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1.
J Comput Assist Tomogr ; 44(1): 13-19, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939876

RESUMEN

OBJECTIVE: To evaluate image quality and radiation dose exposure of low-kV setting and low-volume contrast medium (CM) computed tomography angiography (CTA) protocol for transcatheter aortic valve implantation (TAVI) planning in comparison with standard CTA protocol. METHODS: Sixty-patients were examined with 256-row MDCT for TAVI planning: 32 patients (study group) were evaluated using 80-kV electrocardiogram-gated protocol with 60 mL of CM and IMR reconstruction; 28 patients underwent a standard electrocardiogram-gated CTA study (100 kV; 80 mL of CM; iDose4 reconstruction). Subjective and objective image quality was evaluated in each patient at different aortic levels. Finally, we collected radiation dose exposure data (CT dose index and dose-length product) of both groups. RESULTS: In study protocol, significant higher mean attenuation values were achieved in all measurements compared with the standard protocol. There were no significant differences in the subjective image quality evaluation in both groups. Mean dose-length product of study group was 56% lower than in the control one (P < 0.0001). CONCLUSION: Low-kV and low-CM volume CTA, combined with IMR, allows to correctly performing TAVI planning with high-quality images and significant radiation dose reduction compared with standard CTA protocol.


Asunto(s)
Estenosis de la Válvula Aórtica/diagnóstico por imagen , Angiografía por Tomografía Computarizada/métodos , Medios de Contraste/administración & dosificación , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Adulto , Anciano , Anciano de 80 o más Años , Algoritmos , Estenosis de la Válvula Aórtica/cirugía , Femenino , Humanos , Bases del Conocimiento , Masculino , Persona de Mediana Edad , Tomografía Computarizada Multidetector , Periodo Preoperatorio , Dosis de Radiación , Reemplazo de la Válvula Aórtica Transcatéter
2.
J Comput Assist Tomogr ; 44(1): 26-31, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939878

RESUMEN

Coronary computed tomography angiography is widely used in clinical practice. Although 3-dimensional (D) volume rendering is useful for interpretation of coronary path and territory, 2D output is common for image interpretation. Most picture archiving and communication system is incapable of manipulating 3D due to insufficient graphic specification. Thus, 2D bull's eye map display is frequently used in cardiac imaging. We developed a bull's eye map which emulated the anatomical information of individual coronary path and dominancy.


Asunto(s)
Vasos Coronarios/diagnóstico por imagen , Ventrículos Cardíacos/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Anciano , Algoritmos , Angiografía por Tomografía Computarizada , Femenino , Humanos , Imagen Tridimensional , Masculino , Persona de Mediana Edad , Estudios Retrospectivos
3.
J Comput Assist Tomogr ; 44(1): 37-42, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939880

RESUMEN

OBJECTIVE: The purpose of this study was to determine whether computed tomography (CT) angiography with machine learning (ML) can be used to predict the rapid growth of abdominal aortic aneurysm (AAA). MATERIALS AND METHODS: This retrospective study was approved by our institutional review board. Fifty consecutive patients (45 men, 5 women, 73.5 years) with small AAA (38.5 ± 6.2 mm) had undergone CT angiography. To be included, patients required at least 2 CT scans a minimum of 6 months apart. Abdominal aortic aneurysm growth, estimated by change per year, was compared between patients with baseline infrarenal aortic minor axis. For each axial image, major axis of AAA, minor axis of AAA, major axis of lumen without intraluminal thrombi (ILT), minor axis of lumen without ILT, AAA area, lumen area without ILT, ILT area, maximum ILT area, and maximum ILT thickness were measured. We developed a prediction model using an ML method (to predict expansion >4 mm/y) and calculated the area under the receiver operating characteristic curve of this model via 10-fold cross-validation. RESULTS: The median aneurysm expansion was 3.0 mm/y. Major axis of AAA and AAA area correlated significantly with future AAA expansion (r = 0.472, 0.416 all P < 0.01). Machine learning and major axis of AAA were a strong predictor of significant AAA expansion (>4 mm/y) (area under the receiver operating characteristic curve were 0.86 and 0.78). CONCLUSIONS: Machine learning is an effective method for the prediction of expansion risk of AAA. Abdominal aortic aneurysm area and major axis of AAA are the important factors to reflect AAA expansion.


