Is targeted gene testing cost-effective in patients with metastatic gastrointestinal stromal tumor?KIT exon variation status. The model found that targeted gene testing was cost-effective, with an incremental cost-effectiveness ratio of $92 100, compared with empirical treatment with imatinib.This economic evaluation developed a Markov model to examine the cost-effectiveness of targeted gene testing with tailored imatinib dosing for patients with gastrointestinal stromal tumor based on These findings support the cost-effectiveness of widespread adoption of genetic testing for patients newly diagnosed with metastatic gastrointestinal stromal tumor. This economic evaluation examines the cost-effectiveness of targeted gene testing for tailored first-line treatment among patients with gastrointestinal stromal tumors (GIST). KIT variations. Imatinib targeting of KIT marked a new era in GIST treatment and ushered in precision oncological treatment for all solid malignant neoplasms. However, studies on the molecular biological traits of GIST have found that tumors respond differentially to imatinib dosage based on the KIT exon with variation. Despite this knowledge, few patients undergo genetic testing at diagnosis, and empirical imatinib therapy remains routine. Barriers to genetic profiling include concerns about the cost and utility of testing.Gastrointestinal stromal tumor (GIST) is frequently driven by oncogenic To determine whether targeted gene testing (TGT) is a cost-effective diagnostic for patients with metastatic GIST from the US payer perspective.This economic evaluation developed a Markov model to compare the cost-effectiveness of TGT and tailored first-line therapy compared with empirical imatinib therapy among patients with a new diagnosis of metastatic GIST. The main health outcome, quality-adjusted life years (QALYs), and costs were obtained from the literature, and transitional probabilities were modeled from disease progression and survival estimates from randomized clinical trials of patients with metastatic GIST. Data analyses were conducted October 2019 to January 2020.TGT and tailored first-line therapy.The primary outcome was QALYs and cost. Cost-effectiveness was defined using an incremental cost-effectiveness ratio, with an incremental cost-effectiveness ratio less than $100 000/QALY considered cost-effective. One-way and probabilistic sensitivity analyses were conducted to assess model stability.Therapy directed by TGT was associated with an increase of 0.10 QALYs at a cost of $9513 compared with the empirical imatinib approach, leading to an incremental cost-effectiveness ratio of $92 100. These findings were sensitive to the costs of TGT, drugs, and health utility model inputs. Therapy directed by TGT remained cost-effective for genetic testing costs up to $3730. Probabilistic sensitivity analysis found that TGT-directed therapy was considered cost-effective 70% of the time.KIT variations to imatinib dosing is a cost-effective approach compared with empirical imatinib.These findings suggest that using genetic testing to match treatment of  KIT (OMIM 164920) variations. In the late 1990s, the use of targeted therapy against KIT variations with imatinib marked a new era in GIST treatment and ushered in precision oncological treatment for all solid malignant tumors.1 Although treatment of advanced GIST with imatinib achieved sustained objective responses, primary and acquired secondary resistance to imatinib remains a clinical challenge.2 In the setting of imatinib failure, newer generations of tyrosine kinase inhibitors have shown efficacy as second-line  and third-line  agents.4Gastrointestinal stromal tumor (GIST) is the most common sarcoma and is frequently driven by oncogenic KIT variations, 67% have variations implicating exon 11, 10% to 15% have alterations in exon 9, while exons 17, 18, and 13 account for 1% of patients each.2 Additionally, other genetic drivers, including PDGFRA (OMIM 173490), RAS pathway activation , succinate dehydrogenase complex deficiency, ETV6/NTRK3 (OMIM 191316) fusions, and FGFR1 (OMIM 136350) fusions have also been implicated.10 These subgroups differ not only in terms of genetics but also in terms of clinical features, route of metastasis, patient outcomes, and imatinib responsiveness.Studies on the molecular characteristics of GIST have shown that the disease is genetically diverse. Of approximately 70% of patients with 11 was a pooled meta-analysis of 2 large, randomized clinical trials comparing the effectiveness of low-dose (400 mg) vs high-dose (800 mg) imatinib. The MetaGIST trial11 used variation analysis performed in both trials and identified KIT exon 9 variation as a factor associated with clinical response to high-dose imatinib and with superior recurrence free survival and equivalent overall survival (OS). The National Comprehensive Cancer Network guidelines subsequently recommended testing to identify patients with this variation to ensure initiation of the appropriate starting dose.12With metastatic GIST, the underlying genetic driver influences the probability of treatment success. The MetaGIST trial14 Barriers to genetic profiling may include concerns about the cost and utility of testing. To investigate this, we evaluated the cost-effectiveness of variation profiling for patients with metastatic GIST.Despite this recommendation, only 15% to 33% of patients undergo genetic testing at diagnosis, and 400 mg imatinib is a mainstay of first-line therapy for all GIST.15 Analysis of deidentified published data was granted institutional review board and informed consent exemption by the institutional review board of the University of California, San Diego. We adhered to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) reporting guideline for reporting economic evaluations. Data analyses were conducted October 2019 to January 2020.The design and reporting of this cost-effectiveness analysis follow standard guidelines published elsewhere.16 We modeled outcomes for 3 genomic subpopulations: KIT exon 11, KIT exon 9, and all other variations, based on 2 previous randomized clinical trials.18 The model simulated treatment outcomes, including progression and death, associated with treatment using first-, second-, and third-line therapy for each genomic subpopulation, following the treatment algorithm defined by the National Comprehensive Cancer Network guideline recommended therapy for metastatic GIST.12 Patients within the empirical imatinib group started with low-dose imatinib  as first-line therapy. Disease progression prompted dose escalation to high-dose imatinib . The second occurrence of disease progression was treated with sunitinib. The third occurrence of disease progression was considered treatment failure and patients received best supportive care. In the TGT-directed approach, patients with KIT exon 9 variations started on high-dose imatinib as first-line therapy followed by sunitinib and best supportive care in the setting of disease progressions. Patients with KIT exon 11 and other variations followed the same treatment algorithm as those in the empirical imatinib group (We developed a Markov model to compare the cost-effectiveness of targeted gene testing (TGT) and variation-directed first-line therapy compared with empirical imatinib therapy for patients with metastatic GIST from the US payer perspective.ib group . Treatme18 Disease progression and OS were extracted from Kaplan-Meier curves from each trial using WebPlotDigitizer data extraction tool version 4.2,19 and transition probabilities for progression and risk of death were modeled for each genomic subpopulation  and drug treatment combination . Data were extracted from 2 studies: imatinib data was obtained from the secondary analysis of a 2006 phase III randomized clinical trial by Debiec-Rychter et al17 while sunitinib data were obtained from a 2008 phase I/II randomized clinical trial by Heinrich et al.18 Model transition probabilities were validated by comparison with source clinical trial data for progression free survival  were included in the model and were associated with healthy utility decrease of 0.12 for each disease progression.25 There was no QALY deduction associated with toxic effects from imatinib or sunitinib therapy based on clinical trial data that indicated equivalent quality of life before and after treatment with either medication.30Effectiveness was measured in quality-adjusted life years (QALYs), which estimates a patient’s health utility over time. Health utility measures quality of life on a scale that ranges from 0 (death) to 1 . Health utilities for this study were defined previously using prospective EQ-5D surveys25 . The hea31 with a standard 7% reduction. The base case cost of imatinib was a weighted mean of the cost of brand-name and generic imatinib based on the current estimated market share of 50% for generic and 50% for brand-name.26 The cost of best supportive care was estimated for patients with treatment refractory metastatic GIST.23 The cost of disease progression was based on estimated health care utilization cost of patients with recurrent GIST.29 The cost of disease progression was applied in the first 3 years of the model. Costs of adverse events were obtained from clinical trials.28 All costs were adjusted for inflation to 2019 US dollars using the consumer price index.Costs were estimated using a US payer perspective . The cos32 and varying this number from 10% to 40% in a sensitivity analysis did not impact results of the probabilistic sensitivity analysis , which is the ratio of the difference in costs between the 2 treatments divided by the difference in QALYs. For this study, we used a willingness-to-pay threshold of $100 000 per QALY, with treatments less than $100 000 per QALY considered cost-effective. We used 1-way sensitivity analyses to identify individual variables that influenced the cost-effectiveness results. A probabilistic sensitivity analysis was also conducted to explore model parameter uncertainty in all transition probabilities, costs, and health utilities using a Monte Carlo simulation with 100 000 iterations. Cost estimates were modeled with γ distributions and transition probabilities, and health utilities were modeled