Complexity score-based plan quality control of VMAT / 中华放射肿瘤学杂志

Objective:To explore the difference in the complexity of different treatment planning systems, multi-leaf collimator (MLC) types and treatment sites of volume-modulated arc therapy (VMAT), and propose a complexity score for plan quality control.Methods:Statistical analysis of 12 complexity metrics including Monaco and Eclipse, Agility, Millennium and High-definition MLC, nasopharyngeal, lung and cervical cancer was performed. Spearman correlation coefficient between complexity metrics was calculated. Principal component analysis was conducted to reduce the dimensionality of the original data set to the first two principal components and explain its physical meaning. Complexity score based on the principal components was calculated to establish warning and action thresholds for plan quality control. The correlation between complexity metrics and γ pass rate was analyzed.Results:Except cervical cancer aperture sub-regions metric, other metrics had significant differences between Monaco and Eclipse. Monaco MLC had a more regular field but higher MU, smaller leaf gap, and longer leaf travel distance. High-definition MLC with smaller leaf width significantly added MLC aperture-related metrics. The first two principal components explained over 80% of the total variance of the original dataset, complexity score was weighted average of first two principal components. The distribution of complexity score for different equipment and sites was different. The warning threshold was expressed as the average plus standard deviation, and the action threshold was expressed as the average plus 2 standard deviations. Complexity metrics and complexity scores had small correlation with γ pass rate, showing weak or irrelevant but statistically significant. Conclusions:Different planning systems, MLC types, and treatment site complexity metrics are significantly different. The complexity score is a useful tool for plan quality control.

Weight-for-age standard score distribution and effect on in-hospital mortality: A retrospective analysis in pediatric cardiac surgery.

Objective: To study the distribution of weight for age standard score (Z score) in pediatric cardiac surgery and its effect on in-hospital mortality. Introduction: WHO recommends Standard Score (Z score) to quantify and describe anthropometric data. The distribution of weight for age Z score and its effect on mortality in congenital heart surgery has not been studied. Methods: All patients of younger than 5 years who underwent cardiac surgery from July 2007 to June 2013, under single surgical unit at our institute were enrolled. Z score for weight for age was calculated. Patients were classified according to Z score and mortality across the classes was compared. Discrimination and calibration of the for Z score model was assessed. Improvement in predictability of mortality after addition of Z score to Aristotle Comprehensive Complexity (ACC) score was analyzed. Results: The median Z score was -3.2 (Interquartile range -4.24 to -1.91] with weight (mean±SD) of 8.4 ± 3.38 kg. Overall mortality was 11.5%. 71% and 52.59% of patients had Z score < -2 and < -3 respectively. Lower Z score classes were associated with progressively increasing mortality. Z score as continuous variable was associated with O.R. of 0.622 (95% CI- 0.527 to 0.733, P < 0.0001) for in-hospital mortality and remained significant predictor even after adjusting for age, gender, bypass duration and ACC score. Addition of Z score to ACC score improved its predictability for in-hosptial mortality (δC - 0.0661 [95% CI - 0.017 to 0.0595, P = 0.0169], IDI- 3.83% [95% CI - 0.017 to 0.0595, P = 0.00042]). Conclusion: Z scores were lower in our cohort and were associated with in-hospital mortality. Addition of Z score to ACC score significantly improves predictive ability for in-hospital mortality.

Predicting mortality after congenital heart surgeries: Evaluation of the Aristotle and Risk Adjustement in Congenital Heart surgery-1 risk prediction scoring systems: A retrospective single center analysis of 1150 patients.

Aims and Objectives: To validate Aristotle basic complexity and Aristotle comprehensive complexity (ABC and ACC) and risk adjustment in congenital heart surgery‑1 (RACHS‑1) prediction models for in hospital mortality after surgery for congenital heart disease in a single surgical unit. Materials and Methods: Patients younger than 18 years, who had undergone surgery for congenital heart diseases from July 2007 to July 2013 were enrolled. Scoring for ABC and ACC scoring and assigning to RACHS‑1 categories were done retrospectively from retrieved case files. Discriminative power of scoring systems was assessed with area under curve (AUC) of receiver operating curves (ROC). Calibration (test for goodness of fit of the model) was measured with Hosmer‑Lemeshow modification of χ2 test. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were applied to assess reclassification. Results: A total of 1150 cases were assessed with an all‑cause in‑hospital mortality rate of 7.91%. When modeled for multivariate regression analysis, the ABC (χ2 = 8.24, P = 0.08), ACC (χ2 = 4.17, P = 0.57) and RACHS‑1 (χ2 = 2.13, P = 0.14) scores showed good overall performance. The AUC was 0.677 with 95% confidence interval (CI) of 0.61-0.73 for ABC score, 0.704 (95% CI: 0.64-0.76) for ACC score and for RACHS‑1 it was 0.607 (95%CI: 0.55-0.66). ACC had an improved predictability in comparison to RACHS‑1 and ABC on analysis with NRI and IDI. Conclusions: ACC predicted mortality better than ABC and RCAHS‑1 models. A national database will help in developing predictive models unique to our populations, till then, ACC scoring model can be used to analyze individual performances and compare with other institutes.