Dissociated Response in Metastatic Cancer: An Atypical Pattern Brought Into the Spotlight With Immunotherapy

RECIST 1.1 assessments variability: a systematic pictorial review of blinded double reads

Reader variability is intrinsic to radiologic oncology assessments, necessitating measures to enhance consistency and accuracy. RECIST 1.1 criteria play a crucial role in mitigating this variability by standardizing evaluations, aiming to establish an accepted "truth" confirmed by histology or patient survival. Clinical trials utilize Blind Independent Centralized Review (BICR) techniques to manage variability, employing double reads and adjudicators to address inter-observer discordance effectively. It is essential to dissect the root causes of variability in response assessments, with a specific focus on the factors influencing RECIST evaluations. We propose proactive measures for radiologists to address variability sources such as radiologist expertise, image quality, and accessibility of contextual information, which significantly impact interpretation and assessment precision. Adherence to standardization and RECIST guidelines is pivotal in diminishing variability and ensuring uniform results across studies. Variability factors, including lesion selection, new lesion appearance, and confirmation bias, can have profound implications on assessment accuracy and interpretation, underscoring the importance of identifying and addressing these factors. Delving into the causes of variability aids in enhancing the accuracy and consistency of response assessments in oncology, underscoring the role of standardized evaluation protocols and mitigating risk factors that contribute to variability. Access to contextual information is crucial. CRITICAL RELEVANCE STATEMENT: By understanding the causes of diagnosis variability, we can enhance the accuracy and consistency of response assessments in oncology, ultimately improving patient care and clinical outcomes. KEY POINTS: Baseline lesion selection and detection of new lesions play a major role in the occurrence of discordance. Image interpretation is influenced by contextual information, the lack of which can lead to diagnostic uncertainty. Radiologists must be trained in RECIST criteria to reduce errors and variability.

Multimodal Imaging Approach for Tumor Treatment Response Evaluation in the Era of Immunotherapy

ABSTRACT

Immunotherapy is likely the most remarkable advancement in lung cancer treatment during the past decade. Although immunotherapy provides substantial benefits, their therapeutic responses differ from those of conventional chemotherapy and targeted therapy, and some patients present unique immunotherapy response patterns that cannot be judged under the current measurement standards. Therefore, the response monitoring of immunotherapy can be challenging, such as the differentiation between real response and pseudo-response. This review outlines the various tumor response patterns to immunotherapy and discusses methods for quantifying computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) in the field of lung cancer. Emerging technologies in magnetic resonance imaging (MRI) and non-FDG PET tracers are also explored. With immunotherapy responses, the role for imaging is essential in both anatomical radiological responses (CT/MRI) and molecular changes (PET imaging). Multiple aspects must be considered when assessing treatment responses using CT and PET. Finally, we introduce multimodal approaches that integrate imaging and nonimaging data, and we discuss future directions for the assessment and prediction of lung cancer responses to immunotherapy.

Assessing the Heterogeneity of Response of [68Ga] Ga-PSMA-11 PET/CT Lesions in Patients With Biochemical Recurrence of Prostate Cancer

INTRODUCTION

Treatment of men with metastatic prostate cancer can be difficult due to the heterogeneity of response of lesions. [68Ga]Ga-PSMA-11 (PSMA) PET/CT assists with monitoring and directing clinical intervention; however, the impact of response heterogeneity has yet to be related to outcome measures. The aim of this study was to assess the impact of quantitative imaging information on the value of PSMA PET/CT to assess patient outcomes in response evaluation.

PATIENTS AND METHODS

Baseline and follow-up (6 months) PSMA PET/CT of 162 men with oligometastatic PC treated with standard clinical care were acquired between 2015 and 2016 for analysis. An augmentative software medical device was used to track lesions between scans and quantify lesion change to categorize them as either new, increasing, stable, decreasing, or disappeared. Quantitative imaging features describing the size, intensity, extent, change, and heterogeneity of change (based on percent change in SUVtotal) among lesions were extracted and evaluated for association with overall survival (OS) using Cox regression models. Model performance was evaluated using the c-index.

RESULTS

Forty-one (25%) of subjects demonstrated heterogeneous response at follow-up, defined as having at least 1 new or increasing lesion and at least 1 decreasing or disappeared lesion. Subjects with heterogeneous response demonstrated significantly shorter OS than subjects without (median OS = 76.6 months vs. median OS not reached, P < .05, c-index = 0.61). In univariate analyses, SUVtotal at follow-up was most strongly associated with OS (HR = 1.29 [1.19, 1.40], P < .001, c-index = 0.73). Multivariable models applied using heterogeneity of change features demonstrated higher performance (c-index = 0.79) than models without (c-index = 0.71-0.76, P < .05).

CONCLUSION

Augmentative software tools enhance the evaluation change on serial PSMA PET scans and can facilitate lesional evaluation between timepoints. This study demonstrates that a heterogeneous response at a lesional level may impact adversely on patient outcomes and supports further investigation to evaluate the role of imaging to guide individualized patient management to improve clinical outcomes.

[18F]FDG-PET/CT atypical response patterns to immunotherapy in non-small cell lung cancer patients: long term prognosis assessment and clinical management proposal

AIM

To determine the long-term prognosis of immune-related response profiles (pseudoprogression and dissociated response), not covered by conventional PERCIST criteria, in patients with non-small-cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs).

METHODS

109 patients were prospectively included and underwent [18F]FDG-PET/CT at baseline, after 7 weeks (PETinterim1), and 3 months (PETinterim2) of treatment. On PETinterim1, tumor response was assessed using standard PERCIST criteria. In the event of PERCIST progression at this time-point, the study design provided for continued immunotherapy for 6 more weeks. Additional response patterns were then considered on PETinterim2: pseudo-progression (PsPD, subsequent metabolic response); dissociated response (DR, coexistence of responding and non-responding lesions), and confirmed progressive metabolic disease (cPMD, subsequent homogeneous progression of lesions). Patients were followed up for at least 12 months.

RESULTS

Median follow-up was 21 months. At PETinterim1, PERCIST progression was observed in 60% (66/109) of patients and ICPI was continued in 59/66. At the subsequent PETinterim2, 14% of patients showed PsPD, 11% DR, 35% cPMD, and 28% had a sustained metabolic response. Median overall survival (OS) and progression-free-survival (PFS) did not differ between PsPD and DR (27 vs 29 months, p = 1.0; 17 vs 12 months, p = 0.2, respectively). The OS and PFS of PsPD/DR patients were significantly better than those with cPMD (29 vs 9 months, p < 0.02; 16 vs 2 months, p < 0.001), but worse than those with sustained metabolic response (p < 0.001). This 3-group prognostic stratification enabled better identification of true progressors, outperforming the prognostic value of standard PERCIST criteria (p = 0.03).

CONCLUSION

[18F]FDG-PET/CT enables early assessment of response to immunotherapy. The new wsPERCIST ("wait and see") PET criteria proposed, comprising immune-related atypical response patterns, can refine conventional prognostic stratification based on PERCIST criteria.

TRIAL REGISTRATION

HDH F20230309081206. Registered 20 April 2023. Retrospectively registered.

Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling

The phenomenon of mixed/heterogenous treatment responses to cancer therapies within an individual patient presents a challenging clinical scenario. Furthermore, the molecular basis of mixed intra-patient tumor responses remains unclear. Here, we show that patients with metastatic lung adenocarcinoma harbouring co-mutations of EGFR and TP53, are more likely to have mixed intra-patient tumor responses to EGFR tyrosine kinase inhibition (TKI), compared to those with an EGFR mutation alone. The combined presence of whole genome doubling (WGD) and TP53 co-mutations leads to increased genome instability and genomic copy number aberrations in genes implicated in EGFR TKI resistance. Using mouse models and an in vitro isogenic p53-mutant model system, we provide evidence that WGD provides diverse routes to drug resistance by increasing the probability of acquiring copy-number gains or losses relative to non-WGD cells. These data provide a molecular basis for mixed tumor responses to targeted therapy, within an individual patient, with implications for therapeutic strategies.

Beyond the Barrier: Unraveling the Mechanisms of Immunotherapy Resistance

Immune checkpoint blockade (ICB) induces a remarkable and durable response in a subset of cancer patients. However, most patients exhibit either primary or acquired resistance to ICB. This resistance arises from a complex interplay of diverse dynamic mechanisms within the tumor microenvironment (TME). These mechanisms include genetic, epigenetic, and metabolic alterations that prevent T cell trafficking to the tumor site, induce immune cell dysfunction, interfere with antigen presentation, drive heightened expression of coinhibitory molecules, and promote tumor survival after immune attack. The TME worsens ICB resistance through the formation of immunosuppressive networks via immune inhibition, regulatory metabolites, and abnormal resource consumption. Finally, patient lifestyle factors, including obesity and microbiome composition, influence ICB resistance. Understanding the heterogeneity of cellular, molecular, and environmental factors contributing to ICB resistance is crucial to develop targeted therapeutic interventions that enhance the clinical response. This comprehensive overview highlights key mechanisms of ICB resistance that may be clinically translatable.

