Investigation of brachial plexus dose that exceeds RTOG constraints for apical lung tumors treated with four- or five-fraction stereotactic body radiation therapy.

PURPOSE/OBJECTIVESS: We sought to determine the rate of brachial plexopathy (BPX) in patients exceeding RTOG dose constraints for treatment of apical lung tumors. MATERIALS/METHODS: Patients with apical lung tumors treated with four- or five-fraction SBRT were identified from a prospective registry. Dosimetric data were obtained for ipsilateral subclavian vein (SCV) and anatomic BP (ABP) contours. Cumulative equivalent dose in 2 Gy equivalents (EQD2) was calculated for the SCV contour in patients with a history of prior ipsilateral RT. Five-fraction SBRT RTOG constraints of D0.03cc ≤32.0 Gy and D3cc ≤30.0 Gy were used. BPX was graded according to Common Terminology Criteria for Adverse Events 3.0. RESULTS: A total of 64 patients met inclusion criteria. Median follow-up was 21 months. Six patients (9.4%) had prior ipsilateral conventional fractionated RT with varying degrees of overlap with subsequent SBRT field. Eleven patients without prior ipsilateral RT exceeded D0.03cc ≤32.0 Gy to SCV (mean 43.8 Gy ± 5.8). No BPX was observed in these patients. Out of the six patients who had prior ipsilateral RT, three patients exceeded D0.03cc ≤32.0 Gy to SCV (44.2 Gy ± 11.3), with two of these patients developing Grade 2 BPX within one year of SBRT. The EQD2 cumulative maximum point dose to BP was 122.6 Gy and 184.7 Gy for the two patients who developed Grade 2 BPX. The D0.03cc was >10 Gy higher to the ABP contour than the SCV contour in 14 patients. CONCLUSION: Without a history of prior ipsilateral RT, no BPX was observed at 21 month follow-up in 11 patients who exceeded the RTOG five-fraction BP constraint. This observation is hypothesis generating and more experience with longer follow-up is necessary to validate these findings. For tumors located in close proximity to apical structures, there was substantial variation in dose between the ABP and SCV contours.

Video-Assisted Thoracic Surgery Resection without Intraoperative Fluoroscopy after CT-Guided Microcoil Localization of Peripheral Pulmonary Nodules.

The aim of this brief report is to determine the safety and reliability of minimally invasive video-assisted thoracic surgery (VATS) resection without the aid of intraoperative fluoroscopy after computed tomography (CT)-guided microcoil localization of small peripheral pulmonary nodules. Twenty patients with peripheral lung nodules underwent percutaneous needle localization with a microcoil that was tagged back to the visceral pleural surface. Same-day VATS resection was performed without the use of intraoperative fluoroscopy. All 20 nodules were successfully localized in the CT procedure room, and all 20 nodules were resected with negative margins and no major complications.

Radiologic review of acquired pulmonary vein stenosis in adults.

Acquired pulmonary vein stenosis (PVS) is an uncommon occurrence in adults, but one that carries significant morbidity/mortality. PVS can be secondary to neoplastic infiltration/extrinsic compression, non-neoplastic infiltration/extrinsic compression, or iatrogenic intervention. This article: (I) reviews the common causes of acquired PVS; (II) illustrates direct and indirect cross-sectional imaging findings in acquired PVS (in order to avoid misinterpretation of these imaging findings); and (III) details the role of imaging before and after the treatment of acquired PVS.

Electromagnetic Navigational Bronchoscopy versus CT-guided Percutaneous Sampling of Peripheral Indeterminate Pulmonary Nodules: A Cohort Study.

