36,257 results match your criteria Radiology[Journal]


Left Ventricular Strain Is Abnormal in Preclinical and Overt Hypertrophic Cardiomyopathy: Cardiac MR Feature Tracking.

Radiology 2018 Dec 18:180339. Epub 2018 Dec 18.

From the Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Md (D.M.V., M.W.T.); Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, England (D.M.V., M.W.T., J.A.N.); Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Mass (D.M.V.); Division of Cardiology (E.Y.) and Russell H. Morgan Department of Radiology and Radiological Science (L.C.), Johns Hopkins Hospital, Baltimore, Md; University of Chicago, The College, Chicago, Ill (P.J.J.); Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio (M.W.T.); Cardiovascular Division, Brigham and Women's Hospital, Boston, Mass (H.F., C.Y.H.); Departments of Internal Medicine and Pediatrics, University of Michigan, Ann Arbor, Mich (S.M.D., M.W.R.); Department of Cardiology, Boston Children's Hospital, Boston, Mass (S.D.C.); The Heart Institute and Pediatric Cardiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio (J.T.);New York University Langone Medical Center, New York, NY (M.V.S.); Department of Pediatrics, Washington University School of Medicine, St Louis, Mo (C.E.C.); Department of Nursing, College of Nursing and Health Sciences, University of Massachusetts Boston, Boston, Mass (L.S.); and School of Medicine and Public Health, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792 (D.A.B.).

Purpose To evaluate myocardial strain and circumferential transmural strain difference (cTSD; the difference between epicardial and endocardial circumferential strain) in a genotyped cohort with hypertrophic cardiomyopathy (HCM) and to explore correlations between cTSD and other anatomic and functional markers of disease status. Left ventricular (LV) dysfunction may indicate early disease in preclinical HCM (sarcomere mutation carriers without LV hypertrophy). Cardiac MRI feature tracking may be used to evaluate myocardial strain in carriers of HCM sarcomere mutation. Read More

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http://dx.doi.org/10.1148/radiol.2018180339DOI Listing
December 2018

Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas.

Radiology 2018 Dec 18:180910. Epub 2018 Dec 18.

From the Department of Biomedical Engineering, Case Western Reserve University, 2071 Martin Luther King Dr, Wickenden 523, Cleveland, OH 44106-7207 (N. Beig, M.K., M.A., P.P., N. Braman, M.O., K.B., P.T., A.M.); Taussig Cancer Institute-Cleveland Clinic, Cleveland, Ohio (S.R.); Division of Thoracic and Esophageal Surgery (J.G., P.L.), Division of Pulmonary Critical Care and Sleep Medicine (C.D., F.J.), Department of Pathology (M.Y.), and Department of Radiology (R.G.), University Hospitals of Cleveland, Cleveland, Ohio; Pulmonary Section, Cleveland Veterans Affairs Medical Center, Cleveland, Ohio (F.J.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (P.R.); Department of Internal Medicine, Maimonides Medical Center, Brooklyn, NY (R.T.); and Hematology and Oncology, New York University, Perlmutter Cancer Center, New York, NY (V.V.).

Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials and Methods For this retrospective study, screening or standard diagnostic noncontrast CT images were collected for 290 patients (mean age, 68 years; range, 18-92 years; 125 men [mean age, 67 years; range, 18-90 years] and 165 women [mean age, 68 years; range, 33-92 years]) from two institutions between 2007 and 2013. Histopathologic analysis was available for one nodule per patient. Read More

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http://dx.doi.org/10.1148/radiol.2018180910DOI Listing
December 2018

Perinodular Radiomic Features to Assess Nodule Microenvironment: Does It Help to Distinguish Malignant versus Benign Lung Nodules?

Authors:
Mizuki Nishino

Radiology 2018 Dec 18:182619. Epub 2018 Dec 18.

From the Department of Radiology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215.

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http://dx.doi.org/10.1148/radiol.2018182619DOI Listing
December 2018

Nondiagnostic Percutaneous Transthoracic Needle Biopsy of Lung Lesions: A Multicenter Study of Malignancy Risk.

Radiology 2018 Dec 18:181482. Epub 2018 Dec 18.

From the Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, South Korea (K.H.L.); Department of Radiology, National Cancer Center, Gyeonggi-do, South Korea (K.Y.L.); Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea (Y.J.S., J.H.); Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea (J.H.); Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea (D.H.H.); Department of Radiology, Inje University Sanggyepaik Hospital, Seoul, South Korea (M.J.K.); Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Gyeonggi-do, South Korea (J.Y.C., C.K.); Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul, South Korea (J.I.K.); Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (S.H.Y., C.M.P.); Department of Statistics, Inha University, Incheon, South Korea (W.L.); and Institute of Radiation Medicine, Seoul National University Medical Research Center, 101 Daehak-ro, Jongno-gu, Seoul 03080, South Korea (C.M.P.).

Purpose To evaluate the malignancy risk of lung lesions that show nondiagnostic results at transthoracic needle biopsy (PTNB) of the lung and to identify any malignancy-associated risk factors in each nondiagnostic category. Materials and Methods In this retrospective study, 9384 initial PTNBs (9239 patients [mean age, 65 years; age range, 20-99 years] consisting of 5729 men [mean age, 66 years; age range, 20-99 years] and 3510 women [mean age, 63 years; age range, 20-94 years]) were performed in eight institutions between January 2010 and December 2014. PTNB results were categorized as diagnostic (malignant or specifically benign) or nondiagnostic (nonspecific benign pathologic findings, atypical cells, or insufficient specimen), and the proportion of final malignant diagnoses per nondiagnostic category was obtained. Read More

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http://dx.doi.org/10.1148/radiol.2018181482DOI Listing
December 2018

How Should We Manage Nondiagnostic Lung Biopsies?

