scholarly journals MRI-based Treatment Planning with Electron Density Information Mapped from CT Images: A Preliminary Study

2008 ◽  
Vol 7 (5) ◽  
pp. 341-347 ◽  
Author(s):  
C. Wang ◽  
M. Chao ◽  
L. Lee ◽  
L. Xing
Keyword(s):  
Electron Density ◽  
Radiation Treatment ◽  
Dose Calculation ◽  
Ct Images ◽  
Planar Imaging ◽  
Mr Images ◽  
Dosimetric Accuracy ◽  
Tissue Contrast ◽  
Preliminary Study ◽  
Ct Data

Nowadays magnetic resonance imaging (MRI) has been profoundly used in radiotherapy (RT) planning to aid the contouring of targets and critical organs in brain and intracranial cases, which is attributable to its excellent soft tissue contrast and multi-planar imaging capability. However, the lack of electron density information in MRI, together with the image distortion issues, precludes its use as the sole image set for RT planning and dose calculation. The purpose of this preliminary study is to probe the feasibility and evaluate an MRI-based radiation dose calculation process by providing MR images the necessary electron density (ED) information from a patient's readily available diagnostic/staging computed tomography (CT) images using an image registration model. To evaluate the dosimetric accuracy of the proposed approach, three brain and three intracranial cases were selected retrospectively for this study. For each patient, the MR images were registered to the CT images, and the ED information was then mapped onto the MR images by in-house developed software generating a modified set of MR images. Another set of MR images with voxel values assigned with the density of water was also generated. The original intensity modulated radiation treatment (IMRT) plan was then applied to the two sets of MR images and the doses were calculated. The dose distributions from the MRI-based calculations were compared to that of the original CT-based calculation. In all cases, the MRI-based calculations with mapped ED yielded dose values very close (within 2%) to that of the CT-based calculations. The MRI-based calculations with voxel values assigned with water density indicated a dosimetric error of 3–5%, depending on the treatment site. The present approach offers a means of utilizing MR images for accurate dose calculation and affords a potential to eliminate the redundant simulation CT by planning a patient's treatment with only simulation MRI and any available diagnostic/staging CT data.

Classification of methods for generating pseudo-CT from MRI images for MRI-alone RT

2017 ◽  
Vol 1 (3) ◽  
pp. 54
Author(s):  
BOUKELLOUZ Wafa ◽  
MOUSSAOUI Abdelouahab
Keyword(s):  
Performance Metrics ◽  
Radiation Treatment ◽  
Hybrid Methods ◽  
Dose Calculation ◽  
Absolute Error ◽  
Ct Images ◽  
General Technique ◽  
Therapy Field ◽  
The Brain

Background: Since the last decades, research have been oriented towards an MRI-alone radiation treatment planning (RTP), where MRI is used as the primary modality for imaging, delineation and dose calculation by assigning to it the needed electron density (ED) information. The idea is to create a computed tomography (CT) image or so-called pseudo-CT from MRI data. In this paper, we review and classify methods for creating pseudo-CT images from MRI data. Each class of methods is explained and a group of works in the literature is presented in detail with statistical performance. We discuss the advantages, drawbacks and limitations of each class of methods. Methods: We classified most recent works in deriving a pseudo-CT from MR images into four classes: segmentation-based, intensity-based, atlas-based and hybrid methods. We based the classification on the general technique applied in the approach. Results: Most of research focused on the brain and the pelvis regions. The mean absolute error (MAE) ranged from 80 HU to 137 HU and from 36.4 HU to 74 HU for the brain and pelvis, respectively. In addition, an interest in the Dixon MR sequence is increasing since it has the advantage of producing multiple contrast images with a single acquisition. Conclusion: Radiation therapy field is emerging towards the generalization of MRI-only RT thanks to the advances in techniques for generation of pseudo-CT images. However, a benchmark is needed to set in common performance metrics to assess the quality of the generated pseudo-CT and judge on the efficiency of a certain method.

scholarly journals EP-2085: Simplification of relative electron density information in synthetic CT images for dose calculation

