Test-retest repeatability of organ uptake on PSMA-targeted 18 F-DCFPyL PET/CT in patients with prostate cancer.

OBJECTIVES: We evaluated 18 F-DCFPyL test-retest repeatability of uptake in normal organs. METHODS: Twenty-two prostate cancer (PC) patients underwent two 18 F-DCFPyL PET scans within 7 days within a prospective clinical trial (NCT03793543). In both PET scans, uptake in normal organs (kidneys, spleen, liver, and salivary and lacrimal glands) was quantified. Repeatability was determined by using within-subject coefficient of variation (wCOV), with lower values indicating improved repeatability. RESULTS: For SUVmean , repeatability was high for kidneys, spleen, liver, and parotid glands (wCOV, range: 9.0%-14.3%) and lower for lacrimal (23.9%) and submandibular glands (12.4%). For SUVmax , however, the lacrimal (14.4%) and submandibular glands (6.9%) achieved higher repeatability, while for large organs (kidneys, liver, spleen, and parotid glands), repeatability was low (range: 14.1%-45.2%). CONCLUSION: We found acceptable repeatability of uptake on 18 F-DCFPyL PET for normal organs, in particular for SUVmean in the liver or parotid glands. This may have implications for both PSMA-targeted imaging and treatment, as patient selection for radioligand therapy and standardized frameworks for scan interpretation (PROMISE, E-PSMA) rely on uptake in those reference organs.

Imaging and photodynamic therapy of prostate cancer using a theranostic PSMA-targeting ligand.

PURPOSE: Incomplete resection of prostate cancer (PCa) results in increased risk of disease recurrence. Combined fluorescence-guided surgery with tumor-targeted photodynamic therapy (tPDT) may help to achieve complete tumor eradication. We developed a prostate-specific membrane antigen (PSMA) ligand consisting of a DOTA chelator for 111In labeling and a fluorophore/photosensitizer IRDye700DX (PSMA-N064). We evaluated the efficacy of PSMA-tPDT using PSMA-N064 in cell viability assays, a mouse xenograft model and in an ex vivo incubation study on fresh human PCa tissue. METHODS: In vitro, therapeutic efficacy of PSMA-N064 was evaluated using PSMA-positive LS174T cells and LS174T wild-type cells. In vivo, PSMA-N064-mediated tPDT was tested in immunodeficient BALB/c mice-bearing PSMA-positive LS174T xenografts. Tumor growth and survival were compared to control mice that received either NIR light or ligand injection only. Ex vivo tPDT efficacy was evaluated in excised fresh human PCa tissue incubated with PSMA-N064. RESULTS: In vitro, tPDT led to a PSMA-specific light- and ligand dose-dependent loss in cell viability. In vivo, tPDT-induced tumor cell apoptosis, delayed tumor growth, and significantly improved survival (p = 0.004) of the treated PSMA-positive tumor-bearing mice compared with the controls. In fresh ex vivo human PCa tissue, apoptosis was significantly increased in PSMA-tPDT-treated samples compared to non-treated control samples (p = 0.037). CONCLUSION: This study showed the feasibility of PSMA-N064-mediated tPDT in cell assays, a xenograft model and excised fresh human PCa tissue. This paves the way to investigate the impact of in vivo PSMA-tPDT on surgical outcome in PCa patients.

High Interobserver Agreement on PSMA PET/CT Even in the Absence of Clinical Data.

