Concurrent pembrolizumab with AVD for untreated classic Hodgkin lymphoma.

Concurrent administration of pembrolizumab with chemotherapy in untreated classic Hodgkin lymphoma (CHL) has not been studied previously. To investigate this combination, we conducted a single-arm study of concurrent pembrolizumab with AVD (doxorubicin, vinblastine, and dacarbazine; APVD) for untreated CHL. We enrolled 30 patients and met the primary safety end point with no observed significant treatment delays in the first 2 cycles. Twelve patients experienced grade 3 or 4 nonhematologic adverse events (AEs), most commonly febrile neutropenia and infection/sepsis. Grade 3 or 4 immune-related AEs, including alanine aminotransferase elevation and aspartate aminotransferase elevation were observed in 3 patients. One patient experienced an episode of grade 2 colitis and arthritis. Six patients missed at least 1 dose of pembrolizumab because of AEs, primarily grade 2 or higher transaminitis. Among 29 response-evaluable patients, the best overall response rate was 100% and the complete response rate was 90%. With a median follow-up of 2.1 years, the 2-year progression-free survival (PFS) and overall survival were 97% and 100%, respectively. To date, no patient who has withheld or discontinued pembrolizumab because of toxicity has progressed. Clearance of circulating tumor DNA (ctDNA) was associated with superior PFS when measured after cycle 2 and at the end of treatment (EOT). None of the 4 patients with persistent uptake by fluorodeoxyglucose positron emission tomography (PET) at EOT yet negative ctDNA have relapsed to date. Concurrent APVD shows promising safety and efficacy but may yield spurious PET findings in some patients. This trial was registered at www.clinicaltrials.gov as #NCT03331341.

Artificial intelligence in immunotherapy PET/SPECT imaging.

OBJECTIVE: Immunotherapy has dramatically altered the therapeutic landscape for oncology, but more research is needed to identify patients who are likely to achieve durable clinical benefit and those who may develop unacceptable side effects. We investigated the role of artificial intelligence in PET/SPECT-guided approaches for immunotherapy-treated patients. METHODS: We performed a scoping review of MEDLINE, CENTRAL, and Embase databases using key terms related to immunotherapy, PET/SPECT imaging, and AI/radiomics through October 12, 2022. RESULTS: Of the 217 studies identified in our literature search, 24 relevant articles were selected. The median (interquartile range) sample size of included patient cohorts was 63 (157). Primary tumors of interest were lung (n = 14/24, 58.3%), lymphoma (n = 4/24, 16.7%), or melanoma (n = 4/24, 16.7%). A total of 28 treatment regimens were employed, including anti-PD-(L)1 (n = 13/28, 46.4%) and anti-CTLA-4 (n = 4/28, 14.3%) monoclonal antibodies. Predictive models were built from imaging features using univariate radiomics (n = 7/24, 29.2%), radiomics (n = 12/24, 50.0%), or deep learning (n = 5/24, 20.8%) and were most often used to prognosticate (n = 6/24, 25.0%) or describe tumor phenotype (n = 5/24, 20.8%). Eighteen studies (75.0%) performed AI model validation. CONCLUSION: Preliminary results suggest broad potential for the application of AI-guided immunotherapy management after further validation of models on large, prospective, multicenter cohorts. CLINICAL RELEVANCE STATEMENT: This scoping review describes how artificial intelligence models are built to make predictions based on medical imaging and explores their application specifically in the PET and SPECT examination of immunotherapy-treated cancers. KEY POINTS: • Immunotherapy has drastically altered the cancer treatment landscape but is known to precipitate response patterns that are not accurately accounted for by traditional imaging methods. • There is an unmet need for better tools to not only facilitate in-treatment evaluation but also to predict, a priori, which patients are likely to achieve a good response with a certain treatment as well as those who are likely to develop side effects. • Artificial intelligence applied to PET/SPECT imaging of immunotherapy-treated patients is mainly used to make predictions about prognosis or tumor phenotype and is built from baseline, pre-treatment images. Further testing is required before a true transition to clinical application can be realized.

