The Biomarker Toolkit - an evidence-based guideline to predict cancer biomarker success and guide development.

BACKGROUND: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation. METHODS: All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist. RESULTS: Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869-0.935, CRC: p>0.0001, 95.0% CI: 0.918-0.954). CONCLUSIONS: This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed.

Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma.

BACKGROUND: Oesophageal adenocarcinoma poses a significant global health burden, yet the staging used to predict survival has limited ability to stratify patients by outcome. This study aimed to identify published clinical models that predict survival in oesophageal adenocarcinoma and to evaluate them using an independent international multicentre dataset. METHODS: A systematic literature search (title and abstract) using the Ovid Embase and MEDLINE databases (from 1947 to 11 July 2020) was performed. Inclusion criteria were studies that developed or validated a clinical prognostication model to predict either overall or disease-specific survival in patients with oesophageal adenocarcinoma undergoing surgical treatment with curative intent. Published models were validated using an independent dataset of 2450 patients who underwent oesophagectomy for oesophageal adenocarcinoma with curative intent. RESULTS: Seventeen articles were eligible for inclusion in the study. Eleven models were suitable for testing in the independent validation dataset and nine of these were able to stratify patients successfully into groups with significantly different survival outcomes. Area under the receiver operating characteristic curves for individual survival prediction models ranged from 0.658 to 0.705, suggesting poor-to-fair accuracy. CONCLUSION: This study highlights the need to concentrate on robust methodologies and improved, independent, validation, to increase the likelihood of clinical adoption of survival predictions models.

Identifying the limitations of cardiopulmonary exercise testing prior to esophagectomy using a pooled analysis of patient-level data.

Preoperative cardiopulmonary exercise testing (CPET) provides an objective assessment of aerobic fitness in patients undergoing surgery. While peak oxygen uptake during exercise (VO2peak) and anaerobic threshold have demonstrated a moderate correlation with the development of complications following esophagectomy, no clinically useful threshold values have been defined. By pooling patient level data from existing studies, we aimed to define optimal thresholds for preoperative CPET parameters to predict patients at high risk of postoperative complications. Studies reporting on the relationship between preoperative CPET variables and post-esophagectomy complications were determined from a comprehensive literature search. Patient-level data were obtained from six contributing centers for pooled-analyses. Outcomes of interest included cardiopulmonary and non-cardiopulmonary complications, unplanned intensive care unit readmission, and 90-day and 12-month all-cause mortality. Receiver operating characteristic curves and logistic regression models estimated the predictive value of CPET parameters for each individual outcome of interest. This analysis comprised of 621 patients who underwent CPET prior to esophagectomy during the period from January 2004 to March 2017. For both anaerobic threshold and VO2peak, none of the receiver operating characteristic curves achieved an area under the curve value > 0.66 for the outcomes of interest. The discriminatory ability of CPET for determining high-risk patients was found to be poor in patients undergoing an esophagectomy. CPET may only carry an adjunct role to clinical decision-making.

A systematic approach to therapeutic target selection in oesophago-gastric cancer.

OBJECTIVE: The success of personalised therapy depends on identification and inhibition of the oncogene(s) on which that tumour is dependent. We aimed to determine whether a receptor tyrosine kinase (RTK) array could be used to select the most effective therapeutic strategies in molecularly heterogeneous oesophago-gastric adenocarcinomas. DESIGN: Gene expression profiling from oesophago-gastric tumours (n=75) and preinvasive stages (n=57) identified the active signalling pathways, which was confirmed using immunohistochemistry (n=434). RTK arrays on a cell line panel (n=14) determined therapeutic targets for in vitro cytotoxic testing. Feasibility of this personalised approach was tested in tumour samples (n=46). RESULTS: MAPK was the most frequently activated pathway (32/75 samples (42.7%)) with progressive enrichment in preinvasive disease stages (p<0.05) and ERK phosphorylation in 148/434 (34.3%) independent samples. Cell lines displayed a range of RTK activation profiles. When no RTKs were activated, tyrosine kinase inhibitors (TKIs) and a Mek inhibitor were not useful (MKN1). In lines with a dominant phosphorylated RTK (OE19, MKN45 and KATOIII), selection of this TKI or Mek in nM concentrations induced cytotoxicity and inhibited Erk and Akt phosphorylation. In cells lines with complex activation profiles (HSC39 and OE33), a combination of TKIs or Mek inhibition (in nM concentrations) was necessary for cytotoxicity and inhibition of Erk and Akt phosphorylation. Human tumours demonstrated diverse activation profiles and 65% of cases had two or more active RTKs. CONCLUSIONS: The MAPK pathway is commonly activated in oesophago-gastric cancer following activation of a variety of RTKs. Molecular phenotyping can inform a rational choice of targeted therapy.

