Computed Tomography Reference Research Articles

Comparative Diagnostic Accuracy of Computed Tomography Scan versus Magnetic Resonance Imaging in the Emergency Department for the Evaluation of Dizziness: A Systematic Review.

Introduction Both computed tomography (CT) and magnetic resonance imaging (MRI) play significant roles in assessing patients with dizziness. However, understanding the comparative capabilities of these imaging methods in detecting pathological causes is crucial for determining the most suitable modality. This review aims to evaluate the diagnostic accuracy and clinical utility of MRI and CT scans in managing patients with acute dizziness in the emergency department. Methods Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a comprehensive search in various databases (PubMed, Google Scholar, Cochrane library, British Medical Journals, and ScienceDirect) from 2010 to 2023. We used the QUADAS-2 tool to assess bias risk, considering MRI as the reference standard and CT scan as the index test. Results The final analysis included six studies, with 3,993 patients (48% male, 52% female; average age: 56.7 years). Three studies were of high quality, two of medium quality, and one of low quality. Central ischemia was the predominant diagnosis for dizziness. MRI demonstrated higher diagnostic efficacy for stroke compared with CT scans, while mixed results were observed for other multiple diseases when both MRI and CT scans were used. Conclusion MRI outperforms CT scans in diagnosing dizziness-related strokes. However, for other causes of dizziness, there is no significant difference between these techniques. Nevertheless, it is crucial to acknowledge the limitations associated with MRI. Consequently, to address these concerns, the selection of an imaging technique should be tailored to the individual based on factors such as their clinical presentation, comorbidities, and socioeconomic circumstances.

Novel simulation for dosimetry impact of diaphragm respiratory motion in four-dimensional volumetric modulated arc therapy for esophageal cancer

Background and purposeThe diaphragm respiratory motion (RM) could impact the target dose robustness in the lower esophageal cancer (EC). We aimed to develop a framework evaluating the impact of different RM patterns quantitatively in one patient, by creating virtual four-dimensional computed-tomography (v4DCT) images, which could lead to tailored treatment for the breathing pattern. We validated virtual 4D radiotherapy (v4DRT) along with exploring the acceptability of free-breathing volumetric modulated arc therapy (FB-VMAT). Methods and MaterialsWe assessed 10 patients with superficial EC through their real 4DCT (r4DCT) scans. v4DCT images were derived from the end-inhalation computed tomography (CT) image (reference CT) and the v4DRT dose was accumulated dose over all phases. r4DRT diaphragm shifts were applied with magnitudes derived from r4DCT scans; clinical target volume (CTV) dose of v4DRT was compared with that of r4DRT to validate v4DRT. CTV dosage modifications and planning organ at risk volume (PRV) margins of the spinal cord were examined with the diaphragm movement. The percentage dose differences (ΔDx) were determined between the v4DRT and the dose calculated on the reference CT image. ResultsThe CTV ΔDx between the r4DRT and v4DRT were within 1% in cases with RM ≦ 15 mm. The average ΔD100% and ΔDmean of the CTV ranging from 5 to 15 mm of diaphragm motion was 0.3% to 1.7% and 0.1% to 0.4%, respectively. All CTV index changes were within 3% and ΔD1cc and ΔD2cc of Cord PRV were within 1%. ConclusionWe postulate a novel method for evaluating the CTV robustness, comparable to the conventional r4DCT method under the diaphragm RM ≦ 15 mm permitting an impact of within 3% in FB-VMAT for EC on the CTV dose distribution.

X-ray Computed Tomography Inspection of Novel Ceramic Matrix Composites

Novel Ceramic Matrix Composites (CMCs) offer the promise of more highly performing structures, especially in aerospace applications, due to their excellent mechanical properties at elevated temperatures with respect to their density and their corrosion resistance. However, the development of such materials requires careful characterisation, and any deployment on an aircraft necessitates an appropriate nondestructive testing capability. This work sought to deploy and refine the method of Xray Computed Tomography (CT) in aid of the development of a novel CMC and subsequent deployment in a flying component. The target application was part of the exhaust system of a civil aircraft’s auxiliary power unit. The work included material characterisation at coupon-level, as well as technique development with a view towards the target application. For the former, high-resolution scans were performed in a range of configurations, including during tensile testing, to provide an understanding of microstructure and failure behaviour. For the latter, novel system configurations were explored to try to deal with the challenge of a large, thin-walled structure. Additionally, alternative or complimentary non-X-ray testing methods were trialled, notably including terahertz (THz) imaging. The material characterisation demonstrated the potential for the novel material to meet the requirements of the application. The terahertz imaging in a through transmission configuration was the most capable of the non-radiographic methods tested, providing an image that correlated very well with the reference CT scan, whilst the system development efforts yielded a configuration optimised for this class of 3D X-ray imaging applications.

