Correction: Full-field optical coherence tomography for the diagnosis of giant cell arteritis.

[This corrects the article DOI: 10.1371/journal.pone.0234165.].

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.

Preclinical evaluation of targeted therapies in Sdhb-mutated tumors.

Therapies for metastatic SDHB-dependent pheochromocytoma and paraganglioma (PPGL) are limited and poorly efficient. New targeted therapies and identification of early non-invasive biomarkers of response are thus urgently needed for these patients. We characterized an in vivo allograft model of spontaneously immortalized murine chromaffin cells (imCC) with inactivation of the Sdhb gene by dynamic contrast-enhanced MRI (DCE-MRI) and 18FDG-PET. We evaluated the response to several therapies: IACS-010759 (mitochondrial respiratory chain complex I inhibitor), sunitinib (tyrosine kinase inhibitor with anti-angiogenic activity), talazoparib (poly ADP ribose polymerase (PARP) inhibitor) combined or not to temozolomide (alkylating agent), pharmacological inhibitors of HIF2a (PT2385 and PT2977 (belzutifan)) and molecular inactivation of HIF2a (imCC Sdhb-/- shHIF2a). Multimodal imaging was performed, including magnetic resonance spectroscopy (1H-MRS) to monitor the level of succinate in vivo. The allografted model of Sdhb-/- imCC reflected SDHB-deficient tumors, with increased angiogenesis and a particular avidity for 18FDG. After 14 days of treatment, IACS-010759, sunitinib and talazoparib at high doses allowed a significant reduction of the tumor volumes. In contrast to the tumor growth inhibition observed in Sdhb-/- shHIF2a imCC tumors, pharmacological inhibitors of HIF2a (PT2385 and belzutifan) showed no antitumor action in this model, alone or in combination with sunitinib. 1H-MRS, but not DCE-MRI, enabled the monitoring response to sunitinib, which was the best treatment in this study, promoting a decrease in succinate levels detected in vivo. This study paves the way for new therapeutic options and reveals a potential new early biomarker of response to treatment in SDHB-dependent PPGL.

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.

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.

Dynamic contrast enhanced - MRI efficiency in detecting embolization-induced perfusion defects in a rabbit model of critical-limb-ischemia.

Critical limb ischemia (CLI) is a severe disease which affects about 2 million people in the US. Its prevalence is assessed at 800/100,000 population. However, no reliable tools are currently available to assess perfusion defects at the muscle tissue level. DCE-MRI is a technique that holds the potential to be effective in achieving this goal. However, preclinical studies performed with DCE-MRI have indicated low sensitivity assessing perfusion at resting state. To improve these previous results, in this work we propose new methodologies for data acquisition and analysis and we also revisit the biological model used for evaluation. Eleven rabbits underwent embolization of a lower limb. They were imaged at day 7 after embolization using DCE-MRI, performed on a 4.7 T small imaging device. Among them, n = 4 rabbits were used for MRI sequence optimization and n = 6 for data analysis after one exclusion. Normalized Areas under the curve (AUCn), and kinetic parameters such as Ktrans and Vd resulting from the Tofts-Kety modeling (KTM) were calculated on the embolized and contralateral limbs. Average and heterogeneity features, consisting on standard-deviation and quantiles, were calculated on muscle groups and whole limbs. The Wilcoxon and Fisher-tests were performed to compare embolized and contralateral regions of interests. The Wilcoxon test was also used to compare features of parametric maps. Quantiles of 5 and 95% in the contralateral side were used to define low and high outliers. A P-value <0.05 was considered statistically significant. Average features were inefficient to identify injured muscles, in agreement with the low sensitivity of the technique previously reported by the literature. However, these findings were dramatically improved by the use of additional heterogeneity features (97% of total accuracy for group muscles, P < 0.01 and 100% of total accuracy for the total limbs). The mapping analysis and automatic outlier detection quantification improvement was explained by the presence of local hyperemia that impair the average calculations. The analysis with KTM did not provide any additional information compared to AUCn. The DCE technique can be effective in detecting embolization-induced disorders of limb muscles in a CLI model when heterogeneity is taken into account in the data processing, even without vascular stimulation. The simultaneous presence of areas of ischemia and hyperemia appeared as a signature of the injured limbs. These areas seem to reflect the simultaneous presence of infarcted areas and viable peripheral areas, characterized by a vascular response that is visible in DCE.

