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1.
Sci Rep ; 12(1): 1716, 2022 02 02.
Artigo em Inglês | MEDLINE | ID: mdl-35110593

RESUMO

The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence approaches to these problems, including using deep learning to predict COVID-19 diagnosis and prognosis from chest computed tomography (CT) imaging data. In this work, we assess the value of aggregated chest CT data for COVID-19 prognosis compared to clinical metadata alone. We develop a novel patient-level algorithm to aggregate the chest CT volume into a 2D representation that can be easily integrated with clinical metadata to distinguish COVID-19 pneumonia from chest CT volumes from healthy participants and participants with other viral pneumonia. Furthermore, we present a multitask model for joint segmentation of different classes of pulmonary lesions present in COVID-19 infected lungs that can outperform individual segmentation models for each task. We directly compare this multitask segmentation approach to combining feature-agnostic volumetric CT classification feature maps with clinical metadata for predicting mortality. We show that the combination of features derived from the chest CT volumes improve the AUC performance to 0.80 from the 0.52 obtained by using patients' clinical data alone. These approaches enable the automated extraction of clinically relevant features from chest CT volumes for risk stratification of COVID-19 patients.


Assuntos
COVID-19/diagnóstico , COVID-19/virologia , Aprendizado Profundo , SARS-CoV-2 , Tórax/diagnóstico por imagem , Tórax/patologia , Tomografia Computadorizada por Raios X , Algoritmos , COVID-19/mortalidade , Bases de Dados Genéticas , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Processamento de Imagem Assistida por Computador/métodos , Prognóstico , Tomografia Computadorizada por Raios X/métodos , Tomografia Computadorizada por Raios X/normas
2.
Curr Med Sci ; 42(1): 217-225, 2022 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-35089491

RESUMO

OBJECTIVE: The objective of this study was to investigate the application of unenhanced computed tomography (CT) texture analysis in differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC). METHODS: Preoperative CT images of 112 patients (31 with PASC, 81 with PDAC) were retrospectively reviewed. A total of 396 texture parameters were extracted from AnalysisKit software for further texture analysis. Texture features were selected for the differentiation of PASC and PDAC by the Mann-Whitney U test, univariate logistic regression analysis, and the minimum redundancy maximum relevance algorithm. Furthermore, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the texture feature-based model by the random forest (RF) method. Finally, the robustness and reproducibility of the predictive model were assessed by the 10-times leave-group-out cross-validation (LGOCV) method. RESULTS: In the present study, 10 texture features to differentiate PASC from PDAC were eventually retained for RF model construction after feature selection. The predictive model had a good classification performance in differentiating PASC from PDAC, with the following characteristics: sensitivity, 95.7%; specificity, 92.5%; accuracy, 94.3%; positive predictive value (PPV), 94.3%; negative predictive value (NPV), 94.3%; and area under the ROC curve (AUC), 0.98. Moreover, the predictive model was proved to be robust and reproducible using the 10-times LGOCV algorithm (sensitivity, 90.0%; specificity, 71.3%; accuracy, 76.8%; PPV, 59.0%; NPV, 95.2%; and AUC, 0.80). CONCLUSION: The unenhanced CT texture analysis has great potential for differentiating PASC from PDAC.


Assuntos
Carcinoma Adenoescamoso/diagnóstico por imagem , Carcinoma Ductal Pancreático/diagnóstico por imagem , Neoplasias Pancreáticas/diagnóstico por imagem , Tomografia Computadorizada por Raios X/normas , Adulto , Idoso , Diagnóstico Diferencial , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X/métodos
3.
Technol Cancer Res Treat ; 21: 15330338221074498, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35099325

RESUMO

Object: By retrospectively analyzing the energy spectrum of squamous cell carcinoma, adenocarcinoma, small cell lung cancer (SCLC), and pulmonary metastases that underwent dual-layer detector spectral computed tomography (DLCT) 3-phase scan of the chest, we explored the value of a multiparameter energy spectrum in the assessment of pathological types of lung tumors. Methods: Cases of squamous cell carcinoma (n = 20), adenocarcinoma (n = 24), SCLC (n = 26), and metastases (n = 14) were collected. Then the largest cross-sectional area (LCA) of the lesion, computed tomography (CT) values in the plain scan phase, arterial and venous phases (HU, HUa, and HUv), iodine concentration, and effective atomic number in the arterial and venous phases (ICa, ICv, Zeff[a], and Zeff[v]) were measured and compared among the nonsmall cell lung cancer (NSCLC), SCLC and metastases, and other 3 groups of SCLC, squamous cell carcinoma, and adenocarcinoma. Results: Only the LCA is statistically different among SCLC, NSCLC, and metastases (P < .05). And the treated subgroup analysis did not show significant differences among the groups. However, the untreated subgroup analysis showed that there was a significant difference between NSCLC and metastases in LCA, SCLC and metastases in ICa, NSCLC and SCLC in HUv, NSCLC and SCLC in Zeff(v) (P < .05). Conclusion: The energy spectrum parameters of DLCT have a certain clinical value in distinguishing NSCLC from SCLC in the Zeff(v) and distinguishing SCLC from metastases in the ICa.


