3D Magnetic Resonance Imaging Research Articles

Articulatory and Phonatory Precision When Singing Staccato at Different Speeds

Vocal tract adjustments are important for resonatory modification of the voice and also with respect to interactions concerning the voice source production. It is not clear, however, how fast, separated notes (staccato) influence vocal tract adjustments. Twelve professional singers (four sopranos, three mezzo-sopranos, three tenors, and two baritones/basses) were recorded with dynamic real-time 2D-magnetic resonance imaging (MRI) with 25fps singing a scale in legato and different staccato speeds (60, 120, 180, and 240bps). From the MRI material, the lip opening, jaw opening, jaw protrusion, tongue position, pharynx width, and larynx position were measured. Furthermore, the fundamental frequency was analyzed from the simultaneously recorded audio signal after noise cancellation. The data show only very small differences between the legato and the staccato tasks and no great variations for different staccato speeds. During the pauses in between the staccato notes, minimal vocal tract adjustments were only detectable for the slowest staccato task. There are no great differences in the vocal tract shapes for legato singing in contrast to staccato phonation and no great differences for different staccato speeds.

3D Ultrasound and MRI in Assessing Resection Margins during Tongue Cancer Surgery: A Research Protocol for a Clinical Diagnostic Accuracy Study.

Surgery is the primary treatment for tongue cancer. The goal is a complete resection of the tumor with an adequate margin of healthy tissue around the tumor.Inadequate margins lead to a high risk of local cancer recurrence and the need for adjuvant therapies. Ex vivo imaging of the resected surgical specimen has been suggested for margin assessment and improved surgical results. Therefore, we have developed a novel three-dimensional (3D) ultrasound imaging technique to improve the assessment of resection margins during surgery. In this research protocol, we describe a study comparing the accuracy of 3D ultrasound, magnetic resonance imaging (MRI), and clinical examination of the surgical specimen to assess the resection margins during cancer surgery. Tumor segmentation and margin measurement will be performed using 3D ultrasound and MRI of the ex vivo specimen. We will determine the accuracy of each method by comparing the margin measurements and the proportion of correctly classified margins (positive, close, and free) obtained by each technique with respect to the gold standard histopathology.

Aortic Wall Thickness as a Surrogate for Subclinical Atherosclerosis in Familial and Nonfamilial Hypercholesterolemia: Quantitative 3D Magnetic Resonance Imaging Study and Interrelations with Computed Tomography Calcium Scores, and Carotid Ultrasonography.

We aimed to compare the extent of subclinical atherosclerosis in the ascending and descending aortas by measuring wall area and thickness using 3D cardiovascular magnetic resonance imaging (aAWAI and dAWAI) in patients with asymptomatic familial hypercholesterolemia (FH) and nonfamilial hypercholesterolemia (NFH). We also aimed to establish the interrelations of CMR parameters with other subclinical atherosclerosis measurements, such as calcium scores, obtained using computed tomography in coronary arteries (CCS) and ascending and descending aorta (TCSasc and TCSdsc), as well as the carotid intima-media thicknesses (cIMT) using ultrasonography. A total of 60 patients with FH (29 men and 31 women), with a mean age of 52.3 ± 9.6 years, were analyzed. A subclinical atherosclerosis assessment was also performed on a group consisting of 30 age- and gender-matched patients with NFH, with a mean age of 52.5 ± 7.9 years. We found the ascending and descending aortic wall areas and thicknesses in the FH group to be significantly increased than those of the NFH group. A multivariate logistic regression analysis showed that a positive FH mutation value was a strong predictor of high aAWAI and dAWAI independent of the LDL cholesterol level. Correlations across CMR atherosclerotic parameters, calcium scores, and cIMT in the FH and NFH groups, were significant but low. Most of the atherosclerosis tests with high results belonged to the FH group. We found that patients with documented heterozygous FH had a higher atherosclerosis burden in the aorta compared to patients with severe hypercholesterolemia without FH gene mutation. Atherosclerosis is not severe in asymptomatic patients with FH, but is more pronounced and also more diffuse than in patients with NFH. The etiology of hypercholesterolemia, and not just cholesterol levels, plays a significant role in determining the degree of subclinical atherosclerosis.