Human placental perfusion measured using dynamic contrast enhancement MRI.

OBJECTIVES: To evaluate the feasibility of dynamic contrast enhanced magnetic resonance imaging (DCE MRI) and measure values of in vivo placental perfusion in women. METHODS: This study was part of the Placentimage trial (NCT01092949). Gadolinium-chelate (Gd) enhanced dynamic MRI was performed two days before termination of pregnancies at 16 to 34 weeks gestational age (GA). Quantitative analysis was performed using one-compartment intravascular modeling. DCE perfusion parameters were analyzed across GA and were compared in IUGR and AGA fetuses. RESULTS: 134 patients were enrolled. After quality control check, 62 DCE MRI were analyzed including 48 and 14 pregnancies with normal and abnormal karyotypes, respectively. Mean placental blood flow was 129±61 mL/min/100ml in cases with normal karyotypes. Fetuses affected by IUGR (n = 13) showed significantly lower total placental blood flow values than AGA fetuses (n = 35) (F total = 122±88 mL/min versus 259±34 mL/min, p = 0.002). DCE perfusion parameters showed a linear correlation with GA. CONCLUSIONS: Measuring placental perfusion in vivo is possible using DCE MRI. Although this study has many limitations it gives us the first DCE MRI values that provide a potential standard for future research into placental perfusion methods and suggests that placental functional parameters are altered in IUGR pregnancies.

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.

Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions.

PURPOSE: To assess the diagnostic performance of radiomic analysis using high temporal resolution (HTR)-dynamic contrast enhancement (DCE) MR sequences compared to BI-RADS analysis to distinguish benign from malignant breast lesions. MATERIALS AND METHODS: We retrospectively analyzed data from consecutive women who underwent breast MRI including HTR-DCE MR sequencing for abnormal enhancing lesions and who had subsequent pathological analysis at our tertiary center. Semi-quantitative enhancement parameters and textural features were extracted. Temporal change across each phase of textural features in HTR-DCE MR sequences was calculated and called "kinetic textural parameters." Statistical analysis by LASSO logistic regression and cross validation was performed to build a model. The diagnostic performance of the radiomic model was compared to the results of BI-RADS MR score analysis. RESULTS: We included 117 women with a mean age of 54 years (28-88). Of the 174 lesions analyzed, 75 were benign and 99 malignant. Seven semi-quantitative enhancement parameters and 57 textural features were extracted. Regression analysis selected 15 significant variables in a radiomic model (called "malignant probability score") which displayed an AUC = 0.876 (sensitivity = 0.98, specificity = 0.52, accuracy = 0.78). The performance of the malignant probability score to distinguish benign from malignant breast lesions (AUC = 0.876, 95%CI 0.825-0.925) was significantly better than that of BI-RADS analysis (AUC = 0.831, 95%CI 0.769-0.892). The radiomic model significantly reduced false positives (42%) with the same number of missed cancers (n = 2). CONCLUSION: A radiomic model including kinetic textural features extracted from an HTR-DCE MR sequence improves diagnostic performance over BI-RADS analysis. KEY POINTS: • Radiomic analysis using HTR-DCE is of better diagnostic performance (AUC = 0.876) than conventional breast MRI reading with BI-RADS (AUC = 0.831) (p < 0.001). • A radiomic malignant probability score under 19.5% gives a negative predictive value of 100% while a malignant probability score over 81% gives a positive predictive value of 100%. • Kinetic textural features extracted from HTR-DCE-MRI have a major role to play in distinguishing benign from malignant breast lesions.

Assessment of BOLD response in the fetal lung.

