Automatic Pulp and Teeth Three-Dimensional Modeling of Single and Multi-Rooted Teeth Based on Cone-Beam Computed Tomography Imaging: A Promising Approach With Clinical and Therapeutic Outcomes.

Background Cone-beam computed tomography (CBCT) imaging offers high-quality three-dimensional (3D) acquisition with great spatial resolution, given by the use of isometric voxels, when compared with conventional computed tomography (CT). The current literature supports a median reduction of 76% (up to 85% reduction) of patients' radiation exposure when imaged by CBCT versus CT. Clinical applications of CBCT imaging can benefit both medical and dental professions.

Automatic lower limb bone segmentation in radiographs with different orientations and fields of view based on a contextual network.

Purpose: Bone identification and segmentation in X-ray images are crucial in orthopedics for the automation of clinical procedures, but it often involves some manual operations. In this work, using a modified SegNet neural network, we automatically identify and segment lower limb bone structures on radiographs presenting various fields of view and different patient orientations.

Methods: A wide contextual neural network architecture is proposed to perform a high-quality pixel-wise semantic segmentation on X-ray images presenting structures with a similar appearance and strong superposition.

Simulation of the objective occlusion effect induced by bone-conducted stimulation using a three-dimensional finite-element model of a human head.

The occlusion effect (OE) refers to the phenomenon that more bone-conducted physiological sounds are transmitted into the earcanal when it is blocked and may cause discomfort on users of hearing protection devices. Models have been proposed to study the OE as they can help understand the physical mechanisms and can be used to evaluate the individual contribution on the OE of the factors that may affect it (i.e.

Clinical Evaluation of In-House-Produced 3D-Printed Nasopharyngeal Swabs for COVID-19 Testing.

3D-printed alternatives to standard flocked swabs were rapidly developed to provide a response to the unprecedented and sudden need for an exponentially growing amount of diagnostic tools to fight the COVID-19 pandemic. In light of the anticipated shortage, a hospital-based 3D-printing platform was implemented in our institution for the production of swabs for nasopharyngeal and oropharyngeal sampling based on the freely available, open-source design provided to the community by University of South Florida's Health Radiology and Northwell Health System teams as a replacement for locally used commercial swabs. Validation of our 3D-printed swabs was performed with a head-to-head diagnostic accuracy study of the 3D-printed "Northwell model" with the cobas PCR Media swab sample kit.

Tibial Tunnel Placement in ACL Reconstruction Using a Novel Grid and Biplanar Stereoradiographic Imaging.

Background: Nonanatomic graft placement is a frequent cause of anterior cruciate ligament reconstruction (ACLR) failure, and it can be attributed to either tibial or femoral tunnel malposition. To describe tibial tunnel placement in ACLR, we used EOS, a low-dose biplanar stereoradiographic imaging modality, to create a comprehensive grid that combines anteroposterior (AP) and mediolateral (ML) coordinates.

Purpose: To (1) validate the automated grid generated from EOS imaging and (2) compare the results with optimal tibial tunnel placement.

A method for quantitative evaluation of a valgus knee orthosis using biplane x-ray images.

Knee orthoses are designed to reestablish the normal kinematics of the knee joint. However, the data on the effectiveness of them on modifying the internal joint kinematics are scarce. The aim of this study was to develop a method to allow accurate comparison of the knee contact kinematics in osteoarthritic (OA) subjects with and without wearing a valgus knee orthosis using imaging techniques.

The effect of anterolateral ligament reconstruction on knee constraint: A computer model-based simulation study.

Background: To determine the influence of anterolateral ligament reconstruction (ALLR) on knee constraint through the analysis of knee abduction (valgus) moment when the knee is subjected to external translational (anterior) or rotational (internal) loads.

Methods: A knee computer model simulated from a three-dimensional computed tomography scan of healthy male was implemented for this study. Three groups were designed: (1) intact knee, (2) combined Anterior Cruciate Ligament (ACL) and Antero-Lateral Complex (ALC) deficient knee, and (3) combined ACL and Antero- lateral Ligament (ALL) reconstructed knee.

