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1.
J Neurosurg ; : 1-11, 2022 Sep 16.
Article in English | MEDLINE | ID: covidwho-2039641

ABSTRACT

OBJECTIVE: The outbreak of COVID-19 and the sudden increase in the number of patients requiring mechanical ventilation significantly affected the management of neurooncological patients. Hospitals were forced to reallocate already scarce human resources to maximize intensive care unit (ICU) capacities, resulting in a significant postponement of elective procedures for patients with brain and spinal tumors, who traditionally require elective postoperative surveillance on ICU or intermediate care wards. This study aimed to characterize those patients in whom postoperative monitoring is required by analyzing early postoperative complications and associated risk factors. METHODS: All patients included in the analysis experienced benign or malignant cerebral or intradural tumors and underwent surgery between September 2017 and May 2019 at University Hospital Münster, Germany. Patient data were generated from a semiautomatic, prospectively designed database. The occurrence of adverse events within 24 hours and 30 days postoperatively-including unplanned reoperation, postoperative hemorrhage, CSF leakage, and pulmonary embolism-was chosen as the primary outcome measure. Furthermore, reasons and risk factors that led to a prolonged stay on the ICU were investigated. By performing multivariable logistic regression modeling, a risk score for early postoperative adverse events was calculated by assigning points based on beta coefficients. RESULTS: Eight hundred eleven patients were included in the study. Eleven patients (1.4%) had an early adverse event within 24 hours, which was either an unplanned reoperation (0.9%, n = 7) or a pulmonary embolism (0.5%, n = 4) within 24 hours. To predict the incidence of early postoperative complications, a score was developed including the number of secondary diagnoses, BMI, and incision closure time, termed the SOS score. According to this score, 0.3% of the patients were at low risk, 2.5% at intermediate risk, and 12% at high risk (p < 0.001). CONCLUSIONS: Postoperative surveillance in cranial and spinal tumor neurosurgery might only be required in a distinct patient collective. In this study, the authors present a new score allowing efficient prediction of the likelihood of early adverse events in patients undergoing neurooncological procedures, thus helping to stratify the necessity for ICU or intermediate care unit beds. Nevertheless, validation of the score in a multicenter prospective setting is needed.

2.
Exp Neurobiol ; 31(4): 270-276, 2022 Aug 31.
Article in English | MEDLINE | ID: covidwho-2025199

ABSTRACT

Transsynaptic transport is the most accepted proposal to explain the SARS-CoV-2 infection of the CNS. Nevertheless, emerging evidence shows that neurons do not express the SARS-CoV-2 receptor ACE2, which highlights the importance of the blood-brain barrier (BBB) in preventing virus entry to the brain. In this study, we examine the presence of SARS-CoV-2 messenger ribonucleic acid (mRNA) and the cytokine profile in cerebrospinal fluids (CSF) from two patients with a brain tumor and COVID-19. To determine the BBB damage, we evaluate the Q- albumin index, which is an indirect parameter to assess the permeability of this structure. The Q-albumin index of the patient with an intraventricular brain tumor suggests that the BBB is undamaged, preventing the passage of SARS-CoV-2 and pro-inflammatory molecules. The development of brain tumors that disrupt the BBB (measured by the Q-albumin index), in this case, a petroclival meningioma (Case 1), allows the free passage of the SARS-CoV-2 virus and probably lets the free transit of pro-inflammatory molecules to the CNS, which leads to a possible activation of the microglia (astrogliosis) and an exacerbated immune response represented by IL-13, IFN-γ, and IL-2 trying to inhibit both the infection and the carcinogenic process.

3.
6th International Conference on Advances in Computing and Data Sciences, ICACDS 2022 ; 1614 CCIS:88-99, 2022.
Article in English | Scopus | ID: covidwho-2013954

ABSTRACT

This paper proposed a model that deals with automatic prediction of the disease given the medical imaging. While most of the existing models deals with predicting disease in one part of the body either brain, heart or lungs, this paper focuses on three different organs brain, chest, and knee for better understanding the real word challenge where problems do not include crisp classification but the multiclass classification. For simplicity this paper focuses on just determining whether that organ is affected with the disease or not and future work can be done by further expanding the model for multiple disease detection of that organ. We have used CNN for multiclass image classification to determine the input medical image is brain, chest or knee and then SVM is used for binary classification to determine whether that input image is detected with the disease or not. Three different datasets from Kaggle are used: Brain Tumor MRI Dataset, COVID-19 Chest X-ray Image Dataset and Knee Osteoarthritis Dataset with KL Grading. Images from these datasets are used to make fourth datasets for training and testing the CNN for the prediction of the three different organs and after that output will be the input of respective SVM classifier based on the output result and predict the weather it is diagnostic with the disease or not. The proposed model can be employed as an effective and efficient method to detect different human diseases associated with different parts of the body without explicitly giving the input that it belongs to that part. For the transparency this model displays the accuracy of prediction made for the input image. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