OBJECTIVE: Assessment of lung development and maturity is of utmost importance in prenatal counseling. Blood oxygen level-dependent (BOLD) effect MRI was developed for functional evaluations of organs. To date, no data are available in fetal lungs and nothing is known about the existence of a BOLD effect in the lungs. The aim of our study was to evaluate if a BOLD response could be detected in fetal lungs. MATERIALS AND METHODS: From January 2014 to December 2016, 38 healthy pregnant women were prospectively enrolled. After a routine scan on a 1.5-T MRI device (normoxic period), maternal hyperoxia was induced for 5 min before the BOLD sequence (hyperoxic period). R2* was evaluated by fitting average intensity of the signal, both for normoxic (norm) and hyperoxic (hyper) periods. RESULTS: A significant BOLD response was observed after maternal hyperoxia in the lungs with a mean R2* decrease of 12.1 ± 2.5% (p < 0.001), in line with the placenta response with a mean R2* decrease of 19.2 ± 5.9% (p < 0.0001), confirming appropriate oxygen uptake. Conversely, no significant BOLD effect was observed for the brain nor the liver with a mean ∆R2* of 3.6 ± 3.1% (p = 0.64) and 2.8 ± 3.7% (p = 0.23). CONCLUSION: This study shows for the first time in human that a BOLD response can be observed in the normal fetal lung despite its prenatal "non-functional status." If confirmed in congenital lung and chest malformations, this property could be used in addition to the lung volume for a better prediction of postnatal respiratory status. KEY POINTS: • Blood oxygen level-dependent (BOLD) effect MRI was developed for functional evaluations of organs and could have interesting implications for the fetal organs. • Assessment of lung development is of utmost importance in prenatal counseling, but to date no data are available in fetal lungs. • BOLD response can be observed in the normal fetal lung opening the way to studies on fetus with pathological lungs.

Full-field optical coherence tomography for the diagnosis of giant cell arteritis.

Histopathological examination of temporal artery biopsy (TAB) remains the gold standard for the diagnosis of giant cell arteritis (GCA) but is associated with essential limitations that emphasize the need for an upgraded pathological process. This study pioneered the use of full-field optical coherence tomography (FF-OCT) for rapid and automated on-site pathological diagnosis of GCA. Sixteen TABs (12 negative and 4 positive for GCA) were selected according to major histopathological criteria of GCA following hematoxylin-eosin-saffron-staining for subsequent acquisition with FF-OCT to compare structural modifications of the artery cell wall and thickness of each tunica. Gabor filtering of FF-OCT images was then used to compute TAB orientation maps and validate a potential automated analysis of TAB sections. FF-OCT allowed both qualitative and quantitative visualization of the main structures of the temporal artery wall, from the internal elastic lamina to the vasa vasorum and red blood cells, unveiling a significant correlation with conventional histology. FF-OCT imaging of GCA TABs revealed destruction of the media with distinct remodeling of the whole arterial wall into a denser reticular fibrous neo-intima, which is distinctive of GCA pathogenesis and accessible through automated Gabor filtering. Rapid on-site FF-OCT TAB acquisition makes it possible to identify some characteristic pathological lesions of GCA within a few minutes, paving the way for potential machine intelligence-based or even non-invasive diagnosis of GCA.

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.

Quality-based pharmacokinetic model selection on DCE-MRI for characterizing orbital lesions.