Authors:
Brett M Elicker

Radiology 2018 Dec 18:182630. Epub 2018 Dec 18.

From the Department of Radiology, University of California, San Francisco, 505 Parnassus Ave, Box 0628, San Francisco, CA 94143.

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http://dx.doi.org/10.1148/radiol.2018182630DOI Listing
December 2018

Interstitial Lung Abnormality: Recognition and Perspectives.

Radiology 2018 Dec 18:181684. Epub 2018 Dec 18.

From the Department of Radiology (H.H.) and Pulmonary and Critical Care Division (G.M.H.), Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215; and Department of Radiology, National Jewish Medical and Research Center, Denver, Colo (D.A.L.).

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http://dx.doi.org/10.1148/radiol.2018181684DOI Listing
December 2018

Monitoring Fatty Liver Disease with MRI Following Bariatric Surgery: A Prospective, Dual-Center Study.

Radiology 2018 Dec 18:181134. Epub 2018 Dec 18.

From the Departments of Radiology (B.D.P., C.N.W., A.M., N.S.A., S.B.R.), Medical Physics (S.B.R.), Medicine (S.B.R.), Emergency Medicine (S.B.R.), and General Surgery (L.M.F., J.A.G.), University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252; Madison Radiologists, SC, Madison, Wis (B.D.P.); Department of General Surgery, William S. Middleton Memorial Veterans Hospital, Madison, Wis (L.M.F.); Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (N.S.A.); Departments of Radiology, Liver Imaging Group (A.S., Y.C., J.H., C.B.S.), Pediatrics, Section of Gastroenterology (J.B.S.), General Surgery (G.J., S.H.), and Computational and Applied Statistics Laboratory (T.W., A.C.G.), University of California, San Diego, Calif; and Department of Surgery, Virginia Commonwealth University, Richmond, Va (G.M.C.).

Purpose To longitudinally monitor liver fat before and after bariatric surgery by using quantitative chemical shift-encoded (CSE) MRI and to compare with changes in body mass index (BMI), weight, and waist circumference (WC). Materials and Methods For this prospective study, which was approved by the internal review board, a total of 126 participants with obesity who were undergoing evaluation for bariatric surgery with preoperative very low calorie diet (VLCD) were recruited from June 27, 2010, through May 5, 2015. Written informed consent was obtained from all participants. Read More

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http://dx.doi.org/10.1148/radiol.2018181134DOI Listing
December 2018

Impact of Digital Mammography on Cancer Detection and Recall Rates: 11.3 Million Screening Episodes in the English National Health Service Breast Cancer Screening Program.

Radiology 2018 Dec 11:181426. Epub 2018 Dec 11.

From the Cancer Epidemiology Unit, Nuffield Department of Population Health, Oxford University, Richard Doll Building, Roosevelt Drive, Oxford OX3 7LF, England (R.G.B., J.P., R.A.); Cambridge Breast Unit and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Trust, Cambridge, England (M.G.W.); Screening QA Service, Public Health England, London, England (O.K.); Breast Screening Programme, Public Health England, London, England (J.J.); and Department of Radiology, St George's University Hospital Foundation Trust, London, England (R.M.G.W.).

Purpose To report the impact of changing from screen-film mammography to digital mammography (DM) in a large organized national screening program. Materials and Methods A retrospective analysis of prospectively collected annual screening data from 2009-2010 to 2015-2016 for the 80 facilities of the English National Health Service Breast Cancer Screening Program, together with estimates of DM usage for three time periods, enabled the effect of DM to be measured in a study of 11.3 million screening episodes in women aged 45-70 years (mean age, 59 years). Read More

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http://dx.doi.org/10.1148/radiol.2018181426DOI Listing
December 2018

Combined Benefit of Quantitative Three-Compartment Breast Image Analysis and Mammography Radiomics in the Classification of Breast Masses in a Clinical Data Set.

Radiology 2018 Dec 11:180608. Epub 2018 Dec 11.

From the Department of Radiology, University of Chicago, 5481 S Maryland Ave, MC2026, Chicago, IL 60637 (K.D., M.L.G.); Department of Radiology and Biomedical Imaging (B.N.J., H.G., B.F., S.M., J.A., L.K., J.S.) and Department of Medicine and Epidemiology (K.K.), University of California, San Francisco, San Francisco, Calif; and Department of Diagnostic Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Fla (J.S.D., B.N.).

Purpose To investigate the combination of mammography radiomics and quantitative three-compartment breast (3CB) image analysis of dual-energy mammography to limit unnecessary benign breast biopsies. Materials and Methods For this prospective study, dual-energy craniocaudal and mediolateral oblique mammograms were obtained immediately before biopsy in 109 women (mean age, 51 years; range, 31-85 years) with Breast Imaging Reporting and Data System category 4 or 5 breast masses (35 invasive cancers, 74 benign) from 2013 through 2017. The three quantitative compartments of water, lipid, and protein thickness at each pixel were calculated from the attenuation at high and low energy by using a within-image phantom. Read More

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http://dx.doi.org/10.1148/radiol.2018180608DOI Listing
December 2018
1 Read

Radiomics of Brain MRI: Utility in Prediction of Metastatic Tumor Type.

Radiology 2018 Dec 11:180946. Epub 2018 Dec 11.

From the Department of Diagnostic and Interventional Neuroradiology (H.C.K., T.S., U.H., M.H.S., J.F., S.G.), Department of Radiotherapy and Radiation Oncology (F.M., T.G.), Institute of Medical Biometry and Epidemiology (G.S.), and Institute of Computational Neuroscience (F.M., R.W.); University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany.

