Immune Modulation Therapy and Imaging: Workshop Report

Phenomic Imaging

Human phenomics is defined as the comprehensive collection of observable phenotypes and characteristics influenced by a complex interplay among factors at multiple scales. These factors include genes, epigenetics at the microscopic level, organs, microbiome at the mesoscopic level, and diet and environmental exposures at the macroscopic level. "Phenomic imaging" utilizes various imaging techniques to visualize and measure anatomical structures, biological functions, metabolic processes, and biochemical activities across different scales, both in vivo and ex vivo. Unlike conventional medical imaging focused on disease diagnosis, phenomic imaging captures both normal and abnormal traits, facilitating detailed correlations between macro- and micro-phenotypes. This approach plays a crucial role in deciphering phenomes. This review provides an overview of different phenomic imaging modalities and their applications in human phenomics. Additionally, it explores the associations between phenomic imaging and other omics disciplines, including genomics, transcriptomics, proteomics, immunomics, and metabolomics. By integrating phenomic imaging with other omics data, such as genomics and metabolomics, a comprehensive understanding of biological systems can be achieved. This integration paves the way for the development of new therapeutic approaches and diagnostic tools.

The role of clinical imaging in oncology drug development: progress and new challenges

In 2008, the role of clinical imaging in oncology drug development was reviewed. The review outlined where imaging was being applied and considered the diverse demands across the phases of drug development. A limited set of imaging techniques was being used, largely based on structural measures of disease evaluated using established response criteria such as response evaluation criteria in solid tumours. Beyond structure, functional tissue imaging such as dynamic contrast-enhanced MRI and metabolic measures using [18F]flourodeoxyglucose positron emission tomography were being increasingly incorporated. Specific challenges related to the implementation of imaging were outlined including standardisation of scanning across study centres and consistency of analysis and reporting. More than a decade on the needs of modern drug development are reviewed, how imaging has evolved to support new drug development demands, the potential to translate state-of-the-art methods into routine tools and what is needed to enable the effective use of this broadening clinical trial toolset. In this review, we challenge the clinical and scientific imaging community to help refine existing clinical trial methods and innovate to deliver the next generation of techniques. Strong industry-academic partnerships and pre-competitive opportunities to co-ordinate efforts will ensure imaging technologies maintain a crucial role delivering innovative medicines to treat cancer.

Linear Peptide-Based PET Tracers for Imaging PD-L1 in Tumors

Programmed cell death receptor 1 (PD-1) and its ligand PD-L1 are particularly interesting immune checkpoint proteins for human cancer treatment. Positron emission tomography (PET) imaging allows for the dynamic monitoring of PD-L1 status during tumor progression, thus informing patients' response index. Herein, we report the synthesis of two linear peptide-based radiotracers, [64Cu]/[68Ga]HKP2201 and [64Cu]/[68Ga]HKP2202, and validate their utility for PD-L1 visualization in preclinical models. The precursor peptide HKP2201 was derived from a linear peptide ligand, CLP002, which was previously identified by phage display and showed nanomolar affinity toward PD-L1. Appropriate modification of CLP002 via PEGylation and DOTA conjugation yielded HKP2201. The dimerization of HKP2201 generated HKP2202. The 64Cu and 68Ga radiolabeling of both precursors was studied and optimized. PD-L1 expression in mouse melanoma cell line B16F10, mouse colon cancer cell line MC38, and their allografts were assayed by immunofluorescence and immunohistochemistry staining. Cellular uptake and binding assays were conducted in both cell lines. PET imaging and ex vivo biodistribution studies were employed in tumor mouse models bearing B16F10 and MC38 allografts. [64Cu]/[68Ga]HKP2201 and [64Cu]/[68Ga]HKP2202 were obtained with satisfactory radiocharacteristics. They all showed lower liver accumulation compared to [64Cu]/[68Ga]WL12. B16F10 and MC38 cells and their tumor allografts sections were verified to express PD-L1. These tracers demonstrated a concentration-dependent cell affinity and a comparable half-maximal effect concentration (EC50) with radiolabeled WL12. Competitive binding and blocking studies demonstrated the specific target of these tracers to PD-L1. PET imaging and ex vivo biodistribution studies revealed notable tumor uptake in tumor-bearing mice and rapid clearance from blood and major organs. Importantly, [64Cu]/[68Ga]HKP2202 showed higher tumor uptake compared to [64Cu]/[68Ga]HKP2201. Of note, [64Cu] labeled tracers showed longer retention in tumors than [68Ga] labeled traces, indicating advantages in the long-term tracking of PD-L1 dynamics. In comparison, [68Ga]HKP2201 and [68Ga]HKP2202 showed lower liver accumulation, enabling its great potential in the fast detection of both primary and metastatic tumors, including hepatic carcinoma. [64Cu]/[68Ga]HKP2201 and [64Cu]/[68Ga]HKP2202 are promising PET tracers for visualizing PD-L1 status. Notably, their combination would cooperate in rapid diagnosis and subsequent treatment guidance. Future assessment of the radiotracers in patients is needed to fully evaluate their clinical value.