Assuntos
Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Tomografia Computadorizada por Raios X/métodos , Idoso , Tomada de Decisão Clínica , Diagnóstico Diferencial , Gerenciamento Clínico , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/normas
4.
Acta Radiol ; 63(3): 336-344, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33663246

RESUMO

BACKGROUND: This study examined whether ultra-low-dose chest computed tomography (ULD-CT) could improve detection of acute chest conditions. PURPOSE: To determine (i) whether diagnostic accuracy of ULD-CT is superior to supine chest X-ray (sCXR) for acute chest conditions and (ii) the feasibility of ULD-CT in an emergency department. MATERIAL AND METHODS: From 1 February to 31 July 2019, 91 non-traumatic patients from the Emergency Department were prospectively enrolled in the study if they received an sCXR. An ULD-CT and a non-contrast chest CT (NCCT) scan were then performed. Three radiologists assessed the sCXR and ULD-CT examinations for cardiogenic pulmonary edema, pneumonia, pneumothorax, and pleural effusion. Resources and effort were compared for sCXR and ULD-CT to evaluate feasibility. Diagnostic accuracy was calculated for sCXR and ULD-CT using NCCT as the reference standard. RESULTS: The mean effective dose of ULD-CT was 0.05±0.01 mSv. For pleural effusion and cardiogenic pulmonary edema, no difference in diagnostic accuracy between ULD-CT and sCXR was observed. For pneumonia and pneumothorax, sensitivities were 100% (95% confidence interval [CI] 69-100) and 50% (95% CI 7-93) for ULD-CT and 60% (95% CI 26-88) and 0% (95% CI 0-0) for sCXR, respectively. Median examination time was 10 min for ULD-CT vs. 5 min for sCXR (P<0.001). For ULD-CT 1-2 more staff members were needed compared to sCXR (P<0.001). ULD-CT was rated more challenging to perform than sCXR (P<0.001). CONCLUSION: ULD-CT seems equal or better in detecting acute chest conditions compared to sCXR. However, ULD-CT examinations demand more effort and resources.


Assuntos
Serviço Hospitalar de Emergência , Doses de Radiação , Radiografia Torácica/métodos , Tomografia Computadorizada por Raios X/métodos , Idoso , Intervalos de Confiança , Estudos de Viabilidade , Feminino , Humanos , Masculino , Derrame Pleural/diagnóstico por imagem , Pneumonia/diagnóstico por imagem , Pneumotórax/diagnóstico por imagem , Estudos Prospectivos , Edema Pulmonar/diagnóstico por imagem , Exposição à Radiação , Radiografia Torácica/normas , Padrões de Referência , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X/normas
5.
J Trauma Acute Care Surg ; 92(1): 44-48, 2022 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-34932040

RESUMO

BACKGROUND: Ultrasonography for trauma is a widely used tool in the initial evaluation of trauma patients with complete ultrasonography of trauma (CUST) demonstrating equivalence to computed tomography (CT) for detecting clinically significant abdominal hemorrhage. Initial reports demonstrated high sensitivity of CUST for the bedside diagnosis of pneumothorax. We hypothesized that the sensitivity of CUST would be greater than initial supine chest radiograph (CXR) for detecting pneumothorax. METHODS: A retrospective analysis of patients diagnosed with pneumothorax from 2018 through 2020 at a Level I trauma center was performed. Patients included had routine supine CXR and CUST performed prior to intervention as well as confirmatory CT imaging. All CUST were performed during the initial evaluation in the trauma bay by a registered sonographer. All imaging was evaluated by an attending radiologist. Subgroup analysis was performed after excluding occult pneumothorax. Immediate tube thoracostomy was defined as tube placement with confirmatory CXR within 8 hours of admission. RESULTS: There were 568 patients screened with a diagnosis of pneumothorax, identifying 362 patients with a confirmed pneumothorax in addition to CXR, CUST, and confirmatory CT imaging. The population was 83% male, had a mean age of 45 years, with 85% presenting due to blunt trauma. Sensitivity of CXR for detecting pneumothorax was 43%, while the sensitivity of CUST was 35%. After removal of occult pneumothorax (n = 171), CXR was 78% sensitive, while CUST was 65% sensitive (p < 0.01). In this subgroup, CUST had a false-negative rate of 36% (n = 62). Of those patients with a false-negative CUST, 50% (n = 31) underwent tube thoracostomy, with 85% requiring immediate placement. CONCLUSION: Complete ultrasonography of trauma performed on initial trauma evaluation had lower sensitivity than CXR for identification of pneumothorax including clinically significant pneumothorax requiring tube thoracostomy. Using CUST as the primary imaging modality in the initial evaluation of chest trauma should be considered with caution. LEVEL OF EVIDENCE: Diagnostic Test study, Level IV.