Lung Nodule Detection With Modern Low-Field MRI (0.55 T) in Comparison to CT.

The aim of this study was to evaluate the accuracy of modern low-field magnetic resonance imaging (MRI) for lung nodule detection and to correlate nodule size measurement with computed tomography (CT) as reference. Between November 2020 and July 2021, a prospective clinical trial using low-field MRI at 0.55 T was performed in patients with known pulmonary nodules from a single academic medical center. Every patient underwent MRI and CT imaging on the same day. The primary aim was to evaluate the detection accuracy of pulmonary nodules using MRI with transversal periodically rotated overlapping parallel lines with enhanced reconstruction in combination with coronal half-Fourier acquired single-shot turbo spin-echo MRI sequences. The secondary outcome was the correlation of the mean lung nodule diameter with CT as reference according to the Lung Imaging Reporting and Data System. Nonparametric Mann-Whitney U test, Spearman rank correlation coefficient, and Bland-Altman analysis were applied to analyze the results. A total of 46 participants (mean age ± SD, 66 ± 11 years; 26 women) were included. In a blinded analysis of 964 lung nodules, the detection accuracy was 100% for those ≥6 mm (126/126), 80% (159/200) for those ≥4-<6 mm, and 23% (147/638) for those <4 mm in MRI compared with reference CT. Spearman correlation coefficient of MRI and CT size measurement was r = 0.87 ( P < 0.001), and the mean difference was 0.16 ± 0.9 mm. Modern low-field MRI shows excellent accuracy in lesion detection for lung nodules ≥6 mm and a very strong correlation with CT imaging for size measurement, but could not compete with CT in the detection of small nodules.

Comparison of diagnostic quality of 3D ultrashort-echo-time techniques for pulmonary magnetic resonance imaging in free-breathing.

Ultrashort-echo-time (UTE) sequences have been developed to overcome technical limitations of pulmonary magnetic resonance imaging (MRI). Recently, it has been shown that UTE sequences with breath-hold allow rapid image acquisition with sufficient image quality. However, patients with impaired respiration require alternative acquisition strategies while breathing freely. To compare the diagnostic performance of free-breathing three-dimensional (3D)-UTE sequences with different trajectories based on pulmonary imaging of immunocompromised patients. In a prospective study setting, two 3D-UTE sequences performed in free-breathing and exploiting non-Cartesian trajectories-one using a stack-of-spirals and the other exploiting a radial trajectory-were acquired at 3 T in patients undergoing hematopoietic stem cell transplantation. Two radiologists assessed the images regarding presence of pleural effusions and pulmonary infiltrations. Computed tomography (CT) was used as reference. A total of 28 datasets, each consisting of free-breathing 3D-UTE MRI with the two sequence techniques and a reference CT scan, were acquired in 20 patients. Interrater agreement was substantial for pulmonary infiltrations using both sequence techniques (κ = 0.77 - 0.78). Regarding pleural effusions, agreement was almost perfect in the stack-of-spirals (κ = 0.81) and moderate in the radial sequence (κ = 0.59). No significant differences in detectability of the assessed pulmonary pathologies were observed between both 3D-UTE sequence techniques (P > 0.05), and their level of agreement was substantial throughout (κ = 0.62-0.81). Both techniques provided high sensitivities and specificities (79%-100%) for the detection of pulmonary infiltrations and pleural effusions compared to reference CT. The diagnostic performance of the assessed 3D-UTE MRI sequences was similar. Both sequences enable the detection of typical inflammatory lung pathologies.