5.
Revista Iberoamericana de Cirugia de la Mano ; 50(1):E1-E2, 2022.
Article in English | EMBASE | ID: covidwho-1978064
6.
Neuro-Oncology ; 24:i182, 2022.
Article in English | EMBASE | ID: covidwho-1956583

ABSTRACT

Awareness practices are mind-body medicine techniques that help quiet the chatter of worry, fear, or the “to-do list” in the mind and allows the individual to experience calm and focus. Neuro-Oncology families undergo a variety of stressors that increase the “mind chatter” once their child is diagnosed with a brain tumor. These families not only have to manage the day-to-day tasks of family life, but they are thrust into a world of uncertainty which often can breed anxiety. To help mitigate the stress and anxiety that Neuro-Oncology families undergo, sessions focusing on awareness practices were offered to parent caregivers once a week for 15-20 minutes via the Zoom platform. The goal of these sessions was to offer respite from mental and emotional challenges brought on by the cancer diagnosis and the COVID 19 pandemic. Separate sessions were also offered to Oncology nurse case managers to help decrease compassion fatigue as these nurses also walk alongside oncology families through the cancer journey providing advocacy and patient/family support. Breath awareness, imagery, and meditation practices were used during the sessions to activate the body's relaxation response to allow for rest and restoration.

7.
Neuro-Oncology ; 24:i141, 2022.
Article in English | EMBASE | ID: covidwho-1956575

ABSTRACT

OBJECTIVE: School reentry support focusing on providing information to schools and communication between patient/family-hospital-school is defined as a psychosocial standard of care in pediatric oncology (Thompson et al., 2015). This is critical for students with brain tumors (BT) - although it is not yet universally implemented - especially during follow-up, as they are a risk group for late effects. Due to long distances between family-hospitalschool, limited personnel capacities and since 2020 Covid-19 restrictions, an online-event (OE) for teachers from external schools was designed, with the aim of: (1) strengthening cooperation, (2) breaking down barriers and (3) increasing level of knowledge. METHODS: 54 teachers participated in each of two OEs. Content was presented by an interdisciplinary team (clinician, clinical/neuropsychologist, social worker, teacher), followed by time for sharing experience. Two months after event 2, participants were asked to complete an evaluation in an anonymous online survey. Supportive and inhibiting factors for successful school reintegration were included in the survey and statistically analyzed. RESULTS: 54% of 23 respondents (70% teaching > 10 years) felt that their training before the event did not prepare them adequately for a teaching setting with seriously ill children (1-3 points on a 10-point Likert-scale). 92% rated their knowledge greater after the event. All interdisciplinary inputs were rated very useful and practical (79-88%: 8-10 points). 38% felt relieved to got to know contact persons. 33% rated teaching a student with BT as fundamentally challenging and felt more confident after the event. CONCLUSION: The results of this pilot project indicate that an online-information-event can increase knowledge and cooperation. Resulting promoting and inhibiting factors for school reintegration will be incorporated into future concept improvement. The findings further highlight the great importance of ongoing support in the form of a reintegration teacher and interdisciplinary input for schools to appropriately support students with BT.

