MRI of tumor T cell infiltration in response to checkpoint inhibitor therapy

Prediction of pathological complete response in locally advanced head and neck squamous cell carcinoma treated with neoadjuvant chemo-immunotherapy using volumetric multisequence MRI histogram analysis

PURPOSE

This study aimed to develop a multisequence MRI-based volumetric histogram metrics model for predicting pathological complete response (pCR) in advanced head and neck squamous cell carcinoma (HNSCC) patients undergoing neoadjuvant chemo-immunotherapy (NCIT) and compare its predictive performance with AJCC staging and RECIST 1.1 criteria.

METHODS

Twenty-four patients with locally advanced HNSCC from a prospective phase II trial were enrolled for analysis. All patients underwent pre- and post-NCIT MRI examinations from which whole-tumor histogram features were extracted, including T1WI, T2WI, enhanced T1WI (T1Gd), diffusion-weighted imaging (DWI) sequences, and their corresponding apparent diffusion coefficient (ADC) maps. The pathological results divided the patients into pathological complete response (pCR) and non-pCR (N-pCR) groups. Delta features were calculated as the percentage change in histogram features from pre- to post-treatment. After data reduction and feature selection, logistic regression was used to build prediction models. ROC analysis was performed to assess the diagnostic performance.

RESULTS

Eleven of 24 patients achieved pCR. Pre_T2_original_firstorder_Minimum, Post_ADC_original_firstorder_MeanAbsoluteDeviation, and Delta_T1Gd_original_firstorder_Skewness were associated with achieving pCR after NCIT. The Combined_Model demonstrated the best predictive performance (AUC 0.95), outperforming AJCC staging (AUC 0.52) and RECIST 1.1 (AUC 0.72). The Pre_Model (AUC 0.83) or Post-Model (AUC 0.83) had a better predictive ability than AJCC staging.

CONCLUSION

Multisequence MRI-based volumetric histogram analysis can non-invasively predict the pCR status of HNSCC patients undergoing NCIT. The use of histogram features extracted from pre- and post-treatment MRI exhibits promising predictive performance and offers a novel quantitative assessment method for evaluating pCR in HNSCC patients receiving NCIT.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion

Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T-cell activation by antigen-presenting beads and their subsequent expansion is formulated in silico. The simulation is used as an environment to train RL-agents to dynamically control the number of beads in culture to maximize the population of robust effector cells at the end of the culture. We make periodic decisions of incremental bead addition or complete removal. The simulation is designed to operate in OpenAI Gym, enabling testing of different environments, cell types, RL-agent algorithms, and state inputs to the RL-agent. RL-agent training is demonstrated with three different algorithms (PPO, A2C, and DQN), each sampling three different state input types (tabular, image, mixed); PPO-tabular performs best for this simulation environment. Using this approach, training of the RL-agent on different cell types is demonstrated, resulting in unique control strategies for each type. Sensitivity to input-noise (sensor performance), number of control step interventions, and advantages of pre-trained RL-agents are also evaluated. Therefore, we present an RL framework to maximize the population of robust effector cells in CAR T-cell therapy production.

Detection of Treatment Response in Triple-Negative Breast Tumors to Paclitaxel Using MRI Cell Size Imaging

BACKGROUND

Breast cancer treatment response evaluation using the response evaluation criteria in solid tumors (RECIST) guidelines, based on tumor volume changes, has limitations, prompting interest in novel imaging markers for accurate therapeutic effect determination.

PURPOSE

To use MRI-measured cell size as a new imaging biomarker for assessing chemotherapy response in breast cancer.

STUDY TYPE

Longitudinal; animal model.

STUDY POPULATION

Triple-negative human breast cancer cell (MDA-MB-231) pellets (4 groups, n = 7) treated with dimethyl sulfoxide (DMSO) or 10 nM of paclitaxel for 24, 48, and 96 hours, and 29 mice with MDA-MB-231 tumors in right hind limbs treated with paclitaxel (n = 16) or DMSO (n = 13) twice weekly for 3 weeks.

FIELD STRENGTH/SEQUENCE

Oscillating gradient spin echo and pulsed gradient spin echo sequences at 4.7 T.