Purpose To compare the diagnostic yield and complication rates of electromagnetic navigational bronchoscopic (ENB)-guided and computed tomography (CT)-guided percutaneous tissue sampling of lung nodules. Materials and Methods Retrospectively identified were 149 patients sampled percutaneously with CT guidance and 146 patients who underwent ENB with transbronchial biopsy of a lung lesion between 2013 and 2015. Clinical data, incidence of complications, and nodule pathologic analyses were assessed through electronic medical record review. Lung nodule characteristics were reviewed through direct image analysis. Molecular marker studies and pathologic analyses from surgical excision were reviewed when available. Multiple-variable logistic regression models were built to compare the diagnostic yield and complication rates for each method and for different patient and disease characteristics. Results CT-guided sampling was more likely to be diagnostic than ENB-guided biopsy (86.0% [129 of 150] vs 66.0% [99 of 150], respectively), and this difference remained significant even after adjustments were made for patient and nodule characteristics (P < .001). Age, American Society of Anesthesiologists class, emphysema grade, nodule size, and distance from pleura were not significant predictors of increased diagnostic yield. Intraprocedural time for physicians was significantly lower with CT-guided sampling (P < .001). Similar yield for molecular analyses was noted with the two approaches (ENB-guided sampling, 88.9% [32 of 36]; CT-guided sampling, 82.0% [41 of 50]). The two groups had similar rates of major complications (symptomatic hemorrhage, P > .999; pneumothorax requiring chest tube and/or admission, P = .417). Conclusion CT-guided transthoracic biopsy provided higher diagnostic yield in the assessment of peripheral pulmonary nodules than navigational bronchoscopy with a similar rate of clinically relevant complications. © RSNA, 2017 Online supplemental material is available for this article.

Attenuation-based kV pair selection in dual source dual energy computed tomography angiography of the chest: impact on radiation dose and image quality.

OBJECTIVES: The purpose of this study was to evaluate the impact of attenuation-based kilovoltage (kV) pair selection in dual source dual energy (DSDE)-pulmonary embolism (PE) protocol examinations on radiation dose savings and image quality. METHODS: A prospective study was carried out on 118 patients with suspected PE. In patients in whom attenuation-based kV pair selection selected the 80/140Sn kV pair, the pre-scan 100/140Sn CTDIvol (computed tomography dose index volume) values were compared with the pre-scan 80/140Sn CTDIvol values. Subjective and objective image quality parameters were assessed. RESULTS: Attenuation-based kV pair selection switched to the 80/140Sn kV pair ("switched" cohort) in 63 out of 118 patients (53%). The mean 100/140Sn pre-scan CTDIvol was 8.8 mGy, while the mean 80/140Sn pre-scan CTDIvol was 7.5 mGy. The average estimated dose reduction for the "switched" cohort was 1.3 mGy (95% CI 1.2, 1.4; p < 0.001), representing a 15% reduction in dose. After adjusting for patient weight, mean attenuation was significantly higher in the "switched" vs. "non-switched" cohorts in all five pulmonary arteries and in all lobes on iodine maps. CONCLUSIONS: This study demonstrates that attenuation-based kV pair selection in DSDE examination is feasible and can offer radiation dose reduction without compromising image quality. KEY POINTS: • Attenuation-based kV pair selection in dual energy examination is feasible. • It can offer radiation dose reduction to approximately 50% of patients. • Approximate 15% reduction in radiation dose was achieved using this technique. • The image quality is not compromised by use of attenuation-based kV pair selection.

Spectrum of Imaging Findings Following Bronchoscopic Intervention.

Interventional pulmonology (IP) is a relatively new field that uses endoscopy and other technologies for both the diagnosis and treatment of pulmonary and thoracic conditions. IP is a continually developing field driven by clinical need as well as technological and therapeutic innovation. Developments in IP have increased both the efficacy and breadth of procedures that may be encountered by radiologists on periprocedural and postprocedural imaging. In this article, we will describe commonly performed IP procedures, with a focus on relevant imaging implications for radiologists.

Pulmonary Vasculitis: Spectrum of Imaging Appearances.

Pulmonary vasculitis is a relatively uncommon disorder, usually manifesting as part of systemic vasculitis. Imaging, specifically computed tomography, is often performed in the initial diagnostic workup. Although the findings in vasculitis can be nonspecific, they can provide important clues in the diagnosis, and guide the clinical team toward the right diagnosis. Radiologists must have knowledge of common and uncommon imaging findings in various vasculitides. Also, radiologists should be able to integrate the clinical presentation and laboratory test findings together with imaging features, so as to provide a meaningful differential diagnosis.

Radiographic Evaluation of Valvular Heart Disease With Computed Tomography and Magnetic Resonance Correlation.

Valvular heart disease is a group of complex entities with varying etiologies and clinical presentations. There are a number of imaging tools available to supplement clinical evaluation of suspected valvular heart disease, with echocardiography being the most common and clinically established, and more recent emergence of computed tomography and magnetic resonance imaging as additional supportive techniques. Yet even with these newer and more sophisticated modalities, chest radiography remains one of the earliest and most common diagnostic examinations performed during the triage of patients with suspected cardiac dysfunction. Recognizing the anatomic and pathologic features of cardiac radiography including the heart's adaptation to varying hemodynamic changes can provide clues to the radiologist regarding the underlying etiology. In this article, we will elucidate several principles relating to chamber modifications in response to pressure and volume overload as well as radiographic appearances associated with pulmonary fluid status and cardiac dysfunction. We will also present a pattern approach to optimize analysis of the chest radiograph for valvular heart disease, which will help guide the radiologist down a differential diagnostic pathway and create a more meaningful clinical report.

