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

Radio theranostics in paragangliomas and pheochromocytomas

This continuing education aims to present in a clear and easy-to-understand manner the biology of paragangliomas and pheochromocytomas (PPGLs), the functional imaging studies available for their diagnosis and therapeutic planning, the requirements necessary to administer radioligand therapy (RLT) and the characteristics of these treatments (inclusion criteria, administration protocols, adverse effects and future perspectives). In this pathology we have two RLT options: [131I]MIBG and [177Lu]Lu-DOTA-TATE. The indication for treatment is determined by the expression of its therapeutic target in functional imaging studies, allowing precision and personalized medicine. Although most of the results we have for both treatments have as origin small retrospective series, RLT is presented as a safe and well-tolerated therapeutic option in PPGLs with slow-moderate progression or with uncontrollable symptoms, obtaining high disease control rates.

Peptide Receptor Radionuclide Therapy of Neuroendocrine Tumors: Agonist, Antagonist and Alternatives

Peptide receptor radionuclide therapy (PRRT) today is a well-established treatment strategy for patients with neuroendocrine tumors (NET). First performed already more than 30 years ago, PRRT was incorporated only in recent years into the major oncology guidelines, based on its proven efficacy and safety in clinical trials. Following the phase 3 NETTER-1 trial, which led to the final registration of the radiopharmaceutical Luthatera® for G1/G2 NET patients in 2017, the long-term results of the phase 3 NETTER-2 trial may pave the way for a new treatment option also for advanced G2/G3 patients as first-line therapy. The growing knowledge about the synergistic effect of combined therapies could also allow alternative (re)treatment options for NET patients, in order to create a tailored treatment strategy. The evolving thera(g)nostic concept could be applied for the identification of patients who might benefit from different image-guided treatment strategies. In this scenario, the use of dual tracer PET/CT in NET patients, using both [18F]F-FDG/[68Ga]Ga-DOTA-somatostatin analog (SSA) for diagnosis and follow-up, is under discussion and could also result in a powerful prognostic tool. In addition, alternative strategies based on different metabolic pathways, radioisotopes, or combinations of different medical approaches could be applied. A number of different promising "doors" could thus open in the near future for the treatment of NET patients - and the "key" will be thera(g)nostic!

Prediction of 177Lu-DOTATATE PRRT Outcome Using Multimodality Imaging in Patients with Gastroenteropancreatic Neuroendocrine Tumors: Results from a Prospective Phase II LUMEN Study

Our objective was to predict the outcome of peptide receptor radionuclide therapy (PRRT) using multimodality imaging and tumor dosimetry on gastroenteropancreatic neuroendocrine tumor (GEP-NET) lesions and patients. Methods: This prospective study included patients with progressive GEP-NETs. Treatment consisted of 4 cycles of 7.4 GBq of 177Lu-DOTATATE. Imaging parameters were measured on 68Ga-DOTATATE PET/CT (SUVmax/mean, somatostatin receptor [SSTR] tumor volume [TV], total lesion SSTR expression, and tumor-to-blood and tumor-to-spleen ratios), 18F-FDG PET/CT (SUVmax/mean, metabolically active TV, and total lesion glycolysis), and diffusion-weighted MRI (apparent diffusion coefficient) in a maximum of 5 target lesions per patient at approximately 10 wk after each injection. Tumor dosimetry was performed using SPECT/CT at 3 time points for every cycle. Baseline imaging parameters, their relative changes after PRRT cycle 1 (C1), and the tumor-absorbed dose at C1 were correlated with lesion morphologic outcome. The average values of the imaging parameters and the minimal, maximal, and mean C1 tumor-absorbed dose in each patient were tested for association with progression-free survival (PFS) and best objective response (RECIST 1.1). Results: In the 37 patients, the median PFS was 28 mo. Eleven of the 37 (30%) achieved a partial response (RECIST 1.1). After a median follow-up of 57 mo, the median time to lesion progression had not been reached in 84 morphologically evaluable lesions, with only 12 (14%) progressing (size increase ≥ 20% from baseline). Patients receiving a minimal C1 dose of 35 Gy in all target lesions exhibited a significantly longer PFS (48.1 vs. 26.2 mo; hazard ratio, 0.37; 95% CI, 0.17-0.82; P = 0.02). Volumetric 68Ga-DOTATATE PET parameters correlated with lesion and patient outcome: patients with an SSTR TV decrease of more than 10% after C1 had a longer PFS (51.3 vs. 22.8 mo; hazard ratio, 0.35; 95% CI, 0.16-0.75; P = 0.003). There was no statistical evidence of an association between other dosimetric or imaging parameters and the lesion or patient outcome. Conclusion: Minimal tumor-absorbed dose at C1 is predictive of outcome in patients with GEP-NETs treated with PRRT, providing a basis for personalized dosimetry-guided treatment strategies. An SSTR TV decrease after C1 could be used for early therapy response assessment as a predictor of PRRT outcome.