ASSESSMENT

MDA-MB-231 cells were analyzed using flowcytometry and light microscopy to assess cell cycle phases and cell size distribution. MDA-MB-231 cell pellets were MR imaged. Mice were imaged weekly, with 9, 6, and 14 being sacrificed for histology after MRI at weeks 1, 2, and 3, respectively. Microstructural parameters of tumors/cell pellets were derived by fitting diffusion MRI data to a biophysical model.

STATISTICAL TESTS

One-way ANOVA compared cell sizes and MR-derived parameters between treated and control samples. Repeated measures 2-way ANOVA with Bonferroni post-tests compared temporal changes in MR-derived parameters. A P-value <0.05 was considered statistically significant.

RESULTS

In vitro experiments showed that the mean MR-derived cell sizes of paclitaxel-treated cells increased significantly with a 24-hours treatment and decreased (P = 0.06) with a 96-hour treatment. For in vivo xenograft experiments, the paclitaxel-treated tumors showed significant decreases in cell size at later weeks. MRI observations were supported by flowcytometry, light microscopy, and histology.

DATA CONCLUSIONS

MR-derived cell size may characterize the cell shrinkage during treatment-induced apoptosis, and may potentially provide new insights into the assessment of therapeutic response.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 4.

H-Scan Discrimination for Tumor Microenvironmental Heterogeneity in Melanoma

OBJECTIVE

Melanoma is a form of malignant skin cancer that exhibits significant inter-tumoral differences in the tumor microenvironment (TME) secondary to genetic mutations. The heterogeneity may be subtle but can complicate the treatment of metastatic melanoma, contributing to a high mortality rate. Therefore, developing an accurate and non-invasive procedure to discriminate microenvironmental heterogeneity to facilitate therapy selection is an important goal.

METHODS

In vivo murine melanoma models that recapitulate human disease using synchronous implanted YUMM 1.7 (Yale University Mouse Melanoma) and YUMMER 1.7 (Yale University Mouse Melanoma Exposed to Radiation) murine melanoma lines were investigated. Mice were treated with antibodies to modulate the immune response and longitudinally scanned with ultrasound (US). US radiofrequency data were processed using the H-scan analysis, attenuation estimation and B-mode processing to extract five US features. The measures were used to compare different TMEs (YUMMER vs. YUMM) and responses to immunomodulatory therapies with CD8 depletion or programmed cell death protein 1 (PD-1) inhibition.

RESULTS

Multiparametric analysis produced a combined H-scan parameter, resolving significant differences (i) between untreated YUMMER and YUMM and (ii) between untreated, PD-1-treated and CD8-treated YUMMER. However, more importantly, the B-mode and attenuation measures failed to differentiate YUMMER and YUMM and to monitor treatment responses, indicating that H-scan is required to differentiate subtle differences within the TME.

CONCLUSION

We anticipate that the H-scan analysis could discriminate heterogeneous melanoma metastases and guide diagnosis and treatment selection, potentially reducing the need for invasive biopsies or immunologic procedures.

Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology

Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed. The objective of this article is to review the state-of-the-art of DW-MRI in body imaging (ie, not including the nervous system) in oncology, and to analyze its value as compared to reference colocalized histology measurements, given that demonstrating the histological validity of any new DW-MRI method is essential. In this article, we review the current landscape of DW-MRI techniques that extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, signal models, fitting settings, microstructural parameters, and relationship with histology. Preclinical, clinical, and in/ex vivo studies were included. The most used techniques were intravoxel incoherent motion (IVIM; 36.3% of used techniques), diffusion kurtosis imaging (DKI; 16.7%), vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT; 13.3%), and imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED; 11.7%). Another notable category of techniques relates to innovative b-tensor diffusion encoding or joint diffusion-relaxometry. The reviewed approaches provide histologically meaningful indices of cancer microstructure (eg, vascularization/cellularity) which, while not necessarily accurate numerically, may still provide useful sensitivity to microscopic pathological processes. Future work of the community should focus on improving the inter-/intra-scanner robustness, and on assessing histological validity in broader contexts. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 2.