Historical Evolution of Imaging Techniques for the Evaluation of Pulmonary Embolism.

As we celebrate the 100th anniversary of the founding of the Radiological Society of North America (RSNA), it seems fitting to look back at the major accomplishments of the radiology community in the diagnosis of pulmonary embolism. Few diseases have so consistently captured the attention of the medical community. Since the first description of pulmonary embolism by Virchow in the 1850s, clinicians have struggled to reach a timely diagnosis of this common condition because of its nonspecific and often confusing clinical picture. As imaging tests started to gain importance in the 1900s, the approach to diagnosing pulmonary embolism also began to change. Rapid improvements in angiography, ventilation-perfusion imaging, and cross-sectional imaging modalities such as computed tomography (CT) and magnetic resonance imaging have constantly forced health care professionals to rethink how they diagnose pulmonary embolism. Needless to say, the way pulmonary embolism is diagnosed today is distinctly different from how it was diagnosed in Virchow's era; and imaging, particularly CT, now forms the cornerstone of diagnostic evaluation. Currently, radiology offers a variety of tests that are fast and accurate and can provide anatomic and functional information, thus allowing early diagnosis and triage of cases. This review provides a historical journey into the evolution of these imaging tests and highlights some of the major breakthroughs achieved by the radiology community and RSNA in this process. Also highlighted are areas of ongoing research and development in this field of imaging as radiologists seek to combat some of the newer challenges faced by modern medicine, such as rising health care costs and radiation dose hazards.

Building a bridge to save a failing ventricle: radiologic evaluation of short- and long-term cardiac assist devices.

Heart failure is recognized with increasing frequency worldwide and often progresses to an advanced refractory state. Although the reference standard for treatment of advanced heart failure remains cardiac transplantation, the increasing shortage of donor organs and the unsuitability of many patients for transplantation surgery has led to a search for alternative therapies. One such therapy is mechanical circulatory support, which helps relieve the load on the ventricle and thereby allows it to recover function. In addition, there is increasing evidence supporting the use of mechanical devices as a bridge to recovery in patients with acute refractory heart failure. In this article, the imaging evaluation of various commonly used short- and long-term cardiac assist devices is discussed, and their relevant mechanisms of action and physiology are described. Imaging, particularly computed tomography (CT), plays a crucial role in preoperative evaluation for assessment of candidacy for implantation of a left ventricular assist device (LVAD) or total artificial heart (TAH). Also, echocardiography and CT are indispensable in assessment of complications associated with cardiac devices. Complications commonly associated with short-term assist devices include bleeding and malpositioning, whereas long-term devices such as LVADs may be associated with infection, pump thrombosis, and cannula malfunction, as well as bleeding. CT is also commonly performed for preoperative planning before LVAD or TAH explantation, replacement of a device or one of its components, and cardiac transplantation. Online supplemental material is available for this article.

Intraluminal air within an obstructed appendix: a CT sign of perforated or necrotic appendicitis.

RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the predictive value of intraluminal air for appendiceal necrosis and/or perforation when not apparent on imaging. Additional factors of intraluminal appendicoliths, age, and gender were also assessed. MATERIALS AND METHODS: Patients with pathologically proven appendicitis who underwent multidetector computed tomographic imaging over a 3-year period (n = 487) were retrospectively reviewed. Those with imaging evidence for perforation were excluded to create a study population of apparent uncomplicated acute appendicitis (n = 374). Each scan was assessed for intraluminal appendiceal air and appendicoliths on multidetector computed tomography and compared against surgical and pathologic results for appendiceal necrosis and/or perforation. RESULTS: Image-occult necrosis or perforation was present in 17.4% (65 or 374) of the study cohort. Intraluminal air and appendicoliths were predictive variables by univariate logistic regression (P = .001 and P ≤ .001, respectively), with odds ratios of 2.64 (95% confidence interval, 1.48-4.73) for intraluminal air and 2.67 (95% confidence interval, 1.55-4.61) for appendicoliths. Both remained independent variables on multivariate modeling despite multicollinearity. Increasing age was also predictive (odds ratio, 1.25; 95% confidence interval, 1.09-1.44; P = .002), whereas gender was not (P = .472). CONCLUSIONS: Intraluminal appendiceal air in the setting of acute appendicitis is a marker of perforated or necrotic appendicitis. Recognition of this finding in otherwise uncomplicated appendicitis at imaging should raise suspicion for image-occult perforation or necrosis.