Distortion verification of helical computed tomography for image-guided radiotherapy

Abstract Introduction: In image-guided radiotherapy (IGRT), the imaging conditions of computed tomography (CT) may impact the positioning uncertainty, but verification methods are currently unavailable. This study aimed to propose a validation method for the imaging conditions of helical CT for IGRT. Predicting the impact of image distortion on image guidance may reduce uncertainty in radiotherapy planning. Methods: Image guidance was performed on the reference images of four Duracon balls by changing the imaging conditions and the positions on the CT images by helical scanning. The predictors of image guidance error and those of the contour mismatch between the reference and cone-beam CT (CBCT) images were analysed. Results: The image guidance error exceeded 1 mm when the contour centre of the ball was shifted by more than 1 mm. The mismatch between the contours of the reference and CBCT images occurred with the imaging conditions wherein the first slice of the ball was distorted. Conclusions: Mismatch can be predicted by the coefficient of variation of the radii in the first and centre slices of the ball. Moreover, the image guidance error can be predicted by the contour centre shift of the ball.

A Method Noise-Based Convolutional Neural Network Technique for CT Image Denoising

Medical imaging is a complex process that capitulates images created by X-rays, ultrasound imaging, angiography, etc. During the imaging process, it also captures image noise during image acquisition, some of which are extremely corrosive, creating a disturbance that results in image degradation. The proposed work addresses the challenge to eliminate the corrosive Gaussian additive white noise from computed tomography (CT) images while preserving the fine details. The proposed approach is synthesized by amalgamating the concept of method noise with a deep learning-based framework of a convolutional neural network (CNN). The corrupted images are obtained by explicit addition of Gaussian additive white noise at multiple noise variance levels (σ = 10, 15, 20, 25). The denoised images obtained are then evaluated according to their visual quality and quantitative metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). These metrics for denoised CT images are then compared with their respective values for the reference CT image. The average PSNR value of the proposed method is 25.82, the average SSIM value is 0.85, and the average computational time is 2.8760. To better understand the proposed approach’s effectiveness, an intensity profile of denoised and original medical images is plotted and compared. To further test the performance of the proposed methodology, the results obtained are also compared with that of other non-traditional methods. The critical analysis of the results shows the commendable efficiency of the proposed methodology in denoising the medical CT images corrupted by Gaussian noise. This approach can be utilized in multiple pragmatic areas of application in the field of medical image processing.

Computed tomography reference dimensions for identification of stented surgical mitral bioprostheses valve size

BackgroundSelection of the transcatheter heart valve size for a mitral valve-in-valve procedure is based on the type and manufacturer’s labelled size. However, accurate information of surgical heart valve (SHV) size may not be available in the patient’s medical record. The purpose of this study is to establish reference data for computed tomography (CT) dimensions of commonly used mitral SHV in order to determine the manufacturer’s labelled size from a cardiac CT data set. MethodsCT datasets of 105 patients with surgical mitral bioprosthesis and available manufacturer labeled datasets were included in the analysis. CT derived valve dimensions were assessed by two observers using multiplanar reformats aligned with the basal sewing ring. A circular region of interest was used in a standardized fashion to minimize influence of image acquisition and reconstruction parameters. Interobserver variability was assessed by Bland-Altman analysis. ResultsThe CT-derived dimensions were stratified by valve size and type, and SHV properties were demonstrated for 5 common valve types. Variability of measurements was small and inter-observer limits of agreement were narrow. Stratified by SHV type, no overlap was noted for CT-derived dimensions among different SHV sizes . A reference table of CT characteristics of surgical mitral bioprosthesis types was created. ConclusionThe study provides reference CT data for determining the manufacturers’ labeled SHV size across a range of commonly used mitral SHVs. The findings will be important to help identify types of surgical mitral bioprosthesis utilizing CT characteristics for patients without SHV size documentation.

Contemporary image-guided cervical cancer brachytherapy: Consensus imaging recommendations from the Society of Abdominal Radiology and the American Brachytherapy Society

To present recommendations for the use of imaging for evaluation and procedural guidance of brachytherapy for cervical cancer patients. An expert panel comprised of members of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease Focused Panel and the American Brachytherapy Society jointly assessed the existing literature and provide data-driven guidance on imaging protocol development, interpretation, and reporting. Image-guidance during applicator implantation reduces rates of uterine perforation by the tandem. Postimplant images may be acquired with radiography, computed tomography (CT), or magnetic resonance imaging (MRI), and CT or MRI are preferred due to a decrease in severe complications. Pre-brachytherapy T2-weighted MRI may be used as a reference for contouring the high-risk clinical target volume (HR-CTV) when CT is used for treatment planning. Reference CT and MRI protocols are provided for reference. Image-guided brachytherapy in locally advanced cervical cancer is essential for optimal patient management. Various imaging modalities, including orthogonal radiographs, ultrasound, computed tomography, and magnetic resonance imaging, remain integral to the successful execution of image-guided brachytherapy.