BACKGROUND: Although several studies have evaluated dynamic contrast-enhanced (DCE) MRI in the orbit, showing its utility when detecting and diagnosing orbital lesions, none have evaluated the pharmacokinetic models. PURPOSE: To provide a quality-based pharmacokinetic model selection for characterizing orbital lesions using DCE-MRI at 3.0T. STUDY TYPE: Prospective. POPULATION: From December 2015 to April 2017, 151 patients with an orbital lesion underwent MRI prior to surgery, including a high temporal resolution DCE sequence, divided into one training and one test dataset with 100 and 51 patients, respectively. FIELD STRENGTH/SEQUENCE: 3T/DCE. ASSESSMENT: Six different pharmacokinetic models were tested. STATISTICAL TESTS: Univariate and multivariate analyses were performed using Wilcoxon-2-sample tests and a logistic regression to compare parameters between malignant and benign tumors for each pharmacokinetic model for the whole cohort. Receiver operating characteristic (ROC) curve analyses were performed on the training dataset to determine area under curve (AUC) and optimal cutoff values for each pharmacokinetic model, then validated on the test dataset to calculate sensitivity, specificity, and accuracy. RESULTS: Regardless of the model, tissue blood flow and tissue blood volume values were significantly higher in malignant vs. benign lesions: 103.8-195.1 vs. 65-113.8, P [<10-4 -2.10-4 ] and 21.3-36.9 vs. 15.6-33.6, P [<10-4 -0.03] respectively. Extracellular volume fraction and permeability-surface area product or transfer constant appeared to be less relevant: 17.3-27.5 vs. 22.8-28.2, P [0.01-0.7], 1.7-4.9, P [0.2-0.9] and 9.5-38.8 vs. 8.1-22.8, P [<10-4 -0.6], respectively. ROC curves showed no significant differences in AUC between the different models. The two-compartment exchange (2CX) model ranked first for quality. DATA CONCLUSION: DCE MRI pharmacokinetic model-derived parameters appeared to be useful for discriminating benign from malignant orbital lesions. The 2CX model provided the best quality of modeling and should be recommended. Perfusion-related DCE parameters appeared to be significantly more relevant to the diagnostic process. Level of Evidence 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1514-1525.

Non-invasive assessment of placental perfusion in vivo using arterial spin labeling (ASL) MRI: A preclinical study in rats.

INTRODUCTION: Non-invasive assessment of placental perfusion is of great interest to characterize placental function in clinical practice. This article proposes a strictly non-invasive MRI technique using ASL to quantify placental blood flow in vivo. The aim of this study was to develop a fMRI tool to quantify placental blood flow (PBF) in rat, by using arterial spin labeling (ASL) MRI at 4.7 T. MATERIALS AND METHODS: MRI was performed with a dedicated magnet for small animals, in pregnant rats on day 20 of the 22-day gestation period. A Look-Locker flow-sensitive alternating inversion recovery gradient echo sequence was developed as ASL technique (TE: 1.55 ms; TR: 3.5 ms, TI: 56 ms, deltaTI: 56 ms, FA: 20°, Matrix: 128 × 128, 8 segments, 4 Nex). Labeling was performed with global and slice-selective inversions, and T1 map was obtained for each mode of inversion. PBF was then derived from a compartmental model of the variation of T1 between global and slice-selective inversions. RESULTS: The full protocol was completed and ASL image post-processing was successful in 18 rats. Forty-seven placentas were analyzed, with a mean PBF of 147 ±â€¯70 ml/min/100 g of placenta, consistent with published values of placental perfusion using invasive techniques. CONCLUSION: ASL MRI is feasible for the quantification of PBF in rats at 4.7 T. This technique, which requires no administration of contrast media, could have implications for non-invasive longitudinal and in vivo animal studies and may be useful for the management of human pregnancies.

Gray-level discretization impacts reproducible MRI radiomics texture features.

OBJECTIVES: To assess the influence of gray-level discretization on inter- and intra-observer reproducibility of texture radiomics features on clinical MR images. MATERIALS AND METHODS: We studied two independent MRI datasets of 74 lacrymal gland tumors and 30 breast lesions from two different centers. Two pairs of readers performed three two-dimensional delineations for each dataset. Texture features were extracted using two radiomics softwares (Pyradiomics and an in-house software). Reproducible features were selected using a combination of intra-class correlation coefficient (ICC) and concordance and coherence coefficient (CCC) with 0.8 and 0.9 as thresholds, respectively. We tested six absolute and eight relative gray-level discretization methods and analyzed the distribution and highest number of reproducible features obtained for each discretization. We also analyzed the number of reproducible features extracted from computer simulated delineations representative of inter-observer variability. RESULTS: The gray-level discretization method had a direct impact on texture feature reproducibility, independent of observers, software or method of delineation (simulated vs. human). The absolute discretization consistently provided statistically significantly more reproducible features than the relative discretization. Varying the bin number of relative discretization led to statistically significantly more variable results than varying the bin size of absolute discretization. CONCLUSIONS: When considering inter-observer reproducible results of MRI texture radiomics features, an absolute discretization should be favored to allow the extraction of the highest number of potential candidates for new imaging biomarkers. Whichever the chosen method, it should be systematically documented to allow replicability of results.