Quantitative evaluation of lesion response heterogeneity for superior prognostication of clinical outcome

PURPOSE

Standardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome.

METHODS

[18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score.

RESULTS

Multivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001).

CONCLUSIONS

Quantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable, but is hindered by the limited performance of existing biomarkers. Here, we leveraged in-silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We tested 90 biomarker candidates, including various cellular and molecular species, by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pre-treatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.

An automated methodology for whole-body, multimodality tracking of individual cancer lesions

Objective. Manual analysis of individual cancer lesions to assess disease response is clinically impractical and requires automated lesion tracking methodologies. However, no methodology has been developed for whole-body individual lesion tracking, across an arbitrary number of scans, and acquired with various imaging modalities.Approach. This study introduces a lesion tracking methodology and benchmarked it using 2368Ga-DOTATATE PET/CT and PET/MR images of eight neuroendocrine tumor patients. The methodology consists of six steps: (1) alignment of multiple scans via image registration, (2) body-part labeling, (3) automatic lesion-wise dilation, (4) clustering of lesions based on local lesion shape metrics, (5) assignment of lesion tracks, and (6) output of a lesion graph. Registration performance was evaluated via landmark distance, lesion matching accuracy was evaluated between each image pair, and lesion tracking accuracy was evaluated via identical track ratio. Sensitivity studies were performed to evaluate the impact of lesion dilation (fixed versus automatic dilation), anatomic location, image modalities (inter- versus intra-modality), registration mode (direct versus indirect registration), and track size (number of time-points and lesions) on lesion matching and tracking performance.Main results. Manual contouring yielded 956 lesions, 1570 lesion-matching decisions, and 493 lesion tracks. The median residual registration error was 2.5 mm. The automatic lesion dilation led to 0.90 overall lesion matching accuracy, and an 88% identical track ratio. The methodology is robust regarding anatomic locations, image modalities, and registration modes. The number of scans had a moderate negative impact on the identical track ratio (94% for 2 scans, 91% for 3 scans, and 81% for 4 scans). The number of lesions substantially impacted the identical track ratio (93% for 2 nodes versus 54% for ≥5 nodes).Significance. The developed methodology resulted in high lesion-matching accuracy and enables automated lesion tracking in PET/CT and PET/MR.

PET/Computed Tomography Transformation of Oncology: Immunotherapy Assessment

Immunotherapy approaches have changed the treatment landscape in a variety of malignancies with a high anti-tumor response. Immunotherapy may be associated with novel response and progression patterns that pose a substantial challenge to the conventional criteria for assessing treatment response, including response evaluation criteria in solid tumors (RECIST) 1.1. In addition to the morphologic details provided by computed tomography (CT) and MRI, hybrid molecular imaging emerges as a comprehensive imaging modality with the capacity to interrogate pathophysiological mechanisms like glucose metabolism. This review highlights the current status of 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in prognostication, response monitoring, and identifying immune-related adverse events. Furthermore, it investigates the potential role of novel immuno-PET tracers that could complement the utilization of 18F-FDG PET/CT by imaging the specific pathways involved in immunotherapeutic strategies.

Combined use of CYFRA 21-1 and CA 125 predicts survival of patients with metastatic NSCLC and stable disease in IMpower150

BACKGROUND

Patients with non-small cell lung cancer (NSCLC) and stable disease (SD) have an unmet clinical need to help guide early treatment adjustments.

OBJECTIVE

To evaluate the potential of tumor biomarkers to inform on survival outcomes in NSCLC SD patients.

METHODS

This post hoc analysis included 480 patients from the IMpower150 study with metastatic NSCLC, treated with chemotherapy, atezolizumab and bevacizumab combinations, who had SD at first CT scan (post-treatment initiation). Patients were stratified into high- and low-risk groups (overall survival [OS] and progression-free survival [PFS] outcomes) based on serum tumor biomarker levels.

RESULTS

The CYFRA 21-1 and CA 125 biomarker combination predicted OS and PFS in patients with SD. Risk of death was ~4-fold higher for the biomarker-stratified high-risk versus low-risk SD patients (hazard ratio [HR] 3.80; 95% confidence interval [CI] 3.02-4.78; p < 0.0001). OS in patients with the low- and high-risk SD was comparable to that in patients with the CT-defined partial response (PR; HR 1.10; 95% CI 0.898-1.34) and progressive disease (PD) (HR 1.05; 95% CI 0.621-1.77), respectively. The findings were similar with PFS, and consistent across treatment arms.

CONCLUSIONS

Biomarker testing shows potential for providing prognostic information to help direct treatment in NSCLC patients with SD. Prospective clinical studies are warranted.ClinicalTrials.gov: NCT02366143.

Long-term response with the atypical reaction to nivolumab in microsatellite stability metastatic colorectal cancer: A case report

Immunotherapy has become an integral part of a comprehensive treatment approach to metastatic colorectal cancer (mCRC). Nivolumab (Opdivo) is a human immunoglobulin G4 monoclonal antibody that blocks the interaction between the programmed cell death 1 (PD-1) receptor and its ligands 1/2 (PD-L1/PD-L2), leading to inhibition of T-cell proliferation, cytokine secretion, and enhanced immune response. The US Food and Drug Administration (FDA) has approved this drug for use in high microsatellite instability (MSI-high)/deficiencies in mismatch repair (dMMR) advanced CRC patients. However, its efficacy is extremely limited in microsatellite stability (MSS)/mismatch repair proficient (pMMR) patients. We report a case of a 42-year-old man diagnosed with MSS/pMMR mCRC who has achieved a durable response to nivolumab after a progression under chemotherapy with antiangiogenic treatment. We observed for the first time an atypical response after 8 months of nivolumab treatment, with the regression of previous primary pulmonary lesions and the presence of new para-aortic lymph node lesions. This report demonstrates that a subset of pretreated mCRC patients with the MSS/pMMR phenotype may benefit from nivolumab and these patients need more attention.

Nonlinear multilevel joint model for individual lesion kinetics and survival to characterize intra-individual heterogeneity in patients with advanced cancer

In advanced cancer patients, tumor burden is calculated using the sum of the longest diameters (SLD) of the target lesions, a measure that lumps all lesions together and ignores intra-patient heterogeneity. Here, we used a rich dataset of 342 metastatic bladder cancer patients treated with a novel immunotherapy agent to develop a Bayesian multilevel joint model that can quantify heterogeneity in lesion dynamics and measure their impact on survival. Using a nonlinear model of tumor growth inhibition, we estimated that dynamics differed greatly among lesions, and inter-lesion variability accounted for 21% and 28% of the total variance in tumor shrinkage and treatment effect duration, respectively. Next, we investigated the impact of individual lesion dynamics on survival. Lesions located in the liver and in the bladder had twice as much impact on the instantaneous risk of death compared to those located in the lung or the lymph nodes. Finally, we evaluated the utility of individual lesion follow-up for dynamic predictions. Consistent with results at the population level, the individual lesion model outperformed a model relying only on SLD, especially at early landmark times and in patients with liver or bladder target lesions. Our results show that an individual lesion model can characterize the heterogeneity in tumor dynamics and its impact on survival in advanced cancer patients.

Prognostic Value of Nivolumab Clearance in Non-Small Cell Lung Cancer Patients for Survival Early in Treatment

INTRODUCTION

Immune checkpoint inhibitors improved survival of advanced stage non-small cell lung cancer patients, but the overall response rate remains low. A biomarker that identifies non-responders would be helpful to allow treatment decisions. Clearance of immune checkpoint inhibitors is related to treatment response, but its prognostic potential early in treatment remains unknown. Our primary aim was to investigate the prognostic potential of nivolumab clearance for overall survival early in treatment. Our secondary aim was to evaluate the performance of nivolumab clearance as prognostic biomarker.

PATIENTS AND METHODS

Individual estimates of nivolumab clearances at first dose, 6 and 12 weeks after treatment initiation were obtained via nonlinear mixed-effects modelling. Prognostic value of nivolumab clearance was estimated using univariate Cox regression at first dose and for the ratios between 6 and 12 weeks to first dose. The performance of nivolumab clearance as biomarker was assessed by calculating sensitivity and specificity.