Chemokine Receptor 2-targeted Molecular Imaging in Pulmonary Fibrosis. A Clinical Trial.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a progressive inflammatory lung disease without effective molecular markers of disease activity or treatment responses. Monocyte and interstitial macrophages that express the C-C motif CCR2 (chemokine receptor 2) are active in IPF and central to fibrosis.Objectives: To phenotype patients with IPF for potential targeted therapy, we developed 64Cu-DOTA-ECL1i, a radiotracer to noninvasively track CCR2+ monocytes and macrophages using positron emission tomography (PET).Methods: CCR2+ cells were investigated in mice with bleomycin- or radiation-induced fibrosis and in human subjects with IPF. The CCR2+ cell populations were localized relative to fibrotic regions in lung tissue and characterized using immunolocalization, single-cell mass cytometry, and Ccr2 RNA in situ hybridization and then correlated with parallel quantitation of lung uptake by 64Cu-DOTA-ECL1i PET.Measurements and Main Results: Mouse models established that increased 64Cu-DOTA-ECL1i PET uptake in the lung correlates with CCR2+ cell infiltration associated with fibrosis (n = 72). As therapeutic models, the inhibition of fibrosis by IL-1ß blockade (n = 19) or antifibrotic pirfenidone (n = 18) reduced CCR2+ macrophage accumulation and uptake of the radiotracer in mouse lungs. In lung tissues from patients with IPF, CCR2+ cells concentrated in perifibrotic regions and correlated with radiotracer localization (n = 21). Human imaging revealed little lung uptake in healthy volunteers (n = 7), whereas subjects with IPF (n = 4) exhibited intensive signals in fibrotic zones.Conclusions: These findings support a role for imaging CCR2+ cells within the fibrogenic niche in IPF to provide a molecular target for personalized therapy and monitoring.Clinical trial registered with www.clinicaltrials.gov (NCT03492762).

Radiologic Assessment of Groin Lymph Nodes in Pelvic Malignancies.

INTRODUCTION: Metastatic involvement of groin nodes can alter radiation therapy planning for pelvic tumors. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) can identify nodal metastases; however, interpretation of PET/CT-positive nodes can be complicated by non-malignant processes. We evaluated quantitative metrics as methods to identify groin metastases in patients with pelvic tumors by comparison with standard subjective interpretive criteria, with pathology as the reference standard. METHODS: We retrospectively identified patients with vulvar, vaginal, or anal cancers who underwent 18F-FDG PET/CT before pathologic evaluation of groin nodes between 2007 and 2017. Because patho-radiologic correlation was not possible for every node, one index node identified on imaging was selected for each groin. For each index node, standardized uptake value measurements, total lesion glycolysis, metabolic tumor volume, CT-based volume, and short and long axes were measured. Multivariate logistic regression was used to identify metrics predictive for pathologically positive groins and generate a probabilistic model. Area under the receiver-operating characteristic curves (AUCs) for the model were compared with clinical interpretation from the diagnostic report via a Wald's χ2 test. RESULTS: Of 55 patients identified for analysis, 75 groins had pathologic evaluation resulting in 75 index groin nodes for analysis with 35 groins pathologically positive for malignancy. Logistic regression identified mean standardized-uptake-value (50% threshold) and short-axis length as the most predictive imaging metrics for metastatic nodal involvement. The probabilistic model performed better at predicting pathologic involvement compared with standard clinical interpretation on analysis (AUC 0.91, 95% CI 0.84 to 0.97 vs 0.80, 95% CI 0.71 to 0.89; p<0.01). DISCUSSION: Accuracy of 18F-FDG PET/CT for detecting groin nodal metastases in patients with pelvic tumors may be improved with the use of quantitative metrics. Improving prediction of nodal metastases can aid with appropriate selection of patients for pathologic node evaluation and guide radiation volumes and doses.

Long-range function of secreted small nucleolar RNAs that direct 2'-O-methylation.