with β distributions. We obtained SDs for the probability of toxic effects, progression, and death from the literature. The SDs of cost and health utilities were assumed to be 20% of the mean,In the base case analysis, TGT-directed therapy was associated with an increase in cost of $9513, from $469 106 with the empirical imatinib approach to $478 619 with TGT-directed therapy. The total accrued QALYs increase by 0.10 with TGT-directed therapy, from 4.88 with empirical imatinib to 4.98 with TGT-directed therapy, and TGT-directed therapy was associated with an ICER of $92 100 per QALY compared with the empirical imatinib approach, which was considered cost-effective at a $100 000 per QALY willingness-to-pay threshold.KIT exon 9 variations and found that TGT-directed therapy remained cost-effective if the prevalence was greater than 11.7%, which is 3.3% less than the base case estimate  is often driven by oncogenic variations in 33 compared the use of a single BRAF V600 variation test to a panel of 34 genes in the diagnostic workup for metastatic melanoma and found that the panel was less expensive and yielded more QALYs than the single-gene test. In a 2017 study on lung cancer,34 multiplex targeted sequencing for fourth-line agent selection was cost-ineffective, with an ICER of $485 199 per QALY. Similarly, in a 2016 study on platinum-resistant ovarian cancer,35 compared with chemotherapy, TGT and targeted therapy was not cost-effective, with an ICER of $479 303 per QALY. In the latter 2 studies, high ICERs were driven by the significant costs of targeted therapy while both models were relatively insensitive to the cost of TGT. This is also true in our study, in which the cost of TGT represents a small fraction of the overall cost of treatment. However, the clinical scenario tested in this model differs from the these studies because it did not entail a recommended treatment that is an expensive novel agent. Additionally, it is interesting to note that clinical trials and meta-analysis, which were used in this model, show a difference in progression-free survival but not OS for patients with KIT exon 9 variations treated with high-dose imatinib compared with those treated with low-dose imatinib. This indicates the QALY gain associated with the TGT-directed therapy approach is entirely derived from reduced incidence of tumor progression. The importance of progression-free survival has been shown across a variety of cancer types and is associated with a clinically relevant deterioration in quality of life.36 For these reasons, the cost-effectiveness of withholding futile therapy for patients with KIT exon 9 variation is not surprising.There are few studies on the cost-effectiveness of gene testing and tailored therapy. One study by Li et alKIT exon 9 alterations who were treated with more expensive therapy (high-dose imatinib and sunitinib) compared with the least expensive option . This is also the primary reason why improved survival in sensitivity analyses actually rendered the TGT-directed approach less cost-effective. The cost of imatinib is peculiar—costs of the brand-name drug consistently rose in the years leading up to and after the release of generic imatinib.37 The reasons for this paradoxical trend are not clear but may in part be owing to delays in the availability of a low cost generic imatinib.37 However, recently the brand-name drug has consistently lost market share to the generic option.38 Our results demonstrate that TGT-directed therapy could become progressively more cost-effective as generic imatinib continues to comprise a larger market share.We found the cost of the TGT-directed approach to be $9513 higher than the empirical imatinib approach. This increased cost reflects a subset of patients with Clinically available TGT diagnostic panels vary by read breadth and depth. The least costly of these usually involve focused gene panels, while whole-exome diagnostics are generally more expensive. Retail cost for these diagnostic tests range from several hundred dollars to more than $10 000. This analysis found that a TGT cost of $3730 or less would be considered cost-effective, although many of these more expensive tests would not be cost-effective when considering their list price. However, the Centers for Medicare & Medicaid Services provides reimbursement for TGT panels that profile approximately 300 or more cancer-related genes. Several commonly used clinical panels fall within this coverage and would be cost-effective in our model.40 These studies emphasize that early implementation of TGT is critical to achieving the cost-effectiveness benefit. This finding complements the clinical situation of treating GIST, since patients who initially do not respond to empirical imatinib may undergo TGT before initiating second-line treatment. Our model would suggest that the addition of TGT after the failure of first-line therapy is dramatically less cost-effective than prior to first-line therapy.Several studies have examined the cost-effectiveness of whole-exome and whole-genome assays on diagnostic yield for neurological or neurodevelopmental disorders.41 estimated cost savings associated with withholding empirical imatinib from patients with a PDGFRA D842V variation, which is known to have primary imatinib resistance. Schöffski et al41 found that variation profiling and selectively withholding therapy in this genomic subpopulation was cost-saving. In our study, we focused on the value of TGT results to identify patients who harbor a KIT exon 9 variation, which can inform dose selection for starting imatinib therapy. However, TGT diagnostics yield a variety of actionable information. Well-implemented TGT data for patients with GIST can prevent trials of empirical imatinib therapy in patients who have genetic alterations known to be intrinsically resistant to imatinib. For example, patients with PDGFRA D842V do not respond to imatinib, but preclinical and early clinical trial data have shown excellent results with new targeted therapies.42 Patients with KIT exon 18 variations or succinate dehydrogenase complex deficiency are also known not to respond to imatinib and can be allocated to alternative TKI therapies, repeated surgical resection or clinical trials.17 In this study, we chose to focus on the only 3 genomic subpopulations with robust clinical trial data  to optimize model simulation. As a consequence, management differences among the all other variations group were not addressed. The value of TGT clearly extends beyond identification of KIT exon variations; however, lack of availability of large clinical trials precludes cost-effectiveness modeling of these genomic subpopulations.In a 2016 study on variation analysis in GIST, Schöffski et alKIT exon 9 variations because of the availability of robust clinical trial data that could be used to extrapolate valid transition probabilities for our model. Ideally, additional actionable variations and cognate targeted therapies could be included. However, this is contingent on conducting the appropriate clinical trials to gather the necessary data. Second, many patients who receive imatinib undergo dose reduction after experiencing grade II to III adverse effects. Although dose reduction was not explicitly included in the model, the transition probabilities for progression and OS are based on a patient cohort that underwent dose reductions when necessary. Additionally, it is likely that our model overestimates the cost of imatinib because dose reductions would correspond to lower drug costs. Third, we found that our model was sensitive to the transition probabilities that were modeled from clinical trial data. However, it is important to note that clinical trials of low- vs high-dose imatinib permitted crossover for patients in the low-dose imatinib group. This suggests that the estimated rate of survival may be higher than the actual rate, particularly in the patients with KIT exon 9 variations. Therefore, we anticipate that our transition probabilities are conservative estimates of the differences between treatments. Fourth, cost of imatinib was estimated based on reports of market share data in the literature.26 Although we do not have actual data on the proportion of generic imatinib used, we anticipate that this proportion will increase over time, which would support the conclusions of our model. Fifth, patients in our model were not given a chance to discontinue treatment. This decision was made to develop a theoretical data set to compare TGT-directed therapy vs empirical imatinib. Additionally, we anticipate that rates of treatment discontinuation would be similar in each arm of our model and is unlikely to have a significant impact on the ICER. Sixth, clinical trial patient populations often differ from the general patient populations owing to strict inclusion criteria, which may limit the applicability of our study conclusions. However, the clinical trials analyzed in this model had permissive inclusion criteria, including adult age, confirmed pathologic diagnosis, and only excluded patients with severe comorbidities, which is a reasonable representation of the true patient population. Furthermore, comparisons of clinical trials and population-based observational data show that clinical trial outcomes are generally reliable despite restrictive inclusion criteria.43 Seventh, we used Surveillance, Epidemiology, and End Results data, which lack variation status information, to estimate long-term survival beyond the follow-up of the clinical trials.There are several limitations to this study. First, TGT-guided therapy provides a wide array of actionable information that can lead to patients receiving first-line agents other than low-dose imatinib, which could influence cost-effectiveness of TGT. However, the focus of this study was narrowed to imatinib dose selection for patients with In this economic evaluation, we present a Markov model comparing TGT with tailored dose selection of imatinib to empirical imatinib therapy. The model suggests that TGT-directed therapy is a cost-effective intervention compared to empirical imatinib. These findings support widespread adoption of standard genetic testing for newly diagnosed patients with metastatic GIST.


