However, the applicability of this technology for drug screening is limited, as it is complex to use and features low throughput. Recent studies have demonstrated that 3D-nanostructured electrodes enable to obtain intracellular signals from many cardiomyocytes in parallel; however, the tedious electrode fabrication and limited measurement duration still remain major issues for cardiotoxicity testing. Here, we demonstrate how porous Pt-black electrodes, arranged in high-density micro-electrode arrays, can be used to record intracellular-like signals of cardiomyocytes at large scale repeatedly over an extended period of time. The developed technique, which yields highly parallelized electroporations using stimulation voltages around 1 V peak-to-peak amplitude, enabled intracellular-like recordings at high success rates without causing significant alteration in key electrophysiological features. In a proof-of-concept study, we investigated electrophysiological modulations induced by two clinically applied drugs, nifedipine and quinidine. As the obtained results were in good agreement with previously published data, we are confident that the developed technique has the potential to be routinely used in in vitro platforms for cardiotoxicity screening. Pharmaceutical compounds may have cardiotoxic properties, triggering potentially life-threatening arrhythmias. To investigate proarrhythmic effects of drugs, the patch clamp technique has been used as the gold standard for characterizing the electrophysiology of cardiomyocytes  In addition, drugs that are not targeted at the cardiovascular system need to go through cardiac risk assessment, as they may have cardiotoxic or proarrhythmic features.2 Numerous drugs have been with-drawn from the market due to reports of cardiotoxicity or potentially life-threatening off-target effects,3 such as QT-interval prolongation, myocardial infarction, and torsades de pointes (TdP) tachycardia. For instance, doxorubicin, a topoisomerase II inhibitor, used for chemotherapy of cancers, has well-known side effects on the heart, such as arrhythmia and cardiomyopathy.4 These side effects may endanger the life of the patient and preclude a successful completion of the treatment. Unfortunately, drug-induced cardiotoxicity is often only detected after 5–10 years of drug development in clinical trials, or even after approval and use with larger patient groups. In addition to life-threatening risks for patients, there are substantial financial losses for pharmaceutical companies upon withdrawal of medically efficient, yet cardiotoxic drugs.Cardiovascular diseases remain the leading cause of death in Western countriesin vitro models, such as Chinese hamster ovary (CHO) cells and human embryonic kidney 293 (HEK293) cells that express specific ion channels. Although animal models provide insights into multiorgan interactions, they have several limitations, including interspecies differences, low throughput, high costs, and ethical concerns.7 CHO and HEK293 cells expressing a single-ion-channel gene are limited in recapitulating the properties of human cardiomyocytes (CMs).8 Importantly, genetic and physiological discrepancies between such models and human heart cells challenge the translation of research outcomes to the clinical setting. The advent of human-induced pluripotent stem cell (iPSC) technology and protocols to differentiate them into CMs enables to perform in vitro drug screening and risk assessment on human cells under physiological conditions that resemble those of the human heart.9In the past, drug responses and cardiotoxic effects were evaluated in animal or in vitro10 and to investigate proarrhythmic effects of drugs. Although the originally manual and individual patching of cells provides precise measurement of voltage and current dynamics, the intense training that is needed for applying the patch clamp techniques and the low-throughput limit its application for testing on a large scale. Another drawback of the technique is that it is highly invasive. The patch pipette ruptures the cell membrane over an area of approximately 1–2 μm in diameter upon intracellular access. The membrane remains open for 30–60 min, while the pipette solution mixes with the cell cytosol11 causing gradual cell death.12 The use of automated patch clamp (APC) techniques allows for intracellular recordings of a few hundred suspended cells in parallel by aspirating the cells to orifices and subsequent cell opening,13 which makes APC suitable for high-throughput screening. However, for APC, CMs need to be provided in single-cell suspension, which is different from physiological conditions in the human heart, where CMs form a network and beat synchronously. Fluorescence-based imaging techniques, such as voltage-sensitive dyes or voltage-sensitive fluorescent proteins, are comparably noninvasive and can be used to perform recordings of many cells at a time. Nevertheless, there are limitations concerning cytotoxicity, phototoxicity, photobleaching, or limited efficiency of protein expression.15The patch clamp technique has been the gold standard for measuring action potentials (APs) and ionic currents across the cell membrane 19 at high spatiotemporal or even subcellular resolution.21 Following a relatively simple procedure, several studies reported on utilizing MEAs to assess the proarrhythmic effects of drugs on human iPSC-derived CMs.24 Although extracellular recordings with MEAs have shown a great potential for large-scale cardiotoxicity assessment, extracellular measurement alone is limited in capturing the full dynamics of membrane processes and associated electrical potential alterations in comparison to intracellular AP recordings.25The main advantage of applying microelectrode arrays (MEAs) or, specifically, high-density microelectrode arrays (HD-MEAs) is that it enables long-term and noninvasive extracellular recordings of hundreds to thousands of cells32 have shown that MEAs can be used to measure not only extracellular signals but also intracellular-like signals, by transiently opening nanopores in the cell membrane. Advances in nanotechnology improved the coupling of plasma membrane and electrodes by integrating 3D nanostructures, such as nanopillars,35 nanowires39 nanocrowns,40 nanobranches41 gold-mush-rooms,42 and nanovolcanos,43 all of which enabled spontaneous intracellular access or access via electroporation. Although nanostructured electrodes promote membrane penetration or are advantageous for being engulfed by the cell membrane, the fabrication of such nanostructures requires intensive and expensive cleanroom processing, which, to date, impeded application in large-scale drug screening and cardiotoxicity assays in the pharmaceutical industry. In addition, nanopillar or nanowire electrodes significantly attenuate voltage signals due to the high electrode impedance in comparison to planar electrodes.25 MEAs featuring planar electrodes have been demonstrated to record intracellular-like signals after optoacoustic poration31 or electroporation.28Over the past years, numerous reports44 require that electrical signals—after drug exposure—are compared to baseline signals of the same CMs before drug exposure and that data from large numbers of cells are collected and analyzed to exclude spurious effects and avoid bias. In addition, the evaluation of CM network and signal propagation parameters greatly benefits from having a large sensor density and many data points. Finally, the ability to collect large numbers of data points at once—without having to reproduce the assays many times to achieve the desired statistical power—constitutes a big advantage for drug testing. Repeated intracellular access at a large scale is desirable for reliable cardiotoxicity testing with iPSC-derived CMs, and the effects of (repeated) electroporations on the electro-physiology of the CMs need to be investigated.Optoacoustic poration enabled to record intracellular signals of a few thousand CMs, but this method requires an integration of the MEA with a laser and microscopy system, which renders the setup bulky and complex. While electroporation using commercially available MEAs yielded intracellular-like recordings, the number of CMs that could be measured at a time was limited to a few tens. Moreover, substantial cell-to-cell variations of the electrophysiological waveform characteristics of iPSC-derived CMs16 that enabled us to repeatedly record intracellular-like signals of hundreds of iPSC-derived CMs. The method does not require the fabrication of nanostructures or the use of complex setups to achieve intracellular-like recordings. It relies on the use of electrical stimuli that porate the cell membrane only briefly and can be applied multiple times over an extended period of several hours. The CMs were observed to recover quickly and could be repeatedly porated for a series of intracellular-like measurements. The compactness and simplicity of the setup enabled us to perform experiments in a standard, humidified CO2 incubator, which is a great advantage for long-term cellular assays. We repeatedly electroporated hundreds of iPSC-derived CMs at the same electrode locations within defined time intervals and investigated the corresponding effects on extracellular and intracellular-like signals. We demonstrated that the proposed technology may help to set up a cardiotoxicity assay platform to assess short- and long-term proarrhythmic effects of preclinical drugs. The potential to detect cardiotoxicity at an early stage of drug development will promote patient safety and will be beneficial for cardiac testing in the pharmaceutical industry.Therefore, we developed an electroporation-based method for an existing HD-MEAQuinidine (Cat. 22600)’ nifedipine (Cat. N7634), dimethyl sulfoxide , and human fibronectin (Cat. FC010) were purchased from Merck KGaA . Fetal bovine serum  and Intracellular Fixation Buffer (Cat. FB001) were purchased from Thermo Fisher Scientific (Massachusetts). Y-27632 (Cat. 72302) was purchased from STEMCELL Technologies  and dissolved in sterile deionized water to prepare a 10 mM stock solution. During drug experiments, the concentration of DMSO in the culture medium did not exceed 0.1%. Serum-free CM culture medium used in this study was RPMI with GlutaMAX and HEPES (Cat. 72400021), supplemented with B27 (Cat. 17504044) and PenStrep (Cat. 15070063), all purchased from Thermo Fisher Scientific (Massachusetts).45Frozen vials of human iPSC-derived CMs were purchased together with iCell Plating Medium and iCell Maintenance Medium from Fujifilm Cellular Dynamics International (Wisconsin). The cells were thawed and cultured following the manufacturer’s guidelines. The healthy-donor-derived iPSC line, CW30318CC1, was obtained from the CIRM hPSC Repository funded by the California Institute of Regenerative Medicine . This cell line was differentiated into CMs following a previously published protocol.16 were used to record extracellular and intracellular signals of CMs. The HD-MEA accommodates 26,400 electrodes in an area of ∼4 × 2 mm2. The