Publications by authors named "Prabhakar Rajiah"

164 Publications

First Clinical Photon-counting Detector CT System: Technical Evaluation.

Radiology 2021 Dec 14:212579. Epub 2021 Dec 14.

From the Department of Radiology, Mayo Clinic, Rochester, MN 55905 USA (K.R., A.F., F.B., F.E.D., L.Y., P.R., J.G.F., S.L., C.H.M.), Siemens Healthineers, Forchheim, Germany (M.P., A.H., B.S., T.G.F.) and Siemens Medical Solutions, Malvern, PA, USA (E.R.S.).

Background The first clinical CT system to use photon-counting-detector (PCD) technology has become available for patient care. Purpose To assess the technical performance of the PCD-CT system using phantoms and representative participant exams. Materials and Methods Institutional review board approval and written informed consent from four participants were obtained. Technical performance of a dual-source PCD-CT system was measured for standard and high resolution (HR) collimations. Noise power spectrum (NPS), modulation transfer function (MTF), section sensitivity profile (SSP), iodine CT number accuracy in virtual monoenergetic images (VMI), and iodine concentration accuracy were measured. Four participants were enrolled (between May 2021 and August 2021) in this prospective study and scanned using similar or lower radiation doses compared to same-day exams performed using energy-integrating-detector (EID) CT. Results All standard technical performance measures met accreditation requirements. Relative to filtered-back-projection reconstructions, images from iterative reconstruction had lower noise magnitude but preserved NPS shape and peak-frequency. Maximum in-plane spatial resolutions of 125 and 208 microns were measured for PCD-HR and PCD-standard scans, respectively. Minimum values for SSP full-width-half-maximum measurements were 0.34-mm (0.2 mm nominal section thickness) and 0.64 mm (0.4-mm nominal section thickness) for PCD-HR and PCD-standard scans, respectively. In a PCD-CT 120-kV standard scan of a 40-cm phantom, VMI iodine CT numbers had a mean percent error of 5.7% and iodine concentration had root-mean-squared-error of 0.5 mg/cc, comparable to previously reported values for EID-CT. VMI, iodine map, and virtual non-contrast images were created for a coronary CT angiogram acquired with 66-ms temporal resolution. Participant PCD-CT images showed up to 47% lower noise and/or improved spatial resolution compared to EID-CT. Conclusions Technical performance of a new clinical photon-counting-detector CT is improved relative to current state-of-the-art CT system. The dual-source photon-counting-detector geometry facilitated 66-ms-temporal-resolution multi-energy cardiac imaging. Study-participant images illustrated the impact of the improved technical performance.
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http://dx.doi.org/10.1148/radiol.212579DOI Listing
December 2021

Novel Non-Invasive Radiomic Signature on CT Scans Predicts Response to Platinum-Based Chemotherapy and Is Prognostic of Overall Survival in Small Cell Lung Cancer.

Front Oncol 2021 20;11:744724. Epub 2021 Oct 20.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States.

Background: Small cell lung cancer (SCLC) is an aggressive malignancy characterized by initial chemosensitivity followed by resistance and rapid progression. Presently, there are no predictive biomarkers that can accurately guide the use of systemic therapy in SCLC patients. This study explores the role of radiomic features from both within and around the tumor lesion on pretreatment CT scans to a) prognosticate overall survival (OS) and b) predict response to chemotherapy.

Methods: One hundred fifty-three SCLC patients who had received chemotherapy were included. Lung tumors were contoured by an expert reader. The patients were divided randomly into approximately equally sized training (S = 77) and test sets (S = 76). Textural descriptors were extracted from the nodule (intratumoral) and parenchymal regions surrounding the nodule (peritumoral). The clinical endpoints of this study were OS, progression-free survival (PFS), and best objective response to chemotherapy. Patients with complete or partial response were defined as "responders," and those with stable or progression of disease were defined as "non-responders." The radiomic risk score (RRS) was generated by using the least absolute shrinkage and selection operator (LASSO) with the Cox regression model. Patients were classified into the high-risk or low-risk groups based on the median of RRS. Association of the radiomic signature with OS was evaluated on S and then tested on S. The features identified by LASSO were then used to train a linear discriminant analysis (LDA) classifier (M) to predict response to chemotherapy. A prognostic nomogram (N) was also developed on S by combining clinical and prognostic radiomic features and validated on S. The Kaplan-Meier survival analysis and log-rank statistical tests were performed to assess the discriminative ability of the features. The discrimination performance of the N was assessed by Harrell's C-index. To estimate the clinical utility of the nomogram, decision curve analysis (DCA) was performed by calculating the net benefits for a range of threshold probabilities in predicting which high-risk patients should receive more aggressive treatment as compared with the low-risk patients.

Results: A univariable Cox regression analysis indicated that RRS was significantly associated with OS in S (HR: 1.53; 95% CI, [1.1-2.2; p = 0.021]; C-index = 0.72) and S (HR: 1.4, [1.1-1.82], p = 0.0127; C-index = 0.69). The RRS was also significantly associated with PFS in S (HR: 1.89, [1.4-4.61], p = 0.047; C-index = 0.7) and S (HR: 1.641, [1.1-2.77], p = 0.04; C-index = 0.67). M was able to predict response to chemotherapy with an area under the receiver operating characteristic curve (AUC) of 0.76 ± 0.03 within S and 0.72 within S. Predictors, including the RRS, gender, age, stage, and smoking status, were used in the prognostic nomogram. The discrimination ability of the N model on S and S was C-index [95% CI]: 0.68 [0.66-0.71] and 0.67 [0.63-0.69], respectively. DCA indicated that the N model was clinically useful.