COVID-19 pneumonia is a newly recognized lung infection. Initially, CT imaging was demonstrated to be one of the most sensitive tests for the detection of infection. Currently, with broader availability of polymerase chain reaction for disease diagnosis, CT is mainly used for the identification of complications and other defined clinical indications in hospitalized patients. Nonetheless, radiologists are interpreting lung imaging in unsuspected patients as well as in suspected patients with imaging obtained to rule out other relevant clinical indications. The knowledge of pathological findings is also crucial for imagers to better interpret various imaging findings. Identification of the imaging findings that are commonly seen with the disease is important to diagnose and suggest confirmatory testing in unsuspected cases. Proper precautionary measures will be important in such unsuspected patients to prevent further spread. In addition to understanding the imaging findings for the diagnosis of the disease, it is important to understand the growing set of tools provided by artificial intelligence. The goal of this review is to highlight common imaging findings using illustrative examples, describe the evolution of disease over time, discuss differences in imaging appearance of adult and pediatric patients and review the available literature on quantitative CT for COVID-19. We briefly address the known pathological findings of the COVID-19 lung disease that may help better understand the imaging appearance, and we provide a demonstration of novel display methodologies and artificial intelligence applications serving to support clinical observations. Lower respiratory infection is one of the common manifestations of the disease, and lung pathophysiology is responsible for the majority of deaths. Clinically, the patients frequently present with ‘flu-like illness’. However, dyspnea and shortness of breath are also present in a majority of cases, something not as common in the common flu. Initial studies on a small number of hospitalized patients showed that pneumonia on CT is seen in all cases, with clinical progression to acute respiratory distress syndrome (ARDS) in 17–29% cases.2,3 In one of the largest studies to date, the Chinese Center for Disease Control and Prevention reviewed approximately 44,500 confirmed COVID-19 cases and estimated that nearly 81% of patients present with mild infection (no or mild pneumonia), 14% with severe disease , 5% develop multiorgan failure; and with an overall 2.3% mortality.4COVID-19 global outbreak continues to evolve and is rapidly spreading. The disease started in China in December 2019 when patients with unknown viral pneumonia were diagnosed. The pathogen was characterized as a novel betacoronavirus, which was initially named as 2019 novel coronavirus (2019-nCoV), later renamed as the SARS-CoV-2 virus. After the initial outbreak in China, the disease spread all over the world with some countries affected more than others. As of June 23, 2020, the World Health Organization (WHO) reports that nearly 9 million individuals have been affected by the disease worldwide, and the disease has caused nearly 470,000 deaths.vs reverse-transcription polymerase chain reaction (RT-PCR) testing as the reference standard. CT had a sensitivity of 97%, with a specificity of 25%.5 Another study comparing the United States and Chinese radiologists in differentiating COVID-19 and other viral pneumonia on chest CT showed that radiologists had moderate sensitivity but high specificity in distinguishing between the diseases. Findings that were most helpful to distinguish COVID-19 from other viral pneumonia were ground-glass opacity (GGO), vascular thickening, and peripheral distributions of the lesions .6 Imaging findings are known to evolve during the disease. The most frequently seen finding of GGO usually develops between day 0 to day 4 and peaks at 6–13 days. Later in the course of the illness, consolidation or reverse halo signs are seen.7–9Imaging is frequently abnormal in patients with COVID-19. A recent study was performed consisting of more than 1000 patients comparing the diagnostic performance of visual CT assessment (based on the consensus of two radiologists) 10–12 They recommended that CT should be reserved for hospitalized patients when it is needed for clinical management, for identification of complications in patients diagnosed with COVID-19 or if PCR is unavailable. Due to non-specific symptoms such as shortness of breath and dyspnea, which overlaps with multiple other lung or cardiac diseases for which imaging is obtained, radiologists are highly likely to perform and interpret imaging in an increasing number of patients with suspected or diagnosed COVID-19. Additionally, there are reports of associations between COVID-19 infection and pulmonary thromboembolism.13,14 Expert consensus statements have proposed a standardized CT-based reporting template with suggestions for the COVID-19 disease.15,16 When clinically suspected, the CT imaging patterns have been proposed for the COVID-19 infection: typical  pattern, probable COVID-19 pattern, indeterminate pattern, and a typical imaging pattern.15,16 The goal of this review is to summarize common imaging findings using illustrative examples, discuss the evolution of disease over time, review the differences in imaging appearance of adult and pediatric patients and highlight the advanced application of lung imaging beyond disease diagnosis. We also briefly address the known pathological findings of the COVID-19 lung disease that may help better understand the imaging appearances with examples borrowed from applications of artificial intelligence (AI) and novel image representations.Due to a relatively low prevalence of the disease in March 2020, non-specific imaging findings, and a concern of disease spread, major radiological societies  suggested that CT should not be used for screening of COVID-19.17 The progression of the disease to frank lung injury and acute respiratory distress syndrome (ARDS) depends on factors that are not clearly understood but include a component of cytotoxicity and lymphopenia,18 and subsequent inflammatory response.17,19 Increased expression of inflammatory markers like d-Dimer, ferritin and IL-6 have been linked to poor prognosis.20,21The literature on the pathology of the COVID-19 infection is evolving. The SARS-CoV-2 interacts with host cells by binding its envelope protein  to angiotensin-converting enzyme 2 (ACE-2). ACE-2 is abundantly expressed on the nasal, airway and lung cells, intestinal epithelial cells and cardiovascular cells. In the early stages, the virus infects the nasal cells and mounts a minor inflammatory response. Later, the virus propagates to the conducting respiratory airways at which stage the host immune response is more robust, and the disease clinically manifests.22 One of these cases was an asymptomatic 84-year-old female who underwent right middle lobectomy for a lung nodule (proven as adenocarcinoma) that had GGO of unknown significance on the pre-operative imaging. The patient underwent surgery, became symptomatic, and was tested positive for the SARS-CoV-2 virus. Another case was a 73-year-old male who underwent right lower lobectomy for a lung nodule (proven to be adenocarcinoma). His CT on post-op day 2 showed peripheral GGO, and he was tested positive for COVID-19 on day 9. In these cases, early pathological findings of COVID-19 showed focal areas of alveolar damage with alveolar edema and proteinaceous exudates. Prominent inspissated spherical secretions were seen. There was vascular congestion with focal areas of mononuclear (non-neutrophilic) alveolar inflammation and multinucleated giant cells within the airspaces. Along with these findings, there were noticeable ongoing reparative changes, including severe pneumocyte hyperplasia, a proliferation of interstitial fibroblasts, and interstitial thickening. They also suspected viral inclusions in some cells.22The only description of early pathological features of the disease (to date) is reported from Wuhan in two cases in which infection was noted incidentally on lung tumor surgery specimens.23 The autopsy was on day 14 of a severe, rapidly worsening respiratory disease. The findings showed diffuse alveolar damage with cellular fibromyxoid exudates and hyaline membrane formation, suggesting ARDS. Lymphocytic predominant interstitial and airspace inflammation was seen. Alongside, there were abundant multinucleated syncytial cells and atypical enlarged pneumocytes in the intra-alveolar spaces, suggesting viral cytopathic-like changes. However, no viral inclusions were seen. Recently, a two patient post-mortem series from United States and post-mortem biopsy series were also published, which also showed diffuse alveolar damage and mononuclear airspace and airway inflammation.24,25 In the post-mortem case series,25 authors also showed that the SARS-CoV-2 viral testing could be performed from post-mortem swabs for confirmation if testing could not be performed before death. The pathological findings in the early and late disease, along with an illustration of lung airspace, interstitium, and alveolar–capillary interface, are summarized in The late manifestation of severe COVID-19 infection was first described in a 50-year-old male with ARDS.26 Chest CT are frequently abnormal in symptomatic individuals. In one of the largest study comparing the diagnostic ability of CT among 1014 patients, the chest CT was abnormal in 88% of COVID-19 patients at presentation with a sensitivity of 97% when compared with RT-PCR.5 Multilobar lung involvement is typical and right lower lobe is the most commonly affected lobe.7,27 As the pathogen is commonly inhaled with the respiratory droplets; the disease is usually in bronchocentric distribution, i.e. these patterns are typically along the distribution of the airway. In patients who eventually recover, the imaging findings demonstrate a fairly typical temporal course as described later in the review. The commonly seen imaging findings are illustrated in Imaging findings of COVID-19 can be seen both on chest radiographs (CXR) and chest CT. Ground-glass opacity (GGO) is the most frequent imaging manifestation. Due to the lower sensitivity of CXR for the detection of GGO, it may be negative in the early disease. In a recent study from Hongkong, nearly 30% of symptomatic COVID-19 patients had an initial negative CXR.28 about 60–70% of the patients demonstrated pure GGO on CT. The right lower lobe is the most commonly affected lobe.27 Bilateral GGO, predominantly in a peripheral distribution with a lower lobe predominance, is one of the typical patterns of COVID-19 infection  as well as the recovery phase (from consolidation) of the COVID-19 disease  or patients with influenza that were admitted to ICU (7.5%). Calf