BACKGROUND: Recommended by current guidelines, prostate-specific membrane antigen (PSMA)-directed PET/CT is increasingly used in men with prostate cancer (PC). We aimed to provide concordance rates using the PSMA reporting and data system (RADS) for scan interpretation and also determine whether such agreement rates are affected by available patient characteristics at time of scan. PATIENTS AND METHODS: Sixty men with PC, who all underwent 68Ga-PSMA-11 PET/CT, were included. Three independent, experienced readers indicated general scan parameters (including overall scan result, organ or lymph node [LN] involvement, and appropriateness of radioligand therapy). Applying PSMA-RADS 1.0, observers also had to conduct RADS scoring on a target lesion (TL) and overall scan level. During the first read, observers were masked to all relevant clinical information, whereas on a second read, relevant patient characteristics were displayed, thereby allowing for determination of impact of available clinical information for scan interpretation. We used intraclass correlation coefficients (ICCs; with 95% confidence intervals [CIs]), which were then rated according to Cicchetti (0.4-0.59 fair, 0.6-0.74 good, and 0.75-1 excellent agreement). RESULTS: For general parameters, agreement rates were excellent, including an overall scan result (ICC, 0.85; 95% CI, 0.76-0.90), LN metastases (ICC, 0.89; 95% CI, 0.83-0.93), organ involvement (ICC, 0.82; 95% CI, 0.72-0.89), and indication for radioligand therapy (ICC, 0.94; 95% CI, 0.90-0.96). Overall RADS scoring was also excellent with an ICC of 0.91 (95% CI, 0.96-09.4). On a TL-based level, 251 different lesions were selected by the 3 observers (with 73 chosen by all 3 readers). RADS-based concordance rates were fair to excellent: all lesions, ICC of 0.78 (95% CI, 0.67-0.85); LN, ICC of 0.81 (95% CI, 0.63-0.92); skeleton, ICC of 0.55 (95% CI, 0-0.84); and prostate, ICC of 0.48 (95% CI, 0.17-0.78). When performing a second read displaying patient's characteristics, there were only minor modifications to the previously applied RADS scoring on a TL-based level (overall, n = 8): each reader 1 and 2 in 3/60 (5%) instances, and reader 3 in 2/60 (3.3%) instances. The main reason for recategorization (mainly upstaging) was provided information on PSA levels (4/8, 50%). CONCLUSIONS: Applying PSMA-RADS, concordance rates were fair to excellent, whereas relevant modifications were rarely observed after providing clinical data. As such, even in the absence of patient information, standardized frameworks still provide guidance for reading PSMA PETs. Those findings may have implications for a high throughput in a busy PET practice, where patient details cannot always be retrieved at time of scan interpretation or in the context of clinical trials or central reviews in which readers may be blinded to clinical data.

Lack of repeatability of radiomic features derived from PET scans: Results from a 18 F-DCFPyL test-retest cohort.

OBJECTIVES: PET-based radiomic metrics are increasingly utilized as predictive image biomarkers. However, the repeatability of radiomic features on PET has not been assessed in a test-retest setting. The prostate-specific membrane antigen-targeted compound 18 F-DCFPyL is a high-affinity, high-contrast PET agent that we utilized in a test-retest cohort of men with metastatic prostate cancer (PC). METHODS: Data of 21 patients enrolled in a prospective clinical trial with histologically proven PC underwent two 18 F-DCFPyL PET scans within 7 days, using identical acquisition and reconstruction parameters. Sites of disease were segmented and a set of 29 different radiomic parameters were assessed on both scans. We determined repeatability of quantification by using Pearson's correlations, within-subject coefficient of variation (wCOV), and Bland-Altman analysis. RESULTS: In total, 230 lesions (177 bone, 38 lymph nodes, 15 others) were assessed on both scans. For all investigated radiomic features, a broad range of inter-scan correlation was found (r, 0.07-0.95), with acceptable reproducibility for entropy and homogeneity (wCOV, 16.0% and 12.7%, respectively). On Bland-Altman analysis, no systematic increase or decrease between the scans was observed for either parameter (±1.96 SD: 1.07/-1.30, 0.23/-0.18, respectively). The remaining 27 tested radiomic metrics, however, achieved unacceptable high wCOV (≥21.7%). CONCLUSION: Many common radiomic features derived from a test-retest PET study had poor repeatability. Only Entropy and homogeneity achieved good repeatability, supporting the notion that those image biomarkers may be incorporated in future clinical trials. Those radiomic features based on high frequency aspects of images appear to lack the repeatability on PET to justify further study.

High SUVs Have More Robust Repeatability in Patients with Metastatic Prostate Cancer: Results from a Prospective Test-Retest Cohort Imaged with 18F-DCFPyL.

