Radiomics-based prognosis classification for high-risk prostate cancer treated with radiotherapy
Creators
- 1. Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (Italy)
- 2. Radiotherapy and Radiosurgery Department, Humanitas Clinical and Research Center-IRCCS, Rozzano (Italy)
Description
The present study aimed to investigate if CT-based radiomics features could correlate to the risk of metastatic progression in high-risk prostate cancer patients treated with radical RT and long-term androgen deprivation therapy (ADT). A total of 157 patients were investigated and radiomics features extracted from the contrast-free treatment planning CT series. Three volumes were segmented: the prostate gland only (CTV_p), the prostate gland with seminal vesicles (CTV_psv), and the seminal vesicles only (CTV_sv). The patients were split into two subgroups of 100 and 57 patients for training and validation. Five clinical and 62 radiomics features were included in the analysis. Considering metastases-free survival (MFS) as an endpoint, the predictive model was used to identify the subgroups with favorable or unfavorable prognoses (separated by a threshold selected according to the Youden method). Pure clinical, pure radiomic, and combined predictive models were investigated. With a median follow-up of 30.7 months, the MFS at 1 and 3 years was 97.2% ± 1.5 and 92.1% ± 2.0, respectively. Univariate analysis identified seven potential predictors for MFS in the CTV_p group, 11 in the CTV_psv group, and 9 in the CTV_sv group. After elastic net reduction, these were 4 predictors for MFS in the CTV_p group (positive lymph nodes, Gleason score, H_Skewness, and NGLDM_Contrast), 5 in the CTV_psv group (positive lymph nodes, Gleason score, H_Skewnesss, Shape_Surface, and NGLDM_Contrast), and 6 in the CTV_sv group (positive lymph nodes, Gleason score, H_Kurtosis, GLCM_Correlation, GLRLM_LRHGE, and GLZLM_SZLGE). The patients' group of the training and validation cohorts were stratified into favorable and unfavorable prognosis subgroups. For the combined model, for CTV_p, the mean MFS was 134 ± 14.5 vs. 96.9 ± 22.2 months for the favorable and unfavorable subgroups, respectively, and 136.5 ± 14.6 vs. 70.5 ± 4.3 months for CTV_psv and 150.0 ± 4.2 vs. 91.1 ± 8.6 months for CTV_sv, respectively. Radiomic features were able to predict the risk of metastatic progression in high-risk prostate cancer. Combining the radiomic features and clinical characteristics can classify high-risk patients into favorable and unfavorable prognostic groups.
Availability note (English)
Available from: http://dx.doi.org/10.1007/s00066-021-01886-yAdditional details
Identifiers
Publishing Information
- Journal Title
- Strahlentherapie und Onkologie
- Journal Volume
- 198
- Journal Issue
- 8
- Journal Page Range
- p. 710-718
- ISSN
- 0179-7158
- CODEN
- STONE4
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- Germany
- INIS RN
- 53087480
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ANDROGENS; CARCINOMAS; CLASSIFICATION; COMPUTERIZED TOMOGRAPHY; CORRELATIONS; LYMPH NODES; METASTASES; PROSTATE; RADIOMICS; RADIOTHERAPY; STATISTICS; SURVIVAL CURVES; TRAINING; VALIDATION
- Descriptors DEC
- ANDROSTANES; BODY; DIAGNOSTIC TECHNIQUES; DISEASES; EDUCATION; GLANDS; HORMONES; LYMPHATIC SYSTEM; MALE GENITALS; MATHEMATICS; MEDICINE; NEOPLASMS; NUCLEAR MEDICINE; ORGANIC COMPOUNDS; ORGANS; RADIOLOGY; STEROID HORMONES; STEROIDS; TESTING; THERAPY; TOMOGRAPHY