Artificial Intelligence in Oncological Hybrid Imaging

BACKGROUND

 Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

METHODS AND RESULTS

 The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations.

CONCLUSION

 AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation.

KEY POINTS

  · Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

The prognostic role of whole-body volumetric 68 GA-DOTATATE PET/computed tomography parameters in patients with gastroenteropancreatic neuroendocrine tumor treated with 177 LU-DOTATATE

OBJECTIVE

The aim of this study is to evaluate the prognostic role of Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and quantitative 68 Ga-DOTATATE PET/computed tomography parameters such as maximum standardized uptake value (SUVmax), mean SUV (SUVmean), DOTATATE tumor volume (DTV), total lesion DOTATATE (TLD) in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) treated with 177 Lu-DOTATATE.

MATERIAL AND METHOD

Our retrospective study included 21 patients with GEP-NETs treated with 177 Lu-DOTATATE between January 2017 and January 2022. SUVmax, SUVmean, SUVmax/spleenSUVmax (SUVmax/Sx), DTV, TLD, SUVmean/spleenSUVmean (SUVmean/Sm), TLD/Sm values were calculated and recorded for all patients before and after 177 Lu-DOTATATE treatment.

RESULTS

A total of 319 metastases were detected in the patients included in the study, and a total of 68 target lesions were selected. In univariant Cox regression analysis, TLD/Sm percent change (∆TLD/Sm) was found to be statistically significant on overall survival (OS) ( P  = 0.044). The 3-year survival in nonresponders was 50% ( P  = 0.034) based on ∆SUVmax/Sx values, 50% ( P  = 0.002) based on RECIST values, 50% based on ∆TDTV + new lesion values ( P  = 0.033), and according to ∆TTLD + new lesion values, it was 66% ( P  = 0.030).

CONCLUSION

In our study, we showed that SUVmax/Sx, RECIST, ∆TDTV + new lesion, and ∆TTLD + new lesion parameters can predict OS in the evaluation of response to treatment.

Interim Analysis of a Prospective Validation of 2 Blood-Based Genomic Assessments (PPQ and NETest) to Determine the Clinical Efficacy of 177Lu-DOTATATE in Neuroendocrine Tumors

