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Discovering causal effects is at the core of scientific investigation but remains challenging when only observational data are available. In practice, causal networks are difficult to learn and interpret, and limited to relatively small datasets. We report a more reliable and scalable causal discovery method (iMIIC), based on a general mutual information supremum principle, which greatly improves the precision of inferred causal relations while distinguishing genuine causes from putative and latent causal effects. We showcase iMIIC on synthetic and real-world healthcare data from 396,179 breast cancer patients from the US Surveillance, Epidemiology, and End Results program. More than 90% of predicted causal effects appear correct, while the remaining unexpected direct and indirect causal effects can be interpreted in terms of diagnostic procedures, therapeutic timing, patient preference or socio-economic disparity. iMIIC's unique capabilities open up new avenues to discover reliable and interpretable causal networks across a range of research fields., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)

(1) Background: radiotherapy is a cornerstone of cancer treatment. When delivering a tumoricidal dose, the risk of severe late toxicities is usually kept below 5% using dose-volume constraints. However, individual radiation sensitivity (iRS) is responsible (with other technical factors) for unexpected toxicities after exposure to a dose that induces no toxicity in the general population. Diagnosing iRS before radiotherapy could avoid unnecessary toxicities in patients with a grossly normal phenotype. Thus, we reviewed iRS diagnostic data and their impact on decision-making processes and the RT workflow; (2) Methods: following a description of radiation toxicities, we conducted a critical review of the current state of the knowledge on individual determinants of cellular/tissue radiation; (3) Results: tremendous advances in technology now allow minimally-invasive genomic, epigenetic and functional testing and a better understanding of iRS. Ongoing large translational studies implement various tests and enriched NTCP models designed to improve the prediction of toxicities. iRS testing could better support informed radiotherapy decisions for individuals with a normal phenotype who experience unusual toxicities. Ethics of medical decisions with an accurate prediction of personalized radiotherapy's risk/benefits and its health economics impact are at stake; (4) Conclusions: iRS testing represents a critical unmet need to design personalized radiotherapy protocols relying on extended NTCP models integrating iRS.

Background: Segmentation is a crucial step in treatment planning that directly impacts dose distribution and optimization. The aim of this study was to evaluate the inter-individual variability of common cranial organs at risk (OAR) delineation in neurooncology practice., Methods: Anonymized simulation contrast-enhanced CT and MR scans of one patient with a solitary brain metastasis was used for delineation and analysis. Expert professionals from 16 radiotherapy centers involved in brain structures delineation were asked to segment 9 OAR on their own treatment planning system. As reference, two experts in neurooncology, produced a unique consensual contour set according to guidelines. Overlap ratio, Kappa index (KI), volumetric ratio, Commonly Contoured Volume, Supplementary Contoured Volume were evaluated using Artiview™ v 2.8.2-according to occupation, seniority and level of expertise of all participants., Results: For the most frequently delineated and largest OAR, the mean KI are often good (0.8 for the parotid and the brainstem); however, for the smaller OAR, KI degrade (0.3 for the optic chiasm, 0.5% for the cochlea), with a significant discrimination (p < 0.01). The radiation oncologists, members of Association des Neuro-Oncologue d'Expression Française society performed better in all indicators compared to non-members (p < 0.01). Our exercise was effective in separating the different participating centers with 3 of the reported indicators (p < 0.01)., Conclusion: Our study illustrates the heterogeneity in normal structures contouring between professionals. We emphasize the need for cerebral OAR delineation harmonization-that is a major determinant of therapeutic ratio and clinical trials evaluation.

The last decade has been characterized by breakthroughs in fluorescence microscopy techniques illustrated by spatial resolution improvement but also in live-cell imaging and high-throughput microscopy techniques. This led to a constant increase in the amount and complexity of the microscopy data for a single experiment. Because manual analysis of microscopy data is very time consuming, subjective, and prohibits quantitative analyses, automation of bioimage analysis is becoming almost unavoidable. We built an informatics workflow called Substructure Analyzer to fully automate signal analysis in bioimages from fluorescent microscopy. This workflow is developed on the user-friendly open-source platform Icy and is completed by functionalities from ImageJ. It includes the pre-processing of images to improve the signal to noise ratio, the individual segmentation of cells (detection of cell boundaries) and the detection/quantification of cell bodies enriched in specific cell compartments. The main advantage of this workflow is to propose complex bio-imaging functionalities to users without image analysis expertise through a user-friendly interface. Moreover, it is highly modular and adapted to several issues from the characterization of nuclear/cytoplasmic translocation to the comparative analysis of different cell bodies in different cellular sub-structures. The functionality of this workflow is illustrated through the study of the Cajal (coiled) Bodies under oxidative stress (OS) conditions. Data from fluorescence microscopy show that their integrity in human cells is impacted a few hours after the induction of OS. This effect is characterized by a decrease of coilin nucleation into characteristic Cajal Bodies, associated with a nucleoplasmic redistribution of coilin into an increased number of smaller foci. The central role of coilin in the exchange between CB components and the surrounding nucleoplasm suggests that OS induced redistribution of coilin could affect the composition and the functionality of Cajal Bodies.

