Estonian
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
American Journal of Roentgenology 2011-Jun

Decreased detection of hypovascular liver tumors with MDCT in obese patients: a phantom study.

Ainult registreeritud kasutajad saavad artikleid tõlkida
Logi sisse
Link salvestatakse lõikelauale
Sebastian T Schindera
Jaled Charimo Torrente
Thomas D Ruder
Hanno Hoppe
Daniele Marin
Rendon C Nelson
Zsolt Szucs-Farkas

Märksõnad

Abstraktne

OBJECTIVE

The purpose of this article is to assess the impact of large patient size on the detection of hypovascular liver tumors with MDCT and the effect of a noise filter on image quality and lesion detection in obese patients.

METHODS

A liver phantom with 45 hypovascular tumors (diameters of 5, 10, and 15 mm) was placed into two water containers mimicking intermediate and large patients. The containers were scanned with a 64-MDCT scanner. The CT dataset from the large phantom was postprocessed using a noise filter. The image noise was measured and the contrast-to-noise ratio (CNR) of the tumors was calculated. Tumor detection was independently performed by three radiologists in a blinded fashion.

RESULTS

The application of the noise filter in the large phantom yielded a reduction of image noise by 42% (p < 0.0001). The CNR values of the tumors in the nonfiltered and filtered large phantom were lower than that in the intermediate phantom (p < 0.05). In the non-filtered and filtered large phantom, 25% and 19% fewer tumors, respectively, were detected on average compared with the intermediate phantom (p < 0.01).

CONCLUSIONS

The risk of missing hypovascular liver tumors with CT is substantially increased in large patients. A noise filter improves image quality in obese patients.

Liitu meie
facebooki lehega

Kõige täiuslikum ravimtaimede andmebaas, mida toetab teadus

  • Töötab 55 keeles
  • Taimsed ravimid, mida toetab teadus
  • Maitsetaimede äratundmine pildi järgi
  • Interaktiivne GPS-kaart - märgistage ürdid asukohas (varsti)
  • Lugege oma otsinguga seotud teaduspublikatsioone
  • Otsige ravimtaimi nende mõju järgi
  • Korraldage oma huvisid ja hoidke end kursis uudisteuuringute, kliiniliste uuringute ja patentidega

Sisestage sümptom või haigus ja lugege ravimtaimede kohta, mis võivad aidata, tippige ürdi ja vaadake haigusi ja sümptomeid, mille vastu seda kasutatakse.
* Kogu teave põhineb avaldatud teaduslikel uuringutel

Google Play badgeApp Store badge