Deep pancreas segmentation with uncertain regions of shadowed sets

Morbid obesity is a recognized risk factor for gastrointestinal cancer. Little is known about pancreatic cancer developing after gastric bypass surgery or about surgery for this type of tumor following bariatric surgery. This report describes a case of pancreatic head cancer identified 3 months after laparoscopic sleeve gastrectomy for morbid obesity. During routine follow-up, mild abdominal pain and elevated pancreatic enzymes prompted computed tomography, which revealed mild edematous pancreatitis. Hyperbilirubinemia developed, and magnetic resonance imaging showed a pancreatic head tumor. CA19-9 was elevated. After a pylorus-preserving pancreatic head resection, the postoperative course was uneventful. The patient received adjuvant chemotherapy. Unfortunately, at the time of writing (9 months postoperatively), a local recurrence and hepatic metastases were diagnosed. Patients treated with bariatric surgery who develop new symptoms or report constant mild symptoms should be evaluated using endoscopy and radiomorphological imaging. Interdisciplinary obesity treatment can then offer significant benefits for the patient, particularly in the case of pancreatic cancer, which is still difficult to diagnose. In addition, there is a need for epidemiological studies of patients who undergo bariatric surgery and subsequently develop cancer.

Background and objectiveThe size, shape, and position of the pancreas are affected by the patient characteristics such as age, sex, adiposity. Owing to more complex anatomical structures (size, shape, and position) of the pancreas, specialists have some difficulties in the analysis of pancreatic diseases (diabetes, pancreatic cancer, pancreatitis). Therefore, the treatment of the disease requires enormous time and depends on the experience of specialists. In order to decrease the rate of pancreatic disease deaths and to assist the specialist in the analysis of pancreatic diseases, automatic pancreas segmentation techniques have been actively developed in the research article for many years. MethodsAlthough the rapid growth of deep learning and proving satisfactory performance in many medical image processing and computer vision applications, the maximum Dice Similarity Coefficients (DSC) value of these techniques related to automatic pancreas segmentation is only around 85% due to complex structure of the pancreas and other factors. Contrary to previous techniques which are required significantly higher computational power and memory, this paper suggests a novel two-phase approach for high-accuracy automatic pancreas segmentation in computed tomography (CT) imaging. The proposed approach consists of two phases; (1) Pancreas Localization, where the rough pancreas position is detected on the 2D CT slice by adopting Mask R-CNN model, (2) Pancreas Segmentation, where the segmented pancreas region is produced by refining the candidate pancreas region with 3D U-Net on the 2D sub-CT slices generated in the first phase. Both qualitative and quantitative assessments of the proposed approach are performed on the NIH data set. ResultsIn order to evaluate the achievement of the recommended approach, a total of 16 different automatic pancreas segmentation techniques reported in the literature are compared by utilizing performance assessment procedures which are Dice Similarity Coefficient (DSC), Jaccard Index (JI), Precision (PRE), Recall (REC), Pixel Accuracy (ACC), Specificity (SPE), Receiver Operating Characteristics (ROC) and Area under ROC curve (AUC). The average values of DSC, JI, REC and ACC are computed as 86.15%, 75.93%, 86.27%, 86.27% and 99.95% respectively, which are the best values among well-established studies for automatic pancreas segmentation. ConclusionIt is demonstrated with qualitative and quantitative results that our suggested two-phase approach creates more favorable results than other existing approaches.

Chronic Pancreatitis and Pancreatic Cancer: Prediction and Mechanism

Robust and efficient abdominal CT segmentation using shape constrained multi-scale attention network

Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this work, we describe a custom-build 3D fully convolutional network (FCN) that can process a 3D image including the whole pancreas and produce an automatic segmentation. We investigate two variations of the 3D FCN architecture; one with concatenation and one with summation skip connections to the decoder part of the network. We evaluate our methods on a dataset from a clinical trial with gastric cancer patients, including 147 contrast enhanced abdominal CT scans acquired in the portal venous phase. Using the summation architecture, we achieve an average Dice score of 89.7 $\pm$ 3.8 (range [79.8, 94.8]) % in testing, achieving the new state-of-the-art performance in pancreas segmentation on this dataset.

Racial Disparity Between Whites and African Americans in Incidence and Outcome of Pancreatic Cancer: Have We Made a Difference?

