EFSUMB Technical Review - Update 2023: Dynamic Contrast-Enhanced Ultrasound (DCE-CEUS) for the Quantification of Tumor Perfusion.

Dynamic contrast-enhanced ultrasound (DCE-US) is a technique to quantify tissue perfusion based on phase-specific enhancement after the injection of microbubble contrast agents for diagnostic ultrasound. The guidelines of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) published in 2004 and updated in 2008, 2011, and 2020 focused on the use of contrast-enhanced ultrasound (CEUS), including essential technical requirements, training, investigational procedures and steps, guidance regarding image interpretation, established and recommended clinical indications, and safety considerations. However, the quantification of phase-specific enhancement patterns acquired with ultrasound contrast agents (UCAs) is not discussed here. The purpose of this EFSUMB Technical Review is to further establish a basis for the standardization of DCE-US focusing on treatment monitoring in oncology. It provides some recommendations and descriptions as to how to quantify dynamic ultrasound contrast enhancement, and technical explanations for the analysis of time-intensity curves (TICs). This update of the 2012 EFSUMB introduction to DCE-US includes clinical aspects for data collection, analysis, and interpretation that have emerged from recent studies. The current study not only aims to support future work in this research field but also to facilitate a transition to clinical routine use of DCE-US.

Influence of Different Measurement Methods of Arterial Input Function on Quantitative Dynamic Contrast-Enhanced MRI Parameters in Head and Neck Cancer.

BACKGROUND: Head and neck cancer (HNC) is the sixth most prevalent cancer worldwide. Dynamic contrast-enhanced MRI (DCE-MRI) helps in diagnosis and prognosis. Quantitative DCE-MRI requires an arterial input function (AIF), which affects the values of pharmacokinetic parameters (PKP). PURPOSE: To evaluate influence of four individual AIF measurement methods on quantitative DCE-MRI parameters values (Ktrans , ve , kep , and vp ), for HNC and muscle. STUDY TYPE: Prospective. POPULATION: A total of 34 HNC patients (23 males, 11 females, age range 24-91) FIELD STRENGTH/SEQUENCE: A 3 T; 3D SPGR gradient echo sequence with partial saturation of inflowing spins. ASSESSMENT: Four AIF methods were applied: automatic AIF (AIFa) with up to 50 voxels selected from the whole FOV, manual AIF (AIFm) with four voxels selected from the internal carotid artery, both conditions without (Mc-) or with (Mc+) motion correction. Comparison endpoints were peak AIF values, PKP values in tumor and muscle, and tumor/muscle PKP ratios. STATISTICAL TESTS: Nonparametric Friedman test for multiple comparisons. Nonparametric Wilcoxon test, without and with Benjamini Hochberg correction, for pairwise comparison of AIF peak values and PKP values for tumor, muscle and tumor/muscle ratio, P value ≤ 0.05 was considered statistically significant. RESULTS: Peak AIF values differed significantly for all AIF methods, with mean AIFmMc+ peaks being up to 66.4% higher than those for AIFaMc+. Almost all PKP values were significantly higher for AIFa in both, tumor and muscle, up to 76% for mean Ktrans values. Motion correction effect was smaller. Considering tumor/muscle parameter ratios, most differences were not significant (0.068 ≤ Wilcoxon P value ≤ 0.8). DATA CONCLUSION: We observed important differences in PKP values when using either AIFa or AIFm, consequently choice of a standardized AIF method is mandatory for DCE-MRI on HNC. From the study findings, AIFm and inflow compensation are recommended. The use of the tumor/muscle PKP ratio should be of interest for multicenter studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

BR55 Ultrasound Molecular Imaging of Clear Cell Renal Cell Carcinoma Reflects Tumor Vascular Expression of VEGFR-2 in a Patient-Derived Xenograft Model.

Standard imaging cannot reliably predict the nature of renal tumors. Among malignant renal tumors, clear cell renal cell carcinoma (ccRCC) is the most common histological subtype, in which the vascular endothelial growth factor 2 (VEGFR-2) is highly expressed in the vascular endothelium. BR55, a contrast agent for ultrasound imaging, consists of gas-core lipid microbubbles that specifically target and bind to the extracellular portion of the VEGFR-2. The specific information provided by ultrasound molecular imaging (USMI) using BR55 was compared with the vascular tumor expression of the VEGFR-2 by immunohistochemical (IHC) staining in a preclinical model of ccRCC. Patients' ccRCCs were orthotopically grafted onto Nod-Scid-Gamma (NSG) mice to generate patient-derived xenografts (PdX). Mice were divided into four groups to receive either vehicle or axitinib an amount of 2, 7.5 or 15 mg/kg twice daily. Perfusion parameters and the BR55 ultrasound contrast signal on PdX renal tumors were analyzed at D0, D1, D3, D7 and D11, and compared with IHC staining for the VEGFR-2 and CD34. Significant Pearson correlation coefficients were observed between the area under the curve (AUC) and the CD34 (0.84, p < 10-4), and between the VEGFR-2-specific signal obtained by USMI and IHC (0.72, p < 10-4). USMI with BR55 could provide instant, quantitative information on tumor VEGFR-2 expression to characterize renal masses non-invasively.