Asunto(s)
Aneurisma de la Aorta Abdominal/diagnóstico por imagen , Angiografía por Tomografía Computarizada/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Anciano , Anciano de 80 o más Años , Progresión de la Enfermedad , Femenino , Humanos , Aprendizaje Automático , Masculino , Estudios Retrospectivos
4.
J Comput Assist Tomogr ; 44(1): 53-58, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939882

RESUMEN

OBJECTIVE: In the diagnosis of superior semicircular canal dehiscence (SSCD), computed tomography (CT) is the only imaging method. The aims of the study were to show that reformat images are more accurate than standard planes for diagnosis of SSCD and to determine the prevalence of SSCD. METHODS: The retrospective review yielded 1309 temporal CTs performed in our radiology department for any reason. Two radiologist interpreted CTs in standard planes collaboratively. Patients with SSCD were reinterpreted in Pöschl and Stenvers planes by 2 radiologists separately. RESULTS: Statistical analysis was made by accepting that 2 radiologists diagnosis were accurate in Pöschl plane. Coronal plane sensitivity 86%, specificity 64%, Stenvers plane sensitivity 96%, and specificity 52% have been found in the mean result of 2 observers (P < 0.001). CONCLUSIONS: In the diagnosis of SSCD, standard and Stenvers planes can cause false-negative and false-positive diagnoses. Interpretation in Pöschl plane can significantly increase sensitivity, specificity, negative, and positive predictive values for diagnosing dehiscence.


Asunto(s)
Enfermedades del Laberinto/diagnóstico por imagen , Tomografía Computarizada Multidetector/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Canales Semicirculares/anomalías , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Canales Semicirculares/diagnóstico por imagen , Sensibilidad y Especificidad , Adulto Joven
5.
J Comput Assist Tomogr ; 44(1): 83-89, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939887

RESUMEN

RATIONALE AND OBJECTIVES: This novel study aims to investigate texture parameters in distinguishing malignant and benign breast lesions classified as Breast Imaging Reporting and Data System 4 in dynamic contrast-enhanced magnetic resonance imaging (MRI). MATERIALS AND METHODS: This retrospective study included 203 patients with 136 breast cancer and 67 benign lesions who underwent breast MRI between November 23, 2016, and August 27, 2018. Co-occurrence matrix-based texture features were extracted from each lesion on T1-weighted contrast-enhanced MRI using MatLab software. The association between texture parameters and breast lesions was analyzed, and the diagnostic model for breast cancer was created. Classification performance was evaluated by the area under the receiver operating characteristic curve, sensitivity, and specificity. RESULTS: Significant differences were seen between malignant and benign lesions for a number of textural features, including contrast, correlation, autocorrelation, dissimilarity, cluster shade, and cluster performance (P < 0.05). After the analysis of the multicollinearity, 5 texture features (contrast, correlation, dissimilarity, cluster shade, and cluster performance) were included for the next principal component analysis. The differentiation accuracy of breast cancer based on the diagnostic model was 0.948 (95% confidence interval, 0.908-0.974). CONCLUSIONS: Texture features that measure randomness, heterogeneity, or homogeneity may reflect underlying growth patterns of breast lesions and show great difference in malignant and benign lesions. Therefore, texture analysis may be a valuable assisted tool for diagnostic analysis on breast.


Asunto(s)
Neoplasias de la Mama/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Algoritmos , Área Bajo la Curva , Femenino , Humanos , Imagen por Resonancia Magnética , Persona de Mediana Edad , Estudios Retrospectivos , Sensibilidad y Especificidad , Adulto Joven
6.
J Comput Assist Tomogr ; 44(1): 95-101, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939889

RESUMEN

PURPOSE: This study aimed to evaluate image quality of ultra-low dose chest computed tomography using 6 iterative reconstruction (IR) algorithms. METHOD: A lung phantom was scanned on 4 computed tomography scanners using fixed tube voltages and the lowest mAs available on each scanner, resulting in dose levels of 0.1 to 0.2 mGy (80 kVp) and 0.3 to 1 mGy (140 kVp) volume CT dose index (CTDIvol). Images were reconstructed with IR available on the scanners. Image noise, signal-to-noise ratios, contrast-to-noise ratios, uniformity, and noise power spectrum (NPS) were assessed for evaluation of image quality. RESULTS: Image quality parameters increased with increasing dose for all algorithms. At constant dose levels, model-based techniques improved the contrast-to-noise ratio of lesions more than the statistical algorithms. All algorithms tested at 0.1 mGy showed lower NPS peak frequencies compared with 0.39 mGy. In contrast to the statistical techniques, model-based algorithms showed lower NPS peak frequencies at the lowest doses, indicating a coarser and blotchier noise texture. CONCLUSION: This study shows the importance of evaluating IR when introduced clinically.