192 Background: 5-10% of pancreatic cancer (PC) cases show familial aggregation. 20% of these correspond to syndromes: Peutz Jeghers, hereditary pancreatitis, familial multiple melanoma, breast and ovarian cancer (HBOC) and others. Familial pancreatic cancer (FPC) is defined as: ≥2 first degree relatives with PC and with no other known syndromes. FPC seems to have autosomal dominant inheritance, but the genetic cause is unknown. Methods: The objectives are: 1) To develop the first FPC Spanish Registry, connecting different groups interested in this disease 2) To study inheritance, phenotypic and molecular characteristics of the FPC, and families with early PC 3) To establish a strategy for early detection of PC in high-risk individuals and to implement it 4) To characterize preneoplastic lesions and diagnosed PC by monitoring high-risk individuals. 16 Spanish hospitals are participating. This study has two components: 1) Cohort to identify families with FPC and hereditary PC. Sources for the families are the PanGen-ES Study, a case-control study of PC which identifies families through a questionnaire on family history of cancer, and Genetic Counseling Units, 2) Cohort of high-risk families. The latter will be followed up by endoscopic ultrasound (EUS) and CT ± abdominal magnetic resonance imaging. In addition, circulating tumor cells (CTC) in peripheral blood will be determined. Results: The assessment of family history of the 421 cases included in the PanGen Study has identified 32 (7.6%) families with FPC and 52 patients with PC ≤ 50 years (12.4%). In addition, the 190 families presenting PC aggregation with other neoplasms are being further evaluated. At this time we have obtained clinical data and blood samples to carry out molecular studies of 23 individuals: 17 belonging to 3 families with FPC, and 6 members of 2 families with an HBOC with some cases of pancreatic cancer. 18 relatives at risk began a follow-up with EUS and CT, with no detection of any suspicious pancreatic lesion; also CTC have not been detected. Conclusions: This initiative will permit to know more about FPC and will serve to evaluate protocols and PC markers in screening the high-risk population, and promote connections with other international groups.

Pancreatic cancer is the most devastating of all cancers with an extremely poor prognosis. In US alone, over 50 000 new cases of pancreatic cancer are reported annually, and about the same number succumb to it, making pancreatic cancer the third most common cause of cancer deaths. Most patients with pancreatic cancer present with advanced disease, which cannot be resected surgically, and for these patients chemotherapy is the only option. Even patients who undergo resection require adjuvant therapy to decrease the risk of recurrence. Since the 1950s, a variety of different agents, like antimetabolites, nucleoside analogs, and DNA intercalating compounds, have been used against pancreatic cancer, alone or in combination, with little improvement in the survival statistics. The current article reviews the evolution of chemotherapy for pancreatic cancer, and discusses some novel therapeutic options that are emerging in recent times, with special emphasis on Minnelide, a novel HSP70 inhibitor, which is currently in clinical trials. Approaches towards developing therapies for pancreatic cancer have evolved tremendously over the past decade. Research has shown that apart from the inherent drug resistance, drug delivery to pancreatic cancer has also posed a major challenge. The extensive desmoplastic stroma of pancreatic cancer is believed to create inordinately high interstitial fluid pressures leading to vascular collapse and substantial barrier to perfusion of chemotherapeutics, thus creating an additional layer of protection for pancreatic cancer. Recent research thus is focused not only on understanding the biology and developing strategies to target cancer cells, but also is targeted towards the depletion of stroma in order to ensure better delivery of chemotherapeutic compounds to the tumor. The current article describes the novel therapies that are constantly being evaluated to address and overcome the challenges that make pancreatic cancer a difficult disease to treat.