Diagnostic performance of a 3D double-echo steady-state sequence at 3 T using radial reformats for detecting and grading rotator cuff tears: a pilot diagnostic accuracy study with magnetic resonance imaging and arthroscopic correlation.

In diagnosing rotator cuff tears (RCTs), magnetic resonance imaging (MRI) is the imaging modality of choice, and its accuracy is improving constantly. To evaluate the diagnostic performance of a high-resolution 3D double-echo steady-state (DESS) sequence with radial and paracoronal 3-T MRI regarding the grading of RCTs in correlation with conventional 2D MRI and arthroscopic findings. We retrospectively compared arthroscopic findings of RCTs with preoperative MRI, including conventional 2D sequences and radial and paracoronal DESS images in 20 patients. Two observers evaluated supraspinatus (SSP), infraspinatus (ISP), and subscapularis (SSC) tendon tears using a grading system. For statistical analysis, arthroscopy was used as the reference standard. Inter-observer agreement for detecting and grading SSP, ISP, and SSC tendon tears on radial and paracoronal sliced 3D DESS MRI was excellent (intraclass-correlation [ICC] = 0.92-0.98; all P < 0.001). Regarding the detection of SSP lesions, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 93.8%, 50%, 88.2%, and 66.7% for both radial and paracoronal DESS imaging. A sensitivity of 100%, specificity of 61.1%, PPV of 22.2%, and NPV of 100% were noted for detecting ISP tendon tears using radially reformatted DESS images. Regarding detecting SSC tendon tears using radially reformatted DESS images, sensitivity, specificity, PPV, and NPV were 100%, 81.3%, 50%, and 100%, respectively. The results with standard 2D MRI were similar. The DESS technique with radially reformatted images provided excellent sensitivity and high inter-observer agreement in detecting RCTs. It showed a moderate to high correlation between MRI and arthroscopy for diagnosing SSP and SSC tendon tears.

Analysis of cam location characteristics in FAI syndrome patients from 3D MR images demonstrates sex-specific differences.

Cam femoroacetabular impingement (FAI) syndrome is associated with hip osteoarthritis (OA) development. Hip shape features, derived from statistical shape modeling (SSM), are predictive for OA incidence, progression, and arthroplasty. Currently, no three-dimensional (3D) SSM studies have investigated whether there are cam shape differences between male and female patients, which may be of potential clinical relevance for FAI syndrome assessments. This study analyzed sex-specific cam location and shape in FAI syndrome patients from clinical magnetic resonance examinations (M:F 56:41, age: 16-63 years) using 3D focused shape modeling-based segmentation (CamMorph) and partial least squares regression to obtain shape features (latent variables [LVs]) of cam morphology. Two-way analysis of variance tests were used to assess cam LV data for sex and cam volume severity differences. There was no significant interaction between sex and cam volume severity for the LV data. A sex main effect was significant for LV 1 (cam size) and LV 2 (cam location) with medium to large effect sizes (p < 0.001, d > 0.75). Mean results revealed males presented with a superior-focused cam, whereas females presented with an anterior-focused cam. When stratified by cam volume, cam morphologies were located superiorly in male and anteriorly in female FAI syndrome patients with negligible, mild, or moderate cam volumes. Both male and female FAI syndrome patients with major cam volumes had a global cam distribution. In conclusion, sex-specific cam location differences are present in FAI syndrome patients with negligible, mild, and moderate cam volumes, whereas major cam volumes were globally distributed in both male and female patients.