RESULTS

During follow-up of 75 months, 69 patients were included and 865 died. Patients with a nivolumab clearance ≥ 7.3 mL/h at first dose were more likely to die compared to patients with a nivolumab clearance < 7.3 mL/h at first dose (hazard ratio [HR] = 3.55, 955 CI 1.75-7.20). The HRs of dose nivolumab clearance ratios showed similar results with a HR of 3.93 (955 CI 1.66-9.32) for 6 weeks to first-dose clearance ratio at a 0.953 cut-point and a HR of 2.96 (955 CI 1.32-6.64) for 12 weeks to first-dose clearance ratio at a cut-point of 0.814. For nivolumab clearance at all early time points, sensitivity was high (≥ 0.95) but specificity was low (0.11-0.29).

CONCLUSION

Nivolumab clearance is indicative of survival early in treatment. Our results encourage to further assess the prognostic potential of immunotherapy clearance.

Recent Advances in the Field of Artificial Intelligence for Precision Medicine in Patients with a Diagnosis of Metastatic Cutaneous Melanoma

Standard-of-care medical imaging techniques such as CT, MRI, and PET play a critical role in managing patients diagnosed with metastatic cutaneous melanoma. Advancements in artificial intelligence (AI) techniques, such as radiomics, machine learning, and deep learning, could revolutionize the use of medical imaging by enhancing individualized image-guided precision medicine approaches. In the present article, we will decipher how AI/radiomics could mine information from medical images, such as tumor volume, heterogeneity, and shape, to provide insights into cancer biology that can be leveraged by clinicians to improve patient care both in the clinic and in clinical trials. More specifically, we will detail the potential role of AI in enhancing detection/diagnosis, staging, treatment planning, treatment delivery, response assessment, treatment toxicity assessment, and monitoring of patients diagnosed with metastatic cutaneous melanoma. Finally, we will explore how these proof-of-concept results can be translated from bench to bedside by describing how the implementation of AI techniques can be standardized for routine adoption in clinical settings worldwide to predict outcomes with great accuracy, reproducibility, and generalizability in patients diagnosed with metastatic cutaneous melanoma.

Prognostic value of MRI volumetric parameters in non-small cell lung cancer patients after immune checkpoint inhibitor therapy: comparison with response assessment criteria

BACKGROUND

Accurate response parameters are important for patients with brain metastasis (BM) undergoing clinical trials using immunotherapy, considering poorly defined enhancement and variable responses. This study investigated MRI-based surrogate endpoints for patients with BM receiving immunotherapy.

METHODS

Sixty-three non-small cell lung cancer patients with BM who received immune checkpoint inhibitors and underwent MRI were included. Tumor diameters were measured using a modification of the RECIST 1.1 (mRECIST), RANO-BM, and iRANO adjusted for BM (iRANO-BM). Tumor volumes were segmented on 3D contrast-enhanced T1-weighted imaging. Differences between the sum of the longest diameter (SLD) or total tumor volume at baseline and the corresponding measurement at time of the best overall response were calculated as "changes in SLDs" (for each set of criteria) and "change in volumetry," respectively. Overall response rate (ORR), progressive disease (PD) assignment, and progression-free survival (PFS) were compared among the criteria. The prediction of overall survival (OS) was compared between diameter-based and volumetric change using Cox proportional hazards regression analysis.

RESULTS

The mRECIST showed higher ORR (30.1% vs. both 17.5%) and PD assignment (34.9% vs. 25.4% [RANO-BM] and 19% [iRANO-BM]). The iRANO-BM had a longer median PFS (13.7 months) than RANO-BM (9.53 months) and mRECIST (7.73 months, P = 0.003). The change in volumetry was a significant predictor of OS (HR = 5.87, 95% CI: 1.46-23.64, P = 0.013). None of the changes in SLDs, as determined by RANO-BM or iRANO-BM, were significant predictors of OS, except for the mRECIST, which exhibited a weak association with OS.

CONCLUSION

Quantitative volume measurement may be an accurate surrogate endpoint for OS in patients with BM undergoing immunotherapy, especially considering the challenges of multiplicity and the heterogeneity of sub-centimeter size responses.

Can we predict discordant RECIST 1.1 evaluations in double read clinical trials?

Background

In lung clinical trials with imaging, blinded independent central review with double reads is recommended to reduce evaluation bias and the Response Evaluation Criteria In Solid Tumor (RECIST) is still widely used. We retrospectively analyzed the inter-reader discrepancies rate over time, the risk factors for discrepancies related to baseline evaluations, and the potential of machine learning to predict inter-reader discrepancies.

Materials and methods

We retrospectively analyzed five BICR clinical trials for patients on immunotherapy or targeted therapy for lung cancer. Double reads of 1724 patients involving 17 radiologists were performed using RECIST 1.1. We evaluated the rate of discrepancies over time according to four endpoints: progressive disease declared (PDD), date of progressive disease (DOPD), best overall response (BOR), and date of the first response (DOFR). Risk factors associated with discrepancies were analyzed, two predictive models were evaluated.

Results

At the end of trials, the discrepancy rates between trials were not different. On average, the discrepancy rates were 21.0%, 41.0%, 28.8%, and 48.8% for PDD, DOPD, BOR, and DOFR, respectively. Over time, the discrepancy rate was higher for DOFR than DOPD, and the rates increased as the trial progressed, even after accrual was completed. It was rare for readers to not find any disease, for less than 7% of patients, at least one reader selected non-measurable disease only (NTL). Often the readers selected some of their target lesions (TLs) and NTLs in different organs, with ranges of 36.0-57.9% and 60.5-73.5% of patients, respectively. Rarely (4-8.1%) two readers selected all their TLs in different locations. Significant risk factors were different depending on the endpoint and the trial being considered. Prediction had a poor performance but the positive predictive value was higher than 80%. The best classification was obtained with BOR.

Conclusion

Predicting discordance rates necessitates having knowledge of patient accrual, patient survival, and the probability of discordances over time. In lung cancer trials, although risk factors for inter-reader discrepancies are known, they are weakly significant, the ability to predict discrepancies from baseline data is limited. To boost prediction accuracy, it would be necessary to enhance baseline-derived features or create new ones, considering other risk factors and looking into optimal reader associations.

Response heterogeneity as a new biomarker of treatment response in patients with neuroendocrine tumors

Aim: The RAISE project aimed to find a surrogate end point to predict treatment response early in patients with enteropancreatic neuroendocrine tumors (NET). Response heterogeneity, defined as the coexistence of responding and non-responding lesions, has been proposed as a predictive marker for progression-free survival (PFS) in patients with NETs. Patients & methods: Computerized tomography scans were analyzed from patients with multiple lesions in CLARINET (NCT00353496; n = 148/204). Cox regression analyses evaluated association between response heterogeneity, estimated using the standard deviation of the longest diameter ratio of target lesions, and NET progression. Results: Greater response heterogeneity at a given visit was associated with earlier progression thereafter: week 12 hazard ratio (HR; 95% confidence interval): 1.48 (1.20-1.82); p < 0.001; n = 148; week 36: 1.72 (1.32-2.24); p < 0.001; n = 108. HRs controlled for sum of longest diameter ratio: week 12: 1.28 (1.04-1.59); p = 0.020 and week 36: 1.81 (1.20-2.72); p = 0.005. Conclusion: Response heterogeneity independently predicts PFS in patients with enteropancreatic NETs. Further validation is required.

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.

Performance of an automated registration-based method for longitudinal lesion matching and comparison to inter-reader variability

Objective.Patients with metastatic disease are followed throughout treatment with medical imaging, and accurately assessing changes of individual lesions is critical to properly inform clinical decisions. The goal of this work was to assess the performance of an automated lesion-matching algorithm in comparison to inter-reader variability (IRV) of matching lesions between scans of metastatic cancer patients.Approach.Forty pairs of longitudinal PET/CT and CT scans were collected and organized into four cohorts: lung cancers, head and neck cancers, lymphomas, and advanced cancers. Cases were also divided by cancer burden: low-burden (<10 lesions), intermediate-burden (10-29), and high-burden (30+). Two nuclear medicine physicians conducted independent reviews of each scan-pair and manually matched lesions. Matching differences between readers were assessed to quantify the IRV of lesion matching. The two readers met to form a consensus, which was considered a gold standard and compared against the output of an automated lesion-matching algorithm. IRV and performance of the automated method were quantified using precision, recall, F1-score, and the number of differences.Main results.The performance of the automated method did not differ significantly from IRV for any metric in any cohort (p> 0.05, Wilcoxon paired test). In high-burden cases, the F1-score (median [range]) was 0.89 [0.63, 1.00] between the automated method and reader consensus and 0.93 [0.72, 1.00] between readers. In low-burden cases, F1-scores were 1.00 [0.40, 1.00] and 1.00 [0.40, 1.00], for the automated method and IRV, respectively. Automated matching was significantly more efficient than either reader (p< 0.001). In high-burden cases, median matching time for the readers was 60 and 30 min, respectively, while automated matching took a median of 3.9 minSignificance.The automated lesion-matching algorithm was successful in performing lesion matching, meeting the benchmark of IRV. Automated lesion matching can significantly expedite and improve the consistency of longitudinal lesion-matching.

