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1.
AJR Am J Roentgenol ; 220(5): 672-680, 2023 05.
Article in English | MEDLINE | ID: covidwho-20239781

ABSTRACT

BACKGROUND. Prior work has shown improved image quality for photon-counting detector (PCD) CT of the lungs compared with energy-integrating detector CT. A paucity of the literature has compared PCD CT of the lungs using different reconstruction parameters. OBJECTIVE. The purpose of this study is to the compare the image quality of ultra-high-resolution (UHR) PCD CT image sets of the lungs that were reconstructed using different kernels and slice thicknesses. METHODS. This retrospective study included 29 patients (17 women and 12 men; median age, 56 years) who underwent noncontrast chest CT from February 15, 2022, to March 15, 2022, by use of a commercially available PCD CT scanner. All acquisitions used UHR mode (1024 × 1024 matrix). Nine image sets were reconstructed for all combinations of three sharp kernels (BI56, BI60, and BI64) and three slice thicknesses (0.2, 0.4, and 1.0 mm). Three radiologists independently reviewed reconstructions for measures of visualization of pulmonary anatomic structures and pathologies; reader assessments were pooled. Reconstructions were compared with the clinical reference reconstruction (obtained using the BI64 kernel and a 1.0-mm slice thickness [BI641.0-mm]). RESULTS. The median difference in the number of bronchial divisions identified versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.5), BI600.4-mm (0.3), BI640.2-mm (0.5), and BI600.2-mm (0.2) (all p < .05). The median bronchial wall sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3) and BI640.2-mm (0.3) and was lower for BI561.0-mm (-0.7) and BI560.4-mm (-0.3) (all p < .05). Median pulmonary fissure sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3), BI600.4-mm (0.3), BI560.4-mm (0.5), BI640.2-mm (0.5), BI600.2-mm (0.5), and BI560.2-mm (0.3) (all p < .05). Median pulmonary vessel sharpness versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3), BI600.4-mm (-0.3), BI560.4-mm (-0.7), BI640.2-mm (-0.7), BI600.2-mm (-0.7), and BI560.2-mm (-0.7). Median lung nodule conspicuity versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3) and BI560.4-mm (-0.3) (both p < .05). Median conspicuity of all other pathologies versus the clinical reference reconstruction was lower for reconstructions with BI561.0 mm (-0.3), BI560.4-mm (-0.3), BI640.2-mm (-0.3), BI600.2-mm (-0.3), and BI560.2-mm (-0.3). Other comparisons among reconstructions were not significant (all p > .05). CONCLUSION. Only the reconstruction using BI640.4-mm yielded improved bronchial division identification and bronchial wall and pulmonary fissure sharpness without a loss in pulmonary vessel sharpness or conspicuity of nodules or other pathologies. CLINICAL IMPACT. The findings of this study may guide protocol optimization for UHR PCD CT of the lungs.


Subject(s)
Lung , Tomography, X-Ray Computed , Male , Humans , Female , Middle Aged , Retrospective Studies , Phantoms, Imaging , Tomography, X-Ray Computed/methods , Lung/diagnostic imaging , Bronchi
2.
Head Neck ; 45(8): 1979-1985, 2023 Aug.
Article in English | MEDLINE | ID: covidwho-20233770

ABSTRACT

BACKGROUND: To evaluate the impact of coronavirus disease 2019 (COVID-19) pandemic on disease extent in patients with nasopharyngeal carcinoma (NPC) using 18 fuorodeoxyglucose (FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI). METHODS: This retrospective cohort study included biopsy-proven, newly diagnosed NPC patients using whole-body FDG PET/MR staging in two selected intervals: 1 May 2017 to 31 January 2020 (Group A, the pre-COVID-19 period), and 1 February 2020 to 30 June 2021 (Group B, the COVID-19 period). RESULTS: Three-hundred and ninety patients were included. No significant difference was observed in terms of T classification, N classification, overall stage, N stations, and M stations between the two groups (p > 0.05). For the involved neck node levels, more patients had developed level Vc metastasis in the group B (p = 0.044). CONCLUSION: Although the overall stage was not affected, more patients with NPC had developed level Vc metastasis in the era of COVID-19.


