DCE-MRI perfusion predicts pseudoprogression in metastatic melanoma treated with immunotherapy

Histopathological correlation of brain tumor recurrence vs. radiation effect post-radiosurgery as detected by MRI contrast clearance analysis: a validation study

PURPOSE

The differentiation between adverse radiation effects (ARE) and tumor recurrence or progression (TRP) is a major decision-making point in the follow-up of patients with brain tumors. The advent of immunotherapy, targeted therapy and radiosurgery has made this distinction difficult to achieve in several clinical situations. Contrast clearance analysis (CCA) is a useful technique that can inform clinical decisions but has so far only been histologically validated in the context of high-grade gliomas.

METHODS

This is a series of 7 patients, treated between 2018 and 2023, for various brain pathologies including brain metastasis, atypical meningioma, and high-grade glioma. MRI with contrast clearance analysis was used to inform clinical decisions and patients underwent surgical resection as indicated. The histopathology findings were compared with the CCA findings in all cases.

RESULTS

All seven patients had been treated with gamma knife radiosurgery and were followed up with periodic MR imaging. All patients underwent CCA when the necessity to distinguish tumor recurrence from radiation necrosis arose, and subsequently underwent surgery as indicated. Concordance of CCA findings with histological findings was found in all cases (100%).

CONCLUSIONS

Based on prior studies on GBM and the surgical findings in our series, delayed contrast extravasation MRI findings correlate well with histopathology across a wide spectrum of brain tumor pathologies. CCA can provide a quick diagnosis and have a direct impact on patients' treatment and outcomes.

Correlation of Ktrans derived from dynamic contrast-enhanced MRI with treatment response and survival in locally advanced NSCLC patients undergoing induction immunochemotherapy and concurrent chemoradiotherapy

PURPOSE

This study aimed to investigate the prognostic significance of pretreatment dynamic contrast-enhanced (DCE)-MRI parameters concerning tumor response following induction immunochemotherapy and survival outcomes in patients with locally advanced non-small cell lung cancer (NSCLC) who underwent immunotherapy-based multimodal treatments.

MATERIAL AND METHODS

Unresectable stage III NSCLC patients treated by induction immunochemotherapy, concurrent chemoradiotherapy (CCRT) with or without consolidative immunotherapy from two prospective clinical trials were screened. Using the two-compartment Extend Tofts model, the parameters including Ktrans, Kep, Ve, and Vp were calculated from DCE-MRI data. The apparent diffusion coefficient was calculated from diffusion-weighted-MRI data. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to assess the predictive performance of MRI parameters. The Cox regression model was used for univariate and multivariate analysis.

RESULTS

111 unresectable stage III NSCLC patients were enrolled. Patients received two cycles of induction immunochemotherapy and CCRT, with or without consolidative immunotherapy. With the median follow-up of 22.3 months, the median progression-free survival (PFS) and overall survival (OS) were 16.3 and 23.8 months. The multivariate analysis suggested that Eastern Cooperative Oncology Group score, TNM stage and the response to induction immunochemotherapy were significantly related to both PFS and OS. After induction immunochemotherapy, 67 patients (59.8%) achieved complete response or partial response and 44 patients (40.2%) had stable disease or progressive disease. The Ktrans of primary lung tumor before induction immunochemotherapy yielded the best performance in predicting the treatment response, with an AUC of 0.800. Patients were categorized into two groups: high-Ktrans group (n=67, Ktrans＞164.3×10-3/min) and low-Ktrans group (n=44, Ktrans≤164.3×10-3/min) based on the ROC analysis. The high-Ktrans group had a significantly higher objective response rate than the low-Ktrans group (85.1% (57/67) vs 22.7% (10/44), p<0.001). The high-Ktrans group also presented better PFS (median: 21.1 vs 11.3 months, p=0.002) and OS (median: 34.3 vs 15.6 months, p=0.035) than the low-Ktrans group.

CONCLUSIONS

Pretreatment Ktrans value emerged as a significant predictor of the early response to induction immunochemotherapy and survival outcomes in unresectable stage III NSCLC patients who underwent immunotherapy-based multimodal treatments. Elevated Ktrans values correlated positively with enhanced treatment response, leading to extended PFS and OS durations.