Dissociated response to PD-1 inhibitors combined with radiotherapy in patients with advanced metastatic solid tumors: a single-center experience

BACKGROUND

Anti-programmed death 1/anti-programmed death ligand 1 (PD-1/PD-L1) combined with radiotherapy (RT) has a synergistic effect on systemic tumor control. A dissociated response (DR), characterized by some lesions shrinking and others growing, has been recognized with immune checkpoint inhibitor (ICI) monotherapy or combination therapy. The objective of this study was to assess the frequency and clinical benefit of DR in patients with advanced metastatic solid tumors receiving PD-1 inhibitors in combination with RT.

METHODS

We conducted a single-center retrospective analysis of patients with advanced metastatic solid tumors receiving PD-1 inhibitor combined with RT at the Department of Radiotherapy & Oncology, The Second People's Hospital Affiliated with Soochow University. Treatment response was assessed for each measurable lesion according to the Response Evaluation Criteria in Solid Tumours ( RECIST) v 1.1 guidelines. Patterns of response are divided into four groups: (1) DR, (2) uniform response, (3) uniform progression, and (4) only stable lesions. The overall survival (OS) of different groups was compared using Kaplan-Meier methods and log-rank tests.

RESULTS

Between March 2019 and July 2022, 93 patients were included. The median follow-up was 10.5 months (95% CI 8.8-12.1). The most common tumor types were lung cancer (19.8%), colorectal adenocarcinoma (17.2%), and esophageal cancer (10.8%). DR was observed in 22 (23.7%) patients. The uniform progression and DR are two different patterns of progression. After confirming progression, the overall survival of patients with DR was significantly longer than that of patients with uniform progression (9.9 months (95%CI 5.7-14.1) vs. 4.2 months (95%CI 1.9-6.5), P = 0.028). Compared with DR patients who did not continue PD-1 inhibitor combined with RT or PD-1 inhibitor monotherapy (n = 12), DR patients who continued treatment (n = 10) had significantly longer OS (15.7 (95%CI 3.5-27.9) vs 8.2 (95%CI 5.6-10.8) months, P = 0.035).

CONCLUSIONS

DR is not uncommon (23.7%) in patients with advanced metastatic solid tumors treated with PD-1 inhibitors combined with RT and shows a relatively favorable prognosis. Some patients with DR may benefit from continued PD-1 inhibitor therapy in combination with RT or PD-1 inhibitor monotherapy and may have longer OS.

Semiautomated Pipeline to Quantify Tumor Evolution From Real-World Positron Emission Tomography/Computed Tomography Imaging

PURPOSE

A semiautomated pipeline for the collection and curation of free-text and imaging real-world data (RWD) was developed to quantify cancer treatment outcomes in large-scale retrospective real-world studies. The objectives of this article are to illustrate the challenges of RWD extraction, to demonstrate approaches for quality assurance, and to showcase the potential of RWD for precision oncology.

METHODS

We collected data from patients with advanced melanoma receiving immune checkpoint inhibitors at the Lausanne University Hospital. Cohort selection relied on semantically annotated electronic health records and was validated using process mining. The selected imaging examinations were segmented using an automatic commercial software prototype. A postprocessing algorithm enabled longitudinal lesion identification across imaging time points and consensus malignancy status prediction. Resulting data quality was evaluated against expert-annotated ground-truth and clinical outcomes obtained from radiology reports.

RESULTS

The cohort included 108 patients with melanoma and 465 imaging examinations (median, 3; range, 1-15 per patient). Process mining was used to assess clinical data quality and revealed the diversity of care pathways encountered in a real-world setting. Longitudinal postprocessing greatly improved the consistency of image-derived data compared with single time point segmentation results (classification precision increased from 53% to 86%). Image-derived progression-free survival resulting from postprocessing was comparable with the manually curated clinical reference (median survival of 286 v 336 days, P = .89).

CONCLUSION

We presented a general pipeline for the collection and curation of text- and image-based RWD, together with specific strategies to improve reliability. We showed that the resulting disease progression measures match reference clinical assessments at the cohort level, indicating that this strategy has the potential to unlock large amounts of actionable retrospective real-world evidence from clinical records.

Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?

Background

In clinical trials with imaging, Blinded Independent Central Review (BICR) with double reads ensures data blinding and reduces bias in drug evaluations. As double reads can cause discrepancies, evaluations require close monitoring which substantially increases clinical trial costs. We sought to document the variability of double reads at baseline, and variabilities across individual readers and lung trials.

Material and methods

We retrospectively analyzed data from five BICR clinical trials evaluating 1720 lung cancer patients treated with immunotherapy or targeted therapy. Fifteen radiologists were involved. The variability was analyzed using a set of 71 features derived from tumor selection, measurements, and disease location. We selected a subset of readers that evaluated ≥50 patients in ≥two trials, to compare individual reader’s selections. Finally, we evaluated inter-trial homogeneity using a subset of patients for whom both readers assessed the exact same disease locations. Significance level was 0.05. Multiple pair-wise comparisons of continuous variables and proportions were performed using one-way ANOVA and Marascuilo procedure, respectively.

Results

Across trials, on average per patient, target lesion (TL) number ranged 1.9 to 3.0, sum of tumor diameter (SOD) 57.1 to 91.9 mm. MeanSOD=83.7 mm. In four trials, MeanSOD of double reads was significantly different. Less than 10% of patients had TLs selected in completely different organs and 43.5% had at least one selected in different organs. Discrepancies in disease locations happened mainly in lymph nodes (20.1%) and bones (12.2%). Discrepancies in measurable disease happened mainly in lung (19.6%). Between individual readers, the MeanSOD and disease selection were significantly different (p&lt;0.001). In inter-trials comparisons, on average per patient, the number of selected TLs ranged 2.1 to 2.8, MeanSOD 61.0 to 92.4 mm. Trials were significantly different in MeanSOD (p&lt;0.0001) and average number of selected TLs (p=0.007). The proportion of patients having one of the top diseases was significantly different only between two trials for lung. Significant differences were observed for all other disease locations (p&lt;0.05).

Conclusions

We found significant double read variabilities at baseline, evidence of reading patterns and a means to compare trials. Clinical trial reliability is influenced by the interplay of readers, patients and trial design.

[18F]FDG PET/CT in the Evaluation of Melanoma Patients Treated with Immunotherapy

Immunotherapy is based on manipulation of the immune system in order to act against tumour cells, with growing evidence especially in melanoma patients. The challenges faced by this new therapeutic tool are (i) finding valid evaluation criteria for response assessment; (ii) knowing and distinguishing between "atypical" response patterns; (iii) using PET biomarkers as predictive and response evaluation parameters and (iv) diagnosis and management of immunorelated adverse effects. This review is focused on melanoma patients analysing (a) the role of [18F]FDG PET/CT in the mentioned challenges; (b) the evidence of its efficacy. For this purpose, we performed a review of the literature, including original and review articles. In summary, although there are no clearly established or globally accepted criteria, modified response criteria are potentially appropriate for evaluation of immunotherapy benefit. In this context, [18F]FDG PET/CT biomarkers appear to be promising parameters in prediction and assessment of response to immunotherapy. Moreover, immunorelated adverse effects are recognized as predictors of early response to immunotherapy and may be associated with better prognosis and clinical benefit.

The radiological appearances of lung cancer treated with immunotherapy

Therapy and prognosis of several solid and hematologic malignancies, including non-small cell lung cancer (NSCLC), have been favourably impacted by the introduction of immune checkpoint inhibitors (ICIs). Their mechanism of action relies on the principle that some cancers can evade immune surveillance by expressing surface inhibitor molecules, known as "immune checkpoints". ICIs aim to conceal tumoural checkpoints on the cell surface and reinvigorate the ability of the host immune system to recognize tumour cells, triggering an antitumoural immune response.In this review, we will focus on the imaging patterns of different responses occurring in patients treated by ICIs. We will also discuss imaging findings of immune-related adverse events (irAEs), along with current and future perspectives of metabolic imaging. Finally, we will explore the role of radiomics in the setting of ICI-treated patients.

