title: ÐÑÐµÐ½ÐºÐ° Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÐµÐ¹ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð¾Ð·Ñ Ñ ÑÐµÐ»ÑÑ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¿ÑÐ¾ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ°Ð¿Ð¸Ð¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Evaluation of dose prediction capabilities in order to improve the quality of proton therapy
Creators: name: ÐÐ²ÑÑÑÐ¾Ð², ÐÐ»ÑÑ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð¾Ð·Ð¾Ð²Ð¾Ð³Ð¾ ÑÐ°ÑÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ°Ðº Ð¿ÑÐµÐ´ÑÑÐ°ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¶ÐµÐ»ÐµÐ·Ñ
ÑÐ°Ðº Ð¼Ð¾Ð»Ð¾ÑÐ½Ð¾Ð¹ Ð¶ÐµÐ»ÐµÐ·Ñ
dose distribution prediction
machine learning
prostate cancer
breast cancer

description: Ð Ð°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð¾ÑÐµÐ½ÐºÐµ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸, Ð·Ð°Ð´Ð°ÑÐµÐ¹ ÐºÐ¾ÑÐ¾ÑÐ¾Ð¹ ÑÐ²Ð»ÑÐµÑÑÑ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð´Ð¾Ð·Ð¾Ð²Ð¾Ðµ ÑÐ°ÑÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ðµ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð½Ð¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ: Ð¿Ð¾Ð²ÑÑÐ¸ÑÑ ÐºÐ°ÑÐµÑÑÐ²Ð¾ Ð»ÐµÑÐµÐ±Ð½ÑÑ Ð¿Ð»Ð°Ð½Ð¾Ð² Ð´Ð»Ñ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð¿ÑÐ¾ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ°Ð¿Ð¸Ð¸. ÐÑÐ»Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¾ Ð´Ð²Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½Ð° 30 Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ°Ñ Ñ ÑÐ°ÐºÐ¾Ð¼ Ð¿ÑÐµÐ´ÑÑÐ°ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¶ÐµÐ»ÐµÐ·Ñ Ð¸ 33 Ð´Ð»Ñ Ð»Ð¾ÐºÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ°Ðº Ð¼Ð¾Ð»Ð¾ÑÐ½Ð¾Ð¹ Ð¶ÐµÐ»ÐµÐ·Ñ. ÐÐ°ÑÐµÐ¼ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð° Ð²Ð°Ð»Ð¸Ð´Ð°ÑÐ¸Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ð¸ 10 Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ð´Ð»Ñ ÐºÐ°Ð¶Ð´Ð¾Ð³Ð¾ ÑÐ»ÑÑÐ°Ñ. ÐÐ¾Ð´ÐµÐ»Ð¸ Ð±ÑÐ»Ð¸ Ð¿ÑÐ¾Ð²ÐµÑÐµÐ½Ñ Ð¿ÑÑÑÐ¼ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸ Ð¾ÑÐµÐ½ÐºÐ¸ Ð´Ð¾Ð·Ð¸Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð². ÐÐ¾ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð±ÑÐ»Ð¸ Ð¿Ð¾Ð»ÑÑÐµÐ½Ñ ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¸ Ð¾Ð´Ð¾Ð±ÑÐµÐ½Ð½ÑÐµ Ð¿Ð»Ð°Ð½Ñ. ÐÑÐµÐ¼Ñ Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð±ÑÐ»Ð¾ ÑÐ½Ð¸Ð¶ÐµÐ½Ð¾ Ð½Ð° 50%. ÐÐ»Ñ Ð¿ÐµÑÐ²Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð±ÑÐ»Ð¾ Ð¾ÑÐ¼ÐµÑÐµÐ½Ð¾ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ðµ Ð½Ð°Ð³ÑÑÐ·ÐºÐ¸ Ð½Ð° Ð¿ÑÑÐ¼ÑÑ ÐºÐ¸ÑÐºÑ - ÑÑÐµÐ´Ð½ÐµÐµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ðµ ÑÐ²ÐµÐ»Ð¸ÑÐ¸Ð»Ð¾ÑÑ Ð½Ð° 0.49ï±0.57 ÐÑ.