2196 OBESITY TRIPLES THE RADIATION EXPOSURE OF STONE PROTOCOL CT
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Résumé
You have accessJournal of UrologyImaging/Radiology: Uroradiology II1 Apr 20122196 OBESITY TRIPLES THE RADIATION EXPOSURE OF STONE PROTOCOL CT Zachariah G. Goldsmith, Agnes Wang, Chu Wang, Giao Nguyen, Carolyn Lowry, Gastón M. Astroza, Muhammad W. Iqbal, Michael N. Ferrandino, Leo Ding, Matthew D. Belley, Greta Toncheva, Terry T. Yoshizumi, Glenn M. Preminger, and Michael E. Lipkin Zachariah G. GoldsmithZachariah G. Goldsmith Durham, NC More articles by this author , Agnes WangAgnes Wang Durham, NC More articles by this author , Chu WangChu Wang Durham, NC More articles by this author , Giao NguyenGiao Nguyen Durham, NC More articles by this author , Carolyn LowryCarolyn Lowry Durham, NC More articles by this author , Gastón M. AstrozaGastón M. Astroza Durham, NC More articles by this author , Muhammad W. IqbalMuhammad W. Iqbal Durham, NC More articles by this author , Michael N. FerrandinoMichael N. Ferrandino Durham, NC More articles by this author , Leo DingLeo Ding Durham, NC More articles by this author , Matthew D. BelleyMatthew D. Belley Durham, NC More articles by this author , Greta TonchevaGreta Toncheva Durham, NC More articles by this author , Terry T. YoshizumiTerry T. Yoshizumi Durham, NC More articles by this author , Glenn M. PremingerGlenn M. Preminger Durham, NC More articles by this author , and Michael E. LipkinMichael E. Lipkin Durham, NC More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.2370AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Computed tomography (CT) utilization over the last three decades has exponentially increased. In urology, stone patients constitute a high-risk population for radiation exposure, as CT is frequently employed to diagnose and follow stone formers. Paralleling this growth in CT use is the epidemic of obesity. We theorize that there is a different amount of energy required to penetrate the tissues in an obese compared to a non-obese adult. METHODS A validated, anthropomorphic male phantom (Model 701-D; CIRS, Inc, Norfolk, VA) was scanned on a General Electric Lightspeed 64-slice Volume CT according to our institutional protocol. The obese model consisted of the phantom wrapped in two Custom Fat Layers for Model 701-D, E1397-1 and E1397-2, which have been verified to have the same radiographic tissue density as fat. High sensitivity metal oxide semiconductor field effect transistors (MOSFET) dosimeters (Best Medical, Ottawa, Canada) were placed at 20 organ locations in the phantom and used to measure organ specific radiation doses. The non-obese model has a BMI of 24 kg/m2 while the obese model has a BMI of 30 kg/m2. Three runs of the renal stone protocol CT were performed on each phantom, obese and non-obese. Organ-specific doses were measured and the effective doses were calculated. A paired student's t-test was used for statistical analysis. RESULTS For both models, the bone marrow received the highest dose, with the skin receiving the second highest dose. The mean effective dose for the non-obese model was 3.04 ± 0.34 milli-sieverts (mSv), while the effective dose for the obese model was 9.67 ± 0.44 mSv, P<0.0001. CONCLUSIONS The effective dose of stone protocol CT for obese patients is more than three times the dose for a non-obese patient. To our knowledge, this has not been reported before in the literature. When ordering CTs, the BMI of the patient should also be taken into consideration. The implication of this finding extends beyond the urologic stone population and adds to our understanding of radiation exposure from medical imaging. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e885-e886 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Zachariah G. Goldsmith Durham, NC More articles by this author Agnes Wang Durham, NC More articles by this author Chu Wang Durham, NC More articles by this author Giao Nguyen Durham, NC More articles by this author Carolyn Lowry Durham, NC More articles by this author Gastón M. Astroza Durham, NC More articles by this author Muhammad W. Iqbal Durham, NC More articles by this author Michael N. Ferrandino Durham, NC More articles by this author Leo Ding Durham, NC More articles by this author Matthew D. Belley Durham, NC More articles by this author Greta Toncheva Durham, NC More articles by this author Terry T. Yoshizumi Durham, NC More articles by this author Glenn M. Preminger Durham, NC More articles by this author Michael E. Lipkin Durham, NC More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».