Laryngeal dysplasia: Computed tomographic findings in an Oldenburg mare

SummaryA 5‐year‐old Oldenburg mare presented for poor performance, head‐tossing and bucking when ridden. An abnormal respiratory noise was audible during exercise. Computed tomography (CT) revealed right laryngeal dysplasia; an absent cricothyroid articulation, abnormally shaped thyroid cartilage, underdeveloped cricopharyngeus muscle, rostral displacement of the palatopharyngeal arch and an oesophageal air column. In this case, it was unlikely that the laryngeal pathology was related to the horse's clinical signs. This case report provides a reference CT examination of laryngeal dysplasia, corroborating previous findings using magnetic resonance imaging, radiography, ultrasonography and post‐mortem examination.

Accurate Delineation of Mucosal Lesions in Treatment-Planning Computed Tomography Using Iodine Paste Markers for Oral Mucosal Melanoma

This technical report introduces the utility of iodine paste markers using endodontic materials for the accurate contouring of mucosal lesions of oral mucosal melanoma, which are difficult to delineate on imaging during the planning of carbon-ion radiation therapy (CIRT). The patient had a primary oral mucosal melanoma located in the palatal mucosa without palatal or maxillary bone invasion. A dental root canal filling material, which is a calcium hydroxide/iodoform nonhardenable paste, was used as a marker. We first performed treatment-planning computed tomography (CT) without an iodine paste marker for mucosal lesions. Subsequently, we placed an iodine paste marker on the palatal mucosal lesion to accurately delineate the mucosal lesions of the palate. Finally, we obtained a reference CT image with an iodine paste marker. Computed tomography without the marker was fused to the reference CT with markers during treatment planning, and the gross tumor volume was contoured. Thereafter, CIRT was delivered without markers. During CIRT, expected acute mucositis was observed in the area of the planning target volume, including melanosis, in accordance with the dose distribution. The use of iodine paste markers for localized mucosal lesions, which are difficult to delineate on CT and magnetic resonance imaging, may be useful for accurately contouring gross tumor volumes on treatment-planning CT.

Toward PET/MRI as one-stop shop for radiotherapy planning in cervical cancer patients

Background Radiotherapy (RT) planning for cervical cancer patients entails the acquisition of both Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Further, molecular imaging by Positron Emission Tomography (PET) could contribute to target volume delineation as well as treatment response monitoring. The objective of this study was to investigate the feasibility of a PET/MRI-only RT planning workflow of patients with cervical cancer. This includes attenuation correction (AC) of MRI hardware and dedicated positioning equipment as well as evaluating MRI-derived synthetic CT (sCT) of the pelvic region for positioning verification and dose calculation to enable a PET/MRI-only setup. Material and methods 16 patients underwent PET/MRI using a dedicated RT setup after the routine CT (or PET/CT), including eight pilot patients and eight cervical cancer patients who were subsequently referred for RT. Data from 18 patients with gynecological cancer were added for training a deep convolutional neural network to generate sCT from Dixon MRI. The mean absolute difference between the dose distributions calculated on sCT and a reference CT was measured in the RT target volume and organs at risk. PET AC by sCT and a reference CT were compared in the tumor volume. Results All patients completed the examination. sCT was inferred for each patient in less than 5 s. The dosimetric analysis of the sCT-based dose planning showed a mean absolute error (MAE) of 0.17 ± 0.12 Gy inside the planning target volumes (PTV). PET images reconstructed with sCT and CT had no significant difference in quantification for all patients. Conclusions These results suggest that multiparametric PET/MRI can be successfully integrated as a one-stop-shop in the RT workflow of patients with cervical cancer.

Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region

BackgroundWe investigated the geometric and dosimetric impact of three-dimensional (3D) generative adversarial network (GAN)-based metal artifact reduction (MAR) algorithms on volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT) for the head and neck region, based on artifact-free computed tomography (CT) volumes with dental fillings.MethodsThirteen metal-free CT volumes of the head and neck regions were obtained from The Cancer Imaging Archive. To simulate metal artifacts on CT volumes, we defined 3D regions of the teeth for pseudo-dental fillings from the metal-free CT volumes. HU values of 4000 HU were assigned to the selected teeth region of interest. Two different CT volumes, one with four (m4) and the other with eight (m8) pseudo-dental fillings, were generated for each case. These CT volumes were used as the Reference. CT volumes with metal artifacts were then generated from the Reference CT volumes (Artifacts). On the Artifacts CT volumes, metal artifacts were manually corrected for using the water density override method with a value of 1.0 g/cm3 (Water). By contrast, the CT volumes with reduced metal artifacts using 3D GAN model extension of CycleGAN were also generated (GAN-MAR). The structural similarity (SSIM) index within the planning target volume was calculated as quantitative error metric between the Reference CT volumes and the other volumes. After creating VMAT and IMPT plans on the Reference CT volumes, the reference plans were recalculated for the remaining CT volumes.ResultsThe time required to generate a single GAN-MAR CT volume was approximately 30 s. The median SSIMs were lower in the m8 group than those in the m4 group, and ANOVA showed a significant difference in the SSIM for the m8 group (p < 0.05). Although the median differences in D98%, D50% and D2% were larger in the m8 group than the m4 group, those from the reference plans were within 3% for VMAT and 1% for IMPT.ConclusionsThe GAN-MAR CT volumes generated in a short time were closer to the Reference CT volumes than the Water and Artifacts CT volumes. The observed dosimetric differences compared to the reference plan were clinically acceptable.

Improving CBCT quality to CT level using deep learning with generative adversarial network.

To improve image quality and computed tomography (CT) number accuracy of daily cone beam CT (CBCT) through a deep learning methodology with generative adversarial network. One hundred and fifty paired pelvic CT and CBCT scans were used for model training and validation. An unsupervised deep learning method, 2.5D pixel-to-pixel generative adversarial network (GAN) model with feature mapping was proposed. A total of 12000 slice pairs of CT and CBCT were used for model training, while ten-fold cross validation was applied to verify model robustness. Paired CT-CBCT scans from an additional 15 pelvic patients and 10 head-and-neck (HN) patients with CBCT images collected at a different machine were used for independent testing purpose. Besides the proposed method above, other network architectures were also tested as: 2D vs 2.5D; GAN model with vs without feature mapping; GAN model with vs without additional perceptual loss; and previously reported models as U-net and cycleGAN with or without identity loss. Image quality of deep-learning generated synthetic CT (sCT) images was quantitatively compared against the reference CT (rCT) image using mean absolute error (MAE) of Hounsfield units (HU) and peak signal-to-noise ratio (PSNR). The dosimetric calculation accuracy was further evaluated with both photon and proton beams. The deep-learning generated sCTs showed improved image quality with reduced artifact distortion and improved soft tissue contrast. The proposed algorithm of 2.5 Pix2pix GAN with feature matching (FM) was shown to be the best model among all tested methods producing the highest PSNR and the lowest MAE to rCT. The dose distribution demonstrated a high accuracy in the scope of photon-based planning, yet more work is needed for proton-based treatment. Once the model was trained, it took 11-12ms to process one slice, and could generate a 3D volume of dCBCT (80 slices) in less than a second using a NVIDIA GeForce GTX Titan X GPU (12GB, Maxwell architecture). The proposed deep learning algorithm is promising to improve CBCT image quality in an efficient way, thus has a potential to support online CBCT-based adaptive radiotherapy.

