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Objectif de l’étude Les objectifs de ce travail étaient d’identifier, pour des cancers non oropharyngé localement évolués pris en charge par chimioradiothérapie, des paramètres de tomographie par émission de positons (TEP) quantitatifs prédictif de la survie sans progression et dans un second temps d’établir un score pronostique. Matériel et méthode Un total de 78 patients, avec un suivi médian de 23 mois, issus de trois centres (Rennes, Lorient et Lausanne), ont été inclus dans cette étude rétrospective. En plus de la standard uptake value maximale (SUVMax), les paramètres de TEP de volume ( metabolic tumor volume [MTV] et total lesion glycolysis [TLG]) ont été calculés en utilisant différentes valeurs de seuillage en valeur absolue (de 0 à 20) ou relative (de 0 à 100 % de la SUVMax). L’ensemble des paramètres cliniques et de TEP a été analysé et une corrélation avec la survie sans récidive a été recherchée. Un modèle pronostique de survie sans progression a été défini. Une validation interne a été réalisée par une méthode de ré-échantillonnage ( bootstrap ). Résultats En analyse multifactorielle, le MTV était le seul facteur pronostique indépendant de la survie sans progression, alors que les facteurs classiques cliniques ([stade T, volume tumoral macroscopique], stade selon l’American Joint Committee on Cancer [AJCC]) étaient peu ou pas significatifs. Après ré-échantillonnage, le c-index ajusté était de 0,69. La calibration interne a retrouvé un bon ajustement entre la survie sans progression prédite et la survie sans progression observée à 24 mois. Un score prédictif a été calculé, permettant d’identifier deux groupes à risque. La durée médiane de la survie sans progression était de 37 mois (intervalle de confiance à 95 % [IC95 %] : 36–55 mois pour le groupe de bas risque et de 8 mois [IC95 % : 5–15 mois] pour le groupe de haut risque, p < 0,01). Conclusion Le MTV est un puissant facteur pronostique de la survie sans progression chez les patients pris en charge par chimioradiothérapie. L’utilisation du MTV pourrait permettre une identification précoce des cancers de pronostic défavorable, candidat potentiel à une intensification thérapeutique. Une validation externe prospective sera nécessaire pour confirmer ces résultats. [ABSTRACT FROM AUTHOR]

Rodent models of maternal immune activation (MIA) are increasingly used as experimental tools in preclinical research of immune-mediated neurodevelopmental disorders and mental illnesses. Using a viral-like MIA model that is based on prenatal poly(I:C) exposure in mice, we have recently identified the existence of subgroups of MIA-exposed offspring that show dissociable behavioral, transcriptional, brain network and inflammatory profiles even under conditions of genetic homogeneity and identical MIA. Here, we tested the hypothesis that the intrauterine positions of fetuses, which are known to shape individual variability in litter-bearing mammals through variations in fetal hormone exposure, may contribute to the variable outcomes of MIA in mice. MIA was induced by maternal administration of poly(I:C) on gestation day 12 in C57BL/6N mice. Determining intrauterine positions using delivery by Cesarean section (C-section), we found that MIA-exposed offspring developing between female fetuses only (0M-MIA offspring) displayed significant deficits in sociability and sensorimotor gating at adult age, whereas MIA-exposed offspring developing between one or two males in utero (1/2M-MIA offspring) did not show the same deficits. These intrauterine position effects similarly emerged in male and female offspring. Furthermore, while MIA elevated fetal brain levels of pro- and anti-inflammatory cytokines independently of the precise intrauterine position and sex of adjacent fetuses during the acute phase, fetal brain levels of TNF-α remained elevated in 0M-MIA but not 1/2M-MIA offspring until the post-acute phase in late gestation. As expected, 1/2M offspring generally showed higher testosterone levels in the fetal brain during late gestation as compared to 0M offspring, confirming the transfer of testosterone from male fetuses to adjacent male or female fetuses. Taken together, our findings identify a novel source of within-litter variability contributing to heterogeneous outcomes of short- and long-term effects in a mouse model of MIA. In broader context, our findings highlight that individual differences in fetal exposure to hormonal and inflammatory signals may be a perinatal factor that shapes risk and resilience to MIA., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