Assuntos
Pneumotórax , Traumatismos Torácicos , Toracostomia , Tomografia Computadorizada por Raios X , Ultrassonografia , Erros de Diagnóstico/prevenção & controle , Erros de Diagnóstico/estatística & dados numéricos , Reações Falso-Negativas , Feminino , Humanos , Masculino , Programas de Rastreamento/métodos , Pessoa de Meia-Idade , Posicionamento do Paciente/métodos , Pneumotórax/diagnóstico por imagem , Pneumotórax/etiologia , Radiografia Torácica/métodos , Radiografia Torácica/normas , Sensibilidade e Especificidade , Traumatismos Torácicos/complicações , Traumatismos Torácicos/diagnóstico , Traumatismos Torácicos/epidemiologia , Toracostomia/instrumentação , Toracostomia/métodos , Toracostomia/estatística & dados numéricos , Tempo para o Tratamento , Tomografia Computadorizada por Raios X/métodos , Tomografia Computadorizada por Raios X/normas , Centros de Traumatologia/estatística & dados numéricos , Ultrassonografia/métodos , Ultrassonografia/normas , Estados Unidos/epidemiologia , Ferimentos não Penetrantes/complicações , Ferimentos não Penetrantes/diagnóstico , Ferimentos não Penetrantes/epidemiologia
6.
Am J Emerg Med ; 52: 225-231, 2022 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-34971907

RESUMO

INTRODUCTION: Computed tomography (CT) is a commonly used imaging modality in Emergency Departments (EDs), however its use is questionable in many low yield settings. The Emergency CT Head score (ECHS) is a recently published clinical tool that assists in stratifying the need for CT brain (CTB) for patients presenting without a history of trauma. We sought to validate this tool in an Australian ED setting. METHODS: We prospectively evaluated 412 patients who received CTB without a history of trauma at a large Australian ED. We assessed them for the 4 main ECHS data points: focal neurological deficit on physical examination, new acute onset headache, transient neurological deficit, and a combination of new onset seizures with an altered conscious state. We examined their association with acute and chronic CTB findings. We then applied the ECHS to our data, calculating its sensitivity and its appropriateness at this single site via the calculation of a receiver operating curve (ROC). RESULTS: 10.2% of all CTB performed were positive for an acute or chronic abnormality. Only sex (male) and focal motor deficit were independent predictors of positive CTB at univariate analysis. The ECHS did not perform as anticipated in our population, with a ROC area under the curve of 0.498. An ECHS score of >0, which has been proposed as the threshold to not require imaging, had sensitivity of only 83.3% in our population. CONCLUSIONS: Further research and validation is required in order to safely implement the ECHS clinical score in the Australian ED setting.


Assuntos
Serviço Hospitalar de Emergência/organização & administração , Tomografia Computadorizada por Raios X/normas , Idoso , Idoso de 80 Anos ou mais , Austrália , Traumatismos Craniocerebrais/diagnóstico , Técnicas de Apoio para a Decisão , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Curva ROC
7.
BMC Med Imaging ; 21(1): 192, 2021 12 13.
Artigo em Inglês | MEDLINE | ID: mdl-34903187

RESUMO

AIM: This study is to compare the lung image quality between shelter hospital CT (CT Ark) and ordinary CT scans (Brilliance 64) scans. METHODS: The patients who received scans with CT Ark or Brilliance 64 CT were enrolled. Their lung images were divided into two groups according to the scanner. The objective evaluation methods of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used. The subjective evaluation methods including the evaluation of the fine structure under the lung window and the evaluation of the general structure under the mediastinum window were compared. Kappa method was used to assess the reliability of the subjective evaluation. The subjective evaluation results were analyzed using the Wilcoxon rank sum test. SNR and CNR were tested using independent sample t tests. RESULTS: There was no statistical difference in somatotype of enrolled subjects. The Kappa value between the two observers was between 0.68 and 0.81, indicating good consistency. For subjective evaluation results, the rank sum test P value of fine structure evaluation and general structure evaluation by the two observers was ≥ 0.05. For objective evaluation results, SNR and CNR between the two CT scanners were significantly different (P<0.05). Notably, the absolute values ​​of SNR and CNR of the CT Ark were larger than Brilliance 64 CT scanner. CONCLUSION: CT Ark is fully capable of scanning the lungs of the COVID-19 patients during the epidemic in the shelter hospital.