Assessing the Increased Variability in Individual Lesion Kinetics During Immunotherapy: Does It Exist, and Does It Matter?

PURPOSE

Several studies have raised the hypothesis that immunotherapy may exacerbate the variability in individual lesions, increasing the risk of observing divergent kinetic profiles within the same patient. This questions the use of the sum of the longest diameter to follow the response to immunotherapy. Here, we aimed to study this hypothesis by developing a model that estimates the different sources of variability in lesion kinetics, and we used this model to evaluate the impact of this variability on survival.

METHODS

We relied on a semimechanistic model to follow the nonlinear kinetics of lesions and their impact on the risk of death, adjusted on organ location. The model incorporated two levels of random effects to characterize both between- and within-patient variability in response to treatment. The model was estimated on 900 patients from a phase III randomized trial evaluating programmed death-ligand 1 checkpoint inhibitor atezolizumab versus chemotherapy in patients with second-line metastatic urothelial carcinoma (IMvigor211).

RESULTS

The within-patient variability in the four parameters that characterize individual lesion kinetics represented between 12% and 78% of the total variability during chemotherapy. Similar results were obtained during atezolizumab, except for the durability of the treatment effects, for which the within-patient variability was markedly larger than during chemotherapy (40% v 12%, respectively). Accordingly, the occurrence of divergent profile consistently increased over time in patients treated with atezolizumab and was equal to about 20% after 1 year of treatment. Finally, we show that accounting for the within-patient variability provided a better prediction of most at-risk patients than a model relying solely on the sum of the longest diameter.

CONCLUSION

Within-patient variability provides valuable information for the assessment of treatment efficacy and the detection of at-risk patients.

Emerging and Evolving Concepts in Cancer Immunotherapy Imaging

Criteria based on measurements of lesion diameter at CT have guided treatment with historical therapies due to the strong association between tumor size and survival. Clinical experience with immune checkpoint modulators shows that editing immune system function can be effective in various solid tumors. Equally, novel immune-related phenomena accompany this novel therapeutic paradigm. These effects of immunotherapy challenge the association of tumor size with response or progression and include risks and adverse events that present new demands for imaging to guide treatment decisions. Emerging and evolving approaches to immunotherapy highlight further key issues for imaging evaluation, such as dissociated response following local administration of immune checkpoint modulators, pseudoprogression due to immune infiltration in the tumor environment, and premature death due to hyperprogression. Research that may offer tools for radiologists to meet these challenges is reviewed. Different modalities are discussed, including immuno-PET, as well as new applications of CT, MRI, and fluorodeoxyglucose PET, such as radiomics and imaging of hematopoietic tissues or anthropometric characteristics. Multilevel integration of imaging and other biomarkers may improve clinical guidance for immunotherapies and provide theranostic opportunities.

Tumor response assessment on imaging following immunotherapy

In recent years, various systemic immunotherapies have been developed for cancer treatment, such as monoclonal antibodies (mABs) directed against immune checkpoints (immune checkpoint inhibitors, ICIs), oncolytic viruses, cytokines, cancer vaccines, and adoptive cell transfer. While being estimated to be eligible in 38.5% of patients with metastatic solid or hematological tumors, ICIs, in particular, demonstrate durable disease control across many oncologic diseases (e.g., in melanoma, lung, bladder, renal, head, and neck cancers) and overall survival benefits. Due to their unique mechanisms of action based on T-cell activation, response to immunotherapies is characterized by different patterns, such as progression prior to treatment response (pseudoprogression), hyperprogression, and dissociated responses following treatment. Because these features are not encountered in the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), which is the standard for response assessment in oncology, new criteria were defined for immunotherapies. The most important changes in these new morphologic criteria are, firstly, the requirement for confirmatory imaging examinations in case of progression, and secondly, the appearance of new lesions is not necessarily considered a progressive disease. Until today, five morphologic (immune-related response criteria (irRC), immune-related RECIST (irRECIST), immune RECIST (iRECIST), immune-modified RECIST (imRECIST), and intra-tumoral RECIST (itRECIST)) criteria have been developed to accurately assess changes in target lesion sizes, taking into account the specific response patterns after immunotherapy. In addition to morphologic response criteria, 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG-PET/CT) is a promising option for metabolic response assessment and four metabolic criteria are used (PET/CT Criteria for Early Prediction of Response to Immune Checkpoint Inhibitor Therapy (PECRIT), PET Response Evaluation Criteria for Immunotherapy (PERCIMT), immunotherapy-modified PET Response Criteria in Solid Tumors (imPERCIST5), and immune PERCIST (iPERCIST)). Besides, there is evidence that parameters on 18F-FDG-PET/CT, such as the standardized uptake value (SUV)max and several radiotracers, e.g., directed against PD-L1, may be potential imaging biomarkers of response. Moreover, the emerge of human intratumoral immunotherapy (HIT-IT), characterized by the direct injection of immunostimulatory agents into a tumor lesion, has given new importance to imaging assessment. This article reviews the specific imaging patterns of tumor response and progression and available imaging response criteria following immunotherapy.

Circulating Tumor DNA Monitoring Reveals Molecular Progression before Radiologic Progression in a Real-life Cohort of Patients with Advanced Non-small Cell Lung Cancer

PURPOSE

The clinical potential of liquid biopsy in patients with advanced cancer is real-time monitoring for early detection of treatment failure. Our study aimed to investigate the clinical validity of circulating tumor DNA (ctDNA) treatment monitoring in a real-life cohort of patients with advanced non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

Patients with advanced or noncurative locally advanced NSCLC were prospectively included in an exploratory study (NCT03512847). Selected cancer-specific mutations were measured in plasma by standard or uniquely designed droplet digital PCR assays before every treatment cycle during first-line treatment until progressive disease (PD). Correlation between an increase in ctDNA (= molecular progression) and radiologic PD was investigated, defined as lead time, and the corresponding numbers of likely futile treatment cycles were determined. Utility of ctDNA measurements in clarifying the results of nonconclusive radiologic evaluation scans was evaluated.

RESULTS

Cancer-specific mutations and longitudinal plasma sampling were present in 132 of 150 patients. ctDNA was detectable in 88 (67%) of 132 patients treated by respectively chemotherapy (n = 41), immunotherapy (n = 43), or combination treatment (n = 4). In 66 (90%) of 73 patients experiencing PD, a ctDNA increase was observed with a median lead time of 1.5 months before radiologic PD. Overall, 119 (33%) of 365 treatment cycles were administered after molecular progression. In addition, ctDNA measurements could clarify the results in 38 (79%) of 48 nonconclusive radiologic evaluations.

CONCLUSIONS

ctDNA monitoring leads to earlier detection of treatment failure, and clarifies the majority of nonconclusive radiologic evaluations, giving the potential of sparing patients from likely futile treatments and needless adverse events.

SIGNIFICANCE

Treatment monitoring by ctDNA has the clinical potential to reveal PD before radiologic evaluation and consequently spare patients with advanced cancer from likely ineffective, costly cancer treatments and adverse events.

Differences and Similarities in the Pattern of Early Metabolic and Morphologic Response after Induction Chemo-Immunotherapy versus Induction Chemotherapy Alone in Locally Advanced Squamous Cell Head and Neck Cancer

Background: In head and neck cancer patients, parameters of metabolic and morphologic response of the tumor to single-cycle induction chemotherapy (IC) with docetaxel, cis- or carboplatin are used to decide the further course of treatment. This study investigated the effect of adding a double immune checkpoint blockade (DICB) of tremelimumab and durvalumab to IC on imaging parameters and their significance with regard to tumor cell remission. Methods: Response variables of 53 patients treated with IC+DICB (ICIT) were compared with those of 104 who received IC alone. Three weeks after one cycle, pathologic and, in some cases, clinical and endoscopic primary tumor responses were evaluated and correlated with a change in 18F-FDG PET and CT/MRI-based maximum-standardized uptake values (SUVmax) before (SUVmaxpre), after treatment (SUVmaxpost) and residually (resSUVmax in % of SUVmaxpre), and in maximum tumor diameter (Dmax) before (Dmaxpre) and after treatment (Dmaxpost) and residually (resD). Results: Reduction of SUVmax and Dmax occurred in both groups; values were SUVmaxpre: 14.4, SUVmaxpost: 6.6, Dmaxpre: 30 mm and Dmaxpost: 23 mm for ICIT versus SUVmaxpre: 16.5, SUVmaxpost: 6.4, Dmaxpre: 21 mm, and Dmaxpost: 16 mm for IC alone (all p < 0.05). ResSUVmax was the best predictor of complete response (IC: AUC: 0.77; ICIT: AUC: 0.76). Metabolic responders with resSUVmax ≤ 40% tended to have a higher rate of CR to ICIT (88%; n = 15/17) than to IC (65%; n = 30/46; p = 0.11). Of the metabolic nonresponders (resSUVmax > 80%), 33% (n = 5/15) achieved a clinical CR to ICIT versus 6% (n = 1/15) to IC (p = 0.01). Conclusions: ICIT and IC quickly induce a response and 18F-FDG PET is the more accurate modality for identifying complete remission. The rate of discrepant response, i.e., pCR with metabolic nonresponse after ICIT was >30%.

