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In this report, we present a series involving critically ill patients with known coronavirus disease (COVID-19) infection where a portable X-ray machine equipped with artificial intelligence (AI) software aided in the urgent radiographic diagnosis of pneumothorax. These cases demonstrate how real-world clinical employment of AI tools capable of analyzing and prioritizing studies in the radiologist's worklist can potentially lead to earlier detection of emergent findings like pneumothorax. The use of AI tools in this manner has the potential to both improve radiology workflow and add significant clinical value in managing critically ill patient populations, such as those with severe COVID-19 infection.
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Lung transplant patients often suffer from posttransplant airway pathologies that require placement of endobronchial stents. In addition to surveillance bronchoscopy, patients often undergo radiographic stent evaluations. Chest x-rays are extremely limited in their ability to diagnose stent complications, so many patients require chest computed tomography (CT) scans for stent evaluation. Chest CT scans are costly and expose patients to higher cumulative radiation doses. Digital tomosynthesis (DTS) is an imaging modality that provides high-resolution images using limited angle tomography. The costs and radiation doses are comparable to conventional x-ray. We present a series of 4 postlung transplant patients with bronchial stents in whom we performed DTS and chest x-ray simultaneously. The DTS images were far superior to chest x-ray and comparable with CT in evaluating the placement and patency of the stents, especially in the case of silicone stents. Furthermore, the improved resolution provided clinically relevant diagnostic information that resulted in therapeutic bronchoscopy for suctioning of mucus impaction in one of the patients.
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Radiografía Torácica , Receptores de Trasplantes , Humanos , Radiografía Torácica/métodos , Pulmón , Tomografía Computarizada por Rayos X/métodos , StentsRESUMEN
Coronary artery calcium (CAC) scores obtained from CT scans have been shown to be prognostic in assessment of the risk for development of cardiovascular diseases, facilitating the prediction of outcome in asymptomatic individuals. Currently, several methods to calculate the CAC score exist, and each has its own set of advantages and disadvantages. Agatston CAC scoring is the most extensively used method. CAC scoring is currently recommended for use in asymptomatic individuals to predict the risk of developing cardiovascular diseases and the disease-specific mortality. In specific subsets of patients, the CAC score has also been recommended for reclassifying cardiovascular risk and aiding in decision making when planning primary prevention interventions such as statin therapy. The progression of CAC scores on follow-up images has been shown to be linked to risk of myocardial infarction and cardiovascular mortality. While the CAC score is a validated tool used clinically, several challenges, including various pitfalls associated with the acquisition, calculation, and interpretation of the score, prevent more widespread adoption of this metric. Recent research has been focused extensively on strategies to improve existing scoring methods, including measuring calcium attenuation, detecting microcalcifications, and focusing on extracoronary calcifications, and on strategies to improve image acquisition. A better understanding of CAC scoring approaches will help radiologists and other physicians better use and interpret these scores in their workflows. An invited commentary by S. Gupta is available online. Online supplemental material is available for this article. ©RSNA, 2022.
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Calcinosis , Enfermedades Cardiovasculares , Enfermedad de la Arteria Coronaria , Calcinosis/diagnóstico por imagen , Calcio , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Humanos , Factores de Riesgo , Tomografía Computarizada por Rayos XRESUMEN
Although interest in artificial intelligence (AI) has exploded in recent years and led to the development of numerous commercial and noncommercial algorithms, the process of implementing such tools into day-to-day clinical practice is rarely described in the burgeoning AI literature. In this report, we describe our experience with the successful integration of an AI-enabled mobile x-ray scanner with an FDA-approved algorithm for detecting pneumothoraces into an end-to-end solution capable of extracting, delivering, and prioritizing positive studies within our thoracic radiology clinical workflow. We also detail several sample cases from our AI algorithm and associated PACS workflow in action to highlight key insights from our experience. We hope this report can help inform other radiology enterprises seeking to evaluate and implement AI-related workflow solutions into daily clinical practice.