The Poly (I:C) (polyriboinosinic-polyribocytidilic acid) paradigm of maternal immune activation (MIA) is most widely used as experimental model for the evaluation of the effects of gestational infection on the brain and behavior of the progeny. We have previously reported significant batch-to-batch variability in the effects of Poly (I:C), purchased from the same supplier (Sigma-Aldrich), on maternal and fetal immune responses and found these differences to be dependent on the relative amount of synthetic double-stranded RNA fragments in the high versus low molecular weight (LMW) range contained in the compound. We here resorted to Poly (I:C) purified for LMW dsRNA fragments to establish a MIA paradigm with increased reproducibility and enhanced standardization in an effort to refine the MIA paradigm and characterize its effect on offspring behavior. We found that the parallel application of LMW Poly (I:C) in two different MIA-experienced laboratories (Vienna and Zurich) yielded differential outcomes in terms of maternal immune responses and behavioral phenotypes in the offspring generation. In both experimental sites, administration of LMW Poly (I:C) induced a significant sickness response and cytokine induction in the pregnant dam and fetal brains, while the expected deficit in sociability as one main behavioral outcome parameter in the MIA progeny, was only present in the Zurich, but not the Vienna cohort. We conclude that although using Poly (I:C) purified for a defined molecular weight range reduces batch-to-batch variability, it does not make the MIA model more reliable and robust. The differential response in behavioral phenotypes of the MIA offspring between the two laboratories illustrates the highly complex interaction between prenatal and postnatal milieus - including the laboratory environment - that determine offspring phenotypic outcomes after MIA. Consequently, establishing a new MIA protocol or implementing the MIA model firstly under new or changed environmental conditions must include the assessment of offspring behavior to ensure solid and reproducible experimental outcomes., (© 2024. The Author(s).)

Prenatal exposure to infections is a risk factor for neurodevelopmental disorders in offspring, and alterations in mitochondrial function are discussed as a potential underlying factor. Here, using a mouse model of viral-like maternal immune activation (MIA) based on poly(I:C) (POL) treatment at gestational day (GD) 12, we show that adult offspring exhibit behavioral deficits, such as reduced levels of social interaction. In addition, we found increased nicotinamidadenindinucleotid (NADH)- and succinate-linked mitochondrial respiration and maximal electron transfer capacity in the prefrontal cortex (PFC) and in the amygdala (AMY) of males and females. The increase in respiratory capacity resulted from an increase in mitochondrial mass in neurons (as measured by complex IV activity and transcript expression), presumably to compensate for a reduction in mitochondrion-specific respiration. Moreover, in the PFC of control (CON) male offspring a higher excess capacity compared to females was observed, which was significantly reduced in the POL-exposed male offspring, and, along with a higher leak respiration, resulted in a lower mitochondrial coupling efficiency. Transcript expression of the uncoupling proteins (UCP4 and UCP5) showed a reduction in the PFC of POL male mice, suggesting mitochondrial dysfunction. In addition, in the PFC of CON females, a higher expression of the antioxidant enzyme superoxide dismutase (SOD1) was observed, suggesting a higher antioxidant capacity as compared to males. Finally, transcripts analysis of genes involved in mitochondrial biogenesis and dynamics showed reduced expression of fission/fusion transcripts in PFC of POL offspring of both sexes. In conclusion, we show that MIA causes alterations in neuronal mitochondrial function and mass in the PFC and AMY of adult offspring with some effects differing between males and females., (© 2024. The Author(s).)

Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking., (© RSNA, 2024 See also the editorial by Huisman and D'Antonoli in this issue.)

