Therapeutic Radiology

Development and clinical implementation of SeedNet: A sliding-window convolutional neural network for radioactive seed identification in MRI-assisted radiosurgery (MARS).

PURPOSE: To develop and evaluate a sliding-window convolutional neural network (CNN) for radioactive seed identification in MRI of the prostate after permanent implant brachytherapy.

A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would alleviate this issue by guiding clinical plan optimization to save time and maintain high quality plans. We have modified a convolutional deep network model, U-net...

Intervening Nidal Brain Parenchyma and Risk of Radiation-Induced Changes After Radiosurgery for Brain Arteriovenous Malformation: A Study Using an Unsupervised Machine Learning Algorithm.

OBJECTIVE: To assess the sensitivity and specificity of arteriovenous malformation (AVM) nidal component identification and quantification using an un...

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predic...

Intensity-modulated radiation therapy of anal squamous cell carcinoma: Relationship between delineation quality and regional recurrence.

BACKGROUND AND PURPOSE: Intensity-modulated radiation therapy (IMRT) is currently indicated to treat anal squamous cell carcinoma (ASCC). Conformal do...

Efficacy and safety of CT-guided high-dose-rate interstitial brachytherapy in primary and secondary malignancies of the pancreas.

PURPOSE: To evaluate efficacy and safety of CT-guided iBT in patients with primary and secondary malignancies of the pancreas.

Deep learning for patient-specific quality assurance: Identifying errors in radiotherapy delivery by radiomic analysis of gamma images with convolutional neural networks.

PURPOSE: Patient-specific quality assurance (QA) for intensity-modulated radiation therapy (IMRT) is a ubiquitous clinical procedure, but conventional...

Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique.

PURPOSE: To develop an automated treatment planning strategy for external beam intensity-modulated radiation therapy (IMRT), including a deep learning...

Metal artifact reduction on cervical CT images by deep residual learning.

BACKGROUND: Cervical cancer is the fifth most common cancer among women, which is the third leading cause of cancer death in women worldwide. Brachyth...

[Interest of robotic stereotactic radiosurgery in the management of brain metastases: Results of a retrospective, single center analysis].

PURPOSE: The management of malignant brain metastases becomes a main issue for the treatment of patients, because of the survival extension related to...

Combined Low Dose Rate Brachytherapy and External Beam Radiation Therapy for Intermediate-Risk Prostate Cancer.

INTRODUCTION: This is a retrospective study conducted to report the tumor control and late toxicity outcomes of patients with intermediate-risk prosta...

The application of artificial intelligence in the IMRT planning process for head and neck cancer.

Artificial intelligence (AI) is beginning to transform IMRT treatment planning for head and neck patients. However, the complexity and novelty of AI a...

MRI-based automated detection of implanted low dose rate (LDR) brachytherapy seeds using quantitative susceptibility mapping (QSM) and unsupervised machine learning (ML).

BACKGROUND AND PURPOSE: Permanent seed brachytherapy is an established treatment option for localized prostate cancer. Currently, post-implant dosimet...

Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.

PURPOSE: Intensity modulated radiation therapy (IMRT) is commonly employed for treating head and neck (H&N) cancer with uniform tumor dose and conform...

Deeply-learnt damped least-squares (DL-DLS) method for inverse kinematics of snake-like robots.

Recently, snake-like robots are proposed to assist experts during medical procedures on internal organs via natural orifices. Despite their well-spelt...

MRI-based treatment planning for brain stereotactic radiosurgery: Dosimetric validation of a learning-based pseudo-CT generation method.

Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast without ionizing ...

Automated prediction of dosimetric eligibility of patients with prostate cancer undergoing intensity-modulated radiation therapy using a convolutional neural network.

The quality of radiotherapy has greatly improved due to the high precision achieved by intensity-modulated radiation therapy (IMRT). Studies have been...

Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.

PURPOSE: Treatment effect or radiation necrosis after stereotactic radiosurgery (SRS) for brain metastases is a common phenomenon often indistinguisha...

Deep nets vs expert designed features in medical physics: An IMRT QA case study.

PURPOSE: The purpose of this study was to compare the performance of Deep Neural Networks against a technique designed by domain experts in the predic...

Salvage HDR Brachytherapy: Multiple Hypothesis Testing Versus Machine Learning Analysis.

PURPOSE: Salvage high-dose-rate brachytherapy (sHDRB) is a treatment option for recurrences after prior radiation therapy. However, only approximately...