Small nucleolar RNAs (snoRNAs) are noncoding RNAs that guide chemical modifications of structural RNAs. Whereas snoRNAs primarily localize in the nucleolus, where their canonical function is to target nascent ribosomal RNAs for 2'-O-methylation, recent studies provide evidence that snoRNAs traffic out of the nucleus. Furthermore, RNA-Seq data indicate that extracellular vesicles released from cells contain snoRNAs. However, it is not known whether snoRNA secretion is regulated or whether secreted snoRNAs are functional. Here, we show that inflammation stimulates secretion of Rpl13a snoRNAs U32a (SNORD32a), U33 (SNORD33), U34 (SNORD34), and U35a (SNORD35a) from cultured macrophages, in mice, and in human subjects. Secreted snoRNAs co-fractionate with extracellular vesicles and are taken up by recipient cells. In a murine parabiosis model, we demonstrate that snoRNAs travel through the circulation to function in distant tissues. These findings support a previously unappreciated link between inflammation and snoRNA secretion in mice and humans and uncover a potential role for secreted snoRNAs in cell-cell communication.

Nurse-Led Tele-Coaching on Modifiable Cardiovascular Risk Factors in People with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis.

BACKGROUND: Tele-coaching has been used by nurses as one of the accessible and sustainable interventions for individuals with type 2 diabetes mellitus. However, evidence has been lacking to demonstrate its effectiveness in mitigating the related cardiovascular risk factors. AIMS: To systematically evaluate the effectiveness of nurse-led tele-coaching on the modifiable cardiovascular risk factors (glycated hemoglobin, blood pressure, & lipid levels) among individuals with type 2 diabetes mellitus. METHODS: A systematic search of eight databases (Cochrane Library, PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, Scopus, PsycINFO, Web of Science, & ProQuest Dissertations and Theses) was conducted for randomized controlled trials of nurse-led tele-coaching for individuals with type 2 diabetes mellitus published in English up to October 30, 2018. A meta-analysis was conducted for the primary outcomes of the studies. RESULTS: Twelve randomized controlled trials were selected that included 3,030 participants. Results from the meta-analysis revealed statistically significant reductions for not only glycated hemoglobin (pooled mean difference = -1.23, 95% CI: -1.63 to -0.8, I2  = 0%, p < .00) but also systolic blood pressure (SBP; pooled mean difference = -2.22, 95% CI: -3.95 to -0.49, I2  = 0%, p < .01); such findings are supportive of the use of nurse-led tele-coaching on the primary outcome. LINKING EVIDENCE TO ACTION: Results from the meta-analyses have shown that nurse-led tele-coaching is an effective and accessible intervention that could improve the glycemic control and SBP among individuals with type 2 diabetes mellitus.

Syntheses and in vitro biological evaluation of S1PR1 ligands and PET studies of four F-18 labeled radiotracers in the brain of nonhuman primates.

A series of seventeen hydroxyl-containing sphingosine 1-phosphate receptor 1 (S1PR1) ligands were designed and synthesized. Their in vitro binding potencies were determined using [32P]S1P competitive binding assays. Compounds 10a, 17a, 17b, and 24 exhibited high S1PR1 binding potencies with IC50 values ranging from 3.9 to 15.4 nM and also displayed high selectivity for S1PR1 over other S1P receptor subtypes (IC50 > 1000 nM for S1PR2-5). The most potent compounds 10a, 17a, 17b, and 24 were subsequently radiolabeled with F-18 in high yields and purities. MicroPET studies in cynomolgus macaque showed that [18F]10a, [18F]17a, and [18F]17b but not [18F]24 crossed the blood brain barrier and had high initial brain uptake. Further validation of [18F]10a, [18F]17a, and [18F]17b in preclinical models of neuroinflammation is warranted to identify a suitable PET radioligand to quantify S1PR1 expression in vivo as a metric of an inflammatory response.

PET of Poly (ADP-Ribose) Polymerase Activity in Cancer: Preclinical Assessment and First In-Human Studies.

