A Method of Rapid Quantification of Patient-Specific Organ Dose for CT Using Coupled Deep-Learning based Multi-Organ Segmentation and GPU-accelerated Monte Carlo Dose Computing
Zhao Peng, Xi Fang, Pingkun Yan, Hongming Shan, Tianyu Liu, Xi Pei, Ge Wang, Bob Liu, Mannudeep K. Kalra, X. George Xu
Purpose: This paper describes a new method to apply deep-learning algorithms for automatic segmentation of radiosensitive organs from 3D tomographic CT images before computing organ doses using a GPU-based Monte Carlo code. Methods: A deep convolutional neural network (CNN) for organ segmentation is trained to automatically delineate radiosensitive organs from CT. With a GPU-based Monte Carlo dose engine (ARCHER) to derive CT dose of a phantom made from a subject's CT scan, we are then able to compute the patient-specific CT dose for each of the segmented organs. The developed tool is validated by using Relative Dose Error (RDE) against the organ doses calculated by ARCHER with manual segmentation performed by radiologists. The dose computation results are also compared against organ doses from population-average phantoms to demonstrate the improvement achieved by using the developed tool. In this study, two datasets were used: The Lung CT Segmentation Challenge 2017 (LCTSC) dataset, which contains 60 thoracic CT scan patients each with 5 segmented organs, and the Pancreas-CT (PCT) dataset, which contains 43 abdominal CT scan patients each with 8 segmented organs. Five-fold cross-validation of the new method is performed on both datasets. Results: Comparing with the traditional organ dose evaluation method that based on population-average phantom, our proposed method achieved the smaller RDE range on all organs with -4.3%~1.5% vs -31.5%~33.9% (lung), -7.0%~2.3% vs -15.2%~125.1% (heart), -18.8%~40.2% vs -10.3%~124.1% (esophagus) in the LCTSC dataset and -5.6%~1.6% vs -20.3%~57.4% (spleen), -4.5%~4.6% vs -19.5%~61.0% (pancreas), -2.3%~4.4% vs -37.8%~75.8% (left kidney), -14.9%~5.4% vs -39.9% ~14.6% (gall bladder), -0.9%~1.6% vs -30.1%~72.5% (liver), and -23.0%~11.1% vs -52.5%~-1.3% (stomach) in the PCT dataset.
In this work, we propose a Machine Learning model that generates an adjustable 3D dose distribution for external beam radiation therapy for head-and-neck cancer treatments. In contrast to existing Machine Learning methods that provide a single model, we create pairs of models for each organ-at-risk, namely lower-extreme and upper-extreme models. These model pairs for an organ-at-risk propose doses that give lower and higher doses to that organ-at-risk, while also encapsulating the dose trade-off to other organs-at-risk. By weighting and combining the model pairs for all organs-at-risk, we are …
With X-ray radiation protection and dose management constantly gaining interest in interventional radiology, novel procedures often undergo prospective dose studies using anthropomorphic phantoms to determine expected dose values. Due to inherent uncertainties, these dose values might not allow for patient-specific risk assessment. Therefore, first the aim of this study is to quantify the influence of these parameters on local X-ray dose to evaluate their relevance in the assessment of patient-specific organ doses. Second, this knowledge further enables validating a simulation approach, which …
Purpose: To obtain individualized internal doses with a Monte Carlo method in patients undergoing diagnostic FCH-PET studies and to compare such doses with the MIRD method calculations. Methods: A patient cohort of 17 males were imaged after intravenous administration of a mean FCH activity of 244.3 MBq. The resulting PET/CT images were processed in order to generate individualized input source and geometry files for dose computation with the MC tool GATE. The resulting dose estimates were studied and compared to the MIRD method with two different computational phantoms. Mass correction of the…
Recently, Yamashita et al. reported direct measurements of ionizing radiation doses to individual organs in postmortem (using OSL dosimetry) that were exposed in the most frequent clinical CT scan protocols, corresponding to the whole body, head, thorax and abdomen. The authors compare the experimental results with the values calculated in the Waza-AriV2 software, which is a system based on the MonteCarlo method that performs the estimation of organ doses from the exposure parameters used in the CT equipment. However, the results of the absorbed doses calculated in each examination had signifi…