Reliable biomarkers for neuroendocrine tumor (NET) management during peptide receptor radionuclide therapy (PRRT) are lacking. We validated the role of 2 circulating biomarkers: the PRRT prediction quotient (PPQ) as a predictive marker for response and the NETest as a monitoring biomarker. Furthermore, we evaluated whether tissue-based genetic alterations are effective in predicting progression-free survival (PFS). Methods: Data were prospectively collected on patients at the Memorial Sloan Kettering Cancer Center with 177Lu-DOTATATE-treated somatostatin receptor (SSTR)-positive gastroenteropancreatic and lung NETs (n = 67; median age, 66 y; 52% female; 42% pancreatic, 39% small-bowel; 78% grade 1 or 2). All cases were metastatic (89% liver) and had received 1-8 prior treatments (median, 3), including somatostatin analogs (91%), surgery (55%), or chemotherapy (49%). Treatment response included PFS. According to RECIST, version 1.1, responders had stable disease or a partial response (disease-control rate) and nonresponders had progression. Blood was collected before each cycle and at follow-up. Samples were deidentified and assayed and underwent masked analyses. The gene expression assays included RNA isolation, real-time quantitative polymerase chain reaction, and multialgorithm analyses. The PPQ (positive predicts a responder; negative predicts a nonresponder) at baseline was determined. The NETest (0-100 score) was performed. Statistics were analyzed using Mann-Whitney U testing (2-tailed) or Kaplan-Meier survival testing (PFS). In patients with archival tumor tissue, next-generation sequencing was performed through an institutional platform (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets). Results: Forty-one patients (61%) were responders. PPQ accurately predicted 96% (64/67). The hazard ratio for prediction was 24.4 (95% CI, 8.2-72.5). Twelve-month disease control was 97% for PPQ-positive patients versus 26% for PPQ-negative patients (P < 0.0001). Median progression-free survival was not reached in those predicted to respond (PPQ-positive, n = 40) but was 8 mo in those predicted not to respond (PPQ-negative, n = 27). The NETest result in responders was 67 ± 25 at baseline and significantly (P < 0.05) decreased (-37 ± 44%) at follow-up. The NETest result in nonresponders was 44 ± 23 at baseline and significantly (P < 0.05) increased (+76% ± 56%) at progression. Overall, the NETest changes (increases or decreases) were 90% accurate. Thirty patients underwent next-generation sequencing. Tumors were microsatellite-stable, and the median mutational burden was 1.8. Alterations involved mainly the mTOR/PTEN/TSC pathway (30%). No relationship was associated with PRRT response. Conclusion: Our interim analysis confirmed that PPQ is an accurate predictor of 177Lu-DOTATATE responsiveness (radiosensitivity) and that NETest changes accurately correlated with treatment response. Tissue-based molecular genetic information had little value in PRRT prediction. Blood-based gene signatures may improve the management of patients undergoing 177Lu-DOTATATE by providing information on tumor radiosensitivity and disease course, thus allowing individualized strategies.

Light It Up! The Use of DOTATATE in Diagnosis and Treatment of Neuroendocrine Neoplasms

Radiolabeled somatostatin analogs are increasingly used in the diagnosis and treatment of neuroendocrine tumors. Diagnostic imaging with 68Ga-DOTATATE PET/CT has demonstrated the improved sensitivity in detecting primary and metastatic neuroendocrine lesions compared with conventional imaging and prior generation somatostatin receptor imaging. Peptide receptor radionuclide therapy with 177Lu-DOTATATE is now frequently included in the management of neuroendocrine neoplasms, with prospective randomized control studies demonstrating its beneficial impact on survival and quality of life. Nonetheless, peptide rector radionuclide therapy is still considered palliative rather than curative and may be accompanied by adverse effects.

Artificial Intelligence in Oncological Hybrid Imaging

BACKGROUND

Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

METHODS AND RESULTS

The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations.

CONCLUSION

AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation.

KEY POINTS

· Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

CITATION FORMAT

· Feuerecker B, Heimer M, Geyer T et al. Artificial Intelligence in Oncological Hybrid Imaging. Fortschr Röntgenstr 2023; 195: 105 - 114.

Same-day comparative protocol PET/CT-PET/MRI [68 Ga]Ga-DOTA-TOC in paragangliomas and pheochromocytomas: an approach to personalized medicine

BACKGROUND

PET/MRI is an emerging imaging modality which enables the evaluation and quantification of biochemical processes in tissues, complemented with accurate anatomical information and low radiation exposure. In the framework of theragnosis, PET/MRI is of special interest due to its ability to delineate small lesions, adequately quantify them, and therefore to plan targeted therapies. The aim of this study was to validate the diagnostic performance of [⁶⁸ Ga]Ga-DOTA-TOC PET/MRI compared to PET/CT in advanced disease paragangliomas and pheochromocytomas (PGGLs) to assess in which clinical settings, PET/MRI may have a greater diagnostic yield.

METHODS

We performed a same-day protocol with consecutive acquisition of a PET/CT and a PET/MRI after a single [⁶⁸ Ga]Ga-DOTA-TOC injection in 25 patients. Intermodality agreement, Krenning Score (KS), SUVmax (Standard Uptake Value), target-to-liver-ratio (TLR), clinical setting, location, and size were assessed.