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Neumotórax , Radiología , Algoritmos , Inteligencia Artificial , Humanos , Neumotórax/diagnóstico por imagen , RadiografíaRESUMEN
PURPOSE: To evaluate vessel assessment in virtual monoenergetic images (VMI40keV) and virtual-non-contrast images (VNC) derived from venous phase spectral detector computed tomography (SDCT) acquisitions in comparison to arterial phase and true non-contrast (TNC) images. METHODS: Triphasic abdominal SDCT was performed in 25 patients including TNC, arterial and venous phase. VMI40keV and VNC were reconstructed from the venous phase and compared to conventional arterial-phase images (CIart), TNC and conventional venous-phase images (CIven). Vessel contrast and virtual contrast removal were analyzed with region-of-interest-based measurements and in a qualitative assessment. RESULTS: Quantitative analysis revealed no significant attenuation differences between TNC and VNC in arterial vessels (p-range 0.07-0.47) except for the renal artery (p = 0.011). For venous vessels, significant differences between TNC and VNC were found for all veins (p < 0.001) except the inferior vena cava (p = 0.26), yet these differences remained within a 10 HU range in most patients. No significant attenuation differences were found between CIart/VMI40keV in arterial vessels (p-range 0.06-0.86). Contrast-to-noise ratio provided by VMI40keV and CIart was equivalent for all arterial vessels assessed (p-range 0.14-0.91). Qualitatively, VMI40keV showed similar enhancement of abdominal and pelvic arteries as CIart and VNC were rated comparable to TNC. CONCLUSION: Our study suggests that VNC and VMI40keV derived from single venous-phase SDCT offer comparable assessment of major abdominal vessels as provided by routine triphasic examinations, if no dynamic contrast information is required.
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Abdomen , Tomografía Computarizada por Rayos X , Abdomen/diagnóstico por imagen , Humanos , Arteria Renal , Estudios RetrospectivosRESUMEN
OBJECTIVE: To identify stable and discriminating radiomic features on non-contrast CT scans to develop more generalisable radiomic classifiers for distinguishing granulomas from adenocarcinomas. METHODS: In total, 412 patients with adenocarcinomas and granulomas from three institutions were retrospectively included. Segmentations of the lung nodules were performed manually by an expert radiologist in a 2D axial view. Radiomic features were extracted from intra- and perinodular regions. A total of 145 patients were used as part of the training set (Str), whereas 205 patients were used as part of test set I (Ste1) and 62 patients were used as part of independent test set II (Ste2). To mitigate the variation of CT acquisition parameters, we defined 'stable' radiomic features as those for which the feature expression remains relatively unchanged between different sites, as assessed using a Wilcoxon rank-sum test. These stable features were used to develop more generalisable radiomic classifiers that were more resilient to variations in lung CT scans. Features were ranked based on two criteria, firstly based on discriminability (i.e. maximising AUC) alone and subsequently based on maximising both feature stability and discriminability. Different machine-learning classifiers (Linear discriminant analysis, Quadratic discriminant analysis, Support vector machines and random forest) were trained with features selected using the two different criteria and then compared on the two independent test sets for distinguishing granulomas from adenocarcinomas, in terms of area under the receiver operating characteristic curve. RESULTS: In the test sets, classifiers constructed using the criteria involving maximising feature stability and discriminability simultaneously achieved higher AUC compared with the discriminating alone criteria (Ste1 [n = 205]: maximum AUCs of 0.85versus . 0.80; p-value = 0.047 and Ste2 [n = 62]: maximum AUCs of 0.87 versus. 0.79; p-value = 0.021). These differences held for features extracted from scans with <3 mm slice thickness (AUC = 0.88 versus. 0.80; p-value = 0.039, n = 100) and for the ≥3 mm cases (AUC = 0.81 versus. 0.76; p-value = 0.034, n = 105). In both experiments, shape and peritumoural texture features had a higher stability compared with intratumoural texture features. CONCLUSIONS: Our study suggests that explicitly accounting for both stability and discriminability results in more generalisable radiomic classifiers to distinguish adenocarcinomas from granulomas on non-contrast CT scans. Our results also showed that peritumoural texture and shape features were less affected by the scanner parameters compared with intratumoural texture features; however, they were also less discriminating compared with intratumoural features.