Immune checkpoint inhibitor treatment of brain metastasis associated with a less invasive growth pattern, higher T-cell infiltration and raised tumor ADC on diffusion weighted MRI

BACKGROUND

Brain metastases are the most common intracranial tumors with an increasing incidence. They are an important cause of morbidity and mortality in patients with solid organ cancer and a focus of recent clinical research and experimental interest. Immune checkpoint inhibitors are being increasingly used to treat solid organ cancers.

METHODS

To determine whether immune checkpoint inhibitors were biologically effective in the brain, we compared melanoma brain metastasis samples where treatment with ipilimumab had occurred preoperatively to those who had not received any immune modulating therapy and looked for histopathological (invasion, vascularity, metastasis inducing proteins, matrix metalloproteinases, immune cell infiltration, tissue architecture) and advanced MRI differences (diffusion weighted imaging).

RESULTS

Co-localized tissue samples from the same regions as MRI regions of interest showed significantly lower vascularity (density of CD34 + vessels) in the core and higher T-cell infiltration (CD3 + cells) in the leading edge for ipilimumab-treated brain metastasis samples than for untreated cases and this correlated with a higher tumor ADC signal at post-treatment/preoperative MRI brain.

CONCLUSIONS

Treatment of a melanoma brain metastasis with ipilimumab appears to cause measurable biological changes in the tumor that can be correlated with post-treatment diffusion weighted MRI imaging, suggesting both a mechanism of action and a possible surrogate marker of efficacy.

The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging

In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.

Associations of Multiparametric Breast MRI Features, Tumor-Infiltrating Lymphocytes, and Immune Gene Signature Scores Following a Single Dose of Trastuzumab in HER2-Positive Early-Stage Breast Cancer

Dynamic biomarkers that permit the real-time monitoring of the tumor microenvironment response to therapy are an unmet need in breast cancer. Breast magnetic resonance imaging (MRI) has demonstrated value as a predictor of pathologic complete response and may reflect immune cell changes in the tumor microenvironment. The purpose of this pilot study was to investigate the value of breast MRI features as early markers of treatment-induced immune response. Fourteen patients with early HER2+ breast cancer were enrolled in a window-of-opportunity study where a single dose of trastuzumab was administered and both tissue and MRIs were obtained at the pre- and post-treatment stages. Functional diffusion-weighted and dynamic contrast-enhanced MRI tumor measures were compared with tumor-infiltrating lymphocytes (TILs) and RNA immune signature scores. Both the pre-treatment apparent diffusion coefficient (ADC) and the change in peak percent enhancement (DPE) were associated with increased tumor-infiltrating lymphocytes with trastuzumab therapy (r = -0.67 and -0.69, p < 0.01 and p < 0.01, respectively). Low pre-treatment ADC and a greater decrease in PE in response to treatment were also associated with immune-activated tumor microenvironments as defined by RNA immune signatures. Breast MRI features hold promise as biomarkers of early immune response to treatment in HER2+ breast cancer.

Diffusion time dependency of extracellular diffusion

PURPOSE

To quantify the variations of the power-law dependences on diffusion time t or gradient frequencyf $$ f $$ of extracellular water diffusion measured by diffusion MRI (dMRI).

METHODS

Model cellular systems containing only extracellular water were used to investigate thet / f $$ t/f $$ dependence ofD ex $$ {D}_{ex} $$ , the extracellular diffusion coefficient. Computer simulations used a randomly packed tissue model with realistic intracellular volume fractions and cell sizes. DMRI measurements were performed on samples consisting of liposomes containing heavy water(D2 O, deuterium oxide) dispersed in regular water (H2 O).D ex $$ {D}_{ex} $$ was obtained over a broadt $$ t $$ range (∼1-1000 ms) and then fit power-law equationsD ex ( t ) = D const + const · t - ϑ t $$ {D}_{ex}(t)={D}_{\mathrm{const}}+\mathrm{const}\cdotp {t}^{-{\vartheta}_t} $$ andD ex ( f ) = D const + const · f ϑ f $$ {D}_{ex}(f)={D}_{\mathrm{const}}+\mathrm{const}\cdotp {f}^{\vartheta_f} $$ .