The development process of 'fit-for-purpose' imaging biomarkers to characterize the tumor microenvironment

Immune-based treatment approaches are successfully used for the treatment of patients with cancer. While such therapies can be highly effective, many patients fail to benefit. To provide optimal therapy choices and to predict treatment responses, reliable biomarkers for the assessment of immune features in patients with cancer are of significant importance. Biomarkers (BM) that enable a comprehensive and repeatable assessment of the tumor microenvironment (TME), the lymphoid system, and the dynamics induced by drug treatment can fill this gap. Medical imaging, notably positron emission tomography (PET) and magnetic resonance imaging (MRI), providing whole-body imaging BMs, might deliver such BMs. However, those imaging BMs must be well characterized as being 'fit for purpose' for the intended use. This review provides an overview of the key steps involved in the development of 'fit-for-purpose' imaging BMs applicable in drug development, with a specific focus on pharmacodynamic biomarkers for assessing the TME and its modulation by immunotherapy. The importance of the qualification of imaging BMs according to their context of use (COU) as defined by the Food and Drug Administration (FDA) and National Institutes of Health Biomarkers, EndpointS, and other Tools (BEST) glossary is highlighted. We elaborate on how an imaging BM qualification for a specific COU can be achieved.

Possibilities of Using Multi-b-value Diffusion Magnetic Resonance Imaging for Classification of Brain Lesions

In contrast to conventional diffusion magnetic resonance imaging (MRI), multi-b-value diffusion MRI methods are able to separate the signal from free water, pseudo-diffusion, and non-Gaussian components of water molecule diffusion. These approaches can then be utilised in so-called intravoxel incoherent motion imaging and diffusion kurtosis imaging. Various parameters provided by these methods can describe additional characteristics of the tissue microstructure and potentially help in the diagnosis and classification of various pathological processes. In this review, we present the basic principles and methods of analysing multi-b-value diffusion imaging data and specifically focus on the known possibilities for its use in the diagnosis of brain lesions. We also suggest possible directions for further research.

Radiosurgery for Brain Metastases: Challenges in Imaging Interpretation after Treatment

Stereotactic radiosurgery (SRS) has transformed the management of brain metastases by achieving local tumor control, reducing toxicity, and minimizing the need for whole-brain radiation therapy (WBRT). This review specifically investigates radiation-induced changes in patients treated for metastasis, highlighting the crucial role of magnetic resonance imaging (MRI) in the evaluation of treatment response, both at very early and late stages. The primary objective of the review is to evaluate the most effective imaging techniques for assessing radiation-induced changes and distinguishing them from tumor growth. The limitations of conventional imaging methods, which rely on size measurements, dimensional criteria, and contrast enhancement patterns, are critically evaluated. In addition, it has been investigated the potential of advanced imaging modalities to offer a more precise and comprehensive evaluation of treatment response. Finally, an overview of the relevant literature concerning the interpretation of brain changes in patients undergoing immunotherapies is provided.

Artificial Intelligence and Radiomics: Clinical Applications for Patients with Advanced Melanoma Treated with Immunotherapy

Immunotherapy has greatly improved the outcomes of patients with metastatic melanoma. However, it has also led to new patterns of response and progression, creating an unmet need for better biomarkers to identify patients likely to achieve a lasting clinical benefit or experience immune-related adverse events. In this study, we performed a focused literature survey covering the application of artificial intelligence (AI; in the form of radiomics, machine learning, and deep learning) to patients diagnosed with melanoma and treated with immunotherapy, reviewing 12 studies relevant to the topic published up to early 2022. The most commonly investigated imaging modality was CT imaging in isolation (n = 9, 75.0%), while patient cohorts were most frequently recruited retrospectively and from single institutions (n = 7, 58.3%). Most studies concerned the development of AI tools to assist in prognostication (n = 5, 41.7%) or the prediction of treatment response (n = 6, 50.0%). Validation methods were disparate, with two studies (16.7%) performing no validation and equal numbers using cross-validation (n = 3, 25%), a validation set (n = 3, 25%), or a test set (n = 3, 25%). Only one study used both validation and test sets (n = 1, 8.3%). Overall, promising results have been observed for the application of AI to immunotherapy-treated melanoma. Further improvement and eventual integration into clinical practice may be achieved through the implementation of rigorous validation using heterogeneous, prospective patient cohorts.