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Adenocarcinoma del Pulmón/diagnóstico , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico , Granuloma/diagnóstico , Neoplasias Pulmonares/diagnóstico , Tomografía Computarizada por Rayos X/métodos , Adenocarcinoma del Pulmón/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Diagnóstico Diferencial , Estudios de Seguimiento , Granuloma/diagnóstico por imagen , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Aprendizaje Automático , Pronóstico , Estudios RetrospectivosRESUMEN
Recent advances in dual-energy imaging techniques, dual-energy subtraction radiography (DESR) and dual-energy CT (DECT), offer new and useful additional information to conventional imaging, thus improving assessment of cardiothoracic abnormalities. DESR facilitates detection and characterization of pulmonary nodules. Other advantages of DESR include better depiction of pleural, lung parenchymal, airway and chest wall abnormalities, detection of foreign bodies and indwelling devices, improved visualization of cardiac and coronary artery calcifications helping in risk stratification of coronary artery disease, and diagnosing conditions like constrictive pericarditis and valvular stenosis. Commercially available DECT approaches are classified into emission based (dual rotation/spin, dual source, rapid kilovoltage switching and split beam) and detector-based (dual layer) systems. DECT provide several specialized image reconstructions. Virtual non-contrast images (VNC) allow for radiation dose reduction by obviating need for true non contrast images, low energy virtual mono-energetic images (VMI) boost contrast enhancement and help in salvaging otherwise non-diagnostic vascular studies, high energy VMI reduce beam hardening artifacts from metallic hardware or dense contrast material, and iodine density images allow quantitative and qualitative assessment of enhancement/iodine distribution. The large amount of data generated by DECT can affect interpreting physician efficiency but also limit clinical adoption of the technology. Optimization of the existing workflow and streamlining the integration between post-processing software and picture archiving and communication system (PACS) is therefore warranted.
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Coronary artery disease (CAD) remains the most common cardiovascular disease, accounting for 6% of all Emergency Department visits and 27% of all Emergency Department hospitalizations.1 Invasive coronary angiography with fractional flow reserve (FFR) remains the gold standard to assess for hemodynamically stenosis in CAD patients. However, for low- and intermediate-risk patients, noninvasive modalities have started to gain favor as patients with stable CAD who received optimal medical therapy did as well as patients who underwent percutaneous coronary intervention.2 This led to the incorporation of FFRCT. cCTA provides good spatial resolution for evaluating stenosis. FFR provides additional information regarding whether the stenosis is hemodynamically significant. FFR is the ratio of maximum blood flow in a stenotic artery to the maximum blood flow through that artery without stenosis.3 Computational fluid dynamics involved in FFRCT is based on Navier-Stokes equations, allowing the assessment of pressure and flow across coronary arteries. Limitations do exist with FFRCT which includes false-positive results due to step artifact and left ventricular hypertrophy, as well as manual segmentation and ostial stenosis, which can cause false-negative results. However, there are improvements on the horizon including artificial intelligence-driven computation of FFR and the utilization of virtual stenting for surgical planning. The purpose of this review is to describe the clinical validation, underlying mechanism, and implementation of FFRCT.
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Enfermedad de la Arteria Coronaria , Reserva del Flujo Fraccional Miocárdico , Inteligencia Artificial , Angiografía Coronaria , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Enfermedad de la Arteria Coronaria/terapia , Vasos Coronarios/diagnóstico por imagen , Humanos , Valor Predictivo de las Pruebas , Tomografía Computarizada por Rayos XRESUMEN
Our goal is to assess the ability of physicians to detect coronary calcifications in dual energy chest X-rays processed by a previously developed advanced algorithm. Because the chest X-ray is the most common imaging procedure, because the presence of coronary calcium provides proof of coronary artery disease, and because adherence to therapy can improve health, successful detection could positively impact healthcare for a large number of patients. Both dual energy chest and corroborative CT calcium score images were acquired. Dual energy images were processed with the advanced techniques, including sliding organ registration, so as to enhance coronary calcifications in two-shot dual energy acquisitions. We performed ROC to determine physicians' ability to detect coronary calcifications. Since detection might be easier with heavier calcifications, we used various Agatston score cut-points for determining cases actually positive with calcification in the ROC analysis. In many cases, coronary calcifications were made more visible with the advanced processing as compared to conventional processing. At an Agatston cut-point of 300, coronary calcifications were detected with AUC = 0.85. There were marginal effects on detection performance found with increased X-ray exposure, nearby Agatston cut-point values, and coronary artery territory. Coronary calcifications can be detected in dual energy chest X-rays. The ability to detect disease compares very favorably to other accepted screening methods (e.g., X-ray mammography). As the chest X-ray is an already ordered procedure, there is an opportunity to detect a very large number of persons with coronary artery disease at zero or low cost.
