Society for Immunotherapy of Cancer (SITC) recommendations on intratumoral immunotherapy clinical trials (IICT): from premalignant to metastatic disease.

BACKGROUND: Intratumorally delivered immunotherapies have the potential to favorably alter the local tumor microenvironment and may stimulate systemic host immunity, offering an alternative or adjunct to other local and systemic treatments. Despite their potential, these therapies have had limited success in late-phase trials for advanced cancer resulting in few formal approvals. The Society for Immunotherapy of Cancer (SITC) convened a panel of experts to determine how to design clinical trials with the greatest chance of demonstrating the benefits of intratumoral immunotherapy for patients with cancers across all stages of pathogenesis. METHODS: An Intratumoral Immunotherapy Clinical Trials Expert Panel composed of international key stakeholders from academia and industry was assembled. A multiple choice/free response survey was distributed to the panel, and the results of this survey were discussed during a half-day consensus meeting. Key discussion points are summarized in the following manuscript. RESULTS: The panel determined unique clinical trial designs tailored to different stages of cancer development-from premalignant to unresectable/metastatic-that can maximize the chance of capturing the effect of intratumoral immunotherapies. Design elements discussed included study type, patient stratification and exclusion criteria, indications of randomization, study arm determination, endpoints, biological sample collection, and response assessment with biomarkers and imaging. Populations to prioritize for the study of intratumoral immunotherapy, including stage, type of cancer and line of treatment, were also discussed along with common barriers to the development of these local treatments. CONCLUSIONS: The SITC Intratumoral Immunotherapy Clinical Trials Expert Panel has identified key considerations for the design and implementation of studies that have the greatest potential to capture the effect of intratumorally delivered immunotherapies. With more effective and standardized trial designs, the potential of intratumoral immunotherapy can be realized and lead to regulatory approvals that will extend the benefit of these local treatments to the patients who need them the most.

Early Readout on Overall Survival of Patients With Melanoma Treated With Immunotherapy Using a Novel Imaging Analysis.

IMPORTANCE: Existing criteria to estimate the benefit of a therapy in patients with cancer rely almost exclusively on tumor size, an approach that was not designed to estimate survival benefit and is challenged by the unique properties of immunotherapy. More accurate prediction of survival by treatment could enhance treatment decisions. OBJECTIVE: To validate, using radiomics and machine learning, the performance of a signature of quantitative computed tomography (CT) imaging features for estimating overall survival (OS) in patients with advanced melanoma treated with immunotherapy. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study used radiomics and machine learning to retrospectively analyze CT images obtained at baseline and first follow-up and their associated clinical metadata. Data were prospectively collected in the KEYNOTE-002 (Study of Pembrolizumab [MK-3475] Versus Chemotherapy in Participants With Advanced Melanoma; 2017 analysis) and KEYNOTE-006 (Study to Evaluate the Safety and Efficacy of Two Different Dosing Schedules of Pembrolizumab [MK-3475] Compared to Ipilimumab in Participants With Advanced Melanoma; 2016 analysis) multicenter clinical trials. Participants included 575 patients with a diagnosis of advanced melanoma who were randomly assigned to training and validation sets. Data for the present study were collected from November 20, 2012, to June 3, 2019, and analyzed from July 1, 2019, to September 15, 2021. INTERVENTIONS: KEYNOTE-002 featured trial groups testing intravenous pembrolizumab, 2 mg/kg or 10 mg/kg every 2 or every 3 weeks based on randomization, or investigator-choice chemotherapy; KEYNOTE-006 featured trial groups testing intravenous ipilimumab, 3 mg/kg every 3 weeks and intravenous pembrolizumab, 10 mg/kg every 2 or 3 weeks based on randomization. MAIN OUTCOMES AND MEASURES: The performance of the signature CT imaging features for estimating OS at the month 6 posttreatment landmark in patients who received pembrolizumab was measured using an area under the time-dependent receiver operating characteristics curve (AUC). RESULTS: A random forest model combined 25 imaging features extracted from tumors segmented on CT images to identify the combination (signature) that best estimated OS with pembrolizumab in 575 patients. The signature combined 4 imaging features, 2 related to tumor size and 2 reflecting changes in tumor imaging phenotype. In the validation set (287 patients treated with pembrolizumab), the signature reached an AUC for estimation of OS status of 0.92 (95% CI, 0.89-0.95). The standard method, Response Evaluation Criteria in Solid Tumors 1.1, achieved an AUC of 0.80 (95% CI, 0.75-0.84) and classified tumor outcomes as partial or complete response (93 of 287 [32.4%]), stable disease (90 of 287 [31.3%]), or progressive disease (104 of 287 [36.2%]). CONCLUSIONS AND RELEVANCE: The findings of this prognostic study suggest that the radiomic signature discerned from conventional CT images at baseline and on first follow-up may be used in clinical settings to provide an accurate early readout of future OS probability in patients with melanoma treated with single-agent programmed cell death 1 blockade.

Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.

BACKGROUND: The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiveness studies in children. Automating the WHO methodology may support more widespread application of this endpoint. METHODS: We trained a deep learning model to classify pneumonia CXRs in children using the World Health Organization (WHO)'s standardized methodology. The model was pretrained on CheXpert, a dataset containing 224,316 adult CXRs, and fine-tuned on PERCH, a pediatric dataset containing 4,172 CXRs. The model was then tested on two pediatric CXR datasets released by WHO. We also compared the model's performance to that of radiologists and pediatricians. RESULTS: The average area under the receiver operating characteristic curve (AUC) for primary endpoint pneumonia (PEP) across 10-fold validation of PERCH images was 0.928; average AUC after testing on WHO images was 0.977. The model's classification performance was better on test images with high inter-observer agreement; however, the model still outperformed human assessments in AUC and precision-recall spaces on low agreement images. CONCLUSION: A deep learning model can classify pneumonia CXR images in children at a performance comparable to human readers. Our method lays a strong foundation for the potential inclusion of computer-aided readings of pediatric CXRs in vaccine trials and epidemiology studies.

Comparing RECIST 1.1 and iRECIST in advanced melanoma patients treated with pembrolizumab in a phase II clinical trial.

OBJECTIVES: To compare tumor best overall response (BOR) by RECIST 1.1 and iRECIST, to explore the incidence of pseudoprogression in melanoma treated with pembrolizumab, and to assess the impact of pseudoprogression on overall survival (OS). METHODS: A total of 221 patients with locally advanced/unresectable melanoma who received pembrolizumab as part of KEYNOTE-002 trial were included in this study. Radiological assessment of imaging was centrally reviewed to assess tumor response. Incidence of discordance in BOR between RECIST 1.1 and iRECIST as well as rate of pseudoprogression were measured. OS of patients with pseudoprogression was compared with that of those with uncontrolled disease. RESULTS: Of the 221 patients in this cohort, 136 patients developed PD as per RECIST v1.1 and 78 patients with PD continued treatment and imaging beyond initial RECIST 1.1-defined PD. Among the 78 patients who continued therapy and imaging post-progression, RECIST 1.1 and iRECIST were discordant in 10 patients (12.8%) and pseudoprogression was encountered in 14 patients (17.9%). OS of patients with pseudoprogression was longer than that of patients with uncontrolled disease/true progression (29.9 months versus 8.0 months, p value < 0.001). CONCLUSIONS: Effectiveness of immunotherapy in clinical trials depends on the criterion used to assess tumor response (RECIST 1.1 vs iRECIST) with iRECIST being more appropriate to detect pseudoprogression and potentially prevent premature termination of effective therapy. Pseudoprogression was associated with improved OS in comparison with that of patients with uncontrolled disease. KEY POINTS: • Discordance between iRECIST and RECIST 1.1 was found in 12.8% of unresectable melanoma patients on pembrolizumab who continued therapy beyond initial RECIST 1.1-defined progression. • Pseudoprogression, captured with iRECIST, occurred in 17.9% and was significantly associated with improved overall survival in comparison with uncontrolled disease.

Algorithm Variability in the Estimation of Lung Nodule Volume From Phantom CT Scans: Results of the QIBA 3A Public Challenge.

