[Target volume segmentation of PET images by an iterative method based on threshold value].
OBJECTIVE
An automatic segmentation method is presented for PET images based on an iterative approximation by threshold value that includes the influence of both lesion size and background present during the acquisition.


METHODS
Optimal threshold values that represent a correct segmentation of volumes were determined based on a PET phantom study that contained different sizes spheres and different known radiation environments. These optimal values were normalized to background and adjusted by regression techniques to a two-variable function: lesion volume and signal-to-background ratio (SBR). This adjustment function was used to build an iterative segmentation method and then, based in this mention, a procedure of automatic delineation was proposed. This procedure was validated on phantom images and its viability was confirmed by retrospectively applying it on two oncology patients.


RESULTS
The resulting adjustment function obtained had a linear dependence with the SBR and was inversely proportional and negative with the volume. During the validation of the proposed method, it was found that the volume deviations respect to its real value and CT volume were below 10% and 9%, respectively, except for lesions with a volume below 0.6 ml.


CONCLUSIONS
The automatic segmentation method proposed can be applied in clinical practice to tumor radiotherapy treatment planning in a simple and reliable way with a precision close to the resolution of PET images.
Servicio de Radiofísica y Protección Radiológica, Hospital Universitario Puerta de Hierro-Majadahonda, Majadahonda, Madrid, España. Electronic address: pablo.castro@salud.madrid.org.
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Castro
Servicio de Radiofísica y Radioprotección, Hospital Universitario La Paz, Madrid, España.
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Huerga
Servicio de Oncología Radioterápica, Hospital Universitario La Paz, Madrid, España.
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Glaría
Servicio de Radiofísica y Radioprotección, Hospital Universitario La Paz, Madrid, España.
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Plaza
Servicio de Medicina Nuclear, Hospital Universitario La Paz, Madrid, España.
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Rodado
Servicio de Medicina Nuclear, Hospital Universitario La Paz, Madrid, España.
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Marín
Servicio de Oncología Radioterápica, Hospital Universitario La Paz, Madrid, España.
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Mañas
Servicio de Medicina Nuclear, Hospital Universitario La Paz, Madrid, España.
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Serrada
Servicio de Radiofísica y Protección Radiológica, Hospital Universitario Puerta de Hierro-Majadahonda, Majadahonda, Madrid, España.
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Núñez
D000368:Aged; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging*; D004867:Equipment Design; D005462:Fluorine Radioisotopes / Q000032:analysis; D019788:Fluorodeoxyglucose F18 / Q000032:analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008348:Manikins; D009959:Oropharyngeal Neoplasms / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D000072078:Positron Emission Tomography Computed Tomography / Q000295:instrumentation / Q000379:methods; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals / Q000032:analysis; D012044:Regression Analysis; D012189:Retrospective Studies; D059629:Signal-To-Noise Ratio; D036542:Tomography, Spiral Computed / Q000295:instrumentation / Q000379:methods; D047368:Tumor Burden; D051598:Whole Body Imaging / Q000295:instrumentation
D005462:Fluorine Radioisotopes; D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
Contorneo del volumen tumoral; Iterative method; Método iterativo; PET; Segmentación; Segmentation; Target volume delineation; Thresholding; Umbral