Clinical and baseline computed tomography features of patients infected with the B.1.617.2 (Delta) variant of severe acute respiratory syndrome coronavirus 2

PURPOSE: The purpose of this study was to investigate the clinical and baseline computed tomography (CT) features and their correlation in patients infected with the B.1.617.2 (Delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MATERIALS AND METHODS: Clinical and chest baseline CT data of patients infected with the Delta variant of SARS-CoV-2 from July to August 2021 were collected. First, the correlation between the clinical data and baseline CT results was analyzed according to CT positivity or negativity. Then, subgroup analysis was performed between different age distributions and clinical characteristics. Next, the CT characteristics and clinical data of all baseline CT-positive patients were collected, and the correlations between CT characteristics and age, vaccination status, and chronic disease were analyzed. Lesions in patients with baseline CT positivity were evaluated by semi-quantitative scoring to analyze the correlations between the semi-quantitative scores and vaccination status and age distribution. RESULTS: A total of 221 nucleic acid-positive patients with the SARS-CoV-2 Delta variant were included, of whom 107 patients were baseline CT positive and 114 were baseline CT negative. Baseline CT positivity was associated with age distribution, and baseline CT positivity was most common in patients aged >60 years (P < 0.001), but not with vaccination status or gender. The results of the subgroup analysis according to age distribution indicated that different age distribution subgroups had different vaccination statuses, and the majority of patients aged <18 years and >60 years were unvaccinated (90.5%, 19/21, and 57.3%, 63/110, respectively). In contrast, most patients aged 18–60 years had received two doses of the vaccine (61.1%, 55/90) (P < 0.001). Different age distribution subgroups had different clinical infection types. Asymptomatic and mild cases were most common in patients aged ≤60 years, and moderate and severe or critical cases were most common in patients aged >60 years. For baseline CT-positive patients, the extent of lung involvement was associated with age, vaccination status, and chronic disease. The number of involved lobes was higher in patients who were unvaccinated or who had received one injection, who were aged >60 years or had chronic disease. There was a statistical difference in CT semi-quantitative scores between the different age subgroups. Compared with patients aged < 60 years, patients aged >60 years had higher semi-quantitative scores (P < 0.001). However, there was no statistical difference between the different vaccination groups. CONCLUSIONS: Age had a large effect on baseline CT positivity, CT characteristics, and semi-quantitative CT scores in patients infected with the Delta variant.

Characteristics of cardiac injury complicating with acute kidney injury and mortality risk in coronavirus disease 2019 (COVID-19) patients

Objectives: This study aimed to identify the clinical features of cardiac injury complicating with acute kidney injury (AKI) and its risk for a fatal outcome in patients infected with coronavirus disease 2019 (COVID-19) pneumonia. Methods: Initial signs and symptoms and clinical laboratory, radiological, and treatment information were obtained from seven hospitals in China from January 23, 2020, to March 15, 2020. Results: Of 438 patients, 36 (8.22%) displayed isolated cardiac injury, 17 (3.88%) had isolated AKI, and 17 (3.88%) displayed cardiac injury complicating with AKI. Compared with patients without cardiac injury or AKI, patients with isolated cardiac injury, isolated AKI, and cardiac injury complicating with AKI were older (55, 65, 74 vs. 48 years, P < 0.0001) and critically severe. More patients displayed fatigue, dyspnea, and comorbidities in the group with cardiac injury complicating with AKI. Moreover, the indexes reflecting myocardial, renal, liver, and coagulation dysfunctions and infection-related factors were significantly different among the four groups. After adjustment for covariates, patients with cardiac injury complicating with AKI had a higher hazard ratio for mortality (6.64;95% confidence interval, 1.51–29.30). Conclusion: Cardiac injury complicating with kidney injury significantly increased the risk for in-hospital mortality in COVID-19 pneumonia patients. Therefore, early detection at admission and careful monitoring of myocardial and renal injury through biomarkers during hospitalization is recommended to reduce the harm to patients.