The Reliability of Measurements for Tibial Torsion: A Comparison of CT, MRI, Biplanar Radiography, and 3D Reconstructions With and Without Standardized Measurement Training

Background: Accurate and reliable assessment of tibial torsion is important for the identification and treatment of tibial rotation malalignment; however, the ideal rotational measurement modality and technique are controversial. This study compares rotational measurements between computed tomography (CT), magnetic resonance imaging (MRI), biplanar erect radiograph (BER) reconstructions, and three-dimensional (3D) reconstructed CT before and after standardized training of observers to evaluate the reliability of each assessment method.Methods: Eight adult cadaveric specimens underwent CT, MRI, and BER imaging. Tibial torsion was measured by three independent observers (one resident and two experienced orthopaedic surgeons) both before and after standardized measurement instruction. Reliability for inter-observer measurement was evaluated using the Intraclass Correlation Coefficient (ICC). Measurement values for CT, MRI, and BER reconstructions were compared to 3D CT reconstructions analyzed using custom software to align and measure tibial torsion (used as the reference standard).Results: Before training, there was poor inter-observer reliability for CT (ICC=0.492, p=0.014) and moderate interobserver reliability for MRI (ICC=0.633, p=0.002). There was no inter-method reliability between 3D CT and MRI for two of the three surgeons and moderate to good reliability between 3D CT and CT. After training, the interobserver reliability for CT improved to 0.536 and the inter-observer reliability for MRI improved to 0.701. The BER measurements (no observer involvement) had moderate reliability compared to the 3D CT reconstructions (ICC=0.69, p=0.026). Measurement error was 4 degrees for CT pre-training and 7 degrees post-training, and 7 degrees for MRI pre-training and 8 degrees post-training.Conclusions: A standardized training regimen for MRI measurements improved both inter-observer and intraobserver reliability. Inter-method reliability between CT, MRI, and BER compared to reference 3D CT reconstructions demonstrated that all imaging modalities are a valid means to measure tibial rotation but differ in reliability from moderate to good. When assessing tibial torsional deformities, it is important to consider these variations from true rotation and feel comfortable using them for pre-operative planning purposes.Level of Evidence: N/A for a cadaveric imaging study Key Concepts•A standardized training regimen for MRI measurements of tibial torsion significantly improved inter-observer and intra-observer reliability.•CT, MRI, and BER measurements are valid imaging modalities compared to 3D CT reference standards for measuring tibial rotation.•Established manual measurements of tibial torsion from MRI may be improved with adequate training.•Measurement error of up to 8 degrees can be seen from true tibial torsion during the imaging assessment.

Definition and evaluation of a finite element model of the human heel for diabetic foot ulcer prevention under shearing loads.

Diabetic foot ulcers are triggered by mechanical loadings applied to the surface of the plantar skin. Strain is considered to play a crucial role in relation to ulcer etiology and can be assessed by Finite Element (FE) modeling. A difficulty in the generation of these models is the choice of the soft tissue material properties. In the literature, many studies attempt to model the behavior of the heel soft tissues by implementing constitutive laws that can differ significantly in terms of mechanical response. Moreover, current FE models lack of proper evaluation techniques that could estimate their ability to simulate realistic strains. In this article, we propose and evaluate a FE model of the human heel for diabetic foot ulcer prevention. Soft tissue constitutive laws are defined through the fitting of experimental stretch-stress curves published in the literature. The model is then evaluated through Digital Volume Correlation (DVC) based on non-rigid 3D Magnetic Resonance Image Registration. The results from FE analysis and DVC show similar strain locations in the fat pad and strain intensities according to the type of applied loads. For additional comparisons, different sets of constitutive models published in the literature are applied into the proposed FE mesh and simulated with the same boundary conditions. In this case, the results in terms of strains show great diversity in locations and intensities, suggesting that more research should be developed to gain insight into the mechanical properties of these tissues.

Hybrid Contextual Semantic Network for Accurate Segmentation and Detection of Small-Size Stroke Lesions From MRI.

Stroke is a cerebrovascular disease with high mortality and disability rates. The occurrence of the stroke typically produces lesions of different sizes, with the accurate segmentation and detection of small-size stroke lesions being closely related to the prognosis of patients. However, the large lesions are usually correctly identified, the small-size lesions are usually ignored. This paper provides a hybrid contextual semantic network (HCSNet) that can accurately and simultaneously segment and detect small-size stroke lesions from magnetic resonance images. HCSNet inherits the advantages of the encoder-decoder architecture and applies a novel hybrid contextual semantic module that generates high-quality contextual semantic features from the spatial and channel contextual semantic features through the skip connection layer. Moreover, a mixing-loss function is proposed to optimize HCSNet for unbalanced small-size lesions. HCSNet is trained and evaluated on 2D magnetic resonance images produced from the Anatomical Tracings of Lesions After Stroke challenge (ATLAS R2.0). Extensive experiments demonstrate that HCSNet outperforms several other state-of-the-art methods in its ability to segment and detect small-size stroke lesions. Visualization and ablation experiments reveal that the hybrid semantic module improves the segmentation and detection performance of HCSNet.

