Theragnostic Gadolinium-Based Nanoparticles Safely Augment X-ray Radiation Effects in Patients with Cervical Cancer.

Activated guided irradiation by X-ray (AGuIX) nanoparticles are gadolinium-based agents that have the dual benefit of mimicking the effects of a magnetic resonance imaging (MRI) contrast agent used in a clinical routine and enhancing the radiotherapeutic activity of conventional X-rays (for cancer treatment). This "theragnostic" action is explained on the one hand by the paramagnetic properties of gadolinium and on the other hand by the generation of high densities of secondary radiation following the interaction of ionizing radiation and high-Z atoms, which leads to enhanced radiation dose deposits within the tumors where the nanoparticles accumulate. Here, we report the results of a phase I trial that aimed to assess the safety and determine the optimal dose of AGuIX nanoparticles in combination with chemoradiation and brachytherapy in patients with locally advanced cervical cancer. AGuIX nanoparticles were administered intravenously and appropriately accumulated within tumors on a dose-dependent manner, as assessed by T1-weighted MRI, with a rapid urinary clearance of uncaught nanoparticles. We show that the observed tumor accumulation of the compounds can support precise delineation of functional target volumes at the time of brachytherapy based on gadolinium enhancement. AGuIX nanoparticles combined with chemoradiation appeared well tolerated among the 12 patients treated, with no dose-limiting toxicity observed. Treatment yielded excellent local control, with all patients achieving complete remission of the primary tumor. One patient had a distant tumor recurrence. These results demonstrate the clinical feasibility of using theranostic nanoparticles to augment the accuracy of MRI-based treatments while focally enhancing the radiation activity in tumors.

Trifluridine/tipiracil + oxaliplatin ± nivolumab vs FOLFOX ± nivolumab in HER2 negative advanced oesogastric adenocarcinoma: The PRODIGE73-UCGI40-LOGICAN trial.

BACKGROUND: Trifluridine/tipiracil (FTD/TPI) is approved in third-line treatment of patients with advanced/metastatic gastric and gastroesophageal junction adenocarcinomas (aGA/GEJA). The association of oxaliplatin with FTD/TPI is promising and the combination of FTD/TPI + oxaliplatin + nivolumab has shown a predictable and manageable safety profile. AIMS: The aim is to evaluate the efficacy and safety of FTD/TPI plus oxaliplatin with or without nivolumab in patients, with HER2 negative aGA/GEJA, unfit for triplet chemotherapy (TFOX/mFLOT regimen), in the first-line metastatic setting in comparison with the standard of care FOLFOX with or without nivolumab. METHODS: This study is a prospective randomised, open label, comparative, multicentre, phase II trial designed to include 118 patients. The primary objective is to evaluate the superiority of FTD/TPI plus oxaliplatin with or without nivolumab over FOLFOX regimen with or without nivolumab in terms of PFS in a population of patients non candidate for triplet chemotherapy. Nivolumab will be used for patients whose tumour express PD-L1 with a CPS score ≥5. DISCUSSION: PRODIGE73-UCGI40-LOGICAN study will provide efficacy and safety data on the association of FTD/TPI plus oxaliplatin with or without nivolumab versus FOLFOX regimen with or without nivolumab in first-line palliative setting, in patients with aGA/GEJA (NCT05476796).

Imaging-guided prognostic score-based approach to assess the benefits of combotherapy versus monotherapy with immune checkpoint inhibitors in metastatic MSI-H colorectal cancer patients.