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Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Vasos Coronarios/diagnóstico por imagen , Radiografía Torácica , Tomografía Computarizada por Rayos X , Calcificación Vascular/diagnóstico por imagen , Adulto , Anciano , Algoritmos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Estudios Prospectivos , Interpretación de Imagen Radiográfica Asistida por Computador , Reproducibilidad de los Resultados , Estudios Retrospectivos , Índice de Severidad de la Enfermedad , Programas InformáticosRESUMEN
BACKGROUND: Diagnosis of amiodarone lung toxicity on computerized tomography (CT) can be challenging especially in the presence of mass-like consolidation. Additional causes of mass-like consolidation including malignancy and pneumonia should be excluded, sometimes requiring tissue sampling. CASE: Here we present a case of amiodarone lung toxicity, with diagnosis suspected based on patient's history of chronic cardiac disease, amiodarone treatment, and imaging characteristics. Evaluation with dual energy CT demonstrated high iodine content in the mass-like consolidation further supporting the diagnosis. Biopsy of the mass-like consolidation confirmed amiodarone toxicity. CONCLUSION: Dual energy CT has potential utility in differentiating mass-like consolidation from other etiologies such as malignancy or pneumonia.
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Amiodarona , Enfermedades Pulmonares , Amiodarona/efectos adversos , Antiarrítmicos , Humanos , Pulmón/diagnóstico por imagen , Tomografía Computarizada por Rayos XRESUMEN
Involvement of the coronary arteries by immunoglobulin G4-related disease is rare. It can cause coronary artery aneurysm and arterial wall thickening. Imaging plays a key role in the assessment of the coronary arteries and multimodality approach imaging is helpful to make the diagnosis and provide functional and prognostic information.
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Aneurisma Coronario , Inmunoglobulina G , Aneurisma Coronario/diagnóstico por imagen , Vasos Coronarios/diagnóstico por imagen , Humanos , Imagen MultimodalRESUMEN
Despite advances in cardiovascular imaging, the diagnosis of constrictive pericarditis remains challenging. A multimodality approach to the diagnosis of CP is essential to (a) fully assess the extent of pericardial thickening and calcification, (b) detect the functional and hemodynamic consequences of the constricting pericardium, and (c) implement the optimal management strategy in these often complex cases. This case-based review highlights the role and diagnostic ambiguities of multimodality imaging.
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Calcinosis , Pericarditis Constrictiva , Humanos , Imagen Multimodal , Pericarditis Constrictiva/diagnóstico por imagen , Pericarditis Constrictiva/terapia , PericardioRESUMEN
OBJECTIVES: To evaluate whether combining stability and discriminability criteria in building radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small cell lung cancer on non-contrast computer tomography (CT). MATERIALS AND METHODS: CT scans of 610 patients with early stage (IA, IB, IIA) NSCLC from four independent cohorts were evaluated. A total of 350 patients from Cleveland Clinic Foundation and University of Pennsylvania were divided into two equal sets for training (D1) and validation set (D2). 80 patients from The Cancer Genome Atlas Lung Adenocarcinoma and Squamous Cell Carcinoma and 195 patients from The Cancer Imaging Archive, were used as independent second (D3) and third (D4) validation sets. A linear discriminant analysis (LDA) classifier was built based on the most stable and discriminate features. In addition, a radiomic risk score (RRS) was generated by using least absolute shrinkage and selection operator, Cox regression model to predict time to progression (TTP) following surgery. RESULTS: A feature selection strategy focusing on both feature discriminability and stability resulted in the classifier having a higher discriminability on validation datasets compared to the discriminability alone criteria in discriminating cancer recurrence (D2, AUC of 0.75 vs. 0.65; D3, 0.74 vs. 0.62; D4, 0.76 vs. 0.63). The RRS generated by most stable-discriminating features was significantly associated with TTP compared to discriminating alone criteria (HR = 1.66, C-index of 0.72 vs. HR = 1.04, C-index of 0.62). CONCLUSION: Accounting for both stability and discriminability yielded a more generalizable classifier for predicting cancer recurrence and TTP in early stage NSCLC.
