Multi-institutional investigation into the robustness of intra-cranial multi-target stereotactic radiosurgery plans to patient setup errors.

PURPOSE: This study aimed to analyse correlations between planning factors including plan geometry and plan complexity with robustness to patient setup errors. METHODS: Multiple-target brain stereotactic radiosurgery (SRS) plans were obtained through the Trans-Tasman Radiation Oncology Group (TROG) international treatment planning challenge (2018). The challenge dataset consisted of five intra-cranial targets with a 20 Gy prescription. Setup error was simulated using an in-house tool. Dose to targets was assessed via dose covering 99 % (D99 %) of gross tumour volume (GTV) and 98 % of planning target volume (PTV). Dose to organs at risk was assessed using volume of normal brain receiving 12 Gy and maximum dose covering 0.03 cc of brainstem. Plan complexity was assessed via edge metric, modulation complexity score, mean multi-leaf collimator (MLC) gap, mean MLC speed and plan modulation. RESULTS: Even for small (0.5 mm/°) errors, GTV D99 % was reduced by up to 20 %. The strongest correlation was found between lower complexity plans (larger mean MLC gap and lower edge metric) and higher robustness to setup error. Lower complexity plans had 1 %-20 % fewer targets/scenarios with GTV D99 % falling below the specified tolerance threshold. These complexity metrics correlated with 100 % isodose volume sphericity and dose conformity, though similar conformity was achievable with a range of complexities. CONCLUSIONS: A higher level of importance should be directed towards plan complexity when considering plan robustness. It is recommended when planning multi-target SRS, larger MLC gaps and lower MLC aperture irregularity be considered during plan optimisation due to higher robustness should patient positioning errors occur.

Highlights and hot topics in GPCR research from 'Down Under'.

LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

Development of Putative Bivalent Dicovalent Ligands for the Adenosine A1 Receptor.

Accumulating evidence suggests that G protein-coupled receptors (GPCRs) can exist and function in homodimer and heterodimer forms. The adenosine A1 receptor (A1R) has been shown to form both homodimers and heterodimers, but there is a lack of chemical tools to study these dimeric receptor populations. This work describes the synthesis and pharmacological evaluation of a novel class of bivalent GPCR chemical tools, where each ligand moiety of the bivalent compound contains a sulfonyl fluoride covalent warhead designed to be capable of simultaneously reacting with each A1R of an A1R homodimer. The novel compounds were characterised using radioligand binding assays, including washout assays, and functionally in cAMP assays. The bivalent dicovalent compounds were competitive A1R antagonists and showed evidence of covalent binding and simultaneous binding across an A1R homodimer. Greater selectivity for A1R over the adenosine A3 receptor was observed for bivalent dicovalent over the equivalent monovalent compounds, indicating subtype selectivity can be achieved with dual occupation by a bivalent dicovalent ligand.

Feeding Ration Impacts Larval Pimephales Promelas 7-Day Subchronic Growth Endpoint: Case Study with Perfluorooctanesulfonic Acid.

The larval fathead minnow, Pimephales promelas, 7-day subchronic survival and growth standard toxicity test method is commonly used for research and regulatory testing of effluents and compounds, including emerging contaminants such as Perfluorooctanesulfonic Acid (PFOS). Existing feeding guidelines for testing are described in multiple methods but are open to interpretation. The current study sought to determine the impact of feeding ration on P. promelas survival and biomass during a subchronic exposure to PFOS. The study was conducted in two phases: (1) a control experiment to determine the most significant feeding ration factors that maximize biomass, with consideration to laboratory logistics, and (2) application of down-selected feeding rations in a PFOS exposure to determine toxicity reference values. The control optimization study supported that feeding ration and feeding frequency were significant factors in fish biomass. In the subsequent PFOS study, fish were fed a high or low ration of Artemia twice daily, while exposed to 0.3 to 3.4 mg/L PFOS. Fish fed a high ration of Artemia had significantly (p < 0.05) greater biomass than fish fed a low ration in all exposure concentrations except 3.4 mg/L, where survival was low in both treatments. The feeding ration was not a significant factor on the survival endpoint for either treatment, but the PFOS concentration was (p < 0.0001) (high ration LC50 = 2.44 mg/L; low ration LC50 = 2.25 mg/L). These findings contribute to a better understanding of the impact feeding ration has in toxicity assessments and downstream regulatory decisions.