Purpose To demonstrate that positron emission tomography (PET) with fluorine 18 (18F) fluorthanatrace (FTT) depicts activated poly (adenosine diphosphate-ribose)polymerase (PARP) expression and is feasible for clinical trial evaluation. Materials and Methods All studies were conducted prospectively from February 2012 through July 2015 under protocols approved by the local animal studies committee and institutional review board. The area under the receiver operating characteristic curve (AUC, in g/mL· min) for 18F-FTT was assessed in normal mouse organs before and after treatment with olaparib (n = 14), a PARP inhibitor, or iniparib (n = 11), which has no PARP inhibitory activity. Murine biodistribution studies were performed to support human translational studies. Eight human subjects with cancer and eight healthy volunteers underwent imaging to verify the human radiation dosimetry of 18F-FTT. The Wilcoxon signed rank test was used to assess for differences among treatment groups for the mouse studies. Results In mice, olaparib, but not iniparib, significantly reduced the 18F-FTT AUC in the spine (median difference before and after treatment and interquartile range [IQR]: -17 g/mL· min and 10 g/mL · min, respectively [P = .0001], for olaparib and -3 g/mL · min and 13 g/mL · min [P = .70] for iniparib) and in nodes (median difference and interquartile range [IQR] before and after treatment: -23 g/mL · min and 13 g/mL · min [P = .0001] for olaparib; -9 g/mL · min and 17 g/mL · min [P = .05] for iniparib). The effective dose was estimated at 6.9 mSv for a 370-MBq 18F-FTT dose in humans. In humans, the organs with the highest uptake on images were the spleen and pancreas. Among five subjects with measurable tumors, increased 18F-FTT uptake was seen in one subject with pancreatic adenocarcinoma and another with liver cancer. Conclusion The results suggest that 18F-FTT uptake reflects PARP expression and that its radiation dosimetry profile is compatible with those of agents currently in clinical use. © RSNA, 2016 Online supplemental material is available for this article.

Synthesis, [¹8F] radiolabeling, and evaluation of poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors for in vivo imaging of PARP-1 using positron emission tomography.

Imaging of poly (ADP-ribose) polymerase-1 (PARP-1) expression in vivo is a potentially powerful tool for developing PARP-1 inhibitors for drug discovery and patient care. We have synthesized several derivatives of benzimidazole carboxamide as PARP-1 inhibitors, which can be (18)F-labeled easily for positron emission tomographic (PET) imaging. Of the compounds synthesized, 12 had the highest inhibition potency for PARP-1 (IC50=6.3 nM). [(18)F]12 was synthesized under conventional conditions in high specific activity with 40-50% decay-corrected yield. MicroPET studies using [(18)F]12 in MDA-MB-436 tumor-bearing mice demonstrated accumulation of [(18)F]12 in the tumor that was blocked by olaparib, suggesting that the uptake of [(18)F]12 in the tumor is specific to PARP-1 expression.

Positron Emission Tomography Imaging of Tumor Proliferation and DNA Repair.

ABSTRACT: Positron emission tomography (PET) is an established tool for molecular imaging of cancers, and its role in diagnosis, staging, and phenotyping continues to evolve and expand rapidly. PET imaging of increased glucose utilization with 18F-fluorodeoxyglucose is now entrenched in clinical oncology practice for improving prognostication and treatment response assessment. Additional critical processes for cancer cell survival can also be imaged by PET, helping to inform individualized treatment selections for patients by improving our understanding of cell survival mechanisms and identifying relevant active mechanisms in each patient. The critical importance of quantifying cell proliferation and DNA repair pathways for prognosis and treatment selection is highlighted by the nearly ubiquitous use of the Ki-67 index, an established histological quantitative measure of cell proliferation, and BRCA mutation testing for treatment selection. This review focuses on PET advances in imaging and quantifying cell proliferation and poly(ADP-ribose)polymerase expression that can be used to complement cancer phenotyping approaches that will identify the most effective treatments for each individual patient.

Unmasking hidden Merkel cell carcinoma recurrences: Three illustrative cases of patients with rising viral oncoprotein antibody levels and challenge of requiring multi-modal imaging to detect clinical disease.