BACKGROUND: This retrospective study determined survival responses to immune checkpoint inhibitors (ICIs), comparing mono- (mono) and combo-immunotherapy (combo) in patients with microsatellite instability-high (MSI-H) metastatic colorectal cancer (mCRC) by analyzing quantitative imaging data and clinical factors. METHODS: One hundred fifty patients were included from two centers and divided into training (n = 105) and validation (n = 45) cohorts. Radiologists manually annotated chest-abdomen-pelvis computed tomography and calculated tumor burden. Progression-free survival (PFS) was assessed, and variables were selected through Recursive Feature Elimination. Cutoff values were determined using maximally selected rank statistics to binarize features, forming a risk score with hazard ratio-derived weights. RESULTS: In total, 2258 lesions were annotated with excellent reproducibility. Key variables in the training cohort included: total tumor volume (cutoff: 73 cm3), lesion count (cutoff: 20), age (cutoff: 60) and the presence of peritoneal carcinomatosis. Their respective weights were 1.13, 0.96, 0.91, and 0.38, resulting in a risk score cutoff of 1.36. Low-score patients showed similar overall survival and PFS regardless of treatment, while those with a high-score had significantly worse survivals with mono vs combo (P = 0.004 and P = 0.0001). In the validation set, low-score patients exhibited no significant difference in overall survival and PFS with mono or combo. However, patients with a high-score had worse PFS with mono (P = 0.046). CONCLUSIONS: A score based on total tumor volume, lesion count, the presence of peritoneal carcinomatosis, and age can guide MSI-H mCRC treatment decisions, allowing oncologists to identify suitable candidates for mono and combo ICI therapies.

Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy.

The integration of artificial intelligence (AI) and positron emission tomography (PET) imaging has the potential to become a powerful tool in drug discovery. This review aims to provide an overview of the current state of research and highlight the potential for this alliance to advance pharmaceutical innovation by accelerating the development and deployment of novel therapeutics. We previously performed a scoping review of three databases (Embase, MEDLINE, and CENTRAL), identifying 87 studies published between 2018 and 2022 relevant to medical imaging (e.g., CT, PET, MRI), immunotherapy, artificial intelligence, and radiomics. Herein, we reexamine the previously identified studies, performing a subgroup analysis on articles specifically utilizing AI and PET imaging for drug discovery purposes in immunotherapy-treated oncology patients. Of the 87 original studies identified, 15 met our updated search criteria. In these studies, radiomics features were primarily extracted from PET/CT images in combination (n = 9, 60.0%) rather than PET imaging alone (n = 6, 40.0%), and patient cohorts were mostly recruited retrospectively and from single institutions (n = 10, 66.7%). AI models were used primarily for prognostication (n = 6, 40.0%) or for assisting in tumor phenotyping (n = 4, 26.7%). About half of the studies stress-tested their models using validation sets (n = 4, 26.7%) or both validation sets and test sets (n = 4, 26.7%), while the remaining six studies (40.0%) either performed no validation at all or used less stringent methods such as cross-validation on the training set. Overall, the integration of AI and PET imaging represents a paradigm shift in drug discovery, offering new avenues for more efficient development of therapeutics. By leveraging AI algorithms and PET imaging analysis, researchers could gain deeper insights into disease mechanisms, identify new drug targets, or optimize treatment regimens. However, further research is needed to validate these findings and address challenges such as data standardization and algorithm robustness.

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.

Integrating [18F]-Fluorodeoxyglucose Positron Emission Tomography with Computed Tomography with Radiation Therapy and Immunomodulation in Precision Therapy for Solid Tumors.

[18F]-FDG positron emission tomography with computed tomography (PET/CT) imaging is widely used to enhance the quality of care in patients diagnosed with cancer. Furthermore, it holds the potential to offer insight into the synergic effect of combining radiation therapy (RT) with immuno-oncological (IO) agents. This is achieved by evaluating treatment responses both at the RT and distant tumor sites, thereby encompassing the phenomenon known as the abscopal effect. In this context, PET/CT can play an important role in establishing timelines for RT/IO administration and monitoring responses, including novel patterns such as hyperprogression, oligoprogression, and pseudoprogression, as well as immune-related adverse events. In this commentary, we explore the incremental value of PET/CT to enhance the combination of RT with IO in precision therapy for solid tumors, by offering supplementary insights to recently released joint guidelines.

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.

Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer.

BACKGROUND: Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy. METHODS: We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis. RESULTS: In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p<0.001) for patients with low SFM (<3.95 kg/m2), low FBM (<3.26 kg/m2), low VFM (<0.91 kg/m2), low MBM (<5.85 kg/m2) and low BMI (<24.97 kg/m2). The same parameters were significant in the Cox univariate analysis (p<0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p<0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (<5.22 kg/m2) and MBM (<6.86 kg/m2) (p<0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1 year versus 25% (p=0.0029). CONCLUSIONS: 3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value.

