Defining the potential for sexual structures-sparing for prostate cancer external beam radiotherapy: A dosimetric study.

Purpose: The purpose of the study was to evaluate the dosimetric impact of sexual-sparing radiotherapy for prostate cancer, with magnetic resonance-only treatment planning.

Material And Methods: Fifteen consecutive patients receiving prostate cancer radiotherapy were selected. A synthetic CT was generated with a deep learning method from each T2-weighted MRI performed at the time of treatment planning.

3D Unsupervised deep learning method for magnetic resonance imaging-to-computed tomography synthesis in prostate radiotherapy.

Background And Purpose: Magnetic resonance imaging (MRI)-to-computed tomography (CT) synthesis is essential in MRI-only radiotherapy workflows, particularly through deep learning techniques known for their accuracy. However, current supervised methods are limited to specific center's learnings and depend on registration precision. The aim of this study was to evaluate the accuracy of unsupervised and supervised approaches in the context of prostate MRI-to-CT generation for radiotherapy dose calculation.

A deep learning model to generate synthetic CT for prostate MR-only radiotherapy dose planning: a multicenter study.

Introduction: For radiotherapy based solely on magnetic resonance imaging (MRI), generating synthetic computed tomography scans (sCT) from MRI is essential for dose calculation. The use of deep learning (DL) methods to generate sCT from MRI has shown encouraging results if the MRI images used for training the deep learning network and the MRI images for sCT generation come from the same MRI device. The objective of this study was to create and evaluate a generic DL model capable of generating sCTs from various MRI devices for prostate radiotherapy.

Computed tomography synthesis from magnetic resonance imaging using cycle Generative Adversarial Networks with multicenter learning.

Addressing the need for accurate dose calculation in MRI-only radiotherapy, the generation of synthetic Computed Tomography (sCT) from MRI has emerged. Deep learning (DL) techniques, have shown promising results in achieving high sCT accuracies. However, existing sCT synthesis methods are often center-specific, posing a challenge to their generalizability.

Determination of acceptable Hounsfield units uncertainties via a sensitivity analysis for an accurate dose calculation in the context of prostate MRI-only radiotherapy.

Radiation therapy is moving from CT based to MRI guided planning, particularly for soft tissue anatomy. An important requirement of this new workflow is the generation of synthetic-CT (sCT) from MRI to enable treatment dose calculations. Automatic methods to determine the acceptable range of CT Hounsfield Unit (HU) uncertainties to avoid dose distribution errors is thus a key step toward safe MRI-only radiotherapy.

Automatic segmentation for plan-of-the-day selection in CBCT-guided adaptive radiation therapy of cervical cancer.

Plan-of-the-day (PoD) adaptive radiation therapy (ART) is based on a library of treatment plans, among which, at each treatment fraction, the PoD is selected using daily images. However, this strategy is limited by PoD selection uncertainties. This work aimed to propose and evaluate a workflow to automatically and quantitatively identify the PoD for cervix cancer ART based on daily CBCT images.

Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods.

The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs and their impact on dose distribution. For the analysis to be anatomically meaningful, a customized interpatient registration method brought the population data to the same coordinate system.

Monte Carlo-based software for 3D personalized dose calculations in image-guided radiotherapy.

Background And Purpose: Image-guided radiotherapy (IGRT) involves frequent in-room imaging sessions contributing to additional patient irradiation. The present work provided patient-specific dosimetric data related to different imaging protocols and anatomical sites.

Material And Methods: We developed a Monte Carlo based software able to calculate 3D personalized dose distributions for five imaging devices delivering kV-CBCT (Elekta and Varian linacs), MV-CT (Tomotherapy machines) and 2D-kV stereoscopic images from BrainLab and Accuray.

Planning With Patient-Specific Rectal Sub-Region Constraints Decreases Probability of Toxicity in Prostate Cancer Radiotherapy.