data were sampled at 20 kHz. The switch matrix scheme within the HD-MEA was used to route electrodes to 1024 readout channels for simultaneous readout and to 32 stimulation/poration units. We used and compared two types of electrodes: standard 5.5 × 9.3 μm2 rectangular electrodes and smaller circular electrodes with a diameter of 4 μm, all of which were spaced at 17.5 μm center-to-center pitch.Complementary metal-oxide semiconductor (CMOS)-based HD-MEAs46 , purchased from Fujifilm Cellular Dynamics International (Wisconsin), which are commercially available and have been widely used for drug testing in the literature.27Before plating iPSC-derived CMs, HD-MEAs were sterilized in 70% ethanol for 10 min and rinsed three times with sterile deionized water. The electrode array was coated with human fibronectin at a concentration of 50 2 incubator at 37 °C. HD-MEA chips were mounted on MaxOne Recording Units  for data acquisition and control of electroporation.All extracellular and intracellular measurements were performed in a humidified, 5% CO16 We applied rectangular biphasic voltage pulses of 1-2 V peak-to-peak amplitude (Vpp) and 50 μs to 1 ms phase duration at 1 ms interpulse intervals (IPIs). The poration duration was maximally 35 s. Although the applied voltage amplitude exceeded that of the water window in some instances, the frequency of the AC signal was large enough (333 Hz to 10 kHz range) to not produce electrolysis, and we did not observe any signs of gas evolution. After delivery of the respective voltage pulses, electrodes were disconnected from the stimulation units to perform the voltage recordings. Up to 990 electrodes could be simultaneously connected to stimulation units to perform voltage stimulation.Data acquisition and electroporations were performed using the MaxLive Software  in conjunction with a custom-written Python script for API controls. For electroporation, the selected electrodes were connected to on-chip stimulation/poration units, The core of each unit was a class-AB opamp, capable of driving loads as large as 10 nF, while maintaining a low static power consumption , EGTA (5), HEPES (10), Mg-ATP (5), pH adjusted to 7.2 with KOH.47 We recorded APs of the CMs in the whole-cell current clamp mode . The data were low-pass filtered at 10 kHz and sampled at a rate of 20 kHz . The pClamp suite was used as the recording software . The data were not corrected for the liquid junction potential, which was approximately 3.1 mV. During whole-cell patch recording, the same cell was electroporated through the HD-MEA, and intracellular-like signals were recorded simultaneously by the patch pipette and the HD-MEA electrode.To record intracellular signals of CMs with a patch pipette simultaneously with intracellular-like signals through the HD-MEA, we combined the HD-MEA setup with a patch clamp setup and performed recordings outside the incubator. Two data streams from the simultaneous recordings were synchronized by aligning periodic pulses which were sent to both setups. All measurements reported here were obtained from interconnected and spontaneously beating cardiomyocytes. The culture on the HD-MEA was perfused at 37 °C throughout the experiment with RPMI 1640 with GlutaMAX with HEPES. The resistance of the patch pipettes was 5–7 MΩ. The patch pipette solution contained (in mM): KCI (140), MgClμM and 100 nM, respectively. Postdose recordings were obtained 30 min after the drug administration to allow for equilibration of the compounds in the culture medium.48 The experiments were performed using the following electroporation parameters: rectangular pulses of 1 V peak-to-peak amplitude (Vpp), 200 μs phase duration, 1 ms interpulse interval (IPI), 25,000 pulses simultaneously delivered through each of 200 electrodes of 4 μm diameter. The used parameters are listed in Following the manufacturer’s protocol, iCell Cardiomyocytes  were plated on HD-MEAs and kept in a humidified incubator for at least 10 days. After connecting the HD-MEA chips to the recording units in the humidified incubator, CMs were allowed to equilibrate for at least 30 min. Before drug administration, baseline measurements were performed three times over a time span of 2 h. The reason for this procedure was to rule out the possibility that the electrophysiological perturbation observed after drug administration would arise from CMs themselves and not from the drugs. Stock solutions of quinidine and nifedipine were prepared by dissolving the compounds in DMSO. After baseline measurements, quinidine and nifedipine were added to each of the HD-MEA culture medium to reach final concentrations of 1 μV, and (ii) the peak width was larger than 25 ms. The corresponding AP waveforms were normalized in amplitude since intracellular-like signals obtained by HD-MEAs were attenuated nonuniformly on each electrode depending on cell–electrode sealing resistances or membrane pore sizes.42 The AP parameters used for analysis in this study are displayed in U test was used to compare drug responses to baseline control experiments with a significance level of 0.05. Analyses then yielded alterations or signal changes as mean value ± standard deviation.Intracellular-like signal waveforms after electro-porations were analyzed after adjustment for the amplifier offsets. The waveforms were preprocessed with custom-made MATLAB-based scripts. Three consecutive waveforms, taken either 9 s after poration end or after channel stabilization, were averaged to obtain a single waveform per channel. We considered measured waveforms as intracellular-like signals if (i) the peak amplitude of the waveform was larger than 500 49 After membrane permeabilization and blocking of nonspecific bindings, the samples were incubated with primary antibodies and, thereafter, with secondary antibodies. The used primary and secondary antibodies are listed in Cells on the HD-MEAs were fixated and prepared for immunostaining following a published protocol.Pt-black nanostructures on the HD-MEA electrodes were imaged using an FEI Helios NanoLab DualBeam 650 system after sputter-coating with 25 nm of gold. CMs on the HD-MEAs were fixated with IC Fixation Buffer at room temperature for 15 min and dehydrated by applying graded ethanol series. Subsequently, the sample was dried in a critical-point drier and sputter-coated with 5 nm of iridium. Focused-ion-beam-assisted sample cross section and images were acquired with a Xenon FIB-SEM TESCAN SOLARIS X system.50 Over time, the signal amplitudes of intracellular-like signals decreased, the signal waveforms showed a mix of intracellular-like and extracellular shapes, and the signal characteristics transited back to extracellular signals, as the membrane nanopores presumably resealed.This study was aimed at achieving transient intracellular access on-demand to CMs so that intracellular-like signals could be obtained multiple times within a longer time span without damaging the CMs. Access was enabled by the electrodeposited dendritic Pt-black nanostructures on the electrodes of the HD-MEA . The CM 51 that then led to local membrane opening. Comparably long intracellular measurements were obtained using 5.5 × 9.3 μm2 rectangular electrodes and 10,000 poration pulses featuring 2 Vpp amplitude, 1 ms phase duration, and 1 ms IPI , we could achieve an AP amplitude as high as 44.7 mV  featured a higher yield compared to using the “high-amp config” method  or on random selection from regions where cellular activities were detected . The use of 4 μm diameter electrodes entailed significantly higher poration yield than that of standard electrodes for the same electro-poration pulses . On the other hand, nifedipine increased the depolarization time only slightly , which also is in good agreement with previous studies.59Nifedipine is an L-type Caived CMs  as reporv1.5 and human ether-à-go-go-related gene (hERG) channels.62 Consistent with previous reports, quinidine induced significant prolongation of APD90s and an increase in the depolarization time  with respect to the last baseline measurement. Depolarization times increased by 46.4 ± 30.8% .Quinidine is a Class 1a antiarrhythmic drug, which is known to block Naion time . After tp > 0.05), suggesting that the observed changes in APD90 and depolarization time were caused by the added drugs and not the vehicle DMSO.Since nifedipine and quinidine were dissolved in DMSO, we performed vehicle control experiments to test if 0.1% of DMSO has any effects on APD90 or depolarization time. We found that 0.1% of DMSO did not affect APD90s and depolarization times of iPSC-derived CMs , examples for electrode selection, confocal images of immunostained CMs, impact of stimulation voltage phase duration and amplitude on electroporation yield, and extracellular and intracellular signal features throughout repeated electroporations (PDF)The Supporting Information is available free of charge at


BackgroundPercutaneous transhepatic cholangiography (PTC) is associated with high rates of sepsis. The aim of the current study was to audit the adherence to trust guidelines on antibiotic prophylaxis in patients undergoing PTC. Secondary aims included the management and outcome of patients with sepsis post-procedure.MethodsThis was a retrospective analysis of 50 consecutive patients who underwent a PTC procedure between January 2016 to January 2017. Collated data included PTC indication, drug allergies, antibiotics given pre-PTC, culture results, and antibiotic sensitivities within one-month post-PTC.ResultsComplete data were available for 41 patients and 61 PTC procedures. The median age was 68 years, and 51% were females. The indication for PTC was malignancy , benign conditions , and unknown diagnosis at the time of PTC . Three cases did not receive antibiotic prophylaxis. Only 27 (44%) PTC procedures received appropriate pre-PTC antibiotics as per guidelines, with no adherence to guidelines in all penicillin-allergic patients. In six patients who were not being treated for sepsis pre-PTC, a newly positive post-PTC blood/drain culture was observed within one month. Organisms grown in the post-PTC cultures were 56% gram-negative, the majority being Escherichia coli. The 30-day mortality rate was 12.2% (5/41).ConclusionsPoor adherence to recommended antibiotic regimes is a significant contributing factor for sepsis post-PTC. Investigating barriers to guideline implementation, stricter adherence, and peer education are interventions that could improve post-PTC outcomes. Percutaneous transhepatic cholangiography (PTC) involves the insertion of a needle through the liver into the biliary system and the injection of contrast to allow radiological visualisation of the biliary anatomy. This procedure can be used both for diagnostic and therapeutic purposes. In addition, this procedure is performed in cases where endoscopic retrograde cholangiopancreatography (ERCP) has failed or is contraindicated. Patients with altered anatomy following surgery that prevents endoscopic access to the biliary tree  are also candidates for PTC. Therapeutic indications include