Immunosuppressant mycophenolate mofetil for patients with steroid-refractory immune-related hepatitis induced by checkpoint inhibitors in oncology.

BACKGROUND: Immune-checkpoint inhibitor (ICI) hepatitis, which does not improve with steroids and requires additional immunosuppressant, is defined as steroid-refractory ICI hepatitis. The outcome of patients with steroid-refractory ICI hepatitis remains poorly determined. Herein, we investigated the incidence, clinical features, and outcome of patients treated with second-line immunosuppressant for steroid-refractory ICI hepatitis. METHODS: This is a retrospective analysis of patients who presented ICI hepatitis from 1st June 2016 to 30th September 2022. Steroid-refractory ICI hepatitis was defined as no clinical and biological improvement after systemic steroid therapy ≥1 mg/kg/d. Main objectives were to assess the frequency and risk factors associated with steroid-refractory ICI hepatitis and to evaluate the efficacy of second-line immunosuppressants. RESULTS: In total, 130 patients with grade ≥3 ICI hepatitis were screened, of them 60 (46.2%) were treated with systemic steroids. In total, 11/130 (8.5%) had steroid-refractory hepatitis. Statistically significant factors associated with steroid-refractory hepatitis included previous liver comorbidities (54.5% versus 11.6%; p < 0.01), hyperbilirubinemia (p < 0.001), and general symptoms (fever, jaundice, ascites, and/or encephalopathy) associated with hepatitis (72.7% versus 30.8%; p = 0.015). The 11 patients with steroid-refractory hepatitis were treated with mycophenolate mofetil. In total, resolution or return to grade ≤1 for hepatitis was observed in 81.8% (9/11) of patients. CONCLUSIONS: Steroid-refractory ICI hepatitis accounted for 8.5% of patients with grade ≥3 immune-related hepatitis and was statistically associated with previous liver comorbidities, hyperbilirubinemia, and general symptoms. Mycophenolate mofetil was a suitable option of therapy for steroid-refractory ICI hepatitis.

Intratumoral Immunotherapy: Is It Ready for Prime Time?

PURPOSE OF REVIEW: This review presents the rationale for intratumoral immunotherapy, technical considerations and safety. Clinical results from the latest trials are provided and discussed. RECENT FINDINGS: Intratumoral immunotherapy is feasible and safe in a wide range of cancer histologies and locations, including lung and liver. Studies mainly focused on multi-metastatic patients, with some positive trials such as T-VEC in melanoma, but evidence of clinical benefit is still lacking. Recent results showed improved outcomes in patients with a low tumor burden. Intratumoral immunotherapy can lower systemic toxicities and boost local and systemic immune responses. Several studies have proven the feasibility, repeatability, and safety of this approach, with some promising results in clinical trials. The clinical benefit might be improved in patients with a low tumor burden. Future clinical trials should focus on adequate timing of treatment delivery during the course of the disease, particularly in the neoadjuvant setting.

Profile and outcome of cancer patients enrolled in contemporary phase I trials.

BACKGROUND: Phase I trials historically involved heavily pretreated patients (pts) with no more effective therapeutic options available and with poor expected outcomes. There are scare data regarding profile and outcomes of pts enrolled into modern phase I trials. Here, we sought to provide an overview of pts' profile and outcome into phase I trials at Gustave Roussy (GR). METHODS: This is a monocentric retrospective study, including all pts enrolled into phase I trials at GR from 2017 to 2021. Data regarding pts' demographics, tumour types, investigational treatments and survival outcomes were collected. RESULTS: In total, 9482 pts were referred for early phase trials; 2478 pts were screened, among which 449 (18.1%) failed screening; 1693 pts finally received at least one treatment dose as part of a phase I trial. Median age of pts was 59 years old (range, 18-88) and most common tumour types included gastrointestinal (25.3%), haematological (15%), lung (13.6%), genitourinary (10.5%) and gynaecologic cancers (9.4%). Amongst all pts treated and evaluable for response (1634 pts), objective response rate was 15.9% and disease control rate was 45.4%. Median progression-free survival and overall survival were, respectively, 2.6 months (95% confidence interval [95% CI], 2.3; 2.8) and 12.4 months (95% CI, 11.7; 13.6). CONCLUSION: As compared with historical data, our study shows that outcomes of pts included into modern phase I trials have improved and that these trials constitute nowadays a valid and safe therapeutic option. These updated data provide facts for adapting the methodology, role and place of phase I trials over the next years.