8.
Neuro-Oncology ; 24:i132, 2022.
Article in English | EMBASE | ID: covidwho-1956574

ABSTRACT

Neurofibromatosis (NF) therapeutics is a vital field in the care of children with NF. Recent developments in the treatment of plexiform neurofibromas (PN) have increased the numbers of patients seen for therapy. The Neurofibromatosis Therapeutics Program (NTP) provides high quality care to patients receiving therapy for brain tumors and PNs, as well as tumors related to NF2. The program at Children's Hospital Colorado (CHCO) includes a physician, nurse practitioner, and nurse care coordinator. The team collaborates with other disciplines in the care of the NF patient with plexiform neurofibromas and/or CNS tumors. As the program grew, key players were identified in each subspecialty and educated about the NTP. We have ongoing regular communication with a large number of subspecialists regarding protocols, clinical care pathways, and mutual patients. In addition, an extensive tissue collection study of plexiform neurofibromas and brain tumors enhances NTPs devotion to both clinical and lab research. Weekly clinical care meetings ensure continuity in the care of the nearly 140 patients with NF1 and NF2 under our program. Monthly strategy and vision meetings focus on grant applications, education of primary care providers and subspecialists in our large catchment area, development of new clinical pathways, treatment roadmaps, and growth of our program. Over the last two years of being a formalized program, we have increased research on the epigenetics of plexiform neurofibromas, opened a Phase 2 clinical trial for a Mek inhibitor, and increased our patient volume. The Covid pandemic has increased our ability to manage treatment side effects virtually through telehealth and online patient portals. Future goals of the NTP include completion of a program website, quarterly patient and provider newsletters, educational offerings, collaboration with other centers on Mek inhibitor side effects, adolescent and young adult education on tumor risk, and transition to adult care.

9.
Neuro-Oncology ; 24:i74-i75, 2022.
Article in English | EMBASE | ID: covidwho-1956572

ABSTRACT

INTRODUCTION: High-grade gliomas account for <5% of all pediatric brain tumors with a 20% 5-year overall survival even with maximal safe resection followed by concurrent radiotherapy and chemotherapy. Patients in low-and middle-income countries already face delays and barriers to the treatment they require. The current COVID pandemic has added unique challenges to the delivery of complex, multidisciplinary health services to these patients. METHODOLOGY AND RESULTS: We retrospectively reviewed the records of four patients, ages 2-18 years old, with histologically confirmed high-grade glioma managed in a tertiary government institution from 2020-2021. Three of the patients had a supratentorial tumor and one patient had multiple tumors located in both supra-and infratentorial compartments. Neurosurgical procedures performed were: gross total excision (1), subtotal excision (2), and biopsy (1). The tissue diagnoses obtained were glioblastoma (3) and high-grade astrocytoma (1). Two patients survived and are currently undergoing adjuvant radiotherapy and chemotherapy. The remaining two patients expired: one from hospital-acquired pneumonia and the other from COVID-19 infection. DISCUSSION: Decreased mobility due to lockdowns, the burden of requiring negative COVID-19 results before admission for surgery, reduced hospital capacity to comply with physical distancing measures, the postponement of elective surgery to minimize COVID-19 transmission, physician and nursing shortages due to infection or mandatory isolation of staff, cancellation of face-to-face outpatient clinics, and hesitation among patients and their families to go to the hospital for fear of exposure were found to be common causes of delays in treatment. Also, the redirection of health resources and other government and hospital policies to handle the COVID-19 pandemic resulted in an overall delay in the delivery of health services. In particular, the management of pediatric patients with cancers, especially high-grade gliomas, was significantly disrupted.

10.
Studies in Big Data ; 109:25-45, 2022.
Article in English | Scopus | ID: covidwho-1941430

ABSTRACT

COVID19 is a respiratory illness that is extremely infectious and is spreading at an alarming rate at the moment. Chest radiography images play an important part in the automated diagnosis of COVID19, which is accomplished via the use of several machine learning approaches. This chapter examines prognostic models for COVID-19 patients’ survival prediction based on clinical data and lung/lesion radiometric characteristics retrieved from chest imaging. While it seems that there are various early indicators of prognosis, we will discuss prognostic models or scoring systems that are useful exclusively to individuals who have received confirmation of their cancer diagnosis. A summary of some of the research work and strategies based on machine learning and computer vision that have been applied for the identification of COVID19 have been presented in this chapter. Some strategies based on pre-processing, segmentation, handmade features, deep features, and classification have been discussed, as well as some other techniques. Apart from that, a few relevant datasets have been provided, along with a few research gaps and challenges in the respective sector that have been identified, all of which will be useful for future study efforts. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

11.
Journal of Vascular and Interventional Radiology ; 33(6):S231, 2022.
Article in English | EMBASE | ID: covidwho-1936899