RESULTS

Both simulated and experimental results suggest that no single power-law adequately describes the behavior ofD ex $$ {D}_{ex} $$ over the range of diffusion times of most interest in practical dMRI. Previous theoretical predictions are accurate over only limitedt $$ t $$ ranges; for example,θ t = θ f = - 1 2 $$ {\theta}_t={\theta}_f=-\frac{1}{2} $$ is valid only for short times, whereasθ t = 1 $$ {\theta}_t=1 $$ orθ f = 3 2 $$ {\theta}_f=\frac{3}{2} $$ is valid only for long times but cannot describe other ranges simultaneously. For the specifict $$ t $$ range of 5-70 ms used in typical human dMRI measurements,θ t = θ f = 1 $$ {\theta}_t={\theta}_f=1 $$ matches the data well empirically.

CONCLUSION

The optimal power-law fit of extracellular diffusion varies with diffusion time. The dependency obtained at short or longt $$ t $$ limits cannot be applied to typical dMRI measurements in human cancer or liver. It is essential to determine the appropriate diffusion time range when modeling extracellular diffusion in dMRI-based quantitative microstructural imaging.

Profiling specific cell populations within the inflammatory tumor microenvironment by oscillating-gradient diffusion-weighted MRI

BACKGROUND

The inflammatory tumor microenvironment (TME) is formed by various immune cells, being closely associated with tumorigenesis. Especially, the interaction between tumor-infiltrating T-cells and macrophages has a crucial impact on tumor progression and metastatic spread. The purpose of this study was to investigate whether oscillating-gradient diffusion-weighted MRI (OGSE-DWI) enables a cell size-based discrimination between different cell populations of the TME.

METHODS

Sine-shaped OGSE-DWI was combined with the Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED) approach to measure microscale diffusion distances, here relating to cell sizes. The accuracy of IMPULSED-derived cell radii was evaluated using in vitro spheroid models, consisting of either pure cancer cells, macrophages, or T-cells. Subsequently, in vivo experiments aimed to assess changes within the TME and its specific immune cell composition in syngeneic murine breast cancer models with divergent degrees of malignancy (4T1, 67NR) during tumor progression, clodronate liposome-mediated depletion of macrophages, and immune checkpoint inhibitor (ICI) treatment. Ex vivo analysis of IMPULSED-derived cell radii was conducted by immunohistochemical wheat germ agglutinin staining of cell membranes, while intratumoral immune cell composition was analyzed by CD3 and F4/80 co-staining.

RESULTS

OGSE-DWI detected mean cell radii of 8.8±1.3 µm for 4T1, 8.2±1.4 µm for 67NR, 13.0±1.7 for macrophage, and 3.8±1.8 µm for T-cell spheroids. While T-cell infiltration during progression of 4T1 tumors was observed by decreasing mean cell radii from 9.7±1.0 to 5.0±1.5 µm, increasing amount of intratumoral macrophages during progression of 67NR tumors resulted in increasing mean cell radii from 8.9±1.2 to 12.5±1.1 µm. After macrophage depletion, mean cell radii decreased from 6.3±1.7 to 4.4±0.5 µm. T-cell infiltration after ICI treatment was captured by decreasing mean cell radii in both tumor models, with more pronounced effects in the 67NR tumor model.

CONCLUSIONS

OGSE-DWI provides a versatile tool for non-invasive profiling of the inflammatory TME by assessing the dominating cell type T-cells or macrophages.