The role of an abbreviated ultrasound in the evaluation of necrotizing enterocolitis.

BACKGROUND: Bowel ultrasound is a useful diagnostic tool in the diagnosis and management of necrotizing enterocolitis (NEC) but can be time-consuming and requires technical expertise, particularly for assessing pneumatosis. Previous literature on sonographic evaluation of NEC has focused on a full bowel ultrasound protocol, but the utility of an abbreviated protocol primarily aimed at identifying high-risk sonographic findings without focused bowel assessment has not been well studied. OBJECTIVE: This study aims to describe the diagnostic accuracy of an abbreviated ultrasound protocol for identifying high-risk NEC findings. MATERIALS AND METHODS: This is a retrospective, institutional review board-approved study. We identified all abbreviated NEC ultrasounds performed between January 2014 and August 2022 at our institution. Exams were reviewed for the presence of high-risk findings including pneumoperitoneum, fluid collections, and complex free fluid. Clinical outcome was categorized as poor or good depending on if emergent surgical intervention or death related to NEC occurred. The frequency of follow-up NEC ultrasounds was reviewed to determine if new findings affected outcome. Sensitivity, specificity, and positive and negative predictive values were generated to assess the performance of the abbreviated ultrasounds to identify high-risk findings. RESULTS: A total of 84 abbreviated abdominal ultrasounds were performed on 73 children. Median age at the time of ultrasound was 41 days (interquartile range (IQR) 53 days) and median gestational age was 35 weeks and 3 days (IQR 80 days), and 44/73 (60%) were male. Thirteen ultrasounds had at least one high-risk finding with nine (69%) resulting in a poor outcome, including seven surgical interventions and four deaths. Two patients had surgical intervention and died as a result of necrotizing enterocolitis. Ultrasounds without high-risk findings were not associated with poor clinical outcomes. Sensitivity, specificity, positive predictive value, and negative predictive value of the abbreviated NEC ultrasound were 100% (95% CI 60-100%), 95% (95% CI 86-98%), 69% (95% CI 39-90%), and 100% (95% CI 94-100%), respectively. Twelve abbreviated ultrasounds were followed by a second NEC ultrasound within 5 days. Five follow-up ultrasounds demonstrated new high- or low-risk findings, but the new findings did not correlate with a change in outcome as predicted by the initial ultrasound. CONCLUSION: An abbreviated NEC ultrasound can be of clinical utility in predicting poor outcomes, particularly during non-business hours when resources are limited.

GraphormerDTI: A graph transformer-based approach for drug-target interaction prediction.

The application of Artificial Intelligence (AI) to screen drug molecules with potential therapeutic effects has revolutionized the drug discovery process, with significantly lower economic cost and time consumption than the traditional drug discovery pipeline. With the great power of AI, it is possible to rapidly search the vast chemical space for potential drug-target interactions (DTIs) between candidate drug molecules and disease protein targets. However, only a small proportion of molecules have labelled DTIs, consequently limiting the performance of AI-based drug screening. To solve this problem, a machine learning-based approach with great ability to generalize DTI prediction across molecules is desirable. Many existing machine learning approaches for DTI identification failed to exploit the full information with respect to the topological structures of candidate molecules. To develop a better approach for DTI prediction, we propose GraphormerDTI, which employs the powerful Graph Transformer neural network to model molecular structures. GraphormerDTI embeds molecular graphs into vector-format representations through iterative Transformer-based message passing, which encodes molecules' structural characteristics by node centrality encoding, node spatial encoding and edge encoding. With a strong structural inductive bias, the proposed GraphormerDTI approach can effectively infer informative representations for out-of-sample molecules and as such, it is capable of predicting DTIs across molecules with an exceptional performance. GraphormerDTI integrates the Graph Transformer neural network with a 1-dimensional Convolutional Neural Network (1D-CNN) to extract the drugs' and target proteins' representations and leverages an attention mechanism to model the interactions between them. To examine GraphormerDTI's performance for DTI prediction, we conduct experiments on three benchmark datasets, where GraphormerDTI achieves a superior performance than five state-of-the-art baselines for out-of-molecule DTI prediction, including GNN-CPI, GNN-PT, DeepEmbedding-DTI, MolTrans and HyperAttentionDTI, and is on a par with the best baseline for transductive DTI prediction. The source codes and datasets are publicly accessible at https://github.com/mengmeng34/GraphormerDTI.