Purpose To investigate the feasibility of tumor type prediction with MRI radiomic image features of different brain metastases in a multiclass machine learning approach for patients with unknown primary lesion at the time of diagnosis. Materials and methods This single-center retrospective analysis included radiomic features of 658 brain metastases from T1-weighted contrast material-enhanced, T1-weighted nonenhanced, and fluid-attenuated inversion recovery (FLAIR) images in 189 patients (101 women, 88 men; mean age, 61 years; age range, 32-85 years). Images were acquired over a 9-year period (from September 2007 through December 2016) with different MRI units, reflecting heterogeneous image data. Read More

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http://dx.doi.org/10.1148/radiol.2018180946DOI Listing
December 2018

The Dawn of a New Era in Low-Dose PET Imaging.

Authors:
Ciprian Catana

Radiology 2018 Dec 11:182573. Epub 2018 Dec 11.

From the Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, A.A. Martinos Center, 149 13th St, Room 2.301, Charlestown, MA 02129.

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http://dx.doi.org/10.1148/radiol.2018182573DOI Listing
December 2018

Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning.

Radiology 2018 Dec 11:181432. Epub 2018 Dec 11.

From the Department of Biomedical Engineering and Physiology (A.D.W.) and Department of Radiology (P.K., T.L.K., K.A.P., P.K., T.S., M.S., N.T., B.J.E.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.

Purpose To develop and evaluate a fully automated algorithm for segmenting the abdomen from CT to quantify body composition. Materials and Methods For this retrospective study, a convolutional neural network based on the U-Net architecture was trained to perform abdominal segmentation on a data set of 2430 two-dimensional CT examinations and was tested on 270 CT examinations. It was further tested on a separate data set of 2369 patients with hepatocellular carcinoma (HCC). Read More

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http://dx.doi.org/10.1148/radiol.2018181432DOI Listing
December 2018

Impact of New Technology Adoption on Breast Cancer Screening.

Radiology 2018 Dec 11:182476. Epub 2018 Dec 11.

From the Department of Radiology, University of Washington School of Medicine, 1144 Eastlake Ave E, LG-212, Seattle, Wash 98109 (C.I.L., J.M.L.); Hutchinson Institute for Cancer Outcomes Research, Seattle, Wash (C.I.L., J.M.L.); and Department of Health Services, University of Washington School of Public Health, Seattle, Wash (C.I.L.).

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http://dx.doi.org/10.1148/radiol.2018182476DOI Listing
December 2018

Ultra-Low-Dose F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.

Radiology 2018 Dec 11:180940. Epub 2018 Dec 11.

From the Departments of Radiology (K.T.C., F.B.d.C.M., S.S., G.Z.), Electrical Engineering (E.G., J.M.P.), and Neurology and Neurological Sciences (A.B., K.L.P., S.J.S., M.D.G., E.M.), Stanford University, 1201 Welch Rd, Stanford, CA 94305; Department of Engineering Physics, Tsinghua University, Beijing, PR China (J.X.); GE Healthcare, Menlo Park, Calif (M.K.); and Subtle Medical, Menlo Park, CA (E.G.).

Purpose To reduce radiotracer requirements for amyloid PET/MRI without sacrificing diagnostic quality by using deep learning methods. Materials and Methods Forty data sets from 39 patients (mean age ± standard deviation [SD], 67 years ± 8), including 16 male patients and 23 female patients (mean age, 66 years ± 6 and 68 years ± 9, respectively), who underwent simultaneous amyloid (fluorine 18 [F]-florbetaben) PET/MRI examinations were acquired from March 2016 through October 2017 and retrospectively analyzed. One hundredth of the raw list-mode PET data were randomly chosen to simulate a low-dose (1%) acquisition. Read More

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http://dx.doi.org/10.1148/radiol.2018180940DOI Listing
December 2018

With a Little Help from Machine Learning, Precision Radiology Can Be Feasible.

Authors:
Paul J Chang

Radiology 2018 Dec 11:182557. Epub 2018 Dec 11.

From the Department of Radiology, University of Chicago Medicine, 5841 S Maryland Ave, MC2026, Chicago, IL 60637.

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http://dx.doi.org/10.1148/radiol.2018182557DOI Listing
December 2018

Diagnostic Case-Control versus Diagnostic Cohort Studies for Clinical Validation of Artificial Intelligence Algorithm Performance.

Authors:
Seong Ho Park

Radiology 2018 Dec 4:182294. Epub 2018 Dec 4.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea.

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http://dx.doi.org/10.1148/radiol.2018182294DOI Listing
December 2018

Repeat Contrast Medium Administration for Patients with Mild Immediate Hypersensitivity Reaction to Iodinated Contrast Media.

Authors:
Shoko Abe

Radiology 2018 Dec 4:182146. Epub 2018 Dec 4.

Department of Radiology, St Marianna University School of Medicine, Kawasaki, Japan.

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http://pubs.rsna.org/doi/10.1148/radiol.2018182146
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http://dx.doi.org/10.1148/radiol.2018182146DOI Listing
December 2018
4 Reads

Comparison of Upright Digital Breast Tomosynthesis-guided versus Prone Stereotactic Vacuum-assisted Breast Biopsy.

Radiology 2018 Dec 4:181788. Epub 2018 Dec 4.

From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, WAC 240, Boston, MA 02114.