palliative biliary stenting across malignant strictures, dilatation of post-operative strictures, and removal of gallstones . HoweverSepsis is an important, known complication following PTC and is a leading contributor to morbidity and mortality post-procedure. The current published literature suggests that post-PTC sepsis is usually associated with gram-negative bacteraemia, which is thought to be related to the instrumentation of an infected, obstructed biliary system . AlthougA previous study based at our institution demonstrated a sepsis rate of 2% within 30 days of PTC stent insertion . Other sPatients admitted to Queen’s Medical Center at Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom, who underwent a PTC during the one-year period from January 2016 to January 2017 were identified from the hospital’s Interventional Radiology database Computerised Radiology Information System (CRIS) using the procedure code: FPTCH. Exclusion criteria included paediatric patients (less than 16 years old), incomplete PTC procedures, missing prescription data and patients undergoing any other surgical procedure.This was a registered Clinical Audit No: 17-039c) and the reference standard used was identified from the hospital’s intranet: “Nottingham University Hospitals NHS Trust. Clinical Guideline for Antibiotic Prophylaxis in Adult Gastrointestinal Endoscopy. December 2015” [-039c andCollated data included patient demographics, ethnicity, co-morbidities, clinical presentation, waiting time between request and procedure, drug allergies, antibiotic therapy prior to PTC, identification of the organism in blood/drain culture within one-month post-PTC, and antibiotic sensitivities of positive blood/drain culture within one month of the PTC procedure and clinical outcome.Statistical analysisData were analysed using STATA/SE 15 software . Continuous variables were expressed as means and standard deviation, while categorical variables were represented as percentages. We calculated the relative risk reduction of post-PTC sepsis between patients receiving the appropriate and incorrect PTC prophylaxis.This project evaluated clinical service provision within the department and in line with local policy and hence did not require prospective ethical approval representing a quality improvement exercise.Peer intervention surveyA peer education intervention was designed following the audit findings, with the aim to deliver focussed teaching to foundation year (FY) doctors on antibiotic prophylaxis for PTC. The target audience was asked to complete a pre-intervention survey assessing FY doctors’ knowledge of indications, complications, and knowledge of appropriate antibiotics in non-penicillin allergic and penicillin-allergic patients undergoing a PTC Figure .During the study period, 50 patients underwent PTC, of which 41 patients and 61 PTC procedures were included. Nine patients were excluded due to missing relevant drug charts (n = 6) and the procedure not performed (n = 3). The median age of patients included was 68 years (IQR: 61 - 70 year) and 21 (51%) patients were of the female gender. The majority of patients were Caucasians . The remaining patients were of black , Asian , and unknown ethnicity .A total of 61 PTC procedures were performed in these 41 patients, and the indications included: underlying malignancy , pancreatic cancer , cholangiocarcinoma , metastatic carcinoma , upper gastrointestinal cancers ), benign conditions , and unknown aetiology at the time of PTC .In the 61 PTC procedures performed, only in 27 (44%) cases did patients receive the appropriate pre-PTC antibiotic prophylaxis as recommended by the trust. Three (5%) of the PTC cases did not receive antibiotic prophylaxis. However, with respect to patients who were penicillin-allergic (n=5), none of these patients received the appropriate antibiotic therapy (Table Six 22%) of the 27 patients who were not being treated for sepsis pre-PTC had a newly positive post-PTC blood/drain culture within one month. Organisms grown in the post-PTC cultures were 56% gram-negative (Escherichia coli commonest) followed by 44% gram-positive . However, in those with post-PTC sepsis, the median length of stay (LOS) was 13 days (IQR 6.5 - 17 days). Overall 30-day mortality was 12.2% (5/41) and 16% (1/6) in those with post-PTC sepsis.Peer interventionThere were low levels of FY1 knowledge (49.1% of correct answers) pre-intervention. Peer education improved FY1 knowledge on all points of knowledge assessed. Poorest pre-intervention (4.6%) was on routine pre-PTC antibiotic prophylaxis in penicillin-allergic patients, correlating with the audit, which showed this was the area of least compliance with trust guidelines when prescribing pre-PTC antibiotic prophylaxis. Of note, this was also the area of greatest improvement post-intervention (72.3% increase in correct answers, Figure Whilst PTC is an effective diagnostic and therapeutic intervention in the management of benign and malignant biliary tract disease, the associated morbidity and mortality remains high. Sepsis is one of the most important outcomes post-PTC, which further impacts overall morbidity, length of hospital stay, and mortality. In the present study, poor adherence with respect to the choice of antibiotic prophylaxis administered was observed, with only 44% adherence to the trust guidelines, and none of the penicillin-allergic group patients had appropriate antibiotic prophylaxis prescribed. In addition, there was a high rate of post-PTC sepsis based on positive blood or biliary cultures.Published data have previously shown that the 30-day mortality for PTC ranges from 2%-19.8%, with post-PTC sepsis being a leading contributor to this poor outcome . There mThere are conflicting views on the effectiveness of antibiotic prophylaxis for interventional radiology procedures. The Society of Interventional Radiology recommends prophylactic antibiotics in all patients undergoing PTC and its respective biliary drainage procedures due to the anticipated rate of sepsis of 2% .In contrast, American Society for Gastrointestinal Endoscopy does not advocate the use of prophylactic antibiotics for procedures intended to relieve biliary obstruction where there no signs of cholangitis pre-procedure and where complete drainage is expected .There is also controversy in the literature as to the optimal antibiotic of choice to be used as prophylaxis for this purpose. Piperacillin-tazobactam has been proposed as a suitable prophylactic antibiotic due to its coverage of biliary bacterial flora, action against the B-lactamase producing species of Escherichia coli and low risk of nephrotoxicity . This anIn the present study, there was poor adherence to the trust guidelines on antibiotic prophylaxis for PTC procedures. In addition, there was a higher rate of post-PTC sepsis compared to the older published literature . HoweverIn the present study, there was a significant relative risk reduction in the development of post-PTC sepsis when patients were given the trust-recommended antibiotic prophylaxis when compared with those patients that received no prophylaxis. Of interest, there was also a significant relative risk reduction of post-PTC sepsis when incorrect antibiotic prophylaxis was given compared to when no antibiotic prophylaxis was administered.The benefits of peer education as a model for delivering education has been supported by previous research and has been translated into the context of medical education . Adult lLimitationsThere are limitations to this study. This was a retrospective study, and the data collated represented a one-year period of practice in a tertiary centre, and hence the small sample size. It would, in the future, be important to re-evaluate using larger sample size, however, the findings of increased septic complications is of significant importance to this particular population of patients, 78% of whom had unresectable malignancy. Given that the study was conducted in a large tertiary referral centre that undertakes PTC procedures for the East Midlands region, it could be argued that results could be generalised to the wider UK population, however, the small sample size may limit this study's external validity. Randomising the sample selection using systematic sampling could limit selection bias. The exclusion of nine patients with incomplete data may have further introduced selection bias into our sampling.A non-generalisable finding from this study is the type of antibiotic to be used for prophylaxis, as this is linked to local sensitivities and local antimicrobial policies and guidance.Poor adherence to recommended antibiotic prophylaxis regimes leads to higher rates of sepsis post-PTC with the sequelae of increased morbidity and length of stay. Therefore, investigating barriers to guideline implementation, stricter adherence and peer education are all interventions we anticipate could improve post-PTC outcomes.


These findings suggest that parental reports show more eating problems and emotional disturbances in children with ARFID vs. controls, and more parental feeding problems. Further research is required to determine whether the SFQ-ARFID Scale may serve as an effective screening tool for the identification of ARFID. Avoidant/restrictive food intake disorder (ARFID) is a relatively new diagnostic category. We sought to determine whether the Stanford Feeding Questionnaire (SFQ), an instrument for assessing picky eating, can differentiate children with ARFID from control children, and whether children with ARFID would show more nonfeeding/eating emotional problems than controls. Fifty children with ARFID were compared to 98 controls. Parents completed the SFQ, Screen for Child Anxiety Related Emotional Disorders (SCARED), Strength and Difficulties Questionnaire (SDQ), and Sensory Responsiveness Questionnaire (SRQ). On the SFQ, 12 items represented child ARFID behaviors , and another 15 items represented parental feeding problems . We found that the SFQ-ARFID and SFQ-PFP Scale scores were significantly higher in children with ARFID vs. controls. Children with ARFID demonstrated higher SDQ-Total-Difficulties, higher SDQ-Internalizing-Difficulties and lower SRQ-Hedonic scores compared with controls. Of all parameters, the SFQ-ARFID Scale best differentiated children with ARFID from control children (area under receiver operating characteristics curve = 0.939, 95% CI, 0.895–0.983,  Avoidant/restrictive food intake disorder (ARFID) is a relatively new diagnosis in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5)  and the At present, limited data is available about the incidence and prevalence of ARFID in the general population ,6. This Avoidant/restrictive eating is associated with a wide range of health problems, including malnutrition ; amenorrResearch on psychopathology of ARFID is limited by the lack of tools to identify these eating behaviors . MoreoveWe employed a different design. ARFID, particularly in younger patients, may present both as a parent-related feeding disorder and as a child-related eating disorder. This is of