Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma

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Estimating Local Cellular Density in Glioma Using MR Imaging Data

BACKGROUND AND PURPOSE:Increased cellular density is a hallmark of gliomas, both in the bulk of the tumor and in areas of tumor infiltration into surrounding brain. Altered cellular density causes altered imaging findings, but the degree to which cellular density can be quantitatively estimated from imaging is unknown. The purpose of this study was to discover the best MR imaging and processing techniques to make quantitative and spatially specific estimates of cellular density.MATERIALS AND METHODS:We collected stereotactic biopsies in a prospective imaging clinical trial targeting untreated patients with gliomas at our institution undergoing their first resection. The data included preoperative MR imaging with conventional anatomic, diffusion, perfusion, and permeability sequences and quantitative histopathology on biopsy samples. We then used multiple machine learning methodologies to estimate cellular density using local intensity information from the MR images and quantitative cellular density measurements at the biopsy coordinates as the criterion standard.RESULTS:The random forest methodology estimated cellular density with R² = 0.59 between predicted and observed values using 4 input imaging sequences chosen from our full set of imaging data (T2, fractional anisotropy, CBF, and area under the curve from permeability imaging). Limiting input to conventional MR images (T1 pre- and postcontrast, T2, and FLAIR) yielded slightly degraded performance (R² = 0.52). Outputs were also reported as graphic maps.CONCLUSIONS:Cellular density can be estimated with moderate-to-strong correlations using MR imaging inputs. The random forest machine learning model provided the best estimates. These spatially specific estimates of cellular density will likely be useful in guiding both diagnosis and treatment.

Increased cellular density (CD) is a hallmark of cancer and a key feature in histologic glioma analysis.¹ Mapping cellular density throughout a tumor would be a valuable tool to probe how tumors infiltrate and analyze the transition between diseased and healthy brain. However, measuring CD requires tissue, which entails additional risks and is expensive to obtain. There is no currently accepted clinical algorithm to translate imaging data into quantitative assessments of CD.There is great need for a method to estimate CD noninvasively in human patients with gliomas. In this article, we describe the development of such a method using MR imaging data inputs by correlating with multiple biopsy specimens acquired during a prospective human clinical trial. We obtained comprehensive MR imaging, including conventional, diffusion, perfusion, and permeability imaging sequences. We used machine learning approaches to correlate imaging findings with CD measurements from pathology, devised an algorithm to estimate CD from MR imaging inputs, and generated CD maps for the visual display of the predictions. We identified the most informative imaging data subset. This work has multiple applications in the diagnosis and treatment of patients with gliomas: For example, the method can be used to guide biopsy, resection, and surgery and delineate tumor borderzones both pre- and postoperatively.²     

An assessment of cerebral venous thrombosis risk factors and associated clinical outcomes in Jazan region,Saudi Arabia

Objectives:To assess cerebral venous thrombosis risk factors, and associated clinical outcomes in Jazan region, Kingdom of Saudi Arabia.Methods:This study is a retrospective review of the medical records of patients diagnosed with cerebral venous thrombosis and admitted to King Fahad Central Hospital in Jazan between 2010 and 2019. Data concerning socio-demographics, clinical features, risk factors, laboratory, and imaging investigations were retrieved. Furthermore, data about cases management, and outcomes, including death, were collected and analysed.Results:A total of 51 medical records were identified. The majority of the patients were females (68.6%), and the mean age of the patients was 33.3 years, of which three patients were under 18 years old. The most frequently recorded symptom was headache (76.5%), followed by seizure (45.1%). The most commonly recorded risk factor was protein S deficiency (57%), followed by anaemia (51%). Venous infarction and haemorrhage were the most common acute complications (13.7%). The majority of the patients had a favourable prognosis where only 27.5% recovered with disability and only one patient died due to the disease.Conclusion:Clinical presentation of cerebral venous thrombosis in Jazan region is similar to other local and international studies. However, anaemia was recorded as a main risk factor for the disease, which might require further investigation to assess the possible association between prevalence of anaemia in Jazan region and the incidence of cerebral venous thrombosis.

Cerebral venous thrombosis (CVT) is a rare form of cerebrovascular disease in comparison with arterial stroke. CVT cases represent approximately 0.5-1% of all types of stroke which mainly occur in young and middle-aged adults.1 The data concerning the global epidemiology of CVT is currently limited.2 However, the incidence of CVT has been reported to vary between countries where the incidence might be higher as in Asian and the Middle Eastern countries in comparison to Australia and European countries.3According to a recent study conducted in Australia, the incidence of CVT was reported to reach 15.7 per 1,000,000 persons on a yearly basis. The incidence was higher among women and among those between 31-50 years old.4 In the Middle East, an Iranian study looked at the frequency of CVT between 2001 and 2004, and the annual frequency of CVT was 12.3 per one million.5 An older study, conducted in the city of Riyadh in Saudi Arabia between 1985 and 1994, identified 40 cases of CVT. Those identified were aged between 16 and 40.6 In addition, in a more recent study conducted in Jeddah and Al-Baha between 1990 and 2010, the number of detected cases of CVT was 111 where 19 of these were detected among children.7The CVT occurs when a thrombus develops as a result of a disturbance of the balance between the process of prothrombosis and thrombolysis.8,9 Risk factors for CVT can be categorised into transient and permanent risk factors. Permanent risk factors are hereditary thrombophilia, systemic diseases or miscellaneous factors, such as obesity. Transient risk factors can be subcategorised into sex-specific, iatrogenic, or miscellaneous risk factors, such as infection, head trauma or anaemia.8 The prevalence of CVT risk factors differs between countries. Infection, pregnancy, post-partum period, and dehydration have been reported to be more common in Asia and the Middle Eastern countries in comparison to European countries.8Patients with CVT exhibit variable clinical manifestations and complications, some of which can be life threatening. The most common clinical presentation is a headache, while some patients exhibit other signs and symptoms, such as seizure, decreased level of consciousness, vomiting, focal neurological deficit, or visual symptoms.8-10 Venous infarction and haemorrhage are frequently reported complications of CVT.11 Late presentation of CVT patients can increase the risk of disability and death. The mortality rate among CVT patients has been reported to vary between 4.3% and 6.8%.12Since CVT risk factors and vulnerable groups can vary between different populations, assessment of the distribution of risk factors among local populations can be clinically valuable. Studies assessing CVT prevalence and associated risk factors and clinical outcomes in Saudi populations are currently limited. Furthermore, data about CVT in Jazan region is currently lacking. This investigation aims to identify cases diagnosed with CVT in Jazan region and to evaluate the risk factors and associated clinical outcomes.