An intercomparison exercise is described that examines Monte Carlo modelling of anthropomorphic voxel phantoms in an idealized ground-contamination photon exposure scenario. Thirteen participants calculated and submitted organ and effective dose rates for comparison against a set of verified reference solutions. The effective dose rates are shown to agree with the reference value to within reasonable statistical uncertainties in five of the cases, though in only one of those was similar agreement also demonstrated in the evaluation of all requested organ dose rates. Orders-of-magnitude differe…
Cone beam CT (CBCT) has been widely used for patient setup in image guided radiation therapy (IGRT). Radiation dose from CBCT scans has become a clinical concern. The purposes of this study are 1) to commission a GPU-based Monte Carlo (MC) dose calculation package gCTD for Varian On-Board Imaging (OBI) system and test the calculation accuracy, and 2) to quantitatively evaluate CBCT dose from the OBI system in typical IGRT scan protocols. We first conducted dose measurements in a water phantom. X-ray source model parameters used in gCTD are obtained through a commissioning process. gCTD accurac…
A new set of fluence-to-dose conversion coefficients based on the Chinese reference adult voxel phantoms CRAM and CRAF are presented for six idealized external neutron exposures from 10-8 MeV to 20 MeV. The voxel phantoms CRAM and CRAF were adjusted from the previous phantoms CNMAN and CNWM respectively, and the masses of individual organs have been adjusted to the Chinese reference data. The calculation of organ-absorbed doses and effective doses were performed with the Monte Carlo transport code MCNPX. The resulting dose conversion coefficients were compared with those published in ICRP Publ…
CD16 is a MATLAB-based dosimetry system designed for rapid estimation of organ doses for x-ray guided cardiac catheterization procedures. CD16 is principally designed for epidemiological studies in which dose estimates are required for thousands of cohort members, often based on limited exposure information. The minimum data required for dose estimates are (1) total examination kerma area product (PKA), (2) patient size (age or mass), (3) x-ray spectrum represented by half value layer (HVL, in mm Al) and (4) examination type. These data can be inputted using an Excel spreadsheet. Organ dose es…
The high precision and conformity of intensity-modulated particle therapy (IMPT) comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, however becomes challenging when computing the dose with computationally expensive but accurate Monte Carlo (MC) simulations. This paper introduces an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of …
This work summarises the results of a comparison organized by EURADOS focused on the usage of the ICRP Reference Computational Phantoms. This activity aimed to provide training for the implementation of voxel phantoms in Monte Carlo radiation transport codes and the calculation of the dose equivalent in organs and the effective dose. This particular case describes a scenario of immersion in a 16N beta source distributed in the air of a room with concrete walls where the phantom is located. Seven participants took part in the comparison of results using GEANT4, TRIPOLI-4 and MCNP family codes, …
The area of interests of nuclear physics are studies of reactions, wherein atomic nuclei of projectile collide with target nuclei. An amount of energy lost by projectile nucleus during its passing through the target is a major issue - it is important to know how charged particles interact with matter. It is possible to afford this knowledge by using theoretical programs, which calculate energy loss applying Bethe-Bloch equation. Hadrontherapy, which is a field of still growing interest, is based on interactions of charged particles with matter. Therefore exists a need of creating a simple mode…
SPECT imaging is one of the common modalities used to examine kidney disease. The radiopharmaceuticals such as 99mTc-MAG3, 99mTc-DTPA, and 99mTc-DMSA are commonly employed for pediatric patients. It is generally accepted that children organs are more sensitive to radiation than adults, due to their growth rate. Therefore, evaluating the absorbed dose in children to avoid irrecoverable damage is highly crucial. In this work, absorbed dose by different organs of children within the SPECT imaging for the above-mentioned radiopharmaceuticals were estimated through the use of Monte Carlo simulation…