Structural and functional vascular dysfunction within brain metastases is linked to pembrolizumab inefficacy

Structurally and functionally aberrant vasculature is a hallmark of tumor angiogenesis and treatment resistance. Given the synergistic link between aberrant tumor vasculature and immunosuppression, we analyzed perfusion MRI for 44 patients with brain metastases (BM) undergoing treatment with pembrolizumab. To date, vascular-immune communication, or the relationship between immune checkpoint inhibitor (ICI) efficacy and vascular architecture, has not been well-characterized in human imaging studies. We found that ICI-responsive BM possessed a structurally balanced vascular makeup, which was linked to improved vascular efficiency and an immune-stimulatory microenvironment. In contrast, ICI-resistant BM were characterized by a lack of immune cell infiltration and a highly aberrant vasculature dominated by large-caliber vessels. Peri-tumor region analysis revealed early functional changes predictive of ICI resistance before radiographic evidence on conventional MRI. This study was one of the largest functional imaging studies for BM and establishes a foundation for functional studies that illuminate the mechanisms linking patterns of vascular architecture with immunosuppression, as targeting these aspects of cancer biology may serve as the basis for future combination treatments.

The therapeutic utility of combining dynamic contrast-enhanced magnetic resonance imaging with arterial spin labeling in the staging of nasopharyngeal carcinoma

BACKGROUND

To research the pathological and clinical staging uses of arterial spin labeling (ASL) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

64 newly diagnosed nasopharyngeal carcinoma (NPC) patients were enrolled from December 2020 to January 2022, and 3.0 T MRI (Discovery 750W, GE Healthcare, USA) were used for ASL and DCE-MRI scans. The DCE-MRI and ASL raw data were processed post-acquisition on the GE image processing workstation (GE Healthcare, ADW 4.7, USA). The volume transfer constant (Ktrans), blood flow (BF), and accompanying pseudo-color images were generated automatically. Draw the region of interest (ROIs), and the Ktrans and BF values for each ROI were recorded separately. Based on pathological information and the most recent AJCC staging criteria, patients were divided into low T stage groups = T_1-2 and high T stage groups = T_3-4, low N stage groups = N_0-1 and high N stage groups = N_2-3, and low AJCC stage group = stage I-II and high AJCC stage group = stage III-IV. The association between the Ktrans_t and BF parameters and the T, N, and AJCC stages was compared using an independent sample t-test. Using a receiver operating characteristic (ROC) curve, the sensitivity, specificity, and AUC of Ktrans_t, BF_t, and their combined use in T and AJCC staging of NPC were investigated and assessed.

RESULT

The tumor-BF (BF_t) (t = - 4.905, P < 0.001) and tumor-Ktrans (Ktrans_t) (t = - 3.113, P = 0.003) in the high T stage group were significantly higher than those in the low T stage group. The Ktrans_t in the high N stage group was significantly higher than that in the low N stage group (t = - 2.071, P = 0.042). The BF_t (t = - 3.949, P < 0.001) and Ktrans_t (t = - 4.467, P < 0.001) in the high AJCC stage group were significantly higher than those in the low AJCC stage group. BF_t was moderately positively correlated with the T stage (r = 0.529, P < 0.001) and AJCC stage (r = 0.445, P < 0.001). Ktrans_t was moderately positively correlated with T staging (r = 0.368), N staging (r = 0.254), and AJCC staging (r = 0.411). There was also a positive correlation between BF and Ktrans in gross tumor volume (GTV) (r = 0.540, P < 0.001), parotid (r = 0.323, P < 0.009) and lateral pterygoid muscle (r = 0.445, P < 0.001). The sensitivity of the combined application of Ktrans_t and BF_t for AJCC staging increased from 76.5 and 78.4 to 86.3%, and the AUC value increased from 0.795 and 0.819 to 0.843, respectively.

CONCLUSION

Combining Ktrans and BF measures may make it possible to identify the clinical stages in NPC patients.