A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery.

PURPOSE: A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish tissue type based on spectral data. The aim of this study was to develop a deep learning-based method for DRS probe detection and tracking to aid classification of tumour and non-tumour gastrointestinal (GI) tissue in real time. METHODS: Data collected from both ex vivo human tissue specimen and sold tissue phantoms were used for the training and retrospective validation of the developed neural network framework. Specifically, a neural network based on the You Only Look Once (YOLO) v5 network was developed to accurately detect and track the tip of the DRS probe on video data acquired during an ex vivo clinical study. RESULTS: Different metrics were used to analyse the performance of the proposed probe detection and tracking framework, such as precision, recall, mAP 0.5, and Euclidean distance. Overall, the developed framework achieved a 93% precision at 23 FPS for probe detection, while the average Euclidean distance error was 4.90 pixels. CONCLUSION: The use of a deep learning approach for markerless DRS probe detection and tracking system could pave the way for real-time classification of GI tissue to aid margin assessment in cancer resection surgery and has potential to be applied in routine surgical practice.

Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment.

BACKGROUND: Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and poorer survival. The authors investigated diffuse reflectance spectroscopy (DRS) to distinguish tumour and non-tumour tissue in ex-vivo colorectal specimens, to aid margin assessment and provide augmented visual maps to the surgeon in real-time. METHODS: Patients undergoing elective colorectal cancer resection surgery at a London-based hospital were prospectively recruited. A hand-held DRS probe was used on the surface of freshly resected ex-vivo colorectal tissue. Spectral data were acquired for tumour and non-tumour tissue. Binary classification was achieved using conventional machine learning classifiers and a convolutional neural network (CNN), which were evaluated in terms of sensitivity, specificity, accuracy and the area under the curve. RESULTS: A total of 7692 mean spectra were obtained for tumour and non-tumour colorectal tissue. The CNN-based classifier was the best performing machine learning algorithm, when compared to contrastive approaches, for differentiating tumour and non-tumour colorectal tissue, with an overall diagnostic accuracy of 90.8% and area under the curve of 96.8%. Live on-screen classification of tissue type was achieved using a graduated colourmap. CONCLUSION: A high diagnostic accuracy for a DRS probe and tracking system to differentiate ex-vivo tumour and non-tumour colorectal tissue in real-time with on-screen visual feedback was highlighted by this study. Further in-vivo studies are needed to ensure integration into a surgical workflow.

Feasibility of Implementation and the Impact of a Digital Prehabilitation Service in Patients Undergoing Treatment for Oesophago-Gastric Cancer.

BACKGROUND: Home-based and supervised prehabilitation programmes are shown to have a positive impact on outcomes in patients with oesophago-gastric (OG) cancer. The primary aim of this study was to establish the feasibility of delivering a digital prehabilitation service. METHODS: Patients undergoing treatment for OG cancer with curative intent were recruited into the study. During the COVID-19 pandemic, patients were offered a digital prehabilitation service. Following the lifting of COVID-19 restrictions, patients were also offered both a hybrid clinic-based in-person service and a digital service. Implementation and clinical metrics from the two prehabilitation models were compared. RESULTS: 31 of 41 patients accepted the digital service (75%). Of the people who started the digital programme, 3 dropped out (10%). Compliance with the weekly touchpoints was 86%, and the median length of programme was 12 weeks. Twenty-six patients enrolled in the in-person service. Two patients dropped out (10%). Average compliance to weekly touchpoints was 71%, and the median length of programme was 10 weeks. In the digital group, sit to stand (STS) increased from 14.5 (IQR 10.5-15.5) to 16 (IQR 16-22); p = 0.02. Median heart rate recovery (HRR) increased from 10.5 (IQR 7.5-14) to 15.5 (IQR 11-20) bpm; p = 0.24. There was a significant drop in distress (median 3 (IQR 0-5) to 1 (IQR 0-2); p = 0.04) and a small drop in anxiety (median 3 (0-5) to 2 (0-3); p = 0.22). There was no difference in the postoperative complication rate and length of hospital stay between the two groups. DISCUSSION: This study has shown that digital prehabilitation can be delivered effectively to patients with OG cancer, with high engagement and retention rates. We observed improvements in some physical and psychological parameters with the digital service, with comparable clinical outcomes to the in-person service.