Background: To test and validate novel CT techniques, such as texture analysis in radiomics, repeat measurements are required. Current anthropomorphic phantoms lack fine texture and true anatomic representation. 3D-printing of iodinated ink on paper is a promising phantom manufacturing technique. Previously acquired or artificially created CT data can be used to generate realistic phantoms., Purpose: To present the design process of an anthropomorphic 3D-printed iodine ink phantom, highlighting the different advantages and pitfalls in its use. To analyze the phantom's X-ray attenuation properties, and the influences of the printing process on the imaging characteristics, by comparing it to the original input dataset., Methods: Two patient CT scans and artificially generated test patterns were combined in a single dataset for phantom printing and cropped to a size of 26 × 19 × 30 cm 3 . This DICOM dataset was printed on paper using iodinated ink. The phantom was CT-scanned and compared to the original image dataset used for printing the phantom. The water-equivalent diameter of the phantom was compared to that of a patient cohort (N = 104). Iodine concentrations in the phantom were measured using dual-energy CT. 86 radiomics features were extracted from 10 repeat phantom scans and the input dataset. Features were compared using a histogram analysis and a PCA individually and overall, respectively. The frequency content was compared using the normalized spectrum modulus., Results: Low density structures are depicted incorrectly, while soft tissue structures show excellent visual accordance with the input dataset. Maximum deviations of around 30 HU between the original dataset and phantom HU values were observed. The phantom has X-ray attenuation properties comparable to a lightweight adult patient (∼54 kg, BMI 19 kg/m 2 ). Iodine concentrations in the phantom varied between 0 and 50 mg/ml. PCA of radiomics features shows different tissue types separate in similar areas of PCA representation in the phantom scans as in the input dataset. Individual feature analysis revealed systematic shift of first order radiomics features compared to the original dataset, while some higher order radiomics features did not. The normalized frequency modulus |f(ω)| of the phantom data agrees well with the original data. However, all frequencies systematically occur more frequently in the phantom compared to the maximum of the spectrum modulus than in the original data set, especially for mid-frequencies (e.g., for ω = 0.3942 mm -1 , |f(ω)| original  = 0.09 * |f max | original and |f(ω)| phantom  = 0.12 * |f max | phantom )., Conclusions: 3D-iodine-ink-printing technology can be used to print anthropomorphic phantoms with a water-equivalent diameter of a lightweight adult patient. Challenges include small residual air enclosures and the fidelity of HU values. For soft tissue, there is a good agreement between the HU values of the phantom and input data set. Radiomics texture features of the phantom scans are similar to the input data set, but systematic shifts of radiomics features in first order features, due to differences in HU values, need to be considered. The paper substrate influences the spatial frequency distribution of the phantom scans. This phantom type is of very limited use for dual-energy CT analyses., (© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Background: Radiomics, the field of image-based computational medical biomarker research, has experienced rapid growth over the past decade due to its potential to revolutionize the development of personalized decision support models. However, despite its research momentum and important advances toward methodological standardization, the translation of radiomics prediction models into clinical practice only progresses slowly. The lack of physicians leading the development of radiomics models and insufficient integration of radiomics tools in the clinical workflow contributes to this slow uptake., Methods: We propose a physician-centered vision of radiomics research and derive minimal functional requirements for radiomics research software to support this vision. Free-to-access radiomics tools and frameworks were reviewed to identify best practices and reveal the shortcomings of existing software solutions to optimally support physician-driven radiomics research in a clinical environment., Results: Support for user-friendly development and evaluation of radiomics prediction models via machine learning was found to be missing in most tools. QuantImage v2 (QI2) was designed and implemented to address these shortcomings. QI2 relies on well-established existing tools and open-source libraries to realize and concretely demonstrate the potential of a one-stop tool for physician-driven radiomics research. It provides web-based access to cohort management, feature extraction, and visualization and supports "no-code" development and evaluation of machine learning models against patient-specific outcome data., Conclusions: QI2 fills a gap in the radiomics software landscape by enabling "no-code" radiomics research, including model validation, in a clinical environment. Further information about QI2, a public instance of the system, and its source code is available at https://medgift.github.io/quantimage-v2-info/ . Key points As domain experts, physicians play a key role in the development of radiomics models. Existing software solutions do not support physician-driven research optimally. QuantImage v2 implements a physician-centered vision for radiomics research. QuantImage v2 is a web-based, "no-code" radiomics research platform., (© 2023. The Author(s).)