ABSTRACT

Purpose: To examine the outcomes of patients with venous thromboembolism (VTE) who underwent placement of a bioabsorbable inferior vena cava filter (IVCF) for temporary pulmonary embolism (PE) protection Materials and Methods: From 10/1/2020 to 11/31/2021, 17 patients (mean age 71, range 45-92, 58% female) underwent placement of a bioabsorbable IVCF (Sentry, Boston Scientific) at a single academic center. Thirteen of the 17 filters (76.4%) were placed in the inpatient setting, and the remainder were placed outpatient. VTE risk factors included malignancy (70.6%), immobility (5.9%), COVID-19 (5.9%), and unprovoked (7.6%). Prior to IVCF, 11 patients presented with deep venous thrombosis (DVT) alone, two had PE alone, and four were diagnosed both DVT and PE. The contraindication to anticoagulation (AC) was active bleeding in 47.1% of the cohort, upcoming surgery in 41.2%, worsening of DVT on AC in 5.9%. and brain tumor in 5.9%. The pre-implantation infrarenal IVC diameter ranged from 1.6 to 2.6 cm. Technical success (TS), adverse events (AEs), and follow-up IVCF characteristics were recorded. Results: TS was 100%. No AEs occurred during placement. Mean follow-up period was 4.9 months (range 0-12.9). No new PEs were diagnosed after IVCF placement, and no patients required replacement of IVCF. Nine of the 17 patients had follow-up CTs after filter placement, two had follow up radiographs in which the filter state could be assessed, and the remaining six had no imaging evaluating the filter after placement. Asymptomatic IVCF associated non-occlusive thrombosis was seen in 3 patients. The longest amount of time after placement that a Sentry filter was observed to still be in the filter state was 3.9 months, and the shortest time in which imaging showed a filter bio-converted to the open state was 3.1 months. Three patients underwent serial imaging which incidentally demonstrated the timeframe in which the IVCF converted from a filter-state to an open-state. In one patient this conversion occurred between 2.1 and 3.1 months, in another between 1.7 and 3.3 months, and in the last patient between 3.9 and 4.4 months. Conclusion: In VTE patients with either a temporary contraindication to anticoagulation or a transitory high-PE-risk period, bioconvertible IVC filters are a safe and effective option for short-term protection against pulmonary embolism.

12.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925499

ABSTRACT

Objective: Identify patients who had breakthrough seizures following COVID-19 vaccine administration. Background: Neurologic complications occur following vaccinations. The coronavirus (COVID-19) vaccines are also associated with neurological side effects. For example, 100 cases of Guillian Barre Syndrome were reported following 12.5 million doses of the Johnson & Johnson vaccine. Five case reports of thrombosis and thrombocytopenia, with corresponding cerebral venous sinus thrombosis (CVST) were reported with the Johnson & Johnson vaccine. Lastly, a recent study noted that out of 54 patients with epilepsy, one patient had increased seizure frequency following vaccination and another patient had a new seizure semiology. The impact of the COVID-19 vaccines on primary brain tumor patients is unknown. Design/Methods: We analyzed the 866 patients at the Alvord Brain Tumor Center from January 2021 to April 2021. We describe here 15 patients with primary brain tumors who experienced breakthrough seizures within a week of receiving the first or second dose of the Moderna or Pfizer vaccines. Results: Sixty percent of patients had glioblastoma, the median age of 60 years, with males and females relatively equally affected (47% vs. 53%). Approximately 70% were not on active treatment at the time of seizure breakthrough. The last episode of seizure was at least six months prior to the seizure breakthrough in 33% of patients. Seizures occurred a median of one day after the most recent vaccine. Seizure breakthrough reports were similar between first and second vaccine doses (47% vs. 53%). In two patients, seizure following their COVID-19 vaccine was the first manifestation of their primary brain tumor. Conclusions: COVID-19 vaccines may lower seizure threshold by systemic inflammation or sleep disruption. Given the likely increased risks of COVID-19 infection among patients with brain tumors, vaccination is still recommended. Patient counseling on sleep hygiene, fever, and strict adherence to seizure medication is crucial to mitigate the risk of seizure post-vaccination.