Asunto(s)
Pulmón/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/instrumentación , Algoritmos , Medios de Contraste , Humanos , Fantasmas de Imagen , Dosis de Radiación , Relación Señal-Ruido
7.
J Comput Assist Tomogr ; 44(1): 118-123, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939892

RESUMEN

AIM: This study aimed to assess the interobserver agreement of magnetic resonance (MR) imaging of Liver Imaging Reporting and Data System version 2018 (LI-RADS v2018). SUBJECTS AND METHODS: Retrospective analysis was done for 119 consecutive patients (77 male and 42 female) at risk of hepatocellular carcinoma who underwent dynamic contrast MR imaging. Image analysis was done by 2 independent and blinded readers for arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, and size. Hepatic lesions were classified into 7 groups according to LI-RADS v2018. RESULTS: There was excellent interobserver agreement of both reviewers for LR version 4 (κ = 0.887, P = 0.001) with 90.76% agreement. There was excellent interobserver agreement for nonrim arterial phase hyperenhancement (κ = 0.948; 95% confidence interval [CI], 0.89-0.99; P = 0.001), washout appearance (κ = 0.949; 95% CI, 0.89-1.0; P = 0.001); and enhancing capsule (κ = 0.848; 95% CI, 0.73-0.97; P = 0.001) and excellent reliability of size (interclass correlation, 0.99; P = 0.001). There was excellent interobserver agreement for LR-1 (κ = 1.00, P = 0.001), LR-2 (κ = 0.94, P = 0.001), LR-5 (κ = 0.839, P = 0.001), LR-M (κ = 1.00, P = 0.001), and LR-TIV (κ = 1.00; 95% CI, 1.0-1.0; P = 0.001), and good agreement for LR-3 (κ = 0.61, P = 0.001) and LR-4 (κ = 0.61, P = 0.001). CONCLUSION: MR imaging of LI-RADS v2018 is a reliable imaging modality and reporting system that may be used for standard interpretation of hepatic focal lesions.


Asunto(s)
Carcinoma Hepatocelular/diagnóstico por imagen , Neoplasias Hepáticas/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Variaciones Dependientes del Observador , Estudios Retrospectivos
8.
J Comput Assist Tomogr ; 44(1): 138-144, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939895

RESUMEN

OBJECTIVE: The aim of this study was to determine the influence of virtual monoenergetic images (vMEIs) on renal cortex volumetry (RCV) and estimation of split-renal function. METHODS: Twenty-five patients (mean ± SD, 64.7 ± 9.9 years) underwent a contrast-enhanced dual-layer spectral detector computed tomography. Images were reconstructed with a reference standard (iterative model reconstruction, IMRRef), a newly spectral detector computed tomography algorithm (SPcon) and vMEI at 40, 60, 80, 100, and 120 keV. Two blinded independent readers performed RCV on all data sets with a semiautomated tool. RESULTS: Total kidney volume was up to 15% higher in vMEI at 40/60 keV compared with IMRRef (P < 0.001). Total kidney volume with vMEI at 80/100 keV was similar to IMRRef (P < 0.001). Split-renal function was similar in all reconstructions at approximately 50% ± 3%. Bland-Altman analysis showed no significant differences (P > 0.05), except for 40 keV versus SPcon (P < 0.05). The time required to perform RCV was reasonable, approximately 4 minutes, and showed no significant differences among reconstructions. Interreader agreement was greatest with vMEI at 80 keV (r = 0.68; 95% confidence interval, 0.39-0.85; P < 0.0002) followed by IMRRef images (r = 0.67; 95% confidence interval, 0.37-0.84; P < 0.0003). IMRRef showed the highest mean Hounsfield unit for cortex/medulla of 223.4 ± 73.7/62.5 ± 19.7 and a ratio of 3.7. CONCLUSIONS: Semiautomated RCV performed with vMEI and IMRRef/SPcon is feasible and showed no clinically relevant differences with regard to split-renal function. Low-kiloelectron volt vMEI showed greater tissue contrast and total kidney volume but no benefit for RCV. Moderate-kiloelectron volt vMEI (80 keV) results were similar to IMRRef with a faster postprocessing time.


Asunto(s)
Corteza Renal/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Tomografía Computarizada por Rayos X/métodos , Anciano , Algoritmos , Femenino , Humanos , Corteza Renal/patología , Masculino , Persona de Mediana Edad , Variaciones Dependientes del Observador , Estudios Retrospectivos , Sensibilidad y Especificidad , Relación Señal-Ruido
9.
J Comput Assist Tomogr ; 44(1): 145-152, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31939896

RESUMEN

OBJECTIVES: We investigated the computed tomographic characteristics of gastrointestinal air motion artifact (GIAMA), which can be misinterpreted as active gastrointestinal bleeding. METHODS: We simulated GIAMA using 3 types of air-ball phantoms (air-ball in water, air-ball in oil, air-water-ball in oil) and a bovine intestine in oil phantom. We also performed a retrospective clinical review of precontrast abdominal computed tomography images of 76 patients to investigate the frequency, location, shape, and maximum density of hyperdense GIAMA. RESULTS: In phantom studies, air motion artifacts appeared as dark and bright streak artifacts at the borders of a moving air-ball and water or oil. In the clinical study, hyperdense GIAMA was visualized in 60 (79.0%) of 76 patients. The small intestine was most commonly affected (46.4%), and the intramural type had the highest frequency (58.0%). CONCLUSION: Knowing the radiologic features of GIAMA can assists radiologists in identifying active gastrointestinal bleeding sites accurately.