RATIONALE AND OBJECTIVES: Quantifying changes in lung tumor volume is important for diagnosis, therapy planning, and evaluation of response to therapy. The aim of this study was to assess the performance of multiple algorithms on a reference data set. The study was organized by the Quantitative Imaging Biomarker Alliance (QIBA). MATERIALS AND METHODS: The study was organized as a public challenge. Computed tomography scans of synthetic lung tumors in an anthropomorphic phantom were acquired by the Food and Drug Administration. Tumors varied in size, shape, and radiodensity. Participants applied their own semi-automated volume estimation algorithms that either did not allow or allowed post-segmentation correction (type 1 or 2, respectively). Statistical analysis of accuracy (percent bias) and precision (repeatability and reproducibility) was conducted across algorithms, as well as across nodule characteristics, slice thickness, and algorithm type. RESULTS: Eighty-four percent of volume measurements of QIBA-compliant tumors were within 15% of the true volume, ranging from 66% to 93% across algorithms, compared to 61% of volume measurements for all tumors (ranging from 37% to 84%). Algorithm type did not affect bias substantially; however, it was an important factor in measurement precision. Algorithm precision was notably better as tumor size increased, worse for irregularly shaped tumors, and on the average better for type 1 algorithms. Over all nodules meeting the QIBA Profile, precision, as measured by the repeatability coefficient, was 9.0% compared to 18.4% overall. CONCLUSION: The results achieved in this study, using a heterogeneous set of measurement algorithms, support QIBA quantitative performance claims in terms of volume measurement repeatability for nodules meeting the QIBA Profile criteria.

Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials.

A recent joint meeting was held on January 30, 2014, with the US Food and Drug Administration (FDA), National Cancer Institute (NCI), clinical scientists, imaging experts, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocate groups to discuss imaging endpoints for clinical trials in glioblastoma. This workshop developed a set of priorities and action items including the creation of a standardized MRI protocol for multicenter studies. The current document outlines consensus recommendations for a standardized Brain Tumor Imaging Protocol (BTIP), along with the scientific and practical justifications for these recommendations, resulting from a series of discussions between various experts involved in aspects of neuro-oncology neuroimaging for clinical trials. The minimum recommended sequences include: (i) parameter-matched precontrast and postcontrast inversion recovery-prepared, isotropic 3D T1-weighted gradient-recalled echo; (ii) axial 2D T2-weighted turbo spin-echo acquired after contrast injection and before postcontrast 3D T1-weighted images to control timing of images after contrast administration; (iii) precontrast, axial 2D T2-weighted fluid-attenuated inversion recovery; and (iv) precontrast, axial 2D, 3-directional diffusion-weighted images. Recommended ranges of sequence parameters are provided for both 1.5 T and 3 T MR systems.

The imaging core lab perspective on glioblastoma imaging and response assessment in clinical trials.

Multicenter clinical trials that include medical images as a key component of response assessment often involve an imaging service provider (a core laboratory or contract research organization) to collect images and often to provide independent assessments of treatment response. The brief discussion and recommendations provided here are not intended as a rigorous academic analysis but reflect the practical experience accumulated at one such institution, which has conducted the image collection and review for numerous glioblastoma trials, in every phase of drug development, encompassing over 4000 patients scanned at over 900 sites.

Good outcome rate of 35% in IV-tPA-treated patients with computed tomography angiography confirmed severe anterior circulation occlusive stroke.

BACKGROUND AND PURPOSE: To determine the effect of intravenous tissue plasminogen activator (IV-tPA) on outcomes in patients with severe major anterior circulation ischemic stroke. METHODS: Prospectively, 649 patients with acute stroke had admission National Institutes of Health stroke scale (NIHSS) scores, noncontrast computed tomography (CT), CT angiography (CTA), and 6-month outcome assessed using modified Rankin scale. IV-tPA treatment decisions were made before CTA, at the time of noncontrast CT scanning, as per routine clinical protocol. Severe symptoms were defined as NIHSS>10. Poor outcome was defined as modified Rankin scale >2. Major occlusions were identified on CTA. Univariate and multivariate stepwise-forward logistic regression analyses of the full cohort were performed. RESULTS: Of 649 patients, 188 (29%) patients presented with NIHSS>10, and 64 out of 188 (34%) patients received IV-tPA. Admission NIHSS, large artery occlusion, and IV-tPA all independently predicted good outcomes; however, a significant interaction existed between IV-tPA and occlusion (P<0.001). Of the patients who presented with NIHSS>10 with anterior circulation occlusion, twice the percentage had good outcomes if they received IV-tPA (17 out of 49 patients, 35%) than if they did not (13 out of 77 patients, 17%; P=0.031). The number needed to treat was 7 (95% confidence interval, 3-60). CONCLUSIONS: IV-tPA treatment resulted in significantly better outcomes in patients with severely symptomatic stroke with major anterior circulation occlusions. The 35% good outcome rate was similar to rates found in endovascular therapy trials. Vascular imaging may help in patient selection and stratification for trials of IV-thrombolytic and endovascular therapies.