RESULTS

The diagnostic accuracy with PET/MRI increased by 14.6% compared to PET/CT especially in bone and liver locations (mean size of new lesions was 3.73 mm). PET/MRI revealed a higher overall lesion uptake than PET/CT (TLR 4.12 vs 2.44) and implied an upward elevation of the KS in up to 60% of patients. The KS changed in 30.4% of the evaluated lesions (mean size 11.89 mm), in 18.4% of the lesions it increased from KS 2 on PET/CT to a KS ≥ 3 on PET/MRI and 24.96% of the lesions per patient with multifocal disease displayed a KS ≥ 3 on PET/MR, that were not detected or showed lower KS on PET/CT. In 12% of patients, PET/MRI modified clinical management.

CONCLUSIONS

PET/MRI showed minor advantages over conventional PET/CT in the detection of new lesions but increased the intensity of SSRs expression in a significant number of them, opening the door to select which patients and clinical settings can benefit from performing PET/MRI.

Glucose Metabolism Modification Induced by Radioligand Therapy with [177Lu]Lu/[90Y]Y-DOTATOC in Advanced Neuroendocrine Neoplasms: A Prospective Pilot Study within FENET-2016 Trial

[18F]F-FDG (FDG) PET is emerging as a relevant diagnostic and prognostic tool in neuroendocrine neoplasms (NENs), as a simultaneous decrease in [68Ga]Ga-DOTA peptides and increase in FDG uptake (the “flip-flop” phenomenon) occurs during the natural history of these tumors. The aim of this study was to evaluate the variations on FDG PET in NEN patients treated with two different schemes of radioligand therapy (RLT) and to correlate them with clinical−pathologic variables. A prospective evaluation of 108 lesions in 56 patients (33 males and 23 females; median age, 64.5 years) affected by NENs of various primary origins (28 pancreatic, 13 gastrointestinal, 9 bronchial, 6 unknown primary (CUP-NENs) and 1 pheochromocytoma) and grades (median Ki-67 = 9%) was performed. The patients were treated with RLT within the phase II clinical trial FENET-2016 (CTID: NCT04790708). RLT was offered for 32 patients with the MONO scheme (five cycles of [177Lu]Lu-DOTATOC) and for 24 with the DUO scheme (three cycles of [177Lu]Lu-DOTATOC alternated with two cycles of [90Y]Y-DOTATOC). Variations in terms of the ΔSUVmax of a maximum of three target lesions per patient (58 for MONO and 50 for DUO RLT) were assessed between baseline and 3 months post-RLT FDG PET. In patients with negative baseline FDG PET, the three most relevant lesions on [68Ga]Ga-DOTA-peptide PET were assessed and matched on post-RLT FDG PET, to check for any possible changes in FDG avidity. Thirty-five patients (62.5%) had at least one pathological FDG uptake at the baseline scans, but the number was reduced to 29 (52%) after RLT. In the patients treated with DUO-scheme RLT, 20 out of 50 lesions were FDG positive before therapy, whereas only 14 were confirmed after RLT (p = 0.03). Moreover, none of the 30 FDG-negative lesions showed an increased FDG uptake after RLT. The lesions of patients with pancreatic and CUP-NENs treated with the DUO scheme demonstrated a significant reduction in ΔSUVmax in comparison to those treated with MONO RLT (p = 0.03 and p = 0.04, respectively). Moreover, we found a mild positive correlation between the grading and ΔSUVmax in patients treated with the MONO scheme (r = 0.39, p < 0.02), while no evidence was detected for patients treated with the DUO scheme. Our results suggest that RLT, mostly with the DUO scheme, could be effective in changing NEN lesions’ glycometabolism, in particular, in patients affected by pancreatic and CUP-NENs, regardless of their Ki-67 index. Probably, associating [90Y]Y-labelled peptides, which have high energy emission and a crossfire effect, and [177Lu]Lu ones, characterized by a longer half-life and a safer profile for organs at risk, might represent a valid option in FDG-positive NENs addressed to RLT. Further studies are needed to validate our preliminary findings. In our opinion, FDG PET/CT should represent a potent tool for fully assessing a patient’s disease characteristics, both before and after RLT.