2018 ◽  
Vol 127 ◽  
pp. S1144-S1145
Author(s):  
J. Handrack ◽  
M. Bangert ◽  
C. Möhler ◽  
T. Bostel ◽  
S. Greilich
Keyword(s):  
Electron Density ◽  
Dose Calculation ◽  
Ct Images ◽  
Relative Electron Density ◽  
Relative Electron ◽  
Synthetic Ct

Optimization of T2-weighted imaging for shoulder magnetic resonance arthrography by synthetic magnetic resonance imaging

2017 ◽  
Vol 59 (8) ◽  
pp. 959-965
Author(s):  
Seung Hyun Lee ◽  
Young Han Lee ◽  
Seok Hahn ◽  
Jaemoon Yang ◽  
Ho-Taek Song ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Supraspinatus Tendon ◽  
Joint Fluid ◽  
Resonance Imaging ◽  
Mr Images ◽  
Diagnostic Agreement ◽  
Tissue Contrast ◽  
Synthetic Images ◽  
Synthetic Mri

Background Synthetic magnetic resonance imaging (MRI) allows reformatting of various synthetic images by adjustment of scanning parameters such as repetition time (TR) and echo time (TE). Optimized MR images can be reformatted from T1, T2, and proton density (PD) values to achieve maximum tissue contrast between joint fluid and adjacent soft tissue. Purpose To demonstrate the method for optimization of TR and TE by synthetic MRI and to validate the optimized images by comparison with conventional shoulder MR arthrography (MRA) images. Material and Methods Thirty-seven shoulder MRA images acquired by synthetic MRI were retrospectively evaluated for PD, T1, and T2 values at the joint fluid and glenoid labrum. Differences in signal intensity between the fluid and labrum were observed between TR of 500–6000 ms and TE of 80–300 ms in T2-weighted (T2W) images. Conventional T2W and synthetic images were analyzed for diagnostic agreement of supraspinatus tendon abnormalities (kappa statistics) and image quality scores (one-way analysis of variance with post-hoc analysis). Results Optimized mean values of TR and TE were 2724.7 ± 1634.7 and 80.1 ± 0.4, respectively. Diagnostic agreement for supraspinatus tendon abnormalities between conventional and synthetic MR images was excellent (κ = 0.882). The mean image quality score of the joint space in optimized synthetic images was significantly higher compared with those in conventional and synthetic images (2.861 ± 0.351 vs. 2.556 ± 0.607 vs. 2.750 ± 0.439; P < 0.05). Conclusion Synthetic MRI with optimized TR and TE for shoulder MRA enables optimization of soft-tissue contrast.

scholarly journals AUTOMATIC LUNG NODULE DETECTION BASED ON STATISTICAL REGION MERGING AND SUPPORT VECTOR MACHINES

2017 ◽  
Vol 36 (2) ◽  
pp. 65 ◽  
Author(s):  
Elaheh Aghabalaei Khordehchi ◽  
Ahmad Ayatollahi ◽  
Mohammad Reza Daliri
Keyword(s):  
Lung Nodule ◽  
Three Dimensional ◽  
Pulmonary Nodules ◽  
Ct Images ◽  
Support Vector ◽  
Svm Classifier ◽  
Region Merging ◽  
Three Dimensional Objects ◽  
Ct Data ◽  
Statistical Region Merging

Lung cancer is one of the most common diseases in the world that can be treated if the lung nodules are detected in their early stages of growth. This study develops a new framework for computer-aided detection of pulmonary nodules thorough a fully-automatic analysis of Computed Tomography (CT) images. In the present work, the multi-layer CT data is fed into a pre-processing step that exploits an adaptive diffusion-based smoothing algorithm in which the parameters are automatically tuned using an adaptation technique. After multiple levels of morphological filtering, the Regions of Interest (ROIs) are extracted from the smoothed images. The Statistical Region Merging (SRM) algorithm is applied to the ROIs in order to segment each layer of the CT data. Extracted segments in consecutive layers are then analyzed in such a way that if they intersect at more than a predefined number of pixels, they are labeled with a similar index. The boundaries of the segments in adjacent layers which have the same indices are then connected together to form three-dimensional objects as the nodule candidates. After extracting four spectral, one morphological, and one textural feature from all candidates, they are finally classified into nodules and non-nodules using the Support Vector Machine (SVM) classifier. The proposed framework has been applied to two sets of lung CT images and its performance has been compared to that of nine other competing state-of-the-art methods. The considerable efficiency of the proposed approach has been proved quantitatively and validated by clinical experts as well.