Assuntos
COVID-19/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Unidades Móveis de Saúde/normas , Tomografia Computadorizada por Raios X/instrumentação , Tomografia Computadorizada por Raios X/normas , Adulto , Idoso , COVID-19/epidemiologia , China/epidemiologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Variações Dependentes do Observador , Pandemias , SARS-CoV-2 , Razão Sinal-Ruído
8.
Eur J Endocrinol ; 186(2): 183-193, 2021 Dec 10.
Artigo em Inglês | MEDLINE | ID: mdl-34813495

RESUMO

OBJECTIVE: Reliable results of wash-out CT in the diagnostic workup of adrenal incidentalomas are scarce. Thus, we evaluated the diagnostic accuracy of delayed wash-out CT and determined thresholds to accurately differentiate adrenal masses. DESIGN: Retrospective, single-center cohort study including 216 patients with 252 adrenal lesions who underwent delayed wash-out CT. Definitive diagnoses based on histopathology (n = 92) or comprehensive follow-up. METHODS: Size, average attenuation values of the adrenal lesions in all CT scan phases, and absolute and relative percentage wash-out (APW/RPW) were determined by an expert radiologist blinded for clinical data. Adrenal lesions with unenhanced attenuation values >10 Hounsfield units (HU) built a subgroup (n = 142). Diagnostic accuracy was calculated. RESULTS: The study group consisted of 171 adenomas, 32 other benign tumors, 11 pheochromocytomas, 9 adrenocortical carcinomas, and 29 other malignant tumors. All (potentially) malignant and 46% of benign lesions showed unenhanced attenuation values >10 HU. In this most relevant subgroup, the established thresholds of 60% for APW and 40% for RPW misclassified 35.9 and 35.2% of the masses, respectively. When we applied optimized cutoffs (APW >83%; RPW >58%) and excluded pheochromocytomas, we missed only one malignant tumor by APW and none by RPW. However, only 11 and 15% of the benign tumors were correctly identified. CONCLUSIONS: Wash-out CT with the established thresholds for APW and RPW is insufficient to reliably diagnose adrenal masses. Using the proposed cutoff of 58% for RPW, malignant tumors will be correctly identified, but the added value is limited, namely 15% of patients with benign tumors can be prevented from additional imaging or even unnecessary surgery.


Assuntos
Neoplasias do Córtex Suprarrenal/diagnóstico por imagem , Neoplasias das Glândulas Suprarrenais/diagnóstico por imagem , Adenoma Adrenocortical/diagnóstico por imagem , Tomografia Computadorizada por Raios X/métodos , Neoplasias do Córtex Suprarrenal/fisiopatologia , Neoplasias das Glândulas Suprarrenais/fisiopatologia , Adenoma Adrenocortical/fisiopatologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Diagnóstico Diferencial , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/normas
9.
IEEE Trans Neural Netw Learn Syst ; 32(11): 4781-4792, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34613921

RESUMO

Accurate and rapid diagnosis of COVID-19 using chest X-ray (CXR) plays an important role in large-scale screening and epidemic prevention. Unfortunately, identifying COVID-19 from the CXR images is challenging as its radiographic features have a variety of complex appearances, such as widespread ground-glass opacities and diffuse reticular-nodular opacities. To solve this problem, we propose an adaptive attention network (AANet), which can adaptively extract the characteristic radiographic findings of COVID-19 from the infected regions with various scales and appearances. It contains two main components: an adaptive deformable ResNet and an attention-based encoder. First, the adaptive deformable ResNet, which adaptively adjusts the receptive fields to learn feature representations according to the shape and scale of infected regions, is designed to handle the diversity of COVID-19 radiographic features. Then, the attention-based encoder is developed to model nonlocal interactions by self-attention mechanism, which learns rich context information to detect the lesion regions with complex shapes. Extensive experiments on several public datasets show that the proposed AANet outperforms state-of-the-art methods.


Assuntos
COVID-19/diagnóstico por imagem , Redes Neurais de Computação , Tomografia Computadorizada por Raios X/classificação , Tomografia Computadorizada por Raios X/normas , COVID-19/epidemiologia , Bases de Dados Factuais/normas , Humanos , Tomografia Computadorizada por Raios X/métodos , Raios X
10.
Sci Rep ; 11(1): 19781, 2021 10 05.
Artigo em Inglês | MEDLINE | ID: mdl-34611247

RESUMO

Diffusible iodine-based contrast-enhanced computed tomography (diceCT) is progressively used in clinical and morphological research to study developmental anatomy. Lugol's solution (Lugol) has gained interest as an effective contrast agent; however, usage is limited due to extensive soft-tissue shrinkage. The mechanism of Lugol-induced shrinkage and how to prevent it is largely unknown, hampering applications of Lugol in clinical or forensic cases where tissue shrinkage can lead to erroneous diagnostic conclusions. Shrinkage was suggested to be due to an osmotic imbalance between tissue and solution. Pilot experiments pointed to acidification of Lugol, but the relation of acidification and tissue shrinkage was not evaluated. In this study, we analyzed the relation between tissue shrinkage, osmolarity and acidification of the solution during staining. Changes in tissue volume were measured on 2D-segmented magnetic resonance and diceCT images using AMIRA software. Partial correlation and stepwise regression analysis showed that acidification of Lugol is the main cause of tissue shrinkage. To prevent acidification, we developed a buffered Lugol's solution (B-Lugol) and showed that stabilizing its pH almost completely prevented shrinkage without affecting staining. Changing from Lugol to B-Lugol is a major improvement for clinical and morphological research and only requires a minor adaptation of the staining protocol.