Asunto(s)
Hemorragia Gastrointestinal/diagnóstico por imagen , Tomografía Computarizada Multidetector/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Adulto , Anciano , Anciano de 80 o más Años , Animales , Bovinos , Reacciones Falso Positivas , Femenino , Humanos , Masculino , Persona de Mediana Edad , Fantasmas de Imagen , Estudios Retrospectivos , Sensibilidad y Especificidad , Adulto Joven
10.
J Comput Assist Tomogr ; 44(1): 75-77, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31804241

RESUMEN

Computed tomography perfusion (CTP) is increasingly used to determine treatment eligibility for acute ischemic stroke patients. Automated postprocessing of raw CTP data is routinely used, but it can fail. In reviewing 176 consecutive acute ischemic stroke patients, failures occurred in 20 patients (11%) during automated postprocessing by the RAPID software. Failures were caused by motion (n = 11, 73%), streak artifacts (n = 2, 13%), and poor contrast bolus arrival (n = 2, 13%). Stroke physicians should review CTP results with care before they are being integrated in their decision-making process.


Asunto(s)
Isquemia Encefálica/diagnóstico por imagen , Procesamiento Automatizado de Datos/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Accidente Cerebrovascular/diagnóstico por imagen , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Masculino , Persona de Mediana Edad , Imagen de Perfusión/métodos , Factores de Riesgo , Sensibilidad y Especificidad , Programas Informáticos , Tomografía Computarizada por Rayos X
11.
J Comput Assist Tomogr ; 44(1): 43-46, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-31789683

RESUMEN

OBJECTIVE: The objective of this study was to investigate the frequency of hippocampal sulcus remnants (HSRs) in nonelderly adults using ultra-high-resolution 7T magnetic resonance (MR) images and their imaging features. METHODS: A total of 33 healthy adults underwent 7T MR, and multiplanar images of 66 temporal lobes were reviewed independently by 2 neuroradiologists. The detectability of the HSR was calculated. In addition, the interobserver agreement on the rating scale was evaluated using the κ statistic. RESULTS: Both observers identified HSRs with 7T MR images in all subjects. Excellent interobserver agreement was shown (κ = 1.0). The shape of HSRs was variable (spot-like, curvilinear, ovoid, or beaded appearance). Volumes of the HSRs were not correlated with age. CONCLUSIONS: Hippocampal sulcus remnants are commonly seen in healthy nonelderly adults using 7T MR imaging. Accurate diagnosis of HSR based on the microanatomy of hippocampus makes it easier to differentiate them from lesions, and it may help prevent unnecessary treatment.


Asunto(s)
Hipocampo/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Adulto , Algoritmos , Femenino , Voluntarios Sanos , Humanos , Masculino , Persona de Mediana Edad , Variaciones Dependientes del Observador , Adulto Joven
12.
Int J Cardiovasc Imaging ; 36(1): 149-159, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31538258

RESUMEN

Evaluation of myocardial regional function is generally performed by visual "eyeballing" which is highly subjective. A robust quantifiable parameter of regional function is required to provide an objective, repeatable and comparable measure of myocardial performance. We aimed to evaluate the clinical utility of novel regional myocardial strain software from cardiac computed tomography (CT) datasets. 93 consecutive patients who had undergone retrospectively gated cardiac CT were evaluated by the software, which utilizes a finite element based tracking algorithm through the cardiac cycle. Circumferential (CS), longitudinal (LS) and radial (RS) strains were calculated for each of 16 myocardial segments and compared to a visual assessment, carried out by an experienced cardiologist on cine movies of standard "echo" views derived from the CT data. A subset of 37 cases was compared to speckle strain by echocardiography. The automated software performed successfully in 93/106 cases, with minimal human interaction. Peak CS, LS and RS all differentiated well between normal, hypokinetic and akinetic segments. Peak strains for akinetic segments were generally post-systolic, peaking at 50 ± 17% of the RR interval compared to 43 ± 9% for normokinetic segments. Using ROC analysis to test the ability to differentiate between normal and abnormal segments, the area under the curve was 0.84 ± 0.01 for CS, 0.80 ± 0.02 for RS and 0.68 ± 0.02 for LS. There was a moderate agreement with speckle strain. Automated 4D regional strain analysis of CT datasets shows a good correspondence to visual analysis and successfully differentiates between normal and abnormal segments, thus providing an objective quantifiable map of myocardial regional function.