deep venous thrombosis was only seen in 4.7% of patients with COVID-19 as compared to 4.6% in ICU patients hospitalized with other diseases. Hence, they suggested that the etiology of PE may be pulmonary thrombosis rather than embolization. Some studies have shown that even in the absence of PE, patients treated with anticoagulation have a better prognosis due to thrombogenic state and microemboli.45 In another retrospective study, PE was noted in 30% (32/106 patients) of COVID-19 patients, and the majority (75%) of the cases were critically ill and in ICU. All of these PE cases were identifiable (as compared to COVID-19 patients without PE) by using a relatively higher d-dimer threshold of 2660 µg l−1.44 In another recent autopsy series of 12 patients with COVID-19 disease,46 microthrombi were seen extensively in pulmonary vasculature along with diffuse alveolar damage on histology. In all cases, the lung disease or pulmonary vascular disease was the cause of death. Central pulmonary thrombus was the direct cause of death in one-third of cases.46 Pulmonary vascular immunothrombosis due to macrophage activation has been postulated with COVID-19 disease which leads to multifocal microscopic and large vessel thrombosis and hemorrhage.47,48 Hence, rather than an imaging manifestation of COVID-19, higher incidence of PE should be considered as an associated complication.Studies have also shown that patients with COVID-19 have a higher incidence of pulmonary embolism (PE).These findings are rarely reported in COVID-19, and their presence as the primary pattern in the absence of GGO must necessitate the search for an alternate diagnosis.27 none demonstrated tree-in-bud nodules or cavitation. Lymphadenopathy and pleural effusions are rare and reported in 4–8% of patients with the disease and may suggest worsening of COVID-19 pneumonia or superimposed fluid overload.7 Pericardial effusion is also very rare and was seen in less than 5% of COVID-19 cases in a recent study.37Isolated lobar or segmental pneumonia without associated GGO is typically seen with bacterial pathogens and is uncommon with COVID-19 pneumonia. Similarly, centrilobular nodules and tree-in-bud opacities can occur with tuberculosis or other infections or in a setting of aspiration. Cavitation and calcifications are very uncommon with COVID-19 pneumonia. In a recent study comprising 81 patients,7,9 GGO are the most common imaging finding in the early disease and appear between 0 and 4 days. As the disease progresses, GGO become more extensive and are found in additional lung regions. Superimposed reticular interstitial opacities appear, giving a crazy-paving pattern  compared to SARS and MERS (approximately 80%).55–57 Relative rarity of cavitation, lymphadenopathy, and effusions appear to be common to all the three diseases. Long-term follow-up CT of patients with SARS and MERS demonstrate fibrotic, reticular interstitial changes, and sometimes bronchiectasis. While long-term data on COVID-19 are not available, similar changes can be seen in some cases of COVID-19 during recovery. Both SARS and MERS have a relatively higher mortality rate reaching up to 9% for SARS58 and 34.4%59for MERS.Previously, the world has seen two similar outbreaks from coronavirus family – severe acute respiratory syndrome (SARS) in 2003 and middle east respiratory syndrome (MERS) in 2013. The pathological findings of these coronavirus lung infections (SARS and MERS) overlap with the current pandemic COVID-19.10,11,60 The Royal Australian and New Zealand College of Radiologists (RANZCR) position statement60 encourages the use of AI and advanced medical imaging technology to assist in the clinical care of patients with COVID-19. The statement also highlights that the AI tools are most useful when they ‘add value to the patient care’ beyond what is available through conventional imaging review. One of the primary hurdles towards development and research of AI tools in the multisociety position statement was CT availability, need for disinfection, consumption of personal protective equipment (PPE) and potential exposure to health-care staff.As stated earlier, the position statements from leading radiology socities highlighted that the role of CT is targeted more towards identification of complications or other clinical indications. Imaging was recommended for use as a diagnostic or screening tool only if the RT-PCR was/is unavailable, insensitive, or both.61–64 Some studies have recently explored the application of deep learning models to detect COVID-19 pneumonia on CT images with higher sensitivity and specificity.65–67 Li et al developed a deep learning model using a data set of 3322 patients who were able to differentiate COVID-19 pneumonia from community-acquired pneumonia with a very high degree of sensitivity, and specificity.65Currently, most of these challenges remain, but most clinical settings are witnessing an increasing use of CT imaging. While the existing AI tools for COVID-19 pneumonia are only recently emerging into clinical workflows, the quantitative tools have been studied extensively in diverse populations and environments and have provided a growing list of insights into disease subphenotypes, etiologies and have served to target interventions and to assess outcomes with significant applications to COPD, asthma and pulmonary fibrosis.A newly developed Hyperion view  is an advanced topographic multiplanar image visualization technique in which non-overlapping airways are warped and flattened onto a single image, bringing the lung parenchyma and vessels along with the warped airways. These images provide a unique visual summary of the parenchymal distribution of disease in relationship to airway morphometry. These Hyperion views provide a clear depiction of the typical bronchocentric distribution of the COVID-19 lung disease . Such de61,63,64 A key to the success of AI applications has been the use of standardized imaging protocols.68 In a recent study on density-based COVID-19 disease quantification, Shen et al69 showed that automated disease quantification is accurate and correlates well to radiologist’s disease identification. Tang et al,66 has also demonstrated that a machine learning-based disease quantification is feasible, and the volume of the GGO and GGO/lung ratio closely predicts the disease severity and outcomes. CT texture features have been used to provide disease quantification for a number of lung disease settings. GGO and air trapping are particularly challenging to define visually, and there can be considerable disagreements between radiologists. AI, applied to the regional characterization of lung texture has been shown to provide reliable, repeatable, objective metrics in a variety of lung pathologies.70–77 An example of the application of a texture characterization algorithm (the Adaptive Multiple Feature Method or AMFM)74 is provided in 13,43–45 These hypodense regions of the lung are a regular feature of the tissue classification in COVID-19 patients and with CT showing smaller vessel size in the affected areas, this may be a sign of regional blood volume loss in conjunction with microemboli or thrombosis.Various quantitative CT (qCT) measures based on lung density, texture, and airway or vascular mapping can also be used for objective assessment of a wide variety of lung diseases including COPD, IPF and asthma.78–80 One recent study from Wuhan compared the CT findings in patients who died from COVID-19 to patients who recovered and were discharged from the hospital. They found that patients in the mortality group were older, had more co-morbidities, and had more extensive and multiple lung zone involvement on CT. Also, patients in the mortality group had a higher frequency of consolidations and air bronchograms compared to patients who survived the disease.79 Some investigators have also suggested that architectural distortion and traction bronchiectasis on CT and development of pleural effusions are indicators of severe disease.78 Limited studies have reported that quantitative or semi-quantitative severity scores based on visual analysis on CT images correlate with the clinical severity of the disease.80,81 Except for slight variations, the widely used method is to assign individual scores to each of the involved lung lobes31,81 or zones40 based on the number and extent of acute inflammatory lesions  and then calculate the total lung severity score by summing up the individual scores. These scores are reported to have high consistency and interobserver reliability. It is postulated that these scores might help in identifying patients with severe disease and guide treatment decisions and also can be used to triage patients who might need admission to the hospital. Based on the available literature, the BSTI guidance statement12 has suggested that imaging abnormality can be categorized as mild, moderate, or severe among different imaging pattern groups (Typical, probable or intermediate patterns as described in Several studies have suggested that extent of inflammation on CT correlates with COVID-19 disease severity.COVID-19 is a relatively new disease, and the abnormality is frequently detectable on imaging. The imaging appearance varies among patients as well as along the temporal course of the disease. With increasing disease prevalence, when an imager identifies a typical CT or CXR appearance of this disease, it should be kept among the differential diagnosis, and confirmatory testing should be obtained by the clinical service, based on clinical suspicion. Advanced qCT tools like density-based and texture-based assessment are feasible and may provide tools that yield new insights into disease etiology and an objective and quantitative disease measurement for triage of services and forassessment of early response to therapy.