Objectives: In patients with prostate cancer (PC) receiving prostate-specific membrane antigen- (PSMA-) targeted radioligand therapy (RLT), higher baseline standardized uptake values (SUVs) are linked to improved outcome. Thus, readers deciding on RLT must have certainty on the repeatability of PSMA uptake metrics. As such, we aimed to evaluate the test-retest repeatability of lesion uptake in a large cohort of patients imaged with 18F-DCFPyL. Methods: In this prospective, IRB-approved trial (NCT03793543), 21 patients with history of histologically proven PC underwent two 18F-DCFPyL PET/CTs within 7 days (mean 3.7, range 1 to 7 days). Lesions in the bone, lymph nodes (LN), and other organs were manually segmented on both scans, and uptake parameters were assessed (maximum (SUVmax) and mean (SUVmean) SUVs), PSMA-tumor volume (PSMA-TV), and total lesion PSMA (TL-PSMA, defined as PSMA - TV × SUVmean)). Repeatability was determined using Pearson's correlations, within-subject coefficient of variation (wCOV), and Bland-Altman analysis. Results: In total, 230 pairs of lesions (177 bone, 38 LN, and 15 other) were delineated, demonstrating a wide range of SUVmax (1.5-80.5) and SUVmean (1.4-24.8). Including all sites of suspected disease, SUVs had a strong interscan correlation (R 2 ≥ 0.99), with high repeatability for SUVmean and SUVmax (wCOV, 7.3% and 12.1%, respectively). High SUVs showed significantly improved wCOV relative to lower SUVs (P < 0.0001), indicating that high SUVs are more repeatable, relative to the magnitude of the underlying SUV. Repeatability for PSMA-TV and TL-PSMA, however, was low (wCOV ≥ 23.5%). Across all metrics for LN and bone lesions, interscan correlation was again strong (R 2 ≥ 0.98). Moreover, LN-based SUVmean also achieved the best wCOV (3.8%), which was significantly reduced when compared to osseous lesions (7.8%, P < 0.0001). This was also noted for SUVmax (wCOV, LN 8.8% vs. bone 12.0%, P < 0.03). On a compartment-based level, wCOVs for volumetric features were ≥22.8%, demonstrating no significant differences between LN and bone lesions (PSMA-TV, P =0.63; TL-PSMA, P =0.9). Findings on an entire tumor burden level were also corroborated in a hottest lesion analysis investigating the SUVmax of the most intense lesion per patient (R 2, 0.99; wCOV, 11.2%). Conclusion: In this prospective test-retest setting, SUV parameters demonstrated high repeatability, in particular in LNs, while volumetric parameters demonstrated low repeatability. Further, the large number of lesions and wide distribution of SUVs included in this analysis allowed for the demonstration of a dependence of repeatability on SUV, with higher SUVs having more robust repeatability.

Strain-Promoted Azide-Alkyne Cycloaddition-Based PSMA-Targeting Ligands for Multimodal Intraoperative Tumor Detection of Prostate Cancer.

Strain-promoted azide-alkyne cycloaddition (SPAAC) is a straightforward and multipurpose conjugation strategy. The use of SPAAC to link different functional elements to prostate-specific membrane antigen (PSMA) ligands would facilitate the development of a modular platform for PSMA-targeted imaging and therapy of prostate cancer (PCa). As a first proof of concept for the SPAAC chemistry platform, we synthesized and characterized four dual-labeled PSMA ligands for intraoperative radiodetection and fluorescence imaging of PCa. Ligands were synthesized using solid-phase chemistry and contained a chelator for 111In or 99mTc labeling. The fluorophore IRDye800CW was conjugated using SPAAC chemistry or conventional N-hydroxysuccinimide (NHS)-ester coupling. Log D values were measured and PSMA specificity of these ligands was determined in LS174T-PSMA cells. Tumor targeting was evaluated in BALB/c nude mice with subcutaneous LS174T-PSMA and LS174T wild-type tumors using µSPECT/CT imaging, fluorescence imaging, and biodistribution studies. SPAAC chemistry increased the lipophilicity of the ligands (log D range: -2.4 to -4.4). In vivo, SPAAC chemistry ligands showed high and specific accumulation in s.c. LS174T-PSMA tumors up to 24 h after injection, enabling clear visualization using µSPECT/CT and fluorescence imaging. Overall, no significant differences between the SPAAC chemistry ligands and their NHS-based counterparts were found (2 h p.i., p > 0.05), while 111In-labeled ligands outperformed the 99mTc ligands. Here, we demonstrate that our newly developed SPAAC-based PSMA ligands show high PSMA-specific tumor targeting. The use of click chemistry in PSMA ligand development opens up the opportunity for fast, efficient, and versatile conjugations of multiple imaging moieties and/or drugs.