13.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925255

ABSTRACT

Objective: 1. N/A 2. Background: In the wake of the Coronavirus disease outbreak (COVID-19), clinical trial operations were significantly impacted following the shutdown of elective healthcare services and, in some cases, emergency operations. When the pandemic hit Detroit, Michigan in March 2020, the Hermelin Brain Tumor Center (HBTC) at Henry Ford Health System was consumed in COVID-19 emergency care which affected patient enrollment, conduct of trial activities, therapeutic treatment, deviation from protocol requirements, and sponsor-study site contact. The first Metro-Detroit COVID-19 case was confirmed March 10th 2020. At that time there were 18 active brain tumor clinical trials (phase 1 - 3) providing anti-cancer therapies. Design/Methods: Modifications included decentralized operations to buildings with clinic and radiology access away from inpatient COVID-19 care, utilization of telemedicine for nonessential visits, shipping of investigational products to patient home, and in some cases utilization of local results in place of central histopathological confirmation. By April 2020, trials were ranked based on availability of alternate therapies and subject safety in 4 tiers that correlated with subject benefit and impact on care. Trials were given a prioritization level to commence enrollment with priority given to trials where no standard of care exists. Of the HBTC trials, one was graded Tier 1 and most were graded Tier 2. All patients already enrolled, continued study participation. As restrictions eased, trials were opened in a sequential manner. Results: N/A Conclusions: Changes that were made during the first wave of the pandemic helped to minimize its effect on clinical trial operation and enrollment during the second wave in Fall 2020. Thus, leading toward a decrease in trial deviations and increased enrollment during the 2 wave. Changes made during the first wave helped to safely continue enrollment and treatment during the second wave and will have a longstanding impact on how clinical trials are conducted in the future.

14.
Neurooncol Adv ; 4(1): vdac063, 2022.
Article in English | MEDLINE | ID: covidwho-1901219

ABSTRACT

Background: As the COVID-19 pandemic continues to unfold, the advent of multiple approved vaccines has led to a milestone in the fight against the virus. While vaccination rates and side effects are well established in the general population, these are largely unknown in patients with brain tumors. The purpose of this study was to determine if brain tumor patients and their caregivers have received a COVID-19 vaccine, and explore their thoughts and opinions on these vaccines. Methods: An anonymous 31-question online survey available in 8 languages was conducted from June 30, 2021 to August 31, 2021. The survey was open to adult brain tumor patients over the age of 18 and included both categorical and open-ended questions. Descriptive statistics and modified thematic analyses were performed for all questions as appropriate. Results: A total of 965 unique surveys were completed from 42 countries. The vast majority of both brain tumor patients and their caregivers have been vaccinated against COVID-19 (84.5% and 89.9%, respectively). No patient reported serious adverse events from any vaccine. Less than 10% of patients decided against receiving a vaccination against COVID-19, with the most common reason being concerns over the safety of the vaccine. Patients wanted more specific information on how COVID-19 vaccines might impact their future brain tumor treatment. Conclusions: In conclusion, the majority of brain tumor patients and their caregivers have received COVID-19 vaccines with no major side effects. Patients want more information on how COVID-19 vaccines might directly impact their brain tumor and future management.

15.
Int J Surg Case Rep ; 91: 106774, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1828635

ABSTRACT

BACKGROUND: Patients often present with one or more pre-existing underlying chronic diseases that will affect their prognoses and mortality. A study revealed that the majority of children with SARS-CoV-2 infection presented with either no or a single symptom. Meanwhile, multiple other studies reported of more severe diseases in SARS-CoV-2 infected children with brain tumor and/or cancer as a whole. CASE REPORT: The patient was a 15-year-old male who was referred to our hospital with complaints of vomiting, headache, and signs of worsening right hemiparesis. Initial MRI suggested of a high-grade astrocytoma and hydrocephalus, but a subtotal tumor resection and external ventricular drainage gave light to a histopathological examination conclusive of germinoma. After adhering to radiotherapy and recovering well, the patient fell into unconsciousness 9 months later and tested positive for SARS-CoV-2 infection. The patient deteriorated on the third day of admission with respiratory failure, shock, arrythmias, fever, and increased d-dimer. After multiple attempts stabilization with ventilatory, defibrillator, and medical support, the patient deceased at the 6th day of admission. DISCUSSION: Cancer patients with COVID-19 have been reported to have relatively higher mortality rate when compared to the non-infected patients. Moreover, malignancies were also reported to increase the risk of developing more severe disease in children. Although rare, patients may develop a condition called multisystem inflammatory syndrome in children (MIS-C), which is a state of hyperinflammatory and severe illness temporally associated with COVID-19 infection. No observations have been evident in indicating the influence of COVID-19 on the neurological state of the patient, but we believe that it may be reasonable to not yet exclude the possibility of it of exacerbating the CNS malignancy our patient suffered from. CONCLUSION: Children with intracranial brain tumor infected by SARS-CoV-2 may fall into a worse condition with poor prognosis, exacerbated by severe acute respiratory distress and the need for breathing support in intensive care unit. Multidisciplinary tumor boards have to convene regularly, including through call-conferences and telemedicine platforms.

