytotoxic radiation by radioligand therapy (RLT) is unknown. Here we investigate RLT efficacy as function of PSMA levels/cell, and the fraction of PSMA+ cells in a tumor.

EXPERIMENTAL DESIGN

RM1 cells expressing different levels of PSMA (PSMA-, PSMA+, PSMA++, PSMA+++; study 1) or a mix of PSMA+ and PSMA- RM1 (study 2, 4) or PC-3/PC-3-PIP (study 3) cells at various ratios were injected into mice. Mice received 177Lu- (studies 1-3) or 225Ac- (study 4) PSMA617. Tumor growth was monitored. Two days post-RLT, tumors were resected in a subset of mice. Radioligand uptake and DNA damage were quantified.

RESULTS

177Lu-PSMA617 efficacy increased with increasing PSMA levels (study 1) and fractions of PSMA positive cells (studies 2, 3) in both, the RM1 and PC-3-PIP models. In tumors resected 2 days post-RLT, PSMA expression correlated with 177Lu-PSMA617 uptake and the degree of DNA damage. Compared with 177Lu-PSMA617, 225Ac-PSMA617 improved overall antitumor effectiveness and tended to enhance the differences in therapeutic efficacy between experimental groups.

CONCLUSIONS

In the current models, both the degree of PSMA expression and the fraction of PSMA+ cells correlate with 177Lu-/225Ac-PSMA617 tumor uptake and DNA damage, and thus, RLT efficacy. Low or heterogeneous PSMA expression represents a resistance mechanism to RLT.See related commentary by Ravi Kumar and Hofman, p. 2774.