Value for combination of T1WI starVIBE with TWISTVIBE dynamic contrastenhanced MRI in distinguishing lung nodules

OBJECTIVES

With the increasing detection rate of lung nodules, the qualitative problem of lung nodules has become one of the key clinical issues. This study aims to evaluate the value of combining dynamic contrast-enhanced (DCE) MRI based on time-resolved imaging with interleaved stochastic trajectories-volume interpolated breath hold examination (TWIST-VIBE) with T1 weighted free-breathing star-volumetric interpolated breath hold examination (T1WI star-VIBE) in identifying benign and malignant lung nodules.

METHODS

We retrospectively analyzed 79 adults with undetermined lung nodules before the operation. All nodules of patients included were classified into malignant nodules (n=58) and benign nodules (n=26) based on final diagnosis. The unenhanced T1WI-VIBE, the contrast-enhanced T1WI star-VIBE, and the DCE curve based on TWIST-VIBE were performed. The corresponding qualitative [wash-in time, wash-out time, time to peak (TTP), arrival time (AT), positive enhancement integral (PEI)] and quantitative parameters [volume transfer constant (Ktrans), interstitium-to-plasma rate constant (Kep), and fractional extracellular space volume (Ve)] were evaluated. Besides, the diagnostic efficacy (sensitivity and specificity) of enhanced CT and MRI were compared.

RESULTS

There were significant differences in unenhanced T1WI-VIBE hypo-intensity, and type of A, B, C DCE curve type between benign and malignant lung nodules (all P<0.001). Pulmonary malignant nodules had a shorter wash-out time than benign nodules (P=0.001), and the differences of the remaining parameters were not statistically significant (all P>0.05). After T1WI star-VIBE contrast-enhanced MRI, the image quality was further improved. Compared with enhanced CT scan, the sensitivity (82.76% vs 80.50%) and the specificity (69.23% vs 57.10%) based on MRI were higher than that of CT (both P<0.001).

CONCLUSIONS

T1WI star-VIBE and dynamic contrast-enhanced MRI based on TWIST-VIBE were helpful to improve the image resolution and provide more information for clinical differentiation between benign and malignant lung nodules.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.

Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts

Early diagnosis is essential for completely eradicating skin cancer and maximizing patients' clinical benefits. Emerging optical imaging modalities such as reflectance confocal microscopy (RCM), optical coherence tomography (OCT), magnetic resonance imaging (MRI), near-infrared (NIR) bioimaging, positron emission tomography (PET), and their combinations provide non-invasive imaging data that may help in the early detection of cutaneous tumors and surgical planning. Hence, they seem appropriate for observing dynamic processes such as blood flow, immune cell activation, and tumor energy metabolism, which may be relevant for disease evolution. This review discusses the latest technological and methodological advances in imaging techniques that may be applied for skin cancer detection and monitoring. In the first instance, we will describe the principle and prospective clinical applications of the most commonly used imaging techniques, highlighting the challenges and opportunities of their implementation in the clinical setting. We will also highlight how imaging techniques may complement the molecular and histological approaches in sharpening the non-invasive skin characterization, laying the ground for more personalized approaches in skin cancer patients.

A Multi-Disciplinary Approach to Diagnosis and Treatment of Radionecrosis in Malignant Gliomas and Cerebral Metastases

Radiation necrosis represents a potentially devastating complication after radiation therapy in brain tumors. The establishment of the diagnosis and especially the differentiation from progression and pseudoprogression with its therapeutic implications requires interdisciplinary consent and monitoring. Herein, we want to provide an overview of the diagnostic modalities, therapeutic possibilities and an outlook on future developments to tackle this challenging topic. The aim of this report is to provide an overview of the current morphological, functional, metabolic and evolving imaging tools described in the literature in order to (I) identify the best criteria to distinguish radionecrosis from tumor recurrence after the radio-oncological treatment of malignant gliomas and cerebral metastases, (II) analyze the therapeutic possibilities and (III) give an outlook on future developments to tackle this challenging topic. Additionally, we provide the experience of a tertiary tumor center with this important issue in neuro-oncology and provide an institutional pathway dealing with this problem.

Chemical Exchange Saturation Transfer MRI for Differentiating Radiation Necrosis From Tumor Progression in Brain Metastasis-Application in a Clinical Setting

BACKGROUND

High radiation doses of stereotactic radiosurgery (SRS) for brain metastases (BM) can increase the likelihood of radiation necrosis (RN). Advanced MRI sequences can improve the differentiation between RN and tumor progression (TP).