A review of the results from a patient experience survey of the palliative radiotherapy bone metastases service

Introduction:A patient experience survey was undertaken as part of the role of the Macmillan Consultant Therapy Radiographer for the bone and brain metastases patients to inform future development of the service.Method:A questionnaire was developed and approved by the Trust's local Questionnaire, Interview and Survey Group to survey the experiences and satisfaction of the service including the informed consent process, radiotherapy appointments and overall experience and satisfaction. The survey used qualitative and quantitative methods, including Likert Scales and free comment boxes. The responses were analysed by counting the frequency of each response and identifying any themes in free text responses.Results:Most patients were satisfied with the consent process with 1/36 patients reporting a lack of understandable information and 4/36 wanting more side effect information. The option of plan and treat was a preference of 53% of patients due to travelling back and forth to the centre;however, only 6% stated that they wanted two separate appointments. Ninety-four percent of patients felt that they had complete confidence and trust in the professional who consented them and 86% did not feel fully involved in the decision-making process. Overall, the service was rated as 10/10 by 61% of patients (n = 36).Conclusions:The patients surveyed were satisfied with their experience of the Palliative Radiotherapy Service;however, it needs to be developed further to meet the needs and expectations of the service users.

Mortality risk analysis for patients with severe coronavirus disease 2019 pneumonia

BACKGROUND: Coronavirus Disease 2019 (COVID-19) is currently a global pandemic. Information about predicting mortality in severe COVID-19 remains unclear. METHODS: A total of 151 COVID-19 in-patients from January 23 to March 8, 2020, were divided into severe and critically severe groups and survival and mortality groups. Differences in the clinical and imaging data between the groups were analyzed. Factors associated with COVID-19 mortality were analyzed by logistic regression, and a mortality prediction model was developed. RESULTS: Many clinical and imaging indices were significantly different between groups, including age, epidemic history, medical history, duration of symptoms before admission, routine blood parameters, inflammatory-related factors, Na+, myocardial zymogram, liver and renal function, coagulation function, fraction of inspired oxygen and complications. The proportions of patients with imaging Stage III and a comprehensive computed tomography score were significantly increased in the mortality group. Factors in the prediction model included patient age, cardiac injury, acute kidney injury, and acute respiratory distress syndrome. The area under the receiver operating characteristic curve of the prediction model was 0.9593. CONCLUSIONS: The clinical and imaging data reflected the severity of COVID-19 pneumonia. The mortality prediction model might be a promising method to help clinicians quickly identify COVID-19 patients who are at high risk of death.

Dynamic chest computed tomography change analysis and prediction of length of stay for delta variant COVID-19 patients

OBJECTIVE: As hospital admission rate is high during the COVID-19 pandemic, hospital length of stay (LOS) is a key indicator of medical resource allocation. This study aimed to elucidate specific dynamic longitudinal computed tomography (CT) imaging changes for patients with COVID-19 over in-hospital and predict individual LOS of COVID-19 patients with Delta variant of SARS-CoV-2 using the machine learning method. MATERIALS AND METHODS: This retrospective study recruited 448 COVID-19 patients with a total of 1761 CT scans from July 14, 2021 to August 20, 2021 with an averaged hospital LOS of 22.5 ± 7.0 days. Imaging features were extracted from each CT scan, including CT morphological characteristics and artificial intelligence (AI) extracted features. Clinical features were obtained from each patient's initial admission. The infection distribution in lung fields and progression pattern tendency was analyzed. Then, to construct a model to predict patient LOS, each CT scan was considered as an independent sample to predict the LOS from the current CT scan time point to hospital discharge combining with the patients' corresponding clinical features. The 1761 follow-up CT data were randomly split into training set and testing set with a ratio of 7:3 at patient-level. A total of 85 most related clinical and imaging features selected by Least Absolute Shrinkage and Selection Operator were used to construct LOS prediction model. RESULTS: Infection-related features were obtained, such as the percentage of the infected region of lung, ground-glass opacity (GGO), consolidation and crazy-paving pattern, and air bronchograms. Their longitudinal changes show that the progression changes significantly in the earlier stages (0–3 days to 4–6 days), and then, changes tend to be statistically subtle, except for the intensity range between (−470 and −70) HU which exhibits a significant increase followed by a continuous significant decrease. Furthermore, the bilateral lower lobes, especially the right lower lobe, present more severe. Compared with other models, combining the clinical, imaging reading, and AI features to build the LOS prediction model achieved the highest R2 of 0.854 and 0.463, Pearson correlation coefficient of 0.939 and 0.696, and lowest mean absolute error of 2.405 and 4.426, and mean squared error of 9.176 and 34.728 on the training and testing set. CONCLUSION: The most obvious progression changes were significantly in the earlier stages (0–3 days to 4–6 days) and the bilateral lower lobes, especially the right lower lobe. GGO, consolidation, and crazy-paving pattern and air bronchograms are the most main CT findings according to the longitudinal changes of infection-related features with LOS (day). The LOS prediction model of combining clinical, imaging reading, and AI features achieved optimum performance.