Assuntos
Artefatos , Tecido Conjuntivo/anatomia & histologia , Tecido Conjuntivo/diagnóstico por imagem , Meios de Contraste , Iodetos , Coloração e Rotulagem/métodos , Animais , Feto/diagnóstico por imagem , Humanos , Concentração de Íons de Hidrogênio , Camundongos , Tomografia Computadorizada por Raios X/métodos , Tomografia Computadorizada por Raios X/normas
11.
Medicine (Baltimore) ; 100(42): e27270, 2021 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-34678861

RESUMO

BACKGROUND: Computed tomography (CT) is the current gold standard for the detection of pulmonary nodules but has high radiation burden. In contrast, many radiologists tried to use magnetic resonance imaging (MRI) to replace CT because MRI has no radiation burden associated. Due to the lack of high-level evidence of comparison of the diagnostic accuracy of MRI versus CT for detecting pulmonary nodules, it is unknown whether CT can be replaced successfully by MRI. Therefore, the aim of this study was to compare the diagnostic accuracy of MRI versus CT for detecting pulmonary nodules. METHODS: Electronic databases PubMed, EmBase, and Cochrane Library were systematically searched from their inception to September 2017 to identify studies in which CT/MRI was used to diagnose pulmonary nodules. According to true positive, true negative, false negative, and false positive extracted from the included studies, we calculate the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the curve (AUC) using Stata version 14.0 software (STATA Corp, TX). RESULTS: A total of 8 studies involving a total of 653 individuals were included. The pooled sensitivity, specificity, PLR, NLR, and AUC were 0.91 (95% confidence interval [CI]: 0.80-0.96), 0.76 (95%CI: 0.58-0.87), 3.72 (95%CI: 2.05-6.76), 0.12 (95%CI: 0.06-0.27), and 0.91 (95%CI: 0.88-0.93) for MRI respectively, while the pooled sensitivity, specificity, PLR, NLR, and AUC for CT were 1.00 (95%CI: 0.95-1.00), 0.99 (95%CI: 0.78-1.00), 79.35 (95%CI: 3.68-1711.06), 0.00 (95%CI: 0.00-0.06), and 1.00 (95%CI: 0.99-1.00), respectively. Further, we compared the diagnostic accuracy of CT versus MRI and found that compared with MRI, CT shows statistically higher sensitivity (odds ratio [OR] for MRI vs CT: 0.91; 95%CI: 0.85-0.98; P value .010), specificity (OR: 0.82; 95%CI: 0.69-0.97; P value .019), PLR (OR: 0.29; 95%CI: 0.10-0.83; P value 0.02), AUC (OR: 0.91; 95%CI: 0.89-0.94; P value < .001), and lower NLR (OR: 8.72; 95%CI: 1.57-48.56; P value .013). CONCLUSION: Our study suggested both CT and MRI have a high diagnostic accuracy in diagnosing pulmonary nodules, while CT was superior to MRI in sensitivity, specificity, PLR, NLR, and AUC, indicating that in terms of the currently available evidence, MRI could not replace CT in diagnosing pulmonary nodules.


Assuntos
Imageamento por Ressonância Magnética/métodos , Nódulos Pulmonares Múltiplos/diagnóstico por imagem , Nódulos Pulmonares Múltiplos/patologia , Tomografia Computadorizada por Raios X/métodos , Erros de Diagnóstico , Humanos , Imageamento por Ressonância Magnética/normas , Curva ROC , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X/normas
12.
Medicine (Baltimore) ; 100(37): e27044, 2021 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-34664829

RESUMO

ABSTRACT: The purpose of this retrospective study was to explore the advantages of computed tomography (CT) nano-contrast agent in tumor diagnosis.A total of 100 patients with malignant tumor who were diagnosed in Shaanxi Province Public Hospital between January 2018 and January 2019 were included in this retrospective study. They were randomly divided into observation and control groups with 50 patients in each group. The patients in the observation group used new type of nano-contrast agent for examination, and the patients in the control group used traditional iohexol contrast agent for examination. The detection rate, misdiagnosis rate, and incidence of adverse reactions were observed. In addition, single photon emission computed tomography or CT scan was performed on patients to observe the radioactive concentration.The detection rate was 100% in the observation group and 84% in the control group, and the difference between the 2 groups was statistically significant (χ2 = 8.763, P = .001). The incidence of adverse reactions was 2% in the observation group and 30% in the control group, and the difference between the 2 groups was significantly different (χ2 = 12.683, P = .000). The radioactive concentration in the observation group was markedly higher than that in the control group (t = 19.692, P = .001).The use of CT nano-contrast agent in tumor diagnosis had higher detection rate of tumor and radioactive concentration, and it had lower misdiagnosis rate and adverse reaction rate than traditional iohexol contrast agent.


