Automated Heuristic Optimization of Prostate VMAT Treatment Planning

Purpose: To investigate a genetic algorithm approach to automatic treatment planning. Methods: A Python script based on genetic algorithm (GA) was implemented for VMAT treatment planning of prostate tumor. The script was implemented in RayStation treatment planning system using Python code. Two different clinical prescriptions were considered: 78 Gy prescribed to planning target volume in 39 fractions (GROUP 1) and simultaneous integrated boost (70.2 Gy to prostate bed and 61.1 Gy to seminal vesicles) in 26 fractions (GROUP 2). The script automatically optimizes doses to PTV and OARs according to GA. A comparison with corresponding plans created with Monaco TPS (M) and Auto-Planning module of Pinnacle3 (AP) was carried out. The plans were evaluated with a total score (TS) of PlanIQ software in terms of target coverage and sparing of OARs as well as clinical score (CS) performed by a Radiation Oncologist. Results: In GROUP 1, mean value of TS were 150.6 ± 30.7, 146.3 ± 36.1 and 137.4 ± 35.7 for AP, GA and M respectively. For GROUP 2, mean value for TS were 163.5 ± 16.8, 163.4 ± 24.7 and 162.9 ± 16.6 for AP, GA and M respectively with no significance differences. In terms of CS, the highest value has been attributed to GA in four patients out of five for both GROUP 1 and 2. Conclusions: Genetic approach is practicable for prostate VMAT plan generation and studies are underway in other anatomical sites such as Head and Neck and Rectum

A multi-center output factor intercomparison to uncover systematic inaccuracies in small field dosimetry

Large uncertainties in output factor (OF) small fields dosimetry motivated multicentric studies. The focus of the study was the determination of the OFs, for different linacs and radiosurgery units, using new-generation detectors. Intercomparison studies between radiotherapy centers improved quality dosimetry practices. Results confirmed the effectiveness of the studies to uncover large systematic inaccuracies in small field dosimetry. Keywords: Multicentric studies, Small field dosimetry, Output factor

Variability of clinical target volume delineation for rectal cancer patients planned for neoadjuvant radiotherapy with the aid of the platform Anatom-e

Objective: Delineation of treatment volumes is a major source of uncertainties in radiotherapy (RT). This is also true for rectal cancer patients undergoing neoadjuvant RT, with a potential impact on treatment quality. We investigated the role of the digital platform Anatom-e (Anatom-e Information Sytems Ltd., Houston, Texas) in increasing the compliance to follow a specific treatment protocol in a multicentric setting. Materials and methods: Two clinical cases of locally advanced rectal cancer were chosen. Participants were instructed to follow the 2009 Radiation Therapy Oncology Group consensus atlas and asked to manually segment clinical target volumes (CTVs), for both patient 1 and 2, on day 1 with and without the use of Anatom-e. After one week (day 2), the same radiation oncologist contoured again, with and without Anatom-e, the same CT series. Intraobserver (Intra-OV) and interobserver (Inter-OV) variability were evaluated with the Dice similarity coefficient (DSC), the Hausdorff distance (HD) and mean distance to agreement (MDA). Results: For clinical case 1, no significant difference was found for Intra-OV and Inter-OV. For clinical case 2, no significant difference was found for Intra-OV but a statistically significant difference was found for Inter-OV in DSC when using or not the platform. Mean DCS was 0.65 (SD: ±0.64; range: 0.58–0.79) for day 1 vs reference volume without Anatom-e and 0.72 (SD: ±0.39; range: 0.67–0.77) (p = 0.03) with it. Mean MDA was lower with Anatom-e (3.61; SD: ±1.33; range: 2.85–4.78) than without (4.14; SD: ±2.97; range: 2.18–5.21), with no statistical significance (p = 0.21) The use of Anatom-e decreased the SD from 2.97 to 1.33. Mean HD was lower with Anatom-e (26.06; SD: ±2.05; range: 24.08–32.62), with no statistical significance (p = 0.14) compared to that without (31.39; SD: ±1.31; range: 26.14–48.72). Conclusions: The use of Anatom-e decreased the Inter-OV in the CTV delineation process for locally advanced rectal cancer with complex disease presentation planned for neoadjuvant RT. This system may be potentially helpful in increasing the compliance to follow shared guidelines and protocols. Keywords: Rectal cancer, Neoadjuvant radiotherapy, Interobserver variability, Contouring, Target volume delineatio