Merkel cell carcinoma (MCC) is a neuroendocrine skin cancer with a high risk of recurrence and metastasis. Regular surveillance through physical exams and imaging studies is crucial for the timely detection of recurrences. MCC patients who produce antibodies to the Merkel cell polyomavirus oncoprotein may benefit from antibody testing in addition to routine imaging surveillance for the early detection of disease recurrence. The clinically available Anti MERKel cell panel (AMERK) is a sensitive tumor marker for Merkel cell polyomavirus positive MCC. Although AMERK is highly sensitive, imaging remains necessary to confirm the location of disease recurrence. MCC exhibits characteristic imaging features, making appropriate imaging modalities, and interpretation important for detection. We present 3 representative patient cases that highlight effective utilization of the AMERK test in addition to imaging for the early detection of MCC recurrence. The rise in the AMERK titer may occur before the disease reaches detectable size on computed tomography scans. Positron emission tomography (PET)-CT can serve as an alternative modality for the early detection of disease. Even subtle abnormalities in 18F-FDG uptake may be significant if accompanied by an increased AMERK titer. Alternative imaging modalities, such as 68Ga-DOTATATE PET-CT and magnetic resonance imaging, can be useful in revealing clinically occult disease in MCC patients. In summary, the AMERK antibody test, alongside imaging, enhances sensitivity in detecting recurrence. By combining these strategies of blood test and imaging, healthcare professionals can identify early signs of MCC recurrence, leading to prompt interventions and improved patient outcomes.

Advancing Prostate Cancer Care: Treatment Approaches to Precision Medicine, Biomarker Innovations, and Equitable Access.

Genetic testing and molecular imaging have great promise in the accurate diagnosis and treatment of #prostate #cancer, but only if they can be developed and implemented to achieve equitable benefit for all men.

Prostate-specific membrane antigen-positron emission tomography (PSMA-PET) of prostate cancer: current and emerging applications.

Prostate-specific membrane antigen-positron emission tomography (PSMA-PET) is transforming the management of patients with prostate cancer. In appropriately selected patients, PSMA-PET offers superior sensitivity and specificity compared to conventional imaging (e.g., computed tomography and bone scintigraphy) as well as choline and fluciclovine PET, with the added benefit of consolidating bone and soft tissue evaluation into a single study. Despite being a newly available imaging tool, PSMA-PET has established indications, interpretation guidelines, and reporting criteria, which will be reviewed. The prostate cancer care team, from imaging specialists to those delivering treatment, should have knowledge of physiologic PSMA radiotracer uptake, patterns of disease spread, and the strengths and limitations of PSMA-PET. In this review, current and emerging applications of PSMA-PET, including appropriateness use criteria as well as image interpretation and pitfalls, will be provided with an emphasis on clinical implications.

Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy.

The integration of artificial intelligence (AI) and positron emission tomography (PET) imaging has the potential to become a powerful tool in drug discovery. This review aims to provide an overview of the current state of research and highlight the potential for this alliance to advance pharmaceutical innovation by accelerating the development and deployment of novel therapeutics. We previously performed a scoping review of three databases (Embase, MEDLINE, and CENTRAL), identifying 87 studies published between 2018 and 2022 relevant to medical imaging (e.g., CT, PET, MRI), immunotherapy, artificial intelligence, and radiomics. Herein, we reexamine the previously identified studies, performing a subgroup analysis on articles specifically utilizing AI and PET imaging for drug discovery purposes in immunotherapy-treated oncology patients. Of the 87 original studies identified, 15 met our updated search criteria. In these studies, radiomics features were primarily extracted from PET/CT images in combination (n = 9, 60.0%) rather than PET imaging alone (n = 6, 40.0%), and patient cohorts were mostly recruited retrospectively and from single institutions (n = 10, 66.7%). AI models were used primarily for prognostication (n = 6, 40.0%) or for assisting in tumor phenotyping (n = 4, 26.7%). About half of the studies stress-tested their models using validation sets (n = 4, 26.7%) or both validation sets and test sets (n = 4, 26.7%), while the remaining six studies (40.0%) either performed no validation at all or used less stringent methods such as cross-validation on the training set. Overall, the integration of AI and PET imaging represents a paradigm shift in drug discovery, offering new avenues for more efficient development of therapeutics. By leveraging AI algorithms and PET imaging analysis, researchers could gain deeper insights into disease mechanisms, identify new drug targets, or optimize treatment regimens. However, further research is needed to validate these findings and address challenges such as data standardization and algorithm robustness.

A deep learning anthropomorphic model observer for a detection task in PET.