Purpose To compare the performance of upright digital breast tomosynthesis (DBT)-guided vacuum-assisted breast biopsy (VABB) with that of prone stereotactic (PS) VABB. Materials and Methods This retrospective review involved consecutive patients who underwent PS VABB from August 2014 to December 2015 and upright DBT-guided VABB from February 2016 to June 2017. Tissue sampling methods were the same for PS and DBT-guided biopsies. Read More

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http://dx.doi.org/10.1148/radiol.2018181788DOI Listing
December 2018

PET in Lymphoma: Making a Difference in Patients' Lives.

Authors:
James A Scott

Radiology 2018 Dec 4:182517. Epub 2018 Dec 4.

From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114.

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http://dx.doi.org/10.1148/radiol.2018182517DOI Listing
December 2018

Effect of PET/CT on the Management and Outcomes of Participants with Hodgkin and Aggressive Non-Hodgkin Lymphoma: A Multicenter Registry.

Radiology 2018 Dec 4:181519. Epub 2018 Dec 4.

From the Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital & Women's College Hospital, University of Toronto, 610 University Ave, Suite 3-960, Toronto, ON M5G 2M9, Canada (U.M., N.T.); Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, ON, Canada (A.P.); Department of Radiation Oncology, University of Toronto, and Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada (D.C.H.); Cancer Analytics, Analytics & Informatics (M.M., M.E., V.M.), Quality Measurement and Evaluation, Clinical Programs and Quality Initiatives (B.G.), Cancer Imaging, Clinical Programs and Quality Initiatives (P.M.), and Research Office, Analytics & Informatics (N.M., D.L.L.), Cancer Care Ontario, Toronto, ON, Canada; Department of Nuclear Medicine and Molecular Imaging, Hamilton Health Sciences, McMaster University, Hamilton, ON, Canada (A.S.); and Department of Oncology, Cancer Centre of Southeastern Ontario, Queen's University, Kingston, ON, Canada (J.D.).

Purpose To determine the relationship of PET/CT staging to the management and outcomes of participants with apparent limited-stage (LS) Hodgkin lymphoma (HL) or aggressive non-HL (ANHL) treated with curative intent. Materials and Methods This prospective multicenter registry included 850 participants (467 men and 383 women; median age, 54.1 years) from nine centers who had LS HL or ANHL on the basis of clinical data and CT, or with equivocal CT for advanced stage, who were considered for curative-intent first-line therapy. Read More

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http://dx.doi.org/10.1148/radiol.2018181519DOI Listing
December 2018
2 Reads

Quantitative MRI of Diffuse Liver Disease: Current Applications and Future Directions.

Radiology 2018 Dec 4:172765. Epub 2018 Dec 4.

From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, Campus Box 8131, St Louis, MO 63110.

As radiologic technology advances, quantitative imaging is becoming more prevalent in clinical practice. This article reviews quantitative hepatic MRI, specifically involving fat and iron deposition, by demonstrating how they were iteratively improved. These iterative improvements involved incorporating more knowledge about the physiology of liver disease and MRI physics to reduce the adverse effects caused by confounding factors. Read More

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http://dx.doi.org/10.1148/radiol.2018172765DOI Listing
December 2018
2 Reads

Fluorine 18-FDG PET/CT and Diffusion-weighted MRI for Malignant versus Benign Pulmonary Lesions: A Meta-Analysis.

Radiology 2018 Nov 27:181159. Epub 2018 Nov 27.

From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.).

Purpose To perform a meta-analysis of the literature to compare the diagnostic performance of fluorine 18 fluorodeoxyglucose PET/CT and diffusion-weighted (DW) MRI in the differentiation of malignant and benign pulmonary nodules and masses. Materials and Methods Published English-language studies on the diagnostic accuracy of PET/CT and/or DW MRI in the characterization of pulmonary lesions were searched in relevant databases through December 2017. The primary focus was on studies in which joint DW MRI and PET/CT were performed in the entire study population, to reduce interstudy heterogeneity. Read More

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http://dx.doi.org/10.1148/radiol.2018181159DOI Listing
November 2018
6.867 Impact Factor

Shear-Wave Elastography of Benign versus Malignant Musculoskeletal Soft-Tissue Masses: Comparison with Conventional US and MRI.

Radiology 2018 Nov 27:180950. Epub 2018 Nov 27.

From the Musculoskeletal Centre X-Ray Department, Leeds Teaching Hospitals Trust, Chapel Allerton Hospital, Leeds LS7 4SA, England (A.N.T., E.A., H.G., P.R.); Leeds Biomedical Research Centre, University of Leeds, Leeds, England (A.M.A., E.M.A.H., P.R.); Radiology and Medical Imaging Department, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Kharj, Saudi Arabia (A.M.A.); and Leeds Institute of Rheumatic and Musculoskeletal Medicine, Chapel Allerton Hospital, University of Leeds, England (A.M.A., E.M.A.H.).

Purpose To examine if shear-wave elastography (SWE) improves the accuracy of diagnosing soft-tissue masses as benign or malignant compared with US alone or in combination with MRI. Materials and Methods Two hundred six consecutive adult participants (mean age, 57.7 years; range, 18-91 years), including 89 men (median age, 56. Read More

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http://dx.doi.org/10.1148/radiol.2018180950DOI Listing
November 2018
5 Reads

The RSNA Pediatric Bone Age Machine Learning Challenge.

Radiology 2018 Nov 27:180736. Epub 2018 Nov 27.