Purpose: To verify dose delivery and quality assurance of volumetric modulated arc therapy (VMAT) for head and neck cancer. Method: The Imaging and Radiation Oncology Core Houston (IROC-H) head and neck phantom with thermo- luminescent dosimeters (TLDs) and films, were imaged with computed tomography scan and the reconstructed image was transferred to pinnacle treatment planning system (TPS). On TPS the planning target volume (PTV), secondary target volume (STV) and organ at risk (OAR) were delineated manually and a treatment plan was made. The dose constraints were determined for the concerne…
Amsterdam UMC, University of Amsterdam（阿姆斯特丹大学阿姆斯特丹大学医学中心）；University Medical Center Utrecht（乌得勒支大学医学中心）；Princess Màxima Center for Pediatric Oncology（玛克西玛公主儿科肿瘤中心）；Princess Margaret Cancer Centre（玛格丽特公主癌症中心）
To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, thus 3D dose distributions must be reconstructed from limited information. State-of-the-art methods achieve this by using 3D surrogate anatomies. These can lack personalization and lead to coarse reconstructions. We present and validate a surrogate-free dose reconstruction method based on Machine Learning (ML). Abdominal planning CTs ($n$=142) of rec…
Dose distribution (depthwise and laterally) to organs outside the radiotherapy treatment field can be significant and therefore is of clinical interest from the radiation protection point of view. In the present work, measurements were performed in a locally fabricated polystyrene phantom using TLD chips (LiF-100) for different teletherapy units (Cobalt-60 gamma ray, 120 kVp X-ray and 250 kVp X-ray) to estimate the dose distribution at distances up to 40 cm from the field edge along the central axes of the field size. Finally, the dose distribution for Cobalt-60 beam energy is parameterized as…
This paper describes the development and validation of a Monte Carlo (MC) dose computing module dedicated to organ dose calculations of patients undergoing nuclear medicine (NM) internal radiation exposures involving 18F-FDG PET/CT examination. This new module extends the more-than-10-years-long ARCHER project that developed a GPU-accelerated MC dose engine by adding dedicated NM source-definition features. To validate the code, we compared dose distributions from the 0.511-MeV point photon source calculated for a water phantom as well as a patient PET/CT phantom against a well-tested MC code,…
Dose volume histograms are a useful tool in state-of-the-art radiotherapy planning, and it is essential to be aware of their limitations. Dose distributions computed by treatment planning systems are affected by several sources of uncertainty such as algorithm limitations, measurement uncertainty in the data used to model the beam and residual differences between measured and computed dose, once the model is optimized. In order to take into account the effect of uncertainty, a probabilistic approach is proposed and a new kind of histogram, a dose-expected volume histogram, is introduced. The e…
Fluence map optimization for intensity-modulated radiation therapy planning can be formulated as a large-scale inverse problem with competing objectives and constraints associated with the tumors and organs-at-risk. Unfortunately, clinically relevant dose-volume constraints are nonconvex, so standard algorithms for convex problems cannot be directly applied. While prior work focused on convex approximations for these constraints, we propose a novel relaxation approach to handle nonconvex dose-volume constraints. We develop efficient, provably convergent algorithms based on partial minimization…
Fast and accurate predictions of uncertainties in the computed dose are crucial for the determination of robust treatment plans in radiation therapy. This requires the solution of particle transport problems with uncertain parameters or initial conditions. Monte Carlo methods are often used to solve transport problems especially for applications which require high accuracy. In these cases, common non-intrusive solution strategies that involve repeated simulations of the problem at different points in the parameter space quickly become infeasible due to their long run-times. Intrusive methods h…
University of Texas Southwestern Medical Center（德克萨斯大学西南医学中心）
The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the target. Treatment planning for this site requires a high level of human expertise and a tremendous amount of effort to produce personalized high quality plans, taking as long as a week, which deteriorates the chances of tumor control and patient survival. To solve this problem, we propose to investigate a deep learning-based dose prediction model, Hierarchic…