Tracking transplanted bone marrow stem cells and their effects in the rat MCAO stroke model.

In this study, rat bone marrow stromal stem cells (BMSCs) were tracked after IV administration to rats with experimental stroke caused by middle cerebral artery occlusion (MCAO). In addition, the effects of BMSC treatment on blood cell composition, brain glia and sensorimotor behavior was studied and compared to that which occurred spontaneously during the normal recovery process after stroke. We found that the vast majority of radiolabeled or fluorescently labeled BMSCs traveled to and remained in peripheral organs (lungs, spleen, liver) 3 days after IV injection in the MCAO rat. Once in the circulation, BMSCs also produced rapid alterations in host blood cell composition, increasing both neutrophil and total white blood cell count by 6 hours post-injection. In contrast, few injected BMSCs traveled to the brain and almost none endured there long term. Nonetheless, BMSC treatment produced dramatic changes in the number and activation of brain astroglia and microglia, particularly in the region of the infarct. These cellular changes were correlated with a marked improvement in performance on tests of sensory and motor function as compared to the partial recovery of function seen in PBS-injected control rats. We conclude that the notable recovery in function observed after systemic administration of BMSCs to MCAO rats is likely due to the cellular changes in blood and/or brain cell number, activation state and their cytokine/growth factor products.

The use of tumour volumetrics to assess response to therapy in anticancer clinical trials.

Serial evaluations of tumour burden using imaging, mainly computed tomography and magnetic resonance imaging, form the basis for assessing treatment response in many clinical trials of anticancer therapeutics. Traditionally, these evaluations have been based on linear measurements of tumour size. Such measurements have limitations related to variability in technical factors, tumour morphology and reader decisions. Measurements of entire tumour volumes may overcome some of the limitations of linear tumour measurements, improving our ability to detect small changes reliably and increasing statistical power per subject in a trial. Certain technical factors are known to affect the accuracy and precision of volume measurements, and work is in progress to define these factors more thoroughly and to qualify tumour volume as a biomarker for the purposes of drug development.

Improved outcome prediction using CT angiography in addition to standard ischemic stroke assessment: results from the STOPStroke study.

PURPOSE: To improve ischemic stroke outcome prediction using imaging information from a prospective cohort who received admission CT angiography (CTA). METHODS: In a prospectively designed study, 649 stroke patients diagnosed with acute ischemic stroke had admission NIH stroke scale scores, noncontrast CT (NCCT), CTA, and 6-month outcome assessed using the modified Rankin scale (mRS) scores. Poor outcome was defined as mRS>2. Strokes were classified as "major" by the (1) Alberta Stroke Program Early CT Score (ASPECTS+) if NCCT ASPECTS was ≤7; (2) Boston Acute Stroke Imaging Scale (BASIS+) if they were ASPECTS+ or CTA showed occlusion of the distal internal carotid, proximal middle cerebral, or basilar arteries; and (3) NIHSS for scores >10. RESULTS: Of 649 patients, 253 (39.0%) had poor outcomes. NIHSS, BASIS, and age, but not ASPECTS, were independent predictors of outcome. BASIS and NIHSS had similar sensitivities, both superior to ASPECTS (p<0.0001). Combining NIHSS with BASIS was highly predictive: 77.6% (114/147) classified as NIHSS>10/BASIS+ had poor outcomes, versus 21.5% (77/358) with NIHSS≤10/BASIS- (p<0.0001), regardless of treatment. The odds ratios for poor outcome is 12.6 (95% CI: 7.9 to 20.0) in patients who are NIHSS>10/BASIS+ compared to patients who are NIHSS≤10/BASIS-; the odds ratio is 5.4 (95% CI: 3.5 to 8.5) when compared to patients who are only NIHSS>10 or BASIS+. CONCLUSIONS: BASIS and NIHSS are independent outcome predictors. Their combination is stronger than either instrument alone in predicting outcomes. The findings suggest that CTA is a significant clinical tool in routine acute stroke assessment.