What is the optimal duration of immune checkpoint inhibitors in malignant tumors?

Immunotherapy, represented by immune checkpoint inhibitors (ICIs), has made a revolutionary difference in the treatment of malignant tumors, and considerably extended patients' overall survival (OS). In the world medical profession, however, there still reaches no clear consensus on the optimal duration of ICIs therapy. As reported, immunotherapy response patterns, immune-related adverse events (irAEs) and tumor stages are all related to the diversity of ICIs duration in previous researches. Besides, there lacks clear clinical guidance on the intermittent or continuous use of ICIs. This review aims to discuss the optimal duration of ICIs, hoping to help guide clinical work based on the literature.

Cancer Immunoediting in the Era of Immuno-oncology

Basic science breakthroughs in T-cell biology and immune-tumor cell interactions ushered in a new era of cancer immunotherapy. Twenty years ago, cancer immunoediting was proposed as a framework to understand the dynamic process by which the immune system can both control and shape cancer and in its most complex form occurs through three phases termed elimination, equilibrium, and escape. During cancer progression through these phases, tumors undergo immunoediting, rendering them less immunogenic and more capable of establishing an immunosuppressive microenvironment. Therefore, cancer immunoediting integrates the complex immune-tumor cell interactions occurring in the tumor microenvironment and sculpts immunogenicity beyond shaping antigenicity. However, with the success of cancer immunotherapy resulting in durable clinical responses in the last decade and subsequent emergence of immuno-oncology as a clinical subspecialty, the phrase "cancer immunoediting" has recently, at times, been inappropriately restricted to describing neoantigen loss by immunoselection. This focus has obscured other mechanisms by which cancer immunoediting modifies tumor immunogenicity. Although establishment of the concept of cancer immunoediting and definitive experimental evidence supporting its existence was initially obtained from preclinical models in the absence of immunotherapy, cancer immunoediting is a continual process that also occurs during immunotherapy in human patients with cancer. Herein, we discuss the known mechanisms of cancer immunoediting obtained from preclinical and clinical data with an emphasis on how a greater understanding of cancer immunoediting may provide insights into immunotherapy resistance and how this resistance can be overcome.

Dissociated response among multiple metastatic lesions in the patients with metastatic renal cell carcinoma treated with immune checkpoint inhibitors

INTRODUCTION

Metastases from renal cell carcinoma develop in various organs. However, the breadth of discrepancy in response to immune checkpoint inhibitors across tumor sites within the same individual remains unclear.

PATIENTS AND METHODS

We reviewed 50 patients with metastatic renal cell carcinoma who had target lesions at multiple sites and received nivolumab monotherapy (n = 36) or nivolumab plus ipilimumab (n = 14). When the best overall response in tumor burden increased at one site but decreased at other sites, the response was defined as a dissociated response. The response was evaluated according to the Response Evaluation Criteria in Solid Tumors 1.1, and patients who met the definition of dissociated response were categorized as dissociated response. The rate of dissociated response and prognosis were evaluated.

RESULTS

Eight of 36 (22%) and 4 of 14 (29%) patients treated with nivolumab and nivolumab plus ipilimumab were categorized as having dissociated response, respectively. The median overall survival of the patients treated with nivolumab was 20.2 months for those with a partial response, 6.8 months for those with stable disease, and 13.2 months for those with progressive disease, while dissociated response was not reached. There was no significant difference in the median overall survival between patients categorized as having progressive disease and those with dissociates response (P = 0.224).

CONCLUSION

A certain proportion of patients with metastatic renal cell carcinoma show dissociated response when treated with immune checkpoint inhibitors. The prognosis of patients with dissociated response and progressive disease was not shown to be significantly different.

MALDI-MSI: A Powerful Approach to Understand Primary Pancreatic Ductal Adenocarcinoma and Metastases

Cancer-related deaths are very commonly attributed to complications from metastases to neighboring as well as distant organs. Dissociate response in the treatment of pancreatic adenocarcinoma is one of the main causes of low treatment success and low survival rates. This behavior could not be explained by transcriptomics or genomics; however, differences in the composition at the protein level could be observed. We have characterized the proteomic composition of primary pancreatic adenocarcinoma and distant metastasis directly in human tissue samples, utilizing mass spectrometry imaging. The mass spectrometry data was used to train and validate machine learning models that could distinguish both tissue entities with an accuracy above 90%. Model validation on samples from another collection yielded a correct classification of both entities. Tentative identification of the discriminative molecular features showed that collagen fragments (COL1A1, COL1A2, and COL3A1) play a fundamental role in tumor development. From the analysis of the receiver operating characteristic, we could further advance some potential targets, such as histone and histone variations, that could provide a better understanding of tumor development, and consequently, more effective treatments.

Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [18F]F-FDG PET/CT Radiomic Features for Metabolic Response Prediction of Metastatic Breast Cancer Lesions

Simple Summary

Breast cancer is a leading cause of morbidity and mortality worldwide. The metastatic disease is largely responsible for cancer patient deaths, and its treatment implies usually different therapies. In this context, the prediction of response to treatment or depiction of treatment-resistant phenotypes is essential in clinical practice, especially in the new era of precision medicine. In this study, we used several combinations of feature selection methods and machine-learning classifiers to construct predictive models of the metabolic response to the treatment of metastatic breast cancer lesions. These models were based on clinical variables and radiomic features extracted from 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography/computed tomography ([¹⁸F]F-FDG PET/CT) images, obtained prior to the treatment. Our main goal was to know if this prediction was feasible and to identify those combinations with better predictive performance. We found that several combinations were successful to predict the metabolic response to treatment, of which the least absolute shrinkage and selection operator (Lasso) + support vector machines (SVM) had the best mean performance in terms of area under the curve, in both training and validation cohorts. Model performances depended largely on the selected combinations.

Abstract

Background: This study aimed to identify optimal combinations between feature selection methods and machine-learning classifiers for predicting the metabolic response of individual metastatic breast cancer lesions, based on clinical variables and radiomic features extracted from pretreatment [¹⁸F]F-FDG PET/CT images. Methods: A total of 48 patients with confirmed metastatic breast cancer, who received different treatments, were included. All patients had an [¹⁸F]F-FDG PET/CT scan before and after the treatment. From 228 metastatic lesions identified, 127 were categorized as responders (complete or partial metabolic response) and 101 as non-responders (stable or progressive metabolic response), by using the percentage changes in SULpeak (peak standardized uptake values normalized for body lean body mass). The lesion pool was divided into training (n = 182) and testing cohorts (n = 46); for each lesion, 101 image features from both PET and CT were extracted (202 features per lesion). These features, along with clinical and pathological information, allowed the prediction model’s construction by using seven popular feature selection methods in cross-combination with another seven machine-learning (ML) classifiers. The performance of the different models was investigated with the receiver-operating characteristic curve (ROC) analysis, using the area under the curve (AUC) and accuracy (ACC) metrics. Results: The combinations, least absolute shrinkage and selection operator (Lasso) + support vector machines (SVM), or random forest (RF) had the highest AUC in the cross-validation, with 0.93 ± 0.06 and 0.92 ± 0.03, respectively, whereas Lasso + neural network (NN) or SVM, and mutual information (MI) + RF, had the higher AUC and ACC in the validation cohort, with 0.90/0.72, 0.86/0.76, and 87/85, respectively. On average, the models with Lasso and models with SVM had the best mean performance for both AUC and ACC in both training and validation cohorts. Conclusions: Image features obtained from a pretreatment [¹⁸F]F-FDG PET/CT along with clinical vaiables could predict the metabolic response of metastatic breast cancer lesions, by their incorporation into predictive models, whose performance depends on the selected combination between feature selection and ML classifier methods.