Objective: This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or digital-twins (DT) using patient medical images. The framework is applied to assess radiation dose to radiosensitive organs in CT imaging of individual patients. Method: From patient CT images, iPhantom segments selected anchor organs (e.g. liver, bones, pancreas) using a learning-based model developed for multi-organ CT segmentation. Organs challenging to segment (e.g. intestines) are incorporated from a matched phantom template, using a diffeomorphic registra…
Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present an atlas-based approach which learns a dose prediction model for each patient (atlas) in a training database, and then learns to match novel patients to the most relevant atlases. The method creates a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces any requirement for specifying dose-volume objectives for conveying the goals of tr…
A standard dose of radioactive tracer must be delivered into the patients body to obtain high-quality Positron Emission Tomography (PET) images for diagnostic purposes, which raises the risk of radiation harm. A reduced tracer dose, on the other hand, results in poor image quality and a noise-induced quantitative bias in PET imaging. The partial volume effect (PVE), which is the result of PET intrinsic limited spatial resolution, is another source of quality and quantity degradation in PET imaging. The utilization of anatomical information for PVE correction (PVC) is not straightforward due to…
Verification, Validation, and Uncertainty Quantification (VVUQ) of Physiologically Based Pharmacokinetic Models for Theranostic Digital Twins: Towards Reliable Model-Informed Treatment Planning for Radiopharmaceutical Therapies
Purpose: Radiation therapy treatment planning is a trial-and-error, often time-consuming process. An optimal dose distribution based on a specific anatomy can be predicted by pre-trained deep learning (DL) models. However, dose distributions are often optimized based on not only patient-specific anatomy but also physician preferred trade-offs between planning target volume (PTV) coverage and organ at risk (OAR) sparing. Therefore, it is desirable to allow physicians to fine-tune the dose distribution predicted based on patient anatomy. In this work, we developed a DL model to predict the indiv…
In a treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. To answer questions related to this problem, we establish in this work a new mathematical framework equipped with two theorems. The new framework clarifies the different consequences of adjusting organ-dependent …
PURPOSE: Permanent breast seed implant (PBSI) using 103Pd is emerging as an effective adjuvant radiation technique for early-stage breast cancer. However, clinical dose evaluations follow the water-based TG-43 approach with its considerable approximations. Towards clinical adoption of advanced TG-186 model-based dose evaluations, this study presents a comprehensive investigation for PBSI considering both target and normal tissue doses. METHODS: Dose calculations are performed with the free open-source Monte Carlo (MC) code, egs_brachy, using 2 types of virtual patient models: TG43sim (simulate…
Background: The deep inspiration breath hold technique (DIBH) is widely used for left-sided breast radiotherapy (RT), in order to reduce the dose to the heart and the risk of cardiotoxicity. The volumetric arc therapy (VMAT) technique increases the dose conformity to the planning target volume (PTV). We hereby describe the procedure of combining VMAT and DIBH without a dedicated equipment, and report a dosimetric study related on our implemented technique. Methods: The DIBH technique is based on voluntary breath hold of the patient which is controlled by a laser on tattoo marks. Patients were …
With increasing patient and staff X-ray radiation awareness, many efforts have been made to develop accurate patient dose estimation methods. To date, Monte Carlo (MC) simulations are considered golden standard to simulate the interaction of X-ray radiation with matter. However, sensitivity of MC simulation results to variations in the experimental or clinical setup of image guided interventional procedures are only limited studied. In particular, the impact of patient material compositions is poorly investigated. This is mainly due to the fact, that these methods are commonly validated in pha…