Pelvic Floor Dysfunction Among Persons With Marfan and Loeys-Dietz Syndrome.

IMPORTANCE: Connective tissue disorders are proposed in the literature to be predisposing risk factors for pelvic floor disorders. Prior data characterizing the prevalence of and symptom burden related to pelvic floor disorders are limited for individuals with Marfan syndrome and are nonexistent for those with Loeys-Dietz syndrome. OBJECTIVE: The objective of this study was to determine the prevalence and severity of symptoms related to pelvic floor disorders among individuals with Marfan syndrome and Loeys-Dietz syndrome using the Pelvic Floor Distress Inventory-20 (PFDI-20). STUDY DESIGN: In this cross-sectional study, a survey including the PFDI-20 was administered to biologically female individuals older than 18 years with a confirmed diagnosis of Marfan syndrome or Loeys-Dietz Syndrome. Respondents were solicited through the websites, email lists, and social media forums of The Marfan Foundation and The Loeys-Dietz syndrome Foundation. RESULTS: A total of 286 respondents were included in the final analysis, 213 with Marfan syndrome and 73 with Loeys-Dietz syndrome. The median PFDI-20 score of the cohort was 43.8. Individuals with Loeys-Dietz syndrome had higher PFDI-20 scores and were more likely to have established risk factors for pelvic floor disorders that correlated with their PFDI-20 scores compared with those with Marfan syndrome. CONCLUSIONS: Respondents with Marfan syndrome and Loeys-Dietz syndrome experience a high burden of symptoms related to pelvic floor disorders. Despite the similar pathophysiology and clinical manifestations of these disorders, there were differences in PFDI-20 responses that may suggest that these diseases differ in the ways they affect the pelvic floor.

High-Dose Acetaminophen with Concurrent CYP2E1 Inhibition Has Profound Anticancer Activity without Liver Toxicity.

Acetaminophen (AAP) is metabolized by a variety of pathways such as sulfation, glucuronidation, and fatty acid amide hydrolase-mediated conversion to the active analgesic metabolite AM404. CYP2E1-mediated metabolism to the hepatotoxic reactive metabolite NAPQI (N-acetyl-p-benzoquinone imine) is a minor metabolic pathway that has not been linked to AAP therapeutic benefits yet clearly leads to AAP liver toxicity. N-acetylcysteine (NAC) (an antioxidant) and fomepizole (a CYP2E1 inhibitor) are clinically used for the treatment of AAP toxicity. Mice treated with AAP in combination with fomepizole (plus or minus NAC) were assessed for liver toxicity by histology and serum chemistry. The anticancer activity of AAP with NAC and fomepizole rescue was assessed in vitro and in vivo. Fomepizole with or without NAC completely prevented AAP-induced liver toxicity. In vivo, high-dose AAP with NAC/fomepizole rescue had profound antitumor activity against commonly used 4T1 breast tumor and lewis lung carcinoma lung tumor models, and no liver toxicity was detected. The antitumor efficacy was reduced in immune-compromised NOD-scid IL2Rgammanull mice, suggesting an immune-mediated mechanism of action. In conclusion, using fomepizole-based rescue, we were able to treat mice with 100-fold higher than standard dosing of AAP (650 mg/kg) without any detected liver toxicity and substantial antitumor activity. SIGNIFICANCE STATEMENT: High-dose acetaminophen can be given concurrently with CYP2E1 inhibition to allow for safe dose escalation to levels needed for anticancer activity without detected evidence of toxicity.

Multi-institutional investigation into the robustness of intra-cranial multi-target stereotactic radiosurgery plans to delivery errors.