Radiolabeling Strategies of Nanobodies for Imaging Applications.

Nanobodies are small recombinant antigen-binding fragments derived from camelid heavy-chain only antibodies. Due to their compact structure, pharmacokinetics of nanobodies are favorable compared to full-size antibodies, allowing rapid accumulation to their targets after intravenous administration, while unbound molecules are quickly cleared from the circulation. In consequence, high signal-to-background ratios can be achieved, rendering radiolabeled nanobodies high-potential candidates for imaging applications in oncology, immunology and specific diseases, for instance in the cardiovascular system. In this review, a comprehensive overview of central aspects of nanobody functionalization and radiolabeling strategies is provided.

Evaluating a Machine Learning Tool for the Classification of Pathological Uptake in Whole-Body PSMA-PET-CT Scans.

The importance of machine learning (ML) in the clinical environment increases constantly. Differentiation of pathological from physiological tracer-uptake in positron emission tomography/computed tomography (PET/CT) images is considered time-consuming and attention intensive, hence crucial for diagnosis and treatment planning. This study aimed at comparing and validating supervised ML algorithms to classify pathological uptake in prostate cancer (PC) patients based on prostate-specific membrane antigen (PSMA)-PET/CT. Retrospective analysis of 68Ga-PSMA-PET/CTs of 72 PC patients resulted in a total of 77 radiomics features from 2452 manually delineated hotspots for training and labeled pathological (1629) or physiological (823) as ground truth (GT). As the held-out test dataset, 331 hotspots (path.:128, phys.: 203) were delineated in 15 other patients. Three ML classifiers were trained and ranked to assess classification performance. As a result, a high overall average performance (area under the curve (AUC) of 0.98) was achieved, especially to detect pathological uptake (0.97 mean sensitivity). However, there is still room for improvement to detect physiological uptake (0.82 mean specificity), especially for glands. The ML algorithm applied to manually delineated lesions predicts hotspot labels with high accuracy on unseen data and may be an important tool to assist in clinical diagnosis.

Decision-support for treatment with 177Lu-PSMA: machine learning predicts response with high accuracy based on PSMA-PET/CT and clinical parameters.

BACKGROUND: Treatment with radiolabeled ligands to prostate-specific membrane antigen (PSMA) is gaining importance in the treatment of patients with advanced prostate carcinoma. Previous imaging with positron emission tomography/computed tomography (PET/CT) is mandatory. The aim of this study was to investigate the role of radiomics features in PSMA-PET/CT scans and clinical parameters to predict response to 177Lu-PSMA treatment given just baseline PSMA scans using state-of-the-art machine learning (ML) methods. METHODS: A total of 2,070 pathological hotspots annotated in 83 prostate cancer patients undergoing PSMA therapy were analyzed. Two main tasks are performed: (I) analyzing correlation of averaged (per patient) values of radiomics features of individual hotspots and clinical parameters with difference in prostate specific antigen levels (ΔPSA) in pre- and post-therapy as a therapy response indicator. (II) ML-based classification of patients into responders and non-responders based on averaged features values and clinical parameters. To achieve this, machine learning (ML) algorithms and linear regression tests are applied. Grid search, cross validation (CV) and permutation test were performed to assure that the results were significant. RESULTS: Radiomics features (PET_Min, PET_Correlation, CT_Min, CT_Busyness and CT_Coarseness) and clinical parameters such as Alp1 and Gleason score showed best correlations with ΔPSA. For the treatment response prediction task, 80% area under the curve (AUC), 75% sensitivity (SE), and 75% specificity (SP) were obtained, applying ML support vector machine (SVM) classifier with radial basis function (RBF) kernel on a selection of radiomics features and clinical parameters with strong correlations with ΔPSA. CONCLUSIONS: Machine learning based on 68Ga-PSMA PET/CT radiomics features holds promise for the prediction of response to 177Lu-PSMA treatment, given only base-line 68Ga-PSMA scan. In addition, it was shown that, the best correlating set of radiomics features with ΔPSA are superior to clinical parameters for this therapy response prediction task using ML classifiers.