Treatment with a Cholecystokinin Receptor Antagonist, Proglumide, Improves Efficacy of Immune Checkpoint Antibodies in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-associated deaths worldwide. Treatment with immune checkpoint antibodies has shown promise in advanced HCC, but the response is only 15-20%. We discovered a potential target for the treatment of HCC, the cholecystokinin-B receptor (CCK-BR). This receptor is overexpressed in murine and human HCC and not in normal liver tissue. Mice bearing syngeneic RIL-175 HCC tumors were treated with phosphate buffer saline (PBS; control), proglumide (a CCK-receptor antagonist), an antibody to programmed cell death protein 1 (PD-1Ab), or the combination of proglumide and the PD-1Ab. In vitro, RNA was extracted from untreated or proglumide-treated murine Dt81Hepa1-6 HCC cells and analyzed for expression of fibrosis-associated genes. RNA was also extracted from human HepG2 HCC cells or HepG2 cells treated with proglumide and subjected to RNA sequencing. Results showed that proglumide decreased fibrosis in the tumor microenvironment and increased the number of intratumoral CD8+ T cells in RIL-175 tumors. When proglumide was given in combination with the PD-1Ab, there was a further significant increase in intratumoral CD8+ T cells, improved survival, and alterations in genes regulating tumoral fibrosis and epithelial-to-mesenchymal transition. RNAseq results from human HepG2 HCC cells treated with proglumide showed significant changes in differentially expressed genes involved in tumorigenesis, fibrosis, and the tumor microenvironment. The use of the CCK receptor antagonist may improve efficacy of immune checkpoint antibodies and survival in those with advanced HCC.

Mannosylated-serum albumin nanoparticle imaging to monitor tumor-associated macrophages under anti-PD1 treatment

BACKGROUND

Immune checkpoint inhibitors such as anti-programmed cell death protein 1 (PD1) block tumor growth by reinvigorating the immune system; however, determining their efficacy only by the changes in tumor size may prove inaccurate. As the immune cells including macrophages in the tumor microenvironment (TME) are associated with the response to anti-PD1 therapy, tumor-associated macrophages (TAMs) imaging using nanoparticles can noninvasively provide the immune enrichment status of TME. Herein, the mannosylated-serum albumin (MSA) nanoparticle was labeled with radioactive isotope ⁶⁸Ga to target the mannose receptors on macrophages for noninvasive monitoring of the TME according to anti-PD1 therapy.

RESULTS

B16F10-Luc and MC38-Luc tumor-bearing mice were treated with anti-PD1, and the response to anti-PD1 was determined by the tumor volume. According to the flow cytometry, the responders to anti-PD1 showed an increased proportion of TAMs, as well as lymphocytes, and the most enriched immune cell population in the TME was also TAMs. For noninvasive imaging of TAMs as a surrogate of immune cell augmentation in the TME via anti-PD1, we acquired [⁶⁸Ga] Ga-MSA positron emission tomography. According to the imaging study, an increased number of TAMs in responders at the early phase of anti-PD1 treatment was observed in both B16F10-Luc and MC38-Luc tumor-bearing mice models.

CONCLUSION

As representative immune cells in the TME, non-invasive imaging of TAMs using MSA nanoparticles can reflect the immune cell enrichment status in the TME closely associated with the response to anti-PD1. As non-invasive imaging using MSA nanoparticles, this approach shows a potential to monitor and evaluate anti-tumor response to immune checkpoint inhibitors.

Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models

BACKGROUND

It remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting.

METHODS

Multi-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T2 (relaxation), CEST based APT (probing mobile proteins/peptides) and rNOE (mobile macromolecules), qMT (macromolecules), diffusion based ADC (cell density) and SSIFT iAUC (cell size), and perfusion based DSC (blood volume and flow).

RESULTS

For single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions.

CONCLUSION

A general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.