Quantification and reduction of cross-vendor variation in multicenter DWI MR imaging: results of the Cancer Core Europe imaging task force.

OBJECTIVES: In the Cancer Core Europe Consortium (CCE), standardized biomarkers are required for therapy monitoring oncologic multicenter clinical trials. Multiparametric functional MRI and particularly diffusion-weighted MRI offer evident advantages for noninvasive characterization of tumor viability compared to CT and RECIST. A quantification of the inter- and intraindividual variation occurring in this setting using different hardware is missing. In this study, the MRI protocol including DWI was standardized and the residual variability of measurement parameters quantified. METHODS: Phantom and volunteer measurements (single-shot T2w and DW-EPI) were performed at the seven CCE sites using the MR hardware produced by three different vendors. Repeated measurements were performed at the sites and across the sites including a traveling volunteer, comparing qualitative and quantitative ROI-based results including an explorative radiomics analysis. RESULTS: For DWI/ADC phantom measurements using a central post-processing algorithm, the maximum deviation could be decreased to 2%. However, there is no significant difference compared to a decentralized ADC value calculation at the respective MRI devices. In volunteers, the measurement variation in 2 repeated scans did not exceed 11% for ADC and is below 20% for single-shot T2w in systematic liver ROIs. The measurement variation between sites amounted to 20% for ADC and < 25% for single-shot T2w. Explorative radiomics classification experiments yield better results for ADC than for single-shot T2w. CONCLUSION: Harmonization of MR acquisition and post-processing parameters results in acceptable standard deviations for MR/DW imaging. MRI could be the tool in oncologic multicenter trials to overcome the limitations of RECIST-based response evaluation. KEY POINTS: • Harmonizing acquisition parameters and post-processing homogenization, standardized protocols result in acceptable standard deviations for multicenter MR-DWI studies. • Total measurement variation does not to exceed 11% for ADC in repeated measurements in repeated MR acquisitions, and below 20% for an identical volunteer travelling between sites. • Radiomic classification experiments were able to identify stable features allowing for reliable discrimination of different physiological tissue samples, even when using heterogeneous imaging data.

Comorbidity and frailty assessment in renal cell carcinoma patients.

PURPOSE: Renal cell carcinoma (RCC) incidence has considerably increased during the last decades without any real impact on age-standardized mortality. It questions the relevance of aggressive treatments carrying potential side effects. Conservative management should be considered for frail patients. Comorbidity and frailty assessment in RCC patients is paramount before engaging a treatment. METHODS: Narrative, non-systematic review based on PubMed and EMBASE search with the terms "renal neoplasm", "elderly, frail", "comorbidities", "active surveillance", "metastatic". The selection was restricted to articles written in English. RESULTS: Comorbidity and frailty assessment go along with the cancer-specific aggressivity and intervention risks assessment. In localized disease, several standardized algorithms offer patient health evaluation to define how suitable the patient would be for curative treatment. The pre-operative American Society of Anesthesiologists and the age-adjusted Charlson's scores are the most widely used. At the metastatic stage, drug combinations based on immunotherapies and targeted therapies improved cancer outcomes at the price of significant toxicities. Frail patients are not always suitable for such strategies. Commonly used scores like the International Metastatic RCC Database Consortium or Memorial Sloan Kettering Cancer Center integrate features to define patients' risk groups, more specifically the Karnofsky Performance Score is an easy way to document the frailty. CONCLUSIONS: Comorbidity and frailty have to be assessed at any stage of the RCC disease based on a standardized scoring system to define the most suitable treatment strategy ranging from surveillance to aggressive treatment.

Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers.

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.

New method for quantification of intratumoral heterogeneity: a feasibility study on Ktrans maps from preclinical DCE-MRI.