Fast 5 at RSNA '22: Looking into Radiology's Crystal Ball

In brief TED talk-style presentations on topics ranging from climate change, artificial intelligence (AI) and telemedicine, to the COVID-19 pandemic and emergence of corporate medicine, the radiologists shared their predictions of how these developments could change medical imaging technology and practice during the next five years. Given the expansion of telemedicine, the growth of radiologic consultation, and the emergence of new and improved diagnostic modalities-such as hybrid PET-MRI, photon-counting CT, new nuclear medicine radiotracers, and theranostics-as well as minimally invasive imaging-guided procedures and implementation of AI, Dr Morrison predicted the role of radiologists eventually will go beyond simply supplying and interpreting the images. The Carol D and Henry P Pendergrass Professor, chair of the radiology and radiological science department, and a professor of biomedical engineering at Vanderbilt University Medical Center and School of Medicine in Nashville, Tennessee, addressed the imminent dangers of climate change and radiology's role in both contributing to and helping alleviate those dangers. [...]what was once meant to protect physicians will become a major threat to radiologists over the next several years, says Mark E Schweitzer, MD, vice president of health affairs at Wayne State University in Detroit, Michigan.

Computed tomography findings and clinical evidence of improvement in coronavirus disease 2019 infection after convalescent plasma therapy in a critically ill patient

The spread of severe acute respiratory syndrome coronavirus 2 worldwide has created a major threat to human life and safety. Antiviral drugs and antibiotics have poor therapeutic effects, and there is no specific treatment for this virus. Chest computed tomography (CT) plays an important role in the diagnosis and management of coronavirus disease 2019 (COVID-19). We report a patient who was critically ill with COVID-19 and recovered after receiving transfusions of convalescent plasma. To evaluate the efficacy of convalescent plasma in the treatment of COVID-19, we compared chest CT findings, clinical manifestations, and laboratory findings before and after treatment with convalescent plasma. After the transfusion of convalescent plasma, clinical manifestations and indicators of inflammation improved, accompanied by an increase in the partial pressure of oxygen and oxygen saturation. Chest CT showed some resolution of the lung lesions, and multiple viral nucleic acid tests were negative. Therefore, the patient's condition was improved after the transfusion of convalescent plasma, suggesting that it may be an effective treatment for patients who are critically ill with COVID-19.

Death probability analysis in the old aged population and smokers in India owing to COVID-19

OBJECTIVE: Research has shown that older people and smokers have a higher death probability from coronavirus disease 2019 (COVID-19). Thus, we investigated the effect of COVID-19 on death probability for individuals aged 65–70 years and smokers in India. MATERIALS AND METHODS: We did so using a differential learning (feed-backward) model. In the present study, we examined World Health Organization (WHO) declared COVID-19 data of India. We divided the patients into two groups accordingly: the population aged 65–70 years and female or male smokers. RESULTS: We observed that in the early stages of infection (up to 5 days), there was higher death probability in the older population;among smokers, it occurred in the middle period after infection (5–8 days). We estimated that the death probability among smokers was 1.905 times that of the older population. CONCLUSION: As Government of India, taking various initiatives to curb the spread of COVID-19, but these are not enough, so we suggest measures that should help to reduce COVID-19 infection in India.