Deciphering the underlying genetic basis behind pancreatic cancer (PC) and its associated multimorbidities will enhance our knowledge toward PC control. The study investigated the common genetic background of PC and different morbidities through a computational approach and further evaluated the less explored association between PC and autoimmune diseases (AIDs) through an epidemiological analysis. Gene-disease associations (GDAs) of 26 morbidities of interest and PC were obtained using the DisGeNET public discovery platform. The association between AIDs and PC pointed by the computational analysis was confirmed through multivariable logistic regression models in the PanGen European case-control study population of 1,705 PC cases and 1,084 controls. Fifteen morbidities shared at least one gene with PC in the DisGeNET database. Based on common genes, several AIDs were genetically associated with PC pointing to a potential link between them. An epidemiologic analysis confirmed that having any of the nine AIDs studied was significantly associated with a reduced risk of PC (Odds Ratio (OR) = 0.74, 95% confidence interval (CI) 0.58-0.93) which decreased in subjects having ≥2 AIDs (OR = 0.39, 95%CI 0.21-0.73). In independent analyses, polymyalgia rheumatica, and rheumatoid arthritis were significantly associated with low PC risk (OR = 0.40, 95%CI 0.19-0.89, and OR = 0.73, 95%CI 0.53-1.00, respectively). Several inflammatory-related morbidities shared a common genetic component with PC based on public databases. These molecular links could shed light into the molecular mechanisms underlying PC development and simultaneously generate novel hypotheses. In our study, we report sound findings pointing to an association between AIDs and a reduced risk of PC.

Objective To evaluate the diagnostic value of the metabolic parameters for differentiating focal autoimmune pancreatitis (F-AIP) and pancreatic cancer (PC) by dual time 18F-FDG PET/CT scan. Methods Ten F-AIP patients and 20 PC patients in Changhai Hospital from May 2011 to November 2014 were enrolled in this study. All the AIP patients were histological confirmed or diagnosed by clinical follow up. The PC patients were histological confirmed and gender- and age-matched with F-AIP patients. 50% SUVmax was set as the threshold to fine-tune the boundary of interest. The extracted parameters included SUVmax, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis(TLG), target-to-background ratio (TBR) and the retention indexes(RI) of all the parameters above. The PET/CT imaging features were also observed. Results The high metabolic lesions were observed in both F-AIP patients and PC patients. There were 6 F-AIP patients whose lesion was located in pancreas head, 4 F-AIP patients whose lesion was located in pancreas body and tail. There were 12 PC patients whose lesion was located in pancreas head, 8 PC patients whose lesion was located in pancreas body and tail. In F-AIP patients, 2 cases had dilated pancreatic duct, 6 had dilated biliary duct, 8 had increased metabolism in mediastinal lymph node and 2 had abdominal lymphadenopathy, which were 8, 5, 5 and 14 cases in PC patients. The positive rate of mdeiastinal lymphadenopathy in F-AIP patients was statistically higher than that in PC patients, while the positivity rate of abdominal lymphadenopathy in AIP patients was lower than that in PC patients. The difference was statistically significant (both P<0.05). There were no statistical differences on the positivity rate of the dilated pancreatic duct, intra-and extra-hepatic bile duct between two groups. SUVmax, SUVmean and MTV in F-AIP were 5.37±0.88, 3.48±0.66, 21.79±15.60 in early stage and 6.45±1.51, 4.23±1.10, 19.36±14.63 in delayed stage, and those in PC were 8.31±3.08, 5.41±1.95, 9.26±8.35 in early stage, and 9.75±3.86, 6.36±2.56, 9.09±10.71 in delayed stage. SUVmax and SUVmean in F-AIP were lower than those in PC, whereas MTV were larger in F-AIP than that in PC. ROC curves for SUVmax, SUVmean and MTV were made. The AUC of SUVmean was the highest at 0.85, the cut-off value was 4.45, the corresponding sensitivity was 65% and the specificity was 90%. TLG, TBR and RI of all the parameters were not statistically different in F-AIP and PC. Conclusions The 18F-FDG PET/CT metabolic parameters, such as SUVmax, SUVmean, MTV, could be of special diagnostic significance in discriminating F-AIP from PC. Key words: Autoimmune disease; Pancreatitis; Pancreatic neoplasms; Tomography, emission-computed; Tomography, X-ray computed; Deoxyglucose; Diagnosis, differential

The fully convolutional networks (FCNs) have been widely applied in numerous medical image segmentation tasks. However, tissue regions usually have large variations of shape and scale, so the ability of neural networks to learn multi-scale features is important to the segmentation performance. In this paper, we improve the network for multi-scale feature fusion, in the medical image segmentation by introducing two feature fusion modules: i) global attention multi-scale feature fusion module (GMF); ii) local dense multi-scale feature fusion module (LMF). GMF aims to use global context information to guide the recalibration of low-level features from both spatial and channel aspects, so as to enhance the utilization of effective multi-scale features and suppress the noise of low-level features. LMF adopts bottom-up top-down structure to capture context information, to generate semantic features, and to fuse feature information at different scales. LMF can integrate local dense multi-scale context features layer by layer in the network, thus improving the ability of network to encode interdependent relationships among boundary pixels. Based on the above two modules, we propose a novel medical image segmentation framework (GLF-Net). We evaluated the proposed network and modules on challenging brain tumor segmentation and pancreas segmentation datasets, and very competitive performance has been achieved.