Three-Dimensional Volumetric Magnetic Resonance Imaging Analysis of Syringomyelia Evolution After Posterior Fossa Decompression for Chiari Malformation Type1

This study aims to introduce a method of three-dimensional (3D) volume magnetic resonance imaging (MRI) measurements to evaluate the evolution of syringomyelia (SM) in adults with Chiari malformation type 1 (CM-1) after posterior fossa decompression (PFD), to provide reproducible and accurate measurements. Radiologic and clinical data were obtained for 28 patients. MRI 3D syrinx volumes were evaluated by 2 observers using Philips Healthcare Tumor Tracking tool. The mean SM preoperative volume was 9.1 ± 15.3 cm3 versus 4.6 ± 8.7 cm3 postoperatively, corresponding to a volume variation reduced by -50% ± 33.4%. A total of 21 patients (75%) showed >25% reduction in SM volume postoperatively and 25 patients (89.2%) showed good to excellent postoperative clinical outcomes. Very high interobserver and intraobserver agreement was noted for 3D volumetric analysis with Cohen weighted κ coefficients (0.899-0.991). A negative correlation was found between the number of involved metameres and the postoperative SM volume reduction (Pearson correlation coefficient= 0.378; P= 0.047). Patients with better clinical outcomes had fewer syrinx septae (F= 8.830; P= 0.001). Similarly, better syrinx volume reduction was associated with fewer septae (F= 1.554; P= 0.233). A positive relationship was observed between clinical outcomes and postoperative syrinx volume reduction (F= 1.554; P= 0.233), with data similar to the reported literature. This study shows that 3D volume measurement of the syrinx cavity on MRI is a reproducible and accurate method to assess the postoperative evolution of SM in CM-1 after PFD. Most patients (75%) showed a reduction of SM volume, with a mean volume decrease of 50%. The reliability is yet to be validated in further larger studies.

Automatic segmentation of rectal tumors from MRI using multiscale densely connected convolutional neural network based on attention mechanism

Rectal cancer is one of the most common malignancies in the gastrointestinal tract. Currently, magnetic resonance imaging has become a vital tool in diagnosing and treating patients with rectal cancer. Notably, early diagnosis of rectal cancer can help improve patient survival rate; however, the clinical expertize of physicians is a limiting factor. Therefore, we propose an attention-based multiscale densely connected convolutional neural network based on an attention mechanism to improve the accuracy of diagnosis by automatically segmenting rectal tumors from two-dimensional (2D) magnetic resonance images (MRI) using computer-aided diagnostic techniques. First, to address the inability of U-Net (a classical segmentation network for medical images) and extract rich semantic features and the inconsistent shape and size of tumors between different patients, we replace the conventional convolutional blocks in the U-Net network with multiscale densely connected convolutional blocks. Second, to make the network focus better on global contextual information, we add central blocks with atrous convolution in the final coding layer or the last coding layer. Finally, we add a hybrid attention mechanism to each decoder module to help the model focus on the features of the rectal tumor region. We validated the effectiveness of the proposed method using 3773 2D MRI datasets from 572 patients. The sensitivity, specificity, Dice correlation coefficient, and Hausdorff distance of MRI rectal tumor segmentation were 85.47%, 86.35%, 94.71%, and 7.88 mm, respectively. The results showed that the proposed method outperforms conventional approaches. Moreover, the proposed method has better segmentation results in the rectal tumor segmentation task and can provide physicians with the second-most important clinical diagnostic opinion.

Fast Compressed Sensing of 3D Radial T1 Mapping with Different Sparse and Low-Rank Models.