Conclusions: Radiomic features extracted within and around the lung tumor on CT images were both prognostic of OS and predictive of response to chemotherapy in SCLC patients.
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http://dx.doi.org/10.3389/fonc.2021.744724DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564480PMC
October 2021

Effects of Extracorporeal Membrane Oxygenation Initiation on Oxygenation and Pulmonary Opacities.

J Crit Care Med (Targu Mures) 2021 Jan 29;7(1):6-13. Epub 2021 Jan 29.

University of Texas Southwestern Medical Center at Dallas, TX, USA.

Introduction: There is limited data on the impact of extracorporeal membrane oxygenation (ECMO) on pulmonary physiology and imaging in adult patients. The current study sought to evaluate the serial changes in oxygenation and pulmonary opacities after ECMO initiation.

Methods: Records of patients started on veno-venous, or veno-arterial ECMO were reviewed (n=33; mean (SD): age 50(16) years; Male: Female 20:13). Clinical and laboratory variables before and after ECMO, including daily PaO to FiO ratio (PFR), were recorded. Daily chest radiographs (CXR) were prospectively appraised in a blinded fashion and scored for the extent and severity of opacities using an objective scoring system.

Results: ECMO was associated with impaired oxygenation as reflected by the drop in median PFR from 101 (interquartile range, IQR: 63-151) at the initiation of ECMO to a post-ECMO trough of 74 (IQR: 56-98) on post-ECMO day 5. However, the difference was not statistically significant. The appraisal of daily CXR revealed progressively worsening opacities, as reflected by a significant increase in the opacity score (Wilk's Lambda statistic 7.59, p=0.001). During the post-ECMO period, a >10% increase in the opacity score was recorded in 93.9% of patients. There was a negative association between PFR and opacity scores, with an average one-unit decrease in the PFR corresponding to a +0.010 increase in the opacity score (95% confidence interval: 0.002 to 0.019, p-value=0.0162). The median opacity score on each day after ECMO initiation remained significantly higher than the pre-ECMO score. The most significant increase in the opacity score (9, IQR: -8 to 16) was noted on radiographs between pre-ECMO and forty-eight hours post-ECMO. The severity of deteriorating oxygenation or pulmonary opacities was not associated with hospital survival.

Conclusions: The use of ECMO is associated with an increase in bilateral opacities and a deterioration in oxygenation that starts early and peaks around 48 hours after ECMO initiation.
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http://dx.doi.org/10.2478/jccm-2020-0040DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519372PMC
January 2021

Pulmonary CTA Reporting: Expert Panel Narrative Review.

AJR Am J Roentgenol 2022 Jan 12:1-9. Epub 2022 Jan 12.

Department of Radiology, New York University, New York, NY.

Pulmonary CTA is a ubiquitous study interpreted by radiologists with different levels of experience in a variety of practice settings. Pulmonary embolism (PE) can range from an incidental and clinically insignificant finding to a clinically significant thrombus that can be managed on an outpatient basis to a potentially fatal condition requiring immediate medical or invasive management. Accordingly, a clear and concise pulmonary CTA report should effectively communicate the most pertinent findings to help the treating medical team diagnose or exclude PE and provide information to guide appropriate management. In this Expert Panel Narrative Review, we discuss the purpose of the radiology report for pulmonary CTA, the optimal report format, and the relevant findings that need to be addressed and their clinical significance.
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http://dx.doi.org/10.2214/AJR.21.26646DOI Listing
January 2022

Cardiac MRI for Left Ventricular Dyssynchrony: Time for Coordinated Response.

Radiol Cardiothorac Imaging 2021 Aug 26;3(4):e210193. Epub 2021 Aug 26.

Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905.

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http://dx.doi.org/10.1148/ryct.2021210193DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415138PMC
August 2021

Collaborative Writing Projects: Set Yourself up for Success.

J Comput Assist Tomogr 2021 Jul-Aug 01;45(4):495-499

Department of Radiology, University of Washington, Seattle, WA.

Abstract: This article will review critical components for the successful completion of a multi-institution, multiauthor collaborative paper. Best practices for the creation and publication of a collaborative paper will be addressed.
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http://dx.doi.org/10.1097/RCT.0000000000001187DOI Listing
September 2021

A Novel Nodule Edge Sharpness Radiomic Biomarker Improves Performance of Lung-RADS for Distinguishing Adenocarcinomas from Granulomas on Non-Contrast CT Scans.

Cancers (Basel) 2021 Jun 3;13(11). Epub 2021 Jun 3.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.

