Nuklearmedizin 2005; 44(04): 149-155
DOI: 10.1055/s-0038-1625102
Original Articles
Schattauer GmbH

Anatomical accuracy of lesion localization

Retrospective interactive rigid image registration between 18F-FDG-PET and X-ray CTGenauigkeit der Lokalisierungmaligner Herde mittels retrospektiver, interaktiver starrer Bildfusion von FDG-PET und CT
A. Nömayr
1   Clinic of Nuclear Medicine
,
W. Römer
1   Clinic of Nuclear Medicine
,
T. Hothorn
2   Department of Medical Informatics, Biometry and Epidemiology
,
A. Pfahlberg
2   Department of Medical Informatics, Biometry and Epidemiology
,
J. Hornegger
3   Department of Computer Science, Chair for Pattern Recognition
,
W. Bautz
4   Institute of Diagnostic Radiology, University of Erlangen/Nürnberg, Erlangen, Germany
,
T. Kuwert
1   Clinic of Nuclear Medicine
› Author Affiliations
Further Information

Publication History

Received: 23 December 2004

in revised form: 17 February 2005

Publication Date:
11 January 2018 (online)

Summary

The aim of this study was to evaluate the anatomical accuracy and reproducibility of retrospective interactive rigid image registration (RIR) between routinely archived X-ray computer tomography (CT) and positron emission tomography performed with 18F-deoxyglucose (FDG-PET) in oncological patients. Methods: Two observers registered PET and CT data obtained in 37 patients using a commercially available image fusion tool. RIR was performed separately for the thorax and the abdomen using physiological FDG uptake in several organs as a reference. One observer performed the procedure twice (O1a and O1b), another person once (O2). For 94 malignant lesions, clearly visible in CT and PET, the signed and absolute distances between their representation on PET and CT were measured in X-, Y-, and Z-direction with reference to a coordinate system centered in the CT representation of each lesion (X-, Y-, Z-distances). Results: The mean differences of the signed and absolute distances between O1a, O1b, and O2 did not exceed 3 mm in any dimension. The absolute X-, Y-, and Z-distances ranged between 0.57 ± 0.58 cm for O1a (X-direction) and 1.12 ± 1.28 cm for O2 (Z-direction). When averaging the absolute distances measured by O1a, O1b, and O2, the percentage of lesions misregistered by less than 1.5 cm was 91 % for the X-, 88 % for the Y-, and 77 % for the Z-direction. The larger error of fusion determined for the remaining lesions was caused by non-rigid body transformations due to differences in breathing, arm position, or bowel movements between the two examinations. Mixed effects analysis of the signed and absolute X-, Y-, and Z-distances disclosed a significantly greater misalignment in the thorax than in the abdomen as well as axially than transaxially. Conclusion: The anatomical inaccuracy of RIR can be expected to be <1.5 cm for the majority of neoplastic foci. Errors of alignment are bigger in the thorax and in Z-direction, due to non-rigid body transformations caused, e.g., by breathing.

Zusammenfassung

Ziel: Evaluierung der anatomischen Genauigkeit und Reproduzierbarkeit der Lokalisierung von malignen Herden mittels der retrospektiven, interaktiven, starren Bildfusion von FDG-PET und CT. Methodik: Bei 37 onkologischen Patienten wurden innerhalb von 30 Tagen eine Ganzkörper- FDG-PET und ein Spiral-CT gemäß klinischen Standardprotokollen aufgenommen. Zwei Untersucher fusionierten unabhängig voneinander PET und CT. Die Fusion erfolgte für Thorax und Abdomen getrennt. Hauptorientierungsmarken waren Zwerchfell, Leber, Harnblase, Mediastinum und Lungengrenzen. 94 PET- und CT-positive maligne Läsionen wurden evaluiert. Die Abweichung zwischen der Darstellung in PET und CT wurde in den 3 Ebenen ermittelt. Wir bestimmten den absoluten Betrag der Abweichung sowie die vektorielle Richtung in der X-, Y- und Z-Achse durch das Setzen eines Vorzeichen. Ergebnisse: Die absoluten Werte für die Fehlregistrierung der Läsionen reichten von 0,57 cm ± 0,58 (X-Richtung) bis 1,12 cm ± 1,28 (Z-Richtung). Die Ergebnisse beider Untersucher unterschieden sich um maximal 3 mm in allen Ebenen für die vektorielle oder absolute Fehlregistrierung der Läsion im fusionierten Bild. Die Inter- und Intraobservervariabilität war niedrig und statistisch nicht signifikant. Eine Fehlregistrierung von weniger als 1,5 cm wurde bei 91% (X-Richtung), 88% (Y-Richtung) und 77% (Z-Richtung) der Läsionen erreicht. Größere Abweichungen wurden v. a. durch unterschiedliche Atemlage und Armposition in PET und CT oder durch Peristaltik-bedingte Lageveränderungen von Magen und Darm zwischen den Untersuchungen verursacht. Die statistische Analyse ergab eine signifikant höhere Fehlregistrierung im Thorax als im Abdomen sowie eine höhere Abweichung in Z-Richtung (kranio-kaudal) als in der X/Y-Ebene. Schlussfolgerung: Der Registrierungsfehler bei der retrospektiven, interaktiven Fusion von PET- und CT beträgt bei den meisten neoplastischen Läsionen <1,5 cm. Bedingt durch die Atmung ist der Registrierungsfehler im Thorax größer als abdominell sowie ausgeprägter in Z-Richtung als in der axialen Bildebene.

