Derek D'Souza's research while affiliated with University College London Hospitals NHS Foundation Trust and other places
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Publications (22)
Objectives:
To identify variables predicting inter fractional anatomical variationsmeasured with cone-beam CT (CBCT) throughout abdominal paediatric radiotherapy, and to assess the potential of surface-guided radiotherapy (SGRT) to monitor these changes.
Methods:
Metrics of variation in gastrointestinal (GI) gas volume andseparation of the body...
Adaptive radiotherapy workflows require images with the quality of computed tomography
(CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve quality of
cone beam CT (CBCT) images for dose calculation using deep learning.
Approach: We propose a novel framework for CBCT-to-CT synthesis using cycle-consistent G...
Background
Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introducing interoperator variability, resulting in down...
Background and Purpose
State-of-the-art radiotherapy modalities have the potential of reducing late effects of treatment in childhood cancer survivors. Our aim was to investigate the carcinogenic risk associated with 3D conformal (photon) radiation (3D-CRT), intensity modulated arc therapy (IMAT) and pencil beam scanning proton therapy (PBS-PT) in...
Reducing radiation-induced side effects is one of the most important challenges in paediatric cancer treatment. Recently, there has been growing interest in using spatial normalisation to enable voxel-based analysis of radiation-induced toxicities in a variety of patient groups. The need to consider three-dimensional distribution of doses, rather t...
We proposed a CBCT-to-CT synthesis framework tailored for paediatric abdominal patients. Our approach was based on the cycle-consistent generative adversarial network (cycleGAN) modified to preserve structural consistency. To adjust for differences in field-of-view and body size from different patient groups, our training data was spatially co-regi...
BACKGROUND
Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introducing interoperator variability, resulting in down...
Purpose:
In pencil beam scanning proton therapy, target coverage is achieved by scanning the pencil beam laterally in the x- and y-directions and delivering spots of dose to positions at a given radiological depth (layer). Dose is delivered to the spots on different layers by pencil beams of different energy until the entire volume has been irradi...
Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manually intensive delineation of radiosensitive organs at risk (OARs). This planning process can delay treatment commencement. While auto-segmentation algorithms offer a pote...
Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manually intensive delineation of radiosensitive organs at risk (OARs). This planning process can delay treatment commencement. While auto-segmentation algorithms offer a pote...
Introduction:
Changes in lung architecture during a course of radiotherapy can alter the planned dose distribution to the extent that it becomes clinically unacceptable. This study aims to validate a quantitative method of determining whether a replan is required during the course of conformal radiotherapy. The proposed method uses deformable imag...
Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion t...
Theoretical stopping power values were inter-compared for the Bichsel, Janni, ICRU and Schneider relative stopping power (RSP) estimation models, for a variety of tissues and tissue substitute materials taken from the literature. The RSPs of eleven plastic tissue substitutes were measured using Bragg peak shift measurements in water in order to est...
Radiotherapy is one of the main ways head and neck cancers are treated; radiation is used to kill cancerous cells and prevent their recurrence.
Complex treatment planning is required to ensure that enough radiation is given to the tumour, and little to other sensitive structures (known as organs at risk) such as the eyes and nerves which might oth...
The aim of this study was to assess whether clinically acceptable segmentations of organs at risk (OARs) in head and neck cancer can be obtained automatically and efficiently using the novel "similarity and truth estimation for propagated segmentations" (STEPS) compared to the traditional "simultaneous truth and performance level estimation" (STAPL...
We present simulations and measurements of Cerenkov optical radiation in electron and proton radiotherapy. Photographs of Cerenkov emission from electrons can predict the range to ±1.5mm, but underestimate superficial dose.
A new potential quality assurance (QA) method is explored (including assessment of depth dose, dose linearity, dose rate linearity and beam profile) for clinical electron beams based on imaging Cerenkov light. The potential of using a standard commercial camera to image Cerenkov light generated from electrons in water for fast QA measurement of a c...
The aim of this study was to evaluate the appropriateness of using computed tomography (CT) to cone-beam CT (CBCT) deformable image registration (DIR) for the application of calculating the "dose of the day" received by a head and neck patient.
NiftyReg is an open-source registration package implemented in our institution. The affine registration u...
