CT and (18)F-deoxyglucose (FDG) image fusion for optimization of conformal radiotherapy of lung cancers
To validate a computed tomography (CT) and (18)F-deoxyglucose (FDG) image fusion procedure and to evaluate its usefulness to facilitate target definition and treatment planning in three-dimensional conformal radiation therapy (3D-CRT) for non-small-cell lung cancer. Twelve patients were assessed by...
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Published in | International journal of radiation oncology, biology, physics Vol. 49; no. 5; pp. 1249 - 1257 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.04.2001
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Subjects | |
Online Access | Get full text |
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Summary: | To validate a computed tomography (CT) and (18)F-deoxyglucose (FDG) image fusion procedure and to evaluate its usefulness to facilitate target definition and treatment planning in three-dimensional conformal radiation therapy (3D-CRT) for non-small-cell lung cancer.
Twelve patients were assessed by CT and FDG-coincidence mode dual-head gamma camera (CDET) before radiotherapy. The patients were placed in a similar position during CT and FDG-CDET. Matching was achieved by minimizing the cost function by 3D translation and rotation between four landmarks drawn on the patient's skin. Virtual simulation was performed from image fusion and estimated dose-volume histograms (DVH) were calculated.
Quantitative analysis indicated that the matching error was < 5 mm. Fusion of anatomic and metabolic data corrected staging of lymph nodes (N) for 4 patients and staging of metastases for 1 patient. In these 5 patients, DVH revealed that the lung volume irradiated at 20 Gy (Vl(20)) was decreased by an average of 22.8%, and tumor volume irradiated at the 95% isodose (V(95)) was increased by 22% and 8% for 2 patients, respectively, and was decreased by an average of 59% for 3 patients after fusion. No difference in terms of Vl(20) and V(95) was observed for the other 7 patients.
We have validated CT and FDG-CDET lung image fusion to facilitate determination of lung cancer volumes, which improved the accuracy of 3D-CRT. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0360-3016 |
DOI: | 10.1016/S0360-3016(00)01579-0 |