Asunto(s)
Algoritmos , Cardiopatías/diagnóstico por imagen , Tomografía Computarizada Multidetector/métodos , Contracción Miocárdica , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Programas Informáticos , Función Ventricular Izquierda , Anciano , Automatización , Ecocardiografía , Femenino , Cardiopatías/fisiopatología , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Reproducibilidad de los Resultados , Estudios Retrospectivos
13.
J Laryngol Otol ; 134(1): 52-55, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31865928

RESUMEN

OBJECTIVE: Deep learning using convolutional neural networks represents a form of artificial intelligence where computers recognise patterns and make predictions based upon provided datasets. This study aimed to determine if a convolutional neural network could be trained to differentiate the location of the anterior ethmoidal artery as either adhered to the skull base or within a bone 'mesentery' on sinus computed tomography scans. METHODS: Coronal sinus computed tomography scans were reviewed by two otolaryngology residents for anterior ethmoidal artery location and used as data for the Google Inception-V3 convolutional neural network base. The classification layer of Inception-V3 was retrained in Python (programming language software) using a transfer learning method to interpret the computed tomography images. RESULTS: A total of 675 images from 388 patients were used to train the convolutional neural network. A further 197 unique images were used to test the algorithm; this yielded a total accuracy of 82.7 per cent (95 per cent confidence interval = 77.7-87.8), kappa statistic of 0.62 and area under the curve of 0.86. CONCLUSION: Convolutional neural networks demonstrate promise in identifying clinically important structures in functional endoscopic sinus surgery, such as anterior ethmoidal artery location on pre-operative sinus computed tomography.


Asunto(s)
Senos Etmoidales/irrigación sanguínea , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Aprendizaje Profundo , Senos Etmoidales/diagnóstico por imagen , Femenino , Humanos , Masculino , Tomografía Computarizada por Rayos X
14.
Br J Radiol ; 93(1105): 20190069, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31642702

RESUMEN

OBJECTIVE: To evaluate the impact of different metal artifact reduction (MAR) algorithms on Hounsfield unit (HU) and standardized uptake values (SUV) in a phantom setting and verify these results in patients with metallic implants undergoing oncological PET/CT examinations. METHODS AND MATERIALS: In this prospective study, PET-CT examinations of 28 oncological patients (14 female, 14 male, mean age 69.5 ± 15.2y) with 38 different metal implants were included. CT datasets were reconstructed using standard weighted filtered back projection (WFBP) without MAR, MAR in image space (MARIS) and iterative MAR (iMAR, hip algorithm). The three datasets were used for PET attenuation correction. SUV and HU measurements were performed at the site of the most prominent bright and dark band artifacts. Differences between HU and SUV values across the different reconstructions were compared using paired t-tests. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.017). RESULTS: For bright band artifacts, MARIS led to a non-significant mean decrease of 12.0% (345 ± 315 HU) in comparison with WFBP (391 ± 293 HU), whereas iMAR led to a significant decrease of 68.3% (125 ± 185 HU, p < 0.017). For SUVmean, MARIS showed no significant effect in comparison with WFBP (WFBP: 0.99 ± 0.40, MARIS: 0.96 ± 0.39), while iMAR led to a significant decrease of 11.1% (0.88 ± 0.35, p < 0.017). Similar results were observed for dark band artifacts. CONCLUSION: iMAR significantly reduces artifacts caused by metal implants in CT and thus leads to a significant change of SUV measurements in bright and dark band artifacts compared with WFBP and MARIS, thus probably improving PET quantification. ADVANCES IN KNOWLEDGE: The present work indicates that MAR algorithms such as iMAR algorithm in integrated PET/CT scanners are useful to improve CT image quality as well as PET quantification in the evaluation of tracer uptake adjacent to large metal implants. A detailed analysis of oncological patients with various large metal implants using different MAR algorithms in PET/CT has not been conducted yet.


Asunto(s)
Artefactos , Metales , Tomografía Computarizada por Tomografía de Emisión de Positrones/métodos , Prótesis e Implantes , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Anciano , Algoritmos , Femenino , Fluorodesoxiglucosa F18 , Humanos , Masculino , Fantasmas de Imagen , Estudios Prospectivos , Radiofármacos
15.
Br J Radiol ; 93(1105): 20181019, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31724436

