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1.
Eur Radiol ; 2024 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-38856781

RESUMO

OBJECTIVES: Our study comprised a single-center retrospective in vitro correlation between spectral properties, namely ρ/Z values, derived from scanning blood samples using dual-energy computed tomography (DECT) with the corresponding laboratory hemoglobin/hematocrit (Hb/Hct) levels and assessed the potential in anemia-detection. METHODS: DECT of 813 patient blood samples from 465 women and 348 men was conducted using a standardized scan protocol. Electron density relative to water (ρ or rho), effective atomic number (Zeff), and CT attenuation (Hounsfield unit) were measured. RESULTS: Positive correlation with the Hb/Hct was shown for ρ (r-values 0.37-0.49) and attenuation (r-values 0.59-0.83) while no correlation was observed for Zeff (r-values -0.04 to 0.08). Significant differences in attenuation and ρ values were detected for blood samples with and without anemia in both genders (p value < 0.001) with area under the curve ranging from 0.7 to 0.95. Depending on the respective CT parameters, various cutoff values for CT-based anemia detection could be determined. CONCLUSION: In summary, our study investigated the correlation between DECT measurements and Hb/Hct levels, emphasizing novel aspects of ρ and Zeff values. Assuming that quantitative changes in the number of hemoglobin proteins might alter the mean Zeff values, the results of our study show that there is no measurable correlation on the atomic level using DECT. We established a positive in vitro correlation between Hb/Hct values and ρ. Nevertheless, attenuation emerged as the most strongly correlated parameter with identifiable cutoff values, highlighting its preference for CT-based anemia detection. CLINICAL RELEVANCE STATEMENT: By scanning multiple blood samples with dual-energy CT scans and comparing the measurements with standard laboratory blood tests, we were able to underscore the potential of CT-based anemia detection and its advantages in clinical practice. KEY POINTS: Prior in vivo studies have found a correlation between aortic blood pool and measured hemoglobin and hematocrit. Hemoglobin and hematocrit correlated with electron density relative to water and attenuation but not Zeff. Dual-energy CT has the potential for additional clinical benefits, such as CT-based anemia detection.

2.
Eur Radiol ; 30(4): 1847-1855, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31811427

RESUMO

OBJECTIVE: To develop a deep learning-based artificial intelligence (AI) scheme for predicting the likelihood of the ground-glass nodule (GGN) detected on CT images being invasive adenocarcinoma (IA) and also compare the accuracy of this AI scheme with that of two radiologists. METHODS: First, we retrospectively collected 828 histopathologically confirmed GGNs of 644 patients from two centers. Among them, 209 GGNs are confirmed IA and 619 are non-IA, including 409 adenocarcinomas in situ and 210 minimally invasive adenocarcinomas. Second, we applied a series of pre-preprocessing techniques, such as image resampling, rescaling and cropping, and data augmentation, to process original CT images and generate new training and testing images. Third, we built an AI scheme based on a deep convolutional neural network by using a residual learning architecture and batch normalization technique. Finally, we conducted an observer study and compared the prediction performance of the AI scheme with that of two radiologists using an independent dataset with 102 GGNs. RESULTS: The new AI scheme yielded an area under the receiver operating characteristic curve (AUC) of 0.92 ± 0.03 in classifying between IA and non-IA GGNs, which is equivalent to the senior radiologist's performance (AUC 0.92 ± 0.03) and higher than the score of the junior radiologist (AUC 0.90 ± 0.03). The Kappa value of two sets of subjective prediction scores generated by two radiologists is 0.6. CONCLUSIONS: The study result demonstrates using an AI scheme to improve the performance in predicting IA, which can help improve the development of a more effective personalized cancer treatment paradigm. KEY POINTS: • The feasibility of using a deep learning method to predict the likelihood of the ground-glass nodule being invasive adenocarcinoma. • Residual learning-based CNN model improves the performance in classifying between IA and non-IA nodules. • Artificial intelligence (AI) scheme yields higher performance than radiologists in predicting invasive adenocarcinoma.


Assuntos
Adenocarcinoma in Situ/diagnóstico por imagem , Adenocarcinoma de Pulmão/diagnóstico por imagem , Aprendizado Profundo , Neoplasias Pulmonares/diagnóstico por imagem , Nódulo Pulmonar Solitário/diagnóstico por imagem , Adenocarcinoma in Situ/patologia , Adenocarcinoma de Pulmão/patologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Inteligência Artificial , Progressão da Doença , Estudos de Viabilidade , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica , Redes Neurais de Computação , Curva ROC , Radiologistas , Estudos Retrospectivos , Nódulo Pulmonar Solitário/patologia , Tomografia Computadorizada por Raios X/métodos , Adulto Jovem
3.
Am J Respir Crit Care Med ; 191(3): 316-24, 2015 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-25493340