Estimating the Potential of Radiomics Features and Radiomics Signature from Pretherapeutic PSMA-PET-CT Scans and Clinical Data for Prediction of Overall Survival When Treated with 177Lu-PSMA.

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PSMA-PET/CT) scans can facilitate diagnosis and treatment of prostate disease. Radiomics signature (RS) is widely used for the analysis of overall survival (OS) in cancer diseases. This study aims at investigating the role of radiomics features (RFs) and RS from pretherapeutic gallium-68 (68Ga)-PSMA-PET/CT findings and patient-specific clinical parameters to analyze overall survival of prostate cancer (PC) patients when treated with lutethium-177 (177Lu)-PSMA. A cohort of 83 patients with advanced PC was retrospectively analyzed. Average values of 73 RFs of 2070 malignant hotspots as well as 22 clinical parameters were analyzed for each patient. From the Cox proportional hazard model, the least absolute shrinkage and selection operator (LASSO) regularization method is used to select most relevant features (standardized uptake value (SUV)Min and kurtosis with the coefficients of 0.984 and -0.118, respectively) and to calculate the RS from the RFs. Kaplan-Meier (KM) estimator was used to analyze the potential of RFs and conventional clinical parameters, such as metabolic tumor volume (MTV) and standardized uptake value (SUV) for the prediction of survival. As a result, SUVMin, kurtosis, the calculated RS, SUVMean, as well as Hemoglobin (Hb)1, C-reactive protein (CRP)1, and ECOG1 (clinical parameters) achieved p-values less than 0.05, which suggest the potential of findings from 68Ga-PSMA-PET/CT scans as well as patient-specific clinical parameters for the prediction of OS for patients with advanced PC treated with 177Lu-PSMA therapy.

Photosensitizer-based multimodal PSMA-targeting ligands for intraoperative detection of prostate cancer.

Incomplete resection of prostate cancer (PCa) occurs in 15%-50% of PCa patients. Disease recurrence negatively impacts oncological outcome. The use of radio-, fluorescent-, or photosensitizer-labeled ligands to target the prostate-specific membrane antigen (PSMA) has become a well-established method for the detection and treatment of PCa. Methods: Here, we developed and characterized multimodal [111In]In-DOTA(GA)-IRDye700DX-PSMA ligands, varying in their molecular composition, for use in intraoperative radiodetection, fluorescence imaging and targeted photodynamic therapy of PCa lesions. PSMA-specificity of these ligands was determined in xenograft tumor models and on fresh human PCa biopsies. Results: Ligand structure optimization showed that addition of the photosensitizer (IRDye700DX) and additional negative charges significantly increased ligand uptake in PSMA-expressing tumors. Moreover, an ex vivo incubation study on human tumor biopsies confirmed the PSMA-specificity of these ligands on human samples, bridging the gap to the clinical situation. Conclusion: We developed a novel PSMA-targeting ligand, optimized for multimodal image-guided PCa surgery combined with targeted photodynamic therapy.

Machine Learning Facilitates Hotspot Classification in PSMA-PET/CT with Nuclear Medicine Specialist Accuracy.

Gallium-68 prostate-specific membrane antigen positron emission tomography (68Ga-PSMA-PET) is a highly sensitive method to detect prostate cancer (PC) metastases. Visual discrimination between malignant and physiologic/unspecific tracer accumulation by a nuclear medicine (NM) specialist is essential for image interpretation. In the future, automated machine learning (ML)-based tools will assist physicians in image analysis. The aim of this work was to develop a tool for analysis of 68Ga-PSMA-PET images and to compare its efficacy to that of human readers. Five different ML methods were compared and tested on multiple positron emission tomography/computed tomography (PET/CT) data-sets. Forty textural features extracted from both PET- and low-dose CT data were analyzed. In total, 2419 hotspots from 72 patients were included. Comparing results from human readers to those of ML-based analyses, up to 98% area under the curve (AUC), 94% sensitivity (SE), and 89% specificity (SP) were achieved. Interestingly, textural features assessed in native low-dose CT increased the accuracy significantly. Thus, ML based on 68Ga-PSMA-PET/CT radiomics features can classify hotspots with high precision, comparable to that of experienced NM physicians. Additionally, the superiority of multimodal ML-based analysis considering all PET and low-dose CT features was shown. Morphological features seemed to be of special additional importance even though they were extracted from native low-dose CTs.

