#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Feasibility of thin-slice abdominal CT in overweight patients using a vendor neutral image-based denoising algorithm: Assessment of image noise, contrast, and quality


Autoři: Akio Tamura aff001;  Manabu Nakayama aff001;  Yoshitaka Ota aff002;  Masayoshi Kamata aff002;  Yasuyuki Hirota aff002;  Misato Sone aff001;  Makoto Hamano aff001;  Ryoichi Tanaka aff003;  Kunihiro Yoshioka aff001
Působiště autorů: Department of Radiology, Iwate Medical University School of Medicine, Morioka, Japan aff001;  Division of Central Radiology, Iwate Medical University Hospital, Morioka, Japan aff002;  Division of Dental Radiology, Department of General Dentistry, Iwate Medical University School of Dentistry, Morioka, Japan aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0226521

Souhrn

The purpose of this study was to investigate whether the novel image-based noise reduction software (NRS) improves image quality, and to assess the feasibility of using this software in combination with hybrid iterative reconstruction (IR) in image quality on thin-slice abdominal CT. In this retrospective study, 54 patients who underwent dynamic liver CT between April and July 2017 and had a body mass index higher than 25 kg/m2 were included. Three image sets of each patient were reconstructed as follows: hybrid IR images with 1-mm slice thickness (group A), hybrid IR images with 5-mm slice thickness (group B), and hybrid IR images with 1-mm slice thickness denoised using NRS (group C). The mean image noise and contrast-to-noise ratio relative to the muscle of the aorta and liver were assessed. Subjective image quality was evaluated by two radiologists for sharpness, noise, contrast, and overall quality using 5-point scales. The mean image noise was significantly lower in group C than in group A (p < 0.01), but no significant difference was observed between groups B and C. The contrast-to-noise ratio was significantly higher in group C than in group A (p < 0.01 and p = 0.01, respectively). Subjective image quality was also significantly higher in group C than in group A (p < 0.01), in terms of noise and overall quality, but not in terms of sharpness and contrast (p = 0.65 and 0.07, respectively). The contrast of images in group C was greater than that in group A, but this difference was not significant. Compared with hybrid IR alone, the novel NRS combined with a hybrid IR could result in significant noise reduction without sacrificing image quality on CT. This combined approach will likely be particularly useful for thin-slice abdominal CT examinations of overweight patients.

Klíčová slova:

Imaging techniques – Computed axial tomography – Aorta – Vendors – Noise reduction – Abdominal muscles – Liver and spleen scan – Infrared radiation


Zdroje

1. Mahesh M. MDCT physics: the basics—Technology, image quality and radiation dose. Philadelphia: Lippincott Williams & Williams; 2012, p. 2009

2. National Comprehensive Cancer Network. Clinical practice guidelines in oncology: hepatobiliary cancer. https://www.nccn.org/professionals/physician_gls/pdf/hepatobiliary.pdf

3. National Comprehensive Cancer Network. Clinical practice guidelines in oncology: pancreatic adenocarcinoma. https://www.nccn.org/professionals/physician_gls/pdf/pancreatic.pdf

4. Zins M, Matos C, Cassinotto C. Pancreatic Adenocarcinoma Staging in the Era of Preoperative Chemotherapy and Radiation Therapy. Radiology. 2018;287:374–390. doi: 10.1148/radiol.2018171670 29668413

5. Sprawls P. AAPM tutorial. CT image detail and noise. Radiographics. 1992;12:1041–6. doi: 10.1148/radiographics.12.5.1529128 1529128

6. Schindera ST, Torrente JC, Ruder TD, Hoppe H, Marin D, Nelson RC, et al. Decreased detection of hypovascular liver tumors with MDCT in obese patients: a phantom study. AJR Am J Roentgenol. 2011;196: W772–W776. doi: 10.2214/AJR.10.5351 21606267

7. Funama Y, Awai K, Miyazaki O, Nakayama Y, Goto T, Omi Y, et al. Improvement of low-contrast detectability in low-dose hepatic multidetector computed tomography using a novel adaptive filter: evaluation with a computer-simulated liver including tumors. Invest Radiol. 2006;41: 1–7. doi: 10.1097/01.rli.0000188026.20172.5d 16355033

8. Christianson O, Winslow J, Frush DP, Samei E. Automated Technique to Measure Noise in Clinical CT Examinations. AJR Am J Roentgenol. 2015;205:W93–9. doi: 10.2214/AJR.14.13613 26102424

9. Volders D, Bols A, Haspeslagh M, Coenegrachts K. Model-based iterative reconstruction and adaptive statistical iterative reconstruction techniques in abdominal CT: comparison of image quality in the detection of colorectal liver metastases. Radiology. 2013;269: 469–474. doi: 10.1148/radiol.13130002 23847252

10. Smith EA, Dillman JR, Goodsitt MM, Christodoulou EG, Keshavarzi N, Strouse PJ. Model-based iterative reconstruction: effect on patient radiation dose and image quality in pediatric body CT. Radiology. 2014;270: 526–534. doi: 10.1148/radiol.13130362 24091359

11. Kataria B, Althén JN, Smedby Ö, Persson A, Sökjer H, Sandborg M. Assessment of image quality in abdominal CT: potential dose reduction with model-based iterative reconstruction. Eur Radiol. 2018;28: 2464–2473. doi: 10.1007/s00330-017-5113-4 29368163