Prenatal exposure to infectious or noninfectious immune activation is an environmental risk factor for neurodevelopmental disorders and mental illnesses. Recent research using animal models suggests that maternal immune activation (MIA) during early to middle stages of pregnancy can induce transgenerational effects on brain and behavior, likely via inducing stable epigenetic modifications across generations. Using a mouse model of viral-like MIA, which is based on gestational treatment with poly(I:C), the present study explored whether transgenerational effects can also emerge when MIA occurs in late pregnancy. Our findings demonstrate that the direct descendants born to poly(I:C)-treated mothers display deficits in temporal order memory, which are similarly present in second- and third-generation offspring. These transgenerational effects were mediated via both the maternal and paternal lineages and were accompanied by transient changes in maternal care. In addition to the cognitive effects, late prenatal immune activation induced generation-spanning effects on the prefrontal expression of gamma-aminobutyric acid (GABA)ergic genes, including parvalbumin and distinct alpha-subunits of the GABAA receptor. Together, our results suggest that MIA in late pregnancy has the potential to affect cognitive functions and prefrontal gene expression patterns in multiple generations, highlighting its role in shaping disease risk across generations., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Medical imaging quantitative features had once disputable usefulness in clinical studies. Nowadays, advancements in analysis techniques, for instance through machine learning, have enabled quantitative features to be progressively useful in diagnosis and research. Tissue characterisation is improved via the "radiomics" features, whose extraction can be automated. Despite the advances, stability of quantitative features remains an important open problem. As features can be highly sensitive to variations of acquisition details, it is not trivial to quantify stability and efficiently select stable features. In this work, we develop and validate a Computed Tomography (CT) simulator environment based on the publicly available ASTRA toolbox ( www.astra-toolbox.com ). We show that the variability, stability and discriminative power of the radiomics features extracted from the virtual phantom images generated by the simulator are similar to those observed in a tandem phantom study. Additionally, we show that the variability is matched between a multi-center phantom study and simulated results. Consequently, we demonstrate that the simulator can be utilised to assess radiomics features' stability and discriminative power., (© 2022. The Author(s).)

Cyclometalated Ir(III) complexes are often chosen as catalysts for challenging photoredox and triplet-triplet-energy-transfer (TTET) catalyzed reactions, and they are of interest for upconversion into the ultraviolet spectral range. However, the triplet energies of commonly employed Ir(III) photosensitizers are typically limited to values around 2.5-2.75 eV. Here, we report on a new Ir(III) luminophore, with an unusually high triplet energy near 3.0 eV owing to the modification of a previously reported Ir(III) complex with isocyanoborato ligands. Compared to a nonborylated cyanido precursor complex, the introduction of B(C 6 F 5 ) 3 units in the second coordination sphere results in substantially improved photophysical properties, in particular a high luminescence quantum yield (0.87) and a long excited-state lifetime (13.0 μs), in addition to the high triplet energy. These favorable properties (including good long-term photostability) facilitate exceptionally challenging organic triplet photoreactions and (sensitized) triplet-triplet annihilation upconversion to a fluorescent singlet excited state beyond 4 eV, unusually deep in the ultraviolet region. The new Ir(III) complex photocatalyzes a sigmatropic shift and [2 + 2] cycloaddition reactions that are unattainable with common transition metal-based photosensitizers. In the presence of a sacrificial electron donor, it furthermore is applicable to demanding photoreductions, including dehalogenations, detosylations, and the degradation of a lignin model substrate. Our study demonstrates how rational ligand design of transition-metal complexes (including underexplored second coordination sphere effects) can be used to enhance their photophysical properties and thereby broaden their application potential in solar energy conversion and synthetic photochemistry.