The aim of this study is to evaluate whether NIS radiomics can distinguish lung adenocarcinomas from granulomas on non-contrast CT scans, and also to improve the performance of Lung-RADS by reclassifying benign nodules that were initially assessed as suspicious. The screening or standard diagnostic non-contrast CT scans of 362 patients was divided into training (S, = 145), validation (S, = 145), and independent validation (S, = 62) sets from different institutions. Nodules were identified and manually segmented on CT images by a radiologist. A series of 264 features relating to the edge sharpness transition from the inside to the outside of the nodule were extracted. The top 10 features were used to train a linear discriminant analysis (LDA) machine learning classifier on St. In conjunction with the LDA classifier, NIS radiomics classified nodules with an AUC of 0.82 ± 0.04, 0.77, and 0.71 respectively on S, S, and S. We evaluated the ability of the NIS classifier to determine the proportion of the patients in S that were identified initially as suspicious by Lung-RADS but were reclassified as benign by applying the NIS scores. The NIS classifier was able to correctly reclassify 46% of those lesions that were actually benign but deemed suspicious by Lung-RADS alone on S.
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http://dx.doi.org/10.3390/cancers13112781DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199879PMC
June 2021

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement.

J Digit Imaging 2021 10 28;34(5):1183-1189. Epub 2021 May 28.

Department of Radiology, Mayo Clinic, 200 1stSt SW, Rochester, MN, 55902, USA.

Imaging-based measurements form the basis of surgical decision making in patients with aortic aneurysm. Unfortunately, manual measurement suffer from suboptimal temporal reproducibility, which can lead to delayed or unnecessary intervention. We tested the hypothesis that deep learning could improve upon the temporal reproducibility of CT angiography-derived thoracic aortic measurements in the setting of imperfect ground-truth training data. To this end, we trained a standard deep learning segmentation model from which measurements of aortic volume and diameter could be extracted. First, three blinded cardiothoracic radiologists visually confirmed non-inferiority of deep learning segmentation maps with respect to manual segmentation on a 50-patient hold-out test cohort, demonstrating a slight preference for the deep learning method (p < 1e-5). Next, reproducibility was assessed by evaluating measured change (coefficient of reproducibility and standard deviation) in volume and diameter values extracted from segmentation maps in patients for whom multiple scans were available and whose aortas had been deemed stable over time by visual assessment (n = 57 patients, 206 scans). Deep learning temporal reproducibility was superior for measures of both volume (p < 0.008) and diameter (p < 1e-5) and reproducibility metrics compared favorably with previously reported values of manual inter-rater variability. Our work motivates future efforts to apply deep learning to aortic evaluation.
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http://dx.doi.org/10.1007/s10278-021-00465-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554928PMC
October 2021

Pre- and Postprocedural CT of Transcatheter Left Atrial Appendage Closure Devices.

Radiographics 2021 May-Jun;41(3):680-698

From the Department of Radiology (P. Rajiah, T.F., E.W.) and Department of Cardiology (M.A., J.T.), Mayo Clinic, 200 1st St SW, Rochester, MN 55905; and Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (P. Ranganath).

Transcatheter left atrial appendage (LAA) closure is an alternative to long-term anticoagulation therapy in selected patients with nonvalvular atrial fibrillation who have an increased risk for stroke. LAA closure devices can be implanted by means of either an endocardial or a combined endocardial and epicardial approach. Preprocedural imaging is key to identifying contraindications, accurately sizing the device, and minimizing complications. Transesophageal echocardiography (TEE) has been the reference standard imaging modality to assess the anatomy for LAA closure and to provide intraprocedural guidance. However, CT has emerged as a less-invasive alternative to TEE for pre- and postprocedural imaging. CT is comparable to TEE for exclusion of thrombus but is superior to TEE for the delineation of complex LAA anatomy, measurement for device sizing, and evaluation of pulmonary venous and extracardiac structures. CT provides accurate measurements of the LAA ostial diameter, landing zone diameter, and LAA length, which are vital for accurate sizing of the device. CT allows evaluation of the relationship with the pulmonary veins and other adjacent structures that can be injured during the procedure. CT also simulates procedural fluoroscopic angles and provides evaluation of the interatrial septum, which is punctured during LAA closure. CT also provides a more convenient method for the evaluation of postprocedural complications such as incomplete closure, peridevice leaking, device-related thrombus, and device dislodgement. RSNA, 2021.
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http://dx.doi.org/10.1148/rg.2021200136DOI Listing
November 2021

Imaging Features of Complications after Coronary Interventions and Surgical Procedures.

Radiographics 2021 May-Jun;41(3):699-719. Epub 2021 Apr 2.

From the Department of Cardiac Imaging, Imaging and Diagnostic Center CID, Americas Avenue 2016, Guadalajara, Jalisco, Mexico (H.G.); Department of Radiology, Western National Medical Center IMSS, Guadalajara, Jalisco, Mexico (H.G., D.d.l.F., M.C.); Department of Radiology, University of Rochester Medical Center, Rochester, NY (A.C.); Department of Radiology, University of Colorado Hospital, Denver, Colo (D.V.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.M.Y., P.R.); and Department of Radiology, UT Health Science Center, San Antonio, Tex (S.S.S.).