Harmonization of radiomic feature variability resulting from differences in CT image acquisition and reconstruction: assessment in a cadaveric liver

Studies investigating the effects of computed tomography (CT) image acquisition and reconstruction parameters have mostly been limited to non-human phantoms to limit exposure to patients. This study investigates these variations using a cadaveric liver and determines harmonization methods to mitigate these variations. A reference CT scan of a cadaveric liver was acquired along with 16 modified scans. Modified scans were obtained with altered image acquisition and reconstruction parameters. In each slice, the liver was segmented and used to calculate 142 features. Student’s t-tests assessed differences between reference and modified scans for each feature after correcting for multiple comparisons. Features were harmonized between reference and modified scans using histogram normalization, pixel resampling, Butterworth filtering, resampling and filtering combined, and ComBat harmonization. The number of features reflecting significant differences before and after harmonization were compared across imaging parameters. Reducing the field-of-view (FOV) and using coronal instead of axial scans resulted in the greatest number of features reflecting significant differences (67.6%, and 35.9%, respectively) and resulted in the greatest median relative change in feature values (25.4% and 18.2%, respectively). Changes in tube voltage, pitch, and slice interval resulted in the smallest number of features reflecting significance (0.7%) with median relative changes in feature <2%. Histogram normalization reduced or maintained the number of significantly different features for all scans, while ComBat reduced the number of significantly different features to zero for all scans. The remaining harmonization methods had mixed effects: resampling reduced the number of features reflecting significant differences for half of the imaging parameters, while filtering alone and filtering combined with resampling both reduced the number of features reflecting significance for 10 of the 16 parameters. The dependence of radiomic features on image acquisition and reconstruction parameters varies in a cadaveric liver; however, various harmonization methods have shown promise in mitigating these dependencies, particularly ComBat.

Photothermal Porosity Estimation in CFRP by the Time-of-Flight of Virtual Waves

Porosity is an unavoidable defect in carbon fiber reinforced polymers and has noticeable effects on mechanical properties since gas filled voids weaken the epoxy matrix. Pulsed thermography is advantageous because it is a non-contacting, non-destructive and fast photothermal testing method that allows the estimation of material parameters. Using the Virtual Wave Concept for thermography data, ultrasonic evaluation methods are applicable. In this work, the pulse-echo method for Time-of-Flight measurements is used, whereby the determined Time-of-Flight is directly related to the thermal diffusion time of the examined material. We introduce a signal-to-noise dependent approach, the optimum evaluation time, for evaluating only relevant time ranges which contain information of heat diffusion. After the validation of the method for heterogeneous materials, effective medium theories can be used for quantitative porosity estimation from the estimated diffusion time. This model-based approach for porosity estimation delivers more accurate results for transmission and reflection configuration measurements compared to thermographic state-of-the-art methods. The results are validated by X-ray computed tomography reference measurements on a wide range of different porous carbon fiber reinforced plastic specimens with different number of plies and varying porosity contents.

Stability of daily rectal movement and effectiveness of replanning protocols for sparing rectal doses based on the daily CT images during proton treatment for prostate cancer.

PurposeTo evaluate the optimal period of replanning to spare the rectal dose by investigating daily rectal movements during computed tomography (CT) image‐guided proton therapy for prostate cancer.Materials and methodsTo evaluate the optimum reference period for replanning, we analyzed 1483 sets of daily CT (dCT) images acquired from 40 prostate cancer patients and measured the daily rectal movement along the anterior–posterior direction based on the simulator CT (sCT) images and dCT images. We calculated daily dose distributions based on initial plans on the sCT images and replans on the dCT images for 13 representative patients, and evaluated daily dose volume histograms (DVHs) for the prostate, seminal vesicles, and rectum.ResultsThe rectal anterior side on the dCT images around the seminal vesicles largely deviated toward the anterior side relative to the position on the reference sCT images, but the deviation decreased by referring to the dCT images and became nearly zero when we referred to the dCT images after 10‐day treatment. The daily DVH values for the prostate showed good dose coverage. For six patients showing rectal movement toward the anterior side, the daily rectal DVH (V77%) showed a 3.0 ± 1.7 cc excess from the initial plan and this excess was correlated with 9.9 ± 6.8 mm rectal movement. To identify the patients (37.5% in total) for whom the replanning on the 10th‐day and 20th‐day CT images reduced the V77% excess to 0.4 ± 1.5 cc and −0.2 ± 1.3 cc, respectively, we evaluated the accumulated mean doses with a 1.2 cc criterion.ConclusionOur data demonstrate that the daily movement of the rectal anterior side tends to move toward the anterior side, which results in a rectal overdose, and the mean of the movement gradually decreases with the passage of days. In such cases, replanning with the reference CT after 10 days is effective to spare the rectal dose.

