Quantitative features of liver lesions, lung nodules, and renal stones at multi-detector row CT examinations: Dependency on radiation dose and reconstruction algorithm

Radiology

Volumn 279, Issue 1, 2016, Pages 185-194

  Solomon, Justin ^a   Mileto, Achille ^a   Nelson, Rendon C ^a   Choudhury, Kingshuk Roy ^a   Samei, Ehsan ^a  

^a DUKE UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; COMPUTED TOMOGRAPHY SCANNER; COMPUTER ANALYSIS; FEMALE; HUMAN; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; IMAGING SOFTWARE; LIVER INJURY; LUNG NODULE; MALE; MULTICENTER STUDY (TOPIC); MULTIDETECTOR COMPUTED TOMOGRAPHY; NEPHROLITHIASIS; PRIORITY JOURNAL; PROSPECTIVE STUDY; QUANTITATIVE ANALYSIS; RADIATION DOSE; RETROSPECTIVE STUDY; STONE ANALYSIS; TUMOR VOLUME; ALGORITHM; CLINICAL TRIAL; COMPUTER ASSISTED DIAGNOSIS; LIVER DISEASE; LUNG DISEASE; MIDDLE AGED; MULTICENTER STUDY; RADIOGRAPHY; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; FEMALE; HUMANS; KIDNEY CALCULI; LIVER DISEASES; LUNG DISEASES; MALE; MIDDLE AGED; MULTIDETECTOR COMPUTED TOMOGRAPHY; RADIATION DOSAGE; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RETROSPECTIVE STUDIES;

EID: 84962881129     PISSN: 00338419     EISSN: 15271315     Source Type: Journal    
DOI: 10.1148/radiol.2015150892     Document Type: Article

References (22)

1. Armato S, Goldmacher G, Schwartz L. Quantitative imaging biomarkers alliance (QIBA). Radiological Society of North America. http://qibawiki.rsna.org/index. php?title=Main-Page. Published 2014. Accessed January 30, 2015.
2. Radiological Society of North America. CT Volumetry Technical Committee. CT Tumor Volume Change Profle, Quantitative Imaging Biomarkers Alliance. Oak Brook, Ill: Radiological Society of North America, 2012.
3. Buckler AJ, Mulshine JL, Gottlieb R, Zhao B, Mozley PD, Schwartz L. The use of volumetric CT as an imaging biomarker in lung cancer. Acad Radiol 2010;17(1):100-106.
4. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009;45(2):228-247.
5. Kim HJ, Brown MS, Chong D, et al. Comparison of the quantitative CT imaging bio-markers of idiopathic pulmonary fbrosis at baseline and early change with an interval of 7 months. Acad Radiol 2015;22(1):70-80.
6. Petrick N, Brown DG, Suleiman O, Myers KJ. Imaging as a tumor biomarker in oncology drug trials for lung cancer: the FDA perspective. Clin Pharmacol Ther 2008; 84(4):523-525.
7. Zhang H, Graham CM, Elci O, et al. Locally advanced squamous cell carcinoma of the head and neck: CT texture and histogram analysis allow independent prediction of overall survival in patients treated with induction chemotherapy. Radiology 2013;269 (3):801-809.
8. Thibault JB, Sauer KD, Bouman CA, Hsieh J. A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 2007;34(11):4526-4544.
9. Solomon J, Mileto A, Ramirez Giraldo JC, Samei E. Diagnostic performance of an advanced modeled iterative reconstruction algorithm for low-contrast detectability with a third-generation dual-source multidetec-tor CT scanner: potential for radiation dose reduction in a multireader study. Radiology 2015;275(3):735-745.
10. Pickhardt PJ, Lubner MG, Kim DH, et al. Abdominal CT with model-based iterative reconstruction (MBIR): initial results of a prospective trial comparing ultralow-dose with standard-dose imaging. AJR Am J Roentgenol 2012;199(6):1266-1274.
11. Chen B, Ramirez Giraldo JC, Solomon J, Samei E. Evaluating iterative reconstruction performance in computed tomography. Med Phys 2014;41(12):121913.
12. Beister M, Kolditz D, Kalender WA. Iterative reconstruction methods in X-ray CT. Phys Med 2012;28(2):94-108.
13. Schulz B, Beeres M, Bodelle B, et al. Performance of iterative image reconstruction in CT of the paranasal sinuses: a phantom study. AJNR Am J Neuroradiol 2013;34(5): 1072-1076.
14. Barrett HH, Myers KJ, Hoeschen C, Ku-pinski MA, Little MP. Task-based measures of image quality and their relation to radiation dose and patient risk. Phys Med Biol 2015;60(2):R1-R75.
15. Chen B, Marin D, Richard S, Husarik D, Nelson R, Samei E. Precision of iodine quan-tifcation in hepatic CT: effects of iterative reconstruction with various imaging parameters. AJR Am J Roentgenol 2013;200(5): W475-W482.
16. Chen B, Christianson O, Wilson JM, Samei E. Assessment of volumetric noise and resolution performance for linear and nonlinear CT reconstruction methods. Med Phys 2014;41(7):071909.
17. Chen B, Barnhart H, Richard S, Robins M, Colsher J, Samei E. Volumetric quantifca-tion of lung nodules in CT with iterative reconstruction (ASiR and MBIR). Med Phys 2013;40(11):111902.
18. Hara AK, Paden RG, Silva AC, Kujak JL, Lawder HJ, Pavlicek W. Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. AJR Am J Roentgenol 2009;193(3):764-771.
19. Miéville FA, Gudinchet F, Brunelle F, Bochud FO, Verdun FR. Iterative reconstruction methods in two different MDCT scanners: physical metrics and 4-alternative forced-choice detectability experiments-a phantom approach. Phys Med 2013;29(1):99-110.
20. Tesar L, Shimizu A, Smutek D, Kobatake H, Nawano S. Medical image analysis of 3D CT images based on extension of Haralick texture features. Comput Med Imaging Graph 2008;32(6):513-520.
21. Solomon JB, Ramirez Giraldo JC, Stierstor-fer K, Lin Y, Samei E. Towards virtual clinical trials: a framework for clinically relevant CT simulations [abstr]. In: Radiological Society of North America Scientifc Assembly and Annual Meeting Program. Oak Brook, Ill: Radiological Society of North America, 2013; 413.
22. Solomon J, Samei E. A generic framework to simulate realistic lung, liver and renal pathologies in CT imaging. Phys Med Biol 2014;59(21):6637-6657.