Radiopharmaceutical Treatments for Cancer Therapy, Radionuclides Characteristics, Applications, and Challenges

Advances in the field of molecular biology have had an impact on biomedical applications, which provide greater hope for both imaging and therapeutics. Work has been intensified on the development of radionuclides and their application in radiopharmaceuticals (RP_S) which will certainly influence and expand therapeutic approaches in the future treatment of patients. Alpha or beta particles and Auger electrons are used for therapy purposes, and each has advantages and disadvantages. The radionuclides labeled drug delivery system will deliver the particles to the specific targeting cell. Different radioligands can be chosen to uniquely target molecular receptors or intracellular components, making them suitable for personal patient-tailored therapy in modern cancer therapy management. Advances in nanotechnology have enabled nanoparticle drug delivery systems that can allow for specific multivalent attachment of targeted molecules of antibodies, peptides, or ligands to the surface of nanoparticles for therapy and imaging purposes. This review presents fundamental radionuclide properties with particular reference to tumor biology and receptor characteristic of radiopharmaceutical targeted therapy development.

Combination of [177Lu]Lu-DOTA-TATE Targeted Radionuclide Therapy and Photothermal Therapy as a Promising Approach for Cancer Treatment: In Vivo Studies in a Human Xenograft Mouse Model

Peptide receptor radionuclide therapy (PRRT) relies on α- and β-emitting radionuclides bound to a peptide that commonly targets somatostatin receptors (SSTRs) for the localized killing of tumors through ionizing radiation. A Lutetium-177 (¹⁷⁷Lu)-based probe linked to the somatostatin analog octreotate ([¹⁷⁷Lu]Lu-DOTA-TATE) is approved for the treatment of certain SSTR-expressing tumors and has been shown to improve survival. However, a limiting factor of PRRT is the potential toxicity derived from the high doses needed to kill the tumor. This could be circumvented by combining PRRT with other treatments for an enhanced anti-tumor effect. Photothermal therapy (PTT) relies on nanoparticle-induced hyperthermia for cancer treatment and could be a useful add-on to PRRT. Here, we investigate a strategy combining [¹⁷⁷Lu]Lu-DOTA-TATE PRRT and nanoshell (NS)-based PTT for the treatment of SSTR-expressing small-cell lung tumors in mice. Our results showed that the combination treatment improved survival compared to PRRT alone, but only when PTT was performed one day after [¹⁷⁷Lu]Lu-DOTA-TATE injection (one of the timepoints examined), showcasing the effect of treatment timing in relation to outcome. Furthermore, the combination treatment was well-tolerated in the mice. This indicates that strategies involving NS-based PTT as an add-on to PRRT could be promising and should be investigated further.

Know thy tumour: Biomarkers to improve treatment of molecular radionuclide therapy

Molecular radionuclide therapy (MRT) is an effective treatment for both localised and disseminated tumours. Biomarkers can be used to identify potential subtypes of tumours that are known to respond better to standard MRT protocols. These enrolment-based biomarkers can further be used to develop dose-response relationships using image-based dosimetry within these defined subtypes. However, the biological identity of the cancers treated with MRT are commonly not well-defined, particularly for neuroendocrine neoplasms. The biological heterogeneity of such cancers has hindered the establishment of dose-responses and minimum tumour dose thresholds. Biomarkers could also be used to determine normal tissue MRT dose limits and permit greater injected doses of MRT in patients. An alternative approach is to understand the repair capacity limits of tumours using radiobiology-based biomarkers within and outside patient cohorts currently treated with MRT. It is hoped that by knowing more about tumours and how they respond to MRT, biomarkers can provide needed dimensionality to image-based biodosimetry to improve MRT with optimized protocols and personalised therapies.

[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.

Potential value of pre- and post-therapy [68Ga]Ga-DOTA-TATE PET/CT in the prognosis of response to PRRT in disseminated neuroendocrine tumors

BACKGROUND

Peptide receptor radionuclide therapy (PRRT) is one of the most effective therapeutic options for the treatment of metastatic, well-differentiated neuroendocrine tumors (NETs). It improves progressive disease-free survival and enables the control of hormone secretion in functioning tumors.Currently, there are no clearly established predictors of response to PRRT. The main factors hindering such a prediction are the heterogeneity of somatostatin receptor expression within and between lesions, lack of standardized parameters for functional imaging, and the use of different PRRT protocols.The main goal of our study was to quantify SUVmax changes in [68Ga]Ga-DOTA-TATE PET/CT scans as a potential predictor of long-term response to PRRT.