Â  ÐÐ»Ñ ÑÑÑÑÐºÑÑÑÑ CTV Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐ¾ÑÑÐ°Ð²Ð¸Ð»Ð¸: V103.5 % Ð¸ HI ÑÐ¼ÐµÐ½ÑÑÐ¸Ð»Ð¸ÑÑ Ð½Ð° 1.17Â±1.14 %, 0.3Â±0.3 %, ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²ÐµÐ½Ð½Ð¾, ÑÑÐ¾ ÑÐ²Ð¸Ð´ÐµÑÐµÐ»ÑÑÑÐ²ÑÐµÑ Ð¾ Ð»ÑÑÑÐµÐ¹ Ð³Ð¾Ð¼Ð¾Ð³ÐµÐ½Ð½Ð¾ÑÑÐ¸ Ð¸ Ð¼ÐµÐ½ÑÑÐ¸Ñ Ð²ÑÑÐ¾ÐºÐ¾Ð´Ð¾Ð·Ð¾Ð²ÑÑ Ð¾Ð±Ð»Ð°ÑÑÐµÐ¹. Ð¡ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð²ÑÐ¾ÑÐ¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð±ÑÐ»Ð° ÑÐ½Ð¸Ð¶ÐµÐ½Ð° Ð½Ð°Ð³ÑÑÐ·ÐºÐ° Ð½Ð° Ð»ÐµÐ²Ð¾Ðµ Ð»ÑÐ³ÐºÐ¾Ðµ â V4 ÐÑ Ð¸ V8 ÐÑ ÑÐ¼ÐµÐ½ÑÑÐ¸Ð»Ð¸ÑÑ Ð½Ð° 1.13Â±1.3 % Ð¸ 1.08Â±1.35 %, ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²ÐµÐ½Ð½Ð¾, Ð¸ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð° Ð»ÑÑÑÐµÐµ Ð¿Ð¾ÐºÑÑÑÐ¸Ñ Ð´Ð»Ñ CTV: DÑÑÐµÐ´Ð½ÑÑ ÑÐ¼ÐµÐ½ÑÑÐ¸Ð»Ð¾ÑÑ Ð½Ð° 0.73ï±0.48 % Ð¸ V95 % ÑÐ²ÐµÐ»Ð¸ÑÐ¸Ð»Ð¾ÑÑ Ð½Ð° 0.05Â±0.13 %. ÐÑÐ²Ð¾Ð´Ñ: Ð¿Ð»Ð°Ð½Ñ, Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÐµ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° RPP Ð·Ð° Ð±Ð¾Ð»ÐµÐµ ÐºÐ¾ÑÐ¾ÑÐºÐ¾Ðµ Ð²ÑÐµÐ¼Ñ, Ð¸Ð¼ÐµÑÑ ÑÑÐ°Ð²Ð½Ð¸Ð¼Ð¾Ðµ ÐºÐ°ÑÐµÑÑÐ²Ð¾ Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ°Ð¼Ð¸ ÑÐºÑÐ¿ÐµÑÑÐ¾Ð². ÐÐ´Ð½Ð°ÐºÐ¾, Ð¿ÐµÑÐµÐ´ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»Ñ ÑÑÐ¾Ð¸Ñ Ð¾Ð·Ð½Ð°ÐºÐ¾Ð¼Ð¸ÑÑÑÑ Ð´Ð»Ñ ÐºÐ°ÐºÐ¸Ñ ÑÑÑÑÐºÑÑÑ Ð½Ð°Ð±Ð»ÑÐ´Ð°Ð»Ð°ÑÑ Ð±Ð¾Ð»ÑÑÐ°Ñ Ð½Ð°Ð³ÑÑÐ·ÐºÐ° Ð¿Ð¾ Ð´Ð¾Ð·Ðµ.
description: The work is devoted to evaluating the effectiveness of using a model whose task is to predict the dose distribution based on a trained algorithm. The purpose of the work is to improve the quality of treatment plans for proton therapy. Two models were trained on 30 patients with prostate cancer and 33 for breast cancer localization. Validation was then performed based on 10 patients for each case. The models were verified by comparative analysis and evaluation of dosimetric parameters. According to the results of the study, clinically approved plans were obtained using models. The planning time has been reduced by 50%. For the first model, an increase in the load on the rectum was noted - the average value increased by 0.49Â±0.57 Gy. For the CTV structure, the changes were: V103.5% and HI decreased by 1.17Â±1.14 %, 0.3Â±0.3 %, accordingly, this indicates better homogeneity and smaller high-dose areas. With the help of the second model, the load on the left lung was reduced â V4 Gy and V8 Gy decreased by 1.13Â±1.3% and 1.08Â±1.35%, respectively, and the best coverage for CTV was implemented: Dmean decreased by 0.73Â±0.48% and V95% increased by 0.05Â±0.13%. Conclusions: the plans obtained using the RPP algorithm in a shorter time have comparable quality with the results of experts. However, before use, the user should familiarize himself with which structures a large dose load was observed.