Textural features in FDG-PET/CT can predict outcome in melanoma patients to treatment with Vemurafenib and Ipililumab.

AIM: Recently, textural parameters assessed in FDG-PET/CT as surrogate marker for tumor heterogeneity have been shown to provide prognostic power. Therefore, we investigated the use of such parameters in FDG-PET/CT examinations before the start of immunotherapy with vemurafenib or ipilimumab in patients with malignant melanoma. METHODS: In this retrospective analysis 26 patients with histologically proven advanced melanoma were included. FGD-PET/CT was performed before the start of treatment either with vemurafenib (n = 9) or ipilimumab (n = 17) and tumors were analyzed for textural parameters as well as conventional PET features. Lesions were classified as responding or not responding following PERCIST criteria. ROC analysis was performed to analyze the predictive power and cut-off values. In addition, the change of maximum SUV of the lesions between pretherapeutic PET/CT and another PET/CT performed about 12 weeks after start of treatment was evaluated and correlated with the pretreatment parameters. RESULTS: In both groups, six textural parameters showed statistically significant predictive power as well as the metabolic tumor volume. In the group treated with vemurafenib eight additional textural parameters as well as the maximum and mean SUV and the TLG showed significance. A statistically significant correlation between the change of maximum SUV in the course of treatment and the pretherapeutic parameters was found in both treatment groups for three textural features. CONCLUSION: In patients with malignant melanoma textural parameters in pretherapeutic FDG-PET/CT examinations seem to have prognostic power for treatment response of immunotherapy with vemurafenib and ipilimumab. This can be an important step towards personalized tumor therapy.

Nuclear medicine in SARS-CoV-2 pandemia: 18F-FDG-PET/CT to visualize COVID-19.

The current outbreak of coronavirus SARS-CoV-2 has reached multiple countries worldwide. While the number of newly diagnosed cases and fatalities is rising quickly, far-reaching measures were enacted to prevent further spread. Diagnosis relies on clinical presentation, exposure history, PCR using specimens from the respiratory tract together with computed tomography (CT) imaging. One of the hallmarks of a critical course of COVID-19 is the development of severe acute respiratory distress syndrome (ARDS). As management of COVID-19 can be considered a multi-disciplinary approach involving various medical specialties, we here review the first 18F-FDG-PET/CT scans of COVID-19 to discuss how Nuclear Medicine could contribute to management of this disease.

68Ga-PSMA-HBED-CC PET/CT imaging for adenoid cystic carcinoma and salivary duct carcinoma: a phase 2 imaging study.

Rationale: Treatment options for recurrent and/or metastatic (R/M) adenoid cystic carcinoma (ACC) and salivary duct carcinoma (SDC), major subtypes of salivary gland cancer, are limited. Both tumors often show overexpression of prostate-specific membrane antigen (PSMA). In prostate cancer, PSMA-ligands labeled with 68Ga or 177Lu are used for imaging and therapy, respectively. Primary aim of this study in R/M ACC and SDC patients was to systematically investigate 68Ga-PSMA-uptake by PET/CT imaging to determine if PSMA radionuclide therapy could be a treatment option. Methods: In a prospective phase II study, PET/CT imaging was performed 1 h post injection of 68Ga-PSMA-HBED-CC in 15 ACC patients and 10 SDC patients. Maximum standardized uptake values (SUV) were determined in tumor lesions. Immunohistochemical PSMA expression was scored in primary tumors and metastatic tissue. Standard imaging (MRI or CT) was performed for comparison. Results: In ACC patients, SUVmax ranged from 1.1 to 30.2 with a tumor/liver-ratio >1 in 13 out of 14 evaluable patients (93%). In SDC patients, SUVmax ranged from 0.3 to 25.9 with a tumor/liver-ratio >1 in 4 out of 10 patients (40%). We found a large intra-patient inter-metastatic variation in uptake of 68Ga-PSMA, and immunohistochemistry did not predict ligand uptake in ACC and SDC. Finally, PSMA-PET detected additional bone metastases compared to CT in 2 ACC patients with unexplained pain. Conclusion: In 93% of ACC patients and 40% of SDC patients we detected relevant PSMA-ligand uptake, which warrants to study PSMA radionuclide therapy in these patients. Additionally, our data provide arguments for patient selection and treatment timing. Finally, PSMA-PET imaging has added diagnostic value compared to CT in selected patients.