F18-FDG PET/CT imaging early predicts pathologic complete response to induction chemoimmunotherapy of locally advanced head and neck cancer: preliminary single-center analysis of the checkrad-cd8 trial

Aim

In the CheckRad-CD8 trial patients with locally advanced head and neck squamous cell cancer are treated with a single cycle of induction chemo-immunotherapy (ICIT). Patients with pathological complete response (pCR) in the re-biopsy enter radioimmunotherapy. Our goal was to study the value of F-18-FDG PET/CT in the prediction of pCR after induction therapy.

Methods

Patients treated within the CheckRad-CD8 trial that additionally received FDG- PET/CT imaging at the following two time points were included: 3–14 days before (pre-ICIT) and 21–28 days after (post-ICIT) receiving ICIT. Tracer uptake in primary tumors (PT) and suspicious cervical lymph nodes (LN +) was measured using different quantitative parameters on EANM Research Ltd (EARL) accredited PET reconstructions. In addition, mean FDG uptake levels in lymphatic and hematopoietic organs were examined. Percent decrease (Δ) in FDG uptake was calculated for all parameters. Biopsy of the PT post-ICIT acquired after FDG-PET/CT served as reference. The cohort was divided in patients with pCR and residual tumor (ReTu).

Results

Thirty-one patients were included. In ROC analysis, ΔSUVmax PT performed best (AUC = 0.89) in predicting pCR (n = 17), with a decline of at least 60% (sensitivity, 0.77; specificity, 0.93). Residual SUVmax PT post-ICIT performed best in predicting ReTu (n = 14), at a cutpoint of 6.0 (AUC = 0.91; sensitivity, 0.86; specificity, 0.88). Combining two quantitative parameters (ΔSUVmax ≥ 50% and SUVmax PT post-ICIT ≤ 6.0) conferred a sensitivity of 0.81 and a specificity of 0.93 for determining pCR. Background activity in lymphatic organs or uptake in suspected cervical lymph node metastases lacked significant predictive value.

Conclusion

FDG-PET/CT can identify patients with pCR after ICIT via residual FDG uptake levels in primary tumors and the related changes compared to baseline. FDG-uptake in LN + had no predictive value.

Trial registry

ClinicalTrials.gov identifier: NCT03426657.

Intrahepatic cholangiocarcinoma: MRI texture signature as predictive biomarkers of immunophenotyping and survival

OBJECTIVE

Clinical evidence suggests that the response to immune checkpoint blockade depends on the immune status in the tumor microenvironment. This study aims to predict the immunophenotyping (IP) and overall survival (OS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative magnetic resonance imaging (MRI) texture analysis.

METHODS

A total of 78 ICC patients were included and divided into inflamed (n = 26) or non-inflamed (n = 52) immunophenotyping based on the density of CD8+ T cells. The enhanced T1-weighted MRI in the arterial phase was employed with texture analysis. The logistic regression analysis was applied to select the significant features related to IP. The OS-related feature was determined by Cox proportional-hazards model and Kaplan-Meier analysis. IP and OS predictive models were developed using the selected features, respectively.

RESULTS

Three wavelets and one 3D feature have favorable ability to discriminate IP, a combination of which performed best with an AUC of 0.919. The inflamed immunophenotyping had a better prognosis than the non-inflamed one. The 5-year survival rates of the two groups were 48.5% and 25.3%, respectively (p < 0.05). The only wavelet-HLH_firstorder_Median feature was associated with OS and used to build the OS predictive model with a C-index of 0.70 (95% CI, 0.57, 0.82), which could well stratify ICC patients into high- and low-risk groups. The 1-, 3-, and 5-year survival probabilities of the stratified groups were 62.5%, 30.0%, and 24.2%, and 89.5%, 62.2%, and 42.1%, respectively (p < 0.05).

