Acute stress induces long-term metabolic, functional, and structural remodeling of the heart.

Takotsubo cardiomyopathy is a stress-induced cardiovascular disease with symptoms comparable to those of an acute coronary syndrome but without coronary obstruction. Takotsubo was initially considered spontaneously reversible, but epidemiological studies revealed significant long-term morbidity and mortality, the reason for which is unknown. Here, we show in a female rodent model that a single pharmacological challenge creates a stress-induced cardiomyopathy similar to Takotsubo. The acute response involves changes in blood and tissue biomarkers and in cardiac in vivo imaging acquired with ultrasound, magnetic resonance and positron emission tomography. Longitudinal follow up using in vivo imaging, histochemistry, protein and proteomics analyses evidences a continued metabolic reprogramming of the heart towards metabolic malfunction, eventually leading to irreversible damage in cardiac function and structure. The results combat the supposed reversibility of Takotsubo, point to dysregulation of glucose metabolic pathways as a main cause of long-term cardiac disease and support early therapeutic management of Takotsubo.

Machine Learning of Multi-Modal Tumor Imaging Reveals Trajectories of Response to Precision Treatment.

The standard assessment of response to cancer treatments is based on gross tumor characteristics, such as tumor size or glycolysis, which provide very indirect information about the effect of precision treatments on the pharmacological targets of tumors. Several advanced imaging modalities allow for the visualization of targeted tumor hallmarks. Descriptors extracted from these images can help establishing new classifications of precision treatment response. We propose a machine learning (ML) framework to analyze metabolic-anatomical-vascular imaging features from positron emission tomography, ultrafast Doppler, and computed tomography in a mouse model of paraganglioma undergoing anti-angiogenic treatment with sunitinib. Imaging features from the follow-up of sunitinib-treated (n = 8, imaged once-per-week/6-weeks) and sham-treated (n = 8, imaged once-per-week/3-weeks) mice groups were dimensionally reduced and analyzed with hierarchical clustering Analysis (HCA). The classes extracted from HCA were used with 10 ML classifiers to find a generalized tumor stage prediction model, which was validated with an independent dataset of sunitinib-treated mice. HCA provided three stages of treatment response that were validated using the best-performing ML classifier. The Gaussian naive Bayes classifier showed the best performance, with a training accuracy of 98.7 and an average area under curve of 100. Our results show that metabolic-anatomical-vascular markers allow defining treatment response trajectories that reflect the efficacy of an anti-angiogenic drug on the tumor target hallmark.

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology.

Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management and reporting through standard and rich metadata, as encouraged by open data initiatives such as the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines. This helps data re-users to understand and reuse the shared data with confidence. Therefore, dedicated frameworks are required. The provenance reporting throughout a biomedical study lifecycle has been proposed as a way to increase confidence in data while reusing it. The Biomedical Study - Lifecycle Management (BMS-LM) data model has implemented provenance and lifecycle traceability for several multimodal-imaging techniques but this is not enough for data understanding while reusing it. Actually, in the large scope of biomedical research, a multitude of metadata sources, also called Knowledge Organization Systems (KOSs), are available for data annotation. In addition, data producers uses local terminologies or KOSs, containing vernacular terms for data reporting. The result is a set of heterogeneous KOSs (local and published) with different formats and levels of granularity. To manage the inherent heterogeneity, semantic interoperability is encouraged by the Research Data Management (RDM) community. Ontologies, and more specifically top ontologies such as BFO and DOLCE, make explicit the metadata semantics and enhance semantic interoperability. Based on the BMS-LM data model and the BFO top ontology, the BioMedical Study - Lifecycle Management (BMS-LM) core ontology is proposed together with an associated framework for semantic interoperability between heterogeneous KOSs. It is made of four ontological levels: top/core/domain/local and aims to build bridges between local and published KOSs. In this paper, the conversion of the BMS-LM data model to a core ontology is detailed. The implementation of its semantic interoperability in a specific domain context is explained and illustrated with examples from small animal preclinical research.

