Purpose:
To evaluate the performance of computed tomography (CT) systems of various designs as a source of electron density (ρel) data for treatment planning of radiation therapy.
Material and Methods:
Dependence of CT numbers on relative electron density of tissue-equivalent materials (HU-ρel relationship) was measured for several general-purpose CT systems (single-slice, multislice, wide-bore multislice), for radiotherapy simulators with a single-slice CT and kV CBCT (cone-beam CT) options, as well as for linear accelerators with kV and MV CBCT systems. Electron density phantoms of four sizes were used. Measurement data were compared with the standard HU-ρel relationships predefined in two commercial treatment-planning systems (TPS).
Results:
The HU-ρel relationships obtained with all of the general-purpose CT scanners operating at voltages close to 120 kV were very similar to each other and close to those predefined in TPS. Some dependency of HU values on tube voltage was observed for bone- equivalent materials. For a given tube voltage, differences in results obtained for different phantoms were larger than those obtained for different CT scanners. For radiotherapy simulators and for kV CBCT systems, the information on ρel was much less precise because of poor uniformity of images. For MV CBCT, the results were significantly different than for kV systems due to the differing energy spectrum of the beam.
Conclusion:
The HU-ρel relationships predefined in TPS can be used for general-purpose CT systems operating at voltages close to 120 kV. For nontypical imaging systems (e.g., CBCT), the relationship can be significantly different and, therefore, it should always be measured and carefully analyzed before using CT data for treatment planning.
Ziel:
Vergleich verschiedener Computertomographie-(CT-)Systeme zur Bestimmung der Elektronendichte (ρel) für die Bestrahlungsplanung.
Material und Methodik:
Die Relation des CT-Werts zur Elektronendichte wurde an verschiedenen modernen CT-Scannern („single-slice“, „multislice“, „wide-bore multislice“) ermittelt, für die Therapiesimulatoren mit einem „single-slice“-CT und kV-CBCT-(„cone-beam“-CT-)Optionen sowie für Linearbeschleuniger mit kV- und MV-CBCT-Systemen. Vier unterschiedlich große Phantome zweier Hersteller wurden zur Messung der Elektronendichte benutzt. Die Messdaten wurden mit den Standardumrechnungsformeln zweier marktüblicher Therapieplanungssysteme (TPS) verglichen.
Ergebnisse:
Die HU-ρel-Relationen, die in allen modernen CT-Systemen vorhanden sind, waren untereinander sehr ähnlich, ebenso wie zu den vorgegebenen Relationen in den TPS. Einige Abweichungen der HU-Werte in Abhängigkeit von der Röhrenspannung wurden bei knochenäquivalentem Material beobachtet. Bei vorgegebener Röhrenspannung wurden bei den verschiedenen Phantomen größere Differenzen gemessen als in den verschiedenen CT-Scannern. Weniger exakt waren die Informationen über ρel mit den Therapiesimulatoren und KV-CBCT-Systemen aufgrund der mäßigen Uniformität der Bilder. Die Ergebnisse des MV-CBCT unterschieden sich aufgrund des unterschiedlichen Energiespektrums der Röntgenstrahlen signifikant von denen der kV-Systeme.
Schlussfolgerung:
Die im TPS vorgegebene HU-ρel-Relation kann bei modernen CT-Systemen mit einer Röhrenspannung im Bereich von 120 kV genutzt werden. Signifikant unterschiedlich dagegen ist die Relation bei nichttypischen Bildsystemen (z.B. CBCT). Deshalb sollte bei solchen Systemen immer gemessen und sorgfältig analysiert werden, bevor die CT-Daten für die Therapieplanung herangezogen werden.
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References
Bral S, Vinh-Hung V, Everaert H. The use of molecular imaging to evaluate radiation fields in the adjuvant setting of breast cancer. A feasibility study. Strahlenther Onkol 2008;184:100–4.
Burridge NA, Rowbottom CG, Burt PA. Effect of contrast-enhanced CT scans on heterogeneity corrected dose computations in the lung. J Appl Clin Med Phys 2006;7:1–12.
Constantinou C, Harrington JC, DeWerd LA. An electron density calibration phantom for CT-based treatment planning computers. Med Phys 1992;19:325–37.
Cozzi L, Fogliata A, Buffa F, Bieri S. Dosimetric impact of computed tomography calibration on a commercial treatment planning system for external radiation therapy. Radiother Oncol 1998;48:335–8.
Georg D, Georg P, Hillbrand M, et al. Assessment of improved organ at risk sparing for advanced cervix carcinoma utilizing precision radiotherapy techniques. Strahlenther Onkol 2008;184:586–91.