Potential of iterative reconstruction for maxillofacial cone beam CT imaging: technical note.

Iterative reconstruction has been proven to be an effective tool for low-dose computed tomography imaging. However, this technology is currently not available in commercial diagnostic maxillofacial cone beam CT. For this technical note, an iterative reconstruction technique was applied to cone beam CT raw data of two maxillofacial clinical cases to explore its potential for dose reduction and metal artifact reduction.

Femoral Tunnel Placement Analysis in ACL Reconstruction Through Use of a Novel 3-Dimensional Reference With Biplanar Stereoradiographic Imaging.

Background: The femoral-sided anatomic footprint of the anterior cruciate ligament (ACL) has been widely studied during the past decades. Nonanatomic placement is an important cause of ACL reconstruction (ACLR) failure.

Purpose: To describe femoral tunnel placement in ACLR through use of a comprehensive 3-dimensional (3D) cylindrical coordinate system combining both the traditional clockface technique and the quadrant method.

Shape, Pose and Density Statistical Model for 3D Reconstruction of Articulated Structures from X-Ray Images.

This article proposes a joint statistical model, to describe the volumetric shape + pose + density information, and a reconstruction algorithm to simultaneously recover the volumetric information of several anatomical structures from biplanar radiographs. A PCA-based representation is proposed as compact model representation and a hybrid AAM search and genetic optimization is used to perform the reconstruction. A study was conducted to recover a 3D volume grid containing a human knee mesh from 2 orthogonal simulated radiographs.

A Predictive Model of Progression for Adolescent Idiopathic Scoliosis Based on 3D Spine Parameters at First Visit.

Unlabelled: MINI: The aim of this prospective cohort study was to improve the prediction of curve progression in AIS. By adding the 3D morphology parameters at first visit, the predictive model explains 65% of the variability. It is one of the greatest advances in the understanding of scoliosis progression in the last 30 years.

Predictive Modeling for Personalized Three-Dimensional Burn Injury Assessments.

For patients with major burn injuries, an accurate burn size estimation is essential to plan appropriate treatment and minimize medical and surgical complications. However, current clinical methods for burn size estimation lack accuracy and reliability. To overcome these limitations, this paper proposes a 3D-based approach-with personalized 3D models from a limited set of anthropometric measurements-to accurately assess the percent TBSA affected by burns.

Neuroimage signature from salient keypoints is highly specific to individuals and shared by close relatives.

Neuroimaging studies typically adopt a common feature space for all data, which may obscure aspects of neuroanatomy only observable in subsets of a population, e.g. cortical folding patterns unique to individuals or shared by close relatives.

Iterative reconstruction for image enhancement and dose reduction in diagnostic cone beam CT imaging.

Background: Iterative reconstruction is well-established in diagnostic multidetector computed tomography (MDCT) for dose reduction and image quality enhancement. Its application to diagnostic cone beam computed tomography (CBCT) is only emerging and warrants a quantitative evaluation.

Methods: Several phantoms and a canine head specimen were imaged using a commercially available small-field CBCT scanner.

Can total knee arthroplasty restore the correlation between radiographic mechanical axis angle and dynamic coronal plane alignment during gait?

Background: Total knee arthroplasty (TKA) is the treatment of choice for end-stage knee osteoarthritis. Postoperative static knee alignment has been recognized as a key component of successful surgery. A correction toward the kinematics of a native knee is expected after TKA, with an aim for neutral mechanical alignment.

Lateral extra-articular reconstruction length changes during weightbearing knee flexion and pivot shift: A simulation study.

Introduction: Variations in the length of lateral extra-articular reconstruction (LER) have been widely investigated during knee flexion but there is no information about length changes during pivot shift. This study sought to assess the changes in LER tension during weightbearing knee flexion in a normal knee and in a computer-simulated pivot-shift scenario.

Hypothesis: Placing the femoral tunnel posterior and proximal to the lateral femoral epicondyle allows the LER to tighten early in the flexion range during weightbearing (squatting motion) and simulated pivot-shift.

Automatic self-gated 4D-MRI construction from free-breathing 2D acquisitions applied on liver images.