importance, because treatment strategies for these two types of disorders may differ . The StaSpecifically, we aimed to evaluate whether the use of the SFQ subscales assessing children’s problematic eating and parents’ problematic feeding, would have the potential to support a clinical diagnosis of ARFID obtained according to two sets of criteria: (a) the DSM-5 criteria for ARFID  and (b) We hypothesized that the eating- and feeding-related subscales of the SFQ, would distinguish children diagnosed with ARFID from control children based on the two previously mentioned methods. Additionally, regarding nonfeeding/eating emotional problems, we hypothesized that the ARFID group would show less favorable overall psychiatric conditions, greater anxiety, and more disturbed sensory responsiveness compared with the control group.A cross-sectional study was conducted over 2.5 years (1 January 2017 to 30 June 2019) in the outpatient pediatric eating disorders (ED) clinic, located in the Edmond and Lily Safra Children’s Hospital, the Chaim Sheba Medical Center, Tel Hashomer, Israel. Sample size was calculated using a significance level of 5%, a power of 80%, and a 1:2 ratio of ARFID to control groups. Thus, to identify a medium effect size (Cohen’s d = 0.5), our sample required 48 children who were diagnosed with ARFID and 96 children with typical development  compared to controls [Mean (SD) 1.42 (0.68)], (p = 0.013). A weak correlation was found between the child’s age and the SFQ-ARFID Scale score . After controlling for the child’s age, the between-group difference in SFQ-ARFID Scale score (p < 0.001) was still significant.The findings of this study showed that the score of the proposed SFQ-ARFID Scale, based on 12 selected items from the SFQ describing maladaptive eating-related behaviors, was significantly higher for children with ARFID as diagnosed in the psychiatric evaluation [Mean (SD) 4.46 (1.01) than for control children [Mean (SD) 1.89 (1.18)], (+) was 9.58 (95% CI: 5.10–18.00); and Negative Likelihood Ratio was (LR-) 0.13 (95% CI: 0.06–0.28).The maximal value of the Index was set to reveal the best cutoff point for total SFQ-ARFID Scale and showed a cutoff point of 3.46 with a sensitivity of 88% (95% CI: 76–95%), and a specificity of 90% (95% CI: 83–96%); Positive Predictive value was 83% (95% CI: 70–92%); Negative Predictive Value was 94% (95% CI: 87–98%); Accuracy was 90% (95% CI: 84–94%); Positive Likelihood Ratio  and food variety/day (p = 0.600). Similarly, there was no significant relationship between the Total SFQ-PFP Scale score and the dietitian’s assessment of both caloric intake/day (p = 0.293) and food variety/day (p = 0.173). Regarding the influence of other psychiatric disorders, we found no significant differences in SFQ-ARFID Scale score when comparing ARFID children with additional psychiatric disorders (n = 18) to children with only ARFID . Last, no significant correlations were found in the research group between the BMI Z-score and the SFQ-ARFID Scale (p = 0.793), and SFQ-PFP Scale scores (p = 0.404).No significant correlations were found between the Total SFQ-ARFID Scale score and the dietitian’s assessment of both caloric intake/day (p = 0.048). After controlling for the child’s age, the between-group difference in SDQ-Internalizing Difficulties score (p < 0.001) was still significant.The comparison between the research and control groups in the non-ED related psychometric tools is summarized in The primary aim of the present study was to determine if the SFQ could distinguish between children diagnosed with ARFID using the DSM-5 criteria  from conDSM-5 criteria [In line with our first hypothesis, children diagnosed with ARFID using criteria  were foucriteria , suggestcriteria .The significant correlation found between the SFQ-ARFID Scale and the SFQ-PFP Scale lends further support for the likelihood of an association between the parents feeding patterns and the child’s eating behaviors, both for normally-developing children and for children with ARFID. Nonetheless, because our study was cross-sectional, it is not possible to determine whether in these families the child’s problematic eating behaviors may result from problematic parental feeding patterns, or whether long-standing eating disturbances in children may increase parents’ stress and anxiety, eventually culminating in problematic feeding patterns. A future large-scale prospective longitudinal study might provide adequate answers for these issues.The proposed SFQ-ARFID scale assessing parental report of problematic eating behaviors in their children was found to be a short and easily completed tool that can serve as a screening tool for the identification of children with ARFID. Thus, all 12 items of this scale have distinguished between children who were clinically diagnosed with ARFID using the DSM-5 [The findings are less robust for the 15-item SFQ-PFP Scale, assessing the parents’ perceptions of their own feeding-related behaviors. Although the SFQ-PFP Scale differentiates between the research and control groups, only three of its 15 items have shown significant between-group differences, and AUROC analysis yielded only a fair result. The strength of the SFQ-ARFID Scale relative to the SFQ-PFP Scale suggests that parents may possibly be more accurate informants of their children’s problematic eating behaviors than of their own problematic feeding patterns. Alternatively, from a methodological point of view, all 12 SFQ-ARFID Scale items seem to precisely capture the specific avoidant/restrictive clinical presentation of the disorder. By contrast, many items included in the SFQ-PFP Scale seem to represent relatively nonspecific feeding behaviors  as well as in their internalizing problems, but not in their externalizing problems. The SDQ-Internalizing Difficulties finding, suggesting that children with ARFID may have more emotional and social problems, is not surprising, because psychosocial difficulties associated with eating and feeding difficulties are included among the DSM-5  diagnostHowever, as mentioned above, our findings also show that in contrast to the results on the SDQ-Internalizing Difficulties scale, children with ARFID did not show greater anxiety as rated by parents on the SCARED scale. Moreover, the AUROC analysis pinpointed the SDQ-Internalizing Difficulties scale as showing “good” accuracy for differentiating children with ARFID from control children, whereas the SCARED scale did not distinguish between the two groups. One reason for this discrepancy might be methodological. The five-item SDQ-Internalizing scale encompasses physical complaints, worries, unhappiness, nervousness in new situations, and many fears. By contrast, the SCARED assesses only anxiety related symptoms. Nonetheless, other studies on children with ARFID have emphasized not only their anxious/avoidant characteristics  but alsoThe lack of significant between-group differences for the SDQ-Externalizing Difficulties scale was unexpected, as ARFID was previously associated with elevated rates of ADHD ,54, althRegarding the sensory processing issues that we expected to correlate with ARFID, our findings partially supported our second hypothesis. Thus, children with ARFID did demonstrate significantly lower SRQ-Hedonic scores, associated with a reduction in sensory-seeking behaviors resulting from sensory under-responsiveness, compared to control children. However, unexpectedly, no between-group differences emerged for the SRQ-Aversive score, associated with sensory-avoiding behaviors related to sensory over-responsiveness. The latter finding is unclear, considering that disgust from food is considered a prominent feature in the development and maintenance of ARFID  and is lThe findings of our study should be regarded as preliminary and interpreted with caution because of several limitations. First, as our study was cross-sectional, it was not possible to establish causal relationships between problematic parental feeding behaviors, as well as noneating related psychopathology in the children, and the development and maintenance of ARFID. Second, as we did not assess the nutritional intake of the control children, we could not compare the daily caloric intake and food variety between the two groups. In addition, since weight and height measures were not reported by parents of control children, we could not compare the BMI SDS score of the patients to that of the controls. Third, as our study relied on parental report, this may have affected the results of older participants, less likely to be under close supervision of their parents. Fourth, as the SFQ-ARFID and the SFQ-PFP Scales were developed in our clinic, thus, they have not been studied in non-Hebrew-speaking populations. Therefore, we have yet no knowledge whether the SFQ-ARFID Scale can serve as a potential screening tool in other populations. Lastly, the clinical interview carried out by the psychiatrists, although relying on the DSM-5  criteriaAdvantages of this hypothesis-generated study include the use of both clinical and nutritional interviews to diagnose ARFID, as well as parental reported scales to compare between children diagnosed with ARFID and children with typical development. Furthermore, a thorough investigation of the SFQ items enabled us to develop a novel brief, practical screening tool that could be potentially used to screen patients for further evaluations. The use of the cutoff point of the SFQ-ARFID Scale found in our study for this purpose could greatly assist in such decisions.Another important finding of this study is that elementary-school children with ARFID already exhibit considerable psychiatric morbidity. The finding that over a third of these children (37.5%) had another psychiatric disorder in addition to ARFID is striking, although some studies have shown even higher rates of other psychiatric disorders in children with ARFID, such as 45% in Kambanis et al., , assessiThere is a need to extend the study of the utility of the SFQ-ARFID Scale. Prospective longitudinal, studies using the SFQ-ARFID Scale in both parents and participants of different ages, will show if the tool can also be used for assessing possible changes in the severity of ARFID symptoms over time. Lastly, there is a need to examine whether the SFQ-ARFID Scale can differentiate children with ARFID from children with other types of avoidant restricting eating, e.g., picky eating, and from non-ARFID disordered eating.This study suggests that SFQ-ARFID Scale as completed by parents, has the potential to differentiate children with ARFID from normally-developing children. It may serve as a screening tool in the identification of the disorder. Our findings further suggest that children with ARFID demonstrate not only disturbances in eating and parental feeding behaviors, but also decreased overall psychosocial functioning, and elevated internalizing emotional difficulties. These findings support previous studies showing that ARFID is not just an eating and feeding disorder, but is often associated with additional psychopathology.