FIBER-ML, an Open-Source Supervised Machine Learning Tool for Quantification of Fibrosis in Tissue Sections.

Pathologic fibrosis is a major hallmark of tissue insult in many chronic diseases. Although the amount of fibrosis is recognized as a direct indicator of the extent of disease, there is no consentaneous method for its quantification in tissue sections. This study tested FIBER-ML, a semi-automated, open-source freeware that uses a machine-learning approach to quantify fibrosis automatically after a short user-controlled learning phase. Fibrosis was quantified in sirius red-stained tissue sections from two fibrogenic animal models: acute stress-induced cardiomyopathy in rats (Takotsubo syndrome-like) and HIV-induced nephropathy in mice (chronic kidney disease). The quantitative results of FIBER-ML software version 1.0 were compared with those of ImageJ in Takotsubo syndrome, and with those of inForm in chronic kidney disease. Intra- and inter-operator and inter-software correlation and agreement were assessed. All correlations were excellent (>0.95) in both data sets. The values of discriminatory power between the pathologic and healthy groups were <10-3 for data on Takotsubo syndrome and <10-4 for data on chronic kidney disease. Intra-operator agreement, assessed by intra-class coefficient correlation, was good (>0.8), while inter-operator and inter-software agreement ranged from moderate to good (>0.7). FIBER-ML performed in a fast and user-friendly manner, with reproducible and consistent quantification of fibrosis in tissue sections. It offers an open-source alternative to currently used software, including quality control and file management.

Sunitinib-induced cardiac hypertrophy and the endothelin axis.

Anti-angiogenics drugs in clinical use for cancer treatment induce cardiotoxic side effects. The endothelin axis is involved in hypertension and cardiac remodelling, and addition of an endothelin receptor antagonist to the anti-angiogenic sunitinib was shown to reduce cardiotoxicity of sunitinib in mice. Here, we explored further the antidote effect of the endothelin receptor antagonist macitentan in sunitinib-treated animals on cardiac remodeling. Methods: Tumor-bearing mice treated per os daily by sunitinib or vehicle were imaged before and after 1, 3 and 6 weeks of treatment by positron emission tomography using [18F]fluorodeoxyglucose and by echocardiography. Non-tumor-bearing animals were randomly assigned to be treated per os daily by vehicle or sunitinib or macitentan or sunitinib+macitentan, and imaged by echocardiography after 5 weeks. Hearts were harvested for histology and molecular analysis at the end of in vivo exploration. Results: Sunitinib treatment increases left ventricular mass and ejection fraction and induces cardiac fibrosis. Sunitinib also induces an early increase in cardiac uptake of [18F]fluorodeoxyglucose, which is significantly correlated with increased left ventricular mass at the end of treatment. Co-administration of macitentan prevents sunitinib-induced hypertension, increase in ejection fraction and cardiac fibrosis, but fails to prevent increase of the left ventricular mass. Conclusion: Early metabolic changes predict sunitinib-induced cardiac remodeling. Endothelin blockade can prevent some but not all cardiotoxic side-effects of sunitinib, in particular left ventricle hypertrophy that appears to be induced by sunitinib through an endothelin-independent mechanism.

Ultrafast Ultrasound Imaging for Super-Resolution Preclinical Cardiac PET.