BACKGROUND: Lesion detection is one of the most important clinical tasks in positron emission tomography (PET) for oncology. An anthropomorphic model observer (MO) designed to replicate human observers (HOs) in a detection task is an important tool for assessing task-based image quality. The channelized Hotelling observer (CHO) has been the most popular anthropomorphic MO. Recently, deep learning MOs (DLMOs), mostly based on convolutional neural networks (CNNs), have been investigated for various imaging modalities. However, there have been few studies on DLMOs for PET. PURPOSE: The goal of the study is to investigate whether DLMOs can predict HOs better than conventional MOs such as CHO in a two-alternative forced-choice (2AFC) detection task using PET images with real anatomical variability. METHODS: Two types of DLMOs were implemented: (1) CNN DLMO, and (2) CNN-SwinT DLMO that combines CNN and Swin Transformer (SwinT) encoders. Lesion-absent PET images were reconstructed from clinical data, and lesion-present images were reconstructed with adding simulated lesion sinogram data. Lesion-present and lesion-absent PET image pairs were labeled by eight HOs consisting of four radiologists and four image scientists in a 2AFC detection task. In total, 2268 pairs of lesion-present and lesion-absent images were used for training, 324 pairs for validation, and 324 pairs for test. CNN DLMO, CNN-SwinT DLMO, CHO with internal noise, and non-prewhitening matched filter (NPWMF) were compared in the same train-test paradigm. For comparison, six quantitative metrics including prediction accuracy, mean squared errors (MSEs) and correlation coefficients, which measure how well a MO predicts HOs, were calculated in a 9-fold cross-validation experiment. RESULTS: In terms of the accuracy and MSE metrics, CNN DLMO and CNN-SwinT DLMO showed better performance than CHO and NPWMF, and CNN-SwinT DLMO showed the best performance among the MOs evaluated. CONCLUSIONS: DLMO can predict HOs more accurately than conventional MOs such as CHO in PET lesion detection. Combining SwinT and CNN encoders can improve the DLMO prediction performance compared to using CNN only.

Genomic Correlates of Prostate-Specific Membrane Antigen Expression and Response to 177Lu-PSMA-617: A Retrospective Multicenter Cohort Study.

PURPOSE: While 177Lu-PSMA-617 (LuPSMA) is an effective therapy for many patients with metastatic castration-resistant prostate cancer (mCRPC), biomarkers associated with outcomes are not well defined. We hypothesized that prostate cancer mutational profile may associate with clinical activity of LuPSMA. We devised a study to evaluate associations between mCRPC mutational profile with LuPSMA clinical outcomes. METHODS: This was a multicenter retrospective analysis of patients with mCRPC with next-generation sequencing (NGS) who received LuPSMA. PSA50 response (ie, ≥50% decline in prostate-specific antigen [PSA]) rate, PSA progression free survival (PSA PFS), and overall survival (OS) were compared between genetically defined subgroups. RESULTS: One hundred twenty-six patients with NGS results who received at least one cycle of LuPSMA were identified. The median age was 73 (IQR, 68-78) years, 124 (98.4%) received ≥1 prior androgen receptor-signaling inhibitor, and 121 (96%) received ≥1 taxane-based chemotherapy regimen. Fifty-eight (46%) patients with a DNA damage repair gene mutation (DNA damage response group) and 59 (46.8%) with a mutation in TP53, RB1, or PTEN tumor suppressor genes (TSG group) were identified. After adjusting for relevant confounders, the presence of ≥1 TSG mutation was associated with shorter PSA PFS (hazard ratio [HR], 1.93 [95% CI, 1.05 to 3.54]; P = .034) and OS (HR, 2.65 [95% CI, 1.15 to 6.11]; P = .023). There was improved OS favoring the DNA damage response group (HR, 0.37 [95% CI, 0.14 to 0.97]; P = .044) on multivariable analysis. Univariate analysis of patients with ATM mutations had significantly higher rates of PSA50 response, PSA PFS, and OS. CONCLUSION: Outcomes on LuPSMA varied on the basis of mutational profile. Prospective studies to define the clinical activity of LuPSMA in predefined genomic subgroups are justified.