Knowledge of the relative performance of the well-known sparse and low-rank compressed sensing models with 3D radial quantitative magnetic resonance imaging acquisitions is limited. We use 3D radial T1 relaxation time mapping data to compare the total variation, low-rank, and Huber penalty function approaches to regularization to provide insights into the relative performance of these image reconstruction models. Simulation and ex vivo specimen data were used to determine the best compressed sensing model as measured by normalized root mean squared error and structural similarity index. The large-scale compressed sensing models were solved by combining a GPU implementation of a preconditioned primal-dual proximal splitting algorithm to provide high-quality T1 maps within a feasible computation time. The model combining spatial total variation and locally low-rank regularization yielded the best performance, followed closely by the model combining spatial and contrast dimension total variation. Computation times ranged from 2 to 113 min, with the low-rank approaches taking the most time. The differences between the compressed sensing models are not necessarily large, but the overall performance is heavily dependent on the imaged object.

Three-dimensional ultrasound to investigate synovitis in first carpometacarpal osteoarthritis: A feasibility study.

Synovitis is one of the defining characteristics of osteoarthritis (OA) in the carpometacarpal (CMC1) joint of the thumb. Quantitative characterization of synovial volume is important for furthering our understanding of CMC1 OA disease progression, treatment response, and monitoring strategies. In previous studies, three-dimensional ultrasound (3-D US) has demonstrated the feasibility of being a point-of-care system for monitoring knee OA. However, 3-D US has not been tested on the smaller joints of the hand, which presents unique physiological and imaging challenges. To develop and validate a novel application of 3-D US to monitor soft-tissue characteristics of OA in a CMC1 OA patient population compared to the current gold standard, magnetic resonance imaging (MRI). A motorized submerged transducer moving assembly was designed for this device specifically for imaging the joints of the hands and wrist. The device used a linear 3-D scanning approach, where a 14L5 2-D transducer was translated over the region of interest. Two imaging phantoms were used to test the linear and volumetric measurement accuracy of the 3-D US device. To evaluate the accuracy of the reconstructed 3-D US geometry, a multilayer monofilament string-grid phantom (10mm square grid) was scanned. To validate the volumetric measurement capabilities of the system, a simulated synovial tissue phantom with an embedded synovial effusion was fabricated and imaged. Ten CMC1 OA patients were imaged by our 3-D US and a 3.0 T MRI system to compare synovial volumes. The synovial volumes were manually segmented by two raters on the 2D slices of the 3D US reconstruction and MR images, to assess the accuracy and precision of the device for determining synovial tissue volumes. The Standard Error of Measurement and Minimal Detectable Change was used to assess the precision and sensitivity of the volume measurements. Paired sample t-tests were used to assess statistical significance. Additionally, rater reliability was assessed using Intra-Class Correlation (ICC) coefficients. The largest percent difference observed between the known physical volume of synovial extrusion in the phantom and the volume measured by our 3D US was 1.1% (p-value=0.03). The mean volume difference between the 3-D US and the gold standard MRI was 1.78% (p-value=0.48). The 3-D US synovial tissue volume measurements had a Standard Error Measurement (SEm ) of 11.21mm3 and a Minimal Detectible Change (MDC) of 31.06mm3 , while the MRI synovial tissue volume measurements had an SEM of 16.82mm3 and an MDC of 46.63mm3 . Excellent inter- and intra-rater reliability (ICCs=0.94-0.99) observed across all imaging modalities and raters. Our results indicate the feasibility of applying 3-D US technology to provide accurate and precise CMC1 synovial tissue volume measurements, similar to MRI volume measurements. Lower MDC and SEm values for 3-D US volume measurements indicate that it is a precise measurement tool to assess synovial volume and that it is sensitive to variation between volume segmentations. The application of this imaging technique to monitor OA pathogenesis and treatment response over time at the patient's bedside should be thoroughly investigated in future studies.

MRI Derived Simulations of Flow Patterns in the Stomach.