Recent results of a nationwide study of a new combination of drugs to treat pancreatic cancer show that the rare but deadly disease still has the upper hand.The study was conducted by a national consortium of cancer researchers called the Cancer and Leukemia Group B (CALGB). The CALGB Gastrointestinal Cancer Committee, which designed the study, is headed by Dr. Richard M. Goldberg, professor of medicine, chief of hematology-oncology, and associate director for clinical research at the UNC Lineberger Comprehensive Cancer Center.The study, funded by the National Cancer Institute, was presented January 21 at the American Society of Clinical Oncology’s Gastrointestinal Cancer Symposium in Orlando, Florida. The nine co-authors were from Memorial Sloan-Kettering Cancer Center, Duke University Medical Center, the University of Chicago and Northwestern University Medical Center. Principal investigator is Dr. HedyKindler, associate professor of medicine at the University of Chicago.About 30,000 new cases of pancreatic cancer are diagnosed each year and the overwhelming majority of those new cases will survive only a few months. The disease usually is diagnosed late and, in most cases, doesn’t respond to chemotherapy. While great strides have been made in diagnosing and treating most cancers, “pancreatic cancer is particularly resistant to current therapies,” said Goldberg, “but a recent report offered a glimmer of hope.”That small trial from the University of Chicago used gemcitabine (a chemotherapeutic agent) plus bevacizumab (trade name Avastin®) to treat pancreatic cancer patients. Promising results showed an increase in survival time from the typical 4-6 months to nearly 9 months. Avastin®, an angiogenesis inhibitor, has been shown to be successful in treating colon, lung and other cancers. Angiogenesis inhibitors limit the growth of new blood vessels and make those blood vessels more easy for drugs to pass through allowing chemotherapy to penetrate tumors more effectively.The hopeful results of the earlier trial led the CALGB to conduct a larger national trial. In just under 2 years, over 600 patients were enrolled making this “one of the largest trials on pancreatic cancer ever undertaken,” according to Goldberg. “Getting this number of patients enrolled in such a short time shows the intense interest in finding better treatment options for patients with cancer of the pancreas,” he said.The patients were men and women, most in their middle 60’s, whose disease had already spread beyond the pancreas. Half the patients continued standard therapy (gemcitabine plus a placebo) while the other half took the combination of drugs used in the Chicago trial.Near the conclusion of the project, it became apparent that the new treatment regimen was no better than gemcitabine alone as no difference was observed in survival rates between the 2 groups. At that time, the randomization scheme was revealed, allowing the remaining patients to be treated according to their physician’s discretion.“The primary question was whether an angiogenesis inhibitor combined with a chemotherapeutic agent would improve survival in patients with pancreatic cancer. The answer was clearly no,” Goldberg said.Other aspects of the project included studies still underway to help unravel the molecular biology of the disease, assess the quality of life of enrolled patients, and economic issues.“The potential for side effects and tumor shrinkage are influenced by the patient’s unique genetics that will ultimately affect prognosis. Tumor shrinkage will also affect quality of life and economic aspects of the disease,” Goldberg explained. “Regrettably, this combination of drugs that first appeared to be so hopeful, failed to affect this tumor like it does other tumors.” Noting that treatment effectiveness found in small trials is not always confirmed in larger studies of patients, Goldberg said this larger trial had a more diverse patient population than the Chicago study. “The patient mix was more consistent with the typical patient mix across the country and thisprobably was a factor in our results differing from those seen in the group of patients from Chicago.” Still, the UNC researcher said that results from a negative study give valuable insights into the nature of pancreatic cancer, thus improving our understanding for improved patient care and quality of life. “Results like these demonstrate that research needs to be disease-specific. Investigations will continue to attack this disease,” Goldberg said.The CALGB co-authors included Drs. Hedy Kindler and Richard Schilsky from the University of Chicago, Dr. Deborah Schrag from Memorial Sloan Kettering Cancer Center, Dr. Mary Mulcahy from Northwestern University Medical Center, Dr. Herbert Hurwitz from Duke University Medical Center, Dr. Howard McLeod from the University of North Carolina at Chapel Hill, and CALGB statisticians Drs. Donna Niedzwiecki, Donna Hollis, and Ebele Oraefo from Duke University Medical Center.For more information, please contact: Leslie Lang; Tel.: 919.843.9687 or Dianne Shaw; 919.966.7834.

