Dose-Based Radiomic Analysis (Dosiomics) for Intensity Modulated Radiation Therapy in Patients With Prostate Cancer: Correlation Between Planned Dose Distribution and Biochemical FailureYu Murakami MScTakashi Soyano MDTakuyo Kozuka MD, PhD §Masaru Ushijima PhD ‖Yuuki Koizumi MSc *Hikaru Miyauchi MScMasahiro Kaneko BSc *Masahiro Nakano ...
To predict the incidence of radiation-induced hypothyroidism (RHT) in nasopharyngeal carcinoma (NPC) patients, dosiomics features based prediction models were established. Materials and methods A total of 145 NPC patients treated with radiotherapy from January 2012 to January 2015 were included. Dosiom...
This study was designed to establish radiation pneumonitis (RP) prediction models using dosiomics and/or deep learning-based radiomics (DLR) features based on 3D dose distribution. Methods A total of 140 patients with non-small cell lung cancer who received stereotactic body radiation therapy (SBRT...
DosiomicDeep learningNon-small cell lung cancerRadiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patients' quality of life. This study aimed to establish a combined model of radiomics, dosiomics, deep learning (DL) based on simulated location CT and...
dosiomicslate effectschildhood cancerdosimetryradiotherapyvalvulopathyrandom forestimbalanced classificationChildhood cancer survivors are often prone to experiencing late effects due to treatment complications. Valvular Heart Disease is a known iatrogenic effect of radiation leakage to the heart during ...
DosiomicsField widthModulation factorPitchHelical tomotherapyProstate cancerRadiotherapyThe stability of dosiomics features (DFs) and dose-volume histogram (DVH) parameters for detecting disparities in helical tomotherapy planned dose distributions was assessed. Treatment plans of 18 prostate patients were re...
Finally, three radiomics features and one dosiomics feature were selected for model's development. One clinical factor (Red Blood Cell, RBC) had also been used to construct the model. The combined model showed superior performance in training cohort and validation cohort, the area under the ...
Dosiomics features, such as shape characteristics, statistical properties, and texture metrics (e.g., GLCM, GLSZM), were extracted from RT Dose DICOM files of patients treated with TomoDirect on the Radixact X9 system. Regions of interest (ROI), such as the planning target volume (PTV), ...
DosiomicsMachine learningThis study aims to develop a predictive model for radiation-induced skin toxicity (RIST) in breast cancer patients using dosiomics features extracted from the dose distribution map within the clinical target volume (CTV). This study included breast cancer patients treated with...
Plan complexity score (PCscore) and dosiomics score (Doscore) were derived using the least absolute shrinkage and selection operator (LASSO). Four classification models were developed by combining PCscore, Doscore, and plan parameters according to a gamma criterion of 2%/2 mm (纬2%/2 mm). ...