This review outlines recent preclinical and clinical advances in molecular imaging of abdominal aortic aneurysms (AAA) with a focus on molecular magnetic resonance imaging (MRI) of the extracellular matrix (ECM). In addition, developments in pharmacologic treatment of AAA targeting the ECM will be discussed and results from animal studies will be contrasted with clinical trials. Abdominal aortic aneurysm (AAA) is an often fatal disease without non-invasive pharmacologic treatment options. The ECM, with collagen type I and elastin as major components, is the key structural component of the aortic wall and is recognized as a target tissue for both initiation and the progression of AAA. Molecular imaging allows in vivo measurement and characterization of biological processes at the cellular and molecular level and sets forth to visualize molecular abnormalities at an early stage of disease, facilitating novel diagnostic and therapeutic pathways. By providing surrogate criteria for the in vivo evaluation of the effects of pharmacological therapies, molecular imaging techniques targeting the ECM can facilitate pharmacological drug development. In addition, molecular targets can also be used in theranostic approaches that have the potential for timely diagnosis and concurrent medical therapy. Recent successes in preclinical studies suggest future opportunities for clinical translation. However, further clinical studies are needed to validate the most promising molecular targets for human application. Abdominal aortic aneurysm (AAA) is a fatal, but often asymptomatic disease with controversial treatment and insufficient prediction of complications ,2. The eIn clinical routine, morphological criteria for the determination of the aortic diameter on ultrasound, computed tomography (CT) and MRI have been used in accordance with guidelines as evaluation criteria for therapeutic intervention or conservative therapy. By contrast, molecular imaging enables an in vivo measurement and characterization of biological processes at cellular and molecular level and sets forth to visualize molecular abnormalities at an early stage of disease, facilitating novel diagnostic and also therapeutic pathways . MRI is In the context of AAA, development of pharmacological therapies is of high clinical relevance. It has been estimated that inhibiting the growth of an AAA by 40% could delay the occurrence of a rupture by possibly five years ,9. ConseIn each organ, the composition of the ECM has a different three-dimensional structure and a constant pattern of remodeling to regulate tissue homeostasis . Within Molecular MRI includes both targeted probes with selective binding to molecular targets and probes that accumulate passively within cells  . A majorIn vivo imaging of AAA wall inflammation and ECM remodeling has previously been achieved using ultrasmall superparamagnetic particles of iron oxide (USPIOs), elastin-specific MRI contrast agents (Gd-ESMA) as well as collagen- and fibrin-binding probes ,22,23,243RS study, USPIO enhancement showed no correlation with computed tomography angiogram (CTA) predictions of stress areas, so that localization of rupture-prone areas in the clinical setting has not yet been successful [In a recently published prospective multicenter cohort study (MA3RS) including 342 patients with abdominal aortic aneurysms, USPIO enhancement was associated with higher risk of aortic rupture or repair, reduced event-free survival from aneurysm rupture or repair, and aneurysm expansion, although it was not independent of clinical risk factors and thus had limited additional value beyond current clinical risk prediction . In a successful .A further crucial process in AAA development, related in part to inflammation, is remodeling of the ECM. Dysfunctional ECM remodeling may reduce wall stability and promote AAA formation. Gd-ESMA is an elastin-specific MRI probe that showed high potential in quantitative imaging of vascular diseases . By specAnother protein that may be increased in AAA due to dysfunctional ECM remodeling is tropoelastin, a monomeric precursor of cross-linked elastin . A recenMMPs are also associated with changes in the ECM and the development of AAA. P947 is a gadolinium (DOTA)-binding molecular probe that specifically binds to MMPs, particularly MMP-2 and MMP-9. In AAA-induced wistar rats, P947 MRI images showed good colocalization of the sample with MMPs in wall areas of inflammatory events .99mTc-labeled homolog, RP805 predicted vessel expansion and rupture probability in Ang-II-induced murine AAA [99mTc-labelled pan-MMP inhibitor RYM1 and demonstrated a higher uptake of the tracer in AAA compared to nondilated aorta [MMP tracers have also been developed for nuclear imaging. The rine AAA . Anothered aorta . In addied aorta .Yao et al. investigated a smart activatable MRI nanoprobe to target MMP in early-stage AAA in a mouse model and found that their probe allowed for the detection of MMP activity within the aneurysmal wall, thus representing a potential noninvasive method to predict the risk of rupture in AAA [A recent study by e in AAA .vβ3 is upregulated in proliferating endothelial cells, VSMC and macrophages [99mTc-cyclic RGD tracer for microSPECT-CT displayed increased uptake in murine carotid aneurysms and a correlation with inflammatory activity [64Cu-DOTA-ECL1i [64Cu-DOTA-ECL1i showed significantly increased uptake compared with sham controls and compared with aneurysms that did not rupture during progression [More consistent results were achieved in preclinical studies on integrin-targeted tracers. Integrin αrophages ,35. NC10activity . EnglishTA-ECL1i . CCR2 isgression .Experimental targets for pharmaceutical AAA stabilization, that target the ECM, are thrombospondin inhibitors , cysteinIn humans, elevated thrombospondin-1 (TSP-1) was associated with MMP activitaion, ECM degradation as well as tissue infiltration . CysteinAneurysmal collagen and elastin degradation is caused by a number of endopeptidases called MMPs. MMPs belong to a family of enzymes whose main function is the degradation of ECM components and the disruption of tissue organization ,51. MMP Being among the most abundant elastolytic proteinases produced by human tissue and aneurysm-infiltrating macrophages, MMP-9 has gained particular interest. In a molecular MRI study, Bazeli et al. reported the potential value of an MMP-targeted probe (P947) in rats. P947 was shown to co-localize with markers of inflammation and MMP activity in the area of expanding AAA .99mTc-AGA-2 in murine models, for which they demonstrated specific binding to MMP-12 through ex vivo competition, and found it to be significantly increased in AAA compared to healthy aortae [MMP-12 is the most upregulated MMP in AAA and may therefore be particularly valuable for prediction of AAA progression and rupture risk. Gona et al. recently investigated the MMP-12-inhibitor y aortae .Katsuki et al. recently investigated the use of pitavastatin in a mouse model of AAA and found that it could inhibit AAA formation, being associated with reduced macrophage accumulation, MMP activity and elastin degradation . However3CT)), reporting that doxycycline (200 mg/day) did not reduce AAA growth at 2 years as compared to placebo in patients with small infrarenal AAA [3CT trial corresponded to circulating levels of doxycycline that were required to reduce AAA growth in preclinical studies with mice [The tetracycline antibiotic doxycycline has been studied in the context of AAA for many years. In a series of earlier preclinical studies doxycycline effectively interfered with aneurysm formation or growth ,64. Prevenal AAA . While iith mice . The proPentagalloyl glucose (PGG) is a polyphenolic tannin. In a mouse model of AAA, twice IV application of nanoparticle-loaded PGG (EL-PGG-NPs) showed a reduction of MMP-9, MMP-2 and of macrophages in the vascular media and restored the elastic lamina . FucoidaADAMs and ADAMs with a thrombospondin domain (ADAM-TS) are zinc-dependent endopeptidases and belong to the proteolytic enzyme family, involved in ECM degradation and closely related to other MMPs . They boMicroRNAs (miRNA) are small, 19–24 nucleotide, highly conserved non-coding RNAs that are involved in gene regulation by binding to the 3′ untranslated region of mRNA, thereby inhibiting translation. Through this mechanism, miRNAs are involved in diverse processes of cellular tumorigenesis, apoptosis, and differentiation . In addiWang et al. used ultrasound microbubbles coupled with a VCAM-1-targeted single-chain antibody (scFvmVCAM-1) and a miRNA-126mimic (M126) as carriers, enabling a theranostic approach (TargMB-M126) with simultaneous molecular imaging and targeted therapy of AAA in a mouse model of AAA [Another potential therapeutic target is miRNA-126 with a capability to downregulate vascular cell adhesion molecule-1 (VCAM1) and thereby reduce leukocyte adhesion with a subsequent anti-inflammatory effect . Wang etl of AAA   indicated that anti-miRNA29b treatment was a powerful therapeutic option to limit AAA progression . In addiThe degradation of ECM components is induced in part by cytokines secreted by inflammatory and mesenchymal cells. In this context, macrophages in particular act as important releasers of a variety of proinflammatory cytokines, including tumor necrosis factor α (TNF-α), interleukin (IL)-1β, IL-6, IL-12/IL-23 . Apart fIncreased production of IL-6 causes degradation of the ECM with an increased activity of MMP-9 and a consecutive aortic dilatation. IL-6 deficiency was previously demonstrated to improve AAA pathology by partially preserving ECM structure through a reduction of MMP-9 expression, whereas it could neither prevent rupture nor increase survival .Inhibition of IL-12 and IL-23 has been shown to inhibit macrophage expansion and, in particular, to reduce the expression of macrophage-associated inflammatory mediators and the activity of MMPs . TherefoInterleukin-1β functions as a gatekeeper of inflammation and contributes substantially to the progressive destruction of aortic ECM proteins during the development of AAA. Disruption of the inflammatory pathway by neutralizing IL-1β represents a promising new therapeutic target for AAA therapies . In a moIn addition, they suggested that molecular imaging allowed for differentiation between responders and non-responders early after initiation of therapy .n = 65), but the trial was terminated afterwards for reasons of futility as no difference in aortic diameter expansion could be seen between canakinumab- and placebo-treated patients (both groups: 2.5 mm/y) [In humans, effect of IL-1β neutralization through monthly subcutaneous canakinumab for twelve months was evaluated (.5 mm/y) .Over the past 30 years, a variety of promising gadolinium-based molecular tracers have been developed and their utility confirmed in proof-of-concept animal studies. Nevertheless, only non-targeted contrast agents have made it to clinical approval for use in humans. A challenge in clinical translation is that toxicological testing is time-consuming and costly, requiring substantial financial resources. This contradicts the expected revenues, which are lower for molecular tracers than for clinically proven nonspecific contrast agents due to their limited application in specific settings. Nonetheless, these markers play a prominent role especially in preclinical research and, if validated, can non-invasively image new therapeutic approaches, for example targeting ECM remodeling. In this context, the elastin-specific MRI probe Gd-ESMA and tropoelastin-specific MRI probe Gd-TESMA appear promising, as they can specifically detect the effect of therapeutic strategies affecting the elastin content in the aortic wall via their different pathways. Another novel approach are multitarget probes, which could allow for concurrent imaging of different pathophysiological processes at the molecular level. Molecular agents may also be used within theranostic approaches with the potential for timely diagnosis and concurrent medical therapy. Here, the use of miRNA-based targets is a novel and promising method.Currently, there is no established pharmacologic therapy for the treatment of AAA. The apparent discordance between successes in preclinical studies and partly disappoint results in clinical trials suggests an incomplete understanding of the various pathological processes involved in the development of AAAs and points to possible inadequacies in animal models of the disease. To increase future therapeutic strategies, molecular imaging markers that can specifically visualize and quantify targets of pharmacological agents in ECM in a non-invasive manner hold promise for a better reflection of the pathophysiological processes behind the disease and during therapy. In addition, recent preclinical approaches in large animal models represent a promising option for evaluating therapeutic strategies and create better options for multiparametric functional imaging, which seems to be limited in parts by the low volume in small animal models. With the increasing availability of image-based molecular biomarkers and promising pharmacotherapies, as well as their evaluation in large animal models of AAA and initial human clinical trials, there is reason to hope that molecular therapeutic approaches targeting ECM will enter clinical research in the coming years.