Neuropathic pain is a debilitating secondary condition for many individuals with spinal cord injury. Spinal cord injury neuropathic pain often is poorly responsive to existing pharmacological and nonpharmacological treatments. A growing body of evidence supports the potential for brain-computer interface systems to reduce spinal cord injury neuropathic pain via electroencephalographic neurofeedback. However, further studies are needed to provide more definitive evidence regarding the effectiveness of this intervention.The primary objective of this study is to evaluate the effectiveness of a multiday course of a brain-computer interface neuromodulative intervention in a gaming environment to provide pain relief for individuals with neuropathic pain following spinal cord injury.We have developed a novel brain-computer interface-based neuromodulative intervention for spinal cord injury neuropathic pain. Our brain-computer interface neuromodulative treatment includes an interactive gaming interface, and a neuromodulation protocol targeted to suppress theta (4-8 Hz) and high beta (20-30 Hz) frequency powers, and enhance alpha (9-12 Hz) power. We will use a single-case experimental design with multiple baselines to examine the effectiveness of our self-developed brain-computer interface neuromodulative intervention for the treatment of spinal cord injury neuropathic pain. We will recruit 3 participants with spinal cord injury neuropathic pain. Each participant will be randomly allocated to a different baseline phase , which will then be followed by 20 sessions of a 30-minute brain-computer interface neuromodulative intervention over a 4-week period. The visual analog scale assessing average pain intensity will serve as the primary outcome measure. We will also assess pain interference as a secondary outcome domain. Generalization measures will assess quality of life, sleep quality, and anxiety and depressive symptoms, as well as resting-state electroencephalography and thalamic γ-aminobutyric acid concentration.This study was approved by the Human Research Committees of the University of New South Wales in July 2019 and the University of Technology Sydney in January 2020. We plan to begin the trial in October 2020 and expect to publish the results by the end of 2021.This clinical trial using single-case experimental design methodology has been designed to evaluate the effectiveness of a novel brain-computer interface neuromodulative treatment for people with neuropathic pain after spinal cord injury. Single-case experimental designs are considered a viable alternative approach to randomized clinical trials to identify evidence-based practices in the field of technology-based health interventions when recruitment of large samples is not feasible.Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000556943; https://bit.ly/2RY1jRxPRR1-10.2196/20979 Approximately 50% of individuals with spinal cord injury (SCI) report ongoing neuropathic pain at or below the level of injury -3. NeuroAlthough many brain regions are involved in the experience of neuropathic pain, Gustin and colleagues have identified the key role of the thalamus in the development and maintenance of neuropathic pain following SCI. They have found that neuropathic pain after SCI is associated with altered thalamic volume , neurochThe disruption in thalamocortical rhythms  can be detected by surface electroencephalography (EEG) ,16. EEG There is accumulating evidence that thalamocortical dysrhythmia can be self-regulated by neuromodulative interventions . For exaThree single-arm trials have demonstrated that BCI-N interventions can reduce SCI neuropathic pain -24. ThesCurrent BCI-N interventions for both SCI neuropathic pain ,22,24 anThe primary objective is to evaluate the effectiveness of a multiday course of BCI-N intervention in a gaming environment to provide pain relief for individuals with SCI neuropathic pain. The secondary objective is to assess the intervention’s effectiveness on participants’ pain through pain interference. We will also determine whether the BCI-N intervention improves mood, sleep quality, quality of life, and well-being. Lastly, we will explore the neural mechanisms underlying the effect of a BCI-N intervention on SCI neuropathic pain. In particular, we will measure resting-state EEG and levels of thalamic GABA content pre- and postintervention.This study will be conducted based on a single-case experimental design (SCED) with multiple baselines across participants. The SCED is a powerful and effective method that is increasingly used in clinical trial designs ,34 to evThe SCED method is based on assessing the dependent variables  repeatedly for each of the participants across phases. The design of this study will be AB + follow-ups, where A refers to the baseline phase, B is the intervention phase, and both are followed by a follow-up phase. In addition, we will conduct a further follow-up phase 3 months after completion of the intervention. We will conduct and report the SCED study in accordance with the Single-Case Reporting Guideline in Behavioural Interventions (SCRIBE) 2016 Statement . To meetWe will recruit 3 individuals with complete thoracic SCI  for this study. Participants need to meet the following inclusion criteria: (1) aged 18 to 80 years, (2) having persistent neuropathic pain for 6 months or longer, (3) having an average pain intensity of 2 or more (out of 10) in the past week on a visual analog scale , (4) being medically stable, and (5) demonstrating an ability to use the VAS. With regard to the neuroimaging component of the study, we will exclude individuals who have metal objects inside their body .We will randomly assign 3 participants to different baseline durations of the SCED using a simple randomization method . ConventEach participant will receive 30-minute daily sessions of the BCI-N intervention for 20 days over a 4-week period in their home. Each session will involve two 15-minute BCI-N interventions divided by a 5-minute break, and each session will start and finish with measurement of the resting-state EEG levels. The BCI-N treatment incorporates an interactive gaming interface , and a neuromodulation protocol targeted to suppress theta and low alpha (4-8 Hz) and high beta (20-30 Hz) band powers and to enhance high alpha (9-12 Hz) band power . We willThe VAS will serve as the primary outcome measure of SCI neuropathic pain. We will ask the study participants to rate the average intensity of pain during 3 specific epochs each day, using a VAS. The VAS is a 10-cm horizontal line with “No Pain” at one end and “Maximum Pain Imaginable” at the other end. Respondents are asked to make a mark along the line that represents their pain intensity. At 12 o’clock (noon), participants will rate the average intensity of the pain they experienced from the time they woke up that day until noon. At 6 PM, they will rate their average pain intensity between noon and 6 PM. Finally, at the time they go to bed, they will rate the average of the pain intensity they experienced between 6 PM and the time they went to bed. The mathematical average of the 3 ratings will then be computed to represent that participant’s average daily pain intensity. If any ratings are missing, the score will be the average of the ratings obtained. Although consensus groups recommend the numeric rating scale over the VAS in pain clinical trials because some individuals have problems with understanding the VAS , we chosPain interference will serve as a secondary outcome measure. We will assess the degree of pain interference by 6 items from the Brief Pain Inventory (BPI) . These iWe will have daily contact with the participants, both to address any questions they may have about the VAS and BPI measures, and to ensure they are completing their pain diaries and BPIs during the times they are supposed to.We will collect generalization measures to evaluate whether the effect of the treatment extends beyond improvements in the primary and secondary outcomes . For exaWe will administer the psychological questionnaires at 5 time points: (1) prior to the baseline phase, (2) on the last day of the baseline phase, (3) on the last day of the intervention phase, (4) on the last day of the first follow-up phase, and (5) on the last day of the second follow-up phase. We will collect the resting-state EEG and the neuroimaging data at 2 time points: prior to and following completion of the intervention.Participants will complete the 36-item Short Form Health Survey modified for SCI  , the COMWe will record resting-state EEG with the participants’ eyes closed (3 minutes) and eyes open (3 minutes) using the 24-channel EEG device SMARTING. The electrode placements are according to the standard 10-20 locations. The electrode impedance will be kept under 5 kΩ, and the sampling frequency will be 500 Hz.3), which will be centered in the contralateral (to pain) thalamus in each participant.Participants will lie supine, headfirst, on the bed of a 3-T magnetic resonance imaging machine  with their head immobilized in a 32-channel head coil. We will use multiplanar  reformats for voxel placement. GABA-edited Meshcher-Garwood Point Resolved Spectroscopy (MEGA-PRESS)  will be We will collect participants’ feedback regarding perceived safety and feasibility of the intervention following each session of BCI-N treatment using study-specific questions . Following the completion of 20 sessions of BCI-N treatment, the participants will complete the Usefulness, Satisfaction, and Ease of Use  questionWe will analyze primary and secondary outcomes separately based on the SCED analysis. The SCED analysis mainly relies on visual inspection. However, we will inspect and analyze the outcome measures from this study using both visual analysis and supplementary statistical analysis . In the The data across all phases will be scattered and visually analyzed using both within-phase and between-phase analyses ,59. WithTrend refers to the slope of changes across observations (over time), which we will estimate using the split-middle method /SEdiff, and SEdiff = SD√2(1 – r), where SD is the standard deviation of the measurement and r is the reliability coefficient of the measure.RCI is a ratio of the actual observed difference by the standard error of the difference  and the University of Technology Sydney Human Ethics Committee . Additionally, this study is registered through the Australian and New Zealand Clinical Trials Registry (registration number: ACTRN12620000556943). We plan to commence the trial in October 2020 and expect to publish the results by the end of 2021.Preliminary data in support of BCI-N treatment for SCI neuropathic pain have been reported ,26. HoweThe BCI-N system of this study will address a key limitation of previous EEG neurofeedback interventions, which have mostly relied on a single form of virtual interaction ,22,24. SSCED is a powerful design to establish guidelines for evidence-based interventions . The keyInvestigating our novel self-developed BCI-N intervention with a SCED and evaluating it with visual and statistical analyses will provide a rigorous methodology for this study. The high internal validity of a well-implemented SCED study allows for the results of the data analyses to draw reliable conclusions about the effectiveness of the intervention ,71. ExpeThe SCED trial with multiple baselines will not be able to demonstrate effectiveness of the BCI-N treatment if 1 of the 3 participants drops out during the baseline or intervention phases. To address this limitation, we will perform a mock BCI-N treatment session for each participant prior to commencement of the trial in order to increase compliance and ensure a high comfort level of the EEG headset, a comprehensive understanding of the treatment protocol, assessment procedures, and performance of gameplay during the neurofeedback session.