Rural disparities in head and neck cancer from 2017 to 2021: a single institution analysis

Introduction:This study aims to look at the trends in our head and neck cancer patient population over the past 5 years with an emphasis on the past 2 years to evaluate how the coronavirus disease 2019 (COVID-19) pandemic has impacted our disparities and availability of care for patients, especially those living in rural areas. An additional aim is to identify existing disparities at our institution in the treatment of head and neck patients and determine solutions to improve patient care.Materials and Methods:A retrospective chart review was performed to identify patients who were consulted and subsequently treated with at least one fraction of radiation therapy at our institution with palliative or curative intent. Patient demographic information was collected including hometown, distance from the cancer centre based on zip-codes and insurance information and type of appointment (in-person or telehealth). Rural–urban continuum codes were used to determine rurality.Results:A total of 490 head and neck cancer patients (n = 490) were treated from 2017 to 2021. When broken down by year, there were no significant trends in patient population regarding travel distance or rurality. Roughly 20–30% of our patients live in rural areas and about 30% have a commute > 50 miles for radiation treatment. A majority of our patients rely on public insurance (68%) with a small percentage of those uninsured (4%). Telehealth visits were rare prior to 2019 and rose to 5 and 2 visits in 2020 and 2021, respectively.Conclusions:Head and neck cancer patients, despite rurality or distance from a cancer centre, may present with alarmingly enough symptoms despite limitations and difficulties with seeking medical attention even during the COVID-19 pandemic in 2020. However, providers must be aware of these potential disparities that exist in the rural population and seek to address these.

The use of emoji to establish student wellbeing: does the image reflect the reality?

Introduction:The impact of COVID-19 social restrictions on mental wellbeing of health professional students during placement is largely unknown. Conventional survey methods do not capture emotional fluctuations. Increasing use of smartphones suggests short message service (SMS) functionality could provide easy, rapid data. This project tested the feasibility and validity of gathering data on Therapeutic Radiography student mental wellbeing during clinical placement via emoji and SMS.Methods:Participants provided anonymous daily emoji responses via WhatsApp to a dedicated mobile phone. Additional weekly prompts sought textual responses indicating factors impacting on wellbeing. A short anonymous online survey validated responses and provided feedback on the method.Results:Participants (n = 15) provided 254 daily responses using 108 different emoji;these triangulated with weekly textual responses. Feedback concerning the method was positive. ‘Happy’ emoji were used most frequently;social interaction and fatigue were important wellbeing factors. Anonymity and opportunity to feedback via SMS were received positively;ease and rapidity of response engendered engagement throughout the 3-week study.Conclusions:The use of emoji for rapid assessment of cohort mental wellbeing is valid and potentially useful alongside more formal evaluation and support strategies. Capturing simple wellbeing responses from a cohort may facilitate the organisation of timely support interventions.

Ultrahypofractionated breast radiotherapy during SARS-CoV-2 virus pandemic, beyond fast-forward trial: a local experience

Background:During the SARS-CoV-2 virus pandemic, University Hospital Birmingham NHS Trust Oncology Department incorporated the ultrahypofractionated regime of 26Gy/5 fractions alongside the moderate hypofractionated regime of 40Gy/15 fractions as part of local adjuvant breast radiotherapy treatment (RT) for eligible patients. We conducted a local study to assess the real-life experience of patients undergoing ultrahypofractionated schedule to compare feasibility and toxicity to the fast-forward trial during the COVID − 19 pandemic.Methods:A single institution, retrospective, qualitative study. Patients included had early-stage breast cancer and received adjuvant radiotherapy between 23 March 2020 and 31 May 2020, a total of 211 patients. Inclusion was irrespective of any other neoadjuvant/adjuvant treatments. Data were collected retrospectively for treatment dose, boost dose and toxicity.Results:Of the total 211 patients, 85 were treated with 26Gy in 5# and 19 patients received a boost as per the fast-forward protocol. Of these 85 patients, 15·9% did not report any skin toxicity post-treatment. 63·5% of patients reported RTOG Grade 1, 15·9% had RTOG Grade 2, and 1·6% reported RTOG Grade 3 skin toxicity. 3·2% of the patients could not be contacted for follow-up. Of the 19 patients who received a breast boost, 10·53% reported no skin changes. 78·9% reported Grade 1 skin toxicity. Both Grades 2a and 2b skin toxicity were reported by 5·26% each. The patient demographics and tumour characteristics in our study cohort were comparable to those within the fast-forward trial. In terms of post-RT skin toxicity, fewer patients reported any toxicity in the UHB patient cohort versus those in the trial, and the number of Grade 2/3 toxicities reported was also low. A delay in toxicity reporting from 2 weeks for 40Gy/15 to 3 weeks for 26Gy/5 was observed.Conclusion:Our study concluded that offering ultrahypofractionation was convenient for patients;reducing the number of hospital visits during the SARS-CoV-2 virus pandemic appeared safe in terms of acute post-RT-related skin toxicity. The reduced hospital visits limited exposure of patients and staff to the SARS-CoV-2 virus while also ensuring efficient use of Radiotherapy Department resources. Local follow-up protocols have been amended to ensure review at 3 weeks for the 26Gy/5 schedule to acknowledge the delay in acute toxicity development. To date, there is only 5-year toxicity and relapse data available from the fast-forward trial;therefore, hypofractionation schedules should be offered to patients as long as they fulfil the criteria and understand the limitations of the study as well as accelerated peer review processes in the face of the pandemic.

