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001-es BibID:	BIBFORM065781
Első szerző:	Coucke, Philippe A.
Cím:	Image guided stereotactic treatment with CyberKnife yields surgical precision / P. A. Coucke, N. Withofs, N. Jansen, Zs. Janvary, R. Hustinx
Dátum:	2010
Megjegyzések:	RÉSUMÉ : L'évolution extr©emement rapide en robotique et eninformatique a permis l'avℓenement de techniques telles que leCyberKnife?, capables d'appliquer en radiothérapie des dosesdites ?ablatives? et ceci avec une précision chirurgicale. Ce typede traitement ablatif n'est pas réellement concevable avec destechniques conventionnelles en radiothérapie et des changementsmajeurs de paradigmes ont eu lieu, particuliℓerement dansla méthodologie de définition de la cible et des marges ainsi quedans la maniℓere dont on fractionne le traitement. Gr©ace ℓa ceschangements, on est ℓa m©eme de proposer aux patients des traitementsqui représentent un doublement au niveau de l'efficacitébiologique. Pour obtenir une couverture optimale au niveaude la cible, tout en évitant les structures saines avoisinantes, ilest donc impératif d'obtenir la meilleure définition possible dela cible tant au niveau de la l'extension de la lésion qu'au niveaude son ?contenu?, c'est-ℓa-dire les caractéristiques métaboliqueset fonctionnelles. La révolution technologique en cours dans lemonde de l'imagerie métabolique et fonctionnelle va permettred'utiliser l'information numérisée pour individualiser les traitementset les adapter aux caractéristiques m©emes de la lésionainsi qu'ℓa son évolution au décours du traitement.ENGLISH: SUMMARY : The field of radiation oncology is rapidly evolvingespecially thanks to the tremendous progress in roboticsand computer sciences. One of the consequences is the implementationof a technique like the CyberKnife?. This particularradiation therapy modality allows the use of "ablative"radiation doses, a concept which is not even conceivable withconventional approaches. This has been made possible by majorchanges in the ways target and margins around are defined andthe way radiation therapy is fractionated. The result of thesechanges is for some tumours a doubling of the radiobiologicaleffect of the ionizing irradiation. In order to cover the targetwith the highest possible conformality, without harming surroundinghealthy tissues, optimized definition of the target iskey. It is not only important to get information on the extentof the target with the highest possible resolution, but it is alsoimportant to assess the content i.e. metabolic heterogeneity. Thedevelopments made in the field of diagnostic and functionalradiology and nuclear medicine do allow to take advantage ofthe numerical information to individualize and adapt treatmentprescription, even consider modification throughout thecourse of irradiation.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:	Revue Medical de Liege 65 : Spec. No. (2010), p. 17-22. -
További szerzők:	Withofs, Nadia Jansen, Nicolas Jánváry Zsolt Levente (1977-) (orvos) Hustinx, Roland
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM065767
035-os BibID:	(WoS)000378005000009
Első szerző:	Lovinfosse, Pierre
Cím:	FDG PET/CT texture analysis for predicting the outcome of lung cancer treated by stereotactic body radiation therapy / Pierre Lovinfosse, Zsolt Levente Janvary, Philippe Coucke, Sébastien Jodogne, Claire Bernard, Mathieu Hatt, Dimitris Visvikis, Nicolas Jansen, Bernard Duysinx, Roland Hustinx
Dátum:	2016
ISSN:	1619-7070
Megjegyzések:	Introduction: With 18F-FDG PET/CT, tumor uptake intensityand heterogeneity have been associated with outcome in several cancers. This study aimed at investigating whether 18F-FDG uptake intensity, volume or heterogeneity could predict the outcome in patients with non-small cell lung cancers (NSCLC)treated by stereotactic body radiation therapy (SBRT).Methods: Sixty-three patients with NSCLC treated by SBRTunderwent a 18F-FDG PET/CT before treatment. Maximumand mean standard uptake value (SUVmax and SUVmean),metabolic tumoral volume (MTV), total lesion glycolysis(TLG), as well as 13 global, local and regional textural features were analysed. The predictive value of these parameters,along with clinical features, was assessed using univariate and multivariate analysis for overall survival (OS), disease specific survival (DSS) and disease-free survival (DFS). Cutoff values were obtained using logistic regression analysis,and survivals were compared using Kaplan-Meier analysis.Results: The median follow-up period was 27.1 months for theentire cohort and 32.1 months for the surviving patients. Atthe end of the study, 25 patients had local and/or distant recurrence including 12 who died because of the cancer progression.None of the clinical variables was predictive of the outcome,except age, which was associated with DFS (HR 1.1,P= 0.002). None of the 18F-FDG PET/CT or clinical parameters,except gender, were associated with OS. The univariate analysis showed that only dissimilarity (D) was associated with DSS (HR= 0.822, P=0.037), and that several metabolic measurements were associated with DFS. In multivariate analysis,only dissimilarity was significantly associated with DSS(HR= 0.822, P=0.037) and with DFS (HR= 0.834, P<0.01).Conclusion: The textural feature dissimilarity measured on the baseline 18F-FDG PET/CTappears to be a strong independent predictor of the outcome in patients with NSCLC treated by SBRT. This may help selecting patients who may benefit from closer monitoring and therapeutic optimization.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk 18F-FDG PET/CT Non-small cell lung cancer Stereotactic body radiation therapy Textural analysis Heterogeneity Prognostic factor
Megjelenés:	European Journal Of Nuclear Medicine And Molecular Imaging. - 43 : 8 (2016), p. 1453-1460. -
További szerzők:	Jánváry Zsolt Levente (1977-) (orvos) Coucke, Philippe A. Jodogne, Sébastien Bernard, Claire Hatt, Mathieu Visvikis, Dimitris Jansen, Nicolas Duysinx, Bernard Hustinx, Roland
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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