Intense research using various in vitro and in vivo models is going on in various laboratories to understand the mechanisms involved in these interactions, as understanding of these mechanistic would greatly help in improving clinical transplantations. However, though these elegant studies have identified the molecular interactions involved in the process, harnessing these interactions to the recipients’ benefit would ultimately depend on manipulation of environmental cues initiating them in vivo: hence, these need to be identified at the earliest. HSCs reside in the bone marrow, which is a very complex tissue comprising of various types of stromal cells along with their secreted cytokines, extra-cellular matrix (ECM) molecules and extra-cellular vesicles (EVs). These components control the HSC fate decision through direct cell–cell interactions – mediated via various types of adhesion molecules –, cell-ECM interactions – mediated mostly via integrins –, or through soluble mediators like cytokines and EVs. This could be a very dynamic process involving multiple transient interactions acting concurrently or sequentially, and the adhesion molecules involved in various fate determining situations could be different. If the switch mechanisms governing these dynamic states in vivo are identified, they could be harnessed for the development of novel therapeutics. Here, in addition to reviewing the adhesion molecules involved in the regulation of HSCs, we also touch upon recent advances in our understanding of the physiological cues known to initiate specific adhesive interactions of HSCs with the marrow stromal cells or ECM molecules and EVs secreted by them.Hematopoietic stem cells (HSC) could have several fates in the body; viz. self-renewal, differentiation, migration, quiescence, and apoptosis. These fate decisions play a crucial role in maintaining homeostasis and critically depend on the interaction of the HSCs with their micro-environmental constituents. However, the physiological cues promoting these interactions  Hematopoietic stem cells (HSCs) reside in the bone marrow microenvironment comprising of various types of stromal cells and the ECM molecules secreted by them. This complex microenvironment forms the specialized HSC niche, which controls their maintenance, survival and fate decisions. The HSCs interact and adhere to various niche cells such as MSCs, osteoblasts and ECs as well as with the ECM molecules secreted by them. The graphical abstract illustrates various molecules that have been shown to be expressed on the HSCs as well as stromal cells such as various integrins, N- cadherin, Notch, Ephrins, PSGL-1, CD162, CD44, etc. The image also shows that bone marrow microenvironment also contains extra-cellular vesicles  having an important role in HSC adhesion. The illustration also points out an as yet unexplored aspect of adhesive interactions between various stromal cells . A hematopoietic stem cell (HSC) could have several fates in the body: it could remain quiescent; it could self-renew; it could commit to a particular lineage; it could migrate in response to a chemotactic cue; or it could even undergo apoptosis. In an adult human being the HSCs reside in bone marrow micro-environment comprising of several types of stromal cells along with their secretome. These micro-environmental components regulate or govern the HSC fate via signaling through various types of adhesion mechanisms. Since some of these mechanisms appear to involve short-range signals, HSCs need to be physically associated to the stromal cells: the adhesion molecules serve as the anchors that hold the HSCs in their niche. Although several studies have documented the adhesion mechanisms involved in the HSC fate decisions, the physiological cues that are translated into cellular language for the initiation of specific adhesive interactions of HSCs with stromal cells, or extra-cellular matrix (ECM) molecules and extra-cellular vesicles (EVs) secreted by them are not described to a great extent. Identification of such environmental cues could improve the outcome of clinical transplantations, as they can be harnessed to accrue benefit for the patients. Hence, in addition to reviewing the adhesion mechanisms operative in hematopoietic system, we also touch upon these aspects while describing them.Hematopoietic stem cells are known to interact with a variety of cell types and extracellular components located in their close proximity. These interactions are crucially required for not only maintaining the stemness and the functionality of the HSCs, but also for governing their fate decisions. Caenorhabditis elegans (Drosophila melanogaster (+ MSCs), Nestin positive MSCs, Macrophages, etc.Hematopoietic stem cells niches are thoroughly studied and characterized in invertebrate organisms such as  elegans  and Drosnogaster . Mammalinogaster . This ninogaster . Imagingnogaster . The stunogaster . Similarnogaster . The hisnogaster . The comBone marrow (BM) is a very complex structure made up of a variety of cell types having specific spatial locations . The conIn the embryonic developmental stages, the HSCs are known to mobilize, migrate and home to various HSC niches in a coordinated manner. For example, HSC pool is known to move from yolk sac to fetal liver, from where it moves to thymus, to spleen and finally to the bone marrow just before the birth. These processes are governed by the adhesion molecules expressed on the HSCs during these migratory processes. These adhesion molecules also play an important role in migration and homing of the donor HSCs to the recipient’s bone marrow niche after transplantation. Considering their importance in clinical transplantations, the adhesion molecules are mostly studied either in the context of mobilization of the donor HSCs or their engraftment in the recipients’ marrow: the processes working in exactly opposite direction of each other. Various adhesion molecules  that areIntegrins are one of the most important classes of adhesion molecules involved in the interaction of HSCs with their micro-environment. They not only participate in cell–cell and cell–matrix interactions, but also make connections to the cytoskeleton through their cytoplasmic domains and activate many intra-cellular pathways. Most integrins interact with several different ECM proteins, and individual matrix proteins bind to several integrins . Owing tIntegrins are made up of α and β subunits that are non-covalently associated with each other . There a–/– chimeric embryos were unable to migrate to fetal liver marking the crucial role of β1 integrins in HSC migration and homing. Similarly, the conditional β1 knockout HSCs fail to migrate to hematopoietic organs such as bone marrow, spleen and thymus -1α (CXCL12)-expressing stromal cells  is known to participate in cell adhesion and cell surface-mediated signaling. Its expression is mostly restricted to megakaryocytes, but a small subset of HSCs also expresses CD41. In the embryonic hematopoietic cells, CD41 is considered to be the marker for differentiation. Its expression has been shown to be associated with early stages of hematopoiesis and is tightly regulated during hematopoietic development . Adult Hby Gata1 .An aspect that is now fast emerging is how HSCs use various adhesion molecules and receptors to respond to the changes in the stiffness of the microenvironment; integrins play a crucial role in this process. The integrin-mediated adhesion starts with initial attachment of the cells to the matrix, where integrin clustering, recruitment of adhesion-associated proteins, and the generation of focal adhesion complexes take place . This abin vitro  cells on immobilized P-selectin molecules delays the differentiation process and promotes their proliferation resulting in increased CFU-S and CFC numbers in in vivo mouse models  and stem cell factor (SCF) increases the frequency of CD34 and L-selectin double positive HSCs in the revived cell population, along with an increased number of CFU-forming progenitors (+ cells (+ cells 4 and 6 days post-mobilization (in vitro with anti-L-selectin antibody blocked clonogenic outgrowth of cells in both long-term and short-term (methylcellulose) assays  and a specialized glycoform of CD44 . Although human hematopoietic cells are shown to interact with both the molecules, under shear stress condition, human hematopoietic cells adhere strongly to HCELL, as compared to PSGL-1 . This L-genitors , indicatgenitors . It has  assays . A progr) assays , suggestInterestingly, L-selectin appears to have a role in the adhesion of leukemic stem/progenitor cells. N-cadherin is expressed at extremely low levels in a very limited hematopoietic cell population,or may in fact be absent,” and “the N-cadherin monoclonal antibody,MNCD2,is not specific for N-cadherin expression in the hematopoietic compartment.” Whether such low level expression of N-cadherin on the HSCs as reported by the investigators translates into meaningful regulatory role is still an open question.Role of N-cadherin in the regulation of HSC fate is by far the most controversial matter in the history of adhesion molecules involved in the process. Expression of N-cadherin on HSCs became a matter of hot debate as one group strongly advocated the expression of N-cadherin on the HSCs and its role in the regulation of hematopoiesis , whereasCdh2) in the HSCs (LSK CD150+ CD34–), albeit at a variable level. Using a newly developed antibody to N-cadherin they also showed that the LSK HSCs express N-cadherin and the N-cadherin+ HSCs possess higher engraftment ability. On the background of previous controversy over the N-cadherin antibody (MNCD2), these data need confirmation from other labs. The same group , and the other, primed HSCs , and showed that the N-cadherin+ bone and marrow progenitor cells (BMSPCs) play an important role in protecting rHSCs from chemotherapy. They further found that genetic ablation of N-cadherin from BMSPCs impaired rHSC maintenance during homeostasis and regeneration. These data show that N-cadherin positive stromal cells differentially regulate HSC subsets.As against the expression of N-cadherin in HSCs, there appears to be consensus over the expression of N-cadherin in the stromal cells, but whether it plays any role in the regulation of HSC functions remains controversial. Using genetic manipulation of Cdh2, a gene encoding N-cadherin, two groups demonstrated that deletion of N-cadherin from osteoblastic cells, both, osteoprogenitors and more mature osteoblasts, had no effect on steady state hematopoiesis or on any of the HSC functions such as engraftment, proliferation or mobilization . These d+ HSCs and also on bone marrow stromal cells. A function blocking antibody to N-cadherin diminished the colony formation by the HSCs and also interfered with the adhesion of KG1a cells, a CD34+ cell line of leukemia origin, to stromal cells. + HSCs isolated from cord blood (CB) and mobilized peripheral blood (MPB). Cadherin-11 was expressed on CB HSCs only. Both adhesion molecules were strongly expressed on the MSCs. They also found co-localization of N-cadherin and β-catenin at the junction of HPC and MSC, which could be disrupted using siRNA-mediated knockdown of N-cadherin or cadherin-11 as well as treatment with a blocking antibody. Such intervention also impaired maintenance of long-term culture-initiating cells (LTC-IC) in the co-culture of HSCs and MSCs. These data showed that N-cadherin-mediated adhesive interactions are important for human HSCs. However, in this study they did not determine the in vivo effects of N-cadherin knock out. in vitro. Using atomic force microscopy (AFM)-based single-cell force spectroscopy (SCFS), they showed that human HSCs have a stronger adhesion to human MSCs, as compared to their adhesion with murine MSCs. They correlated this difference to the N-cadherin levels in these MSCs. These data suggest that N-cadherin could have a species-specific