Techniques for and uncertainties of MRI-based reconstruction of titanium tandem and ring brachytherapy applicators

PurposeEliminating patient computed tomography (CT) scans for tandem and ring (T&R) brachytherapy can reduce overall procedure time and eliminates imaging dose. However, reconstructing titanium applicators in magnetic resonance imaging (MRI) is challenging. We evaluated the uncertainty of different applicator reconstruction workflows in MR-guided brachytherapy, and assessed the clinical impact of reconstruction uncertainties. Methods and materialsTitanium MRI-compatible T&Rs with aqueous gel in the buildup cap were reconstructed on CTs and MRIs to assess the uncertainties of four different workflows. Reconstruction was performed using (1) proton density–weighted MRIs with solid applicator from a library, (2) applicator-only reference CT fused with MRIs, (3) T2-weighted (T2W) MRIs following GEC-ESTRO guidelines, and (4) patient CTs fused with patient MRIs with in situ applicators. We evaluated dwell positions and plan quality differences using high-risk clinical target volume coverage, and EQD2 D2cc of rectum, sigmoid, bladder, and small bowel. ResultsThe 2σ uncertainty for dwell positions for each workflow were (1) 2.7 mm for both ring and tandem, (2) 1.4 mm ring and 0.8 mm tandem, (3) 0.2 mm ring and 0.8 mm tandem, and (4) 1.9 mm ring and 0.4 mm tandem. Reconstruction uncertainties resulted in dose variations within acceptable levels (below 10%) except for (1) which resulted in larger dose to the rectum (20%). Dose uncertainties were similar between reference CT and patient CT. ConclusionsReconstruction with a reference CT results in similar uncertainty to a patient CT. T2W MRI plans have acceptable uncertainty levels for the applicator reconstruction and resulting dose distributions.

NMAR3: Normalized Metal Artifact Reduction for Cone Beam Computed Tomography.

Metal Artifact Reduction (MAR) plays an important role in Computed Tomography (CT) research and application because severe artifacts degrade the image quality and diagnosis value if metal objects are present in the field of measurement. Although there are already many works for MAR, these works are for fan beam CT, not for cone beam CT, which is the trend and receiving much research attention. In this paper, we extend the Normalized Metal Artifact Reduction (NMAR) for fan beam CT to NMAR3 for cone beam CT, by replacing the linear interpolation in the NMAR with bi-linear interpolation. Experiments are carried out on 17 sets of spine phantom CT. 15 of them have reference CT as ground truth and 2 ones not. Both quantitative and qualitative results verified that NMAR3 outperforms the baseline method, i.e., bi-linear interpolation based method.

Influence of different urinary bladder filling levels and controlling regions of interest selection on deformable image registration algorithms

PurposeEvaluation of Raystation ANAtomically CONstrained Deformation Algorithm (ANACONDA) performance to different urinary bladder filling levels in male pelvis anatomic site varying the controlling Regions Of Interest (ROIs). MethodsDifferent image datasets were obtained with ImSimQA (Oncology System Limited, Shrewsbury, UK) to evaluate ANACONDA performances (RaySearch Laboratories, Stockholm, Sweden). Deformation vector fields were applied to a synthetic man pelvis and a real patient computed tomography (CT) dataset (reference CTs) resulting in deformed CTs (target CTs) with various bladder filling levels. Different deformable image registrations (DIRs) were generated between each target CTs and reference CTs varying the controlling ROIs subset. Deformed ROIs were mapped from target CT to reference CT and then compared to reference ROIs. Evaluation was performed by Dice Similarity Coefficient (DSC), Correlation Coefficient (CC), Mean Distance to Agreement (MDA), maximum Distance to Agreement (maxDA) and with the introduction of global DSC (global_DSC) and global CC (global_CC) parameters. ResultsIn both synthetic and real patient CT cases, DSC scored less than 0.75 and MDA greater than 3 mm when no ROIs or only bladder were exploited as controlling ROI. DSC and CC increased by increasing the number of controlling ROIs selected whereas, an opposite behavior was observed for MDA and maxDA. ConclusionsANACONDA performances can be influenced by bladder filling fluctuation if no controlling ROIs are selected. Global_DSC and global_CC are useful parameters to quantitatively compare DIR algorithms. DIR performances improve by increasing the number of controlling ROIs selected, reaching a saturation level after a defined ROIs subset selection.