16.
Applied Sciences ; 12(8):3773, 2022.
Article in English | ProQuest Central | ID: covidwho-1809667

ABSTRACT

Brain tumor is a severe cancer and a life-threatening disease. Thus, early detection is crucial in the process of treatment. Recent progress in the field of deep learning has contributed enormously to the health industry medical diagnosis. Convolutional neural networks (CNNs) have been intensively used as a deep learning approach to detect brain tumors using MRI images. Due to the limited dataset, deep learning algorithms and CNNs should be improved to be more efficient. Thus, one of the most known techniques used to improve model performance is Data Augmentation. This paper presents a detailed review of various CNN architectures and highlights the characteristics of particular models such as ResNet, AlexNet, and VGG. After that, we provide an efficient method for detecting brain tumors using magnetic resonance imaging (MRI) datasets based on CNN and data augmentation. Evaluation metrics values of the proposed solution prove that it succeeded in being a contribution to previous studies in terms of both deep architectural design and high detection success.

17.
2nd International Conference on Computer Vision, High-Performance Computing, Smart Devices, and Networks, CHSN 2021 ; 853:215-225, 2022.
Article in English | Scopus | ID: covidwho-1797675

ABSTRACT

The year 2019 brought the once in hundred years’ experience for the whole world. COVID-19 pandemic shaken almost all segments of everyone’s life and scientists all over the world are engaged in saving our existence. As there is a need of capturing microstructural changes like tumor boundary pixel level shifts and/or growth, deep learning can be a very promising to identify the pixel level changes occurred in brain MR images. The multi-layer execution using CNN architecture is possible, but there is a need for fast convolution and de-convolution with lowered strides. Conventional methods can provide acceptable results, but to identify the microstructural changes in (COVID-19 patient) MR image, accuracy and visibility at pixel level need to be very precise. Hence, this paper presents the methodology for analysis of pre- and post-COVID-19 brain tumor microstructures by means of development of novel CNNPostCoV deep learning algorithm. Proposed research uses IIARD-19 and IIARD-20 dataset of COVID-19 patient. Algorithm framed with convolution neural network architecture which provides better performance of dice score, sensitivity, and PPV parameters. Paper also presents the training and validation analysis for HGG, LGG, and combined dataset of multi-modal brain tumors. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

18.
Pediatr Blood Cancer ; 69(6): e29645, 2022 06.
Article in English | MEDLINE | ID: covidwho-1756630

ABSTRACT

BACKGROUND: Pediatric brain tumor survivors are at risk for poor social outcomes. It remains unknown whether cognitive sparing with proton radiotherapy (PRT) supports better social outcomes relative to photon radiotherapy (XRT). We hypothesized that survivors treated with PRT would outperform those treated with XRT on measures of cognitive and social outcomes. Further, we hypothesized that cognitive performance would predict survivor social outcomes. PROCEDURE: Survivors who underwent PRT (n = 38) or XRT (n = 20) participated in a neurocognitive evaluation >1 year post radiotherapy. Group differences in cognitive and social functioning were assessed using analysis of covariance (ANCOVA). Regression analyses examined predictors of peer relations and social skills. RESULTS: Age at evaluation, radiation dose, tumor diameter, and sex did not differ between groups (all p > .05). XRT participants were younger at diagnosis (XRT M = 5.0 years, PRT M = 7.6 years) and further out from radiotherapy (XRT M = 8.7 years, PRT M = 4.6 years). The XRT group performed worse than the PRT group on measures of processing speed (p = .01) and verbal memory (p < .01); however, social outcomes did not differ by radiation type. The proportion of survivors with impairment in peer relations and social skills exceeded expectation; χ2 (1) = 38.67, p < .001; χ2 (1) = 5.63, p < .05. Household poverty predicted peer relation difficulties (t = 2.18, p < .05), and verbal memory approached significance (t = -1.99, p = .05). Tumor diameter predicted social skills (t = -2.07, p < .05). CONCLUSIONS: Regardless of radiation modality, survivors are at risk for social challenges. Deficits in verbal memory may place survivors at particular risk. Results support monitoring of cognitive and social functioning throughout survivorship, as well as consideration of sociodemographic risk factors.