OBJECT: To develop new imaging biomarkers of therapeutic efficacy through the quantification of intratumoral microvascular heterogeneity. MATERIALS AND METHODS: The described method was a combination of non-supervised clustering and extraction of intratumoral complexity features (ICF): number of non-connected objects, volume fraction. It was applied to a set of 3D DCE-MRI Ktrans maps acquired previously on tumor bearing mice prior to and on day 4 of anti-angiogenic treatment. Evolutions of ICF were compared to conventional summary statistics (CSS) and to heterogeneity related whole tumor texture features (TF) on treated (n = 9) and control (n = 6) mice. RESULTS: Computed optimal number of clusters per tumor was 4. Several intratumoral features extracted from the clusters were able to monitor a therapy effect. Whereas no feature significantly changed for the control group, 6 features significantly changed for the treated group (4 ICF, 2 CSS). Among these, 5 also significantly differentiated the two groups (3 ICF, 2 CSS). TF failed in demonstrating differences within and between the two groups. DISCUSSION: ICF are potential imaging biomarkers for anti-angiogenic therapy assessment. The presented method may be expected to have advantages with respect to texture analysis-based methods regarding interpretability of results and setup of standardized image analysis protocols.

Advanced Ultrasound Imaging for Patients in Oncology: DCE-US.

Neovascularization is a key stage in the growth of malignancies beyond 2-3 mm3. This neoangiogenesis is an important target for novel anticancer treatments [1], and many new antiangiogenesis or antivascular treatments aim at destroying or limiting the growth of tumor vessels [2].

Association of metastatic pattern and molecular status in stage IV non-small cell lung cancer adenocarcinoma.

OBJECTIVES: The aim of our study was to investigate the association between driver oncogene alterations and metastatic patterns on imaging assessment, in a large cohort of metastatic lung adenocarcinoma patients. METHODS: From January 2010 to May 2017, 550 patients with stage IV lung adenocarcinoma with molecular analysis were studied retrospectively including 135 EGFR-mutated, 81 ALK-rearrangement, 47 BRAF-mutated, 141 KRAS-mutated, and 146 negative tumors for these 4 mutations (4N). After review of the complete imaging report by two radiologists (junior and senior) to identify metastatic sites, univariate correlation analyzes were performed. RESULTS: We found differences in metastatic tropism depending on the molecular alteration type when compared with the non-mutated 4N group: in the EGFR group, pleural metastases were more frequent (32% versus 20%; p = 0.021), and adrenal and node metastases less common (6% versus 23%; p < 0.001 and 11% versus 23%; p = 0.011). In the ALK group, there were more brain and lung metastases (respectively 42% versus 29%; p = 0.043 and 37% versus 24%; p = 0.037). In the BRAF group, pleural and pericardial metastases were more common (respectively 47% versus 20%; p < 0.001 and 11% versus 3%; p = 0.04) and bone metastases were rarer (21% versus 42%; p = 0.011). Lymphangitis was more frequent in EGFR, ALK, and BRAF groups (respectively 6%, 7%, and 15% versus 1%); p = 0.016; p = 0.009; and p < 0.001. CONCLUSION: The application of these correlations between molecular status and metastatic tropism in clinical practice may lead to earlier and more accurate identification of patients for targeted therapy. KEY POINTS: • Bone and brain metastasis are the most common organs involved in lung adenocarcinoma but the relative incidence of each metastatic site depends on the molecular alteration. • EGFR-mutated tumors preferentially spread to the pleura and less commonly to adrenals, ALK-rearrangement tumors usually spread to the brain and the lungs, whereas BRAF-mutated tumors are unlikely to spread to bones and have a serous (pericardial ad pleural) tropism. • These correlations could help in the clinical management of patients with metastatic lung adenocarcinoma.

Guidelines and Good Clinical Practice Recommendations for Contrast Enhanced Ultrasound (CEUS) in the Liver - Update 2020 - WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS.

The present, updated document describes the fourth iteration of recommendations for the hepatic use of contrast enhanced ultrasound (CEUS), first initiated in 2004 by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB). The previous updated editions of the guidelines reflected changes in the available contrast agents and updated the guidelines not only for hepatic but also for non-hepatic applications.The 2012 guideline requires updating as previously the differences of the contrast agents were not precisely described and the differences in contrast phases as well as handling were not clearly indicated. In addition, more evidence has been published for all contrast agents. The update also reflects the most recent developments in contrast agents, including the United States Food and Drug Administration (FDA) approval as well as the extensive Asian experience, to produce a truly international perspective.These guidelines and recommendations provide general advice on the use of ultrasound contrast agents (UCA) and are intended to create standard protocols for the use and administration of UCA in liver applications on an international basis to improve the management of patients.

Carbonic Anhydrase IX in Renal Cell Carcinoma, Implications for Disease Management.