Coronary artery interventions and surgical procedures are used in the treatment of coronary artery disease and some congenital heart diseases. Cardiac and noncardiac complications can occur at variable times after these procedures, with the clinical presentation ranging from asymptomatic to devastating symptoms. Invasive coronary angiography is the reference standard modality used in the evaluation of coronary arteries, with intravascular US and optical coherence tomography providing high-resolution information regarding the vessel wall. CT is the mostly commonly used noninvasive imaging modality in the evaluation of coronary artery intervention complications and allows assessment of the stent, lumen of the stent, lumen of the coronary arteries, and extracoronary structures. MRI is limited to the evaluation of the proximal coronary arteries but allows comprehensive evaluation of the myocardium, including ischemia and infarction. The authors review the clinical symptoms and pathophysiologic and imaging features of various complications of coronary artery interventions and surgical procedures. Complications of percutaneous coronary interventions are discussed, including restenosis, thrombosis, dissection of coronary arteries or the aorta, coronary wall rupture or perforation, stent deployment failure, stent fracture, stent infection, stent migration or embolism, and reperfusion injury. Complications of several surgical procedures are reviewed, including coronary artery bypass grafting, coronary artery reimplantation procedure (for anomalous origin from opposite sinuses or the pulmonary artery or as part of surgical procedures such as arterial switching surgery and the Bentall and Cabrol procedures), coronary artery unroofing, and the Takeuchi procedure. RSNA, 2021.
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http://dx.doi.org/10.1148/rg.2021200147DOI Listing
November 2021

Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans.

Eur J Cancer 2021 05 17;148:146-158. Epub 2021 Mar 17.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA. Electronic address:

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 (S), whereas 205 patients were used as part of test set I (S) and 62 patients were used as part of independent test set II (S). 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 (S [n = 205]: maximum AUCs of 0.85versus . 0.80; p-value = 0.047 and S [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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http://dx.doi.org/10.1016/j.ejca.2021.02.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087632PMC
May 2021

ACR Appropriateness Criteria® Nonischemic Myocardial Disease with Clinical Manifestations (Ischemic Cardiomyopathy Already Excluded).

J Am Coll Radiol 2021 May 27;18(5S):S83-S105. Epub 2021 Feb 27.

Specialty Chair, UT Southwestern Medical Center, Dallas, Texas.

Nonischemic cardiomyopathies encompass a broad spectrum of myocardial disorders with mechanical or electrical dysfunction without evidence of ischemia. There are five broad variants of nonischemic cardiomyopathies; hypertrophic cardiomyopathy (Variant 1), restrictive or infiltrative cardiomyopathy (Variant 2), dilated or unclassified cardiomyopathy (Variant 3), arrhythmogenic cardiomyopathy (Variant 4), and inflammatory cardiomyopathy (Variant 5). For variants 1, 3, and 4, resting transthoracic echocardiography, MRI heart function and morphology without and with contrast, and MRI heart function and morphology without contrast are the usually appropriate imaging modalities. For variants 2 and 5, resting transthoracic echocardiography and MRI heart function and morphology without and with contrast are the usually appropriate imaging modalities. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
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http://dx.doi.org/10.1016/j.jacr.2021.01.019DOI Listing
May 2021

Recognizing and Minimizing Artifacts at Dual-Energy CT.

Radiographics 2021 Mar-Apr;41(2):509-523. Epub 2021 Feb 19.

From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, Calif (C.A., B.M.Y.); Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); and Department of Radiology, University of Washington, Seattle, Wash (D.V.S.).

Dual-energy CT (DECT) is an exciting innovation in CT technology with profound capabilities to improve diagnosis and add value to patient care. Significant advances in this technology over the past decade have improved our ability to successfully adopt DECT into the clinical routine. To enable effective use of DECT, one must be aware of the pitfalls and artifacts related to this technology. Understanding the underlying technical basis of artifacts and the strategies to mitigate them requires optimization of scan protocols and parameters. The ability of radiologists and technologists to anticipate their occurrence and provide recommendations for proper selection of patients, intravenous and oral contrast media, and scan acquisition parameters is key to obtaining good-quality DECT images. In addition, choosing appropriate reconstruction algorithms such as image kernel, postprocessing parameters, and appropriate display settings is critical for preventing quantitative and qualitative interpretive errors. Therefore, knowledge of the appearances of these artifacts is essential to prevent errors and allows maximization of the potential of DECT. In this review article, the authors aim to provide a comprehensive and practical overview of possible artifacts that may be encountered at DECT across all currently available commercial clinical platforms. They also provide a pictorial overview of the diagnostic pitfalls and outline strategies for mitigating or preventing the occurrence of artifacts, when possible. The broadening scope of DECT applications necessitates up-to-date familiarity with these technologies to realize their full diagnostic potential.
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http://dx.doi.org/10.1148/rg.2021200049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924411PMC
November 2021

Multimodality Imaging of Transposition of the Great Arteries.

Radiographics 2021 Mar-Apr;41(2):338-360. Epub 2021 Jan 22.

From the Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (A.C.); Department of Cardiology, University of Iowa Stead Family Children's Hospital, Iowa City, Iowa (R.A.); Department of Radiology, University of Michigan, Ann Arbor, Mich (P.P.A.); and Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905 (C.F., P.R.).