Clinical transfer of AGuIX®-based radiation treatments for locally advanced cervical cancer: MR quantification and in vitro insights in the NANOCOL clinical trial framework.

Clinical trials incorporating metallic nanoparticles (NPs) have recently begun. Radiotherapy planning does not take into account NPs concentrations observed in the patients' target volumes. In the framework of the NANOCOL clinical trial including patients treated for locally advanced cervical cancers, this study proposes a complete method to evaluate the radiation-induced biological effects of NPs. For this, calibration phantom was developed and MRI sequences with variable flip angles were acquired. This process allowed the quantification of NPs in the tumor of 4 patients, which was compared to the results of mass spectrometry obtained from 3 patient biopsies. The concentration of the NPs was reproduced in 3D cell models. Based on clonogenic assays, the radio-enhancement effects were quantified for radiotherapy and brachytherapy, and the impact in terms of local control was evaluated. T1 signal change in GTVs revealed NPs accumulation ∼12.4 µmol/L, in agreement with mass spectrometry. Radio-enhancement effects of about 15 % at 2 Gy were found for both modalities, with a positive impact on local tumor control. Even if further follow-up of patients in this and subsequent clinical trials will be necessary to assess the reliability of this proof of concept, this study opens the way to the integration of a dose modulation factor to better take into account the impact of NPs in radiotherapy treatment.

Genomic Instability and Protumoral Inflammation Are Associated with Primary Resistance to Anti-PD-1 + Antiangiogenesis in Malignant Pleural Mesothelioma.

Cancer immunotherapy combinations have recently been shown to improve the overall survival of advanced mesotheliomas, especially for patients responding to those treatments. We aimed to characterize the biological correlates of malignant pleural mesotheliomas' primary resistance to immunotherapy and antiangiogenics by testing the combination of pembrolizumab, an anti-PD-1 antibody, and nintedanib, a pan-antiangiogenic tyrosine kinase inhibitor, in the multicenter PEMBIB trial (NCT02856425). Thirty patients with advanced malignant pleural mesothelioma were treated and explored. Unexpectedly, we found that refractory patients were actively recruiting CD3+CD8+ cytotoxic T cells in their tumors through CXCL9 tumor release upon treatment. However, these patients displayed high levels of somatic copy-number alterations in their tumors that correlated with high blood and tumor levels of IL6 and CXCL8. Those proinflammatory cytokines resulted in higher tumor secretion of VEGF and tumor enrichment in regulatory T cells. Advanced mesothelioma should further benefit from stratified combination therapies adapted to their tumor biology. SIGNIFICANCE: Sequential explorations of fresh tumor biopsies demonstrated that mesothelioma resistance to anti-PD-1 + antiangiogenics is not due to a lack of tumor T-cell infiltration but rather due to adaptive immunosuppressive pathways by tumors, involving molecules (e.g., IL6, CXCL8, VEGF, and CTLA4) that are amenable to targeted therapies. This article is highlighted in the In This Issue feature, p. 799.

Better than RECIST and Faster than iRECIST: Defining the Immunotherapy Progression Decision Score to Better Manage Progressive Tumors on Immunotherapy.