UT Southwestern Medical Center（德克萨斯大学西南医学中心）；University of Texas Southwestern Medical Center（德克萨斯大学西南医学中心）
Inter-observer variation is a significant problem in clinical target volume(CTV) segmentation in postoperative settings, where there is no gross tumor present. In this scenario, the CTV is not an anatomically established structure, but one determined by the physician based on the clinical guideline used, the preferred tradeoff between tumor control and toxicity, their experience and training background, and other factors. This results in high inter-observer variability between physicians. This variability has been considered an issue, but the absence of multiple physician CTV contours for each…
The diverse near-Earth radiation environment due to cosmic rays and solar radiation has direct impact on human civilization. In the present and upcoming era of increasing air transfer, it is important to have precise idea of radiation dose effects on human body during air travel. Here, we calculate the radiation dose on the human body at the aviation altitude, also considering the shielding effect of the aircraft structure, using Monte Carlo simulation technique based on Geant4 toolkit. We consider proper 3D mathematical model of the atmosphere and geomagnetic field, updated profile of the inc…
Medical Center – University of Freiburg（弗莱堡大学医学中心）；University of Freiburg（弗莱堡大学）
Stereotactic body radiation therapy allows for a precise and accurate dose delivery. Organ motion during treatment bears the risk of undetected high dose healthy tissue exposure. An organ very susceptible to high dose is the oesophagus. Its low contrast on CT and the oblong shape renders motion estimation difficult. We tackle this issue by modern algorithms to measure the oesophageal motion voxel-wise and to estimate motion related dosimetric impact. Oesophageal motion was measured using deformable image registration and 4DCT of 11 internal and 5 public datasets. Current clinical practice of c…
In this study, two proton beam delivery designs, passive scattering proton therapy (PSPT) and pencil beam scanning (PBS), were quantitatively compared in terms of dosimetric indices. The GATE Monte Carlo code was used to simulate the proton beam system; and the developed simulation engines were benchmarked with respect to the experimental measurements. A water phantom was used to simulate system energy parameters using a set of depth-dose data in the energy range of 120-235 MeV. To compare the performance of PSPT against PBS, multiple dosimetric parameters including FWHM, peak position, range,…
The specific absorbed fractions (SAF) for self- and cross-irradiation are effective tools for the internal dose estimation of inhalation and ingestion intakes of radionuclides. A set of SAFs of photon and electron were calculated using the Rad-HUMAN phantom, a computational voxel phantom of Chinese adult female and created using the color photographic image of the Chinese Visible Human (CVH) data set. The model can represent most of Chinese adult female anatomical characteristics and can be taken as an individual phantom to investigate the difference of internal dose with Caucasians. In this s…
Focal-point scanning for dose delivery and optimization with focused laser-accelerated very-high-energy electron beams
Zhengzhou University（郑州大学）；Tsinghua University（清华大学）；Microsoft Research, AI for Science（微软研究院 AI for 科学）；The First Affiliated Hospital of Zhengzhou University（郑州大学第一附属医院）；University of Michigan, Ann Arbor（密歇根大学安娜堡分校）；National Institute of Metrology（中国计量科学研究院）
Radiotherapy treatment planning currently requires many trail-and-error iterations between the planner and treatment planning system, as well as between the planner and physician for discussion/consultation. The physician's preferences for a particular patient cannot be easily quantified and precisely conveyed to the planner. In this study we present a real-time volumetric Pareto surface dose generation deep learning neural network that can be used after segmentation by the physician, adding a tangible and quantifiable end-point to portray to the planner. From 70 prostate patients, we first ge…
University of Texas Southwestern Medical Center（德克萨斯大学西南医学中心）
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 (originally designed for segmentation purposes), for predicting dose from patient image contours of the planning target volume (PTV) and organs at risk (OAR). We show that, as an example, we are able…