Immune Checkpoint Imaging in Oncology: A Game Changer Toward Personalized Immunotherapy?

Immune checkpoint blockade represents a promising approach in oncology, showing antitumor activities in various cancers. However, although being generally far better tolerated than classic cytotoxic chemotherapy, this treatment, too, may be accompanied by considerable side effects and not all patients benefit equally. Therefore, careful patient selection and monitoring of the treatment response is mandatory. At present, checkpoint-specific molecular imaging is being increasingly investigated as a tool for patient selection and response evaluation. Here, an overview of the current developments in immune checkpoint imaging is provided.

PSMA-targeting agents for radio- and fluorescence-guided prostate cancer surgery.

Despite recent improvements in imaging and therapy, prostate cancer (PCa) still causes substantial morbidity and mortality. In surgical treatment, incomplete resection of PCa and understaging of possible undetected metastases may lead to disease recurrence and consequently poor patient outcome. To increase the chance of accurate staging and subsequently complete removal of all cancerous tissue, prostate specific membrane antigen (PSMA) targeting agents may provide the surgeon an aid for the intraoperative detection and resection of PCa lesions. Two modalities suitable for this purpose are radionuclide detection, which allows sensitive intraoperative localization of tumor lesions with a gamma probe, and fluorescence imaging, allowing tumor visualization and delineation. Next to fluorescence, use of photosensitizers may enable intraoperative targeted photodynamic therapy to eradicate remaining tumor lesions. Since radiodetection and optical imaging techniques each have their own strengths and weaknesses, a combination of both modalities could be of additional value. Here, we provide an overview of recent preclinical and clinical advances in PSMA-targeted radio- and fluorescence-guided surgery of PCa.

Therapy of Patients with Neuroendocrine Neoplasia-Evidence-Based Approaches and New Horizons.

Neuroendocrine tumors (NETs) show low but increasing incidence and originate in multiple organs, including the pancreas, midgut, caecum, rectum, appendix, colon, and lungs. Due to their stunning genetic, histological, and clinical variability, diagnosis and treatment of NETs are challenging. In addition, low incidence and high variability hamper the implementation of high evidence trials. Therefore, guidelines do not cover the complexity of NETs and, frequently, treatment decisions are taken by interdisciplinary tumor conferences at comprehensive cancer centers. Treatment aims are (i) control of tumor growth, (ii) symptom control, as well as (iii) the improvement of progression-free survival (PFS) and overall survival (OS). Here, we discuss high evidence trials facilitating the achievement of these treatment aims. The majority of the evidence exists for treatment with somatostatin analogue, everolimus, peptide receptor radionuclide therapy (PRRT) with 177Lu-DOTATATE, sunitinib, and telotristat. Among those, PRRT is the only treatment option that has the potential to control symptoms, stop tumor growth, and to improve PFS and OS. In contrast, only a low level of evidence exists for treatment with cytotoxic drugs such as streptozotocin and doxorubicine. Finally, we discuss novel treatment options by a combination of cytotoxic drugs, 177Lu-DOTATATE, and tyrosine kinase inhibitors to be tested in randomized prospective trials in the future. In addition, the application of innovative isotopes, such as 225Ac, for PRRT is discussed.

A pretargeted multimodal approach for image-guided resection in a xenograft model of colorectal cancer.