Digital outpatient health solutions as a vehicle to improve healthcare sustainability-a United Kingdom focused policy and practice perspective.

Introduction: In the midst of a global climate emergency and with health care systems across the world facing extreme pressure, interest in digital approaches as a potential part-solution to these challenges has increased rapidly. The evidence base to support the role that digitalization can play in moving towards more sustainable models of healthcare is growing, as is the awareness of this key area of healthcare reform amongst policy makers, clinicians and the public. Method and Results: In this policy and practice review we explore four domains of healthcare sustainability-environmental, economic, and patient and clinician, delineating the potential impact that digitally enabled healthcare can have on each area. Real-world examples are provided to illustrate the impact individual digital interventions can have on each pillar of sustainability and demonstrate the scale of the potential benefits which can be achieved. Discussion: Digitally enabled healthcare solutions present an approach which offer numerous benefits, including environmental sustainability, economic benefits, and improved patient experience. There are also potential drawbacks such as the risk of digital exclusion and the need for integration with existing technology platforms. Overall, it is essential to strike a balance between the benefits and potential drawbacks of digital healthcare solutions to ensure that they are equitable, effective, and sustainable.

Why are women still leaving academic medicine? A qualitative study within a London Medical School.

OBJECTIVES: To identify factors that influenced women who chose to leave academic medicine. DESIGN AND MAIN OUTCOME MEASURES: Independent consultants led a focus group of women in medicine who had left academia after completion of their postgraduate research degree at Imperial College London Faculty of Medicine. Thematic analysis was performed on the transcribed conversations. PARTICIPANTS AND SETTING: Nine women physicians who completed a postgraduate degree (MD or PhD) at a large London Medical School and Academic Health Sciences Centre, Imperial College London, but did not go on to pursue a career in academic medicine. RESULTS: Influences to leave clinical academia were summarised under eight themes-career intentions, supervisor support, institutional human resources support, inclusivity, work-life balance, expectations, mentors and role models, and pregnancy and maternity leave. CONCLUSION: The women in our focus group reported several factors contributing to their decision to leave clinical academia, which included lack of mentoring tailored to specific needs, low levels of acceptance for flexible working to help meet parental responsibilities and perceived explicit gender biases. We summarise the multiple targeted strategies that Imperial College London has implemented to promote retention of women in academic medicine, although more research needs to be done to ascertain the most effective interventions.

Real-time tracking of a diffuse reflectance spectroscopy probe used to aid histological validation of margin assessment in upper gastrointestinal cancer resection surgery.

SIGNIFICANCE: Diffuse reflectance spectroscopy (DRS) allows discrimination of tissue type. Its application is limited by the inability to mark the scanned tissue and the lack of real-time measurements. AIM: This study aimed to develop a real-time tracking system to enable localization of a DRS probe to aid the classification of tumor and non-tumor tissue. APPROACH: A green-colored marker attached to the DRS probe was detected using hue-saturation-value (HSV) segmentation. A live, augmented view of tracked optical biopsy sites was recorded in real time. Supervised classifiers were evaluated in terms of sensitivity, specificity, and overall accuracy. A developed software was used for data collection, processing, and statistical analysis. RESULTS: The measured root mean square error (RMSE) of DRS probe tip tracking was 1.18 ± 0.58 mm and 1.05 ± 0.28 mm for the x and y dimensions, respectively. The diagnostic accuracy of the system to classify tumor and non-tumor tissue in real time was 94% for stomach and 96% for the esophagus. CONCLUSIONS: We have successfully developed a real-time tracking and classification system for a DRS probe. When used on stomach and esophageal tissue for tumor detection, the accuracy derived demonstrates the strength and clinical value of the technique to aid margin assessment in cancer resection surgery.