PURPOSE: Physiological motion and partial volume effect (PVE) significantly degrade the quality of cardiac positron emission tomography (PET) images in the fast-beating hearts of rodents. Several Super-resolution (SR) techniques using a priori anatomical information have been proposed to correct motion and PVE in PET images. Ultrasound is ideally suited to capture real-time high-resolution cine images of rodent hearts. Here, we evaluated an ultrasound-based SR method using simultaneously acquired and co-registered PET-CT-Ultrafast Ultrasound Imaging (UUI) of the beating heart in closed-chest rodents. PROCEDURES: The method was tested with numerical and animal data (n = 2) acquired with the non-invasive hybrid imaging system PETRUS that acquires simultaneously PET, CT, and UUI. RESULTS: We showed that ultrasound-based SR drastically enhances the quality of PET images of the beating rodent heart. For the simulations, the deviations between expected and mean reconstructed values were 2 % after applying SR. For the experimental data, when using Ultrasound-based SR correction, contrast was improved by a factor of two, signal-to-noise ratio by 11 %, and spatial resolution by 56 % (~ 0.88 mm) with respect to static PET. As a consequence, the metabolic defect following an acute cardiac ischemia was delineated with much higher anatomical precision. CONCLUSIONS: Our results provided a proof-of-concept that image quality of cardiac PET in fast-beating rodent hearts can be significantly improved by ultrasound-based SR, a portable low-cost technique. Improved PET imaging of the rodent heart may allow new explorations of physiological and pathological situations related with cardiac metabolism.

Concurrent imaging of vascularization and metabolism in a mouse model of paraganglioma under anti-angiogenic treatment.

Rationale: Deregulation of metabolism and induction of vascularization are major hallmarks of cancer. Using a new multimodal preclinical imaging instrument, we explored a sequence of events leading to sunitinib-induced resistance in a murine model of paraganglioma (PGL) invalidated for the expression of succinate dehydrogenase subunit B (Sdhb-/-). Methods: Two groups of Sdhb-/- tumors bearing mice were treated with sunitinib (6 weeks) or vehicle (3 weeks). Concurrent Positron Emission Tomography (PET) with 2' -deoxy-2'-[18F]fluoro-D-glucose (FDG), Computed Tomography (CT) and Ultrafast Ultrasound Imaging (UUI) imaging sessions were performed once a week and ex vivo samples were analyzed by western blots and histology. Results: PET-CT-UUI enabled to detect a rapid growth of Sdhb-/- tumors with increased glycolysis and vascular development. Sunitinib treatment prevented tumor growth, vessel development and reduced FDG uptake at week 1 and 2 (W1-2). Thereafter, imaging revealed tumor escape from sunitinib treatment: FDG uptake in tumors increased at W3, followed by tumor growth and vessel development at W4-5. Perfused vessels were preferentially distributed in the hypermetabolic regions of the tumors and the perfused volume increased during escape from sunitinib treatment. Finally, initial changes in total lesion glycolysis and maximum vessel length at W1 were predictive of resistance to sunitinib. Conclusion: These results demonstrate an adaptive resistance of Sdhb-/- tumors to six weeks of sunitinib treatment. Early metabolic changes and delayed vessel architecture changes were detectable and predictable in vivo early during anti-angiogenic treatment. Simultaneous metabolic, anatomical and functional imaging can monitor precisely the effects of anti-angiogenic treatment of tumors.

Performance evaluation of the PET component of a hybrid PET/CT-ultrafast ultrasound imaging instrument.

We recently introduced a hybrid imaging instrument, PETRUS, based on a combination of positron emission tomography (PET) for molecular imaging, x-ray computed tomography (CT) for anatomical imaging, co-registration and attenuation correction, and ultrafast ultrasound imaging (UUI) for motion-correction, hemodynamic and biomechanical imaging. In order to ensure a precise co-registration of simultaneous PET-UUI acquisitions, ultrasound probes attached to an ultrafast ultrasound scanner are operated in the field of view (FOV) of a small animal PET/CT scanner using a remote-controlled micro-positioner. Here we explore the effect of the presence of ultrasound probes on PET image quality. We compare the performance of PET and image quality with and without the presence of probes in the PET field of view, both in vitro following the NEMA-NU-4-2008 standard protocol, and in vivo in small animals. Overall, deviations in the quality of images acquired with and without the ultrasound probes were under 10% and under 7% for the NEMA protocol and in vivo tests, respectively. Our results demonstrate the capability of the PETRUS device to acquire multimodal images in vivo without significant degradation of image quality.