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Adenocarcinoma del Pulmón/patología , Carcinoma de Pulmón de Células no Pequeñas/patología , Carcinoma de Células Escamosas/patología , Neoplasias Pulmonares/patología , Recurrencia Local de Neoplasia/patología , Neumonectomía/mortalidad , Adenocarcinoma del Pulmón/diagnóstico por imagen , Adenocarcinoma del Pulmón/cirugía , Adulto , Anciano , Anciano de 80 o más Años , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/cirugía , Carcinoma de Células Escamosas/diagnóstico por imagen , Carcinoma de Células Escamosas/cirugía , Femenino , Estudios de Seguimiento , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/cirugía , Masculino , Persona de Mediana Edad , Recurrencia Local de Neoplasia/diagnóstico por imagen , Recurrencia Local de Neoplasia/cirugía , Pronóstico , Estudios Retrospectivos , Tasa de Supervivencia , Adulto JovenRESUMEN
The chest radiograph is the most frequently performed imaging in radiology and by including the heart and central vessels can suggest the presence of cardiovascular disease. Dual-energy subtraction radiography of the chest provides improved detection of a wide variety of cardiovascular pathologies including coronary artery disease, valvular pathologies, and pericardial disease given the presence of calcification in many subtypes of these diseases. We review the principles of dual-energy subtraction radiography and demonstrate its added value in the assessment of cardiovascular disease.
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Enfermedades Cardiovasculares/diagnóstico por imagen , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Radiografía Torácica/métodos , HumanosRESUMEN
OBJECTIVE. The purpose of this article is to outline the utility of iodine density maps for evaluating cardiothoracic disease and abnormalities. Multiple studies have shown that the variety of images generated from dual-energy spectral detector CT (SDCT) improve identification of cardiothoracic conditions. CONCLUSION. Understanding the technique of SDCT and being familiar with the features of different cardiothoracic conditions on iodine density map images help the radiologist make a better diagnosis.
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Enfermedades Cardiovasculares/diagnóstico por imagen , Medios de Contraste/farmacocinética , Yodo/farmacocinética , Imagen Radiográfica por Emisión de Doble Fotón/métodos , Radiografía Torácica/métodos , Enfermedades Respiratorias/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Humanos , Interpretación de Imagen Radiográfica Asistida por ComputadorRESUMEN
Lipomatous hypertrophy of the right ventricle is a rare entity that is usually asymptomatic and diagnosed incidentally in an otherwise healthy individual. Accurate diagnosis and assessment of possible hemodynamic consequences of this pathology is, however, necessary to secure an appropriate treatment. Multimodality imaging with echocardiography, CT, and cardiac MR can provide useful functional and anatomic information that can help to reach this goal.
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Ventrículos Cardíacos , Obstrucción del Flujo Ventricular Externo , Ecocardiografía , Ventrículos Cardíacos/diagnóstico por imagen , Humanos , Hipertrofia , Imagen Multimodal , Obstrucción del Flujo Ventricular Externo/diagnóstico por imagenRESUMEN
Electronic-cigarette use (vaping), has gained popularity among the young adult population, causing an alarming rise in electronic-cigarette, or vaping, product use-associated lung injury (EVALI). The specific chemical agent(s) responsible for lung injuries remains to be further investigated, but tetrahydrocannabinol, the active ingredient in marijuana, and vitamin E acetate are involved in most cases. A variety of pulmonary diseases causing different imaging findings have been described with EVALI. The clinical and imaging findings of three cases recently seen in our emergency department are reviewed.