Assuntos
Neoplasias/diagnóstico por imagem , Neoplasias/diagnóstico , Tomografia Computadorizada por Raios X/normas , China , Meios de Contraste/farmacologia , Meios de Contraste/uso terapêutico , Humanos , Neoplasias/classificação , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/métodos , Tomografia Computadorizada por Raios X/estatística & dados numéricos
13.
PLoS One ; 16(9): e0257294, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34516579

RESUMO

RATIONALE AND OBJECTIVES: This study aimed to compare the volume computed tomography dose index (CTDIvol), dose length product (DLP), and size-specific dose estimate (SSDE), with the China and updated 2017 American College of Radiology (ACR) diagnostic reference levels (DRLs) in chest CT examinations of adults based on the water-equivalent diameter (Dw). MATERIALS AND METHODS: All chest CT examinations conducted without contrast administration from January 2020 to July 2020 were retrospectively included in this study. The Dw and SSDE of all examinations were calculated automatically by "teamplay". The CTDIvol and DLP were displayed on the DICOM-structured dose report in the console based on a 32cm phantom.The differences in patient CTDIvol, DLP, and SSDE values between groups were examined by the one-way ANOVA. The differences in patient CTDIvol, DLP, and SSDE values between the updated 2017 ACR and the China DRLs were examined with one sample t-tests. RESULTS: In total 14666 chest examinations were conducted in our study. Patients were divided into four groups based on Dw:270 (1.84%) in 15-20 cm group, 10287 (70.14%) in the 21-25 cm group, 4097 (27.94%) in the 26-30 cm group, and 12 (0.08%) patients had sizes larger than 30 cm. CTDIvol, DLP, and SSDE increased as a function of Dw (p<0.05). CTDIvol was smaller than SSDE among groups (p<0.05). The mean CTDIvol and DLP values were lower than the 25th, 50th, and 75th percentile of the China DRLs (p <0.05). The CTDIvol, DLP, and SSDE were lower than the 50th and 75th percentiles of the updated 2017 ACR DRLs (p <0.05) among groups. CONCLUSIONS: SSDE takes into account the influence of the scanning parameters, patient size, and X-ray attenuation on the radiation dose, which can give a more realistic estimate of radiation exposure dose for patients undergoing CT examinations. Establishing hospital's own DRL according to CTDIvol and SSDE is very important even though the radiation dose is lower than the national DRLs.


Assuntos
Tomografia Computadorizada por Raios X/métodos , Adulto , China , Níveis de Referência de Diagnóstico , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Doses de Radiação , Valores de Referência , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/normas
15.
Sci Rep ; 11(1): 18422, 2021 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-34531429

RESUMO

To determine whether temporal subtraction (TS) CT obtained with non-rigid image registration improves detection of various bone metastases during serial clinical follow-up examinations by numerous radiologists. Six board-certified radiologists retrospectively scrutinized CT images for patients with history of malignancy sequentially. These radiologists selected 50 positive and 50 negative subjects with and without bone metastases, respectively. Furthermore, for each subject, they selected a pair of previous and current CT images satisfying predefined criteria by consensus. Previous images were non-rigidly transformed to match current images and subtracted from current images to automatically generate TS images. Subsequently, 18 radiologists independently interpreted the 100 CT image pairs to identify bone metastases, both without and with TS images, with each interpretation separated from the other by an interval of at least 30 days. Jackknife free-response receiver operating characteristics (JAFROC) analysis was conducted to assess observer performance. Compared with interpretation without TS images, interpretation with TS images was associated with a significantly higher mean figure of merit (0.710 vs. 0.658; JAFROC analysis, P = 0.0027). Mean sensitivity at lesion-based was significantly higher for interpretation with TS compared with that without TS (46.1% vs. 33.9%; P = 0.003). Mean false positive count per subject was also significantly higher for interpretation with TS than for that without TS (0.28 vs. 0.15; P < 0.001). At the subject-based, mean sensitivity was significantly higher for interpretation with TS images than that without TS images (73.2% vs. 65.4%; P = 0.003). There was no significant difference in mean specificity (0.93 vs. 0.95; P = 0.083). TS significantly improved overall performance in the detection of various bone metastases.