Transposition of the great arteries (TGA) is a congenital conotruncal abnormality characterized by discordant connections between the ventricles and great arteries, with the aorta originating from the right ventricle (RV), and the pulmonary artery (PA) originating from the left ventricle (LV). The two main types of TGA are complete transposition or dextro-transposition of the great arteries (D-TGA), commonly referred to as d-loop, and congenitally corrected transposition (CCTGA), commonly referred to as l-loop or L-TGA. In D-TGA, the connections between the ventricles and atria are concordant, whereas in CCTGA they are discordant, with the left atrium connected to the RV, and the right atrium connected to the LV. D-TGA manifests during the neonatal period and can be surgically managed by atrial switch operation (AtrSO), arterial switch operation (ASO), Rastelli procedure, or Nikaidoh procedure. Arrhythmia, systemic ventricular dysfunction, baffle stenosis, and baffle leak are the common complications of AtrSO, whereas supravalvular pulmonary or branch PA stenosis, neoaortic dilatation, and coronary artery narrowing are the common complications of ASO. CCTGA may manifest late in life, even in adulthood. Surgeries for associated lesions such as tricuspid regurgitation, subpulmonic stenosis, and ventricular septal defect may be performed. A double-switch operation that includes both the atrial and arterial switch operations constitutes anatomic correction for CCTGA. Imaging plays an important role in the evaluation of TGA, both before and after surgery, for helping define the anatomy, quantify hemodynamics, and evaluate complications. Transthoracic echocardiography is the first-line imaging modality for presurgical planning in children with TGA. MRI provides comprehensive morphologic and functional information, particularly in adults after surgery. CT is performed when MRI is contraindicated or expected to generate artifacts. The authors review the imaging appearances of TGA, with a focus on pre- and postsurgical imaging. RSNA, 2021.
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http://dx.doi.org/10.1148/rg.2021200069DOI Listing
November 2021

Leadership Lessons From Equity Theory: The Interplay Between Radiologist Compensation and Motivation.

J Am Coll Radiol 2021 Jan;18(1 Pt B):211-213

Professor,Department of Radiology, Director, Gastrointestinal Imaging, University of Washington School of Medicine, Seattle, Washington. Electronic address:

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http://dx.doi.org/10.1016/j.jacr.2020.08.012DOI Listing
January 2021

Dual-Energy CT Images: Pearls and Pitfalls.

Radiographics 2021 Jan-Feb;41(1):98-119

From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, White 270, Boston, MA 02114 (A.P., S.L., F.J.S., A.R.K.); Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, Calif (C.A., B.M.Y.); Department of Radiology, Mayo Clinic, Rochester, Minn (P.R.); Department of Radiology, University of Washington, Seattle, Wash (D.V.S.); and Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany (S.L.).

Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. RSNA, 2021.
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http://dx.doi.org/10.1148/rg.2021200102DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7853765PMC
November 2021

Bilateral meandering pulmonary vein complex and unusual associated cardiovascular anomalies and shunt: Extremely rare entity.

Lung India 2021 Jan-Feb;38(1):74-76

Department of Radiology, University of Texas Health Science Center, San Antonio, TX, USA.

Meandering pulmonary vein (MPV) is a rare entity that can be associated with an additional cardiac and pulmonary venous variations, including left-to-right shunts. Clinicians should consider further workup with dedicated cardiac imaging to evaluate for associated cardiovascular abnormalities after an abnormal pulmonary vein draining is initially identified on routine computed tomography or echocardiogram. Pulmonary venous variations in MPV represent a spectrum of disorders, and no consistent nomenclature has been established.
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http://dx.doi.org/10.4103/lungindia.lungindia_47_20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8066919PMC
January 2021

The RSNA International COVID-19 Open Radiology Database (RICORD).

Radiology 2021 04 5;299(1):E204-E213. Epub 2021 Jan 5.

From the Department of Radiology, Stanford University, Stanford, Calif (E.B.T., J.S., B.P.P.); Department of Radiology, University of Pennsylvania Hospital, Philadelphia, Pa (S.S., M. Hershman, L.R.); Department of Radiology, Stanford University School of Medicine, Stanford University Medical Center, 725 Welch Rd, Room 1675, Stanford, CA 94305-5913 (M.P.L.); Department of Medical Imaging, University of Toronto, Unity Health Toronto, Toronto, Canada (E.C.); Department of Radiology, Mayo Clinic, Rochester, Minn (B.J.E., P.R.); Department of Radiology, Weill Cornell Medicine, New York, NY (G.S.); MD.ai, New York, NY (A.S.); Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Mass (J.K.C.); Department of Diagnostic and Interventional Radiology, Cairo University Kasr Alainy Faculty of Medicine, Cairo, Egypt (M. Hafez); Department of Radiology, The Ottawa Hospital, Ottawa, Canada (S.J.); Department of Radiology and Biomedical Imaging, Center for Intelligent Imaging, San Francisco, Calif (J.M.); Department of Radiology, Koç University School of Medicine, Koç University Hospital, Istanbul, Turkey (E.A.); Department of Radiology, ETZ Hospital, Tilburg, the Netherlands (E.R.R.); Department of Radiology, University of Ghent, Ghent, Belgium (E.R.R.); Department of Diagnostic Imaging, Universidade Federal de São Paulo, São Paulo, Brazil (F.C.K.); Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (L.T.); Department of Radiology, NYU Grossman School of Medicine, Center for Advanced Imaging Innovation and Research, Laura and Isaac Perlmutter Cancer Center, New York, NY (L.M.); Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (J.P.K.); and Department of Thoracic Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.C.W.).