Identification of biomarkers for risk stratification of cardiovascular events using genetic algorithm with recursive local floating search.

Conventional biomarker discovery focuses mostly on the identification of single markers and thus often has limited success in disease diagnosis and prognosis. This study proposes a method to identify an optimized protein biomarker panel based on MS studies for predicting the risk of major adverse cardiac events (MACE) in patients. Since the simplicity and concision requirement for the development of immunoassays can only tolerate the complexity of the prediction model with a very few selected discriminative biomarkers, established optimization methods, such as conventional genetic algorithm (GA), thus fails in the high-dimensional space. In this paper, we present a novel variant of GA that embeds the recursive local floating enhancement technique to discover a panel of protein biomarkers with far better prognostic value for prediction of MACE than existing methods, including the one approved recently by FDA (Food and Drug Administration). The new pragmatic method applies the constraints of MACE relevance and biomarker redundancy to shrink the local searching space in order to avoid heavy computation penalty resulted from the local floating optimization. The proposed method is compared with standard GA and other variable selection approaches based on the MACE prediction experiments. Two powerful classification techniques, partial least squares logistic regression (PLS-LR) and support vector machine classifier (SVMC), are deployed as the MACE predictors owing to their ability in dealing with small scale and binary response data. New preprocessing algorithms, such as low-level signal processing, duplicated spectra elimination, and outliner patient's samples removal, are also included in the proposed method. The experimental results show that an optimized panel of seven selected biomarkers can provide more than 77.1% MACE prediction accuracy using SVMC. The experimental results empirically demonstrate that the new GA algorithm with local floating enhancement (GA-LFE) can achieve the better MACE prediction performance comparing with the existing techniques. The method has been applied to SELDI/MALDI MS datasets to discover an optimized panel of protein biomarkers to distinguish disease from control.

Computational prediction models for early detection of risk of cardiovascular events using mass spectrometry data.

Early prediction of the risk of cardiovascular events in patients with chest pain is critical in order to provide appropriate medical care for those with positive diagnosis. This paper introduces a computational methodology for predicting such events in the context of robust computerized classification using mass spectrometry data of blood samples collected from patients in emergency departments. We applied the computational theories of statistical and geostatistical linear prediction models to extract effective features of the mass spectra and a simple decision logic to classify disease and control samples for the purpose of early detection. While the statistical and geostatistical techniques provide better results than those obtained from some other methods, the geostatistical approach yields superior results in terms of sensitivity and specificity in various designs of the data set for validation, training, and testing. The proposed computational strategies are very promising for predicting major adverse cardiac events within six months.

Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke.

BACKGROUND: Strokes are a leading cause of morbidity and the first cause of adult disability in the United States. Currently, no biomarkers are being used clinically to diagnose acute ischemic stroke. A diagnostic test using a blood sample from a patient would potentially be beneficial in treating the disease. RESULTS: A classification approach is described for differentiating between proteomic samples of stroke patients and controls, and a second novel predictive model is developed for predicting the severity of stroke as measured by the National Institutes of Health Stroke Scale (NIHSS). The models were constructed by applying the Logical Analysis of Data (LAD) methodology to the mass peak profiles of 48 stroke patients and 32 controls. The classification model was shown to have an accuracy of 75% when tested on an independent validation set of 35 stroke patients and 25 controls, while the predictive model exhibited superior performance when compared to alternative algorithms. In spite of their high accuracy, both models are extremely simple and were developed using a common set consisting of only 3 peaks. CONCLUSION: We have successfully identified 3 biomarkers that can detect ischemic stroke with an accuracy of 75%. The performance of the classification model on the validation set and on cross-validation does not deteriorate significantly when compared to that on the training set, indicating the robustness of the model. As in the case of the LAD classification model, the results of the predictive model validate the function constructed on our support-set for approximating the severity scores of stroke patients. The correlation and root mean absolute error of the LAD predictive model are consistently superior to those of the other algorithms used (Support vector machines, C4.5 decision trees, Logistic regression and Multilayer perceptron).