A rectal sub-region (SRR) has been previously identified by voxel-wise analysis in the inferior-anterior part of the rectum as highly predictive of rectal bleeding (RB) in prostate cancer radiotherapy. Translating the SRR to patient-specific radiotherapy planning is challenging as new constraints have to be defined. A recent geometry-based model proposed to optimize the planning by determining the achievable mean doses (AMDs) to the organs at risk (OARs), taking into account the overlap between the planning target volume (PTV) and OAR.

Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.

Purpose: Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) from CBCT to perform dose calculation.

Comparison of Deep Learning-Based and Patch-Based Methods for Pseudo-CT Generation in MRI-Based Prostate Dose Planning.

Purpose: Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) for magnetic resonance imaging (MRI) based dose planning. This study aims to evaluate and compare DLMs (U-Net and generative adversarial network [GAN]) using various loss functions (L2, single-scale perceptual loss [PL], multiscale PL, weighted multiscale PL) and a patch-based method (PBM).

Methods And Materials: Thirty-nine patients received a volumetric modulated arc therapy for prostate cancer (78 Gy).

Deformable image registration for radiation therapy: principle, methods, applications and evaluation.

Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods. Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct.

Voxel-Based Analysis for Identification of Urethrovesical Subregions Predicting Urinary Toxicity After Prostate Cancer Radiation Therapy.

Purpose: To apply a voxel-based analysis to identify urethrovesical symptom-related subregions (SRSs) associated with acute and late urinary toxicity in prostate cancer radiation therapy.

Methods And Materials: Two hundred seventy-two patients with prostate cancer treated with intensity-modulated radiation therapy/image-guided radiation therapy were analyzed prospectively. Each patient's computed tomography imaging was spatially normalized to a common coordinate system via nonrigid registration.

Pseudo-CT Generation for MRI-Only Radiation Therapy Treatment Planning: Comparison Among Patch-Based, Atlas-Based, and Bulk Density Methods.

Purpose: Methods have been recently developed to generate pseudo-computed tomography (pCT) for dose calculation in magnetic resonance imaging (MRI)-only radiation therapy. This study aimed to propose an original nonlocal mean patch-based method (PBM) and to compare this PBM to an atlas-based method (ABM) and to a bulk density method (BDM) for prostate MRI-only radiation therapy.

Materials And Methods: Thirty-nine patients received a volumetric modulated arc therapy for prostate cancer.

Statistical Shape Model to Generate a Planning Library for Cervical Adaptive Radiotherapy.

External beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over five weeks.

CBCT-guided evolutive library for cervical adaptive IMRT.

Purpose: In the context of adaptive radiation therapy (ART) for locally advanced cervical carcinoma (LACC), this study proposed an original cone-beam computed tomography (CBCT)-guided "Evolutive library" and evaluated it against four other known radiotherapy (RT) strategies.

Material And Methods: For 20 patients who underwent intensity-modulated radiation therapy (IMRT) for LACC, three planning CTs [with empty (EB), intermediate (IB), and full (FB) bladder volumes], a CT scan at 20 Gy and bi-weekly CBCTs for 5 weeks were performed. Five RT strategies were simulated for each patient: "Standard RT" was based on one IB planning CT; "internal target volume (ITV)-based RT" was an ITV built from the three planning CTs; "RT with one mid-treatment replanning (MidTtReplan)" corresponded to the standard RT with a replanning at 20 Gy; "Pretreatment library ART" using a planning library based on the three planning CTs; and the "Evolutive library ART", which was the "Pretreatment library ART" strategy enriched by including some CBCT anatomies into the library when the daily clinical target volume (CTV) shape differed from the ones in the library.

Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy.

In radiotherapy for prostate cancer irradiation of neighboring organs at risk may lead to undesirable side-effects. Given this setting, the bladder presents the largest inter-fraction shape variations hampering the computation of the actual delivered dose vs. planned dose.

Is Dose Deformation-Invariance Hypothesis Verified in Prostate IGRT?