Improving MR cell size imaging by inclusion of transcytolemmal water exchange

The goal of the current study is to include transcytolemmal water exchange in MR cell size imaging using the IMPULSED model for more accurate characterization of tissue cellular properties (e.g., apparent volume fraction of intracellular space v in ) and quantification of indicators of transcytolemmal water exchange. We propose a heuristic model that incorporates transcytolemmal water exchange into a multicompartment diffusion-based method (IMPULSED) that was developed previously to extract microstructural parameters (e.g., mean cell size d and apparent volume fraction of intracellular space v in ) assuming no water exchange. For t diff ≤ 5 ms, the water exchange can be ignored, and the signal model is the same as the IMPULSED model. For t diff ≥ 30 ms, we incorporated the modified Kärger model that includes both restricted diffusion and exchange between compartments. Using simulations and previously published in vitro cell data, we evaluated the accuracy and precision of model-derived parameters and determined how they are dependent on SNR and imaging parameters. The joint model provides more accurate d values for cell sizes ranging from 10 to 12 microns when water exchange is fast (e.g., intracellular water pre-exchange lifetime τ in ≤ 100 ms) than IMPULSED, and reduces the bias of IMPULSED-derived estimates of v in , especially when water exchange is relatively slow (e.g., τ in &gt; 200 ms). Indicators of transcytolemmal water exchange derived from the proposed joint model are linearly correlated with ground truth τ in values and can detect changes in cell membrane permeability induced by saponin treatment in murine erythroleukemia cancer cells. Our results suggest this joint model not only improves the accuracy of IMPULSED-derived microstructural parameters, but also provides indicators of water exchange that are usually ignored in diffusion models of tissues.

MRI techniques for immunotherapy monitoring

MRI is a widely available clinical tool for cancer diagnosis and treatment monitoring. MRI provides excellent soft tissue imaging, using a wide range of contrast mechanisms, and can non-invasively detect tissue metabolites. These approaches can be used to distinguish cancer from normal tissues, to stratify tumor aggressiveness, and to identify changes within both the tumor and its microenvironment in response to therapy. In this review, the role of MRI in immunotherapy monitoring will be discussed and how it could be utilized in the future to address some of the unique clinical questions that arise from immunotherapy. For example, MRI could play a role in identifying pseudoprogression, mixed response, T cell infiltration, cell tracking, and some of the characteristic immune-related adverse events associated with these agents. The factors to be considered when developing MRI imaging biomarkers for immunotherapy will be reviewed. Finally, the advantages and limitations of each approach will be discussed, as well as the challenges for future clinical translation into routine clinical care. Given the increasing use of immunotherapy in a wide range of cancers and the ability of MRI to detect the microstructural and functional changes associated with successful response to immunotherapy, the technique has great potential for more widespread and routine use in the future for these applications.

Granzyme B PET Imaging in Response to In Situ Vaccine Therapy Combined with αPD1 in a Murine Colon Cancer Model

Immune checkpoint inhibitors (ICIs) block checkpoint receptors that tumours use for immune evasion, allowing immune cells to target and destroy cancer cells. Despite rapid advancements in immunotherapy, durable response rates to ICIs remains low. To address this, combination clinical trials are underway assessing whether adjuvants can enhance responsiveness by increasing tumour immunogenicity. CpG-oligodeoxynucleotides (CpG-ODN) are synthetic DNA fragments containing an unmethylated cysteine-guanosine motif that stimulate the innate and adaptive immune systems by engaging Toll-like receptor 9 (TLR9) present on the plasmacytoid dendritic cells (pDCs) and B cells. Here, we have assessed the ability of AlF-mNOTA-GZP, a peptide tracer targeting granzyme B, to serve as a PET imaging biomarker in response to CpG-ODN 1585 in situ vaccine therapy delivered intratumourally (IT) or intraperitoneally (IP) either as monotherapy or in combination with αPD1. [¹⁸F]AlF-mNOTA-GZP was able to differentiate treatment responders from non-responders based on tumour uptake. Furthermore, [¹⁸F]AlF-mNOTA-GZP showed positive associations with changes in tumour-associated lymphocytes expressing GZB, namely GZB+ CD8+ T cells, and decreases in suppressive F4/80+ cells. [¹⁸F]AlF-mNOTA-GZP tumour uptake was mediated by GZB expressing CD8+ cells and successfully stratifies therapy responders from non-responders, potentially acting as a non-invasive biomarker for ICIs and combination therapy evaluation in a clinical setting.

Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better

BACKGROUND

Recently, the US Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) for treating cancer patients with tumor mutation burden (TMB) >10 mutations/megabase (mut/Mb). However, high TMB (TMB-H) defined by >10 mut/Mb fails to predict ICB response across different cancer types, which has raised serious concerns on the current FDA approval. Thus, to better implement TMB as a robust biomarker of ICB response, an optimal and generalizable TMB cut-off within and across cancer types must be addressed as soon as possible.