RESUMEN

OBJECTIVE: The aim of this phantom study was to investigate the effect of scan parameters and noise suppression techniques on the minimum radiation dose for acceptable image quality for CT emphysema densitometry. METHODS: The COPDGene phantom was scanned on a third generation dual-source CT system with 16 scan setups (CTDIvol 0.035-10.680 mGy). Images were reconstructed at 1.0/0.7 mm slice thickness/increment, with three kernels (one soft, two hard), filtered backprojection and three grades of third-generation iterative reconstruction (IR). Additionally, deep learning-based noise suppression software was applied. Main outcomes: overlap in area of the normalized histograms of CT density for the emphysema insert and lung material, and the radiation dose required for a maximum of 4.3% overlap (defined as acceptable image quality). RESULTS: In total, 384 scan reconstructions were analyzed. Decreasing radiation dose resulted in an exponential increase of the overlap in normalized histograms of CT density. The overlap was 11-91% for the lowest dose setting (CTDIvol 0.035mGy). The soft kernel reconstruction showed less histogram overlap than hard filter kernels. IR and noise suppression also reduced overlap. Using intermediate grade IR plus noise suppression software allowed for 85% radiation dose reduction while maintaining acceptable image quality. CONCLUSION: CT density histogram overlap can quantify the degree of discernibility of emphysema and healthy lung tissue. Noise suppression software, IR, and soft reconstruction kernels substantially decrease the dose required for acceptable image quality. ADVANCES IN KNOWLEDGE: Noise suppression software, IR, and soft reconstruction kernels allow radiation dose reduction by 85% while still allowing differentiation between emphysema and normal lung tissue.


Asunto(s)
Fantasmas de Imagen , Enfisema Pulmonar/diagnóstico por imagen , Dosis de Radiación , Tomografía Computarizada por Rayos X/métodos , Humanos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos
16.
Eur Radiol ; 30(1): 163-174, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31359127

RESUMEN

OBJECTIVES: To assess the impact of recently developed respiratory motion correction software on contrast-enhanced cone beam CT angiography (CBCT-a) for intraprocedural image guidance during intra-arterial liver-directed therapy. METHODS: From 2015 to 2017, two groups of patients who underwent intra-arterial liver-directed therapy with (breathing, n = 30) or without (still, n = 30) significant respiratory motion artifacts were retrospectively included. All CBCT-a were processed with and without dedicated respiratory motion correction software. Four readers independently assessed the following in both reconstructions (motion correction ON and OFF): (1) overall image quality on a 0-to-5 point scale, and (2) presence of relevant peri-procedural information on tumor and vasculature (overall vessel geometry, visibility of extrahepatic vessels, target tumor conspicuity, visibility of tumor feeders). RESULTS: Motion correction increased the average image quality in the breathing group from 2.0 ± 0.9 to 2.9 ± 1.0 (p < 0.01). The visibility of vessel geometry, extrahepatic vessels, and tumor feeders was significantly improved for all readers, and tumor conspicuity was improved for three readers. The average image quality was not significantly different between reconstructions in the still group (motion correction ON and OFF), for any of the readers (4.0 ± 0.6 vs 4.2 ± 0.6; p = 0.12). There was no change in the visibility of vessel geometry, extrahepatic vessels, tumor feeders, or tumor conspicuity for the four readers using the respiratory motion correction software in this group. CONCLUSIONS: Using the dedicated respiratory motion correction software during intra-arterial liver-directed procedures increases the visualization of relevant peri-procedural information and image quality in CBCT-a corrupted by respiratory motion artifacts without affecting these elements in still CBCT-a. KEY POINTS: • The use of respiratory motion correction software could reduce the need for cone beam CT angiography acquisition retake. • Motion correction software significantly increases the visibility of vessel geometry, extrahepatic vessels, and tumor feeders, as well as tumor conspicuity in cone beam CT angiography corrupted by respiratory motion artifacts. • The use of respiratory motion correction software on cone beam CT angiography uncorrupted by respiratory motion artifact does not result in decreased image quality.


Asunto(s)
Artefactos , Angiografía por Tomografía Computarizada/métodos , Tomografía Computarizada de Haz Cónico/métodos , Neoplasias Hepáticas , Intensificación de Imagen Radiográfica/métodos , Anciano , Anciano de 80 o más Años , Algoritmos , Quimioembolización Terapéutica/métodos , Femenino , Humanos , Neoplasias Hepáticas/diagnóstico por imagen , Neoplasias Hepáticas/terapia , Persona de Mediana Edad , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Respiración , Estudios Retrospectivos , Programas Informáticos
17.
Eur Radiol ; 30(1): 571-580, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31385049