Subject(s)
COVID-19 , Nasopharyngeal Neoplasms , Humans , Nasopharyngeal Carcinoma/diagnostic imaging , Nasopharyngeal Carcinoma/pathology , Fluorodeoxyglucose F18 , Pandemics , Retrospective Studies , Nasopharyngeal Neoplasms/pathology , Tomography, X-Ray Computed/methods , Neoplasm Staging , Positron-Emission Tomography/methods , Magnetic Resonance Imaging , Radiopharmaceuticals
3.
PLoS One ; 18(6): e0286395, 2023.
Article in English | MEDLINE | ID: covidwho-20232835

ABSTRACT

PURPOSE: This retrospective study investigated the correlation between bone mineral density (BMD) and COVID-19 severity among COVID-19 patients who underwent chest computed tomography (CT) scans. METHODS: This study was carried out at the King Abdullah Medical Complex in Jeddah, Saudi Arabia, one of the largest COVID-19 centers in the western province. All adult COVID-19 patients who had a chest CT between January 2020 and April 2022 were included in the study. The pulmonary severity scores (PSS) and vertebral BMD measurements were obtained from the patient's CT chest. Data from the patients' electronic records were collected. RESULTS: The average patient age was 56.4 years, and most (73.5%) patients were men. Diabetes (n = 66, 48.5%), hypertension (n = 56, 41.2%), and coronary artery disease (n = 17, 12.5%) were the most prevalent comorbidities. Approximately two-thirds of hospitalized patients required ICU admission (64%), and one-third died (30%). The average length of stay in the hospital was 28.4 days. The mean CT pneumonia severity score (PSS) was 10.6 at the time of admission. Patients with lower vertebral BMD (< = 100) numbered 12 (8.8%), while those with higher vertebral BMD (>100) numbered 124 (91.2%). Only 46 out of the total survived patients (n = 95) were admitted to the ICU versus all deceased (P<0.01). The logistic regression analysis revealed that an elevated PSS upon admission resulted in a reduced chance of survival. Age, gender, and BMD did not predict survival chances. CONCLUSION: The BMD had no prognostic advantage, and the PSS was the significant factor that could have predicted the outcome.


Subject(s)
COVID-19 , Male , Adult , Humans , Middle Aged , Female , COVID-19/diagnostic imaging , Bone Density , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
4.
Clin Lab ; 69(6)2023 Jun 01.
Article in English | MEDLINE | ID: covidwho-20245311

ABSTRACT

BACKGROUND: Lymphopenia and high CT score is associated with COVID-19 severity. Herein we describe the change pattern in lymphocyte count and CT score during hospitalization and explore a possible association with the severity of COVID-19. METHODS: In this retrospective study, 13 non-severe COVID-19 patients diagnosed at admission were enrolled. One patient progressed to severe disease. Change patterns in lymphocyte counts and CT scores of all patients were analyzed. RESULTS: Lymphocyte count increased gradually from day 5 post-illness onset (day 5 vs. day 15, p = 0.001). Lymphocyte count of the severe patient fluctuated at low levels throughout the 15-day period. Chest CT scores of non-severe patients increased significantly during the first 5 days of illness onset, but decreased gradually beginning day 9 (illness onset vs. day 5, p = 0.002, day 9 vs. day 15, p = 0.015). In the severe patient, CT score continued to increase over the 11 days post-illness onset period. CONCLUSIONS: Non-severe COVID-19 patients had significantly increased lymphocyte counts and decreased CT scores beginning day 5 and day 9 of illness onset, respectively. The patients without increased lymphocyte counts and decreased CT scores during the early 2nd week of illness onset may develop to severe COVID-19.


Subject(s)
COVID-19 , Humans , Retrospective Studies , Hospitalization , Lymphocyte Count , Tomography, X-Ray Computed
5.
J Int Med Res ; 51(6): 3000605231177187, 2023 Jun.
Article in English | MEDLINE | ID: covidwho-20244292

ABSTRACT

OBJECTIVE: To investigate characteristics that may be associated with radiologic and functional findings following discharge in patients with severe coronavirus disease 2019 (COVID-19). METHODS: This single-center, prospective, observational cohort study comprised patients aged >18 years who were hospitalized with COVID-19 pneumonia, between May and October 2020. After 3 to 6 months of discharge, patients were clinically evaluated and underwent spirometry, a 6-minute walk test (6MWT), and chest computed tomography (CT). Statistical analysis was performed using association and correlation tests. RESULTS: A total of 134 patients were included (25/114 [22%] were admitted with severe hypoxemia). On the follow-up chest CT, 29/92 (32%) had no abnormalities, regardless of the severity of the initial involvement, and the mean 6MWT distance was 447 m. Patients with desaturation on admission had an increased risk of remaining CT abnormalities: patients with SpO2 between 88 and 92% had a 4.0-fold risk, and those with SpO2 < 88% had a 6.2-fold risk. The group with SpO2 < 88% also walked shorter distances than patients with SpO2 between 88 and 92%. CONCLUSION: Initial hypoxemia was found to be a good predictor of persistent radiological abnormalities in follow-up and was associated with low performance in 6MWT.