Subject(s)
Brain Neoplasms , Proton Therapy , Brain Neoplasms/pathology , Child , Cognition , Humans , Proton Therapy/adverse effects , Proton Therapy/methods , Protons , Social Adjustment , Survivors/psychology
19.
J Clin Exp Neuropsychol ; 43(10): 980-990, 2021 12.
Article in English | MEDLINE | ID: covidwho-1747019

ABSTRACT

INTRODUCTION: Few studies have considered health-related quality of life (HRQOL) as a primary outcome measure in adult survivors of primary brain tumor (PBT), and fewer still have studied the cognitive factors that may influence it. Research suggests that executive functions (EFs) are associated with HRQOL, but there is scant evidence to support this. The present study was conducted to (1) extend prior findings about HRQOL limitations in a sample of stable, long-term adult survivors of PBT, (2) investigate the associations between objective/reported EFs and HRQOL, and (3) identify the EFs that contribute most to HRQOL. METHOD: We recruited 40 survivors of PBT (> 2 years post-treatment) and 40 matched healthy controls. Participants completed an objective EF assessment (inhibition, working memory, shifting, and rule detection) and two self-report questionnaires probing EFs (Behavior Rating Inventory of Executive Function-Adult) and HRQOL (Medical Outcomes Study Short-Form 36). Participants' relatives completed observer-rated versions of these questionnaires. RESULTS: Patients' objective EF performances were relatively intact. However, patients and caregivers reported significantly more problems than healthy controls and their relatives, for both EFs and HRQOL. There were only negligible links between objective EFs and HRQOL, whereas numerous associations were found between reported EFs and HRQOL components. ANCOVA models revealed that specific reported EF processes contributed to both the physical and mental components of HRQOL, regardless of group. CONCLUSIONS: From a clinical point of view, this study demonstrates that even several years after end of treatment, adult PBT survivors experience substantial problems across different HRQOL domains. HRQOL assessment should therefore be part of the long-term follow-up of PBT survivors, and clinicians should consider EF limitations when designing appropriate survivorship care plans. These findings indicate that cognitive interventions targeting EFs could improve HRQOL.


Subject(s)
Brain Neoplasms , Executive Function , Quality of Life , Adult , Brain Neoplasms/complications , Brain Neoplasms/psychology , Case-Control Studies , Executive Function/physiology , Humans , Surveys and Questionnaires , Survivors
20.
Biomedical Signal Processing and Control ; 76:103631, 2022.
Article in English | ScienceDirect | ID: covidwho-1748175

ABSTRACT

The major intention of this work is to detect the Brain tumor with accuracy by reducing error rate and computational complexity. Therefore, in this manuscript, a Deep Convolutional Neural Network with Nature-inspired Res net 152 Transfer Learning model using CNN and Transfer learning tactics is proposed to detect and classify the brain images. Here, the images are pre-processed to remove the noises, also enhance the quality of the images by using Otsu binarization method. The image features, like contrast, Energy, Correlation, Homogeneity, Entropy are extracted with the help of Gray-Level Co-Occurrence Matrix methods. Then, the images are classified using the hybrid Deep Convolutional Neural Network with Nature-inspired Res Net 152 Transfer Learning (Hyb-DCNN-ResNet 152 TL), in which the batch normalization layer of the Deep CNN is removed and added with ResNet 152 layer. Here, hybrid Deep Convolutional Neural Network with Nature-inspired Res Net 152 Transfer Learning classifies as normal, benign and malignant. Then the Hyb-DCNN-ResNet 152 TL weight parameters are tuned using Covid-19 optimization algorithm (CoV-19 OA). The simulation process is executed in the MATLAB platform. The proposed method attains higher accuracy of 99.57%, 97.28%, 94.31%, 95.48%, 96.38%, 98.41% and 96.34%, lower Error rate of 0.012(s), 0.014(s), 0.011(s), 1.052(S), 0.013(S), 0.016(S) and 0.015(s) compared with existing methods, like BTC-Deep CNN-Dolphin-SCA, BTC-Deep CNN-WHHO, BTC-AFDNN-FLA, BTC-MLPNN-IWOA, BTC-ANN-PSO, BTC-RF-WSO and BTC-WRF-ACO.

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