A framework to simulate the flow in the stomach using subject-specific motility patterns and geometries was developed. Dynamic 2D magnetic resonance images (MRIs) were obtained. Motility parameters such as contraction speed and occlusion were quantified, and 3D stomach geometries were reconstructed using a semi-automated approach. Computational fluid dynamics (CFD) simulations were performed, and flow patterns were investigated. The stomach of both subjects had distinct anatomical features with computed volumes of 789 mL and 619 mL. For the one subject, the occlusion (i.e., normalized contraction size) was 12% while it was around 25% for the other subject. Contraction speeds were also different (1.9-2.8 mm/s vs 3.0-5.1 mm/s) for each subject. CFD simulations resulted in unsteady laminar flow for both subjects with average velocities of 2.1 and 3.2 mm/s. While antegrade flow was mainly observed in the simulations, a retropulsive jet was also present in both stomachs. The versatile framework developed within this study would allow the generation of CFD models of gastric motility from dynamic MRIs.Clinical Relevance- Subject-specific models of flow patterns informed by gastric motility features can elucidate the impact of contractions and anatomical variations on digestion. Such models can inform therapies to treat gastric dysfunctions and improve their efficacy.

Quantifying Muscle Size Asymmetry in Adolescent Idiopathic Scoliosis Using Three-dimensional Magnetic Resonance Imaging.

This is a case-control study of prospectively collected data. To quantify paraspinal muscle size asymmetry in adolescent idiopathic scoliosis (AIS) and determine if this asymmetry is (i) greater than observed in adolescent controls with symmetrical spines; and (ii) positively associated with skeletal maturity using Risser grade, scoliosis severity using the Cobb angle, and chronological age in years. AIS is a three-dimensional deformity of the spine which occurs in 2.5% to 3.7% of the Australian population. There is some evidence of asymmetry in paraspinal muscle activation and morphology in AIS. Asymmetric paraspinal muscle forces may facilitate asymmetric vertebral growth during adolescence. An asymmetry index [Ln(concave/convex volume)] of deep and superficial paraspinal muscle volumes, at the level of the major curve apex (Thoracic 8-9 th vertebral level) and lower-end vertebrae ( LEV , Thoracic 10-12 th vertebral level), was determined from three-dimensional Magnetic Resonance Imaging of 25 adolescents with AIS (all right thoracic curves), and 22 healthy controls (convex=left); all female, 10 to 16 years. Asymmetry index of deep paraspinal muscle volumes was greater in AIS (0.16±0.20) than healthy spine controls (-0.06±0.13) at the level of the apex ( P <0.01, linear mixed-effects analysis) but not LEV ( P >0.05). Asymmetry index was positively correlated with Risser grade ( r =0.50, P <0.05) and scoliosis Cobb angle ( r =0.45, P <0.05), but not age ( r =0.34, P >0.05). There was no difference in the asymmetry index of superficial paraspinal muscle volumes between AIS and controls ( P >0.05). The asymmetry of deep apical paraspinal muscle volume in AIS at the scoliosis apex is greater than that observed at equivalent vertebral levels in controls and may play a role in the pathogenesis of AIS.

Automated Brain Tumour Detection and Classification using Deep Features and Bayesian Optimised Classifiers.

Brain tumour detection and classification require trained radiologists for efficient diagnosis. The proposed work aims to build a Computer Aided Diagnosis (CAD) tool to automate brain tumour detection using Machine Learning (ML) and Deep Learning (DL) techniques. Magnetic Resonance Image (MRI) collected from the publicly available Kaggle dataset is used for brain tumour detection and classification. Deep features extracted from the global pooling layer of Pretrained Resnet18 network are classified using 3 different ML Classifiers, such as Support vector Machine (SVM), K-Nearest Neighbour (KNN), and Decision Tree (DT). The above classifiers are further hyperparameter optimised using Bayesian Algorithm (BA) to enhance the performance. Fusion of features extracted from shallow and deep layers of the pretrained Resnet18 network followed by BA-optimised ML classifiers is further used to enhance the detection and classification performance. The confusion matrix derived from the classifier model is used to evaluate the system's performance. Evaluation metrics, such as accuracy, sensitivity, specificity, precision, F1 score, Balance Classification Rate (BCR), Mathews Correlation Coefficient (MCC) and Kappa Coefficient (Kp), are calculated. Maximum accuracy, sensitivity, specificity, precision, F1 score, BCR, MCC, and Kp of 99.11 %, 98.99 %, 99.22 %, 99.09 %, 99.09 %, 99.10 %, 98.21 %, 98.21 %, respectively, were obtained for detection using fusion of shallow and deep features of Resnet18 pretrained network classified by BA optimized SVM classifier. Feature fusion performs better for classification task with accuracy, sensitivity, specificity, precision, F1 score, BCR, MCC and Kp of 97.31 %, 97.30 %, 98.65 %, 97.37 %, 97.34 %, 97.97%, 95.99 %, 93.95 %, respectively. The proposed brain tumour detection and classification framework using deep feature extraction from Resnet 18 pretrained network in conjunction with feature fusion and optimised ML classifiers can improve the system performance. Henceforth, the proposed work can be used as an assistive tool to aid the radiologist in automated brain tumour analysis and treatment.