role in the regulation of human HSCs. However, more rigorous in vivo studies are needed to come to a definitive conclusion.In contrast to the murine data, an early study by + on the co-cultured HSCs, leading to a significant reduction in their chemotactic migration toward SDF1α. Such silencing of N-cadherin in the stromal cells results in an increased pool of HSCs, but the frequency of CXCR4+ HSCs goes down drastically. Based on our results, we speculated that perhaps the temporary normoxia that follows myeloablation as a consequence of reduction in the cell number perhaps leads to a transient down-regulation of N-cadherin in the BMSCs, thereby allowing the HSCs to proliferate. After HSC regeneration, hypoxia sets in due to high consumption of local oxygen and the expression of N-cadherin returns to the normal level. Although speculative, this study points toward the role of hypoxia as a physiological cue involved in the regulation of N-cadherin-mediated adhesion of HSCs with the BMSCs. This needs to be formally examined in in vivo situation.In spite of several studies dealing with the role of N-cadherin in hematopoiesis, the physiological stimulus or cue regulating the N-cadherin expression on the HSCs or the niche cells has not been examined. In this context, using murine BMSCs we showed that hypoxia up-regulates expression of N-cadherin in them and this expression is very sensitive to oxygen . InteresNotch is a cell-surface receptor that transduces short-range signals by interacting with transmembrane ligands such as Delta-like and Jagged on neighboring cells . In mammtrans) the interaction becomes productive, whereas when they are present on the same cell (in cis), the activation is inhibited , which then travels to the nucleus and binds to CSL [CBF1/RBPjk/Su(H)/Lag1]. CSL interacts with many other proteins to form either repressor complexes comprising histone deacetylases (HDACs), which preserve a closed chromatin conformation, or activating complexes containing NICD and histone acetyltransferases (HATs), which open up chromatin. The extracellular domain of all Notch receptors contains 29–36 tandem epidermal growth factor (EGF)-like repeats. Interestingly, when Notch receptors and their respective ligands are present on adjacent cells  secreted by nitric oxide-primed BMSCs (primed MVs) contain significantly higher concentration of Jagged-1-specific mRNAs that upon transfer to the HSCs increase the level of Jagged-1 in them leading to their enhanced engraftment  is the most abundantly expressed isoform in mammalian cells. It binds to several ECM molecules, amongst which hyaluronan is the most common ligand. Hyaluronan is an important component of the HSC niche and participates in HSC lodgement in the endosteal region. CD44, hyaluronan and SDF-1 interaction has been shown to affect HSC and progenitor cell trafficking . Using a+ HSCs and found that the CD44 TT genotype was the only factor associated with a higher risk of poor mobilization of HSCs in patients with hematological malignancies. Specifically, among the single nucleotide polymorphisms (SNPs) investigated in the study, only CD44 rs13347 was found to have an impact on the efficacy of HSCs mobilization, suggesting that analysis of CD44 SNPs may help in identifying the poor mobilizers. Such analysis could lead to the development of novel approaches of using inhibitors of adhesion molecules for HSC mobilization. + HSCs in the peripheral blood after mobilization. They determined the correlation between various cell adhesion molecules (CAMs) with the yield of CD34+ cells and found that poor yield of CD34+ HSCs correlated with a higher expression of CD44, CD106, and CD49d, as compared with those with good CD34+ cell yield. Mobilized CD34+ HSCs showed a reduced expression of several CAMs like CD44, CD106, CD135, CD49d, and CD11a, but this did not correlate with the yield. These data show the importance of various adhesion molecules in the mobilization of HSCs required for clinical transplantations and suggest that alternate strategies involving targeting of these adhesion molecules might be required to be applied in case of poor mobilizers. + HSCs on plates coated with antibodies to CD44 and CD43 reduced their mobility and enabled colony formation in liquid cultures, increased imaging throughput in time-lapse microscopy, and also facilitated media change without affecting cell positions –CXCR4 axis plays a crucial role in the process . SDF1α p+ HSCs in the bone marrow.Both, HSC retention and mobilization are largely governed by SDF-1α- CXCR4 axis and by α4-integrin signaling. Both pathways are dependent on c-kit activity. Inhibition of c-kit kinase affects HSC mobilization in response to either CXCR4 antagonists or α4-integrin blocking agents and also prevents the retention of CXCR4+ cells to bone marrow stroma and promotes cycling of CD34+ human HSCs. They further showed that use of a function disrupting antibody or CD164 knock down by RNAi significantly inhibits the migration of CB-derived CD133+ HSCs toward SDF1α in vitro. They further showed that CD164 associates with CXCR4 in the presence of SDF1α and fibronectin, followed by the association of CXCR4 with the integrins VLA-4 and VLA-5. This interaction leading to the activation of PKC-zeta and Akt signaling gets disrupted in the absence of CD164. –/– HSCs display poor localization to bone marrow niches leading to poor engraftment. Interestingly, loss of Robo4 led to up-regulation of both Scf1 and Cxcr4, perhaps as a compensatory mechanism. Robo4 deletion also affects the efficiency of HSC mobilization, demonstrating that HSC mobilization involved inhibition of both, Cxcr4- and Robo4-mediated niche interactions.Some adhesion molecules like endolyn (CD164) have been shown to impart specificity to the HSC-niche interactions mediated by the SDF1α-CXCR4 axis. in vitro (Expression of Eph (erythropoietin-producing hepatocellular) molecules and their cognate ligands Ephrins on the HSCs and stromal cells has been documented by several studies . EphA1–Ein vitro . Consistin vitro .in vivo homing properties of HSC (Ephrin-A5 has been reported to enhance HSC trafficking and adhesion  via phoss of HSC .In vitro these HSCs gave rise to more granulocyte/monocytes and in vivo gave a higher T cell: B cell ratio when transplanted into congenic mice. These studies suggest that Esam1 may play role in HSC proliferation and lineage commitment.Cytohesin1 (CYTH1), a guanine-nucleotide exchange factor for multiple guanosine triphosphate (GTP)–binding protein, forms a complex with integrin β1 and αL to mediate adhesion to ICAM1. However, it was not studied in the context of HSC adhesion. Using a CYTH1 knock out HSCs, –/– mice showed expansion of HSC having impaired quiescence and myeloid bias. ICAM-1-deficient HSCs exhibited normal reconstitution capacity during serial transplantation; however, transplantation of wild type HSCs in ICAM-1–/– mice showed that ICAM-1 deficient niche affects HSC quiescence and fails to retain HSCs in the bone marrow. These data revealed the role of ICAM-1 as an important adhesion molecule involved in the retention of HSCs in the bone marrow niche.Intercellular adhesion molecule 1 (ICAM-1) has been shown to maintain quiescence of HSCs and also their repopulation in the niche . ICAM-1–Srf), a transcription factor, regulates genes controlling cytoskeletal components involved in cell spreading, adhesion, and migration. Srf binds to CC(A/T)6GG (CArG) motif, but its transcriptional activity depends on various signal-regulated cofactors. Srf in BM cells expanded HSCs and multipotent progenitors (MPPs), without having much effect on cell cycle dynamics. However, Srf loss resulted in defect in mature cell formation and severe thrombocytopenia. Srf-null HSCs also showed reduced engraftment properties. Srf was found to control the genes governing cell migration and adhesion. Srf-null HSCs had impaired expression of the integrin network and decreased adherence in vitro. Consistent with this, the Srf-null mice had increased numbers of circulating HSCs in their peripheral blood. These studies suggest that Srf regulates HSC adhesion through HSC-ECM interactions and integrin signaling.The serum response factor , EVs are also secreted by healthy cells, either constitutively or after activation. These EVs are classified into two main subtypes, namely, micro-vesicles  and exosomes  with the plasma membrane, whereas MVs are shed by outward blebbing of the plasma membrane . MVs andin vivo migration to the BM niche in NSG mice  produced by niche cells may alter the HSC response and their functionality. Thus, HSC functionality can be modulated by “priming” the parent cells with pharmacological means to modulate their EV profiles for their application for therapeutic purpose .Besides the cells of non-hematopoietic origin, HSC niche consists of hematopoietic cells like megakaryocytes (Mgk)  and macrIn specific conditions such as aging, HSCs show a reduced expression of CXCR4  and consHoming of HSCs to the appropriate place in the bone marrow niche is an important process involving coordinated functioning of various signaling and adhesion molecules. Individual roles of most of the adhesion molecules have been discussed earlier in this review. However, these molecules do not operate independently, but rather work in an orchestrated manner to guide the infused HSCs to their exact destination in the bone marrow. The processes of migration and homing require sequential formation and disruption of various adhesion bonds between the HSCs and the bone marrow cells. The important steps involve the rolling of HSCs on the walls of endothelial capillaries, followed by their further migration into the bone marrow compartment and finally their engraftment in the specific HSC-supportive microenvironment.Bone marrow is a primary organ of hematopoiesis and large numbers of hematopoietic cells are known to traffic from and to the bone marrow. Thus, for efficient homing of HSCs to the bone marrow very specific mechanisms are required to selectively attract the HSCs to the bone marrow niche. First, the intravenously infused HSCs migrate to the bone marrow niche via chemotactic migration mediated by the SDF1α-CXCR4 axis. Thereafter, the L- and P- selectin molecules expressed on the ECs present on the lining of the blood sinusoids and capillaries in bone marrow get involved in the homing process, as the ligands for these selectins are expressed on the HSCs . Once brtrans-endothelial migration to migrate along the SDF-1 gradient. E- and P- selectins once again play an important role in the recruitment of HSC to the ECs and subsequent trans-endothelial migration , the stromal cells also could initiate homotypic  or heterotypic  interactions among themselves and these interactions could in turn lead to HSC adhesion and fate change. This possibility also needs to be addressed. Such studies could provide better insight to the mechanisms involved in HSC adhesion.RK and VK researched the literature and wrote the manuscript. VK conceived the contents, wrote, edited, and approved the final version. Both authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The treatment and monitoring of patients with neuroendocrine tumors (NET) has been a major challenge during the COVID-19 pandemic. In a survey, we investigated the influence of COVID-19 on the care of NET patients in the German speaking countries Germany, Austria and Switzerland. The multidisciplinarity of all treating physicians in the outpatient and inpatient sector was reflected in our survey. Furthermore, we were able to present findings pertaining to the university and non-university medical care. Overall, only a minority of appointments were cancelled, mostly as a result of medical prioritization and less for fear of infection by patients. In the university sector, longer delays for diagnostic measures were observed in comparison to non-university care. During the COVID-19 crisis, NET patients