PURPOSE: The objective of the study is to propose the immunotherapy progression decision (iPD) score, a practical tool based on patient features that are available at the first evaluation of immunotherapy treatment, to help oncologists decide whether to continue the treatment or switch rapidly to another therapeutic line when facing a progressive disease patient at the first evaluation. EXPERIMENTAL DESIGN: This retrospective study included 107 patients with progressive disease at first evaluation according to RECIST 1.1. Clinical, radiological, and biological data at baseline and first evaluation were analyzed. An external validation set consisting of 31 patients with similar baseline characteristics was used for the validation of the score. RESULTS: Variables were analyzed in a univariate study. The iPD score was constructed using only independent variables, each considered as a worsening factor for the survival of patients. The patients were stratified in three groups: good prognosis (GP), poor prognosis (PP), and critical prognosis (CP). Each group showed significantly different survivals (GP: 11.4, PP: 4.4, CP: 2.3 months median overall survival, P < 0.001, log-rank test). Moreover, the iPD score was able to detect the pseudoprogressors better than other scores. On the validation set, CP patients had significantly worse survival than PP and GP patients (P < 0.05, log-rank test). CONCLUSIONS: The iPD score provides oncologists with a new evaluation, computable at first progression, to decide whether treatment should be continued (for the GP group), or immediately changed for the PP and CP groups. Further validation on larger cohorts is needed to prove its efficacy in clinical practice.

Body Composition to Define Prognosis of Cancers Treated by Anti-Angiogenic Drugs.

Background: Body composition could help to better define the prognosis of cancers treated with anti-angiogenics. The aim of this study is to evaluate the prognostic value of 3D and 2D anthropometric parameters in patients given anti-angiogenic treatments. Methods: 526 patients with different types of cancers were retrospectively included. The software Anthropometer3DNet was used to measure automatically fat body mass (FBM3D), muscle body mass (MBM3D), visceral fat mass (VFM3D) and subcutaneous fat mass (SFM3D) in 3D computed tomography. For comparison, equivalent two-dimensional measurements at the L3 level were also measured. The area under the curve (AUC) of the receiver operator characteristics (ROC) was used to determine the parameters' predictive power and optimal cut-offs. A univariate analysis was performed using Kaplan−Meier on the overall survival (OS). Results: In ROC analysis, all 3D parameters appeared statistically significant: VFM3D (AUC = 0.554, p = 0.02, cutoff = 0.72 kg/m2), SFM3D (AUC = 0.544, p = 0.047, cutoff = 3.05 kg/m2), FBM3D (AUC = 0.550, p = 0.03, cutoff = 4.32 kg/m2) and MBM3D (AUC = 0.565, p = 0.007, cutoff = 5.47 kg/m2), but only one 2D parameter (visceral fat area VFA2D AUC = 0.548, p = 0.034). In log-rank tests, low VFM3D (p = 0.014), low SFM3D (p < 0.0001), low FBM3D (p = 0.00019) and low VFA2D (p = 0.0063) were found as a significant risk factor. Conclusion: automatic and 3D body composition on pre-therapeutic CT is feasible and can improve prognostication in patients treated with anti-angiogenic drugs. Moreover, the 3D measurements appear to be more effective than their 2D counterparts.

Synthetic MR image generation of macrotrabecular-massive hepatocellular carcinoma using generative adversarial networks.

PURPOSE: The purpose of this study was to develop a method for generating synthetic MR images of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC). MATERIALS AND METHODS: A set of abdominal MR images including fat-saturated T1-weighted images obtained during the arterial and portal venous phases of enhancement and T2-weighted images of 91 patients with MTM-HCC, and another set of MR abdominal images from 67 other patients were used. Synthetic images were obtained using a 3-step pipeline that consisted in: (i), generating a synthetic MTM-HCC tumor on a neutral background; (ii), randomly selecting a background among the 67 patients and a position inside the liver; and (iii), merging the generated tumor in the background at the specified location. Synthetic images were qualitatively evaluated by three radiologists and quantitatively assessed using a mix of 1-nearest neighbor classifier metric and Fréchet inception distance. RESULTS: A set of 1000 triplets of synthetic MTM-HCC images with consistent contrasts were successfully generated. Evaluation of selected synthetic images by three radiologists showed that the method gave realistic, consistent and diversified images. Qualitative and quantitative evaluation led to an overall score of 0.64. CONCLUSION: This study shows the feasibility of generating realistic synthetic MR images with very few training data, by leveraging the wide availability of liver backgrounds. Further studies are needed to assess the added value of those synthetic images for automatic diagnosis of MTM-HCC.