A narrative review exploring the professional practice training requirement of therapeutic radiographers undertaking effective remote/telephone review clinics in place of face-to-face radiographer-led review clinics during the COVID-19 pandemic

Background and purpose:The COVID-19 pandemic has led to the introduction of alternative on-treatment and post-treatment radiographer-led review clinics in an attempt to protect patients, staff and the public. Pre-COVID, patient reviews were routinely undertaken face-to-face, led by therapeutic review radiographers with advanced practice qualifications and skills in radiotherapy symptom management, triage, referral and support services. During the COVID-19 pandemic, an alternative option has been to follow-up in the form of telephone reviews to reduce face-to-face exposure whilst continuing to manage patient radiotherapy treatment-related toxicities. The aim of the narrative review is to explore the subject of telephone reviews and how therapeutic review radiographers might need to adapt communication skills so that they can continue to effectively assess and manage radiotherapy patient treatment reactions remotely.Method and discussion:A narrative review was conducted using the SCOPUS database and 28 publications were included from 2013 to 2021. The review highlights a paucity of literature exploring specific telephone training for radiographers and other allied healthcare professionals. Experiences within medical and nursing programmes demonstrate that development and integration of training in this area is critical in preparing for patient interaction via telephone.Conclusion and implications for practice:Multiple teaching modalities including simulation are ideal for teaching telephone-specific skills and content, demonstrating improvement in student knowledge, competence and confidence. Less is known regarding whether this knowledge translates to an improved patient experience. Enhancements in education and training, guided by the Health and Care Professions Council, may be warranted to ensure that patients continue to receive the optimal quality of care in a world where remote reviews are likely to become commonplace. Patient-reported outcome measures might be utilized for future training evaluations to ensure that effective patient care is being maintained.

Diagnostic value of ground-glass opacity in suspected coronavirus disease 2019 patients: A meta-analysis

OBJECTIVE: The aim of the study was to evaluate the diagnostic efficiency of ground-glass opacity (GGO) for coronavirus disease 2019 (COVID-19) in suspected patients. MATERIALS AND METHODS: In this systematic review and meta-analysis, PubMed, Embase, Cochrane Library, Scopus, Web of Science, CNKI, and Wanfang databases were searched from November 01, 2019 to November 29, 2020. Studies providing the diagnostic test accuracy of chest computed tomography (CT) and description of detailed CT features for COVID-19 were included. Data were extracted from the publications. The sensitivity, specificity, and summary receiver operating characteristic curves were pooled. Heterogeneity was detected across included studies. RESULTS: Eleven studies with 1618 cases were included. The pooled sensitivity, specificity and area under the curve were 0.74 (95% confidence interval [CI], 0.61–0.84), 0.52 (95% CI, 0.33–0.70), and 0.70 (95% CI, 0.66–0.74), respectively. There was obvious heterogeneity among included studies (P < 0.05). Differences in the study region, inclusion criteria, research quality, or research methods might have contributed to the heterogeneity. The included studies had no significant publication bias (P > 0.1). CONCLUSIONS: COVID-19 was diagnosed not only by GGO with a medium level of diagnostic accuracy but also by white blood cell counts, epidemic history, and revers transcription-polymerase chain reaction testing.