From the Department of Radiology, Stanford University, 300 Pasteur Dr, MC 5105, Stanford, CA 94305 (S.S.H.); Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio (L.M.P.); Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, Mass (J.K.C.); Massachusetts General Hospital & Brigham and Women's Hospital Center for Clinical Data Science, Boston, Mass (A.B.M., K.A.); Department of Radiology, University of Toronto, Toronto, Ontario, Canada (A.B.); Department of Radiology, St. Michael's Hospital, Toronto, Ontario, Canada (M.C.); Department of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Rhode Island Hospital, Providence, RI (I.P.); Universidade Federal de Goiás, Goiânia, Brazil (L.A.P., R.T.S.); Universidade Federal de São Paulo, São Paulo, Brazil (N.A., F.C.K.); Visiana, Hørsholm, Denmark (H.H.T.); MD.ai, New York, NY (L.C.); Department of Radiology, Weill Cornell Medicine, New York, NY (G.S.) Department of Radiology, University of California-San Francisco, San Francisco, Calif (M.D.K.); Department of Radiology, Mayo Clinic, Rochester, Minn (B.J.E.); and Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (A.E.F.).

Purpose The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning (ML) and artificial intelligence (AI) in medical imaging, promote collaboration to catalyze AI model creation, and identify innovators in medical imaging. Materials and Methods The goal of this challenge was to solicit individuals and teams to create an algorithm or model using ML techniques that would accurately determine skeletal age in a curated data set of pediatric hand radiographs. The primary evaluation measure was the mean absolute distance (MAD) in months, which was calculated as the mean of the absolute values of the difference between the model estimates and those of the reference standard, bone age. Read More

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http://dx.doi.org/10.1148/radiol.2018180736DOI Listing
November 2018

Detection of Colorectal Hepatic Metastases Is Superior at Standard Radiation Dose CT versus Reduced Dose CT.

Radiology 2018 Nov 27:181657. Epub 2018 Nov 27.

From the Departments of Diagnostic Radiology (C.T.J., N.A.W., L.N.V., B.R., D.M., S.G.), Biostatistics (W.W.), and Physics (X.L.), University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; and Duke University Medical Center, Durham, NC (Y.C., E.S.).

Purpose To evaluate colorectal cancer hepatic metastasis detection and characterization between reduced radiation dose (RD) and standard dose (SD) contrast material-enhanced CT of the abdomen and to qualitatively compare between filtered back projection (FBP) and iterative reconstruction algorithms. Materials and Methods In this prospective study (from May 2017 through November 2017), 52 adults with biopsy-proven colorectal cancer and suspected hepatic metastases at baseline CT underwent two portal venous phase CT scans: SD and RD in the same breath hold. Three radiologists, blinded to examination details, performed detection and characterization of 2-15-mm lesions on the SD FBP and RD adaptive statistical iterative reconstruction (ASIR)-V 60% series images. Read More

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http://pubs.rsna.org/doi/10.1148/radiol.2018181657
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http://dx.doi.org/10.1148/radiol.2018181657DOI Listing
November 2018
4 Reads

Interreader Variability of Dynamic Contrast-enhanced MRI of Recurrent Glioblastoma: The Multicenter ACRIN 6677/RTOG 0625 Study.

Radiology 2018 Nov 27:181296. Epub 2018 Nov 27.

From the Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Durham, NC 27710 (D.P.B.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, RI (Z.Z.); Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, Tex (P.D.); Center for Statistical Sciences, Brown University School of Public Health, Providence, RI (B.S.S.); Pharmascan Clinical Trials and Radiology Associates of Clearwater, University of South Florida, Clearwater, Fla (Y.S.); Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (R.C.M.); Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel (F.B.); A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Mass (G.S.); Siemens Healthcare, Malvern, Pa (G.S.); Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Tex (M.R.G.); and Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, RI (J.L.B.).

Purpose To evaluate factors contributing to interreader variation (IRV) in parameters measured at dynamic contrast material-enhanced (DCE) MRI in patients with glioblastoma who were participating in a multicenter trial. Materials and Methods A total of 18 patients (mean age, 57 years ± 13 [standard deviation]; 10 men) who volunteered for the advanced imaging arm of ACRIN 6677, a substudy of the RTOG 0625 clinical trial for recurrent glioblastoma treatment, underwent analyzable DCE MRI at one of four centers. The 78 imaging studies were analyzed centrally to derive the volume transfer constant (K) for gadolinium between blood plasma and tissue extravascular extracellular space, fractional volume of the extracellular extravascular space (v), and initial area under the gadolinium concentration curve (IAUGC). Read More

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http://dx.doi.org/10.1148/radiol.2019181296DOI Listing
November 2018
2 Reads

Autologous Blood Patch Injection versus Hydrogel Plug in CT-guided Lung Biopsy: A Prospective Randomized Trial.

Radiology 2018 Nov 27:181140. Epub 2018 Nov 27.

From the Departments of Radiology (M.M., N.M., K.T.B., C.L.Z., M.J., C.I.G., C.T.S., J.P.E., A.M.C., L.A.B., H.Y., A.R.D., Y.B., W.A., R.H.S., J.C.D., A.J.G., E.Z., F.E.B., S.B.S.) and Epidemiology and Biostatistics (C.S.M., M.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, M276C, New York, NY 10065.

Purpose To compare the effect of autologous blood patch injection (ABPI) with that of a hydrogel plug on the rate of pneumothorax at CT-guided percutaneous lung biopsy. Materials and Methods In this prospective randomized controlled trial ( https://ClinicalTrials.gov , NCT02224924), a noninferiority design was used for ABPI, with a 10% noninferiority margin when compared with the hydrogel plug, with the primary outcome of pneumothorax rate within 2 hours of biopsy. Read More

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November 2018
1 Read

Editor's Recognition Awards.

Authors:
David A Bluemke

Radiology 2018 Nov 27:182471. Epub 2018 Nov 27.

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November 2018

MRI of Recurrent Glioblastoma: Reliability and Reality.