Coronavirus disease 2019 (COVID-19) is a zoonotic respiratory infection originating from Wuhan, China. Rapidly spreading from Wuhan to all inhabited continents of the world, the World Health Organisation declared COVID-19 a pandemic on March 11, 2019. Infected patients present with fever and cough; radiological features include bilateral infiltrates on chest x-ray and computed tomography scanning. Management is supportive with oxygen supplementation, broad-spectrum antibiotics as well as careful fluid balancing. A number of drugs, both new and old, are currently in clinical trials and being used on an experimental basis in clinical practice. The COVID-19 pandemic is the greatest worldwide public health crisis of a generation, and has led to seismic political, economic and social changes. This review provides an overview of COVID-19 for junior doctors who find themselves on a new frontline of healthcare. •Coronavirus disease 2019 is a zoonotic respiratory infection that rapidly spread from China to become a pandemic.•The most common symptoms are cough, fever and shortness of breath; infection typically produces mild symptoms.•A minority of patients have severe symptoms, such as respiratory failure, which requires hospital admission and even intensive care unit admission.•Guidelines suggest that the management of coronavirus disease 2019, in most cases, is supportive•Several agents, such as hydroxychloroquine, azithromycin and remdesivir are currently under investigation as treatment for the disease. On the 2nd January, the virus was identified as the 2019-novel Coronavirus and its genetic sequence shared with the WHO [The COVID-19 outbreak can be traced to an unusual cluster of 27 pneumonia cases with unknown aetiology in Wuhan, China (1). The Hunan Seafood Wholesale Market which hosted a variety of exotic live and deceased wildlife including bamboo rats, badgers and wolf clubs was a common reported link. The Wuhan Municipal Health Commission subsequently reported this case cluster to the World Health Organization (WHO) on the 31st December 2019. Reports of the first fatality came on the 11.2Wuhan is the capital of central China's Hubei province and is itself is a major hub of economic activity. It has a population of 11 million. Every day, 3500 people fly internationally from the province (1). Within 30 days of outbreak reports, COVID-19 had already spread from Wuhan to other Chinese settlements and the number of confirmed cases rose to 9000 (more than the number of SARS and MERS cases reported to date) [Multiple domestic measures to contain the outbreak were enforced including the banning of wildlife and poultry in wet markets, contact tracing of cases, increasing lockdown and quarantine restrictions, school closures and prohibition of large gatherings. Similarly, neighbouring countries commenced airport screening, travel bans and quarantining of evacuated citizens from the Hubei province . The firThe WHO issued a statement on the 19th January warning of human-human transmission and by the 31st it was announced that COVID-19 was now a Public Health Emergency of International Concern and calls were made for an international coordinated response . By the 1.3The SARS-CoV-2 virus belongs to the family of coronaviruses which are enveloped, positive-stranded RNA viruses with nucleocapsids . Six oth1.3.1Viral transmission of SARS-CoV-2 occurs directly via respiratory droplets when infected individuals cough, sneeze or talk in close proximity to others and indirectly via fomites objects or surfaces. Although some studies have suggested SARS-CoV2 virus may remain viable for at least 3 h in experimentally generated aerosols, it is not fully clear on whether this has clinical implications in the epidemiology of COVID-19 .1.3.2Incubation times have been estimated to range between 1 and 14 days (median duration of 5 days) whilst the median duration of viral shedding is around 20 days in those who recover . The rep1.3.3The pathogenesis of SARS-CoV2 remains poorly understood and still requires further elucidation. Research on other viruses from the coronavirus family such as SARS-CoV and MERS-CoV may help to provide analogous mechanistic insights.One notable structural feature of coronaviruses is that they have spike glycoproteins. In the case of SARS-Cov-2, receptor-binding domains on these spike glycoproteins are responsible for viral entry into host cells via angiotensin-converting-enzyme-2 (ACE2) receptors. These spike glycoprotein receptor-binding domains in the SARS-CoV-2 virus appear to have a greater affinity to ACE-2 receptors than the SARS-CoV virus and given the high conservation of the S2 subunit, these receptor-binding domains have been identified as possible targets for antiviral compounds . ACE2 re1.3.4The host immune response to SARS-CoV-2 is still not fully understood. Viral antigens are likely presented to host immune cells to trigger humoral and cellular immunity by virus-specific B and T lymphocytes. SARS-CoV2 is likely to trigger IgM and IgG production in a similar humoral immunity response to SARS-CoV . Further1.3.5Similar to the SARS-CoV and MERS-CoV viruses, the SARS-CoV-2 virus can trigger a violent and potentially fatal dysregulated immune host response. This response is thought to be mediated by the triggered release of large numbers of pro-inflammatory cytokines and chemokines in a ‘cytokine storm’ by immune effector cells and can result in Acute Respiratory Distress Syndrome (ARDS) and multiple organ failure . ARDS is2The clinical history is critical to determine the risk of COVID-19. Symptoms of the disorder resemble those of a viral pneumonia and include: persistent cough, shortness of breath, pyrexia, myalgia and fatigue. Other non-specific symptoms may also be present, such as headache, nasal congestion, sore throat, diarrhoea, nausea and vomiting .The World Health Organization stipulates that the diagnosis of COVID-19 should be suspected in patients who present with acute respiratory illness in conjunction with a history of travel to a high prevalence area; or contact with a confirmed or suspected COVID-19 case within 14 days prior to symptoms onset. Additionally, acute respiratory illness in the absence of a more likely alternative diagnosis should prompt suspicion of COVID-19 . In pracCertain groups, particularly the elderly and those with significant comorbidities such as cardiovascular disease, hypertension and diabetes are at increased risk of severe disease . The sevClinical examination will reveal signs consistent with an upper or lower respiratory tract infection. The patient's observations may show pyrexia, tachypnoea, tachycardia and hypoxia. Examination of the chest may show inspiratory crackles, which is consistent with underlying consolidation.NICE guidelines suggest that, at the time of initial presentation, an assessment of frailty using the Clinical Frailty Score (CFS) should be made and documented in the patient's notes . The CFSEarly discussion regarding suitability for intensive care admission are warranted, as well as consideration of patient preferences. Patients with a CFS score less than 5 (mildly frail) are most likely to benefit from organ support measures in critical care. Conversely, patients with a CFS score greater than 5 are less likely to benefit from such treatment. Early discussion regarding resuscitation is also warranted; patients with a CFS score greater than 5 are less likely to benefit . Clinici3Patients presented to the emergency department or acute medical take are likely to have basic investigations, such as blood tests and a chest x-ray, taken. In addition, diagnostic testing using a nasopharyngeal or oropharyngeal swab is now commonly completed. Furthermore, some centres conduct CT scans on patients presenting with the most severe symptoms.Blood results in COVID-19 infection show derangements in multiple biomarkers. Isolated lymphopaenia has been noted in multiple studies with incidence ranging from 43 to 83% ,20,21,45Diagnostic testing is being performed using real-time reverse transcriptase polymerase chain reaction (rRT-PCR) testing. Current PHE guidelines recommend an upper respiratory tract sample (combination of nose and throat swab) and a lower respiratory tract sample, if possible, to be sent for testing . CompariRadiological changes have been strongly associated with COVID-19 infection, with prevalence ranging from 86 to 100% ,20,21. A44.1Infection prevention and control in the form of personal protective equipment (PPE) and patient isolation are the most important initial steps in managing suspected COVID-19 infection . Public Despite intensive research into targeted therapy, supportive measures currently form the basis of management. Supplemental oxygen should be titrated according to pulse oximetry and empirical antibiotics given to cover all likely pathogens of acute respiratory infection. Intravenous fluids should be given conservatively to avoid exacerbation of ARDS, of which noncardiogenic pulmonary oedema is the hallmark feature .Hypoxemic respiratory failure secondary to ARDS is the most common cause of deterioration and death, with one report documenting 67% of COVID-19 ITU admissions developing ARDS . Prompt 4.2in vitro efficacy against zika and rhinoviruses [The safety of hydroxychloroquine, a drug used against malaria and autoimmune diseases, was established in the 1950s. The drug, on the WHO list of essential medicines, was recognised to have broad-spectrum anti-viral activity in 2006, and most recently was shown to be highly effective in controlling 2019-nCov infection ,56. Azitoviruses ,58.A recent open-label non-randomised clinical trial in 42 patients comparing treatment with either hydroxychloroquine treatment or combination hydroxychloroquine-azithromycin treatment reported a significant reduction in viral carriage at day 6 post inclusion compare to standard of care. Combination treatment also showed significantly increased efficiency in viral elimination, with 100% of patients virologically cured at day 6, versus 12.5% in the control group (p < 0.001) . Subsequ4.3There appears to be a subset of severe COVID-19 patients who develop hyperinflammation due to an underlying cytokine storm syndrome. Two studies showed an association between glucocorticoid therapy and clinical improvement and reduced inflammatory cytokine levels in SARS patients in the 2003 epidemic ,65. Two 4.4Remdesivir, a broad-spectrum anti-viral agent developed in 2017 as a treatment for Ebola virus, had its development halted when a randomised controlled trial of 673 participants with Ebola virus disease showed that 28-day mortality was significantly inferior in the Remdesivir group versus monoclonal antibodies mAb114 and REGN-EB3. There are currently eight RCTs registered specifically investigating the safety and efficacy of Remdesivir in treating COVID-19 patients . No resu4.5Lopinavir/ritonavir, a combination antiretroviral medication used to treat human immunodeficiency virus (HIV), has been studied for the treatment of COVID-19. A randomized-controlled trial of 199 hospitalized participants showed no benefit of lopinavir/ritonavir in reducing time to clinical improvement, mortality and serum viral load beyond standard care .4.6Concerns regarding use of NSAIDs in COVID-19 have been raised since French Health Minister Olivier Véran released a statement advising against the use of ibuprofen in COVID-19 due to potential worsening of severity of symptoms . NHS Eng5The COVID-19 pandemic is evolving, with numbers infected and deaths attributed to the disease increasing rapidly. This has led to a global effort to create widely available detection assays and to identify a targeted treatment. The cornerstone of management throughout the world is currently supportive management with oxygen therapy alongside treatment for sepsis and ARDS with broad-spectrum antibiotics and careful rationing of intravenous fluids. Stratification of risk is a priority, with a focus on identifying those most at need and most likely to benefit from invasive ventilation. Though some facilities are trialling specific treatments, with hydroxychloroquine and azithromycin most commonly used among these, there are no widely used guidelines as to their use as yet. There is a plethora of expedited clinical trials currently ongoing .Nil required.Nil.Billy Down – conceptualisation, writing original draft, refinement and editing.Sagar Kulkarni - conceptualisation, writing original draft, refinement and editing.Ameer Hamid Ahmed Khan - writing original draft, refinement and editing.Benjamin Barker - writing original draft, refinement and editing.Ivan Tang - refinement and editing.1Name of the registry:2Unique Identifying number or registration ID:3Hyperlink to your specific registration (must be publicly accessible and will be checked):Billy Down.Not commissioned, externally peer reviewed.The authors of this article have no conflicts of interest to declare.