Assessment of human placental perfusion by intravoxel incoherent motion MR imaging.

PURPOSE: To provide functional information on the human placenta, including perfusion, and diffusion, with no contrast agent injection, and to study correlations between intravoxel incoherent motion (IVIM) placental parameters and fetal growth. MATERIALS AND METHODS: MRI was performed in women undergoing legal termination of pregnancy at 17-34 weeks, including a 4-b-value and 11-b-value DW sequences. The apparent diffusion coefficient (ADC), the restricted diffusion coefficient (D), the pseudoperfusion coefficient (D*), and the perfusion fraction (f) were calculated. Their relationships with gestational age, Z-scores for fetal and placental weight were evaluated by means of regression analysis. Logistic regression analysis was used to assess the ability of IVIM parameters to predict/detect intrauterine growth retardation (SGA). RESULTS: Fifty-five pregnant women, including nine cases of SGA (16%), were included in the study. The ADC (n = 55) showed a quadratic correlation with gestational age (p < .001) and a linear correlation with the fetal weight Z-score (p = .02). Mean ADC values were significantly different between normally growing and SGA fetuses (2.37 ± 0.25 versus 2.29 ± 0.33 10-3.mm2.s-1, p=.048). The perfusion fraction f (n = 23) showed a quadratic correlation with gestational age (p = .017) and a linear correlation with the fetal weight Z - score (p = .008). Mean f values differed significantly between normally growing and SGA fetuses (42.55 ± 9.30% versus 27.94 ± 8.76%, p = .002). The receiver operating characteristics (ROC) curve for f to predict SGA was produced (area under the ROC curve = 0.9). CONCLUSIONS: The observed association between f and fetal weight suggests that fMRI could be suitable for studying placental insufficiency and for identifying risk of SGA.

Assessment of Placental Perfusion in the Preeclampsia L-NAME Rat Model with High-Field Dynamic Contrast-Enhanced MRI.

PURPOSE: To evaluate placental function and perfusion in a rat model of preeclampsia infused with L-nitro-arginine methyl ester (L-NAME) by dynamic contrast-enhanced (DCE) MRI using gadolinium chelates. METHODS: Pregnant female Sprague-Dawley rats were fitted on embryonic day 16 (E16) with subcutaneous osmotic minipumps loaded to deliver, continuously, L-NAME (50 mg/day per rat; case group) or saline solution (control group). DCE MRI was performed on E19 using gadolinium chelates and a 4.7-T MRI apparatus for small animals. Quantitative analysis was performed using an image software program: placental blood flow (perfusion in mL/min/100 mL of placenta) and fractional volume of the maternal vascular placental compartment (ratio between the placental blood volume and the placental volume, Vb in %) were calculated by compartmental analysis. RESULTS: A total of 176 placentas (27 rats) were analyzed by DCE MRI (97 cases and 79 controls). The model was effective, inducing intrauterine growth retardation, as there was a significant difference between the two groups for placental weight (p < 0.01), fetal weight (p = 0.019), and fetal length (p < 0.01). There was no significant difference in placental perfusion between the L-NAME and control groups (140.1 ± 74.1 vs. 148.9 ± 97.4, respectively; p = 0.496). There was a significant difference between the L-NAME and control groups for Vb (53 ± 12.9 vs. 46.7 ± 9%, respectively; p < 0.01). CONCLUSION: In the L-NAME preeclampsia model, placental perfusion is normal and the fractional blood volume is increased, suggesting that preeclampsia is not always expressed as a result of decreased placental perfusion. This highlights the usefulness of MRI for investigating the physiopathology of preeclampsia.