Authors:
Ronald L Wolf

Radiology 2018 Nov 27:182530. Epub 2018 Nov 27.

From the Department of Radiology, Neuroradiology Section, Perelman School of Medicine, University of Pennsylvania Health System, Dulles 219, 3400 Spruce St, Philadelphia, PA 19104.

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November 2018

Can Solitary Pulmonary Nodules Be Accurately Characterized with Diffusion-weighted MRI?

Authors:
Mark L Schiebler

Radiology 2018 Nov 27:182442. Epub 2018 Nov 27.

From the Department of Radiology, University of Wisconsin at Madison School of Medicine and Public Health, 600 Highland Ave, Madison, WI 53792-3252.

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http://dx.doi.org/10.1148/radiol.2018182442DOI Listing
November 2018

Detecting Breast Cancers with Mammography: Will AI Succeed Where Traditional CAD Failed?

Authors:
Manisha Bahl

Radiology 2018 Nov 20:182404. Epub 2018 Nov 20.

From the Department of Radiology, Division of Breast Imaging, Massachusetts General Hospital, 55 Fruit St, WAC 240, Boston, MA 02114.

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http://dx.doi.org/10.1148/radiol.2018182404DOI Listing
November 2018

A Decision Analysis of Follow-up and Treatment Algorithms for Nonsolid Pulmonary Nodules.

Radiology 2018 Nov 20:180867. Epub 2018 Nov 20.

From the Department of Radiology, Brigham and Women's Hospital, Boston, Mass (M.M.H.); Institute for Technology Assessment, Massachusetts General Hospital, 101 Merrimac St, 10th Floor, Boston, MA 02114 (L.L.P., A.L.E., C.Y.K.); Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa, (E.M.B.); and Harvard Medical School, Boston, Mass (C.Y.K.).

Purpose To evaluate management strategies and treatment options for patients with ground-glass nodules (GGNs) by using decision-analysis models. Materials and Methods A simulation was developed for 1 000 000 hypothetical patients with GGNs undergoing follow-up per the Lung Imaging Reporting and Data System (Lung-RADS) recommendations. The initial age range was 55-75 years (mean, 64 years). Read More

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November 2018
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Imaging of Cancer Immunotherapy: Current Approaches and Future Directions.

Radiology 2018 Nov 20:181349. Epub 2018 Nov 20.

From the Departments of Radiology (M.N., H.H.), Medical Oncology (F.S.H.), and Medicine (F.S.H.), Brigham and Women's Hospital and Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215.

Cancer immunotherapy using immune-checkpoint inhibitors has emerged as an effective treatment option for a variety of advanced cancers in the past decade. Because of the distinct mechanisms of immunotherapy that activate the host immunity to treat cancers, unconventional immune-related phenomena are encountered in terms of tumor response and progression, as well as drug toxicity. Imaging plays an important role in objectively characterizing immune-related tumor responses and progression and in detecting and monitoring immune-related adverse events. Read More

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November 2018
7 Reads

Virtual Hepatic Venous Pressure Gradient with CT Angiography (CHESS 1601): A Prospective Multicenter Study for the Noninvasive Diagnosis of Portal Hypertension.

Radiology 2018 Nov 20:180425. Epub 2018 Nov 20.

From the Chinese Portal Hypertension Diagnosis and Monitoring Study Group (CHESS), CHESS Frontier Center, Lanzhou University, Lanzhou, China (Xiaolong Qi); Hepatic Hemodynamic Laboratory, Institute of Hepatology, Nanfang Hospital, Southern Medical University, Guangzhou, China (Xiaolong Qi, Y.L., Chuan Liu, Y.X., J. Hui, Z. Liu, J. Hou); Department of Radiology (W.A., Changchun Liu), Department of General Surgery (R.Q., Z. Li), and Center for Therapeutic Research of Hepatocarcinoma (Y.Y.), 302 Hospital of PLA, Beijing, China; Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing, China (F.L., L.W.); Department of Gastroenterology, General Hospital of Shenyang Military Area, Shenyang, China (Xingshun Qi); Department of Hepatobiliary Surgery (B.P.) and Organ Transplant Center (X.H.), The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Department of Gastroenterology and Hepatology, Beijing You'an Hospital, Capital Medical University, Beijing, China (H.D.); Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Hepatobiliary Surgery, The Third People's Hospital of Shenzhen, Shenzhen, China (Z. Li).

Purpose To develop and validate a computational model for estimating hepatic venous pressure gradient (HVPG) based on CT angiographic images, termed virtual HVPG, to enable the noninvasive diagnosis of portal hypertension in patients with cirrhosis. Materials and Methods In this prospective multicenter diagnostic trial (ClinicalTrials.gov identifier: NCT02842697), 102 consecutive eligible participants (mean age, 47 years [range, 21-75 years]; 68 men with a mean age of 44 years [range, 21-73 years] and 34 women with a mean age of 52 years [range, 24-75 years]) were recruited from three high-volume liver centers between August 2016 and April 2017. Read More

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http://dx.doi.org/10.1148/radiol.2018180425DOI Listing
November 2018
7 Reads

Strain Measures Predict Outcome after ST-Segment-Elevation Myocardial Infarction: Now What?

Radiology 2018 Nov 20:182319. Epub 2018 Nov 20.

From the Departments of Medicine and Radiology and the Cardiovascular Imaging Center, University of Virginia Health System, Lee Street, Box 800170, Charlottesville, VA 22908.

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http://dx.doi.org/10.1148/radiol.2018182319DOI Listing
November 2018

Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System.

Radiology 2018 Nov 20:181371. Epub 2018 Nov 20.