R2 > 0.97, varying negligibly with lesion morphology. Such models can quantify enhancing tumour without the administration of intravenous contrast, inviting a revision of the notion of tumour enhancement if the same information can be extracted without contrast-enhanced imaging. Our analysis includes validation on a heterogeneous, real-world 50 patient sample of brain tumour imaging acquired over the last 15 years at our tertiary centre, demonstrating maintained accuracy even on non-isotropic MRI acquisitions, or even on complex post-operative imaging with tumour recurrence. This work substantially extends the translational opportunity for quantitative analysis to clinical situations where the full complement of sequences is not available and potentially enables the characterization of contrast-enhanced regions where contrast administration is infeasible or undesirable.Progress in neuro-oncology is increasingly recognized to be obstructed by the marked heterogeneity—genetic, pathological, and clinical—of brain tumours. If the treatment susceptibilities and outcomes of individual patients differ widely, determined by the interactions of many multimodal characteristics, then large-scale, fully-inclusive, richly phenotyped data—including imaging—will be needed to predict them at the individual level. Such data can realistically be acquired only in the routine clinical stream, where its quality is inevitably degraded by the constraints of real-world clinical care. Although contemporary machine learning could theoretically provide a solution to this task, especially in the domain of imaging, its ability to cope with realistic, incomplete, low-quality data is yet to be determined. In the largest and most comprehensive study of its kind, applying state-of-the-art brain tumour segmentation models to large scale, multi-site MRI data of 1251 individuals, here we quantify the comparative fidelity of automated segmentation models drawn from MR data replicating the various levels of completeness observed in real life. We demonstrate that models trained on incomplete data can segment lesions very well, often equivalently to those trained on the full completement of images, exhibiting Dice coefficients of 0.907 (single sequence) to 0.945 (complete set) for whole tumours and 0.701 (single sequence) to 0.891 (complete set) for component tissue types. This finding opens the door both to the application of segmentation models to large-scale historical data, for the purpose of building treatment and outcome predictive models, and their application to real-world clinical care. We further ascertain that segmentation models can accurately detect enhancing tumour in the absence of contrast-enhancing imaging, quantifying the burden of enhancing tumour with an  Brain tumour segmentation models with incomplete sets of MRI sequences—common in clinical practice—still delineate lesions well and even identify enhancing tumour without post-contrast imaging. The observed marginal benefits of additional MR sequences—especially contrast-enhanced—suggest that the costs and risks of imaging ordinarily sufficient to permit high-definition quantitative analysis may be reducible.  If the treatment susceptibilities and outcomes of individual patients differ widely, determined by the interactions of many multimodal characteristics,1 then large-scale, fully-inclusive, richly phenotyped data—including imaging—will be needed to predict them at the individual level. Such data can realistically be acquired only in the routine clinical stream, where its quality is inevitably degraded by the constraints of real-world clinical care. Although contemporary machine learning could theoretically provide a solution to this task, especially in the domain of imaging, its ability to cope with realistic, incomplete, low-quality data is yet to be determined.Progress in neuro-oncology is increasingly recognized to be obstructed by the marked 2-4 medical imaging,6 biomedical engineering,7 machine, and deep learning.8 The ability to segment an anatomical or pathological lesion in 3D confers the ability to evaluate it quantitatively—moving beyond visual qualitative assessment—with greater richness and fidelity than conventional 2D measurements repeatedly shown to be often spurious and inconsistent between radiologists,9-11 and with greater sensitivity to the heterogeneity of the underlying pathological patterns.12 Enabling radiological image segmentation opens a wide array of possibilities for downstream innovation in neuro-oncological healthcare and research, ranging from clinical stratification, outcome prediction, response assessment, treatment allocation, and risk quantification, many of which have already shown great promise. The underlying goal is to enhance the individual fidelity of data-driven decision-making, facilitating better patient-centred care,13-15 a remit especially warranted in neuro-oncology.Over the last few decades, lesion segmentation has formed a cornerstone of innovation across the domains of neuro-oncology,16-18 Its difficulty has even inspired an international competition for cutting-edge deep learning groups to create the best segmentation model. Known as the brain tumour segmentation challenge (BraTS), it is attracting increasing attention as well as support from both the Radiological Society of North America and the American Society of Neuroradiology, providing large-scale data with multimodal MRI—fluid-attenuated inversion recovery (FLAIR), T1, T2, and contrast-enhanced T1 (T1CE) sequences—as well as the labelled ground-truths of oedema, non-enhancing, and enhancing tumour.20The segmentation of brain tumours remains a particularly challenging task owing to the marked heterogeneity of their imaging appearances: spatial distribution, morphology, signal characteristics, and impact on adjacent healthy anatomical structures.21But while benchmark tasks have unquestionably aided the advancement of lesion segmentation—indeed of computer vision generally—they have compelled a research focus on developing uniformly multimodal models trained on sequence-complete acquisition sets, often rare in real-world clinical practice. The causes of incomplete data are legion, but common examples include patient contraindications to contrast, corruption by image artefacts, and image acquisition constraints such as those imposed in pre-operative stealth studies. Taking just one of many possible causes for image degradation, the prevalence of motion artefact has been reported as 7.5% of outpatient and 29.4% of inpatient MRI studies, with an estimated economic impact of $115 000 per scanner, per year.The real-world utility of tumour segmentation must lie within the clinical domain, such as for treatment planning and monitoring across neuro-oncology. Yet, the ability to undertake segmentation in these real-world clinical situations, where complete—‘perfect’—data is scarce, remains completely unknown. How well do contemporary segmentation modelling architectures perform when trained on sequence-incomplete data, and what features of the lesion are correctly identifiable under such circumstances?Here, we aimed to systematically quantify and answer these questions with the largest and most comprehensive study of its kind based on the application of state-of-the-art deep learning tumour segmentation models to large-scale MRI of brain tumours. We hypothesized that the decrement in segmentation performance with the loss of sequences would be modest, rendering good quality segmentations feasible with incomplete data.The study was approved by the local ethics committee. We received ethical permission for the consentless analysis of irrevocably anonymized data collected during routine clinical care.23 In brief, it includes a large retrospective sample of multi-institutional brain tumour MRI scans, with heterogeneous equipment, protocols, and image quality. The following sequences are included: T1-weighted, T2-weighted, FLAIR, and T1CE, with a pre-processing pipeline consisting of image co-registration, sampling to a 1 mm3 isotropic space, and brain extraction. Lesions were segmented with an ensemble of previous top-ranking BraTS algorithms with subsequent manual refinement and checking by a panel of board-certified attending neuroradiologists with more than 15 years of clinical experience in neuro-oncology.24 We used the training set of 1251 individuals of the BraTS 2021 challenge data—comprising 5004 separate images—as this group included all ground-truth labels for model cross-validation.We used the BraTS 2021 challenge data for all model training. This dataset is described in detail by its curators elsewhere.n = 5) and 3 T (n = 6) field strengths, from multiple different manufacturers, and over a 15-year period. Moreover, of our 50 participants, we also chose to include 10 of those with post-operative imaging and evidential tumour recurrence. This choice increased the difficulty of the task, for a model would need to recognize post-operative resection/surgical bed as separate from the subsequent disease recurrence, as well as capturing the instrumental heterogeneity of different MRI machines distributed in time and place.Having trained and evaluated a set of models on the BraTS 2021 challenge data, we sought to separately evaluate their performance on an additional held-out population from our own centre. The aim of this was to provide an additional robust safeguard of model performance with international and external validation. Specifically, we acquired retrospective imaging for a random sample of 50 individuals who underwent gadolinium-enhanced MRI head studies between 2006 and 2021 for a known glioblastoma as part of their routine clinical care at our centre. The random allocation of year selected was to further instil heterogeneity to our sample, as data would be acquired over one of 11 possible MRI scanners of both 1.5  self-configuring deep learning biomedical image segmentation modelling architecture,28 is in particular a self-configuring U-Net,31 incorporating the standard encoder-decoder architecture and skip connections, instance normalization and leaky rectified linear units. We used the high-resolution 3D architectural formulation in all experiments. The nnU-Net approach employs a polynomially decaying learning rate, initially set to 0.01, with stochastic gradient descent optimization. The loss function is a weighted sum of the Sørenson-Dice coefficient and cross-entropy. Training data is augmented on the fly, including with rotations, scaling, Gaussian noise and blur, brightness and contrast shifting, and gamma correction. Patch and batch size are also self-configured. Model training utilizes 1000 epochs, with foreground oversampling to mitigate the impact of class imbalances. We used 5-fold cross-validation for each experiment and its evaluation with the BraTS 2021 challenge data, as well as additional external/international out-of-sample evaluation of models with the additional data from our own centre as detailed above. A schematic of the model architecture is shown in Each nnU-NetWe trained all possible combinations of the MRI sequences T1, T2, FLAIR, and T1CE as separate models. This included all models using only a single sequence, two sequences, three sequences, and finally a complete four-sequence model. We also trained separate models for abnormality detection (i.e. a