title: ÐÐ½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ ÐÐ­Ð¢ Ñ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ñ Ð¿ÑÐ¸Ñ Ð¾ÑÐ¸ÑÐµÑÐºÐ¸Ð¼Ð¸ ÑÐ°ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð°Ð¼Ð¸ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÐºÐ¸
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: Analysis of PET data in patients with psychotic disorders using radiomics methods
Creators: name: Ð¨Ð°Ð¹Ð´ÑÐ»Ð¸Ð½, ÐÐ»Ð°Ð´Ð¸ÑÐ»Ð°Ð²
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Ð¸Ñ Ð¾ÑÐ¸ÑÐµÑÐºÐ¸Ðµ ÑÐ°ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð°
ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÐºÐ°
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
psychotic disorders
radiomics
machine learning

description: ÐÐµÑÐ¾Ð´Ñ ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÐºÐ¸ ÑÑÐ¿ÐµÑÐ½Ð¾ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð¸ ÑÐµÐ±Ñ Ð² Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸ÑÑ Ð¾Ð½ÐºÐ¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ñ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ð¹. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¿Ð¾ÐºÐ°Ð·Ð°ÑÑ Ð¿Ð¾ÑÐµÐ½ÑÐ¸Ð°Ð» Ð´Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¼ÐµÑÐ¾Ð´Ð° Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¿ÑÐ¸ÑÐ¾ÑÐ¸ÑÐµÑÐºÐ¸Ñ ÑÐ°ÑÑÑÑÐ¾Ð¹ÑÑÐ² Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÐÐ­Ð¢. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð° Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÐÐ­Ð¢/ÐÐ¢ ÑÐºÐ°Ð½Ð¾Ð² Ñ 18F-Ð¤ÐÐ Ñ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÐ¾Ð² Ð¿ÑÐ¸ÑÐ¾ÑÐ¸ÑÐµÑÐºÐ¸Ð¼Ð¸ ÑÐ°ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð°Ð¼Ð¸ Ð½Ð° Ð´Ð²Ðµ Ð³ÑÑÐ¿Ð¿Ñ: Ð¿Ð°ÑÐ¸ÐµÐ½ÑÑ, ÑÐ¿Ð¾ÑÑÐµÐ±Ð»ÑÑÑÐ¸Ðµ Ð¿ÑÐ¸ÑÐ¾Ð°ÐºÑÐ¸Ð²Ð½ÑÐµ Ð²ÐµÑÐµÑÑÐ²Ð° Ð¸ Ð¿Ð°ÑÐ¸ÐµÐ½ÑÑ Ñ Ð½ÐµÐ¹ÑÐ¾Ð´ÐµÐ³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð²Ð½ÑÐ¼Ð¸ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸ÑÐ¼Ð¸. ÐÐ¾ÑÑÐ¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸ Ð²ÑÐ´ÐµÐ»ÐµÐ½Ð¸Ðµ Ð·Ð¾Ð½ Ð¸Ð½ÑÐµÑÐµÑÐ° Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸Ð»Ð¸ÑÑ ÑÑÐµÐ´ÑÑÐ²Ð°Ð¼Ð¸ ÐÐ SPM12. 21 Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ Ð±ÑÐ»Ð¾ Ð½Ð¾ÑÐ¼Ð°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð¾, ÑÐ³Ð»Ð°Ð¶ÐµÐ½Ð¾ Ð¸ Ð¿Ð¾Ð´Ð²ÐµÑÐ³Ð½ÑÑÐ¾ Ð¾ÑÐ½Ð¾ÑÐ¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð´Ð¸ÑÐºÑÐµÑÐ¸Ð·Ð°ÑÐ¸Ð¸ ÑÑÐ¾Ð²Ð½ÐµÐ¹ ÑÐµÑÐ¾Ð³Ð¾. ÐÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ðµ Ð´Ð²ÑÑ Ð²ÑÐ±Ð¾ÑÐ¾ÑÐ½Ð¾Ð³Ð¾ t-ÑÐµÑÑÐ° Ð¡ÑÑÑÐ´ÐµÐ½ÑÐ° Ð¿Ð¾Ð·Ð²Ð¾Ð»Ð¸Ð»Ð¾ Ð²ÑÐ´ÐµÐ»Ð¸ÑÑ ÑÑÐ¸ Ð·Ð¾Ð½Ñ Ð¸Ð½ÑÐµÑÐµÑÐ°, Ð´Ð»Ñ ÐºÐ¾ÑÐ¾ÑÑÑ Ð±ÑÐ»Ð¸ ÑÐ°ÑÑÑÐ¸ÑÐ°Ð½Ñ ÑÐµÐºÑÑÑÑÐ½ÑÐµ Ð²ÐµÐ»Ð¸ÑÐ¸Ð½Ñ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¿Ð°ÐºÐµÑÐ° PyRadiomics Ð½Ð° ÑÐ·ÑÐºÐµ Python. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° Ð°Ð»ÑÑÐ° ÐÑÐ¾Ð½Ð±Ð°ÑÐ°, U-ÐºÑÐ¸ÑÐµÑÐ¸Ñ ÐÐ°Ð½Ð½Ð°-Ð£Ð¸ÑÐ½Ð¸ Ð¸ Ð¼Ð°ÑÑÐ¸ÑÑ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸ Ð¡Ð¿Ð¸ÑÐ¼ÐµÐ½Ð° Ð±ÑÐ»Ð¾ Ð¾ÑÐ¾Ð±ÑÐ°Ð½Ð¾ ÑÑÐ¸ Ð¿ÑÐµÐ´Ð¸ÐºÑÐ¾ÑÐ° Ð´Ð»Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð»Ð¾Ð³Ð¸ÑÑÐ¸ÑÐµÑÐºÐ¾Ð¹ ÑÐµÐ³ÑÐµÑÑÐ¸Ð¸. Ð¢Ð¾ÑÐ½Ð¾ÑÑÑ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¾ÑÐµÐ½Ð¸Ð²Ð°Ð»Ð°ÑÑ Ð¿ÑÑÐµÐ¼ 3-ÑÐ¾Ð»Ð´Ð¾Ð²Ð¾Ð¹ 10-ÐºÑÐ°ÑÐ½Ð¾Ð¹ Ð¿ÐµÑÐµÐºÑÑÑÑÐ½Ð¾Ð¹ Ð¿ÑÐ¾Ð²ÐµÑÐºÐ¸. Ð¡ÑÐµÐ´Ð½Ð¸Ðµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ñ Ð¼ÐµÑÑÐ¸Ðº accuracy, sensitivity, specificity Ð¸ AUC Ð¿Ð¾Ð»ÑÑÐ¸Ð»Ð¸ÑÑ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ð¼Ð¸: 0.90 Â± 0.10, 0.91 Â± 0.15, 0.90 Â± 0.14, 0.90 Â± 0.10. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÑÑÑ ÑÐ²Ð½ÑÐµ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²ÐµÐ½Ð½ÑÐµ ÑÐ°Ð·Ð»Ð¸ÑÐ¸Ñ Ð´Ð²ÑÑ Ð³ÑÑÐ¿Ð¿ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹, Ð¾Ð´Ð½Ð°ÐºÐ¾ ÑÑÐµÐ±ÑÑÑÑÑ Ð´Ð°Ð»ÑÐ½ÐµÐ¹ÑÐ¸Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ.
description: Radiomics methods have been successfully applied in cancer research. The goal of this study is to demonstrate the potential of these methods in the field of psychotic disorder research using PET imaging. During the project, a machine learning model was developed to classify PET/CT scans of patients with psychotic disorders who have taken 18F-FDG into two categories: patients who use psychoactive substances and patients with neurodegenerative disorders. Post-processing and identification of regions of interest were performed using SM12 software. 21 images were normalized, smoothed, and subjected to a relative quantization of gray levels. Performing a two-sample Student t-test allowed us to identify three regions of interest for which texture features were calculated using the PyRadiomics package in Python. Based on the Cronbachs alpha coefficient, the Mann-Whitney U-test and the Spearmans correlation matrix, three predictors were selected for the logistic regression model. The model was assessed using 10 times repeated 3-fold cross-validation strategy. The mean values for the accuracy, sensitivity, specificity, and AUC were 0.90 Â± 0.10, 0.91 Â± 0.15, 0.90 Â± 0.14, and 0.90 Â± 0.10 respectively. The results clearly demonstrate quantitative differences between the two image groups, but further research is required.