A New Medical Analytical Framework for Automated Detection of MRI Brain Tumor Using Evolutionary Quantum Inspired Level Set Technique.

Segmenting brain tumors in 3D magnetic resonance imaging (3D-MRI) accurately is critical for easing the diagnostic and treatment processes. In the field of energy functional theory-based methods for image segmentation and analysis, level set methods have emerged as a potent computational approach that has greatly aided in the advancement of the geometric active contour model. An important factor in reducing segmentation error and the number of required iterations when using the level set technique is the choice of the initial contour points, both of which are important when dealing with the wide range of sizes, shapes, and structures that brain tumors may take. To define the velocity function, conventional methods simply use the image gradient, edge strength, and region intensity. This article suggests a clustering method influenced by the Quantum Inspired Dragonfly Algorithm (QDA), a metaheuristic optimizer inspired by the swarming behaviors of dragonflies, to accurately extract initial contour points. The proposed model employs a quantum-inspired computing paradigm to stabilize the trade-off between exploitation and exploration, thereby compensating for any shortcomings of the conventional DA-based clustering method, such as slow convergence or falling into a local optimum. To begin, the quantum rotation gate concept can be used to relocate a colony of agents to a location where they can better achieve the optimum value. The main technique is then given a robust local search capacity by adopting a mutation procedure to enhance the swarm's mutation and realize its variety. After a preliminary phase in which the cranium is disembodied from the brain, tumor contours (edges) are determined with the help of QDA. An initial contour for the MRI series will be derived from these extracted edges. The final step is to use a level set segmentation technique to isolate the tumor area across all volume segments. When applied to 3D-MRI images from the BraTS' 2019 dataset, the proposed technique outperformed state-of-the-art approaches to brain tumor segmentation, as shown by the obtained results.

Initial Observation of Contrast Profiles for 2-Dimensional and 3-Dimensional Magnetic Resonance Imaging Sequences in Magnetic Resonance–Guided Radiation Therapy for Locally Advanced Pancreatic Cancer

In our experience treating locally advanced pancreatic cancer with magnetic resonance-guided radiation therapy (MRgRT), the true-fast imaging with steady-state free precession sequences used to generate both the real-time 2-dimensional (2D) magnetic resonance images (MRI; 2D cine) and the pretreatment high-resolution 3-dimensional (3D) MRI impart differing intensities for relevant structures between the 2 scans. Since these variations can confound target tracking selection, we propose that an understanding of the differing contrast profiles could improve selection of tracking structures. We retrospectively reviewed both 2D cine and 3D MRI images for 20 patients with pancreatic cancer treated with MRgRT. At simulation, an appropriate tracking target was identified and contoured on a single 3-mm sagittal slice of the 3D MRI. This sagittal slice was directly compared with the coregistered 7-mm 2D cine to identify structures with notable discrepancies in signal intensity. The 3D MRI was then explored in additional planes to confirm structure identities. For quantitative verification of the clinically observed differences, the pixel intensity distributions of 2D cine and 3D MRI digital imaging and communications in medicine data sets were statistically compared. In all patients reviewed, arteries (aorta, celiac, superior mesenteric artery, hepatic artery) appeared mildly hyperintense on both scans. However, veins (portal vein, superior mesenteric vein) appeared hyperintense on 2D cine but isointense on 3D MRI. Biliary structures appeared mildly hyperintense on 2D cine but starkly hyperintense on 3D MRI. The pixel intensity distributions extracted from 2D cine and 3D MRI images were confirmed to differ significantly (2 sample Kolmogorov-Smirnov test; test statistic, 0.40; P < .001). There are significant variations in image intensity between the immediate pretreatment 2D cine compared with the initial planning 3D MRI. Understanding variations of image intensity between the different MRI sequences used in MRgRT is valuable to radiation oncologists and may lead to improved target tracking and optimized treatment delivery.