Assuntos
Neoplasias Ósseas/tratamento farmacológico , Tomografia Computadorizada por Raios X/normas , Idoso , Idoso de 80 Anos ou mais , Neoplasias Ósseas/secundário , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Variações Dependentes do Observador , Radiologistas/estatística & dados numéricos , Sensibilidade e Especificidade , Software , Tomografia Computadorizada por Raios X/métodos
16.
Technol Cancer Res Treat ; 20: 15330338211039125, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34499018

RESUMO

Purpose: This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). Method: A total of 28 patients with HL and 101 patients with ICCA were included. A total of 45 texture features were extracted by the software LifeX from contrast-enhanced computer tomography (CECT) images and 38 of them were eligible. A total of 5 feature selection methods and 9 feature classification methods were used to build the best diagnostic models, combining with the 10-fold cross-validation to assess the accuracy of these models. The discriminative ability of each model was evaluated by receiver operating characteristic analysis. Result: A total of 45 predictive models were built by the cross combination of each selection and classification method to differentiate ICCA from HL. According to the results of test group, most of the models performed well with a large area under the curve (AUC) (>0.85) and high accuracy (>0.85). Random Forest (RF)_Linear Discriminant Analysis (LDA) (AUC = 0.997, accuracy = 0.969) was the best model among all the 45 models. Conclusion: Combining texture parameters from CECT with multiple machine learning models can differentiate ICCA and HL effectively, and RF_LDA performed the best in this process.


Assuntos
Neoplasias dos Ductos Biliares/diagnóstico , Colangiocarcinoma/diagnóstico , Linfoma/diagnóstico , Aprendizado de Máquina , Tomografia Computadorizada por Raios X , Idoso , Algoritmos , Meios de Contraste , Diagnóstico Diferencial , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Masculino , Pessoa de Meia-Idade , Gradação de Tumores , Curva ROC , Intensificação de Imagem Radiográfica , Reprodutibilidade dos Testes , Tomografia Computadorizada por Raios X/métodos , Tomografia Computadorizada por Raios X/normas , Carga Tumoral
17.
Chest ; (21): 1959-1980, 20210908.
Artigo em Inglês | BIGG - guias GRADE, BIGG - guias GRADE | ID: biblio-1292446

RESUMO

Low-dose chest CT screening for lung cancer has become a standard of care in the United States, in large part because of the results of the National Lung Screening Trial (NLST). Additional evidence supporting the net benefit of low-dose chest CT screening for lung cancer, and increased experience in minimizing the potential harms, has accumulated since the prior iteration of these guidelines. Here, we update the evidence base for the benefit, harms, and implementation of low-dose chest CT screening. We use the updated evidence base to provide recommendations where the evidence allows, and statements based on experience and expert consensus where it does not. Approved panelists reviewed previously developed key questions using the Population, Intervention, Comparator, Outcome format to address the benefit and harms of low-dose CT screening, and key areas of program implementation. A systematic literature review was conducted using MEDLINE via PubMed, Embase, and the Cochrane Library on a quarterly basis since the time of the previous guideline publication. Reference lists from relevant retrievals were searched, and additional papers were added. Retrieved references were reviewed for relevance by two panel members. The quality of the evidence was assessed for each critical or important outcome of interest using the Grading of Recommendations, Assessment, Development and Evaluation approach. Meta-analyses were performed where appropriate. Important clinical questions were addressed based on the evidence developed from the systematic literature review. Graded recommendations and ungraded statements were drafted, voted on, and revised until consensus was reached. The systematic literature review identified 75 additional studies that informed the response to the 12 key questions that were developed. Additional clinical questions were addressed resulting in seven graded recommendations and nine ungraded consensus statements. Evidence suggests that low-dose CT screening for lung cancer can result in a favorable balance of benefit and harms. The selection of screen-eligible individuals, the quality of imaging and image interpretation, the management of screen-detected findings, and the effectiveness of smoking cessation interventions can impact this balance.


Assuntos
Humanos , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Tabagismo/complicações , Programas de Rastreamento , Neoplasias Pulmonares/diagnóstico por imagem , Portador Sadio , Tomografia Computadorizada por Raios X/normas , Detecção Precoce de Câncer
18.
Sci Prog ; 104(3): 368504211016204, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34424791

