ABSTRACT
Evaluar el algoritmo de segmentación tumoral de la imagen PET semiautomatizada para delinear el volumen tumoral grueso (GTV) en pacientes con cáncer cervical localmente avanzado. Material y métodos. Se evaluó retrospectivamente a 32 pacientes con cáncer cervical localmente avanzado. Se utilizó la delineación GTV basada en imagen PET semiautomatizada, utilizando un algoritmo previamente establecido (GTV2SD) y 2 métodos basados en umbrales fijos (GTV40% y GTV50%). Se calculó GTV2SD, como el píxel con el valor medio más 2 desviaciones estándar de la intensidad del hígado, y GTV40% y GTV50% con el 40% y el 50% de intensidad tumoral máxima (Tmáx), respectivamente. A continuación se compararon los volúmenes derivados con los GTV generados manualmente, utilizando RM (GTVMR). Resultados. El valor medio de GTV2SD, GTV40% y GTV50% fue de 85,3 cc; 16,2 cc y 24,1 cc, respectivamente. Se halló una buena concordancia entre GTV2SD y GTVMR (rho=0,88). GTV40% y GTV50% mostraron una menor correlación con GTVMR (rho=0,68 y rho=0,71, respectivamente). Conclusiones. Este estudio prueba de modo preliminar que la delimitación del volumen tumoral metabólico es posible utilizando las mediciones generadas informáticamente en las imágenes de 18F-FDG PET. La generación de los volúmenes tumorales basados en PET se ve afectada por la elección del nivel de umbral utilizado. El grueso del tumor metabólico calculado utilizando el píxel con el valor medio más 2 desviaciones de la intensidad del hígado (GTV2SD) guarda una mejor correlación con los volúmenes tumorales derivados de RM. El método constituye un enfoque simple y clínicamente aplicable para generar el GTV derivado del PET, para la planificación de la terapia de radiación del cáncer cervical(AU)
Objective. To evaluate a semi-automated PET-image tumor segmentation algorithm for gross tumor volume (GTV) delineation in patients with locally advanced cervical cancer. Material and methods. Thirty-two patients with locally advanced cervical cancer were retrospectively evaluated. Semi-automated PET-image-based GTV delineation was applied using a previous established algorithm (GTV2SD) and 2 fixed threshold-based methods (GTV40% and GTV50%). GTV2SD was determined as the pixel with the mean value plus 2-standard deviation of the liver intensity, and GTV40% and GTV50% with 40% and 50% of the maximum tumor intensity (Tmax), respectively. The derived volumes were then compared with the GTVs generated manually using MR (GTVMR). Results. The mean value of GTV2SD, GTV40% and GTV50% was 85.3cc, 16.2cc and 24.1cc, respectively. Good agreement was noticed between GTV2SD and GTVMR (rho=0.88). GTV40% and GTV50% showed weaker correlation with GTVMR (rho=0.68 and rho=0.71, respectively). Conclusions. This study provides preliminary evidence that metabolic tumor volume delineation is feasible using computer-generated measurements in 18F-FDG PET images. Generation of PET-based tumor volumes is affected by the choice of threshold level used. Metabolic tumor bulk calculated using the pixel with the mean value plus 2-standard deviations of the liver intensity (GTV2SD) correlates better with the MR-derived tumor volumes. The method is a simple and clinically applicable approach to generate PET-derived GTV for radiation therapy planning of cervical cancer(AU)
Subject(s)
Humans , Female , Adult , Middle Aged , Fluorodeoxyglucose F18 , Uterine Cervical Dysplasia/complications , Uterine Cervical Dysplasia , Uterine Cervical Neoplasms , Algorithms , Retrospective Studies , HydronephrosisABSTRACT
OBJECTIVE: To evaluate a semi-automated PET-image tumor segmentation algorithm for gross tumor volume (GTV) delineation in patients with locally advanced cervical cancer. MATERIAL AND METHODS: Thirty-two patients with locally advanced cervical cancer were retrospectively evaluated. Semi-automated PET-image-based GTV delineation was applied using a previous established algorithm (GTV2SD) and 2 fixed threshold-based methods (GTV40% and GTV50%). GTV2SD was determined as the pixel with the mean value plus 2-standard deviation of the liver intensity, and GTV40% and GTV50% with 40% and 50% of the maximum tumor intensity (Tmax), respectively. The derived volumes were then compared with the GTVs generated manually using MR (GTVMR). RESULTS: The mean value of GTV2SD, GTV40% and GTV50% was 85.3cc, 16.2cc and 24.1cc, respectively. Good agreement was noticed between GTV2SD and GTVMR (ρ=0.88). GTV40% and GTV50% showed weaker correlation with GTVMR (ρ=0.68 and ρ=0.71, respectively). CONCLUSIONS: This study provides preliminary evidence that metabolic tumor volume delineation is feasible using computer-generated measurements in (18)F-FDG PET images. Generation of PET-based tumor volumes is affected by the choice of threshold level used. Metabolic tumor bulk calculated using the pixel with the mean value plus 2-standard deviations of the liver intensity (GTV2SD) correlates better with the MR-derived tumor volumes. The method is a simple and clinically applicable approach to generate PET-derived GTV for radiation therapy planning of cervical cancer.
Subject(s)
Algorithms , Fluorodeoxyglucose F18 , Multimodal Imaging , Positron-Emission Tomography , Radiopharmaceuticals , Tumor Burden , Uterine Cervical Neoplasms/diagnosis , Adult , Aged , Female , Humans , Middle Aged , Retrospective StudiesABSTRACT
PURPOSE: To compare a specific decision-making process-the analytic hierarchy process (AHP)-with the traditional informal selection process in the selection of general surgery residents. METHOD: The study focused on 1994 and 1995 applicants for the four positions in the five-year general surgery residency program at the Graduate Hospital in Philadelphia. Three criteria were used: academic performance, personal fit, and surgical appropriateness. The relative importance of each was determined by pairwise comparison. For each hierarchy level, these comparisons were combined into a pairwise comparison matrix, and weights were determined for each criterion and rating category. The rating-category weights for each criterion were scaled so that outstanding received the full criterion weight. Each applicant was interviewed by three committee members and rated with both the AHP system and the traditional 0-10 scoring system. In both cases the rating scores were averaged to create a single score for each applicant. The final ranking list (advocacy ranking) was compiled at a meeting of the entire selection committee, during which each member spoke on behalf of the candidates he or she had interviewed. RESULTS: Significant Spearman correlations were found between the AHP ranking and the traditional ranking in both years (1994: n = 26, r = .63, p = .0005; 1995: n = 25, r = .061, p = .0012). The AHP ranking was also significantly correlated with the advocacy ranking in 1994 (n = 26, r = .43, p = .0273); however, there was no significant correlation found in 1995. In 1994 the traditional ranking significantly correlated with the advocacy ranking (n = 26, r = .40, p = .0423). This was not the case in 1995, suggesting that the results of the interviewing process had minimal influence on the outcome of the selection process that year. CONCLUSION: The findings from this pilot study support the use of the AHP as a viable alternative for the selection of surgical residents. Although the small sample size limits the generalizability of the results, the AHP is a quantitative alternative to the traditional, unwieldy, and subjective selection process. Quantitative assessment and ranking of all aspects of a candidate's attributes and performance allow a program to more closely match a candidate to that particular institution.