CONCLUSION

The MRI texture signature could serve as a potential predictive biomarker for the IP and OS of ICC patients.

KEY POINTS

• The MRI texture signature, including three wavelets and one 3D feature, showed significant associations with immunophenotyping of ICC, and all have favorable ability to discriminate immunophenotyping; a combination of the above features performed best with an AUC of 0.919. • The only wavelet-HLH_firstorder_Median feature was associated with the OS of ICC and used to build the OS predictive model, which could well stratify ICC patients into high- and low-risk groups.

Nomogram development and validation to predict hepatocellular carcinoma tumor behavior by preoperative gadoxetic acid-enhanced MRI

OBJECTIVES

Pretreatment evaluation of tumor biology and microenvironment is important to predict prognosis and plan treatment. We aimed to develop nomograms based on gadoxetic acid-enhanced MRI to predict microvascular invasion (MVI), tumor differentiation, and immunoscore.

METHODS

This retrospective study included 273 patients with HCC who underwent preoperative gadoxetic acid-enhanced MRI. Patients were assigned to two groups: training (N = 191) and validation (N = 82). Univariable and multivariable logistic regression analyses were performed to investigate clinical variables and MRI features' associations with MVI, tumor differentiation, and immunoscore. Nomograms were developed based on features associated with these three histopathological features in the training cohort, then validated, and evaluated.

RESULTS

Predictors of MVI included tumor size, rim enhancement, capsule, percent decrease in T1 images (T1_D%), standard deviation of apparent diffusion coefficient, and alanine aminotransferase levels, while capsule, peritumoral enhancement, mean relaxation time on the hepatobiliary phase (T1_E), and alpha-fetoprotein levels predicted tumor differentiation. Predictors of immunoscore included the radiologic score constructed by tumor number, intratumoral vessel, margin, capsule, rim enhancement, T1_D%, relaxation time on plain scan (T1_P), and alpha-fetoprotein and alanine aminotransferase levels. Three nomograms achieved good concordance indexes in predicting MVI (0.754, 0.746), tumor differentiation (0.758, 0.699), and immunoscore (0.737, 0.726) in the training and validation cohorts, respectively.

CONCLUSION

MRI-based nomograms effectively predict tumor behaviors in HCC and may assist clinicians in prognosis prediction and pretreatment decisions.

KEY POINTS

• This study developed and validated three nomograms based on gadoxetic acid-enhanced MRI to predict MVI, tumor differentiation, and immunoscore in patients with HCC. • The pretreatment prediction of tumor microenvironment may be useful to guide accurate prognosis and planning of surgical and immunological therapies for individual patients with HCC.

Monitoring von Immuntherapien

Hintergrund

Immuntherapien spielen in der Behandlung fortgeschrittener onkologischer Erkrankungen eine zunehmende Rolle. Bei einigen Patienten birgt die radiologische Diagnostik durch atypische, immuntherapieinduziete Therapieverläufe neue Herausforderungen.

Ziel der Arbeit

Dieser Beitrag soll einen Überblick über die bildgebenden Methoden des Monitorings von Immuntherapien geben, die assoziierten Phänomene Pseudoprogress und Hyperprogress erörtern sowie die Evaluationskriterien iRECIST vorstellen, welche sich als Evaluationsstandard für klinische Studien anbieten. Zusätzlich werden die radiologisch wichtigsten Nebenwirkungen und ihre bildmorphologischen Charakteristika beschrieben.

Material und Methoden

Für diesen Übersichtsartikel wurden Studienergebnisse und Reviews seit 2009 ausgewertet. Die Literaturrecherche erfolgte mittels PubMed, die Suchbegriffe enthielten „immunotherapy“, „checkpoint inhibitor“, „pseudoprogression“, „iRECIST“ und „immune related adverse events“.

Ergebnisse und Diskussion

Mit einer Inzidenz von bis zu 10 % ist der Pseudoprogress insgesamt selten; aktuell ist die Differenzierung von einem echten Progress nur durch eine Beobachtung des zeitlichen Verlaufs möglich. Die 2017 erschienenen iRECIST-Kriterien enthalten daher die neuen Kategorien unbestätigter (immune unconfirmed progressive disease iUPD) und bestätigter Progress (immune confirmed progressive disease iCPD). Bisher konnte keine evidenzbasierte Empfehlung bezüglich des Zeitintervalls zwischen den Untersuchungen gegeben werden. Als radiologisch wichtigste Nebenwirkungen sind die Hypophysitis und die Pneumonitis zu nennen. Letztere kann sich in verschiedenen Mustern der interstitiellen Pneumonie präsentieren. Die Differenzierung zwischen Pneumonitis, Infektion und Tumorprogress kann diagnostische Schwierigkeiten mit sich bringen.