Subject(s)
COVID-19 , Humans , Prospective Studies , Oximetry , Hypoxia/diagnostic imaging , Tomography, X-Ray Computed
6.
Sci Rep ; 13(1): 8516, 2023 05 25.
Article in English | MEDLINE | ID: covidwho-20243375

ABSTRACT

COVID-19, a global pandemic, has killed thousands in the last three years. Pathogenic laboratory testing is the gold standard but has a high false-negative rate, making alternate diagnostic procedures necessary to fight against it. Computer Tomography (CT) scans help diagnose and monitor COVID-19, especially in severe cases. But, visual inspection of CT images takes time and effort. In this study, we employ Convolution Neural Network (CNN) to detect coronavirus infection from CT images. The proposed study utilized transfer learning on the three pre-trained deep CNN models, namely VGG-16, ResNet, and wide ResNet, to diagnose and detect COVID-19 infection from the CT images. However, when the pre-trained models are retrained, the model suffers the generalization capability to categorize the data in the original datasets. The novel aspect of this work is the integration of deep CNN architectures with Learning without Forgetting (LwF) to enhance the model's generalization capabilities on both trained and new data samples. The LwF makes the network use its learning capabilities in training on the new dataset while preserving the original competencies. The deep CNN models with the LwF model are evaluated on original images and CT scans of individuals infected with Delta-variant of the SARS-CoV-2 virus. The experimental results show that of the three fine-tuned CNN models with the LwF method, the wide ResNet model's performance is superior and effective in classifying original and delta-variant datasets with an accuracy of 93.08% and 92.32%, respectively.


Subject(s)
COVID-19 , Humans , COVID-19/diagnostic imaging , SARS-CoV-2 , Computers , Machine Learning , Tomography, X-Ray Computed
7.
Sensors (Basel) ; 23(11)2023 Jun 03.
Article in English | MEDLINE | ID: covidwho-20242759

ABSTRACT

Coronavirus disease 2019 (COVID-19) has seen a crucial outburst for both females and males worldwide. Automatic lung infection detection from medical imaging modalities provides high potential for increasing the treatment for patients to tackle COVID-19 disease. COVID-19 detection from lung CT images is a rapid way of diagnosing patients. However, identifying the occurrence of infectious tissues and segmenting this from CT images implies several challenges. Therefore, efficient techniques termed as Remora Namib Beetle Optimization_ Deep Quantum Neural Network (RNBO_DQNN) and RNBO_Deep Neuro Fuzzy Network (RNBO_DNFN) are introduced for the identification as well as classification of COVID-19 lung infection. Here, the pre-processing of lung CT images is performed utilizing an adaptive Wiener filter, whereas lung lobe segmentation is performed employing the Pyramid Scene Parsing Network (PSP-Net). Afterwards, feature extraction is carried out wherein features are extracted for the classification phase. In the first level of classification, DQNN is utilized, tuned by RNBO. Furthermore, RNBO is designed by merging the Remora Optimization Algorithm (ROA) and Namib Beetle Optimization (NBO). If a classified output is COVID-19, then the second-level classification is executed using DNFN for further classification. Additionally, DNFN is also trained by employing the newly proposed RNBO. Furthermore, the devised RNBO_DNFN achieved maximum testing accuracy, with TNR and TPR obtaining values of 89.4%, 89.5% and 87.5%.