BACKGROUND: The use of modulated techniques for intra-cranial stereotactic radiosurgery (SRS) results in highly modulated fields with small apertures, which may be susceptible to uncertainties in the delivery device. PURPOSE: This study aimed to quantify the impact of simulated delivery errors on treatment plan dosimetry and how this is affected by treatment planning system (TPS), plan geometry, delivery technique, and plan complexity. A beam modelling error was also included as context to the dose uncertainties due to treatment delivery errors. METHODS: Delivery errors were assessed for multiple-target brain SRS plans obtained through the Trans-Tasman Radiation Oncology Group (TROG) international treatment planning challenge (2018). The challenge dataset consisted of five intra-cranial targets, each with a prescription of 20 Gy. Of the final dataset of 54 plans, 51 were created using the volumetric modulated arc therapy (VMAT) technique and three used intensity modulated arc therapy (IMRT). Thirty-five plans were from the Varian Eclipse TPS, 17 from Elekta Monaco TPS, and one plan each from RayStation and Philips Pinnacle TPS. The errors introduced included: monitor unit calibration errors, multi-leaf collimator (MLC) bank offset, single MLC leaf offset, couch rotations, and collimator rotations. Dosimetric leaf gap (DLG) error was also included as a beam modelling error. Dose to targets was assessed via dose covering 98% of planning target volume (PTV) (D98%), dose covering 2% of PTV (D2%), and dose covering 99% of gross tumor volume (GTV) (D99%). Dose to organs at risk (OARs) was assessed using the volume of normal brain receiving 12 Gy (V12Gy), mean dose to normal brain, and maximum dose covering 0.03cc brainstem (D0.03cc). Plan complexity was also assessed via edge metric, modulation complexity score (MCS), mean MLC gap, mean MLC speed, and plan modulation (PM). RESULTS: PTV D98% showed high robustness on average to most errors with the exception of a bank shift of 1.0 mm and large rotational errors ≥1.0° for either the couch or collimator. However, in some cases, errors close to or within generally accepted machine tolerances resulted in clinically relevant impacts. The greatest impact upon normal brain V12Gy, mean dose to normal brain, and D0.03cc brainstem was found for DLG error in alignment with other recent studies. All delivery errors had on average a minimal impact across these parameters. Comparing plans from the Monaco TPS and the Eclipse TPS, showed a lesser increase to V12Gy, mean dose to normal brain, and D0.03cc brainstem for Monaco plans (p < 0.01) when DLG error was simulated. Monaco plans also correlated to lower plan complexity. Using Spearman's correlation coefficient (r) a strong negative correlation (r ≤ -0.8) was found between the mean MLC gap and dose to OARs for DLG errors. CONCLUSIONS: Reducing MLC complexity and using larger mean MLC gaps is recommended to improve plan robustness and reduce sensitivity to delivery and modelling errors. For cases in which the calculated dose distribution or dose indices are close to the clinically acceptable limits, this is especially important.

Small molecule allosteric modulation of the adenosine A1 receptor.

G protein-coupled receptors (GPCRs) represent the target for approximately a third of FDA-approved small molecule drugs. The adenosine A1 receptor (A1R), one of four adenosine GPCR subtypes, has important (patho)physiological roles in humans. A1R has well-established roles in the regulation of the cardiovascular and nervous systems, where it has been identified as a potential therapeutic target for a number of conditions, including cardiac ischemia-reperfusion injury, cognition, epilepsy, and neuropathic pain. A1R small molecule drugs, typically orthosteric ligands, have undergone clinical trials. To date, none have progressed into the clinic, predominantly due to dose-limiting unwanted effects. The development of A1R allosteric modulators that target a topographically distinct binding site represent a promising approach to overcome current limitations. Pharmacological parameters of allosteric ligands, including affinity, efficacy and cooperativity, can be optimized to regulate A1R activity with high subtype, spatial and temporal selectivity. This review aims to offer insights into the A1R as a potential therapeutic target and highlight recent advances in the structural understanding of A1R allosteric modulation.

Structure-based virtual screening discovers potent and selective adenosine A1 receptor antagonists.

Development of subtype-selective leads is essential in drug discovery campaigns targeting G protein-coupled receptors (GPCRs). Herein, a structure-based virtual screening approach to rationally design subtype-selective ligands was applied to the A1 and A2A adenosine receptors (A1R and A2AR). Crystal structures of these closely related subtypes revealed a non-conserved subpocket in the binding sites that could be exploited to identify A1R selective ligands. A library of 4.6 million compounds was screened computationally against both receptors using molecular docking and 20 A1R selective ligands were predicted. Of these, seven antagonized the A1R with micromolar activities and several compounds displayed slight selectivity for this subtype. Twenty-seven analogs of two discovered scaffolds were designed, resulting in antagonists with nanomolar potency and up to 76-fold A1R-selectivity. Our results show the potential of structure-based virtual screening to guide discovery and optimization of subtype-selective ligands, which could facilitate the development of safer drugs.

Sex Differences in Lung Cancer.