Brain Parcellation Repeatability and Reproducibility Using Conventional and Quantitative 3D MR Imaging.

Automatic brain parcellation is typically performed on dedicated MR imaging sequences, which require valuable examination time. In this study, a 3D MR imaging quantification sequence to retrieve R1 and R2 relaxation rates and proton density maps was used to synthesize a T1-weighted image stack for brain volume measurement, thereby combining image data for multiple purposes. The repeatability and reproducibility of using the conventional and synthetic input data were evaluated. Twelve subjects with a mean age of 54 years were scanned twice at 1.5T and 3T with 3D-QALAS and a conventionally acquired T1-weighted sequence. Using SyMRI, we converted the R1, R2, and proton density maps into synthetic T1-weighted images. Both the conventional T1-weighted and the synthetic 3D-T1-weighted inversion recovery images were processed for brain parcellation by NeuroQuant. Bland-Altman statistics were used to correlate the volumes of 12 brain structures. The coefficient of variation was used to evaluate the repeatability. A high correlation with medians of 0.97 for 1.5T and 0.92 for 3T was found. A high repeatability was shown with a median coefficient of variation of 1.2% for both T1-weighted and synthetic 3D-T1-weighted inversion recovery at 1.5T, and 1.5% for T1-weighted imaging and 4.4% for synthetic 3D-T1-weighted inversion recovery at 3T. However, significant biases were observed between the methods and field strengths. It is possible to perform MR imaging quantification of R1, R2, and proton density maps to synthesize a 3D-T1-weighted image stack, which can be used for automatic brain parcellation. Synthetic parameter settings should be reinvestigated to reduce the observed bias.

Virtual 4DCT generated from 4DMRI in gated particle therapy: phantom validation and application to lung cancer patients

Objective. Respiration negatively affects the outcome of a radiation therapy treatment, with potentially severe effects especially in particle therapy (PT). If compensation strategies are not applied, accuracy cannot be achieved. To support the clinical practice based on 4D computed tomography (CT), 4D magnetic resonance imaging (MRI) acquisitions can be exploited. The purpose of this study was to validate a method for virtual 4DCT generation from 4DMRI data for lung cancers on a porcine lung phantom, and to apply it to lung cancer patients in PT. Approach. Deformable image registration was used to register each respiratory phase of the 4DMRI to a reference phase. Then, a static 3DCT was registered to this reference MR image set, and the virtual 4DCT was generated by warping the registered CT according to previously obtained deformation fields. The method was validated on a physical phantom for which a ground truth 4DCT was available and tested on lung tumor patients, treated with gated PT at end-exhale, by comparing the virtual 4DCT with a re-evaluation 4DCT. The geometric and dosimetric evaluation was performed for both proton and carbon ion treatment plans. Main results. The phantom validation exhibited a geometrical accuracy within the maximum resolution of the MRI and mean dose deviations, with respect to the prescription dose, up to 3.2% for target D 95%, with a mean gamma pass rate of 98%. For patients, the virtual and re-evaluation 4DCTs showed good correspondence, with errors on target D 95% up to 2% within the gating window. For one patient, dose variations up to 10% at end-exhale were observed due to relevant inter-fraction anatomo-pathological changes that occurred between the planning and re-evaluation CTs. Significance. Results obtained on phantom data showed that the virtual 4DCT method was accurate, allowing its application on patient data for testing within a clinical scenario.

Paper 48: Association of 3D MRI Volumetric Assessment of Rotator Cuff Pathology with Preoperative Patient Reported Outcomes

Paper 48: Association of 3D MRI Volumetric Assessment of Rotator Cuff Pathology with Preoperative Patient Reported Outcomes