An artificial intelligence-based radiomics model for differential diagnosis between coronavirus disease 2019 and other viral pneumonias

OBJECTIVE: To set up a differential diagnosis radiomics model to identify coronavirus disease 2019 (COVID-19) and other viral pneumonias based on an artificial intelligence (AI) approach that utilizes computed tomography (CT) images. MATERIALS AND METHODS: This retrospective multi-center research involved 225 patients with COVID-19 and 265 patients with other viral pneumonias. The least absolute shrinkage and selection operator algorithm was used for the optimized features selection from 1218 radiomics features. Finally, a logistic regression (LR) classifier was applied to construct different diagnosis models. The receiver operating characteristic curve analysis was applied to evaluate the accuracy of different models. RESULTS: The patients were divided into a training set (313 of 392, 80%), an internal test set (79 of 392, 20%) and an external test set (n = 98). Thirteen features were selected to build the machine learning-based CT radiomics models. LR classifiers performed well in the training set (area under the curve [AUC] = 0.91), internal test set (AUC = 0.94), and external test set (AUC = 0.91). Delong tests suggested there was no significant difference between training and the two test sets (P > 0.05). CONCLUSION: The use of an AI-based radiomics model enables rapid discrimination of patients with COVID-19 from other viral infections, which can aid better surveillance and control during a pneumonia outbreak.

Lesion types, pathogenesis, pathological manifestations, and imaging findings of cardiovascular complications induced by coronavirus disease 2019: Current status

The coronavirus disease 2019 (COVID-19) has formed a worldwide pandemic trend. Despite the virus usually invades lungs and presents with various respiratory symptoms, it can also affect the cardiac function in multiple ways and result in high mortality. Various possible mechanisms have been proposed to explain these manifestations at present, including cytokine storm and direct invasion of the virus. There are a series of feasible schemes in clinical work to reduce the incidence of complications now, but the layered management of hospitalized patients, the early prevention, and the early detection of complications seem to be more important. Cardiac imaging examinations (such as computed tomography coronary angiography, magnetic resonance imaging multi-parameter scan, and enhanced scan, etc.) are very essential in these aspects. However, radiological data of the cardiac complications are not comprehensive enough in accessing the prognosis due to the limitation of examination. This paper summarized the imaging findings of cardiac complications of COVID-19, providing the possible morphological basis or hypothesis for cardiac multimode imaging by analyzing the pathological manifestations retrospectively.

CT quantitative analysis in patients with severe coronavirus disease 2019 and its correlation with laboratory examination results

OBJECTIVE: To quantitatively analyze the longitudinal changes of ground-glass opacity (GGO), consolidation and total lesion in patients infected with severe coronavirus disease 2019 (COVID-19), and its correlation with laboratory examination results. MATERIALS AND METHODS: All 76 computed tomography (CT) images and laboratory examination results from the admission to discharge of 15 patients confirmed with severe COVID-19 were reviewed, whereas the GGO volume ratio, consolidation volume ratio, and total lesion volume ratio in different stages were analyzed. The correlations of lesions volume ratio and laboratory examination results were investigated. RESULTS: Four stages were identified based on the degree of lung involvement from day 1 to day 28 after disease onset. GGO was the most common CT manifestation in the four stages. The peak of lung involvement was at around stage 2, and corresponding total lesion volume ratio, GGO volume ratio, and consolidation volume ratio were 17.48 (13.44−24.33), 12.11 (7.34−17.08), and 5.51 (2.58−8.58), respectively. Total lesion volume ratio was positively correlated with neutrophil percentage, C-reactive protein (CRP), high-sensitivity CRP (Hs-CRP), procalcitonin, lactate dehydrogenase (LD), and creatine kinase isoenzyme MB (CK-MB), but negatively correlated with lymphocyte count, lymphocyte percentage, arterial oxygen saturation, and arterial oxygen tension. Consolidation volume ratio was correlated with most above laboratory examination results except Hs-CRP, LD, and CK-MB. GGO, however, was only correlated with lymphocyte count. CONCLUSION: CT quantitative parameters could show longitudinal changes well. Total lesion volume ratio and consolidation volume ratio are well correlated with laboratory examination results, suggesting that CT quantitative parameters may be an effective tool to reflect the changes in the condition.