Top 10 Challenges in Cancer Immunotherapy

Cancer immunotherapy is a validated and critically important approach for treating patients with cancer. Given the vast research and clinical investigation efforts dedicated to advancing both endogenous and synthetic immunotherapy approaches, there is a need to focus on crucial questions and define roadblocks to the basic understanding and clinical progress. Here, we define ten key challenges facing cancer immunotherapy, which range from lack of confidence in translating pre-clinical findings to identifying optimal combinations of immune-based therapies for any given patient. Addressing these challenges will require the combined efforts of basic researchers and clinicians, and the focusing of resources to accelerate understanding of the complex interactions between cancer and the immune system and the development of improved treatment options for patients with cancer.

18FDG PET/CT in the early assessment of non-small cell lung cancer response to immunotherapy: frequency and clinical significance of atypical evolutive patterns

PURPOSE

This prospective study aimed (1) to assess the non-small cell lung cancer (NSCLC) evolutive patterns to immunotherapy using FDG-PET and (2) to describe their association with clinical outcome.

DESIGN

Fifty patients with metastatic NSCLC were included before pembrolizumab or nivolumab initiation. FDG-PET scan was performed at baseline and after 7 weeks of treatment (PET_interim1) and different criteria/parameters of tumor response were assessed, including PET response criteria in solid tumors (PERCIST). If a first PERCIST progressive disease (PD) without clinical worsening was observed, treatment was continued and a subsequent FDG-PET (PET_interim2) was performed at 3 months of treatment. Pseudo-progression (PsPD) was defined as a PERCIST response/stability on PET_interim2 after an initial PD. If a second PERCIST PD was assessed on PET_interim2, a homogeneous progression of lesions (termed immune homogeneous progressive-disease: iPD_homogeneous) was distinguished from a heterogeneous evolution (termed immune dissociated-response: iDR). A durable clinical benefit (DCB) of immunotherapy was defined as treatment continuation over a 6-month period. The association between PET evolutive profiles and DCB was assessed.

RESULTS

Using PERCIST on PET_interim1, 42% (21/50) of patients showed a response or stable disease, most of them (18/21) reached a DCB. In contrast, 58% (29/50) showed a PD, but more than one-third (11/29) were misclassified as they finally reached a DCB. No standard PET_interim1 criteria could accurately distinguished responding from non-responding patients. Treatment was continued in 19/29 of patients with a first PERCIST PD; the subsequent PET_interim2 demonstrated iPD_homogeneous, iDR and PsPD in 42% (8/19), 26% (5/19), and 32% (6/19), respectively. Whereas no patients with iPD_homogeneous experienced a DCB, all patients with iDR and PsPD reached a clinical benefit to immunotherapy.

CONCLUSION

In patients with a first PD on PERCIST and treatment continuation, a subsequent PET identifies more than half of them with iDR and PsPD, both patterns being strongly associated with a clinical benefit of immunotherapy.

Role of medical imaging for immune checkpoint blockade therapy: From response assessment to prognosis prediction

Immune checkpoint blockade (ICB) represents a promising approach in cancer therapy. Owing to the peculiar biologic mechanisms of anticancer activity, checkpoint blockers are accompanied with distinctive response patterns and toxicity profiles. Medical imaging is the cornerstone for response assessment to immunotherapy and plays a critical role in monitoring of immune-related adverse events (irAEs). Imaging-based biomarkers have shown tremendous potential for the prediction of therapeutic efficacies and clinical outcomes in patients treated with checkpoint inhibitors. In this article, the landscape of current response assessment systems for immunotherapy was reviewed with a special focus on the latest advances in the assessment of responses to ICB. Emerging imaging biomarkers were discussed along with the challenges regarding their clinical transformation. In addition, the biological mechanisms and clinical applications of ICB and irAEs were also within the scope of this review.