Carbonic Anhydrase IX (CAIX) is a well-described enzyme in renal cell carcinoma, with its expression being regulated by the hypoxia-inducible factor 1 alpha, it is known for interfering with hypoxia processes. Renal carcinoma encompasses a broad spectrum of histological entities and is also described as a heterogeneous malignant tumor. Recently, various combinations of checkpoint inhibitors and targeted therapies have been validated to manage this disease. Reliable markers to confirm the diagnosis, estimate the prognosis, predict or monitor the treatment response are required. Molecular imaging developments allow a comprehensive analysis of the tumor, overcoming the spatial heterogeneity issue. CAIX, being highly expressed at the tumor cell surfaces of clear cell renal carcinoma, also represents a potential treatment target. In this manuscript we reviewed the current knowledge from the literature on the pathophysiological interactions between renal cell carcinoma and CAIX, the role of CAIX as a marker for diagnosis, prognosis, treatment monitoring and molecular imaging, and the potential target for therapeutic strategies.

The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Long Version).

The updated version of the EFSUMB guidelines on the application of non-hepatic contrast-enhanced ultrasound (CEUS) deals with the use of microbubble ultrasound contrast outside the liver in the many established and emerging applications.

The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Short Version).

The updated version of the EFSUMB guidelines on the application of non-hepatic contrast-enhanced ultrasound (CEUS) deals with the use of microbubble ultrasound contrast outside the liver in the many established and emerging applications.

A Novel Microflow Phantom Dedicated to Ultrasound Microvascular Measurements.

Tumor microvascularization is a biomarker of response to antiangiogenic treatments and is accurately assessed by ultrasound imaging. Imaging modes used to visualize slow flows include Power Doppler imaging, dynamic contrast-enhanced ultrasonography, and more recently, microvascular Doppler. Flow phantoms are used to evaluate the performance of Doppler imaging techniques, but they do not have a steady flow and sufficiently small channels. We report a novel device for robust and stable microflow measurements and the study of the microvascularization. Based on microfluidics technology, the prototype features wall-less cylindrical channels of diameters ranging from as small as 147 up to 436 µm, cast in a soft silicone polymer and perfused via a microfluidic flow pressure controller. The device was assessed using flow rates from 49 to 146 µL/min, with less than 1% coefficient of variation over three minutes, corresponding to velocities of 6 to 142 mm/s. This enabled us to evaluate and confirm the reliability of the Superb Microvascular Imaging Doppler mode compared with the Power Doppler mode at these flow rates in the presence of vibrations mimicking physiological motion.

A French national breast and thyroid cancer screening programme for survivors of childhood, adolescent and young adult (CAYA) cancers - DeNaCaPST programme.

BACKGROUND: Survival of childhood, adolescent and young adult (CAYA) cancers has increased with progress in the management of the treatments and has reached more than 80% at 5 years. Nevertheless, these survivors are at great risk of second cancers and non-malignant co-morbidities in later life. DeNaCaPST is a non-interventional study whose aim is to organize a national screening for thyroid cancer and breast cancer in survivors of CAYA cancers. It will study the compliance with international recommendations, with the aim, regarding a breast screening programme, of offering for every woman living in France, at equal risk, an equal screening. METHOD: DeNaCaPST trial is coordinated by the INSERM 1018 unit in cooperation with the LEA (French Childhood Cancer Survivor Study for Leukaemia) study's coordinators, the long term follow up committee and the paediatric radiation committee of the SFCE (French Society of Childhood Cancers). A total of 35 centres spread across metropolitan France and la Reunion will participate. FCCSS (French Childhood Cancer Survivor Study), LEA and central registry will be interrogated to identify eligible patients. To participate, centers agreed to perform a complete "long-term follow-up consultations" according to good clinical practice and the guidelines of the SFCE (French Society of Children Cancers). DISCUSSION: As survival has greatly improved in childhood cancers, detection of therapy-related malignancies has become a priority even if new radiation techniques will lead to better protection for organs at risk. International guidelines have been put in place because of the evidence for increased lifetime risk of breast and thyroid cancer. DeNaCaPST is based on these international recommendations but it is important to recognize that they are based on expert consensus opinion and are supported by neither nonrandomized observational studies nor prospective randomized trials in this specific population. Over-diagnosis is a phenomenon inherent in any screening program and therefore such programs must be evaluated.

Sorafenib plus dacarbazine in solid tumors: a phase I study with dynamic contrast-enhanced ultrasonography and genomic analysis of sequential tumor biopsy samples.