Purpose: MRI slice reordering is a necessary step when three-dimensional (3D) motion of an anatomical region of interest has to be extracted from multiple two-dimensional (2D) dynamic acquisition planes, e.g., for the construction of motion models used for image-guided radiotherapy.

Dual-energy computed tomography for prediction of loco-regional recurrence after radiotherapy in larynx and hypopharynx squamous cell carcinoma.

Purpose: To investigate the role of quantitative pre-treatment dual-energy computed tomography (DECT) for prediction of loco-regional recurrence (LRR) in patients with larynx/hypopharynx squamous cell cancer (L/H SCC).

Methods: Patients with L/H SCC treated with curative intent loco-regional radiotherapy and that underwent treatment planning with contrast-enhanced DECT of the neck were included. Primary and nodal gross tumor volumes (GTVp and GTVn) were contoured and transferred into a Matlab® workspace.

Quantification of joint alignment and stability during a single leg stance task in a knee osteoarthritis cohort.

Background: Knee osteoarthritis alters joint stability but its kinematics during functional weight-bearing tasks remain unclear. We propose and validate an assessment technique for the quantification of knee alignment and stability in patients during a short single leg stance task.

Methods: Three-dimensional knee kinematics were acquired non-invasively from 31 knee osteoarthritis patients (subdivided as moderate or severe) and 15 asymptomatic individuals during six short single-leg stance tasks.

An analysis of 3D knee kinematic data complexity in knee osteoarthritis and asymptomatic controls.

Three-dimensional (3D) knee kinematic data, measuring flexion/extension, abduction/adduction, and internal/external rotation angle variations during locomotion, provide essential information to diagnose, classify, and treat musculoskeletal knee pathologies. However, and so across genders, the curse of dimensionality, intra-class high variability, and inter-class proximity make this data usually difficult to interpret, particularly in tasks such as knee pathology classification. The purpose of this study is to use data complexity analysis to get some insight into this difficulty.

In a Heartbeat: An Assessment of Dynamic Dose Variation to Cardiac Structures Using Dual Source Computed Tomography.

Purpose: To assess radiation dose variation to the left anterior descending artery (LAD), left main coronary artery (LMCA), left ventricle (LV), and whole heart (WH) during the cardiac cycle using dual source computed tomography (DSCT).

Methods And Materials: The present prospective study included patients with left-side breast cancer planned to undergo tangential radiation therapy. An electrocardiogram-synchronized contrast-injected DSCT scan was obtained with the patient in the treatment position, in deep-inspiration breath-hold, using retrospective sequential acquisition.

Phase 1-2 Study of Dual-Energy Computed Tomography for Assessment of Pulmonary Function in Radiation Therapy Planning.

Purpose: To quantify lung function according to a dual-energy computed tomography (DECT)-derived iodine map in patients treated with radiation therapy for lung cancer, and to assess the dosimetric impact of its integration in radiation therapy planning.

Methods And Materials: Patients treated with stereotactic ablative radiation therapy for early-stage or intensity modulated radiation therapy for locally advanced lung cancer were prospectively enrolled in this study. A DECT in treatment position was obtained at time of treatment planning.

Liver segmentation: indications, techniques and future directions.

Objectives: Liver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals.

Larynx motion considerations in partial larynx volumetric modulated arc therapy for early glottic cancer.

Introduction: To assess laryngeal motion in early glottic cancer in order to determine safe margins for partial larynx volumetric modulated arc therapy (PL-VMAT), and to quantify dosimetric advantages of PL-VMAT.

Methods: This prospective study included T1-2N0 glottic cancers treated with whole larynx VMAT (WL-VMAT). Pre- and mid-treatment 4D-computed tomography (4D-CT) and dynamic magnetic resonance imaging (MRI) allowed for assessment of larynx swallowing and respiratory motion.

A multi-criteria evaluation platform for segmentation algorithms.

The purpose of this paper is to present a platform for evaluating segmentation algorithms that detect anatomical structures in medical images. Structure detection being subject to human interpretation, we first describe a method to define a ground truth model, i.e.