MATERIAL AND METHODS

Out of 20 patients treated with PRRT using [177Lu]Lu and/or [177Lu]Lu/[90Y]Y-DOTA-TATE in 2017-2019 due to dissemination of neuroendocrine neoplasm, 12 patients underwent [68Ga]Ga-DOTA-TATE PET/CT on average 3.1 months before and 4.5 months after PRRT and were eligible for the analysis.In total, 76 NET lesions were evaluated. We measured SUVmax for every lesion in both PET/CT scans (before and after PRRT). Those values were corrected by liver SUVmax and liver SUVmean measured in volumetric analysis and specified as SUVlmax and SUVlmean. As a next step, changes in SUVlmax and SUVlmean were assessed based on both PET/CT scans. Finally, results were correlated with the clinical outcome assessed as progressive disease, disease stabilization, or partial response.

RESULTS

The mean follow-up period was 19.9 months. Progressive disease, partial response, and disease stabilization were found in five, two, and five patients, respectively. Among patients with a partial response, the decrease in mean SUVlmax was 66.3% when compared to baseline. In patients with stable disease, the decrease in SUVlmax was 30.3% when compared to baseline. In patients with progressive disease, the mean increase in SUVlmax was 9.1% when compared to baseline. The changes in SUVlmean were -69,8%, -30.8%, and -3.7%, respectively.

CONCLUSIONS

A decrease in the SUVmax value in NET lesions, corrected by normal liver tissue uptake assessed in [68Ga]Ga-DOTA-TATE PET/CT scans, indicates a lower risk for NET progressive disease within 20 months after PRRT and may constitute an additional and independent parameter for the estimation of overall risk for disease progression.

Safety and Efficacy of Peptide-Receptor Radionuclide Therapy in Elderly Neuroendocrine Tumor Patients

Simple Summary

We compared the safety and efficacy of targeted radionuclide therapy between elderly (79 years old and older) and disease-matched younger patients (between 60 and 70 years of age) with metastatic neuroendocrine tumour (NET). To our knowledge, this is the first paper addressing this important clinical question of the outcome of radionuclide therapy in this particularly vulnerable population. We found that targeted radionuclide therapy did not cause increased side effects in the elderly NET population, while toxicity remains modest and comparable in both groups. We also find that survival (after adjusting for differences in life expectancy) is not inferior for the elderly compared to younger NET patients.

Abstract

Peptide receptor radionuclide therapy (PRRT) is a well-established treatment in somatostatin receptor-expressing neuroendocrine tumours (NETs). The safety and efficacy of PRRT in >79 years old patients (EP) have not been systematically investigated. All patients with inoperable/metastatic/progressive G1/G2 NET, >79 years (EP), treated with PRRT at the University Hospital of Basel between 2006 and 2018, were enrolled in this retrospective matched cohort study. Each patient was manually matched with ≥1 younger patient (YP = 60–70 years). The primary endpoint was toxicity. Toxicity (subacute, long-term) was graded according to the criteria for adverse events (CTCAE) v5.0. All toxicity grades ≥ 3, or whose delta (Δ) to baseline were ≥2, were considered significant. The odds ratio (OR) for developing toxicity was tested for non-inferiority of EP vs. YP. Clinical response to PRRT and overall survival (OS) were assessed as secondary outcome measures. Forty-eight EP and 68 YP were enrolled. Both cohorts were balanced regarding median time since diagnosis, tumour location, grading, treatment scheme, and baseline biochemical parameters, except for eGFR (EP: 61 ± 16 vs. YP: 78 ± 19; mL/min/1.73 m²). Twenty-two grade ≥ 3 or Δ ≥ 2 subacute hematotoxicities occurred in 10 EP (10.3% of cycles) and 37 in 19 YP (11.6% of cycles; p = NS). Long-term grade ≥ 3 renal toxicity occurred in 7 EP and 2 YP (p = NS). The median OS was 3.4 years (EP) vs. 6.0 years (YP), HR: 1.50 [0.75, 2.98], p = NS. PRRT is a valid therapeutic option in elderly NET patients with similar toxicity and non-inferior survival compared to matched younger patients.