Evidence-based practice is highly dependent upon up-to-date systematic reviews (SR) for decision making. However, conducting and updating systematic reviews, especially the citation screening for identification of relevant studies, requires much human work and is therefore expensive. Automating citation screening using machine learning (ML) based approaches can reduce cost and labor. Machine learning has been applied to automate citation screening but not for the SRs with very narrow research questions. This paper reports the results and observations for an ongoing research that aims to automate citation screening for SRs with narrow research questions using machine learning. The research also sheds light on the problem of class imbalance and class overlap on the performance of ML classifiers when applied to SRs with narrow research questions.

Background: The introduction of digital pathology into clinical practice has led to the development of clinical workflows with digital images, in connection with pathology reports. Still, most of the current work is time-consuming manual analysis of image areas at different scales. Links with data in the biomedical literature are rare, and a need for search based on visual similarity within whole slide images (WSIs) exists., Objectives: The main objective of the work presented is to integrate content-based visual retrieval with a WSI viewer in a prototype. Another objective is to connect cases analyzed in the viewer with cases or images from the biomedical literature, including the search through visual similarity and text., Methods: An innovative retrieval system for digital pathology is integrated with a WSI viewer, allowing to define regions of interest (ROIs) in images as queries for finding visually similar areas in the same or other images and to zoom in/out to find structures at varying magnification levels. The algorithms are based on a multimodal approach, exploiting both text information and content-based image features., Results: The retrieval system allows viewing WSIs and searching for regions that are visually similar to manually defined ROIs in various data sources (proprietary and public datasets, e.g., scientific literature). The system was tested by pathologists, highlighting its capabilities and suggesting ways to improve it and make it more usable in clinical practice., Conclusions: The developed system can enhance the practice of pathologists by enabling them to use their experience and knowledge to control artificial intelligence tools for navigating repositories of images for clinical decision support and teaching, where the comparison with visually similar cases can help to avoid misinterpretations. The system is available as open source, allowing the scientific community to test, ideate and develop similar systems for research and clinical practice., Competing Interests: There are no conflicts of interest.

Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud-based evaluation framework is presented in this paper including results of benchmarking current state-of-the-art medical imaging algorithms for anatomical structure segmentation and landmark detection: the VISCERAL Anatomy benchmarks. The algorithms are implemented in virtual machines in the cloud where participants can only access the training data and can be run privately by the benchmark administrators to objectively compare their performance in an unseen common test set. Overall, 120 computed tomography and magnetic resonance patient volumes were manually annotated to create a standard Gold Corpus containing a total of 1295 structures and 1760 landmarks. Ten participants contributed with automatic algorithms for the organ segmentation task, and three for the landmark localization task. Different algorithms obtained the best scores in the four available imaging modalities and for subsets of anatomical structures. The annotation framework, resulting data set, evaluation setup, results and performance analysis from the three VISCERAL Anatomy benchmarks are presented in this article. Both the VISCERAL data set and Silver Corpus generated with the fusion of the participant algorithms on a larger set of non-manually-annotated medical images are available to the research community.

Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Most sudden cardiac problems require rapid treatment to preserve life. In this regard, electrocardiograms (ECG) shown on vital parameter monitoring systems help medical staff to detect problems. In some situations, such monitoring systems may display information in a less than convenient way for medical staff. For example, vital parameters are displayed on large screens outside the field of view of a surgeon during cardiac surgery. This may lead to losing time and to mistakes when problems occur during cardiac operations. In this paper we present a novel approach to display vital parameters such as the second derivative of the ECG rhythm and heart rate close to the field of view of a surgeon using Google Glass. As a preliminary assessment, we run an experimental study to verify the possibility for medical staff to identify abnormal ECG rhythms from Google Glass. This study compares 6 ECG rhythms readings from a 13.3 inch laptop screen and from the prism of Google Glass. Seven medical residents in internal medicine participated in the study. The preliminary results show that there is no difference between identifying these 6 ECG rhythms from the laptop screen versus Google Glass. Both allow close to perfect identification of the 6 common ECG rhythms. This shows the potential of connected glasses such as Google Glass to be useful in selected medical applications.