Multi-centre real-world validation of automated treatment planning for breast radiotherapy.

PURPOSE: To present the results of the first multi-centre real-world validation of autoplanning for whole breast irradiation after breast-sparing surgery, encompassing high complexity cases (e.g. with a boost or regional lymph nodes) and a wide range of clinical practices. METHODS: The 24 participating centers each included 10 IMRT/VMAT/Tomotherapy patients, previously treated with a manually generated plan ('manplan'). There were no restrictions regarding case complexity, planning aims, plan evaluation parameters and criteria, fractionation, treatment planning system or treatment machine/technique. In addition to dosimetric comparisons of autoplans with manplans, blinded plan scoring/ranking was conducted by a clinician from the treating center. Autoplanning was performed using a single configuration for all patients in all centres. Deliverability was verified through measurements at delivery units. RESULTS: Target dosimetry showed comparability, while reductions in OAR dose parameters were 21.4 % for heart Dmean, 16.7 % for ipsilateral lung Dmean, and 101.9 %, 45.5 %, and 35.7 % for contralateral breast D0.03cc, D5% and Dmean, respectively (all p < 0.001). Among the 240 patients included, the clinicians preferred the autoplan for 119 patients, with manplans preferred for 96 cases (p = 0.01). Per centre there were on average 5.0 ± 2.9 (1SD) patients with a preferred autoplan (range [0-10]), compared to 4.0 ± 2.7 with a preferred manplan ([0,9]). No differences were observed regarding deliverability. CONCLUSION: The automation significantly reduced the hands-on planning workload compared to manual planning, while also achieving an overall superiority. However, fine-tuning of the autoplanning configuration prior to clinical implementation may be necessary in some centres to enhance clinicians' satisfaction with the generated autoplans.

A machine learning tool for re-planning and adaptive RT: A multicenter cohort investigation.

PURPOSE: To predict patients who would benefit from adaptive radiotherapy (ART) and re-planning intervention based on machine learning from anatomical and dosimetric variations in a retrospective dataset. MATERIALS AND METHODS: 90 patients (pts) treated for head-neck cancer (H&N) formed a multicenter data-set. 41 H&N pts (45.6%) were considered for learning; 49 pts (54.4%) were used to test the tool. A homemade machine-learning classifier was developed to analyze volume and dose variations of parotid glands (PG). Using deformable image registration (DIR) and GPU, patients' conditions were analyzed automatically. Support Vector Machines (SVM) was used for time-series evaluation. "Inadequate" class identified patients that might benefit from replanning. Double-blind evaluation by two radiation oncologists (ROs) was carried out to validate day/week selected for re-planning by the classifier. RESULTS: The cohort was affected by PG mean reduction of 23.7±8.8%. During the first 3weeks, 86.7% cases show PG deformation aligned with predefined tolerance, thus not requiring re-planning. From 4th week, an increased number of pts would potentially benefit from re-planning: a mean of 58% of cases, with an inter-center variability of 8.3%, showed "inadequate" conditions. 11% of cases showed "bias" due to DIR and script failure; 6% showed "warning" output due to potential positioning issues. Comparing re-planning suggested by tool with recommended by ROs, the 4th week seems the most favorable time in 70% cases. CONCLUSIONS: SVM and decision-making tool was applied to overcome ART challenges. Pts would benefit from ART and ideal time for re-planning intervention was identified in this retrospective analysis.

Prediction of (89)Zr production using the Monte Carlo code FLUKA.

The widely used Monte Carlo simulation code FLUKA has been utilized to prototype a solid target for the production of (89)Zr by irradiation of a metallic (89)Y target foil in a 16.5MeV proton biomedical cyclotron, through the reaction (89)Y(p, n)(89)Zr. Simulations were performed with and without an Al energy degrader. In the setup of the geometry of the target, state of the art support tools, like SimpleGeo, were used for accurate, detailed modeling. The results permitted a quick assessment of all possible radionuclidic contaminants and confirmed that the use of an energy degrader avoids production of the most important impurity, (88)Zr. The estimated value for the activity produced in one hour of irradiation at 20µA is 384 ± 42MBq; this is encouraging, indicating possible production of clinically significant amounts of activity with the relatively simple target setup adopted. Initial experimental tests gave results in excellent agreement with simulations, confirming the usefulness and accuracy of FLUKA as a tool for the design and optimization of targets for the production of PET radionuclides.

Gender affects the pattern of neuroendocrine response to head-up tilt.

One of the major concerns in space medicine is post-mission postural hypotension. Since the beginning, most of the studies have been aimed at the identification of mechanical and neuroautonomic mechanisms within the cardiovascular system potentially involved in this phenomenon. Some gender differences in the cardiovascular reactivity to changing posture have been described so far, which still need better clarification. Moreover, the neuroendocrine contribution to postflight readaptation deserves more indepth studies. Sudden passive head-up tilting is considered to be a good simulation method for hemodynamic changes occurring during transition from 0xg to 1xg. The aim of this study was to verify whether cardiovascular or neuroendocrine changes occurring after sudden passive +70 degrees head-up tilt (HUT) became already evident within 10 min and were similar in healthy young-adult men and women.

Hormonal adaptation to real and simulated microgravity.

NASA: The authors provide an overview of relevant results from endocrine studies in astronauts before, during, and after space flight. The hormonal systems examined are the water-electrolyte regulation, the hypothalamic-pituitary-adrenal axis, the hypothalamic-pituitary gonadal axis, the growth hormone-insulin like growth factor 1-prolactin system, hormones which affect bone turnover, the hypothalamic-pituitary-thyroid axis, and the endocrine pancreas. Hormones studied include renin, aldosterone, vasopressin, atrial natriuretic factor, cortisol, testosterone, lutenizing hormone, prolactin, growth hormone, insulin-like growth factor-1, insulin, glucose, T4, thyroid stimulating hormone, calcitonin, active D3, and parathyroid hormone.^ieng