The standard European radiotherapy technique for children with neuroblastoma is a conventional parallel opposed pair. This frequently results in compromise on planning target volume coverage to stay within normal tissue tolerances. This study investigates the use of an intensity-modulated arc therapy (IMAT) technique to improve dose distribution an...
This study tested the principle that (68)Ga-DOTATATE PET/CT may be used to select children with primary refractory or relapsed high-risk neuroblastoma for treatment with (177)Lu-DOTATATE and evaluated whether this is a viable therapeutic option for those children.
Between 2008 and 2010, 8 children with relapsed or refractory high-risk neuroblastoma...
Citations
... Due to the inaccuracy of the CT numbers, the use of CBCT has been limited to assisting with daily patient setup. Various methods of utilizing CBCTs for plan recalculation have been explored, such as deforming the planning CT to the CBCT using deformable image registration [20][21][22][23][24][25][26][27], scatter correction methods [26,28,29], image correction utilizing deep convolution neural networks (DCNN) [27,[30][31][32], histogram matching [33], and corrections via look-up tables [25]. In this study, we propose a CBCT-based dose monitoring and adaptive planning trigger process for head and neck adaptive proton therapy, allowing for more frequent dose verifications and the ability to recognize changes in both anatomy and setup geometry. ...
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... The chosen tolerance allows a maximum distance between surface voxels on the reference and predicted masks to be considered true positive voxels. We use this metric to account for possible pathophysiological and modality-related lower signals that cause more variability in the outer compared to the inner region of the ischemic stroke [31,32]. ...
... The corresponding dimensions for the female phantom were 1627 mm and 66 kg. The XCAT phantoms have already been used for treatment planning and dosimetric purposes in radiation therapy [10][11][12]. ...
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... The atlas was obtained from a groupwise registration which spatially normalized a cohort of patients [1]1 . 16,31 In the procedure of the projection, the planning CT (pCT) of each patient was the reference geometry, and the CT acquired during the first treatment week (CT t ) was registered to the pCT to produce v v v p→t , where p stands for pCT and t stands for the week (in this case t = 1) when the weekly CT acquired. Then, each patient's pCT was registered to the atlas to pro- ...
... In the proton scenario, Alshaikhi et al. [125] tested the effect of varying planning parameters on pencil beam scanning dose distributions of four proton TPSs: Eclipse, Pinnacle, RayStation and XiO. An investigation was made into the implementation and optimal selection of different proton planning parameters by each system. ...
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... The Lung-RadOnc and Lung-AI contours were compared against the reference Lung-Manual contours using Dice similarity coefficient (DSC) and Surface Dice similarity coefficient (SD) [40], Average Surface Distance (ASD), and 95% Hausdorff distance (HD95). DSC is commonly used for segmentation evaluation, but DSC is volume-based contour evaluator, which might not be sensitive to evaluate the differences between advanced lung contours and standard thoracic treatment planning contours. ...
... More accurate information of the actual dose delivered for a given fraction could help establish better decision making criteria in clinical practice. Developments in the field of automatic contouring, deformable registration, synthetic CT, dose summation and autoplanning play a role in simplifying and improving this decision making process by providing quicker and more accurate information about the dose distribution [19][20][21][22][23]. ...
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... Image registration has been widely implemented in many tasks. For example, image guidance [254][255][256][257][258][259][260], image segmentation [261][262][263], dose accumulation [264][265][266][267], image reconstruction [268][269][270][271] and so on. There are some reviews and surveys specific to image registration in medical image analysis [253,[272][273][274]. We will list the weakly supervised learning-based registration works in the remaining part of this section. ...
Reference: Weakly supervised machine learning
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... In contrast, the RSP calculation is affected by the I-values. For example, Doolan et al. (2016) showed that the root-mean-square error of RSP based on equation (4) are reportedly accurate to 2% (Ziegler 1980). Therefore, we used 2% as the RSP error. ...
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... Beispielsweise kann KI Zielzonen für die Kopf-Hals-Strahlentherapie genauer und viel schneller berechnen als ein Mensch. Die KI spielt eine wichtige Hintergrundrolle beim Schutz des Patienten vor schädlicher Strahlung, jedoch ist ein Radiologe letztendlich immer noch für die Durchführung der Therapie verantwortlich [271]. Ähnliches könnte in biomechanischen Kontexten denkbar sein. ...