PURPOSE

To use saturation transfer MRI methods including chemical exchange saturation transfer (CEST) and magnetization transfer (MT) to distinguish RN from TP.

STUDY TYPE

Prospective cohort study.

SUBJECTS

Seventy patients (median age 60; 73% females) with BM (75 lesions) post-SRS.

FIELD STRENGTH/SEQUENCE

3-T, CEST imaging using low/high-power (saturation B₁  = 0.52 and 2.0 μT), quantitative MT imaging using B₁  = 1.5, 3.0, and 5.0 μT, WAter Saturation Shift Referencing (WASSR), WAter Shift And B₁ (WASABI), T₁ , and T₂ mapping. All used gradient echoes except T₂ mapping (gradient and spin echo).

ASSESSMENT

Voxel-wise metrics included: magnetization transfer ratio (MTR); apparent exchange-dependent relaxation (AREX); MTR asymmetry; normalized MT exchange rate and pool size product; direct water saturation peak width; and the observed T₁ and T₂ . Regions of interests (ROIs) were manually contoured on the post-Gd T₁ w. The mean (of median ROI values) was compared between groups. Clinical outcomes were determined by clinical and radiologic follow-up or histopathology.

STATISTICAL TESTS

t-Test, univariable and multivariable logistic regression, receiver operating characteristic, and area under the curve (AUC) with sensitivity/specificity values with the optimal cut point using the Youden index, Akaike information criterion (AIC), Cohen's d. P < 0.05 with Bonferroni correction was considered significant.

RESULTS

Seven metrics showed significant differences between RN and TP. The high-power MTR showed the highest AUC of 0.88, followed by low-power MTR (AUC = 0.87). The combination of low-power CEST scans improved the separation compared to individual parameters (with an AIC of 70.3 for low-power MTR/AREX). Cohen's d effect size showed that the MTR provided the largest effect sizes among all metrics.

DATA CONCLUSION

Significant differences between RN and TP were observed based on saturation transfer MRI.

EVIDENCE LEVEL

3 Technical Efficacy: Stage 2.

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.

Prediction of Early Response to Immunotherapy: DCE-US as a New Biomarker

Simple Summary

Immune checkpoint inhibitors (ICI) have revolutionized cancer care. However, assessing the efficacy of these new molecules with targeted therapeutic responses may induce too much delay when using classical biomarkers derived from morphological imaging (CT). The objective of our study is to propose fast, cost-effective, convenient, and effective biomarkers using the perfusion parameters from dynamic contrast-enhanced ultrasound (DCE-US) for the evaluation of ICI early response. In a population of 63 patients with metastatic cancer eligible for immunotherapy, we demonstrate that a decrease of more than 45% in the area under the perfusion curve (AUC) between baseline and day 21 is significantly associated with better overall survival. Thus, AUC from DCE-US looks to be a promising new biomarker for the early evaluation of response to immunotherapy.

Abstract

Purpose: The objective of our study is to propose fast, cost-effective, convenient, and effective biomarkers using the perfusion parameters from dynamic contrast-enhanced ultrasound (DCE-US) for the evaluation of immune checkpoint inhibitors (ICI) early response. Methods: The retrospective cohort used in this study included 63 patients with metastatic cancer eligible for immunotherapy. DCE-US was performed at baseline, day 8 (D8), and day 21 (D21) after treatment onset. A tumor perfusion curve was modeled on these three dates, and change in the seven perfusion parameters was measured between baseline, D8, and D21. These perfusion parameters were studied to show the impact of their variation on the overall survival (OS). Results: After the removal of missing or suboptimal DCE-US, the Baseline-D8, the Baseline-D21, and the D8-D21 groups included 37, 53, and 33 patients, respectively. A decrease of more than 45% in the area under the perfusion curve (AUC) between baseline and D21 was significantly associated with better OS (p = 0.0114). A decrease of any amount in the AUC between D8 and D21 was also significantly associated with better OS (p = 0.0370). Conclusion: AUC from DCE-US looks to be a promising new biomarker for fast, effective, and convenient immunotherapy response evaluation.