scholarly journals ACTIVE INVOLVEMENT OF RADIOLOGIST IN RADIATION ONCOLOGY PRACTICE

2021 ◽  
Vol 10 (4) ◽  
pp. 3199-3201
Author(s):  
Anurag A. Luharia
Keyword(s):  
Radiation Oncology ◽  
Normal Tissue ◽  
Radiation Treatment ◽  
Imaging Modality ◽  
Tumour Volume ◽  
Target Volume ◽  
Ct Images ◽  
Radiotherapy Planning ◽  
Internal Target Volume ◽  
Radiotherapy Treatment

Advancements in Radiation Oncology from conventional to 3D conformal radiotherapy treatment demands expertise in many steps of radiation planning, the horizon of radiologist is now expanded by many folds and made radiologist as a integral part of the Radiation Oncology Department. A critical aspect of radiotherapy treatment planning (RTP) is determining how to deliver the required radiation dosage to cancer cells while minimising the exposure to normal tissue for which the prerequisite is identification and accurate delineation of tumour volume as well as normal structure resulted in an increase in the therapeutic ratio by reducing complication associated with normal tissue and allowing for higher target dosage and better local control. In modern radiotherapy CT images are the standard set of imaging modality required for the radiotherapy planning along with it many other modalities like MRI, PET or DSA are used by superimposing on original CT images in order to contour or delineate the structures defined by International Commission on Radiation Units and Measurements in Reports 50, 62 and 71 (ICRU) for radiotherapy planning which comprise of Gross tumour volume, clinical target volume, planning target volume, irradiated volume, Internal target volume and the normal structures as Organ at risk. It is self-evident that the contribution of a radiologist with a thorough knowledge of the development of these new modalities is critical for optimising the potential of these novel modes of radiation treatment delivery.

scholarly journals 454 Echo Planar Imaging on 0.5T MRI : A preliminary study

1997 ◽  
Vol 53 (8) ◽  
pp. 1323
Author(s):  
Kouzou Miyakawa ◽  
Takashi Asakura ◽  
Toshio Watanabe ◽  
Kiyotaka Nakajima ◽  
Kouki Oumi ◽  
...  
Keyword(s):  
Echo Planar Imaging ◽  
Planar Imaging ◽  
Preliminary Study ◽  
Echo Planar

Evolution of Meso-Structure of Intact Loess during Wetting

2012 ◽  
Vol 204-208 ◽  
pp. 188-191
Author(s):  
Xiang Wei Fang ◽  
Chun Ni Shen ◽  
Pei Jiang Cheng ◽  
Long Wang
Keyword(s):  
Volumetric Strain ◽  
Ct Images ◽  
Deviatoric Stress ◽  
Cell Stress ◽  
Degree Of Saturation ◽  
Triaxial Apparatus ◽  
Evolution Of Structure ◽  
Ct Data ◽  
Intact Loess

To study the evolution of meso-structure of unsaturated intact loess during wetting, a series of CT-triaxial-collapse tests were conducted using CT-multi-function triaxial apparatus. The distinct CT images and detailed CT data were attained nondestructively during wetting. A parameter and an evolution variable which characterized evolution of meso-structure were defined based CT data. An equation describing the evolution of structure during wetting was proposed. The equation reflected the influences of net cell stress, deviatoric stress and suction on the evolution of meso-structure. In the equation, volumetric strain, deviatoric strain and incremental degree of saturation are included.

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