RESUMO

RATIONALE: The relationship between clinical phenotype of childhood primary ciliary dyskinesia (PCD) and ultrastructural defects and genotype is poorly defined. OBJECTIVES: To delineate clinical features of childhood PCD and their associations with ultrastructural defects and genotype. METHODS: A total of 118 participants younger than 19 years old with PCD were evaluated prospectively at six centers in North America using standardized procedures for diagnostic testing, spirometry, chest computed tomography, respiratory cultures, and clinical phenotyping. MEASUREMENTS AND MAIN RESULTS: Clinical features included neonatal respiratory distress (82%), chronic cough (99%), and chronic nasal congestion (97%). There were no differences in clinical features or respiratory pathogens in subjects with outer dynein arm (ODA) defects (ODA alone; n = 54) and ODA plus inner dynein arm (IDA) defects (ODA + IDA; n = 18) versus subjects with IDA and central apparatus defects with microtubular disorganization (IDA/CA/MTD; n = 40). Median FEV1 was worse in the IDA/CA/MTD group (72% predicted) versus the combined ODA groups (92% predicted; P = 0.003). Median body mass index was lower in the IDA/CA/MTD group (46th percentile) versus the ODA groups (70th percentile; P = 0.003). For all 118 subjects, median number of lobes with bronchiectasis was three and alveolar consolidation was two. However, the 5- to 11-year-old IDA/CA/MTD group had more lobes of bronchiectasis (median, 5; P = 0.0008) and consolidation (median, 3; P = 0.0001) compared with the ODA groups (median, 3 and 2, respectively). Similar findings were observed when limited to participants with biallelic mutations. CONCLUSIONS: Lung disease was heterogeneous across all ultrastructural and genotype groups, but worse in those with IDA/CA/MTD ultrastructural defects, most of whom had biallelic mutations in CCDC39 or CCDC40.


Assuntos
Alelos , Proteínas do Citoesqueleto/genética , Síndrome de Kartagener/genética , Mutação , Proteínas/genética , Adolescente , Biomarcadores/sangue , Biópsia , Índice de Massa Corporal , Canadá , Criança , Pré-Escolar , Feminino , Genótipo , Humanos , Síndrome de Kartagener/diagnóstico , Masculino , Fenótipo , Estudos Prospectivos , Índice de Gravidade de Doença , Espirometria , Estados Unidos
4.
Aust Dent J ; 64(2): 161-166, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-30839124

RESUMO

OBJECTIVE: To determine the accuracy of various cone beam computed tomography (CBCT) devices in assessing the buccal bone in anterior teeth. MATERIAL AND METHODS: A skull encased in tissue equivalent material was imaged with six CBCT devices: 3D Accuitomo 170 (J. Morita, Japan), CS 9000 3D (Carestream Dental, France), CS 9300 (Carestream Dental, France), Eagle 3D (Dabi Atlante, Brazil), i-CAT Classic (Imaging Sciences International, USA) and Orthophos XG 3D (Sirona Dental System, USA). The exposure and acquisition protocols were determined using the manufacturer's guidelines, the voxel size adjusted as close as possible to 0.2 mm. Cross-sectional images were evaluated randomly, and the buccal bone was assessed. RESULTS: The statistics were calculated based on a logistic regression model with the significance level set at 5%. All CBCT devices showed high accuracy; however, observers noted that the accuracy and sensitivity of CS 9300 device were slightly superior. CONCLUSION: The diagnostic performance of all CBCT devices was high for the evaluation of buccal bone in anterior teeth. When the clinical usefulness of an imaging modality is equivalent, the choice of appropriate imaging should be directed towards the modality that delivers the least radiation dose to the patient for a specific diagnostic task.


Assuntos
Tomografia Computadorizada de Feixe Cônico , Mandíbula , Maxila , Tomografia Computadorizada de Feixe Cônico/métodos , Estudos Transversais , Humanos , Processamento de Imagem Assistida por Computador , Imageamento Tridimensional , Mandíbula/anatomia & histologia , Mandíbula/diagnóstico por imagem , Maxila/anatomia & histologia , Maxila/diagnóstico por imagem
5.
Healthc Inform Res ; 22(4): 305-315, 2016 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-27895963

RESUMO

OBJECTIVES: This work was a comparative study that aimed to find a proper method for accurately segmenting persistent ground glass nodules (GGN) in thin-section computed tomography (CT) images after detecting them. METHODS: To do this, we first applied five types of semi-automatic segmentation methods (i.e., level-set-based active contour model, localized region-based active contour model, seeded region growing, K-means clustering, and fuzzy C-means clustering) to preprocessed GGN images, respectively. Then, to measure the similarities, we calculated the Dice coefficient of the segmented area using each semiautomatic method with the result of the manually segmented area by two radiologists. RESULTS: Comparison experiments were performed using 40 persistent GGNs. In our experiment, the mean Dice coefficient for each semiautomatic segmentation tool with manually segmented area was 0.808 for the level-set-based active contour model, 0.8001 for the localized region-based active contour model, 0.629 for seeded region growing, 0.7953 for K-means clustering, and 0.7999 for fuzzy C-means clustering, respectively. CONCLUSIONS: The level-set-based active contour model algorithm showed the best performance, which was most similar to the result of manual segmentation by two radiologists. From the differentiation between the normal parenchyma and the nodule, it was also the most efficient. Effective segmentation methods will be essential for the development of computer-aided diagnosis systems for more accurate early diagnosis and prognosis of lung cancer in thin-section CT images.

6.
Malays J Med Sci ; 19(1): 69-72, 2012 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-22977378

RESUMO

Obturator hernia is a rare condition that may present in an acute or subacute setting in correlation with the degree of small-bowel obstruction. Pre-operative diagnosis is difficult, as symptoms are often non-specific. A high index of suspicion should be maintained for emaciated elderly women with small-bowel obstruction without a previous abdominal operation and a positive Howship-Romberg sign. When diagnosis is in doubt, computed tomography scan of the abdomen and the pelvis (if available) or laparotomy should be performed immediately, as high mortality rate is related to the perforation of gangrenous bowels. We present 2 cases of strangulated obturator hernia, managed differently with both open and laparoscopic approaches. The diagnostic accuracy of computed tomography scan is highlighted followed by a brief literature review with an emphasis placed on surgical management.

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