METHODS

Using Morris's and Kurzrock's cohorts (n=1662 and 102), we exhaustively tested all possible TMB cut-offs for predicting ICB treatment outcomes in 10 cancer types. The bootstrap method was applied to generate 10,000 randomly resampled cohorts using original cohorts to measure the reproducibility of TMB cut-off. ICB treatment outcomes were analyzed by overall survival, progression-free survival and objective response rate.

RESULTS

No universally valid TMB cut-off was available for all cancer types. Only in cancer types with higher TMB (category I), such as melanoma, colorectal cancer, bladder cancer, and non-small cell lung cancer, the associations between TMB-H and ICB treatment outcomes were less affected by TMB cut-off selection. Moreover, high TMB (category I) cancer types shared a wide range of TMB cut-offs and a universally optimal TMB cut-off of 13 mut/Mb for predicting favorable ICB outcomes. In contrast, low TMB (category II) cancer types, for which the prognostic associations were sensitive to TMB cut-off selection, showed markedly limited and distinct ranges of significantly favorable TMB cut-offs. Equivalent results were obtained in the analyses of pooled tumors.

CONCLUSIONS

Our finding-the correlation that TMB-H is more robustly associated with favorable ICB treatment outcomes in cancer types with higher TMBs-can be used to predict whether TMB could be a robust predictive biomarker in cancer types for which TMB data are available, but ICB treatment has not been investigated. This theory was tested in cancer of unknown primary successfully. Additionally, the universal TMB cut-off of 13 mut/Mb might reveal a general requirement to trigger the sequential cascade from somatic mutations to an effective antitumor immunity.

Non-invasive cell-tracking methods for adoptive T cell therapies

Adoptive T cell therapies (ACT) have demonstrated groundbreaking results in blood cancers and melanoma. Nevertheless, their significant cost, the occurrence of severe adverse events, and their poor performance in solid tumors are important hurdles hampering more widespread applicability. In vivo cell tracking allows instantaneous and non-invasive monitoring of the distribution, tumor homing, persistence, and redistribution to other organs of infused T cells in patients. Furthermore, cell tracking could aid in the clinical management of patients, allowing the detection of non-responders or severe adverse events at an early stage. This review provides a concise overview of the main principles and potential of cell tracking, followed by a discussion of the clinically relevant labeling strategies and their application in ACT.

MR cell size imaging with temporal diffusion spectroscopy

Cytological features such as cell size and intracellular morphology provide fundamental information on cell status and hence may provide specific information on changes that arise within biological tissues. Such information is usually obtained by invasive biopsy in current clinical practice, which suffers several well-known disadvantages. Recently, novel MRI methods such as IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) have been developed for direct measurements of mean cell size non-invasively. The IMPULSED protocol is based on using temporal diffusion spectroscopy (TDS) to combine measurements of water diffusion over a wide range of diffusion times to probe cellular microstructure over varying length scales. IMPULSED has been shown to provide rapid, robust, and reliable mapping of mean cell size and is suitable for clinical imaging. More recently, cell size distributions have also been derived by appropriate analyses of data acquired with IMPULSED or similar sequences, which thus provides MRI-cytometry. This review summarizes the basic principles, practical implementations, validations, and example applications of MR cell size imaging based on TDS and demonstrates how cytometric information can be used in various applications. In addition, the limitations and potential future directions of MR cytometry are identified including the diagnosis of nonalcoholic steatohepatitis of the liver and the assessment of treatment response of cancers.

Granzyme B PET Imaging of Combined Chemotherapy and Immune Checkpoint Inhibitor Therapy in Colon Cancer

Purpose

Chemotherapeutic adjuvants, such as oxaliplatin (OXA) and 5-fluorouracil (5-FU), that enhance the immune system, are being assessed as strategies to improve durable response rates when used in combination with immune checkpoint inhibitor (ICI) monotherapy in cancer patients. In this study, we explored granzyme B (GZB), released by tumor-associated immune cells, as a PET imaging-based stratification marker for successful combination therapy using a fluorine-18 (¹⁸F)-labelled GZB peptide ([¹⁸F]AlF-mNOTA-GZP).

