Strahlentherapie und Onkologie

, Volume 190, Issue 6, pp 555–562 | Cite as

Influence of experience and qualification on PET-based target volume delineation

When there is no expert—ask your colleague
  • C. Doll
  • V. Duncker-Rohr
  • G. Rücker
  • M. Mix
  • M. MacManus
  • D. De Ruysscher
  • W. Vogel
  • J. G. Eriksen
  • W. Oyen
  • A.-L. Grosu
  • W. Weber
  • U. Nestle
Original article

Abstract

Background and purpose

The integration of positron emission tomography (PET) information for target volume delineation in radiation treatment planning is routine in many centers. In contrast to automatic contouring, research on visual-manual delineation is scarce. The present study investigates the dependency of manual delineation on experience and qualification.

Patients and methods

A total of 44 international interdisciplinary observers each defined a [18F]fluorodeoxyglucose (FDG)-PET based gross tumor volume (GTV) using the same PET/CT scan from a patient with lung cancer. The observers were “experts” (E; n = 3), “experienced interdisciplinary pairs” (EP; 9 teams of radiation oncologist (RO) + nuclear medicine physician (NP)), “single field specialists” (SFS; n = 13), and “students” (S; n = 10). Five automatic delineation methods (AM) were also included. Volume sizes and concordance indices within the groups (pCI) and relative to the experts (eCI) were calculated.

Results

E (pCI = 0.67) and EP (pCI = 0.53) showed a significantly higher agreement within the groups as compared to SFS (pCI = 0.43, p = 0.03, and p = 0.006). In relation to the experts, EP (eCI = 0.55) showed better concordance compared to SFS (eCI = 0.49) or S (eCI = 0.47). The intermethod variability of the AM (pCI = 0.44) was similar to that of SFS and S, showing poorer agreement with the experts (eCI = 0.35).

Conclusion

The results suggest that interdisciplinary cooperation could be beneficial for consistent contouring. Joint delineation by a radiation oncologist and a nuclear medicine physician showed remarkable agreement and better concordance with the experts compared to other specialists. The relevant intermethod variability of the automatic algorithms underlines the need for further standardization and optimization in this field.

Keywords

18F-FDG PET Lung cancer Radiation therapy planning Interobserver variability Visual-manual delineation 

Einfluss von Erfahrung und Qualifikation auf die PET-basierte Zielvolumenkonturierung

Ist kein Experte da – frage deinen Kollegen

Zusammenfassung

Hintergrund

Die Daten aus der Positronenemissionstomographie (PET) werden in vielen Kliniken routinemäßig zur Zielvolumendefinition bei der Bestrahlungsplanung verwendet. Im Gegensatz zur automatischen Konturierung wird die visuell-manuellen Konturierung nur unzureichend beforscht. Die vorliegende Studie untersucht den Einfluss von Erfahrung und Qualifikation auf die manuelle Konturierung.

Material und Methode

Insgesamt 44 internationale interdisziplinäre Untersucher konturierten jeweils ein [18F]Fluordesoxyglukose(FDG)-PET-basiertes makroskopisches Tumorvolumen („gross tumor volume“, GTV) anhand desselben PET-/CT-Scans eines Patienten mit Lungenkarzinom. Die Untersucher waren sog. Experten (E; n = 3), erfahrene interdisziplinäre Zweierteams aus Strahlentherapeut und Nuklearmediziner(EP; n = 9), einzelne Fachärzte des Behandlungsfelds (SFS; n = 13) und Studenten (S; n = 10). Ferner wurden 5 automatische Konturierungsmethoden (AM) ebenfalls angewendet. Die Größe der Volumina und die Konkordanzindizes innerhalb der Gruppen (pCI) und relativ zu den Experten (eCI) wurden berechnet.