Progress with Metabolomic Blood Tests for Gastrointestinal Cancer Diagnosis-An Assessment of Biomarker Translation.

There is an urgent need for cost-effective, non-invasive tools to detect early stages of gastrointestinal cancer (colorectal, gastric, and esophageal cancers). Despite many publications suggesting circulating metabolites acting as accurate cancer biomarkers, few have reached the clinic. In upper gastrointestinal cancer this is critically important, as there is no test to complement gold-standard endoscopic evaluation in patients with mild symptoms that do not meet referral criteria. Therefore, this study aimed to describe and solve this translational gap. Studies reporting diagnostic accuracy of metabolomic blood-based gastrointestinal cancer biomarkers from 2007 to 2020 were systematically reviewed and progress of each biomarker along the discovery-validation-adoption pathway was mapped. Successful biomarker translation was defined as a composite endpoint, including patent protection/FDA approval/recommendation in national guidelines. The review found 77 biomarker panels of gastrointestinal cancer, including 25 with an AUROC >0.9. All but one was stalled at the discovery phase, 9.09% were patented and none were clinically approved, confirming the extent of biomarker translational gap. In addition, there were numerous "re-discoveries," including histidine, discovered in 7 colorectal studies. Finally, this study quantitatively supports the presence of a translational gap between discovery and clinical adoption, despite clear evidence of highly performing biomarkers with significant potential clinical value.

Real-time Tracking and Classification of Tumor and Nontumor Tissue in Upper Gastrointestinal Cancers Using Diffuse Reflectance Spectroscopy for Resection Margin Assessment.

Importance: Cancers of the upper gastrointestinal tract remain a major contributor to the global cancer burden. The accurate mapping of tumor margins is of particular importance for curative cancer resection and improvement in overall survival. Current mapping techniques preclude a full resection margin assessment in real time. Objective: To evaluate whether diffuse reflectance spectroscopy (DRS) on gastric and esophageal cancer specimens can differentiate tissue types and provide real-time feedback to the operator. Design, Setting, and Participants: This was a prospective ex vivo validation study. Patients undergoing esophageal or gastric cancer resection were prospectively recruited into the study between July 2020 and July 2021 at Hammersmith Hospital in London, United Kingdom. Tissue specimens were included for patients undergoing elective surgery for either esophageal carcinoma (adenocarcinoma or squamous cell carcinoma) or gastric adenocarcinoma. Exposures: A handheld DRS probe and tracking system was used on freshly resected ex vivo tissue to obtain spectral data. Binary classification, following histopathological validation, was performed using 4 supervised machine learning classifiers. Main Outcomes and Measures: Data were divided into training and testing sets using a stratified 5-fold cross-validation method. Machine learning classifiers were evaluated in terms of sensitivity, specificity, overall accuracy, and the area under the curve. Results: Of 34 included patients, 22 (65%) were male, and the median (range) age was 68 (35-89) years. A total of 14 097 mean spectra for normal and cancerous tissue were collected. For normal vs cancer tissue, the machine learning classifier achieved a mean (SD) overall diagnostic accuracy of 93.86% (0.66) for stomach tissue and 96.22% (0.50) for esophageal tissue and achieved a mean (SD) sensitivity and specificity of 91.31% (1.5) and 95.13% (0.8), respectively, for stomach tissue and of 94.60% (0.9) and 97.28% (0.6) for esophagus tissue. Real-time tissue tracking and classification was achieved and presented live on screen. Conclusions and Relevance: This study provides ex vivo validation of the DRS technology for real-time differentiation of gastric and esophageal cancer from healthy tissue using machine learning with high accuracy. As such, it is a step toward the development of a real-time in vivo tumor mapping tool for esophageal and gastric cancers that can aid decision-making of resection margins intraoperatively.

A 4-gene signature predicts survival of patients with resected adenocarcinoma of the esophagus, junction, and gastric cardia.