Subject(s)
COVID-19 , Coleoptera , Deep Learning , Perciformes , Pneumonia , Female , Male , Animals , COVID-19/diagnostic imaging , Fishes , Tomography, X-Ray Computed , Lung/diagnostic imaging
8.
Rev Assoc Med Bras (1992) ; 69(5): e20221427, 2023.
Article in English | MEDLINE | ID: covidwho-20242292

ABSTRACT

OBJECTIVE: This study aimed to investigate if there is any correlation between the quantitative computed tomography and the impulse oscillometry or spirometry results of post-COVID-19 patients. METHODS: The study comprised 47 post-COVID-19 patients who had spirometry, impulse oscillometry, and high-resolution computed tomography examinations at the same time. The study group consisted of 33 patients with quantitative computed tomography involvement, while the control group included 14 patients who did not have CT findings. The quantitative computed tomography technology was used to calculate percentages of density range volumes. The relationship between percentages of density range volumes for different quantitative computed tomography density ranges and impulse oscillometry-spirometry findings was statistically analyzed. RESULTS: In quantitative computed tomography, the percentage of relatively high-density lung parenchyma, including fibrotic areas, was 1.76±0.43 and 5.65±3.73 in the control and study groups, respectively. The percentages of primarily ground-glass parenchyma areas were found to be 7.60±2.86 and 29.25±16.50 in the control and study groups, respectively. In the correlation analysis, the forced vital capacity% predicted in the study group was correlated with DRV%[(-750)-(-500)] (volume of the lung parenchyma that has density between (-750)-(-500) Hounsfield units), but no correlation with DRV%[(-500)-0] was detected. Also, reactance area and resonant frequency were correlated with DRV%[(-750)-(-500)], while X5 was correlated with both DRV%[(-500)-0] and DRV%[(-750)-(-500)] density. Modified Medical Research Council score was correlated with predicted percentages of forced vital capacity and X5. CONCLUSION: After COVID-19, forced vital capacity, reactance area, resonant frequency, and X5 correlated with the percentages of density range volumes of ground-glass opacity areas in the quantitative computed tomography. X5 was the only parameter correlated with density ranges consistent with both ground-glass opacity and fibrosis. Furthermore, the percentages of forced vital capacity and X5 were shown to be associated with the perception of dyspnea.


Subject(s)
COVID-19 , Humans , Oscillometry , Spirometry , Thorax , Tomography, X-Ray Computed
9.
West J Emerg Med ; 23(4): 497-504, 2022 Jun 05.
Article in English | MEDLINE | ID: covidwho-20242018

ABSTRACT

Point-of-care lung ultrasonography is an evidence-based application that may play a vital role in the care of critically ill pediatric patients. Lung ultrasonography has the advantage of being available at the patient's bedside with results superior to chest radiography and comparable to chest computed tomography for most lung pathologies. It has a steep learning curve. It can be readily performed in both advanced healthcare systems and resource-scarce settings. The purpose of this review is to discuss the basic principles of lung ultrasonography and its applications in the evaluation and treatment of critically ill pediatric patients.


Subject(s)
Critical Illness , Point-of-Care Systems , Child , Humans , Lung/diagnostic imaging , Tomography, X-Ray Computed , Ultrasonography/methods
10.
Am J Gastroenterol ; 115(8): 1286-1288, 2020 08.
Article in English | MEDLINE | ID: covidwho-2324863

ABSTRACT

INTRODUCTION: Although coronavirus disease (COVID-19) has been associated with gastrointestinal manifestations, its effect on the pancreas remains unclear. We aimed to assess the frequency and characteristics of hyperlipasemia in patients with COVID-19. METHODS: A retrospective cohort study of hospitalized patients across 6 US centers with COVID-19. RESULTS: Of 71 patients, 9 (12.1%) developed hyperlipasemia, with 2 (2.8%) greater than 3 times upper limit of normal. No patient developed acute pancreatitis. Hyperlipasemia was not associated with poor outcomes or symptoms. DISCUSSION: Although a mild elevation in serum lipase was observed in some patients with COVID-19, clinical acute pancreatitis was not seen.