From the Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB Nijmegen, Geert Grooteplein 10, 6525 GA, Post 766, Nijmegen, the Netherlands (A.R.R., I.S., R.M.M.); Department of Radiology & Imaging Sciences, Emory University, Atlanta, Ga (E.K.); ScreenPoint Medical BV, Nijmegen, the Netherlands (J.J.M.); Lynn Women's Health & Wellness Institute, Boca Raton Regional Hospital, Boca Raton, Fla (K.S.); Referenzzentrum Mammographie Munich, Brustdiagnostik München and FFB, Munich, Germany (S.H.H.); and Dutch Expert Centre for Screening, Nijmegen, the Netherlands (I.S.).

Purpose To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods An enriched retrospective, fully crossed, multireader, multicase, HIPAA-compliant study was performed. Screening digital mammographic examinations from 240 women (median age, 62 years; range, 39-89 years) performed between 2013 and 2017 were included. Read More

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November 2018
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Virtual Hepatic Venous Pressure Gradient with CT: Ready for Prime Time?

Radiology 2018 Nov 20:182351. Epub 2018 Nov 20.

From the Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115.

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http://dx.doi.org/10.1148/radiol.2018182351DOI Listing
November 2018

Circumferential Strain Predicts Major Adverse Cardiovascular Events Following an Acute ST-Segment-Elevation Myocardial Infarction.

Radiology 2018 Nov 20:181253. Epub 2018 Nov 20.

From the British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences (K.M., D.C., J.C., C.M., M.C.P., C.B.), and Robertson Centre for Biostatistics (C.E.H.), University of Glasgow, 126 University Place, Glasgow G12 8TA, Scotland; West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, Scotland (K.M., D.C., A.M., K.G.O., H.E., M.L., M.M., S.H., M.C.P., S.W., A.D., C.B.); Department of Clinical Physics, NHS Greater Glasgow and Clyde, Glasgow, Scotland (C.M.); Department of MR R&D Collaborations, Siemens Healthcare, Atlanta, Ga (X.Z.); and Department of Biomedical Engineering, University of Virginia, Charlottesville, Va (F.H.E.).

Purpose To investigate the prognostic value of circumferential left ventricular (LV) strain measured by using cardiac MRI for prediction of major adverse cardiac events (MACE) following an acute ST-segment-elevation myocardial infarction (STEMI). Materials and Methods Participants with acute STEMI were prospectively enrolled from May 11, 2011, to November 22, 2012. Cardiac MRI was performed at 1. Read More

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http://dx.doi.org/10.1148/radiol.2018181253DOI Listing
November 2018

Diagnosis of Knee Meniscal Injuries by Using Three-dimensional MRI: A Systematic Review and Meta-Analysis of Diagnostic Performance.

Radiology 2018 Nov 20:181212. Epub 2018 Nov 20.

From the Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University, 601 N Caroline St, JHOC 4240, Baltimore, Md, 21287 (D.S., J.F., S.J.F., J.E., S.D.); Department of Radiology, University of Wisconsin, Clinical Science Center, Madison, Wis (R.K.); Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, Mass (A.G., F.W.R.); and Department of Radiology, University of Erlangen-Nuremberg, Erlangen, Germany (F.W.R.).

Purpose To investigate the diagnostic performance of three-dimensional (3D) MRI for depicting meniscal injuries of the knee by using surgery as the standard of reference. Materials and Methods A literature search was performed to identify original studies published between 1985 and 2017. Summary receiver operating characteristic curve and sensitivity analyses were performed to compare the diagnostic performance of 3D versus two-dimensional (2D) MRI for the assessment of knee meniscal injuries and to evaluate the impact of relevant covariates on the diagnostic performance for assessment of knee meniscal injuries. Read More

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http://dx.doi.org/10.1148/radiol.2018181212DOI Listing
November 2018
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Three-dimensional Distribution of Muscle and Adipose Tissue of the Thigh at CT: Association with Acute Hip Fracture.

Radiology 2018 Nov 20:181112. Epub 2018 Nov 20.

From the Institute of Medical Physics (A.M., O.M., K.E.) and Department of Medicine 3 (K.E.), University Hospital, Friedrich-Alexander University Erlangen-Nuremberg, Henkestr 91, Erlangen 91052, Germany; and Department of Radiology, AP-HP, Hôpital Lariboisière and Université Paris Diderot, Paris, France (V.B., P.P., J.D.L.).

Purpose To evaluate determinants of hip fracture by assessing soft-tissue composition of the upper thigh at CT. Materials and Methods In this retrospective analysis of prospectively collected data, CT studies in 55 female control participants (mean age, 73.1 years ± 9. Read More

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November 2018
6 Reads

Dynamic MRI of a Large Fetal Cardiac Mass.

Radiology 2018 Nov 20:182025. Epub 2018 Nov 20.

From the Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Vaud, Switzerland (C.W.R.); Department of Medical Biophysics, University of Toronto, Toronto, Canada (C.K.M.); and Division of Translational Medicine, the Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, 686 Bay St, Toronto, ON, Canada M5G 0A4 (C.K.M.).

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http://dx.doi.org/10.1148/radiol.2018182025DOI Listing
November 2018
3 Reads

Strategically Guiding Research through Careful Consideration of the Path to Impact.

Radiology 2018 Nov 20:181475. Epub 2018 Nov 20.

From the Department of Radiology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02115 (D.B.); and Teaching and Learning Laboratory (R.M.) and Institute for Medical Engineering and Science (M.L.G.), Massachusetts Institute of Technology, Cambridge, Mass.

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http://dx.doi.org/10.1148/radiol.2018181475DOI Listing
November 2018
2 Reads

Case 260: Endobronchial Posttransplantation Lymphoproliferative Disease.