12. Minamishima K, Sugisawa K, Yamada Y, Jinzaki M. Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study. J Appl Clin Med Phys. 2018;19:318–325. doi: 10.1002/acm2.12304 29493077

13. Brennan DD, Zamboni GA, Raptopoulos VD, Kruskal JB. Comprehensive preoperative assessment of pancreatic adenocarcinoma with 64-section volumetric CT. Radiographics. 2007;27: 1653–1666. doi: 10.1148/rg.276075034 18025509

14. Oguro S, Funabiki T, Hosoda K, et al. 64-Slice multidetector computed tomography evaluation of gastrointestinal tract perforation site: detectability of direct findings in upper and lower GI tract. Eur Radiol. 2010;20:1396–403. doi: 10.1007/s00330-009-1670-5 19997849

15. Abdelmoumene A, Chevallier P, Chalaron M, Schneider F, Verdun FR, Frascarolo P, et al. Detection of liver metastases under 2 cm: comparison of different acquisition protocols in four row multidetector-CT (MDCT). Eur Radiol. 2005;15: 1881–1887. doi: 10.1007/s00330-005-2741-x 15868125

16. Soo G, Lau KK, Yik T, Kutschera P. Optimal reconstructed section thickness for the detection of liver lesions with multidetector CT. Clin Radiol. 2010;65:193–197. doi: 10.1016/j.crad.2009.10.009 20152274

17. Boedeker KL, McNitt-Gray MF. Application of the noise power spectrum in modern diagnostic MDCT: part II. Noise power spectra and signal to noise. Phys Med Biol. 2007;52: 4047–4061. doi: 10.1088/0031-9155/52/14/003 17664594

18. Bushberg JT, Seibert JA, Leidholdt EM, et al. The essential physics of medical imaging. 2nd ed. Philadelphia, Lippincott Williams & Wilkins; 2002, PA:369

19. Sagara Y, Hara AK, Pavlicek W, Silva AC, Paden RG, Wu Q. Abdominal CT: comparison of low-dose CT with adaptive statistical iterative reconstruction and routine-dose CT with filtered back projection in 53 patients. AJR Am J Roentgenol. 2010;195: 713–719. doi: 10.2214/AJR.09.2989 20729451

20. Hara AK, Wellnitz CV, Paden RG, Pavlicek W, Sahani DV. Reducing body CT radiation dose: beyond just changing the numbers. AJR Am J Roentgenol. 2013;201: 33–40. doi: 10.2214/AJR.13.10556 23789656

21. Schindera ST, Odedra D, Raza SA, Kim TK, Jang HJ, Szucs-Farkas Z, et al. Iterative reconstruction algorithm for CT: can radiation dose be decreased while low-contrast detectability is preserved? Radiology. 2013;269: 511–518. doi: 10.1148/radiol.13122349 23788715

22. Schindera ST, Odedra D, Mercer D, Thipphavong S, Chou P, Szucs-Farkas Z, et al. Hybrid iterative reconstruction technique for abdominal CT protocols in obese patients: assessment of image quality, radiation dose, and low-contrast detectability in a phantom. AJR Am J Roentgenol. 2014;202: W146–W152. doi: 10.2214/AJR.12.10513 24450696

23. Del Gaizo AJ, Fletcher JG, Yu L, Paden RG, Spencer GC, Leng S, et al. Reducing radiation dose in CT enterography. Radiographics. 2013;33: 1109–1124. doi: 10.1148/rg.334125074 23842974

24. Hara AK, Paden RG, Silva AC, et al. Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. AJR 2009; 193:764–771. doi: 10.2214/AJR.09.2397 19696291

25. Manduca A, Yu L, Trzasko JD, et al. Projection space denoising with bilateral filtering and CT noise modeling for dose reduction in CT. Med Phys 2009; 36:4911–4919. doi: 10.1118/1.3232004 19994500

26. Thibault JB, Sauer KD, Bouman CA, Hsieh J. A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 2007; 34:4526–4544 doi: 10.1118/1.2789499 18072519

27. Singh S, Kalra MK, Hsieh J, Licato PE, Do S, Pien HH, et al. Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology. 2010;257: 373–383. doi: 10.1148/radiol.10092212 20829535

28. Ehman EC, Guimarães LS, Fidler JL, et al. Noise reduction to decrease radiation dose and improve conspicuity of hepatic lesions at contrast-enhanced 80-kV hepatic CT using projection space denoising. AJR Am J Roentgenol. 2012;198:405–11. doi: 10.2214/AJR.11.6987 22268185

29. Marin D, Nelson RC, Schindera ST, Richard S, Youngblood RS, Yoshizumi TT, et al. Low-tube-voltage, high-tube-current multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm—initial clinical experience. Radiology. 2010;254: 145–153. doi: 10.1148/radiol.09090094 20032149

30. Nakaura T, Awai K, Oda S, et al. Low-kilovoltage, high-tube-current MDCT of liver in thin adults: pilot study evaluating radiation dose, image quality, and display settings. AJR Am J Roentgenol. 2011;196:1332–8. doi: 10.2214/AJR.10.5698 21606297


Článok vyšiel v časopise

PLOS One


2019 Číslo 12
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#