Current and Future Imaging Methods for Evaluating Response to Immunotherapy in Neuro-Oncology

Imaging plays a central role in evaluating responses to therapy in neuro-oncology patients. The advancing clinical use of immunotherapies has demonstrated that treatment-related inflammatory responses mimic tumor growth via conventional imaging, thus spurring the development of new imaging approaches to adequately distinguish between pseudoprogression and progressive disease. To this end, an increasing number of advanced imaging techniques are being evaluated in preclinical and clinical studies. These novel molecular imaging approaches will serve to complement conventional response assessments during immunotherapy. The goal of these techniques is to provide definitive metrics of tumor response at earlier time points to inform treatment decisions, which has the potential to improve patient outcomes. This review summarizes the available immunotherapy regimens, clinical response criteria, current state-of-the-art imaging approaches, and groundbreaking strategies for future implementation to evaluate the anti-tumor and immune responses to immunotherapy in neuro-oncology applications.

The beginning of the end for conventional RECIST - novel therapies require novel imaging approaches

Owing to improvements in our understanding of the biological principles of tumour initiation and progression, a wide variety of novel targeted therapies have been developed. Developments in biomedical imaging, however, have not kept pace with these improvements and are still mainly designed to determine lesion size alone, which is reflected in the Response Evaluation Criteria in Solid Tumors (RECIST). Imaging approaches currently used for the evaluation of treatment responses in patients with solid tumours, therefore, often fail to detect successful responses to novel targeted agents and might even falsely suggest disease progression, a scenario known as pseudoprogression. The ability to differentiate between responders and nonresponders early in the course of treatment is essential to allowing the early adjustment of treatment regimens. Various imaging approaches targeting a single dedicated tumour feature, as described in the hallmarks of cancer, have been successful in preclinical investigations, and some have been evaluated in pilot clinical trials. However, these approaches have largely not been implemented in clinical practice. In this Review, we describe current biomedical imaging approaches used to monitor responses to treatment in patients receiving novel targeted therapies, including a summary of the most promising future approaches and how these might improve clinical practice.

Tumor Drug Penetration Measurements Could Be the Neglected Piece of the Personalized Cancer Treatment Puzzle

Precision medicine aims to use patient genomic, epigenomic, specific drug dose, and other data to define disease patterns that may potentially lead to an improved treatment outcome. Personalized dosing regimens based on tumor drug penetration can play a critical role in this approach. State-of-the-art techniques to measure tumor drug penetration focus on systemic exposure, tissue penetration, cellular or molecular engagement, and expression of pharmacological activity. Using in silico methods, this information can be integrated to bridge the gap between the therapeutic regimen and the pharmacological link with clinical outcome. These methodologies are described, and challenges ahead are discussed. Supported by many examples, this review shows how the combination of these techniques provides enhanced patient-specific information on drug accessibility at the tumor tissue level, target binding, and downstream pharmacology. Our vision of how to apply tumor drug penetration measurements offers a roadmap for the clinical implementation of precision dosing.

Imaging of Activated T Cells as an Early Predictor of Immune Response to Anti-PD-1 Therapy

Compelling evidence points to immune cell infiltration as a critical component of successful immunotherapy. However, there are currently no clinically available, noninvasive methods capable of evaluating immune contexture prior to or during immunotherapy. In this study, we evaluate a T-cell-specific PET agent, [18F]F-AraG, as an imaging biomarker predictive of response to checkpoint inhibitor therapy. We determined the specificity of the tracer for activated T cells in vitro and in a virally induced model of rhabdomyosarcoma. Of all immune cells tested, activated human CD8⁺ effector cells showed the highest accumulation of [18F]F-AraG. Isolation of lymphocytes from the rhabdomyosarcoma tumors showed that more than 80% of the intratumoral signal came from accumulation of [18F]F-AraG in immune cells, primarily CD8⁺ and CD4⁺. Longitudinal monitoring of MC38 tumor-bearing mice undergoing anti-PD-1 treatment revealed differences in signal between PD-1 and isotype antibody-treated mice early into treatment. The differences in [18F]F-AraG signal were also apparent between responders and nonresponders to anti-PD-1 therapy. Importantly, we found that the signal in the tumor-draining lymph nodes provides key information about response to anti-PD-1 therapy. Overall, [18F]F-AraG has potential to serve as a much needed immunomonitoring clinical tool for timely evaluation of immunotherapy. SIGNIFICANCE: These findings reveal differences in T-cell activation between responders and nonresponders early into anti-PD-1 treatment, which may impact many facets of immuno-oncology, including patient selection, management, and development of novel combinatorial approaches.

Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging

OBJECTIVES

Immunoscore evaluates the density of CD3+ and CD8+ T cells in both the tumor core and invasive margin. Pretreatment prediction of immunoscore in hepatocellular cancer (HCC) is important for precision immunotherapy. We aimed to develop a radiomics model based on gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced MRI for pretreatment prediction of immunoscore (0-2 vs. 3-4) in HCC.

MATERIALS AND METHODS

The study included 207 (training cohort: n = 150; validation cohort: n = 57) HCC patients with hepatectomy who underwent preoperative Gd-EOB-DTPA-enhanced MRI. The volumes of interest enclosing hepatic lesions including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase of MRI images, from which 1044 quantitative features were extracted and analyzed. Extremely randomized tree method was used to select radiomics features for building radiomics model. Predicting performance in immunoscore was compared among three models: (1) using only intratumoral radiomics features (intratumoral radiomics model); (2) using combined intratumoral and peritumoral radiomics features (combined radiomics model); (3) using clinical data and selected combined radiomics features (combined radiomics-based clinical model).

RESULTS

The combined radiomics model showed a better predicting performance in immunoscore than intratumoral radiomics model (AUC, 0.904 (95% CI 0.855-0.953) vs. 0.823 (95% CI 0.747-0.899)). The combined radiomics-based clinical model showed an improvement over the combined radiomics model in predicting immunoscore (AUC, 0·926 (95% CI 0·884-0·967) vs. 0·904 (95% CI 0·855-0·953)), although differences were not statistically significant. Results were confirmed in validation cohort and calibration curves showed good agreement.

CONCLUSION

The MRI-based combined radiomics nomogram is effective in predicting immunoscore in HCC and may help making treatment decisions.

KEY POINTS

• Radiomics obtained from Gd-EOB-DTPA-enhanced MRI help predicting immunoscore in hepatocellular carcinoma. • Combined intratumoral and peritumoral radiomics are superior to intratumoral radiomics only in predicting immunoscore. • We developed a combined clinical and radiomicsnomogram to predict immunoscore in hepatocellular carcinoma.

Management guidelines for paediatric patients receiving chimeric antigen receptor T cell therapy

In 2017, an autologous chimeric antigen receptor (CAR) T cell therapy indicated for children and young adults with relapsed and/or refractory CD19+ acute lymphoblastic leukaemia became the first gene therapy to be approved in the USA. This innovative form of cellular immunotherapy has been associated with remarkable response rates but is also associated with unique and often severe toxicities, which can lead to rapid cardiorespiratory and/or neurological deterioration. Multidisciplinary medical vigilance and the requisite health-care infrastructure are imperative to ensuring optimal patient outcomes, especially as these therapies transition from research protocols to standard care. Herein, authors representing the Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network Hematopoietic Stem Cell Transplantation (HSCT) Subgroup and the MD Anderson Cancer Center CAR T Cell Therapy-Associated Toxicity (CARTOX) Program have collaborated to provide comprehensive consensus guidelines on the care of children receiving CAR T cell therapy.

Role of noninvasive molecular imaging in determining response

The intersection of immunotherapy and radiation oncology is a rapidly evolving area of preclinical and clinical investigation. The strategy of combining radiation and immunotherapy to enhance local and systemic antitumor immune responses is intriguing yet largely unproven in the clinical setting because the mechanisms of synergy and the determinants of therapeutic response remain undefined. In recent years, several noninvasive molecular imaging approaches have emerged as a platform to interrogate the tumor immune microenvironment. These tools have the potential to serve as robust biomarkers for cancer immunotherapy and may hold several advantages over conventional anatomic imaging modalities and contemporary invasive tissue acquisition techniques. Given the key and expanding role of precision imaging in radiation oncology for patient selection, target delineation, image guided treatment delivery, and response assessment, noninvasive molecular-specific imaging may be uniquely suited to evaluate radiation/immunotherapy combinations. Herein, we describe several experimental imaging-based strategies that are currently being explored to characterize in vivo immune responses, and we review a growing body of preclinical data and nascent clinical experience with immuno-positron emission tomography molecular imaging as a putative biomarker for cancer immunotherapy. Finally, we discuss practical considerations for clinical translation to implement noninvasive molecular imaging of immune checkpoint molecules, immune cells, or associated elements of the antitumor immune response with a specific emphasis on its potential application at the interface of radiation oncology and immuno-oncology.