Pancreatic cancer is an aggressive disease and is usually advanced at the time of diagnosis. Median life of pancreatic cancer patients post-diagnosis is &amp;lt;6 months and an overall 5-year survival rate is 3-5%. In 2013, ∼44,980 new cases of pancreatic cancer are expected in United States with ∼38,460 deaths. In most cases, disease relapse occurs due to development of resistance towards gemcitabine (the frontline therapy for pancreatic cancer) and is the main cause for dismal rate of survival in pancreatic cancer patients. Therefore, overcoming gemcitabine resistance remains a major challenge towards effectively treating this deadly malignancy. Several molecular mechanisms are known to contribute to gemcitabine-resistance in pancreatic cancer; however, metabolism and bioenergetic alterations in gemcitabine-resistant pancreatic cancer cells have not yet been characterized. Here, we analyzed and compared the metabolic and bioenergetic functions between gemcitabine-resistance and sensitive pancreatic cancer cells along with underlying molecular mechanisms. Furthermore, we also assessed the anticancer efficacy of a natural agent bitter melon (Momordica charantia, Family: Cucurbitaceae) juice (BMJ) against gemcitabine-resistant pancreatic cancer cells. Results showed that gemcitabine-resistant human pancreatic adenocarcinoma AsPC-1 and MiaPaCa-2 cells have distinct morphological features including spindle-shaped morphology and a decrease in E-cadherin expression. Interestingly, gemcitabine-resistant cells showed higher ATP production along with an increase in oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) confirming an increase in both cellular oxidative phosphorylation and glycolysis. Molecular studies showed a higher expression of glucose transporters GLUT1 and GLUT4 suggesting an increase in glucose uptake by gemcitabine-resistant cells. Importantly, gemcitabine-resistant cells exhibited a significant increase in Akt and ERK1/2 phosphorylation, and Akt and/or ERK1/2 inhibition by specific chemical inhibitors significantly decreased the gemcitabine-resistant cells viability, suggesting the critical role of these molecules in the survival and drug resistance of these cells. Recently, BMJ has shown strong efficacy in a panel of gemcitabine-sensitive cells in culture and nude mice, which we expanded here and found that BMJ was also effective in strongly decreasing both Akt and ERK1/2 phosphorylation and viability of gemcitabine-resistant pancreatic cancer cells. Overall, we have identified novel mechanisms of gemcitabine-resistance in pancreatic cancer cells that are targeted by BMJ. Considering a short survival-rate in pancreatic cancer patient, our findings could have high translational potential in controlling this deadly malignancy. Citation Format: Ranganatha Somasagara, Gagan Deep, Sangeeta Shrotriya, Manisha Patel, Chapla Agarwal, Rajesh Agarwal. Bitter melon juice targets molecular mechanisms underlying gemcitabine resistance in pancreatic cancer cells. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 698A. doi:10.1158/1538-7445.AM2014-698A