 
  • References

  • 1 Audette MA, Ferrie FP, Peters TM. An algorithmic overview of surface registration techniques for medical imaging. Med Image Anal 2000; 4: 201-17.
  • 2 Bates M, Sakar D. lme4: Linear mixed-effects models using S4 classes. R package version 0.6–7 2004 http://CRAN.R-project.org.
  • 3 Buell U, Wieres FJ, Schneider W. et al. 18FDG-PET in 733 consecutive patients with or without sideby- side CT evaluation: Analysis of 921 lesions. Nuklearmedizin 2004; 43: 210-6.
  • 4 Cai J, Chu JC, Recine D. et al. CT and PET lung image registration and fusion in radiotherapy treatment planning using the chamfer-matching method. Int J Radiat Oncol Biol Phys 1999; 43: 883-91.
  • 5 Cohade C, Osman M, Marshall LN. et al. PET-CT: accuracy of PET and CT spatial registration of lung lesions. Eur J Nucl Med Mol Imaging 2003; 30: 721-6.
  • 6 D‘Amico TA, Wong TZ, Harpole DH. et al. Impact of computed tomography-positron emission tomography fusion in staging patients with thoracic malignancies. Ann Thorac Surg 2002; 74: 160-3.
  • 7 Dietlein M, Weber W, Schwaiger M. et al. 18F-Fluorodeoxyglucose positron emission tomography in restaging of colorectal cancer. Nuklearmedizin 2003; 42: 145-56.
  • 8 Dresel S, Schwenzer K, Brinkbaumer K. et al. 18F-FDG imaging of head and neck tumors: comparison of hybrid PET, dedicated PET and CT. Nuklearmedizin 2001; 40: 172-8.
  • 9 Faulhaber P, Nelson A, Mehta L. et al. The fusion of anatomic and physiologic tomographic images to enhance accurate interpretation. Clin Positron Imaging 2000; 3: 178.
  • 10 Goerres GW, Burger C, Schwitter MR. et al. PET/ CT of the abdomen: optimizing the patient breathing pattern. Eur Radiol 2003; 13: 734-9.
  • 11 Goerres GW, Kamel E, Heidelberg TN. et al. PETCT image co-registration in the thorax: influence of respiration. Eur J Nucl Med Mol Imaging 2002; 29: 351-60.
  • 12 Herzog HTL, Hocke C, Pietrzyk U. et al. NEMA NU2–2001 guided performance evaluation of four Siemens ECAT PET-Scanners. IEEE Trans Nucl Sci 2004; 51: 2662-9.
  • 13 Hosten N, Kreissig R, Puls R. et al. Fusion of CT and PET data: methods and clinical relevance for planning laser-induced thermotherapy of liver metastases. Rofo Fortschr Geb Rontgenstr Neuen Bildgeb Verfahr 2000; 172: 630-5.
  • 14 Inagaki H, Kato T, Tadokoro M. et al. Interactive fusion of three-dimensional images of upper abdominal CT and FDG PET with no body surface markers. Radiat Med 1999; 17: 155-63.
  • 15 Jager PL, Slart RH, Corstens F. et al. PET-CT: a matter of opinion?. Eur J Nucl Med Mol Imaging 2003; 30: 470-1.
  • 16 Kawaharada Y, Itou A. Registration of chest PET and CT images-fusion technique using the PET/Tr image by the respiration compensation. Kaku Igaku 2003; 40: 1-9.
  • 17 Löffler M, Weckesser M, Franzius C. et al. Malignant melanoma and 18F-FDG-PET: Should the whole body scan include the legs?. Nuklearmedizin 2003; 42: 167-72.
  • 18 Magnani P, Carretta A, Rizzo G. et al. FDG/PET and spiral CT image fusion for medistinal lymph node assessment of non-small cell lung cancer patients. J Cardiovasc Surg (Torino) 1999; 40: 741-8.