RESUMO

As the coronavirus disease 2019 (COVID-19) epidemic spreads around the world, the demand for imaging examinations increases accordingly. The value of conventional chest radiography (CCR) remains unclear. In this study, we aimed to investigate the diagnostic value of CCR in the detection of COVID-19 through a comparative analysis of CCR and CT. This study included 49 patients with 52 CT images and chest radiographs of pathogen-confirmed COVID-19 cases and COVID-19-suspected cases that were found to be negative (non-COVID-19). The performance of CCR in detecting COVID-19 was compared to CT imaging. The major signatures that allowed for differentiation between COVID-19 and non-COVID-19 cases were also evaluated. Approximately 75% (39/52) of images had positive findings on the chest x-ray examinations, while 80.7% (42/52) had positive chest CT scans. The COVID-19 group accounted for 88.4% (23/26) of positive chest X-ray examinations and 96.1% (25/26) of positive chest CT scans. The sensitivity, specificity, and accuracy of CCR for abnormal shadows were 88%, 80%, and 87%, respectively, for all patients. For the COVID-19 group, the accuracy of CCR was 92%. The primary signature on CCR was flocculent shadows in both groups. The shadows were primarily in the bi-pulmonary, which was significantly different from non-COVID-19 patients (p = 0.008). The major CT finding of COVID-19 patients was ground-glass opacities in both lungs, while in non-COVID-19 patients, consolidations combined with ground-glass opacities were more common in one lung than both lungs (p = 0.0001). CCR showed excellent performance in detecting abnormal shadows in patients with confirmed COVID-19. However, it has limited value in differentiating COVID-19 patients from non-COVID-19 patients. Through the typical epidemiological history, laboratory examinations, and clinical symptoms, combined with the distributive characteristics of shadows, CCR may be useful to identify patients with possible COVID-19. This will allow for the rapid identification and quarantine of patients.


Assuntos
COVID-19/diagnóstico por imagem , Radiografia Torácica/métodos , Tomografia Computadorizada por Raios X/métodos , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Radiografia Torácica/normas , Tomografia Computadorizada por Raios X/normas
19.
Sci Rep ; 11(1): 17051, 2021 08 23.
Artigo em Inglês | MEDLINE | ID: mdl-34426587

RESUMO

Machine learning (ML) holds great promise in transforming healthcare. While published studies have shown the utility of ML models in interpreting medical imaging examinations, these are often evaluated under laboratory settings. The importance of real world evaluation is best illustrated by case studies that have documented successes and failures in the translation of these models into clinical environments. A key prerequisite for the clinical adoption of these technologies is demonstrating generalizable ML model performance under real world circumstances. The purpose of this study was to demonstrate that ML model generalizability is achievable in medical imaging with the detection of intracranial hemorrhage (ICH) on non-contrast computed tomography (CT) scans serving as the use case. An ML model was trained using 21,784 scans from the RSNA Intracranial Hemorrhage CT dataset while generalizability was evaluated using an external validation dataset obtained from our busy trauma and neurosurgical center. This real world external validation dataset consisted of every unenhanced head CT scan (n = 5965) performed in our emergency department in 2019 without exclusion. The model demonstrated an AUC of 98.4%, sensitivity of 98.8%, and specificity of 98.0%, on the test dataset. On external validation, the model demonstrated an AUC of 95.4%, sensitivity of 91.3%, and specificity of 94.1%. Evaluating the ML model using a real world external validation dataset that is temporally and geographically distinct from the training dataset indicates that ML generalizability is achievable in medical imaging applications.


Assuntos
Hemorragias Intracranianas/diagnóstico por imagem , Aprendizado de Máquina , Tomografia Computadorizada por Raios X/métodos , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/normas , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X/normas
20.
Int J Rheum Dis ; 24(12): 1473-1481, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34212506

RESUMO

OBJECTIVE: High-resolution peripheral quantitative computed tomography (HR-pQCT) requires longer immobilization time than conventional radiography, which challenges patient acceptance and image quality. Therefore, the aim was to investigate the acceptance of HR-pQCT in patients with rheumatoid arthritis (RA), and secondly the effect of an inflatable hand immobilization device on motion artefacts of the metacarpophalangeal (MCP) joints. METHODS: Fifty patients with established RA and a median (interquartile range) age of 64.3 (55.0-71.2) years had their MCP joints scanned by HR-pQCT with the hand positioned with and without an inflatable immobilization device followed by a full radiographic examination and a questionnaire on the imaging experience. The comparability of the erosion measures was investigated with and without the immobilization device using Bland-Altman plot and intrareader repeatability by intraclass correlation coefficient. The motion artefacts were graded for each acquisition, and intrareader repeatability was investigated by Cohen's kappa coefficient. RESULTS: Forty percent of the patients preferred HR-pQCT imaging, only 6% preferred conventional X-ray. Seventy-four percent reported it was not difficult to keep their fingers steady during the scan. Sixty percent of the patients reported the immobilization device helped keep their fingers steady. However, as motion artefacts were sparse, no clinically relevant difference was observed concerning the effect of the immobilization device on readability. The intrareader repeatability and comparability for the erosion measures were excellent. CONCLUSION: The high patient acceptance adds to the feasibility of HR-pQCT imaging of MCP joints in RA. The inflatable immobilization device did not reduce motion-induced image degradation.


Assuntos
Artrite Reumatoide/diagnóstico por imagem , Articulação Metacarpofalângica/diagnóstico por imagem , Tomografia Computadorizada por Raios X/normas , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Preferência do Paciente , Medidas de Resultados Relatados pelo Paciente
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