Sex disparities in the incidence and mortality of lung cancer have been observed since cancer statistics have been recorded. Social and economic differences contribute to sex disparities in lung cancer incidence and mortality, but evidence suggests that there are also underlying biological differences that contribute to the disparity. This review summarizes biological differences which could contribute to the sex disparity. Sex hormones and other biologically active molecules, tumor cell genetic differences, and differences in the immune system and its response to lung cancer are highlighted. How some of these differences contribute to disparities in the response to therapies, including cytotoxic, targeted, and immuno-therapies, is also discussed. We end the study with a discussion of our perceived future directions to identify the key biological differences which could contribute to sex disparities in lung cancer and how these differences could be therapeutically leveraged to personalize lung cancer treatment to the individual sexes.

The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at multiple stages during the drug discovery process, from aiding our understanding of the fundamental actions of GPCRs to the discovery of new ligand-GPCR interactions or the prediction of clinical responses. Here, we provide an overview of the concepts behind artificial intelligence, including the subfields of machine learning and deep learning. We summarise the published applications of artificial intelligence to different stages of the GPCR drug discovery process. Finally, we reflect on the benefits and limitations of artificial intelligence and share our vision for the exciting potential for further development of applications to aid GPCR drug discovery. In addition to making the drug discovery process "faster, smarter and cheaper," we anticipate that the application of artificial intelligence will create exciting new opportunities for GPCR drug discovery.

Targeting G protein-coupled receptors for heart failure treatment.

Heart failure remains a leading cause of morbidity and mortality worldwide. Current treatment for patients with heart failure include drugs targeting G protein-coupled receptors such as ß-adrenoceptor antagonists (ß-blockers) and angiotensin II type 1 receptor antagonists (or angiotensin II receptor blockers). However, many patients progress to advanced heart failure with persistent symptoms, despite treatment with available therapeutics that have been shown to reduce mortality and mortality. GPCR targets currently being explored for the development of novel heart failure therapeutics include adenosine receptor, formyl peptide receptor, relaxin/insulin-like family peptide receptor, vasopressin receptor, endothelin receptor and the glucagon-like peptide 1 receptor. Many GPCR drug candidates are limited by insufficient efficacy and/or dose-limiting unwanted effects. Understanding the current challenges hindering successful clinical translation and the potential to overcome existing limitations will facilitate the future development of novel heart failure therapeutics.

The role of the adenosine system in epilepsy and its comorbidities.

Epilepsy is one of the most serious and common chronic neurological conditions, characterised by recurrent hypersynchronous electrical activity in the brain that lead to seizures. Despite over 50 million people being affected worldwide, only ~70% of people with epilepsy have their seizures successfully controlled with current pharmacotherapy, and many experience significant psychiatric and physical comorbidities. Adenosine, a ubiquitous purine metabolite, is a potent endogenous anti-epileptic substance that can abolish seizure activity via the adenosine A1 G protein-coupled receptor. Activation of A1 receptors decreases seizure activity in animal models, including models of drug-resistant epilepsy. Recent advances have increased our understanding of epilepsy comorbidities, highlighting the potential for adenosine receptors to modulate epilepsy-associated comorbidities, including cardiovascular dysfunction, sleep and cognition. This review provides an accessible resource of the current advances in understanding the adenosine system as a therapeutic target for epilepsy and epilepsy-associated comorbidities.

The epigenetic regulation of cancer cell recovery from therapy exposure and its implications as a novel therapeutic strategy for preventing disease recurrence.

The ultimate goal of cancer therapy is the elimination of disease from patients. Most directly, this occurs through therapy-induced cell death. Therapy-induced growth arrest can also be a desirable outcome, if prolonged. Unfortunately, therapy-induced growth arrest is rarely durable and the recovering cell population can contribute to cancer recurrence. Consequently, therapeutic strategies that eliminate residual cancer cells reduce opportunities for recurrence. Recovery can occur through diverse mechanisms including quiescence or diapause, exit from senescence, suppression of apoptosis, cytoprotective autophagy, and reductive divisions resulting from polyploidy. Epigenetic regulation of the genome represents a fundamental regulatory mechanism integral to cancer-specific biology, including the recovery from therapy. Epigenetic pathways are particularly attractive therapeutic targets because they are reversible, without changes in DNA, and are catalyzed by druggable enzymes. Previous use of epigenetic-targeting therapies in combination with cancer therapeutics has not been widely successful because of either unacceptable toxicity or limited efficacy. The use of epigenetic-targeting therapies after a significant interval following initial cancer therapy could potentially reduce the toxicity of combination strategies, and possibly exploit essential epigenetic states following therapy exposure. This review examines the feasibility of targeting epigenetic mechanisms using a sequential approach to eliminate residual therapy-arrested populations, that might possibly prevent recovery and disease recurrence.