The coronavirus disease 2019 (COVID-19) pandemic is a global health care emergency. Although reverse-transcription polymerase chain reaction testing is the reference standard method to identify patients with COVID-19 infection, chest radiography and CT play a vital role in the detection and management of these patients. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making. However, inadequate availability of a diverse annotated data set has limited the performance and generalizability of existing models. To address this unmet need, the RSNA and Society of Thoracic Radiology collaborated to develop the RSNA International COVID-19 Open Radiology Database (RICORD). This database is the first multi-institutional, multinational, expert-annotated COVID-19 imaging data set. It is made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. Pixel-level volumetric segmentation with clinical annotations was performed by thoracic radiology subspecialists for all COVID-19-positive thoracic CT scans. The labeling schema was coordinated with other international consensus panels and COVID-19 data annotation efforts, the European Society of Medical Imaging Informatics, the American College of Radiology, and the American Association of Physicists in Medicine. Study-level COVID-19 classification labels for chest radiographs were annotated by three radiologists, with majority vote adjudication by board-certified radiologists. RICORD consists of 240 thoracic CT scans and 1000 chest radiographs contributed from four international sites. It is anticipated that RICORD will ideally lead to prediction models that can demonstrate sustained performance across populations and health care systems.
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http://dx.doi.org/10.1148/radiol.2021203957DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993245PMC
April 2021

CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction.

Lancet Digit Health 2020 03 13;2(3):e116-e128. Epub 2020 Feb 13.

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, Ohio, USA. Electronic address:

Background: Use of adjuvant chemotherapy in patients with early-stage lung cancer is controversial because no definite biomarker exists to identify patients who would receive added benefit from it. We aimed to develop and validate a quantitative radiomic risk score (QuRiS) and associated nomogram (QuRNom) for early-stage non-small cell lung cancer (NSCLC) that is prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy following surgery.

Methods: We did a retrospective multicohort study of individuals with early-stage NSCLC (stage I and II) who either received surgery alone or surgery plus adjuvant chemotherapy. We selected patients for whom we had available pre-treatment diagnostic CT scans and corresponding survival information. We used radiomic texture features derived from within and outside the primary lung nodule on chest CT scans of patients from the Cleveland Clinic Foundation (Cleveland, OH, USA; cohort D) to develop QuRiS. A least absolute shrinkage and selection operator-Cox regularisation model was used for data dimension reduction, feature selection, and QuRiS construction. QuRiS was independently validated on a cohort of patients from the University of Pennsylvania (Philadephia, PA, USA; cohort D) and a cohort of patients whose CT scans were derived from The Cancer Imaging Archive (cohort D). QuRNom was constructed by integrating QuRiS with tumour and node descriptors (according to the tumour, node, metastasis staging system) and lymphovascular invasion. The primary endpoint of the study was the assessment of the performance of QuRiS and QuRNom in predicting disease-free survival. The added benefit of adjuvant chemotherapy estimated using QuRiS and QuRNom was validated by comparing patients who received adjuvant chemotherapy versus patients who underwent surgery alone in cohorts D-D.

Findings: We included: 329 patients in cohort D (73 [22%] had surgery plus adjuvant chemotherapy and 256 (78%) had surgery alone); 114 patients in cohort D (33 [29%] had surgery plus adjuvant chemotherapy and 81 (71%) had surgery alone); and 82 patients in cohort D (24 [29%] had surgery plus adjuvant chemotherapy and 58 (71%) had surgery alone). QuRiS comprised three intratumoral and 10 peritumoral CT-radiomic features and was found to be significantly associated with disease-free survival (ie, prognostic validation of QuRiS; hazard ratio for predicted high-risk vs predicted low-risk groups 1·56, 95% CI 1·08-2·23, p=0·016 for cohort D; 2·66, 1·24-5·68, p=0·011 for cohort D; and 2·67, 1·39-5·11, p=0·0029 for cohort D). To validate the predictive performance of QuRiS, patients were partitioned into three risk groups (high, intermediate, and low risk) on the basis of their corresponding QuRiS. Patients in the high-risk group were observed to have significantly longer survival with adjuvant chemotherapy than patients who underwent surgery alone (0·27, 0·08-0·95, p=0·042, for cohort D; 0·08, 0·01-0·42, p=0·0029, for cohorts D and D combined). As concerns QuRNom, the nomogram-estimated survival benefit was predictive of the actual efficacy of adjuvant chemotherapy (0·25, 0·12-0·55, p<0·0001, for cohort D; 0·13, <0·01-0·99, p=0·0019 for cohort D).

Interpretation: QuRiS and QuRNom were validated as being prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy, especially in clinically defined low-risk groups. Since QuRiS is based on routine chest CT imaging, with additional multisite independent validation it could potentially be employed for decision management in non-invasive treatment of resectable lung cancer.

Funding: National Cancer Institute of the US National Institutes of Health, National Center for Research Resources, US Department of Veterans Affairs Biomedical Laboratory Research and Development Service, Department of Defence, National Institute of Diabetes and Digestive and Kidney Diseases, Wallace H Coulter Foundation, Case Western Reserve University, and Dana Foundation.
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http://dx.doi.org/10.1016/S2589-7500(20)30002-9DOI Listing
March 2020

CT for Pre- and Postprocedural Evaluation of Transcatheter Mitral Valve Replacement.

Radiographics 2020 Oct;40(6):1528-1553

From the Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (P. Ranganath); Department of Radiology, Baylor University Medical Center, Dallas, Tex (A.M.); and Department of Cardiology (M.G.) and Department of Radiology (J.C., T.F., E.W., P. Rajiah), Mayo Clinic, 200 1st St SW, Rochester, MN 55905.