Ergebnisse

E (pCI = 0,67) und EP (pCI = 0,53) zeigten eine signifikant höhere Übereinstimmung innerhalb der Gruppen im Vergleich zu SFS (pCI = 0,43, p = 0,03 und p = 0,006). Relativ zu E zeigte EP (eCI = 0,55) eine bessere Übereinstimmung verglichen mit SFS (eCI = 0,49) oder S (eCI = 0,47). Die Intermethodenvariabilität von AM (pCI = 0,44) war ähnlich der von SFS und S, zeigte aber eine geringere Übereinstimmung mit E (eCI = 0,35).

Schlussfolgerung

Die Ergebnisse legen nahe, dass interdisziplinäre Kooperation für konsistentes Konturieren vorteilhaft sein kann. Eine gemeinsame Konturierung durch einen Strahlentherapeuten und einen Nuklearmediziner zeigte einen beachtlichen Konsens und eine bessere Übereinstimmung mit den Experten im Vergleich zu anderen Fachärzten. Eine relevante Intermethodenvariabilität der automatischen Algorithmen verdeutlicht die Notwendigkeit weiterer Standardisierung und Optimierung auch auf diesem Gebiet.

Schlüsselwörter

18F-FDG PET Lungenkarzinom Bestrahlungsplanung Interobservervariabilität Visuell-manuelle Konturierung 

Notes

Acknowledgments

The authors thank the patient for agreement to use his image data and all participants of this contouring exercise, namely the participants of the ESTRO-EANM and the DEGRO-Akademie teaching courses and the Freiburg colleagues, for allowing us to analyze their contours. We thank ESTRO, EANM, and DEGRO for permitting this kind of research in the context of their teaching courses. We especially thank David Gibon and his team from Aquilab for their helpful collaboration in the transfer and technical evaluation of the contours. We furthermore thank Scott Kaylor from Educase for transmitting the html contour files from FALCON for further evaluation and Christine Verfaille from ESTRO for her help herewith. This work would not have been possible without the assistance of the staff of the Departments of Radiation Oncology and Nuclear Medicine of the University Medical Center Freiburg. This study was supported by the Radiation Oncology Department of the University Medical Center Freiburg.

Compliance with ethical guidelines

Conflict of interest

C. Doll, V. Duncker-Rohr, G. Rücker, M. Mix, M. MacManus, D. De Ruysscher, W. Vogel, J. Grau Eriksen, W. Oyen, A. L. Grosu, W. Weber, and U. Nestle state that there are no conflicts of interest.

Supplementary material

66_2014_644_MOESM1_ESM.pdf (234 kb)
(PDF 235 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • C. Doll
    • 1
  • V. Duncker-Rohr
    • 1
    • 2
  • G. Rücker
    • 3
  • M. Mix
    • 4
  • M. MacManus
    • 5
  • D. De Ruysscher
    • 6
  • W. Vogel
    • 7
  • J. G. Eriksen
    • 8
  • W. Oyen
    • 9
  • A.-L. Grosu
    • 1
  • W. Weber
    • 4
    • 10
  • U. Nestle
    • 1
  1. 1.Radiation Oncology DepartmentUniversity Medical Center FreiburgFreiburg/BreisgauGermany
  2. 2.Radiation Oncology DepartmentOrtenau Clinical Center OffenburgOffenburgGermany
  3. 3.Institute of Medical Biometry und Medical InformaticsUniversity of FreiburgFreiburgGermany
  4. 4.Nuclear Medicine DepartmentUniversity Medical Center FreiburgFreiburgGermany
  5. 5.The Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneAustralia
  6. 6.Department of Radiation OncologyUniversity Hospital Leuven/KU LeuvenLeuvenBelgium
  7. 7.Department of Nuclear Medicine, The Netherlands Cancer InstituteAntoni van Leeuwenhoek HospitalAmsterdamThe Netherlands
  8. 8.Department of OncologyOdense University HospitalOdenseDenmark
  9. 9.Department of Nuclear MedicineRadboud University Nijmegen Medical CenterNijmegenThe Netherlands
  10. 10.Department of Radiology/Molecular Imaging and Therapy ServiceMemorial Sloan-Kettering Cancer CenterNew YorkUSA

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