RESUMEN

OBJECTIVE: To clarify the relationship between entrance surface dose (ESD) and physical image quality of original and bone-suppressed chest radiographs acquired using high and low tube voltages. METHODS: An anthropomorphic chest phantom and a 12-mm diameter spherical simulated nodule with a CT value of approximately + 100 HU were used. The lung field in the chest radiograph was divided into seven areas, and the nodule was set in a total of 66 positions. A total of 264 chest radiographs were acquired using four ESD conditions: approximately 0.3 mGy at 140 and 70 kVp and approximately 0.2 and 0.1 mGy at 70 kVp. The radiographs were processed to produce bone-suppressed images. Differences in contrast and contrast-to-noise ratio (CNR) values of the nodule between each condition and between the original and bone-suppressed images were analyzed by a two-sided Wilcoxon signed-rank test. RESULTS: In the areas not overlapping with the ribs, both contrast and CNR values were significantly increased with the bone-suppression technique (p < 0.01). In the bone-suppressed images, these values of the three conditions at 70 kVp were equal to or significantly higher than those of the condition at 140 kVp. There was no apparent decrease in these values between the ESD of approximately 0.3 and 0.1 mGy at 70 kVp. CONCLUSION: By using the shortest exposure time and the lowest tube voltage possible not to increase in blurring artifact and image noise, it is possible to improve the image quality of bone-suppressed images and reduce the patient dose. KEY POINTS: • The effectiveness of bone-suppression techniques differs in areas of lung field. • Image quality of bone-suppressed chest radiographs is improved by lower tube voltage. • Applying lower tube voltage to bone-suppressed chest radiographs leads to dose reduction.


Asunto(s)
Mejoramiento de la Calidad/estadística & datos numéricos , Dosis de Radiación , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Radiografía Torácica/métodos , Tomografía Computarizada por Rayos X/métodos , Artefactos , Humanos , Fantasmas de Imagen , Reproducibilidad de los Resultados
18.
Eur Radiol ; 30(1): 425-431, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31332557

RESUMEN

OBJECTIVES: To assess the capability of a newly developed material decomposition method from contrast-enhanced dual-energy CT images, aiming to better visualize the aortic wall and aortic intramural hematoma (IMH), compared with true non-contrast (TNC) CT. MATERIALS AND METHODS: Twenty-two patients (11 women; mean age, 61 ± 20 years) with acute chest pain underwent 25 dual-layer non-contrast and contrast-enhanced CT. CT-angiography images were retrospectively processed using two-material decomposition analysis, where we defined the first material as the content of a region of interest placed in the ascending aorta for each patient, and the second material as water. Two independent radiologists assessed the images from the second material termed "dark-blood" images and the TNC images regarding contrast-to-noise ratio (CNR) between the wall and the lumen, diagnostic quality regarding the presence of aortic wall thickening, and the inner/outer vessel wall conspicuity. RESULTS: Diagnostic quality scores in normal aortic segments were 0.9 ± 0.3 and 2.7 ± 0.6 (p < 0.001) and wall conspicuity scores were 0.7 ± 0.5 and 1.8 ± 0.3 (p < 0.001) on TNC and dark-blood images, respectively. In aortic segments with IMH, diagnostic quality scores were 1.7 ± 0.5 and 2.4 ± 0.6 (p < 0.001) and wall conspicuity scores were 0.7 ± 0.7 and 1.8 ± 0.3 (p < 0.001) on TNC and dark-blood images, respectively. In normal aortic segments, CNRs were 0.3 ± 0.2 and 2.8 ± 0.9 on TNC and dark-blood images, respectively (p < 0.001). In aortic segments with IMH, CNRs were 0.3 ± 0.2 and 4.0 ± 1.0 on TNC and dark-blood images, respectively (p < 0.001). CONCLUSIONS: Compared with true non-contrast CT, dark-blood material decomposition maps enhance quantitative and qualitative image quality for the assessment of normal aortic wall and IMH. KEY POINTS: • Current dual-energy CT-angiography provides virtual non-contrast and bright-blood images. • Dark-blood images represent a new way to assess the vascular wall structure with dual-energy CT and can improve the lumen-to-wall contrast compared with true non-contrast CT. • This dual-energy CT material decomposition method is likely to improve contrast resolution in other applications as well, taking advantage of the high spatial resolution of CT.


Asunto(s)
Aorta Torácica/diagnóstico por imagen , Enfermedades de la Aorta/diagnóstico por imagen , Hematoma/diagnóstico por imagen , Adulto , Anciano , Anciano de 80 o más Años , Angiografía por Tomografía Computarizada/métodos , Medios de Contraste , Estudios de Factibilidad , Femenino , Humanos , Masculino , Persona de Mediana Edad , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Reproducibilidad de los Resultados , Estudios Retrospectivos , Sensibilidad y Especificidad , Tomografía Computarizada por Rayos X/métodos
19.
Eur Radiol ; 30(1): 487-500, 2020 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-31359122