Goerlitz E, Albers D, Cremers F, Schmidt R. Influence of the CT calibration process on the dose computation in radiotherapy treatment planning. Proceedings of the International Conference on Quality Assurance and New Techniques in Radiation Medicine, Vienna, November 13–15, 2006:226–7.
Guan H, Fang-Fang Y, Kim JH. Accuracy of inhomogeneity correction in photon radiotherapy from CT scans with different settings. Phys Med Biol 2002;47:N223–31.
International Commission on Radiation Units and Measurements. ICRU report 44: tissue substitutes in radiation dosimetry and measurement. Bethesda: ICRU, 1989.
Jessen KA. Application of CT in treatment planning. Proceedings of the College on Medical Physics: Radiation Protection and Imaging Technologies; Trieste, Sep 5–23, 1994.
Kilby W, Sage J, Rabett V. Tolerance levels for quality assurance of electron density values generated from CT in radiotherapy treatment planning. Phys Med Biol 2002;47:1485–92.
Knöös T, Nilsson M, Ahlgren L. A method for conversion of Hounsfield number to electron density and prediction of macroscopic pair production cross section. Radiother Oncol 1986;5:337–45.
Lo T, Yang Y, Schreibmann E, et al. Mapping electron density distribution from planning CT to cone-beam CT (CBCT): a novel strategy for accurate dose calculation based on CBCT. Int J Radiat Oncol Biol Phys 2005;63:S507.
Mijnheer B, Olszewska A, Fiorino C, et al. Quality assurance of treatment planning systems — practical examples for non-IMRT photon beams. ESTRO booklet nr 7. Brussels: ESTRO, 2004.
Morin O, Aubry JF, Aubin M, et al. Physical performance and image optimization of megavoltage cone-beam CT. Med Phys 2009;36:1421–32.
Morin O, Chen J, Aubin M, et al. Dose calculation using megavoltage cone-beam CT. Int J Radiat Oncol Biol Phys 2007;67:1201–10.
Nucletron. Oncentra MasterPlan v1.5 SP1 physics reference manual 192.724ENG-02. Veenendaal: Nucletron, 2006.
Parker RP, Hobday PA, Cassell KJ. The direct use of CT numbers in radiotherapy dosage calculations for inhomogeneous media. Phys Med Biol 1979;24:802–9.
Pech M, Mohnike K, Wieners G, et al. Radiotherapy of liver metastases. Comparison of target volumes and dose-volume histograms employing CT- or MRI-based treatment planning. Strahlenther Onkol 2008;184:256–61.
Qamhiyeh S. A Monte Carlo study of the accuracy of CT-numbers for range calculations in carbon ion therapy. PhD Thesis, Ruperto-Carola University of Heidelberg, 2007.
Seco J, Evans PM. Assessing the effect of electron density in photon dose calculations. Med Phys 2006;33:540–52.
Siewerdsen JH, Jaffray DA. Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. Med Phys 2001;28:220–31.
Sterzing F, Schubert K, Sroka-Perez, et al. Helical tomotherapy. Experiences of the first 150 patients in Heidelberg. Strahlenther Onkol 2008;184:8–14.
Sua Y, Fang-Fang Y. Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning. Int J Radiat Oncol Biol Phys 2006;66:1553–61.
Thomas SJ. Relative electron density calibration of CT scanners for radiotherapy treatment planning. Br J Radiol 1999;72:781–6.
Thomas THM, Devakumar D, Purnima S, et al. The adaptation of megavoltage cone beam CT for use in standard radiotherapy treatment planning. Phys Med Biol 2009;54:2067–77.
Vandecasteele K, De Neve W, De Gersem W. Intensity-modulated arc therapy with simultaneous integrated boost in the treatment of primary irresectable cervical cancer. Treatment planning, quality control, and clinical implementation. Strahlenther Onkol 2009;185:799–807.
Varian Oncology Systems. Cadplan external beam modeling physics, manual. Palo Alto: Varian Oncology Systems, 1998.
Zabel-du Bois A, Ackermann B, Hauswald H, et al. Influence of intravenous contrast agent on dose calculation in 3-D treatment planning for radiosurgery of cerebral arteriovenous malformations. Strahlenther Onkol 2009;185:318–24.
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Skrzyński, W., Zielińska-Dąbrowska, S., Wachowicz, M. et al. Computed Tomography as a Source of Electron Density Information for Radiation Treatment Planning. Strahlenther Onkol 186, 327–333 (2010). https://doi.org/10.1007/s00066-010-2086-5
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DOI: https://doi.org/10.1007/s00066-010-2086-5