PURPOSE: Improved prognostic accuracy for treatment response and a wider understanding of drug effects in humans are crucial for enhancing the utility of sorafenib and other promising targeted therapies. We developed a strategy of global genomic investigation of sequential tumor biopsy samples at baseline and 21 days post treatment, and applied this approach in a phase I study of sorafenib plus dacarbazine in patients with solid tumors. The objective of this study was also to validate functional parameters of DCE-US as surrogate markers to predict earlier response. EXPERIMENTAL DESIGN: Patients received 21-day cycles of oral sorafenib, 400 mg twice daily and dacarbazine, 1,000 mg/m(2) in a 1-h intravenous infusion on day 1. Efficacy was assessed using response evaluation criteria in solid tumors. Sequential biopsy samples (baseline and day 21) were obtained from the same tumor. Changes from baseline in global gene expression (GE) measured by genomic microarrays and in tumor vascularity at baseline, D8, D21, D 42 and every 2 cycles using dynamic contrast-enhanced ultrasonography (DCE-US) were analyzed for patients with and without a clinical response to treatment at 3 months. RESULTS: Among 23 patients evaluable for treatment efficacy, 17 were eligible for gene expression and DCE-US analyses. One patient achieved a partial response; 14 exhibited stable disease. Ten patients were defined as exhibiting stable disease (SD) and 7, progressive disease (PD) at 3 months. Genomic analyses identified a 237-gene signature that distinguished SD from PD at 3 months. Of note, CDK4 overexpression and PDGFR downregulation were associated with PD. Functional parameters of DCE-US representing the blood volume at baseline, day 8, and day 21 were correlated with disease progression at 3 months. CONCLUSIONS: This novel approach of sequential investigations in a phase I trial was feasible, detecting early changes in gene expression and tumor vascularity evaluated using DCE-US that may be predictive of clinical outcome.

Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.

The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and specificity, often leading to surgery for diagnostic purposes. The aim of this paper is (1) to develop a machine learning algorithm based on MR images characteristics to automatically classify parotid gland tumours and (2) compare its results with the diagnoses of junior and senior radiologists in order to evaluate its utility in routine practice. While automatic algorithms applied to parotid tumours classification have been developed in the past, we believe that our study is one of the first to leverage four different MRI sequences and propose a comparison with clinicians. In this study, we leverage data coming from a cohort of 134 patients treated for benign or malignant parotid tumours. Using radiomics extracted from the MR images of the gland, we train a random forest and a logistic regression to predict the corresponding histopathological subtypes. On the test set, the best results are given by the random forest: we obtain a 0.720 accuracy, a 0.860 specificity, and a 0.720 sensitivity over all histopathological subtypes, with an average AUC of 0.838. When considering the discrimination between benign and malignant tumours, the algorithm results in a 0.760 accuracy and a 0.769 AUC, both on test set. Moreover, the clinical experiment shows that our model helps to improve diagnostic abilities of junior radiologists as their sensitivity and accuracy raised by 6 % when using our proposed method. This algorithm may be useful for training of physicians. Radiomics with a machine learning algorithm may help improve discrimination between benign and malignant parotid tumours, decreasing the need for diagnostic surgery. Further studies are warranted to validate our algorithm for routine use.

Detection and characterization of pancreatic lesion with artificial intelligence: The SFR 2023 artificial intelligence data challenge.

PURPOSE: The purpose of the 2023 SFR data challenge was to invite researchers to develop artificial intelligence (AI) models to identify the presence of a pancreatic mass and distinguish between benign and malignant pancreatic masses on abdominal computed tomography (CT) examinations. MATERIALS AND METHODS: Anonymized abdominal CT examinations acquired during the portal venous phase were collected from 18 French centers. Abdominal CT examinations were divided into three groups including CT examinations with no lesion, CT examinations with benign pancreatic mass, or CT examinations with malignant pancreatic mass. Each team included at least one radiologist, one data scientist, and one engineer. Pancreatic lesions were annotated by expert radiologists. CT examinations were distributed in balanced batches via a Health Data Hosting certified platform. Data were distributed into four batches, two for training, one for internal evaluation, and one for the external evaluation. Training used 83 % of the data from 14 centers and external evaluation used data from the other four centers. The metric (i.e., final score) used to rank the participants was a weighted average of mean sensitivity, mean precision and mean area under the curve. RESULTS: A total of 1037 abdominal CT examinations were divided into two training sets (including 500 and 232 CT examinations), an internal evaluation set (including 139 CT examinations), and an external evaluation set (including 166 CT examinations). The training sets were distributed on September 7 and October 13, 2023, and evaluation sets on October 15, 2023. Ten teams with a total of 93 members participated to the data challenge, with the best final score being 0.72. CONCLUSION: This SFR 2023 data challenge based on multicenter CT data suggests that the use of AI for pancreatic lesions detection is possible on real data, but the distinction between benign and malignant pancreatic lesions remains challenging.