Subject(s)
Coronavirus Infections/epidemiology , Lipase/blood , Pancreatitis/epidemiology , Pneumonia, Viral/epidemiology , Abdominal Pain/epidemiology , Aged , Aged, 80 and over , Anorexia/epidemiology , Betacoronavirus , COVID-19 , Cohort Studies , Coronavirus Infections/blood , Diarrhea/epidemiology , Female , Humans , Male , Middle Aged , Nausea/epidemiology , Pancreatitis/blood , Pancreatitis/diagnostic imaging , Pandemics , Pneumonia, Viral/blood , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed , United States/epidemiology , Vomiting/epidemiology
11.
JBJS Case Connect ; 13(2)2023 04 01.
Article in English | MEDLINE | ID: covidwho-2324830

ABSTRACT

CASE: A 4-year-old girl sustained a traumatic atlantoaxial rotatory subluxation. She presented at the treating facility 8 months after injury with cervical deformity, neck pain, gait instability, and decreased cervical motion. Her delay in presentation was partially because of international Corona Virus of 2019 (COVID-19) travel restrictions. The case was successfully treated with halo traction, followed by halo vest immobilization. CONCLUSION: Chronic atlantoaxial rotatory fixation can be treated nonsurgically with closed reduction and halo traction, but is associated with operative risks. Optimal pin placement is challenging in the pediatric skull and may be improved with a preoperative or intraoperative computed tomography (CT) scan.


Subject(s)
COVID-19 , Joint Dislocations , Female , Child , Humans , Child, Preschool , Traction/methods , COVID-19/complications , Tomography, X-Ray Computed , Joint Dislocations/surgery , Neck Pain
12.
Eur Rev Med Pharmacol Sci ; 27(9): 4085-4097, 2023 May.
Article in English | MEDLINE | ID: covidwho-2322908

ABSTRACT

OBJECTIVE: The aim of this study was to describe the Computed Tomography (CT) features of pulmonary embolism in patients hospitalized for acute COVID-19 pneumonia and to evaluate the prognostic significance of these features. PATIENTS AND METHODS: This retrospective study included 110 consecutive patients who were hospitalized for acute COVID-19 pneumonia and underwent pulmonary computed tomography angiography (BTPA) on the basis of clinical suspicion. The diagnosis of COVID-19 infection was determined by CT findings typical of COVID-19 pneumonia and/or a positive result of a reverse transcriptase-polymerase chain reaction test. RESULTS: Of the 110 patients, 30 (27.3%) had acute pulmonary embolism and 71 (64.5%) had CT features of chronic pulmonary embolism. Of the 14 (12.7%) patients who died despite receiving therapeutic doses of heparin, 13 (92.9%) had CT features of chronic pulmonary embolism and 1 (7.1%) of acute pulmonary embolism. CT features of chronic pulmonary embolism were more common in deceased patients than in surviving patients (92.9% vs. 60.4%, p=0.01, respectively). Low oxygen saturation and high urine microalbumin creatinine ratio at admission in COVID-19 patients are important determinants of mortality after adjusting for sex and age in logistic procedures. CONCLUSIONS: CT features of chronic pulmonary embolism are common in COVID-19 patients undergoing Computed Tomography Pulmonary Angiography (CTPA) in the hospital. The coexistence of albuminuria, low oxygen saturation and CT features of chronic pulmonary embolism at admission in COVID-19 patients may herald fatal outcomes.


Subject(s)
COVID-19 , Pulmonary Embolism , Humans , COVID-19/complications , COVID-19/diagnostic imaging , Retrospective Studies , Pulmonary Embolism/diagnostic imaging , Tomography, X-Ray Computed , Lung/diagnostic imaging , Acute Disease
13.
Tomography ; 9(3): 981-994, 2023 05 11.
Article in English | MEDLINE | ID: covidwho-2322229

ABSTRACT

Elevated inflammatory markers are associated with severe coronavirus disease 2019 (COVID-19), and some patients benefit from Interleukin (IL)-6 pathway inhibitors. Different chest computed tomography (CT) scoring systems have shown a prognostic value in COVID-19, but not specifically in anti-IL-6-treated patients at high risk of respiratory failure. We aimed to explore the relationship between baseline CT findings and inflammatory conditions and to evaluate the prognostic value of chest CT scores and laboratory findings in COVID-19 patients specifically treated with anti-IL-6. Baseline CT lung involvement was assessed in 51 hospitalized COVID-19 patients naive to glucocorticoids and other immunosuppressants using four CT scoring systems. CT data were correlated with systemic inflammation and 30-day prognosis after anti-IL-6 treatment. All the considered CT scores showed a negative correlation with pulmonary function and a positive one with C-reactive protein (CRP), IL-6, IL-8, and Tumor Necrosis Factor α (TNF-α) serum levels. All the performed scores were prognostic factors, but the disease extension assessed by the six-lung-zone CT score (S24) was the only independently associated with intensive care unit (ICU) admission (p = 0.04). In conclusion, CT involvement correlates with laboratory inflammation markers and is an independent prognostic factor in COVID-19 patients representing a further tool to implement prognostic stratification in hospitalized patients.