Joint EANM/SNMMI/ANZSNM practice guidelines/procedure standards on recommended use of [18F]FDG PET/CT imaging during immunomodulatory treatments in patients with solid tumors version 1.0

PURPOSE

The goal of this guideline/procedure standard is to assist nuclear medicine physicians, other nuclear medicine professionals, oncologists or other medical specialists for recommended use of [18F]FDG PET/CT in oncological patients undergoing immunotherapy, with special focus on response assessment in solid tumors.

METHODS

In a cooperative effort between the EANM, the SNMMI and the ANZSNM, clinical indications, recommended imaging procedures and reporting standards have been agreed upon and summarized in this joint guideline/procedure standard.

CONCLUSIONS

The field of immuno-oncology is rapidly evolving, and this guideline/procedure standard should not be seen as definitive, but rather as a guidance document standardizing the use and interpretation of [18F]FDG PET/CT during immunotherapy. Local variations to this guideline should be taken into consideration.

PREAMBLE

The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association founded in 1985 to facilitate worldwide communication among individuals pursuing clinical and academic excellence in nuclear medicine. The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote science, technology and practical application of nuclear medicine. The Australian and New Zealand Society of Nuclear Medicine (ANZSNM), founded in 1969, represents the major professional society fostering the technical and professional development of nuclear medicine practice across Australia and New Zealand. It promotes excellence in the nuclear medicine profession through education, research and a commitment to the highest professional standards. EANM, SNMMI and ANZSNM members are physicians, technologists, physicists and scientists specialized in the research and clinical practice of nuclear medicine. All three societies will periodically put forth new standards/guidelines for nuclear medicine practice to help advance the science of nuclear medicine and improve service to patients. Existing standards/guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each standard/guideline, representing a policy statement by the EANM/SNMMI/ANZSNM, has undergone a thorough consensus process, entailing extensive review. These societies recognize that the safe and effective use of diagnostic nuclear medicine imaging requires particular training and skills, as described in each document. These standards/guidelines are educational tools designed to assist practitioners in providing appropriate and effective nuclear medicine care for patients. These guidelines are consensus documents based on current knowledge. They are not intended to be inflexible rules or requirements of practice, nor should they be used to establish a legal standard of care. For these reasons and those set forth below, the EANM, SNMMI and ANZSNM caution against the use of these standards/guidelines in litigation in which the clinical decisions of a practitioner are called into question. The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by medical professionals considering the unique circumstances of each case. Thus, there is no implication that an action differing from what is laid out in the guidelines/procedure standards, standing alone, is below standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the standards/guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources or advances in knowledge or technology subsequent to publication of the guidelines/procedure standards. The practice of medicine involves not only the science, but also the art of dealing with the prevention, diagnosis, alleviation and treatment of disease. The variety and complexity of human conditions make it impossible for general guidelines to consistently allow for an accurate diagnosis to be reached or a particular treatment response to be predicted. Therefore, it should be recognized that adherence to these standards/ guidelines will not ensure a successful outcome. All that should be expected is that practitioners follow a reasonable course of action, based on their level of training, current knowledge, clinical practice guidelines, available resources and the needs/context of the patient being treated. The sole purpose of these guidelines is to assist practitioners in achieving this objective. The present guideline/procedure standard was developed collaboratively by the EANM, the SNMMI and the ANZSNM, with the support of international experts in the field. They summarize also the views of the Oncology and Theranostics and the Inflammation and Infection Committees of the EANM, as well as the procedure standards committee of the SNMMI, and reflect recommendations for which the EANM and SNMMI cannot be held responsible. The recommendations should be taken into the context of good practice of nuclear medicine and do not substitute for national and international legal or regulatory provisions.

Immune-related dissociated response as a specific atypical response pattern in solid tumors with immune checkpoint blockade

Immune checkpoint blockade using immune checkpoint inhibitors, including cytotoxic T-lymphocyte-associated antigen–4 and programmed cell death protein-1/programmed cell death ligand–1 inhibitors, has revolutionized systematic treatment for advanced solid tumors, with unprecedented survival benefit and tolerable toxicity. Nivolumab, pembrolizumab, cemiplimab, avelumab, durvalumab, atezolizumab, and ipilimumab are currently approved standard treatment options for various human cancer types. The response rate to immune checkpoint inhibitors, however, is unsatisfactory, and unexpectedly, atypical radiological responses, including delayed responses, pseudoprogression, hyperprogression, and dissociated responses (DRs), are observed in a small subgroup of patients. The benefit of immunotherapy for advanced patients who exhibit atypical responses is underestimated according to the conventional response evaluation criteria in solid tumors (RECIST). In particular, DR is considered a mixed radiological or heterogeneous response pattern when responding and nonresponding lesions or new lesions coexist simultaneously. The rate of DR reported in different studies encompass a wide range of 3.3–47.8% based on diverse definition of DR. Although DR is also associated with treatment efficacy and a favorable prognosis, it is different from pseudoprogression, which has concordant progressive lesions and can be regularly captured by immune RECIST. This review article aims to comprehensively determine the frequency, definition, radiological evaluation, probable molecular mechanisms, prognosis, and clinical management of immune-related DR and help clinicians and radiologists objectively and correctly interpret this specific atypical response and better understand and manage cancer patients with immunotherapy and guarantee their best clinical benefit.

Prognostic value of immunotherapy-induced organ inflammation assessed on 18FDG PET in patients with metastatic non-small cell lung cancer

PURPOSE

We evaluated the prognostic value of immunotherapy-induced organ inflammation observed on ¹⁸FDG PET in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs).

METHODS

Data from patients with IIIB/IV NSCLC included in two different prospective trials were analyzed. ¹⁸FDG PET/CT exams were performed at baseline (PET_Baseline) and repeated after 7-8 weeks (PET_Interim1) and 12-16 weeks (PET_Interim2) of treatment, using iPERCIST for tumor response evaluation. The occurrence of abnormal organ ¹⁸FDG uptake, deemed to be due to ICPI-related organ inflammation, was collected.

RESULTS

Exploratory cohort (Nice, France): PET_Interim1 and PET_Interim2 revealed the occurrence of at least one ICPI-induced organ inflammation in 72.8% of patients, including midgut/hindgut inflammation (33.7%), gastritis (21.7%), thyroiditis (18.5%), pneumonitis (17.4%), and other organ inflammations (9.8%). iPERCIST tumor response was associated with improved progression-free survival (p < 0.001). iPERCIST tumor response and immuno-induced gastritis assessed on PET were both associated with improved overall survival (OS) (p < 0.001 and p = 0.032). Combining these two independent variables, we built a model predicting patients' 2-year OS with a sensitivity of 80.3% and a specificity of 69.2% (AUC = 72.7). Validation cohort (Genova, Italy): Immuno-induced gastritis (19.6% of patients) was associated with improved OS (p = 0.04). The model built previously predicted 2-year OS with a sensitivity and specificity of 72.0% and 63.6% (AUC = 70.7) and 3-year OS with a sensitivity and specificity of 69.2% and 80.0% (AUC = 78.2).

CONCLUSION

Immuno-induced gastritis revealed by early interim ¹⁸FDG PET in around 20% of patients with NSCLC treated with ICPI is a novel and reproducible imaging biomarker of improved OS.

Real-time PACS-integrated longitudinal brain metastasis tracking tool provides comprehensive assessment of treatment response to radiosurgery

Background

Treatment of brain metastases can be tailored to individual lesions with treatments such as stereotactic radiosurgery. Accurate surveillance of lesions is a prerequisite but challenging in patients with multiple lesions and prior imaging studies, in a process that is laborious and time consuming. We aimed to longitudinally track several lesions using a PACS-integrated lesion tracking tool (LTT) to evaluate the efficiency of a PACS-integrated lesion tracking workflow, and characterize the prevalence of heterogenous response (HeR) to treatment after Gamma Knife (GK).

Methods

We selected a group of brain metastases patients treated with GK at our institution. We used a PACS-integrated LTT to track the treatment response of each lesion after first GK intervention to maximally seven diagnostic follow-up scans. We evaluated the efficiency of this tool by comparing the number of clicks necessary to complete this task with and without the tool and examined the prevalence of HeR in treatment.

Results

A cohort of eighty patients was selected and 494 lesions were measured and tracked longitudinally for a mean follow-up time of 374 days after first GK. Use of LTT significantly decreased number of necessary clicks. 81.7% of patients had HeR to treatment at the end of follow-up. The prevalence increased with increasing number of lesions.

Conclusions

Lesions in a single patient often differ in their response to treatment, highlighting the importance of individual lesion size assessments for further treatment planning. PACS-integrated lesion tracking enables efficient lesion surveillance workflow and specific and objective result reports to treating clinicians.

Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

Immunotherapy with checkpoint inhibitors has prompted a major change not only in cancer treatment but also in medical imaging. In parallel with the implementation of new drugs modulating the immune system, new response criteria have been developed, aiming to overcome clinical drawbacks related to the new, unusual, patterns of response characterizing both solid tumors and lymphoma during the course of immunotherapy. The acknowledgement of pseudo-progression, hyper-progression, immune-dissociated response and so forth, has become mandatory for all imagers dealing with this clinical scenario. A long list of acronyms, i.e., irRC, iRECIST, irRECIST, imRECIST, PECRIT, PERCIMT, imPERCIST, iPERCIST, depicts the enormous effort made by radiology and nuclear medicine physicians in the last decade to optimize imaging parameters for better prediction of clinical benefit in immunotherapy regimens. Quite frequently, a combination of clinical-laboratory data with imaging findings has been tested, proving the ability to stratify patients into various risk groups. The next steps necessarily require a large scale validation of the most robust criteria, as well as the clinical implementation of immune-targeting tracers for immuno-PET or the exploitation of radiomics and artificial intelligence as complementary tools during the course of immunotherapy administration. For the present review article, a summary of PET/CT role for immunotherapy monitoring will be provided. By scrolling into various cancer types and applied response criteria, the reader will obtain necessary information for better understanding the potentials and limitations of the modality in the clinical setting.

Imaging of Cancer Immunotherapy: Response Assessment Methods, Atypical Response Patterns, and Immune-Related Adverse Events, From the AJR Special Series on Imaging of Inflammation

The introduction of immunotherapy with immune-checkpoint inhibitors (ICIs) has revolutionized cancer treatment paradigms. Since the FDA approval of the first ICI in 2011, multiple additional ICIs have been approved and granted marketing authorization, and many promising agents are in early clinical adoption. Due to the distinctive biologic mechanisms of ICIs, the patterns of tumor response and progression differ for immunotherapy from those observed with cytotoxic chemotherapies. With increasing clinical adoption of immunotherapy, it is critical for radiologists to recognize different response patterns and common pitfalls to avoid misinterpretation of imaging studies or prompt premature cessation of potentially effective treatment. This article provides an overview of ICIs and their mechanisms of action and reviews the anatomic and metabolic immune-related response assessment methods, typical and atypical patterns of immunotherapy response (including pseudoprogression, hyper-progression, dissociated response, and durable response), and common imaging features of immune-related adverse events. Future multicenter trials are needed to validate the proposed immune-related response criteria and identify the functional imaging markers of early treatment response and survival.

Predictive value of 3'-deoxy-3'-18F-fluorothymidine PET in the early response to anti-programmed death-1 therapy in patients with advanced non-small cell lung cancer

Background

Anti-programmed death-1 (anti-PD-1) therapy has shown clinical success in patients with advanced non-small cell lung cancer (NSCLC). However, it is difficult to evaluate the early response to anti-PD-1 therapy. We determined whether changes in 3′-deoxy-3′-[¹⁸F]-fluorothymidine (¹⁸F-FLT) PET parameters before and soon after treatment initiation predicted the therapeutic effect of anti-PD-1 antibody.

Methods

Twenty-six patients with advanced NSCLC treated with anti-PD-1 antibody were enrolled prospectively and underwent ¹⁸F-FLT PET before and at 2 and 6 weeks after treatment initiation. Changes in maximal standardized uptake value (ΔSUV_max), proliferative tumor volume (ΔPTV) and total lesion proliferation (ΔTLP) of the lesions were calculated and evaluated for their associations with the clinical response to therapy.

Results

The disease control rate was 64%. Patients with non-progressive disease (non-PD) had significantly decreased TLP at 2 weeks, and decreased SUV_max, PTV, and TLP at 6 weeks, compared with those with PD, while three of eight (37.5%) patients who responded had increased TLP from baseline at 2 weeks (ie, pseudoprogression). Among the parameters that changed between baseline and 2 weeks, ΔPTV0-2 and ΔTLP0-2 had the highest accuracy (76.0%) to predict PD. Among the parameters that changed between baseline and 6 weeks, ΔSUV_max0-6, ΔPTV0-6 and ΔTLP0-6 had the highest accuracy (90.9%) to predict PD. ΔTLP0-2 (≥60%, HR 3.41, 95% CI 1.34–8.65, p=0.010) and ΔTLP0-6 (≥50%, HR 31.4, 95% CI 3.55 to 276.7, p=0.0019) were indicators of shorter progression-free survival.

Conclusions

Changes in ¹⁸F-FLT PET parameters may have value as an early predictive biomarker for the response to anti-PD-1 therapy in patients with NSCLC. However, it should be noted that pseudoprogression was observed in ¹⁸F-FLT PET imaging at 2 weeks after treatment initiation.

Trial registration number

jRCTs051180147.

FDG-PET/CT Variants and Pitfalls in Haematological Malignancies

Hematologic malignancies represent a vast group of hematopoietic and lymphoid cancers that typically involve the blood, the bone marrow, and the lymphatic organs. Due to extensive research and well defined and standardized response criteria, the role of [¹⁸F]FDG-PET/CT is well defined in these malignancies. Never the less, the reliability of visual and quantitative interpretation of PET/CT may be impaired by several factors including inconsistent scanning protocols and image reconstruction methods. Furthermore, the uptake of [¹⁸F]FDG not only reflects tissue glucose consumption by malignant lesions, but also in other situations such as in inflammatory lesions, local and systemic infections, benign tumors, reactive thymic hyperplasia, histiocytic infiltration, among others; or following granulocyte colony stimulating factors therapy, radiation therapy, chemotherapy or surgical interventions, all of which are a potential source of false-positive or negative interpretations. Therefore it is of paramount importance for the Nuclear Medicine Physician to be familiar with, not only the normal distribution of [¹⁸F]FDG in the body, but also with the most frequent findings that may hamper a correct interpretation of the scan, which could ultimately alter the patients management. In this review, we describe these myriad of situations so the interpreting physician can be familiar with them, providing tools for their correct identification and interpretation when possible.

Immune response evaluation criteria in solid tumors for assessment of atypical responses after immunotherapy

In 2017, immune response evaluation criteria in solid tumors (iRECIST) were introduced to validate radiologic and clinical interpretations and to better analyze tumor’s response to immunotherapy, considering the different time of following and response, between this new therapy compared to the standard one. However, even if the iRECIST are worldwide accepted, to date, different aspects should be better underlined and well reported, especially in clinical practice. Clinical experience has demonstrated that in a non-negligible percentage of patients, it is challenging to determine the correct category of response (stable disease, progression disease, partial or complete response), and consequently, to define which is the best management for those patients. Approaching radiological response in patients who underwent immunotherapy, a new uncommon kind of target lesions behavior was found. This phenomenon is mainly due to the different mechanisms of action of immunotherapeutic drug. Therefore, new groups of response have been described in clinical practice, defined as “atypical responses,” and categorized into three new groups: pseudoprogression, hyperprogression, and dissociated response. This review summarizes and reports these patterns, helping clinicians and radiologists get used to atypical responses, in order to identify patients that respond best to treatment.

Atypical Response Patterns in Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors-Navigating the Radiologic Potpourri

BACKGROUND

Atypical response patterns have been a topic of increasing relevance since the advent of immune checkpoint inhibitors (ICIs), challenging the traditional RECIST (Response Evaluation Criteria in Solid Tumors) method of tumor response assessment. Newer immune-related response criteria can allow for the evolution of radiologic pseudoprogression, but still fail to capture the full range of atypical response patterns encountered in clinical reporting.

METHODS

We did a detailed lesion-by-lesion analysis of the serial imaging of 46 renal cell carcinoma (RCC) patients treated with ICIs with the aim of capturing the full range of radiologic behaviour.

RESULTS

Atypical response patterns observed included pseudoprogression (n = 15; 32.6%), serial pseudoprogression (n = 4; 8.7%), dissociated response (n = 22; 47.8%), abscopal response (n = 9; 19.6%), late response (n = 5; 10.9%), and durable response after cessation of immunotherapy (n = 2; 4.3%). Twenty-four of 46 patients (52.2%) had at least one atypical response pattern and 18 patients (39.1%) had multiple atypical response patterns.

CONCLUSIONS

There is a high incidence of atypical response patterns in RCC patients receiving ICIs and the study contributes to the growing literature on the abscopal effect. The recognition of these interesting and overlapping radiologic patterns challenges the oncologist to tweak treatment options such that the clinical benefits of ICIs are potentially maximized.