Generative adversarial networks (GAN)-based data augmentation of rare liver cancers: The SFR 2021 Artificial Intelligence Data Challenge.

PURPOSE: The 2021 edition of the Artificial Intelligence Data Challenge was organized by the French Society of Radiology together with the Centre National d'Études Spatiales and CentraleSupélec with the aim to implement generative adversarial networks (GANs) techniques to provide 1000 magnetic resonance imaging (MRI) cases of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC), a rare and aggressive subtype of HCC, generated from a limited number of real cases from multiple French centers. MATERIALS AND METHODS: A dedicated platform was used by the seven inclusion centers to securely upload their anonymized MRI examinations including all three cross-sectional images (one late arterial and one portal-venous phase T1-weighted images and one fat-saturated T2-weighted image) in compliance with general data protection regulation. The quality of the database was checked by experts and manual delineation of the lesions was performed by the expert radiologists involved in each center. Multidisciplinary teams competed between October 11th, 2021 and February 13th, 2022. RESULTS: A total of 91 MTM-HCC datasets of three images each were collected from seven French academic centers. Six teams with a total of 28 individuals participated in this challenge. Each participating team was asked to generate one thousand 3-image cases. The qualitative evaluation was performed by three radiologists using the Likert scale on ten randomly selected cases generated by each participant. A quantitative evaluation was also performed using two metrics, the Frechet inception distance and a leave-one-out accuracy of a 1-Nearest Neighbor algorithm. CONCLUSION: This data challenge demonstrates the ability of GANs techniques to generate a large number of images from a small sample of imaging examinations of a rare malignant tumor.

Immune-related generalised oedema - A new category of adverse events with immune checkpoint inhibitors.

BACKGROUND: Generalised oedema was occasionally reported associated with immune checkpoint inhibitors (ICPIs). The purpose of this study is to investigate immune-related generalised oedema (ir-GE) drug related to ICPI, through frequency, clinical and pathological characteristics, and patient's outcome. PATIENTS AND METHODS: Objectives of the study were to report on ir-GE associated with ICPI to define frequency, associated signs and symptoms, pathological characteristics, severity, and response to corticosteroids. To be included in the study, adult patients had to have ir-GE related to ICPI with certain or likely link, without any other known causes of generalised oedema. The study design was observational, over the period 2014-2020, from pharmacovigilance databases in France, including the prospective Registre des Effets Indésirables Sévères des Anticorps Monoclonaux Immunomodulateurs en Cancérologie (REISAMIC) registry. Calculation of the frequency of ir-GE was restricted to the prospective REISAMIC registry. RESULTS: Over 6633 screened patients, 20 had ir-GE confirmed drug related to ICPI. Based on the prospective REISAMIC registry, the frequency of ir-GE was 0.19% of ICPI-treated patients (3 cases out of 1598 screened patients). The 20 patients with ir-GE had a median (range) age of 62 (26-81) years, most frequent tumour types were melanoma (n = 9; 45%) and lung cancer (n = 6; 30%). The most frequent localisations of oedema were peripheral (n = 17; 85%), pleural (n = 13; 65%), and peritoneal (n = 10; 50%). Polyserositis was observed in 11 (55%) patients. The median (range) weight gain per patient was 9 (2-30) kg. Associated signs and symptoms met criteria for capillary leak syndrome (n = 4; 20%), sinusoidal obstruction syndrome/veno-occlusive disease (SOS/VOD) (n = 3; 15%), or subcutaneous autoimmune syndrome (n = 2; 10%). Corticosteroids were administered to 15 patients; of them, 10 (67%) improved clinically after corticosteroids. Based on CTCAEV5.0, the highest severity of ir-GE was grade ≥4 in 11 (55%) patients and four (20%) patients died due to ir-GE. CONCLUSIONS: Generalised immune system-related oedema is a new category of adverse event with immune checkpoint inhibitors and is often associated with a life-threatening condition. The pathophysiology may in some cases be related to endothelial dysfunctions, such as SOS/VOD or capillary leak syndrome.

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.