RESUMEN

PURPOSE: To assess the dose performance in terms of image quality of filtered back projection (FBP) and two generations of iterative reconstruction (IR) algorithms developed by the most common CT vendors. MATERIALS AND METHODS: We used four CT systems equipped with a hybrid/statistical IR (H/SIR) and a full/partial/advanced model-based IR (MBIR) algorithms. Acquisitions were performed on an ACR phantom at five dose levels. Raw data were reconstructed using a standard soft tissue kernel for FBP and one iterative level of the two IR algorithm generations. The noise power spectrum (NPS) and the task-based transfer function (TTF) were computed. A detectability index (d') was computed to model the detection task of a large mass in the liver (large feature; 120 HU and 25-mm diameter) and a small calcification (small feature; 500 HU and 1.5-mm diameter). RESULTS: With H/SIR, the highest values of d' for both features were found for Siemens, then for Canon and the lowest values for Philips and GE. For the large feature, potential dose reductions with MBIR compared with H/SIR were - 35% for GE, - 62% for Philips, and - 13% for Siemens; for the small feature, corresponding reductions were - 45%, - 78%, and - 14%, respectively. With the Canon system, a potential dose reduction of - 32% was observed only for the small feature with MBIR compared with the H/SIR algorithm. For the large feature, the dose increased by 100%. CONCLUSION: This multivendor comparison of several versions of IR algorithms allowed to compare the different evolution within each vendor. The use of d' is highly adapted and robust for an optimization process. KEY POINTS: • The performance of four CT systems was evaluated by using imQuest software to assess noise characteristic, spatial resolution, and lesion detection. • Two task functions were defined to model the detection task of a large mass in the liver and a small calcification. • The advantage of task-based image quality assessment for radiologists is that it does not include only complicated metrics, but also clinically meaningful image quality.


Asunto(s)
Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Algoritmos , Calcinosis/diagnóstico por imagen , Humanos , Hepatopatías/diagnóstico por imagen , Neoplasias Hepáticas/diagnóstico por imagen , Fantasmas de Imagen , Garantía de la Calidad de Atención de Salud/métodos , Dosis de Radiación , Interpretación de Imagen Radiográfica Asistida por Computador/normas , Radiometría/métodos , Cintigrafía , Programas Informáticos , Tomografía Computarizada por Rayos X/normas
20.
Medicine (Baltimore) ; 98(52): e18500, 2019 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-31876738

RESUMEN

Developmental dysplasia of the hip (DDH) is common, and features a widened Sharp's angle as observed on pelvic x-ray images. Determination of Sharp's angle, essential for clinical decisions, can overwhelm the workload of orthopedic surgeons. To aid diagnosis of DDH and reduce false negative diagnoses, a simple and cost-effective tool is proposed. The model was designed using artificial intelligence (AI), and evaluated for its ability to screen anteroposterior pelvic radiographs automatically, accurately, and efficiently.Orthotopic anterior pelvic x-ray images were retrospectively collected (n = 11574) from the PACS (Picture Archiving and Communication System) database at Second Hospital of Jilin University. The Mask regional convolutional neural network (R-CNN) model was utilized and finely modified to detect 4 key points that delineate Sharp's angle. Of these images, 11,473 were randomly selected, labeled, and used to train and validate the modified Mask R-CNN model. A test dataset comprised the remaining 101 images. Python-based utility software was applied to draw and calculate Sharp's angle automatically. The diagnoses of DDH obtained via the model or the traditional manual drawings of 3 orthopedic surgeons were compared, each based on the degree of Sharp's angle, and these were then evaluated relative to the final clinical diagnoses (based on medical history, symptoms, signs, x-ray films, and computed tomography images).Sharp's angles on the left and right measured via the AI model (40.07°â€Š±â€Š4.09° and 40.65°â€Š±â€Š4.21°), were statistically similar to that of the surgeons' (39.35°â€Š±â€Š6.74° and 39.82°â€Š±â€Š6.99°). The measurement time required by the AI model (1.11 ±â€Š0.00 s) was significantly less than that of the doctors (86.72 ±â€Š1.10, 93.26 ±â€Š1.12, and 87.34 ±â€Š0.80 s). The diagnostic sensitivity, specificity, and accuracy of the AI method for diagnosis of DDH were similar to that of the orthopedic surgeons; the diagnoses of both were moderately consistent with the final clinical diagnosis.The proposed AI model can automatically measure Sharp's angle with a performance similar to that of orthopedic surgeons, but requires far less time. The AI model may be a viable auxiliary to clinical diagnosis of DDH.


Asunto(s)
Luxación Congénita de la Cadera/diagnóstico por imagen , Pelvis/diagnóstico por imagen , Interpretación de Imagen Radiográfica Asistida por Computador , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Inteligencia Artificial , Niño , Luxación Congénita de la Cadera/diagnóstico , Humanos , Persona de Mediana Edad , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Radiografía/métodos , Estudios Retrospectivos , Adulto Joven
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