  • 19 Mattes D, Haynor DR, Vesselle H. et al. PET-CT image registration in the chest using free-form deformations. IEEE Trans Med Imaging 2003; 22: 120-8.
  • 20 Nakamoto Y, Tatsumi M, Cohade C. et al. Accuracy of image fusion of normal upper abdominal organs visualized with PET/CT. Eur J Nucl Med Mol Imaging 2003; 30: 597-602.
  • 21 Nowak B, Di Martino E, Jänicke S. et al. Diagnostic evaluation of malignant head and neck cancer by 18F-FDG PET compared to CT/MRI. Nuklearmedizin 1999; 38: 312-8.
  • 22 Pinheiro JC, Bates M. Mixed-Effects Models in S and S-PLUS. New York: Springer; 2000
  • 23 Reinartz P, Schneider WF-J, Schur A. et al. Sideby- side reading of PET and CT scans in oncology: which patients might profit from integrated PET/ CT?. Eur J Nucl Med Mol Imaging 2004; 31: 1456-61.
  • 24 Reske SN, Kotzerke J. FDG-PET for clinical use. Results of the 3rd German Interdisciplinary Consensus Conference, „Onko-PET III“, 21 July and 19 September 2000. Eur J Nucl Med 2001; 28: 1707-23.
  • 25 Römer W, Chung M, Chan A. et al. Single-detector helical CT in PET-CT: assessment of image quality. AJRAm J Roentgenol 2004; 182: 1571-7.
  • 26 Römer WFE, Pavel M, Pfahlberg A. et al. Attenuation correction of SPECT images based on separately performed CT. Nuklearmedizin 2005; 44: 20-8.
  • 27 Rosa F, Meimarakis G, Stahl A. et al. Colorectal cancer patients before resection of hepatic metastases. Impact of 18F-FDG PET on detecting extrahepatic disease. Nuklearmedizin 2004; 43: 135-40.
  • 28 Schillaci O, Simonetti G. Fusion imaging in nuclear medicine--applications of dual-modality systems in oncology. Cancer Biother Radiopharm 2004; 19: 1-10.
  • 29 Sethian J. Level Set Methods, Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision, and Materials Science. In: C. U. Press (ed). Cambridge Monograph on Applied and Computational Mathematics. Cambridge: 1996
  • 30 Slomka PJ. Software approach to merging molecular with anatomic information. J Nucl Med 2004; 45 (Suppl. 01) 36S-45.
  • 31 Slomka PJ, Dey D, Przetak C. et al. Automated 3-dimensional registration of stand-alone 18F-FDG whole-body PET with CT. J Nucl Med 2003; 44: 1156-67.
  • 32 Somer EJ, Marsden PK, Benatar NA. et al. PETMR image fusion in soft tissue sarcoma: accuracy, reliability and practicability of interactive pointbased and automated mutual information techniques. Eur J Nucl Med Mol Imaging 2003; 30: 54-62.
  • 33 Team RDC. A language and environment for statistical computing. Vienna, Austria: R Foundation for statistical Computing; 2004. www.R-project.org
  • 34 Weckesser M, Schober O. PET in oncology: standardization and specificity. Nuklearmedizin 1999; 38: 3-5.
  • 35 Wolf G, Nicoletti R, Schultes G. et al. Preoperative image fusion of fluoro-2-deoxy-D-glucose-positron emission tomography and computed tomography data sets in oral maxillofacial carcinoma: potential clinical value. J Comput Assist Tomogr 2003; 27: 889-95.
  • 36 Yu JN, Fahey FH, Gage HD. et al. Intermodality, retrospective image registration in the thorax. J Nucl Med 1995; 36: 2333-8.
  • 37 Zimny M, Wildberger JE, Cremerius U. et al. Combined image interpretation of computed tomography and hybrid PET in head and neck cancer. Nuklearmedizin 2002; 41: 14-21.