binary lesion mask to detect and segment the whole tumour) as well as tumour segmentation with the tissue classes of oedema, enhancing and non-enhancing tumour. This approach comprised 30 different models in total.33 in accordance with typical research practices.8 This metric derives the area of overlap between the model prediction and the labelled ground-truth. The Sørenson-Dice coefficient, or Dice coefficient, is given as:Performance was principally quantified by the out-of-sample Sørenson-Dice coefficient between ground truth and inferred labels,where TP is true positive, FP is false positive, and FN is false negative.34 All listed metrics were derived for whole tumour and the separate tissue constituents of oedema, enhancing and non-enhancing tumour, including with 95% confidence intervals (CIs), which are provided in detail throughout the We also quantified overall model accuracy, false discovery rate, false negative rate, false omission rate, false positive rate, negative predictive value, precision, and recall, ensuring a broad range of possible performance metrics.R2. We acquired the acquisition times of contemporaneous imaging protocols at our centre for a given imaging sequence, to allow comparison between a gain in model performance aligned to the time it would take to be acquired. Lastly, we applied t-distributed stochastic neighbour embedding (tSNE)35—a nonlinear dimensionality reduction technique—to the contrast-enhancing components of all lesions in the BraTS dataset to create a 2D representation of the lesions, projecting their high-dimensional similarities and differences into a readily surveyable space. We overlaid lesion volume and the Sørenson-Dice coefficient of lesion segmentations to display any variation in these indices with the morphology of the lesion.We constructed regression models between ground truth tumour volumes and model predictions, reporting the https://github.com/high-dimensional/tumour-seg. All BraTS 2021 challenge data are readily available from the challenge website at http://braintumorsegmentation.org20. Original nnU-Net source code is available at https://github.com/MIC-DKFZ/nnUNet28. Patient imaging data from our external validation site is not available for dissemination under the ethical framework that governs its use.All trained model weights, source code, and usage documentation are publicly availble at All models were trained on an NVIDIA DGX-1 with 8 16GB Tesla P100 GPUs. With approximately 3.5 days to train a single model, the task required just over 13 days utilization of all cards.All models performed well on whole tumour segmentation qualitatively, despite varying degrees sequence-completeness, with quantitative performance ranging from a Dice coefficient of 0.907 (95% CI 0.904–0.910) (single sequence) to 0.945 (95% CI 0.943–0.947) (complete sequence set) . ResultsWe aligned the acquisition times of all possible combinations of sequences using contemporaneous scanner protocol data at our centre and from which determined the gain in model fidelity in Dice per scanning minute . This deR2 0.964); T1 alone (R2 0.953); T2 alone (R2 0.966); FLAIR + T1 (R2 0.973); FLAIR + T2 (R2 0.976); T1 + T2 (R2 0.962); FLAIR + T1 + T2 (R2 0.972). Furthermore, inspection of the t-SNE-derived low dimensional representation of the lesions did not reveal any clear relation between lesion anatomy and segmentation performance across models lacking contrast-enhanced sequences   . This wa20 we therefore then utilized these model predictions using complete imaging sets as our new ground-truth with subsequent manual checking and refinement where required. We then compared the performance of all other models, i.e. those without four sequences, to this revised ground-truth. Model performances were again highly reproducible between the BraTS 2021 challenge data and that of our own external sample, with Dice coefficients significantly correlated   . As is uWe applied our segmentation pipeline to a single patient from our own centre with variable quality (and availability) of imaging during their routine clinical care between 2010 and 2015. We also used this to quantitatively demonstrate lesion volumetry across this time, showing treatment response in early years, followed by stability, and later disease progression .We have systematically surveyed the ability of state-of-the-art tumour segmentation models in delineating and quantifying brain tumour components in real-world clinical situations of incomplete and/or low-quality data. We reveal there is surprisingly little variation in the performance of segmenting a whole tumour with the number of modelled imaging modalities. Greater variation is observed when segmenting tumour components: a clear pattern of incremental improvement with the addition of further sequences emerges. These findings open the door both to the application of segmentation models to large-scale historical data, for the purpose of building treatment and outcome predictive models, and their deployment to real-world clinical care.https://github.com/high-dimensional/tumour-seg).Strikingly, we find that segmentation models trained without contrast-enhancing imaging still characterize the anatomy of enhancing tumour components remarkably well. This includes quantification of the volumetric burden of enhancing tumour with high accuracy. Out-of-sample validation illustrates strong generalizability of these findings, including across super-resolved non-isotropic acquisitions, in varying MRI field strengths, and in tumour recurrences on complex postoperative imaging of limited quality. Our analyses show that current segmentation models generalize surprisingly well to real-world clinical imaging varying in quality and sequence completeness. We also use a case-based example  to demonModel fidelity unsurprisingly rose with the number of modelled sequences. What is, however, surprising is the ability of models based on limited data to delineate lesions very well. This is particularly striking in the segmentation of the whole tumour, where only marginal differences in Dice coefficient were seen across the range of sequence combinations. We can conclude that even single sequences may be sufficient for segmenting brain tumours with fidelity adequate for many downstream tasks.38The segmentation of tumour compartments—oedema, enhancing, and non-enhancing tumour—however presents a more complex picture. Single sequence models of oedema and enhancing tumour perform best with FLAIR and T1CE sequences, respectively. But models of two or three sequences exhibit less intuitive behaviour. Adding FLAIR to T1CE achieves whole tumour performance very close to that of the complete, four-sequence model, despite receiving only half the data. To that end, single T1CE MRI studies  may therefore benefit from the addition of a FLAIR sequence to enable more optimum visualization of the entire lesion to aid pre-operative planning. A two-sequence model of T1 and T1CE can delineate oedema well without the T2 or FLAIR typically used to identify it. Overall, these findings illustrate the ability of contemporary computer vision models to extract information from multiple sequences with greater efficiency than intuitive perception may suggest.38 without any information about its enhancing properties, reveals the presence of non-intuitive imaging features that could render the enhancing component quantifiable without the use of contrast. This challenges the current dogma of ‘enhancing tumour’, given a machine can identify it without the administration of intravenous agents ordinarily required to reveal it. Further investigation of this possibility is warranted, including the detectability of the presence of any degree of enhancement. These findings also illustrate a clinically important opportunity in oncological imaging when contrast enhanced imaging cannot be acquired, not least in situations of repeated follow-up where the over-use of contrast should ideally be limited, for example to minimize Gadolinium retention in paediatric patients. We note recent research on completing image sets synthetically may be fruitful in this domain,39-42 as well as a wider body of literature aiming to reduce the requirement for contrast.43Strikingly, we found that models without the contrast enhancing sequence (T1CE) can still segment what has been hand-labelled by experienced neuroradiologists with full imaging datasets as the enhancing component of the tumour well, not least with performance largely invariant to the size, shape, and neuroanatomical location of the enhancing component. This introduces the possibility—across both research and clinical practice—to make approximate inferences about the anatomy of enhancing components without the use of contrast. Moreover, that a model can identify what has been termed the ‘enhancing’ tumour,29 The use of this software is well justified given its validated performance across many domains of medical imaging.30 But segmentation models are a rapidly evolving field, and so it is possible that other architectures might perform differently, perhaps even superiorly, to that used here. It is however important to note that our aim was not to identify the definitive ‘best’ tumour segmentation model but to quantify the impact of sequence completeness. Our aim is to determine how such models could perform in real-world clinical situations where ‘perfect’ data rarely exists, quantifying their appropriateness for translation to the clinical frontline. Furthermore, BraTS training data includes only preoperative imaging, yet it is plausible that much of the value in segmentation models may lie in longitudinal follow-up including that of postoperative resection appearances. Whilst we included a selection of postoperative imaging in our additional external validation, a more dedicated evaluation in the postoperative setting should form an area for future investigation.In our systematic evaluation of the ability of deep learning models to identify brain tumours with varying degrees of sequence-incomplete data, we opted to use one single self-configuring architecture—nnU-Net.without the use of contrast-enhanced imaging, potentially providing clinical guidance in circumstances where contrast administration is contraindicated or where its repeated use should be minimized. This opens the way to quantifying enhancing components without the administration of intravenous agents, not least invites a revision of the notion of tumour enhancement if the same information can be extracted without contrast. Its applicability includes not just prospective scenarios wherein a full scan may not be possible such as patients unable to receive intravenous contrast but also applies to historical datasets where certain sequences might not have been acquired. Out-of-sample validation illustrates strong generalizability, across non-isotropic acquisitions and even on complex postoperative imaging where tumours have recurred. Translation of such models to the clinical frontline for response assessment—where complete data is a rarity—may be easier than hitherto believed.Automated segmentation models can characterize tumours in real-world clinical situations of incomplete imaging data remarkably well. Such models are also able to identify enhancing tumour Brain Communications online.fcad118_Supplementary_DataClick here for additional data file.