Methods

Using the immunocompetent CT26 syngeneic mouse model of colon cancer, we assessed the potential for [¹⁸F]AlF-mNOTA-GZP to stratify OXA/5-FU and ICI combination therapy response via GZB PET. In vivo tumor uptake of [¹⁸F]AlF-mNOTA-GZP in different treatment arms was quantified by PET, and linked to differences in tumor-associated immune cell populations defined by using multicolour flow cytometry.

Results

[¹⁸F]AlF-mNOTA-GZP tumor uptake was able to clearly differentiate treatment responders from non-responders when stratified based on changes in tumor volume. Furthermore, [¹⁸F]AlF-mNOTA-GZP showed positive associations with changes in tumor-associated lymphocytes expressing GZB, namely GZB+ CD8+ T cells and GZB+ NK+ cells.

Conclusions

[¹⁸F]AlF-mNOTA-GZP tumor uptake, driven by changes in immune cell populations expressing GZB, is able to stratify tumor response to chemotherapeutics combined with ICIs. Our results show that, while the immunomodulatory mode of action of the chemotherapies may be different, the ultimate mechanism of tumor lysis through release of Granzyme B is an accurate biomarker for treatment response.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11307-021-01596-y.

MRI-cytometry: Mapping nonparametric cell size distributions using diffusion MRI

PURPOSE

This report introduces and validates a new diffusion MRI-based method, termed MRI-cytometry, which can noninvasively map intravoxel, nonparametric cell size distributions in tissues.

METHODS

MRI was used to acquire diffusion MRI signals with a range of diffusion times and gradient factors, and a model was fit to these data to derive estimates of cell size distributions. We implemented a 2-step fitting method to avoid noise-induced artificial peaks and provide reliable estimates of tumor cell size distributions. Computer simulations in silico, experimental measurements on cultured cells in vitro, and animal xenografts in vivo were used to validate the accuracy and precision of the method. Tumors in 7 patients with breast cancer were also imaged and analyzed using this MRI-cytometry approach on a clinical 3 Tesla MRI scanner.

RESULTS

Simulations and experimental results confirm that MRI-cytometry can reliably map intravoxel, nonparametric cell size distributions and has the potential to discriminate smaller and larger cells. The application in breast cancer patients demonstrates the feasibility of direct translation of MRI-cytometry to clinical applications.

CONCLUSION

The proposed MRI-cytometry method can characterize nonparametric cell size distributions in human tumors, which potentially provides a practical imaging approach to derive specific histopathological information on biological tissues.

Diffusion-weighted MRI improves response assessment after definitive radiotherapy in patients with NSCLC

Background

Computed tomography (CT) is the standard procedure for follow-up of non-small-cell lung cancer (NSCLC) after radiochemotherapy. CT has difficulties differentiating between tumor, atelectasis and radiation induced lung toxicity (RILT). Diffusion-weighted imaging (DWI) may enable a more accurate detection of vital tumor tissue. The aim of this study was to determine the diagnostic value of MRI versus CT in the follow-up of NSCLC.

Methods

Twelve patients with NSCLC stages I-III scheduled for radiochemotherapy were enrolled in this prospective study. CT with i.v. contrast agent and non enhanced MRI were performed before and 3, 6 and 12 months after treatment. Standardized ROIs were used to determine the apparent diffusion weighted coefficient (ADC) within the tumor. Tumor size was assessed by the longest longitudinal diameter (LD) and tumor volume on DWI and CT. RILT was assessed on a 4-point-score in breath-triggered T2-TSE and CT.

Results

There was no significant difference regarding LD and tumor volume between MRI and CT (p ≥ 0.6221, respectively p ≥ 0.25). Evaluation of RILT showed a very high correlation between MRI and CT at 3 (r = 0.8750) and 12 months (r = 0.903). Assessment of the ADC values suggested that patients with a good tumor response have higher ADC values than non-responders.

Conclusions

DWI is equivalent to CT for tumor volume determination in patients with NSCLC during follow up. The extent of RILT can be reliably determined by MRI. DWI could become a beneficial method to assess tumor response more accurately. ADC values may be useful as a prognostic marker.