The impact of cryo-EM on determining allosteric modulator-bound structures of G protein-coupled receptors.

G-protein coupled receptors (GPCRs) are important therapeutic targets for the treatment of human disease. Although GPCRs are highly successful drug targets, there are many challenges associated with the discovery and translation of small molecule ligands that target the endogenous ligand-binding site for GPCRs. Allosteric modulators are a class of ligands that target alternative binding sites known as allosteric sites and offer fresh opportunities for the development of new therapeutics. However, only a few allosteric modulators have been approved as drugs. Advances in GPCR structural biology enabled by the cryogenic electron microscopy (cryo-EM) revolution have provided new insights into the molecular mechanism and binding location of small molecule allosteric modulators. This review highlights the latest findings from allosteric modulator-bound structures of Class A, B, and C GPCRs with a focus on small molecule ligands. Emerging methods that will facilitate cryo-EM structures of more difficult ligand-bound GPCR complexes are also discussed. The results of these studies are anticipated to aid future structure-based drug discovery efforts across many different GPCRs.

Diagnosing Midline Neck Masses: Comparing Clinical Exam, the SIST Score, and the 4S Algorithm.

OBJECTIVE: To validate and compare novel ultrasound scoring systems for dermoid cysts and thyroglossal duct cysts among pediatric patients. STUDY DESIGN: Retrospective study. SETTING: Tertiary care children's hospital. METHODS: An electronic medical record query of patients younger than 18 years old who underwent primary excision of a neck mass between January 2005 and February 2022, who underwent preoperative ultrasound, and had final histopathologic diagnosis of either thyroglossal duct cysts or dermoid cysts. This generated 260 results, of which 134 patients met the inclusion criteria. Charts were reviewed for demographic data, clinical impressions, and radiographic studies. Radiologists blindly reviewed ultrasound for SIST score (septae + irregular walls + solid components = thyroglossal), and 4S algorithm (Septations, depth relative to Strap muscles, Shape, Solid parts). Statistical analyses were performed to determine the accuracy of each diagnostic modality. RESULTS: Of 134 patients, 90 (67%) had a final histopathologic diagnosis of thyroglossal duct cysts, and 44 (33%) were dermoid cysts. The accuracy of clinical diagnosis was 52%, and preoperative ultrasound report accuracy was 31%. The 4S and SIST accuracies were each 84%. CONCLUSION: Both the 4S algorithm and SIST score provide increased accuracy of diagnosis relative to standard preoperative ultrasound assessment. Neither scoring modality was determined to be superior. Further research is warranted in improving the accuracy of preoperative assessments for pediatric congenital neck masses.

Ultrasound for necrotizing enterocolitis: how can we optimize imaging and what are the most critical findings?

Necrotizing enterocolitis (NEC) is a common condition in the neonatal intensive care unit that continues to present challenges in terms of diagnosis and management. Traditionally NEC has been diagnosed and managed by clinical and radiographic findings, but US has shown promise in characterizing and prognosticating NEC. In this manuscript we review the abdominal US technique for NEC, the clinical significance of individual sonographic findings of NEC, and how US can be integrated in the clinical decision process for diagnosing and managing NEC. We also discuss the potential value-added role of a limited abdominal US protocol that focuses on the sonographic findings most indicative of a poor prognosis to include pneumoperitoneum, complex free fluid and focal fluid collections.

The ductus arteriosus: a review of embryology to intervention.

This article reviews the physiology of the ductus arteriosus, the pathophysiology of the patent ductus arteriosus (PDA), and the role advanced imaging such as computed tomography (CT) and magnetic resonance imaging (MRI) can play in guiding diagnosis and percutaneous or surgical intervention. A PDA can have variable clinical and radiologic presentations and can be important to characterize in patients with vascular rings, aortic maldevelopment and congenital heart disease. An understanding of the PDA and the application of CT and MRI can allow the radiologist to provide key information to physicians who plan to close a PDA or maintain PDA patency in the setting of ductal-dependent congenital heart disease.