Background: We examined the association between opium consumption and pancreatic cancer incidence in a large-scale prospective cohort of the general population in northeastern Iran.Methods: A total of 50,045 adults were systematically followed up (median of 7.4 years), and incident cases of pancreatic cancer were identified. Self-reported data on opium consumption was collected at baseline. Cumulative use (-year) was defined as number of nokhods (a local unit, approximately 0.2 g) of opium consumed per day multiplied by number of years consuming. Adjusted HRs and 95% confidence intervals (CIs) for the association between opium consumption and pancreatic cancer were calculated using Cox proportional hazards regression models.Results: Overall, 54 confirmed cases of pancreatic cancer were identified. Opium use of more than 81 nokhod-years (high cumulative use), compared with never use, was strongly associated with pancreatic cancer even after adjustments for multiple potential confounding factors [HR = 3.01; 95% CI, 1.25-7.26]. High cumulative consumption of opium was significantly associated with risk of pancreatic cancer after adjusting for cumulative dose of cigarette smoking [HR = 3.56; 95% CI, 1.49-8.50]. In a sensitivity analysis, we excluded participants (including 2 pancreatic cancer cases) who were recruited within the first 5 years of starting opium consumption; high cumulative use of opium was still associated with pancreatic cancer risk [HR = 2.75; 95% CI, 1.14-6.64].Conclusions: Our results showed a positive association between opium consumption and pancreatic cancer.Impact: This is the first prospective large-scale study to show the association of opium consumption with pancreatic cancer as a risk factor. Cancer Epidemiol Biomarkers Prev; 27(3); 268-73. ©2017 AACR.

Gao and colleague's recent study explored the workforce implications in Victoria, Australia, if screening for pancreatic cancer (PC) were adopted in the primary care setting.1 The screening programme explored in the article would involve analysis of clinical risk factors to identify individuals at higher risk of PC, excluding genetic predispositions already covered by surveillance programs, who would then undergo cancer screening. The analysis model assumed that 20–70% of all new PC cases would be diagnosed at an earlier stage due to screening, and estimated the workforce implications that this would have. The authors suggested that there would be an inadequate workforce to manage the increase in earlier stage cancer, who are more likely to receive active cancer treatment. A greater impact on regional and rural populations was predicted. This is a relevant topic and important for future service planning, particularly given the known challenges in access to specialized healthcare rurally, however, we have reservations about the analysis that currently limits its applicability. First, the number of pancreatic cancer cases identified with screening would be significantly fewer than modelled. UK analyses have demonstrated that 10% of the population would be eligible for PC screening (based on pre-screening risk assessment), contributing 35% of all PC diagnoses.2 The uptake rate of PC screening in Victoria would likely not exceed 50% of the eligible population, based on patterns from the Australian bowel and breast cancer screening programs. Therefore, if population-based asymptomatic PC screening was rolled out, a maximum of 17% of pancreatic cancers would be screen-detected. This is less than the lowest estimated stage shift of 20–70% proposed in the model. Second, not all patients with screen-detected early-stage cancer would be fit for surgery or other cancer specific treatments. PC is a disease largely of the elderly, thus even with earlier diagnosis, many patients would still not be fit for surgery or chemotherapy. Furthermore, the model did not account for lead time bias. Third, the time for progression from early to advanced disease is much less than 5 years suggested by the study. Based on imaging, tumour markers, and age-adjusted analyses, studies have estimated 1–2 years between detectable early cancer and advanced cancer.3 Even if there were a diagnostic liquid biopsy available, without an identifiable mass on imaging or endoscopic ultrasound, there is no precedent to offer treatment. Fourth, pancreatic surgery is performed by specialized pancreatic surgeons at centres with appropriate perioperative support. The suggestion that pancreatic surgery will be performed in small to medium rural towns by general surgeons is misleading. Finally, the timeline for implementation of population-based screening for PC in Victoria is unrealistic. While screening for PC based on genetics is currently recommended, screening of asymptomatic individuals without a genetic predisposition or significant family history is not yet supported by any professional body. Of local relevance, a trial among 15 Victorian primary care physicians found that none of the participants would be comfortable using the QCancer risk prediction tool in clinical practice.4 The authorship includes experts in the fields of health economics who have substantial knowledge about workforce planning, but the inclusion of a clinician with expertise in pancreatic cancer would provide a valuable perspective regarding how PC care is provided. We commend the authors for this relevant analysis that explores the possible implications of a PC screening innovation, however, changes to the model will provide a more realistic assessment for future healthcare planning in Victoria. Elizabeth Lockie is the recipient of the University of Melbourne Melville Hughes Scholarship. Elizabeth B. Lockie: Conceptualization; writing – original draft. Anita Skandarajah: Writing – review and editing. John Zalcberg: Writing – review and editing. Benjamin P. Loveday: Conceptualization; writing – review and editing.