Subject(s)
COVID-19 , Lung , Receptors, Interleukin-6 , Humans , COVID-19/diagnostic imaging , Cytokines , Inflammation , Lung/diagnostic imaging , Lung/pathology , Prognosis , Receptors, Interleukin-6/antagonists & inhibitors , Retrospective Studies , Tomography, X-Ray Computed , COVID-19 Drug Treatment
14.
Emerg Radiol ; 27(6): 755-759, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-2317640

ABSTRACT

Neurological manifestations and complications are increasingly reported in coronavirus disease-19 (COVID-19) patients. Although pulmonary manifestations are more common, patients with severe disease may present with neurological symptoms such as in our case. We describe a case report of a 50-year-old male without previous known comorbidity who was found unresponsive due to COVID-19-related neurological complications. During this pandemic, an emergency radiologist should be well acquainted with various neurological manifestations of COVID-19. In this article, we will discuss the pathogenesis, imaging findings, and differentials of this disease.


Subject(s)
Brain Diseases/diagnostic imaging , Brain Diseases/virology , Coronavirus Infections/complications , Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Betacoronavirus , COVID-19 , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , SARS-CoV-2 , Tomography, X-Ray Computed
15.
Math Biosci Eng ; 20(6): 10954-10976, 2023 Apr 21.
Article in English | MEDLINE | ID: covidwho-2319238

ABSTRACT

For the problems of blurred edges, uneven background distribution, and many noise interferences in medical image segmentation, we proposed a medical image segmentation algorithm based on deep neural network technology, which adopts a similar U-Net backbone structure and includes two parts: encoding and decoding. Firstly, the images are passed through the encoder path with residual and convolutional structures for image feature information extraction. We added the attention mechanism module to the network jump connection to address the problems of redundant network channel dimensions and low spatial perception of complex lesions. Finally, the medical image segmentation results are obtained using the decoder path with residual and convolutional structures. To verify the validity of the model in this paper, we conducted the corresponding comparative experimental analysis, and the experimental results show that the DICE and IOU of the proposed model are 0.7826, 0.9683, 0.8904, 0.8069, and 0.9462, 0.9537 for DRIVE, ISIC2018 and COVID-19 CT datasets, respectively. The segmentation accuracy is effectively improved for medical images with complex shapes and adhesions between lesions and normal tissues.


Subject(s)
COVID-19 , Deep Learning , Humans , COVID-19/diagnostic imaging , Algorithms , Technology , Tomography, X-Ray Computed , Image Processing, Computer-Assisted
16.
Clin Med Res ; 21(1): 14-25, 2023 03.
Article in English | MEDLINE | ID: covidwho-2317722

ABSTRACT

Objective: We evaluated the triage and prognostic performance of seven proposed computed tomography (CT)-severity score (CTSS) systems in two different age groups.Design: Retrospective study.Setting: COVID-19 pandemic.Participants: Admitted COVID-19, PCR-positive patients were included, excluding patients with heart failure and significant pre-existing pulmonary disease.Methods: Patients were divided into two age groups: ≥65 years and ≤64 years. Clinical data indicating disease severity at presentation and at peak disease severity were recorded. Initial CT images were scored by two radiologists according to seven CTSSs (CTSS1-CTSS7). Receiver operating characteristic (ROC) analysis for the performance of each CTSS in diagnosing severe/critical disease on admission (triage performance) and at peak disease severity (prognostic performance) was done for the whole cohort and each age group separately.Results: Included were 96 patients. Intraclass correlation coefficient (ICC) between the two radiologists scoring the CT scan images were good for all the CTSSs (ICC=0.764-0.837). In the whole cohort, all CTSSs showed an unsatisfactory area under the curve (AUC) in the ROC curve for triage, excluding CTSS2 (AUC=0.700), and all CTSSs showed acceptable AUCs for prognostic usage (0.759-0.781). In the older group (≥65 years; n=55), all CTSSs excluding CTSS6 showed excellent AUCs for triage (0.804-0.830), and CTSS6 was acceptable (AUC=0.796); all CTSSs showed excellent or outstanding AUCs for prognostication (0.859-0.919). In the younger group (≤64 years; n=41), all CTSSs showed unsatisfactory AUCs for triage (AUC=0.487-0.565) and prognostic usage (AUC=0.668-0.694), excluding CTSS6, showing marginally acceptable AUC for prognostic performance (0.700).Conclusion: Those CTSSs requiring more numerous segmentations, namely CTSS2, CTSS7, and CTSS5 showed the best ICCs; therefore, they are the best when comparison between two separate scores is needed. Irrespective of patients' age, CTSSs show minimal value in triage and acceptable prognostic value in COVID-19 patients. CTSS performance is highly variable in different age groups. It is excellent in those aged ≥65 years, but has little if any value in younger patients. Multicenter studies with larger sample size to evaluate results of this study should be conducted.