Adapting Imaging Protocols for PET-CT and PET-MRI for Immunotherapy Monitoring

Hybrid imaging with positron emission tomography (PET) in combination with computer tomography (CT) is a well-established diagnostic tool in oncological staging and restaging. The combination of PET with magnetic resonance imaging (MRI) as a clinical scanner was introduced approximately 10 years ago. Although MRI provides superb soft tissue contrast and functional information without the radiation exposure of CT, PET-MRI is not as widely introduced in oncologic imaging as PET-CT. One reason for this hesitancy lies in the relatively long acquisition times for a PET-MRI scan, if the full diagnostic potential of MRI is exploited. In this review, we discuss the possible advantages of combined imaging protocols of PET-CT and PET-MRI, within the context of staging and restaging of patients under immunotherapy, in order to achieve "multi-hybrid imaging" in one single patient visit.

Pseudoprogression in lung cancer patients treated with immunotherapy

Lung cancer has attracted much attention because of its high morbidity and mortality worldwide. The advent of immunotherapy approaches, especially the application of immune checkpoint inhibitors (ICIs) has dramatically changed the treatment of lung cancer, but a novel and unexpected pattern of treatment response-- pseudoprogression, has been observed simultaneously which complicates the routine clinical evaluation and management. However, manifestations of pseudoprogression vary and there are many disputes on immune-related response assessment and corresponding treatments for lung cancer. Therefore, we summarized the possible mechanisms, clinical manifestations and corresponding treatment measures of pseudoprogression in lung cancer, as well as potential methods to differentiate pseudoprogression from true tumor progression.

The Role of the Immune Response in Brain Metastases: Novel Imaging Biomarkers for Immunotherapy

Brain metastases are a major clinical problem, and immunotherapy offers a novel treatment paradigm with the potential to synergize with existing focal therapies like surgery and radiosurgery or even replace them in future. The brain is a unique microenvironment structurally and immunologically. The immune response is likely to be crucial to the adaptation of systemic immune modulating agents against this disease. Imaging is frequently employed in the clinical diagnosis and management of brain metastasis, so it is logical that brain imaging techniques are investigated as a source of biomarkers of the immune response in these tumors. Current imaging techniques in clinical use include structural MRI (post-contrast T1W sequences, T2, and FLAIR), physiological sequences (perfusion- and diffusion-weighted imaging), and molecular imaging (MR spectroscopy and PET). These are reviewed for their application to predicting and measuring the response to immunotherapy in brain metastases.

Multiparametric MRI of early tumor response to immune checkpoint blockade in metastatic melanoma

BACKGROUND

Immune checkpoint inhibitors are now standard of care treatment for many cancers. Treatment failure in metastatic melanoma is often due to tumor heterogeneity, which is not easily captured by conventional CT or tumor biopsy. The aim of this prospective study was to investigate early microstructural and functional changes within melanoma metastases following immune checkpoint blockade using multiparametric MRI.

METHODS

Fifteen treatment-naïve metastatic melanoma patients (total 27 measurable target lesions) were imaged at baseline and following 3 and 12 weeks of treatment on immune checkpoint inhibitors using: T2-weighted imaging, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI. Treatment timepoint changes in tumor cellularity, vascularity, and heterogeneity within individual metastases were evaluated and correlated to the clinical outcome in each patient based on Response Evaluation Criteria in Solid Tumors V.1.1 at 1 year.

RESULTS

Differential tumor growth kinetics in response to immune checkpoint blockade were measured in individual metastases within the same patient, demonstrating significant intertumoral heterogeneity in some patients. Early detection of tumor cell death or cell loss measured by a significant increase in the apparent diffusivity (Dapp) (p<0.05) was observed in both responding and pseudoprogressive lesions after 3 weeks of treatment. Tumor heterogeneity, as measured by apparent diffusional kurtosis (Kapp), was consistently higher in the pseudoprogressive and true progressive lesions, compared with the responding lesions throughout the first 12 weeks of treatment. These preceded tumor regression and significant tumor vascularity changes (Ktrans, ve, and vp) detected after 12 weeks of immunotherapy (p<0.05).

CONCLUSIONS

Multiparametric MRI demonstrated potential for early detection of successful response to immune checkpoint inhibitors in metastatic melanoma.