BACKGROUND & AIMS: The incidence of esophageal and junctional adenocarcinoma has increased 6-fold in the past 30 years and 5-year survival remains approximately 20%. Current staging is limited in its ability to predict survival which has ramifications for treatment choices. The aim of this study was to generate and validate a molecular prognostic signature for esophageal adenocarcinoma. METHODS: Gene expression profiling was performed and the resulting 42,000 gene signatures correlated with clinical and pathologic features for 75 snap-frozen esophageal and junctional resection specimens. External validation of selected targets was performed on 371 independent cases using immunohistochemistry to maximize clinical applicability. RESULTS: A total of 119 genes were associated significantly with survival and 270 genes with the number of involved lymph nodes. Filtering of these lists resulted in a shortlist of 10 genes taken forward to validation. Four genes proved to be prognostic at the protein level (deoxycytidine kinase [DCK], 3'-phosphoadenosine 5'-phosphosulfate synthase 2 [PAPSS2], sirtuin 2 [SIRT2], and tripartite motif-containing 44 [TRIM44]) and were combined to create a molecular prognostic signature. This 4-gene signature was highly predictive of survival in the independent external validation cohort (0/4 genes dysregulated 5-year survival, 58%; 95% confidence interval [CI], 36%-80%; 1-2/4 genes dysregulated 5-year survival, 26%; 95% CI, 20%-32%; and 3-4/4 genes dysregulated 5-year survival, 14%; 95% CI, 4%-24% (P = .001). Furthermore, this 4-gene signature was independently prognostic in a multivariable model together with the existing clinical TNM staging system (P = .013). CONCLUSIONS: This study has generated a clinically applicable prognostic gene signature that independently predicts survival in an external validation cohort and may inform management decisions.

Do smaller adults wait longer for liver transplantation? A comparison of the UK and the USA data.

BACKGROUND: The number of patients on the UK and the USA liver transplant list is increasing. As size match is an important factor in the UK organ allocation, we studied the effect of recipient size on liver transplantation in the UK and the USA. METHODS: The UK Transplant and United Network for Organ Sharing databases were used to assess difference in access to transplantation between smaller adult patients and their larger counterparts over three time periods. Subsequently, proportions of split, NHBD and living-donor transplants were analyzed. RESULTS: There were 1576 UK and 29,150 USA patients in our analysis. The UK small patients have been significantly disadvantaged in access to transplantation particularly in early years and in adult only transplant units. This contrasts to the USA where smaller patients have never been disadvantaged and transplantation rates are steadily increasing. Split-liver transplants are being carried out in increasing numbers in the UK but not the USA. CONCLUSIONS: Small adults are still less likely to be transplanted at six months in adult only units in the UK. The lack of size matched organs for smaller adults and the overall decrease in rates of transplantation in the UK may be remedied by careful consideration of allocation policy and increased use of innovative techniques.

Progressive silencing of p14ARF in oesophageal adenocarcinoma.

The frequency of oesophageal adenocarcinoma is increasing in Western countries for unknown reasons, and correlates with a corresponding increase in the pre-malignant condition, Barrett's Oesophagus, which raises the risk of adenocarcinoma by some 40- to 125-fold. We have examined how disease progression correlates with changes in expression of the p14ARF (ARF) tumour suppressor, a key regulator of the p53 tumour suppressor pathway that is silenced in some 30% of cancers overall, but for which a role in oesophageal cancer is unclear. We have used quantitative PCR, RT-PCR, methylation-specific PCR and chromatin-immunoprecipitation to examine the regulation and function of ARF in oesophageal adenocarcinoma tissue specimens and cell lines. We find highly significant reductions (P< 0.001) in ARF expression during disease progression from normal oesophageal epithelium to Barrett's Oesophagus to adenocarcinoma, with 57/76 (75%) adenocarcinomas displaying undetectable levels of ARF expression. Retention of ARF expression in adenocarcinoma is a highly significant indicator of increased survival (P< 0.001) and outperforms all clinical variables in a multivariate model. CpG methylation as well as histone H3 methylation of lysines 9 and 27 contribute independently to ARF gene silencing in adenocarcinoma cell lines and can be reversed by 5-aza-2'-deoxycytidine. The results suggest that silencing of ARF is involved in the pathogenesis of oesophageal adenocarcinoma and show that either DNA or histone methylation can provide the primary mechanism for ARF gene silencing. Silencing of ARF could provide a useful marker for increased risk of progression and poor prognosis.