Purpose: To assess dose uncertainties resulting from the dose deformation-invariance hypothesis in prostate cone beam computed tomography (CT)-based image guided radiation therapy (IGRT), namely to evaluate whether rigidly propagated planned dose distribution enables good estimation of fraction dose distributions.

Methods And Materials: Twenty patients underwent a CT scan for planning intensity modulated radiation therapy-IGRT delivering 80 Gy to the prostate, followed by weekly CT scans. Two methods were used to obtain the dose distributions on the weekly CT scans: (1) recalculating the dose using the original treatment plan; and (2) rigidly propagating the planned dose distribution.

The benefit of using bladder sub-volume equivalent uniform dose constraints in prostate intensity-modulated radiotherapy planning.

Background: To assess the benefits of bladder wall sub-volume equivalent uniform dose (EUD) constraints in prostate cancer intensity-modulated radiotherapy (IMRT) planning.

Methods: Two IMRT plans, with and without EUD constraints on the bladder wall, were generated using beams that deliver 80 Gy to the prostate and 46 Gy to the seminal vesicles and were compared in 53 prostate cancer patients. The bladder wall was defined as the volume between the external manually delineated wall and a contraction of 7 mm apart from it.

Interindividual registration and dose mapping for voxelwise population analysis of rectal toxicity in prostate cancer radiotherapy.

Purpose: Recent studies revealed a trend toward voxelwise population analysis in order to understand the local dose/toxicity relationships in prostate cancer radiotherapy. Such approaches require, however, an accurate interindividual mapping of the anatomies and 3D dose distributions toward a common coordinate system. This step is challenging due to the high interindividual variability.

Identification of a rectal subregion highly predictive of rectal bleeding in prostate cancer IMRT.

Background And Purpose: To identify rectal subregions at risks (SRR) highly predictive of 3-year rectal bleeding (RB) in prostate cancer IMRT.

Materials And Methods: Overall, 173 prostate cancer patients treated with IMRT/IGRT were prospectively analyzed, divided into "training" (n=118) and "validation" cohorts (n=53). Dose-volume histograms (DVHs) were calculated in three types of rectal subregions: "geometric", intuitively defined (hemi-rectum,…); "personalized", obtained by non-rigid registration followed by voxel-wise statistical analysis (SRRp); "generic", mapped from SRRps, located within 8×8 rectal subsections (SRRg).

DEMAT: A multi-institutional dosimetry audit of rotational and static intensity-modulated radiotherapy.

Purpose: Static beam intensity-modulated-radiation-therapy (IMRT) and/or Volumetric-Modulated-Arc-Therapy (VMAT) are now available in many regional radiotherapy departments. The aim of this multi-institutional audit was to design a new methodology based on radiochromic films to perform an independent quality control.

Methods: A set of data were sent to all participating centres for two clinical localizations: prostate and Head and Neck (H&N) cancers.

Quantification of dose uncertainties in cumulated dose estimation compared to planned dose in prostate IMRT.

Background And Purpose: In prostate IMRT, the objectives were to quantify, for the bladder and the rectum: (i) the dose difference (DD) between the planned dose (PD) and the estimated cumulated dose (ECD) by deformable image registration (DIR); (ii) the dose accumulation uncertainties (DAU).

Materials And Methods: A series of 24 patients receiving 80Gy in the prostate was used to calculate the ECDpts and the DDpts. To evaluate the DAU, a numerical phantom (ph) simulating deformations of main pelvic organs was used to calculate the ECDph using the same DIR method.

Roles of Deformable Image Registration in adaptive RT: From contour propagation to dose monitoring.

Adaptive radiation therapy (ART) is based on the optimization of the treatment plan during the treatment delivery to compensate for anatomical deformations. Deformable Image Registration (DIR) then constitutes a key step in order to analyze the huge amount of daily or weekly images to provide clinically usefull information. Two main applications of DIR have been developped in ART: delineation propagation and dose accumulation.