Radiology 2018 Dec;289(3):876-880

From the Department of Radiology, Duke University Medical Center, DUMC Box 3808, Durham, NC 27710.

History A 31-year-old woman with a history of bilateral orthotopic lung transplantation performed 10 months earlier for cystic fibrosis presented for a routine follow-up appointment, with her chief symptom being a cough. The cough started approximately 1 month prior to this appointment and was minimally productive of clear to yellow phlegm. In addition to her cough, she reported increased sinus congestion and a sensation of "something in her upper chest. Read More

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http://pubs.rsna.org/doi/10.1148/radiol.2018161689
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December 2018
4 Reads

Case 264.

Radiology 2018 Dec;289(3):873-875

From the Department of Radiology, CHU Toulouse-Purpan, Place du docteur Baylac, 31059 Toulouse Cedex 9, France.

History A 28-year-old woman presented to the emergency department with painful swelling of the third finger on her right hand, which developed quickly. She had no relevant medical or surgical history. Her pain was worse at night, with stiffness decreasing during the morning. Read More

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http://dx.doi.org/10.1148/radiol.2018162093DOI Listing
December 2018
1 Read

Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs.

Radiology 2018 Nov 13:181422. Epub 2018 Nov 13.

From the Departments of Computer Science (J.A.D., C.R.), Biomedical Data Science (D.Y., D.L.R.), and Radiology (C.P.L., D.L.R., M.P.L.), Stanford University, 300 Pasteur Dr, Stanford, CA 94305.

Purpose To assess the ability of convolutional neural networks (CNNs) to enable high-performance automated binary classification of chest radiographs. Materials and Methods In a retrospective study, 216 431 frontal chest radiographs obtained between 1998 and 2012 were procured, along with associated text reports and a prospective label from the attending radiologist. This data set was used to train CNNs to classify chest radiographs as normal or abnormal before evaluation on a held-out set of 533 images hand-labeled by expert radiologists. Read More

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http://dx.doi.org/10.1148/radiol.2018181422DOI Listing
November 2018
6 Reads

Native T1 and Extracellular Volume Measurements by Cardiac MRI in Healthy Adults: A Meta-Analysis.

Radiology 2018 Nov 13:180226. Epub 2018 Nov 13.

From the Departments of Medicine (M.G., C.M.K., M.S.), Radiology (C.M.K., M.S.), and Biomedical Engineering (M.S.) and Cardiovascular Imaging Center (M.G., C.M.K., M.S.), University of Virginia Health System, 1215 Lee St, Box 800158, Charlottesville, VA 22908.

Purpose To summarize the literature by performing a systematic review and pooled analysis of the data, to understand the extent of variability among studies of native T1 and extracellular volume (ECV) measurements, and to identify covariates that account for heterogeneity between studies. Materials and Methods PubMed, Web of Science, and Cochrane Central were searched for native T1 and ECV measurements of the left ventricle in health adult study participants. The search terms used were "T1 mapping heart," "Native T1 heart," and "ECV heart. Read More

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http://dx.doi.org/10.1148/radiol.2018180226DOI Listing
November 2018
5 Reads

Long-term Excretion of Gadolinium-based Contrast Agents: Linear versus Macrocyclic Agents in an Experimental Rat Model.

Radiology 2018 Nov 13:180135. Epub 2018 Nov 13.

From the Department of MR and CT Contrast Media Research, Bayer, Muellerstr 178, Berlin 13353, Germany (G.J., T.F., J.L., H.P.); Institute of Physiology, Charité, Berlin, Germany (J.B.); and Forschungszentrum Juelich, Juelich, Germany (V.N.).

Purpose To investigate the long-term course of MRI signal intensity (SI) changes and the presence of gadolinium in the rat brain during a 1-year period after multiple administrations of gadolinium-based contrast agents (GBCAs). Materials and Methods Rats received a linear GBCA (gadodiamide, gadopentetate dimeglumine, gadobenate dimeglumine), a macrocyclic GBCA (gadobutrol, gadoterate meglumine, gadoteridol), or saline. Animals received eight injections over 2 weeks (1. Read More

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http://dx.doi.org/10.1148/radiol.2018180135DOI Listing
November 2018
3 Reads

Fluoroscopy and Cone-Beam CT-guided Fixation by Internal Cemented Screw for Pathologic Pelvic Fractures.

Radiology 2018 Nov 13:181105. Epub 2018 Nov 13.

From the Interventional Radiology Unit, Imaging Department, Gustave Roussy Cancer Campus, 114 rue Edouard Vaillant, Villejuif 94805, France (C.R., L.T., S.Y., R.S.S., A.H., C.T., G.G., T.d.B., F.D.); and Université Paris-Sud, Le Kremlin Bicêtre, France (L.T., T.d.B., F.D.).

Purpose To evaluate the safety and efficacy of palliative treatment of patients with pathologic pelvic by using fluoroscopy and cone-beam CT needle guidance software to perform percutaneous fixation by internal cemented screw (FICS). Materials and Methods This single-center study involved retrospective analysis of 100 consecutive patients with cancer with pathologic pelvic fractures managed with percutaneous FICS. Image guidance was performed with fluoroscopy and cone-beam CT needle guidance software. Read More

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http://dx.doi.org/10.1148/radiol.2018181105DOI Listing
November 2018

Deep Learning for Triage of Chest Radiographs: Should Every Institution Train Its Own System?

Radiology 2018 Nov 13:182318. Epub 2018 Nov 13.

From the Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands.

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http://dx.doi.org/10.1148/radiol.2018182318DOI Listing
November 2018