Stereotactic radiotherapy (SRT) is recommended for treatment of brain oligometastasis (BoM) in patients with controlled primary disease. Where contrast enhancement enlargement occurs during follow-up, distinguishing between radionecrosis and progression presents a critical challenge. Without pathological confirmation, decision-making may be inappropriate and delayed. Quantitative imaging features extracted from routinely performed examinations are of interest in potentially addressing this problem. We explored the added value of the radiomics method for the differential diagnosis of these two entities. Twenty patients who received SRT for BoM, from any primary location, were included (8 radionecrosis, 12 progressions, pathologically confirmed). We assessed the clinical relevance of 1,766 radiomics features, extracted using IBEX software, from the first T1-weighted postcontrast magnetic resonance imaging (MRI) after SRT showing a lesion modification. We evaluated seven feature-selection methods and 12 classification methods in terms of respective predictive performance. The classification accuracy was measured using Cohen's kappa after leave-one-out cross-validation. In this work, the best predictive power reached was a Cohen's kappa of 0.68 (overall accuracy of 85%), expressing a strong agreement between the algorithm prediction and the histological gold standard. Prediction accuracy was 75% for radionecrosis, and 91% for progression. The area under a curve reached 0.83 using a bagging algorithm trained with the chi-square score features set. These findings indicated that the radiomics method is able to discriminate radionecrosis from progression in an accurate, early and noninvasive way. This promising study is a proof of concept, preceding a larger prospective study for defining a robust model to support decision-making in BoM. In summary, distinguishing between radionecrosis and progression is challenging without pathology. We built a classification model based on imaging data and machine learning. Using this model, we were able predict progression and radionecrosis in, respectively, 91% and 75% of cases.

Background: Well-differentiated papillary mesothelioma of the peritoneum (WDPMP) is a rare entity. Questions regarding management are still being debated as no more than 50 cases have been reported in the literature., Objective: We aimed to analyze the clinical, therapeutic, and prognostic data of patients with WDPMP from the RENAPE observational registry., Patients and Methods: All patients diagnosed with WDPMP and prospectively included in the RENAPE national registry between 2010 and 2018 were also included in our study. Expert pathologists from the RENA-PATH group confirmed all cases. All clinical, therapeutic, postoperative, and prognostic data were extracted and analyzed., Results: We report on 56 patients with a mean age of 52 years (range 21-74). WDPMP was incidentally diagnosed during imaging or surgery in 16% and 36% of patients, respectively, and an association with synchronous malignancy was found in 18% of patients. Nine lesions showed discrete signs of fatty invasion. The median Peritoneal Cancer Index was 11 (range 0-33). Eleven patients were treated with definitive excision, 4 were treated with cytoreductive surgery (CRS) only, 37 were treated with CRS and hyperthermic intraperitoneal chemotherapy (HIPEC), and 2 were treated with CRS plus HIPEC plus early postoperative intraperitoneal chemotherapy. CRS was considered to be complete in 90% of cases. One patient died postoperatively and 16 patients (31%) faced postoperative complications. The median disease-free survival was 144 months; Four patients relapsed, with a median period of 27 months. No prognostic factors could be identified., Conclusions: Our analysis confirms the favorable prognosis of WDPMP. CRS and HIPEC could be a therapeutic option for diffuse, symptomatic, and/or recurrent disease.

Background: Approximately 900 children/adolescents are treated with radiotherapy (RT) every year in France. However, among the 80% of survivors, the cumulative incidence of long-term morbidity - including second malignancies - reach 73.4% thirty years after the cancer diagnosis. Identifying a priori the subjects at risk for RT sequelae is a major challenge of paediatric oncology. Individual radiosensitivity (IRS) of children/adolescents is unknown at this time, probably with large variability depending on the age when considering the changes in metabolic functions throughout growth. We previously retrospectively showed that unrepaired DNA double strand breaks (DSB) as well a delay in the nucleoshuttling of the pATM protein were common features to patients with RT toxicity. We aim to validate a high performance functional assay for IRS prospectively., Methods/design: ARPEGE is a prospective open-label, non-randomized multicentre cohort study. We will prospectively recruit 222 children/adolescents who require RT as part of their routine care and follow them during 15 years. Prior RT we will collect blood and skin samples to raise a primary dermal fibroblast line to carry out in blind the IRS assay. As a primary objective, we will determine its discriminating ability to predict the occurrence of unusual early skin, mucous or hematological toxicity. The primary endpoint is the measurement of residual double-strand breaks 24 h after ex vivo radiation assessed with indirect immunofluorescence (γH2AX marker). Secondary endpoints include the determination of pATM foci at 10 min and 1 h (pATM marker) and micronuclei at 24 h. In parallel toxicity including second malignancies will be reported according to NCI-CTCAE v4.0 reference scale three months of the completion of RT then periodically during 15 years. Confusion factors such as irradiated volume, skin phototype, previous chemotherapy regimen, smoking, comorbities (diabetes, immunodeficiency, chronic inflammatory disease...) will be reported., Discussion: ARPEGE would be the first study to document the distribution of IRS in the pediatric subpopulation. Screening hypersensitive patients would be a major step forward in the management of cancers, opening a way to personalized pediatric oncology., Trial Registration: ID-RCB number: 2015-A00975-44, ClinicalTrials.gov Identifier: NCT02827552 Registered 7/6/2016.