BACKGROUND: Image-guided surgery may improve surgical outcome for colorectal cancer patients. Here, we evaluated the feasibility of a pretargeting strategy for multimodal imaging in colorectal cancer using an anti-carcinoembryonic antigen (CEA) x anti-histamine-succinyl-glycine (HSG) bispecific antibody (TF2) in conjunction with the dual-labeled diHSG peptide (RDC018), using both a fluorophore for near-infrared fluorescence imaging and a chelator for radiolabeling. METHODS: Nude mice with subcutaneous (s.c) CEA-expressing LS174T human colonic tumors and CEA-negative control tumors were injected with TF2. After 16 h, different doses of 111In-labeled IMP-288 (non-fluorescent) or its fluorescent derivative RDC018 were administered to compare biodistributions. MicroSPECT/CT and near-infrared fluorescence imaging were performed 2 and 24 h after injection. Next, the biodistribution of the dual-labeled humanized anti-CEA IgG antibody [111In]In-DTPA-hMN-14-IRDye800CW (direct targeting) was compared with the biodistribution of 111In-RDC018 in mice with TF2-pretargeted tumors, using fluorescence imaging and gamma counting. Lastly, mice with intraperitoneal LS174T tumors underwent near-infrared fluorescence image-guided resection combined with pre- and post-resection microSPECT/CT imaging. RESULTS: 111In-RDC018 showed specific tumor targeting in pretargeted CEA-positive tumors (21.9 ± 4.5 and 10.0 ± 4.7% injected activity per gram (mean ± SD %IA/g), at 2 and 24 hours post-injection (p.i.), respectively) and a biodistribution similar to 111In-IMP288. Both fluorescence and microSPECT/CT images confirmed preferential tumor accumulation. At post mortem dissection, intraperitoneal tumors were successfully identified and removed using pretargeting with TF2 and 111In-RDC018. CONCLUSION: A pretargeted approach for multimodal image-guided resection of colorectal cancer in a preclinical xenograft model is feasible, enables preoperative SPECT/CT, and might facilitate intraoperative fluorescence imaging.

Development and characterization of a theranostic multimodal anti-PSMA targeting agent for imaging, surgical guidance, and targeted photodynamic therapy of PSMA-expressing tumors.

Rationale: Prostate cancer (PCa) recurrences after surgery frequently occur. To improve the outcome after surgical resection of the tumor, the theranostic multimodal anti-PSMA targeting agent 111In-DTPA-D2B-IRDye700DX was developed and characterized for both pre- and intra-operative tumor localization and eradication of (residual) tumor tissue by PSMA-targeted photodynamic therapy (tPDT), which is a highly selective cancer treatment based on targeting molecules conjugated to photosensitizers that can induce cell destruction upon exposure to near-infrared (NIR) light. Methods: The anti-PSMA monoclonal antibody D2B was conjugated with IRDye700DX and DTPA and subsequently radiolabeled with 111In. To determine the optimal dose and time point for tPDT, BALB/c nude mice with PSMA-expressing (PSMA+) s.c. LS174T-PSMA xenografts received the conjugate (24-240 µg/mouse) intravenously (8 MBq/mouse) followed by µSPECT/CT, near-infrared fluorescence imaging, and ex vivo biodistribution at 24, 48, 72 and 168 h p.i. Tumor growth of LS174T-PSMA xenografts and overall survival of mice treated with 1-3 times of NIR light irradiation (50, 100, 150 J/cm2) 24 h after injection of 80 µg of DTPA-D2B-IRDye700DX was compared to control conditions. Results: Highest specific tumor uptake was observed at conjugate doses of 80 µg/mouse. Biodistribution revealed no significant difference in tumor uptake in mice at 24, 48, 72 and 168 h p.i. PSMA+ tumors were clearly visualized with both µSPECT/CT and NIR fluorescence imaging. Overall survival in mice treated with 80 µg of DTPA-D2B-IRDye700DX and 1x 150 J/cm2 of NIR light at 24 h p.i. was significantly improved compared to the control group receiving neither conjugate nor NIR light (73 days vs. 16 days, respectively, p=0.0453). Treatment with 3x 150 J/cm2 resulted in significantly prolonged survival compared to treatment with 3x 100 J/cm2 (p = 0.0067) and 3x 50 J/cm2 (p = 0.0338). Principal conclusions:111In-DTPA-D2B-IRDye700DX can be used for pre- and intra-operative detection of PSMA+ tumors with radionuclide and NIR fluorescence imaging and PSMA-targeted PDT. PSMA-tPDT using this multimodal agent resulted in significant prolongation of survival and shows great potential for treatment of (metastasized) prostate cancer.