Delta Radiomics Analysis for Local Control Prediction in Pancreatic Cancer Patients Treated Using Magnetic Resonance Guided Radiotherapy.

Diagnostics (Basel) 2021 Jan 5;11(1). Epub 2021 Jan 5.

Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy.

The aim of this study is to investigate the role of Delta Radiomics analysis in the prediction of one-year local control (1yLC) in patients affected by locally advanced pancreatic cancer (LAPC) and treated using Magnetic Resonance guided Radiotherapy (MRgRT). A total of 35 patients from two institutions were enrolled: A 0.35 Tesla T2*/T1 MR image was acquired for each case during simulation and on each treatment fraction. Physical dose was converted in biologically effective dose (BED) to compensate for different radiotherapy schemes. Delta Radiomics analysis was performed considering the gross tumour volume (GTV) delineated on MR images acquired at BED of 20, 40, and 60 Gy. The performance of the delta features in predicting 1yLC was investigated in terms of Wilcoxon Mann-Whitney test and area under receiver operating characteristic (ROC) curve (AUC). The most significant feature in predicting 1yLC was the variation of cluster shade calculated at BED = 40 Gy, with a -value of 0.005 and an AUC of 0.78 (0.61-0.94). Delta Radiomics analysis on low-field MR images might play a promising role in 1yLC prediction for LAPC patients: further studies including an external validation dataset and a larger cohort of patients are recommended to confirm the validity of this preliminary experience.

Download full-text PDF

Source
http://dx.doi.org/10.3390/diagnostics11010072DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824764PMC
January 2021

Publication Analysis

Top Keywords

delta radiomics
16
radiomics analysis
16
treated magnetic
8
magnetic resonance
8
resonance guided
8
predicting 1ylc
8
guided radiotherapy
8
pancreatic cancer
8
local control
8
patients
5
delta
5
delta features
4
operating characteristic
4
features predicting
4
characteristic roc
4
performance delta
4
bed performance
4
roc curve
4
receiver operating
4
test area
4

Similar Publications

Delta radiomics for rectal cancer response prediction with hybrid 0.35 T magnetic resonance-guided radiotherapy (MRgRT): a hypothesis-generating study for an innovative personalized medicine approach.

Radiol Med 2019 Feb 29;124(2):145-153. Epub 2018 Oct 29.

Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Istituto di Radiologia, Fondazione Policlinico A. Gemelli IRCCS - Università Cattolica Sacro Cuore, Largo A. Gemelli, 8, 00168, Rome, Italy.

The aim of this study was to evaluate the variation of radiomics features, defined as "delta radiomics", in patients undergoing neoadjuvant radiochemotherapy (RCT) for rectal cancer treated with hybrid magnetic resonance (MR)-guided radiotherapy (MRgRT). The delta radiomics features were then correlated with clinical complete response (cCR) outcome, to investigate their predictive power. A total of 16 patients were enrolled, and 5 patients (31%) showed cCR at restaging examinations. Read More

View Article and Full-Text PDF
February 2019

External Validation of Early Regression Index (ERI) as Predictor of Pathologic Complete Response in Rectal Cancer Using Magnetic Resonance-Guided Radiation Therapy.

Int J Radiat Oncol Biol Phys 2020 Dec 3;108(5):1347-1356. Epub 2020 Aug 3.

Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome, Italy.

Purpose: Tumor control probability (TCP)-based early regression index (ERI) is a radiobiological parameter that showed promising results in predicting pathologic complete response (pCR) on T2-weighted 1.5 T magnetic resonance (MR) images of patients with locally advanced rectal cancer. This study aims to validate the ERI in the context of low-tesla MR-guided radiation therapy, using images acquired with different magnetic field strength (0. Read More

View Article and Full-Text PDF
December 2020

Predictive value of 0.35 T magnetic resonance imaging radiomic features in stereotactic ablative body radiotherapy of pancreatic cancer: A pilot study.

Med Phys 2020 Aug 16;47(8):3682-3690. Epub 2020 May 16.

Department of Radiation Oncology, University of Miami, Miami, FL, 33136, USA.

Purpose: The aim of this study was to evaluate the potential and feasibility of radiomic features extracted from low field strength (0.35 T) magnetic resonance images (MRIs) in predicting treatment response for patients with pancreatic cancer undergoing stereotactic body radiotherapy (SBRT).

Methods: Twenty patients with unresected, non-metastatic pancreatic ductal adenocarcinoma (PDAC) were enrolled, all of whom received neoadjuvant chemotherapy followed by five-fraction MR-guided SBRT with a radiation dose range of 33-50 Gy. Read More

View Article and Full-Text PDF
August 2020

An investigation of machine learning methods in delta-radiomics feature analysis.

PLoS One 2019 13;14(12):e0226348. Epub 2019 Dec 13.

Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina, United States of America.

Purpose: This study aimed to investigate the effectiveness of using delta-radiomics to predict overall survival (OS) for patients with recurrent malignant gliomas treated by concurrent stereotactic radiosurgery and bevacizumab, and to investigate the effectiveness of machine learning methods for delta-radiomics feature selection and building classification models.

Methods: The pre-treatment, one-week post-treatment, and two-month post-treatment T1 and T2 fluid-attenuated inversion recovery (FLAIR) MRI were acquired. 61 radiomic features (intensity histogram-based, morphological, and texture features) were extracted from the gross tumor volume in each image. Read More

View Article and Full-Text PDF
April 2020