Kinetics Model of Femtosecond Laser Ionization in Nitrogen and Comparison to Experiment.

A zero-dimensional kinetics simulation of femtosecond laser ionization in nitrogen is proposed that includes fast gas heating effects, electron scattering (elastic and inelastic) rate coefficients from BOLSIG+ and photoionization based on filamentation theory. Key rate coefficients possessing significant uncertainty are tuned (within the range of variation found in literature) to reproduce the time-varying signal acquired by a bandpass-filtered photomultiplier tube with good agreement up to several hundred nanoseconds. Separate spectral measurements calibrate the relative strength of signal components. Derived equations relate the model to experimental measurements in absolute units. Reactions contributing to the rate of change of important species are displayed in terms of absolute rate and relative fraction. In general, decreasing the gas density lengthens the duration of early reactions and delays the start of later reactions. The model agrees with data taken in a variable temperature and pressure free jet by an intensified camera. Results demonstrate that initial signal depends primarily on gas density and secondarily on gas temperature. The optimal (maximum) initial signal occurs at a gas density below atmospheric. Decreases in gas density alter the evolution of excited-state populations, postponing the peak (while reducing its value) and slowing the rate of decay. For the optimal case, populations are favorably shifted in time with respect to the gate delay (and width) to boost the signal. Reductions in gas temperature generally enhance initial signal due to elevated dissociative recombination of cluster ions (along with excited-state coupling from quenching and energy pooling).

Unseeded Velocimetry in Nitrogen for High-Pressure, Cryogenic Wind Tunnels, Part 1: Femtosecond-Laser Tagging.

Femtosecond laser electronic excitation tagging (FLEET) velocimetry is characterized for the first time at high-pressure, low-temperature conditions. FLEET signal intensity and signal lifetime data are examined for their thermodynamic dependences; temperatures range from 89 K to 275 K while pressures are varied from 85 kPa to 400 kPa. The FLEET signal intensity is found to scale linearly with the flow density. An inverse density dependence is observed in the FLEET signal lifetime data, with little independent sensitivity to the other thermodynamic conditions apparent. FLEET velocimetry is demonstrated in the NASA Langley 0.3-m Transonic Cryogenic Tunnel. Velocity measurements are made over the entire operational envelope: Mach numbers from 0.2 to 0.75, total (stagnation) temperatures from 100 K to 280 K, and total pressures from 100 kPa to 400 kPa. The velocity measurement accuracy is assessed over this domain of conditions. Measurement errors below 1.15 percent are typical, with slightly decreasing accuracy as temperatures are decreased. Assessment of the measurement precision finds a zero-velocity precision of 0.4 m/s. The precision is observed to have a weak temperature dependence as well, likely a result of the shorter lifetimes experienced at higher densities. The velocity dynamic range is found to have a nominal value of 650. Finally the spatial resolution of the measurements is found to be a dominated by the physical size of the FLEET signal and advective motion. The transverse spatial resolution is found to be 1 mm, while the streamwise spatial resolution is dependent on velocity with a minimum of 2 mm and a maximum of 3.3 mm.

Tension haemothorax from a bleeding branch of the renal artery following isolated penetrating thoracic trauma: a rare presentation.

A 27-year-old man presented to a major trauma centre with two posterolateral thoracic stab injuries over the right scapula and thoracoabdominal junction. He was tachycardic and hypotensive with a chest X-ray revealing a large right-sided tension haemothorax, requiring insertion of two intercostal chest drains. A subsequent CT scan demonstrated a grade 4 right kidney laceration with active back bleeding from a renal artery branch, through a right diaphragmatic defect, into the pleural cavity. Embolisation of the feeding renal vessel controlled the bleeding and avoided the need for a nephrectomy. The patient required subsequent video-assisted thoracoscopic evacuation of the haemothorax and diaphragmatic repair, confirming that there was no associated lung or major vessel injury. A ureteric stent was ultimately inserted to manage a persistent urinary leak. This case highlights a rare cause for a common traumatic presentation and the need for a multidisciplinary approach in effective management of complex, multiorgan trauma.