Transcatheter mitral valve replacement (TMVR) is a catheter-based interventional technique for treating mitral valve disease in patients who are at high risk for open mitral valve surgery and with unfavorable anatomy for minimally invasive edge-to-edge transcatheter mitral valve repair. There are several TMVR devices with different anchoring mechanisms, delivered by either transapical or transseptal approaches. Transthoracic echocardiography is the first-line imaging modality used for characterization and quantification of mitral valve disorders. CT is complementary to echocardiography and has several advantages, including high isotropic spatial resolution, good temporal resolution, large field of view, multiplanar reconstruction capabilities, and rapid turnaround time. CT is essential for multiple aspects of preprocedural planning. Accurate and reproducible techniques to prescribe the mitral annulus at CT have been described from which important measurements such as the area, perimeter, trigone-trigone distance, intercommissural distance, and septolateral distance are obtained. The neo-left ventricular outflow tract (LVOT) can be simulated by placing a virtual prosthesis in the CT data to predict the risk of TMVR-induced LVOT obstruction. The anatomy of the landing zone and subvalvular apparatus as well as the relationship of the virtual device to adjacent structures such as the coronary sinus and left circumflex coronary artery can be evaluated. CT also stimulates procedural fluoroscopic angles. CT can be used to evaluate the chest wall for transapical access and the atrial septum for transseptal access. Follow-up CT is useful in identifying complications such as LVOT obstruction, paravalvular leak, pseudoaneurysm, and valve embolization. RSNA, 2020.
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http://dx.doi.org/10.1148/rg.2020200027DOI Listing
October 2020

Cinematic Rendering Technique in Adult Congenital Heart Disease.

Semin Roentgenol 2020 07 24;55(3):241-250. Epub 2020 Jun 24.

Department of Radiology, Cardiovascular Imaging, Mayo Clinic, Rochester, MN. Electronic address:

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http://dx.doi.org/10.1053/j.ro.2020.06.013DOI Listing
July 2020

Update on Multienergy CT: Physics, Principles, and Applications.

Radiographics 2020 Sep-Oct;40(5):1284-1308. Epub 2020 Aug 21.

From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.R., S.L.); Department of Radiology, Massachusetts General Hospital, Boston, Mass (A.P., A.R.K.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (F.K.); and Department of Radiology, Medical University of South Carolina, Charleston, SC (D.B.).

Multienergy CT involves acquisition of two or more CT measurements with distinct energy spectra. Using the differential attenuation of tissues and materials at different x-ray energies, multienergy CT allows distinction of tissues and materials beyond that possible with conventional CT. Multienergy CT technologies can operate at the source or detector level. Dual-source, rapid tube-voltage switching, and dual-layer detector CT are the most commonly used multienergy CT technologies. Most of the currently available technologies typically use two energy levels, commonly referred to as . With use of two or more energy bins, photon-counting detector CT can perform multienergy CT beyond current dual-energy CT technologies. Multienergy CT postprocessing can be performed in the projection or image domain using two-material or multimaterial decomposition. The most commonly used multienergy CT images are virtual monoenergetic images (VMIs), iodine maps, virtual noncontrast (VNC) images, and uric acid images. Low-energy VMIs are used to boost contrast signal and enhance lesion conspicuity. High-energy VMIs are used to decrease some artifacts. Iodine maps are used to evaluate perfusion, characterize lesions, and evaluate response to therapy. VNC images are used to characterize lesions and save radiation dose by eliminating true noncontrast images from multiphasic acquisitions. Uric acid images are used for characterization of renal calculi and gout. RSNA, 2020.
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http://dx.doi.org/10.1148/rg.2020200038DOI Listing
July 2021

A Comprehensive CT Radiation Dose Reduction and Protocol Standardization Program in a Complex, Tertiary Hospital System.

Curr Probl Diagn Radiol 2020 Sep - Oct;49(5):340-346. Epub 2020 May 17.

Department of Radiology, UT Southwestern Medical Center, Dallas, TX.

Purpose: To present our experience in reducing CT radiation doses in a complex tertiary health system through CT protocol standardization and optimization.

Methods: A CT radiation task force was created to reduce CT protocol heterogeneity and radiation doses. Redundant protocols were eliminated. By an iterative process, protocols with least radiation dose were identified. Radiation dose tracking software was used to store and analyze radiation doses. CT protocols were published in an intranet site after training of technologists. SOPs were established for maintaining and changing protocols. The radiation doses for each CT protocol before and after optimization were compared using geometric means.

Results: A total of 222 CT protocols were reviewed, with elimination of 86 protocols. One-year follow-up showed homogeneous protocols with lower radiation doses. The improvement in radiation doses ranged from 23% to 58% (P< 0.001).

Conclusion: CT radiation dose reduction of up to 58% can be achieved by homogenizing and optimizing CT protocols through a comprehensive CT operations program.
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http://dx.doi.org/10.1067/j.cpradiol.2020.04.007DOI Listing
April 2021

Introduction to Special Issue on Performance Improvement and Safety.

Curr Probl Diagn Radiol 2020 Sep - Oct;49(5):305. Epub 2020 May 11.

Mayo Clinic, Rochester, MN.

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http://dx.doi.org/10.1067/j.cpradiol.2020.04.004DOI Listing
April 2021

Updates in Vascular Computed Tomography.