Subject(s)
COVID-19 , Humans , Aged , COVID-19/diagnostic imaging , Retrospective Studies , Triage/methods , Prognosis , Pandemics , Tomography, X-Ray Computed/methods
17.
Eur Radiol ; 33(6): 4280-4291, 2023 Jun.
Article in English | MEDLINE | ID: covidwho-2317195

ABSTRACT

OBJECTIVES: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiological diagnosis and the impact on relevant parameters such as accuracy of the diagnosis, diagnostic time, and confidence. METHODS: We included n = 1591 multicenter, multivendor chest CT scans and divided them into AI training and validation datasets to develop an AI algorithm (n = 991 CT scans; n = 462 COVID-19, and n = 529 CAP) from three centers in China. An independent Chinese and German test dataset of n = 600 CT scans from six centers (COVID-19 / CAP; n = 300 each) was used to test the performance of eight blinded radiologists and the AI algorithm. A subtest dataset (180 CT scans; n = 90 each) was used to evaluate the radiologists' performance without and with AI assistance to quantify changes in diagnostic accuracy, reporting time, and diagnostic confidence. RESULTS: The diagnostic accuracy of the AI algorithm in the Chinese-German test dataset was 76.5%. Without AI assistance, the eight radiologists' diagnostic accuracy was 79.1% and increased with AI assistance to 81.5%, going along with significantly shorter decision times and higher confidence scores. CONCLUSION: This large multicenter study demonstrates that AI assistance in CT-based differentiation of COVID-19 and CAP increases radiological performance with higher accuracy and specificity, faster diagnostic time, and improved diagnostic confidence. KEY POINTS: • AI can help radiologists to get higher diagnostic accuracy, make faster decisions, and improve diagnostic confidence. • The China-German multicenter study demonstrates the advantages of a human-machine interaction using AI in clinical radiology for diagnostic differentiation between COVID-19 and CAP in CT scans.


Subject(s)
COVID-19 , Community-Acquired Infections , Deep Learning , Pneumonia , Humans , Artificial Intelligence , SARS-CoV-2 , Tomography, X-Ray Computed/methods , COVID-19 Testing
18.
Curr Oncol ; 30(4): 3817-3828, 2023 03 29.
Article in English | MEDLINE | ID: covidwho-2316151

ABSTRACT

The PACIFIC trial showed a survival benefit with durvalumab through five years in stage III unresectable non-small cell lung cancer (NSCLC). However, optimal use of imaging to detect disease progression remains unclearly defined for this population. An expert working group convened to consider available evidence and clinical experience and develop recommendations for follow-up imaging after concurrent chemotherapy and radiation therapy (CRT). Voting on agreement was conducted anonymously via online survey. Follow-up imaging was recommended for all suitable patients after CRT completion regardless of whether durvalumab is received. Imaging should occur every 3 months in Year 1, at least every 6 months in Year 2, and at least every 12 months in Years 3-5. Contrast computed tomography was preferred; routine brain imaging was not recommended for asymptomatic patients. The medical oncologist should follow-up during Year 1 of durvalumab therapy, with radiation oncologist involvement if pneumonitis is suspected; medical and radiation oncologists can subsequently alternate follow-up. Some patients can transition to the family physician/community primary care team at the end of Year 2. In Years 1-5, patients should receive information regarding smoking cessation, comorbidity management, vaccinations, and general follow-up care. These recommendations provide guidance on follow-up imaging for patients with stage III unresectable NSCLC whether or not they receive durvalumab consolidation therapy.


Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Carcinoma, Non-Small-Cell Lung/therapy , Carcinoma, Non-Small-Cell Lung/drug therapy , Lung Neoplasms/therapy , Lung Neoplasms/drug therapy , Follow-Up Studies , Chemoradiotherapy/methods , Neoplasm Staging , Tomography, X-Ray Computed
19.
J Cardiovasc Med (Hagerstown) ; 24(Suppl 1): e67-e76, 2023 04 01.
Article in English | MEDLINE | ID: covidwho-2315036

ABSTRACT

There is increasing evidence that in patients with atherosclerotic cardiovascular disease (ASCVD) under optimal medical therapy, a persisting dysregulation of the lipid and glucose metabolism, associated with adipose tissue dysfunction and inflammation, predicts a substantial residual risk of disease progression and cardiovascular events. Despite the inflammatory nature of ASCVD, circulating biomarkers such as high-sensitivity C-reactive protein and interleukins may lack specificity for vascular inflammation. As known, dysfunctional epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) produce pro-inflammatory mediators and promote cellular tissue infiltration triggering further pro-inflammatory mechanisms. The consequent tissue modifications determine the attenuation of PCAT as assessed and measured by coronary computed tomography angiography (CCTA). Recently, relevant studies have demonstrated a correlation between EAT and PCAT and obstructive coronary artery disease, inflammatory plaque status and coronary flow reserve (CFR). In parallel, CFR is well recognized as a marker of coronary vasomotor function that incorporates the haemodynamic effects of epicardial, diffuse and small-vessel disease on myocardial tissue perfusion. An inverse relationship between EAT volume and coronary vascular function and the association of PCAT attenuation and impaired CFR have already been reported. Moreover, many studies demonstrated that 18F-FDG PET is able to detect PCAT inflammation in patients with coronary atherosclerosis. Importantly, the perivascular FAI (fat attenuation index) showed incremental value for the prediction of adverse clinical events beyond traditional risk factors and CCTA indices by providing a quantitative measure of coronary inflammation. As an indicator of increased cardiac mortality, it could guide early targeted primary prevention in a wide spectrum of patients. In this review, we summarize the current evidence regarding the clinical applications and perspectives of EAT and PCAT assessment performed by CCTA and the prognostic information derived by nuclear medicine.


Subject(s)
Coronary Artery Disease , Nuclear Medicine , Plaque, Atherosclerotic , Humans , Coronary Angiography/methods , Coronary Artery Disease/diagnostic imaging , Tomography, X-Ray Computed/methods , Computed Tomography Angiography/methods , Adipose Tissue , Inflammation/diagnostic imaging , Coronary Vessels
20.
Am J Case Rep ; 24: e939170, 2023 May 01.
Article in English | MEDLINE | ID: covidwho-2320757

ABSTRACT

BACKGROUND Pneumomediastinum, or mediastinal emphysema, means air present inside the mediastinum. It usually presents with symptoms of chest pain and shortness of breath. Examination can be significant for crepitus along the neck area. There are many risk factors associated with pneumomediastinum, including asthma and COVID-19. Most cases of pneumomediastinum improve with conservative management, and surgery (mediastinotomy) is reserved for complicated cases with tension pneumomediastinum. CASE REPORT This is the case of a 23-year-old man who presented with chest tightness after 3.5 h of cycling. The patient did have a prior history of clinically stable asthma, with no recent exacerbation, and denied any other associative factors. Imaging was significant for pneumomediastinum. The patient was admitted for observation in the hospital and treated with supportive care, without any surgical intervention. The patient had appropriate improvement in his symptoms in 24 h. Repeat imaging showed improvement in the pneumomediastinum, and the patient was discharged to outpatient follow-up. CONCLUSIONS Our case presents a unique link between cycling and pneumomediastinum. Prolonged cycling may emerge as a risk factor for this complication. People with a previous history of pneumomediastinum should be careful to review other risk factors prior to planning long-distance bicycling. Physicians need to keep this differential diagnosis in mind when encountering a patient with similar symptoms so that a timely diagnosis is made.


Subject(s)
Asthma , COVID-19 , Mediastinal Emphysema , Male , Humans , Young Adult , Adult , Mediastinal Emphysema/diagnostic imaging , Mediastinal Emphysema/complications , Bicycling , COVID-19/complications , Tomography, X-Ray Computed , Asthma/complications , Chest Pain/diagnosis , Chest Pain/etiology
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