Prognostic value of whole-body PET volumetric parameters extracted from 68Ga-DOTATOC-PET/CT in well-differentiated neuroendocrine tumors

Aim: To evaluate the prognostic value of somatostatin receptor tumor burden (SRTB) at ⁶⁸Ga-DOTATOC positron emission tomography/computed tomography (PET/CT) in patients with well-differentiated neuroendocrine tumors (WD-NETs). Methods: We retrospectively analyzed ⁶⁸Ga-DOTATOC-PET/CT of 84 patients with histologically confirmed WD-NETs (51 G1, 30 G2 and 3 G3). For each PET/CT, all DOTATOC-avid lesions were independently segmented by 2 operators using a customized threshold based on the healthy liver maximum standardized uptake value (SUV_max) using LIFEx 5.1. Somatostatin receptor expressing tumor volume (SRETV) and total lesion somatostatin receptor expression (TLSRE=SRETV*SUVmean) were extracted for each lesion and then whole-body SRETV and TLSRE (SRETVwb and TLSREwb) were defined as the sum of SRETV and TLSRE of all segmented lesions in each patient, respectively. Time to progression (TTP) was defined as the combination of disease-free-survival in patients undergoing curative surgery (n = 10) and progression-free survival for patients with unresectable/metastatic disease (n = 74). TTP and overall survival (OS) were calculated by Kaplan-Meier analysis, log-rank test, and Cox's proportional hazard model. Results: After a median follow-up period of 15.5 months disease progression was confirmed in 35 patients (41.7%) and 14 patients died. Higher SRETVwb (>39.1ml) and TLSREwb (>306.8g) were significantly correlated with shorter median TTP (TTP = 12months vs not reached; p<0.001). In multivariate analysis, SRETVwb (P = 0.005) was the only independent predictor of TTP regardless of histopathologic grade and TNM staging. Conclusion: According to our results, SRETVwb and TLSREwb extracted from ⁶⁸Ga-DOTATOC-PET/CT could predict TTP/OS and might have an important clinical utility in the management of in patients with WD-NETs.

Automated liver lesion detection in 68Ga DOTATATE PET/CT using a deep fully convolutional neural network

BACKGROUND

Gastroenteropancreatic neuroendocrine tumors most commonly metastasize to the liver; however, high normal background ⁶⁸Ga-DOTATATE activity and high image noise make metastatic lesions difficult to detect. The purpose of this study is to develop a rapid, automated and highly specific method to identify ⁶⁸Ga-DOTATATE PET/CT hepatic lesions using a 2D U-Net convolutional neural network.

METHODS

A retrospective study of ⁶⁸Ga-DOTATATE PET/CT patient studies (n = 125; 57 with ⁶⁸Ga-DOTATATE hepatic lesions and 68 without) was evaluated. The dataset was randomly divided into 75 studies for the training set (36 abnormal, 39 normal), 25 for the validation set (11 abnormal, 14 normal) and 25 for the testing set (11 abnormal, 14 normal). Hepatic lesions were physician annotated using a modified PERCIST threshold, and boundary definition by gradient edge detection. The 2D U-Net was trained independently five times for 100,000 iterations using a linear combination of binary cross-entropy and dice losses with a stochastic gradient descent algorithm. Performance metrics included: positive predictive value (PPV), sensitivity, F₁ score and area under the precision-recall curve (PR-AUC). Five different pixel area thresholds were used to filter noisy predictions.

RESULTS

A total of 233 lesions were annotated with each abnormal study containing a mean of 4 ± 2.75 lesions. A pixel filter of 20 produced the highest mean PPV 0.94 ± 0.01. A pixel filter of 5 produced the highest mean sensitivity 0.74 ± 0.02. The highest mean F₁ score 0.79 ± 0.01 was produced with a 20 pixel filter. The highest mean PR-AUC 0.73 ± 0.03 was produced with a 15 pixel filter.

CONCLUSION

Deep neural networks can automatically detect hepatic lesions in ⁶⁸Ga-DOTATATE PET. Ongoing improvements in data annotation methods, increasing sample sizes and training methods are anticipated to further improve detection performance.

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.