Authors:
Prabhakar Rajiah

Radiol Clin North Am 2020 Jul;58(4):671-691

Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55904, USA. Electronic address:

Computed tomography angiography (CTA) has become a mainstay for the imaging of vascular diseases, because of high accuracy, availability, and rapid turnaround time. High-quality CTA images can now be routinely obtained with high isotropic spatial resolution and temporal resolution. Advances in CTA have focused on improving the image quality, increasing the acquisition speed, eliminating artifacts, and reducing the doses of radiation and iodinated contrast media. Dual-energy computed tomography provides material composition capabilities that can be used for characterizing lesions, optimizing contrast, decreasing artifact, and reducing radiation dose. Deep learning techniques can be used for classification, segmentation, quantification, and image enhancement.
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http://dx.doi.org/10.1016/j.rcl.2020.02.011DOI Listing
July 2020

The Role of Imaging in Health Screening: Overview, Rationale of Screening, and Screening Economics.

Acad Radiol 2021 04 12;28(4):540-547. Epub 2020 May 12.

Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas.

Imaging screening examinations are growing in their indications and volume to identify conditions at an early, treatable stage. The Radiology Research Alliance's 'Role of Imaging in Health Screening' Task Force provides a review of imaging-based screening rationale, economics, and describes established guidelines by various organizations. Various imaging modalities can be employed in screening, and are often chosen based on the specific pathology and patient characteristics. Prevalent disease processes with identifiable progression patterns that benefit from early potentially curative interventions are ideal for screening. Two such examples include colonic precancerous polyp progression to adenocarcinoma in colon cancer formation and atypical ductal hyperplasia progression to ductal carcinoma in situ and invasive ductal carcinoma in breast cancer. Economic factors in imaging-based screening are reviewed, including in the context of value-based reimbursements. Global differences in screening are outlined, along with the role of various organizational guidelines, including the American Cancer Society, the US Preventive Services Task Force, and the American College of Radiology.
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http://dx.doi.org/10.1016/j.acra.2020.03.038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7655697PMC
April 2021

The Role of Imaging in Health Screening: Screening for Specific Conditions.

Acad Radiol 2021 04 11;28(4):548-563. Epub 2020 May 11.

Department of Breast Imaging, The University of Texas MD Anderson Cancer Center; Houston, Texas.

There are well-established and emerging screening examinations aimed at identifying malignant and nonmalignant conditions at early, treatable stages. The Radiology Research Alliance's "Role of Imaging in Health Screening" Task Force provides a comprehensive review of specific imaging-based screening examinations. This work reviews and serves as a reference for screening examinations for breast and colon cancer in a healthy population along with screening for lung cancer, hepatocellular carcinoma, and the use of whole body magnetic resonance imaging in at-risk individuals. American College of Radiology scoring systems, along with case-based examples, are included to illustrate the different disease entities. The future of screening is discussed, particularly in the context of artificial intelligence.
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http://dx.doi.org/10.1016/j.acra.2020.03.039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7655640PMC
April 2021

ACR Appropriateness Criteria® Chest Pain-Possible Acute Coronary Syndrome.

J Am Coll Radiol 2020 May;17(5S):S55-S69

Specialty Chair, UT Southwestern Medical Center, Dallas, Texas.

Chest pain is a frequent cause for emergency department visits and inpatient evaluation, with particular concern for acute coronary syndrome as an etiology, since cardiovascular disease is the leading cause of death in the United States. Although history-based, electrocardiographic, and laboratory evaluations have shown promise in identifying coronary artery disease, early accurate diagnosis is paramount and there is an important role for imaging examinations to determine the presence and extent of anatomic coronary abnormality and ischemic physiology, to guide management with regard to optimal medical therapy or revascularization, and ultimately to thereby improve patient outcomes. A summary of the various methods for initial imaging evaluation of suspected acute coronary syndrome is outlined in this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
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http://dx.doi.org/10.1016/j.jacr.2020.01.027DOI Listing
May 2020

CAD-RADS: Pushing the Limits.

Radiographics 2020 May-Jun;40(3):629-652. Epub 2020 Apr 10.

From the Department of Radiology, Division of Cardiothoracic Imaging, UT Southwestern Medical Center, Dallas, Tex (A.C., P. Ranganath, H.G., S.A., P. Rajiah); Imaging and Diagnosis Center, Guadalajara, Mexico (H.G.); and Department of Radiology, University of Chicago Medical Center, Chicago, Ill (L.L.).

Coronary CT angiography is now established as the first-line diagnostic imaging test to exclude coronary artery disease (CAD) in the population at low to intermediate risk. Wide variability exists in both the reporting of coronary CT angiography and the interpretation of these reports by referring physicians. The CAD Reporting and Data System (CAD-RADS) is sponsored by multiple societies and is a collaborative effort to provide standard classification of CAD, which is then integrated into patient clinical care. The main goals of the CAD-RADS are to decrease variability among readers; enhance communication between interpreting and referring clinicians, allowing collaborative determination of the best course of patient care; and generate consistent data for auditing, data mining, quality improvement, research, and education. There are several scenarios in which the CAD-RADS guidelines are ambiguous or do not provide definite recommendations for further management of CAD. The authors discuss the CAD-RADS categories and modifiers, highlight a variety of complex or ambiguous scenarios, and provide recommendations for managing these scenarios. RSNA, 2020 See discussion on this article by Aviram and Wolak.
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http://dx.doi.org/10.1148/rg.2020190164DOI Listing
April 2021
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