rarely changed their current therapy, but the pandemic impacted the assessment of the different treatment modalities at risk of developing severe COVID-19 disease. This survey provides the first real-world data on the treatment of NET patients from the physicians’ perspective during the COVID-19 crisis. Despite delays in diagnostic procedures and outpatient appointments, only a minority of physicians foresee a major impact of COVID-19 on NET patient care. The outbreak of COVID-19 caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) was declared as global health emergency by the world health organization (WHO) in January 2020. Until now COVID-19 has had detrimental effects on many aspects of human life, leading to both economic consequences such as high unemployment and recession, and heavy burdens on global health care systems [The number of patients suffering from COVID-19 continues to rise worldwide, especially in some European countries like Spain and France. In Germany, the burden on the health care system is currently estimated to be relatively low in large parts of the country. However, with daily numbers of new cases again increasing in the last weeks, the burden could rapidly rise locally and then strain the public health systems, especially facilities for outpatient and inpatient medical care .The COVID-19 pandemic has a significant impact on the care of patients with chronic diseases like cancer patients, who need frequent hospital admissions and visits. Cancer patients are at high risk for a severe course of COVID-19 due to several factors such as immunosuppressed state, higher age and comorbidities . Therefore, in the COVID-19 era, oncologists should carefully weigh risks/benefits when planning cancer therapies and follow-up appointments .ESMO guidelines classified cancer patients in two groups: patients off therapy (A) and patients under treatment (B). For all patients (A and B), it is mandatory to provide health education. For patients receiving active treatment (B), hospitals (physicians) should provide specific pathways in order to guarantee timing of treatment, modify regimen schedules to reduce number of clinic visits, favor phone or web-technology contacts. More intensive surveillance should be used during treatment for patients with lung cancer or those who received previous lung surgery, and for older patients or those patients with other comorbidities .Furthermore, ESMO established a tiered approach for categorizing patients into three levels of priority  to receive active cancer treatment during the COVID-19 pandemic and developed “COVID-19 era recommendations” for the management of the main types of tumors . HoweverNeuroendocrine neoplasias are rare tumor types. However, several studies have shown an enormous increase in the incidence in recent decades. The age-adjusted NET incidence has increased 6.4-fold from 1973  to 2012 . The incidence and prevalence of NET are steadily rising, possibly owing to detection of early-stage disease and stage migration [There are several general recommendations from cancer societies and loco-regional reports ,9,10, buIn this study we assessed the impact of COVID-19 on current NET patient care in Germany. We conducted a survey to investigate how strongly further diagnostic and therapeutic procedures of NET patients in outpatient and inpatient settings were affected.Ethical approval was obtained from the local ethical review committee of the Martin-Luther-University Halle/Wittenberg . A total of 16 questions were developed, including four general questions about characteristics of physicians and facilities and 12 specific questions about the influence of COVID-19 on the management of NET patients. Either several answers of a given choice, only one answer (multiple choice) or yes/no answers were possible. In some cases, free text was possible to specify the answer.The survey was performed between 1 July and 31 July in the following three German-speaking countries: Austria, Switzerland and Germany. The survey was open to physicians who treat NET patients in inpatient and outpatient settings, regardless of the disease stage and whether they received current therapy or follow-up care. Although there was no restriction regarding the inclusion of COVID-19-positive patients, it can be assumed that the responding physicians only saw COVID-19-negative patients, because COVID-19-positive patients were treated separately in the inpatient area depending on the care structure and were not treated routinely in the outpatient area in order to minimize the risk of transmission. The questionnaire and was distributed via the German NET-Registry and via personal contacting. The full survey is provided in the The software LimeSurvey  was used to conduct the survey online. Descriptive statistics were calculated using Office Excel 2016  and GraphPad Prism 5 .n = 71) of the participants answered all questions completely. Most physicians worked in a university hospital , followed by non-university hospitals  and specialist practices . The question of clinical specialization was answered as follows: oncology , endocrinology , gastroenterology , surgery , nuclear medicine , internists  (n = 46). Typically, physicians spend 5–20% of their time treating NET patients. Only 6 participants spend more than 40% of their time on the care of NET patients.A total of 92 participants took part in the survey and 77.2%  . In mostn = 48 and 90%, n = 58 respectively). We found that 55% (n = 39) and 62% (n = 44) of the appointments for the treatment of NET patients were never or rarely postponed or cancelled for outpatient and inpatient treatment, respectively. In the inpatient sector, 9% (n = 6) of the participants stated that more than 25% of the consultations were cancelled, while the corresponding number in the outpatient sector was significantly higher   . The infn = 26), endoscopic workups  and with FDG/Ga68-PET/CT , with more extensive delays in the university sector . Only 13% (n = 9) believed that this will have a significant impact in the future.Whether the COVID-19 situation has a long-term effect on referrals/admissions to NET patients was negated in 57% (n = 60) than the patient’s preference . Twenty percent (n = 14) of the participants reported that more than 20% of all cases were cancelled due to the patients’ fear of an infection, while 80% (n = 56) stated that less than 20% of the cases were cancelled due to this reason. We found that 47% of physicians were asked frequently/very frequently by patients about their personal risk of disease. In the university setting the demand was higher than in the non-university setting (59% vs. 37%).When asked about the reasons for postponing a consultation, medical priority ranked higher  of the respondents answered “no”. In 24% (n = 17) of cases this was rarely carried out.One of the main objectives of this survey was to evaluate the different existing therapies for NET patients according to their risk for a severe course of COVID-19 infection. As shown in Overall, a COVID-19 test was recommended in 62% of NET patients; more often in non-university than in university settings (78% vs. 49%).Care of patients with neuroendocrine tumors demands an interdisciplinary approach with regular in- and outpatient appointments. Although the course of the disease is frequently slower than in other tumor entities, there is still a high need for care in patients with advanced disease. In our survey we aimed to assess the impact of the SARS-COV-2 pandemic on patient care for neuroendocrine tumors from the perspective of the treating physicians. Although the pandemic influenced appointments, diagnostic procedures and preferences for treatment, only a minority of participating physicians were worried about a significant impact in the future.During the lockdown phase of the SARS-COV-2 pandemic in Austria, Switzerland and Germany, most hospitals were faced with strict regulations regarding patient contacts. This was reflected in our survey as most participants experienced a strong impact on outpatient appointments. Interestingly, this effect was much stronger in the university setting than in non-university hospitals and private practice. Current ESMO guidelines emphasize the evaluation of phone consultations and video contacts with patients to avoid hospital or outpatient clinic visits . WhetherAs NET is a rare disease and requires a multi-professional team for appropriate care, most patients are treated in specialized centers within university hospitals. In the lockdown phase, these specialized hospitals were strictly regulated by governmental action to prioritize activities towards care for patients with COVID-19. Thus, it is not unexpected that physicians in a university setting report delays in diagnostic procedures more frequently than physicians in non-university hospitals or private practice. Although imaging procedures were delayed by up to 50% in university hospitals, no major delays for PRRT treatments were reported. This is in stark contrast to the data from the Italian survey, who reported delays in initiating PRRT treatment in up to 50% of patients .When asked about patients worries related to COVID-19 and requests for assessment on patient’s personal risks, physicians reported a high demand for information. As most NET patients either have an ongoing treatment for metastatic disease or have had a major operation in the past, these patients might fall into categories of increased risk for a severe disease course of COVID-19 . FurtherThe most important point of the survey was to assess how the SARS-COV-2 pandemic would influence choice and decisions for treatment in NET patients. Risk assessments of treatments have been published by medical societies for other tumor entities . Only reOne limitation of this study is the purely observational character relying on the participation of contacted physicians. Thus, this survey does not include all centers treating NET patients nor all specialties involved in the care of NET patients. Centers of Excellence (COEs) were not specified explicitly. Nevertheless, we received responses from six different groups of physicians involved in the care of NET patients. Not unexpected, most participants in this survey were oncologists, endocrinologists and gastroenterologists providing outpatients care for NET patients. The number of participants does not reflect the number of participating hospitals, because potentially multiple colleagues from one and different disciplines per hospital could take part in the survey. The survey questions were compiled very succinctly in order to increase the response rate. Unfortunately, we did not include questions on specific measures taken by different physicians to adjust medical care to the crisis. Thus, we cannot report on the use of video-consultations, phone consultations or community-based patient care as recommended by oncological societies. The survey did not distinguish between advanced high-grade neuroendocrine neoplasms (NEN) and advanced low grade NEN as physicians were addressed who treat NET patients in general, regardless of the disease stage. Nor did the survey distinguish between COVID-19-positive and COVID-19-negative patients. It can be assumed, however, that the survey only reflects the practice of COVID-19-negative patients. COVID-19-positive patients were treated separately in the inpatient area depending on the care structure and were not treated routinely in the outpatient area in order to minimize the risk of transmission.This survey provides the first real-world insight into the physician’s attitude towards the SARS-COV-2 pandemic and the experience and consequences for the treatment of patients with neuroendocrine tumor disease. Although some delays in diagnostic procedures were experienced in the lockdown phase of the pandemic, only a minority of physicians report a major impact of the pandemic on care for NET patients in Germany, Austria, and Switzerland.